Search results for: ECG signal compression

Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

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In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: Fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange.

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Authors: A. R. Nezamabadi, M. Karami Khorramabadi

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This paper presents the elastic buckling of homogeneous beams with a pair of piezoelectric layers surface bonded on both sides of the beams. The displacement field of beam is assumed based on the Engesser-Timoshenko beam theory. Applying the Hamilton's principle, the equilibrium equation is established. The influences of applied voltage, dimensionless geometrical parameter and piezoelectric thickness on the critical buckling load of beam are presented. To investigate the accuracy of the present analysis, a compression study is carried out with a known data.

Keywords: Mechanical Buckling, Engesser-Timoshenko beam theory - Piezoelectric layer.

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Authors: A. Samraj, S. Sayeed, J. E. Raja., J. Hossen, A. Rahman

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Monitoring the tool flank wear without affecting the throughput is considered as the prudent method in production technology. The examination has to be done without affecting the machining process. In this paper we proposed a novel work that is used to determine tool flank wear by observing the sound signals emitted during the turning process. The work-piece material we used here is steel and aluminum and the cutting insert was carbide material. Two different cutting speeds were used in this work. The feed rate and the cutting depth were constant whereas the flank wear was a variable. The emitted sound signal of a fresh tool (0 mm flank wear) a slightly worn tool (0.2 -0.25 mm flank wear) and a severely worn tool (0.4mm and above flank wear) during turning process were recorded separately using a high sensitive microphone. Analysis using Singular Value Decomposition was done on these sound signals to extract the feature sound components. Observation of the results showed that an increase in tool flank wear correlates with an increase in the values of SVD features produced out of the sound signals for both the materials. Hence it can be concluded that wear monitoring of tool flank during turning process using SVD features with the Fuzzy C means classification on the emitted sound signal is a potential and relatively simple method.

Keywords: Fuzzy c means, Microphone, Singular ValueDecomposition, Tool Flank Wear.

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Authors: H. B. Kekre, Tanuja K. Sarode

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This paper presents a very simple and efficient algorithm for codebook search, which reduces a great deal of computation as compared to the full codebook search. The algorithm is based on sorting and centroid technique for search. The results table shows the effectiveness of the proposed algorithm in terms of computational complexity. In this paper we also introduce a new performance parameter named as Average fractional change in pixel value as we feel that it gives better understanding of the closeness of the image since it is related to the perception. This new performance parameter takes into consideration the average fractional change in each pixel value.

Keywords: Vector Quantization, Data Compression, Encoding, Searching.

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Authors: K. Masera, A. K. Hossain

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Hardly any neat biodiesel satisfies the European EN14214 standard for compression ignition engine application. To satisfy the EN14214 standard, various additives are doped into biodiesel; however, biodiesel additives might cause other problems such as increase in the particular emission and increased specific fuel consumption. In addition, the additives could be expensive. Considering the increasing level of greenhouse gas GHG emissions and fossil fuel depletion, it is forecasted that the use of biodiesel will be higher in the near future. Hence, the negative aspects of the biodiesel additives will likely to gain much more importance and need to be replaced with better solutions. This study aims to satisfy the European standard EN14214 by blending the biodiesels derived from sustainable feedstocks. Waste Cooking Oil (WCO) and Animal Fat Oil (AFO) are two sustainable feedstocks in the EU (including the UK) for producing biodiesels. In the first stage of the study, these oils were transesterified separately and neat biodiesels (W100 & A100) were produced. Secondly, the biodiesels were blended together in various ratios: 80% WCO biodiesel and 20% AFO biodiesel (W80A20), 60% WCO biodiesel and 40% AFO biodiesel (W60A40), 50% WCO biodiesel and 50% AFO biodiesel (W50A50), 30% WCO biodiesel and 70% AFO biodiesel (W30A70), 10% WCO biodiesel and 90% AFO biodiesel (W10A90). The prepared samples were analysed using Thermo Scientific Trace 1300 Gas Chromatograph and ISQ LT Mass Spectrometer (GC-MS). The GS-MS analysis gave Fatty Acid Methyl Ester (FAME) breakdowns of the fuel samples. It was found that total saturation degree of the samples was linearly increasing (from 15% for W100 to 54% for A100) as the percentage of the AFO biodiesel was increased. Furthermore, it was found that WCO biodiesel was mainly (82%) composed of polyunsaturated FAMEs. Cetane numbers, iodine numbers, calorific values, lower heating values and the densities (at 15 ^oC) of the samples were estimated by using the mass percentages data of the FAMEs. Besides, kinematic viscosities (at 40 °C and 20 °C), densities (at 15 °C), heating values and flash point temperatures of the biomixture samples were measured in the lab. It was found that estimated and measured characterisation results were comparable. The current study concluded that biomixture fuel samples W60A40 and W50A50 were perfectly satisfying the European EN 14214 norms without any need of additives. Investigation on engine performance, exhaust emission and combustion characteristics will be conducted to assess the full feasibility of the proposed biomixture fuels.

