检索结果-内蒙古大学图书馆

engineering & Computing Technologies (ICECT), International Conference on

作者： Muhammad Ahmed Umer Liaquat Attique Ur Rehman Sabeen Javaid Tahir Muhammad Ali Azka Mir Department of Software Engineering University of Sialkot Sialkot Pakistan Department of Computer Science Gulf University for Science and Technology Kuwait

ISBN: (数字)9798350349719

ISBN: (纸本)9798350349726

Brain stroke is the world's leading cause of death, impacting numerous lives annually. The chances of having a stroke have increased by 50% over one's lifetime, impacting one in four people worldwide. Machine learning may assist in the prior detection of strokes, allowing for more timely diagnosis which can save a person's life and disability. However, existing methods face challenges in integrating ML models with clinical applications to predict patient stroke status with optimal accuracy. This study conducts a comprehensive investigation into brain stroke risk prediction using numerous ML algorithms, including Random Forest, Logistic Regression, KNN, Naive Bayes, XGBoost, and LightGBM. Our main contribution is the development of a web app that predicts stroke based on user inputs with optimal accuracy. The selected dataset contains 5110 records of normal people and 249 records of people having strokes which is highly imbalanced. To ensure model robustness, the dataset undergoes balancing through SMOTE oversampling and KNN Imputation for handling missing values. Custom thresholds for classifiers optimize training, with comprehensive evaluations utilizing key statistics such as confusion matrices, F1-Score, recall, accuracy, and precision. Cross-validation is employed to assess potential overfitting and underfitting risks in machine learning models. Random Forest ranked as the most imposing, reaching a remarkable 99.85% accuracy on the test set with a custom threshold of 0.6 and a random state at 42. Additionally, a user-friendly Web App has been developed to predict stroke status based on user input, enhancing practical usability and accessibility for individuals seeking risk assessments.

关键词： Training Logistic regression Accuracy Predictive models Prediction algorithms Robustness Imputation

来源：评论

学校读者我要写书评

暂无评论

On Federated Multi-Armed Bandits for Mobile Social Networks

On Federated Multi-Armed Bandits for Mobile Social Networks

引用

International Conference on Distributed Computing Systems

作者： Kazuya Sakai Takeshi Kitamura Min-Te Sun Wei-Shinn Ku Department of Electrical Engineering and Computer Science Tokyo Metropolitan University Tokyo Japan Department of Computer Science and Information Engineering National Central University Taoyuan Taiwan Department of Computer Science and Software Engineering Auburn University Auburn Alabama USA

ISBN: (数字)9798350386059

ISBN: (纸本)9798350386066

Multi-armed bandits (MABs) are widely used for decision making processes, in which an agent tries to maximize a long-term reward by balancing exploiting and exploring actions. In this paper, we are particularly interested in federated MABs for mobile social networks (MSNs), where a collection of agents learn action values by locally observing rewards and exchanging estimated action values with other agents. Our research differs from the existing federated MABs in the underlying network setting, such that agents can communicate with each other only at opportunistic contact events. To this end, we first design the weighted-connectivity (WC) centrality to quantify the importance of agents in an MSN, and then, we propose the weighted-connectivity upper confidence bound (WC-UCB) algorithm for the MSN contexts. The key idea to reduce biases at each agent and to utilize limited opportunities of federated updates is to prioritize the estimates of action-value functions computed by the agents with a high WC centrality. In addition, the performance bound in terms of the cumulative regret is analyzed. The performance of the proposed algorithm is evaluated by simulations using real mobility traces and the results demonstrate that our WC-UCB outperforms the state-of-the-art algorithms in terms of the average reward and the cumulative regret.

关键词： Social networking (online) Simulation Computational modeling Decision making Optical wavelength conversion Complexity theory Distributed computing

来源：评论

学校读者我要写书评

暂无评论

Aerial Vehicle Detection and Classification Through Fusion of Multi-Domain Features of Acoustic Signals

Aerial Vehicle Detection and Classification Through Fusion o...

