检索结果-内蒙古大学图书馆

3rd iEEE international Conference on iCT in Business industry and Government, iCTBiG 2023

作者： Naik, Nitin Jenkins, Paul Grace, Paul Naik, Dishita Song, Jingping Prajapat, Shaligram Mishra, Durgesh Yang, Longzhi Boongoen, Tossapon iam-On, Natthakan School of Informatics and Digital Engineering Aston University United Kingdom Cardiff School of Technologies Cardiff Metropolitan University United Kingdom Birmingham City University United Kingdom Software College Northeastern University China International Institute of Professional Studies Devi Ahilya University India School of Computer Science & Information Technology Symbiosis University of Applied Sciences India Northumbria University Department of Computer and Information Sciences United Kingdom Aberystwyth University Department of Computer Science United Kingdom

ISBN: (纸本)9798350343274

Organisations and users have been experiencing significant rises in cyberattacks and their severity, which means that they require a greater awareness and understanding of the anatomy of cyberattacks, to prevent and mitigate their effects. in analysing cyberattacks, there are a number of different approaches that may be used to assess their potential risks and effects. However, these are utilised in specific types of cyberattacks and their analysis, which means they cannot be applied in every situation or cyberattack. Moreover, several other factors may influence the decision to use these approaches, such as cost, complexity, skills and adaptability. As a result, continuous research to design and enhance these approaches is undertaken to produce a generic, cost-effective, easy and adaptable approach. This paper presents one such approach to assess the risk of cyberattacks utilising an attack tree and fuzzy logic. An attack tree is a systematic and illustrative method for describing an attack on a system and analysing its taxonomy and other aspects. Subsequently, the probability and risk of each leaf node in the attack tree are calculated using the proposed formulas. Finally, fuzzy logic enables decision making based on imprecise data and heuristics to obtain the overall risk of attack. This proposed approach comprises systematic steps to accomplish an assessment of any cyberattack and its associated risks in an uncomplicated and effective manner, enabling its prevention and mitigation to be determined. The paper illustrates an application of the proposed approach to assess the risk of an information theft attack on an organisation, which can then be utilised to assess the risk of other cyberattacks. © 2023 iEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Enhancing Autonomous intrusion Detection System with Generative Adversarial Networks

Enhancing Autonomous Intrusion Detection System with Generat...

引用

iEEE international Conference on e-science and Grid Computing

作者： Kevin Kostage David West Tim Meinert Chengyi Qu Prasad Calyam Luca Mazzola Department of Computing and Software Engineering Florida Gulf Coast University Florida USA Department of Electrical Engineering and Computer Science University of Missouri Columbia USA Lucerne University of Applied Sciences and Arts Lucerne Switzerland

ISBN: (数字)9798350365610

ISBN: (纸本)9798350365627

Effective training in Machine Learning and Deep Learning models necessitates datasets that provide sufficient patterns and contextual information, particularly crucial in ioT networks. imbalanced datasets, however, significantly challenge the performance of Autonomous intrusion Detection Systems (iDS), leading to suboptimal detection rates for minority classes. in this paper, we address this issue by utilizing various Generative Adversarial Network (GAN) models, including WGANGP, CGAN, CTGAN, and CWGANGP, to generate synthetic data that balance these imbalanced datasets. We evaluate the performance of iDS models trained on GAN-augmented datasets against those trained on unbalanced datasets, considering metrics such as fitting duration, generation duration, accuracy, precision, recall, and F1 score. Our findings reveal substantial improvements in iDS performance with the application of GANs across binary, general, and specific attack classifications. Additionally, we compare the effectiveness of GANs with classical sampling algorithms, such as SMOTE and Random Oversampling. This comprehensive evaluation underscores the potential of GANs as a sophisticated solution for improving iDS accuracy and reliability in handling complex and highly imbalanced datasets.

关键词： Training Measurement Deep learning Accuracy Fitting intrusion detection Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Online Container Scheduling for Data-intensive Applications in Serverless Edge Computing

Online Container Scheduling for Data-intensive Applications ...

