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International Journal of Electrical and Computer Engineering

IJECE
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Published by Institute of Advanced Engineering and Science

ISSN : 20888708 EISSN : 27222578 DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics 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.

Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)

Articles 6,301 Documents

156 157 158 159 160

Dual iris authentication system using dezert smarandache theory Kamel Ghanem Ghalem; Fatiha Hendel
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

In this paper, a dual iris authentication using Dezert Smarandache theory is presented. The proposed method consists of three main steps: In the first one, the iris images are segmented in order to extract only half iris disc that contains relevant information and is less affected by noise. For that, a Hough transform is used. The segmented images are normalized by Daugman rubber sheet model. In the second step, the normalized images are analyzed by a bench of two 1D Log-Gabor filters to extract the texture characteristics. The encoding is realized with a phase of quantization developed by J. Daugman to generate the binary iris template. For the authentication and the similarity measurement between both binary irises templates, the hamming distances are used with a previously calculated threshold. The score fusion is applied using DSmC combination rule. The proposed method has been tested on a subset of iris database CASIA-IrisV3-Interval. The obtained results give a satisfactory performance with accuracy of 99.96%, FAR of 0%, FRR of 3.89%, EER of 2% and processing time for one iris image of 12.36 s.

Herb Leaves Recognition using Gray Level Co-occurrence Matrix and Five Distance-based Similarity Measures R. Rizal Isnanto; Munawar Agus Riyadi; Muhammad Fahmi Awaj
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

Herb medicinal products derived from plants have long been considered as an alternative option for treating various diseases. In this paper, the feature extraction method used is Gray Level Co-occurrence Matrix (GLCM), while for its recognition using the metric calculations of Chebyshev, Cityblock, Minkowski, Canberra, and Euclidean distances. The method of determining the GLCM Analysis based on the texture analysis resulting from the extraction of this feature is Angular Second Moment, Contrast, Inverse Different Moment, Entropy as well as its Correlation. The recognition system used 10 leaf test images with GLCM method and Canberra distance resulted in the highest accuracy of 92.00%. While the use of 20 and 30 test data resulted in a recognition rate of 50.67% and 60.00%.

Iterative improved learning algorithm for petrographic image classification accuracy enhancement Ashutosh Marathe; Priya Jain; Vibha Vyas
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 1: February 2019
Publisher : Institute of Advanced Engineering and Science

Rock image classification using image processing has been practiced to assist trained geologists in decision making. However, the study of microstructures of rocks and their use in geological investigations offer challenges in the areas of Image processing and Pattern Classification due to the stochastic nature of the mineral textures that is revealed at the microscopic level. Locally relevant Igneous Rock Microstructure images were classified from Volcanic and Plutonic Rock subtypes. The imaging method used mineral grain size as the key physical feature of classification. Three algorithms, namely Radial Basis Function (RBF) Support Vector Machine classifier; Improved (RBF) Support Vector Machine classifier; and AdaBoost algorithm with Improved RBF Support Vector Machine algorithm as base classifier, were used as a base classifier in a novel ‘Iterative Improved Learning (IIL)’ approach. Implementing the IIL approach in the chosen algorithm resulted in accurately classified images that were added to the training set to enhance the ‘breadth and depth’ of the learning knowledge. The algorithm iterated through all available classifier approaches and compared the inter-classifier performance and knowledge of the misclassified images accumulated during the execution of all algorithms.

A Novel Method based on Gaussianity and Sparsity for Signal Separation Algorithms Abouzid Houda; Chakkor Otman
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 4: August 2017
Publisher : Institute of Advanced Engineering and Science

Blind source separation is a very known problem which refers to finding the original sources without the aid of information about the nature of the sources and the mixing process, to solve this kind of problem having only the mixtures, it is almost impossible , that why using some assumptions is needed in somehow according to the differents situations existing in the real world, for exemple, in laboratory condition, most of tested algorithms works very fine and having good performence because the nature and the number of the input signals are almost known apriori and then the mixing process is well determined for the separation operation. But in fact, the real-life scenario is much more different and of course the problem is becoming much more complicated due to the the fact of having the most of the parameters of the linear equation are unknown. In this paper, we present a novel method based on Gaussianity and Sparsity for signal separation algorithms where independent component analysis will be used. The Sparsity as a preprocessing step, then, as a final step, the Gaussianity based source separation block has been used to estimate the original sources. To validate our proposed method, the FPICA algorithm based on BSS technique has been used.

Fiber optics based schemes modeling and simulation of QoS for Wi-Fi scenarios using OPNET modeler Suhad Hasan Rhaif; Adnan Hussein Ali; Rana K. Abdulnabi; Ali Abdulwahhab Abdulrazzaq
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Wireless Fidelity (Wi-Fi) network is created on the IEEE 802.11 standard. Connections for local devices in homes and business arenas are provided by Wi-Fi units. With the growing demand as well as penetration of wireless services, the wireless networks users now assume Quality of Service (QoS) besides performances comparable to what is accessible from secure networks. In this paper, OPNET Modeler is used as module and for the simulation of a fiber optic-based Wi-Fi network within a fixed local area network. The aim of this paper is to evaluate their Quality of service (QoS) performances in terms of Wi-Fi voice-packet delay and End-to-End for both Wi-Fi base fiber and Wi-Fi base line. Many scenarios, with same Physical and MAC parameters, have many subnet networks are implementing with fiber optics baseline in addition to Wi-Fi baseline, were created in the network OPNET simulation tool for obtaining the results. The results of simulation reveal that base line demonstrated more delay than base fiber.

