检索结果-内蒙古大学图书馆

21st International Conference on Networking, Sensing and Control, ICNSC 2024

作者： Guo, Zeyu Guo, Xiwang Wang, Jiacun Qin, Shujin Qi, Liang Kang, Qi Liaoning Petrochemical University Information and Control Engineering Fushun China Monmouth University Computer Science and Software Eng. Wes Long BranchNJ United States Shangqiu Normal University Economics and Management Shangqiu China Shandong Technology University Computer Science Department Qingdao China New Jersey Institute of Technology Electrical and Computer Engineering Newark United States

ISBN: (纸本)9798350365221

As disassembly lines evolve, keeping workers safe from all potential dangers has become paramount. This work proposes an improved approach, Proximal Policy Optimization for Disassembly Line(PPO-DL), to address Multi-objective Dis-assembly Line Balancing Problem(MDLBP) that integrates task switching time and hazardous tasks. The MDLBP model aims to optimize disassembly net profit, balance workstation utilization, and mitigate penalties from hazardous tasks. The proposed PPO-DL modifies the action space of PPO to accommodate MD LBP characteristics, ensuring efficient learning by restricting actions to valid ranges through action masking. Comparative experiments with PPO, Q-learning, and A2C demonstrate PPO-DL's superiority in finding near-optimal solutions across various scenarios. © 2024 IEEE.

关键词： Assembly machines

来源：评论

学校读者我要写书评

暂无评论

Medical Cyber-Physical Systems in Society 5.0: Are We Ready?

IEEE Transactions on Technology and Society

引用

IEEE Transactions on Technology and Society 2022年第3期3卷 189-198页

作者： Patil, Rajkumar V. Ambritta, Nancy P. Mahalle, Parikshit N. Dey, Nilanjan Vishwakarma Institute of Information Technology Department of Information Technology Pune411048 India Glareal Software Solutions PTE. Ltd. Singapore200809 Singapore Vishwakarma Institute of Information Technology Department of Artificial Intelligence and Data Science Pune411048 India Jis University Department of Computer Science and Engineering Kolkata700109 India

Advancements in cyber-physical systems (CPSs) makes CPSs essential entities in society today, and have made them prominent across all fields. For example, the healthcare industry has evolved technologically and has effectively incorporated CPS into many application areas. While these advancements, involving medical CPSs (MCPS), have been revised according to Society 4.0, there are still issues that need to be considered while we transition from an information-based society (Society 4.0) to a human-centric society (Society 5.0). In this article, we propose an MCPS framework for Society 5.0 in the context of some state-of-the-art technologies. The proposed system focuses on enhancing security aspects of Society 5.0 through introduction of a security layer equipped with protocols, such as open authorization (OAuth), user-managed access (UMA), and self-sovereign identity (SSI). The added security layer is designed to incorporate country-specific security laws. Challenges and design issues in developing a trusted and secure service for MCPS are also discussed using vulnerability assessment and attack modeling. Finally, we discuss ethical aspects that need to be addressed in the transition from Society 4.0 to Society 5.0. © 2020 IEEE.

关键词： Cyber Physical System

来源：评论

学校读者我要写书评

暂无评论

Light gradient boosting machine with optimized hyperparameters for identification of malicious access in IoT network

引用

Digital Communications and Networks 2023年第1期9卷 125-137页

作者： Debasmita Mishra Bighnaraj Naik Janmenjoy Nayak Alireza Souri Pandit Byomakesha Dash S.Vimal Department of Computer Application Veer Surendra Sai University of TechnologyBurlaSambalpur768018OdishaIndia Department of Computer Science Maharaja Sriram Chandra Bhanja Deo(MSCB)UniversityBaripada757003OdishaIndia Department of Software Engineering HaliçUniversity34394IstanbulTurkey Department of Information Technology Aditya Institute of Technology and Management(AITAM)Tekkali532201Andhra PradeshIndia Data Analytics Lab Department of Artificial Intelligence and Data ScienceRamco Institute of TechnologyNorth Venganallur VillageRajapalayam 626117 Virudhunagar DistrictTamilnaduIndia

