Bulletin of Electrical Engineering and Informatics最新文献_第5页

Palmprint recognition system using VR-LBP and KAZE features for better recognition accuracy 利用 VR-LBP 和 KAZE 特征提高识别准确率的掌纹识别系统

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.4739

Noor Aldeen A. Khalid, Muhammad Imran Ahmad, Tan Shie Chow, Thulfiqar H. Mandeel, Ibrahim Majid Mohammed, Mokhalad Abdulameer Kadhim Alsaeedi

{"title":"Palmprint recognition system using VR-LBP and KAZE features for better recognition accuracy","authors":"Noor Aldeen A. Khalid, Muhammad Imran Ahmad, Tan Shie Chow, Thulfiqar H. Mandeel, Ibrahim Majid Mohammed, Mokhalad Abdulameer Kadhim Alsaeedi","doi":"10.11591/eei.v13i2.4739","DOIUrl":"https://doi.org/10.11591/eei.v13i2.4739","url":null,"abstract":"The palmprint recognition system has gained significant attention in security and law enforcement due to its unique features, such as principle lines, ridges, and wrinkles. However, many existing methods for extracting these features have limited accuracy, especially when the image illumination varies or the size of the processed pixels increases. Previous studies have shown that the local binary patterns (LBP) algorithm is effective for palmprint recognition due to the rich texture characteristics of a palmprint. In this paper, we propose a new technique for a robust contact-based palmprint identification system using vertical-LBP and KAZE feature detection. Our technique aims to improve recognition accuracy by using KAZE, which is a nonlinear diffusion approach that extracts nonlinear features from the evolution of the illuminance of an image. We also utilize principal component analysis (PCA) to reduce the dimensionality of the generated descriptor vector elements. The proposed method was tested on the PolyU database and achieved recognition accuracy of 99.7%.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-time monitoring tool for heart rate and oxygen saturation in young adults 青壮年心率和血氧饱和度实时监测工具

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.6371

Siti Fatimah Abdul Razak, Yap Jia Wee, S. Yogarayan, Sharifah Noor Masidayu Sayed Ismail, Mohd Fikri Azli Abdullah

{"title":"Real-time monitoring tool for heart rate and oxygen saturation in young adults","authors":"Siti Fatimah Abdul Razak, Yap Jia Wee, S. Yogarayan, Sharifah Noor Masidayu Sayed Ismail, Mohd Fikri Azli Abdullah","doi":"10.11591/eei.v13i2.6371","DOIUrl":"https://doi.org/10.11591/eei.v13i2.6371","url":null,"abstract":"Health monitoring is crucial to maintain optimal well-being, especially for young adults. Wearable sensors have become popular for collecting healthcare data, but there are concerns regarding their reliability and safety, particularly with wireless sensors that use radio-frequency (RF) based devices. Researchers have proposed real-time monitoring systems for measuring heart rate beats per minute (BPM) and blood oxygen saturation (SpO2) saturation levels, but more studies are needed to determine the accuracy and user acceptance of these tools among young adults. To address these concerns, this study proposes a real-time monitoring tool that incorporates MAX 30100 sensors to collect heart rate BPM and SpO2 data. The collected data is then connected to a visualization platform, i.e., InfluxDB and Grafana, to provide valuable insights of the body’s physiological state. By testing the feasibility and usability of the tool, we found motivating differences in resting heart rates and changes in heart rate after activity between male and female participants. By developing this real-time monitoring tool and investigating gender-specific differences in heart rate and activity-induced changes, our study contributes to the advancement of health monitoring technologies for young adults, ultimately promoting personalized healthcare and well-being.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140355731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A low-cost Wi-Fi smart home socket using internet of things 使用物联网的低成本 Wi-Fi 智能家居插座

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.6521

Ahmad Danish Suffian Ahmad Taufik, R. Abdullah, A. Jaafar, Nik Nur Shaadah Nik Dzulkefli, S. I. Ismail

