Search results for: back trajectory model

Authors: A. J. Al-Shareef, E. A. Mohamed, E. Al-Judaibi

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Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This article presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data and historical electric load-related data using the data from the calendar years 2001, 2002, 2003, and 2004 for training. The model tested for one week at five different seasons, typically, winter, spring, summer, Ramadan and fall seasons, and the mean absolute average error for one hour-ahead load forecasting found 1.12%.

Keywords: Artificial neural networks, short-term load forecasting, back propagation.

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Authors: Venkatesh C., K. Shanti Swarup

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This paper investigates the impact on operating time delay and relay maloperation when 1st,2nd and 3rd order analog antialiasing filters are used in numerical distance protection. RC filter with cut-off frequency 90 Hz is used. Simulations are carried out for different SIR (Source to line Impedance Ratio), load, fault type and fault conditions using SIMULINK, where the voltage and current signals are fed online to the developed numerical distance relay model. Matlab is used for plotting the impedance trajectory. Investigation results shows that, about 75 % of the simulated cases, numerical distance relay operating time is not increased even-though there is a time delay when higher order filters are used. Relay maloperation (selectivity) also reduces (increases) when higher order filters are used in numerical distance protection.

Keywords: Antialiasing, capacitive voltage transformers, delay estimation, discrete Fourier transform (DFT), distance measurement, low-pass filters, source to line impedance ratio (SIR), protective relaying.

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Authors: Yahya H. Zweiri

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The back-propagation algorithm calculates the weight changes of an artificial neural network, and a two-term algorithm with a dynamically optimal learning rate and a momentum factor is commonly used. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third term increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and optimization approaches for evaluating the learning parameters are required to facilitate the application of the three terms BP algorithm. This paper considers the optimization of the new back-propagation algorithm by using derivative information. A family of approaches exploiting the derivatives with respect to the learning rate, momentum factor and proportional factor is presented. These autonomously compute the derivatives in the weight space, by using information gathered from the forward and backward procedures. The three-term BP algorithm and the optimization approaches are evaluated using the benchmark XOR problem.

Keywords: Neural Networks, Backpropagation, Optimization.

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Authors: Roberto Sabatini, Alessandro Gardi, Mark A. Richardson

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The availability of powerful eye-safe laser sources and the recent advancements in electro-optical and mechanical beam-steering components have allowed laser-based Light Detection and Ranging (LIDAR) to become a promising technology for obstacle warning and avoidance in a variety of manned and unmanned aircraft applications. LIDAR outstanding angular resolution and accuracy characteristics are coupled to its good detection performance in a wide range of incidence angles and weather conditions, providing an ideal obstacle avoidance solution, which is especially attractive in low-level flying platforms such as helicopters and small-to-medium size Unmanned Aircraft (UA). The Laser Obstacle Avoidance Marconi (LOAM) system is one of such systems, which was jointly developed and tested by SELEX-ES and the Italian Air Force Research and Flight Test Centre. The system was originally conceived for military rotorcraft platforms and, in this paper, we briefly review the previous work and discuss in more details some of the key development activities required for integration of LOAM on UA platforms. The main hardware and software design features of this LOAM variant are presented, including a brief description of the system interfaces and sensor characteristics, together with the system performance models and data processing algorithms for obstacle detection, classification and avoidance. In particular, the paper focuses on the algorithm proposed for optimal avoidance trajectory generation in UA applications.

Keywords: LIDAR, Low-Level Flight, Nap-of-the-Earth Flight, Near Infra-Red, Obstacle Avoidance, Obstacle Detection, Obstacle Warning System, Sense and Avoid, Trajectory Optimisation, Unmanned Aircraft.

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Authors: S. Chonsatidjamroen , K-N. Areerak, K-L. Areerak

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This paper presents the averaging model of a buck converter derived from the generalized state-space averaging method. The sliding mode control is used to regulate the output voltage of the converter and taken into account in the model. The proposed model requires the fast computational time compared with those of the full topology model. The intensive time-domain simulations via the exact topology model are used as the comparable model. The results show that a good agreement between the proposed model and the switching model is achieved in both transient and steady-state responses. The reported model is suitable for the optimal controller design by using the artificial intelligence techniques.

