Search results for: Combinational logic output
495 The Performance of an 802.11g/Wi-Fi Network Whilst Streaming Voice Content
Authors: P. O. Umenne, Odhiambo Marcel O.
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A simple network model is developed in OPNET to study the performance of the Wi-Fi protocol. The model is simulated in OPNET and performance factors such as load, throughput and delay are analysed from the model. Four applications such as oracle, http, ftp and voice are applied over the Wireless LAN network to determine the throughput. The voice application utilises a considerable amount of bandwidth of up to 5Mbps, as a result the 802.11g standard of the Wi-Fi protocol was chosen which can support a data rate of up to 54Mbps. Results indicate that when the load in the Wi-Fi network is increased the queuing delay on the point-to-point links in the Wi-Fi network significantly reduces until it is comparable to that of WiMAX. In conclusion, the queuing delay of the Wi-Fi protocol for the network model simulated was about 0.00001secs comparable to WiMAX network values.Keywords: WLAN-Wireless Local Area Network, MIMO-Multiple Input Multiple Output, Queuing delay, Throughput, AP-Access Point, IP-Internet protocol, TOS-Type of Service.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2131494 Application of Data Envelopment Analysis and Performance Indicators to Irrigation Systems in Thessaloniki Plain (Greece)
Authors: Ntantos P.N, Karpouzos D.K
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In this paper, a benchmarking framework is presented for the performance assessment of irrigations systems. Firstly, a data envelopment analysis (DEA) is applied to measure the technical efficiency of irrigation systems. This method, based on linear programming, aims to determine a consistent efficiency ranking of irrigation systems in which known inputs, such as water volume supplied and total irrigated area, and a given output corresponding to the total value of irrigation production are taken into account simultaneously. Secondly, in order to examine the irrigation efficiency in more detail, a cross – system comparison is elaborated using a performance indicators set selected by IWMI. The above methodologies were applied in Thessaloniki plain, located in Northern Greece while the results of the application are presented and discussed. The conjunctive use of DEA and performance indicators seems to be a very useful tool for efficiency assessment and identification of best practices in irrigation systems management.Keywords: Benchmarking, D.E.A, Performance Indicators, Irrigation systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2097493 Effect of Adaptation Gain on system Performance for Model Reference Adaptive Control Scheme using MIT Rule
Authors: Pankaj Swarnkar, Shailendra Jain, R.K Nema
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Adaptive control involves modifying the control law used by the controller to cope with the fact that the parameters of the system being controlled change drastically due to change in environmental conditions or in system itself. This technique is based on the fundamental characteristic of adaptation of living organism. The adaptive control process is one that continuously and automatically measures the dynamic behavior of plant, compares it with the desired output and uses the difference to vary adjustable system parameters or to generate an actuating signal in such a way so that optimal performance can be maintained regardless of system changes. This paper deals with application of model reference adaptive control scheme in first order system. The rule which is used for this application is MIT rule. This paper also shows the effect of adaptation gain on the system performance. Simulation is done in MATLAB and results are discussed in detail.Keywords: Adaptive control system, Adaptation gain, MIT rule, Model reference adaptive control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2225492 FPGA based Relative Distance Measurement using Stereo Vision Technology
Authors: Manasi Pathade, Prachi Kadam, Renuka Kulkarni, Tejas Teredesai
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In this paper, we propose a novel concept of relative distance measurement using Stereo Vision Technology and discuss its implementation on a FPGA based real-time image processor. We capture two images using two CCD cameras and compare them. Disparity is calculated for each pixel using a real time dense disparity calculation algorithm. This algorithm is based on the concept of indexed histogram for matching. Disparity being inversely proportional to distance (Proved Later), we can thus get the relative distances of objects in front of the camera. The output is displayed on a TV screen in the form of a depth image (optionally using pseudo colors). This system works in real time on a full PAL frame rate (720 x 576 active pixels @ 25 fps).Keywords: Stereo Vision, Relative Distance Measurement, Indexed Histogram, Real time FPGA Image Processor
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3002491 Energy Recovery from Swell with a Height Inferior to 1.5 m
Authors: A. Errasti, F. Doffagne, O. Foucrier, S. Kao, A. Meigne, H. Pellae, T. Rouland
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Renewable energy recovery is an important domain of research in past few years in view of protection of our ecosystem. Several industrial companies are setting up widespread recovery systems to exploit wave energy. Most of them have a large size, are implanted near the shores and exploit current flows. However, as oceans represent 70% of Earth surface, a huge space is still unexploited to produce energy. Present analysis focuses on surface small scale wave energy recovery. The principle is exactly the opposite of wheel damper for a car on a road. Instead of maintaining the car body as non-oscillatory as possible by adapted control, a system is designed so that its oscillation amplitude under wave action will be maximized with respect to a boat carrying it in view of differential potential energy recuperation. From parametric analysis of system equations, interesting domains have been selected and expected energy output has been evaluated.
