检索结果-内蒙古大学图书馆

Assessing and prioritizing crucial drivers for CloudIoT-based healthcare adoption: an analytic hierarchy process approach

引用

International Journal of Information Technology (Singapore) 2024年 1-18页

作者： Altawaiha, Iyad Atan, Rodziah Yaakob, Razali Bin Abdullah, Rusli Bin Hj Department of Software Engineering and Information Systems Faculty of Computer Science and Information Technology Universiti Putra Malaysia (UPM) Serdang 43400 Malaysia Department of Computer Science Faculty of Computer Science and Information Technology Universiti Putra Malaysia (UPM) Serdang 43400 Malaysia

The CloudIoT paradigm has profoundly transformed the healthcare industry, providing outstanding innovation and practical applications. However, despite its many advantages, the adoption of this paradigm in healthcare settings remains limited. There is a lack of comprehensive understanding of the factors that ensure successful implementation. To address this issue, we have used the Analytic Hierarchy Process to prioritize 26 factors that could potentially influence the adoption of CloudIoT-based healthcare. These factors were derived from existing literature and categorized into four main groups: personal-specific, technology-specific, environment-specific, and organization-specific factors. Our findings revealed that performance expectancy, trust, facilitating conditions, task complexity, and perceived security are the top five critical factors influencing CloudIoT-based healthcare adoption. Interestingly, our results indicated that environmental factors were less influential than those in the other categories, with personal, technological, and organizational factors dominating the top ten significant factors. The insights from this study can help policymakers, CloudIoT service providers, healthcare providers, designers, and developers better understand the factors contributing to the successful implementation of CloudIoT-based healthcare. This understanding can guide decision-making and inform the development of strategies to promote the broader adoption of this innovative technology. © The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Adoption Analytic hierarchy process CloudIoT Factors Healthcare industry

来源：评论

学校读者我要写书评

暂无评论

Understanding the Definitions of Microcredentials in Higher Education: Systematic Literature Review

Understanding the Definitions of Microcredentials in Higher ...

引用

2024 International Conference on TVET Excellence and Development, ICTeD 2024

作者： Wihendro Warnars, Harco Leslie Hendric Spits Prabowo, Harjanto Sfenrianto Bina Nusantara University BINUS Graduate Program- Computer Science Information Systems Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program- Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Business School Undergraduate Program Management Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program-Master of Information Systems Management Information Systems Management Department Jakarta Indonesia

ISBN: (纸本)9798331516413

The growing focus on microcredentials emphasizes the urgent need for precise and widely accepted definitions, as existing uncertainties hinder their effective implementation. This research aims to investigate the comprehension of microcredentials definitions in the context of higher education by conducting a systematic literature review. The goal is to identify current definitions of microcredentials to facilitate standardization initiatives. Following The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) methodology to systematically search in Scopus database within 2019-2024 resulting 940 articles, by removing the duplicates, 280 articles were initially reviewed, with 29 selected for detailed thematic analysis based on specific inclusion and exclusion criteria. By adapting the six phases of thematic analysis, selected articles were identified analyzed, organized, described, and themes found the data set were reported. Key findings reveal that, while a universally accepted definition is lacking, common themes emerge: microcredentials are competency-based, modular, portable, stackable, and often include quality assurance. These attributes highlight microcredentials as valuable for upskilling and reskilling in a flexible manner. The study concludes that establishing standard definitions can increase the recognition and utility of microcredentials across educational and professional sectors and recommends further research to strengthen core elements for consistency. © 2024 IEEE.

关键词： Competency-based Higher Education Microcredentials Modular Reskilling Upskilling

来源：评论

学校读者我要写书评

暂无评论

ELCD-NSC2: a novel early lung cancer detection and non-small cell classification framework

引用

Neural Computing and Applications 2024年第24期36卷 15149-15164页

作者： Helaly, Hadeer A. Badawy, Mahmoud El-Gendy, Eman M. Haikal, Amira Y. Electrical Engineering Department Faculty of Engineering Damietta University Damietta Egypt Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura Egypt Department of Computer Science and Informatics Taibah University Medina Saudi Arabia

