Search results for: signal power

Authors: Seok Hong Min, Jung Ho Moon, Woo Young Jung, Tae Kwon Ha

Abstract:

The hot deformation behavior of high strength low alloy (HSLA) steels with different chemical compositions under hot working conditions in the temperature range of 900 to 1100℃ and strain rate range from 0.1 to 10 s-1 has been studied by performing a series of hot compression tests. The dynamic materials model has been employed for developing the processing maps, which show variation of the efficiency of power dissipation with temperature and strain rate. Also the Kumar-s model has been used for developing the instability map, which shows variation of the instability for plastic deformation with temperature and strain rate. The efficiency of power dissipation increased with decreasing strain rate and increasing temperature in the steel with higher Cr and Ti content. High efficiency of power dissipation over 20 % was obtained at a finite strain level of 0.1 under the conditions of strain rate lower than 1 s-1 and temperature higher than 1050 ℃ . Plastic instability was expected in the regime of temperatures lower than 1000 ℃ and strain rate lower than 0.3 s-1. Steel with lower Cr and Ti contents showed high efficiency of power dissipation at higher strain rate and lower temperature conditions.

Keywords: High strength low alloys steels, hot workability, Dynamic materials model, Processing maps.

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Authors: Sathans, A. Swarup

Abstract:

This paper presents the development and application of an adaptive neuro fuzzy inference system (ANFIS) based intelligent hybrid neuro fuzzy controller for automatic generation control (AGC) of two-area interconnected thermal power system with reheat non linearity. The dynamic response of the system has been studied for 1% step load perturbation in area-1. The performance of the proposed neuro fuzzy controller is compared against conventional proportional-integral (PI) controller, state feedback linear quadratic regulator (LQR) controller and fuzzy gain scheduled proportionalintegral (FGSPI) controller. Comparative analysis demonstrates that the proposed intelligent neuro fuzzy controller is the most effective of all in improving the transients of frequency and tie-line power deviations against small step load disturbances. Simulations have been performed using Matlab®.

Keywords: Automatic generation control, ANFIS, LQR, Hybrid neuro fuzzy controller

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Authors: Ezenwa Chinenye Amanamba

Abstract:

There is a call to ensure that the issues of safety and efficient throughput are considered during design; the solutions to these issues can also be retrofitted at locations where they were not captured during design, but have become problems to road users over time. This paper adopts several methods to analyze the performance of an intersection which was formerly a ‘priority-controlled’ intersection, but has now been converted to a ‘signal-controlled’ intersection. Extensive review of literature helped form the basis for result analysis and discussion. The Ikot-Ekpene/Anagha-Ezikpe intersection, located at the heart of Umuahia was adopted as case study; considering the high traffic volume on the route. Anecdotal evidence revealed that traffic signals imposed enormous delays at the intersection, especially for traffic on the major road. The major road has arrival flow which surpasses the saturation flow obtained from modelling of the isolated signalized intersection. Similarly, there were several geometric elements that did not agree with the specific function of the road. A roundabout, particularly flower roundabout was recommended as a better traffic control measure.

Keywords: Highway function, level of service, roundabout, traffic delays, Umuahia.

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Authors: Mohammad Reza Tabatabaei, Mohammad Bagher Haddadi, Mojtaba Saeedimoghadam, Ali Vaseghi Ardekani

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Economic Dispatch (ED) is one of the most challenging problems of power system since it is difficult to determine the optimum generation scheduling to meet the particular load demand with the minimum fuel costs while all constraints are satisfied. The objective of the Economic Dispatch Problems (EDPs) of electric power generation is to schedule the committed generating units outputs so as to meet the required load demand at minimum operating cost while satisfying all units and system equality and inequality constraints. In this paper, an efficient and practical steady-state genetic algorithm (SSGAs) has been proposed for solving the economic dispatch problem. The objective is to minimize the total generation fuel cost and keep the power flows within the security limits. To achieve that, the present work is developed to determine the optimal location and size of capacitors in transmission power system where, the Participation Factor Algorithm and the Steady State Genetic Algorithm are proposed to select the best locations for the capacitors and determine the optimal size for them.