Efficient Feature Subset Selection Algorithm for High Dimensional Data Smita Chormunge; Sudarson Jena
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 4: August 2016
Publisher : Institute of Advanced Engineering and Science

Feature selection approach solves the dimensionality problem by removing irrelevant and redundant features. Existing Feature selection algorithms take more time to obtain feature subset for high dimensional data. This paper proposes a feature selection algorithm based on Information gain measures for high dimensional data termed as IFSA (Information gain based Feature Selection Algorithm) to produce optimal feature subset in efficient time and improve the computational performance of learning algorithms. IFSA algorithm works in two folds: First apply filter on dataset. Second produce the small feature subset by using information gain measure. Extensive experiments are carried out to compare proposed algorithm and other methods with respect to two different classifiers (Naive bayes and IBK) on microarray and text data sets. The results demonstrate that IFSA not only produces the most select feature subset in efficient time but also improves the classifier performance.

An Efficient Adaptive Noise Cancellation Scheme Using ALE and NLMS Filters Jafar Ramadhan Mohammed; Muhammad Safder Shafi; Sahar Imtiaz; Rafay Iqbal Ansari; Mansoor Khan
International Journal of Electrical and Computer Engineering (IJECE) Vol 2, No 3: June 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (310.103 KB)

The basic theme of our paper is to implement a new idea of noise reduction in the real time applications using the concepts of adaptive filters. Our model which is presented as one of the solutions is based on two stages of operation with the first stage based on the ALE (Adaptive Line Enhancer) filters and the second stage on NLMS (Normalized Least Mean Square) filter. The first stage reduces the sinusoidal noise from the input signal and the second stage reduces the wideband noise. Two input sources of voice are used; one for the normal speech and the other for the noise input, using separate microphones for both signals. The first signal is of the corrupted speech signal and the second signal is of only the noise containing both wideband and narrowband noise. In the first stage the narrowband noise is reduced by using the ALE technique. The second stage gets a signal with ideally only the wideband noise which is reduced using the NLMS technique. In both the stages the concerned algorithms are used to update the filter coefficients in such a way that the noise is cancelled out from the signal and a clean speech signal is heard at the output.DOI:http://dx.doi.org/10.11591/ijece.v2i3.246

Design of Slotted and Slotless AFPM Synchronous Generators and their Performance Comparison Analysis by using FEA Method Saint Saint Soe; Yan Aung Oo
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 4: August 2015
Publisher : Institute of Advanced Engineering and Science

Axial-flux permanent magnet machines are popular and widely used for many applications due to their attractive features such as light weight, low noise, high torque, robust and higher efficiency due to lack of field excitation. The main essence of this paper is to perform slotted and slotless axial-flux permanent magnet synchronous generator design based on theoretical sizing equations and then finite element analysis is reinforcement in order to get a more reliable and accuracy machine design. A comparative study of machine design and performances over the same rating but different configurations i.e., slotted and slotless are also discussed. And then, finite-element method (FEM) software was made for the slotted stator and slotless stator (AFPMSG) in order to compare their magnetic flux density and efficiency. The AFPMSG topology considered in this paper is a three-phase double-rotor single-stator topology with 16 pole-pairs, 2kW rated power and 188 rpm rated speed.

Design of an Interdigital Structure Planar Bandpass Filter for UWB Frequency S. M. A. Motakabber; M. N. Haidari
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

A new topology of miniaturized interdigital structuremicrostrip planar bandpass filter for Ultra-Wideband (UWB) frequency has been discussed in this paper. The proposed design and its simulation have been carried out by using an electromagnetic simulation software named CST microwave studio. The Taconic TLX-8 microwave substrate has been used in this research. The experimental result and analysis have been performed by using the microwave vector network analyzer. The experimental result showed that the -10dB bandwidth of the filter is 7.5GHz. The lower and upper corner frequencies of the filter have been achieved at 3.1GHz and 10.6GHz respectively. At the center frequency of 6.85GHz, the -1dB insertion loss and the -7dB return losshave been observed. The simulated and experimental results are well agreed with a compact size filter of 19×21×0.5mm3.

Lithium-Ion batteries modeling and state of charge estimation using Artificial Neural Network Younes Boujoudar; Hassan Elmoussaoui; Tijani Lamhamdi
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

In This paper, we propose an effective and online technique for modeling nd State of Charge (SoC) estimation of Lithium-Ion (Li-Ion) batteries using Feed Forward Neural Networks(FFNN) and Nonlinear Auto Regressive model with eXogenous input(NARX). The both Artificial Neural Network (ANN) are rained using the data collected from the batterycharging and discharging pro ess. The NARX network finds the needed battery model, where the input ariables are the battery terminal voltage, SoC at the previous sample, and the urrent, temperature at the present sample. The proposed method is imple mented on a Li-Ion battery cell to estimate online SoC. Simulation results show good estimation of theSoC.

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Home Page

OAI Link

Editorial Team

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Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

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Journal Mail Official ijece@iaesjournal.com

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

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Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA