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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 67 Documents
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Search results for , issue "Vol 21, No 2: February 2021" : 67 Documents clear
Predicting RNA-seq data using genetic algorithm and ensemble classification algorithms Micheal Olaolu Arowolo; Marion O. Adebiyi; Ayodele A. Adebiyi; Olatunji J. Okesola
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1073-1081

Abstract

Malaria parasites accept uncertain, inconsistent life span breeding through vectors of mosquitoes stratospheres. Thousands of different transcriptome parasites exist. A prevalent ribonucleic acid sequencing (RNA-seq) technique for gene expression has brought about enhanced identifications of genetical queries. Computation of RNA-seq gene expression data transcripts requires enhancements using analytical machine learning procedures. Numerous learning approaches have been adopted for analyzing and enhancing the performance of biological data and machines. In this study, a genetic algorithm dimensionality reduction technique is proposed to fetch relevant information from a huge dimensional RNA-seq dataset, and classification uses Ensemble classification algorithms. The experiment is performed using a mosquito Anopheles gambiae dataset with a classification accuracy of 81.7% and 88.3%.
Reduction of common mode voltage for cascaded multilevel inverters using phase shift keying technique Vinh-Quan Nguyen; QuangTho Tran
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp691-706

Abstract

Demand of cascaded multilevel inverters in industries of electric drives and renewable energy is increasing due to their large-scale capacity and high voltage. The modulation technique of inverters significantly affects the power quality of the inverter output voltage. This paper proposes a new method of carrier wave modulation using the phase shift keying technique for cascaded multilevel inverters. The phase of a constant frequency carrier wave is changed at an accurate time by an input sinusoidal control signal. This modulation technique is simply implemented and only needs a small memory. It also helps reduce the common mode voltage of inverters in order to suppress the output voltage harmonics. Moreover, the ability to reduce switching count also helps the inverters decrease switching loss. The simulated and experienced results on a cascaded 9-level 3-phase inverter and an F28379D DSP kit have validated the performance of the proposed technique compared with that of the APOD and POD methods.
Network loss reduction and voltage improvement by optimal placement and sizing of distributed generators with active and reactive power injection using fine-tuned PSO Eshan Karunarathne; Jagadeesh Pasupuleti; Janaka Ekanayake; Dilini Almeida
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp647-656

Abstract

Minimization of real power loss and improvement of voltage authenticity of the network are amongst the key issues confronting power systems owing to the heavy demand development problem, contingency of transmission and distribution lines and the financial costs. The distributed generators (DG) has become one of the strongest mitigating strategies for the network power loss and to optimize voltage reliability over integration of capacitor banks and network reconfiguration. This paper introduces an approach for the optimizing the  placement and sizes of different types of DGs in radial distribution systems using a fine-tuned particle swarm optimization (PSO). The suggested approach is evaluated on IEEE 33, IEEE 69 and a real network in Malaysian Context. Simulation results demonstrate the productiveness of active and reactive power injection into the electric power system and the comparison depicts that the suggested fine-tuned PSO methodology could accomplish a significant reduction in network power loss than the other research works.
High speed pulse generators with electro-optic modulators based on different bit sequence for the digital fiber optic communication links Mahmoud M. A. Eid; Ashraf S. Seliem; Ahmed Nabih Zaki Rashed; Abd El-Naser A. Mohammed; Mohamed Yassin Ali; Shaimaa S. Abaza
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp957-967

Abstract

The paper outlines the simulation of various pulse generators for the enhancement of optical fiber access transmission networks within flow rate of 10 Gbps and transmission range of 100 km. The pulse generators are gaussian, hyperbolic secant, triangle, sine, raised cosine in the transmission stage. Proposed pulse generators are mixed with both electro-absorption modulator (EAM) and mach-zehnder modulator (MZM) for efficient transmission. We have compared the max.  the quality factor with using proposed pulse generators against nonreturn to zero (NRZ) return to zero (RZ) pulse generators in the previous research works for different bit sequences. The signal power amplitude is tested for both optical fiber and PIN photodetector optical time-domain visualizer and RF spectrum analyzer by using in the optimum cases for different bit sequence. It is observed that proposed pulse generators/EAM have presented an efficient increase in Q-factor value compared with proposed pulse generators/MZM for different bit sequences.
Reducing image search time by improved BOVW with wavelet decomposition Mohammed El Amin Kourtiche; Mohammed Beladgham; Abdelmalik Taleb-Ahmed
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1201-1208

Abstract

In the last decade, the bag of visual words (BOVW) has been used widely in image classification, image retrieval and has significantly improved the performance of CBIR system. In this paper we propose a new method to enhance BOVW using features obtained from wavelet decomposition in order to reduce computational costs in vocabulary construction and training time. We apply several level of wavelet decompositions and evaluate their impact on accuracy of the BOVW. We apply our method on MURA-v1.1 dataset and the experiments results confirm the performance of our approach.
Solving combined economic emission dispatch problem in wind integrated power systems Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp635-641

