Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the engineering of Telecommunication and Information Technology, Applied Computing & Computer, Instrumentation & Control, Electrical (Power), Electronics, and Informatics.
Articles
783 Documents
Persian Text Classification using naive Bayes algorithms and Support Vector Machine algorithm
Naeim Rezaeian;
Galina Novikova
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020
Publisher : IAES Indonesian Section
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DOI: 10.52549/ijeei.v8i1.1696
One of the several benefits of text classification is to automatically assign document in predefined category is one of the primary steps toward knowledge extraction from the raw textual data. In such tasks, words are dealt with as a set of features. Due to high dimensionality and sparseness of feature vector results from traditional feature selection methods, most of the proposed text classification methods for this purpose lack performance and accuracy. Many algorithms have been implemented to the problem of Automatic Text Categorization that’s why, we tried to use new methods like Information Extraction, Natural Language Processing, and Machine Learning. This paper proposes an innovative approach to improve the classification performance of the Persian text. Naive Bayes classifiers which are widely used for text classification in machine learning are based on the conditional probability. we have compared the Gaussian, Multinomial and Bernoulli methods of naive Bayes algorithms with SVM algorithm. for statistical text representation, TF and TF-IDF and character-level 3 (3-Gram) [6,9] were used. Finally, experimental results on 10 newsgroups.
A Comprehensive Insight into Game Theory in relevance to Cyber Security
Farhat Anwar;
Burhan UI Islam Khan;
Rashidah F. Olanrewaju;
Bisma Rasool Pampori;
Roohie Naaz Mir
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020
Publisher : IAES Indonesian Section
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DOI: 10.52549/ijeei.v8i1.1810
The progressively ubiquitous connectivity in the present information systems pose newer challenges tosecurity. The conventional security mechanisms have come a long way in securing the well-definedobjectives of confidentiality, integrity, authenticity and availability. Nevertheless, with the growth in thesystem complexities and attack sophistication, providing security via traditional means can beunaffordable. A novel theoretical perspective and an innovative approach are thus required forunderstanding security from decision-making and strategic viewpoint. One of the analytical tools whichmay assist the researchers in designing security protocols for computer networks is game theory. Thegame-theoretic concept finds extensive applications in security at different levels, including thecyberspace and is generally categorized under security games. It can be utilized as a robust mathematicaltool for modelling and analyzing contemporary security issues. Game theory offers a natural frameworkfor capturing the defensive as well as adversarial interactions between the defenders and the attackers.Furthermore, defenders can attain a deep understanding of the potential attack threats and the strategiesof attackers by equilibrium evaluation of the security games. In this paper, the concept of game theoryhas been presented, followed by game-theoretic applications in cybersecurity including cryptography.Different types of games, particularly those focused on securing the cyberspace, have been analysed andvaried game-theoretic methodologies including mechanism design theories have been outlined foroffering a modern foundation of the science of cybersecurity.
Frequency Control of Microgrid with Renewable Generation using PID Controller based Krill Herd
Mohamed Regad;
M'hamed Helaimi;
Rachid Taleb;
Ahmed M. Othman;
Hossam A.Gabbar
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020
Publisher : IAES Indonesian Section
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DOI: 10.52549/ijeei.v8i1.1291
The main of this paper is to provide optimal control of a state microgrid system. The proposed configuration composes of renewable generation systems such as solar photovoltaic system and wind turbine generator with a Diesel Engine Generator and Fuel-Cell. An Aqua electrolyzer and other energy storage systems such as battery and flywheel are also used in the proposed microgrid. A standard PID (Proportional Integral Derivative) controller scheme is introduced whose its parameters are determined using different optimizations algorithm such as Algorithm Genetic, Particle Swarm Optimization, and Krill Herd algorithm for minimizing frequency and power deviations, in order to enhance the operation of this system. The PID controller gains are optimized by resolving an objective function. The simulation results are shown, and given that the Krill Herd algorithm improves the performance of the system in comparison with GA and PSO based on PID. The efficiency of the system is improved.