In this paper,an advanced and optimized Light Gradient Boosting Machine(LGBM)technique is proposed to identify the intrusive activities in the Internet of Things(IoT)*** followings are the major contributions:i)An optimized LGBM model has been developed for the identification of malicious IoT activities in the IoT network;ii)An efficient evolutionary optimization approach has been adopted for finding the optimal set of hyper-parameters of LGBM for the projected ***,a Genetic Algorithm(GA)with k-way tournament selection and uniform crossover operation is used for efficient exploration of hyper-parameter search space;iii)Finally,the performance of the proposed model is evaluated using state-of-the-art ensemble learning and machine learning-based model to achieve overall generalized performance and *** outcomes reveal that the proposed approach is superior to other considered methods and proves to be a robust approach to intrusion detection in an IoT environment.

关键词： IoT security Ensemble method Light gradient boosting machine Machine learning Intrusion detection

来源：评论

学校读者我要写书评

暂无评论

Handwritten Prescription Recognition Using VGG Based Architecture with Bi-LSTM

Handwritten Prescription Recognition Using VGG Based Archite...

引用

International Research Conference on Smart Computing and Systems engineering (SCSE)

作者： Isuru Kavinda Harinda Fernando Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer System Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798350375688

ISBN: (纸本)9798350375695

Illegible handwriting on medical prescriptions poses a significant challenge, often leading to the misinterpretation of drug names and dosages. This issue primarily stems from doctors’ use of Latin abbreviations, driven by time constraints during patient consultations. The resultant discrepancies in prescription interpretation can potentially expose patients to incorrect medications and dosages, leading to adverse effects. In response to this concern, this study proposes a novel system integrating Convolution Neural Network (CNN) and Recurrent Neural Network (RNN) models. Promising findings are reported in this study, achieving a loss of 0.4874 and an accuracy of 0.83 in the latest trial. The final model offers a potential solution to the persistent problem of illegible prescriptions, enhancing patient safety in the healthcare domain.

关键词： Training Handwriting recognition Recurrent neural networks Convolution Computational modeling Transfer learning Medical services

来源：评论

学校读者我要写书评

暂无评论

COVID 19 Navigator Taxi Application for Urban Mobility during Pandemic Period 2

COVID 19 Navigator Taxi Application for Urban Mobility durin...

引用

2nd International Conference on Advanced Research in Computing, ICARC 2022

作者： Peiris, Rojith Kanchana, Bimsara Perera, Damitha Wickramarathne, Jagath Sri Lanka Institute of Information Technology Faculty of Graduate Studies and Research Malabe Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9781665407410

This research paper focuses on increasing the awareness between taxi users and can help to protect themselves in COVID-19 and take precautions. Since 2019 the global pandemic of Covid-19 is spreading at an astonishing rate and causes a negative impact for economic, social, and cultural factors. Government agencies are warning people to reduce the transportation and to maintain social distance. To stop the spread of COVID-19 required to identify persons who are susceptible to infection and need to trace the COVID-19 positive first contacts. Most people are reduced to using public transportations and taxi services due to unidentifiable health conditions in earlier users. The proposed approach can be used to track the taxi drivers and their passengers previous COVID-19 status as well as navigate the safest route by showing the COVID-19 contamination areas. By using this approach users can be aware of earlier users of the taxi service and COVID-19 status of the taxi driver or passenger before taking the trip as well as if they get touch with any COVID-19 patients, can take immediate precautions. This application helps to increase the usage of taxis by making users trust and confidence against COVID-19 infection. By testing with real users our system was able to trace down 45 passengers and 16 drivers within 3 months. © 2022 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Empirical Analysis of software Success Rate Forecasting During Requirement engineering Processes

