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Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 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. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 64 Documents
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Search results for , issue "Vol 11, No 5: October 2022" : 64 Documents clear
Measurement and analysis of conductor surface temperature in dependence of current variation Ali Hlal Mutlaq; Mahmood Ali Ahmed; Diadeen Ali Hameed; Ghanim Thiab Hasan
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3915

Abstract

The reliability and service life of power cables is closely related to the cable ampacity and temperature rise in the power cable. In a conductor carries AC current, complex processes may appear, which directly affect the temperature of the conductor surface. So, to keep a conductor in a good state, it is necessary to maintain the conductor temperature in a acceptable value. In this paper, a procedure for measuring the temperature of conductor surface and the corresponding numerical processing of measurement results has been presented. The measurement of the temperature probe characteristics and the temperature measurement on the surface of the conductor, both required the use of certain numerical methods, such as interpolation and fitting of the measured values in time diagrams. The procedure was applied to three copper conductors with different cross section area and one aluminum conductor and the final results are presented graphically, in the form of time diagrams.
Neural network based seizure detection system using statistical package analysis Priyanka Rajendran; Kirupa Ganapathy
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3771

Abstract

Due to the unpredictable interruptions within the functions of the human brain, disturbance occurs and it affects the behavior of the human and is equally laid low with the frequent occurrence termed as seizures. Therefore, the proposed system detects the seizure using machine learning algorithms. The electroencephalogram (EEG) contains information of the brain to detect the seizure. The objective is to evaluate the performance of machine learning classifiers K-nearest neighbors (KNN), artificial neural network (ANN), support vector machine (SVM) and principal component analysis (PCA) by comparing the accuracy of the classifier. This work uses total of 11,500 EEG samples from the UCI machine learning repository. The seizure detection was done in two ways. First method, features extracted from the EEG signal and classification techniques are done to classify the seizure. The second method uses the principal component analysis algorithm to improve the significant selections of features from the dataset. The outcomes are analyzed using the statistical package for the social science (SPSS) tools. ANN with extracted functions achieved 96% of accuracy and significant efficiency of (p less than 0.05) in comparison with different machine learning classifiers. It would be prudent to conclude that the ANN demonstrated the best accuracy, sensitivity, and specificity.
A methodology for transforming BPMN to IFML into MDA Abir Sajji; Yassine Rhazali; Youssef Hadi
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3973

Abstract

Responding to rising information system complexity and the high expense of technological migration, model driven architecture (MDA) was created. As a result, the OMG advocates raising the abstraction level to overcome technological limitations. MDA seeks to describe the functional and performance requirements of an application on a platform independently. Using the MDA approach, the business process model and notation (BPMN), and interaction flow modeling language (IFML) standards, we represent a methodology that allows transforming semi-automatically from the computation independent model (CIM) level to the platform independent model (PIM) level; to achieve this a collection of unique rules for transforming in a semi-automatic manner from CIM to PIM were developed. At the CIM level, we create models of business process using the notation standard BPMN, and IFML is used to adapt PIM models with web-oriented graphical user interfaces (GUI). To properly demonstrate the transformation procedure from CIM to PIM models a case study of the order management process was presented.
Nutrition information estimation from food photos using machine learning based on multiple datasets Mustafa Al-Saffar; Wadhah R. Baiee
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.4007

Abstract

Bodyweight, blood pressure, and cholesterol are all risk variables that can aid people in making educated decisions regarding their health promotion activities. Food choices are among the most effective methods for preventing chronic illnesses, including heart disease, diabetes, stroke, and some malignancies. Because various meals give varying amounts of energy and minerals, good eating necessitates keeping track of the nutrients we ingest. Furthermore, there is a paucity of information on whether understanding food constituents might aid in more accurate nutrition calculations. Therefore, this research suggests processing food images on social media to anticipate the contents of each food and extracting nutrition information for each food image to serve as healthy implicit feedback to take advantage of the rapid accumulation of rich photos on social media. The proposed methodology is a framework based on a machine-learning model for predicting food ingredients. We also compute critical health metrics for each ingredient and combine them to obtain nutrition data for the food. The result revealed a promising way of extracting food components and nutrition information. Compared with other researchs, our proposed prediction and attribute extraction strategy achieves a remarkable accuracy of 85%.
Integrating security and privacy in mmWave communications Ghadah M. Faisal; Hasanain Abdalridha Abed Alshadoodee; Haider Hadi Abbas; Hassan Muwafaq Gheni; Israa Al-Barazanchi
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.4314