Keywords: Biodiesel, blending, characterisation, CI Engine.

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Authors: Samira Vafaye Eslahi

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BCI (Brain Computer Interface) is a communication machine that translates brain massages to computer commands. These machines with the help of computer programs can recognize the tasks that are imagined. Feature extraction is an important stage of the process in EEG classification that can effect in accuracy and the computation time of processing the signals. In this study we process the signal in three steps of active segment selection, fractal feature extraction, and classification. One of the great challenges in BCI applications is to improve classification accuracy and computation time together. In this paper, we have used student’s 2D sample t-statistics on continuous wavelet transforms for active segment selection to reduce the computation time. In the next level, the features are extracted from some famous fractal dimension estimation of the signal. These fractal features are Katz and Higuchi. In the classification stage we used ANFIS (Adaptive Neuro-Fuzzy Inference System) classifier, FKNN (Fuzzy K-Nearest Neighbors), LDA (Linear Discriminate Analysis), and SVM (Support Vector Machines). We resulted that active segment selection method would reduce the computation time and Fractal dimension features with ANFIS analysis on selected active segments is the best among investigated methods in EEG classification.

Keywords: EEG, Student’s t- statistics, BCI, Fractal Features, ANFIS, FKNN.

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Authors: R.V Pawar, P.P.Kajave, S.N.Mali

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The speech signal conveys information about the identity of the speaker. The area of speaker identification is concerned with extracting the identity of the person speaking the utterance. As speech interaction with computers becomes more pervasive in activities such as the telephone, financial transactions and information retrieval from speech databases, the utility of automatically identifying a speaker is based solely on vocal characteristic. This paper emphasizes on text dependent speaker identification, which deals with detecting a particular speaker from a known population. The system prompts the user to provide speech utterance. System identifies the user by comparing the codebook of speech utterance with those of the stored in the database and lists, which contain the most likely speakers, could have given that speech utterance. The speech signal is recorded for N speakers further the features are extracted. Feature extraction is done by means of LPC coefficients, calculating AMDF, and DFT. The neural network is trained by applying these features as input parameters. The features are stored in templates for further comparison. The features for the speaker who has to be identified are extracted and compared with the stored templates using Back Propogation Algorithm. Here, the trained network corresponds to the output; the input is the extracted features of the speaker to be identified. The network does the weight adjustment and the best match is found to identify the speaker. The number of epochs required to get the target decides the network performance.

Keywords: Average Mean Distance function, Backpropogation, Linear Predictive Coding, MultilayeredPerceptron,

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Authors: C. Gunavathi, K. Premalatha

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Microarray technology is universally used in the study of disease diagnosis using gene expression levels. The main shortcoming of gene expression data is that it includes thousands of genes and a small number of samples. Abundant methods and techniques have been proposed for tumor classification using microarray gene expression data. Feature or gene selection methods can be used to mine the genes that directly involve in the classification and to eliminate irrelevant genes. In this paper statistical measures like T-Statistics, Signal-to-Noise Ratio (SNR) and F-Statistics are used to rank the genes. The ranked genes are used for further classification. Particle Swarm Optimization (PSO) algorithm and Shuffled Frog Leaping (SFL) algorithm are used to find the significant genes from the top-m ranked genes. The Naïve Bayes Classifier (NBC) is used to classify the samples based on the significant genes. The proposed work is applied on Lung and Ovarian datasets. The experimental results show that the proposed method achieves 100% accuracy in all the three datasets and the results are compared with previous works.