The survival rate of lung cancer relies significantly on how far the disease has spread when it is detected, how it reacts to the treatment, the patient’s overall health, and other factors. Therefore, the earlier the lung cancer diagnosis, the higher the survival rate. For radiologists, recognizing malignant lung nodules from computed tomography (CT) scans is a challenging and time-consuming process. As a result, computer-aided diagnosis (CAD) systems have been suggested to alleviate these burdens. Deep-learning approaches have demonstrated remarkable results in recent years, surpassing traditional methods in different fields. Researchers are currently experimenting with several deep-learning strategies to increase the effectiveness of CAD systems in lung cancer detection with CT. This work proposes a deep-learning framework for detecting and diagnosing lung cancer. The proposed framework used recent deep-learning techniques in all its layers. The autoencoder technique structure is tuned and used in the preprocessing stage to denoise and reconstruct the medical lung cancer dataset. Besides, it depends on the transfer learning pre-trained models to make multi-classification among different lung cancer cases such as benign, adenocarcinoma, and squamous cell carcinoma. The proposed model provides high performance while recognizing and differentiating between two types of datasets, including biopsy and CT scans. The Cancer Imaging Archive and Kaggle datasets are utilized to train and test the proposed model. The empirical results show that the proposed framework performs well according to various performance metrics. According to accuracy, precision, recall, F1-score, and AUC metrics, it achieves 99.60, 99.61, 99.62, 99.70, and 99.75%, respectively. Also, it depicts 0.0028, 0.0026, and 0.0507 in mean absolute error, mean squared error, and root mean square error metrics. Furthermore, it helps physicians effectively diagnose lung cancer in its early stages and allows spe

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Detailed Study on Various Techniques for Detecting Railway Track Anomaly 2

Detailed Study on Various Techniques for Detecting Railway T...

引用

2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Komarasamy, Dinesh Iyapparaja, M. Mohana Saranya, S. Cibi Chakravarthy, M. Fredolin Tibba, B. Gayathri, R. Kongu Engineering College Department of Computer Science and Engineering Erode Tamil Nadu Perundurai India School of Computer Science Engineering and Information Systems Vit Tamil Nadu Vellore India

ISBN: (纸本)9798350328202

A vital part of today's transportation infrastructure is the railway system that facilitates the massive movement of people and products. With so many people and commodities being transported, the rail tracks could develop defects and flaws over time. The development of these defects might jeopardize the safety and integrity of the rails due to persistent wear and tear, exposure to harsh environmental factors and the enormous loads carried by trains. Hence, to prevent faults and to avoid accidents, it is essential to maintain track safety. Thus, researchers focused on different technologies with different methodologies for detecting the defect that occurred in rail tracks as early as possible. Therefore, this paper summarizes the available methods and technologies for detecting defects and faults in railway tracks. © 2024 IEEE.

关键词： Defects

来源：评论

学校读者我要写书评

暂无评论

Multi-Scale Time Series Segmentation Network Based on Eddy Current Testing for Detecting Surface Metal Defects

引用

IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 528-538页

作者： Xiaorui Li Xiaojuan Ban Haoran Qiao Zhaolin Yuan Hong-Ning Dai Chao Yao Yu Guo Mohammad S.Obaidat George Q.Huang the School of Intelligence Science and Technology University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering the Key Laboratory of Intelligent Bionic Unmanned Systems and the Institute of Materials Intelligent Technology Liaoning Academy of Materials IEEE the Department of Computer Science Hong Kong Baptist University the School of Computer and Communication Engineering Key Laboratory of Advanced Materials and Devices for Post-Moore Chips Ministry of Education University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing the School of Computer and Communication Engineering University of Science and Technology Beijing the King Abdullah Ⅱ School of Information Technology The University of Jordan the Department of Computational Intelligence the School of Computing SRM University the School of Engineering The Amity University The Hong Kong Polytechnic University

In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh environment leads to significant variations in the shape and size of the defects. To address this challenge, we propose the multivariate time series segmentation network(MSSN), which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates. To tackle the classification difficulty caused by structural signal variance, MSSN employs logarithmic normalization to adjust instance distributions. Furthermore, it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences. Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95% localization and demonstrates the capture capability on the synthetic dataset. In a nuclear plant's heat transfer tube dataset, it captures 90% of defect instances with75% middle localization F1 score.