Keywords: Generalized state-space averaging method, buck converter, sliding mode control, modeling, simulation.

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Authors: Maad Kamal Al-Anni

Abstract:

This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Mobile ad hoc network, MANET, intrusion detection system, back propagation algorithm, neural networks, traffic table, multilayer perceptron, feed-forward back-propagation, network simulator 2.

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Authors: Yi-Chang Chen, Shan-Lin Chang, Chia-Chun Wu

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Unlike this study focused extensively on trading behavior of option market, those researches were just taken their attention to model-driven option pricing. For example, Black-Scholes (B-S) model is one of the most famous option pricing models. However, the arguments of B-S model are previously mentioned by some pricing models reviewing. This paper following suggests the importance of the dynamic character for option pricing, which is also the reason why using the genetic algorithm (GA). Because of its natural selection and species evolution, this study proposed a hybrid model, the Genetic-BS model which combining GA and B-S to estimate the price more accurate. As for the final experiments, the result shows that the output estimated price with lower MAE value than the calculated price by either B-S model or its enhanced one, Gram-Charlier garch (G-C garch) model. Finally, this work would conclude that the Genetic-BS pricing model is exactly practical.

Keywords: genetic algorithm, Genetic-BS, option pricing model.

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Authors: Amitabh Wahi, Sundaramurthy S.

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Natural outdoor scene classification is active and promising research area around the globe. In this study, the classification is carried out in two phases. In the first phase, the features are extracted from the images by wavelet decomposition method and stored in a database as feature vectors. In the second phase, the neural classifiers such as back-propagation neural network (BPNN) and resilient back-propagation neural network (RPNN) are employed for the classification of scenes. Four hundred color images are considered from MIT database of two classes as forest and street. A comparative study has been carried out on the performance of the two neural classifiers BPNN and RPNN on the increasing number of test samples. RPNN showed better classification results compared to BPNN on the large test samples.

Keywords: BPNN, Classification, Feature extraction, RPNN, Wavelet.

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Authors: L. Dzierzbicka-Głowacka, M. Janecki

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Dynamic of phytoplankton blooms in the Baltic Sea has been analyzed applying the numerical ecosystem model 3D CEMBS. The model consists of the hydrodynamic model (POP, version 2.1) and the ice model (CICE, version 4.0), which are imposed by the atmospheric data model (DATM7). The 3D model has an ecosystem module, activated in 2012 in the operational mode. The ecosystem model consists of 11 main variables: biomass of small-size phytoplankton and large-size phytoplankton and cyanobacteria, zooplankton biomass, dissolved and molecular detritus, dissolved oxygen concentration, as well as concentrations of nutrients, including: nitrates, ammonia, phosphates and silicates. The 3D-CEMBS model is an effective tool for solving problems related to phytoplankton blooms dynamic in the Baltic Sea

Keywords: Ecosystem model, phytoplankton, Baltic Sea

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Authors: Jianqiao. Yu, Jianbo. Wang, Xinzhen. He

Abstract:

This paper presents a longitudinal quasi-linear model for the ADMIRE model. The ADMIRE model is a nonlinear model of aircraft flying in the condition of high angle of attack. So it can-t be considered to be a linear system approximately. In this paper, for getting the longitudinal quasi-linear model of the ADMIRE, a state transformation based on differentiable functions of the nonscheduling states and control inputs is performed, with the goal of removing any nonlinear terms not dependent on the scheduling parameter. Since it needn-t linear approximation and can obtain the exact transformations of the nonlinear states, the above-mentioned approach is thought to be appropriate to establish the mathematical model of ADMIRE. To verify this conclusion, simulation experiments are done. And the result shows that this quasi-linear model is accurate enough.

Keywords: quasi-linear model, simulation, state transformation approach, the ADMIRE model.

