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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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Convolutional neural network for color images classification Nora Ahmed Mohammed; Mohammed Hamzah Abed; Alaa Taima Albu-Salih
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3730

Abstract

Artificial intelligent and application of computer vision are an exciting topic in last few years, and its key for many real time applications like video summarization, image retrieval and image classifications. One of the most trend method in deep learning is a convolutional neural network, used for many applications of image processing and computer vision. In this work convolutional neural networks CNN model proposed for color image classification, the proposed model build using MATLAB tools of deep learning. In addition, the suggested model tested on three different datasets, with different size. The proposed model achieved highest result of accuracy, precision and sensitivity with the largest dataset and it was as following: accuracy is 0.9924, precision is 0.9947 and sensitivity is 0.9931, compare with other models.
Detection and mitigation of DDoS attacks in internet of things using a fog computing hybrid approach Karrar Falih Hassan; Mehdi Ebady Manaa
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3643

Abstract

The introduction of a new technology has aided the exponential growth of the internet of things (IoT), allowing for the connecting of more devices in the IoT network to be made possible by the availability of quicker connections and reduced latency. As IoT networks have become more prevalent and widely used, security has become one of the fundamental requirements, and a distributed denial of service (DDoS) attack poses a significant security threat due to the limited resources (CPU, memory, open source, persistent connection) that can be used to either intentionally or unintentionally increase DDOS attacks. Fog computing is proposed in this study as a framework for real-time detection and mitigation of DDoS assaults. Fog computing is accurate and quick in detecting attacks due to its proximity to IoT devices. DDOS assaults are detected using an approach that combines randomness measurement of traffic with k-nearest neighbors (KNN) machine learning algorithm. Suggested system obtained 100% detection accuracy for transmission control protocol TCP attacks, 98.79% detection accuracy for UDP attacks, and 100% detection accuracy for internet control message protocol ICMP attacks.
A comprehensive analysis on IoT based smart farming solutions using machine learning algorithms Ahamed Ali Samsu Aliar; Justindhas Yesudhasan; Manjunathan Alagarsamy; Karthikram Anbalagan; Jeevitha Sakkarai; Kannadhasan Suriyan
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3310

Abstract

Agriculture and farming are the most important and basic industries that are very important to humanity and generate a considerable portion of any nation's GDP. For good agricultural and farming management, technological advancements and support are required. Smart agriculture (or) farming is a set of approaches that uses a variety of current information and communication technology to improve the production and quality of agricultural products with minimum human involvement and at a lower cost. Smart farming is mostly based on IoT technology, since there is a need to continually monitor numerous aspects in the agricultural field, such as water level, light, soil characteristics, plant development, and so on. Machine learning algorithms are used in smart farming to increase production and reduce the risk of crop damage. Data analytics has been shown through extensive study to improve the accuracy and predictability of smart agricultural systems. Data analytics is utilised in agricultural fields to make decisions and recommend acceptable crops for production. This study provides a comprehensive overview of the different methods and structures utilised in smart farming. It also provides a thorough analysis of different designs and recommends appropriate answers to today's smart farming problems.
Classification of handwritten Javanese script using random forest algorithm Mohammad Arif Rasyidi; Taufiqotul Bariyah; Yohanes Indra Riskajaya; Ayunda Dwita Septyani
Bulletin of Electrical Engineering and Informatics Vol 10, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i3.3036

Abstract

The ability to read and write Javanese scripts is one of the most important competencies for students to have in order to preserve the Javanese language as one of the Indonesian cultures. In this study, we developed a predictive model for 20 Javanese characters using the random forest algorithm as the basis for developing Javanese script learning media for students. In building the model, we used an extensive handwritten image dataset and experimented with several different preprocessing methods, including image conversion to black-and-white, cropping, resizing, thinning, and feature extraction using histogram of oriented gradients. From the experiment, it can be seen that the resulting random forest model is able to classify Javanese characters very accurately with accuracy, precision, and recall of 97.7%.
Design and characterization substrate integrated waveguide antenna for WBANS application Mustafa Mohammed Jawad Abed; Nik Noordini Nik Abd Malik; Noor Asniza Murad; Mona Riza Mohd Esa; Mohd Riduan Ahmad; Ola Hussein Abed Al Radh; Ali Abdulateef Abdulbari; Yaqdhan Mahmood Hussein; Fahad Taha Al-Dhief
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3492

