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TOC Alert for Publication# 6287639 2019July 22<![CDATA[Front cover]]>7C1C198<![CDATA[IEEE Access Editorial Board]]>7ix239<![CDATA[IEEE Access® Editorial Board]]>7xixv1641<![CDATA[Timing Channel in IaaS: How to Identify and Investigate]]>71115202<![CDATA[Machine Learning Approach-Based Gamma Distribution for Brain Tumor Detection and Data Sample Imbalance Analysis]]>712193755<![CDATA[Multi-Attribute Group Decision Making Based on Intuitionistic Uncertain Linguistic Hamy Mean Operators With Linguistic Scale Functions and Its Application to Health-Care Waste Treatment Technology Selection]]>720466684<![CDATA[Hammerstein Adaptive Impedance Controller for Bionic Wrist Joint Actuated by Pneumatic Muscles]]>747567576<![CDATA[Using Deep Convolutional Neural Network for Emotion Detection on a Physiological Signals Dataset (AMIGOS)]]>7576712200<![CDATA[Hyper-Heuristic Coevolution of Machine Assignment and Job Sequencing Rules for Multi-Objective Dynamic Flexible Job Shop Scheduling]]>768885518<![CDATA[A Declarative Service-Based Method for Adaptive Aggregation of Sensor Streams]]>789985542<![CDATA[Using a Vertical-Stream Variational Auto-Encoder to Generate Segment-Based Images and Its Biological Plausibility for Modelling the Visual Pathways]]>7991104928<![CDATA[Stability Analysis of Sampled-Data Control Systems With Constant Communication Delays]]>$x({t_{k}})$ to $x(t)$ , $x(t)$ to $x({t_{k + 1}})$ , $x(t_{k}-tau)$ to $x(t-tau)$ , and $x(t-tau)$ to $x(t_{k+1}-tau)$ . Second, in the derivative of the Lyapunov function, the integral term which has the information of sampling-period plus communication delay is divided into three parts. Then, by employing integral inequality techniques, some improved stability conditions are derived. The numerical examples demonstrate the validity of the proposed methods.]]>71111163142<![CDATA[A Security-Enhanced Cluster Size Adjustment Scheme for Cognitive Radio Networks]]>711713013194<![CDATA[State-of-Charge Balancing Control for ON/OFF-Line Internal Cells Using Hybrid Modular Multi-Level Converter and Parallel Modular Dual L-Bridge in a Grid-Scale Battery Energy Storage System]]>713114714056<![CDATA[Deployment and Resource Distribution of Mobile Edge Hosts Based on Correlated User Mobility]]>714815910596<![CDATA[Rich Feature Combination for Cost-Based Broad Learning System]]>716017211185<![CDATA[Lag Exponential Synchronization of Delayed Memristor-Based Neural Networks via Robust Analysis]]>71731823597<![CDATA[Compact UWB Antenna With Integrated Triple Notch Bands for WBAN Applications]]>${X}$ -band downlink satellite communication systems (7.25–7.75 GHz). A complementary split ring resonator slot and two L-shaped stubs are introduced on an elliptical-shaped radiating patch to obtain UWB coverage from 2.9 to 12 GHz with three notch bands. The overall antenna structure is fabricated on FR4 substrate with a size of $12,,text {mm} times 19,,text {mm}$ which provides a size reduction of more than 42% with respect to recent literature. The simulated and measured results indicate that the proposed antenna is a good candidate for WBAN applications.]]>718319017901<![CDATA[Effective Information Filtering Mining of Internet of Brain Things Based on Support Vector Machine]]>719120211195<![CDATA[PCI Planning Based on Binary Quadratic Programming in LTE/LTE-A Networks]]>$q$ interference, where $q=3$ for Single-Input Single-Output (SISO) system, and $q=6$ for Multiple-Input Multiple-Output (MIMO) system. In this study, a new definition of neighborhood relations was proposed based on the measurement report (MR) data in the actual network. Binary quadratic programming (BQP) model was built for PCI planning through a series of model deductions and mathematical proofs. Since BQP is known as NP-hard, a heuristic Greedy algorithm was proposed and its low complexity both in time and space can ensure large-scale computing. Finally, based on the raw data extracted from the actual SISO system network and the simulation calculation of MATLAB, the experimental results demonstrated that Greedy algorithm not only eliminates conflict and confusion completely, but also reduces the mod 3 interference of 26.213% more than the baseline scheme and far more than the improvement ratio of 4.436% given by the classical graph coloring algorithm.]]>72032144773<![CDATA[A Generic Spatiotemporal UAV Scheduling Framework for Multi-Event Applications]]>721522917765<![CDATA[A Programmable Multi-Biomarker Neural Sensor for Closed-Loop DBS]]>in-vitro tests using pre-recorded neural signals in saline solution; and 3) in-vivo tests by recording neural signals from freely moving laboratory mice. The animals were implanted with a PlasticsOne electrode, and recording was conducted after recovery from the electrode implantation surgery. The experimental results are presented and discussed confirming the successful operation of the device. The size and weight of the device enable tetherless back-mountable use in pre-clinical trials.]]>723024413990<![CDATA[A Concept Map-Based Learning Paths Automatic Generation Algorithm for Adaptive Learning Systems]]>72452559225<![CDATA[Evolutionary 4G/5G Network Architecture Assisted Efficient Handover Signaling]]>725628315095<![CDATA[CarvingNet: Content-Guided Seam Carving Using Deep Convolution Neural Network]]>728429219454<![CDATA[Pavo: A RNN-Based Learned Inverted Index, Supervised or Unsupervised?]]>72933038573<![CDATA[A Review of Mobile Crowdsourcing Architectures and Challenges: Toward Crowd-Empowered Internet-of-Things]]>73043245047<![CDATA[Method of Synthesizing Orthogonal Beam-Forming Networks Using <italic>QR</italic> Decomposition]]>$Q_{1}$ and $Q_{2}$ which are mentioned by Sodin. The solution of such a design problem can be carried out by applying $QR$ decomposition based on Givens transformations. Such a design method also takes into account the computer programming realization. Numerical results are obtained through the commercial simulator to prove the correctness of the method. The ease, accuracy, and efficiency of this synthesis method for the design of BFN make it very useful in modern applications of multi-beam antenna arrays.]]>73253312919<![CDATA[Reducing Signal Overload by Disconnection Tolerant Voice Service in Heterogeneous Networks]]>733234611034<![CDATA[Exploring Deep Recurrent Convolution Neural Networks for Subjectivity Classification]]>73473575741<![CDATA[Fault/State Estimation Observer Synthesis for Uncertain T-S Fuzzy Systems]]>73583693597<![CDATA[SCUT-EPT: New Dataset and Benchmark for Offline Chinese Text Recognition in Examination Paper]]>73703822581<![CDATA[The Uncertainty Analysis of Vague Sets in Rough Approximation Spaces]]>738339514268<![CDATA[SDN-Based End-to-End Fragment-Aware Routing for Elastic Data Flows in LEO Satellite-Terrestrial Network]]>73964109568<![CDATA[Exploring Social Media Network Landscape of Post-Soviet Space]]>741142618638<![CDATA[Frontal-Sagittal Dynamic Coupling in the Optimal Design of a Passive Bipedal Walker]]>742744911290<![CDATA[Design of a Ku-Band High-Purity Transducer for the TM<sub>01</sub> Circular Waveguide Mode by Means of T-Type Junctions]]>10 rectangular waveguide mode to the TM_{01} circular waveguide mode is presented. The novel topology is based on two T-type junctions with in-phase excitation at their input rectangular ports. The first one is an H-plane T-junction in rectangular waveguide. The second one differs from the standard E-plane T-junction in the excitation, which is carried out by modes excited with fields having the same in-phase polarization at the input rectangular ports, and has the output port in circular waveguide. This configuration exploits the symmetry of the modes under consideration to achieve a high-purity conversion, controlling the propagating circular waveguide TE_{11} mode to a maximum level of -42 dB in the whole operation band. The design bandwidth is 2 GHz centered at 12 GHz with a return loss level higher than 28 dB. In addition, the transducer can be divided in a main body plus a cover for easing the manufacturing. In order to verify the proposed geometry, a back-to-back arrangement has been measured connecting two similar aluminum transducers with four different angles between their rectangular ports (0°, 45°, 90°, and 180°). The excellent experimental results validate the novel transducer with a measured converting efficiency higher than 98.2% in a 16.7% relative frequency bandwidth.]]>74504562527<![CDATA[Bibliographic Network Representation Based Personalized Citation Recommendation]]>74574676074<![CDATA[A New Algorithm for Blood Flow Measurement Based on the Doppler Flow Spectrogram]]>$KS205D-1$ using the SonixTouch ultrasonic system. In addition, linear-regression analysis is carried out to observe the correlation factors between the experimental values and real values of different flow rates. Experimental results show that the calculated values and real values correlate significantly $(r>0.969, P < 0.0000001)$ . Experimental results both on males and females also verified the proposed algorithm $(r>0.915, P < 0.00053)$ . Hence the proposed algorithm is proven effective for relative mean blood flow measurement. Due to the special structure of the human brain, it is difficult to measure the cross sectional area of blood vessel with ultrasound imaging. In this algorithm, there is no need to measure the cross sectional area of the blood vessel. Therefore, the proposed algorithm has the potential to be a new method for clinical ultrasonic blood flow measurement, especially cerebral blood flow measurement.]]>74684775855<![CDATA[Optical Modeling and Physical Experiments on Ocular UV Manikins Exposure]]>74784861968<![CDATA[Empirical Frequency-Dependent Wall Insertion Loss Model at 3–6 GHz for Future Internet-of-Things Applications]]>74874977326<![CDATA[A Survey on Cluster-Based Routing Protocols for Unmanned Aerial Vehicle Networks]]>74985169381<![CDATA[Unsupervised Band Selection Method Based on Importance-Assisted Column Subset Selection]]>75175279683<![CDATA[User Satisfaction-Aware Resource Allocation for D2D Enhanced Communication]]>752853911239<![CDATA[An Iterative Reputation Ranking Method via the Beta Probability Distribution]]>$tau $ of the IBeta algorithm are larger than those generated by the RBPD method with different fractions of random ratings. Moreover, the results for the empirical networks indicate that the presented algorithm is more accurate and robust than the RBPD method when the rating systems are under spamming attacks. This paper provides a further understanding on the role of the probability for the online user reputation identification.]]>75405473944<![CDATA[Analysis of Smart Loads in Nanogrids]]>754856210953<![CDATA[Study on Mutual Coupling Reduction Technique for MIMO Antennas]]>75635863705<![CDATA[A Graph-Theory-Based Method for Topological and Dimensional Representation of Planar Mechanisms as a Computational Tool for Engineering Design]]>75875966688<![CDATA[Soil Moisture Retrieval Algorithm Based on TFA and CNN]]>75976049245<![CDATA[Synchronization Mechanisms for Multi-User and Multi-Device Hybrid Broadcast and Broadband Distributed Scenarios]]>760562419306<![CDATA[Two-Stage Control of Endpoint Temperature for Pebble Stove Combustion]]>76256408578<![CDATA[What Clinics are Expecting From Data Scientists? A Review on Data Oriented Studies Through Qualitative and Quantitative Approaches]]>76416546922<![CDATA[A Novel VLSI Architecture for Multi-Constellation and Multi-Frequency GNSS Acquisition Engine]]>2 and consumes only 72.02-mW power while realizing the maximum clock frequency at about 333.33 MHz.]]>76556657661<![CDATA[Fuzzy Sliding Mode Control for Systems With Matched and Mismatched Uncertainties/Disturbances Based on ENDOB]]>$n$ th order systems. By integrating the mismatched disturbance estimation and its derivative into the sliding mode surface, an ENDOB-based SMC method is developed for these systems. A fuzzy control system is designed to adjust the gain of the sliding mode dynamically. Compared with the nominal SMC method, the proposed method has a stronger anti-disturbance ability in the presence of matched and mismatched uncertainties/disturbances. It can ensure a satisfactory system performance and reduce the chattering. The stability of the system is proved by using Lyapunov theory. The final simulation results of two examples are provided to verify the effectiveness of the proposed control method.]]>76666734379<![CDATA[AgileSAR: Achieving Wide-Swath Spaceborne SAR Based on Time-Space Sampling]]>$text{l}_{1}$ relaxation method is used to reconstruct sparse SAR images, and the reconstruction performance is quantitatively analyzed based on the estimation error. The simulation results validating the proposed method with sub-Nyquist samples can achieve approximately similar performance as conventional SAR with Nyquist samples.]]>76746867351<![CDATA[<inline-formula> <tex-math notation="LaTeX">$tau$ </tex-math></inline-formula>-Safe (<inline-formula> <tex-math notation="LaTeX">$l,k$ </tex-math></inline-formula>)-Diversity Privacy Model for Sequential Publication With High Utility]]>$tau $ -safety model is the state-of-the-art model in sequential publication. However, it is based on the generalization technique, which has some drawbacks such as heavy information loss and difficulty of supporting marginal publication. Besides, the privacy of individuals is the major aspect that needs to be protected in privacy preserving data publishing. In this paper, to protect the privacy of individuals in sequential publication, we develop a new $tau $ -safe ($l,k$ )-diversity privacy model based on generalization and segmentation by record anonymity satisfying $l$ -diversity and individual anonymity satisfying $k$ -anonymity. This privacy model ensures that each record’s signatures keep consistency or have no intersection in all releases. It can get high data utility while resisting the linking attacks due to arbitrary updates. In addition, it can also be applied to a dataset where individual has multiple records and arbitrary marginal publication. The results of our experiments show that the proposed privacy model achieves better anonymization quality and query accuracy in comparison with the $m$ -invariance and $tau $ -safety model in the sequential publication with arbitrary updates.]]>76877012647<![CDATA[A Dual-Channel Equilibrium Management Model for Service Products Under Electronic Commerce Environment]]>77027132072<![CDATA[Unsupervised Clustering for Nonlinear Equalization in Indoor Millimeter-Wave Communications]]>77147275816<![CDATA[Multistage Fusion With Dissimilarity Regularization for SAR/IR Target Recognition]]>772874013420<![CDATA[Research on the Active Guidance Control System in High Speed Maglev Train]]>$H_{infty } $ control theory. The simulation and experiment demonstrate that the high-speed maglev train using the designed guidance controller has relatively desirable performance and achieves stable guidance ability successfully.]]>77417528480<![CDATA[Spatiotemporal Adaptive Nonuniformity Correction Based on BTV Regularization]]>775376216172<![CDATA[On-Chip Optical Vector Quadrature De-Multiplexer Proposal for QAM De-Aggregation by Single Bi-Directional SOA-Based Phase-Sensitive Amplifier]]>−3, respectively. Also, to optimize the performance of the subsystem, the BER performance dependence on the phase difference between two arms in the subsystem is also examined. The simulation results reveal that the proposed QD can accomplish the function of optical vector de-aggregation well for the high-level QAM signals. The proposed QD can be applied to information de-aggregation, format conversion, and direct detection for optical vector signals, which may have great potential values for the flexible optical networks.]]>77637726249<![CDATA[Multi-Fault Rapid Diagnosis for Wind Turbine Gearbox Using Sparse Bayesian Extreme Learning Machine]]>77737819098<![CDATA[2D and 3D Image Quality Assessment: A Survey of Metrics and Challenges]]>77828018337<![CDATA[Mobility Prediction: A Survey on State-of-the-Art Schemes and Future Applications]]>78028228996<![CDATA[Simultaneous Wireless Information and Power Transfer for Dynamic Cooperative Spectrum Sharing Networks]]>78238343282<![CDATA[Real-Time Interference Identification via Supervised Learning: Embedding Coexistence Awareness in IoT Devices]]>783585010650<![CDATA[Chip Power Scaling in Recent CMOS Technology Nodes]]>78518564238<![CDATA[Topological Analysis on the Belief Rule Base Space]]>78578652834<![CDATA[Adaptive Differential Evolution With Evolution Memory for Multiobjective Optimization]]>78668768991<![CDATA[Image Classification Using Low-Rank Regularized Extreme Learning Machine]]>78778835071<![CDATA[ULW-DMM: An Effective Topic Modeling Method for Microblog Short Text]]>78848933238<![CDATA[Control Method for Maximizing Fault Voltage of Wind Generation-Integrated Power Systems With Consideration of DFIG–Grid Coupling]]>78949055371<![CDATA[Efficient Algorithm for Multi-Bit Montgomery Inverse Using Refined Multiplicative Inverse Modular <inline-formula> <tex-math notation="LaTeX">$2^K$ </tex-math></inline-formula>]]>$2^{k}$ without using integer division by refining the Arazi–Qi algorithm. We then generalize this algorithm into a scalable algorithm to compute an inverse modulo $2^{kl}$ by iteratively exploiting a $k$ -bit-based process when the inverse modulo $2^{k}$ is given. Because of its scalability, this generalized algorithm can be cost-effectively implemented on hardware and applied to larger modulus operations by iteratively applying a processing unit. Furthermore, we highlight the possibility of the derivation of a binary representation of an inverse $P^{-1}$ in terms of a representation of $P$ and demonstrate this operation for up to eight bits. Second, using this direct relationship, we propose a multi-bit Montgomery inverse algorithm that is at least three times faster than the original version. Finally, we derive various properties of this algorithm and compare it with previous algorithms. This fast calculation of a Montgomery inverse is important for public key cryptographic applications, such as elliptic curve cryptosystems, because the relative speed of calculating a modular inverse for modular multiplication is a critical parameter for deciding which coordinate systems to adopt.]]