检索结果-内蒙古大学图书馆

4th International Conference on Signal Processing and computer science, SPCS 2023

作者： Jin, Qinchao Yang, Peihao Wang, Tiantian Wu, Xianghu Wang, Kechao School of Computer Science and Technology Harbin Institute of Technology Harbin China School of Information Engineering Harbin University Harbin China

ISBN: (纸本)9781510672505

With the development and widespread application of Model-Based Systems engineering (MBSE) in the aerospace domain continue to grow, System Modeling Language (SysML) has become increasingly important as the most popular modeling language in MBSE. It is crucial to provide developers with an efficient and secure SysML editing tool to enhance their productivity. However, our research has revealed issues with the existing SysML editing tools, particularly in terms of data storage, resulting in a decline in efficiency as project data grows. Therefore, this paper proposes a GEF-based SysML development tool that supports developers in creating, editing, and exporting graphics. This tool addresses the data storage issues, improving development efficiency. Additionally, we present a model validation approach and extend the existing validation rules to ensure the correctness, reliability, and security of graphical elements and diagrams. © 2023 SPIE.

关键词： Modeling languages

来源：评论

学校读者我要写书评

暂无评论

CyclicSim: Comprehensive Evaluation of Cyclic Shapers in Time-Sensitive Networking 22

CyclicSim: Comprehensive Evaluation of Cyclic Shapers in Tim...

引用

22nd IEEE Consumer Communications and Networking Conference, CCNC 2025

作者： Debnath, Rubi Zhao, Luxi Barzegaran, Mohammadreza Steinhorst, Sebastian Tum School of Computation Information and Technology Technical University of Munich Germany Beihang University Department of Electronic and Information Engineering Beijing China University of California Department of Electrical Engineering and Computer Science Irvine United States

ISBN: (纸本)9798331508050

Cyclic Queuing and Forwarding (CQF) is a key Time-Sensitive Networking (TSN) shaping mechanism that ensures bounded latency using a simple gate control list (GCL). Recently, variants of CQF, including Cycle Specific Queuing and Forwarding (CSQF) and Multi Cyclic Queuing and Forwarding (MCQF), have emerged. While popular TSN mechanisms such as the Time-Aware Shaper (TAS), Asynchronous Traffic Shaper (ATS), Credit-Based Shaper (CBS), and Strict Priority (SP) have been extensively studied, cyclic shapers have not been thoroughly evaluated. This paper presents a comprehensive analysis of CQF, CSQF, and MCQF, providing insights into their performance. We quantify delays through simulations and quantitative analysis on both synthetic and realistic networks. For the first time, we introduce an open-source OMNeT++ and INET4.4 based framework capable of modeling all three cyclic shaper variants. Our tool facilitates the validation of new algorithms and serves as a benchmark for cyclic shapers. Our evaluations reveal that MCQF supports diverse timing requirements, whereas CSQF, with its additional queue, often results in larger delays and jitter for some TT flows compared to CQF. Additionally, CSQF does not demonstrate significant advantages in TSN networks where propagation delays are less critical than in wide-area networks (WANs). © 2025 IEEE.

关键词： Queueing networks

来源：评论

学校读者我要写书评

暂无评论

Advanced prediction and classification of pulmonary emphysema in COPD using deep graph convolutional neural network with improved weighted quantum ant bee optimization for CT-based diagnosis

引用

Iran Journal of computer science 2025年 1-18页

作者： Jeyakumar, Suganya Selvaraj, Senthil Kumar Muthusamy, Prakash Sritharan, Akilandeswari Mariadass, Paul Arokiadass Jerald Department of Computer Applications SRM Institute of Science and Technology Tiruchchirappalli India Department of Information Technology Sri Krishna Adithya College of Arts and Science Coimbatore India Department of Artificial Intelligence and Data Science E.G.S. Pillay Engineering College Nagapattinam India Department of Computer Science Periyar Arts College Cuddalore India

Pulmonary emphysema, a progressive respiratory disease and a subset of Chronic Obstructive Pulmonary Disease (COPD), is characterized by lung tissue degradation. Accurate prediction and classification of emphysema are essential for effective management and early detection. Although existing diagnostic methods such as spirometry and CT-based evaluations are valuable, they often have limitations due to interpretive variability and the inability to detect specific emphysema patterns. This paper introduces a novel approach to enhancing the accuracy and efficiency of CT-based pulmonary emphysema diagnosis by integrating an improved weighted quantum ant bee optimization (IWQABO) method with a deep convolutional neural network (DCNN). The primary challenges addressed include improving classification reliability across various emphysema subtypes and extracting optimal features from high-dimensional CT scan data. The IWQABO method optimizes the network’s hyperparameters to enhance classification accuracy, while the DCNN excels at extracting features from complex imaging data. Two data sets were employed in the study: the CTED data set and a real-time emphysema data set. The experimental results demonstrate significant improvements in classification accuracy, with a precision of 95.8%, a sensitivity of 94.5%, and a specificity of 96.3%. These results outperform traditional diagnostic methods, such as spirometry and manual CT assessments. The findings highlight the advantages of combining DCNN and IWQABO techniques for diagnosing pulmonary emphysema, showcasing their potential to improve treatment outcomes and enhance clinical decision-making for COPD patients. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Automated diagnosis COPD CT-based diagnosis DCNN Hyperparameter optimization Improved weighted quantum ant bee optimization Pulmonary emphysema

来源：评论

学校读者我要写书评

暂无评论

The Impact of Blockchain technology for Evaluation of Electronic Medical Certification

引用

SN computer science 2025年第5期6卷 1-14页

作者： Azam Zia, M. Anwar, Munazza Mehmood, Faisal Razzaq, Abdul Asif, Muhammad Department of Computer Science University of Agriculture Faisalabad Punjab Faisalabad 38000 Pakistan Department of Civil and Transportation Engineering Shenzhen University Shenzhen 518060 China Computer Science Muhammad Nawaz Shareef University of Agriculture Punjab Multan 59300 Pakistan Department of Computer and Software Engineering Information Technology University (ITU) Punjab Lahore Pakistan

Evaluation of Electronic Medical Certification (EMC) is integral to today's healthcare systems since they are a consolidated database of individual patients' medical histories. Security measures and privacy issues are standard in electronic medical certification. Incompatible systems make sharing data across healthcare providers difficult, which may lead to data breaches and a lack of patient authority over their medical data. Blockchain has become essential for real-world corporate applications where confidentiality of information is paramount. The handling of security in medical records through a decentralized peer-to-peer network might be revolutionized by blockchain technology and improving the protection of the interchange of healthcare records. This study proposes a lightweight flask framework-based blockchain strategy to store and display patient status and transaction log information about their disease diagnosis. In a potential Blockchain system, the diseased patients act as assets, and their records contain any prior illnesses as blocks. The report analyzes a lot of national and international EHR standards. It identifies which of these interoperability needs to be addressed, discusses the interoperability challenges in but also outlines the standards. Current blockchain-based EHR frameworks. Without the suggested has the requirement for centralized systems. By using this framework, the healthcare industry can be provided safer ways to while also providing the exchange of health information. It offers features of immutability, security, and user control over stored records. This work contributes to an understanding of what potential Blockchain technology has offered an interoperable application in the EHR frameworks. Meet the blockchain-based EHR framework. Multiple national and international EHR standards. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Blockchain Cryptography Decentralized Electronic medical certification (EMC) Transaction

来源：评论

学校读者我要写书评

暂无评论

DeepSVDNet:A Deep Learning-Based Approach for Detecting and Classifying Vision-Threatening Diabetic Retinopathy in Retinal Fundus Images

引用

computer Systems science & engineering 2024年第2期48卷 511-528页

作者： Anas Bilal Azhar Imran Talha Imtiaz Baig Xiaowen Liu Haixia Long Abdulkareem Alzahrani Muhammad Shafiq College of Information Science and Technology Hainan Normal UniversityHaikou571158China Department of Creative Technologies Air UniversityIslamabadPakistan School of Life Science and Technology University of Electronic Science and Technology of China UESTCChengduChina School of Science and Technology University of Management and Technology UMTLahorePunjabPakistan Faculty of Computer Science&Information Technology Al Baha UniversityAl BahaSaudi Arabia School of Information Engineering Qujing Normal UniversityQujingChina