引用

computers, Materials & Continua 2023年第1期74卷 783-799页

作者： Muhammad Hasnain Imran Ghani Seung Ryul Jeong Muhammad Fermi Pasha Sardar Usman Anjum Abbas Lahore Leads University Lahore42000Pakistan Computer and Information Sciences Virginia Military InstituteLexingtonVA24450USA Graduate School of Business IT Kookmin UniversitySeoul136Korea School of Information Technology Monash UniversityBandar Sunway47500Malaysia Department of Computer Science and Software Engineering Grand Asian University Sialkot51040Pakistan Government Sarwar Shaheed Associate College Gujjar KhanRawalpindi46000Pakistan

Forecasting on success or failure of software has become an interesting and,in fact,an essential task in the software development *** order to explore the latest data on successes and failures,this research focused on certain questions such as is early phase of the software development life cycle better than later phases in predicting software success and avoiding high rework?What human factors contribute to success or failure of a software?What software practices are used by the industry practitioners to achieve high quality of software in their day-to-day work?In order to conduct this empirical analysis a total of 104 practitioners were recruited to determine how human factors,misinterpretation,and miscommunication of requirements and decision-making processes play their roles in software success *** discussed a potential relationship between forecasting of software success or failure and the development *** noticed that experienced participants had more confidence in their practices and responded to the questionnaire in this empirical study,and they were more likely to rate software success forecasting linking to the development *** analysis also shows that cognitive bias is the central human factor that negatively affects forecasting of software success *** results of this empirical study also validated that requirements’misinterpretation and miscommunication were themain causes behind software systems’*** has been seen that reliable,relevant,and trustworthy sources of information help in decision-making to predict software systems’success in the software *** empirical study highlights a need for other software practitioners to avoid such bias while working on software *** investigation can be performed to identify the other human factors that may impact software systems’success.

关键词： Cognitive bias misinterpretation of requirements miscommunication software success and failure prediction decision making

来源：评论

学校读者我要写书评

暂无评论

Smart Diagnostic System for Early Detection and Prediction of Polycystic Ovary Syndrome

Smart Diagnostic System for Early Detection and Prediction o...

引用

2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Harish, K.P. Dhivyanchali, M.N. Devi, K.Nirmala Krishnamoorthy, N. Dhana Sree, R. Dharanidharan, R. Kongu Engineering College Department of Computer Science & Engineering Erode India Swamy Vivekanandha Medical College Hospital and Research Institute Elayampalayam Tamilnadu Tiruchengode637 205 India Vellore Institute of Technology Vellore Campus School of Information Technology and Engineering Department of Software Systems and Engineering Tamilnadu 632014 India

ISBN: (纸本)9798350348217

PCOS are the serious condition which affects female ovaries during their reproductive age of 15 to 45. This disease affects 5 to 10% of reproductive-age females. Although it is difficult to fully resolve this issue,the PCOS affected women can be mitigated through proper exercise, by taking proper nutritious diet and maintaining the healthy BMI. Until they take a pregnancy test, the majority of women are unaware of the disease. The clinical dataset has the 541 instances and 45 attributes of unbalanced classes of 0 and 1 (no and yes) which has 364 instances of 0 (no) class and 177 instances of 1 (yes) class. Preprocessing is done for the unbalanced dataset by filling the null values and changing the datatype of all attributes to numeric datatypes. The unbalanced dataset is balanced by the balancing techniques of SMOTE and Random Over Sampling. Comparing the both balanced techniques through the accuracy the random oversampling gives the *** supervised learning algorithms are Decision tree, KNN,Random Forest,AdaBoost, Logistic regression,Gradient boosting, cat boosting, XGBoosting, Linear SVM, Radial SVM, Linear discriminant analysis and Quadratic discriminant analysis are *** supervised learning algorithms are trained and tested by splitting the dataset to 70% for training and 30% for testing. The ensemble stacking techniques are used by implementing the all models at the cross validation of *** xgboost gives the accuracy of 96% for the balanced dataset. © 2023 IEEE.