>79069183110<![CDATA[Segmentation of the Main Vessel of the Left Anterior Descending Artery Using Selective Feature Mapping in Coronary Angiography]]>79199303152<![CDATA[A Multidimensional Cadastral Topological Data Model: Design and Implementation]]>79319434944<![CDATA[Tanner <italic><inline-formula> <tex-math notation="LaTeX">$(J,L)$ </tex-math></inline-formula></italic> Quasi-Cyclic LDPC Codes: Girth Analysis and Derived Codes]]>$(J,L)$ QC-LDPC codes where $J$ and $L$ can be any two positive integers. According to the sufficient and necessary conditions for the existence of cycles of lengths 4, 6, 8, and 10, we propose an algorithm to determine the girth of Tanner $(J,L)$ QC-LDPC codes with finite code lengths. Through the analysis of the obtained girth values, we generalize the laws of the girth distributions of Tanner $(J,L)$ QC-LDPC codes. Furthermore, based on the exponent matrices of Tanner $(J,L)$ QC-LDPC codes with known girths, we employ the column selection method and/or the masking technique to construct binary/nonbinary LDPC codes. The numerical results show that the constructed LDPC codes have good performance under iterative decoding over the additive white Gaussian noise channel.]]>794495712837<![CDATA[Health and Safety Situation Awareness Model and Emergency Management Based on Multi-Sensor Signal Fusion]]>79589687640<![CDATA[Robust Beamforming Design for Secure DM-Based Relay Networks With Self-Sustained Jammers]]>79699833782<![CDATA[Research and Application of Acoustic Emission Signal Processing Technology]]>79849936240<![CDATA[Robust Gossiping for Distributed Average Consensus in IoT Environments]]>799410058265<![CDATA[An Efficient Density-Based Local Outlier Detection Approach for Scattered Data]]>7100610203421<![CDATA[Generative Adversarial Network-Based Method for Transforming Single RGB Image Into 3D Point Cloud]]>7102110291727<![CDATA[Design of <inline-formula> <tex-math notation="LaTeX">$H_infty$ </tex-math></inline-formula> Output Feedback Controller for Gas Turbine Engine Distributed Control With Random Packet Dropouts]]>$H_infty $ output feedback under random packet-dropouts. The sufficient robust mean-stable conditions are derived via the Lyapunov stability theory and linear matrix inequality approach. In addition, the effectiveness of the presented method is illustrated through a series of simulations.]]>7103010394786<![CDATA[Tree-Search-Based Any-Time Time-Optimal Path-Constrained Trajectory Planning With Inadmissible Island Constraints]]>71040105113815<![CDATA[Depth and All-in-Focus Image Estimation in Synthetic Aperture Integral Imaging Under Partial Occlusions]]>7105210676032<![CDATA[Design and Analysis of a Persistent, Efficient, and Self-Contained WSN Data Collection System]]>et al., have improved the persistence of data and the efficiency of reliable data collection in disaster scenarios. However, there are still some problems that reduce the overall efficiency. In this paper, we analyze the factors that affect the collection efficiency from a new perspective, the ratio of redundant symbols. Random feedback digestion (RFDG) model is proposed to digest the redundant symbols, similiar to our stomach digesting food, to remove redundant symbols and reduce resource consumption by using the feedback information of the already decoded code words sent by the sink node. This model can increase the valid information ratio in the network and finally increase data decoding efficiency. Three protocols are proposed in this paper according to different feedback mechanisms based on RFDG. It is shown that protocols based on RFDG outperform the growth codes protocol in data collection efficiency and reduce the delayed effect.]]>7106810838750<![CDATA[Toward Device-Free Micro-Gesture Tracking via Accurate Acoustic Doppler-Shift Detection]]>DMT, a device-free finger gesture tracking system that can track and recognize the finger motion accurately. To achieve this, we transform the mobile device, such as a smart phone, into an active sonar system by establishing inaudible audio links between the built-in speakers and microphone. The finger motion will have an effect (e.g., Doppler-shift) on the audio signals, which makes it possible to track the finger motion according to the received signal characteristics at the microphone side. Due to the small reflection energy and slow moving speed of the finger, the existing methods cannot detect the Doppler-shift accurately. To this end, a Fourier fitting-based method is proposed in the DMT to accurately detect the Doppler-shift. With the detected Doppler-shift, the DMT can track the finger motion with high accuracy. The DMT supports all kinds of finger gestures interaction, including characters and shapes. Extensive experiments demonstrate the high accuracy and robustness of the DMT in dynamic environments.]]>7108410949946<![CDATA[Credibility Evaluation of Twitter-Based Event Detection by a Mixing Analysis of Heterogeneous Data]]>7109511067497<![CDATA[Deriving Probabilistic SVM Kernels From Flexible Statistical Mixture Models and its Application to Retinal Images Classification]]>7110711179377<![CDATA[Efficient and Accurate Detection and Frequency Estimation of Multiple Sinusoids]]>7111811253670<![CDATA[Parallel Data Transmission in Indoor Visible Light Communication Systems]]>–6 for each light unit, using simple on-off-keying (OOK).]]>7112611388075<![CDATA[A Novel RF-Powered Wireless Pacing via a Rectenna-Based Pacemaker and a Wearable Transmit-Antenna Array]]>in vivo ECG results. Besides measuring the efficiency of the rectenna, the computations of specific absorption rate (SAR) are presented and found to be under the IEEE recommended limits. We conclude that a wearable RF-powered leadless pacing system is realizable with the SAR under the safe levels. Thus, the proposed leadless pacing method has the potential to be significantly safer as it completely eliminates the battery, leads, and device pocket and all the associated complications.]]>7113911482071<![CDATA[A Flip-Syndrome-List Polar Decoder Architecture for Ultra-Low-Latency Communications]]>$O(1)$ time. The proposed flip-syndrome-list decoder fully parallelizes all constituent code blocks without sacrificing performance, and thus is suitable for ultra-low-latency applications. Meanwhile, two code construction optimizations are presented to further reduce complexity and improve performance.]]>7114911598087<![CDATA[Digitized Metamaterial Absorber-Based Compressive Reflector Antenna for High Sensing Capacity Imaging]]>7116011732568<![CDATA[Stability of Switched Time-Delay Systems via Mode-Dependent Average Dwell Time Switching]]>7117411812526<![CDATA[A Study on the Acceleration Optimization Control Method for the Integrated Helicopter/Engine System Based on Torsional Vibration Suppression]]>7118211947887<![CDATA[Fuzzy TOPSIS Approaches for Assessing the Intelligence Level of IoT-Based Tourist Attractions]]>7119512077695<![CDATA[Buffering Time for Wireless Full-Duplex Systems Under Random Arrival]]>7120812237741<![CDATA[Weighted Incoherent Signal Subspace Method for DOA Estimation on Wideband Colored Signals]]>71224123314670<![CDATA[Planning City-Wide Package Distribution Schemes Using Crowdsourced Public Transportation Systems]]>71234124610772<![CDATA[Cone-Beam Computed Tomography Deblurring Using an Overrelaxed Chambolle-Pock Algorithm]]>7124712591354<![CDATA[Novel Two-Fold Data Aggregation and MAC Scheduling to Support Energy Efficient Routing in Wireless Sensor Network]]>2R^{2} routing algorithm uses a hierarchical WSN model to minimize energy consumption in the WSN. However, it increases complexity, time consumption, and energy consumption due to the hierarchical model. To resolve these problems, this paper proposes a novel ring partitioned based MAC (RP-MAC) protocol for the energy-efficient WSN with a mobile sink node. Energy efficiency is achieved by the following phases: clustering phase, MAC scheduling phase, data aggregation phase, and routing phase. Clustering phase is initiated by a weighted Voronoi diagram (WVD) algorithm by assigning a weight value for each node. Energy consumption due to idle listening is minimized by enabling novel RP-MAC scheduling in each cluster. Involvement of RP-MAC protocol also achieves collision-free data transmission in the network. A two-fold data aggregation (TFDA) scheme is proposed for the data aggregation phase to minimize energy consumption by reducing the number of transmissions. Routing phase supports both intra-cluster routing and inter-cluster routing. For intra-cluster routing, a hybrid chicken swarm optimization algorithm is proposed. For inter-cluster routing, position-based routing tree is constructed based on the sink node’s position. Our proposed RP-MAC protocol minimizes energy consumption in all possible ways for improving the network lifetime. Extensive simulation in ns-3 shows that the RP-MAC protocol achieves promising results in the following performance metrics: the number of dead nodes, average energy consumption, network lifetime, and throughput.]]>7126012748072<![CDATA[Carrier-Based Double Integral Sliding-Mode Controller of Class-D Amplifier]]>$Q$ -factor and ensure a flatter frequency response. The carrier-based approach guarantees the fixation of switching frequency and improves the total harmonic distortion plus noise (THD + N) by reducing the effect of nonlinearities in the power stage. In addition to the output voltage, the CBDISM controller requires current feedback from the capacitive filter, which is advantageous as the capacitor current is bidirectional and enables the use of a current transformer for feedback, thereby not affecting the cost and overall efficiency. The effectiveness of the proposed CBDISM controller is verified using computer simulation and experimental study.]]>7127512836568<![CDATA[Review of Applications of Fuzzy Logic in Multi-Agent-Based Control System of AC-DC Hybrid Microgrid]]>71284129910433<![CDATA[A Review of Sparse Recovery Algorithms]]>7130013229087<![CDATA[Stability Analysis of Boolean Networks With Stochastic Function Perturbations]]>7132313291474<![CDATA[Flow Network-Based Real-Time Scheduling for Reducing Static Energy Consumption on Multiprocessors]]>7133013449539<![CDATA[Building a Cloud IDS Using an Efficient Feature Selection Method and SVM]]>7134513544454<![CDATA[Clasp-Knife Model of Muscle Spasticity for Simulation of Robot-Human Interaction]]>$(n=9times 4)$ linear (Pearson) correlated average of $bar {r}=0.8348$ for nine subjects with correlation significant at the 0.01 level ($p< 0.01$ ) and five of them presented a distinctive clasp-knife phenomenon with correlation average of $bar {r}=0.8631$ .]]>7135513648172<![CDATA[Metabolic Syndrome and Development of Diabetes Mellitus: Predictive Modeling Based on Machine Learning Techniques]]>7136513756358<![CDATA[Corrections to “Secrecy Outage Analysis for Distributed Antenna Systems in Heterogeneous Cellular Networks”]]>[1], the calculation of (8) was erroneous. To be specific, as shown in (8) of [1], the average transmit power of a specially-designed signal ${x_{m} = - {{sqrt {P_{S}} {h_{Sm}}h_{Am}^{*}{x_{S}}}}/{{{{left |{ {{h_{Am}}} }right |}^{2}}}}}$ was obtained as begin{equation*}{P_{m} = frac {{sigma _{Sm}^{2}}}{{sigma _{Am}^{2}}}}P_{S},end{equation*} where $sigma _{Sm}^{2} = E(|{h_{Sm}}{|^{2}})$ and $sigma _{Am}^{2} = E(|{h_{Am}}{|^{2}})$ . This calculation was obtained by mistaking an expectation of $1/|h_{Am}|^{2}$ for $E(1/|h_{Am}|^{2})=1/E(|h_{Am}|^{2})= 1/sigma _{Am}^{2}$ , which is erroneous to be corrected. Actually, considering that $|h_{Am}|^{2}$ is an exponentially distributed random variable with a mean of $sigma ^{2}_{Am}$ , the expectation of $1/|h_{Am}|^{2}$ tends toward infinity, rather than $1/sigma _{Am}^{2}$ .]]>713761378883<![CDATA[Mitigating the Impact of Renewable Variability With Demand-Side Resources Considering Communication and Cyber Security Limitations]]>7137913899643<![CDATA[Modeling Metropolitan-Area Ambulance Mobility Under Blue Light Conditions]]>7139014034221<![CDATA[A Unified Framework for Sparse Relaxed Regularized Regression: SR3]]>relaxation of the regularized problem, which has three advantages over the state-of-the-art: 1) solutions of the relaxed problem are superior with respect to errors, false positives, and conditioning; 2) relaxation allows extremely fast algorithms for both convex and nonconvex formulations; and 3) the methods apply to composite regularizers, essential for total variation (TV) as well as sparsity-promoting formulations using tight frames. We demonstrate the advantages of SR3 (computational efficiency, higher accuracy, faster convergence rates, and greater flexibility) across a range of regularized regression problems with synthetic and real data, including applications in compressed sensing, LASSO, matrix completion, TV regularization, and group sparsity. Following standards of reproducible research, we also provide a companion MATLAB package that implements these examples.]]>7140414235830<![CDATA[Protograph Based Low-Density Parity-Check Codes Design With Mixed Integer Linear Programming]]>7142414384181<![CDATA[On the Inter-Departure Times in <inline-formula> <tex-math notation="LaTeX">$M/widetilde{D}/1/{B}_{on}$ </tex-math></inline-formula> Queue With Queue-Length Dependent Service and Deterministic/Exponential Vacations]]>$(R_{1})$ of packets are served, whichever occurs first, in the current busy period. We consider two types of vacation distributions: 1) deterministic and 2) exponential. Queue-length distribution at embedded points is derived first, then, the distribution and variance of inter-departure times are derived, for both types of vacations. The simulation results are in good agreement with the derived analytical results. The above framework would be useful at the receiver in modeling and analyzing the jitter and the waiting time of time-division multiplexing (TDM) emulated packets in TDM over packet-switched network (TDM over PSN) technology as a function of a buffer size.]]>7143914535290<![CDATA[Spectral Efficient Spatial Modulation Techniques]]>7145414692879<![CDATA[Testbed Evaluation of Real-Time Route Guidance in Inter-Vehicular Communication Urban Networks]]>71470148513791<![CDATA[From Threads to Smart Textile: Parametric Characterization and Electromagnetic Analysis of Woven Structures]]>7148615015211<![CDATA[On Performance Analysis of Single Frequency Network With C-RAN]]>7150215192149<![CDATA[Evolutionary Deep Learning-Based Energy Consumption Prediction for Buildings]]>7152015318230<![CDATA[An Overview on Concept Drift Learning]]>7153215474922<![CDATA[Dynamic Data Allocation and Task Scheduling on Multiprocessor Systems With NVM-Based SPM]]>7154815596694<![CDATA[A Decentralized Reciprocity Calibration Approach for Cooperative MIMO]]>7156015694164<![CDATA[Emergency Message Dissemination Schemes Based on Congestion Avoidance in VANET and Vehicular FoG Computing]]>7157015858855<![CDATA[Applying Bayesian Network Approach to Determine the Association Between Morphological Features Extracted from Prostate Cancer Images]]>$to $ Equidiameter), (Area $to $ Circulatory 2), (Circulatory $1to $ (Elongatedness), (Circulatory $1to $ Entropy), (Circulatory $1to $ Max. Radiu-