Artificial Intelligence(AI)is being increasingly used for diagnosing Vision-Threatening Diabetic Retinopathy(VTDR),which is a leading cause of visual impairment and blindness ***,previous automated VTDR detection methods have mainly relied on manual feature extraction and classification,leading to *** paper proposes a novel VTDR detection and classification model that combines different models through majority *** proposed methodology involves preprocessing,data augmentation,feature extraction,and classification *** use a hybrid convolutional neural network-singular value decomposition(CNN-SVD)model for feature extraction and selection and an improved SVM-RBF with a Decision Tree(DT)and K-Nearest Neighbor(KNN)for *** tested our model on the IDRiD dataset and achieved an accuracy of 98.06%,a sensitivity of 83.67%,and a specificity of 100%for DR detection and evaluation tests,*** proposed approach outperforms baseline techniques and provides a more robust and accurate method for VTDR detection.

关键词： Diabetic retinopathy(DR) fundus images(FIs) support vector machine(SVM) medical image analysis convolutional neural networks(CNN) singular value decomposition(SVD) classification

来源：评论

学校读者我要写书评

暂无评论

Analysis of Resource Allocation in Wavelength Division Multiplexing Optical Networks 15

Analysis of Resource Allocation in Wavelength Division Multi...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Deepak, J. Pandeya, Megha Saraswat, Nidhi School of Engineering and Technology Department of Mechanical Engineering Karnataka Bangalore India Maharishi University of Information Technology Maharishi School of Engineering & Technology Uttar Pradesh India Sanskrit University Department of Computer Science Engineering Uttar Pradesh Mathura India

ISBN: (纸本)9798350370249

This paper explores useful resource allocation rules inside Wavelength Department Multiplexing (WDM) Optical Networks. WDM optical networks are leveraged to provide dependable and high-capability transmission for network offerings. To accurately version the complex topologies and useful resource allocations associated with this generation, researchers are faced with combinatorial optimization and ensemble gaining knowledge of issues, amongst others. The authors of this study's paper observe present aid project techniques within each static and dynamic scenario and outline an evaluation of metaheuristic methods that may be of help. They then introduce their proposed acyclic-based approach, which outlines a community structure based totally on the candidate dominant hyperlink (CDL) principle and explores its performance under high dynamic networks. Constructing upon their research in associated paintings, the authors then speak about the results of their method in the context of the distributed Context-conscious Computing framework. The paper culminates by discussing destiny directions for researchers to influence the development of WDM networks. © 2024 IEEE.

关键词： Hyperlink Multiplexing Networks Optimization Wavelength

来源：评论

学校读者我要写书评

暂无评论

Can a Simple Approach Perform Better for Cross-Project Defect Prediction? 19

Can a Simple Approach Perform Better for Cross-Project Defec...

引用

19th International Conference on Evaluation of Novel Approaches to Software engineering, ENASE 2024

作者： Hossain, Md. Arman Akhter, Suravi Islam, Md. Shariful Alam, Muhammad Mahbub Shoyaib, Mohammad Institute of Information Technology University of Dhaka Dhaka Bangladesh Department of Computer Science and Engineering University of Liberal Arts Bangladesh Dhaka Bangladesh Department of Mathematics University of Dhaka Dhaka Bangladesh Department of Computer Science and Engineering Islamic University of Technology Dhaka Gazipur Bangladesh

ISBN: (纸本)9789897586965

Cross-Project Defect Prediction (CPDP) has gained considerable research interest due to the scarcity of historical labeled defective modules in a project. Although there are several approaches for CPDP, most of them contains several parameters that need to be tuned optimally to get the desired performance. Often, higher computational complexities of these methods make it difficult to tune these parameters. Moreover, existing methods might fail to align the shape and structure of the source and target data which in turn deteriorates the prediction performance. Addressing these issues, we investigate correlation alignment for CPDP (CCPDP) and compare it with state-of-the-art transfer learning methods. Rigorous experimentation over three benchmark datasets AEEEM, RELINK and SOFTLAB that include 46 different project-pairs, demonstrate its effectiveness in terms of F1-score, Balance and AUC compared to six other methods TCA, TCA+, JDA, BDA, CTKCCA and DMDA JFR. In terms of AUC, CCPDP wins at least 32 and at most 42 out of 46 project pairs compared to all transfer learning based method. © 2024 by SCITEPRESS – science and technology Publications, Lda.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Techniques for Alzheimer's Disease Prediction 5