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Authors: C. C. Okafor, E. E. Ugwu

Abstract:

A comparative study on the feasibility of producing instant high fibre plantain flour for diabetic fufu by blending soy residence with different plantain (Musa spp) varieties (Horn, false Horn and French), all sieved at 60 mesh, mixed in ratio of 60:40 was analyzed for their passing properties using standard analytical method. Results show that VIIIS60 had the highest peak viscosity (303.75 RVU), Trough value (182.08 RVU), final viscosity (284.50 RVU), and lowest in breakdown viscosity (79.58 RVU), set back value (88.17 RVU), peak time (4.36min), pasting temperature (81.18°C) and differed significantly (p <0.05) from other samples. VIS60 had the lowest in peak viscosity (192.25 RVU), Trough value (112.67 RVU), final viscosity (211.92 RVU), but highest in breakdown viscosity (121.61 RVU), peak time (4.66min) pasting temperature (82.35°C), and differed significantly (p <0.05), from other samples. VIIS60 had the medium peak viscosity (236.67 RVU), Trough value (116.58 RVU), Break down viscosity (120:08 RVU), set back viscosity (167.92 RVU), peak time (4.39min), pasting temp (81.44°C) and differed significantly (p <0.05) from other samples. High final viscosity and low set back values of the French variety with soy residue blended at 60 mesh particle size recommends this french variety and fibre composition as optimum for production of instant plantain soy residue flour blend for production of diabetic fufu. 

Keywords: Plantain, soy residue pasting properties particle size.

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

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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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Authors: Bahr Eldin S. M, K. S. Rama Rao, N. Perumal

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A generalized unified power quality conditioner (GUPQC) by using three single-phase three-level voltage source converters (VSCs) connected back-to-back through a common dc link is proposed in this paper as a new custom power device for a three-feeder distribution system. One of the converters is connected in shunt with one feeder for mitigation of current harmonics and reactive power compensation, while the other two VSCs are connected in series with the other two feeders to maintain the load voltage sinusoidal and at constant level. A new control scheme based on synchronous reference frame is proposed for series converters. The simulation analysis on compensation performance of GUPQC based on PSCAD/EMTDC is reported.

Keywords: Custom power device, generalized unified power quality conditioner, PSCAD/ETMDC, voltage source converter

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Authors: Lenka Ševelová, Aleš Florian

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Appropriate and progressive tool for analyzing behavior of low volume roads are probabilistic models used in reliability analyses. The necessary part of the probabilistic model is the deterministic model of structural behavior. The FE model of low volume roads is created in the ANSYS software. It is able to determine the state of stress and deformation in any point of the structure and thus generate data required for the reliability analysis. The paper compares two material constitutive models used for modeling of unbound non-homogenous materials used in low volume roads. The first model is linear elastic model according to Hook theory (H model), the second one is nonlinear elastic-plastic Drucker-Prager model (D-P model).

Keywords: FEA, FEM, geotechnical materials, low volume roads, material constitutive models, pavement.

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Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Inderpreet Kaur, Birinderjit S. Kalyan

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This work is a proposed model of CMOS for which the algorithm has been created and then the performance evaluation of this proposition has been done. In this context, another commonly used model called ZSTT (Zero Switching Time Transient) model is chosen to compare all the vital features and the results for the Proposed Equivalent CMOS are promising. In the end, the excerpts of the created algorithm are also included

Keywords: Dual Capacitor Model, ZSTT, CMOS, SPICEMacro-Model.

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Authors: Mehrdad N. Khajavi , Golamhassan Paygane, Ali Hakima

Abstract:

Vehicle which are turning or maneuvering at high speeds are susceptible to sliding and subsequently deviate from desired path. In this paper the dynamics governing the Yaw/Roll behavior of a vehicle has been simulated. Two different simulations have been used one for the real vehicle, for which a fuzzy controller is designed to increase its directional stability property. The other simulation is for a hypothetical vehicle with much higher tire cornering stiffness which is capable of developing the required lateral forces at the tire-ground patch contact to attain the desired lateral acceleration for the vehicle to follow the desired path without slippage. This simulation model is our reference model. The logic for keeping the vehicle on the desired track in the cornering or maneuvering state is to have some braking forces on the inner or outer tires based on the direction of vehicle deviation from the desired path. The inputs to our vehicle simulation model is steer angle δ and vehicle velocity V , and the outputs can be any kinematical parameters like yaw rate, yaw acceleration, side slip angle, rate of side slip angle and so on. The proposed fuzzy controller is a feed forward controller. This controller has two inputs which are steer angle δ and vehicle velocity V, and the output of the controller is the correcting moment M, which guides the vehicle back to the desired track. To develop the membership functions for the controller inputs and output and the fuzzy rules, the vehicle simulation has been run for 1000 times and the correcting moment have been determined by trial and error. Results of the vehicle simulation with fuzzy controller are very promising and show the vehicle performance is enhanced greatly over the vehicle without the controller. In fact the vehicle performance with the controller is very near the performance of the reference ideal model.

