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Face and number plate recognition for car anti-theft 人脸和车牌识别用于汽车防盗
CTU Journal of Innovation and Sustainable Development Pub Date : 2023-10-16 DOI: 10.22144/ctujoisd.2023.041
Quoc Bao Truong, Tan-Loc Tran, Thanh Tan-Kiet Nguyen, Huu Cuong Nguyen
{"title":"Face and number plate recognition for car anti-theft","authors":"Quoc Bao Truong, Tan-Loc Tran, Thanh Tan-Kiet Nguyen, Huu Cuong Nguyen","doi":"10.22144/ctujoisd.2023.041","DOIUrl":"https://doi.org/10.22144/ctujoisd.2023.041","url":null,"abstract":"Smart parking systems along with that is continuous development of new technologies, are widely applied to improve our lives. It can also add new technologies with advanced functions making it a multi-functional management system. Thanks to the anti-theft technologies that are installed, modern cars are significantly more difficult to steal than they once were. However, electrical systems can still experience issues, though and malfunction at some point. This paper suggests using video image recognition technology, at car parks and parking lots as an anti-theft solution, alerting the presence of the non-owner of vehicle in the driver’s seat. The system automatically predicts whether the driver is valid with the registration number plate. The image of the car is captured by the camera at the entrance gates of the parking lot. The proposed algorithm includes face recognition in images, building a deep learning convolutional network that classifies faces (subscriber’s images); using Cascade trainer to train number plate object recognition, vehicle number recognition through character recognition technique. The system can recognize reality through a personal computer connected to the camera at the scene or through photos and video files. Result, the model can face recognition and match to license plate in at a moment.","PeriodicalId":310835,"journal":{"name":"CTU Journal of Innovation and Sustainable Development","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136077691","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: 1
Analysis of printed document identification based on Deep Learning 基于深度学习的打印文档识别分析
CTU Journal of Innovation and Sustainable Development Pub Date : 2023-10-16 DOI: 10.22144/ctujoisd.2023.042
Dinh Thong Nguyen, Phu Quang Nguyen, Hoang Bao An Mai
{"title":"Analysis of printed document identification based on Deep Learning","authors":"Dinh Thong Nguyen, Phu Quang Nguyen, Hoang Bao An Mai","doi":"10.22144/ctujoisd.2023.042","DOIUrl":"https://doi.org/10.22144/ctujoisd.2023.042","url":null,"abstract":"In this study, we investigate the effectiveness of ResNet, a deep neural network architecture, for a deep learning approach to address the problem of printed document identification. ResNet is known for its ability to handle the vanishing gradient problem and learn highly representative features. Multiple variations of ResNet have been applied, including ResNet50, ResNet101, and ResNet152, which provide the backbone architecture of our classification model and are trained on a comprehensive dataset of microscopic printed images containing some microscopic printing patterns from various source printers. We also incorporate Mix-up augmentation, a technique that generates virtual training samples by interpolating pairs of images and labels, to further enhance the performance and generalization capability of the model. The experimental results showed that ResNet101 and ResNet152 variants outperformed in accurately distinguishing printer sources based on microscopic printed patterns. We developed a mobile app to test the feasibility of our findings in practice. In conclusion, this study aims to lay the groundwork for creating a sufficiently pre-trained model with accurate performance of identification that can be deployed on mobile devices to detect the printed sources of documents.","PeriodicalId":310835,"journal":{"name":"CTU Journal of Innovation and Sustainable Development","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136183411","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
Application of IoT technology on control system and monitoring for Cucumis Melo L. grown in greenhouse 物联网技术在温室甜瓜控制系统与监控中的应用
CTU Journal of Innovation and Sustainable Development Pub Date : 2023-10-16 DOI: 10.22144/ctujoisd.2023.037
Lam Minh Dung, Quoc Bao Truong, Hoang Dung Nguyen, Van Vu Lam
