检索结果-内蒙古大学图书馆

1st International Conference on Computer science and Emerging Technologies, CSET 2023

作者： Alkhazali, Abdel Rahman Mohammad Khasawneh, Ahmad M. Alzoubi, Sharaf Magableh, Murad Mohamed, Rajina R. Pandey, Bishwajeet Irbid National University Faculty of Business and Financial Science MIS Bi and Data Analysis Department Irbid Jordan Department of Information Technology Jordan College of Computing Dan Informatics Universiti Tenaga Nasional Malaysia Eurasian National University Astana It University Astana Kazakhstan Jain Deemed to Be University Bangalore India

ISBN: (纸本)9798350341737

The rapid development of cloud computing technologies has revolutionized various sectors, and smart cities are no exception. Smart cities leverage cloud computing to optimize urban services, enhance resource management, and improve the overall quality of life for their inhabitants. However, as these technological advancements proliferate, concerns about privacy, ethical considerations, and social implications have emerged. This research paper critically examines the multifaceted challenges associated with the integration of cloud computing in smart cities, shedding light on the potential risks and highlighting the need for comprehensive solutions. The research employs a mixed-methods approach, combining quantitative data analysis and qualitative case studies to offer a comprehensive perspective on the identified issues. The primary focus lies in identifying privacy risks, ethical dilemmas, and social disparities that arise due to the extensive use of cloud-based systems and data in smart cities. Furthermore, the study investigates the role of key stakeholders, including governments, technology providers, and citizens, in mitigating or exacerbating these challenges. Key findings reveal that while cloud computing empowers smart cities with unparalleled capabilities, it also exposes residents' personal information to potential breaches and misuse. Ethical concerns arise from the handling of sensitive data, data ownership, and algorithmic biases that could perpetuate discrimination. Moreover, social issues like the digital divide and access disparities may further exacerbate existing inequalities in smart city implementation. This research paper concludes by proposing a comprehensive framework of guidelines and best practices to address the identified issues effectively. These recommendations encompass enhanced data privacy measures, transparent and accountable data governance, the promotion of ethical data usage, and inclusive strategies to bridge social disparities. B

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

引用

Computers, Materials & Continua 2024年第10期81卷 1029-1057页

作者： Vincent Omollo Nyangaresi Arkan A.Ghaib Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennaiTamilnadu602105India Information Technology Department Management Technical CollegeSouthern Technical UniversityBasrah61004Iraq Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq College of Big Data and Internet Shenzhen Technology UniversityShenzhen518118China Huazhong University of Science and Technology Shenzhen InstituteShenzhen518000China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen518060China Computer Technology Engineering Department Iraq University CollegeBasrah61004Iraq Department of Mathematics College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq Institute of Mathematics University of DebrecenDebrecenH-4002Hungary Department of Electrical Engineering and Mechatronics Faculty of EngineeringUniversity of DebrecenDebrecen4028Hungary

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation ***,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy *** address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed ***,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many *** such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)*** formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably *** proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and ***,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and *** the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security ***,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

关键词： Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)

来源：评论

学校读者我要写书评

暂无评论

An Early Detection Model of Prostate Cancer Based on MRI 9

An Early Detection Model of Prostate Cancer Based on MRI

引用

9th IEEE International Conference on data science in Cyberspace, DSC 2024

作者： Liu, Yuankun Xing, Lumin Wang, Di Nie, Xin Zhang, Xueyan Wu, Di Liu, Wenjian The First Affiliated Hospital of Shandong First Medical University Shandong Provincial Qianfoshan Hospital Jinan China City University of Macau Faculty of Data Science China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China Chongqing Jianzhu College Chongqing China Shandong Youth University of Political Science School of Information Work Office Jinan China University of Southern Queensland School of Mathematics Physics and Computing QLD Australia

ISBN: (纸本)9798350391367

Prostate cancer is a prevalent form of cancer among men, with a high rate of occurrence but relatively lower mortality compared to other types of cancer. Early detection is crucial because it allows for earlier intervention, potentially preventing progression to more severe stages, and improving patient outcomes. However, human diagnosis is time-consuming and inefficient, an autonomous early detection system is essential for saving lives. To address this challenge, we propose a novel MoE-MRIViT framework that uses advanced machine learning and computer vision techniques to analyze MRI images and identify features indicative of prostate cancer. The system processes the data using a vision transformer to extract precise prostate cancer features from MRI scans, and uses attention mechanisms to focus on significant areas. Through the MoE-MRIViT intervention in two stages, we have achieved superior results compared to the state-of-the-art (SOTA) methods. Experimental results demonstrate that our model achieves an impressive accuracy of 94.84%, outperforming the ResNet-101 and the basic ViT models, which achieve accuracies of 89.4% and 92.31%, respectively. © 2024 IEEE.