Keywords: Vehicle, Directional Stability, Fuzzy Logic Controller, ANFIS..

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Authors: H.Mohammadi Majd, M.Jalali Azizpour

Abstract:

In this paper back-propagation artificial neural network (BPANN )with Levenberg–Marquardt algorithm 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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Authors: May-Ling Tan, Yi Su, Chi-Wan Lim, Liang Zhong, Ru-San Tan

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This paper describes an automatic algorithm to restore the shape of three-dimensional (3D) left ventricle (LV) models created from magnetic resonance imaging (MRI) data using a geometry-driven optimization approach. Our basic premise is to restore the LV shape such that the LV epicardial surface is smooth after the restoration. A geometrical measure known as the Minimum Principle Curvature (κ2) is used to assess the smoothness of the LV. This measure is used to construct the objective function of a two-step optimization process. The objective of the optimization is to achieve a smooth epicardial shape by iterative in-plane translation of the MRI slices. Quantitatively, this yields a minimum sum in terms of the magnitude of κ 2, when κ2 is negative. A limited memory quasi-Newton algorithm, L-BFGS-B, is used to solve the optimization problem. We tested our algorithm on an in vitro theoretical LV model and 10 in vivo patient-specific models which contain significant motion artifacts. The results show that our method is able to automatically restore the shape of LV models back to smoothness without altering the general shape of the model. The magnitudes of in-plane translations are also consistent with existing registration techniques and experimental findings.

Keywords: Magnetic Resonance Imaging, Left Ventricle, ShapeRestoration, Principle Curvature, Optimization

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Authors: Alpha Agape Gopalai, S. M. N. Arosha Senanayake

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This paper explores the opportunity of using tri-axial wireless accelerometers for supervised monitoring of sports movements. A motion analysis system for the upper extremities of lawn bowlers in particular is developed. Accelerometers are placed on parts of human body such as the chest to represent the shoulder movements, the back to capture the trunk motion, back of the hand, the wrist and one above the elbow, to capture arm movements. These sensors placement are carefully designed in order to avoid restricting bowler-s movements. Data is acquired from these sensors in soft-real time using virtual instrumentation; the acquired data is then conditioned and converted into required parameters for motion regeneration. A user interface was also created to facilitate in the acquisition of data, and broadcasting of commands to the wireless accelerometers. All motion regeneration in this paper deals with the motion of the human body segment in the X and Y direction, looking into the motion of the anterior/ posterior and lateral directions respectively.

Keywords: Motion Regeneration, Virtual Instrumentation, Wireless Accelerometers.

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Authors: Mohammad Fuad Mohammad Naser, Faycal Ikhouane

Abstract:

LuGre friction model is an ordinary differential equation that is widely used in describing the friction phenomenon for mechanical systems. The importance of this model comes from the fact that it captures most of the friction behavior that has been observed including hysteresis. In this paper, we study some aspects related to the hysteresis behavior induced by the LuGre friction model.

Keywords: Hysteresis, LuGre model, operator, (strong) consistency.

