检索结果-内蒙古大学图书馆

44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023

作者： De Silva, Upeka Madanian, Samaneh Templeton, John Michael Poellabauer, Christian Schneider, Sandra L. Narayanan, Ajit Department of Computer Science and Software Engineering Auckland University of Technology Auckland New Zealand Department of Computer Science and Engineering University of South Florida TampaFL33620 United States School of Computing and Information Sciences Florida International University MiamiFL33199 United States Department of Communicative Sciences and Disorders Saint Mary's College Notre DameIN46556 United States

ISBN: (纸本)9781713893622

Mental health has become a global issue with growing numbers of cases. Digital phenotyping in mental healthcare provides a highly effective, scaled, cost-effective approach to handling global mental health problems. Monitoring and diagnosis of mental health through mobile technologies are at an early stage. This paper proposes a novel architecture for a mobile application design based on speech and behavioural analysis that can lead to evidence-based monitoring outside of clinical settings. The application is designed to monitor the overall mental health status of individuals based on mood, stress, behaviour, and personality. It proposes to integrate objective mental health assessment from smartphone data with subjective assessments via periodic, short, self-reported, standardized questionnaires. The solution proposes explainable assessments for individual users and clinicians to build user trust and system credibility. This research provides insight into how digitally assisted mental health monitoring can be implemented in future mobile digital technologies using passive sensing. Copyright © 2023 De Silva, Madanian, Templeton, Poellabauer, Schneider and Narayanan.

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

Competitive and Cooperative Computation Offloading for Intensive Heterogeneous Tasks in Vehicular Edge computing Networks

Competitive and Cooperative Computation Offloading for Inten...

引用

IEEE International Conference on Communications (ICC)

作者： Yuan Chen Xiuhua Li Guozeng Xu Ling Liu Xiaofei Wang Victor C. M. Leung School of Big Data & Software Engineering Chongqing University Chongqing China TKLAN College of Intelligence & Computing Tianjin University Tianjin China College of Computer Science & Software Engineering Shenzhen University Shenzhen China Department of Electrical & Computer Engineering The University of British Columbia Vancouver Canada

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Computation offloading is widely used in vehicular edge computing (VEC) networks to satisfy the computational intensity and latency sensitivity requirements. However, many existing offloading algorithms do not comprehensively consider the dynamically changing characteristics of heterogeneous tasks within a roadside unit (RSU), resulting in tasks timeout and being dropped. In this paper, we design a competitive and cooperative computation offloading (C3O) model to reduce task execution latency. Specifically, when intensive heterogeneous tasks are generated, these vehicles jointly compete for the computing resource of a RSU, or they can also offload tasks to the task vehicle (TaV) with free computing resource. Meanwhile, We analyze the latency model of local execution and offloading to RSU or TaV execution and formulate a sequential task offloading decision problem, NP-hard. To address it, we propose a multi-agent reinforcement learning algorithm based on C3O (MARC3O) to intelligently determine the computation offloading policy for each vehicle according to the state of VEC networks. Simulation results demonstrate that the proposed algorithm can significantly reduce task execution latency and improve task completion rates compared with baseline schemes.

关键词： Analytical models Sensitivity Costs Computational modeling Simulation Heuristic algorithms Collaboration

来源：评论

学校读者我要写书评

暂无评论

Natural Language Processing for Analyzing Electronic Health Records and Clinical Notes in Cancer Research: A Review

arXiv

引用

arXiv 2024年

作者： Bilal, Muhammad Hamza, Ameer Malik, Nadia Department of Pharmaceutical Outcomes and Policy University of Florida GainesvilleFL32611 United States Department of Computer Science Faculty of Computing and IT University of Sargodha Punjab Sargodha40100 Pakistan Department of Software Engineering Faculty of Computing and IT University of Sargodha Punjab Sargodha40100 Pakistan

