检索结果-内蒙古大学图书馆

2025 IEEE Wireless Communications and Networking Conference, WCNC 2025

作者： Tsipi, Lefteris Michailidis, Emmanouel T. Maliatsos, Konstantinos Vouyioukas, Demosthenes University of the Aegean Dept. of Information and Communication Systems Engineering Samos83200 Greece University of West Attica Dept. of Informatics and Computer Engineering Egaleo12243 Greece University of Piraeus Dept. of Digital Systems Piraeus18534 Greece

ISBN: (纸本)9798350368369

In this paper, multiple relay selection (MRS) schemes for untrusted unmanned aerial vehicle (UAV)-enabled networks are proposed. In this context, various machine learning (ML) models are employed to improve secrecy performance by optimally selecting multiple aerial relays from the available ones, all of which are regarded as untrusted. Notably, these ML models can cope with the quickly changing and random positioning of the aerial relays, effectively decoupling the intricate coupling relationship between the secrecy rate, channel coefficients, and inter-node distances. The results indicate that the ML-based MRS schemes obtain sufficient accuracy and better decoupling than a respective exhaustive searching (ES) approach, while also maintaining a lower computational complexity. © 2025 IEEE.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Impact of Artificial Intelligence on Decision-Making in Information systems 5

Impact of Artificial Intelligence on Decision-Making in Info...

引用

5th International Conference on Advanced Research in computing, ICARC 2025

作者： Rajasinghe, Rwmr Dharani Faculty of Computing Nsbm Green University Dept. of Software Engineering & Information Systems Homagama Sri Lanka

ISBN: (纸本)9798331530983

The study examines how artificial intelligence (AI) affects information systems (IS) decision-making, emphasizing how AI improves precision, speed, and flexibility in a range of industries. AI presents potential and problems, including ethical, legal, and societal ramifications, as it revolutionizes organizational decision-making. In order to demonstrate AI's function in intricate IS systems, this paper examines a variety of AI strategies used in decision-making, assesses their efficacy using accepted metrics, and examines real-world case studies. Key findings address issues including data bias, lack of transparency, and job displacement while highlighting the advantages of AI in processing massive information and producing useful insights. The recommendations highlight the necessity of worker reskilling, sector-specific adaptability, explainable AI (XAI) models, and regulatory frameworks. In order to facilitate sustainable AI integration in IS for improved organizational and social results, this research emphasizes the significance of striking a balance between AI-driven innovation and ethical issues. © 2025 IEEE.

关键词： Risk perception

来源：评论

学校读者我要写书评

暂无评论

TPTO: A Transformer-PPO based Task Offloading Solution for Edge computing Environments 29

TPTO: A Transformer-PPO based Task Offloading Solution for E...

引用

29th IEEE International Conference on Parallel and Distributed systems, ICPADS 2023

作者： Gholipour, Niloofar De Assuncao, Marcos Dias Agarwal, Pranav Gascon-Samson, Julien Buyya, Rajkumar Univ. of Quebec Dept. of Software Engineering and IT École de Technologie Supérieure Montreal Canada The Univ. of Melbourne CLOUDS Lab School of Computing and Information Systems Australia

ISBN: (纸本)9798350330717

Emerging applications in healthcare, autonomous vehicles, and wearable assistance require interactive and low-latency data analysis services. Unfortunately, cloud-centric architectures cannot fulfill the low-latency demands of these applications, as user devices are often distant from cloud data centers. Edge computing aims to reduce the latency by enabling processing tasks to be offloaded to resources located at the network's edge. However, determining which tasks must be offloaded to edge servers to reduce the latency of application requests is not trivial, especially if the tasks present dependencies. This paper proposes a Deep Reinforcement Learning (DRL) approach called TPTO, which leverages Transformer Networks and Proximal Policy Optimization (PPO) to offload dependent tasks of IoT applications in edge computing. We consider users with various preferences, where devices can offload computation to an edge server via wireless channels. Performance evaluation results demonstrate that under fat application graphs, TPTO is more effective than state-of-the-art methods, such as Greedy, HEFT, and MRLCO, by reducing latency by 30.24%, 29.61%, and 12.41%, respectively. In addition, TPTO presents a training time approximately 2.5 times faster than an existing DRL approach. © 2023 IEEE.

