By Topic

Electro/Information Technology (EIT), 2012 IEEE International Conference on

Date 6-8 May 2012

Filter Results

Displaying Results 1 - 25 of 83
  • Overlay-NoC and H-Phy based computing using modern Chip Multiprocessors

    Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (727 KB) |  | HTML iconHTML  

    Constant growth in demand for computational power requires advances in the internal mechanisms of multiprocessor computing structures. Such architectures may include many (sometimes, even millions of) processors performing processing tasks. Each technique that increases efficiency leads to significant benefits in operational energy and task execution time. Due the scale of multiprocessor computing structures, the importance of achieving faster and efficient systems is invaluable. In this paper, we present two different approaches for processing tasks on multiprocessor architectures: Hardware-Physical (H-Phy) and Overlay-Network-on-Chip (Overlay-NoC). Both methods are described and compared. We also present the research plan, models, simulation assumptions, and results of research. The paper is summarized with conclusions and future work plan. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Factors impacting innovation in a product development organization

    Page(s): 1 - 11
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (631 KB) |  | HTML iconHTML  

    Numerous product development (PD) organizations have integrated innovative products in order to remain competitive and retain their customer base. The major goal of this study is to assist managers in the selection of appropriate innovative CAD technology for their organizations by focusing on eight critical factors that could guide their decision-making process when recommending specific innovative CAD technologies; perceived usefulness, perceived ease of use, organization support, organizational size, cost-effectiveness, system quality, organizational need, and function-effectiveness. Theoretical foundation used for this study was the technology acceptance model (TAM). Parametric statistic methods were used to test perceptions of decision makers toward innovative CAD technologies. Results indicated perceived usefulness, perceived ease of use, organizational support, cost-effectiveness, system quality, organizational need, and functional effectiveness are important attributes in the decision process of acceptance of innovative CAD technologies. The positive relationship indicates that when these seven variables increased the intent to adopt increased as well. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Design of cyber-physical interface for automated vital signs reading in electronic medical records systems

    Page(s): 1 - 10
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1031 KB) |  | HTML iconHTML  

    The focus of this project is to study the design of a cyber-physical interface for automated vital sign readings in Electronic Medical Record Systems. This is presented as a solution for a need in actual EMR systems where the reading of vital signs is done manually which is error prone and time consuming. The domain application knowledge and prototype used for the development of this paper is made possible with the collaboration of the Alliance of Chicago Community Health Center LLC. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An algorithm to solve the Dominating Set Problem on GPUs

    Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (105 KB) |  | HTML iconHTML  

    A brute-force algorithm to solve small instances of the Dominating Set Problem on GPUs is presented. Two implementations of the algorithm are discussed, one that uses atomic operations and one that uses reductions. Experimental results are reported. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Enhancing S-LEACH security for wireless sensor networks

    Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (235 KB) |  | HTML iconHTML  

    Developing effective security solutions for wireless sensor networks (WSN) are not easy due to limited resources of WSNs and the hazardous nature of wireless medium. The implementation of encryption/decryption algorithms which are the most essential part of the secure communication can be very intricate in WSNs since they incorporate routines that having very complex and intense computing procedures. A secure clustering protocol that achieves the desired security goals while keeping an acceptable level of energy consumption is a challenging problem in wireless sensor network. LEACH (Low-Energy Adaptive Clustering Hierarchy) protocol is a basic clustering-based routing protocol for WSNs. S-LEACH is the first modified version of LEACH with cryptographic protection against outsider attacks. This paper proposes MS-LEACH to enhance the security of S-LEACH by providing data confidentiality and node to cluster head (CH) authentication using pairwise keys shared between CHs and their cluster members. The security analysis of proposed MS-LEACH shows that it has efficient security properties and achieves all WSN security goals compared to the existing secured solutions of LEACH protocol. A simulation based performance evaluation of MS-LEACH demonstrates the effectiveness of proposed MS-LEACH protocol and shows that the protocol achieves the desired security goals and outperforms other protocols in terms of energy consumption, network lifetime, network throughput and normalized routing load. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Avian detection & tracking algorithm using infrared imaging

    Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1160 KB) |  | HTML iconHTML  

    This paper presents a method for target detection and tracking of IR images in the application of avian surveillance. As there are many reports of avian mortality due to collision with turbine blades, the detection and tracking of birds at turbine sites is an important issue. In this work, three different background subtraction techniques are first applied to detect moving objects. Otsu thresholding method is then extended by incorporating an adaptive variable based on the mean of each frame and certain constant value. Filtering using morphological operations is applied. Results of three different techniques are then compared. Selected technique (RA) followed by thresholding and filtering is then used for tracking and information extraction. Results show that proposed method provides the needed accuracy for IR imagery. This method can be effectively used in different applications of IR imaging. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The BIO-acoustic feature extraction and classification of bat echolocation calls

    Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (789 KB) |  | HTML iconHTML  

    There are reports that large number of bat fatalities occur near wind turbines. Acoustic characteristics can be employed for bat call recognition to better understand the effects of turbines on different bat species. Acoustic features of bat echolocation calls are extracted based on three different techniques: Short Time Fourier Transform (STFT), Mel Frequency Cepstrum Coefficient (MFCC) and Discrete Wavelet Transform (DWT). These features are fed into an Evolutionary Neural Network (ENN) for their classification at the species level using acoustic features. Results from different feature extraction techniques are compared based on classification accuracy. The technique can identify bats and will contribute towards developing mitigation procedures for reducing bat fatalities. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Evolutionary Neural Network parallelization with multicore systems on chip

    Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (810 KB) |  | HTML iconHTML  

    Evolutionary Neural Network (ENN) has attracted great attention among the researchers in recent years because of its effectiveness at function optimization and, its efficiency in searching large and complex spaces to find nearly global optima. In this work, Parallel Evolutionary Neural Network algorithm is proposed and implemented on Multi-core system on chip. The algorithm is parallelized, partitioned, mapped, and scheduled on multicore. The algorithm is also implemented on single core for comparison. The parallel ENN is developed in C# using .Net framework 4.0. The .Net framework offers comprehensive and flexible threads APIs that allow the efficient implementation of multithreaded applications. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Parallelization of feature extraction techniques on consumer-level multicore system

    Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (795 KB) |  | HTML iconHTML  

    Three different feature extractions techniques Fast Fourier Transform (FFT), Mel-Frequency Ceptral Coefficient (MFCC), and Discrete Wavelet Transform (DWT) are parallelized in this study and used for classification. The Evolutionary Neural Network (ENN) is used as a classifier. In the scope of classification, ENN is a new technique that can be effectively used as a classifier. This research will help to extract the features in the most efficient way with less computation time in real life use. The parallel FFT, MFCC and DWT are developed in C# for multicore using .Net framework 4.0. The .Net framework offers comprehensive and flexible threads APIs that allow the efficient implementation of multithreaded application. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Robust consensus control by state-dependent dithers

    Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (179 KB) |  | HTML iconHTML  

    This paper introduces a new method for enhancing robustness against communication uncertainties in consensus control by using a state and sampling-interval dependent dither in signal transmission. This method is based on the principle of Itô's formula for stochastic differential equation in which the diffusion term introduces a quadratic term in stability analysis. It is revealed that this feature can be utilized to provide robustness against communication multiplicative uncertainties, much beyond the ability of traditional feedback robustness design. Algorithms are introduced and their convergence properties are established. It is shown that appropriate design of the dithers can create a highly robust consensus control. Simulation results are used to illustrate the benefits of this method. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An ontology-based data fusion framework for profiling sensors

    Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (718 KB) |  | HTML iconHTML  

    Data-to-decision systems must fuse information from heterogeneous sources to infer a high-level understanding of a situation. A high degree of confidence in the inferred knowledge is necessary for appropriate actions to be taken based upon the assessment of a situation. This paper presents an extensible Semantic Web compatible framework that uses rich ontological descriptions for the autonomous and human-aided fusion of heterogeneous sensors and algorithms to create evidence-based hypotheses of a situation under persistent surveillance. Raw data acquired from profiling sensors is combined with the output of visualization and classification algorithms, yielding information with a higher degree of confidence than what would be obtained without the fusion process. The framework can readily accommodate other data sources and algorithms into the fusion process. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Custom designed CPU architecture based on a hardware scheduler and independent pipeline registers — Concept and theory of operation

    Page(s): 1 - 5
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (964 KB) |  | HTML iconHTML  

    System response time is a key element in hard real time systems. In classical Real Time Operating Systems (RTOS) based on software schedulers, overhead and jitter are a major problem when the number of tasks and the rate of context switches are high. Increased values for those parameters over admissible values can lead to performance degradation, increased power consumption or even deadline misses. If a part of the scheduling components or the entire functionality is moved from software to hardware, a significant improvement in task switching times can be achieved. This paper presents a custom designed multi pipeline register architecture (MPRA) that has a dedicated hardware scheduler unit integrated into the CPU. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An image-based pavement distress detection and classification

    Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1036 KB) |  | HTML iconHTML  

    This paper presents a pavement segmentation and crack detection system from pavement images with complicated background information. The proposed method consists of three steps. In the first step, a Support Vector Machine, which shows a high degree of accuracy in classifying data, was employed to classify the image into two categories: a pavement group and a background group. In the second step, the crack was extracted by a fractal thresholding. Finally, a Radon Transform was applied to the crack image to classify the cracks into four different types. The experimental results show that the proposed system is robust and can effectively be used in pavement images with complicated background components such as trees, houses, etc. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A road extraction method using beamlet transform

    Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (886 KB) |  | HTML iconHTML  

    Synthetic Aperture Radar (SAR) systems have been widely used to estimate the various features on the ground. However, the images are often corrupted by noise that can impede further investigation of SAR images. Therefore, the extraction of features from SAR images with noisy backgrounds becomes a challenging issue in SAR image processing. The goal of this paper is to develop and implement a more robust method based on a beamlet transform to extract linear features such as roads from SAR images. The proposed method consists of three steps: First, an image pre-processing technique is used to offset the noise and low-contrast problems by recalculating the pixel values. Second, linear features such as road networks are then extracted by applying a beamlet transform based algorithm. In the third step, a post-processing algorithm is developed to analyze and link the discontinuities in order to connect the road networks in the image. Experimental results have demonstrated the effectiveness of this method. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Word boundary detection through frame classification using bispectral analysis

    Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1017 KB) |  | HTML iconHTML  

    This paper presents a word boundary detection technique based on frame classification using the nonlinear characteristics of speech. Bispectral analysis was used to classify speech frames into voiced, unvoiced and noise segments. To improve classification accuracy, bispectral features were combined with other features such as short time energy, zero-crossing rate, autocorrelation and high-to-low frequency ratio. Experimental results indicate that classification error decreases when bispectrum is combined with other features. Thus bispectral features can be used as supplementary to augment simple time domain features for demarcating word boundaries in speech. Validation of results was carried out by manual verification. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fuzzy controller design of a new biomimetic earthworm robot for endoscopy actuated by SMA wires

    Page(s): 1 - 5
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (237 KB) |  | HTML iconHTML  

    Shape Memory Alloy (SMA) wires are widely employed in robotics, as actuators of prosthetic limbs and medical equipment. Due to advantages such as reducing the size in the application, high power-to-weight ratio and elimination of complex transmission systems and compatibility with the human body, these materials are used as actuators in different types of medical robots. But hysteresis phenomenon is an unsightly effect of SMAs that its compensation is a momentous task in controlling them. In this paper, a fuzzy control system has been designed for SMA actuators in the endoscope robot with 2 segments. The controller schema is developed on the simulated system, and its efficiency is investigated. The accuracy of robot response to achieve the preferred position is examined and compared with other results. The results have shown the current applied to SMA wires has minimum overshoot and output of system has minimal time to achieve stability. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Optical properties of PLD-deposited barium strontium titanate (BaxSr1−xTiO3) thin films

    Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (568 KB) |  | HTML iconHTML  

    Optical properties of PLD-deposited barium strontium titanate thin-films consisting of three stoichiometries have been investigated. Dielectric layers containing BaxSr1-xTiO3 (x = 30, 40, 50) have been deposited on glass substrates using pulsed laser deposition techniques using oxygen partial pressures of 1.3 Pa ± 0.13 Pa at 500 °C. The optical property investigation includes direct measurement of reflectance and transmittance using spectrophotometric methods to subsequently determine the refractive index (n), extinction coefficient (k), optical conductivity (σ), absorption coefficient (α) and optical band gap (Eg) using swept spectra in the ultraviolet, visible and near-infrared range (200-1100 nm). In this work these parameters are reported for Ba0.4Sr0.6TiO3. Small differences in the transmittance were observed near the visible band edges when comparing each stoichiometry; sharp cutoffs were observed at the bands edges with a strong absorbance in the 200-300 nm band. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Word recognition in continuous speech with background noise based on posterior probability measure

    Page(s): 1 - 7
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (860 KB) |  | HTML iconHTML  

    To overcome the issues of speech recognition, most of the existing research work considers pre-treatment techniques (noise reduction, end point detection) combined with the training models and pattern recognition techniques. To find the target word in a predefined speech sentence, various similarity measure techniques have been developed. However, the existence of background noise in speech signal degrades the performance of the system in terms of target word identification. In this paper, a novel technique for Word Recognition in Continuous Speech with Background Noise (WRBN) is proposed which differentiates the background noise from speech signal. The proposed technique uses Posterior Probability Measure (PPM), used in image processing for target localisation. Unlike PPM, background speech components which participate actively in mismatching or misidentification, have not been considered in the literature. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Life cycle costs of electric and hybrid electric vehicle batteries and End-of-Life uses

    Page(s): 1 - 7
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (626 KB) |  | HTML iconHTML  

    This paper investigates the pertinent concepts centric to electric vehicle (EV) and hybrid electric vehicle (HEV) battery value. The factors that contribute to battery degradation, and thus devaluation, are examined. While a battery may no longer be useful in a vehicle, this does not mean the battery can no longer be used in other applications. Four strategies for alternative uses of battery packs are discussed. Finally, a simplified analysis of battery value over time is presented. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • State-of-charge and state-of-health monitoring: Implications for industry, academia, and the consumer

    Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (614 KB) |  | HTML iconHTML  

    This paper investigates the concepts of state-of-charge and state of health. The technical challenges that each method faces are discussed, in addition to current research methodologies that are conducted in the academy and industry. A proposed strategy is presented to prepare consumers to the application of these construct in every-day use of electric vehicles. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Artificial intelligence algorithm for heart disease diagnosis using Phonocardiogram signals

    Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (705 KB) |  | HTML iconHTML  

    An artificial intelligence system has been developed using Artificial Neural Networks (ANN) algorithms to diagnose heart disease from Phonocardiogram (PCG) signals. Four new featured characteristics of the signals, namely activity, complexity, mobility and the spectral peaks from the power spectral density plots are used as input to the neural network. Ninety-four PCG signals for three heart diseases were used in this study to test the accuracy of the neural networks. After the signals are filtered and the feature characteristics are extracted, the features are fed to the neural networks. Classification is carried using the Radial Basis Function (RBF) network and the Back Propagation Network (BPN) techniques. Receiver operating characteristic (ROC) is calculated to measure the accuracy for both structures. The results show that RBF provided 98% accuracy in predicting the disease compared with 90.8% for BPN. The developed artificial intelligence algorithm has been shown to be a powerful technique in automatic diagnosis of heart diseases using PCG signals. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Applying resource capability for planning and managing contingency reserves for software and information engineering projects