), and (Min. Radius $to $ Eccentricity). Moreover, interaction impact among nodes and node force was also computed. This analysis will help in finding the features that are more dominant to establish the relationship and can further increase the detection performance.]]>7158616018842<![CDATA[Spectrum Sharing in Multi-Tenant 5G Cellular Networks: Modeling and Planning]]>7160216168804<![CDATA[Collaborative Coexistence Management Scheme for Industrial Wireless Sensor Networks]]>71617162610806<![CDATA[A Non-Intrusive Heuristic for Energy Messaging Intervention Modeled Using a Novel Agent-Based Approach]]>7162716468622<![CDATA[Comparison of Econometric Models and Artificial Neural Networks Algorithms for the Prediction of Baltic Dry Index]]>7164716577310<![CDATA[Enhanced Path Detection Based on Interference Cancellation for Range Estimation of Communication-Based Positioning System in Indoor Environment]]>71658166710670<![CDATA[Improving Spatial Locality in Virtual Machine for Flash Storage]]>71668167610550<![CDATA[New Stability Criteria of Discrete Systems With Time-Varying Delays]]>7167716842748<![CDATA[Sparse Data Acquisition on Emerging Memory Architectures]]>7168516934710<![CDATA[Design of an Internet of Brain Things Network Security System Based on ICN]]>7169417058118<![CDATA[Joint Model Feature Regression and Topic Learning for Global Citation Recommendation]]>7170617207726<![CDATA[Asymmetric Loss Functions and Deep Densely-Connected Networks for Highly-Imbalanced Medical Image Segmentation: Application to Multiple Sclerosis Lesion Detection]]>$F_beta $ scores). We used large overlapping image patches as inputs for intrinsic and extrinsic data augmentation, a patch selection algorithm, and a patch prediction fusion strategy using B-spline weighted soft voting to account for the uncertainty of prediction in patch borders. We applied this method to multiple sclerosis (MS) lesion segmentation based on two different datasets of MSSEG 2016 and ISBI longitudinal MS lesion segmentation challenge, where we achieved average Dice similarity coefficients of 69.9% and 65.74%, respectively, achieving top performance in both the challenges. We comp-
red the performance of our network trained with $F_beta $ loss, focal loss, and generalized Dice loss functions. Through September 2018, our network trained with focal loss ranked first according to the ISBI challenge overall score and resulted in the lowest reported lesion false positive rate among all submitted methods. Our network trained with the asymmetric similarity loss led to the lowest surface distance and the best lesion true positive rate that is arguably the most important performance metric in a clinical decision support system for lesion detection. The asymmetric similarity loss function based on $F_beta $ scores allows training networks that make a better balance between precision and recall in highly unbalanced image segmentation. We achieved superior performance in MS lesion segmentation using a patch-wise 3D FC-DenseNet with a patch prediction fusion strategy, trained with asymmetric similarity loss functions.]]>7172117355218<![CDATA[Machine Learning Based Optimized Pruning Approach for Decoding in Statistical Machine Translation]]>7173617518462<![CDATA[A Single-Channel SSVEP-Based BCI Speller Using Deep Learning]]>71752176312367<![CDATA[The Installation Performance Control of Three Ducts Separate Exhaust Variable Cycle Engine]]>7176417746144<![CDATA[Towards a Hybrid Expert System Based on Sleep Event’s Threshold Dependencies for Automated Personalized Sleep Staging by Combining Symbolic Fusion and Differential Evolution Algorithm]]>71775179211347<![CDATA[Flexible Filter Bank Multi-Carriers PON Based on Two-Dimensional Multiple Probabilistic Shaping Distribution]]>7179317998823<![CDATA[Branch Point Selection in RNA Splicing Using Deep Learning]]>https://home.jbnu.ac.kr/NSCL/rnabps.htm.]]>71800180710132<![CDATA[Decentralized Real-Time Estimation and Tracking for Unknown Ground Moving Target Using UAVs]]>7180818176407<![CDATA[Wide-Area Vehicle-Drone Cooperative Sensing: Opportunities and Approaches]]>7181818289906<![CDATA[Scene-Awareness Based Single Image Dehazing Technique via Automatic Estimation of Sky Area]]>7182918393694<![CDATA[A Novel Wide, Dual-and Triple-Band Frequency Reconfigurable Butler Matrix Based on Transmission Line Resonators]]>$lambda $ /4) of the open stub resonator length. To demonstrate the design approach, two prototypes of coupler and Butler matrix are fabricated and tested. Good agreement between the measured and simulated results is obtained. The proposed designs show good results in terms of compactness, low insertion loss, and high isolation with a minimal number of RF p-i-n diodes used for all states.]]>7184018476087<![CDATA[Deep Decoupling Convolutional Neural Network for Intelligent Compound Fault Diagnosis]]>71848185810615<![CDATA[Indoor Scene Understanding in 2.5/3D for Autonomous Agents: A Survey]]>7185918872686<![CDATA[Integrated Test Automation for Evaluating a Motion-Based Image Capture System Using a Robotic Arm]]>7188818966935<![CDATA[An End-to-End Multi-Task and Fusion CNN for Inertial-Based Gait Recognition]]>7189719085676<![CDATA[Comparative Study of Inkjet-Printed Silver Conductive Traces With Thermal and Electrical Sintering]]>71909191910053<![CDATA[A Far-Field Evaluation Method for Interfacial Defects Existed in Composite Insulators Based on Transient Thermal Wave]]>7192019267145<![CDATA[Frequency Selection Approach for Energy Aware Cloud Database]]>7192719428356<![CDATA[Image Noise Level Estimation for Rice Noise Based on Extended ELM Neural Network Training Algorithm]]>7194319517965<![CDATA[Robust Stereo Visual Odometry Based on Probabilistic Decoupling Ego-Motion Estimation and 3D SSC]]>7195219614114<![CDATA[KSVD-Based Multiple Description Image Coding]]>71962197211578<![CDATA[On Modified Multi-Output Chebyshev-Polynomial Feed-Forward Neural Network for Pattern Classification of Wine Regions]]>7197319804666<![CDATA[Mutual Information-Weighted Principle Components Identified From the Depth Features of Stacked Autoencoders and Original Variables for Oil Dry Point Soft Sensor]]>$r$ indicators in the experiments and was thus proved feasible and useful.]]>7198119904556<![CDATA[DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series]]>time series predictor module uses deep convolutional neural network (CNN) to predict the next time stamp on the defined horizon. This module takes a window of time series (used as a context) and attempts to predict the next time stamp. The predicted value is then passed to the anomaly detector module, which is responsible for tagging the corresponding time stamp as normal or abnormal. DeepAnT can be trained even without removing the anomalies from the given data set. Generally, in deep learning-based approaches, a lot of data are required to train a model. Whereas in DeepAnT, a model can be trained on relatively small data set while achieving good generalization capabilities due to the effective parameter sharing of the CNN. As the anomaly detection in DeepAnT is unsupervised, it does not rely on anomaly labels at the time of model generation. Therefore, this approach can be directly applied to real-life scenarios where it is practically impossible to label a big stream of data coming from heterogeneous sensors comprising of both normal as well as anomalous points. We have performed-
a detailed evaluation of 15 algorithms on 10 anomaly detection benchmarks, which contain a total of 433 real and synthetic time series. Experiments show that DeepAnT outperforms the state-of-the-art anomaly detection methods in most of the cases, while performing on par with others.]]>7199120052157<![CDATA[A Noninvasive and Robust Diagnostic Method for Open-Circuit Faults of Three-Level Inverters]]>7200620168727<![CDATA[Link Prediction Approach for Opportunistic Networks Based on Recurrent Neural Network]]>7201720252531<![CDATA[A New Lattice-Based Signature Scheme in Post-Quantum Blockchain Network]]>RandBasis algorithm from the root keys, which not only ensure the randomness, but also construct the lightweight nondeterministic wallets. Then, the proposed scheme can be proved secure in random oracle model, and it is also more efficient than similar literatures. In addition, we also give the detailed description of the post-quantum blockchain transaction. Furthermore, this work can help to enrich the research on the future post-quantum blockchain (PQB).]]>7202620333720<![CDATA[Deployable Linear-to-Circular Polarizer Using PDMS Based on Unloaded and Loaded Circular FSS Arrays for Pico-Satellites]]>72034204111093<![CDATA[Dynamic Evolution Analysis of Metro Network Connectivity and Bottleneck Identification: From the Perspective of Individual Cognition]]>7204220523392<![CDATA[Energy Efficient Downlink Resource Allocation for D2D-Assisted Cellular Networks With Mobile Edge Caching]]>7205320674983<![CDATA[Sensitivity of Low-Voltage Variable-Frequency Devices to Voltage Sags]]>7206820798326<![CDATA[RLizard: Post-Quantum Key Encapsulation Mechanism for IoT Devices]]>7208020912762<![CDATA[A Review on Miniaturized Ultrasonic Wireless Power Transfer to Implantable Medical Devices]]>7209221067010<![CDATA[Enhanced Association With Supervoxels in Multiple Hypothesis Tracking]]>7210721171570<![CDATA[Effective Fat Quantification Using Multiple Region Growing Scheme at High-Field MRI]]>7211821256363<![CDATA[On-Device AI-Based Cognitive Detection of Bio-Modality Spoofing in Medical Cyber Physical System]]>7212621372322<![CDATA[Multi-Robot Path Planning Based on Multi-Objective Particle Swarm Optimization]]>7213821478021<![CDATA[SER Analysis of Adaptive Threshold-Based Relay Selection With Limited Feedback for Type II Relay]]>$n$ -bit feedback-based ATRS scheme. Finally, for practical consideration, we provide useful discussion on the plausibility that the extended scheme can be implemented with only a 1-bit feedback.]]>7214821604807<![CDATA[A Deep Learning Approach for Credit Scoring of Peer-to-Peer Lending Using Attention Mechanism LSTM]]>7216121683719<![CDATA[Multi-Agent-Based Unsupervised Detection of Energy Consumption Anomalies on Smart Campus]]>receiver operating characteristic or precision recall curves can be used to compare the performance of different anomaly detection algorithms. In a smart campus environment, it is difficult to acquire labeled data to train a model due to the limited capabilities of the sensing devices. Therefore, distributed intelligence is preferred. In this paper, we present a multi-agent-based unsupervised anomaly detection method. We tackle these challenges in two stages with this method. First, we label the data using ensemble models. Second, we propose a method based on deep learning techniques to detect anomalies in an unsupervised fashion. The result of the first stage is used to evaluate the performance of the proposed method. We validate the proposed method with several datasets, and the experimental results demonstrate the effectiveness of our method.]]>7216921786275<![CDATA[MemWander: Memory Dynamic Remapping via Hypervisor Against Cache-Based Side-Channel Attacks]]>72179219911964<![CDATA[Frame-Type-Aware Static Time Slotted Channel Hopping Scheduling Scheme for Large-Scale Smart Metering Networks]]>7220022092030<![CDATA[A Failure Mechanism Cumulative Model for Reliability Evaluation of a k-Out-of-n System With Load Sharing Effect]]>7221022227277<![CDATA[Experimental Design via Generalized Mean Objective Cost of Uncertainty]]>7222322304366<![CDATA[A High-Speed, Scalable, and Programmable Traffic Manager Architecture for Flow-Based Networking]]>72231224311264<![CDATA[Analysis of Morphing Modes of Hypersonic Morphing Aircraft and Multiobjective Trajectory Optimization]]>7224422554555<![CDATA[Improvement of 60 GHz Transparent Patch Antenna Array Performance Through Specific Double-Sided Micrometric Mesh Metal Technology]]>$4 times 2$ microstrip patch antenna arrays operating at 60 GHz and made from double-sided micrometric mesh metal layers. A high level of optical transparency (higher than 80%) over the entire visible light spectrum coupled with a sheet resistance lower than 0.5 $Omega $ /sq of the mesh metal films are achieved. Microwave performance of the transparent antenna arrays has been performed from two different mesh ground plane patterns and compared with those of an opaque antenna array made of double-sided continuous metal films. A gain value equal to 13.6 dBi at 58.0 GHz has been recorded, against 15.6 dBi at 59.7 GHz for the opaque antenna array. The influence of the mesh structure and mesh parameters of the ground plane is investigated and discussed.]]>7225622621914<![CDATA[Locally Shared Features: An Efficient Alternative to Conditional Random Field for Semantic Segmentation]]>7226322721639<![CDATA[Prune Deep Neural Networks With the Modified <inline-formula> <tex-math notation="LaTeX">$L_{1/2}$ </tex-math></inline-formula> Penalty]]>$L_{1/2}$ penalty that reduces incorrect pruning by increasing the sparsity of the pretrained models. The modified $L_{1/2}$ penalty yields better sparsity than the $L_{1}$ penalty at a similar computational cost. Compared with the past work that numerically defines the importance of connections and re-establishes important weights when incorrect pruning occurs, our method achieves faster convergence by using a simpler pruning strategy. The results of experiments show that our method can compress LeNet300-100, LeNet-5, ResNet, AlexNet, and VGG16 by factors of $66times $ , $322times $ , $26times $ , $21times $ , and $16times $ , respectively, with negligible loss of accuracy.]]>7227322805228<![CDATA[Composition of Partially-Observable Services]]>7228122901260<![CDATA[In-Band Full-Duplex Relay-Assisted Millimeter-Wave System Design]]>7229123048094<![CDATA[SEMAX: Multi-Task Learning for Improving Recommendations]]>7230523144236<![CDATA[Design and Experimental Research of Movable Cable-Driven Lower Limb Rehabilitation Robot]]>7231523262603<![CDATA[An Analysis on the Negative Effect of Multiple-Faults for Spectrum-Based Fault Localization]]>72327234716579<![CDATA[Big Medical Data Decision-Making Intelligent System Exploiting Fuzzy Inference Logic for Prostate Cancer in Developing Countries]]>7234823638651<![CDATA[Hierarchical Distributed Coordinated Control Strategy for Hybrid Energy Storage Array System]]>7236423757622<![CDATA[Real-Time Simulation of Hybrid Modular Multilevel Converters Using Shifted Phasor Models]]>72376238611005<![CDATA[Automatic Face Recognition Based on Sparse Representation and Extended Transfer Learning]]>7238723957228<![CDATA[Comments on “Stability, l<sub>2</sub>-Gain, and Robust <inline-formula> <tex-math notation="LaTeX">$text{H}_{infty}$ </tex-math></inline-formula> Control for Switched Systems via <italic>N</italic>-Step-Ahead Lyapunov Function Approach”]]>7239624002400<![CDATA[The Devil is in the Detail: SDP-Driven Malformed Message Attacks and Mitigation in SIP Ecosystems]]>72401241712637<![CDATA[A Robust Multilevel Speech Verification With Wavelet Decomposition for Inadequate Training Data Sets of Mobile Device Systems]]>7241824286858<![CDATA[Topology-Oriented Virtual Network Embedding Approach for Data Centers]]>7242924384068<![CDATA[Brain Computer Interface for Neurodegenerative Person Using Electroencephalogram]]>72439245217783<![CDATA[Augmented Reality Based on SLAM to Assess Spatial Short-Term Memory]]>7245324662322<![CDATA[Realistic Multi-Scale Modeling of Household Electricity Behaviors]]>7246724893524<![CDATA[Prior Image Induced Regularization Method for Electrical Capacitance Tomography]]>7249025014678<![CDATA[Cooperative NOMA System With Virtual Full Duplex User Relaying]]>7250225114226<![CDATA[Analysis of the Magnetic Field in the Cavity of Multi-Layer Winding Electromagnetic Water Processor]]>7251225196983<![CDATA[3D Band-Absorptive Frequency Selective Rasorber: Concept and Analysis]]>$vert S_{11}vert le -10$ dB and $vert S_{21}vert le -10$ dB) from 4.21 to 6.51 GHz, with a thickness of 0.17 wavelength at 4.21 GHz. Moreover, $vert S_{21}vert $ is higher than −1 dB at the frequencies below 1.28 GHz. The proposed band-absorptive FSR can be used as radomes for low-frequency antennas in military communications or spectrum monitoring systems.]]>7252025286759<![CDATA[Cognitive Radio Made Practical: Forward-Lookingness and Calculated Competition]]>forward-looking ability, which enables competing radios to see beyond the present time, negotiate and optimize their actions toward a more agreeable equilibrium. Technically speaking, we adopt a belief-directed game where each mobile radio, regarded as player, formulates a belief function to project how the radio environment as a whole would respond to any of its action. This model facilitates engineering of the equilibrium by different choices of the players’ belief functions. Under this model, players will negotiate naturally through a sequence of calculated competition (i.e., cycles of teaching and learning with each other). We apply this methodology to a cognitive orthogonal frequency-division multiple-access radio network where mobile users are free to access any of the subcarriers and thus compete for radio resources to maximize their rates. The results reveal that the proposed negotiation-by-forward-looking competition mechanism guides users to converge to an equilibrium that benefits not only the individual users but the entire network approaching the maximum achievable sum-rate.]]