关键词： Urology

来源：评论

学校读者我要写书评

暂无评论

A Prompt Learning Framework for Source Code Summarization

arXiv

引用

arXiv 2023年

作者： Xu, Tingting Miao, Yun Fang, Chunrong Qian, Hanwei Feng, Xia Chen, Zhenpeng Wang, Chong Zhang, Jian Sun, Weisong Chen, Zhenyu Liu, Yang College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore State Key Laboratory for Novel Software Technology Nanjing University Nanjing210093 China Faculty of Data Science City University of Macau 999078 China

(Source) code summarization is the task of automatically generating natural language summaries (also called comments) for given code snippets. Recently, with the successful application of large language models (LLMs) in numerous fields, software engineering researchers have also attempted to adapt LLMs to solve code summarization tasks. The main adaptation schemes include instruction prompting, task-oriented (full-parameter) fine-tuning, and parameter-efficient fine-tuning (PEFT). However, instruction prompting involves designing crafted prompts and requires users to have professional domain knowledge, while task-oriented fine-tuning requires high training costs, and effective, tailored PEFT methods for code summarization are still lacking. In this paper, we propose an effective prompt learning framework for code summarization called PromptCS. It no longer requires users to rack their brains to design effective prompts. Instead, PromptCS trains a prompt agent that can generate continuous prompts to unleash the potential for LLMs in code summarization. Compared to the human-written discrete prompt, the continuous prompts are produced under the guidance of LLMs and are therefore easier to understand by LLMs. PromptCS is non-invasive to LLMs and freezes the parameters of LLMs when training the prompt agent, which can greatly reduce the requirements for training resources. We evaluate the effectiveness of PromptCS on the CodeSearchNet dataset involving multiple programming languages. Experimental results show that PromptCS significantly outperforms instruction prompting schemes (including zero-shot learning and few-shot learning) on all four widely used metrics, including BLEU, METEOR, ROUGE-L, and SentenceBERT, and is comparable to the task-oriented fine-tuning scheme. In some base LLMs, e.g., CodeGen-Multi-2B and StarCoderBase-1B and -3B, PromptCS even outperforms the task-oriented fine-tuning scheme. More importantly, the training efficiency of PromptCS is faster tha

关键词： Application programs

来源：评论

学校读者我要写书评

暂无评论

Quantifying the Benefits of Implementing Big data Analytics on Consumers’ Online Purchase Intentions in e-Commerce

Quantifying the Benefits of Implementing Big Data Analytics ...

引用

2024 IEEE International Conference on computing, ICOCO 2024

作者： Wei, Justin Ang Kang Mansor, Mahayaudin M. Derasit, Zuraidah Bakar, Mohd Aftar Abu Ul-Saufie, Ahmad Zia Hamzah, Firdaus Mohamad Faculty of Business Economics and Accounting HELP University Kuala Lumpur Malaysia School of Mathematical Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Malaysia Institute for Big Data Analytics and Artificial Intelligence Universiti Teknologi MARA Selangor Shah Alam Malaysia Department of Mathematical Sciences Faculty of Science & Technology Universiti Kebangsaan Malaysia Malaysia Centre for Defence Foundation Studies Universiti Pertahanan Nasional Malaysia Kuala Lumpur Malaysia

ISBN: (纸本)9798331530303

The digital revolution has reshaped the global economy, especially e-commerce. Innovative technologies such as big data analytics, artificial intelligence, and cloud computing drive this transformation, enabling companies to make informed business decisions and influence consumers’ online purchasing behaviour. This study explores empirical evidence for the benefits of using big data analytics (BDA) to influence consumers’ online purchasing decisions in e-commerce. Primary data was collected via an online survey targeting 300 customers with online shopping experience on platforms that have adopted the digital technologies of BDA. Statistical methods used in this study included questionnaire design, reliability test, descriptive analysis, and multiple regression modelling and diagnostics. The findings indicate that the benefits of implementing BDA in e-commerce for information search, recommendation systems, consumer services, dynamic pricing, security and fraud detection are strongly associated with consumers’ online purchasing intentions. The study underscores the importance of businesses leveraging BDA, as the benefits significantly and positively impact consumers’ purchasing intentions in e-commerce while addressing security and fraud detection concerns that undermine its advantage. Nevertheless, we encourage all companies to leverage BDA implementation in their digital marketplace, which ultimately contributes to achieving e-commerce goals, such as increased market reach, cost reduction, and revenue growth. ©2024 IEEE.