Objective: This review aims to analyze the application of natural language processing (NLP) techniques in cancer research using electronic health records (EHRs) and clinical notes. This review addresses gaps in the existing literature by providing a broader perspective than previous studies focused on specific cancer types or applications. Methods: A comprehensive literature search was conducted using the Scopus database, identifying 94 relevant studies published between 2019 and 2024. Data extraction included study characteristics, cancer types, NLP methodologies, dataset information, performance metrics, challenges, and future directions. Studies were categorized based on cancer types and NLP applications. Results: The results showed a growing trend in NLP applications for cancer research, with breast, lung, and colorectal cancers being the most studied. Information extraction and text classification emerged as predominant NLP tasks. A shift from rule-based to advanced machine learning techniques, particularly transformer-based models, was observed. The Dataset sizes used in existing studies varied widely. Key challenges included the limited generalizability of proposed solutions and the need for improved integration into clinical workflows. Conclusion: NLP techniques show significant potential in analyzing EHRs and clinical notes for cancer research. However, future work should focus on improving model generalizability, enhancing robustness in handling complex clinical language, and expanding applications to understudied cancer types. Integration of NLP tools into clinical practice and addressing ethical considerations remain crucial for utilizing the full potential of NLP in enhancing cancer diagnosis, treatment, and patient outcomes. © 2024, CC BY.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Chest Radiographs Based Pneumothorax Detection Using Federated Learning

引用

Computer Systems Science & engineering 2023年第11期47卷 1775-1791页

作者： Ahmad Almadhor Arfat Ahmad Khan Chitapong Wechtaisong Iqra Yousaf Natalia Kryvinska Usman Tariq Haithem Ben Chikha Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakaka72388Saudi Arabia Department of Computer Science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand School of Telecommunication Engineering Suranaree University of TechnologyNakhon Ratchasima30000Thailand Department of Computer Science and Software Engineering International Islamic UniversityIslamabadPakistan Information Systems Department Faculty of ManagementComenius University in BratislavaOdbojárovBratislava440Slovakia Prince Sattam bin Abdulaziz University AlKharjSaudi Arabia

Pneumothorax is a thoracic condition that occurs when a person’s lungs collapse,causing air to enter the pleural cavity,the area close to the lungs and chest *** most persistent disease,as well as one that necessitates particular patient care and the privacy of their health *** radiologists find it challenging to diagnose pneumothorax due to the variations in *** learning-based techniques are commonly employed to solve image categorization and segmentation ***,it is challenging to employ it in the medical field due to privacy issues and a lack of *** address this issue,a federated learning framework based on an Xception neural network model is proposed in this *** pneumothorax medical image dataset is obtained from the Kaggle *** preprocessing is performed on the used dataset to convert unstructured data into structured information to improve the model’s ***-max normalization technique is used to normalize the data,and the features are extracted from chest Xray *** dataset converts into two windows to make two clients for local model *** neural network model is trained on the dataset individually and aggregates model updates from two clients on the server *** decrease the over-fitting effect,every client analyses the results three *** 1 performed better in round 2 with a 79.0%accuracy,and client 2 performed better in round 2 with a 77.0%*** experimental result shows the effectiveness of the federated learning-based technique on a deep neural network,reaching a 79.28%accuracy while also providing privacy to the patient’s data.

关键词： Privacy preserving pneumothorax disease federated learning chest x-ray images healthcare machine learning deep learning

来源：评论

学校读者我要写书评

暂无评论

A Smart City Concept for Botswana in the Sub Saharan Region of Africa 2

A Smart City Concept for Botswana in the Sub Saharan Region ...

引用

2nd International Conference on Innovative Sustainable Computational Technologies, CISCT 2022

作者： Andrews, Leo John Baptist Alagappan, Annamalai Venkatachary, Sampath Kumar Sarathkumar, D. Raj, Raymon Antony Botho University Department of Software Engineering Faculty of Computing Botswana Botho University Department of Network and Infrastructure Management Faculty of Engineering and Technology Gaborone Botswana Grant Thornton Botswana Plot 50370 Acument Park Fair Grounds Gaborone Botswana Kongu Engineering College Department of Electrical and Electronics Engineering Tamilnadu Erode638 060 India

ISBN: (纸本)9781665474160

The Internet of Things (IoT) as a technology and its adaptation into mainstreams by various governments across the globe has set developmental pace for many new innovations in IoT. IoTs are transforming cities across globe in the form of ensuring healthcare, understanding traffic, building better and efficient services in the form of delivery in various sectors like energy, water and sanitation etc while improving quality of life and to establish the smart city. This paper place aims to understand some of these technologies and how it can be adopted as technology into the Sub-Sharan African region with a focus on Botswana to make a smart city. The article attempts to highlight key issues that must be resolved to achieve improved IoT adoption for Botswana's development of smart cities in Sub-Saharan Africa. © 2022 IEEE.