引用

iEEE Annual Joint Conference: iNFOCOM, iEEE computer and Communications Societies

作者： Xiaojun Shang Yingling Mao Yu Liu Yaodong Huang Zhenhua Liu Yuanyuan Yang Department of Electrical and Computer Engineering Stony Brook University USA College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Applied Mathematics and Statistics Stony Brook University USA

introducing the emerging serverless paradigm into edge computing could avoid over- and under-provisioning of limited edge resources and make complex edge resource management transparent to application developers, which largely facilitates the cost-effectiveness, portability, and short time-to-market of edge applications. However, the computation/data dispersion and device/network heterogeneity of edge environments prevent current serverless computing platforms from acclimating to the network edge. in this paper, we address such challenges by formulating a container placement and data flow routing problem, which fully considers the heterogeneity of edge networks and the overhead of operating serverless platforms on resource-limited edge servers. We design an online algorithm to solve the problem. We further show its local optimum for each arriving container and prove its theoretical guarantee to the optimal offline solution. We also conduct extensive simulations based on practical experiment results to show the advantages of the proposed algorithm over existing baselines.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Probabilistic Framework for Pruning Transformers Via a Finite Admixture of Keys 48

A Probabilistic Framework for Pruning Transformers Via a Fin...

引用

48th iEEE international Conference on Acoustics, Speech and Signal Processing, iCASSP 2023

作者： Nguyen, Tan M. Nguyen, Tam Bui, Long Do, Hai Nguyen, Duy Khuong Le, Dung D. Tran-The, Hung Ho, Nhat Osher, Stan J. Baraniuk, Richard G. University of California Department of Mathematics Los Angeles United States Rice University Department of Electrical and Computer Engineering Houston United States Fpt Software Ai Center Ha Noi Viet Nam Vin University College of Engineering and Computer Science Viet Nam Deakin University Applied Artificial Intelligence Institute Geelong Australia The University of Texas Department of Statistics and Data Sciences Austin United States

ISBN: (纸本)9781728163277

Pairwise dot product-based self-attention is key to the success of transformers which achieve state-of-the-art performance across a variety of applications in language and vision, but are costly to compute. it has been shown that most attention scores and keys in transformers are redundant and can be removed without loss of accuracy. in this paper, we develop a novel probabilistic framework for pruning attention scores and keys in transformers. We first formulate an admixture model of attention keys whose input data to be clustered are attention queries. We show that attention scores in self-attention correspond to the posterior distribution of this model when attention keys admit a uniform prior distribution. We then relax this uniform prior constraint and let the model learn these priors from data, resulting in a new Finite Admixture of Keys (FiAK). The learned priors are used for pruning away redundant attention scores and keys in the baseline transformers, improving the diversity of attention patterns that the models capture. We corroborate the efficiency of transformers pruned with FiAK on the imageNet object classification and WikiText-103 language modeling tasks. Our experiments demonstrate that transformers pruned with FiAK yield similar or better accuracy than the baseline dense transformers while being much more efficient in terms of memory and computational cost. © 2023 iEEE.

关键词： admixture models pruning Transformers

来源：评论

学校读者我要写书评

暂无评论

A Supervised Approach For Superpixel Segmentation 1

A Supervised Approach For Superpixel Segmentation

引用

1st international Conference on Machine Learning, computer Systems and Security, MLCSS 2022

作者： Chatterjee, Pubali Das Sharma, Kaushik Chakrabarti, Amlan Soa University Department of Computer Science and Engineering India University of Calcutta Department of Applied Physics India A. K. Choudhury School of I.T. University of Calcutta India

ISBN: (纸本)9781665454933

Automatic detection of brain lesion in magnetic resonance imaging (MRi) plays an important role in clinical assistance. in this paper, we propose an enhanced brain lesion detection scheme based on the Dense Convolutional Neural Network (DCNN) where the MR-image is input and the brain lesion is the output. The proposed methodology includes two stages: (a) super-pixel segmentation and (b) classification of super-pixel. in the initial stage, applying the SLiC algorithm separates the lesion and non-lesion area. in the next stage, This segmented lesion and non-lesion regions are used for DCNN training and classification. An modified classifier is used to handle this complex task. The experimental results show that the proposed segmentation scheme achieves a better accuracy than other existing schemes for the detection of brain lesion in MR images. © 2022 iEEE.

关键词： image segmentation

来源：评论

学校读者我要写书评

暂无评论

Optimizing Weighted Ensemble ML iDS Using Parallelization and Batch Learning in Healthcare Networks

Optimizing Weighted Ensemble ML IDS Using Parallelization an...