关键词： Marketplaces

来源：评论

学校读者我要写书评

暂无评论

Regression Analysis of Humidity and Temperature on Chicken Lifespan

Regression Analysis of Humidity and Temperature on Chicken L...

引用

Agrosystem Engineering, Technology & Applications (AGRETA), IEEE International Conference on

作者： Sittilin Salleh Razak Mohd Ali Lee Nurul Rawaida Ain Burhani Kennedy Juani Farah Hasanah Ab Jaid Electrical and Electronics Engineering Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Sabah Malaysia Mechanical Engineering Faculty of Mechanical Engineering Universiti Teknologi Malaysia Johor Malaysia Department of Veterinary Services Sabah Malaysia Computer Science (Data Science) Faculty of Computing & Informatics Universiti Malaysia Sabah

ISBN: (数字)9798350373660

ISBN: (纸本)9798350373677

This study presents a comprehensive analysis of the effects of humidity and temperature variations on the lifespan of Ross broiler chickens at two different locations over two 35-day experimental periods. The study initially included a group of 20 chickens, followed by another group of 41 chickens. Through rigorous regression analysis, the research evaluates the correlation between environmental variables and chicken lifespan, using a multi-sensor system integrated with IoT technology to monitor temperature and humidity values in poultry farms. The results presented in significant MSE and R 2 values for Batch 2 using correlation matrix and polynomial regression provide valuable insights for optimizing poultry management practices.

关键词： Temperature sensors Temperature measurement Correlation Humidity Polynomials Regression analysis Monitoring

来源：评论

学校读者我要写书评

暂无评论

A Graph-Transformer for Whole Slide Image Classification

引用

IEEE Transactions on Medical Imaging 2022年第11期41卷 3003-3015页

作者： Zheng, Yi Gindra, Rushin H. Green, Emily J. Burks, Eric J. Betke, Margrit Beane, Jennifer E. Kolachalama, Vijaya B. Boston University Department of Computer Science BostonMA02215 United States Boston University School of Medicine Department of Medicine BostonMA02218 United States Boston University School of Medicine Department of Pathology and Laboratory Medicine BostonMA02218 United States Boston University Faculty of Computing and Data Sciences Department of Computer Science BostonMA02215 United States

Deep learning is a powerful tool for whole slide image (WSI) analysis. Typically, when performing supervised deep learning, a WSI is divided into small patches, trained and the outcomes are aggregated to estimate disease grade. However, patch-based methods introduce label noise during training by assuming that each patch is independent with the same label as the WSI and neglect overall WSI-level information that is significant in disease grading. Here we present a Graph-Transformer (GT) that fuses a graph-based representation of an WSI and a vision transformer for processing pathology images, called GTP, to predict disease grade. We selected 4,818 WSIs from the Clinical Proteomic Tumor Analysis Consortium (CPTAC), the National Lung Screening Trial (NLST), and The Cancer Genome Atlas (TCGA), and used GTP to distinguish adenocarcinoma (LUAD) and squamous cell carcinoma (LSCC) from adjacent non-cancerous tissue (normal). First, using NLST data, we developed a contrastive learning framework to generate a feature extractor. This allowed us to compute feature vectors of individual WSI patches, which were used to represent the nodes of the graph followed by construction of the GTP framework. Our model trained on the CPTAC data achieved consistently high performance on three-label classification (normal versus LUAD versus LSCC: mean accuracy = 91.2 ± 2.5%) based on five-fold cross-validation, and mean accuracy = 82.3 ± 1.0% on external test data (TCGA). We also introduced a graph-based saliency mapping technique, called GraphCAM, that can identify regions that are highly associated with the class label. Our findings demonstrate GTP as an interpretable and effective deep learning framework for WSI-level classification. © 1982-2012 IEEE.

关键词： Tumors

来源：评论

学校读者我要写书评

暂无评论

ReviewRanker: A Semi-supervised Learning-Based Approach for Code Review Quality Estimation 6th

ReviewRanker: A Semi-supervised Learning-Based Approach for ...