关键词： Smart city

来源：评论

学校读者我要写书评

暂无评论

Resource provisioning in collaborative fog computing for multiple delay-sensitive users

Resource provisioning in collaborative fog computing for mul...

引用

作者： Lu, Shuaibing Wu, Jie Wang, Ning Duan, Yubin Liu, Haiming Zhang, Jiayue Fang, Juan Faculty of Information Technology Beijing University of Technology Beijing China Center for Networked Computing Temple University PhiladelphiaPA United States Department of Computer Science Rowan University GlassboroNJ United States School of Software Engineering Beijing Jiaotong University Beijing China

Fog computing is an emerging paradigm that supplies storage, computation, and networking resources between traditional cloud data centers and end devices. This article focuses on the resource provisioning problem in collaborative fog computing for multiple delay-sensitive users. Our goal is to implement a resource provisioning strategy for network operators to minimize the total monetary cost by considering the deadline and capacity constraints. Two scenarios are considered: unlimited-processor fog nodes (UPFN) and limited-processor fog nodes (LPFN). In either scenario, we prove that the resource provisioning problem is NP-hard. First, we consider the UPFN scenario that the processors of fog nodes are unlimited and users' requests can be ideally processed in parallel. Two algorithms are proposed which greedily delete fog nodes based on the local or global collaborative influences until there is no feasible provisioning to guarantee the deadline of users. Then we extend the resource provisioning problem to a more realistic and complicated scenario LPFN in which the scheduling delay cannot be ignored. Two types of tasks are considered. One is the arbitrarily divided tasks, and a near-optimal solution bounded by (Formula presented.) has been found. m is the number of fog nodes, and (Formula presented.) is the upper bound on the Lipschitz constant of the delay function. Another one is the application-driven tasks, and we propose a heuristic algorithm. Extensive experiments validate the efficiency of the proposed algorithms. © 2021 John Wiley & Sons, Ltd.

关键词： Fog

来源：评论

学校读者我要写书评

暂无评论

Studying Risks of Hybrid Reengineering on Air-Transportation Systems Management 'A Case Study on Jordanian Civil Aviation Regulatory Commission (CARC)' 24

Studying Risks of Hybrid Reengineering on Air-Transportation...

引用

24th International Arab Conference on Information Technology, ACIT 2023

作者： Al Refai Mohammed, N. Taani, M.K. Otoom, Ahmed Ali Samara, Ghassan Hanandeh, S.E. Khafajeh, Hayel Zarqa University Software Engineering Dep. Zarqa Jordan Applied Science Private University Cybersecurity and Cloud Computing Dep. Amman Jordan Zarqa University Department of Computer Science Zarqa Jordan Zarqa University Artificial Intelligence Dep. Zarqa Jordan

ISBN: (纸本)9798350384307

This study examines decision-making in software re-engineering within businesses, focusing on the challenges and considerations involved. Financial constraints, time, and staff efforts are critical factors in these decisions. The study identifies difficulties faced by top-level management with legacy systems, existing systems, underused systems, and packaged software due to user resistance and customer dissatisfaction. The primary goal of the study is to assess the importance of software quality factors, especially from the users' perspective, in making re-engineering decisions. It uses the ISO 9126 Model to analyze quality elements in the case study software, aiming to provide guidance for deciding whether to proceed with re-engineering. The study explores functionality, reliability, usability, efficiency, maintainability, and portability as factors influencing re-engineering decisions, based on the ISO 9126 model. To understand user interactions and program performance, the study used unstructured participant observation in the case study software, highlighting the challenges faced by top management due to user resistance. These findings were further confirmed through face-to-face interviews with software users and department employees, offering insights into their perspectives on software quality elements. The results reveal that, despite some flaws, the system has valuable features and capabilities. Most employees express a desire to undergo re-engineering to enhance service quality, align with ISO 9126 standards, and leverage the expertise of competent staff for re-engineering activities. © 2023 IEEE.