引用

2024 International Conference on engineering and Computing, ICECT 2024

作者： Sumble, Malaika Aziz, Sumair Khan, Muhammad Umar Iqtidar, Khushbakht Fernandez-Rojas, Raul University of Engg. and Tech. Taxila Department of Electronics Engineering Taxila Pakistan University of Canberra Faculty of Science and Technology CanberraACT Australia National University of Sciences & Tech. Dept. of Computer and Software Engineering Islamabad Pakistan

ISBN: (纸本)9798350349719

Detection of aerial vehicles is a challenging task. Over time, the significance of developing such vehicles has increased rapidly. However, an utmost concern arises from the potential misuse of these small-sized vehicles in illicit activities such as unauthorized surveillance, smuggling contraband, or disrupting critical infrastructure significant security threats. Recognizing the gravity of this issue, we have opted to introduce an innovative approach to automate the detection processes for aerial vehicles. This initiative aims to deploy effective drone detection systems to mitigate risks and safeguard against illegal activities. We put use to two datasets from GitHub depot. Cepstral, spectral, and time domain features were extracted from the data, followed by classification. We conducted two experiments, with the first (Drone, No-Drone) yielding 98.6% accuracy, using the Ensemble (Bagged Trees) classifier. The second set of experimentation addressed five classes: Background Noises, Bebop Drone, Drone, Helicopter, and Mambo Drone. Ensemble (Bagged trees) again outperformed all other classifiers and achieved 98.3% accuracy. The results highlight that our proposed framework gives effective results based on audio signals of different aerial vehicles. © 2024 IEEE.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

PPDMIT: a lightweight architecture for privacy-preserving data aggregation in the Internet of Things

引用

Journal of Ambient Intelligence and Humanized Computing 2023年第5期14卷 5211-5223页

作者： Gheisari, Mehdi Javadpour, Amir Gao, Jiechao Abbasi, Aaqif Afzaal Pham, Quoc-Viet Liu, Yang Department of Computer Science and Technology Harbin Institute of Technology Shenzhen China Department of Computer Science University of Virginia VA United States Department of Software Engineering Foundation University Islamabad44000 Pakistan Korean Southeast Center for the 4Th Industrial Revolution Leader Education Pusan National University Busan46241 Korea Republic of ADiT-Lab Electrotechnics and Telecommunications Department Instituto Politécnico de Viana do Castelo Porto4900-347 Portugal

Data is generated over time by each device in the Internet of Things (IoT) ecosphere. Recent years have seen a resurgence in interest in the IoT due to its positive impact on society. However, due to the automatic management of IoT devices, the possibility of disclosing sensitive information without user consent is high. A situation in which information should not be unintentionally disclosed to outside parties we do not trust, i.e., privacy-preservation. Additionally, IoT devices should share their data with others to perform data aggregation and provide high-level services. There is a trade-off between the amount of data utility and the amount of disclosure of data. This trade-off has been causing a big challenge in this field. To improve the efficiency of this trade-off rather than current studies, in this study, we propose a Privacy-Preserving Data Aggregation architecture, PPDMIT, that leverages Homomorphic Paillier Encryption (HPE), K-means, a One-way hash chain, and the Chinese Remainder Theorem (CRT). We have found that the proposed privacy-preserving architecture achieves more efficient data aggregation than current studies and improves privacy preservation by utilizing extensive simulations. Moreover, we found that our proposed architecture is highly applicable to IoT environments while preventing unauthorized data disclosure. Specifically, our solution depicted an 8.096% improvement over LPDA and 6.508% over PPIOT. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Video Surveillance-Based Intrusion Detection System in Edge Cloud Environment 3rd

Video Surveillance-Based Intrusion Detection System in Edge ...

引用

3rd International Conference on Emergent Converging Technologies and Biomedical Systems, ETBS 2023

作者： Sharma, Annu Devasenapathy, Deepa Raja, M. Shadrach, Finney Daniel Shirgire, Anil Arun, R. Yau, Thomas Moh Shan Department of Computer Science and Applications Rajarajeshwari College of Engineering Karnataka Bengaluru560074 India Instructor-II/Computing and Software Engineering U.A. Whitaker College of Engineering Florida Gulf Coast University Fort Myers United States Department of Computer Science and Engineering CMR Institute of Technology Karnataka Bengaluru560037 India Department of Electronics and Communication Engineering KPR Institute of Engineering and Technology Tamil Nadu Coimbatore641407 India Department of Civil Engineering Dr. D Y Patil Institute of Technology Maharashtra Pimpri Pune411018 India Department of Computer Science and Engineering Hindusthan Institute of Technology Coimbatore India Director of Centre of University Courses and Innovative Learning University of Technology Sarawak Jalan Universiti Sibu Sarawak96000 Malaysia