Keywords: Microarray, T-Statistics, Signal-to-Noise Ratio, FStatistics, Particle Swarm Optimization, Shuffled Frog Leaping, Naïve Bayes Classifier.

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Authors: Seung-Mok Han, Woo-Jin Nam, Seongsoo Lee

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This paper proposes and implements an core transform architecture, which is one of the major processes in HEVC video compression standard. The proposed core transform architecture is implemented with only adders and shifters instead of area-consuming multipliers. Shifters in the proposed core transform architecture are implemented in wires and multiplexers, which significantly reduces chip area. Also, it can process from 4×4 to 16×16 blocks with common hardware by reusing processing elements. Designed core transform architecture in 0.13um technology can process a 16×16 block with 2-D transform in 130 cycles, and its gate count is 101,015 gates.

Keywords: HEVC, Core transform, Low area, Shift-and-add, PE reuse

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Authors: R. Amrollahi, M. Habibi

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When the shock front (SF) hits the central electrode axis of plasma focus device, a reflected shock wave moves radially outwards. The current sheath (CS) results from ionization of filled gas between two electrodes continues to compress inwards until it hits the out-going reflected shock front. In this paper the Lagrangian equations are solved for a parabolic shock trajectory yielding a first and second approximation for the CS path. To determine the accuracy of the approximation, the same problem is solved for a straight shock.

Keywords: Radial compression, Shock wave trajectory, Current sheath, Slog model.

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Authors: Adrienne Kline, Jaydip Desai

Abstract:

Electroencephalogram (EEG) is a noninvasive technique that registers signals originating from the firing of neurons in the brain. The Emotiv EEG Neuroheadset is a consumer product comprised of 14 EEG channels and was used to record the reactions of the neurons within the brain to two forms of stimuli in 10 participants. These stimuli consisted of auditory and visual formats that provided directions of ‘right’ or ‘left.’ Participants were instructed to raise their right or left arm in accordance with the instruction given. A scenario in OpenViBE was generated to both stimulate the participants while recording their data. In OpenViBE, the Graz Motor BCI Stimulator algorithm was configured to govern the duration and number of visual stimuli. Utilizing EEGLAB under the cross platform MATLAB®, the electrodes most stimulated during the study were defined. Data outputs from EEGLAB were analyzed using IBM SPSS Statistics® Version 20. This aided in determining the electrodes to use in the development of a brain-machine interface (BMI) using real-time EEG signals from the Emotiv EEG Neuroheadset. Signal processing and feature extraction were accomplished via the Simulink® signal processing toolbox. An Arduino™ Duemilanove microcontroller was used to link the Emotiv EEG Neuroheadset and the right and left Mecha TE™ Hands.

Keywords: Brain-machine interface, EEGLAB, emotiv EEG neuroheadset, openViBE, simulink.

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Authors: Salama Meghriche, Amer Draa, Mohammed Boulemden

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Heart failure is the most common reason of death nowadays, but if the medical help is given directly, the patient-s life may be saved in many cases. Numerous heart diseases can be detected by means of analyzing electrocardiograms (ECG). Artificial Neural Networks (ANN) are computer-based expert systems that have proved to be useful in pattern recognition tasks. ANN can be used in different phases of the decision-making process, from classification to diagnostic procedures. This work concentrates on a review followed by a novel method. The purpose of the review is to assess the evidence of healthcare benefits involving the application of artificial neural networks to the clinical functions of diagnosis, prognosis and survival analysis, in ECG signals. The developed method is based on a compound neural network (CNN), to classify ECGs as normal or carrying an AtrioVentricular heart Block (AVB). This method uses three different feed forward multilayer neural networks. A single output unit encodes the probability of AVB occurrences. A value between 0 and 0.1 is the desired output for a normal ECG; a value between 0.1 and 1 would infer an occurrence of an AVB. The results show that this compound network has a good performance in detecting AVBs, with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy value is 87.9%.

Keywords: Artificial neural networks, Electrocardiogram(ECG), Feed forward multilayer neural network, Medical diagnosis, Pattern recognitionm, Signal processing.

