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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 12, No 2: April 2023" : 64 Documents clear
Simulating fog computing in OMNeT++ Noor Razaq Obaied Al-Rubaie; Rafal Nader Neamah Kamel; Raghda M. Alshemari
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.v12i2.4201

Abstract

Fog computing is a technology architecture in which data from IoT devices is received in real time by a number of nodes. These nodes process the data they receive in real time, with millisecond reaction times. The nodes communicate analytical summary data to the cloud on a regular basis. Fog computing scenario demands higher output, reduced latency, and greater performance as demand and requirements for improving performance in IoT applications grow. The resources allocation in effective manner in the fog environment is also a major problem in IoT-fog computing. Fog computing has been considered as a necessity within several IoT resources domains. In this paper the proposed fog simulation environment is focused on IoT sensors, fog node, and cloud as the used network architecture. However, the network features are properly explored in the proposed system and they are evaluated based on the throughput, latency, and channel allocation.
Design UWB antenna with notch band for WiMAX application Alaa Mohsen Ali; ِAli Khalid Jassim
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.v12i2.4104

Abstract

During the last two decades, radar, remote sensing, and imaging applications have all made use of ultra-wide band (UWB) technology. UWB systems are susceptible to interference from narrowband signals, hence this work provides a single-notch antenna for the UWB system. There are two stages to the design process. After creating the baseband antenna, it is necessary to create a notched band UWB antenna by carving a slot into patch antenna. In the UWB range (3.1-10.6) GHz, the UWB antenna has the dimensions of 20x30 mm with substrate thickness 1.6 mm made from FR4 lossy. The design relative permittivity was 4.3, a rectangular patch with a portion of the ground is used in the design. A typical slot-shaped resonator is connected to the patch to reject a frequency band (3.273-3.81) GHz which is a world interoperability for microwave access (WiMAX) to solve the problem of the interference with other bands in UWB system For WiMAX applications. The suggested UWB filter will achieve notch band response centered at the resonance frequency of 3,4 GHz. Analysis CSTS v2020 software was used to carry out the simulation. Priority should be given to what has been learned rather than what has been accomplished.
A framework for predicting lncRNAs expression in human dendritic cells in response to M. tuberculosis infection Faizah Aplop; Saharuddin Mohamad
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.v12i2.4289

Abstract

Tuberculosis (TB) is an air-borne infectious diseases caused by M. tuberculosis bacteria that primarily affects human lungs. Existing vaccine does not work well due to the evolvement and latent movement of this bacteria. Developing an effective vaccine to combat Tuberculosis is very difficult as the interaction between the bacteria and human immune system is not fully understood. With recent advancement of transcriptome profiling analysis, long noncoding ribonukleat acids (lncRNAs) are found to be widely expressed in immune system. However, the role of lncRNAs is still not been widely explored in understanding human immune response to TB infection. In this paper, we propose a general framework for predicting lncRNAs being expressed in human dendritic cells. By incorporating deep learning method with RNA-seq data analysis, we intend to identify and characterize the lncRNAs found in dendritic cells from two groups of TB resistant patients through their RNA-seq expression data.
Dental caries classification using depthwise separable convolutional neural network for teledentistry system Trie Maya Kadarina; Zendi Iklima; Rinto Priambodo; Riandini Riandini; Rika Novita Wardhani
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.v12i2.4428

Abstract

Caries may be halted or reversed in their progression by early detection, better hygiene habits, and coadministered drugs. The major clinical procedures for identifying dental caries are visual-tactile examination and dental radiography. However, due to their location, approximate caries exceedingly difficult to detect and affect the clinical assessment. Incorrect interpretations may also hinder the diagnostic procedure. Computational approaches and technology can be used to help dentists assess caries. Teledentistry has the ability to improve dental health care by providing access to dental care services from a remote location. Teledentistry helps identifying various stages of caries lesions using neural network and devices connected to the internet. This research develops an image classification for teledentistry systems using depthwise separable convolutional neural network. The trainable parameters reduction of depthwise separable convolution (DSC) successfully reduces the computational cost of conventional convolutional neural networks (CNN). As a result, the DSC model is reduced by 91.49% when compared to the traditional CNN model. Several DSC models improve conventional CNN accuracies in the training, validation, evaluation, and testing stages.
Analysis of a Li-ion battery state of charge by artificial neural network Sumithara Arunagirinathan; Chitra Subramanian
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.v12i2.5175

Abstract

The state of charge (SOC) is a battery residual capacity crucial assessment metric. The need for a precise SOC estimate is very important to ensure the safe functioning of a Li-ion battery and to prevent overload and over-depletion. However, the renewable energy-based standalone application has become a key problem to determine the exact capacity of SOC of the Li-ion battery. To estimate the capacity over time, the battery management system calculates the SOC of a Li-ion battery. This allows for the implementation of intelligent control systems. This paper presents an enhanced radial basis function (RBF) of the SOC battery estimate following the limits and weaknesses of the back propagation (BP) neural network (NN) in estimating battery SOC, such as sluggish convergence speed, poor generalization and can increase the accuracy of the network but it takes time to iterate. Train the enhanced RBF with experimental data in real-time. The trained NN of SOC is compared to actual values and the MATLAB is used to simulate the method to evaluate its accuracy.
A latent semantic analysis method for ranking the results of human disease search engine Loi Chan Quan Lam; Tran Kim Toai; Snasel Vaclav
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.v12i2.4602