Abstract

A meta-heuristic based optimization method for solving combined economic emission dispatch (CEED) problem for the power system with thermal and wind energy generating units is proposed in this paper. Wind energy is environmentally friendly and abundantly available, but the intermittency and variability of wind power affects the system operation. Therefore, the system operator (SO) must aware of wind forecast uncertainty and dispatch the wind power accordingly. Here, the CEED problem is solved by including the nonlinear characteristics of thermal generators, and the stochastic behavior of wind generators. The stochastic nature of wind generators is handled by using probability distribution analysis. The purpose of this CEED problem is to optimize fuel cost and emission levels simultaneously. The proposed problem is changed into a single objective optimization problem by using weighted sum approach. The proposed problem is solved by using particle swarm optimization (PSO) algorithm. The feasibility of proposed methodology is demonstrated on six generator power system, and the obtained results using the PSO approach are compared with results obtained from genetic algorithm (GA) and enhanced genetic algorithms (EGA).
Dynamic state estimation of multi-machine power system with UPFC using EKF algorithm Meera R Karamta; Jitendra G Jamnani
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp642-646

Abstract

Estimation of dynamic state variables in a multi-machine power system connected with UPFC is presented in this paper, using Extended Kalman filter (EKF) algorithm. A two-generator test case is used to estimate the generator rotor angle and rotor speed. The DC link voltage of the UPFC is the additional state variable to be estimated. Dynamic mathematical modeling of the multi-machine system with UPFC is explained in this work. DSE is done under transient condition of three-phase fault.
Performance evaluation of PV penetration at different locations in a LV distribution network connected with an off-load tap changing transformer Dilini Almeida; Jagadeesh Pasupuleti; Janaka Ekanayake
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp987-993

Abstract

Solar photovoltaic (PV) power generation has shown a worldwide remarkable growth in recent years. In order to achieve the increasing energy demand, a large number of residential PV units are connected to the low voltage (LV) distribution networks. However, high integration of solar PV could cause negative impacts on distribution grids leading to violations of limits and standards. The voltage rise has been recognized as one of the major implications of increased PV integration, which could significantly restrict the capacity of the distribution network to support higher PV penetration levels. This study addresses the performance of the off-load tap changing transformer under high solar PV penetration and a detailed analysis has been carried out to examine the maximum allowable PV penetration at discrete tap positions of the transformer. The maximum PV penetration has been determined by ensuring that all nodal voltages adhere to grid voltage statutory limits. The simulation results demonstrate that the first two tap positions could be adopted to control the grid voltage under higher PV penetrations thus facilitating further PV influx into the existing network.
Hybrid algorithm for two-terminal reliability evaluation in communication networks Musaria Karim Mahmood; Osman Ucan; Zahraa Zaidan; Sulaiman M. Karim
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1185-1192

Abstract

Network reliability is valuable in establishing a survivable communication network. Reliability evaluation algorithms are used in the design stage and during the network deployment. This work presents a new multistage hybrid technique for two-terminal reliability evaluation problem. It is based on a combination of graph reduction techniques and tie-set method. A new approach has been introduced for deducing tie-sets in a network containing both unidirectional and bi-directional edges. The proposed algorithm can be applied for both simple and complex networks without restrictions. The results confirm that new algorithm evaluates network's reliability with decreasing computing time compared to classical algorithms. The results for a case study of a 20-node network have demonstrated that the required time for reliability evaluation is decreased from (t>1 hour) in the case of using a classical algorithm, to (t<1 second) for the new algorithm.
Quality and energy optimized scheduling technique for executing scientific workload in cloud computing environment Nagendra Prasad S; Subash Kulkarni S
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1039-1047

Abstract

Modern BigData data-intensive and scientific workload execution is challenging. The major issues are reliable processing, performance efficiency and energy efficacy perquisite of BigData processing framework. This work assume self-aware MC architectures that autonomously adjust or optimize their performance to accommodate users quality of service (QoS) performance requirement, job execution performance, energy efficiency, and resource accessibility. Extensive workload scheduling has been presented to minimize energy consumption in cloud computing (CC) environment. However, the existing workload scheduling model induces higher amount of interaction cost between inter-processors communications. Further, due to poor resource utilization, routing inefficiency these existing model induces higher energy cost and fails to meet workload QoS prerequisite. For overcoming research challenges, this paper presented quality and energy optimized scheduling (QEOS) technique for executing data-intensive workload by employing dynamic voltage and frequency scaling (DVFS) technique. Experiment outcome shows QEOS model attains good trade-off between system performance and energy consumption in multi-core cloud computing (CC) architectures when compared with existing model.

Page 4 of 7 | Total Record : 67

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