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Authors: V. K. Bheemineni, B. Käfer, H. Lammer, M. Kotnik, F. O. Riemelmoser

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This paper concerns about the experimental and numerical investigations of energy absorption and axial tearing behaviour of aluminium 6060 circular thin walled tubes under static axial compression. The tubes are received in T66 heat treatment condition with fixed outer diameter of 42mm, thickness of 1.5mm and length of 120mm. The primary variables are the conical die angles (15°, 20° and 25°). Numerical simulations are carried on ANSYS/LS-DYNA software tool, for investigating the effect of friction between the tube and the die.

Keywords: Angled die, ANSYS/LS-DYNA, Axial tearing, Energy absorption.

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Authors: Rami N. Khushaba, Adel Al-Jumaily

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The myoelectric signal (MES) is one of the Biosignals utilized in helping humans to control equipments. Recent approaches in MES classification to control prosthetic devices employing pattern recognition techniques revealed two problems, first, the classification performance of the system starts degrading when the number of motion classes to be classified increases, second, in order to solve the first problem, additional complicated methods were utilized which increase the computational cost of a multifunction myoelectric control system. In an effort to solve these problems and to achieve a feasible design for real time implementation with high overall accuracy, this paper presents a new method for feature extraction in MES recognition systems. The method works by extracting features using Wavelet Packet Transform (WPT) applied on the MES from multiple channels, and then employs Fuzzy c-means (FCM) algorithm to generate a measure that judges on features suitability for classification. Finally, Principle Component Analysis (PCA) is utilized to reduce the size of the data before computing the classification accuracy with a multilayer perceptron neural network. The proposed system produces powerful classification results (99% accuracy) by using only a small portion of the original feature set.

Keywords: Biomedical Signal Processing, Data mining andInformation Extraction, Machine Learning, Rehabilitation.

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Authors: H. B. Kekre, Tanuja K. Sarode, Bhakti Raul

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In this paper we propose segmentation approach based on Vector Quantization technique. Here we have used Kekre-s fast codebook generation algorithm for segmenting low-altitude aerial image. This is used as a preprocessing step to form segmented homogeneous regions. Further to merge adjacent regions color similarity and volume difference criteria is used. Experiments performed with real aerial images of varied nature demonstrate that this approach does not result in over segmentation or under segmentation. The vector quantization seems to give far better results as compared to conventional on-the-fly watershed algorithm.

Keywords: Image Segmentation, , Codebook, Codevector, data compression, Encoding

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Authors: Vasily G. Moshnyaga

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This paper presents an optimized MPEG2 video codec implementation, which drastically reduces the number of computations and memory accesses required for video compression. Unlike traditional scheme, we reuse data stored in frame memory to omit unnecessary coding operations and memory read/writes for unchanged macroblocks. Due to dynamic memory sharing among reference frames, data-driven macroblock characterization and selective macroblock processing, we perform less than 15% of the total operations required by a conventional coder while maintaining high picture quality.

Keywords: Data reuse, adaptive processing, video coding, MPEG

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Authors: C. Gunavathi, K. Premalatha

Abstract:

Tumor classification is a key area of research in the field of bioinformatics. Microarray technology is commonly used in the study of disease diagnosis using gene expression levels. The main drawback of gene expression data is that it contains thousands of genes and a very few samples. Feature selection methods are used to select the informative genes from the microarray. These methods considerably improve the classification accuracy. In the proposed method, Genetic Algorithm (GA) is used for effective feature selection. Informative genes are identified based on the T-Statistics, Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate solutions of GA are obtained from top-m informative genes. The classification accuracy of k-Nearest Neighbor (kNN) method is used as the fitness function for GA. In this work, kNN and Support Vector Machine (SVM) are used as the classifiers. The experimental results show that the proposed work is suitable for effective feature selection. With the help of the selected genes, GA-kNN method achieves 100% accuracy in 4 datasets and GA-SVM method achieves in 5 out of 10 datasets. The GA with kNN and SVM methods are demonstrated to be an accurate method for microarray based tumor classification.

Keywords: F-Test, Gene Expression, Genetic Algorithm, k- Nearest-Neighbor, Microarray, Signal-to-Noise Ratio, Support Vector Machine, T-statistics, Tumor Classification.

