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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 :
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Articles 64 Documents
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Search results for , issue "Vol 32, No 3: December 2023" : 64 Documents clear
Exploring the potential of skeleton and machine learning in classroom cheating detection Nha Tran; Minh Nguyen; Tri Le; Tuong Nguyen; Tinh Nguyen; Tuan Nguyen
Indonesian Journal of Electrical Engineering and Computer Science Vol 32, No 3: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v32.i3.pp1533-1544

Abstract

In recent years, there have been certain drawbacks in the behavior of students in school cultural activities, especially the frequent occurrence of cheating in exams. Although many manual cheating detection methods have been applied, cheating behaviors have become increasingly sophisticated and difficult to detect. This makes manual cheating detection methods unable to completely prevent cheating in exams. Therefore, applying advanced technologies to automatically detect cheating cases becomes necessary to help supervisors better control the exam process. In this study, we propose a model architecture to monitor students’ cheating activities during exams. Firstly, we apply YOLO - Pose to detect skeleton keypoints, which are then passed through machine learning models such as support vector machine (SVM), decision tree (DT) classifier, random forest (RF), extreme gradient bo osting (XGBoost), and propose the Ac Long short - term memory (LSTM) to detect cheating behavior. The experimental results show the feasibility of the model on various metrics. The model is tested on a dataset of cheating behaviors in the classroom, which is designed to simulate paper - based exams. Moreover, the results showed that the proposed method can detect cheating behavior in a short amount of time and can be deployed for real - world applications.
Implementation of a long range-based monitoring system for environmental remote safety schemes Mahmood Jalal Ahmad Alsammarraie; Adnan Hussein Ali; Aqeel A. Al-Hilali; Hind Q. Mohammad Monir; Mohannad Sameer Jabbar; Haitham Bashar Qasim
Indonesian Journal of Electrical Engineering and Computer Science Vol 32, No 3: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v32.i3.pp1462-1475

Abstract

The effects of poor air quality on people are profound. Air pollution and health issues are linked to millions of deaths. The World Health Organization (WHO)and the environmental protection agency (EPA)have produced several regulations and guidelines to control and enhanceair quality. Several authors have recently suggested low-cost tools for instantly assessing air quality. the abundance of inexpensive ways to assess air quality and collect sensor data. The design and employment of remote safety monitoring for humidity, temperature, and carbon monoxide has been merged into a single tool in this work. The results findings can be observed on the actual measured instrument’s organic light-emitting diode (OLED)show and the liquid crystal display (LCD)remote monitoring system. This device uses ESP32 microcontroller with long range (LoRa)wireless communication technology.The DHT22 sensor is used to detect humidity and temperature, while the MQ-7 sensor is used to monitor carbon monoxide levels. Testing measurements are calibrated using instruments that meet industrial standards (AS8700A CO meter and 4,000 NV weather tracker) used in environmental station. If the abnormalities in the recorded parameters are detected, then alert will be triggered. This instrument can help patients and workers to check their surroundings and provide remote monitoring to health service providers.
Improving graphics processing unit performance based on neural network direct memory access controller Santosh Kumar; Neelappa Neelappa; Saroja Bhusare; Veeramma Yatnalli
Indonesian Journal of Electrical Engineering and Computer Science Vol 32, No 3: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v32.i3.pp1476-1484

Abstract

In this paper proposes the design and implementation of the back propagation algorithm based neural network DMA (Direct Memory Access) Controller for use of multimedia applications. The proposed DMA controller work with the back propagation-training algorithm. The advantages of the back propagation algorithm it will be work on the gradient loss w.r.t the network weights. So this back propagation algorithm is used as training algorithm for the DMA controller. The proposed method is test with the different workload characteristics like heavy workload, medium workload and normal workload. The performance parameters are considered here is like accuracy, precision, recall and F1 score etc. The proposed method is compared with existing methods like CNN (Convolutional Neural Network), RNN (Recurrent Neural Network), LSTM (Long Sort term Memory) and GRU (Gated Recurrent Unit) etc. Finally, the proposed design will give the better performance than existing methods.
Restoration of the service and loss minimization in electrical distribution systems Ganney Poorna Chandra Rao; Pallikonda Ravi Babu
Indonesian Journal of Electrical Engineering and Computer Science Vol 32, No 3: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v32.i3.pp1267-1277

Abstract

Restoration of service during faults to healthy zones and the minimization of true or real power losses are the main aspects of the satisfactory operation of an electrical distribution system (EDS). These objectives can be achieved with artificially intelligent optimisation techniques through electrical distribution system reconfiguration. The restoration of service is an important part of ensuring a stable power supply. If there is a fault with the EDS, the damaged zone is separated, and the healthy system is restored without breaching limitations. In the distribution system, ohmic losses are 25-35%. It is essential to reconfigure the system toreduce these losses. In this paper, a hybrid artificial rabbits’optimisation and improved mayfly optimisation (ARO-IMO) technique is adopted for restoration of serviceand loss minimization. The method being suggested will be carried out on an IEEE 4-feeder network for restoration of service and on IEEE 33 and69 radial distribution networks (RDN) for diminution of losses.

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