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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
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University of Kufa unified laboratories management system using computer application Faris Sattar Hadi; Ali Al Farawn; Ahmed Hazim Alhilali
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1617-1623

Abstract

The laboratory organization is essential in the university to maximize system convenience, accuracy, appropriateness, and sustainability. The laboratory data system is an information supplier that aids in arranging data sources and decision-making processes. In this work, unified laboratories management system (ULMS) was presented in the educational field for managing and scheduling lab equipment information. There are two steps in the research process: the first is to examine the old approach for organizing and scheduling laboratory equipment and suggest a better one. The approach adopted in this system is the first come, first served rule governs task priority (FCFS). The second step is creating a computerized system for scheduling and managing laboratory equipment. For programming, C# and structured query language (SQL) are used. This system's design included user and administrative integration (manager, technicians, and researchers). An information application system plan was created because of this research to manage the scheduling information for lab equipment. As a result, it can help the management of the laboratory describe all operational tasks in a way that is considerably simpler and produces outcomes more quickly and accurately.
Effective resource virtualization for dynamic IoT devices in road network Padmanabhan P.; Sampath Kumar K.; John A.
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1777-1785

Abstract

Internet of things (IoT), which is considerably innovating and generating a large volume of processes in every field worldwide, is one of the recent and next disruptive technologies. As a result, IoT devices and others are increasing network connections in the relevant field. It is essential to maximize and process these kinds of resources. The effective usage of resources is one of the most important and very difficult to manage the resource in the dynamic environments. Many studies are performed in the effective usage of resource in the static and dynamic environments. However, the dynamic environments have still different issues and have to solve different dynamic networking issues. In this work, present a mechanism for managing different connecting devices in the dynamic environments. Especially this system is concentrating on road network device management in dynamic environments. The proposed system called dynamic road sensing (DyRSen) connectivity is support to different continuous connectivity. The DyRSen provides: i) continuous connectivity using available resources and provide virtual environment for computing, ii) temporary data storage in dynamic environment for effective resource sharing, and iii) reduce the energy utilization and network overhead and the effective resource management is compared to the other works.
Voltage and frequency stabilization by fuzzy integrated droop control of a multi renewable source micro grid Savitri Swathi; Bhaskaruni Suresh Kumar; Jalla Upendar
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1308-1320

Abstract

A multi renewable source micro-grid system has many power quality issues when it is operated in grid islanding condition. During grid connected mode the voltage and frequency of the system will remain stable for small disturbances like load changes or environmental changes. During these sudden variations in the system, the grid supports the load maintaining the system stable. In this paper a droop control is introduced for the renewable source module 3-ph inverter during standalone mode supporting the load. For detection of grid islanding, an active islanding detection control is adopted which makes the 3-ph inverter to shift from synchronous reference frame (SRF) control to droop control. The performance of the droop control is improvised with fuzzy interference structure (FIS) module replacing the conventional proportional integral and derivative (PID) control. A comparative analysis is done in this paper with different controllers in droop control scheme using matrix laboratory (MATLAB) Simulink software. Stability analysis is carried out on the system determining the voltage and frequency fluctuations during grid disturbances. There is an improvement in load compensation, voltage ripple, voltage magnitude, frequency ripple and settling time with the introduced fuzzy droop controller.
Harmful gases detection using artificial neural networks of the environment Pratiksha Rai; Syed Hasan Saeed; Shri Om Mishra
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1389-1398

Abstract

This work describes a small, low-cost electronic nose device which can detect harmful substances that can harm human health, such as flammable gas like acetone, ethanol, butane as well as methane, among others. An artificial olfactory instrument consists of a set of metal oxide semiconductor sensors as well as a computer-based communications channel for signal gathering, proceeding, and presentation. We used three sensors instead of six, and the results were plotted as a variance, score as well as loading plot with crossvalidation. For gas identification, we use artificial neural network (ANN) and compare them to parallel factor analysis. Electronic nose (e-nose) has provided numerous benefits in a variety of logical study disciplines. Our goal is to create a sensor exhibit framework that can discriminate the most exceedingly contaminated gases while also being extremely responsive, precise, and less power consuming. Thus, for gas detection, we employ an ANN as well as make a comparison of results with parallel factor analysis (PARAFAC).
Design and fabrication of an IoT-based smart electrical meter for residential energy management Thanh Ba Nguyen; Tri Cao Nguyen
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1259-1268

Abstract

Transparency in electricity measurement and efficient use of electricity are issues of concern to households. Electricity customers want to have confidence in their utility company's electricity meters installed at their houses. This study designs and constructs an internet of things (IoT)-based smart electric meter to measure electricity and remotely control domestic appliances. This device can monitor, calculate electricity bills and remotely control the appliances via the internet; electrical quantities are displayed in real-time on the Blynk app, liquid crystal display (LCD) screen and Google Sheet. The device is also capable of emailing the electricity user. The proposed system is designed and developed based on ESP32, a LCD, a PZEM 004T, four relays and a DC source. The results show that the device works stably and the device’s error is less than 5%. This research makes it possible for users to conveniently monitor their power consumption while enhancing their energy-saving awareness.
Anomaly-based intrusion detection system based on feature selection and majority voting Mina Eshak Magdy; Ahmed M. Matter; Saleh Hussin; Doaa Hassan; Shaimaa Ahmed Elsaid
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1699-1706

