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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
 552   553   554   555   556 
The effect of automated swab robot: new technology drives new behavior Jonalyn Mae E. Aranda; Jasper Rae Zeus A. Antonio
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp99-107

Abstract

The world is now faced with a devastating pandemic outbreak coronavirus disease-2019 (COVID-19). The latest coronavirus infected almost all continents and witnessed sharp rises in cases diagnosed. The engineers tend to eliminate the matter and have solutions, one in every utilizing technical innovation. Researchers from Singapore, Taiwan, and Denmark have developed a fully automated robot that may take coronavirus swabs in order for health care professionals don’t seem to be exposed to the chance of infection. The objective of this study is to present the potential effects of robotics to help healthcare professionals on getting specimens and testing for COVID-19. These possible consequences include positive and negative outcomes and as a result, the overall impact on the profit or loss to society is far from obvious. The paper discusses two theoretical scenarios, distinguished fundamentally by the different behavioral responses of the automated swab robot and the selection of results in line with policy interventions.
Voltage instability identification with modified L-index using synchrophasor data V. Vijaya Rama Raju; K. H. Phani Shree; S. V. Jayarama Kumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1340-1349

Abstract

In the prevailing open-access environment, one of the limitations for power exchanges has been voltage stability. The study of voltage stability necessitates a complete network representation. In this paper, the advantage of the dynamic behavior of generators is considered by incorporating dynamic models for generators. It has been shown dynamic models resulted in more accurate results compared to the conventional PV buses or ideal voltage source models that are used in most of the voltage stability studies. Moreover, the traditional L-index is augmented by incorporating real-time and synchronized phasor data collected from the optimally located phasor measurement units (PMU) in a wide-area measurement system (WAMS) to estimate more accurate voltage stability margins. Simulation studies carried out on IEEE 9-bus and IEEE 14-bus systems under various system conditions. It has been demonstrated that the inclusion of dynamic models and synchrophasor data from WAMS significantly improves the precision with which voltage stability analysis results are obtained.
Evolutionary approach to secure mobile telecommunication networks Abdelkader Ghazli; Adda Alipacha; Naima Hadj Said
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp357-366

Abstract

A series of encryption algorithms called A5 is used to secure mobile telephone communications, producing a pseudo-random sequence that will be exclusive OR (XORed) with the data flowing in the air interface in order to secure them. These algorithms are essentially composed of shift registers with linear feedback, controlled generally by a function or with another register in order to favor the randomness character of the keystream generated. Evolutionary algorithms are bioinspired calculation methods, whose principle is inspired by the theory of evolution, which consists in evolving a set of solutions to a problem given in order to find better results. This paper presents an improvement of the A5/1 algorithm by an evolutionary approach based on the use of particle swarm optimization algorithm (PSO) in order to limit some weaknesses and drawbacks found in the conventional A5/1 version, which have been cryptanalysed and several attacks have been published such as time memory trade off attacks and guess and determine attacks. Our technique does not alter the A5/1's architecture, but it does help to improve its shifting system by an evolutionary approach, which guarantees the quality of the keystream generated and makes it more complex and more secure.
Static hand gesture recognition of Arabic sign language by using deep CNNs Mohammad H. Ismail; Shefa A. Dawwd; Fakhradeen H. Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp178-188

Abstract

An Arabic sign language recognition using two concatenated deep convolution neural network models DenseNet121 & VGG16 is presented. The pre-trained models are fed with images, and then the system can automatically recognize the Arabic sign language. To evaluate the performance of concatenated two models in the Arabic sign language recognition, the red-green-blue (RGB) images for various static signs are collected in a dataset. The dataset comprises 220,000 images for 44 categories: 32 letters, 11 numbers (0:10), and 1 for none. For each of the static signs, there are 5000 images collected from different volunteers. The pre-trained models were used and trained on prepared Arabic sign language data. These models were used after some modification. Also, an attempt has been made to adopt two models from the previously trained models, where they are trained in parallel deep feature extractions. Then they are combined and prepared for the classification stage. The results demonstrate the comparison between the performance of the single model and multi-model. It appears that most of the multi-model is better in feature extraction and classification than the single models. And also show that when depending on the total number of incorrect recognize sign image in training, validation and testing dataset, the best convolutional neural networks (CNN) model in feature extraction and classification Arabic sign language is the DenseNet121 for a single model using and DenseNet121 & VGG16 for multi-model using.
Improved fingerprinting performance in indoor positioning by reducing duration of the training phase process Andika Muharam; Abdi Wahab; Mudrik Alaydrus
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp236-244

Abstract

Wireless sensor network (WSN) can be used as a solution to find out the position of an object that cannot be reached by global positioning system (GPS), for example to find out the position of objects in a room known as Indoor Positioning. One method in indoor positioning that can be used is fingerprinting. Inside there are two main work phases, namely training and positioning. The training phase is the process of collecting received signal strength indication (RSSI) data levels from each sensor Node reference that will be used as a reference value for the positioning phase. The more sensor Nodes used, the longer the processing time needed in the training phase. This research focussed on the duration of the training phase, the implementation of which are used 4 sensor Nodes, namely Zigbee (IEEE 802.15.4 protocol) arranged according to mesh network topology, one as Node X (positioning target) and 3 as reference Nodes. There are two methods used in the training phase, namely fixed target parameter (FTP) and moving target parameter (MTP). MTP took 5 seconds faster than FTP in terms of the duration of RSSI data collection from each reference Node. 
Integrated data aggregation with fault-tolerance and lifetime energy-aware adaptive routing in coffee plantations using WSNs Roshan Zameer Ahmed; Sravani K.; Shilpa S. Chaudhari; S. Sethu Selvi; S. L. Gangadharaiah
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp376-385