关键词： Eddy current testing nondestructive testing semantic segmentation time series analysis

来源：评论

学校读者我要写书评

暂无评论

Intelligent Optimization Under Multiple Factories: Hybrid Flow Shop Scheduling Problem with Blocking Constraints Using an Advanced Iterated Greedy Algorithm

引用

Complex System Modeling and Simulation 2023年第4期3卷 282-306页

作者： Yong Wang Yuting Wang Yuyan Han Junqing Li Kaizhou Gao Yusuke Nojima School of Computer Science Liaocheng UniversityLiaocheng 252000China School of Computer Science Shandong Normal UniversityJinan 252000China Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China Department of Computer Science and Intelligent Systems Osaka Prefecture UniversityOsaka 599-8531Japan

The distributed hybrid flow shop scheduling problem(DHFSP),which integrates distributed manufacturing models with parallel machines,has gained significant ***,in actual scheduling,some adjacent machines do not have buffers between them,resulting in *** paper focuses on addressing the DHFSP with blocking constraints(DBHFSP)based on the actual production *** solve DBHFSP,we construct a mixed integer linear programming(MILP)model for DBHFSP and validate its correctness using the Gurobi ***,an advanced iterated greedy(AIG)algorithm is designed to minimize the makespan,in which we modify the Nawaz,Enscore,and Ham(NEH)heuristic to solve blocking *** balance the global and local search capabilities of AIG,two effective inter-factory neighborhood search strategies and a swap-based local search strategy are ***,each factory is mutually independent,and the movement within one factory does not affect the *** view of this,we specifically designed a memory-based decoding method for insertion operations to reduce the computation time of the ***,two shaking strategies are incorporated into the algorithm to mitigate premature *** advanced algorithms are used to conduct comparative experiments with AIG on 80 test instances,and experimental results illustrate that the makespan and the relative percentage increase(RPI)obtained by AIG are 1.0%and 86.1%,respectively,better than the comparative algorithms.

关键词： blocking distributed hybrid flow shop neighborhood search iterated greedy algorithm

来源：评论

学校读者我要写书评

暂无评论

Improved-Equalized Cluster Head Election Routing Protocol for Wireless Sensor Networks

引用

computer systems science & engineering 2023年第1期44卷 845-858页

作者： Muhammad Shahzeb Ali Ali Alqahtani Ansar Munir Shah Adel Rajab Mahmood Ul Hassan Asadullah Shaikh Khairan Rajab Basit Shahzad Department of Computer Science Institute of Southern PunjabMultan5932Pakistan College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia Department of Computer Skills Deanship of Preparatory YearNajran UniversityNajran61441Saudi Arabia Department of Engineering National University of Modern LanguagesIslamabad44000Pakistan

Throughout the use of the small battery-operated sensor nodes encou-rage us to develop an energy-efficient routing protocol for wireless sensor networks(WSNs).The development of an energy-efficient routing protocol is a mainly adopted technique to enhance the lifetime of *** routing protocols are available,but the issue is still *** is one of the most important techniques in the existing routing *** the clustering-based model,the important thing is the selection of the cluster *** this paper,we have proposed a scheme that uses the bubble sort algorithm for cluster head selection by considering the remaining energy and the distance of the nodes in each ***,the bubble sort algorithm chose the two nodes with the maximum remaining energy in the cluster and chose a cluster head with a small *** proposed scheme performs hierarchal routing and direct routing with some energy *** simulation will be performed in MATLAB to justify its performance and results and compared with the ECHERP model to justify its ***,the simulations will be performed in two scenarios,gate-way-based and without gateway to achieve more energy-efficient results.

关键词： Bubble sort algorithm gateway energy thresholds wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

Scheduling Bi-Objective Lot-Streaming Hybrid Flow Shops with Consistent Sublots via an Enhanced Artificial Bee Colony Algorithm

引用

Complex System Modeling and Simulation 2025年第1期5卷 46-67页

作者： Lu, Benxue Gao, Kaizhou Duan, Peiyong Slowik, Adam School of Computer Science Liaocheng University Liaocheng252000 China Macau Institute of Systems Engineering Macau University of Science and Technology Macau999078 China School of Information and Automation Engineering Qilu University of Technology Jinan250353 China Koszalin University of Technology Department of Electronics and Computer Science Koszalin75-453 Poland

