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30,907 Article Results

A hybrid bacterial foraging and modified particle swarm optimization for model order reduction

10.11591/ijece.v9i2.pp1100-1109
Hadeel N. Abdullah
This paper study the model reduction procedures used for the reduction of large-scale dynamic models into a smaller one through some sort of differential and algebraic equations. A confirmed relevance between these two models exists, and it shows same characteristics under study. These reduction procedures are generally utilized for mitigating computational complexity, facilitating system analysis, and thence reducing time and costs. This paper comes out with a study showing the impact of the consolidation between the Bacterial-Foraging (BF) and Modified particle swarm optimization (MPSO) for the reduced order model (ROM). The proposed hybrid algorithm (BF-MPSO) is comprehensively compared with the BF and MPSO algorithms; a comparison is also made with selected existing techniques.
Volume: 9
Issue: 2
Page: 1100-1109
Publish at: 2019-04-01

Improved power quality buck boost converter for SMPS

10.11591/ijece.v9i2.pp789-801
J. Jayachandran , S. Malathi
In this paper, a Neural Network (NN) controlled Buck-Boost Converter (BBC) based Switched Mode Power Supply (SMPS) for a PC application is proposed. The proposed BBC is analyzed, modeled and designed for the rated load. Generally, the utilization of Multiple Output SMPS (MOSMPS) for PC application introduces Power Quality (PQ) issues in the power system network. Unlike conventional SMPS the proposed NN controlled BBC can accomplish improvement of power quality. The NN controller reduces the Total Harmonic Distortion (THD) of source current below 5%, maintains input side Power Factor (PF) to be nearly unity and improves the output voltage regulation. In the proposed system, NN controller replaces the conventional PI controller and overcomes the drawbacks of the conventional system. The proposed BBC is validated adopting MATLAB/SIMULINK software. The simulation analysis validate that the proposed NN controlled BBC performs better than conventional converter in terms of PQ indices under fluctuating conditions.
Volume: 9
Issue: 2
Page: 789-801
Publish at: 2019-04-01

Game theory for resource sharing in large distributed systems

10.11591/ijece.v9i2.pp1249-1257
Sara Riahi , Azzeddine Riahi
In game theory, cooperative and non-cooperative approaches are distinguished in terms of two elements. The first refers to the player's ability to engage: in a non-cooperative context, they are entirely free to make decisions when they make their choices; However, in a cooperative context, they have the opportunity to engage contractually the strategies that should be adopted during the game, that during a phase of discussions held before the game and during combinations which may be formed.In this context, the problem is not so much to predict the outcome of the game between players to leave the benefit of cooperation. To achieve this, and this is the second major difference with the non-cooperative approach, it adopts an axiomatic approach (or normative) by which we set upstream properties a priori reasonable (or desirable) on the outcome of the game. The purpose of this paper is to present briefly the main types of non-cooperative games and the tools that allow them to be analyzed in a complete information context where all aspects of the game are well known to decision makers.
Volume: 9
Issue: 2
Page: 1249-1257
Publish at: 2019-04-01

Introducing LQR-fuzzy for a dynamic multi area LFC-DR model

10.11591/ijece.v9i2.pp861-874
Palakaluri Srividya Devi , R.Vijaya Santhi
It is well known that Load Frequency Control (LFC) model plays a vital role in electric power system design and operation. In the literature, much research works has stated on the advantages and realization of DR (Demand Response), which has proved to be an important part of the future smart grid. In an interconnected power system, if a load   demand changes randomly, both frequency and tie line power varies. LFC-DR model is tuned by standard controllers like PI, PD, PID controllers, as they have constant gains. Hence, they are incapable of acquiring desirable dynamic performance for an extensive variety of operating conditions and various load changes. This paper presents the idea of introducing a DR control loop in the traditional Multi area LFC model (called LFC -DR) using LQR- Fuzzy Logic Control. The effect of DR-CDL i.e. (Demand Response Communication Delay Latency) in the design is also considered and is linearized using Padé approximation. Simulation results shows that the addition of DR control loop with proposed controller guarantees stability of the overall closed-loop LFC-DR system which effectively improves the system dynamic performance and is superior over a classical controller at different operating scenarios.
Volume: 9
Issue: 2
Page: 861-874
Publish at: 2019-04-01