Adaptive Parameter Control Strategy for Ant-Miner Classification Algorithm
Hayder Naser Khraibet Al-Behadili;
Rafid Sagban;
Ku Ruhana Ku-Mahamud
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020
Publisher : IAES Indonesian Section
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DOI: 10.52549/ijeei.v8i1.1423
Pruning is the popular framework for preventing the dilemma of overfitting noisy data. This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-AntMiner. A key aspect of this algorithm is the selection of an appropriate number of terms to be included in the classification rule. ACS-AntMiner introduces a new parameter called importance rate (IR) which is a pre-pruning criterion based on the probability (heuristic and pheromone) amount. This criterion is responsible for adding only the important terms to each rule, thus discarding noisy data. The ACS algorithm is designed to optimize the IR parameter during the learning process of the Ant-Miner algorithm. The performance of the proposed classifier is compared with related ant-mining classifiers, namely, Ant-Miner, CAnt-Miner, TACO-Miner, and Ant-Miner with a hybrid pruner across several datasets. Experimental results show that the proposed classifier significantly outperforms the other ant-mining classifiers.
Genetic Algorithm-Based Approach for Minimising Losses in Substrate-Integrated Waveguide
Nur Hidayah Mansor;
Razi Abdul-Rahman
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020
Publisher : IAES Indonesian Section
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DOI: 10.52549/ijeei.v8i1.1532
The transitions in air-filled substrate-integrated waveguide (SIW) are studied here for millimetre-wave applications. A good design of an air-filled SIW (AFSIW) must allow for minimum losses in its interconnects between the air-filled and dielectric-filled regions of the SIW. This paper assesses the influence of the geometry of transition taper in an AFSIW on the return and insertion losses using full-wave analysis of a complete AFSIW structure. The data from the return and transmission losses provide a basis in the optimisation of the design of the transition tapers. The optimisation approach uses the multi-objective genetic algorithm (GA) with full-wave analysis to find an optimum profile of the transition. Defining the profile of the transition taper with a clamped cubic spline as a phenotype, the developed procedure shows that further losses are possible within the prescribed frequency bands. Furthermore, the length of the transition taper can be significantly reduced while maintaining an optimal quality of signal transmission in the transition. The simulation results show the efficacy of the proposed strategy where the optimal taper geometry is shown to provide a wider band of operating frequencies with lower return loss compared to a more established taper geometry.
Noise Cancellation Employing Adaptive Digital Filters for Mobile Applications
AM Prasanna Kumar;
SM Vijaya
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020
Publisher : IAES Indonesian Section
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DOI: 10.52549/ijeei.v8i1.1155
The persistent improvement of the hybrid adaptive algorithms and the swift growth of signal processing chip enhanced the performance of signal processing technique exalted mobile telecommunication systems. The proposed Artificial Neural Network Hybrid Back Propagation Adaptive Algorithm (ANNHBPAA) for mobile applications exploits relationship among the pure speech signal and noise corrupted signal in order to estimate of the noise. An adaptive linear system responds for changes in its environment as it is operating. Linear networks are gets adjusted at each time step based on new input and target vectors can find weights and biases that minimize the networks sum squared error for recent input and target vectors. Networks of this kind are quite oftenly used for error cancellation, speech signal processing and control systems. Noise in an audio signal has become major problem and hence mobile communication systems are demanding noise-free signal. In order to achieve noise-free signal various research communities have provided significant techniques. Adaptive noise cancellation (ANC) is a kind of technique which helps in estimation of un-wanted signal and removes them from corrupted signal. This paper introduces an Adaptive Filter Based Noise Cancellation System (AFNCS) that incorporates a hybrid back propagation learning for the adaptive noise cancellation in mobile applications. An extensive study has been made to explore the effects of different parameters, such as number of samples, number of filter coefficients, step size and noise level at the input on the performance of the adaptive noise cancelling system. The proposed hybrid algorithm consists all the significant features of Gradient Adaptive Lattice (GAL) and Least Mean Square (LMS) algorithms. The performance analysis of the method is performed by considering convergence complexity and bit error rate (BER) parameters along with performance analyzed with varying some parameters such as number of filter coefficients, step size, number of samples and input noise level. The outcomes suggest the errors are reduced significantly when the numbers of epochs are increased. Also incorporation of less hidden layers resulted in negligible computational delay along with effective utilization of memory. All the results have been obtained using computer simulations built on MATLAB platform
Improvement of alzheimer disease diagnosis accuracy using ensemble methods
Mohammed Abdullah Al-Hagery;
Ebtehal Ibrahim Al-Fairouz;
Norah Ahmed Al-Humaidan
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020
Publisher : IAES Indonesian Section
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DOI: 10.52549/ijeei.v8i1.1321
Nowadays, there is a significant increase in the medical data that we should take advantage of that. The application of the machine learning via the data mining processes, such as data classification depends on using a single classification algorithm or those complained as ensemble models. The objective of this work is to improve the classification accuracy of previous results for Alzheimer disease diagnosing. The Decision Tree algorithm with three types of ensemble methods combined, which are Boosting, Bagging and Stacking. The clinical dataset from the Open Access Series of Imaging Studies (OASIS) was used in the experiments. The experimental results of the proposed approach were better than the previous work results. Where the Random Forest (Bagging) achieved the highest accuracy among all algorithms with 90.69%, while the lowest one was Stacking with 79.07%. All these results generated in this paper are higher in accuracy than that done before.