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Authors: Karchung, S. Ruangsinchaiwanich

Abstract:

This paper presents open-loop vector control method of induction motor with space vector pulse width modulation (SVPWM) technique. Normally, the closed loop speed control is preferred and is believed to be more accurate. However, it requires a position sensor to track the rotor position which is not desirable to use it for certain workspace applications. This paper exhibits the performance of three-phase induction motor with the simplest control algorithm without the use of a position sensor nor an estimation block to estimate rotor position for sensorless control. The motor stator currents are measured and are transformed to synchronously rotating (d-q-axis) frame by use of Clarke and Park transformation. The actual control happens in this frame where the measured currents are compared with the reference currents. The error signal is fed to a conventional PI controller, and the corrected d-q voltage is generated. The controller outputs are transformed back to three phase voltages and are fed to SVPWM block which generates PWM signal for the voltage source inverter. The open loop vector control model along with SVPWM algorithm is modeled in MATLAB/Simulink software and is experimented and validated in TMS320F28335 DSP board.

Keywords: Electric drive, induction motor, open-loop vector control, space vector pulse width modulation technique.

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Authors: Fahad Alhussein, Huaping Liu

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This paper compares the multipath mitigation performance of code correlation reference waveform receivers with variable and fixed window width, for binary offset carrier and multiplexed binary offset carrier signals typically used in global navigation satellite systems. In the variable window width method, such width is iteratively reduced until the distortion on the discriminator with multipath is eliminated. This distortion is measured as the Euclidean distance between the actual discriminator (obtained with the incoming signal), and the local discriminator (generated with a local copy of the signal). The variable window width have shown better performance compared to the fixed window width. In particular, the former yields zero error for all delays for the BOC and MBOC signals considered, while the latter gives rather large nonzero errors for small delays in all cases. Due to its computational simplicity, the variable window width method is perfectly suitable for implementation in low-cost receivers.

Keywords: Correlation reference waveform receivers, binary offset carrier, multiplexed binary offset carrier, global navigation satellite systems.

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Authors: S. Bouharati, I. Bouharati, C. Benzidane, F. Alleg, M. Belmahdi

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Sensors possess several properties of physical measures. Whether devices that convert a sensed signal into an electrical signal, chemical sensors and biosensors, thus all these sensors can be considered as an interface between the physical and electrical equipment. The problem is the analysis of the multitudes of saved settings as input variables. However, they do not all have the same level of influence on the outputs. In order to identify the most sensitive parameters, those that can guide users in gathering information on the ground and in the process of model calibration and sensitivity analysis for the effect of each change made. Mathematical models used for processing become very complex. In this paper a fuzzy rule-based system is proposed as a solution for this problem. The system collects the available signals information from sensors. Moreover, the system allows the study of the influence of the various factors that take part in the decision system. Since its inception fuzzy set theory has been regarded as a formalism suitable to deal with the imprecision intrinsic to many problems. At the same time, fuzzy sets allow to use symbolic models. In this study an example was applied for resolving variety of physiological parameters that define human health state. The application system was done for medical diagnosis help. The inputs are the signals expressed the cardiovascular system parameters, blood pressure, Respiratory system paramsystem was done, it will be able to predict the state of patient according any input values.

Keywords: Sensors, Sensivity, fuzzy logic, analysis, physiological parameters, medical diagnosis.

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Authors: A. R. Nezamabadi, M. Karami Khorramabadi

Abstract:

This paper studies dynamic stability of homogeneous beams with piezoelectric layers subjected to periodic axial compressive load that is simply supported at both ends lies on a continuous elastic foundation. The displacement field of beam is assumed based on Bernoulli-Euler beam theory. Applying the Hamilton's principle, the governing dynamic equation is established. The influences of applied voltage, foundation coefficient and piezoelectric thickness on the unstable regions are presented. To investigate the accuracy of the present analysis, a compression study is carried out with a known data.

Keywords: Dynamic stability, Homogeneous graded beam-Piezoelectric layer, Harmonic balance method.