{"title":"A low-cost Wi-Fi smart home socket using internet of things","authors":"Ahmad Danish Suffian Ahmad Taufik, R. Abdullah, A. Jaafar, Nik Nur Shaadah Nik Dzulkefli, S. I. Ismail","doi":"10.11591/eei.v13i2.6521","DOIUrl":"https://doi.org/10.11591/eei.v13i2.6521","url":null,"abstract":"With the emergence of smart home appliances, traditional power sockets are becoming less compatible with modern living styles. Furthermore, modern commercialized sockets are expensive and unaffordable. This project presents the development of a low-cost Wi-Fi smart home socket using internet of things (IoT) technology that is user-friendly for smartphone users to control home appliances. Smart home socket devices can turn on and off power outlets automatically from any location if they are linked to the internet and providing the user with more convenience and energy savings. This project uses a node microcontroller unit (NodeMCU) Wi-Fi module (ESP8266) as the main microcontroller unit to connect to a cloud platform. It also uses a mobile phone application to send instructions to the microcontroller for turning on and off household appliances remotely through a smart socket. The switching mechanism is monitored and controlled through the Blynk platform. A 4-channel relay module is used to transition DC current loads to AC current loads in order to activate switching processes. According to the study’s findings, the Wi-Fi smart home socket system is able to save on excessive usage of electrical appliances while also increasing electrical appliance safety.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140356747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Definite time over-current protection on transmission line using MATLAB/Simulink 使用 MATLAB/Simulink 对输电线路进行定时过流保护

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5301

T. A. Taha, Hussein I. Zaynal, A. T. T. Hussain, H. Desa, Faris Hassan Taha

引用次数: 0

Squirrel search method for deep learning-based anomaly identification in videos 基于深度学习的视频异常识别松鼠搜索法

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5933

Laxmikant Malphedwar, Thevasigamani Rajesh Kumar

{"title":"Squirrel search method for deep learning-based anomaly identification in videos","authors":"Laxmikant Malphedwar, Thevasigamani Rajesh Kumar","doi":"10.11591/eei.v13i2.5933","DOIUrl":"https://doi.org/10.11591/eei.v13i2.5933","url":null,"abstract":"The monitoring of human behavior and traffic surveillance in various locations has become increasingly important in recent years. However, identifying abnormal activity in real-world settings is a challenging task due to the many different types of worrisome and abnormal actions, including theft, violence, and accidents. To address this issue, this paper proposes a new framework for deep learning-based anomaly identification in videos using the squirrel search algorithm and bidirectional long short-term memory (BiLSTM). The proposed method combines the squirrel search algorithm, an optimization technique inspired by nature, with BiLSTM for anomaly recognition. The framework uses the knowledge gained from a sequence of frames to categorize the video as either typical or abnormal. The proposed method was exhaustively tested in several benchmark datasets for anomaly detection to confirm its functionality in challenging surveillance circumstances. The results show that the proposed framework outperforms existing methods in terms of area under curve (AUC) values, with a test set AUC score of 93.1%. The paper also discusses the importance of feature selection and the benefits of using BiLSTM over traditional unidirectional long short-term memory (LSTM) models for anomaly detection in videos. Overall, the proposed framework provides a highly precise computerization of the system, making it an effective tool for identifying abnormal human behavior in surveillance footage.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140352951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and implementation of energy-efficient hybrid data aggregation in heterogeneous wireless sensor network 异构无线传感器网络中高能效混合数据聚合的设计与实现

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5582

M. M. Al-Heeti, Jamal A. Hammad, Ahmed Shamil Mustafa

{"title":"Design and implementation of energy-efficient hybrid data aggregation in heterogeneous wireless sensor network","authors":"M. M. Al-Heeti, Jamal A. Hammad, Ahmed Shamil Mustafa","doi":"10.11591/eei.v13i2.5582","DOIUrl":"https://doi.org/10.11591/eei.v13i2.5582","url":null,"abstract":"Heterogeneous wireless sensor network (HWSN) is a trending technology in both the industrial and academic sectors, consisting of a large number of interconnected sensors. However, higher energy consumption and delay are significant drawbacks of this technology in applications such as military, healthcare, and industrial automation. The main objective of this research is to enhance the energy efficiency of HWSN using a clustering technique. In this article, a novel approach, namely power optimization and hybrid data aggregation (POHDA), is proposed to address these challenges in HWSN. POHDA-HWSN focuses on power optimization and congestion avoidance through effective CH selection using hybrid data aggregation based on parameters such as residual energy, distance, mobility, threshold value of the node, and latency. By weight-based effective cluster head (CH) selection, the energy consumption, end-to-end delay, and overhead during communication are reduced in this network. The POHDA-HWSN approach considers specific parameters to compare the results and outcomes with earlier research such as HCCS-WSN, FMCA-WSN, and APCC-WSN. The results prove that the proposed POHDA-HWSN approach achieves higher energy efficiency and delivery ratio.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simulation of autonomous navigation of turtlebot robot system based on robot operating system 基于机器人操作系统的海龟机器人自主导航仿真系统

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.6419

M. Ghazal, Murtadha Al-Ghadhanfari, N. Waisi

引用次数: 0

Reliability analysis in distribution system by deep belief neural network 利用深度信念神经网络进行配电系统可靠性分析

