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Signal Processing and its Applications (CSPA), 2012 IEEE 8th International Colloquium on

Date 23-25 March 2012

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Displaying Results 1 - 25 of 115
  • [Front cover]

    Page(s): c1
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    Freely Available from IEEE
  • [Copyright notice]

    Page(s): ii
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  • Organizing Committee

    Page(s): iii
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  • Reviewers

    Page(s): iv
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  • Table of contents

    Page(s): v - xii
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  • Design and simulation of low-noise bandpass filter by using active capacitance circuit

    Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (775 KB) |  | HTML iconHTML  

    This article aims to design and simulation of the active capacitance circuit and its Negative resistance feature. It also suggests a novel method in the field of active filters which is based on an active capacitance circuit. ADS2010 software was employed to perform the simulations. It is demonstrated via the simulated results that the proposed RF active filter is capable of being applied to the narrow bandpass filter (BPF) design, and also is stable and possesses Low-noise features. The frequency range within which the circuit shows a negative resistance is 2GHz to 6.8GHz, and the center frequency is 5.5GHz. The gain is obtained 1dB at the center frequency with a quality factor (Q) of 26. At the center frequency, the noise-figure of active filter is 1.925 dB. Generally, the K factor is larger than 1 and the circuit is entirely stable within the frequency range. View full abstract»

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  • Evaluation of circuit reliability based on distribution of different signal input patterns

    Page(s): 5 - 9
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (848 KB) |  | HTML iconHTML  

    As digital logic circuit are being fabricated at nanometer scale, the reliability of the circuit becomes an important issue. Therefore the reliability modeling is increasingly important subject to be considered in designing modern logic integrated circuits at submicron level. This drives a need to compute reliability measure for nano-scale circuits. Two main reliability measuring tools used commonly in the literature are e.g. Probabilistic Gate Model (PGM) and Boolean Difference-based Error Calculator (BDEC) other than Probabilistic Transfer Matrix (PTM). Here, the research work is constrained to PGM and BDEC models only as PTM model consume higher execution time and memory usage. This paper looks into the accuracy of circuit's reliability evaluation by BDEC compared to control reliability evaluation method, PGM. Both models are able to estimate circuit's reliability in the presence of soft errors. It is shown that BDEC model gives higher reliability values compared to PGM model for a set of circuits with same functionality but as the complexity of the circuits and the gate error values increases, BDEC tend to be inferior compared to PGM. This occurrence is explained in this paper using distribution of different signal input patterns overtime for same functionality circuits. Simulation results conclude that the reliability measure for BDEC depends on the circuit design (though with same functionality), gate error and probability of the input signal, being one or zero. View full abstract»

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  • Design and simulation of recursive RF filter by using HEMT technology

    Page(s): 10 - 13
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (752 KB) |  | HTML iconHTML  

    An active recursive filter using HEMT technology is proposed in the following article. An ED02AH HEMT technology with advanced design system (ADS 2010) was used to design a test circuit. This kind of filter appeared feasible in simulations, and reasonably practically good performance was achieved. Gain and Q-value were capable to be tuned within a wide range. A center frequency was 4GHz for which S21=20.134dB, S11=-15dB and S22=-21.2dB. Simulations demonstrate a center frequency tuning range of 1.5GHz to 6GHz. View full abstract»

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  • Design and fabrication of Programmable Logic Controller Kit with multiple output module for teaching and learning purposes

    Page(s): 14 - 18
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1358 KB) |  | HTML iconHTML  

    Programmable Logic Controller (PLC) Kit for teaching and learning is developed based on the existing PLC Trainer that is not able to achieve the objective and learning outcome in enhancing the hands on skill aspect through circuit designing, installation and trouble shooting. The existing PLC trainer board comes with a casing where students have the difficulty in observing and understanding the connection between the input module, PLC controller and output modules. The development of PLC Kit has been designed and improved by increasing the number of input and output components, cost reduction and it is also user friendly. This PLC Kit is embedded with I/O module such as normally open push buttons, 24VDC motor, 24VDC relay, 24VDC solenoid cylinder and 24VDC lamp. This PLC Kit can be interfaced to various types of PLC controller such as Omron, Siemens and Panasonic (NAIS). Based on students Lab Practical Assessment record, it is found that there is 39% improvement of knowledge and hands on skill when students use the PLC Kit. View full abstract»

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  • Artificial neural network coupled with robust principal components in near infrared spectroscopic analysis