Keywords: Small scale wave, potential energy, optimized energy recovery, auto-adaptive system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1194490 Performance Analysis of Wavelet Based Multiuser MIMO OFDM
Authors: Md. Mahmudul Hasan
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Wavelet analysis has some strong advantages over Fourier analysis, as it allows a time-frequency domain analysis, allowing optimal resolution and flexibility. As a result, they have been satisfactorily applied in almost all the fields of communication systems including OFDM which is a strong candidate for next generation of wireless technology. In this paper, the performances of wavelet based Multiuser Multiple Input and Multiple Output Orthogonal Frequency Division Multiplexing (MU-MIMO OFDM) systems are analyzed in terms of BER. It has been shown that the wavelet based systems outperform the classical FFT based systems. This analysis also unfolds an interesting result, where wavelet based OFDM system will have a constant error performance using Regularized Channel Inversion (RCI) beamforming for any number of users, and outperforms in all possible scenario in a multiuser environment. An extensive computer simulations show that a PAPR reduction of up to 6.8dB can be obtained with M=64.
Keywords: Wavelet Based OFDM, Optimal Beam-forming, Multiuser MIMO OFDM, Signal to Leakage Ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2616489 A New Technique for Solar Activity Forecasting Using Recurrent Elman Networks
Authors: Salvatore Marra, Francesco C. Morabito
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In this paper we present an efficient approach for the prediction of two sunspot-related time series, namely the Yearly Sunspot Number and the IR5 Index, that are commonly used for monitoring solar activity. The method is based on exploiting partially recurrent Elman networks and it can be divided into three main steps: the first one consists in a “de-rectification" of the time series under study in order to obtain a new time series whose appearance, similar to a sum of sinusoids, can be modelled by our neural networks much better than the original dataset. After that, we normalize the derectified data so that they have zero mean and unity standard deviation and, finally, train an Elman network with only one input, a recurrent hidden layer and one output using a back-propagation algorithm with variable learning rate and momentum. The achieved results have shown the efficiency of this approach that, although very simple, can perform better than most of the existing solar activity forecasting methods.
Keywords: Elman neural networks, sunspot, solar activity, time series prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1854488 MIMO Broadcast Scheduling for Weighted Sum-rate Maximization
Authors: Swadhin Kumar Mishra, Sidhartha Panda, C. Ardil
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Multiple-Input-Multiple-Output (MIMO) is one of the most important communication techniques that allow wireless systems to achieve higher data rate. To overcome the practical difficulties in implementing Dirty Paper Coding (DPC), various suboptimal MIMO Broadcast (MIMO-BC) scheduling algorithms are employed which choose the best set of users among all the users. In this paper we discuss such a sub-optimal MIMO-BC scheduling algorithm which employs antenna selection at the receiver side. The channels for the users considered here are not Identical and Independent Distributed (IID) so that users at the receiver side do not get equal opportunity for communication. So we introduce a method of applying weights to channels of the users which are not IID in such a way that each of the users gets equal opportunity for communication. The effect of weights on overall sum-rate achieved by the system has been investigated and presented.