Abstract

Millimetre-wave frequencies are defined as one of the front-runner contenders for body-centric wireless communication. In this study, low-profile antenna with the substrate integrated waveguide (SIW) has been proposed that operate in the band of the millimetre-wave frequency that has been centred at 60 GHz. The proposed antenna has been implemented with the use of the FR4 substrate with εr and tangent loss of 4.3 and 0.025, respectively. The substrate height and size are 1.5875 mm and 20 mm x 20 mm, respectively. The performance of the antenna is evaluated in off-body (free space) and on-body (human voxel model), through simulation. The proposed antenna has an ultra-wideband (UWB) and a specific absorption rate the maximal (SAR) for (10 g) is 0.0344815 W/kg and for (1 g) is 0.0184723 W/kg. It achieves 74% and 63% efficiency in the off and on-body scenario, respectively. The small antenna with the exceptional matching of impedance, low SAR, broad bandwidth, and good efficiency, a good voltage standing wave ratio good (VSWR), and good front-to-back ratio (FBR). As a result, its characteristics make it one of the best potential candidates for the simultaneous transmission and reception of data at (mm-wave) band for WBAN applications.
Design and performance analysis of frequency hopping OFDM based noise reduction DCSK system Mokhalad L. Mohammed; Fadhil S. Hasan
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3836

Abstract

The reference chaotic signal in the differential chaos shift keying (DCSK) system causes both bit error rate (BER) and security performance degradation. In this paper, a frequency hopping orthogonal frequency division multiplexing based noise reduction DCSK (FH-OFDM-NR-DCSK) system is proposed to enhance both the BER and security performance of the OFDM-DCSK system. This system combines the advantages of both FH-OFDM-DCSK and NR-DCSK. Rather than creating β separate chaotic samples to utilize as a reference sequence, β/P chaotic samples are created and then replicated P times. Moving average filters of size P are applied after the frequency hopper to average the repeated chips of the reference and data-bearing signals. A new frequency hopping pattern is designed depending on the chaotic map on which the matrix pattern is designed efficiently. The performance of the proposed system is examined, and bit error rate analytic equations of the FH-OFDM-NR-DCSK system over an AWGN and two-path Rayleigh fading channel are derived. The simulation results show that the theoretical BER expressions and simulation performance match. The findings show that for the same spreading factor, the proposed system outperforms the DCSK and FH-OFDM-DCSK when P more than 1. This method decreases noise variance and improves BER without adding to the system's complexity.
A smart water grid network for water supply management systems Ali Adil Ali; Saadi Mohammed Saadi; Tameem Mohammed Mahmood; Salama A. Mostafa
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3227

Abstract

This paper proposes a smart water grids network (SWGN) architecture that combines the advantages of fog computing, internet of things (IoT), long range wide area network (LoRaWAN), and Software-defined networking (SDN). The main aims of the SWG architecture are to optimize data routing and monitor water supply and quality in real-time. SWGN handles a vast amount of data that is collected by IoT devices from different points related to water supply and quality. The data is processed in a distributed way by a number of fog servers that are located at the edge of the network. The fog controllers are deployed at the fog layer in order to take action locally for frequent events. The cloud layer has a cloud controller to take actions globally for infrequent events. The LoRaWAN provides communication technology that allows devices to operate regularly. The SDN technology decouples network traffic to control data routing decisions efficiently. A primitive evaluation under the Mininet emulator, focusing on SDN, shows the feasibility and efficiency of the architecture.
Using liquid phase precursor method to create a high-efficiency Ca2SiO4:Eu2+ green-emitting phosphor Phuc Dang Huu; Dieu An Nguyen Thi
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3767