Deep Learning Techniques for Alzheimer's Disease Prediction

引用

5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Mahesh, T.R. Agarwal, Ankita Nair, Amrutha V. Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Maharishi University of Information Technology Maharishi School of Engineering & Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798350383522

Deep learning, a cutting-edge approach of machine learning, surpasses classical machine learning when it comes to detecting particular structures in complicated, high-dimensional data in the area of computer vision. The fast improvement of neuroimaging technologies and the associated creation of huge volumes of multimodal neuroimaging data have led in a noteworthy surge in interest in the application of deep learning for automated categorization and early diagnosis of Alzheimer's disease (AD). The best classification results were achieved utilizing multimodal neuroimaging in conjunction with fluid biomarkers. © 2024 IEEE.

关键词： and Alzheimer's disease (AD) Deep learning feature selection gradient descent multimodal neuroimaging data performance evaluation repeatability

来源：评论

学校读者我要写书评

暂无评论

Impediments of Cognitive System engineering in Machine-Human Modeling

引用

computers, Materials & Continua 2023年第3期74卷 6689-6701页

作者： Fayaz Ahmad Fayaz Arun Malik Isha Batra Akber Abid Gardezi Syed Immamul Ansarullah Shafiq Ahmad Mejdal Alqahtani Muhammad Shafiq National Institute of Electronics and Information Technology(NIELIT) J&K191132India Department of Computer Science&Engineering Lovely Professional University(LPU)Punjab144402India Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Computer Science Govt.Degree College Sumbal Kashmir193501India Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

A comprehensive understanding of human intelligence is still an ongoing process,i.e.,human and information security are not yet perfectly *** understanding cognitive processes,designers can design humanized cognitive information systems(CIS).The need for this research is justified because today’s business decision makers are faced with questions they cannot answer in a given amount of time without the use of cognitive information *** researchers aim to better strengthen cognitive information systems with more pronounced cognitive thresholds by demonstrating the resilience of cognitive resonant frequencies to reveal possible responses to improve the efficiency of human-computer interaction(HCI).Apractice-oriented research approach included research analysis and a review of existing articles to pursue a comparative research model;thereafter,amodel development paradigm was used to observe and monitor the progression of CIS during *** scope of our research provides a broader perspective on how different disciplines affect HCI and how human cognitive models can be enhanced to enrich *** have identified a significant gap in the current literature on mental processing resulting from a wide range of theory and practice.

关键词： Cognitive-IoT human-computer interaction decision making

来源：评论

学校读者我要写书评

暂无评论

Smartphone based Human Activity Recognition using CNNs and Autoencoder Features 7

Smartphone based Human Activity Recognition using CNNs and A...

引用

7th International Conference on Trends in Electronics and Informatics, ICOEI 2023

作者： Mitra, Sowmen Kanungoe, Proma School of Artificial Intelligence Hebei University of Technology Department of Computer Science and Technology Beijing China School of Information Technology and Engineering Vellore Institute of Technology Department of Information Technology Vellore India

ISBN: (纸本)9798350397284

Recognition of human activities is essential for many applications, and the widespread availability of low-cost sensors on smartphones and wearables has enabled the development of mobile apps capable of tracking user activities 'in the wild.' However, dealing with heterogeneous data from different devices and real-time scenarios presents significant challenges. In this study, a novel learning framework is proposed for Human Activity Recognition (HAR) that combines a Convolutional Neural Network (CNN) with an autoencoder for feature extraction. The study also investigates the importance of preprocessing techniques, including orientation-independent transformation, to mitigate heterogeneity when dealing with multiple types of smartphones. The results show that the proposed approach outperforms state-of-the-art methods in HAR, with an accuracy of 95.74% on the heterogeneous dataset used in this study. Furthermore, the study demonstrates that proposed framework can be effectively deployed on smartphones with limited computational resources, making it suitable for real-world applications. © 2023 IEEE.

关键词： Smartphones

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：