{"title":"Application of IoT technology on control system and monitoring for Cucumis Melo L. grown in greenhouse","authors":"Lam Minh Dung, Quoc Bao Truong, Hoang Dung Nguyen, Van Vu Lam","doi":"10.22144/ctujoisd.2023.037","DOIUrl":"https://doi.org/10.22144/ctujoisd.2023.037","url":null,"abstract":"In this paper, we propose developing a system for optimally watering Cucumis Melo L. crops based on an application Internet of Things (IoT). The three components are hardware, a web application, and a mobile application. The first component was designed and implemented in control box hardware connected to collect crop datas. Soil moisture sensors are used to monitor the greenhouse, connected to the control box. The second component is a web-based application that was designed and implemented to manipulate the crop data and field information. This component applied data mining to analyze the data for predicting suitable temperature, humidity, and soil moisture for optimal future management of crop growth. The final component is mainly used to control crop watering through a mobile application on a smartphone. This allows either automatic or manual control of the user. The automatic control uses data from soil moisture sensors for water. The results showed the implementation to be useful in agriculture. The moisture content of the soil was maintained appropriately for Cucumis Melo L. growth, reducing costs and increasing agricultural productivity. Moreover, this work represents improvements to agriculture through digital innovation.","PeriodicalId":310835,"journal":{"name":"CTU Journal of Innovation and Sustainable Development","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136183873","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
Factorizing social advanced aspects in modern life on human health 将社会先进方面纳入现代生活对人体健康的影响
CTU Journal of Innovation and Sustainable Development Pub Date : 2023-10-16 DOI: 10.22144/ctujoisd.2023.034
Phan Yen Ngan Nguyen, Hai Dung Dinh, Hong Ngoc Tran
{"title":"Factorizing social advanced aspects in modern life on human health","authors":"Phan Yen Ngan Nguyen, Hai Dung Dinh, Hong Ngoc Tran","doi":"10.22144/ctujoisd.2023.034","DOIUrl":"https://doi.org/10.22144/ctujoisd.2023.034","url":null,"abstract":"The emergence of technology has brought about a dramatic shift in different aspects of life, especially the aspect of societal advancement. As people adapt to such transformation, it is undoubted that their lifestyles adapt as well. However, whether such changes oppose the well-being of an individual and whether there is a relationship between daily habits and health condition is an interesting topic that this research is going to focus on. Meanwhile, the benefits of implementing data analysis have been proven regarding understanding statistical problems. On such account, this work is going to use the powerful method of data analysis into investigating the relationship between lifestyle and health conditions, with the practice of big data sets deploying R programming language. The procedure from gathering to interpreting data is going to be introduced, and the result is then placed in comparison with related existing studies. By doing so, it has shown that the result has reflected accurately the topics and thus, given evidence for the potential of analyzing the connection between habitual practice and health status.","PeriodicalId":310835,"journal":{"name":"CTU Journal of Innovation and Sustainable Development","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136183606","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
An interpretable approach for trustworthy intrusion detection systems against evasion samples 一种针对逃避样本的可信入侵检测系统的可解释方法
CTU Journal of Innovation and Sustainable Development Pub Date : 2023-10-16 DOI: 10.22144/ctujoisd.2023.030
Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham
{"title":"An interpretable approach for trustworthy intrusion detection systems against evasion samples","authors":"Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham","doi":"10.22144/ctujoisd.2023.030","DOIUrl":"https://doi.org/10.22144/ctujoisd.2023.030","url":null,"abstract":"In recent years, Deep Neural Networks (DNN) have demonstrated remarkable success in various domains, including Intrusion Detection Systems (IDS). The ability of DNN to learn complex patterns from large datasets has significantly improved IDS performance, leading to more accurate and efficient threat detection. Despite their effectiveness, DNN models exhibit vulnerabilities to adversarial attacks, where malicious inputs are specifically crafted to deceive the models and evade detection. This paper provides insights into the effectiveness of deep learning-based IDS (DL-IDS) against adversarial example (AE) attacks. We tackle the weaknesses of DNN in detecting adversarial attacks by proposing the Convolutional Neural Network (CNN), which serves as an AE detector. We also utilize one of the XAI techniques, specifically SHAP, to enhance the transparency of the AE detector. Our results show that the AE detector has obvious effects for detecting adversarial examples and achieves an impressive 99.46% accuracy in our experimental environment.","PeriodicalId":310835,"journal":{"name":"CTU Journal of Innovation and Sustainable Development","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136183418","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