Abstract

A standard solid-state reaction (SSR), a new fluid phase preparatory method utilizing LPP-SiO2(sol), and a water-based soluble silicone compound were employed to manufacture green Eu2+-based Ca2SiO4 phosphors liquid phase precursor (LPP-WSS). The generated phosphors feature large excitation spectra in the range of 225–450 nm and a strong green emission reaches the peak value at 502 nm owing to a 4f65d1→4f7(8S7/2) transition of Eu2+. These samples burned at 1100 1C produce the highest luminous intensity. The luminous properties of phosphors, which are manufactured by the liquid phase precursor LPP-WSS technique, were investigated at the range of 0.1-5.0 mol percent of Eu2+, with the maximum emission density observed at the value of 3.0 mol percent of Eu2+. The phosphors produced by the LPP-WSS technique exhibited a more uniform phase dispersion and higher luminous strength than those produced using the other procedures, according to a detailed report based on numerous characterizations. As a result, Ca2SiO4:Eu2+ has an indisputable possibility in white light-emitting diodes WLEDs and fluorescent lighting.
Outage performance analysis of NOMA over log-normal fading distribution in presence of CSI and SIC imperfections Chi-Bao Le; Hong-Nhu Nguyen; Huy Hung Nguyen; Thi-Hau Nguyen; Nhan Duc Nguyen
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3395

Abstract

The evolution of wireless communication networks has introduced various applications that require massive device connectivity and high spectral efficiency. Non-orthogonal multiple access (NOMA) technique is one of the most promising technologies to perform efficiently data transmission. The NOMA technique can allocate the same resource block for two users by super-imposing signals. At the receiver, the signals are separated by performing successive interference cancellation (SIC) technique. For efficient data transmission, the fading and shadowing effects of channels also play a pivotal role. Many researches have considered Rayleigh, Rician, Nakagami-m, and other fading channels in various perspectives. In our paper, a system model based on a NOMA network with two users over log-normal fading distribution in the presence of channel estimation errors and SIC imperfections is proposed. The performance is analyzed in terms of outage probability and simulations are performed with the assistance of Monte-Carlo simulations. The obtained results shown the effectiveness in comparison with the traditionally used fading distributions. The same analysis is also performed in various scenarios of power allocation levels, target rates, and imperfections. The transmit SNR and power allocation of the users are important for efficient communication in any fading distribution as shown in this paper.
Burg power spectral density-based characterization of Doppler blood flow sound during hemorrhoidal artery ligation Daniel Santoso; Oyas Wahyunggoro; Prapto Nugroho
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3309

Abstract

Hemorrhoidal artery ligation (HAL) has become universally accepted minimally invasive treatment of hemorrhoids disease. HAL involves precise identification of the superior rectal arteries supplying hemorrhoidal tissues using ultrasonic Doppler principles. During this process, at least there are three distinct sounds may be encountered by the surgeon. Only the pulsing Doppler sound is useful as it indicates the presence of hemorrhoidal artery. The accuracy based on traditional auscultation is commonly affected by surgeon’s hearing sensitivity and clinical experience. Therefore, automatic Doppler blood flow sound will be a great help in locating hemorrhoidal arteries. In this paper, a method based on the center frequency and kurtosis features extracted from Burg’s power spectral density (PSD) to distinguish three different types of Doppler blood flow sound signal during HAL procedure is proposed. Separability measurement was carried out using K– means clustering with the city block distance and three clusters corresponding to different sound types are successfully formed. In terms of arterial sound detection, an accuracy of 94.11% can be achieved. This result suggests that centre frequency, kurtosis, and maybe some other statistical features extracted from Burg PSD have the potential to be utilized as a means in automatic Doppler blood flow sound recognition.

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