Search results for: Fast output sampling
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2470

Search results for: Fast output sampling

1120 Influence of Silica Surface Hydrophilicity on Adsorbed Water and Isopropanol Studied by in-situ NMR

Authors: Hyung T. Kwak, Jun Gao, Yao An, Alfred Kleinhammes, Yue Wu

Abstract:

Surface wettability is a crucial factor in oil recovery. In oil industry, the rock wettability involves the interplay between water, oil, and solid surface. Therefore, studying the interplay between adsorptions of water and hydrocarbon molecules on solid surface would be very informative for understanding rock wettability. Here we use the in-situ Nuclear Magnetic Resonance (NMR) gas isotherm technique to study competitive adsorptions of water and isopropanol, an intermediate step from hydrocarbons. This in-situ NMR technique obtains information on thermodynamic properties such as the isotherm, molecular dynamics via spin relaxation measurements, and adsorption kinetics such as how fast the system can reach thermal equilibrium after changes of vapor pressures. Using surfaces of silica glass beads, which can be modified from hydrophilic to hydrophobic, we obtained information on the influence of surface hydrophilicity on the state of surface water via obtained thermodynamic and dynamic properties.

Keywords: Competitive adsorption, nuclear magnetic resonance, wettability.

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1119 Evolving Knowledge Extraction from Online Resources

Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

Abstract:

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.

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1118 A Study of Relationship between Mountaineering Participation Motivation and Risk Perception

Authors: Yen-Chieh Wen, Ching-Hui Lin

Abstract:

The main purpose of this study is to analyze climbers involved in motivation and risk perception and analysis of the predictive ability of the risk perception "mountaineering" involved in motivation. This study used questionnaires, to have to climb the 3000m high mountain in Taiwan climbers object to carry out an investigation in order to non-random sampling, a total of 231 valid questionnaires were. After statistical analysis, the study found that: 1. Climbers the highest climbers involved in motivation "to enjoy the natural beauty of the fun. 2 climbers for climbers "risk perception" the highest: the natural environment of risk. 3. Climbers “seeking adventure stimulate", “competence achievement" motivation highly predictive of risk perception. Based on these findings, this study not only practices the recommendations of the outdoor leisure industry, and also related research proposals for future researchers.

Keywords: Mountaineering, motivation, risk perception, decision-making.

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1117 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

Abstract:

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).

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1116 Short-Term Electric Load Forecasting Using Multiple Gaussian Process Models

Authors: Tomohiro Hachino, Hitoshi Takata, Seiji Fukushima, Yasutaka Igarashi

Abstract:

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.

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1115 Computer Aided Detection on Mammography

Authors: Giovanni Luca Masala

Abstract:

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.

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1114 Ballast Water Management Triad: Administration, Ship Owner and the Seafarer

Authors: Rajoo Balaji, Omar Yaakob

Abstract:

The Ballast Water Convention requires less than 5% of the world tonnage for ratification. Consequently, ships will have to comply with the requirements. Compliance evaluation and enforcement will become mandatory. Ship owners have to invest in treatment systems and shipboard personnel have to operate them and ensure compliance. The monitoring and enforcement will be the responsibilities of the Administrations. Herein, a review of the current status of the Ballast Water Management and the issues faced by these are projected. Issues range from efficacy and economics of the treatment systems to sampling and testing. Health issues of chemical systems, paucity of data for decision support etc., are other issues. It is emphasized that management of ballast water must be extended to ashore and sustainable solutions must be researched upon. An exemplar treatment system based on ship’s waste heat is also suggested.

Keywords: Ballast water management, Compliance evaluation, Compliance enforcement, Sustainability.

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1113 Relationship between Functionality and Cognitive Impairment in Older Adult Women from the Southeast of Mexico

Authors: Estrella C. Damaris, Ingrid A. Olais, Gloria P. Uicab

Abstract:

This study explores the relationship between the level of functionality and cognitive impairment in older adult women from the south-east of Mexico. It is a descriptive, cross-sectional study; performed with 172 participants in total who attended a health institute and live in Merida, Yucatan Mexico. After a non-probabilistic sampling, Barthel and Pfeiffer scales were applied. The results show statistically significant correlation between the cognitive impairment (Pfeiffer) and the levels of independence and function (Barthel) (r =0.489; p =0.001). Both determine a dependence level so they need either a little or a lot of help. Society needs that the older woman be healthy and that the professionals of mental health develop activities to prevent and rehabilitate because cognitive impairment and function are directly related with the quality of life.

