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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 9,174 Documents
 698   699   700   701   702 
Improving WSNs execution using energy-efficient clustering algorithms with consumed energy and lifetime maximization Mohanad Sameer Jabbar; Samer Saeed Issa; Adnan Hussein Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp1122-1131

Abstract

Wireless sensor networks (WSNs) has a major designing feature representing by energy. Specifically, the sensor nodes have limited battery energy and are deployed remote from base station (BS); therefore, the actual enhancement dealing with energy turns into the Clustering routing protocols fundamentals which concerned in network lifetime improvement. Though, unexpected and energy insensible of the clusters head (CH) selection is not the best of WSN for greatly lowering lifetime network. A presentation article of an WSNs incoming routing approach using a mix of the fuzzy approach besides hybrid energy-efficient distributing (HEED) algorithm for increasing the lifetime and node’s energy. The FLH-P proposal algorithm is split into two parts. The stable election protocol HEED approach is used to arrange WSNs into clusters. Then, using a combination of fuzzy inference and the low energy adaptive clustering hierarchy (LEACH) algorithm, metrics like residual energy, minimal hops, with node traffic counts are taken into account. A comparison of FLH-P proposal algorithm with LEACH algorithm, fuzzy approach, and HEED utilizing identical guiding standards was used for demonstrating the performance of the suggested technique from where corresponding consumed energy as well as lifetime maximization. The suggested routing strategy considerably increases the network lifetime and transmitted packet throughput, according to simulation findings.
Securing data using deep hiding selected least significant bit and adaptive swarm algorithm Bashar Izzeddin Issa Aljidi; Sundresan Perumal; Sakinah Ali Pitchay
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1573-1581

Abstract

The emphasis on data protection is improved in particular with respect to the transmission protocols utilized. Different research on numerous data protection areas such as authentication, encryption, hiding of data and validation were performed. In addition, a cybersecurity standard, such as IP-SEC, and secure sockets layer (SSL), were introduced to solve privacy infringement problems by applying encryption, authorization and protection to data exchanged and data stored in the cloud. This study suggests a new steganography algorithm, a data protection tool used to conceal massive amounts of data from graphic and statistic attacks in color images. The proposed algorithm is a multi-level steganography modified deep hiding/extracting technique (MDHET), which implements a selected least signified bit (SLSB) for color picture dispersal of the information. In addition, an accurate pixel location randomization feature has been applied. After MDHET, the predicted results will effectively conceal data up to 6 bpp (bit per pixel) with high safety levels by improving the quality of images. In addition, MDHET can be useful for encoding a deep series of images into one in which the testing procedure is carried out using regular reference images used in color image processing and compression analysis from different institutions.
Advanced compensation scheme for enhancing photovoltaic power quality Mohammad Ehtesham; Md Junaid
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1223-1230

Abstract

With the photovoltaic (PV) system becoming highly popular in distribution network, there is also a growing concern regarding its adverse impacts over the power quality (PQ) of integrated system. This deterioration in PQ hassparked a new interest in the filtering techniques used in the power systemfor mitigating these problems. In contrast to conventional passive filters now active power filters (APFs) are being looked as the predominant solution.This paper presents a state-estimation based effective compensation strategy for enhancing performance of employed APF scheme. A novel control technique for PQ enhancement is proposed where Kalman filtering approach has been applied for generating the reference signals. Also, an adaptive hysteresis band technique has been applied here in the switching strategy. Thus an enhanced filter performance is achieved with reduced complexity and better elimination of distortions. Simulated results obtained in MATLAB/Simulink platform have been analyzed completely, where the superiority of filtering algorithm has been also demonstrated through leasttotal harmonic distortion (THD) achieved in source current among all the existing Kalman filters.
The effect of electrolyte parameter variation upon the performance of lithium iron phosphate (LiFePO4) Rahifa Ranom; Risna Syakinah Bacho; Saidatul Nur Aisyahtun Sakinah Ahmad Jamal
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp58-66

Abstract

This study focuses on the effect of electrolyte parameter variation upon the performance of lithium iron phosphate (LiFePO4) due to high demand of the electronic devices among consumers and industrial sectors that require efficicent LiFePO4 batteries. Hence, it is essential to improve its performance by optimizing the electrolyte parameter of the cell. The mathematical models of lithium-ion batteries based on the drift-diffusion model consists of the electrolyte and lithium transport equations in the electrode particles which incorporated the geometry of cell microstructure to the coefficients in the macroscopic model was solved numerically using the method of lines (MOL) technique. The effect of electrolyte parameter variation on the discharge curve of LiFePO4 using lithium hexa-fluoro-phosphate (LiPF6 ) as the base electrolyte is examined by varying the electrolyte parameters: initial concentration of lithium ions (c0), the effective diffusivity of lithium ions (D) and the effective ionic conductivity (????). The simulations show that higher diffusivity of lithium ions produces large discharge curve and higher ionic conductivity increase the mobility of the ion in the cell. Meanwhile, higher initial concentration of lithium ions produced high battery performance compared to lower initial concentration of lithium ion resulting more discharge time before electrolyte depletion occurs.
Generating himawari-8 time series data for meteorological application Ahmad Luthfi Hadiyanto; Ketut Wikantika; Ary Setijadi Prihatmanto; Nurjanna Joko Trilaksono; Dedi Irawadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp780-787