>7254425635925<![CDATA[A Multi-Species Artificial Bee Colony Algorithm and Its Application for Crowd Simulation]]>7254925587755<![CDATA[A Proposed Modular Work Integrated Learning Framework for South Africa]]>7255925662637<![CDATA[A Symbiotic Organisms Search Algorithm for Optimal Allocation of Blood Products]]>72567258811511<![CDATA[On the Application of Massive MIMO Systems to Machine Type Communications]]>7258926118873<![CDATA[Periodic Charging for Wireless Sensor Networks With Multiple Portable Chargers]]>7261226232531<![CDATA[Lightweight and Low-Loss 3-D Printed Millimeter-Wave Bandpass Filter Based on Gap-Waveguide]]>7262426326881<![CDATA[Next Generation Technology for Epidemic Prevention and Control: Data-Driven Contact Tracking]]>7263326428153<![CDATA[A Framework to Estimate the Nutritional Value of Food in Real Time Using Deep Learning Techniques]]>7264326525332<![CDATA[Time-Varying Social-Aware Resource Allocation for Device-to-Device Communication]]>7265326634719<![CDATA[A Non-Invasive Sleep Analysis Approach Based on a Fuzzy Inference System and a Finite State Machine]]>7266426763003<![CDATA[Robust Adaptive Beamforming for Uniform Linear Arrays With Sensor Gain and Phase Uncertainties]]>7267726854406<![CDATA[Adaptive Covariance Feedback Cubature Kalman Filtering for Continuous-Discrete Bearings-Only Tracking System]]>7268626943322<![CDATA[Total Variation and Signature-Based Regularizations on Coupled Nonnegative Matrix Factorization for Data Fusion]]>72695270612638<![CDATA[Determination of Radiation Pressure in Acoustic Levitation by Optical Acoustic-Field Measurement]]>72707271911570<![CDATA[Detection and Pose Estimation for Short-Range Vision-Based Underwater Docking]]>72720274934204<![CDATA[Volume Data Denoising via Extended Weighted Least Squares]]>72750275812177<![CDATA[A Meta-Surface Decoupling Method for Two Linear Polarized Antenna Array in Sub-6 GHz Base Station Applications]]>7275927686210<![CDATA[A Novel Miniaturized Planar Ultra-Wideband Antenna]]>$times64$ mm, equivalent to a compact electrical size of $0.19lambda times 0.32 lambda $ at 1.5 GHz. The important design parameters are analyzed to comprehend the operating principle of the antenna. A good agreement between the simulated and measured results is achieved.]]>7276927736459<![CDATA[Optimal Dual Frames for Probabilistic Erasures]]>et al. investigated its dual frames for signal decoding which minimize the maximal error when the probabilistic erasures occur in the transmission process. In this paper, we present a new sufficient condition such that the canonical dual is the unique probability optimal dual for erasures. The determination conditions in our results reduces the computational complexity. We also give a necessary and sufficient condition under which a kind of alternative dual frames are probability optimal dual, and study the relation between the optimal duals of equivalent frames. Moreover, we present several examples which show that the general optimal dual frame is not a probability optimal dual frame and compare the reconstruction effects when the general optimal dual frames, the new probability optimal, and the existing probability optimal dual frames are used for decoding.]]>7277427812298<![CDATA[Parallel Implementation of Reinforcement Learning Q-Learning Technique for FPGA]]>7278227982602<![CDATA[Beamforming and Resource Allocation for a Multi-Pair Wireless Powered Two-Way Relay Network With Fairness]]>7279928103410<![CDATA[Asymmetric Controlled Bidirectional Remote Preparation of Single- and Three-Qubit Equatorial State in Noisy Environment]]>Hadamard (${H}$ ) and CNOT operations. Second, we consider our scheme in the noiseless environment and construct the appropriate measurement bases. In addition, the participants can recover the prepared states through implementing the corresponding recovery operations determinately. Third, we discuss our scheme in five types of noisy environments (amplitude-damping, phase-damping, bit-flip, phase-flip, and depolarizing noisy environment). The fidelities of the output states are calculated, which depend on the coefficients of the prepared states and the decoherence rates. Finally, some discussions and conclusions are given. Compared with previous schemes, our scheme does not need additional operations or auxiliary qubits. So it is slightly more efficient.]]>7281128223463<![CDATA[An Improved Model Combining Evolutionary Algorithm and Neural Networks for PV Maximum Power Point Tracking]]>7282328272373<![CDATA[Credibility in Online Social Networks: A Survey]]>72828285513863<![CDATA[A Decision Support System for Managing the Water Space]]>72856286910361<![CDATA[Analyzing Emergent Users’ Text Messages Data and Exploring Its Benefits]]>emergent users cannot afford this luxury, and hence, they adapt themselves to the technology that is readily available. When technology is designed, such as the mobile-phone technology, it is an implicit assumption that it would be adopted by the emergent users in due course. However, such user groups have different needs, and they follow different usage patterns as compared to users from the developed world. In this paper, we target an emergent user base, i.e., users from a university in Pakistan, and analyze their texting behavior on mobile phones. We see interesting results, such as the long-term linguistic adaptation of users in the absence of reasonable Urdu keyboards, the overt preference for communicating in Roman Urdu, and the social forces related to textual interaction. We also present two case studies on how a single dataset can effectively help understand emergent users, improve usability of some tasks, and also help users perform previously difficult tasks with ease.]]>7287028794292<![CDATA[A Clustering-Based Energy Saving Scheme for Dense Small Cell Networks]]>72880289311145<![CDATA[Exploiting Low Complexity Beam Allocation in Multi-User Switched Beam Millimeter Wave Systems]]>7289429036697<![CDATA[Aligning Business Processes With the Services Layer Using a Semantic Approach]]>7290429279158<![CDATA[Real-Time Delay Minimization for Data Processing in Wirelessly Networked Disaster Areas]]>7292829375818<![CDATA[Output Voltage Identification Based on Transmitting Side Information for Implantable Wireless Power Transfer System]]>7293829469932<![CDATA[Application of Clustering Analysis in Brain Gene Data Based on Deep Learning]]>7294729565779<![CDATA[What are the Indonesian Concerns About the Internet of Things (IoT)? Portraying the Profile of the Prospective Market]]>7295729687593<![CDATA[Terminal Guidance Based on Bézier Curve for Climb-and-Dive Maneuvering Trajectory With Impact Angle Constraint]]>$alpha $ is obtained based on the missile inverse dynamics. The shape of flight trajectory can be modified by regulating the Bézier parameters $b_{1}$ and $b_{2}$ to satisfy different tactical requirements without changing the boundary conditions. Simulation results demonstrate the effectiveness of the proposed method applied in cruise missile terminal guidance.]]>72969297711485<![CDATA[A Model of Factors Affecting Cyber Bullying Behaviors Among University Students]]>7297829855557<![CDATA[New Normal Parameter Reduction Method in Fuzzy Soft Set Theory]]>7298629987076<![CDATA[Golay Code Based Bit Mismatch Mitigation for Wireless Channel Impulse Response Based Secrecy Generation]]>7299930071796<![CDATA[Surface Charge Transport Characteristics of ZnO/Silicone Rubber Composites Under Impulse Superimposed on DC Voltage]]>7300830176474<![CDATA[An Energy Efficient Integration Model for Sensor Cloud Systems]]>7301830307212<![CDATA[Selective Timewarp Based on Embedded Motion Vectors for Interactive Cloud Virtual Reality]]>7303130454092<![CDATA[Semi-Supervised Automatic Segmentation of Layer and Fluid Region in Retinal Optical Coherence Tomography Images Using Adversarial Learning]]>73046306113380<![CDATA[ISO/IEEE 11073 Personal Health Device (X73-PHD) Standards Compliant Systems: A Systematic Literature Review]]>7306230736988<![CDATA[Energy-Delay Evaluation and Optimization for NB-IoT PSM With Periodic Uplink Reporting]]>7307430813795<![CDATA[Low-Light Image Enhancement by Principal Component Analysis]]>73082309210727<![CDATA[Recurrent Metric Networks and Batch Multiple Hypothesis for Multi-Object Tracking]]>7309331053502<![CDATA[Understanding Time-Based Trends in Stakeholders’ Choice of Learning Activity Type Using Predictive Models]]>7310631216122<![CDATA[Towards Optimizing WLANs Power Saving: Novel Context-Aware Network Traffic Classification Based on a Machine Learning Approach]]>7312231355258<![CDATA[Carrier Aggregated Radio-Over-Fiber Downlink for Achieving 2Gbps for 5G Applications]]>7313631426239<![CDATA[On Electromagnetic Radiation Control for Wireless Power Transfer in Adhoc Communication Networks: Key Issues and Challenges]]>7314331696489<![CDATA[Analysis and Accurate Prediction of User’s Response Behavior in Incentive-Based Demand Response]]>73170318012012<![CDATA[Retrieval of Ionospheric Faraday Rotation Angle in Low-Frequency Polarimetric SAR Data]]>$L$ -band or $P$ -band, has great advantages of military target detection and biomass monitoring. Nevertheless, it is more susceptible to ionospheric effects compared with the higher frequency system. A trans-ionospheric wave propagation model is established in this paper to incorporate ionospheric effects on SAR signals. As one of the significant distortion sources for the polarimetric SAR (PolSAR), Faraday rotation (FR) is mainly imposed by background ionosphere, and its spatial variation is discussed. FR estimators have been devised in succession to estimate FR angle (FRA), and various potential novel estimators can still be derived. But, from a viewpoint of theoretical expressions, the earliest estimator is bound to be the optimal one. Based on PolSAR real data, this mathematical conclusion is further validated via comprehensive performance analysis as to estimation bias and standard deviation rather than the existent root-mean-square principle. Finally, a step-by-step procedure of the FRA map is proposed and operated with an application of the airborne P-band PolSAR data. In particular, the ambiguity error of FRA estimates within a SAR observation is simulated and resolved. By processing the ALOS-2 real data, the spatial distribution of FRAs is retrieved and used to operate ionospheric total electron content soundings.]]>7318131935000<![CDATA[UAV Hovering Strategy Based on a Wirelessly Powered Communication Network]]>7319432056025<![CDATA[Efficient Object-Oriented Semantic Mapping With Object Detector]]>7320632133257<![CDATA[Utilizing Multiple-Access Communication to Realize FNN Computation in Wireless Networks]]>7321432235960<![CDATA[An Empirical Study on Forensic Analysis of Urdu Text Using LDA-Based Authorship Attribution]]>7322432345677<![CDATA[Research on Recognition of Nine Kinds of Fine Gestures Based on Adaptive AdaBoost Algorithm and Multi-Feature Combination]]>7323532468830<![CDATA[Joint Multiple Sources Localization Using TOA Measurements Based on Lagrange Programming Neural Network]]>73247326310533<![CDATA[On the Modeling of Near-Field Scattering of Vehicles in Vehicle-to-X Wireless Channels Based on Scattering Centers]]>73264327415814<![CDATA[Robust <inline-formula> <tex-math notation="LaTeX">$L_{2,1}$ </tex-math></inline-formula>-Norm Distance Enhanced Multi-Weight Vector Projection Support Vector Machine]]>$L_{2}$ -norm, which exaggerates the effects of outliers or noisy data. In order to alleviate this problem, we propose an effective novel EMVSVM, termed robust EMVSVM based on the L_{2,1}-norm distance (L_{2,1}-EMVSVM). The distances in the objective of our algorithm are measured by the L_{2,1}-norm. Besides, a new powerful iterative algorithm is designed to solve the formulated objective, whose convergence is ensured by theoretical proofs. Finally, the effectiveness and robustness of L_{2,1}-EMVSVM are verified through extensive experiments.]]>7327532866844<![CDATA[On Improving Recovery Performance in Multiple Measurement Vector Having Dependency]]>$X$ can be decomposed into a mixing matrix $A$ and a sparse matrix with independent columns $S$ . The key idea of this model is that the matrix S can be sparser than the mixing matrix $A$ . Previous MMV algorithms did not consider such a structure for $X$ . This paper proposes two algorithms, which are based on orthogonal matching pursuit and basis pursuit, and derives the exact recovery guarantee conditions for both approaches. We compare the simulation results of the proposed algorithms with the conventional algorithms and show that the proposed algorithms outperform previous algorithms especially in the case of the low number of measurements.]]>7328732972059<![CDATA[Classification of 3D Archaeological Objects Using Multi-View Curvature Structure Signatures]]>$K$ -nearest neighbor, support vector machine, and structured support vector machine. Our object descriptors classification results are compared against five popular 3D descriptors in the literature, namely, rotation invariant spherical harmonic, histogram of spherical orientations, signature of histograms of orientations, symmetry descriptor, and reflective symmetry descriptor. Experimentally, we were able to verify that our machine learnt and handcrafted descriptors offer the best classification accuracy (20% better on ave-
age than comparative descriptors), independently of the classification methods. Our proposed descriptors are able to capture sufficient information to discern among different classes, concluding that it adequately characterizes the datasets.]]>73298331313817<![CDATA[Joint Optimization on Bandwidth Allocation and Route Selection in QoE-Aware Traffic Engineering]]>7331433196408<![CDATA[Minimizing Geo-Distributed Interactive Service Cost With Multiple Cloud Service Providers]]>7332033355657<![CDATA[Jointly Optimized Energy-Minimal Resource Allocation in Cache-Enhanced Mobile Edge Computing Systems]]>7333633475591<![CDATA[Enhancement of the Duty Cycle Cooperative Medium Access Control for Wireless Body Area Networks]]>7334833598153<![CDATA[Diagnosis of Diabetic Retinopathy Using Deep Neural Networks]]>7336033705882<![CDATA[Secure Communication in Non-Geostationary Orbit Satellite Systems: A Physical Layer Security Perspective]]>7337133822644<![CDATA[A Cohesion-Based Heuristic Feature Selection for Short-Term Traffic Forecasting]]>7338333897403<![CDATA[Robust <inline-formula> <tex-math notation="LaTeX">$H_{infty}$ </tex-math></inline-formula> Control of Lurie Nonlinear Stochastic Network Control Systems With Multiple Additive Time-Varying Delay Components]]>$H_{infty }$ stability criterion is established and the controller is designed for the system in this paper. Some numerical examples are given to demonstrate the applicability of the proposed method.]]>7339034053333<![CDATA[Optimal Periodic Control of Hypersonic Cruise Vehicle: Trajectory Features]]>7340634216829<![CDATA[Rectangular Dielectric Resonator Antenna With Corrugated Walls]]>7342234296914<![CDATA[Unlabeled Short Text Similarity With LSTM Encoder]]>7343034374022<![CDATA[Accurate and Fast Harmonic Detection Based on the Generalized Trigonometric Function Delayed Signal Cancellation]]>7343834472026<![CDATA[A Robust Parameter-Free Thresholding Method for Image Segmentation]]>7344834586945<![CDATA[Digital Image Inpainting by Estimating Wavelet Coefficient Decays From Regularity Property and Besov Spaces]]>73459347110092<![CDATA[Cache Aware User Association for Wireless Heterogeneous Networks]]>73472348510208<![CDATA[Analyzing Power Beacon Assisted Multi-Source Transmission Using Markov Chain]]>7348634999213<![CDATA[Deep Reinforcement Learning Paradigm for Performance Optimization of Channel Observation–Based MAC Protocols in Dense WLANs]]>${i}$ QRA) mechanism is proposed for MAC layer channel access in dense WLANs. The performance of the proposed mechanism is evaluated through extensive simulations. Simulation results indicate that the proposed intelligent paradigm learns diverse WLAN environments and optimizes performance, compared to conventional non-intelligent MAC protocols. The performance of the proposed ${i}$ QRA mechanism is evaluated in diverse WLANs with throughput, channel access delay, and fairness as perfor-