    Page(s): 1 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (644 KB) |  | HTML iconHTML  

    In project management, an important means to reduce risks is to provide adequate quantities of contingency reserve in terms of capital (fund), person, time (person hours), in the estimate of required project resources. Experienced project managers usually provide more accurate estimate of these quantities. The traditional project management methodologies, such as System Development Life Cycle (SDLC), were developed to handle software and information engineering projects of longer duration and larger number of project members. Many projects in modern days have short duration and smaller number of project members. They tend to follow newer methodologies, such as Agile Development, to adapt to the faster changes of modern technologies and user requirements. For a project manager, gathering information to properly create an effective project plan is like identifying a collection of problems and solving them. Solving problems needs supporting resources, which is analogous to the fact that projects need adequate supporting resources. Chang [1] proposed three elements of methods of problem solving with supporting resource capabilities. This paper proposes an approach that uses these resource capabilities to estimate and manage contingency reserves of a modern-day project in software or information engineering. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Intelligent optimization models for disease diagnosis using a service-oriented architecture and management science

    Page(s): 1 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (905 KB) |  | HTML iconHTML  

    The accuracy of disease diagnosis remains a significant challenge that medical and health care industries experience due to a relative lack of misdiagnosis studies and a difficulty of retrieving patients' information. Validation of diagnosis and certainty of its accuracy is the goal of this research. The research, as reported in this paper introduces an innovative solution to determine the accuracy of disease diagnosis. The solution is based on Intelligent Optimization Models (IOM) using integration of Service-Oriented Architecture (SOA) and Management Science (MS). These models enable medical doctors to make inference about disease diagnosis and allow a quick diagnosis of diseases at higher level of accuracy. The models also have the advantage of reducing health risk associated with experimenting with real patients. In particular, bad decisions that cause death or wrong treatment can be avoided. About 44,000 to 98,000 Americans die annually as the result of medical errors. Experimenting with these models requires less time and is less expensive than experimenting with studying patient's condition. In a SOA environment, the study of this research develops new intelligent concepts. These concepts integrate approaches of management science models including linear programming and network, search methodologies, information retrieval, clustering extended genetic algorithm, and intelligent agents. A prototype is created and examined in order to validate the concepts. The proposed concepts strengthen the capacity and quality of STEM undergraduate degree programs. The concepts also promote a vigorous STEM academic environment to increase the number of students entering STEM careers. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Sensory system device for suture-manipulation tension measurement for surgery

    Page(s): 1 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1433 KB) |  | HTML iconHTML  

    In this paper, we describe a sensor-based device for suture-manipulation tension measurement for surgical purposes. The main purpose of this device is to protect the surgeon from applying the excessive force in making suture knots for any kind of surgery. This excessive tension might lead to skin rupture, tissue damage, and suture cut, etc. It is a simple device that can be used to train the new surgeons before working on real stitching on the human body, or used for future robotic system to perform delicate stitching and do plastic operations. We have used two-way visualization of suture tension using MATLAB GUI (tension vs. time) and LCD (numerical value-Newton) display on the device. The device is equipped with special phonic warning system using HCS12 microcontroller. When tension reaches to certain threshold (depends on the suture category), warning system starts alarming. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fuel temperature control in LPG fuelled SI engines

    Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (738 KB) |  | HTML iconHTML  

    LPG is the most widely used fuel in spark ignition (SI) engines after gasoline. In SI engines, temperature of the fuel-air charge affects the engine performance and exhaust emission characteristics. At higher engine loads and speeds, LPG can be overheated. This will cause an increase in the charge temperature, and a decrease in engine performance. NOx emissions will also increase as the charge temperature increases. By controlling the LPG temperature, some advantages can be gained. In this study, some preliminary results of a fuel temperature control system on engine performance and emission characteristics will be discussed. As the temperature of the engine cooling fluid changes, a valve controlled by LabVIEW adjusts the mass flow rate of the fluid to hold the LPG temperature in a band before injecting it to the engine intake manifold. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.