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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 1: February 2023" : 64 Documents clear
Automatic liver segmentation in computed tomography scans using deep semantic segmentation Ezzat, Kadry Ali; Omran, Lamia Nabil; Seddawy, Ahmed Ibrahim Bahgat El
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.v12i1.4022

Abstract

Division of the liver from figured computed tomography (CT) images is fundamental for the greater part of the PC supported clinical applications, for instance, the arranging period of a liver transfer, liver volume assessment, and radiotherapy. In this paper, a programmed liver location model from clinical CT filters utilizing profound semantic division convolutional neural organization will be introduced, this model will actually want to subsequently isolate the liver utilizing CT images. The proposed model presents simultaneously the liver ID and the probabilistic division utilizing a profound convolutional neural organization. The proposed approach was endorsed on 10 CT volumes taken from open data sets 3Dircadb1. The proposed model is totally programmed with no requirement for client mediation. Quantitative results show that proposed model is reliable and exact for hepatic volume assessment in a clinical course of action with testing exactness 98.8%.
Offline signature verification using long short-term memory and histogram orientation gradient Alsuhimat, Fadi Mohammad; Mohamad, Fatma Susilawati
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.v12i1.4024

Abstract

The signing process is a critical step that organizations take to ensure the confidentiality of their data and to safeguard it against unauthorized penetration or access. Within the last decade, offline handwritten signature research has grown in popularity as a common method for human authentication via biometric features. It is not an easy task, despite the importance of this method; the struggle in such a system stem from the inability of any individual to sign the same signature each and every time. Additionally, we are indeed interested in the dataset’s features that could affect the model's performance; thus, from extracted features from the signature images using the histogram orientation gradient (HOG) technique. In this paper, we suggested a long short-term memory (LSTM) neural network model for signature verification, with input data from the USTig and CEDAR datasets. Our model’s predictive ability is quite outstanding: The classification accuracy efficiency LSTM for USTig was 92.4% with a run-time of 1.67 seconds and 87.7% for CEDAR with a run-time of 2.98 seconds. Our proposed method outperforms other offline signature verification approaches such as K-nearest neighbour (KNN), support vector machine (SVM), convolution neural network (CNN), speeded-up robust features (SURF), and Harris in terms of accuracy.
Stereo matching algorithm for autonomous vehicle navigation using integrated matching cost and non-local aggregation Zahari, Madiha; Hamzah, Rostam Affendi; Manap, Nurulfajar Abd; Herman, Adi Irwan
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.v12i1.4122

Abstract

Stereo matching algorithm plays an important role in an autonomous vehicle navigation system to ensure accurate three-dimensional (3D) information is provided. The disparity map produced by the stereo matching algorithm directly impacts the quality of the 3D information provided to the navigation system. However, the accuracy of the matching algorithm is a challenging part to be solved since it is directly affected by the surrounding environment such as different brightness, less texture surface, and different image pair exposure. In this paper, a new framework of stereo matching algorithm that used the integration of census transform (CT) and sum of absolute difference (SAD) at the matching cost computation step, non-local cost aggregation at the second step, winner take all strategy at the third step, and a median filter at the final step to minimize disparity map error. The results show that the accuracy of the disparity map is improved using the proposed methods after some parameter adjustment. Based on the standard Middlebury and KITTI benchmarking dataset, it shows that the proposed framework produced accurate results compared with other established methods.
Efficient model for detecting application layer distributed denial of service attacks Kareem, Morenikeji Kabirat; Aborisade, Olaniyi Dada; Onashoga, Saidat Adebukola; Sutikno, Tole; Olayiwola, Olaniyi Mathew
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.v12i1.3871

Abstract

The increasing advancement of technologies and communication infrastructures has been posing threats to the internet services. One of the most powerful attack weapons for disrupting web-based services is the distributed denial of service (DDoS) attack. The sophisticated nature of attack tools being created and used for launching attacks on target systems makes it difficult to distinguish between normal and attack traffic. Consequently, there is a need to detect application layer DDoS attacks from network traffic efficiently. This paper proposes a detection system coined eXtreme gradient boosting (XGB-DDoS) using a tree-based ensemble model known as XGBoost to detect application layer DDoS attacks. The Canadian institute for cybersecurity intrusion detection systems (CIC IDS) 2017 dataset consisting of both benign and malicious attacks was used in training and testing of the proposed model. The performance results of the proposed model indicate that the accuracy rate, recall, precision rate, and F1-score of XGB-DDoS are 0.999, 0.997, 0.995, and 0.996, respectively, as against those of k-nearest neighbor (KNN), support vector machine (SVM), principal component analysis (PCA) hybridized with XGBoost, and KNN with SVM. So, the XGB-DDoS detection model did better than the models that were chosen. This shows that it is good at finding application layer DDoS attacks.
Relay node placement in wireless sensor network for manufacturing industry Safiee, Rabiatul Adawiyah; Apandi, Nur Ilyana Anwar; Muhammad, Nor Aishah; Sheng, Wan Wing; Sarijari, Mohd Adib
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.v12i1.3978