Abstract

The aim of this paper is to integrate security and privacy in mmWave communications. MmWave communication mechanism access three major key components of secure communication (SC) operations. proposed design for mmWave communication facilitates the detection of the primary signal in physical (PHY) layer to find the spectrum throughput for primary user (PU) and secondary user (SU). The throughput of SC for PU with maximum throughput being recorded at 0.7934 while maximum throughput for SU is recorded at 0.7679. So, we will design a mmWave communication mechanism for solving this problem. The probability for sensing where the probability of detection (PD) is predicted at a defined range of 690 km with an estimated accuracy of 83.56% while the probability of false alarm (PFA) is predicted at a defined range of 230 km with an estimated accuracy of 81.39%. This conflicting but interrelated issue is investigated over three stages for the purpose of solving with a cross-layer model with MAC and PHY layers for a secure communication network (SCN) while reducing the collision effect concurrently with a 92.76% for both cross-layers. MATLAB 2019b would be forwarded in use as the increasing demand for augmenting the bandwidth in secure communications has actuated the evolutionary technology.
Radiation effect of M-slot patch antenna for wireless application Yousif Allbadi; Huda Ibrahim Hamd; Ilham H. Qaddoori
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3801

Abstract

Today, the specific absorption rate has become an important and necessary measurement when designing and implementing any type of antenna. In recent years, various devices have appeared that use different frequencies for wireless communication systems, which are a source of electromagnetic radiation. The M-slot antenna is designed in this paper to operate in multi-band frequencies for wireless communications using computer simulation technology (CST) software 2020. The radiation effect for this antenna is calculated for tissue mass of the human fingertips, which consists of three layers (skin, meat, and bone), over a mass of 1 g and 10 g according to the IEEE and International Commission on Non-Ionizing Radiation Protection (ICNIRP) organization. The results are shown three applications in the communication system, which are Wi-Fi, worldwide interoperability for microwave access (Wi-Max) and, satellite X-band and, the value of specific absorption rate (SAR) increase with increased frequency.
Super-opposition spiral dynamic-based fuzzy control for an inverted pendulum system Ahmad Azwan Abdul Razak; Ahmad Nor Kasruddin Nasir; Nor Maniha Abd Ghani
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3825

Abstract

This paper presents a hybrid spiral dynamic algorithm with a super-opposition spiral dynamic algorithm (SOSDA) strategy. An improvement on the spiral dynamic algorithm (SDA), this method uses a concept centered on opposition-based learning, which is used to evaluate the fitness of agents at the opposite location to the current solution. The SDA is a simple-structured and deterministic type of algorithm, which also performs competitively in terms of solution accuracy. However, its deterministic characteristic means the SDA suffers premature convergence caused by the unbalanced diversification and intensification during its search procedure. Thus, the algorithm fails to achieve highly accurate solutions. It is proposed that adopting super-opposition into the SDA would enable the deterministic and random techniques to complement one another. The SOSDA was tested on four benchmark functions and compared to the original SDA. To analyze the result statistically, the Friedman and Wilcoxon tests were conducted. Furthermore, the SOSDA was applied to optimize the parameters of an interval type-2 fuzzy logic control (IT2FLC) for an inverted pendulum (IP). The statistical results produced by the SOSDA for both benchmark functions and the IP show that the proposed algorithm significantly outperformed the SDA. The SOSDA-based IT2FLC scheme also produced better IP responses than the SDA-based IT2FLC. 
Hybrid security in AOMDV routing protocol with improved salp swarm algorithm in wireless sensor network Yousif Hardan Sulaiman; Sami Abduljabbar Rashid; Mustafa Maad Hamdi; Zaid Omar Abdulrahman Faiyadh; Abdulrahman Sabah Jaafar Sadiq; Ahmed Jamal Ahmed
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3696

Abstract

During these years the current trends shows a fast expansion in the field of wireless sensor network (WSN) based applications. Due to this much vulnerability are created and also coverage optimization becomes essential to improve overall performance. However, maximum of the model concentrates only on security or efficiency. In order to create a highly efficient protocol both concepts need to get concerted. So, we developed a protocol namely hybrid security in ad-hoc on-demand multipath distance vector (AOMDV) routing protocol with improved salp swarm algorithm (HSA-ISSA). This model is sub-divided into three sections. They are, wormhole attack and gray hole attack construction AOMDV protocol, improved salp swarm algorithm (SSA) model is used for weighted distance position updates which leads to improve the efficiency. And to secure the network from attacks we use hybrid security with the help of Diffie-Hellman key interchange algorithm and elliptic-curve cryptography (ECC) algorithm. During performance evaluation the proposed HS-ISSA protocol provide stable results in terms of message success rate (MSR), end to end delay (E2E_Delay), network throughput (NT), and average energy efficiency (AEE). Our HAS-ISSA protocol outperformed all the other earlier works by providing hybrid security, optimized coverage as well as energy efficiency to the wireless sensor networks.
Integration of ontology with machine learning to predict the presence of covid-19 based on symptoms Hakim El Massari; Noreddine Gherabi; Sajida Mhammedi; Hamza Ghandi; Fatima Qanouni; Mohamed Bahaj
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.4392

Abstract

Coronavirus (covid 19) is one of the most dangerous viruses that have spread all over the world. With the increasing number of cases infected with the coronavirus, it has become necessary to address this epidemic by all available means. Detection of the covid-19 is currently one of the world's most difficult challenges. Data science and machine learning (ML), for example, can aid in the battle against this pandemic. Furthermore, various research published in this direction proves that ML techniques can identify illness and viral infections more precisely, allowing patients' diseases to be detected at an earlier stage. In this paper, we will present how ontologies can aid in predicting the presence of covid-19 based on symptoms. The integration of ontology and ML is achieved by implementing rules of the decision tree algorithm into ontology reasoner. In addition, we compared the outcomes with various ML classifications used to make predictions. The findings are assessed using performance measures generated from the confusion matrix, such as F-measure, accuracy, precision, and recall. The ontology surpassed all ML algorithms with high accuracy value of 97.4%, according to the results.
A generic and smart automation system for home using internet of things Perumal Iyappan; Jayakumar Loganathan; Manoj Kumar Verma; Ankur Dumka; Rajesh Singh; Anita Gehlot; Shaik Vaseem Akram; Sukhdeep Kaur; Kapil Joshi
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3785

Abstract

Home automation systems are expanding increasingly popular because they can conveniently be employed to manage devices and appliances via voice or focused on physical activity utilizing sensor. From the various research, it shows that affording cost in bringing smartness to small organizations as well as normal users is challenging and there is a requirement for a better obvious and convenient method of connecting and managing equipment with mobile applications. The proposed system is created and built with the aim of enhancing control system performance and reliability. This technology may operate on any system and manage devices by connecting with home appliances and connected devices via a Wi-Fi device. The system involves a central processing module to manage devices via a home Wi-Fi connection that is linked to the internet for internet of things operations. It is recommended that an application be developed to connect, and configure new and current home appliances for control, which will lead to the connection and handling of other third-party devices via their software development kits. The suggested system enables additional features via a mobile application that allows the user to install new features created by the user to execute any activity with the system.

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