Keywords: Economic Dispatch, Lagrange, Capacitors Placement, Losses Reduction, Genetic Algorithm.

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Authors: V. Bezlepkin, M. Karaseva, A. Frolov, E. Kharchenko, L. Lebedev

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The main features of NPP-2006/MIR-1200 design are described. Estimation of individual doses for population under normal operation and accident conditions is performed for Leningradskaya NPP – 2 as an example. The radiation effect on population and environment doesn-t exceed the established normative limit and is as low as reasonably achievable. NPP- 2006/MIR-1200 design meets all Russian and international requirements for power units under construction.

Keywords: Accident release, beyond design basis accident (BDBA), nuclear power plant (NPP), radiation safety.

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Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar

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DNA Barcode provides good sources of needed information to classify living species. The classification problem has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use the similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. However, all the used methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. In fact, our method permits to avoid the complex problem of form and structure in different classes of organisms. The empirical data and their classification performances are compared with other methods. Evenly, in this study, we present our system which is consisted of three phases. The first one, is called transformation, is composed of three sub steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. Moreover, the second phase step is an approximation; it is empowered by the use of Multi Library Wavelet Neural Networks (MLWNN). Finally, the third one, is called the classification of DNA Barcodes, is realized by applying the algorithm of hierarchical classification.

Keywords: DNA Barcode, Electron-Ion Interaction Pseudopotential, Multi Library Wavelet Neural Networks.

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Authors: Hirbod Varasteh, Hamidreza Gohari Darabkhani

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The global warming and its impact on climate change is one of main challenges for current century. Global warming is mainly due to the emission of greenhouse gases (GHG) and carbon dioxide (CO₂) is known to be the major contributor to the GHG emission profile. Whilst the energy sector is the primary source for CO₂ emission, Carbon Capture and Storage (CCS) are believed to be the solution for controlling this emission. Oxyfuel combustion (Oxy-combustion) is one of the major technologies for capturing CO₂ from power plants. For gas turbines, several Oxy-combustion power cycles (Oxyturbine cycles) have been investigated by means of thermodynamic analysis. NetPower cycle is one of the leading oxyturbine power cycles with almost full carbon capture capability from a natural gas fired power plant. In this manuscript, sensitivity analysis of the heat exchanger design in NetPower cycle is completed by means of process modelling. The heat capacity variation and supercritical CO₂ with gaseous admixtures are considered for multi-zone analysis with Aspen Plus software. It is found that the heat exchanger design has a major role to increase the efficiency of NetPower cycle. The pinch-point analysis is done to extract the composite and grand composite curve for the heat exchanger. In this paper, relationship between the cycle efficiency and the minimum approach temperature (∆Tmin) of the heat exchanger has also been evaluated.  Increase in ∆Tmin causes a decrease in the temperature of the recycle flue gases (RFG) and an overall decrease in the required power for the recycled gas compressor. The main challenge in the design of heat exchangers in power plants is a tradeoff between the capital and operational costs. To achieve lower ∆Tmin, larger size of heat exchanger is required. This means a higher capital cost but leading to a better heat recovery and lower operational cost. To achieve this, ∆Tmin is selected from the minimum point in the diagrams of capital and operational costs. This study provides an insight into the NetPower Oxy-combustion cycle’s performance analysis and operational condition based on its heat exchanger design.

Keywords: Carbon capture and storage, oxy-combustion, netpower cycle, oxyturbine power cycles, heat exchanger design, supercritical carbon dioxide, pinch point analysis.

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Authors: Omer Cahana, Maya Herman, Ofer Levi

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Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: Accelerate MRI scans, image reconstruction, pyramid network, deep learning.