Keywords: Antenna selection, Identical and Independent Distributed (IID), Sum-rate capacity, Weighted sum rate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1590487 Assessment of the Validity of Sentiment Analysis as a Tool to Analyze the Emotional Content of Text
Authors: Trisha Malhotra
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Sentiment analysis is a recent field of study that computationally assesses the emotional nature of a body of text. To assess its test-validity, sentiment analysis was carried out on the emotional corpus of text from a personal 15-day mood diary. Self-reported mood scores varied more or less accurately with daily mood evaluation score given by the software. On further assessment, it was found that while sentiment analysis was good at assessing ‘global’ mood, it was not able to ‘locally’ identify and differentially score synonyms of various emotional words. It is further critiqued for treating the intensity of an emotion as universal across cultures. Finally, the software is shown not to account for emotional complexity in sentences by treating emotions as strictly positive or negative. Hence, it is posited that a better output could be two (positive and negative) affect scores for the same body of text.
Keywords: Analysis, data, diary, emotions, mood, sentiment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1125486 Optimal Space Vector Control for Permanent Magnet Synchronous Motor based on Nonrecursive Riccati Equation
Authors: Marian Gaiceanu, Emil Rosu
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In this paper the optimal control strategy for Permanent Magnet Synchronous Motor (PMSM) based drive system is presented. The designed full optimal control is available for speed operating range up to base speed. The optimal voltage space-vector assures input energy reduction and stator loss minimization, maintaining the output energy in the same limits with the conventional PMSM electrical drive. The optimal control with three components is based on the energetically criteria and it is applicable in numerical version, being a nonrecursive solution. The simulation results confirm the increased efficiency of the optimal PMSM drive. The properties of the optimal voltage space vector are shown.Keywords: Matlab/Simulink, optimal control, permanent magnet synchronous motor, Riccati equation, space vector PWM
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2025485 Optimal Linear Quadratic Digital Tracker for the Discrete-Time Proper System with an Unknown Disturbance
Authors: Jason Sheng-Hong Tsai, Faezeh Ebrahimzadeh, Min-Ching Chung, Shu-Mei Guo, Leang-San Shieh, Tzong-Jiy Tsai, Li Wang
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In this paper, we first construct a new state and disturbance estimator using discrete-time proportional plus integral observer to estimate the system state and the unknown external disturbance for the discrete-time system with an input-to-output direct-feedthrough term. Then, the generalized optimal linear quadratic digital tracker design is applied to construct a proportional plus integral observer-based tracker for the system with an unknown external disturbance to have a desired tracking performance. Finally, a numerical simulation is given to demonstrate the effectiveness of the new application of our proposed approach.
Keywords: Optimal linear quadratic tracker, proportional plus integral observer, state estimator, disturbance estimator.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1293484 Information Support for Emergency Staff Processes and Effective Decisions
Authors: Tomáš Ludík, Josef Navrátil
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Managing the emergency situations at the Emergency Staff requires a high co-operation between its members and their fast decision making. For these purpose it is necessary to prepare Emergency Staff members adequately. The aim of this paper is to describe the development of information support that focuses to emergency staff processes and effective decisions. The information support is based on the principles of process management, and Process Framework for Emergency Management was used during the development. The output is the information system that allows users to simulate an emergency situation, including effective decision making. The system also evaluates the progress of the emergency processes solving by quantitative and qualitative indicators. By using the simulator, a higher quality education of specialists can be achieved. Therefore, negative impacts resulting from arising emergency situations can be directly reduced.Keywords: Information Support for Emergency Staff, Effective Decisions, Process Framework, Simulation of Emergency Processes, System Development.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1321483 System Reliability by Prediction of Generator Output and Losses in a Competitive Energy Market
Authors: Perumal Nallagownden, Ravindra N. Mukerjee, Syafrudin Masri
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In a competitive energy market, system reliability should be maintained at all times. Power system operation being of online in nature, the energy balance requirements must be satisfied to ensure reliable operation the system. To achieve this, information regarding the expected status of the system, the scheduled transactions and the relevant inputs necessary to make either a transaction contract or a transmission contract operational, have to be made available in real time. The real time procedure proposed, facilitates this. This paper proposes a quadratic curve learning procedure, which enables a generator-s contribution to the retailer demand, power loss of transaction in a line at the retail end and its associated losses for an oncoming operating scenario to be predicted. Matlab program was used to test in on a 24-bus IEE Reliability Test System, and the results are found to be acceptable.Keywords: Deregulation, learning coefficients, reliability, prediction, competitive energy market.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1478482 Single-Camera Basketball Tracker through Pose and Semantic Feature Fusion
Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro
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Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.Keywords: Basketball, deep learning, feature extraction, single-camera, tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 698481 A Development of the Multiple Intelligences Measurement of Elementary Students
Authors: Chaiwat Waree
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This research aims at development of the Multiple Intelligences Measurement of Elementary Students. The structural accuracy test and normality establishment are based on the Multiple Intelligences Theory of Gardner. This theory consists of eight aspects namely linguistics, logic and mathematics, visual-spatial relations, body and movement, music, human relations, self-realization/selfunderstanding and nature. The sample used in this research consists of elementary school students (aged between 5-11 years). The size of the sample group was determined by Yamane Table. The group has 2,504 students. Multistage Sampling was used. Basic statistical analysis and construct validity testing were done using confirmatory factor analysis. The research can be summarized as follows; 1. Multiple Intelligences Measurement consisting of 120 items is content-accurate. Internal consistent reliability according to the method of Kuder-Richardson of the whole Multiple Intelligences Measurement equals .91. The difficulty of the measurement test is between .39-.83. Discrimination is between .21-.85. 2). The Multiple Intelligences Measurement has construct validity in a good range, that is 8 components and all 120 test items have statistical significance level at .01. Chi-square value equals 4357.7; p=.00 at the degree of freedom of 244 and Goodness of Fit Index equals 1.00. Adjusted Goodness of Fit Index equals .92. Comparative Fit Index (CFI) equals .68. Root Mean Squared Residual (RMR) equals 0.064 and Root Mean Square Error of Approximation equals 0.82. 3). The normality of the Multiple Intelligences Measurement is categorized into 3 levels. Those with high intelligence are those with percentiles of more than 78. Those with moderate/medium intelligence are those with percentiles between 24 and 77.9. Those with low intelligence are those with percentiles from 23.9 downwards.
Keywords: Multiple Intelligences, Measurement, Elementary Students.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2958480 Power Allocation in User-Centric Cell-Free Massive MIMO Systems with Limited Fronthaul Capacity
Authors: Siminfar Samakoush Galougah
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In this paper, we study two power allocation problems for an uplink user-centric (UC) cell-free massive multiple-input multiple-output (CF-mMIMO) system. Besides, we assume each access point (AP) is connected to a central processing unit (CPU) via fronthaul link with limited capacity. To efficiently use the fronthaul capacity, two strategies for transmitting signals from APs to the CPU are employed; namely: compress-forward-estimate (CFE), estimate-compress-forward (ECF). The capacity of the aforementioned strategies in user-centric CF-mMIMO are drived. Then, we solved the two power allocation problems with minimum Spectral Efficiency (SE) and sum-SE maximization objectives for ECF and CFE strategies.
Keywords: Cell-free massive MIMO, limited capacity fronthaul, spectral efficiency, power allocation problem.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 72479 Prediction of Phenolic Compound Migration Process through Soil Media using Artificial Neural Network Approach
Authors: Supriya Pal, Kalyan Adhikari, Somnath Mukherjee, Sudipta Ghosh
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This study presents the application of artificial neural network for modeling the phenolic compound migration through vertical soil column. A three layered feed forward neural network with back propagation training algorithm was developed using forty eight experimental data sets obtained from laboratory fixed bed vertical column tests. The input parameters used in the model were the influent concentration of phenol(mg/L) on the top end of the soil column, depth of the soil column (cm), elapsed time after phenol injection (hr), percentage of clay (%), percentage of silt (%) in soils. The output of the ANN was the effluent phenol concentration (mg/L) from the bottom end of the soil columns. The ANN predicted results were compared with the experimental results of the laboratory tests and the accuracy of the ANN model was evaluated.Keywords: Modeling, Neural Networks, Phenol, Soil media
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2144478 Evolving Knowledge Extraction from Online Resources
Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao
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In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.Keywords: Evolving learning, knowledge extraction, knowledge graph, text mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 942477 Design of PI and Fuzzy Controller for High-Efficiency and Tightly Regulated Full Bridge DC-DC Converter
Authors: Sudha Bansal, Lalit Mohan Saini, Dheeraj Joshi
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The controller is used to improve the dynamic performance of DC-DC converter by achieving a robust output voltage against load disturbances. This paper presents the performance of PI and Fuzzy controller for a phase- shifted zero-voltage switched full-bridge PWM (ZVS FB- PWM) converters with a closed loop control. The proposed converter is regulated with minimum overshoot and good stability. In this paper phase-shift control method is used as an effective tool to reduce switching losses and duty cycle losses. A 1kW/100KHz dc/dc converter is simulated and analyzed using MATLAB. The circuit is simulated for static and dynamic load (DC motor). It has been observed that performance of converter with fuzzy controller is better than that of PI controller. An efficiency comparison of the converter with a reported topology has also been carried out.