Abstract

Optical remote sensing images have been widely used for temporal monitoring. The data is acquired by sensors on satellites with better spatial resolution compared to in-situ measurements by meteorological stations. The problem with utilizing optical images is the cloud, which blocks the ground and near-ground information collected by satellites. To overcome this problem, especially when dealing with thermal bands, we propose a procedure including aggregation and spatial interpolation methods to obtain time series data over a region. There is still no reference to selecting the data period to calculate the aggregate value and apply spatial interpolation. An assessment is proposed by applying Yamane’s formula in the time domain and thresholding the number of pixels in the spatial domain. Himawari-8 data was utilized and collected on an hourly basis over Java Island. This algorithm is applied to a sequence of periodic datasets to obtain a time series of aggregate data for meteorological applications. The result of this study is a recommendation to use three-month periods of data over the eastern part of Java.
Improvement of conjugate gradient methods for removing impulse noise images Basim A. Hassan; Ali Ahmed A. Abdullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp245-251

Abstract

Optimization problems occur in most disciplines like engineering, physics, mathematics, economics, administration, commerce, social sciences, and even politics. The conjugate coefficient is the cornerstone of conjugate gradient algorithms with the desired conjugate property. In this study, we discovered fresh second order information for the Hessian from the target function, which might lead to a new search direction. Based on a unique search direction, we proposed the update formula and nonlinear conjugate gradient technique. Under Wolfe line search and moderate objective function assumptions, the strategy has acceptable descent property and is always globally convergent. According to numerical results, the technique is successful and competitive in recovering the original picture from an image corrupted by impulsive noise.
Classification of malware using multinomial linked latent modular double q learning Sheelavathy Veerabhadrappa Kudrekar; Udaya Rani Vinayakamurthy
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp577-586

Abstract

In recent times, malware has progressed by utilizing distinct advanced machine learning techniques for detection. However, the model becomes complicated and the singular value decomposition and depth-based malware detectors failed to detect the malware significantly with minimum time and overhead. This paper proposes a multinomial linked latent dirichlet and modular double q learning (MLLD-MDQL) to efficiently detect malware based on the network behavior patterns. First, multinomial linked latent dirichlet network behavior extraction (ML-LDNBE) is applied to the input network for anomaly detection that extracts the behavior based on the network pattern. The behavior is extracted which are grouped to perform on the path protocol for analyzing repeated behaviors. Finally, the modular double q learning malware classification model is the grouped behaviors for significant malware detection. The effectiveness of proposed MLLD-M DQL method is compared with existing models. The results obtained by the proposed method show that the model combined with the machine learning (ML) significantly determined malware detection time and also reduced the false positive rate (FPR). The results showed that the false positive rate is significantly reduced by 42% for the proposed method better when compared to the existing behavior based malware detection model that obtained 62% of FPR.
Study and innovation of effective classification of XML documents using an advanced deep learning approach Sahunthala Sanmugam; Angelina Geetha; Latha Parthiban
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1551-1559

Abstract

In the digital world, classifying real sensed data in huge volumes derived from numerical problems is a challenging task due to the computational complexity of the metaheuristic searching process. The deep learning approach includes convolutional neural network (CNN), long short-term memory (LSTM), and Bidirectional (BI)-LSTM, suitable for an optimistic processing time of analyzing XML datasets (i.e., social media, trade center, and surveillance data exchanged in the internet world). However, it faces process deviation when datasets extend their range beyond the expected volume. This paper proposes a novel deep learning formwork referred to as archimed improved numerical optimization deep learning (AINODL) to improve the classification of XML datasets. The proposed AINODL framework first extracts feature from XML documents using the vector space model. Secondly, it classifies the XML data using the inbuilt function of the AINODL framework. The experiments demonstrate that the performance parameters accuracy (90%), sensitivity (93%), and specificity (94%) of the proposed AINODL framework are significantly enhanced compared with the existing approaches CNN, LSTM, and BI-LSTM.
Priority-based market clearing model for off-grid P2P energy trading Wan Azlan Wan Zainal Abidin; Alan Ling Sieng Yew
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp24-37

Abstract

Standalone solar PV power system is being used as an option for electrification in remote areas around the world providing basic electricity needs. However, the approach suffers from power mismatch and energy efficiency issues. This paper proposes market-clearing model peer-to-peer energy trading (P2PET) based on multiple standalone solar power system design specification in rural Sarawak, Malaysia. The proposed system combined multiple standalone solar PV system within the community through P2PET trading concept. P2PET creates the platform for energy transaction between each system and even support business such as a workshop to operate high-power electrical appliances. As energy generation is constrained in an off-grid system, the proposed market-clearing model prioritizes the energy trading between the seller and business buyer who bring more benefit to the community. Subsequently, participants in energy trading have a selection of strategies to maximize personal benefits such as profit earning or energy sufficiency. Simulation studies are applied to verify the performance of the proposed model which increases energy efficiency, improves the local economy, and maximizes the community’s welfare from electrification.
An evaluation of automated measurement of slice sensitivity profile of computed tomography image: field of view variations Elvira Rizqi Widyanti; Choirul Anam; Eko Hidayanto; Ariij Naufal; Mohammad Haekal
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1430-1437

Abstract

This study aims to evaluate the automated measurement of slice sensitivity profile (SSP) on the American Association of Physicists in Medicine (AAPM) computed tomography (CT) performance phantom for variations of slice thickness and field of view (FOV). The AAPM CT performance phantom was scanned using a Philips MRC 880 CT Scanner for variations of slice thickness and FOV. The slice thickness values were 1, 3, and 5 mm. The FOV values were 240, 300, 340, 400, and 440 mm. The automated SSPs and their fullwidth at half maximums (FWHMs) were automatically measured from the middle stair object of the phantom. To validate the automated measurement results, the FWHM values of SSPs obtained were compared to those from manual measurements. The differences between FWHMs from automated measurements and set slice thicknesses are less than 0.3 mm, while the differences between FWHMs from automated and manual measurements are less than 0.2 mm. The results from automated measurements are closer to the set slice thickness than those from manual measurements. This automated SSP measurement provides high accuracy and precision for both the slice thickness and the FOV variations.

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