检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Du, Qianmin Zhou, Jianhong Ma, Maode School of Computer and Software Engineering Xihua University Sichuan China KINDI Computing Research Center College of Engineering Qatar University Qatar

Vehicle Ad-hoc Networks (VANETs) have experienced significant development in recent years, playing a crucial role in enhancing the driving experience by enabling safer and more efficient inter-vehicle interactions through information exchange. Vehicle-to-vehicle (V2V) communication is particularly vital as it not only helps to prevent collisions and improve traffic efficiency but also provides essential situational awareness to drivers or autonomous driving systems. Communication is typically supported by Roadside Units (RSUs);however, in practical applications, vehicles may exceed the communication range of RSUs, thus exposing them to various malicious attacks. Additionally, considering the limited computational resources of onboard units (OBUs) in vehicles, there is a high demand for designing lightweight security protocols that support V2V communication. To address this issue, this paper proposes an efficient anonymous V2V identity authentication protocol tailored for scenarios that lack RSU support. The proposed protocol has been formally assessed using the Scyther tool, demonstrating its capability to withstand major typical malicious attacks. Performance evaluations indicate that the proposed protocol is efficient in terms of communication and computational overhead, making it a viable solution for V2V vehicle communication. Copyright © 2024, The Authors. All rights reserved.

关键词： Vehicle to vehicle communications

来源：评论

学校读者我要写书评

暂无评论

QoE-oriented Soft Caching with Content Recommendation for Edge computing Networks

QoE-oriented Soft Caching with Content Recommendation for Ed...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Wang, Chenyang Chen, Yan Sun, Chuan Jia, Bosen Wang, Xiaofei Taleb, Tarik Leung, Victor C. M. Shenzhen University College of Computer Science & Software Engineering Shenzhen China Shenzhen518132 China Ruhr University Bochum Faculty of Electrical Engineering and Information Technology Bochum Germany Nanyang Technological University College of Computing and Data Science Singapore China Unicom Digital Technology Co. Ltd Beijing China Tianjin University College of Intelligence and Computing Tianjin China University of British Columbia Vancouver Canada

ISBN: (纸本)9798350351255

Mobile Edge Caching (MEC) can potentially alleviate Internet transmission congestion by delivering content at the network edge. However, current MEC solutions suffer from low resource utilization efficiency and often fail to meet user Quality of Experience (QoE), primarily due to dynamic user requests and obsessive pursuit of direct caching hits. Given the prevalence of recommendation systems, users often lack precise requests when using recommendation-based applications like TikTok and Taobao, insted passively enjoying recommended content. In this paper, we introduce a recommendation-enabled MEC architecture to enhance resource utilization and QoE. We develop a recommendation-enabled soft caching model and formulate the optimization problem as maximizing joint system revenue. To address this, we propose an attention-assisted federated learning deep Q-network algorithm. We conduct the simulations by using the real-world MIND dataset. The results demonstrate that our proposed algorithm outperforms existing baselines, demonstrating its effectiveness in improving resource utilization and QoE. © 2024 IEEE.

关键词： Mobile edge computing

来源：评论

学校读者我要写书评

暂无评论

The Robustness of Spiking Neural Networks in Communication and its Application towards Network Efficiency in Federated Learning

arXiv

引用

arXiv 2024年

作者： Nguyen, Manh V. Zhao, Liang Deng, Bobin Severa, William Xu, Honghui Wu, Shaoen College of Computing and Software Engineering Kennesaw State University Georgia United States Department of Cognitive & Emerging Computing Sandia National Laboratories NM United States