引用

international Conference on e-health Networking, Applications and Services (HealthCom)

作者： Blake Ward Daniel Gonzalez Jake Alt Dongfeng Fang Shengjie Xu Department of Computer Science and Software Engineering College of Engineering California Polytechnic State University San Luis Obispo CA USA Department of Cyber Intelligence and Information Operations College of Applied Science and Technology University of Arizona Tucson AZ USA

ISBN: (数字)9798350350548

ISBN: (纸本)9798350350555

The increasing adoption of loT devices in healthcare necessitates the development of lightweight and fast intrusion de-tection systems (iDS). This paper proposes a weighted ensemble ML iDS with parallelized batch learning to optimize runtime while maintaining ML performance. The proposed method is compared to other solutions, evaluating ML performance and runtime across three different datasets. Experimental results demonstrate that although batch learning introduces feedback delay that slightly degrades ML performance, parallel computing significantly reduces runtime.

关键词： Performance evaluation Degradation Runtime Accuracy Wireless personal area networks Medical services Machine learning Parallel processing Delays

来源：评论

学校读者我要写书评

暂无评论

A Novel Machine Learning Based Framework for Bridge Condition Analysis

A Novel Machine Learning Based Framework for Bridge Conditio...

引用

2022 iEEE international Conference on Big Data, Big Data 2022

作者： Masum, Mohammad Anjum, Nafisa Hossain Faruk, Md Jobair Shahriar, Hossain Sakib, Nazmus Valero, Maria Karim, M.A. Rahman, Akond Wu, Fan Cuzzocrea, Alfredo San Jose State University Department of Applied Data Science San Jose United States Kennesaw State University Department of Information Technology United States Kennesaw State University Department of Software Engineering and Game Development United States Kennesaw State University Department of Civil and Environmental Engineering United States Auburn University Department of Computer Science and Software Engineering United States Tuskegee University Department of Computer Science United States University of Calabria IDEA Lab Rende Italy

ISBN: (纸本)9781665480451

Bridges play a vital part in the transportation system by ensuring the connectedness of transportation systems, which is critical for a country's social and economic prosperity by offering daily mobility to the people. However, according to the American Society of Civil Engineers (ASCE 2017), many U.S. bridges are in critical condition, raising safety issues, with 9.1 and 13.6 percent of the country's 614,387 bridges, respectively, structurally defective, and functionally obsolete. Every day, 178 million people traverse these structurally defective bridges. Furthermore, the average annual failure rate is expected to be between 87 and 222. Bridge breakdowns have disastrous repercussions, and in many cases, result in death. While bridge authorities strive to improve bridge conditions, budget limits make it difficult to make cost-effective maintenance decisions. Bridge authorities distribute limited repair resources based on projected future bridge conditions. As a result, building a data-driven, autonomous, and effective bridge condition prediction model is critical for improving maintenance decision-making. in this paper, we present a novel bridge condition prediction framework using advanced Machine Learning (ML) algorithms on the National Bridge inventory (NBi) dataset. The framework consists of two stages, where the most informative features from the NBi dataset are selected using the Recursive Feature Elimination process and in the 2nd step, ML classifiers are applied to the selected features for bridge condition prediction. The experimental results show that the proposed framework can effectively predict bridge conditions by producing highly accurate results in terms of accuracy, precision, recall, and f1-score. © 2022 iEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Exploring the role of project status information in effective code smell detection

引用

Cluster Computing 2025年第1期28卷 1-18页

作者： Alkharabsheh, Khalid Alawadi, Sadi Crespo, Yania Taboada, José A. Software Engineering Department Prince Abdullah bin Ghazi Faculty of Information and Communication Technology Al-Balqa Applied University Al-Salt19117 Jordan School of Computer Science Blekinge Tekniska Högskola Blekinge Tekniska Högskola Blekinge Karlskrona37179 Sweden Departamento de Informática Escuela de Ingeniería Informática Universidad de Valladolid Paseo de Belén 15 Valladolid47011 Spain Department of Electronics and Computing Universidad de Santiago de Compostela Santiago15782 Spain

