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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 64 Documents
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Search results for , issue "Vol 29, No 1: January 2023" : 64 Documents clear
Increasing validation accuracy of a face mask detection by new deep learning model-based classification Mohanad Azeez Joodi; Muna Hadi Saleh; Dheyaa Jasim Kadhim
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp304-314

Abstract

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieved lower computational complexity and number of layers, while being more reliable compared with other algorithms applied to recognize face masks. The findings reveal that the model's validation accuracy reaches 97.55% to 98.43% at different learning rates and different values of features vector in the dense layer, which represents a neural network layer that is connected deeply of the CNN proposed model training. Finally, the suggested model enhances recognition performance parameters such as precision, recall, and area under the curve (AUC).
Automatic essay assessment in e-learning using winnowing algorithm Eka Larasati Amalia; Vivin Ayu Lestari; Vivi Nur Wijayaningrum; Ali Ar Ridla
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp572-582

Abstract

The pandemic has caused almost all educational institutions to use online learning media to support learning activities. E-learning is a technology that is widely used because it can accommodate all learning activities. However, in general, e-learning can only perform automatic assessments for multiple choice answers but not for essay answers, so that manual assessment by the teacher becomes difficult and takes a long time. In this study, the winnowing algorithm was applied to the automatic assessment process on students' essay answers by measuring their similarity to the teacher's answer key. The stages in the automatic assessment using the winnowing algorithm begin with forming a series of k-grams, calculating the hash value, forming a window from the hash value, calculating the fingerprint value, and calculating the Jaccard Coefficient to obtain the percentage of text similarity results. The test results show that the winnowing algorithm can provide good performance when the answers to questions are in the form of short entries with the number of hashes not smaller than the window value. Meanwhile, on questions with long answers, the winnowing algorithm can still work well with an average difference of 5.2% from the results of the assessment carried out by the teacher.
Proper insertion of DSTATCOM in distribution networks based on VSM with network reconfiguration Abdullah Fawzi Shafeeq; Inaam Ibrahim Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp66-74

Abstract

Voltage stability is necessary to maintain the grid system healthily. The load demand has been steadily increasing that causing high losses and voltage drops, endangering the system's stability. This study proposes the suitable insertion of distribution static compensator (DSTATCOM) based on voltage stability margin (VSM) with optimum network reconfiguration (ONR) to reduce losses and enhance the voltage profile. The findings are acquired utilizing recommended methodologies and test systems such as the IEEE-33 bus and 39 bus of an Iraqi distribution network, which are done using CYME and MATLAB software. The proposed approach may be able to solve the problem by aiding distribution network operators in estimating the size and location of DSTATCOM.
Wireless hand motion controlled robotic arm using flex sensors Zakiah Mohd Yusoff; Siti Aminah Nordin; Arni Munira Markom; Nurul Nadia Mohammad
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp133-140

Abstract

In today's world, in almost all industries, much of the work is performed by robots or robotic arms with varying degrees of freedom (DOF) as necessary. The aim of this study is to adjust the perception of remote controls for manually controlled robotic-arm operation. This paper offers a way of thinking and a way to eradicate the keys, joysticks and replace them with some of the more intuitive strategy that is to operate the full robotic arm by hand movements operators. The robotic arm is constructed in such a way that it consists of two movable fingers and other movement, which is, a spreading elbow and the up down movement. The robotic arm is designed to mimic the motions of human hands using a hand glove. The hand glove consists of 3 flex sensors for controlling the motions of the finger, the elbow, and other movements. Servo motors are the actuators used by the robotic arm. The proposed electronics device recognizes a basic hand gesture that will be made in real lifetime and will relay valued signals wirelessly through the RF module.
An adaptive algorithm based on principal component analysis-deep learning for anomalous events detection Zainab K. Abbas; Ayad A. Al-Ani
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp421-430

Abstract

One of the most often used applications of human activity detection is anomaly detection, which is covered in this paper. Providing security for a person is a key issue in every community nowadays because of the constantly expanding activities that pose danger, from planned violence to harm caused by an accident. Existing classical closed-circuit television considered is insufficient since it needs a person to stay awake and constantly monitor the cameras, which is expensive. In addition, a person's attention decreases after a certain time. For these reasons, the development of an automated security system that can identify suspicious activities in real-time and quickly aid victims is required. Because identifying activity must be with high accuracy, and in the shortest possible time. We adopt an adaptive algorithm based on the combination of machine learning (ML), principal component analysis (PCA) and deep learning (DL). The UCF-crime dataset was used for the experimentation in this work. Where the area under the curve (AUC) with the proposed approach was equal to 94.21% while the detection accuracy was equal to 88.46% on the test set database. The suggested system has demonstrated its robustness and accomplishment of the best accuracy when compared with earlier designed systems.
Construct an efficient distributed denial of service attack detection system based on data mining techniques Dhurgham Kareem Gharkan; Amer A. Abdulrahman
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp591-597

Abstract

Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynamically and periodically by evaluating the set of attackers of the current node with its neighbors. We use dataset named CICDDoS2019 that contains on binary classes benign and DDoS. Performance has evaluated by applying data mining algorithms as well as applying the best features to discover potential attack classes.
Hyperspectral image classification using Hyb-3D convolution neural network spectral partitioning Easala Ravi Kondal; Soubhagya Sankar Barpanda
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp295-303