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.6324

Likhitha Ramalingappa, Prathibha Ekanthaiah, MD Irfan Ali, Aswathnarayan Manjunatha

{"title":"Reliability analysis in distribution system by deep belief neural network","authors":"Likhitha Ramalingappa, Prathibha Ekanthaiah, MD Irfan Ali, Aswathnarayan Manjunatha","doi":"10.11591/eei.v13i2.6324","DOIUrl":"https://doi.org/10.11591/eei.v13i2.6324","url":null,"abstract":"Rapid increase in the usage of intermittent renewable energy, ongoing changes in electrical power system structure and operational needs posing growing problems while ensuring adequate service reliability and retaining the quality of power. Power system reliability is a pertinent factor to consider while planning, designing, and operating distribution systems. utilities are obligated to offer their customers uninterrupted electrical service at the least cost while maintaining a satisfactory level of service quality. The important metrics for gauging the effect of distributed renewable energy on distribution networks is reliability analysis. Reliability analysis in distribution systems involves evaluating the performance and robustness of electrical distribution networks. An artificial intelligence approach is implemented in this paper to improve reliability analysis with dispersed generations in distribution network. Deep belief neural networks (DBNNs) are a type of artificial neural network that can be used for various tasks, including analyzing complex data such as those found in power distribution systems. This paper integrated a DBNN using a particle swarm optimization (PSO) technique. The proposed model performance is assessed using mean square error, mean absolute error, root mean square error, and R squared error. The findings reveal that reliability analysis with this novel technique is more accurate.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140354292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel women's ovulation prediction through salivary ferning using the box counting and deep learning 利用盒式计数和深度学习通过唾液拈取预测女性排卵的新方法

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5847

Heri Pratikno, Mohd Zamri Ibrahim, J. Jusak

{"title":"A novel women's ovulation prediction through salivary ferning using the box counting and deep learning","authors":"Heri Pratikno, Mohd Zamri Ibrahim, J. Jusak","doi":"10.11591/eei.v13i2.5847","DOIUrl":"https://doi.org/10.11591/eei.v13i2.5847","url":null,"abstract":"There are several methods to predict a woman's ovulation time, including using a calendar system, basal body temperature, ovulation prediction kit, and OvuScope. This is the first study to predict the time of ovulation in women by calculating the results of detecting the fractal shape of the full ferning (FF) line pattern in salivary using pixel counting, box counting, and deep learning for computer vision methods. The peak of a woman's ovulation every month in her menstrual cycle occurs when the number of ferning lines is the most numerous or dense, and this condition is called FF. In this study, the computational results based on the visualization of the fractal shape of the salivary ferning line pattern from the pixel-counting method have an accuracy of 80%, while the fractal dimensions achieved by the box-counting are 1.474. On the other hand, using the deep learning image classification, we obtain the highest accuracy of 100% with a precision value of 1.00, recall of 1.00, and F1-score 1.00 on the pre-trained network model ResNet-18. Furthermore, visualization of the ResNet-34 model results in the highest number of patches, i.e., 586 patches (equal to 36,352 pixels), by applying fern-like lines pattern detection with windows size 8x8 pixels.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140354527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Portable smart attendance system on Jetson Nano 基于 Jetson Nano 的便携式智能考勤系统

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.6061

Edward Yose, Victor Victor, Nico Surantha

{"title":"Portable smart attendance system on Jetson Nano","authors":"Edward Yose, Victor Victor, Nico Surantha","doi":"10.11591/eei.v13i2.6061","DOIUrl":"https://doi.org/10.11591/eei.v13i2.6061","url":null,"abstract":"The masked face recognition-based attendance management system is an important biometric-based attendance tracking solution, especially in light of the COVID-19 pandemic. Despite the use of various methods and techniques for face detection and recognition, there currently needs to be a system that can accurately recognize individuals while they are wearing a mask. This system has been designed to overcome the challenges of widespread mask use, impacting the effectiveness of traditional face recognition-based attendance systems. The proposed system uses an innovative method that recognizes individuals even while wearing a mask without the need for removal. With its high compatibility and real-time operation, it can be easily integrated into schools and workplaces through an embedded system like the Jetson Nano or conventional computers executing attendance applications. This innovative approach and its compatibility make it a desirable solution for organizations looking to improve their attendance-tracking process. The Experimental results indicates using maximum resources possible the execution time needed on Jetson Nano is 15 to 22 seconds and 14 to 18 seconds respectively and the average frame capture if there are at least one face detected on Jetson Nano is 3-4 frames.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140356698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0