关键词： customer dissatisfaction ISO 9126 model decision-making software quality factors software re-engineering User acceptance

来源：评论

学校读者我要写书评

暂无评论

Cybersecurity Risks Mitigation in the Internet of Things 2

Cybersecurity Risks Mitigation in the Internet of Things

引用

2nd International Conference on Innovative Sustainable Computational Technologies, CISCT 2022

作者： Alagappan, Annamalai Andrews, Leo John Baptist Venkatachary, Sampath Kumar Sarathkumar, D. Raj, Raymon Antony Botho University Faculty of Engineering and Technology Department of Network and Infrastructure Management Gaborone Botswana Botho University Faculty of Computing Department of Software Engineering Botswana Grant Thornton Botswana Plot 50370 Acument Park Fair Grounds Gaborone Botswana Kongu Engineering College Department of Electrical and Electronics Engineering Tamilnadu Erode638 060 India

ISBN: (纸本)9781665474160

Internet of Things is a dynamic platform and involves data which in turn attracts cybersecurity threats. Numerous organisations are increasingly placing its focus towards understanding cyber risks in a dynamic and complex environment while also trying to quantify their exposure. This article focuses on addressing the assessment of cybersecurity threats in IoT and its vectors through a risk-based approach using machine learning algorithms while highlighting and discussing the traditional cyber risk assessment techniques at length. Built on the statistics analysis, it can be decided that the Bayesian algorithm performs in estimating the potential risks at 82% and in comparison, the CAQ model using J48 classifies at 94%. The Bayes algorithm also helps in quantifying the complex risks originating from different sources and helps in understanding how the risk factors emerge and connect in an IoT environment and what controls are required for mitigating them. © 2022 IEEE.

关键词： Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

Retrieval-Augmented Generation for Multiple-Choice Questions and Answers Generation 6

Retrieval-Augmented Generation for Multiple-Choice Questions...

引用

6th International Conference on Futuristic Trends in Networks and computing Technologies, FTNCT 2024

作者： Pradeesh, N. Remya, T. Thushara, M.G. Krishna, K. Arun Pranav, V. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India Omnex Software Solutions Pvt. Ltd Thoraipakkam Chennai India Department of Computer Science and Applications Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

Generating a large volume of diverse questions for educational purposes can be a challenging and time-consuming task for educators. Traditional methods like manually writing questions or using templates often fall short when it comes to variety and relevance. In order to cope with these difficulties, we have examined a different approach adopting Retrieval-Augmented Generation (RAG). RAG is an enhancement technique that allows retrieving independent documents and combines it with artificial intelligence that is able to qualitatively generate contextually adequate questions. In this research, RAG was employed through the Ample LMS platform in which PDF documents were the source of generating MCQ questions. The results of the research indicate that with this method, the process of formulating the questions is relatively faster and the questions generated are of better and diverse in nature. With RAG, the burden of constructing questions is lessened for teachers and the students are provided with better interactive learning opportunities. This approach presents a better alternative that is flexible and suitable for various educational requirements, demonstrating the effectiveness of AI in the improvement of the learning and teaching processes. © 2025 The Author(s). Published by Elsevier B.V.

关键词： Teaching

来源：评论

学校读者我要写书评

暂无评论

Multi-Agent Deep Reinforcement Learning for Computation Offloading in Multi-IRS Assisted Mobile Edge computing Networks

Multi-Agent Deep Reinforcement Learning for Computation Offl...

引用

IEEE Conference on Wireless Communications and Networking

作者： Lingxiao Chen Xiuhua Li Chuan Sun Qilin Fan Xiaofei Wang Victor C. M. Leung School of Big Data & Software Engineering Chongqing University Chongqing China TKLAN College of Intelligence & Computing Tianjin University Tianjin China College of Computer Science & Software Engineering Shenzhen University Shenzhen China Department of Electrical & Computer Engineering The University of British Columbia Vancouver Canada

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Mobile edge computing (MEC) as a potential technology can offload tasks from user devices (UDs) to network edges to alleviate network congestion and reduce task execution delay. However, computation offloading faces two challenges: 1) Poor wireless channel quality causes high transmission delay; 2) computing tasks may be obtained by eavesdroppers (Eves) during task offloading. Therefore, we consider deploying intel-ligent reflecting surface (IRS) in MEC networks to increase data transmission rate and ensure data transmission security. This paper investigates the issue of joint computation offloading and resource allocation in a multi-IRS assisted MEC network. Our goal is to minimize task execution delay. To address this problem, we propose a multi-agent deep deterministic policy gradient algorithm to determine the optimal offloading strategy for each UD. Simulation results show that the proposed algorithm can significantly reduce task execution delay and ensure data transmission security.

关键词： Wireless communication Multi-access edge computing Simulation Delays Data communication Security Resource management

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：