Abstract

The human disease search engine based on the search query about disease factors (symptom, cause, position happening symptoms, i.e.,) helps users to conveniently diagnose the disease they may have anytime, anywhere. Therefore, the disease results returned by the search engine need to be accurate and ranked reasonably so that users can know which disease has the highest probability for their search query. We propose a method to arrange the returned diseases based on the latent semantic analysis (LSA) technique. This method helps to rank the disease results reasonably and meaningfully because it not only exploits the matching term frequency-inverse document frequency (TF-IDF) scores between the disease factors in the query and the disease results, but it also exploits the implicit relationship between the disease factors in the search query and the disease factors in the disease results.
A novel microstrip fed triple band patch antenna with TM10, TM02 and TM12 induced modes Revansiddappa S. Kinagi; Ravi M. Yadahalli; Siddarama R. Patil
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.v12i2.4072

Abstract

In this study, a patch antenna with three different operating frequencies (2.94 GHz, 4.5 GHz, and 5.7 GHz) is proposed. The dimensions of the antenna are as follows: 23.4 mm by 30.4 mm by 1.6 mm. The triple band characteristic may be achieved by adjusting the width of the quarter wave transformer (QWT), which in turn modifies the impedance matching in such a manner as to excite the TM10, TM02, and TM12 modes. These modes are able to have additional verification provided by the current distribution on the patch. Altering the width of the QWT provides the proposed antenna with the ability to fine-tune its resonant frequencies. At the resonant frequencies, the impedance bandwidths of -10 dB are 69 MHz, 40 MHz, and 110 MHz, respectively. 5.7 GHz has a gain of 1.5 dB, while 4.5 GHz has a gain of 0.7 dB, and 2.94 GHz has a gain of 2 dB. Additionally, this antenna finds its applications in wireless systems in the S and C bands of the frequency spectrum. The antennas are validated using a vector network analyzer (VNA) after being simulated with mentor graphics software three-dimensional electromagnetic modeling (3DEM) and analyzed with it.
Carbon nanomaterials advancements for biomedical applications Hamza Abu Owida; Nidal M. Turab; Jamal Al-Nabulsi
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.v12i2.4310

Abstract

The development of new technologies has helped tremendously in delivering timely, appropriate, acceptable, and reasonably priced medical treatment. Because of developments in nanoscience, a new class of nanostructures has emerged. Nanomaterials, because of their small size, display exceptional physio-chemical capabilities such as enhanced absorption and reactivity, increased surface area, molar extinction coefficients, tunable characteristics, quantum effects, and magnetic and optical properties. Researchers are interested in carbon-based nanomaterials due to their unique chemical and physical properties, which vary in thermodynamic, biomechanical, electrical, optical, and structural aspects. Due to their inherent properties, carbon nanomaterials, including fullerenes, graphene, carbon nanotubes (CNTs), and carbon nanofibers (CNFs), have been intensively studied for biomedical applications. This article is a review of the most recent findings about the development of carbon-based nanomaterials for use in biosensing, drug delivery, and cancer therapy, among other things.
A battery integrated multiple input DC-DC boost converter Azuka Affam; Yonis M. Yonis Buswig; Al-Khalid Hj Othman; Norhuzaimin Julai; Hani Albalawi
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.v12i2.4272

Abstract

In this paper, the proposed single boost converter aims to harness more than one renewable energy (RE) input source and achieve a high voltage gain. The interleaved technique combined with voltage multiplier (VM) cells, reduced inductor current and attained high voltage transfer ratio. The boost converter possesses two unidirectional input ports and a bidirectional input port that is connected to a battery storage. The duty ratios of the power and interleaving switches are used to regulate the output voltage of the proposed converter. Three operation modes are identified, and steady state analyses of the converter are presented and discussed. The converter can store excess energy in the battery during periods of abundance and deliver power to the loads when the RE sources are low or unavailable. In addition, the output voltage is higher than that of the conventional boost converter. The converter delivered 278 V from 12 V and 24 V dual input sources. The converter operation is simulated and verified using MATLAB/Simulink.
Mobile agents assisted data collection in wireless sensor networks utilizing ZigBee technology Hoang Thuan Tran; Cuong V. Nguyen; Nghia Trung Phung; Minh T. Nguyen
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.v12i2.4541

Abstract

Wireless sensor networks (WSNs) are being utilized widely in many different industries, including agriculture, medicine, and the military. They contain many distributed sensors to monitor physical or environmental factors, such as temperature, humidity, pressure, etc. and use various communication technologies, including WiFi, radio frequency (RF), Bluetooth, and ZigBee. ZigBee is always a preferred choice for applications in WSNs. ZigBee has remarkable capabilities, such as saving energy and transmitting data over long distances. ZigBee end devices, as well as a ZigBee coordinator (ZC) and a ZigBee router (ZR), are crucial components of the WSNs. This article discusses the fundamentals of the ZigBee network, one of the most popular data transmission technologies in wireless sensor networks (WSNs). Additionally, we want to discuss the ZigBee communication technologies and their applications, particularly in the networks. Different scenarios for mobile agents including their routing protocols in WSNs are considered. Simulation results of different scenarios demonstrate how easily scalability can be achieved and provide a foundation for further ZigBee application development. At last, some conclusions and ideas are presented for considerations.

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