Keywords: Full-bridge converter, phase-shifted, synchronous rectifier (SR), zero-voltage switching (ZVS).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2979476 Short-Term Electric Load Forecasting Using Multiple Gaussian Process Models
Authors: Tomohiro Hachino, Hitoshi Takata, Seiji Fukushima, Yasutaka Igarashi
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This paper presents a Gaussian process model-based short-term electric load forecasting. The Gaussian process model is a nonparametric model and the output of the model has Gaussian distribution with mean and variance. The multiple Gaussian process models as every hour ahead predictors are used to forecast future electric load demands up to 24 hours ahead in accordance with the direct forecasting approach. The separable least-squares approach that combines the linear least-squares method and genetic algorithm is applied to train these Gaussian process models. Simulation results are shown to demonstrate the effectiveness of the proposed electric load forecasting.
Keywords: Direct method, electric load forecasting, Gaussian process model, genetic algorithm, separable least-squares method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1984475 Computer Aided Detection on Mammography
Authors: Giovanni Luca Masala
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A typical definition of the Computer Aided Diagnosis (CAD), found in literature, can be: A diagnosis made by a radiologist using the output of a computerized scheme for automated image analysis as a diagnostic aid. Often it is possible to find the expression Computer Aided Detection (CAD or CADe): this definition emphasizes the intent of CAD to support rather than substitute the human observer in the analysis of radiographic images. In this article we will illustrate the application of CAD systems and the aim of these definitions. Commercially available CAD systems use computerized algorithms for identifying suspicious regions of interest. In this paper are described the general CAD systems as an expert system constituted of the following components: segmentation / detection, feature extraction, and classification / decision making. As example, in this work is shown the realization of a Computer- Aided Detection system that is able to assist the radiologist in identifying types of mammary tumor lesions. Furthermore this prototype of station uses a GRID configuration to work on a large distributed database of digitized mammographic images.Keywords: Computer Aided Detection, Computer Aided Diagnosis, mammography, GRID.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1927474 Negative Slope Ramp Carrier Control for High Power Factor Boost Converters in CCM Operation
Authors: T. Tanitteerapan, E.Thanpo
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This paper, a simple continuous conduction mode (CCM) pulse-width-modulated (PWM) controller for high power factor boost converters is introduced. The duty ratios were obtained by the comparison of a sensed signal from inductor current or switch current and a negative slope ramp carrier waveform in each switching period. Due to the proposed control requires only the inductor current or switch current sensor and the output voltage sensor, its circuit implementation was very simple. To verify the proposed control, the circuit experimentation of a 350 W boost converter with the proposed control was applied. From the results, the input current waveform was shaped to be closely sinusoidal, implying high power factor and low harmonics.