ance metrics.]]>7350035119176<![CDATA[Adversarial Knowledge Representation Learning Without External Model]]>7351235246385<![CDATA[Modeling Stochastic Overload Delay in a Reliability-Based Transit Assignment Model]]>7352535332690<![CDATA[Robust Visual Tracking Based on Adaptive Extraction and Enhancement of Correlation Filter]]>7353435462582<![CDATA[Secure Transmission in Multi-Pair AF Relaying Massive MIMO Networks Against Active Pilot Spoofing Attacks]]>7354735605145<![CDATA[Data Analysis Approaches of Interval-Valued Fuzzy Soft Sets Under Incomplete Information]]>7356135714174<![CDATA[A Novel Control Scheme for Aircraft Engine Based on Sliding Mode Control With Acceleration/Deceleration Limiter]]>$dot {N}_{c}$ , high-pressure turbine outlet temperature increment $Delta T_{48}$ , high-pressure compressor stall margin increment $Delta SmHPC$ , and so on, are well controlled.]]>7357235803580<![CDATA[Input-to-State Stabilization of Uncertain Parabolic PDEs Using an Observer-Based Fuzzy Control]]>7358135919916<![CDATA[Multi-Set Space-Time Shift Keying Assisted Adaptive Inter-Layer FEC for Wireless Video Streaming]]>7359236091961<![CDATA[dSPACE Controller-Based Enhanced Piezoelectric Energy Harvesting System Using PI-Lightning Search Algorithm]]>73610362613179<![CDATA[The Importance of Dithering Technique Revisited With Biomedical Images—A Survey]]>7362736344496<![CDATA[Finite-Difference Time-Domain Modeling for Electromagnetic Wave Analysis of Human Voxel Model at Millimeter-Wave Frequencies]]>73635364311835<![CDATA[Cognitive Heterogeneous Networks With Multiple Primary Users and Unreliable Backhaul Connections]]>73644365511976<![CDATA[False Data Injection Attacks With Incomplete Network Topology Information in Smart Grid]]>73656366415162<![CDATA[Secure and Efficient Multi-Authority Attribute-Based Encryption Scheme From Lattices]]>$mathbb {Z}_{q}$ -invertible matrix with a lower runtime. Based on it, combining the trapdoor generation and delegation algorithm in MP12, we designed multiple attribute authorities which can manage different attribute sets and generate private keys for the user independently. In addition, the Shamir’s secret sharing technique is introduced to support policies expressed in any monotone access structures. Compared with the existing related schemes, the proposed scheme can improve the functional agility and the flexibility of the access policy prominently, and it also can achieve a better performance with less lattice dimension, trapdoor storage occupation, and ciphertext expansion rate. The analysis shows that our scheme is feasible and superior in the large-scale distributed environment.]]>7366536743606<![CDATA[An Asymptotic Ensemble Learning Framework for Big Data Analysis]]>7367536937709<![CDATA[Gale-Shapley Matching Game Selection—A Framework for User Satisfaction]]>7369437035251<![CDATA[Design of a Frequency-Selective Rasorber Based on Notch Structure]]>7370437112822<![CDATA[Using Firework Algorithm for Multi-Objective Hardware/Software Partitioning]]>73712372115035<![CDATA[Pre-Migration of Vehicle to Network Services Based on Priority in Mobile Edge Computing]]>7372237304742<![CDATA[Guaranteed Performance of Nonlinear Attitude Filters on the Special Orthogonal Group SO(3)]]>$mathbb {SO}left ({3}right)$ , able to ensure prescribed measures of transient and steady-state performance. The tracking performance of the normalized Euclidean distance of attitude error is trapped to initially start within a large set and converge systematically and asymptotically to the origin from almost any initial condition. The convergence rate is guaranteed to be less than the prescribed value, and the steady-state error does not exceed a predefined small value. The first filter uses a set of vectorial measurements with the need for attitude reconstruction. The second filter does not require attitude reconstruction and instead uses only a rate gyroscope measurement and two or more vectorial measurements. These filters provide good attitude estimates with superior convergence properties and can be applied to measurements obtained from low-cost inertial measurement units. The simulation results illustrate the robustness and effectiveness of the proposed attitude filters with guaranteed performance considering high level of uncertainty in angular velocity along with body-frame vector measurements.]]>7373137456107<![CDATA[Big Data Driven Oriented Graph Theory Aided tagSNPs Selection for Genetic Precision Therapy]]>73746375412276<![CDATA[Full State Tracking and Formation Control for Under-Actuated VTOL UAVs]]>7375537666295<![CDATA[Artificial-Noise-Aided Precoding Design for Multi-User Visible Light Communication Channels]]>7376737775178<![CDATA[Power- and Time-Aware Deep Learning Inference for Mobile Embedded Devices]]>7377837895234<![CDATA[Integrating Economic Model Predictive Control and Event-Triggered Control: Application to Bi-Hormonal Artificial Pancreas System]]>7379037999416<![CDATA[Laparoscopic Image-Guided System Based on Multispectral Imaging for the Ureter Detection]]>7380038094796<![CDATA[Research on Big Data Security Storage Based on Compressed Sensing]]>7381038258874<![CDATA[Integrating an Attention Mechanism and Convolution Collaborative Filtering for Document Context-Aware Rating Prediction]]>7382638354251<![CDATA[Moth-Flame Algorithm for Accurate Simulation of a Non-Uniform Electric Field in the Presence of Dielectric Barrier]]>$left ({beta }right)$ , which is dependant on three values, relative permittivity, barrier location, and barrier thickness. The MFO is working to minimize the error given by $beta $ using two new optimization factors in the $beta $ equation. To ensure the accurate validation of MFO with a minimum error for field problem simulation, various artificial intelligence (AI) optimization techniques have been compared with the MFO obtained results. The comparative study shows that MFO is more effective, especially at 30% of the gap length from the HV electrode which represents the region of highly non-uniform field along the gap configuration. The numerical results of the field simulation that are held by different types of AI techniques are compared with those obtained from the accurate simulation results using the finite-element method. The value of the error between the numerical and simulation results shows that MFO is the most effective optimization techniques that can be used in the numerical equation-
to obtain the best value of the correction factor. With MFO, good agreement has been reached between the proposed numerical equation and the accurate simulation values of the electric field problem.]]>73836384710837<![CDATA[Quantitative Analysis of Blood Flow in Cerebral Venous Sinus With Stenosis by Patient-Specific CFD Modeling]]>7384838546861<![CDATA[A Survey on Mobile Crowd-Sensing and Its Applications in the IoT Era]]>73855388112285<![CDATA[Multi-Label Question Classification for Factoid and List Type Questions in Biomedical Question Answering]]>Coenzyme Q(10) is classified under two categories in Unified Medical Language System (UMLS): organic chemical and biologically active substance. This inherent characteristic of biomedical entities makes question classification in the biomedical domain a multi-label classification problem, where one question might expect answers belonging to more than one semantic type. To the best of our knowledge, several QA systems deal with question classification as a multi-class classification problem and only one state-of-the-art system – OAQA – deals with it as a multi-label classification problem. In this paper, we analyze the pipeline of the OAQA system for factoid and list type questions, emphasizing the multi-label question classification. We use an improved question classification dataset with the copy transformation technique to improve the performance of list type -
uestions. Moreover, we introduce a binary transformation in the pipeline of factoid questions to increase its performance. Our modified methodology enhances the performance of both list and factoid type questions by a margin of 2% and 3% evaluated on standard $F_{1}$ and Mean Reciprocal Rank measures, respectively.]]>7388238967367<![CDATA[Fully Coupled Electrothermal Simulation of Large RRAM Arrays in the “Thermal-House”]]>73897390812764<![CDATA[Similarity Measure Based on Incremental Warping Window for Time Series Data Mining]]>7390939175919<![CDATA[Face Detection for Privacy Protected Images]]>et al.’s homomorphic encryption algorithm to protect image privacy. The security analysis of Li et al.’s encryption algorithm shows that the scheme we proposed is secure under the known plaintext attack and ciphertext attack. The experimental results show that the scheme can be implemented in polynomial time.]]>7391839277066<![CDATA[An Improved Multisensor Data Fusion Method and Its Application in Fault Diagnosis]]>7392839374696<![CDATA[An Efficient Strong Designated Verifier Signature Based on <inline-formula> <tex-math notation="LaTeX">$mathcal{R}-$ </tex-math></inline-formula>SIS Assumption]]>et al., has the property that only the designated verifier can verify the generated signature. In order to prevent an eavesdropper to get the signature on-line before the designated verifier receives it, they also proposed strong designated verifier signature (SDVS). In this paper, according to an efficient SDVS proposed by Saeednia et al., we present a post-quantum SDVS in the random oracle model based on lattice assumption. The unforgeability is based on the hardness of the average-case hard problem $mathcal {R}-$ SIS$_{q,n,m,beta }$ , which is at least as hard as worst-case SVP$_{gamma }$ over ideal lattices. In addition, compared with existing lattice-based SDVS schemes, our scheme cuts by more than 50 percent repetitions and the size of signature is shorter with 256 bits security.]]>7393839473851<![CDATA[Clone Detection Based on Physical Layer Reputation for Proximity Service]]>73948395713632<![CDATA[An Effective Dictionary Learning Algorithm Based on fMRI Data for Mobile Medical Disease Analysis]]>$mathrm {ell 2}$ -norm and $mathfrak{F}$ -norm regularization constraint is adopted to avoid over-fitting, achieve the limitations of the model space, and improve the generalization ability of the model. In order to extract features better, this paper uses the cosine similarity method to select good feature subsets, which effectively improves further the generalization ability and enhances the feature extraction accuracy. The results show that the improved dictionary classification algorithm has better performance in terms of accuracy, sensitivity, and specificity, and it also demonstrates that the proposed algorithm has an effective classification about mobile multimedia medical diseases, which can provide a better guidance for the diagnosis of later diseases, so as to promote the rapid development of medical feature extraction.]]>7395839665737<![CDATA[Multiple Kernel Fuzzy Clustering With Unsupervised Random Forests Kernel and Matrix-Induced Regularization]]>7396739799563<![CDATA[Frequency Hopping and Parallel Driving With Random Delay Especially Suitable for the Charger Noise Problem in Mutual-Capacitive Touch Applications]]>7398039938414<![CDATA[A Community Merger of Optimization Algorithm to Extract Overlapping Communities in Networks]]>7399440055842<![CDATA[Domain-RIP Analysis: A Technique for Analyzing Mutation Stubbornness]]>7400640238349<![CDATA[Intrinsic Image Sequence Decomposition Using Low-Rank Sparse Model]]>7402440306189<![CDATA[Zone-Based Cooperative Content Caching and Delivery for Radio Access Network With Mobile Edge Computing]]>7403140449069<![CDATA[Enhanced Deep Networks for Short-Term and Medium-Term Load Forecasting]]>7404540556907<![CDATA[Machine Learning and Uncertainty Quantification for Surrogate Models of Integrated Devices With a Large Number of Parameters]]>74056406610828<![CDATA[Efficient Confidence-Based Hierarchical Stereo Disparity Upsampling for Noisy Inputs]]>74067408214955<![CDATA[Protective Performance of Different Passivators on Oil-Paper Insulation Containing Multiple Corrosive Sulphides]]>74083409013968<![CDATA[Revenue Model of Supply Chain by Internet of Things Technology]]>7409141009697<![CDATA[Face Alignment via Multi-Regressors Collaborative Optimization]]>7410141121748<![CDATA[A <italic>Posteriori</italic> Multiobjective Self-Adaptive Multipopulation Jaya Algorithm for Optimization of Thermal Devices and Cycles]]>2 cycle and the irreversible Carnot power cycle. A posteriori is proposed, and it is applied for the multiobjective optimization of the selected thermal devices and cycles to obtain the sets of nondominated alternative solutions. The results of computational experiments obtained by the MO-SAMP Jaya algorithm are found to be better than those obtained by the latest reported optimization algorithms.]]>7411341346154<![CDATA[Fall Detection in Videos With Trajectory-Weighted Deep-Convolutional Rank-Pooling Descriptor]]>7413541444205<![CDATA[Health Status Prediction Based on Belief Rule Base for High-Speed Train Running Gear System]]>74145415911273<![CDATA[Multiplexed OAM Wave Communication With Two-OAM-Mode Antenna Systems]]>7416041661369<![CDATA[Smart Information Retrieval: Domain Knowledge Centric Optimization Approach]]>7416741839461<![CDATA[Block-Based Optical Color Image Encryption Based on Double Random Phase Encoding]]>7418441944315<![CDATA[AI-Powered Green Cloud and Data Center]]>7419542034861<![CDATA[Fog Load Balancing for Massive Machine Type Communications: A Game and Transport Theoretic Approach]]>7420442185122<![CDATA[IEC 61850-Based Communication Modeling of EV Charge-Discharge Management for Maximum PV Generation]]>7421942318657<![CDATA[Gene Expression Analysis for Early Lung Cancer Prediction Using Machine Learning Techniques: An Eco-Genomics Approach]]>7423242383436<![CDATA[An Implantable Wideband Circularly Polarized Microstrip Patch Antenna via Two Pairs of Degenerate Modes]]>30 and TM_{03}) in MPA have been excited and lowered for resonance in proximity to a pair of fundamental degenerate modes (TM_{10} and TM_{01}). The proper disturbance of these two pairs of radiative resonant modes can contribute to the generation of two CP radiating waves at two near-by operating frequencies, aiming to realize CP radiation in a wide operating band covered by these two frequencies. A novel implantable wideband CP MPA is proposed and developed due to the emergence of two minima in the axial-ratio (AR) frequency response. The designed MPA is then demonstrated to tremendously achieve the wide 3-dB AR bandwidth which covers the 2.4 to 2.48 GHz ISM-band in the cubic human skin model. Moreover, the proposed CP MPA shows good tolerance to the variety of tissue according to our study on sensitivity and model integrity. Finally, the designed CP MPA is fabricated and tested, and a good agreement exists between measured and simulated results in a wide frequency region.]]>7423942472263<![CDATA[Cyclical NOMA Based UAV-Enabled Wireless Network]]>7424842595546<![CDATA[A New Adaptive Compensation Control for Parametric Systems With Actuator Aging]]>7426042667346<![CDATA[A Horst-Type Power Divider With Wide Frequency Tuning Range Using Varactors]]>${f}_{H}/{f}_{L}= 4.67$ :1), with in-band input and output return losses, both better than 22 dB, and an insertion loss of 3.2–4 dB. The measured in-band isolation is better than 15 dB. The power divider has a simple layout and a compact size of $0.2,,lambda _{g} times 0.16,,lambda _{g}$ , which demonstrates the excellent potential of the proposed power divider for modern communication systems.]]>7426742745550<![CDATA[A Modified Deep Convolutional Neural Network for Abnormal Brain Image Classification]]>7427542835177<![CDATA[A Connecting Timetable Rescheduling Model for Production and Rail Transportation With Unexpected Disruptions]]>7428442948301<![CDATA[Semi-Global Robust Stabilization for a Class of Nonlinear Systems With Uncertain Measurement Functions]]>7429543011692<![CDATA[A Survey on the Progress of Testing Techniques and Methods for Wireless Sensor Networks]]>74302431612352<![CDATA[Channel Constrained Multiple Selective Retransmissions for OFDM System: BER and Throughput Analysis]]>7431743262996<![CDATA[Discrete-Time Adaptive Control for Systems With Input Time-Delay and Non-Sector Bounded Nonlinear Functions]]>et al. for italic uncertain scalar and multivariable input delay systems with uncertain parameters as well as uncertain input gain. While it has been shown by Kanellakopoulos and Fu, et al. that it is possible to design adaptive control laws that compensate for the growth of the nonlinearity for single parameter scalar systems, a rigorous analysis of multiple parameter systems is not shown. In this paper, it is shown that an adaptive controller design that compensates for the growth of the nonlinearity is possible for both multiple parameter scalar and multivariable systems with input delay. Rigorous stability proofs and simulations are presented to verify the validity of the approach.]]>7432743373753<![CDATA[Multi-Hop Cognitive Wireless Powered Networks: Outage Analysis and Optimization]]>7433843477438<![CDATA[Interference Alignment Schemes Using Latin Square for K <inline-formula> <tex-math notation="LaTeX">$times$ </tex-math></inline-formula> 3 MIMO X Channel]]>$K times 3$ multiple-input multiple-output X channel. Since the proposed scheme can have a larger set of possible beamformers than the conventional schemes, its performance is improved by efficient beamformer selection for a given channel realization. Also, we propose a condition number-based beamformer selection method with low computational complexity and its performance improvement is numerically verified.]]>7434843576946<![CDATA[An Approximate Schur Decomposition-Based Spatial Domain Color Image Watermarking Method]]>74358437013753<![CDATA[Sliding-Mode-Based Trajectory Tracking and Load Sway Suppression Control for Double-Pendulum Overhead Cranes]]>74371437914582<![CDATA[Physical Layer Encryption Algorithm Based on Polar Codes and Chaotic Sequences]]>7438043905129<![CDATA[MF-TDMA Scheduling Algorithm for Multi-Spot Beam Satellite Systems Based on Co-Channel Interference Evaluation]]>7439143997052<![CDATA[Joint VMIMO and LDPC Decoders for IR-UWB Wireless Body Area Network]]>74400440912133<![CDATA[Energy-Efficient Distributed Leader Selection Algorithm for Energy-Constrained Wireless Sensor Networks]]>7441044217808<![CDATA[Total Variation Denoising With Non-Convex Regularizers]]>$ell _{1}$ regularizer for anisotropic case and $ell _{2}$ regularizer for isotropic case). However, these convex regularizers often underestimate the high-amplitude components of the true image. In this paper, non-convex regularizers for 2-D TV denoising models are proposed. These regularizers are based on the Moreau envelope and minimax-concave penalty, which can maintain the convexity of the cost functions. Then, efficient algorithms based on forward–backward splitting are proposed to solve the new cost functions. The numerical results show the effectiveness of the proposed non-convex regularizers for both synthetic and real-world image.]]