ISBN: (纸本)9789819986453

Video surveillance is mostly used for monitoring distant videos and the cloud memory in the system provides more secure to the data. But, in the existing methodologies poor intrusion detection accuracy as well as poor performance rate is considered as the main demerits. So, to overcome the above-mentioned demerits, a novel video surveillance-based Intrusion Detection System (IDS) (VS-IDS) in the edge cloud environment via deep learning method has been developed in this research. Different algorithms are used for object detection and intrusion detection. Subsequently, the proposed model can be implemented and verified in NVIDIA Jetson TX2 platform. The proposed model attains better rate of performance than the existing models. The Performance of the proposed model can be validated with accuracy, precision, recall, MSE and F-measure. Higher performance rate indicates that the system can detect intrusion more accurately than the existing mechanisms. 99% of detection accuracy can be attained through the proposed model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Intrusion detection

来源：评论

学校读者我要写书评

暂无评论

The Myth of Immutability: A Multivocal Review on Smart Contract Upgradeability

arXiv

引用

arXiv 2025年

作者： Qasse, Ilham Ali, Isra M. Ahmed, Nafisa Hamdaqa, Mohammad Jónsson, Björn Þór Department of Computer Science Reykjavik University Reykjavik Iceland College of Science and Engineering Hamad Bin Khalifa University Doha Qatar Department of Computer Engineering and Software Engineering Polytechnique Montreal Montreal Canada

Background: The immutability of smart contracts on blockchain platforms like Ethereum promotes security and trustworthiness but presents challenges for updates, bug fixes, or adding new features post-deployment. These limitations can lead to vulnerabilities and outdated functionality, impeding the evolution and maintenance of decentralized applications. Despite various upgrade mechanisms proposed in academic research and industry, a comprehensive analysis of their trade-offs and practical implications is lacking. Aims: This study aims to systematically identify, classify, and evaluate existing smart contract upgrade mechanisms, bridging the gap between theoretical concepts and practical implementations. It introduces standardized terminology and evaluates the trade-offs of different approaches using software quality attributes. Methods: We conducted a Multivocal Literature Review (MLR) to analyze upgrade mechanisms from both academic research and industry practice. We first establish a unified definition of smart contract upgradeability and identify core components essential for understanding the upgrade process. Based on this definition, we classify existing methods into full upgrade and partial upgrade approaches, introducing standardized terminology to harmonize the diverse terms used in the literature. We then characterize each approach and assess its benefits and limitations using software quality attributes such as complexity, flexibility, security, and usability. Results: The analysis highlights significant trade-offs among upgrade mechanisms, providing valuable insights into the benefits and limitations of each approach. These findings guide developers and researchers in selecting mechanisms tailored to specific project requirements. Conclusions: By offering a comprehensive evaluation that bridges theoretical concepts and practical implementations, this study contributes to the development of more resilient, adaptable, and secure decentralized systems. © 202

关键词： software quality

来源：评论

学校读者我要写书评

暂无评论

Towards Defect Prediction for Quantum software*

Towards Defect Prediction for Quantum Software*

引用

Quantum software engineering (Q-SE), International Workshop on

作者： Xuan Mao Zijie Huang Jianxin Ge Chao Wang Wuxu Wang Lizhi Cai Department of Computer Science and Engineering East China University of Science and Technology Shanghai China Shanghai Key Laboratory of Computer Software Testing & Evaluating Shanghai Development Center of Computer Software Technology Shanghai China

ISBN: (数字)9798331526214

ISBN: (纸本)9798331526221

software defects are faults or bugs within a program that can lead to incorrect or unexpected outcomes. Efficiently allocating software quality assurance (SQA) resources to components with a higher likelihood of defects, based on software defect prediction (SDP) models, can save significant effort. Although SDP has been extensively studied in classical software, its applicability to quantum software remains unexplored. Defect prediction for quantum software presents unique challenges, including the susceptibility to quantum-specific defects arising from quantum coding conventions and the limited size of available datasets. To address these issues, we propose QDP-FSL, an SDP model using a pre-trained code model to capture the semantics of quantum software code, and applying few-shot learning (FSL) to learn effectively from a small number of defective samples. Results show that QDP-FSL outperforms baseline methods that rely on static analysis. This work lays the foundation for future research in defect prediction for quantum software engineering and outlines potential directions for further improvement.

关键词： Codes Conferences Semantics computer bugs software quality Static analysis Predictive models Encoding Few shot learning software engineering

来源：评论

学校读者我要写书评

暂无评论

Towards Early Warning and Migration of High-Risk Dormant Open-Source software Dependencies

Towards Early Warning and Migration of High-Risk Dormant Ope...

