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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 2,901 Documents
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The ability to detect the linear attack of WL-CUSUM and FMA algorithms Nguyen, Duc Duong; Le, Minh Thuy; Cung, Thanh Long
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.4400

Abstract

The problem of detecting linear attacks on industrial systems is presented in this paper. The object is attacked by linear attack is the wireless communication process from sensors to controller with simulated mathematical model (stochastic dynamical systems and random noises). The attack matrices are calculated to ensure that Kullback-Leiber (K-L) algorithm is passed. With these matrices, the window limited cumulative SUM (WL-CUSUM) algorithm and finite moving average (FMA) algorithm are utilized to detect the changes in the sequence of residuals generated from Kalman filter method and are appreciated the ability to detect the linear attack. The simulated results show that an appropriate range of threshold of the WL-CUSUM and FMA algorithm can be chosen to detect the linear attack in case the K-L method cannot detect. Moreover, tested results using the Monte Carlo simulation also show that the evaluation performance of the FMA detection algorithm is better than that of WL-CUSUM, CUSUM, and Chi-squared (Chi2).
Economic dispatch problem in smart grid system with considerations for pumped storage Adil Rizki; Rachid Habachi; Karim Tahiry; Abdelwahed Echchatbi
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4207

Abstract

There are two significant issues with the incorporation of smart grid technology in power system operating studies including the economic emission, unit commitment problem (UCP). Economic dispatch problem (EDP) is a UCP sub-problem which find the optimum output for a given combination of running units. When using electro-energy systems to strategically distribute the power produced by all plants, the power economic dispatch problem is especially important. Pumped storage units that have the capacity to store energy can provide spinning reserves, which will lower overall costs and emissions. The general goal of this study is to develop control and optimization algorithms that are appropriate for managing new generation electrical networks. In this research work, the economic dispatch issue in a ten-unit smart grid system is resolved using the crow search algorithm (CSA), which acts as a local optimizer of the eagle strategy (ES). The outcomes of the ES-CSA program are compared to those found in the literature. The results of simulations suggest that adopting ES-CSA can lead to the generation of reliable and enough power that can meet the needs of both civil and industrial areas.
Human–machine interaction for motorized wheelchair based on single-channel electroencephalogram headband Yasir M. Abdal; Mohammed G. Ayoub; Mazin N. Farhan; Hasan A. Abdulla
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4163

Abstract

Human machine interaction (HMI) allows persons to control and interact with devices. Starting from elementary apparatus which acquires input bio-signals to controlling various applications. Medical applications are amongst the very important applications of HMI. One of these medical applications is assisting fully/partially paralyzed patients to restore movements or freely move using exoskeletons or motorized wheelchairs. Helping patients with spinal cord injury or serious neurological diseases to restore their movements is a key role objective for most researchers in this field. In this paper, an EEG-based HMI system is proposed to assist patients with tetraplegia/quadriplegia to mentally control a motorized wheelchair so they can move freely and independently. EEG power spectrum (α, β, δ, θ, and γ) from the frontal lobe of brain is recorded, filtered and wirelessly sent to the wheelchair to control directions and engine status. Four different experiments were conducted using the proposed system in order to validate the performance. Two different GUIs scenarios (cross-shaped and horizontal bar) were used with the experiments. Results showed that the horizontal bar scenario considered more user friendly while the cross-shaped is the more suitable for navigation. The implemented system can be equipped with modules and sensors such as GPS, ultrasound and accelerometer that improve the system performance and reliability.
Strategy to reduce solar power fluctuations by using battery energy storage system for UTeM’s grid-connected solar system Wei Hown Tee; Yen Hoe Yee; Chin Kim Gan; Kyairul Azmi Baharin; Pi Hua Tan
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.3862

Abstract

Recent years have witnessed the increasing uptake of solar photovoltaic (PV) installations, ranging from a few kilowatts for residential rooftops to a few megawatts for large-scale solar farms. One of the key challenges for the solar PV systems is its dependency on the solar energy, which is intermittent in nature and highly unpredictable. In this regard, battery energy storage system (BESS) is regarded as the effective solution that can smoothen the output power fluctuation from the solar PV system. Hence, this work utilized BESS that had fast response time with high power and energy density to reduce the solar output fluctuations from a real grid-connected solar system installed at the campus rooftop. The characteristic of the PV power fluctuation and the BESS storage requirement to smooth out the fluctuation within the allowable limit were determined and analyzed. More importantly, actual solar irradiance data with an interval of one minute was utilized in this work. The findings suggest that BESS with 66% of the installed solar capacity and 21% of the average daily solar generation of the installed system are required to smoothen the solar fluctuation that exceeds the ramp rate limit of 10%/min.
Enabling unmanned aerial vehicle to serve ground users in downlink NOMA system Nhat-Tien Nguyen; Hong-Nhu Nguyen; Leminh Thien Huynh; Miroslav Voznak
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.3945