Impact of dimensionality reduction techniques on student performance prediction using machine learning 使用机器学习的降维技术对学生成绩预测的影响
CTU Journal of Innovation and Sustainable Development Pub Date : 2023-10-16 DOI: 10.22144/ctujoisd.2023.039
Koushik Roy, Huu-Hoa Nguyen, Dewan Md. Farid
{"title":"Impact of dimensionality reduction techniques on student performance prediction using machine learning","authors":"Koushik Roy, Huu-Hoa Nguyen, Dewan Md. Farid","doi":"10.22144/ctujoisd.2023.039","DOIUrl":"https://doi.org/10.22144/ctujoisd.2023.039","url":null,"abstract":"This study addresses the crucial issue of predicting student performance in educational data mining (EDM) by proposing an Adaptive Dimensionality Reduction Algorithm (ADRA). ADRA efficiently reduces the dimensionality of student data, encompassing various academic, demographic, behavioral, social, and health-related features. It achieves this by iteratively selecting the most relevant features based on a combined normalized mean rank of five feature ranking methods. This reduction in dimensionality enhances the performance of predictive models and provides valuable insights into the key factors influencing student performance. The study evaluates ADRA using four different student performance datasets and six machine learning algorithms, comparing it to three existing dimensionality reduction methods. The results show that ADRA achieves an average dimensionality reduction factor of 6.2 while maintaing comprable accuracy with other mehtods.","PeriodicalId":310835,"journal":{"name":"CTU Journal of Innovation and Sustainable Development","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136183874","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
New data about library service quality and convolution prediction 图书馆服务质量与卷积预测的新数据
CTU Journal of Innovation and Sustainable Development Pub Date : 2023-10-16 DOI: 10.22144/ctujoisd.2023.032
Minh Tuan Nguyen, Meesad Phayung, Van Hieu Duong, Maliyaem Maleerat
{"title":"New data about library service quality and convolution prediction","authors":"Minh Tuan Nguyen, Meesad Phayung, Van Hieu Duong, Maliyaem Maleerat","doi":"10.22144/ctujoisd.2023.032","DOIUrl":"https://doi.org/10.22144/ctujoisd.2023.032","url":null,"abstract":"Library service quality, one of the key performance indicators of service qualities in universities, has been considered deeply in management strategies as part of the Fourth Industrial Revolution, especially, after the Covid-19 pandemic. We undertook a survey around Universities in Ho Chi Minh City and Tien Giang University, Vietnam focused on freshmen and sophomores to assess library service quality for improving the learning service quality. Machine learning has been deployed for predicting the library service, quality, and has been adopted successfully in depicting the assessment results. To perform the effectiveness of data, the Convolution Bidirectional Long-Short Term Memory (Conv-BiLSTM), and Convolution Bidirectional Gated Recurrent Unit (ConvBiGRU) were used. The models have illustrated appropriate performances when providing sufficient accuracy and extracting the prediction of the output.","PeriodicalId":310835,"journal":{"name":"CTU Journal of Innovation and Sustainable Development","volume":"271 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136183875","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
An environment monitoring system for a rice production model adaptive to climate change in the Mekong Delta of Viet Nam 越南湄公河三角洲适应气候变化的水稻生产模式环境监测系统
CTU Journal of Innovation and Sustainable Development Pub Date : 2023-10-16 DOI: 10.22144/ctujoisd.2023.044
Minh Thai Truong, Dai Nghia Nguyen, Minh Qui Trinh, Khoi Nghia Nguyen, Huu Thien Nguyen, Quy Khang Huynh, Ca Luu, Huynh Tram Vo