Spiking Neural Networks (SNNs) have recently gained significant interest in on-chip learning in embedded devices and emerged as an energy-efficient alternative to conventional Artificial Neural Networks (ANNs). However, to extend SNNs to a Federated Learning (FL) setting involving collaborative model training, the communication between the local devices and the remote server remains the bottleneck, which is often restricted and costly. In this paper, we first explore the inherent robustness of SNNs under noisy communication in FL. Building upon this foundation, we propose a novel Federated Learning with Top-κ Sparsification (FLTS) algorithm to reduce the bandwidth usage for FL training. We discover that the proposed scheme with SNNs allows more bandwidth savings compared to ANNs without impacting the model’s accuracy. Additionally, the number of parameters to be communicated can be reduced to as low as 6% of the size of the original model. We further improve the communication efficiency by enabling dynamic parameter compression during model training. Extensive experiment results demonstrate that our proposed algorithms significantly outperform the baselines in terms of communication cost and model accuracy and are promising for practical network-efficient FL with SNNs. Copyright © 2024, The Authors. All rights reserved.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Motivational factors and Challenges in the adoption of latest digital technology in educational institutes: A thematic analysis

引用

Procedia Computer Science 2024年 239卷 1670-1677页

作者： Maryam Gulzar Kari Smolander Arshad Ali Bilal Naqvi Department of Software Engineering LUT University Lappeenranta 53851 Finland FAST School of Computing National University of Computer and Emerging Sciences Lahore 54770 Pakistan

Information technology infrastructure (ITI) has gone through an exponential change due to the rapid evolution of digital technologies during the past few years. It is therefore relevant to identify the factors that push organizations towards the adoption of new technologies. This paper considers a specific case study of the higher education institutions (HEI) to present (i) the motivational factors that push HEIs toward the adoption of new technologies, and (ii) the key challenges HEIs face in the adoption of these technologies. The data was gathered after conducting 17 open-ended interviews with practitioners working at HEIs in Finland and Pakistan. Data analysis identified 10 motivational factors and 41 challenges faced by HEI in the adoption of the latest technologies. Furthermore, the data was further classified to identify broad themes and categories representing the challenges and motivation factors.

关键词： Challenges Motivational factors Technology adoption IT infrastructure

来源：评论

学校读者我要写书评

暂无评论

Hybrid Automated Program Repair by Combining Large Language Models and Program Analysis

arXiv

引用

arXiv 2024年

作者： Li, Fengjie Jiang, Jiajun Sun, Jiajun Zhang, Hongyu College of Intelligence and Computing Tianjin University China School of Big Data and Software Engineering Chongqing University China

Automated Program Repair (APR) has garnered significant attention due to its potential to streamline the bug repair process for human developers. Recently, LLM-based APR methods have shown promise in repairing real-world bugs. However, existing APR methods often utilize patches generated by LLMs without further optimization, resulting in reduced effectiveness due to the lack of program-specific knowledge. Furthermore, the evaluations of these APR methods have typically been conducted under the assumption of perfect fault localization, which may not accurately reflect their real-world effectiveness. To address these limitations, this paper introduces an innovative APR approach called GIANTREPAIR. Our approach leverages the insight that LLM-generated patches, although not necessarily correct, offer valuable guidance for the patch generation process. Based on this insight, GIANTREPAIR first constructs patch skeletons from LLM-generated patches to confine the patch space, and then generates high-quality patches tailored to specific programs through context-aware patch generation by instantiating the skeletons. To evaluate the performance of our approach, we conduct two large-scale experiments. The results demonstrate that GIANTREPAIR not only effectively repairs more bugs (an average of 27.78% on Defects4J v1.2 and 23.40% on Defects4J v2.0) than using LLM-generated patches directly, but also outperforms state-of-the-art APR methods by repairing at least 42 and 7 more bugs under perfect and automated fault localization scenarios, respectively. © 2024, CC BY.

关键词： Repair

来源：评论

学校读者我要写书评

暂无评论

Predicting Lung Cancer Recurrence Using a Mobile Application Framework

Predicting Lung Cancer Recurrence Using a Mobile Application...