A novel sketch-based 3D model retrieval approach based on skeleton

10.11591/ijict.v8i1.pp1-12
Jing Zhang , Bao Sheng Kang , Bo Jiang , Di Zhang
Since the skeleton represents the topology structure of the query sketch and 2D views of 3D model, this paper proposes a novel sketch-based 3D model retrieval algorithm which utilizes skeleton characteristics as the features to describe the object shape. Firstly, we propose advanced skeleton strength map (ASSM) algorithm to create the skeleton which computes the skeleton strength map by isotropic diffusion on the gradient vector field, selects critical points from the skeleton strength map and connects them by Kruskal's algorithm. Then, we propose histogram feature comparison algorithm which adopts the radii of the disks at skeleton points and the lengths of skeleton branches to extract the histogram feature, and compare the similarity between two skeletons using the histogram feature matrix of skeleton endpoints. Experiment results demonstrate that our approach which combines these two algorithms significantly outperforms several leading sketch-based retrieval approaches.
Volume: 8
Issue: 1
Page: 1-12
Publish at: 2019-04-01

Advanced teaching-learning-based optimization algorithm for actual power loss reduction

10.11591/ijra.v9i1.pp46-50
Lenin Kanagasabai
In this work Advanced Teaching-Learning-Based Optimization algorithm (ATLBO) is proposed to solve the optimal reactive power problem. Teaching-Learning-Based Optimization (TLBO) optimization algorithm has been framed on teaching learning methodology happening in classroom. Algorithm consists of “Teacher Phase”, “Learner Phase”. In the proposed Advanced Teaching-Learning-Based Optimization algorithm non-linear inertia weighted factor is introduced into the fundamental TLBO algorithm to manage the memory rate of learners. In order to control the learner’s mutation arbitrarily during the learning procedure a non-linear mutation factor has been applied. Proposed Advanced Teaching-Learning-Based Optimization algorithm (ATLBO) has been tested in standard IEEE 14, 30 bus test systems and simulation results show the proposed algorithm reduced the real power loss effectively.
Volume: 9
Issue: 1
Page: 46-50
Publish at: 2019-03-06

Nonlinear systems identification with discontinuous nonlinearity

10.11591/ijra.v9i1.pp34-41
Mohamed Benyassi , Adil Brouri , Smail Slassi
In this paper, nonparametric nonlinear systems identification is proposed. The considered system nonlinearity is nonparametric and is of hard type. This latter can be discontinuous and noninvertible. The entire nonlinear system is structured by Hammerstein model. Furthermore, the linear dynamic block is of any order and can be nonparametric. The problem identification method is done within two stages. In the first stage, the system nonlinearity is identified using simple input signals. In the first stage, the linear dynamic block parameters are estimated using periodic signals. The proposed algorithm can be used of large class of nonlinear systems.
Volume: 9
Issue: 1
Page: 34-41
Publish at: 2019-03-06

Performance evaluation of SEPIC, Luo and ZETA converter

10.11591/ijpeds.v10.i1.pp374-380
Niranjana Siddharthan , Baskaran Balasubramanian
DC-DC converters are devices which convert direct current (DC) from one voltage level to another by changing the duty cycle of the main switches in the circuits. These converters are widely used in switched mode power supplies and it is important to supply a constant output voltage, regardless of disturbances on the input voltage. In this work, the performance of three different converters such as Single-Ended Primary-Inductance Converter (SEPIC), Luo converter and ZETA converter have been analyzed. Further, the parameters values such as ripple voltage, switching losses and efficiency of the proposed three different converters were compared with each other. Also, the simulation work has been carried out using MATLAB/SIMULINK software. From the comparison of obtained results, it is observed that the ZETA converter has high significance than the SEPIC and Luo converter.
Volume: 10
Issue: 1
Page: 374-380
Publish at: 2019-03-01