{"title":"An environment monitoring system for a rice production model adaptive to climate change in the Mekong Delta of Viet Nam","authors":"Minh Thai Truong, Dai Nghia Nguyen, Minh Qui Trinh, Khoi Nghia Nguyen, Huu Thien Nguyen, Quy Khang Huynh, Ca Luu, Huynh Tram Vo","doi":"10.22144/ctujoisd.2023.044","DOIUrl":"https://doi.org/10.22144/ctujoisd.2023.044","url":null,"abstract":"This article presents an environment monitoring model for agricultural production applied to farmers in the Mekong Delta, Viet Nam. The proposed model's special feature is a system combining techniques such as IoT, agent-based, sensor networks, and data warehouses. Successfully deploying the model in monitoring the water level, and the environmental factors of the rice soil such as NPK, pH, EC, temperature, and soil moisture not only aids managers and farmers monitor environmental quality indicators in real time, but also experts to analyze data, give warnings and appropriate response solutions in agricultural production according to the pivot strategy towards Agriculture 4.0 proposed by the Minister of the Ministry of Agriculture and Rural Development of Viet Nam.","PeriodicalId":310835,"journal":{"name":"CTU Journal of Innovation and Sustainable Development","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136183872","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
Career path prediction using XGBoost Model and students’ academic results 基于XGBoost模型和学生学业成绩的职业道路预测
CTU Journal of Innovation and Sustainable Development Pub Date : 2023-10-16 DOI: 10.22144/ctujoisd.2023.036
Hong Quan Nguyen, Duc Dang Khoi Nguyen, Tan Duy Le, An Mai, Kha Tu Huynh
{"title":"Career path prediction using XGBoost Model and students’ academic results","authors":"Hong Quan Nguyen, Duc Dang Khoi Nguyen, Tan Duy Le, An Mai, Kha Tu Huynh","doi":"10.22144/ctujoisd.2023.036","DOIUrl":"https://doi.org/10.22144/ctujoisd.2023.036","url":null,"abstract":"This paper proposes an approach for constructing a system for career prediction by applying the eXtreme Gradient Boosting (XGBoost) Decision Tree model to the academic results of Ho Chi Minh International University’s School of Computer Science and Engineering graduates in the past 5 years. Initially, the dataset is cleaned up and normalized to be usable for the prediction algorithm with the help of Python 3 programming language. It is then split into 2 subsets: one for training (80 percent) and the other for testing (20 percent). After that, the algorithm uses the training subset to build the classification model. Finally, the testing subset is loaded into the model to predict each student’s career path based on the respective inputs and hyper-parameters tuning is employed to boost the model’s accuracy. By utilizing this solution, the problem related to predicting students’ future career paths based on their performance throughout their years studying at the university can be adequately addressed and handled.","PeriodicalId":310835,"journal":{"name":"CTU Journal of Innovation and Sustainable Development","volume":"13 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136183602","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
Exploring MediaPipe optimization strategies for real-time sign language recognition 探索实时手语识别的MediaPipe优化策略
CTU Journal of Innovation and Sustainable Development Pub Date : 2023-10-16 DOI: 10.22144/ctujoisd.2023.045
Phuoc Thanh Nguyen, Thanh Hoang Nguyen, Ngoc Xuan Nguyen Hoang, Huynh Thanh Binh Phan, Hoang Son Hai Vu, Hieu Nhan Huynh
{"title":"Exploring MediaPipe optimization strategies for real-time sign language recognition","authors":"Phuoc Thanh Nguyen, Thanh Hoang Nguyen, Ngoc Xuan Nguyen Hoang, Huynh Thanh Binh Phan, Hoang Son Hai Vu, Hieu Nhan Huynh","doi":"10.22144/ctujoisd.2023.045","DOIUrl":"https://doi.org/10.22144/ctujoisd.2023.045","url":null,"abstract":"The present study meticulously investigates optimization strategies for real-time sign language recognition (SLR) employing the MediaPipe framework. We introduce an innovative multi-modal methodology, amalgamating four distinct Long Short-Term Memory (LSTM) models dedicated to processing skeletal coordinates ascertained from the MediaPipe framework. Rigorous evaluations were executed on esteemed sign language datasets. Empirical findings underscore that the multi-modal approach significantly elevates the accuracy of the SLR model while preserving its real-time capabilities. In comparative analyses with prevalent MediaPipe-based models, our multi-modal strategy consistently manifested superior performance metrics. A distinguishing characteristic of this approach is its inherent adaptability, facilitating modifications within the LSTM layers, rendering it apt for a myriad of challenges and data typologies. Integrating the MediaPipe framework with real-time SLR markedly amplifies recognition precision, signifying a pivotal advancement in the discipline.","PeriodicalId":310835,"journal":{"name":"CTU Journal of Innovation and Sustainable Development","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136183413","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
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