引用

Emerging Trends in Smart Technologies (ICETST), 2020 International Conference on

作者： M. Imran Saeed Fahad Sherwani FAST School of Computing National University of Computer and Emerging Sciences Karachi Pakistan Department of Software Engineering MAJU

ISBN: (数字)9798331515850

ISBN: (纸本)9798331515867

It is a well-known fact that globally, lung cancer is the major issue that causes number of people to expire; this is due to the fact of its recurrence that is an important concern for those who have survived it. This article presents a mobile app framework which uses past medical records and chest X-ray images to predict possible reoccurrence of lung cancer. The framework includes elements such as data preparation, transfer learning through image classifiers, and CDC-Net which is a specialized model. Users interact with the app by carrying out self-assessments and entering their medical history. This information undergoes standardization or processing particularly for radiographic pictures like chest x -rays. Specifically, categorizes datasets are used in training the Chest Disease Classification Network model to determine whether there is a danger of another outbreak taking place or not. The app gives personalized predictions such as a likelihood ratio for return and provides medical advice along with preventive steps based on the findings presented herein. The strategy seeks to educate users on how to manage their own health effectively.

关键词： Training Transfer learning Lung cancer Standardization Medical services Market research Mobile handsets Mobile applications X-ray imaging Biomedical imaging

来源：评论

学校读者我要写书评

暂无评论

ThyroidNet:A Deep Learning Network for Localization and Classification of Thyroid Nodules

引用

Computer Modeling in engineering & Sciences 2024年第4期139卷 361-382页

作者： Lu Chen Huaqiang Chen Zhikai Pan Sheng Xu Guangsheng Lai Shuwen Chen Shuihua Wang Xiaodong Gu Yudong Zhang Ultrasonic Department Zhongda Hospital Affiliated to Southeast UniversityNanjing210009China School of Physics and Information Engineering Jiangsu Second Normal UniversityNanjing211200China School of Computing and Mathematical Sciences University of LeicesterLeicesterLE17RHUK Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia State Key Laboratory of MillimeterWaves Southeast UniversityNanjing210096China Jiangsu Province Engineering Research Center of Basic Education Big Data Application Jiangsu Second Normal UniversityNanjing211200China School of Software Engineering Quanzhou Normal UniversityQuanzhou362000China Department of Biological Sciences Xi’an Jiaotong-Liverpool UniversitySuzhou215123China

Aim:This study aims to establish an artificial intelligence model,ThyroidNet,to diagnose thyroid nodules using deep learning techniques ***:A novel method,ThyroidNet,is introduced and evaluated based on deep learning for the localization and classification of thyroid ***,we propose the multitask TransUnet,which combines the TransUnet encoder and decoder with multitask ***,we propose the DualLoss function,tailored to the thyroid nodule localization and classification *** balances the learning of the localization and classification tasks to help improve the model’s generalization ***,we introduce strategies for augmenting the ***,we submit a novel deep learning model,ThyroidNet,to accurately detect thyroid ***:ThyroidNet was evaluated on private datasets and was comparable to other existing methods,including U-Net and *** results show that ThyroidNet outperformed these methods in localizing and classifying thyroid *** achieved improved accuracy of 3.9%and 1.5%,***:ThyroidNet significantly improves the clinical diagnosis of thyroid nodules and supports medical image analysis *** research directions include optimization of the model structure,expansion of the dataset size,reduction of computational complexity and memory requirements,and exploration of additional applications of ThyroidNet in medical image analysis.

关键词： ThyroidNet deep learning TransUnet multitask learning medical image analysis

来源：评论

学校读者我要写书评

暂无评论

Open-Book Neural Algorithmic Reasoning

arXiv

引用

arXiv 2024年

作者： Li, Hefei Peng, Chao Xu, Chenyang Yang, Zhengfeng Shanghai Key Laboratory of Trustworthy Computing Software Engineering Institute East China Normal University Shanghai China

