International Journal of Electrical and Computer Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Articles
6,301 Documents
Log-domain electronically-tuneable fully differential high order multi-function filter
Osama O. Fares
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i2.pp1263-1272
This paper presents the synthesis of fully deferential circuit that is capable of performing simultaneous high-pass, low-pass, and band-pass filtering in the log domain. The circuit utilizes modified Seevinck’s integrators in the current mode. The transfer function describing the filter is first presented in the form of a canonical signal flow graph through applying Mason’s gain formula. The resulting signal flow graph consists of summing points and pick-off points associated with current mode integrators within unity-gain negative feedback loops. The summing points and the pick-off points are then synthesized as simple nodes and current mirrors, respectively. A new fully differential current-mode integrator circuit is proposed to realize the integration operation. The proposed integrator uses grounded capacitors with no resistors and can be adjusted to work as either lossless or lossy integrator via tuneable current sources. The gain and the cutoff frequency of the integrator are adjustable via biasing currents. Detailed design and simulation results of an example of a 5th order filter circuit is presented. The proposed circuit can perform simultaneously 5th order low-pass filtering, 5th order high-pass filtering, and 4th order band-pass filtering. The simulation is performed using Pspice with practical Infineon BFP649 BJT model. Simulation results show good matching with the target.
PORM: Predictive Optimization of Risk Management to control Uncertainty Problems in Software Engineering
Salma Firdose;
L. Manjunath Rao
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v8i6.pp4735-4744
Irrespective of different research-based approaches toward risk management, developing a precise model towards risk management is found to be a computationally challenging task owing to critical and vague definition of the origination of the problems. This research work introduces a model called as PROM i.e. Predictive Optimization of Risk Management with the perspective of software engineering. The significant contribution of PORM is to offer a reliable computation of risk analysis by considering generalized practical scenario of software development practices in Information Technology (IT) industry. The proposed PORM system is also designed and equipped with better risk factor assessment with an aid of machine learning approach without having more involvement of iteration. The study outcome shows that PORM system offers computationally cost effective analysis of risk factor as assessed with respect to different quality standards of object oriented system involved in every software projects.
Electricity Peak Load Demand using De-noising Wavelet Transform integrated with Neural Network Methods
Pituk Bunnoon
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 1: February 2016
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v6i1.pp12-20
One of most important elements in electric power system planning is load forecasts. So, in this paper proposes the load demand forecasts using de-noising wavelet transform (DNWT) integrated with neural network (NN) methods. This research, the case study uses peak load demand of Thailand (Electricity Generating Authority of Thailand: EGAT). The data of demand will be analyzed with many influencing variables for selecting and classifying factors. In the research, the de-noising wavelet transform uses for decomposing the peak load signal into 2 components these are detail and trend components. The forecasting method using the neural network algorithm is used. The work results are shown a good performance of the model proposed. The result may be taken to the one of decision in the power systems operation.
Minimum Eigenvalue Detection for Spectrum Sensing in Cognitive Radio
Syed Sajjad Ali;
Chang Liu;
Minglu Jin
International Journal of Electrical and Computer Engineering (IJECE) Vol 4, No 4: August 2014
Publisher : Institute of Advanced Engineering and Science
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Spectrum sensing is a key task for cognitive radio. Our motivation is to increase the probability of detection for spectrum sensing in cognitive radio. In this paper, we proposed a new semi blind method which is based on minimum Eigenvalue of a covariance matrix. The ratio of the minimum eigenvalue to noise power is used as the test statistic. The method does not need channel and signal information as prior knowledge. Eigenvalue based algorithm perform better than energy detection for correlated signal. Our proposed method is better than the maximum eigenvalue and energy detection for correlated signal. We perform Simulation which is based on digital TV signal. In all tests, our method performs better than maximum eigenvalue detection and energy detection.DOI:http://dx.doi.org/10.11591/ijece.v4i4.6226
Area & Power Efficient VLSI Architecture of Mode Decision in Integer Motion Estimation for HEVC Video Coding Standard
EL Ansari Abdessamad;
Nejmeddine Bahri;
Anass Mansouri;
Nouri Masmoud;
Ahaitouf Ali
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v9i4.pp2469-2480
In this paper, we propose a new parallel hardware architecture for the mode decision algorithm, that it is based on the Sum Absolute of the Difference (SAD) for compute the motion estimation, which is the most critical algorithm in the recent video encoding standard HEVC. In fact, this standard introduced new large variable block sizes for the motion estimation algorithm and therefore the SAD requires a more reduced execution time in order to achieve the real time processing even for the ultra-high resolution sequences. The proposed accelerator executes the SAD algorithm in a parallel way for all sub-block prediction units (PUs) and coding unit (CU) whatever their sizes, which turns in a huge improvements in the performances, given that all the block sizes, PUs in each CU, are supported and processed in the same time. The Xilinx Artix-7 (Zynq-7000) FPGA is used for the prototyping and the synthesis of the proposed accelerator. The mode decision for motion estimation scheme is implemented with 32K LUTs, 50K registers and 108Kb BRAMs. The implementation results show that our hardware architecture can achieve 30 frames per second of the 4K (3840 × 2160) resolutions in real time processing at 115.15MHz.