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Authors: Bharat Mishra, Sanjay Kumar Awasthi, Raj Kumar Rajak

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The devices, which convert the energy in the form of electricity from organic matters, are called microbial fuel cell (MFC). Recently, MFCs have been given a lot of attention due to their mild operating conditions, and various types of biodegradable substrates have been used in the form of fuel. Traditional MFCs were included in anode and cathode chambers, but there are single chamber MFCs. Microorganisms actively catabolize substrate, and bioelectricities are produced. In the field of power generation from non-conventional sources, apart from the benefits of this technique, it is still facing practical constraints such as low potential and power. In this study, most suitable, natural, low cost MFCs components are electrodes (anode and cathode), organic substrates, membranes and its design is selected on the basis of maximum potential (voltage) as an electrical parameter, which indicates a vital role of affecting factor in MFC for sustainable power production.

Keywords: Substrates, electrodes, membranes, microbial fuel cells, voltage.

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Authors: Hyun-Young Kim, Chung-Kwang Lee, Han-Hee Cho, Sang-Woon Cho, Yong-Seo Koo

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In this paper, we proposed a novel SCR (Silicon Controlled Rectifier) - based ESD (Electrostatic Discharge) protection device for I/O and power clamp. The proposed device has a higher holding voltage characteristic than conventional SCR. These characteristics enable to have latch-up immunity under normal operating conditions as well as superior full chip ESD protection. The proposed device was analyzed to figure out electrical characteristics and tolerance robustness in term of individual design parameters (D1, D2, D3). They are investigated by using the Synopsys TCAD simulator. As a result of simulation, holding voltage increased with different design parameters. The holding voltage of the proposed device changes from 3.3V to 7.9V. Also, N-Stack structure ESD device with the high holding voltage is proposed. In the simulation results, 2-stack has holding voltage of 6.8V and 3-stack has holding voltage of 10.5V. The simulation results show that holding voltage of stacking structure can be larger than the operation voltage of high-voltage application.

Keywords: ESD, SCR, holding voltage, stack, power clamp.

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Authors: S. Ganesh

Abstract:

Power distribution systems typically have tie and sectionalizing switches whose states determine the topological configuration of the network. The aim of network reconfiguration of the distribution network is to minimize the losses for a load arrangement at a particular time. Thus the objective function is to minimize the losses of the network by satisfying the distribution network constraints. The various constraints are radiality, voltage limits and the power balance condition. In this paper the status of the switches is obtained by using Artificial Bee Colony (ABC) algorithm. ABC is based on a particular intelligent behavior of honeybee swarms. ABC is developed based on inspecting the behaviors of real bees to find nectar and sharing the information of food sources to the bees in the hive. The proposed methodology has three stages. In stage one ABC is used to find the tie switches, in stage two the identified tie switches are checked for radiality constraint and if the radilaity constraint is satisfied then the procedure is proceeded to stage three otherwise the process is repeated. In stage three load flow analysis is performed. The process is repeated till the losses are minimized. The ABC is implemented to find the power flow path and the Forward Sweeper algorithm is used to calculate the power flow parameters. The proposed methodology is applied for a 33–bus single feeder distribution network using MATLAB.

Keywords: Artificial Bee Colony (ABC) algorithm, Distribution system, Loss reduction, Network reconfiguration.

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Authors: Rajendraprasad Narne, P. C. Panda

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In this article, coordinated tuning of power system stabilizer (PSS) with static var compensator (SVC) and thyristor controlled series capacitor (TCSC) in multi-machine power system is proposed. The design of proposed coordinated damping controller is formulated as an optimization problem and the controller gains are optimized instantaneously using advanced adaptive particle swarm optimization (AAPSO). The objective function is framed with the inter-area speed deviations of the generators and it is minimized using AAPSO to improve the dynamic stability of power system under severe disturbance. The proposed coordinated controller performance is evaluated under a wide range of system operating conditions with three-phase fault disturbance. Using time domain simulations the damping characteristics of proposed controller is compared with individually tuned PSS, SVC and TCSC controllers. Finally, the real-time simulations are carried out in Opal-RT hardware simulator to synchronize the proposed controller performance in the real world.

Keywords: Advanced adaptive particle swarm optimization, Coordinated design, Power system stabilizer, Real-time implementation, static var compensator, Thyristor controlled series capacitor.