Keywords: Functionality, cognition, routine activities, cognitive impairment.

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1112 Negative Slope Ramp Carrier Control for High Power Factor Boost Converters in CCM Operation

Authors: T. Tanitteerapan, E.Thanpo

Abstract:

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.

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1111 Inspection of Geometrical Integrity of Work Piece and Measurement of Tool Wear by the Use of Photo Digitizing Method

Authors: R. Alipour, F. Nadjarian, A. Alinaghizade

Abstract:

Considering complexity of products, new geometrical design and investment tolerances that are necessary, measuring and dimensional controlling involve modern and more precise methods. Photo digitizing method using two cameras to record pictures and utilization of conventional method named “cloud points" and data analysis by the use of ATOUS software, is known as modern and efficient in mentioned context. In this paper, benefits of photo digitizing method in evaluating sampling of machining processes have been put forward. For example, assessment of geometrical integrity surface in 5-axis milling process and measurement of carbide tool wear in turning process, can be can be brought forward. Advantages of this method comparing to conventional methods have been expressed.

Keywords: photo digitizing, tool wear, geometrical integrity, cloud points

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1110 Multi-View Neural Network Based Gait Recognition

Authors: Saeid Fazli, Hadis Askarifar, Maryam Sheikh Shoaie

Abstract:

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.

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1109 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

Abstract:

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.

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1108 Additional Considerations on a Sequential Life Testing Approach using a Weibull Model

Authors: D. I. De Souza, D. R. Fonseca, R. Rocha

Abstract:

In this paper we will develop further the sequential life test approach presented in a previous article by [1] using an underlying two parameter Weibull sampling distribution. The minimum life will be considered equal to zero. We will again provide rules for making one of the three possible decisions as each observation becomes available; that is: accept the null hypothesis H0; reject the null hypothesis H0; or obtain additional information by making another observation. The product being analyzed is a new type of a low alloy-high strength steel product. To estimate the shape and the scale parameters of the underlying Weibull model we will use a maximum likelihood approach for censored failure data. A new example will further develop the proposed sequential life testing approach.

Keywords: Sequential Life Testing, Underlying Weibull Model, Maximum Likelihood Approach, Hypothesis Testing.

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1107 Experimental Characterization of the Color Quality and Error Rate for an Red, Green, and Blue-Based Light Emission Diode-Fixture Used in Visible Light Communications

Authors: Juan F. Gutierrez, Jesus M. Quintero, Diego Sandoval

Abstract:

An important feature of Lighting Emitting Diodes (LED) technology is the fast on-off commutation. This fact allows data transmission using modulation formats such as On-Off Keying (OOK) and Color Shift Keying (CSK). Since, CSK based on three color bands uses red, green, and blue monochromatic LED (RGB-LED) to define a pattern of chromaticities; this type of CSK provides poor color quality on the illuminated area. In this work, we present the design and implementation of a VLC system using RGB-based CSK with 16, 8, and 4 color points, mixing with a steady baseline of a phosphor white-LED, to improve the color quality of the LED-Fixture. The experimental system was assessed in terms of the Symbol Error Rate (SER) and the Color Rendering Index (CRI). Good color quality performance of the LED-Fixture was obtained with an acceptable SER. We describe the laboratory setup used to characterize and calibrate an LED-Fixture.

Keywords: Color rendering index, symbol error rate, color shift keying, visible light communications.

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1106 Neural Network Optimal Power Flow(NN-OPF) based on IPSO with Developed Load Cluster Method

Authors: Mat Syai'in, Adi Soeprijanto

Abstract:

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

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1105 Stability Improvement of AC System by Controllability of the HVDC

Authors: Omid Borazjani, Alireza Rajabi, Mojtaba Saeedimoghadam, Khodakhast Isapour

Abstract:

High Voltage Direct Current (HVDC) power transmission is employed to move large amounts of electric power. There are several possibilities to enhance the transient stability in a power system. One adequate option is by using the high controllability of the HVDC if HVDC is available in the system. This paper presents a control technique for HVDC to enhance the transient stability. The strategy controls the power through the HVDC to help make the system more transient stable during disturbances. Loss of synchronism is prevented by quickly producing sufficient decelerating energy to counteract accelerating energy gained during. In this study, the power flow in the HVDC link is modulated with the addition of an auxiliary signal to the current reference of the rectifier firing angle controller. This modulation control signal is derived from speed deviation signal of the generator utilizing a PD controller; the utilization of a PD controller is suitable because it has the property of fast response. The effectiveness of the proposed controller is demonstrated with a SMIB test system.