    Page(s): 19 - 22
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (717 KB) |  | HTML iconHTML  

    The objectives of this paper are to demonstrate the use of a combination of artificial neural network and robust principal components (RPCs-ANN) to predict the soluble solid content of intact pineapple, non-invasively, based on near infrared spectral data, and to compare the performance of RPCs-ANN with artificial neural network based on classical principal components (PCs-ANN). First, we implemented second order derivative with first order Savitzky-Golay (SG) smoothing filter to pre-process the spectral data. Second, robust and classical principal component analysis approaches were utilized to reduce the dimension of spectral data and to produce robust principal components (RPCs) and principal components (PCs), respectively. Third, artificial neural network with RPCs as its inputs (RPCs-ANN) was trained based on Bayesian regularization to improve the generalization of the network by optimizing its regularization parameters. The effects of different number of inputs and hidden neurons are discussed. The findings suggest that RPCs-ANN is superior to PCs-ANN. View full abstract»

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  • Image analysis for deformation behavior of optical based silicone tactile sensor

    Page(s): 23 - 28
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    This paper presents a tactile sensor which is made of a silicone based material. The tactile sensor is designed similarly like a human finger. The hollow space inside the tactile sensor is marked at the `finger tip' inner side to sense any deformation when force is apply outside the `finger tip'. The force is apply by using micrometer tip. A CCD camera is connected to a fiberscope and the fiberscope is connected to the tactile sensor to `see' the deformed image inside the silicone dome. Several images is captured. The captured image is analyzed by a WiT image processing algorithm. Based on the processed images, the result is analyzed and the deformation behavior is studied. View full abstract»

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  • A 6-bit digital phase shifter by using HEMT technology

    Page(s): 29 - 32
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (930 KB) |  | HTML iconHTML  

    A 6-bit passive phase shifter for S frequency band has been designed in a standard HEMT technology. A new switched-network topology has been proposed for implementing the 5.625 phase shift step which these digital bits are series with each other. We used Advanced Design System (ADS2010) to perform simulations. These digital bits will produce 64 different mode phase shift of -177.15 to +177.15 degree. In all cases simulation obtained less than 1 % error. View full abstract»

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  • Down-conversion self-oscillating mixer by using CMOS technology

    Page(s): 33 - 36
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (746 KB) |  | HTML iconHTML  

    In this paper a self-oscillating mixer is presented fundamental signal generated by the oscillator subcircuit in the mixing process. The oscillator core consumes 3mA of current from a 1.8 V DC supply and results in an output power of -0.867 dBm per oscillator, and a measured phase noise of -91, -102 and -108 dBc/Hz at 100 KHz, 600 KHz and 1 MHz from the carrier, respectively. In the mixing process the proposed mixer achieved IIP3 of 0 dBm with conversation gain of 1.93 dB. The circuit was designed and simulated in 0.18-μm CMOS technology by ADS2010. View full abstract»

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  • Wideband microstrip passband filter by using ADS software

    Page(s): 37 - 40
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (889 KB) |  | HTML iconHTML  

    Space mapping is a powerful technique to optimize such complex models by efficiently substituting accurate but expensive electromagnetic models, fine models, with fast and approximate models, coarse models. In this paper, we apply space mapping, an explicit space mapping techniques to Design, a microstrip passband filter. The filter configuration is made of a perfect conductor on the top of a substrate (RT_DURROID_5880) with a relative dielectric constant of 2.21 and a height of 20mil, backed with a perfect conductor ground plane. The proposed passband filter 9GHz to 10GHz is designed and simulated with Advanced Design System (ADS 2010) and was implemented with good compactness and low insertion loss. View full abstract»

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  • Development of a piezoelectric chemical sensor using metalloporphyrins compounds as a coating material