>74422443117089<![CDATA[Energy Management and Coordinated Control Strategy of PV/HESS AC Microgrid During Islanded Operation]]>7443244415135<![CDATA[Spherical Coverage Characterization of 5G Millimeter Wave User Equipment With 3GPP Specifications]]>7444244522585<![CDATA[Modeling and Analysis of Aeroelasticity and Sloshing for Liquid Rocket]]>7445344656509<![CDATA[CXNet-m1: Anomaly Detection on Chest X-Rays With Image-Based Deep Learning]]>74466447716573<![CDATA[Social Network Rumor Diffusion Predication Based on Equal Responsibility Game Model]]>74478448611188<![CDATA[Analysis of Information Reliability on Dynamics of Connected Vehicles]]>7448744958009<![CDATA[QFM Signals Parameters Estimation Based on Double Scale Two Dimensional Frequency Distribution]]>7449645053265<![CDATA[An Easily Fabricated Linear Piezoelectric Actuator Using Sandwich Longitudinal Vibrators With Four Driving Feet]]>${V} _{mathrm {P-P}}$ . The mechanical characteristics of the prototype show that the exciting voltages can be used for the speed control due to the approximately linear relationship between them.]]>74506451512169<![CDATA[A Self-Reconfiguration Planning Strategy for Cellular Satellites]]>7451645282755<![CDATA[Incorporating Importance Sampling in EM Learning for Sequence Detection in SPAD Underwater OWC]]>7452945373545<![CDATA[Label-Free Detection of Dissolved Carbon Dioxide Utilizing Multimode Tapered Optical Fiber Coated Zinc Oxide Nanorice]]>2) is developed using a tapered optical fiber sensor. The tapered region of the optical fiber is coated with the zinc oxide (ZnO) nanorice and used as a probe for dCO_{2} sensing. The sensor probe was exposed to different concentrations of dCO_{2} solution ranging from 10 to 100 ppm. ZnO nanorice can adsorb dCO_{2} via strong hydrogen bonding due to the presence of plenty of oxygen atoms on its surface layer. The interaction between ZnO nanorice and dCO_{2} changes the optical properties of the ZnO nanorice layer, resulting in the change in reflectance. From the experiment, the result shows that there is an improvement in the sensitivity of the sensor when higher concentration was used. A broad linear trend ranging from 0 to 60 ppm ($R^{2} = 0.972$ ) is observed for the sensor probe that is coated with 1.0 M of ZnO nanorice compared with the 0.1 M and 0.5 M ZnO nanorice concentrations. The sensor sensitivity obtained is 0.008 mW/ppm. The sensor demonstrates a response and recovery time of 0.47 and 1.70 min, respectively. Good repeatability is obtained with the standard deviation in the range of 0.008–0.027. The average resolution calculated for this sensor is 4.595 ppm.]]>7453845456181<![CDATA[Determining the Required Probe Vehicle Size for Real-Time Travel Time Estimation on Signalized Arterial]]>7454645546089<![CDATA[Comparative Review of Energy Storage Systems, Their Roles, and Impacts on Future Power Systems]]>7455545854245<![CDATA[Research on Series Arc Fault Detection Based on Higher-Order Cumulants]]>74586459715081<![CDATA[Security of Functionally Obfuscated DSP Core Against Removal Attack Using SHA-512 Based Key Encryption Hardware]]>74598461012223<![CDATA[Human Interactive Behavior: A Bibliographic Review]]>74611462812044<![CDATA[An Attribute-Based High-Level Image Representation for Scene Classification]]>7462946407368<![CDATA[Robust Locally Discriminant Analysis via Capped Norm]]>$L_{2} $ -norm with $L_{2,1} $ - norm to construct the robust between-class scatter matrix and using the capped norm to further reduce the negative impact of outliers in constructing the within-class scatter matrix, we can guarantee the robustness of the proposed methods. In addition, we also impose $L_{2,1} $ -norm regularized term on projection matrix, so that its joint sparsity can be ensured. Since we redefine the scatter matrices in traditional LDA, the projection numbers we obtain are no longer restricted by the class numbers. The experimental results show the superior performance of RLDA to other compared dimensionality reduction methods.]]>7464146525119<![CDATA[The Asynchronous Gimbal-Rotation-Based Calibration Method for Lever-Arm Errors of Two Rotational Inertial Navigation Systems]]>74653466310951<![CDATA[Friction Damper-Based Passive Vibration Control Assessment for Seismically-Excited Buildings Through Comparison With Active Control: A Case Study]]>74664467513095<![CDATA[Adaptive Sample Weight for Machine Learning Computer Vision Algorithms in V2X Systems]]>7467646874682<![CDATA[Multi-Channel System for Simultaneous <italic>In Situ</italic> Monitoring of Ion Flux and Membrane Potential in Plant Electrophysiology]]>in vivo and in situ in plants is a challenging research task. To explore the mechanisms of plant electrical activity, researchers urgently need to understand and determine the types of ions and the ion fluxes that pass in and out of cells during polarization and repolarization, but the required measurements are very difficult to perform. In this paper, we have developed a versatile system that can detect the ionic flux and the membrane potential, in vivo and in situ, simultaneously. The system uses a self-referencing ion-selective glass microelectrode and a membrane potential glass microelectrode as sensors. These sensors are linked through a preamplifier with high input impedance to a specific dynamic measurement system that can amplify small extracellular concentration gradient signals and realize simultaneous measurement of both the ion flux and the membrane potential. In addition, an interpolation fitting algorithm has been proposed to reduce the artifacts that are present in the in situ measurements during plant growth. The hydrogen ion fluxes in wheat roots were measured using the self-referencing ion-selective microelectrodes, and the proposed system was used to measure NaCl stimulation-induced changes in the membrane potentials and hydrogen ion fluxes of wheat root epidermal cells. The results demonstrate that the system can meet the ion flux and membrane potential measurement requirements.]]>74688469714584<![CDATA[Do Google App Engine’s Runtimes Perform Homogeneously? An Empirical Investigation for Bonus Computing]]>southamerica-east1 and us-central1 performs dramatically worse than that in the other regions.]]>7469847086483<![CDATA[Day-Ahead and Intraday Forecasts of the Dynamic Line Rating for Buried Cables]]>7470947258647<![CDATA[Circuit Aware Approximate System Design With Case Studies in Image Processing and Neural Networks]]>7472647345015<![CDATA[Design of a 3-D Integrated Wideband Filtering Magneto-Electric Dipole Antenna]]>$text {SWR}le 1.5$ from 1.58 to 2.79 GHz. Moreover, the low back radiation levels (${le } -16$ dB), stable radiation patterns with low cross polarization levels (${le } -26$ dB), and an average antenna gain of 7.8 dBi are achieved within the operating band. In addition, an out-of-band suppression level, better than 17 dB, is reached.]]>7473547407383<![CDATA[New Approach for Automated Epileptic Disease Diagnosis Using an Integrated Self-Organization Map and Radial Basis Function Neural Network Algorithm]]>7474147474235<![CDATA[Efficient Authentication of Multi-Dimensional Top-<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> Queries]]>$k$ queries to retrieve $k$ records whose outputs with user-supplied scoring function are among the top $k$ . Multi-dimensional top-$k$ query is widely used in real applications, such as information retrieval, decision making, and disease prediction. Unfortunately, the traditional query authentication methods cannot be directly deployed on multi-dimensional top-$k$ query, thus it is still a challenging problem to authenticate multi-dimensional top-$k$ query results. We first propose an authentication solution to support multi-dimensional top-$k$ query based on signature chain. By using signature chain for each record and its successors on each dimension, our solution allows users to efficiently verify the soundness and completeness of the multi-dimensional top-$k$ query results. In addition, we propose an extended solution using larger grid size in order to decrease the overhead in the data owner side in sparse data distribution. The security analysis shows that our multi-dimensional top-$k$ query authentication solutions are secure. Through theoretical analysis and simulation, we demonstrate the effectiveness and efficiency of our proposed solution.]]>74748476212571<![CDATA[AP Selection Scheme Based on Achievable Throughputs in SDN-Enabled WLANs]]>7476347725711<![CDATA[The Influence of Junction Temperature Variation of LED on the Lifetime Estimation During Accelerated Aging Test]]>74773478114385<![CDATA[Epsim: A Scalable and Parallel Marssx86 Simulator With Exploiting Epoch-Based Execution]]>$12.8times $ speed on average with 16-core parallel simulation from the SPEC CPU2006 benchmarks and the PARSEC benchmarks, providing the performance scalability.]]>74782479410812<![CDATA[STANN: A Spatio–Temporal Attentive Neural Network for Traffic Prediction]]>7479548069855<![CDATA[Bilinear Adaptive Generalized Vector Approximate Message Passing]]>${text {Y}}sim p({text {Y}}|{text {Z}})=prod limits _{i,j}p(Y_{ij}|Z_{ij})$ , where ${text {Z}}={text {A}}({text {b}}){text {X}}$ , ${text {A}}(cdot)$ is a known affine linear function of b, and $p(Y_{ij}|Z_{ij})$ is a scalar conditional distribution that models the general output transform. A wide range of real-world applications, e.g., quantized compressed sensing with matrix uncertainty, blind self-calibration and dictionary learning from nonlinear measurements, one-bit matrix completion, and joint channel and data decoding, can be cast as the generalized bilinear recovery problem. To address this problem, we propose a novel algorithm called the Bilinear Adaptive Generalized Vector Approximate Message Passing (BAd-GVAMP), which extends the recently proposed Bilinear Adaptive Vector AMP algorithm to incorporate arbitrary distributions on the output transform. The numerical results on various applications demonstrate the effectiveness of the proposed BAd-GVAMP algorithm.]]>7480748153163<![CDATA[High-Gain Fabry-Perot Antennas With Wideband Low Monostatic RCS Using Phase Gradient Metasurface]]>74816482410423<![CDATA[Quantum Algorithm for Spectral Regression for Regularized Subspace Learning]]>7482548326780<![CDATA[Deep Hierarchical Network With Line Segment Learning for Quantitative Analysis of Facial Palsy]]>7483348429641<![CDATA[An Efficient Neighbor Discovery Scheme for Mobile WSN]]>7484348554025<![CDATA[Latency Analysis of Wireless Networks for Proximity Services in Smart Home and Building Automation: The Case of Thread]]>74856486715961<![CDATA[Development of a Wall-Climbing Drone Capable of Vertical Soft Landing Using a Tilt-Rotor Mechanism]]>7486848792114<![CDATA[OFDM Modulated PNC in V2X Communications: An ICI-Aware Approach Against CFOs and Time-Frequency-Selective Channels]]>7488048973295<![CDATA[A More Reasonable Definition of Failure Mode for Mechanical Systems Using Meta-Action]]>7489849045388<![CDATA[Energy Efficiency Analysis of Bidirectional Wireless Information and Power Transfer for Cooperative Sensor Networks]]>7490549123021<![CDATA[Machine-Learning-Based Parallel Genetic Algorithms for Multi-Objective Optimization in Ultra-Reliable Low-Latency WSNs]]>$K$ -means clustering algorithm to construct a 2-tier network topology, the proposed algorithm designs the fetal dataset, denoted by the population, and develops a clustering method of energy conversion to prevent overloaded cluster heads. A multi-objective optimization model is formulated to simultaneously satisfy multiple optimization objectives including the longest network lifetime and the highest network connectivity and reliability. Under this model, the principal component analysis algorithm is adopted to eliminate the various optimization objectives’ dependencies and rank their importance levels. Considering the NP-hardness of wireless network scheduling, the genetic algorithm is used to identify the optimal chromosome for designing a near-optimal clustering network topology. Moreover, we prove the convergence of the proposed algorithm both locally and globally. Simulation results are presented to demonstrate the viability of the proposed algorithm compared to state-of-the-art algorithms at an acceptable computational complexity.]]>74913492611093<![CDATA[Spiking Echo State Convolutional Neural Network for Robust Time Series Classification]]>74927493511013<![CDATA[Speech Enhancement Based on Dictionary Learning and Low-Rank Matrix Decomposition]]>7493649477252<![CDATA[A Comprehensive Review of Enhancements and Prospects of Fast Handovers for Mobile IPv6 Protocol]]>7494849787831<![CDATA[Unwrapped Phase Estimation via Normalized Probability Density Function for Multibaseline InSAR]]>$2pi $ period for different baseline cases. Then, a new maximum likelihood estimation is established using the MB normalized pdfs, which has a much steeper peak around the true phase value than the single baseline case and leads to higher estimation accuracy. The proposed W2UP method estimates the unwrapped phase from multiple filtered interferograms, so it is less influenced by the phase noise. Both the theoretical analysis and results using the simulated and real MB data are provided to verify the effectiveness of the proposed method.]]>74979498819186<![CDATA[Exploiting the Clustered Sparsity for Channel Estimation in Hybrid Analog-Digital Massive MIMO Systems]]>7498950005167<![CDATA[Energy Efficiency Optimization of Distributed Massive MIMO Systems Under Ergodic QoS and Per-RAU Power Constraints]]>$textit {ergodic}$ per-user quality-of-service and per-remote antenna unit (RAU) transmit power constraints, we investigate the problem of maximizing energy efficiency (EE) of distributed massive MIMO systems, which is known to be non-convex. To solve this challenging problem efficiently, we first derive closed-form expressions for the spectral efficiency and the power control parameters (related to per-RAU transmit power constraint) with zero-forcing (ZF) and maximum ratio transmission (MRT) beamforming, and then develop a computationally feasible power allocation algorithm using the tools of fractional programming and sequential convex approximation. The derived closed-form expressions are functions of only slowly changing large-scale fading which enables us to solve the optimization problem over a longer time interval. The proposed power allocation algorithm is guaranteed to converge to the Karush–Kuhn–Tucker points of the original non-convex EE maximization problem. The simulation results demonstrate the accuracy of the derived expressions and the effectiveness of the proposed algorithm. Moreover, some insightful conclusions are arrived at from the EE comparisons between different beamforming schemes (ZF and MRT) and different antenna deployments (distributed and co-located).]]>7500150133391<![CDATA[Syntax-Directed Hybrid Attention Network for Aspect-Level Sentiment Analysis]]>75014502510887<![CDATA[Low Cross-Polarization, High-Isolation Microstrip Patch Antenna Array for Multi-Mission Applications]]>$2 times 2$ element subarrays of the proposed unit cell, while the horizontal polarization ports are mirrored, are designed and fabricated, and a lower than −39-dB cross-polarization level is achieved in the measurement results. Finally, to characterize the scan performance of the unit cell and subarray, a $4 times 10$ element array of the proposed single element is fabricated and a better than −45-dB cross-polarization level is observed while scanning up to 45°.]]>7502650332108<![CDATA[Low-Power (1T1N) Skyrmionic Synapses for Spiking Neuromorphic Systems]]>75034504417482<![CDATA[Closed-Form Solution for Optimal Compression Matrix Design in Distributed Estimation]]>7504550562479<![CDATA[Robust Adaptive Trajectory Linearization Control for Tracking Control of Surface Vessels With Modeling Uncertainties Under Input Saturation]]>75057507014892<![CDATA[Optimal Power and Performance Management for Heterogeneous and Arbitrary Cloud Servers]]>7507150847448<![CDATA[Binary Output Layer of Feedforward Neural Networks for Solving Multi-Class Classification Problems]]>$r$ ($rgeq 3$ ) classes of samples. The common and conventional setting of the output layer called “$one - to - one~approach$ ” in this paper, is as follows: The output layer contains $r$ output nodes corresponding to the $r$ classes. And for an input sample of the $i$ -th class ($1leq ileq r$ ), the ideal output is 1 for the $i$ -th output node, and 0 for all the other output nodes. We propose in this paper a new “$binary~approach$ ”: Suppose $2^{q-1}< rleq 2^{q}$ with $qgeq 2$ , then we let the output layer contain $q$ output nodes, and let the ideal outputs for the $r$ classes be designed in a binary manner. This idea of binary output is also applied for other classifiers, such as support vector machines and associative pulsing neural networks. Numerical simulations are carried out on eight rea-