Abstract

Relay nodes are necessary to maintain scalability and increase longevity as the number of manufacturing industrial sensors grows. In a fixed-budget circumstance, however, the cost of purchasing the bare minimum of relay nodes to connect the network may exceed the budget. Although it is hard to establish a network that connects all sensor nodes, in this case, a network with a high level of connection is still desirable. This paper proposes two metrics for determining the connectedness of a disconnected graph of sensor nodes and determining the optimum deployment method for relay nodes in a network with the highest connectedness while staying within a budget restriction. The metrics are the number of connected graph components and the size of the most significant connected graph component. Prim's algorithm and the approximation minimum spanning tree algorithm are applied to construct a disconnected graph and discover the best relay node placement to solve these two criteria. Compared to the other metrics, simulation findings suggest that prioritizing the most significant connected components in the disconnected graph can yield superior outcomes by deploying the fewest number of relay nodes while retaining the connectedness of the graph.
Performance analysis of CMOS based analog circuit design with PVR variation Prajapati, Pankaj P.; Kshatriya, Anilkumar J.; Bharvad, Sureshbhai L.; Upadhyay, Abhay B.
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.v12i1.4357

Abstract

Process, supply voltage, and temperature (PVT) are three important factors which contribute to performance variation of the complementary metal–oxide–semiconductor (CMOS) based analog circuits. In this paper, CMOS based analog circuit design with the PVT variation effects are explored. The effects of the PVT variation on the performance of CMOS based analog circuits are introduced. The optimization of CMOS based analog circuits such as differential amplifier (DA) and two-stage operational amplifier (op amp) circuits with PVT variations with different algorithms such as cockoo search (CS), particle swam optimization (PSO), hybrid CSPSO, and differential evaluation (DE) algorithms is presented. Each algorithm is implemented using the C programming language, interfaced with Ngspice circuit simulator, and tested on the Intel®core™ i5, 2.40 GHz processor with 8 GB internal RAM using the Ubuntu operating system (OS). The result shows PVT variation affects the performance of CMOS circuit.
Deep learning-based methods for anomaly detection in video surveillance: a review Berroukham, Abdelhafid; Housni, Khalid; Lahraichi, Mohammed; Boulfrifi, Idir
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.v12i1.3944

Abstract

Detecting anomalous events in videos is one of the most popular computer vision topics. It is considered a challenging task in video analysis due to its definition, which is subjective or context-dependent. Various approaches have been proposed to address the anomaly detection problems. These approaches vary from hand-crafted to deep learning. Many researchers have gone into determining the best approach for effectively detecting anomalies in video streams while maintaining a low false alarm rate. The results proved that approaches based on deep learning offer very interesting results in this field. In this paper, we review a family of video anomaly detection approaches based on deep learning techniques, which are compared in terms of their algorithms and models. Moreover, we have grouped state-of-the-art methods into different categories based on the approach adopted to differentiate between normal and abnormal events, and the underlying assumptions. Furthermore, we also present publicly available datasets and evaluation metrics used in existing works. Finally, we provide a comparison and discussion on the results of various approaches according to different datasets. This paper can be a good starting point for such researchers to understand this field and review existing work related to this topic.
A proposed software for controlling operating system-dependent functionality Abdulameer Alazawi, Sundos; Mahmood Hussien, Nadia; Makki Mohialden, Yasmin; Mohammed, Mostafa Abdulghafoor
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.v12i1.4536

Abstract

When the operating system environment temperature rises above safety, the CPU may become unresponsive or even malfunction. To address this problem, to achieve this goal a two-part system was designed. The first, consists of a controlled sensor that constantly monitors the room environment temperature and alerts the user if it rises above acceptable levels for computer use. The second part adopts a Python that uses the OS module, which provides a portable interface for OS-dependent tasks and shuts down the device to prevent it from behaving unexpectedly. A series of experiments at different temperatures demonstrated the ability of the device to alert the user.
Arabic vowels characterization and classification using the normalized energy in frequency bands Farchi, Mohamed; Tahiry, Karim; Mouhsen, Ahmed
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.v12i1.4395

Abstract

The main objective of this work is to conduct an acoustic study of Arabic vowels (/a/, /a:/, /u/, /u:/, /i/ and /i:/) in order to determine the most relevant characteristics that allow recognizing these vowels. The analysis of vowel spectrograms reveals that the energy distribution as a function of time and frequency clearly differs according to the considered vowel. Thus, we used the normalized energy in frequency bands to classify these vowels. Thereafter, we have exploited the obtained results to develop algorithms that allow the classification of vowels and the distinction of the long vowels from the short ones. The efficiency of these algorithms was evaluated by testing their performances on our Arabic corpus.
The software requirements process for designing a microcontroller-based voice-controlled system Hussien, Nadia Mahmood; Mohialden, Yasmin Makki; Akawee, Mustafa Mahmood; Mohammed, Mostafa Abdulghafoor
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.v12i1.4407

Abstract

Smartphones of today are capable of controlling motors, music systems, and lighting. This project's objective is to construct a robot car for the elderly and disabled that is based on the Arduino platform. Voice instructions can be used to wirelessly control the robotic car that the user is riding. The robot is able to move to the left and right, as well as forward and backward, and it can also stop. The voice-controlled robot vehicle built using Arduino and operated by an HC-05 module is connected to Bluetooth. The exact spoken commands are sent to the robot through the phone via an application that runs on android. The Arduino, which is in charge of controlling the robotic automobile, gets commands through a Bluetooth transceiver module, which then relays them to the Arduino. The hardware consists of an android phone, an android-powered motor drive, an Arduino, and Bluetooth. This system was developed with the help of Arduino C and the android-meets-robot framework. The primary goals of this piece of writing are to gain an understanding of how to create the criteria for a voice-controlled system that is based on Arduino.

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