引用

IEEE/ACM International Conference on software engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)

作者： Zijie Huang Lizhi Cai Xuan Mao Kang Yang Shanghai Key Laboratory of Computer Software Testing & Evaluating Shanghai Development Center of Computer Software Technology Shanghai China Department of Computer Science and Engineering East China University of Science and Technology Shanghai China

ISBN: (数字)9798331537111

ISBN: (纸本)9798331537128

Dormant open-source software (OSS) dependencies are no longer maintained or actively developed, their related code components are more vulnerable and error-prone since they can hardly keep up with evolving software dependents. Presently, their migration remains costly and challenging for practitioners. To tackle such a challenge, we intend to characterize, predict, and automatically migrate high-risk dormant OSS dependencies. Our pilot study of 4,945 Maven dependencies reveals over half of them are dormant, and 12.15% pose a high security risk. These high-risk dependencies can be predicted early based on their version release and usage characteristics. They are rarely migrated by developers, and simple one-to-one API migrations can be achieved with little context using Large Language Models (LLMs). Future research will be conducted on a more complete dataset, incorporate socio-technical features for improved high-risk prediction, and fine-tune a migration code generator.

关键词： Analytical models Codes Large language models Supply chains Predictive models Security Sustainable development Open source software software engineering Context modeling

来源：评论

学校读者我要写书评

暂无评论

Mobile Medical Assistant System for Laboratory Report Analysis and Medical Drug Identification 4

Mobile Medical Assistant System for Laboratory Report Analys...

引用

4th International Conference on Advancements in Computing, ICAC 2022

作者： Warnakulasuriya, Deshani Dewangi, Tharushi Sewwandi, Navodya Rathnayake, Minoli Kodagoda, Nuwan Suriyawansha, Kushanra Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

It is quite common for medical drugs and prescriptions to be misidentified by hospitals and after drugs are being dispensed to the patients. Misidentification of medical drugs is more common among elderly and visually impaired patients. In hospital organizations, the leading medical error is adverse drug events. Another most common issue patients face is keeping track of medical lab reports. Our proposed mobile medical assistant system uses image processing to identify drugs with or without packaging, identifying prescription and medical lab reports. Furthermore, the mobile application will identify the trends of medical lab reports and predict next month's results of the medical lab report of the patient using machine learning. © 2022 IEEE.

关键词： Hospitals

来源：评论

学校读者我要写书评

暂无评论

Digital Forensics Across Multiple Android Versions Using the MOBILEdit Forensic Tool

Digital Forensics Across Multiple Android Versions Using the...

引用

IEEE International Conference on Multi Topic

作者： Kohal Deep Maheshwari Pardeep Kumar Najma Imtiaz Ali Imtiaz Ali Brohi Dua Agha Department of Computer Science & IT NED University Karachi Pakistan Department of Software Engineering QUEST Univesity Nawabshah Pakistan Institute of Mathematics and Computer Science University of Sindh Jamshoro Pakistan Department of Computer Science Government College University Hyderabad Pakistan Department of Software Engineering Mehran University of Engineering and Technology Jamshoro Pakistan

ISBN: (数字)9798331507213

ISBN: (纸本)9798331507220

Open-source Android smartphones present both opportunities and difficulties for forensic investigators as they become more widely used. Advancements in Android security, encryption, and storage features necessitate newer forensic methods. The performance of MOBILedit Forensic across several Android versions will be covered in this article, with a concentrate on those running the Android 4.x version series. Data extraction, file recovery from deletion, and examination of call logs, messages, multimedia, and social media activity were among the main forensic activities carried out using this program. The tool's performance was evaluated on data from locked or corrupted devices, including its ability to decrypt information. The findings indicate that while MOBILedit Forensic is compatible with many Android versions, the speed and effectiveness of data extraction depend on the particular security measures used on each version. Newer Android models with advanced encryption and secure boot processes require more complex recovery techniques compared to older models, which recover data more quickly due to fewer security mechanisms. MOBILedit Forensic is still helpful in mobile forensics despite its flaws, but only partially understanding of encrypted data. This study also provides a more thorough understanding of the tool's functionality across different Android versions, which can help forensic investigators make better decisions about the best evidence extraction methods. Regular updates to forensic tools are crucial to adapt to evolving Android security measures.

关键词： Social networking (online) Operating systems Forensics Digital forensics Feature extraction Data models Encryption Data mining Smart phones Secure storage

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：