Keywords: High power factor converters, boost converters, low harmonic rectifiers, power factor correction, and current control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1811473 Multi-View Neural Network Based Gait Recognition
Authors: Saeid Fazli, Hadis Askarifar, Maryam Sheikh Shoaie
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Human identification at a distance has recently gained growing interest from computer vision researchers. Gait recognition aims essentially to address this problem by identifying people based on the way they walk [1]. Gait recognition has 3 steps. The first step is preprocessing, the second step is feature extraction and the third one is classification. This paper focuses on the classification step that is essential to increase the CCR (Correct Classification Rate). Multilayer Perceptron (MLP) is used in this work. Neural Networks imitate the human brain to perform intelligent tasks [3].They can represent complicated relationships between input and output and acquire knowledge about these relationships directly from the data [2]. In this paper we apply MLP NN for 11 views in our database and compare the CCR values for these views. Experiments are performed with the NLPR databases, and the effectiveness of the proposed method for gait recognition is demonstrated.Keywords: Human motion analysis, biometrics, gait recognition, principal component analysis, MLP neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2105472 A Novel EMG Feedback Control Method in Functional Electrical Stimulation Cycling System for Stroke Patients
Authors: Chien-Chih Chen, Ya-Hsin Hsueh, Zong-Cian He
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With getting older in the whole population, the prevalence of stroke and its residual disability is getting higher and higher recently in Taiwan. The functional electrical stimulation cycling system (FESCS) is useful for hemiplegic patients. Because that the muscle of stroke patients is under hybrid activation. The raw electromyography (EMG) represents the residual muscle force of stroke subject whereas the peak-to-peak of stimulus EMG indicates the force enhancement benefiting from ES. It seems that EMG signals could be used for a parameter of feedback control mechanism. So, we design the feedback control protocol of FESCS, it includes physiological signal recorder, FPGA biomedical module, DAC and electrical stimulation circuit. Using the intensity of real-time EMG signal obtained from patients, as a feedback control method for the output voltage of FES-cycling system.Keywords: Functional Electrical Stimulation cycling system EMG, control protocol.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2115471 Neural Network Optimal Power Flow(NN-OPF) based on IPSO with Developed Load Cluster Method
Authors: Mat Syai'in, Adi Soeprijanto
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An Optimal Power Flow based on Improved Particle Swarm Optimization (OPF-IPSO) with Generator Capability Curve Constraint is used by NN-OPF as a reference to get pattern of generator scheduling. There are three stages in Designing NN-OPF. The first stage is design of OPF-IPSO with generator capability curve constraint. The second stage is clustering load to specific range and calculating its index. The third stage is training NN-OPF using constructive back propagation method. In training process total load and load index used as input, and pattern of generator scheduling used as output. Data used in this paper is power system of Java-Bali. Software used in this simulation is MATLAB.Keywords: Optimal Power Flow, Generator Capability Curve, Improved Particle Swarm Optimization, Neural Network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1951470 Design of a Low Power Compensated 90nm RF Multiplier with Improved Isolation Characteristics for a Transmitted Reference Receiver Front End
Authors: Apratim Roy, A. B. M. H. Rashid
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In this paper, a double balanced radio frequency multiplier is presented which is customized for transmitted reference ultra wideband (UWB) receivers. The multiplier uses 90nm model parameters and exploits compensating transistors to provide controllable gain for a Gilbert core. After performing periodic and quasiperiodic non linear analyses the RF mixer (multiplier) achieves a voltage conversion gain of 16 dB and a DSB noise figure of 8.253 dB with very low power consumption. A high degree of LO to RF isolation (in the range of -94dB), RF to IF isolation (in the range of -95dB) and LO to IF isolation (in the range of -143dB) is expected for this design with an input-referred IP3 point of -1.93 dBm and an input referred 1 dB compression point of -10.67dBm. The amount of noise at the output is 7.7 nV/√Hz when the LO input is driven by a 10dBm signal. The mixer manifests better results when compared with other reported multiplier circuits and its Zero-IF performance ensures its applicability as TR-UWB multipliers.Keywords: UWB, Transmitted Reference, Controllable Gain, RFMixer, Multiplier.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1340469 Comparison of the Performance of GaInAsSb and GaSb Cells under Different Temperature Blackbody Radiations