Keywords: HVDC, SMIB, Stability, Power System.

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1104 ESS Control Strategy for Primary Frequency Response in Microgrid Considering Ramp Rate

Authors: Ho-Jun Jo, Wook-Won Kim, Yong-Sung Kim, Jin-O Kim

Abstract:

The application of ESS (Energy Storage Systems) in the future grids has been the solution of the microgrid. However, high investment costs necessitate accurate modeling and control strategy of ESS to justify its economic viability and further underutilization. Therefore, the reasonable control strategy for ESS which is subjected to generator and usage helps to curtail the cost of investment and operation costs. The rated frequency in power system is decreased when the load is increasing unexpectedly; hence the thermal power is operated at the capacity of only its 95% for the Governor Free (GF) to adjust the frequency as reserve (5%) in practice. The ESS can be utilized with governor at the same time for the frequency response due to characteristic of its fast response speed and moreover, the cost of ESS is declined rapidly to the reasonable price. This paper presents the ESS control strategy to extend usage of the ESS taken account into governor’s ramp rate and reduce the governor’s intervention as well. All results in this paper are simulated by MATLAB.

Keywords: Micro grid, energy storage systems, ramp rate, control strategy.

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1103 LiDAR Based Real Time Multiple Vehicle Detection and Tracking

Authors: Zhongzhen Luo, Saeid Habibi, Martin v. Mohrenschildt

Abstract:

Self-driving vehicle require a high level of situational awareness in order to maneuver safely when driving in real world condition. This paper presents a LiDAR based real time perception system that is able to process sensor raw data for multiple target detection and tracking in dynamic environment. The proposed algorithm is nonparametric and deterministic that is no assumptions and priori knowledge are needed from the input data and no initializations are required. Additionally, the proposed method is working on the three-dimensional data directly generated by LiDAR while not scarifying the rich information contained in the domain of 3D. Moreover, a fast and efficient for real time clustering algorithm is applied based on a radially bounded nearest neighbor (RBNN). Hungarian algorithm procedure and adaptive Kalman filtering are used for data association and tracking algorithm. The proposed algorithm is able to run in real time with average run time of 70ms per frame.

Keywords: LiDAR, real-time system, clustering, tracking, data association.

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1102 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

Abstract:

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.

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1101 Elephant Herding Optimization for Service Selection in QoS-Aware Web Service Composition

Authors: Samia Sadouki Chibani, Abdelkamel Tari

Abstract:

Web service composition combines available services to provide new functionality. Given the number of available services with similar functionalities and different non functional aspects (QoS), the problem of finding a QoS-optimal web service composition is considered as an optimization problem belonging to NP-hard class. Thus, an optimal solution cannot be found by exact algorithms within a reasonable time. In this paper, a meta-heuristic bio-inspired is presented to address the QoS aware web service composition; it is based on Elephant Herding Optimization (EHO) algorithm, which is inspired by the herding behavior of elephant group. EHO is characterized by a process of dividing and combining the population to sub populations (clan); this process allows the exchange of information between local searches to move toward a global optimum. However, with Applying others evolutionary algorithms the problem of early stagnancy in a local optimum cannot be avoided. Compared with PSO, the results of experimental evaluation show that our proposition significantly outperforms the existing algorithm with better performance of the fitness value and a fast convergence.

Keywords: Elephant herding optimization, web service composition, bio-inspired algorithms, QoS optimization.

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1100 Comparison of the Performance of GaInAsSb and GaSb Cells under Different Temperature Blackbody Radiations

Authors: Liangliang Tang, Chang Xu, Xingying Chen

Abstract:

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.

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1099 Dimensional Accuracy of CNTs/PMMA Parts and Holes Produced by Laser Cutting

Authors: A. Karimzad Ghavidel, M. Zadshakouyan

Abstract:

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.

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1098 Improving the LDMOS Temperature Compensation Bias Circuit to Optimize Back-Off

Authors: Antonis Constantinides, Christos Yiallouras, Christakis Damianou

Abstract:

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.

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1097 Distance Transmission Line Protection Based on Radial Basis Function Neural Network

Authors: Anant Oonsivilai, Sanom Saichoomdee

Abstract:

To determine the presence and location of faults in a transmission by the adaptation of protective distance relay based on the measurement of fixed settings as line impedance is achieved by several different techniques. Moreover, a fast, accurate and robust technique for real-time purposes is required for the modern power systems. The appliance of radial basis function neural network in transmission line protection is demonstrated in this paper. The method applies the power system via voltage and current signals to learn the hidden relationship presented in the input patterns. It is experiential that the proposed technique is competent to identify the particular fault direction more speedily. System simulations studied show that the proposed approach is able to distinguish the direction of a fault on a transmission line swiftly and correctly, therefore suitable for the real-time purposes.