-world data sets, showing that our binary approach performs as well as, but uses less output nodes and hidden-output weights than, the traditional one-to-one approach.]]>7508550947432<![CDATA[All Passive Realization of Lossy Coupling Matrices Using Resistive Decomposition Technique]]>7509551057818<![CDATA[A Branch-and-Bound Algorithm for Minimizing the Total Tardiness of a Three-Agent Scheduling Problem Considering the Overlap Effect and Environmental Protection]]>7510651239324<![CDATA[Defeating Untrustworthy Testing Parties: A Novel Hybrid Clustering Ensemble Based Golden Models-Free Hardware Trojan Detection Method]]>75124514011251<![CDATA[Machine Learning Model for Adaptive Modulation of Multi-Stream in MIMO-OFDM System]]>75141515213288<![CDATA[On the Girth of Tanner (3, 13) Quasi-Cyclic LDPC Codes]]>$13p$ for $p$ being a prime of the form $(39m+1)$ . First, the cycle structure of Tanner (3, 13) QC-LDPC codes is analyzed, and the cycles of length lesser than 12 are divided into five equivalent classes. Based on each equivalent class, the existence of the cycles is equivalent to the solution of polynomial equations in a 39th unit root in the prime filed $mathbb {F}_{p}$ . By solving these polynomial equations over $mathbb {F}_{p}$ and summarizing the resulting candidate prime values, the girth of Tanner (3, 13) QC-LDPC codes is obtained. As an advantage, Tanner (3, 13) QC-LDPC codes have much higher code rates than Tanner (3, 5), (3, 7), (3, 11), and (5, 7) QC-LDPC codes, and provide a promising coding scheme for the data storage systems and optical communications.]]>7515351795987<![CDATA[Ontology-Based Personalized Course Recommendation Framework]]>75180519910398<![CDATA[Facial Action Units-Based Image Retrieval for Facial Expression Recognition]]>7520052077965<![CDATA[2D Image Deformation Based on Guaranteed Feature Correspondence and Mesh Mapping]]>7520852213587<![CDATA[Declarative Specification of Bidirectional Transformations Using Design Patterns]]>75222524911092<![CDATA[Remote Sensing Image Haze Removal Using Gamma-Correction-Based Dehazing Model]]>75250526113725<![CDATA[New Approach for Conversational Agent Definition by Non-Programmers: A Visual Domain-Specific Language]]>7526252768731<![CDATA[Edge Cache-Based ISP-CP Collaboration Scheme for Content Delivery Services]]>7527752848250<![CDATA[Screen Content Image Quality Assessment With Edge Features in Gradient Domain]]>75285529512794<![CDATA[Multi-Regularization-Constrained Blur Kernel Estimation Method for Blind Motion Deblurring]]>${L} _{0}$ norm, and the dark channel prior. Second, in order to preserve the continuity and the sparsity, and to remove the flaw in the BK, a dual-constrained regularization model, which combines the ${L} _{0}$ -regularized intensity prior and the ${L} _{2}$ -regularized gradient prior, is proposed for accurate BK estimation. The proposed model can not only preserve the continuity and the sparsity of the BK very well but also can remove the flaw thoroughly. Finally, we propose an efficient optimization strategy which can solve the proposed model efficiently. Extensive experiments compared with the state-of-the-art methods demonstrate that our method estimates more accurate BKs and obtains higher quality deblurring images in terms of both subjective vision and quantitative metrics.]]>7529653114550<![CDATA[A Modified GLT Double Faults Isolation Approach Based on MLE and RPV for Six-Gyro Redundant SINS]]>75312533216506<![CDATA[A Novel Region-Refinement Pulse Width Modulation Method for Torque Ripple Reduction of Brushless DC Motors]]>75333534211009<![CDATA[Multi-Gram CNN-Based Self-Attention Model for Relation Classification]]>75343535711340<![CDATA[Single Fuzzy Parameter Seepage Model of Oil and Gas Reservoir]]>7535853672950<![CDATA[Efficient Calculation of Minimum Distance Between Capsules and Its Use in Robotics]]>7536853739565<![CDATA[Sensing Platform for Two-Phase Flow Studies]]>7537453825878<![CDATA[Raccoon Optimization Algorithm]]>7538353998514<![CDATA[Self-Organizing Approximation Command Filtered Backstepping Control for Higher Order SISO Systems in Internet of Things]]>7540054118165<![CDATA[IPSO Task Scheduling Algorithm for Large Scale Data in Cloud Computing Environment]]>7541254204963<![CDATA[Improved Alpha-Guided Grey Wolf Optimizer]]>75421543718139<![CDATA[Deep Learning Assessment of Myocardial Infarction From MR Image Sequences]]>7543854469919<![CDATA[General Reentry Trajectory Planning Method Based on Improved Maneuver Coefficient]]>7544754567199<![CDATA[Photoacoustic Image Classification and Segmentation of Breast Cancer: A Feasibility Study]]>7545754669706<![CDATA[Sensing Performance of Modified Single Mode Optical Fiber Coated With Nanomaterials-Based Ammonia Sensors Operated in the C-Band]]>3) in low concentrations. The SMF is etched with hydrofluoric acid and subsequently tapered using a glass processing workstation. The etched tapered SMF is coated with PANI via spray-coating deposition. This SMF modification significantly enhances the interaction of the evanescent field of the light propagating in the core with the PANI-sensing layer. The modified fiber sensor response is investigated by exposing the sensor to different concentrations of NH_{3} over the C-band wavelengths of 1535–1565 nm. Integrating the modified optical fiber with the nanostructured PANI films produces highly sensitive optical sensor that operates at room temperature. The $50~mu text{m}$ etched tapered SMF coated with PANI produced response, recovery times, and sensitivity of 58 and 475 s, and 231.5%, respectively, in the C-band range. The limit of detection of the modified fiber sensor was 0.0025%, which is equal to 25 ppm. The developed sensor exhibits good repeatability, reversibility, and selectivity.]]>75467547611413<![CDATA[Deep Learning-Based Sustainable Data Center Energy Cost Minimization With Temporal MACRO/MICRO Scale Management]]>75477549111679<![CDATA[SPADE: Activity Prediction in Smart Homes Using Prefix Tree Based Context Generation]]>7549255016789<![CDATA[A H<inline-formula> <tex-math notation="LaTeX">$_{infty}$ </tex-math></inline-formula> PI<inline-formula> <tex-math notation="LaTeX">$_{varepsilon}$ </tex-math></inline-formula>D-Based Observer Designed by LMI for Some Special System]]>$Hinfty $ proportional–integral–derivative ($PI^{varepsilon }D$ )-based observer designed by linear matrix inequality (LMI). First, an augmented system is designed to ensure the asymptotic stability of the system with the $Hinfty $ -based $PI^{varepsilon }D$ observer. Then, the proportional, integral, and derivative gains of $PI^{varepsilon }D$ observer are designed based on $Hinfty $ synthesis. Finally, the $Hinfty $ synthesis problem is translated into LMI, and through solving the LMI, the proposed observer can ensure the performance of $Hinfty $ . The observation of vehicle longitudinal tire force is followed as an example, whose closed-loop system with traditional PID observer could not guarantee asymptotic stability. Both simulation and experimental results illustrate the great performance of the proposed observer.]]>7550255075738<![CDATA[Application of Internet of Things Technology in 3D Medical Image Model]]>7550855186120<![CDATA[Adaptive Robust Control of Multi-Axle Vehicle Electro-Hydraulic Power Steering System With Uncertain Tire Steering Resistance Moment]]>7551955305923<![CDATA[Secure Wireless Information and Power Transfer Based on Tilt Adaptation in 3-D Massive MIMO Systems]]>7553155406911<![CDATA[Development of Modular Cable-Driven Parallel Robotic Systems]]>7554155532135<![CDATA[An Effective Algorithm for Delay Fractional Convection-Diffusion Wave Equation Based on Reversible Exponential Recovery Method]]>$L_{1}$ approximation and the second-order spatial derivative is approximated by the centered finite difference scheme. The numerical solution can be obtained by an inverse exponential recovery method. By introducing a new weighted norm and applying discrete Gronwall inequality, the solvability, unconditionally stability, and convergence in the sense of $L_{2}$ - and $L_{infty }$ - norms are proved rigorously. Finally, we present a numerical example to verify the effectiveness of our algorithm.]]>7555455633931<![CDATA[Ensemble Learning of Multiple-View 3D-CNNs Model for Micro-Nodules Identification in CT Images]]>$20times 20times 3$ , $16times 16times 3$ , $12times 12times 3$ , $8times 8times 3$ , and $4times 4times 3$ . Then, five distinct 3D-CNN models are built and implemented on one size of the nodule candidates. An extreme learning machine (ELM) network is utilized to integrate the five 3D-CNN outputs, yielding the final classification results. The performance of the proposed system is assessed in terms of accuracy, area under the curve (AUC), F-score, and sensitivity. It is found that the proposed system yields an accuracy, AUC, F-score, and sensitivity of 97.35%, 0.98, 96.42%, and 96.57%, respectively. These performances are highly superior to those of 2D-CNNs, single 3D-CNN model, as well as those-
by the state-of-the-art methods implemented on the same dataset. For the ensemble method, ELM achieves better performance than the majority voting, averaging, AND operator, and autoencoder. The results demonstrate that developing an automatic system for discriminating between micro-nodules and non-nodules in CT images is feasible, which extends lung cancer studies to micro-nodules. The combination of multiple-view 3D-CNNs and ensemble learning contribute to excellent identification performance, and this strategy may help develop other reliable clinical-decision support systems.]]>7556455767568<![CDATA[Neural Network Based Brain Tumor Detection Using Wireless Infrared Imaging Sensor]]>75577558812100<![CDATA[Robust Array Diagnosis Against Array Mismatch Using Amplitude-Only Far Field Data]]>$ell _{2}$ -norm of the array excitation vector based on Gaussian probability distribution is formulated. Besides, the prior knowledge on ideal array excitation and array mismatch are utilized to facilitate array excitation restoration. The alternating direction method of multipliers which performs well with the large-scale data is applied to solve the proposed optimization problem. Computer simulations are conducted to verify the validity and superiority of the proposed method. It is shown that in the presence of array mismatch, the proposed method provides better accuracy of the restored array excitation and smaller diagnosis error rate than the method which does not consider array mismatch. Furthermore, results using experimental data are also included to verify the validity of the proposed method.]]>7558955964715<![CDATA[Combining Adaptive Hierarchical Depth Motion Maps With Skeletal Joints for Human Action Recognition]]>7559756088746<![CDATA[A Switching Approach to Packet Loss Compensation Strategy]]>7560956151943<![CDATA[Verifiable Keyword-Based Semantic Similarity Search on Social Data Outsourcing]]>7561656255783<![CDATA[Web News Mining Using New Features: A Comparative Study]]>75626564111745<![CDATA[Low-Rank Phase Retrieval via Variational Bayesian Learning]]>7564256482877<![CDATA[Localization Performance Under Middle and Low Frequency Sound Source Based on Time Reversal Method in Enclosed Space]]>75649566110585<![CDATA[A Cooperative Coevolution Algorithm for the <italic>Seru</italic> Production With Minimizing Makespan]]>Seru production can be used to enhance productivity, such as makespan reduction and manpower saving. Seru system operation includes two NP-hard problems, i.e., seru formation and seru scheduling. The exact solution cannot be obtained by solving only one of seru formation and seru scheduling. We develop a cooperative coevolution algorithm for the Seru production with minimizing makespan by solving the seru formation and seru scheduling simultaneously. The cooperative coevolution algorithm includes two evolution algorithms, i.e., the algorithm combining generic algorithm and local search, and the ant colony optimization algorithm. The former algorithm is used to deal with the evolution of seru formation. The latter is used to find a better seru scheduling. In the cooperative mechanism, the two algorithms cooperate to seek a better solution of seru system operation. Finally, extensive-tested experiments show that the proposed cooperative coevolution algorithm can obtain a better solution than all the existing algorithms and, even, can obtain the exact solution for some medium-and-small instances.]]>7566256704314<![CDATA[Gate Switch Selection for In-Band Controlling in Software Defined Networking]]>exhaustive search and random search. Through extensive simulation, we demonstrate that the proposed algorithm performs much better than the random search and is comparable to the exhaustive search.]]>75671568111093<![CDATA[CP-ABSE: A Ciphertext-Policy Attribute-Based Searchable Encryption Scheme]]>dynamics), and search results verifiable capability (verifiability). However, most of the existing works endow the data user an unlimited search capacities and do not consider a data user’s search permissions. In practical application, granting search privileges for data users is a very important measure to enforce data access control. In this paper, we propose an attribute-based searchable encryption scheme by leveraging the ciphertext-policy attribute-based encryption technique. Our scheme allows the data owner to conduct a fine-grained search authorization for a data user. The main idea is that a data owner encrypts an index keyword under a specified access policy, if and only if, a data user’s attributes satisfy the access policy, the data user can perform search over the encrypted index keyword. We provide the detailed correctness analyses, performance analyses, and security proofs for our scheme. The extensive experiments demonstrate that our proposed scheme outperforms the similar work CP-ABKS proposed by Zheng on many aspects.]]>75682569413237<![CDATA[Markov Chain Based Efficient Defense Against Adversarial Examples in Computer Vision]]>7569557069870<![CDATA[Collaborative Additional Variational Autoencoder for Top-N Recommender Systems]]>7570757135040<![CDATA[EMI-Free Bidirectional Real-Time Indoor Environment Monitoring System]]>2 concentration, volatile organic compound level, O_{2} concentration, temperature, and relative humidity, at multiple positions in real time. In addition, a proposed average-voltage tracking algorithm is adopted to allow the LED illumination to be used as a lighting system and as a long-range wireless communication system. As a result, the proposed system is demonstrated to be error-free when the distance between the base station and the smart sensor tags is 6 m. The measured live data are aggregated and visualized in a cloud platform by a graphical user interface. A web-based application and a mobile application are also developed to display the real-time data.]]>75714572212702<![CDATA[Learning to Fuse Multiscale Features for Visual Place Recognition]]>7572357352045<![CDATA[Weakly Supervised Deep Depth Prediction Leveraging Ground Control Points for Guidance]]>7573657485483<![CDATA[Understanding the User’s Economical and Psychological Intentions to Snatch Electronic Red Envelopes: An Experimental Study]]>7574957592152<![CDATA[Performances Enhancement of Fingerprint Recognition System Using Classifiers]]>7576057689965<![CDATA[Directional Receivers for Diffusion-Based Molecular Communications]]>7576957835840<![CDATA[Achieving Semantic Secure Search in Cloud Supported Information-Centric Internet of Things]]>7578457948561<![CDATA[Indoor Collaborative Positioning With Adaptive Particle-Pair Filtering Based on Dynamic User Pairing]]>75795580711205<![CDATA[MT-DMA: A DMA Controller Supporting Efficient Matrix Transposition for Digital Signal Processing]]>7580858186376<![CDATA[Registration Center Based User Authentication Scheme for Smart E-Governance Applications in Smart Cities]]>75819583310216<![CDATA[Stabilization of a Relative Equilibrium for an Underactuated AUV With Disturbances Rejection]]>7583458455615<![CDATA[Synchronous and Asynchronous Radar Interference Mitigation]]>75846585218152<![CDATA[Finite-Time Formation Control for Unmanned Aerial Vehicle Swarm System With Time-Delay and Input Saturation]]>7585358645449<![CDATA[Distributed Small-Signal Equivalent Circuit Model and Parameter Extraction for SiGe HBT]]>$1times 1.2times 30,,mu text{m}^{2}$ SiGe HBT from 100 MHz to 20.89 GHz. The simulated $S$ -parameters in the proposed transmission line model are in close agreement with the measured data, and the frequency characteristics of the transistors are well predicted.]]>7586558735078<![CDATA[Nearest Centroid Neighbor Based Sparse Representation Classification for Finger Vein Recognition]]>${k}$ NCN-SRC) is presented. The previously proposed recognition algorithms are mainly based on distance computation. In the proposed method, the distance, as well as the spatial distribution, are considered to achieve a better recognition rate. The proposed method consists of two stages: first, the ${k}$ nearest neighbors of the test sample are selected based on the nearest centroid neighbor, and then, in the second stage, based on the selected number of closest nearest centroid neighbors (${k}$ ), the test sample is classified by sparse representation. Findings from the proposed method ${k}$ NCN-SRC demonstrated an increased recognition rate. This improvement can be attributed to the selection of the train samples, where the train samples are selected by considering the spatial and distance distribution. In addition, the complexity of SRC is reduced by reducing the number of train samples for the classification of the test sample by sparse representation and the processing speed of the proposed algorithm is significantly improved in comparison with the conventional SRC which is due to the reduced number of training samples. It can be concluded that the ${k}$ NCN-SRC classification method is efficient for finger vein recognition. An increase in the recognition rate of 3.35%, 9.07%, 20.23%, and 0.81%-