Performance realization of Bridge Model using Ethernet-MAC for NoC based system with FPGA Prototyping
SP Guruprasad;
BS Chandrasekar
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020
Publisher : IAES Indonesian Section
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DOI: 10.52549/ijeei.v8i1.1216
The System on Chip (SoC) integrates the number of processing elements (PE) with different application requirements on a single chip. The SoC uses bus-based interconnection with shared memory access. However, buses are not scalable and limited to particular interface protocol. To overcome these problems, The Network on Chip (NoC) is an emerging interconnect solution with a scalable and reliable solution over SoC. The bridge model is essential to communicate the NoC based system on SoC. In this article, a cost-effective and efficient bridge model with ethernet-MAC is designed and also the placement of the bride with NoC based system is prototyped on Artix-7 FPGA. The Bridge model mainly contains FIFO modules, Serializer and de-serializer, priority-based arbiter with credit counter, packet framer and packet parser with Ethernet-MAC transceiver Module. The bridge with a single router and different sizes of the NoC based systems with mesh topology are designed using adaptive-XY routing. The performance metrics are evaluated for bridge with NoC in terms of average latency and maximum throughput for different Packet Injection Rate (PIR).
Real-time Implementation of Space Vector Modulation using Arduino as a Low-cost Microcontroller for Three-phase Grid-connected Inverter
Amal Satif;
Laamari Hlou;
Abdelkarim Zemmouri;
Hamad Dahou;
Rachid Elgouri
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020
Publisher : IAES Indonesian Section
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DOI: 10.52549/ijeei.v8i1.1207
This work aims to facilitate the approach of a promising and fascinating technology, which is the photovoltaic (PV) energy, concerning the integration of PV systems to the utility grid from the control/synchronization point of view. Within this context, this paper gives a performance analysis of modeling and driving a two-level three-phase grid-connected PV system, in order to reduce the variations in frequency and phase, as a result, the synchronization between the inverter and the utility grid is accomplished and the correct function of the inverter is performed. MATLAB/Simulink software was utilized to develop the model of the suggested control algorithms. Then, as an interfacing device between the software and the inverter, the Arduino UNO microcontroller is proposed as a low-cost and simplified method to control the three-phase grid-connected inverter
Sensorless Predictive Direct Power Control PDPC_SVM For PWM Converter Under Different Input Voltage Conditions
Ismail Boukhechem;
Ahcen Boukadoum;
Lahcene Boukelkoul;
Houssam Eddine Medouce
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 1: March 2020
Publisher : IAES Indonesian Section
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DOI: 10.52549/ijeei.v8i1.1542
In this paper, a new virtual flux (VF) based predictive direct power control (VF_PDPC) applied for three-phase pulse width modulation (PWM) rectifier is proposed. The virtual flux estimation is performed using a pure integrator in series with a new adaptive algorithm in order to cancel dc offset and harmonic distortions in the estimated VF. The introduced structure is able to produce two virtual flux positive sequence components orthogonal output signals under unbalanced and distorted voltage conditions. The main features of the proposed virtual flux estimator are, it's simple structure, accuracy, and fast VF estimation over the excited integrators. Therefore, the estimated VF is then used for robust sensorless VF-PDPC with a constant switching frequency using space vector modulation (SVM) and tested through numerical simulations. The instantaneous active and reactive powers provided by orthogonal (VF) positive sequence components are directly controlled. More importantly, this configuration gives quasi-sinusoidal and balanced current under different input voltage conditions without using the power compensation methods. The results of the simulation confirmed the validity of the proposed virtual flux algorithm and demonstrated excellent performance under different input voltage conditions, complete rejection of disturbances.