Abstract

Recently, cyberattacks have been more complex than in the past, as a new cyber-attack is initiated almost every day. Therefore, researchers should develop efficient intrusion detection systems (IDS) to detect cyber-attacks. In order to improve the detection and prevention of the aforementioned cyber-attacks, several articles developed IDSs exploiting machine learning and deep learning. In this paper, a way to find network intrusions using a combination of feature selection and adoptive voting is investigated. NSL-KDD dataset, a high-dimensional dataset that has been widely used for network intrusion detection, is applied in this approach. Feature selection plays an important role for improving accuracy and testing time as it eliminates the less significant attributes from the data set, thus saving computational power and effort. The experimental results show that the proposed approach achieves an accuracy of 86.5% on the NSL-KDD test dataset using an adoptive voting algorithm trained with the selected features. In addition, the time to process each record is 97.5 microseconds, which reflects the proposed model's superior performance. Comparing the proposed model with the existing models in the literature shows that the proposed adaptive voting approach significantly improves intrusion detection accuracy, enhances computational efficiency, and reduces false positives.
Utilizing deep neural network for web-based blood glucose level prediction system Ganjar Alfian; Yuris Mulya Saputra; Lukman Subekti; Ananda Dwi Rahmawati; Fransiskus Tatas Dwi Atmaji; Jongtae Rhee
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1829-1837

Abstract

Machine learning algorithms can be used to forecast future blood glucose (BG) levels for diabetes patients, according to recent studies. In this study, dataset from continuous glucose monitoring (CGM) system was used as the sole input for the machine learning models. To forecast blood glucose levels 15, 30, and 45 minutes in the future, we suggested deep neural network (DNN) and tested it on 7 patients with type 1 diabetes (T1D). The suggested prediction model was evaluated against a variety of machine learning models, such as k-nearest neighbor (KNN), support vector regression (SVR), decision tree (DT), adaptive boosting (AdaBoost), random forest (RF), and eXtreme gradient boosting (XGBoost). The experimental findings demonstrated that the proposed DNN model outperformed all other models, with average root mean square errors (RMSEs) of 17.295, 25.940, and 35.146 mg/dL over prediction horizons (PHs) of 15, 30, and 45 minutes, respectively. Additionally, we have included the suggested prediction model in web-based blood glucose level prediction tools. By using this web-based system, patients may readily acquire their future blood glucose levels, allowing for the generation of preventative alarms prior to crucial hypoglycemia or hyperglycemic situations.
Parallel processing of E-Atheer algorithm using pthread paradigm Atheer Akram AbdulRazzaq; Mohammed A. Fadhel; Laith Alzubaidi; Omran Al-Shamma
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1624-1633

Abstract

The development in the field of computer technology, and the increase in the growth rate of database, alongside the extraction of certain data from a huge pool of database involve intricate and complex processes. The processes comprise text mining, pattern recognition, retrieval of information and text processing. Thus, the need for enhancing the performance of string matching algorithms is required, which is considered as one of the challenges to the researchers. Consequently, one of the resolution to address this problem is the parallelization for exact string matching algorithms. In this study, we implemented the parallel exact string matching algorithm termed as E-Atheer with multi-core processing utilizing Pthread (POSIX) for the reduction of time consumption. The Pitch, XML, Protein, and DNA database types are utilized to test the impact of the proposed parallel algorithm. The parallelization algorithm obtained positive results in the parallel execution time, and a more superior expediting capabilities, in comparison to the sequential result. The Pitch database indicated optimal results in parallel execution time, and when utilizing long and short pattern lengths. The DNA database indicated optimal speedup performance when utilizing short and long pattern length, meanwhile the XML and Protein on the other hand indicated the worst results.
An intelligent road accident reduction system using device-to-device communication Taskeed Jabid; Nazmul Hasan Rizvy; Fateza Tuj Zohora Mow; Tanjina Zaman Shosy; Md. Sawkat Ali; Maheen Islam; Samia Binta Hassan; Mahamudul Hasan
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1729-1739

Abstract

Every year thousands of people are dying due to road accidents and most of the accidents are occurring in urban areas and highways. As the number of vehicles is increasing day by day, the probability of the occurrence of the accident is also increasing. A system has been introduced in this paper that can reduce road accidents by sending an alert to drivers via smartphones. For this purpose, an android-based application has been developed. To reduce the accident, every driver of the car must have the application. Firstly, the location of the vehicle will be collected from the driver’s smartphone, then the data will be sent to the server through the application. An algorithm has been also developed using Haversine Formula which calculates the distance among the vehicles. A total of five cases have been implemented according to the dataset and compared for the performance evaluation. An extensive experimental study and comparison have been performed with the other methods where a complete performance is focused that can be claimed to reduce road accidents via the device-to-device communication process.
Investigating and calculating the temperature of hot-spot factor for transformers Khalid Yahya; Hani Attar; Haitham Issa; Jamal Ali Ramadan Dofan; Nassim A. Iqteit; Adel E. M. Yahya; Ahmed Amin Ahmed Solyman
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1297-1307

Abstract

This article explores the measurement of temperature in transient states, utilizing the principles of heat transfer and thermal-electrical metaphor. The study focuses on the nonlinear thermal resistances present in various locations within a distribution transformer, while taking into account variations in oil physical variables and temperature loss. Real-time data obtained from heat run tests on a 250-MVA-ONAF cooled unit, conducted by the transformer manufacturer, is used to verify the thermal designs. The observations are then compared to the loading framework of the IEC 60076-7:2005 system. The findings of this research provide a better understanding of temperature measurement in transient states, particularly in distribution transformers, and can be applied to the design and development of more efficient and reliable transformer systems.

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