Framework for Contextual Outlier Identification using Multivariate Analysis approach and Unsupervised Learning
Madhu Chandra G.;
Sreerama Reddy G. M.
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v8i2.pp1092-1101
Majority of the existing commercial application for video surveillance system only captures the event frames where the accuracy level of captures is too poor. We reviewed the existing system to find that at present there is no such research technique that offers contextual-based scene identification of outliers. Therefore, we presented a framework that uses unsupervised learning approach to perform precise identification of outliers for a given video frames concerning the contextual information of the scene. The proposed system uses matrix decomposition method using multivariate analysis to maintain an equilibrium better faster response time and higher accuracy of the abnormal event/object detection as an outlier. Using an analytical methodology, the proposed system blocking operation followed by sparsity to perform detection. The study outcome shows that proposed system offers an increasing level of accuracy in contrast to the existing system with faster response time.
Optimal Siting of Distributed Generators in a Distribution Network using Artificial Immune System
Meera P.S.;
S. Hemamalini
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 2: April 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v7i2.pp641-649
Distributed generation (DG) sources are being installed in distribution networks worldwide due to their numerous advantages over the conventional sources which include operational and economical benefits. Random placement of DG sources in a distribution network will result in adverse effects such as increased power loss, loss of voltage stability and reliability, increase in operational costs, power quality issues etc. This paper presents a methodology to obtain the optimal location for the placement of multiple DG sources in a distribution network from a technical perspective. Optimal location is obtained by evaluating a global multi-objective technical index (MOTI) using a weighted sum method. Clonal selection based artificial immune system (AIS) is used along with optimal power flow (OPF) technique to obtain the solution. The proposed method is executed on a standard IEEE-33 bus radial distribution system. The results justify the choice of AIS and the use of MOTI in optimal siting of DG sources which improves the distribution system efficiency to a great extent in terms of reduced real and reactive power losses, improved voltage profile and voltage stability. Solutions obtained using AIS are compared with Genetic algorithm (GA) and Particle Swarm optimization (PSO) solutions for the same objective function.
Modelling and Passivity-based Control of a Non-isolated DC-DC Converter in a Fuel Cell System
Moutabir Ahmed;
Abdelmounim Elhassane;
Aboulfatah Mohamed
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v8i5.pp3436-3443
This paper presents the model of a fuel cell and the design and simulation of a cascade of two DC-DC converters. First, a detailed mathematical model of fuel cell is presented and simulated. Then, a nonlinear model of the whole controlled system is developed and a robust nonlinear controller of currents is synthesized using a passivity-based control. A formal analysis based on Lyapunov stability and average theory is developed to describe the control currents loops performances. A classical PI controller is used for the voltages loops. The simulation models have been developed and tested in the MATLAB/SIMULINK. Simulated results are displayed to validate the feasibility and the effectiveness of the proposed strategy.
Voltage collapse point evaluation considering the load dependence in a power system stability problem
Zaid Garcia Sanchez;
Jose Antonio González;
Gustavo Crespo;
Hernan Hernandez Herrera;
Jorge Iván Silva
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v10i1.pp61-71
Voltage Stability has emerged in recent decades as one of the most common phenomena, occurrence in Electrical Power Systems. Prior researches focused on the development of algorithm indices to solve the stability problem and in the determination of factors with most influence in voltage collapse to solve the stability problem. This paper evaluates the influence that the load dependence has with the voltage on the phenomenon of the voltage stability and especially on the characteristics the collapse point or instability point. Load modeling used is detailed and comparisons of the results obtained are made with those described in the bibliography and those obtained with commercial software. The results of the load margin are also compared when a constant load or a voltage-dependent load is considered as well as the values obtained at the maximum load point and the point of voltage instability.
Modeling and Simulation of a Photovoltaic Field for 13 kW
Salah Eddine Mankour;
Ahmed Wahid Belarbi;
Mohammed Tarik Benmessaoud
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v7i6.pp3271-3281
In the future solar energy will be very important source of energy. More than 45% of needed energy in the world will be generated by photovoltaic module. Therefore it is necessary to concentrate our efforts in order to reduce the application costs .This work investigates on the modeling of a Stand Alone Power System focusing on Photovoltaic energy systems. We introduce the models of the system components Therefore a maximum power point tracking (MPPT) technique is needed to track the peak power in order to make full utilization of PV array output power under varying conditions. This paper presents two widely-adopted MPPT algorithms, perturbation & observation (P&O) and incremental conductance (IC).A complete characterization and simulation model was implemented in the Matlab-Simulink environment. Design complete system is done to analyze its behavior for a typical year, with the aim to evaluate their energetic effectiveness.