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Authors: Vahid Mazloum, Mansour Sahebozamani, Amirhossein Barati, Nouzar Nakhaee, Pouya Rabiei

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Non-specific chronic low back pain (NSCLBP) is a common condition with no exact diagnosis and mechanism for its occurrence. Recently, different therapeutic exercises have taken into account to manage NSCLBP. So, the aim of this study has mainly been placed on comparing the effects of Pilates and Mackenzie exercises on quality of life (QOL) lumbar spine position sense (LSPS) in patients with NSCLBP. In this randomized clinical trial, 47 patients with NSCLBP were voluntarily divided into three groups of Pilates (n=16) (with mean age 37.1 ± 9.5 years, height 168.9 ± 7.4 cm, body mass 76.1 ± 5.9 k), McKenzie (n=15) (with mean age 42.7 ± 8.1 years, height 165.7 ± 6.8, body mass 74.1 ± 4.8 kg) and control (n=16) (with mean age 39.3 ± 9.8 years, height 168.1 ± 8.1 cm, body mass 74.2 ± 5.8 kg). Primary outcome included QOL and secondary was LSPS. Both variables were assessed by the WHOQOL-BREF questionnaires and electrogoniameter, respectively. The measurements were performed at baseline, following a 6-week intervention, and after a 4-week follow-up. The ANCOVA test at P < 0.05 was administrated to analyze the collected data using SPSS software. There was a statistically significant difference between experimental groups and the control group to improve QOL. But, no difference was seen regarding the effects of two exercises on LSPS (p < 0.05). Both Pilates and Mackenzie exercises demonstrated improvement in QOL after 6-week intervention and a 4-week follow-up while none of them considerably affected LSPS. Further studies are required to establish a supporting evidence for the effectiveness of two exercises on NSCLBP.

Keywords: Pilates, Mackenzie, proprioception, low back pain, physical health.

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Authors: Bogdan Walek, Jiri Bartos, Cyril Klimes

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This article deals with the conceptual modeling under uncertainty. First, the division of information systems with their definition will be described, focusing on those where the construction of a conceptual model is suitable for the design of future information system database. Furthermore, the disadvantages of the traditional approach in creating a conceptual model and database design will be analyzed. A comprehensive methodology for the creation of a conceptual model based on analysis of client requirements and the selection of a suitable domain model is proposed here. This article presents the expert system used for the construction of a conceptual model and is a suitable tool for database designers to create a conceptual model.

Keywords: Conceptual model, conceptual modeling, database, methodology, uncertainty, information system, entity, attribute, relationship, conceptual domain model, fuzzy.

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Authors: B. Ladghem Chikouche

Abstract:

The influence of slot wedges permeability on the electromagnetic performance of three-phase permanent magnet synchronous machine is investigated in this paper. It is shown that the back-EMF waveform, electromagnetic torque and electromagnetic torque ripple are all significantly affected by slot wedges permeability. The paper presents an accurate analytical subdomain model and confirmed by finite-element analyses.

Keywords: Exact analytical calculation, finite-element method, magnetic field distribution, permanent magnet machines performance, stator slot wedges permeability.

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Authors: Muhammad Marsudi, Dzuraidah Abdul Wahab, Che Hassan Che Haron

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Modeling of a manufacturing system enables one to identify the effects of key design parameters on the system performance and as a result to make correct decision. This paper proposes a manufacturing system modeling approach using a spreadsheet model based on queuing network theory, in which a static capacity planning model and stochastic queuing model are integrated. The model was used to improve the existing system utilization in relation to product design. The model incorporates few parameters such as utilization, cycle time, throughput, and batch size. The study also showed that the validity of developed model is good enough to apply and the maximum value of relative error is 10%, far below the limit value 32%. Therefore, the model developed in this study is a valuable alternative model in evaluating a manufacturing system

Keywords: Manufacturing system, product design, spreadsheet model, utilization.

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Authors: Tai Yuan Yu, Pei-Jen Wang

Abstract:

A simulation scheme of rotational motions for predictions of bump-type gas foil bearings operating at steady-state is proposed. The scheme is based on multi-physics coupling computer aided engineering packages modularized with computational fluid dynamic model and structure elasticity model to numerically solve the dynamic equation of motions of a hydrodynamic loaded shaft supported by an elastic bump foil. The bump foil is assumed to be modelled as infinite number of Hookean springs mounted on stiff wall. Hence, the top foil stiffness is constant on the periphery of the bearing housing. The hydrodynamic pressure generated by the air film lubrication transfers to the top foil and induces elastic deformation needed to be solved by a finite element method program, whereas the pressure profile applied on the top foil must be solved by a finite element method program based on Reynolds Equation in lubrication theory. As a result, the equation of motions for the bearing shaft are iteratively solved via coupling of the two finite element method programs simultaneously. In conclusion, the two-dimensional center trajectory of the shaft plus the deformation map on top foil at constant rotational speed are calculated for comparisons with the experimental results.