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Authors: Gelareh Mohammadi, Parisa Shoushtari, Behnam Molaee Ardekani, Mohammad B. Shamsollahi

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A direct connection between ElectroEncephaloGram (EEG) and the genetic information of individuals has been investigated by neurophysiologists and psychiatrists since 1960-s; and it opens a new research area in the science. This paper focuses on the person identification based on feature extracted from the EEG which can show a direct connection between EEG and the genetic information of subjects. In this work the full EO EEG signal of healthy individuals are estimated by an autoregressive (AR) model and the AR parameters are extracted as features. Here for feature vector constitution, two methods have been proposed; in the first method the extracted parameters of each channel are used as a feature vector in the classification step which employs a competitive neural network and in the second method a combination of different channel parameters are used as a feature vector. Correct classification scores at the range of 80% to 100% reveal the potential of our approach for person classification/identification and are in agreement to the previous researches showing evidence that the EEG signal carries genetic information. The novelty of this work is in the combination of AR parameters and the network type (competitive network) that we have used. A comparison between the first and the second approach imply preference of the second one.

Keywords: Person Identification, Autoregressive Model, EEG, Neural Network

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Authors: Samee Ullah Khan, C.Ardil

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With data centers, end-users can realize the pervasiveness of services that will be one day the cornerstone of our lives. However, data centers are often classified as computing systems that consume the most amounts of power. To circumvent such a problem, we propose a self-adaptive weighted sum methodology that jointly optimizes the performance and power consumption of any given data center. Compared to traditional methodologies for multi-objective optimization problems, the proposed self-adaptive weighted sum technique does not rely on a systematical change of weights during the optimization procedure. The proposed technique is compared with the greedy and LR heuristics for large-scale problems, and the optimal solution for small-scale problems implemented in LINDO. the experimental results revealed that the proposed selfadaptive weighted sum technique outperforms both of the heuristics and projects a competitive performance compared to the optimal solution.

Keywords: Meta-heuristics, distributed systems, adaptive methods, resource allocation.

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Authors: Musthafah b. Mohd.Tahir, Noboru Yamada, Tetsuya Hoshino

Abstract:

This paper describes the experimental efficiency of a compact organic Rankine cycle (ORC) system with a compact rotary-vane-type expander. The compact ORC system can be used for power generation from low-temperature heat sources such as waste heat from various small-scale heat engines, fuel cells, electric devices, and solar thermal energy. The purpose of this study is to develop an ORC system with a low power output of less than 1 kW with a hot temperature source ranging from 60°C to 100°C and a cold temperature source ranging from 10°C to 30°C. The power output of the system is rather less due to limited heat efficiency. Therefore, the system should have an economically optimal efficiency. In order to realize such a system, an efficient and low-cost expander is indispensable. An experimental ORC system was developed using the rotary-vane-type expander which is one of possible candidates of the expander. The experimental results revealed the expander performance for various rotation speeds, expander efficiencies, and thermal efficiencies. Approximately 30 W of expander power output with 48% expander efficiency and 4% thermal efficiency with a temperature difference between the hot and cold sources of 80°C was achieved.

Keywords: Organic Rankine cycle, Thermodynamic cycle, Thermal efficiency, Turbine efficiency, Waste heat recovery, Powergeneration, Low temperature heat engine.

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Authors: Isao Tomita

Abstract:

The principle of all-silicon Raman lasers for an output wavelength of 1.3 μm is presented, which employs quasi-phase-matched structures and resonators to enhance the output power. 1.3-μm laser beams for GE-PONs in FTTH systems generated from a silicon device are very important because such a silicon device can be monolithically integrated with the silicon planar lightwave circuits (Si PLCs) used in the GE-PONs. This reduces the device fabrication processes and time and also optical losses at the junctions between optical waveguides of the Si PLCs and Si laser devices when compared with 1.3-μm III-V semiconductor lasers set on the Si PLCs employed at present. We show that the quasi-phase-matched Si Raman laser with resonators can produce about 174 times larger laser power at 1.3 μm (at maximum) than that without resonators for a Si waveguide of Raman gain 20 cm/GW and optical loss 1.2 dB/cm, pumped at power 10 mW, where the length of the waveguide is 3 mm and its cross-section is (1.5 μm)2.