Augmented reality application for location finder guidance

10.11591/ijeecs.v13.i3.pp1237-1242
Anatun Nadrah Rosman , Noor Azah Samsudin , Azizan Ismail , Muhammad Syariff Aripin , Shamsul Kamal Ahmad Khalid
Finding directions to a specific location can be troublesome especially when we are not familiar with a new area. Conventionally, we may want to ask people around or possibly we use Global Positioning System (GPS) navigator. However, using GPS navigator may not be the best solution if the address is not entered accurately.  Therefore, this paper presents an augmented reality (AR) application for location finder guidance. Instead, a user is only required to scan the address indicated on a surface such as card or flyer using smart phone camera.The proposed application has utilized various components of AR technology including multiple image target, virtual button and markerless features. The development of the AR application follows phases of activities in Multimedia Mobile Content Development (MMCD) model. The proposed application is found to be very interactive and convenient in finding directions to specific location.
Volume: 13
Issue: 3
Page: 1237-1242
Publish at: 2019-03-01

Multilayer neural network synchronized secured session key based encryption in wireless communication

10.11591/ijai.v8.i1.pp44-53
Arindam Sarkar
In this paper, multilayer neural network synchronized session key based encryption has been proposed for wireless communication of data/information. Multilayer perceptron transmitting systems at both ends accept an identical input vector, generate an output bit and the network are trained based on the output bit which is used to form a protected variable length secret-key. For each session, different hidden layer of multilayer neural network is selected randomly and weights or hidden units of this selected hidden layer help to form a secret session key. The plain text is encrypted through chaining, cascaded xoring of multilayer perceptron generated session key. If size of the final block of plain text is less than the size of the key then this block is kept unaltered. Receiver will use identical multilayer perceptron generated session key for performing deciphering process for getting the plain text. Parametric tests have been done and results are compared in terms of Chi-Square test, response time in transmission with some existing classical techniques, which shows comparable results for the proposed technique.
Volume: 8
Issue: 1
Page: 44-53
Publish at: 2019-03-01

A comparison between the secp256r1 and the koblitz secp256k1 bitcoin curves

10.11591/ijeecs.v13.i3.pp910-918
Azine Houria , Bencherif Mohamed Abdelkader , Guessoum Abderezzak
Bitcoin uses elliptic curve cryptography for its keys and signatures, but the specific secp256k1 curve used is rather unusual. The ECDSA keys used to generate Bitcoin addresses and sign transactions are derived from some specific parameters. Due to this characteristic, several questions come up concerning Satoshi’s choice of this curve rather than that of the NIST standard secp256r1 curve. Former President Dan Brown’s address to Bitcoin users on the Bitcoin talk.org online forum concerning the use of secp256k1 in Bitcoin of SECG showed his surprise to see someone uses SECG secp256k1 instead of secp256r1 of NIST.In this article, we will analyze the random secp256r1 curve and the Koblitz Secp256k1 curve (parameters, equation, automorphism…), by giving the strengths and weaknesses of each one of them, in order to justify the choice of Bitcoin’s creator, and then we will tackle the mining using the new graphic cards.
Volume: 13
Issue: 3
Page: 910-918
Publish at: 2019-03-01

Optimization study of fuzzy parametric uncertain system

10.11591/ijai.v8.i1.pp14-25
Tejal D. Apale , Ajay B. Patil
This paper deals with the analysis and design of the optimal robust controller for the fuzzy parametric uncertain system. An LTI system in which coefficients depends on parameters described by a fuzzy function is called as fuzzy parametric uncertain system. By optimal control design, we get control law and feedback gain matrix which can stabilize the system. The robust controller design is a difficult task so we go for the optimal control approach. The system can be converted into state space controllable canonical form with the α-cut property fuzzy. For optimal control design, we find control law and get the feedback gain matrix which can stabilize the system and optimizes the cost function. Stability analysis is done by using the Kharitonov theorem and Lyapunov-Popov method. The proposed method applied to a response of Continuous Stirred Tank Reactor (CSTR).
Volume: 8
Issue: 1
Page: 14-25
Publish at: 2019-03-01