This work addresses bi-objective hybrid flow shop scheduling problems considering consistent sublots (Bi-HFSP_CS). The objectives are to minimize the makespan and total energy consumption. First, the Bi-HFSP_CS is formalized, followed by the establishment of a mathematical model. Second, enhanced version of the artificial bee colony (ABC) algorithms is proposed for tackling the Bi-HFSP_CS. Then, fourteen local search operators are employed to search for better solutions. Two different O-learning tactics are developed to embed into the ABC algorithm to guide the selection of operators throughout the iteration process. Finally, the proposed tactics are assessed for their efficacy through a comparison of the ABC algorithm, its three variants, and three effective algorithms in resolving 95 instances of 35 different problems. The experimental results and analysis showcase that the enhanced ABC algorithm combined with O-learning (QABC1) demonstrates as the top performer for solving concerned problems. This study introduces a novel approach to solve the Bi-HFSP_CS and illustrates its efficacy and superior competitive strength, offering beneficial perspectives for exploration and research in relevant domains. © 2021 TUP.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Cloud Computing and the Gig Economy Pricing Strategies

Comparative Analysis of Cloud Computing and the Gig Economy ...

引用

2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Jothish Kumar, M. Reddy, Gajulapalli Venkata Karthik Kumar Iyapparaja Nowritha, S. School of Computer Science Engineering and Information Systems Vit Vellore Department of Smart Computing Tamil Nadu Vellore India School of Computer Science Engineering and Information Systems Vit Vellore Tamil Nadu Vellore India School of Computer Science Engineering and Information Systems Vit University Department of Smart Computing Tamil Nadu Vellore India

ISBN: (纸本)9798331543617

Cloud computing services and gig economy platforms vary in flexibility, efficiency, and scalability due to their pricing schemes. Cloud computing services provide flexibility and cost control via pay-as-you-go, subscription, and freemium models. Like gig economy platforms, workers and customers pay for task completion, time-based contracts, and premium services. Assessing how successfully different pricing techniques fulfil varied demands, from short-term initiatives to long-term commitments, requires identifying their strengths and weaknesses. The goal is to evaluate these models' capacity to meet shifting demand, save money, and scale. The methodology also assesses cost predictability and company and consumer advantages of each pricing structure. The comparison seeks to improve resource allocation and financial planning by revealing how various pricing systems function in different circumstances. The research helps decision-makers use cloud services or gig economy platforms for different operational purposes by emphasizing their economic consequences. From datasets, simulated pricing model data was examined. The first example includes settings such as Hours Used (5-25), Pay-as-You-Go (10-50 USD), and Subscription-Based (30 USD). The second instance has Job Size (Resources) from 5 to 25, Freemium Model (USD) from 10 to 30, and Usage-Based Pricing (USD) from 10 to 50. © 2024 IEEE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

Periodic Physical Activity Information Segmentation, Counting and Recognition From Video

引用

IEEE Access 2023年 11卷 23019-23031页

作者： Cheng, Sheng-Hsien Sarwar, Muhammad Atif Daraghmi, Yousef-Awwad Ik, Tsi-Ui Li, Yih-Lang National Yang Ming Chiao Tung University College of Computer Science Department of Computer Science Hsinchu30010 Taiwan Palestine Technical University-Kadoorie Department of Computer Systems Engineering TulkaremP310 Palestine

The research on complex human body motion including sports and workout activity recognition is a major challenge and long-lasting problem for the computer vision community. Recent development in deep learning algorithms to track people's workout activity characteristics based on video sensors can be used to infer the human body pose for further analysis. Specifically, tracking complex body movements while performing multi-pose physical exercise helps individuals provide fine granularity feedback including activity repetition counting and activity recognition. Therefore, this research proposes a system that provides a repetition counter and activity recognition of physical exercise from video frames (extracted 3D human skeleton using VIBE) based on the deep semantic features and repetitive segmentation algorithm. The proposed system locates both ends of the activity's action and segments the activity into multiple unit actions which improves activity recognition, time intervals, # of sets, and other quantitative values of activity. The proposed system is evaluated on the physical activities dataset named "NOL-18 Exercise"through extensive experiments. The proposed system results show that the accuracy of the repetitive action segmentation is 96.27% with 0.23% time error, and action recognition reaches 99.06%. The system can be employed to fitness or rehabilitation centers and used for treating patients. © 2013 IEEE.

关键词： Sports

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：