关键词： Adaptive boosting

来源：评论

学校读者我要写书评

暂无评论

Class-attention video transformer for engagement prediction

引用

Multimedia Tools and Applications 2024年 1-20页

作者： Ai, Xusheng Sheng, Victor Li, Chunhua Yang, Han Cui, Zhiming Software and Service Outsourcing College Suzhou Vocational Institute of Industrial Technology 1 Zhineng Avenue Jiangsu Suzhou215104 China Department of Computer Science Texas Tech University 2500 Broadway LubbockTX79409 United States School of Electronics and Information Engineering Suzhou University of Science and Technology No.1 Kerui Road Jiangsu Suzhou215009 China

In this paper, we propose the Class Attention in Video Transformer (CavT), an end-to-end method designed to process both long and short variant-length videos for student engagement prediction. CavT introduces a single vector for class embedding and incorporates the Binary-Order Representatives Sampling (BorS) technique to augment the dataset by adding multiple video sequences. Our method outperforms the state-of-the-art with MSE values of 0.0495 on the EmotiW-EP and 0.0377 on the DAiSEE datasets, providing a robust and scalable solution for engagement prediction. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

A Correlation And Order-Aware Rule Learning Method For Knowledge Graph Reasoning 29

A Correlation And Order-Aware Rule Learning Method For Knowl...

引用

29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： He, Yuefeng He, Yang Zheng, Xu Hui, Bei Tian, Bin University of Electronic Science and Technology of China Shenzhen Institute for Advanced Study Shenzhen China University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu China University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu China Naval University of Engineering Wuhan China

ISBN: (纸本)9798350330717

Mining high-quality logical rules is crucial as they can provide beneficial interpretability for predictions. Recent methods that incorporate logical rules into learning tasks have been proven to yield high-quality logical rules successfully. However, existing methods either rely on the rule instances observed to support rule mining, or simply embed the rule head and the rule body to learn from them. Additionally, they can not fully utilize the rich semantic information contained in logical rules and overlook the intrinsic correlations between all relations within the domain. In this paper, we propose a model called Correlation and order-Aware Rule Learning (CARL) that captures deeper semantic information in rules by allowing relations to be co-aware of each other and paying attention to logical sequence sensitivity. CARL utilizes semantic consistency between the rule body and rule head as its learning objective, continuously introducing more semantic information and logically simplifying the rule body while considering logical sequence sensitivity. We explored the internal correlations between domain relations and used the thought of knowledge distillation to simplify modules so that relations in CARL can share or perceive each other's information or state efficiently. Experiments on link prediction tasks have demonstrated that CARL can learn higher-quality rules and yield state-of-the-art results on four popular public datasets. https://***/burning5112/CARL © 2023 IEEE.

关键词： knowledge graph reasoning rule learning

来源：评论

学校读者我要写书评

暂无评论

Gamifying Coding Education for Beginners: Empowering Learners with HTML, CSS and JavaScript

Gamifying Coding Education for Beginners: Empowering Learner...

引用

International Research Conference on Smart Computing and Systems engineering (SCSE)

作者： Santhush Chandrasekara Dileep Hewavitharana Maleesha Weerasinghe Binod Gayasri Dinuka Wijendra Dilshan De Silva Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798331523268

ISBN: (纸本)9798331523275

Traditional coding education often fails to engage and motivate beginners due to its lack of interactivity and personalized learning experiences. This paper presents a gamified learning platform designed to teach Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), and JavaScript (JS) to beginners. The platform incorporates interactive lessons, AI (Artificial Intelligence)-powered coding assistance, and advanced gamification mechanics to enhance learner motivation, engagement, and success. Furthermore, key features include performance-based recommendation engines, virtual coding environments with real-time feedback, and a collaborative platform for peer interactions. The integration of AI provides personalized feedback and adaptive learning paths, while gamified elements such as badges, points, and leaderboards foster competitive and enjoyable experiences. Preliminary findings demonstrate a 40% increase in student engagement metrics and a 35% improvement in coding competency compared to traditional methods. This research lays the groundwork for future expansion to additional programming languages and broader educational applications, with potential implications for transforming computer science education on a scale.

关键词： Technological innovation Education Collaboration Systems engineering and theory Encoding Real-time systems HTML computer science education Artificial intelligence Programming profession

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：