Keywords: radial basis function neural network, transmission lines protection, relaying, power system.

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1096 Calculation of Water Economy Balance for Water Management

Authors: Vakhtang Geladze, Nana Bolashvili, Tamazi Karalashvili, Nino Machavariani, Ana Karalashvili, George Geladze, Nana Kvirkvelia

Abstract:

Fresh water deficit is one of the most important global problems today. It must be taken into consideration that in the nearest future fresh water crisis will become even more acute owing to the global climate warming and fast desertification processes in the world. Georgia is rich in water resources, but there are disbalance between the eastern and western parts of the country. The goal of the study is to integrate the recent mechanisms compatible with European standards into Georgian water resources management system on the basis of GIS. Moreover, to draw up water economy balance for the purpose of proper determination of water consumption priorities that will be an exchange ratio of water resources and water consumption of the concrete territory. For study region was choose south-eastern part of country, Kvemo kartli Region. This is typical agrarian region, tends to the desertification. The water supply of the region was assessed on the basis of water economy balance, which was first time calculated for this region.

Keywords: GIS, water economy balance, water resources.

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1095 Sparse Coding Based Classification of Electrocardiography Signals Using Data-Driven Complete Dictionary Learning

Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

Abstract:

In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: Electrocardiogram, dictionary learning, sparse coding, classification.

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1094 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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1093 IIR Filter design with Craziness based Particle Swarm Optimization Technique

Authors: Suman Kumar Saha, Rajib Kar, Durbadal Mandal, S. P. Ghoshal

Abstract:

This paper demonstrates the application of craziness based particle swarm optimization (CRPSO) technique for designing the 8th order low pass Infinite Impulse Response (IIR) filter. CRPSO, the much improved version of PSO, is a population based global heuristic search algorithm which finds near optimal solution in terms of a set of filter coefficients. Effectiveness of this algorithm is justified with a comparative study of some well established algorithms, namely, real coded genetic algorithm (RGA) and particle swarm optimization (PSO). Simulation results affirm that the proposed algorithm CRPSO, outperforms over its counterparts not only in terms of quality output i.e. sharpness at cut-off, pass band ripple, stop band ripple, and stop band attenuation but also in convergence speed with assured stability.

Keywords: IIR Filter, RGA, PSO, CRPSO, Evolutionary Optimization Techniques, Low Pass (LP) Filter, Magnitude Response, Pole-Zero Plot, Stability.

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1092 1 kW Power Factor Correction Soft Switching Boost Converter with an Active Snubber Cell

Authors: Yakup Sahin, Naim Suleyman Ting, Ismail Aksoy

Abstract:

A 1 kW power factor correction boost converter with an active snubber cell is presented in this paper. In the converter, the main switch turns on under zero voltage transition (ZVT) and turns off under zero current transition (ZCT) without any additional voltage or current stress. The auxiliary switch turns on and off under zero current switching (ZCS). Besides, the main diode turns on under ZVS and turns off under ZCS. The output current and voltage are controlled by the PFC converter in wide line and load range. The simulation results of converter are obtained for 1 kW and 100 kHz. One of the most important feature of the given converter is that it has direct power transfer as well as excellent soft switching techniques. Also, the converter has 0.99 power factor with the sinusoidal input current shape.

Keywords: Power factor correction, direct power transfer, zero-voltage transition, zero-current transition, soft switching.

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1091 Prediction the Deformation in Upsetting Process by Neural Network and Finite Element

Authors: H.Mohammadi Majd, M.Jalali Azizpour , Foad Saadi

Abstract:

In this paper back-propagation artificial neural network (BPANN) is employed to predict the deformation of the upsetting process. To prepare a training set for BPANN, some finite element simulations were carried out. The input data for the artificial neural network are a set of parameters generated randomly (aspect ratio d/h, material properties, temperature and coefficient of friction). The output data are the coefficient of polynomial that fitted on barreling curves. Neural network was trained using barreling curves generated by finite element simulations of the upsetting and the corresponding material parameters. This technique was tested for three different specimens and can be successfully employed to predict the deformation of the upsetting process

Keywords: Back-propagation artificial neural network(BPANN), prediction, upsetting

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