Repairing code smells detected in the code or design of the system is one of the activities contributing to increasing the software quality. in this study, we investigate the impact of non-numerical information of software, such as project status information combined with machine learning techniques, on improving code smell detection. For this purpose, we constructed a dataset consisting of 22 systems with various project statuses, 12,040 classes, and 18 features that included 1935 large classes. A set of experiments was conducted with ten different machine learning techniques by dividing the dataset into training, validation, and testing sets to detect the large class code smell. Feature selection and data balancing techniques have been applied. The classifier’s performance was evaluated using six indicators: precision, recall, F-measure, MCC, ROC area, and Kappa tests. The preliminary experimental results reveal that feature selection and data balancing have poor influence on the accuracy of machine learning classifiers. Moreover, they vary their behavior when utilized in sets with different values for the selected project status information of their classes. The average value of classifiers performance when fed with status information is better than without. The Random Forest achieved the best behavior according to all performance indicators (100%) with status information, while AdaBoostM1 and SMO achieved the worst in most of them (> 86%). According to the findings of this study, providing machine learning techniques with project status information about the classes to be analyzed can improve the results of large class detection. © The Author(s) 2024.

关键词： software quality

来源：评论

学校读者我要写书评

暂无评论

Automated Test Case Generation from Requirements: A Systematic Literature Review

引用

computers, Materials & Continua 2021年第5期67卷 1819-1833页

作者： Ahmad Mustafa Wan M.N.Wan-Kadir Noraini ibrahim Muhammad Arif Shah Muhammad Younas Atif Khan Mahdi Zareei Faisal Alanazi Department of Software Engineering School of ComputingUniversiti Teknologi Malaysia Johor BahruJohor81310Malaysia Department of Computer Science Government College UniversityFaisalabad38000Pakistan Department of Software Engineering Pak-Austria Fachhochschule Institute of Applied Sciences and TechnologyHaripur22620Pakistan Department of Computer Science Islamia College PeshawarPeshawarPakistan Tecnologico de Monterrey School of Engineering and SciencesZapopan45201Mexico Department of Electrical Engineering Prince Sattam Bin Abdulaziz UniversityAl Kharj11942Saudi Arabia

software testing is an important and cost intensive activity in software *** major contribution in cost is due to test case ***-based testing is an approach in which test cases are derivative from requirements without considering the implementation’s internal ***-based testing includes functional and nonfunctional *** objective of this study is to explore the approaches that generate test cases from requirements.A systematic literature review based on two research questions and extensive quality assessment criteria includes *** study identies 30 primary studies from 410 studies spanned from 2000 to *** review’s nding shows that 53%of journal papers,42%of conference papers,and 5%of book chapters’address requirementsbased *** of the studies use UML,activity,and use case diagrams for test case generation from *** of the signicant lessons learned is that most software testing errors are traced back to errors in natural language requirements.A substantial amount of work focuses on UML diagrams for test case generations,which cannot capture all the system’s developed ***,there is a lack of UML-based models that can generate test cases from natural language requirements by rening them in *** criteria indicate how efciently the testing has been performed 12.37%of studies use requirements coverage,20%of studies cover path coverage,and 17%study basic coverage.

关键词： Test case generation functional testing techniques requirementsbased test case generation system testing natural language requirement requirements tractability coverage criteria

来源：评论

学校读者我要写书评

暂无评论

A Chatbot Assistant for Reducing Risk in Machinery Design

A Chatbot Assistant for Reducing Risk in Machinery Design

引用

iEEE international Conference on industrial informatics (iNDiN)

作者： Padma iyenghar Michael Kieviet Elke Pulvermueller Juergen Wuebbelmann innotec GmbH Erlenweg 12 Melle Germany Faculty of Engineering and Computer Science Osnabrueck University of Applied Sciences Germany Software Engineering Research Group University of Osnabrueck Germany

in this paper, a novel chatbot for risk reduction as an aid during machinery design is presented. The general workflow of the chatbot involves the identification of the hazard described by the user using a neural network model followed by an interactive dialog based conversation, in which the risk reduction measures are outlined. A prototype implementation of the chatbot presents the steps to generate and pre-process the training data for Artificial intelligence (Ai) based models. Different neural network models are trained and evaluated for the proposed risk reduction chatbot. A comparative study is presented by employing an in-depth qualitative and quantitative evaluation. The work presented in this paper shows significant promise in ensuring safety awareness, thereby aiding in implementing functional safety in the early stages of machinery design and development.

关键词：

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：