Keywords: All-silicon raman laser, FTTH, GE-PON, quasi-phase-matched structure, resonator.

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Authors: Yi-Cheng Huang, Yan-Chen Shin

Abstract:

This paper proposes method of diagnosing ball screw preload loss through the Hilbert-Huang Transform （HHT） and Multiscale entropy （MSE） process. The proposed method can diagnose ball screw preload loss through vibration signals when the machine tool is in operation. Maximum dynamic preload of 2 %, 4 %, and 6 % ball screws were predesigned, manufactured, and tested experimentally. Signal patterns are discussed and revealed using Empirical Mode Decomposition（EMD）with the Hilbert Spectrum. Different preload features are extracted and discriminated using HHT. The irregularity development of a ball screw with preload loss is determined and abstracted using MSE based on complexity perception. Experiment results show that the proposed method can predict the status of ball screw preload loss. Smart sensing for the health of the ball screw is also possible based on a comparative evaluation of MSE by the signal processing and pattern matching of EMD/HHT. This diagnosis method realizes the purposes of prognostic effectiveness on knowing the preload loss and utilizing convenience.

Keywords: Empirical Mode Decomposition, Hilbert-Huang Transform, Multi-scale Entropy, Preload Loss, Single-nut Ball Screw

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Authors: Mukul Shukla, Rasheedat M. Mahamood, Esther T. Akinlabi, Sisa. Pityana

Abstract:

Laser Metal Deposition (LMD) is an additive manufacturing process with capabilities that include: producing new part directly from 3 Dimensional Computer Aided Design (3D CAD) model, building new part on the existing old component and repairing an existing high valued component parts that would have been discarded in the past. With all these capabilities and its advantages over other additive manufacturing techniques, the underlying physics of the LMD process is yet to be fully understood probably because of high interaction between the processing parameters and studying many parameters at the same time makes it further complex to understand. In this study, the effect of laser power and powder flow rate on physical properties (deposition height and deposition width), metallurgical property (microstructure) and mechanical (microhardness) properties on laser deposited most widely used aerospace alloy are studied. Also, because the Ti6Al4V is very expensive, and LMD is capable of reducing buy-to-fly ratio of aerospace parts, the material utilization efficiency is also studied. Four sets of experiments were performed and repeated to establish repeatability using laser power of 1.8 kW and 3.0 kW, powder flow rate of 2.88 g/min and 5.67 g/min, and keeping the gas flow rate and scanning speed constant at 2 l/min and 0.005 m/s respectively. The deposition height / width are found to increase with increase in laser power and increase in powder flow rate. The material utilization is favoured by higher power while higher powder flow rate reduces material utilization. The results are presented and fully discussed.

Keywords: Laser Metal Deposition, Material Efficiency, Microstructure, Ti6Al4V.

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Authors: Aumnad Phdungsilp, Teeradej Wuttipornpun

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Decision support based upon risk analysis into comparison of the electricity generation from different renewable energy technologies can provide information about their effects on the environment and society. The aim of this paper is to develop the assessment framework regarding risks to health and environment, and the society-s benefits of the electric power plant generation from different renewable sources. The multicriteria framework to multiattribute risk analysis technique and the decision analysis interview technique are applied in order to support the decisionmaking process for the implementing renewable energy projects to the Bangkok case study. Having analyses the local conditions and appropriate technologies, five renewable power plants are postulated as options. As this work demonstrates, the analysis can provide a tool to aid decision-makers for achieving targets related to promote sustainable energy system.

Keywords: Analytic Hierarchy Process, Bangkok, MultiattributeRisk Analysis, Renewable Energy Technology.