    Page(s): 41 - 43
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    The piezoelectric quartz crystal chemical sensor was developed for volatile organic compounds (VOCs) detection. The sensing sensitivity of the devices was measured based on the small change in mass of quartz crystal. The addition of mass causes changes its natural frequency when exposing the thin film towards vapor molecules. The system sensor was used with metalloporphyrin thin films as a sensing element. Seven types of metalloporphyrin compounds have been used for deposition of the thin films. They were: 2-nitro-5, 10, 15, 20-tetraphenyl-21H, 23H-porphyrin copper (III) (CuTPPnitro), 5, 10, 15, 20-tetraphenyl-21H, 23H-porphyrin ruthinium (II) carbonyl (RuTPP), 5, 10, 15, 20-tetraphenyl-21H, 23H-porphyrin iron (III) cloride (FeTPP), 5, 10, 15, 20-tetraphenyl-21H, 23H-porphyrin manganese (III) cloride (MnTPP), 5, 10, 15, 20-tetraphenyl-21H, 23H-porphyrin cobalt (II) (CoTPP), 5, 10, 15, 20-tetraphenyl-21H, 23H-porphyrin nickel (II) (NiTPP) and 5, 10, 15, 20-tetraphenyl-21H, 23H-porphyrin zinc (ZnTPP). The LB technique has been used to form metalloporphyrin organic compounds as a thin films onto quartz crystal surface. The sensing sensitivity was studied by exposing saturated vapor of o-xylene towards LB thin films. From the result it was observed that the various responses were shown for each of the thin films towards o-xylene vapor. The physical and chemical interaction between thin films and the vapor molecule are the factors influencing the sensing sensitivity of the sensor system. View full abstract»

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  • Fast Evolutionary Programming-based Hybrid Multi-Layer Feedforward Neural Network for predicting Grid-Connected Photovoltaic system output

    Page(s): 44 - 47
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (782 KB) |  | HTML iconHTML  

    This paper presents a Hybrid Multi-Layer Feedforward Neural Network (HMLFNN) technique for predicting the output from a Grid-Connected Photovoltaic (GCPV) system. In the proposed HMLFNN, Fast Evolutionary Programming (FEP) was employed to optimize the training process of the Multi-Layer Feedforward Neural Network (MLFNN). FEP was used to select the optimal values for the number of neurons in the hidden layer, the learning rate, the momentum rate, the type of activation function and the learning algorithm. In addition, the MLFNN utilized solar irradiance (SI) and module temperature (MT) as its inputs and AC kWh energy as its output. When compared with the Classical Evolutionary Programming (CEP) trained MLFNN, the proposed FEP-based HMLFNN offered superior performance by producing lower computation time and lower prediction error. View full abstract»

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  • A non linear face recognition system using Support Vector Machine

    Page(s): 48 - 51
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (833 KB) |  | HTML iconHTML  

    A face recognition system uses face to verify individuals using computing capability. However, its performances often degrade due to high dimensional data and large feature appearance of the face image. This paper present a face recognition system based on non linear feature extraction technique to reduce the dimensionality of the face image, called Locally Linear Embedding. This method considers the hidden layer of face manifold to be the input of a SVM multiclass classifier. The performance is evaluated using the ORL database and achieved better recognition rates than the Principal Component Analysis. View full abstract»

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  • Optimizing the frequency of Ultrasonic Tomography system with a metal pipe conveyor

    Page(s): 52 - 57
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1136 KB) |  | HTML iconHTML  

    Ultrasonic Tomography has an important role in industry to produce scanned images for various propose. In this paper, producing the cross sectional images of pipe for detecting percentage of attendance of solid, liquid and gas inside the metal pipe has been investigated. The correct method of mounting of Ultrasonic sensors and behavior of the ultrasonic wave propagation in different layers has been simulated by the use of finite element software (COMSOL Multiphysics 3.5). To increase in practical nondestructive evaluation and inspection, we should increase our understanding of the basic physics and wave mechanics associated with guided wave inspection. Finding the proper ultrasonic sensor base on its efficiency is the main step of designing an Ultrasonic Tomography system. This is done by estimating the resonance frequency of sensor due to manner of ultrasonic wave propagation in different frequencies shown in simulation results. Optimum frequency of the system is proposed 45 kHz. View full abstract»

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  • The application of Near-Infrared Spectroscopy for poultry meat grading

    Page(s): 58 - 62
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (840 KB) |  | HTML iconHTML  

    The quality of meat in consumer perception is affected by the most important factor which is tenderness. Traditionally, the meat quality grading is done destructively by the human graders and also using destructive measurements that will destroy the samples. Destructive measurement also caused less-accurate results, time-consuming and high cost. Therefore, a low cost, fast, reliable and non-destructive technique which is The Near-Infrared Spectroscopy (NIRS) is required in order to gain accurate results in tenderness prediction. This NIRS will then be able to improve the agricultural industries in meat quality grading. View full abstract»

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  • Classification of Parkinson's disease based on Multilayer Perceptrons (MLPs) Neural Network and ANOVA as a feature extraction