Abstract

The emergence of internet-of-things (IoT) devices in homes and industry, has resulted in the current and future generation of wireless communications facing unique challenges in spectral efficiency, energy efficiency, and massive connectivity issues. Non-orthogonal multiple access (NOMA) has been proposed as a viable solution to address these challenges as it offers low-latency, spectral efficiency, and massive connectivity capabilities, which are key requirements in upcoming next-generation networks. In addition, another technology that has emerged as a solution to spectral efficiency and coverage is an unmanned aerial vehicle (UAV). Therefore, the combination of UAVs with NOMA has great potential to minimize the challenges and maximize the benefits. Specifically, we investigate the outage performance of the NOMA-UAV network over Nakagami-m channel fading. To this end, we derive a closed-form outage performance metric. The formulated framework is validated using simulations to verify the effectiveness of the proposed solution.
Temperature and performance evaluation of multiprocessors chips by optimal control method Porya Soltani Hanafi Por; Abbas Ramazani; Mojtaba Hosseini Toodeshki
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4291

Abstract

Multi-core processors support all modern electronic devices nowadays. However, temperature and performance management are one of the most critical issues in the design of today’s microprocessors. In this paper, we propose a framework by using an optimal control method based on fan speed and frequency control of the multi-core processor. The goal is to optimize performance and at the same time avoid violating an expected temperature. Our proposed method uses a high-precision thermal and power model for multi-core processors. This method is validated on asymmetric ODROID-XU4 multi-core processor. The experimental results show the ability of the proposed method to achieve the adequate trade-off between performance and temperature control.
Analysis of a new voltage stability pointer for line contingency ranking in a power network Tayo Uthman Badrudeen; Funso Kehinde Ariyo; Ayodeji Olalekan Salau; Sepiribo Lucky Braide
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4266

Abstract

Improper management of reactive power in a power network could lead to voltage instability. This paper presents a well-detailed study on voltage instability due to violation of power equilibrium in a power network and introduces a new voltage stability pointer (NVSP). The proposed NVSP is developed from a reduced 2-bus interconnected network to predict the sensistivity of voltage stability to reactive power variation. The simulation results from MATLAB were evaluated on IEEE 14-bus test system. The contingency ranking was achieved by varying the reactive power on the load buses to its maximum loading limit. The maximum reactive power point was taken at each load bus and the critical lines were ranked according to their vulnerability to voltage collapse. The results were compared with other notable voltage stability indices. The results prove that the NVSP is an essential tool in predicting voltage collapse.
A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation Nursabillilah Mohd Ali; Rosli Besar; Nor Azlina Ab Aziz
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4838

Abstract

Breast cancer is one of the leading causes of death and most frequently diagnosed cancer amongst women. Annually, almost half a million women do not survive the disease and die from breast cancer. Machine learning is a subfield of artificial intelligence (AI) and computer science that uses data and algorithms to mimic how humans learn, and gradually improving its accuracy. In this work, simple machine learning methods are used to classify breast cancer microarray data to normal and relapse. The data is from the gene expression omnibus (GEO) website namely GSE45255 and GSE15852. These two datasets are integrated and combined to form a single dataset. The study involved three machine learning algorithms, random forest (RF), extra tree (ET), and support vector machine (SVM). Grid search cross validation (CV) is applied for hyperparameter tuning of the algorithms. The result shows that the tuned SVM is best among the tested algorithms with accuracy of 97.78%. In the future it is recommended to include feature selection method to get the optimal features and better classification accuracies.
Machine learning approaches in the diagnosis of infectious diseases: a review Smriti Mishra; Ranjan Kumar; Sanjay Kumar Tiwari; Priya Ranjan
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4225

Abstract

Infectious diseases are a group of medical conditions caused by infectious agents such as parasites, bacteria, viruses, or fungus. Patients who are undiagnosed may unwittingly spread the disease to others. Because of the transmission of these agents, epidemics, if not pandemics, are possible. Early detection can help to prevent the spread of an outbreak or put an end to it. Infectious disease prevention, early identification, and management can be aided by machine learning (ML) methods. The implementation of ML algorithms such as logistic regression, support vector machine, Naive Bayes, decision tree, random forest, K-nearest neighbor, artificial neural network, convolutional neural network, and ensemble techniques to automate the process of infectious disease diagnosis is investigated in this study. We examined a number of ML models for tuberculosis (TB), influenza, human immunodeficiency virus (HIV), dengue fever, COVID-19, cystitis, and nonspecific urethritis. Existing models have constraints in data handling concerns such data types, amount, quality, temporality, and availability. Based on the research, ensemble approaches, rather than a typical ML classifier, can be used to improve the overall performance of diagnosis. We highlight the need of having enough diverse data in the database to create a model or representation that closely mimics reality.
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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