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Authors: Maisara Mohyeldin Gasim, A. K. Amirruddin, A. Shahrani

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This paper investigates the effect of replacing crankshaft with cam on the indicated torque during compression and power strokes in internal combustion engines. A Cycloidal cam profile was used in Revetec engine to calculate and compare the torque to a conventional engine, using a computational method. Firstly, the cylinder pressure was calculated using Ferguson equation, and then the torque calculated depending on cylinder pressure values in every crank angle. the results showed that by using Cycloidal cam profile in Revetec engine the torque can increased by 14% compared with conventional engines, which means an increase in engine efficiency.

Keywords: Revetec engine, indicated torque, cam profile.

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Authors: Gabriel Sitler, Yousef Sardahi, Asad Salem

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This paper presents an optimal and robust sliding mode controller (SMC) to regulate the position of the knee joint angle for patients suffering from knee injuries. The controller imitates the role of active orthoses that produce the joint torques required to overcome gravity and loading forces and regain natural human movements. To this end, a mathematical model of the shank, the lower part of the leg, is derived first and then used for the control system design and computer simulations. The design of the controller is carried out in optimal and multi-objective settings. Four objectives are considered: minimization of the control effort and tracking error; and maximization of the control signal smoothness and closed-loop system’s speed of response. Optimal solutions in terms of the Pareto set and its image, the Pareto front, are obtained. The results show that there are trade-offs among the design objectives and many optimal solutions from which the decision-maker can choose to implement. Also, computer simulations conducted at different points from the Pareto set and assuming knee squat movement demonstrate competing relationships among the design goals. In addition, the proposed control algorithm shows robustness in tracking a standard gait signal when accounting for uncertainty in the shank’s parameters.

Keywords: Optimal control, multi-objective optimization, sliding mode control, wearable knee exoskeletons.

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Authors: M. Ahmadi, M. Kafil, H. Ebrahimi

Abstract:

Nowadays, induction motors have a significant role in industries. Condition monitoring (CM) of this equipment has gained a remarkable importance during recent years due to huge production losses, substantial imposed costs and increases in vulnerability, risk, and uncertainty levels. Motor current signature analysis (MCSA) is one of the most important techniques in CM. This method can be used for rotor broken bars detection. Signal processing methods such as Fast Fourier transformation (FFT), Wavelet transformation and Empirical Mode Decomposition (EMD) are used for analyzing MCSA output data. In this study, these signal processing methods are used for broken bar problem detection of Mobarakeh steel company induction motors. Based on wavelet transformation method, an index for fault detection, CF, is introduced which is the variation of maximum to the mean of wavelet transformation coefficients. We find that, in the broken bar condition, the amount of CF factor is greater than the healthy condition. Based on EMD method, the energy of intrinsic mode functions (IMF) is calculated and finds that when motor bars become broken the energy of IMFs increases.

Keywords: Broken bar, condition monitoring, diagnostics, empirical mode decomposition, Fourier transform, wavelet transform.

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Authors: S. Z. A. Zaidi, A. Crosky

Abstract:

Biocomposites is a field that has gained much scientific attention due to the current substantial consumption of non-renewable resources and the environmentally harmful disposal methods required for traditional polymer composites. Research on natural fiber reinforced polyhydroxyalkanoates (PHAs) has gained considerable momentum over the past decade. There is little work on PHAs reinforced with unidirectional (UD) natural fibers and little work on using epoxidized natural rubber (ENR) as a toughening agent for PHA-based biocomposites. In this work, we prepared polyhydroxybutyrate-co-valerate (PHBV) biocomposites reinforced with UD 30 wt.% flax fibers and evaluated the use of ENR with 50% epoxidation (ENR50) as a toughening agent for PHBV biocomposites. Quasi-unidirectional flax/PHBV composites were prepared by hand layup, powder impregnation followed by compression molding.  Toughening agents – polybutylene adiphate-co-terephthalate (PBAT) and ENR50 – were cryogenically ground into powder and mechanically mixed with main matrix PHBV to maintain the powder impregnation process. The tensile, flexural and impact properties of the biocomposites were measured and morphology of the composites examined using optical microscopy (OM) and scanning electron microscopy (SEM). The UD biocomposites showed exceptionally high mechanical properties as compared to the results obtained previously where only short fibers have been used. The improved tensile and flexural properties were attributed to the continuous nature of the fiber reinforcement and the increased proportion of fibers in the loading direction. The improved impact properties were attributed to a larger surface area for fiber-matrix debonding and for subsequent sliding and fiber pull-out mechanisms to act on, allowing more energy to be absorbed. Coating cryogenically ground ENR50 particles with PHBV powder successfully inhibits the self-healing nature of ENR-50, preventing particles from coalescing and overcoming problems in mechanical mixing, compounding and molding. Cryogenic grinding, followed by powder impregnation and subsequent compression molding is an effective route to the production of high-mechanical-property biocomposites based on renewable resources for high-obsolescence applications such as plastic casings for consumer electronics.