引用

6th International Conference on Recent Innovations in computing, ICRIC 2023

作者： Mahbub, Saifullah Easin Arafat, Md. Rahman, Chowdhury Rafeed Ferdows, Zannatul Hasan, Masum Department of Computer Science and Engineering United International University United City Madani Avenue Dhaka1212 Bangladesh Data Science and Engineering Department Faculty of Informatics Eötvös Loránd University Pázmány Péter Str. 1/A Budapest1117 Hungary Department of Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka1000 Bangladesh School of Computing National University of Singapore Singapore Singapore Department of Computer Science University of Rochester RochesterNY United States

ISBN: (纸本)9789819734412

Code review is considered a key process in the software industry for minimizing bugs and improving code quality. Inspection of review process effectiveness and continuous improvement can boost development productivity. Such inspection is a time-consuming and human-bias-prone task. We propose a semi-supervised learning-based system ReviewRanker which is aimed at assigning each code review a confidence score which is expected to resonate with the quality of the review. Our proposed method is trained based on simple and well-defined labels provided by developers. The labeling task requires little to no effort from the developers and has an indirect relation to the end goal (assignment of review confidence score). ReviewRanker is expected to improve industry-wide code review quality inspection by reducing human bias and the effort required for such a task. The system has the potential of minimizing the back-and-forth cycle existing in the development and review process. Usable code and dataset for this research can be found at: https://***/saifarnab/code_review. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

C Programming Skill Levels Determination Using Fuzzy Logic 7

C Programming Skill Levels Determination Using Fuzzy Logic

引用

7th International Conference on Software Engineering and Computer Systems and 4th International Conference on Computational science and Information Management, ICSECS-ICOCSIM 2021

作者： Aiman Al-Falah Muhd Yazid, Muhammad Azida Sahabudin, Noor Farihan Mat Raffei, Anis Akmal Remli, Muhammad Universiti Malaysia Pahang Faculty of Computing Pahang Pekan Malaysia Universiti Malaysia Kelantan Department of Data Science Kota Bahru Kelantan Malaysia

ISBN: (纸本)9781665414074

Programming language is known among computer science students. One should know at least one programming language throughout their studies. However, mastering one programming language is challenging. Most of the new student find challenging to learn and understand the language as they are not familiar with it. This can cause a problem throughout their studies or even in future jobs. Thus, implementing artificial intelligence to identify students' understandability level towards programming skills is expected to improve their knowledge and weakness about that programming language. This paper presents proposed work for designing the level of programming knowledge for new computer science student. The level of programming knowledge is identified and analyzed based on the student input. The fuzzy logic approach is employed in this study to obtain the target result based on several criterion. Several tools are used to develop the platform for collecting user input data. The output of this work shows that the student can identify their element on each spoke and the programming language level with a short description by displaying data visualization as the output to user in the radar chart. © 2021 IEEE.

关键词： Membership functions

来源：评论

学校读者我要写书评

暂无评论

Optimizing Diabetic Foot Ulcer Detection: Leveraging SSD and YOLO Architectures

Optimizing Diabetic Foot Ulcer Detection: Leveraging SSD and...

引用

International Symposium on High Capacity Optical Networks and Enabling Technologies, HONET

作者： Muhammad Azeem Muhammad Zaman Adnan Akhunzada Tanzila Kehkashan Imran Ashraf Abdul Rehman Department of Computer Science The University of Lahore Sargodha Pakistan Department of Computer Science COMSATS University Islamabad Islamabad Pakistan Department of Data and Cybersecurity University of Doha for Science and Technology Doha Qatar Faculty of Computing Universiti Teknologi Malaysia Johor Bahru Malaysia Faculty of Computer Science The University of Lahore Sargodha Pakistan

ISBN: (数字)9798350378078

ISBN: (纸本)9798350378085

Diabetic foot ulcer (DFU) are a severe complication in diabetic patients, requiring accurate and early diagnosis to prevent further complications such as infection or amputation. To address this, Research employed YOLO and SSD models for automated DFU detection from medical images, comparing their performance based on key evaluation metrics, including accuracy, precision, recall, and F1-score. Results demonstrate that both models perform exceptionally well, with SSD achieving an accuracy of 98.7%, surpassing YOLO's 97.5%. Additionally, SSD exhibited superior precision (99%), recall (98.9%), and F1-score (99.1%), indicating its robustness in detecting ulcerated regions of varying sizes and stages. These results were further contextualized through a comparison with previous studies, where SSD outperformed several CNN-based models, which achieved accuracy ranging from 93.7% to 97.0%. The SSD model's multi-scale object detection capabilities, combined with transfer learning and data augmentation techniques, contributed to its high performance. Overall, this study demonstrates the potential of deploying SSD and YOLO models in clinical settings for early and accurate DFU detection, paving the way for more reliable and timely interventions in diabetic care. The findings underline the significance of advanced object detection methods, offering promising avenues for improving patient outcomes in medical imaging

关键词： YOLO Accuracy Smart cities Computational modeling Transfer learning Robustness Distance measurement Diabetes Medical diagnostic imaging Robots

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：