is obtained for the proposed ${k}$ NCN-SRC method in comparison with the conventional SRC for the four tested public finger vein databases.]]>7587458852738<![CDATA[Pattern Recognition Using Relevant Vector Machine in Optical Fiber Vibration Sensing System]]>7588658951203<![CDATA[A Game-Theoretical Modelling Approach for Enhancing the Physical Layer Security of Non-Orthogonal Multiple Access System]]>7589659043925<![CDATA[Echo: An Edge-Centric Code Offloading System With Quality of Service Guarantee]]>7590559173198<![CDATA[Passive Earth Pressures on Retaining Walls for Pit-in-Pit Excavations]]>75918593115279<![CDATA[Indoor Positioning of RBF Neural Network Based on Improved Fast Clustering Algorithm Combined With LM Algorithm]]>7593259457219<![CDATA[Multi-Objective Migrating Birds Optimization Algorithm for Stochastic Lot-Streaming Flow Shop Scheduling With Blocking]]>7594659628851<![CDATA[A Review of Biosensors for Non-Invasive Diabetes Monitoring and Screening in Human Exhaled Breath]]>7596359746999<![CDATA[Energy-Efficient Clustering Algorithm for Magnetic Induction-Based Underwater Wireless Sensor Networks]]>7597559839085<![CDATA[A Modified Gravitational Search Algorithm for Function Optimization]]>$Kbest$ is used in a new version of GSA, which is called repulsive GSA with exponential $Kbest$ (EKRGSA). In this algorithm, heavy particles repulse or attract all particles according to distance, and all particles search the solution space under the combined action of repulsive force and gravitational force. In this way, the exploration ability of the algorithm is improved and a proper balance between exploration and exploitation is established. Moreover, the exponential $Kbest$ significantly decreases the computational time. The proposed algorithm is tested on a set of benchmark functions and compared with other algorithms. The experimental results confirm the high efficiency of EKRGSA.]]>75984599314198<![CDATA[A Survey on Biometric Authentication: Toward Secure and Privacy-Preserving Identification]]>7599460099384<![CDATA[Tuning the Aggressive Slow-Start Behavior of MPTCP for Short Flows]]>76010602412533<![CDATA[Frequency Selective Rasorber and Reflector With Two-Sided Absorption Bands]]>7602560311868<![CDATA[Cooperative SWIPT Transmission in Overlay Multi-Antennas Hierarchical Cognitive Radio Networks]]>7603260463592<![CDATA[Reliable Integrated ASC and DYC Control of All-Wheel-Independent-Drive Electric Vehicles Over CAN Using a Co-Design Methodology]]>76047605910064<![CDATA[Recommendation System Based on Singular Value Decomposition and Multi-Objective Immune Optimization]]>7606060716114<![CDATA[Observer-Based Adaptive Neural Control for Non-Triangular Form Systems With Input Saturation and Full State Constraints]]>7607260833606<![CDATA[Wavelet Transform Time-Frequency Image and Convolutional Network-Based Motor Imagery EEG Classification]]>7608460932211<![CDATA[Sparse Bayesian Learning Based Space-Time Adaptive Processing Against Unknown Mutual Coupling for Airborne Radar Using Middle Subarray]]>7609461087456<![CDATA[Design and Implementation on Hyperledger-Based Emission Trading System]]>7610961163801<![CDATA[PBCert: Privacy-Preserving Blockchain-Based Certificate Status Validation Toward Mass Storage Management]]>76117612813441<![CDATA[GIS-Based Rapid Disaster Loss Assessment for Earthquakes]]>76129613910710<![CDATA[Visualization and Interpretation Tool for Expert Systems Based on Fuzzy Cognitive Maps]]>7614061503874<![CDATA[Performance Improvement of Microwave Vector Modulator Through Coupler Characteristic Impedance Optimization and Bond-Wire Inductance Utilization]]>$mu text{m}$ GaAs pHEMT process and assembled on Rogers 5880 substrate with 10-mil-thick printed circuit board. The assembled vector modulator is characterized using an automatic test setup. The measured symmetric constellation is in good agreement with the simulation result, which indicates the effectiveness of the proposed design method and assembly process.]]>76151616012289<![CDATA[Not in My Neighborhood: A User Equipment Perspective of Cellular Planning Under Restrictive EMF Limits]]>76161618524372<![CDATA[Recurrent Conditional Generative Adversarial Network for Image Deblurring]]>7618661935415<![CDATA[Reliability and Safety Modelling of the Electrical Control System of the Subsea Control Module Based on Markov and Multiple Beta Factor Model]]>76194620812568<![CDATA[Non-Ionized, High-Resolution Measurement of Internal and Marginal Discrepancies of Dental Prosthesis Using Optical Coherence Tomography]]>7620962181899<![CDATA[Oil-in-Water Two-Phase Flow Pattern Identification From Experimental Snapshots Using Convolutional Neural Network]]>7621962255665<![CDATA[Provable Data Integrity of Cloud Storage Service With Enhanced Security in the Internet of Things]]>7622662398091<![CDATA[Proximity Effects of Lateral Conductivity Variations on Geomagnetically Induced Electric Fields]]>7624062485490<![CDATA[3-D Localization With Multiple LEDs Lamps in OFDM-VLC System]]>versus computational complexity comparative analysis is carried out with the parameter variations of these estimators. The numerical results indicate a decade improvement in the RMSE for every two decades of decrement of power noise on the receiver photodiode. The best clipping factor is obtained through the analysis of locator accuracy and transmission capacity for each simulated system. Finally, the numerical results also demonstrate effectiveness, robustness, and efficiency of the proposed architecture.]]>7624962618820<![CDATA[Secure Identifier Management Based on Blockchain Technology in NDN Environment]]>7626262684204<![CDATA[Optimal Transport for Gaussian Mixture Models]]>7626962783736<![CDATA[Deep Learning With Emerging New Labels for Fault Diagnosis]]>76279628710182<![CDATA[Decentralized Big Data Auditing for Smart City Environments Leveraging Blockchain Technology]]>76288629616639<![CDATA[Development of Super-Resolution Sharpness-Based Axial Localization for Ultrasound Imaging]]>$f_{0} = 7$ MHz and wavelength $lambda = 220,,mu text{m}$ ) showed that the normalized sharpness method can provide scatterer axial localization with an accuracy down to $2~mu text{m}$ ($< 0.01lambda $ ), which is a two-order of magnitude improvement compared to that achievable by the conventional imaging ($approx lambda $ ), and a five-fold improvement compared to the COM estimate ($approx 10~mu text{m}$ or $0.05lambda $ ). Similar results were obtained experimentally using wire-target data acquired by the Synthetic Aperture Real-time Ultrasound System. The performance of the proposed method was also found to be consistent across different types of ultrasound transmission. The localization precision deteriorates in the presence of noise, but even in very low signal-to-noise ratio (SNR = 0 dB), the uncertainty was not higher than $6~mu text{m}$ , which outperforms the COM estimate. The method can be implemented in image data as well as by using the raw signals. It is proposed that the signal-derived localization s-
ould replace the image-based equivalent, as it provides at least 10 times improved accuracy.]]>7629763098052<![CDATA[Effects of Lateral Conductivity Variations on Geomagnetically Induced Currents: H-Polarization]]>7631063187945<![CDATA[Finite-Time Non-Fragile Control of a Class of Uncertain Linear Positive Systems]]>$H_{infty }$ performance in a specified time interval. The main issue is to give a sufficient condition for the solution of the designed finite-time non-fragile $H_{infty }$ controller associated with the several control techniques applied to the positive system. The design result is described as an optimization problem that can be expressed through a couple of linear matrix inequalities. In the end, we use a practical RL circuit model to evaluate the performance of the proposed controller.]]>7631963262229<![CDATA[Efficient Multiple Concatenated Codes With Turbo-Like Decoding for UEP Wireless Transmission of Scalable JPEG 2000 Images]]>7632763369631<![CDATA[A Novel Nested Q-Learning Method to Tackle Time-Constrained Competitive Influence Maximization]]>7633763526934<![CDATA[DQ-Voltage Droop Control and Robust Secondary Restoration With Eligibility to Operate During Communication Failure in Autonomous Microgrid]]>7635363615912<![CDATA[Noncoherent Detection With Polar Codes]]>76362637211524<![CDATA[Approximate Computing With Stochastic Transistors’ Voltage Over-Scaling]]>76373638514394<![CDATA[Mining Dynamics of Research Topics Based on the Combined LDA and WordNet]]>7638663999464<![CDATA[Research on the Isolation and Collection Method of Multi-Channel Temperature and Power Supply Voltage Under Strong Marine Controlled Source EMI]]>7640064119168<![CDATA[Controllable Sparse Antenna Array for Adaptive Beamforming]]>$l_{0}$ -norm constrained normalized least-mean-square (CNLMS) adaptive beamforming algorithm for controllable sparse antenna arrays. To control the sparsity of the antenna array, an $l_{0}$ -norm penalty is used as a constraint in the CNLMS algorithm. The proposed algorithm inherits the advantages of the CNLMS algorithm in beamforming. The $l_{0}$ -norm constraint can force the quantities of antennas to a certain number to control the sparsity by selecting a suitable parameter. In addition, the proposed algorithm accelerates the convergence process compared with the existing algorithms in sparse array beamforming, and its convergence is presented in this paper. To reduce the computation burden, an approximating $l_{0}$ -norm method is employed. The performance of the proposed algorithm is analyzed through simulations for various array configurations.]]>76412642310362<![CDATA[Local Feature Descriptor for Image Matching: A Survey]]>76424643412716<![CDATA[Joint Transmit Power and Bandwidth Allocation for Cognitive Satellite Network Based on Bargaining Game Theory]]>7643564491680<![CDATA[Stochastic Security Assessment for Power Systems With High Renewable Energy Penetration Considering Frequency Regulation]]>7645064604571<![CDATA[Trace Ratio Criterion Based Large Margin Subspace Learning for Feature Selection]]>$ell _{2,1}$ -norm is imposed on the subspace projection matrix to enforce row sparsity. The resulting trace ratio optimization problem, which can be connected to a nonlinear eigenvalue problem, is hard to solve. Thus, we design an efficient iterative algorithm and present a theoretical analysis of the convergence. Finally, we evaluate the proposed method by comparing it against several other state-of-the-art methods. The extensive experiments on real-world datasets show the superiority of our proposed approach.]]>76461647211350<![CDATA[Deployment of IoV for Smart Cities: Applications, Architecture, and Challenges]]>76473649211649<![CDATA[A Self-Organized Task Distribution Framework for Module-Based Event Stream Processing]]>EdgeCEP. Our system request is event-dependent specified in a brand-new event specification language; still, the event is stored and processed by the relational database. We newly formulate the problem of self-organized task distribution subjective to preferable constraints of computation and communication. The solution for each broker to find individual optimal decision is to apply tabu search with flow-based greedy move regarding pre-ranking flow table. Many experiments are conducted to study and evaluate the performance of the proposed system. The simulation shows that the proposed flow optimization outperforms the naïve algorithm, concretely, 2-times more tasks getting processed and successfully delivered within the same fixed period. The proposed edge-centric method achieves data traffic 7-times less than the cloud-centric approach. The prototype engines have been deployed and evaluated in the real environment.]]>7649365092138<![CDATA[Analysis and Modeling for the Real-Time Condition Evaluating of MOSFET Power Device Using Adaptive Neuro-Fuzzy Inference System]]>76510651810239<![CDATA[A Survey of Super-Resolution in Iris Biometrics With Evaluation of Dictionary-Learning]]>$15times 15$ pixels being the smallest resolution evaluated. To the best of our knowledge, this is the smallest resolutions employed in the literature. The experimental framework is complemented with six publicly available iris comparators that were used to carry out biometric verification and identification experiments. The experimental results show that the proposed method significantly outperforms both the bilinear and bicubic interpolations at a very low resolution. The performance of a number of comparators attains an impressive equal error rate as low as 5% and a Top-1 accuracy of 77%–84% when considering the iri-
images of only $15 times 15$ pixels. These results clearly demonstrate the benefit of using trained super-resolution techniques to improve the quality of iris images prior to matching.]]>7651965444589<![CDATA[Feasibility of Index-Coded Retransmissions for Enhancing Sidelink Channel Efficiency of V2X Communications]]>sidelink, which enables direct data transfer among vehicle user equipments (UEs) without the aid of network infrastructure. Since a sidelink transmitter is not able to have the receiver information due to the lack of feedback channels, the vehicle UE unconditionally triggers sidelink retransmissions regardless of the receiver’s status. Although this retransmission scheme is essential in a vehicular environment, the scheme has an inherent limitation in a performance aspect due to its redundant retransmissions, which eventually reduces the amount of the radio resource available for new sidelink transmissions. To resolve this issue, we propose to exploit the concept of index coding, which is effective for transferring multiple data blocks in an efficient way, to the sidelink retransmissions. We add an index-coding process to the sidelink retransmission procedure to make it consume the radio resource more efficiently. We also investigate how the sidelink protocol can be modified so that the proposed scheme can be realized in practical LTE systems. The intensive simulations and numerical analysis validate the feasibility of the proposed scheme for the enhancement of the sidelink performance in the aspect of channel efficiency.]]>7654565526978<![CDATA[Adaptive Interaction Controller for Compliant Robot Base Applications]]>7655365615741<![CDATA[Decision Provenance: Harnessing Data Flow for Accountable Systems]]>Decision provenance entails using provenance methods to provide information exposing decision pipelines: chains of inputs to, the nature of, and the flow-on effects from the decisions and actions taken (at design and run-time) throughout systems. This paper introduces the concept of decision provenance, and takes an interdisciplinary (tech-legal) exploration into its potential for assisting accountability in algorithmic systems. We argue that decision provenance can help facilitate oversight, audit, compliance, risk mitigation, and user empowerment, and we also indicate the implementation considerations and areas for research necessary for realizing its vision. More generally, we make the case that considerations of data flow, and systems more broadly, are important to discussions of accountability, and complement the considerable attention already given to algorithmic specifics.]]>7656265743396<![CDATA[<inline-formula> <tex-math notation="LaTeX">$L_{21}$ </tex-math></inline-formula>-Norm Based Loss Function and Regularization Extreme Learning Machine]]>$L_{21} $ -norm minimization of both loss function and regularization (LR21-ELM). Our $L_{21} $ -norm-based loss function can diminish the undue influence of noises and outliers of data points compared with the $L_{2} $ -norm based loss function and make the learned ELM model more robust and stable. The powerful structural sparse-inducing $L_{21} $ -norm regularization is integrated into the ELM objective function to eliminate the potential redundant neurons of ELM adaptively and reduce the complexity of the learning model. We introduce an effective iterative optimization algorithm to solve the $L_{21} $ -norm minimization problem. Empirical tests on a number of benchmark datasets indicate that our proposed algorithm can generate a more compact, robust, and discriminative model compared with the original ELM algorithm.]]>7657565866983<![CDATA[Research on Scene Understanding-Based Encrypted Image Retrieval Algorithm]]>7658765965466<![CDATA[Single RF-Chain Beam Training for MU-MIMO Energy Efficiency and Information-Centric IoT Millimeter Wave Communications]]>7659766104589<![CDATA[A Wearable Activity Recognition Device Using Air-Pressure and IMU Sensors]]>