Neural algorithmic reasoning is an emerging area of machine learning that focuses on building neural networks capable of solving complex algorithmic tasks. Recent advancements predominantly follow the standard supervised learning paradigm - feeding an individual problem instance into the network each time and training it to approximate the execution steps of a classical algorithm. We challenge this mode and propose a novel open-book learning framework. In this framework, whether during training or testing, the network can access and utilize all instances in the training dataset when reasoning for a given instance. Empirical evaluation is conducted on the challenging CLRS Algorithmic Reasoning Benchmark, which consists of 30 diverse algorithmic tasks. Our open-book learning framework exhibits a significant enhancement in neural reasoning capabilities. Further, we notice that there is recent literature suggesting that multi-task training on CLRS can improve the reasoning accuracy of certain tasks, implying intrinsic connections between different algorithmic tasks. We delve into this direction via the open-book framework. When the network reasons for a specific task, we enable it to aggregate information from training instances of other tasks in an attention-based manner. We show that this open-book attention mechanism offers insights into the inherent relationships among various tasks in the benchmark and provides a robust tool for interpretable multi-task training. Copyright © 2024, The Authors. All rights reserved.

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

UX Researchers in the Information Technology Field in Sri Lanka: Why So Few?

UX Researchers in the Information Technology Field in Sri La...

引用

Advances in Technology and computing (ICATC), International Conference on

作者： Bimali Wickramasinghe Lankeshwara Munasinghe Nimasha Arambepola Software Engineering Teaching Unit University of Kelaniya Sri Lanka School of Computing Engineering and Technology Robert Gordan University Aberdeen Scotland

ISBN: (数字)9798331518219

ISBN: (纸本)9798331518226

User experience research (UXR) is a new career that is emerging in the world. People who engage in this career, known as UX (User Experience) researchers, provide immense support for Information Technology (IT) from the aspect of Human-Computer Interaction (HCI) and UX. Yet professional employee in this career is very few to find in the IT industry in Sri Lanka. The goal of this research was to find issues and restrictions experienced in the academia and IT industry that affect the growth of the UX researcher profession in Sri Lanka. This research utilized a mixed methodology where the qualitative study was conducted to gain in-depth insights from industry experts, allowing for a deeper exploration of the underlying causes of the shortage of UX researchers in Sri Lanka, and a survey-based quantitative and qualitative analysis was conducted among undergraduate students enrolled in IT-related degree programs to examine their perspectives on the shortage of UX researchers in Sri Lanka. The study determined that the main reason for the limited pool of UX researchers in Sri Lanka is a deficiency in interest in the UXR role, particularly regarding career opportunities and UX research practices. The research uncovered more facts associated with the scarcity of UXR roles which should be examined in future studies.

关键词： Industries Human computer interaction engineering profession Education Companies User experience Remuneration Information technology

来源：评论

学校读者我要写书评

暂无评论

Design of a Secured and Trusted E-Voting System Using Blockchain Technology

Design of a Secured and Trusted E-Voting System Using Blockc...

引用

SmartBlock4Africa, IEEE

作者： Elegba Jeremiah. O. Agbelusi O. Olutayo Victor A. Akintola Kolawole G. Department of Software Engineering School of Computing The Federal University of Technology Akure Nigeria Department of Computer Science School of Computing The Federal University of Technology Akure Nigeria

ISBN: (数字)9798350376838

ISBN: (纸本)9798350376845

The state of election in Nigeria is worrisome. Electoral malpractices have been a major challenge to the Nigerian government in recent times. Government has made frantic efforts to tackle these electoral challenges but the recent event in year 2023 presidential election is worrisome suggests that the solution is not near. Recently, the percentage of eligible voters who vote on election days is declining. Voters turnout went up from 52.3% in 1999 - the first general election since 1993 - to 69% in 2003. But, it has been on the decline nearly ever since − 57.5% in 2007, 53.7% in 2011, 43.7% in 2015 and 34.8% in 2019. In 2023, it is 28.63%. With the way things are going, if urgent action is not taken, this could signal the end of democracy in Nigeria. This research presents the design and implementation of a trusted and secured e-voting based on blockchain technology that will increase voters confidence and trust. The system utilizes *** for the frontend and Solidity on the Polygon blockchain for the backend, ensuring transparency, tamper-resistance, and heightened security. This innovative approach addresses trust and reliability concerns in traditional voting systems, offering a modernized and trustworthy electoral process.

关键词： Smart contracts Authentication Blockchains Reliability Security Electronic voting

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：