    Page(s): 63 - 67
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (634 KB) |  | HTML iconHTML  

    Parkinson's disease (PD) is the second commonest late life neurodegenerative disease after Alzheimer's disease. It is prevalent throughout the world and predominantly affects patients above 60 years old. It is caused by progressive degeneration of dopamine containing cells (neurons) within the deep structures of the brain called the basal ganglia and substantia nigra. Therefore, accurate prediction of PD need to be done in order to assist medical or bio-informatics practitioners for initial diagnose of PD based on variety of test results. This paper described the analysis conducted based on two training algorithms namely Levenberg-Marquardt (LM) and Scaled Conjugate Gradient (SCG) of Multilayer Perceptrons (MLPs) Neural Network in diagnosing PD with Analysis of Variance (ANOVA) as a feature selection. The dataset information of this project has been taken from the Parkinson Disease Data Set. Results attained confirmed that the LM performed well with accuracy rate of above 90% before and after feature selection whilst SSG attained above 85% subsequent to implementation of ANOVA as feature selection. View full abstract»

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  • The application of Near-Infrared spectroscopy to investigate the amylose content in rice

    Page(s): 68 - 73
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    NIR spectroscopy can be used to measure the amylose content in rough rice, brown rice and milled rice. From the investigation in this research, if the amylose content is high in the rice, the rate of digestion, glucose absorption is slow and it can reduce insulin responses. So, diabetics patient can start practice to have a proper diet by choosing rice with high amylose content such us Basmati rice and brown rice. View full abstract»

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  • Segmentation of mitral regurgitant jet using the combination of wavelet and watershed transformation

    Page(s): 74 - 79
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1623 KB) |  | HTML iconHTML  

    This paper concentrates on automatic segmentation of the regurgitation jet from the color Doppler echocardiographic image during the mitral regurgitation. Segmentation of color jet area is not an easy task especially when the background image is also color image. In this case it is not possible to do pixel classification for the separation of the color area. Jet area is directly related to the severity of mitral regurgitation. Here the main objective is to segment the color mosaic pattern from the color Doppler image. For this a multistep algorithm has been applied. The first stage of the proposed algorithm is dual-tree complex wavelet transform. Next stage is the watershed transform and then similarity measure has been done to get the final segmented image. Jet area obtained with the proposed method satisfies the clinical results. View full abstract»

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  • Using multiple view in optimizing detector placement for petrochemical plant

    Page(s): 80 - 84
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (837 KB) |  | HTML iconHTML  

    The aim of this work is to provide current oil and gas industries with a method to determine the placement of visual detectors for processing plant such as petrochemical plant. Nowadays industries practices are replacing conventional IR and UV detector with more advanced visual fire detector, which are less prone to false alarm, and having similar properties as CCTV camera. Development of the proposed method will follow the conventional protocol of fire detector mapping used by oil and gas industry. Several restriction and limitation have been stated to narrow down the scope to provide more applicable solution. By using multiple views, the proposed method is able to estimate the optimal placement of detector as similar to 3D methods. View full abstract»

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  • System identification and control of an Electro-Hydraulic Actuator system

    Page(s): 85 - 88
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (749 KB) |  | HTML iconHTML  

    Precise control of Electro-Hydraulic Actuator (EHA) system has been a challenging task due to nonlinearities, time varying characteristics and uncertainties of the system. A controller can be designed when given accurate model of the system. This paper presents the process to obtain an EHA system's model using system identification approach. System identification process has merit in obtaining system model as it requires only input and output data pairs from the system. Validation of the model is done by comparing the performance with the actual EHA system. A PID controller is later designed based on model obtained for accurate position tracking of the system. Simulation result and real time experiment show that the system which is applied with the proposed controller is able to perform position tracking with high accuracy. View full abstract»

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  • ANFIS modeling of electro-hydraulic actuator system

    Page(s): 89 - 92
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    Precise control of electro-hydraulic actuator (EHA) system has been an interesting subject due to its nonlinearities and uncertainties characteristics. Good control can be designed when precise model of the system is available. ANFIS (Adaptive Neuro-Fuzzy Inference System) modeling technique has proven to be able to model various nonlinear systems. The objective of this paper is to obtain an ANFIS model from EHA system stimulus-response data. The prediction ability of ANFIS is also tested using limited data set for model training. Results show that ANFIS model is able to estimate nonlinear EHA system with high precision, even when training data provided is limited. View full abstract»

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