Abstract

The pest namely coffee white stem borer (CWSB) has harmed the economic progress of many emerging countries as a result of arabica coffee’s agricultural products. The boring activity causes the stem to shrink, fade in color, and acquire translucent margins across the stem. The pest multiplier can be controlled by capturing the location with the utilization of a wireless sensor networks (WSNs) and blocking its exit point at the user end. In this work, we propose an integrated data aggregation with faulttolerance and lifetime energy-aware adaptive routing (IDALAR) approach to transfer the sensed pest location data. The efficient packet format and statistical models based routing between clusterheads (CHs) and base station (BS) is proposed considering the availability of resources such as message overhead, algorithmic complexity, residual energy, and control overhead are all used to calculate its performance.
NB-IoT and LTE-M towards massive MTC: Complete performance evaluation for 5G mMTC Adil Abou El Hassan; Abdelmalek El Mehdi; Mohammed Saber
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp308-320

Abstract

Since the emerging 5G wireless network is expected to significantly revolutionize thefield of communication, its standardization and design should regard the internet ofthings (IoT) among the main orientations. Also, emerging IoT applications introducenew requirements other than throughput to support massive machine-type commu-nication (mMTC) where small data packets are occasionally sent. Therefore, moreimportance is attached to coverage, latency, power consumption, and connection den-sity. For this purpose, the third generation partnership project (3GPP) has introducedtwo novel cellular IoT technologies supporting mMTC, known as NB-IoT and LTE-M. This paper aims to determine the system configuration and deployment required forNB-IoT and LTE-M technologies to fully meet the 5G mMTC requirements in termsof coverage, throughput, latency, battery life, and connection density. An overview ofthese technologies and their design principles is also described. A complete evalua-tion of NB-IoT and LTE-M performance against 5G mMTC requirements is presented,and it is shown that these requirements can be met but only under certain conditionsregarding system configuration and deployment. This is followed by a performancecomparative analysis, which is mainly conducted to determine the limits and suitableuse cases of each technology.
Optimized machine learning algorithm for intrusion detection Royida A. Ibrahem Alhayali; Mohammad Aljanabi; Ahmed Hussein Ali; Mostafa Abdulghfoor Mohammed; Tole Sutikno
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp590-599

Abstract

Intrusion detection is mainly achieved by using optimization algorithms. The need for optimization algorithms for intrusion detection is necessitated by the increasing number of features in audit data, as well as the performance failure of the human-based smart intrusion detection system (IDS) in terms of their prolonged training time and classification accuracy. This article presents an improved intrusion detection technique for binary classification. The proposal is a combination of different optimizers, including Rao optimization algorithm, extreme learning machine (ELM), support vector machine (SVM), and logistic regression (LR) (for feature selection & weighting), as well as a hybrid Rao-SVM algorithm with supervised machine learning (ML) techniques for feature subset selection (FSS). The process of selecting the least number of features without sacrificing the FSS accuracy was considered a multi-objective optimization problem. The algorithm-specific, parameter-less concept of the proposed Rao-SVM was also explored in this study. The KDDCup 99 and CICIDS 2017 were used as the intrusion dataset for the experiments, where significant improvements were noted with the new Rao-SVM compared to the other algorithms. Rao-SVM presented better results than many existing works by reaching 100% accuracy for KDDCup 99 dataset and 97% for CICIDS dataset.
An investigation of inertia constant in single generator on transient analysis for an isolated electrical network system M. Saifuzam Jamri; Muhammad Nizam Kamarudin; Mohd Luqma Mohd Jamil
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1299-1305

Abstract

An isolated electrical network which fed by an independent generator for a low voltage system is considerable in remote and islandic areas. Although the network system has less complexity in term of system structure, its stability level is crucial due to frequency dynamical responses. An influence of initial stability margin on frequency stability study during contingency situation is a thing rather than being ignored. Here the initial transient response inherently delivers important info such as system inertia and momentarily power deficit. In this paper, an investigation of transient stability responses under different inertia values is carried out. The investigation is carried out by modelling the isolated system in MATLAB/Simulink environment which consists of state-space mathematical equations. It is confirmed that the generator system inertia shapes the initial slope, speed droop and oscillation. For a verification purpose, the influence of system inertia is also analyzed using bode diagram in which system gain and frequency margin are evaluated. 
Electro mechanical properties changes of LDPE doped with industrial type MgO for cable insulation purposes Sherif Haggag; Loai Nasrat; Hanafy Ismail
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1315-1323

Abstract

This manuscript introduces the changes of a comprehensive electromechanical properties bundle for low density polyethylene compounded to microscale magnesia (LDPE/MgO) to obtain electrical cables insulating material. Composites of various filler loading weight ratios were prepared by melt intercalation technique; multiple samples were produced in sets as they were cut with definite dimensions as per recommendations of the related testing standard then electrically and mechanically examined following the instruction dictated by the code while preserving typical test condition for all sets. Dielectric strength, volume resistivity, capacitance, and loss angle were the tests of the electrical test pack, while elongation, tensile strength, and melt flow rate were the mechanical and rheological tests applied. Test’s findings were compared to each other’s and to the base material to identify the differentiation. Electrical test results show improvements in the composite features at low loading percentages, whereas the mechanical tests revealed a deterioration in the mechanical properties along with all ratios under investigation. The research aims to determine the compositing benefit extents and drawbacks when a conventional compounding method and inexpensive filler are used, incurring marginal cost impact.

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