Abstract

Hyperspectral image classification (HSIC) on remote sensing imaging has brought immersive achievement using artificial intelligence technology. In deep learning convolution neural networks (CNN), 2D-CNN, and 3D-CNN methods are widely used to classify the spectral-spatial bands of hyperspectral images (HSI). The proposed Hybrid 3D-CNN (H3D-CNN) model framework for deeper features extraction predicts classification accuracy in supervised learning. The model reduces the narrow gap between supervised and unsupervised learning and the complexity and cost of the previous models. The HSI classification analysis is carried out on real-world data sets of Indian pines Salinas datasets captured by Airborne visible, infrared imaging spectrometer (AVIRIS) sensors that performed superior classification accuracy results.
Design and realization of a dual-wavelength low level light therapy for acne and face rejuvenation treatment Napat Watjanatepin; Paiboon kiatsookkanatorn; Chaiyant Boonmee; Sarayoot Thongkullaphat; Tuanjai Archevapanich; Patcharanan Sritanauthaikorn; Khanittha Wannakam
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp147-160

Abstract

Low-level light therapy (LLLT) uses the light of wavelength between 400–700 nm to treat acne, reduce inflammation, stimulate collagen production, and rejuvenate the facial skin. This study designed and constructed a dual-wavelength LED LLLT device for the facial treatment. The light spectrum, power density, uniformity, stability, and safety of the device were analyzed. The proposed system consisted of an LED array with 415 and 633 nm wavelengths. Human machine interface with embedded system was used to control light intensity and treatment time. The phototherapy device is designed to be curvaceously sized to suit the face shape of Asian people. The results showed that the LLLT device emitted 633±5 nm red and 415±5 nm blue light with a linear adjustable light power density of 0-18.56 mW/cm2 and 0-3.70 mW/cm2, respectively. The spectrum distribution of the red and blue light was relatively constant over 30 minutes of operation. The uniformity and stability of red spectrum were about 89.9% and 95.08% and blue spectrum were 87.6% and 97.08%, respectively. The experimental face’s temperature was below 31.5 . For the future study, the LED phototherapy device will be applied for clinical research in collaboration with dermatologists.Low-level light therapy (LLLT) uses the light of wavelength between 400–700 nm to treat acne, reduce inflammation, stimulate collagen production, and rejuvenate the facial skin. This study designed and constructed a dual-wavelength LED LLLT device for the facial treatment. The light spectrum, power density, uniformity, stability, and safety of the device were analyzed. The proposed system consisted of an LED array with 415 and 633 nm wavelengths. Human machine interface with embedded system was used to control light intensity and treatment time. The phototherapy device is designed to be curvaceously sized to suit the face shape of Asian people. The results showed that the LLLT device emitted 633±5 nm red and 415±5 nm blue light with a linear adjustable light power density of 0-18.56 mW/cm2 and 0-3.70 mW/cm2, respectively. The spectrum distribution of the red and blue light was relatively constant over 30 minutes of operation. The uniformity and stability of red spectrum were about 89.9% and 95.08% and blue spectrum were 87.6% and 97.08%, respectively. The experimental face’s temperature was below 31.5 . For the future study, the LED phototherapy device will be applied for clinical research in collaboration with dermatologists.
Near-field microwave focusing evaluation of dielectric lens antenna for human body model Amirah Abd Rahman; Kamilia Kamardin; Yoshihide Yamada; Masaharu Takahashi
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp161-173

Abstract

Various small focus spot applicators are being investigated for hyperthermia therapy, which requires microwave concentration to heat tumors in the human body. Dielectric lens antenna is frequency independent and has strong focusing capability to achieve a very small focusing spot. In this paper, lenses with diameters of 30, 50 and 70 cm were designed to evaluate the size of the focal spot in the human body model. The electromagnetic simulator, FEKO was used to generate rays and near-field focusing data of dielectric lenses at a frequency of 2.45 GHz. The simulated focal spot sizes agreed well with the theoretical values. An analytical investigation into the power at the focal spot was conducted using the proposed power relations of the focused lens novel equation. The theoretical propagation loss is used to represent the power density degradation at the focal spot caused by microwave absorption by the human body. The simulation results of the focused lens in the human body indicated that the 30 cm lens achieved a larger focal spot with a greater focusing power, 0.714 mW compared to the 70 cm lens, which achieved a smaller focal spot but a lower focusing power, which was 0.393 mW.
D flip-flop design by adiabatic technique for low power applications Minakshi Sanadhya; Devendra Kumar Sharma
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp141-146

Abstract

Indigital circuits, energy reduction is the most important parameter in the design of handy and battery-operated devices. Flip- flop is an important component in any digital system. By improving the performance of flip-flop, complete system performance is better. This paper addresses the design of D flip-flop using direct current diode-based positive feedback adiabatic logic (DC-DB PFAL) at various frequencies at 45nm technology node. Further, the layout for the proposed design is also presented. The performance analysis is carried out for delay, power dissipation, power delay product and transistor count. Circuit simulation is done by using cadence virtuoso tool at 10 MHz and 100 MHz frequencies. The results show an improvement in power dissipation of 18% with less transistors count compared to exiting designs in the literature.

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