Electric vehicle technology impacts on energy

10.11591/ijpeds.v10.i1.pp1-9
Wael A. Salah , Basim Alsayid , Mahmoud A. M. Albreem , Basem Abu Zneid , Mutasem Alkhasawneh , Anwar Al–Mofleh , Anees Abu Sneineh , Amir Abu Al-Aish
The CO2 emission level is becoming a serious issue worldwide. The continuous increase in gasoline price forms the essential base of development of electric vehicle (EV) drives. Moreover, economic and environmental issues relate to fabrication and operation of traditional powered vehicles. The basic considerations and development perspectives of EVs are presented in this paper. The development of an efficiently designed motor and drive satisfy the need of efficient characteristics that enable EVs to perform as part of the propulsion unit. The use of digital signal controllers compared with conventional control systems minimizes the motor’s total harmonic distortion, lowers operating temperatures, and produces high efficiency and power factor ratings. This paper addresses the view of EV technology as well its advantages over other technologies.
Volume: 10
Issue: 1
Page: 1-9
Publish at: 2019-03-01

An improved radial basis function networks in networks weights adjustment for training real-world nonlinear datasets

10.11591/ijai.v8.i1.pp63-76
Lim Eng Aik , Tan Wei Hong , Ahmad Kadri Junoh
In neural networks, the accuracies of its networks are mainly relying on two important factors which are the centers and the networks weight. The gradient descent algorithm is a widely used weight adjustment algorithm in most of neural networks training algorithm. However, the method is known for its weakness for easily trap in local minima. It suffers from a random weight generated for the networks during initial stage of training at input layer to hidden layer networks. The performance of radial basis function networks (RBFN) has been improved from different perspectives, including centroid initialization problem to weight correction stage over the years. Unfortunately, the solution does not provide a good trade-off between quality and efficiency of the weight produces by the algorithm. To solve this problem, an improved gradient descent algorithm for finding initial weight and improve the overall networks weight is proposed. This improved version algorithm is incorporated into RBFN training algorithm for updating weight. Hence, this paper presented an improved RBFN in term of algorithm for improving the weight adjustment in RBFN during training process. The proposed training algorithm, which uses improved gradient descent algorithm for weight adjustment for training RBFN, obtained significant improvement in predictions compared to the standard RBFN. The proposed training algorithm was implemented in MATLAB environment. The proposed improved network called IRBFN was tested against the standard RBFN in predictions. The experimental models were tested on four literatures nonlinear function and four real-world application problems, particularly in Air pollutant problem, Biochemical Oxygen Demand (BOD) problem, Phytoplankton problem, and forex pair EURUSD. The results are compared to IRBFN for root mean square error (RMSE) values with standard RBFN. The IRBFN yielded a promising result with an average improvement percentage more than 40 percent in RMSE.
Volume: 8
Issue: 1
Page: 63-76
Publish at: 2019-03-01

Determination of pre-service science teachers’ attitudes towards reading science texts

10.11591/ijere.v8i1.16856
Şendil Can , Gülperi Öztürk
The purpose of the current study is to determine the effects of the variables such as gender, grade level, grade point average and book reading frequency on pre-service science teachers’ attitudes towards science texts. The sampling of the current study is comprised of 103 pre-service science teachers enrolled at the Education Faculty of Muğla Sıtkı Koçman University in the spring term of 2017-2018 academic year. In the current study, in order to determine the pre-service teachers’ attitudes towards reading science texts, “The Scale of Attitudes towards Reading Science Texts” was used. The effects of gender and grade level on the pre-service science teachers’ attitudes towards reading science texts were analyzed with independent samples t-test and the effects of academic achievement and book reading frequency were analyzed with one-way variance analysis (ANOVA). As a result of the study, it was concluded that the gender and grade level variables have significant effects on the pre-service teachers’ attitudes towards reading science texts in the sub-dimensions of making use of science texts when possible, denial and contribution of reading science texts to learning and skills and that the general grade point average and book reading frequency have significant effects on the pre-service teachers’ attitudes towards reading science texts in the sub-dimension of making use of science texts when possible.
Volume: 8
Issue: 1
Page: 181-188
Publish at: 2019-03-01
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