Authors: Liangliang Tang, Chang Xu, Xingying Chen
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GaInAsSb cells probably show better performance than GaSb cells in low-temperature thermophotovoltaic systems due to lower bandgap; however, few experiments proved this phenomenon so far. In this paper, numerical simulation is used to evaluate GaInAsSb and GaSb cells with similar structures under different radiation temperatures. We found that GaInAsSb cells with n-type emitters show slightly higher output power densities compared with that of GaSb cells with n-type emitters below 1,550 K-blackbody radiation, and the power density of the later cells will suppress the formers above this temperature point. During the temperature range of 1,000~2,000 K, the efficiencies of GaSb cells are about twice of GaInAsSb cells if perfect filters are used to prevent the emission of the non-absorbed long wavelength photons. Several parameters that affect the GaInAsSb cell were analyzed, such as doping profiles, thicknesses of GaInAsSb epitaxial layer and surface recombination velocity. The non-p junctions, i.e., n-type emitters are better for GaInAsSb cell fabrication, which is similar to that of GaSb cells.Keywords: Thermophotovoltaic cell, GaSb, GaInAsSb, diffused emitters.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1174468 Dimensional Accuracy of CNTs/PMMA Parts and Holes Produced by Laser Cutting
Authors: A. Karimzad Ghavidel, M. Zadshakouyan
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Laser cutting is a very common production method for cutting 2D polymeric parts. Developing of polymer composites with nano-fibers makes important their other properties like laser workability. The aim of this research is investigation of the influence different laser cutting conditions on the dimensional accuracy of parts and holes from poly methyl methacrylate (PMMA)/carbon nanotubes (CNTs) material. Experiments were carried out by considering of CNTs (in four level 0,0.5, 1 and 1.5% wt.%), laser power (60, 80, and 100 watt) and cutting speed 20, 30, and 40 mm/s as input variable factors. The results reveal that CNTs adding improves the laser workability of PMMA and the increasing of power has a significant effect on the part and hole size. The findings also show cutting speed is effective parameter on the size accuracy. Eventually, the statistical analysis of results was done, and calculated mathematical equations by the regression are presented for determining relation between input and output factor.
Keywords: Dimensional accuracy-PMMA-CNTs-laser cutting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1190467 Improving the LDMOS Temperature Compensation Bias Circuit to Optimize Back-Off
Authors: Antonis Constantinides, Christos Yiallouras, Christakis Damianou
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The application of today's semiconductor transistors in high power UHF DVB-T linear amplifiers has evolved significantly by utilizing LDMOS technology. This fact provides engineers with the option to design a single transistor signal amplifier which enables output power and linearity that was unobtainable previously using bipolar junction transistors or later type first generation MOSFETS. The quiescent current stability in terms of thermal variations of the LDMOS guarantees a robust operation in any topology of DVB-T signal amplifiers. Otherwise, progressively uncontrolled heat dissipation enhancement on the LDMOS case can degrade the amplifier’s crucial parameters in regards to the gain, linearity and RF stability, resulting in dysfunctional operation or a total destruction of the unit. This paper presents one more sophisticated approach from the traditional biasing circuits used so far in LDMOS DVB-T amplifiers. It utilizes a microprocessor control technology, providing stability in topologies where IDQ must be perfectly accurate.
Keywords: Amplifier, DVB-T, LDMOS, MOSFETS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3271466 An Efficient Technique for Extracting Fuzzy Rulesfrom Neural Networks
Authors: Besa Muslimi, Miriam A. M. Capretz, Jagath Samarabandu
Abstract:
Artificial neural networks (ANN) have the ability to model input-output relationships from processing raw data. This characteristic makes them invaluable in industry domains where such knowledge is scarce at best. In the recent decades, in order to overcome the black-box characteristic of ANNs, researchers have attempted to extract the knowledge embedded within ANNs in the form of rules that can be used in inference systems. This paper presents a new technique that is able to extract a small set of rules from a two-layer ANN. The extracted rules yield high classification accuracy when implemented within a fuzzy inference system. The technique targets industry domains that possess less complex problems for which no expert knowledge exists and for which a simpler solution is preferred to a complex one. The proposed technique is more efficient, simple, and applicable than most of the previously proposed techniques.
Keywords: fuzzy rule extraction, fuzzy systems, knowledgeacquisition, pattern recognition, artificial neural networks.
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