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Authors: S. K. Satpathy, S. Panda, K. K. Nagwanshi, S. K. Nayak, C. Ardil

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Removing noise from the any processed images is very important. Noise should be removed in such a way that important information of image should be preserved. A decisionbased nonlinear algorithm for elimination of band lines, drop lines, mark, band lost and impulses in images is presented in this paper. The algorithm performs two simultaneous operations, namely, detection of corrupted pixels and evaluation of new pixels for replacing the corrupted pixels. Removal of these artifacts is achieved without damaging edges and details. However, the restricted window size renders median operation less effective whenever noise is excessive in that case the proposed algorithm automatically switches to mean filtering. The performance of the algorithm is analyzed in terms of Mean Square Error [MSE], Peak-Signal-to-Noise Ratio [PSNR], Signal-to-Noise Ratio Improved [SNRI], Percentage Of Noise Attenuated [PONA], and Percentage Of Spoiled Pixels [POSP]. This is compared with standard algorithms already in use and improved performance of the proposed algorithm is presented. The advantage of the proposed algorithm is that a single algorithm can replace several independent algorithms which are required for removal of different artifacts.

Keywords: Filtering, Decision Based Algorithm, noise, imagerestoration.

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Authors: Y. Ates, A. R. Boynuegri, M. Uzunoglu, A. Karakas

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The recent interest in alternative and renewable energy systems results in increased installed capacity ratio of such systems in total energy production of the world. Specifically, Wind Energy Conversion Systems (WECS) draw significant attention among possible alternative energy options, recently. On the contrary of the positive points of penetrating WECS in all over the world in terms of environment protection, energy independence of the countries, etc., there are significant problems to be solved for the grid connection of large scale WECS. The reactive power regulation, voltage variation suppression, etc. can be presented as major issues to be considered in this regard. Thus, this paper evaluates the application of a Static VAr Compensator (SVC) unit for the reactive power regulation and operation continuity of WECS during a fault condition. The system is modeled employing the IEEE 13 node test system. Thus, it is possible to evaluate the system performance with an overall grid simulation model close to real grid systems. The overall simulation model is developed in MATLAB/Simulink/SimPowerSystems® environments and the obtained results effectively match the target of the provided study.

Keywords: IEEE 13 bus distribution system, reactive power regulation, static VAr compensator, wind energy conversion system.

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Authors: S. Sendilkumar, B. L. Mathur, Joseph Henry

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A new approach for protection of power transformer is presented using a time-frequency transform known as Wavelet transform. Different operating conditions such as inrush, Normal, load, External fault and internal fault current are sampled and processed to obtain wavelet coefficients. Different Operating conditions provide variation in wavelet coefficients. Features like energy and Standard deviation are calculated using Parsevals theorem. These features are used as inputs to PNN (Probabilistic neural network) for fault classification. The proposed algorithm provides more accurate results even in the presence of noise inputs and accurately identifies inrush and fault currents. Overall classification accuracy of the proposed method is found to be 96.45%. Simulation of the fault (with and without noise) was done using MATLAB AND SIMULINK software taking 2 cycles of data window (40 m sec) containing 800 samples. The algorithm was evaluated by using 10 % Gaussian white noise.

Keywords: Power Transformer, differential Protection, internalfault, inrush current, Wavelet Energy, Db9.

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Authors: Sidhartha Panda, N. P. Padhy

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The application of a Static Synchronous Series Compensator (SSSC) controller to improve the transient stability performance of a power system is thoroughly investigated in this paper. The design problem of SSSC controller is formulated as an optimization problem and Particle Swarm Optimization (PSO) Technique is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor angle of the generator is involved; transient stability performance of the system is improved. The proposed controller is tested on a weakly connected power system subjected to different severe disturbances. The non-linear simulation results are presented to show the effectiveness of the proposed controller and its ability to provide efficient damping of low frequency oscillations. It is also observed that the proposed SSSC controller improves greatly the voltage profile of the system under severe disturbances.

Keywords: Particle swarm optimization, transient stability, power system oscillations, SSSC.