Keywords: Natural fibers, natural rubber, polyhydroxyalkanoates, unidirectional.

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Authors: Raheleh Hedayati, Sanaz Haddadian, Hooman Nabovati

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A 2.4GHz (RF) down conversion Gilbert Cell mixer, implemented in a 0.18-μm CMOS technology with a 1.8V supply, is presented. Current bleeding (charge injection) technique has been used to increase the conversion gain and the linearity of the mixer. The proposed mixer provides 10.75 dB conversion gain ( C G ) with 14.3mw total power consumption. The IIP3 and 1-dB compression point of the mixer are 8dbm and -4.6dbm respectively, at 300 MHz IF frequencies. Comparing the current design against the conventional mixer design, demonstrates better performance in the conversion gain, linearity, noise figure and port-to-port isolation.

Keywords: Mixer, Gilbert Cell, Charge Injection, RFIC, CMOSTechnology.

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Authors: Maryam Jasim Abdullah, Bassim. H. Graimed, Jalal. S. Hameed

Abstract:

Demand over web services is in growing with increases number of Web users. Web service is applied by Web application. Web application size is affected by its user-s requirements and interests. Differential in requirements and interests lead to growing of Web application size. The efficient way to save store spaces for more data and information is achieved by implementing algorithms to compress the contents of Web application documents. This paper introduces an algorithm to reduce Web application size based on reduction of the contents of HTML files. It removes unimportant contents regardless of the HTML file size. The removing is not ignored any character that is predicted in the HTML building process.

Keywords: HTML code, HTML tag, WEB applications, Document compression, DOM tree.

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Authors: Shimal Das, Dibyendu Ghoshal

Abstract:

The effect of directional search using iterated functional system has been studied on four images taken from databases. The images are portioned successively towards smaller dimension. Presented method provides the faster rate of convergence with respect to processing time in the flat region, but the same has been found to be slower at the border of the images and edges. It has also been revealed that the PSNR is lower at the edges and border portions of the image, and it is found to be higher in the uniform gray region, under the same external illumination and external noise environment.

Keywords: Iterated functional system, fractal compression, structural similarity index measure, fractal block coding, affine transformations.

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Authors: A. R. Nezamabadi, M. Karami Khorramabadi

Abstract:

This paper studies stability of homogeneous beams with piezoelectric layers subjected to axial load that is simply supported at both ends lies on a continuous elastic foundation. The displacement field of beam is assumed based on first order shear deformation beam theory. Applying the Hamilton's principle, the governing equation is established. The influences of applied voltage, dimensionless geometrical parameter and foundation coefficient on the stability of beam are presented. To investigate the accuracy of the present analysis, a compression study is carried out with a known data.

Keywords: Stability, Homogeneous beam- Piezoelectric layer

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Authors: Haroun A.K. Shahad, Nabeel Abdul-Hadi

Abstract:

Experiments were carried out to evaluate the influence of the addition of hydrogen to the inlet air on the performance of a single cylinder direct injection diesel engine. Hydrogen was injected in the inlet manifold. The addition of hydrogen was done on energy replacement basis. It was found that the addition of hydrogen improves the combustion process due to superior combustion characteristics of hydrogen in comparison to conventional diesel fuels. It was also found that 10% energy replacement improves the engine thermal efficiency by about 40% and reduces the sfc by about 35% however the volumetric efficiency was reduced by about 35%.

Keywords: Hydrogen, Blended fuel, Manifold injection , Performance , Combustion

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