Keywords: Computational fluid dynamics, fluid structure interaction multi-physics simulations, gas foil bearing, load capacity.

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Authors: Jaswinder Kaur, Satwinder Singh, Karanjeet Singh Kahlon

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Accurate software cost estimates are critical to both developers and customers. They can be used for generating request for proposals, contract negotiations, scheduling, monitoring and control. The exact relationship between the attributes of the effort estimation is difficult to establish. A neural network is good at discovering relationships and pattern in the data. So, in this paper a comparative analysis among existing Halstead Model, Walston-Felix Model, Bailey-Basili Model, Doty Model and Neural Network Based Model is performed. Neural Network has outperformed the other considered models. Hence, we proposed Neural Network system as a soft computing approach to model the effort estimation of the software systems.

Keywords: Effort Estimation, Neural Network, Halstead Model, Walston-Felix Model, Bailey-Basili Model, Doty Model.

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents a model predictive control (MPC) of a utility interactive three phase inverter (TPI) for a photovoltaic (PV) system at commercial level. The proposed model uses phase locked loop (PLL) to synchronize the TPI with the power electric grid (PEG) and performs MPC control in a dq reference frame. TPI model consists of a boost converter (BC), maximum power point tracking (MPPT) control, and a three-leg voltage source inverter (VSI). The operational model of VSI is used to synthesize the sinusoidal current and track the reference. The model is validated using a 35.7 kW PV system in Matlab/Simulink. Implementation results show simplicity and accuracy, as well as reliability of the model.

Keywords: Model predictive control, three phase voltage source inverter, PV system, Matlab/Simulink.

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Authors: Ondruska Marek, Matustik Ondrej

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The main goal of the article is to present new model of application architecture of banking IT solution providing the Internet Banking services that is particularly outsourced. At first, we propose business rationale and a SWOT analysis to explain the reasons for the model in the article. The most important factor for our model is nowadays- big boom around smart phones and tablet devices. As next, we focus on IT architecture viewpoint where we design application, integration and security model. Finally, we propose a generic governance model that serves as a basis for the specialized governance model. The specialized instance of governance model is designed to ensure that the development and the maintenance of different parts of the IT solution are well governed in time.

Keywords: governance model, front-end application, Internet Banking, smart phones

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Authors: Vishnu Pratap Singh Kirar

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Artificial Neural Network (ANN) can be trained using back propagation (BP). It is the most widely used algorithm for supervised learning with multi-layered feed-forward networks. Efficient learning by the BP algorithm is required for many practical applications. The BP algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a twoterm algorithm consisting of a learning rate (LR) and a momentum factor (MF). The major drawbacks of the two-term BP learning algorithm are the problems of local minima and slow convergence speeds, which limit the scope for real-time applications. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and criteria for evaluating convergence are required to facilitate the application of the three terms BP algorithm. Although these two seem to be closely related, as described later, we summarize various improvements to overcome the drawbacks. Here we compare the different methods of convergence of the new three-term BP algorithm.

Keywords: Neural Network, Backpropagation, Local Minima, Fast Convergence Rate.

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Authors: N. H. Mvungi

Abstract:

Control of commutation of switched reluctance (SR) motor has been an area of interest for researchers for sometime now with mixed successes in addressing the inherent challenges. New technologies, processing schemes and methods have been adopted to make sensorless SR drive a reality. There are a number of conceptual, offline, analytical and online solutions in literature that have varying complexities and achieved equally varying degree of robustness and accuracies depending on the method used to address the challenges and the SR drive application. Magnetic coupling is one such challenge when using active probing techniques to determine rotor position of a SR motor from stator winding. This paper studies the effect of back-of-core saturation on the detected rotor position and presents results on measurement made on a 4- phase SR motor. The results shows that even for a four phase motor which is excited one phase at a time and using the electrically opposite phase for active position probing, the back-of-core saturation effects should not be ignored.

Keywords: Sensorless, SR motor, saturation effects, detection.

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