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Authors: Renzo Carta, Francesco Desogus

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Variations in the growth rate constant of the Listeria monocytogenes bacterial species were determined at 37°C in irradiated environments and compared to the situation of a nonirradiated environment. The bacteria cells, contained in a suspension made of a nutrient solution of Brain Heart Infusion, were made to grow at different frequency (2.30e2.60 GHz) and power (0e400 mW) values, in a plug flow reactor positioned in the irradiated environment. Then the reacting suspension was made to pass into a cylindrical cuvette where its optical density was read every 2.5 minutes at a wavelength of 600 nm. The obtained experimental data of optical density vs. time allowed the bacterial growth rate constant to be derived; this was found to be slightly influenced by microwave power, but not by microwave frequency; in particular, a minimum value was found for powers in the 50e150 mW field.

Keywords: Growth rate constant, irradiated environment, Listeria monocytogenes, microwaves, plug flow reactor.

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Authors: Fawaz S. Al-Anzi, Dia AbuZeina

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Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: Speech recognition, acoustic features, Mel Frequency Cepstral Coefficients.

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Authors: Naoki Saito, Daisuke Kon, Toshiyuki Sato

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This paper describes an underactuated robot hand operated by low-power actuators. It can grasp objects of various shapes using easy operations. This hand is suitable for use as a lightweight prosthetic hand that can grasp various objects using few input channels. To realize operations using a low-power actuator, a cross section deformation spring is proposed. The design procedure of the underactuated robot finger is proposed to realize an adaptive grasping movement. The validity of this mechanism and design procedure are confirmed through an object grasping experiment. Results demonstrate the effectiveness of across section deformation spring in reducing the actuator power. Moreover, adaptive grasping movement is realized by an easy operation.

Keywords: Robot hand, Underactuated mechanism, Cross section deformation spring, Prosthetic hand.

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Authors: Mihaela Popescu, Alexandru Bitoleanu, Mircea Dobriceanu, Vlad Suru

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The aim of this paper is to identify an optimum control strategy of three-phase shunt active filters to minimize the total harmonic distortion factor of the supply current. A classical PIPI cascade control solution of the output current of the active filterand the voltage across the DC capacitor based on Modulus–Optimum criterion is taken into consideration. The control system operation has been simulated using Matlab-Simulink environment and the results agree with the theoretical expectation. It is shown that there is an optimum value of the DC-bus voltage which minimizes the supply current harmonic distortion factor. It corresponds to the equality of the apparent power at the output of the active filter and the apparent power across the capacitor. Finally, predicted results are verified experimentally on a MaxSine active power filter.

Keywords: Active filtering, Controller tuning, Modulus Optimum criterion, Optimum control.

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Authors: Emilio Delgado, William Aperador, Alis Pataquiva

Abstract:

Biomass is becoming a large renewable resource for power generation; it is involved in higher frequency in environmentally clean processes, and even it is used for biofuels preparation. On the other hand, hydrogen – other energy source – can be produced in a variety of methods including gasification of biomass. In this study, the production of hydrogen by gasification of biomass waste is examined. This work explores the production of a gaseous mixture with high power potential from Amazonas´ specie known as copoazu, using a counter-flow fixed-bed bioreactor.

Keywords: Copoazu, Gasification, Hydrogen production.

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Authors: L. C. Ding, Bradley. G. Orr, K. Rahaoui, S. Truza, A. Date, A. Akbarzadeh

Abstract:

The research on thermoelectric has been a blooming field of research for the latest decade, owing to large amount of heat source available to be harvested, being eco-friendly and static in operation. This paper provides the performance of thermoelectric generator (TEG) with bulk material of bismuth telluride, Bi₂Te₃. Later, the performance of the TEGs is evaluated by considering attaching the TEGs on a plastic (polyethylene sheet) in contrast to the common method of attaching the TEGs on the metal surface.

Keywords: Electric power, heat transfer, renewable energy, thermoelectric generator.

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Authors: Gilberto Gonzalez-A

Abstract:

Bond graph models of an electrical transformer including the nonlinear saturation are presented. These models determine the relation between self and mutual inductances, and the leakage and magnetizing inductances of power transformers with two and three windings using the properties of a bond graph. The modelling and analysis using this methodology to three phase power transformers or transformers with internal incipient faults can be extended.

Keywords: Bond graph, electrical transformer, nonlinear saturation

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