关键词： Edge computing reinforcement learning task offloading Transformers

来源：评论

学校读者我要写书评

暂无评论

QCRMut: Quantum Circuit Random Mutant generator tool

arXiv

引用

arXiv 2024年

作者： Gil, Sinhué García Díaz, Luis Llana Jarabo, José Ignacio Requeno Dept. of Information Systems and Computing Faculty of Computer Engineering Complutense University of Madrid Madrid Spain

Quantum computing has been on the rise in recent years, evidenced by a surge in publications on quantum software engineering and testing. Progress in quantum hardware has also been notable, with the introduction of impressive systems like Condor boasting 1121 qubits, and IBM Quantum System Two, which employs three 133-qubit Heron processors. As this technology edges closer to practical application, ensuring the efficacy of our software becomes imperative. Mutation testing, a well-established technique in classical computing, emerges as a valuable approach in this context. In our paper, we aim to introduce QCRMut, a mutation tool tailored for quantum programs, leveraging the inherent Quantum Circuit structure. We propose a randomised approach compared to previous works with exhaustive creation processes and the capability for marking immutable positions within the circuit. These features facilitate the preservation of program structure, which is crucial for future applications such as metamorphic testing. © 2024, CC BY-NC-SA.

关键词： Application programs

来源：评论

学校读者我要写书评

暂无评论

Data Mining and Text Mining Approach: Query based Information Retrieval using Genetic Algorithm 5

Data Mining and Text Mining Approach: Query based Informatio...

引用

5th International Conference on Image Processing and Capsule Networks, ICIPCN 2024

作者： Ananthi, S. Venkateswaran, R. Vijaya, G. Arun, J. Sathya, R. Sri Eshwar College of Engineering Advanced Research Centre for Future Networks and Digital Twin Coimbatore India College of Computing & Information Sciences University of Technology and Applied Sciences Faculty-Cyber and Information Security Salalah Oman Sri Krishna College of Engineering and Tech Dept. of CSE Coimbatore India Sri Eshwar College of Engineering Dept. of ECE Coimbatore India Kongunadu College of Engg and Tech Department of IT Namakkal India

ISBN: (纸本)9798350367171

Information Retrieval system facilitates the retrieval efficiency of the user's requirement from a collection of information resources. In this research work, Genetic Algorithm (GA) with various fitness functions are implemented for retrieving the relevant document for the given textual query. To increase the efficiency of the retrieval system extended keywords are added to the retrieval system using query reformulation method. Furthermore, the selection procedure namely fitness proportionate selection is used to identify the best fit individual among the chosen population. This selection algorithm assumes that, for the chosen population, the fittest individuals have a greater chance of endurance than weaker ones. The performance of the proposed system is evaluated with three different datasets solely consists of 20,322 documents are analyzed using various matching functions and their results are examined. © 2024 IEEE.

关键词： Content based retrieval

来源：评论

学校读者我要写书评

暂无评论

Hybrid Deep Clustering-Based Algorithm for Anomaly Detection in Network Attacks 26

Hybrid Deep Clustering-Based Algorithm for Anomaly Detection...

引用

26th International Conference on Industrial Technology, ICIT 2025

作者： Xu, Mingdi Wang, Wei Jin, Zhaoyang Li, Zhengxiao Cui, Feng Fan, Haipeng Wuhan Institute of Digital Engineering Dept. of Computing Environment Wuhan China School of Automation China University of Geosciences Wuhan China

ISBN: (纸本)9798331521950

The rapid development of information technologies such as the internet and big data has greatly facilitated people's work and life, but it has also led to security issues such as data breaches, online fraud, and system hijacking. Currently, in most research on deep learning-based clustering algorithms, issues such as the feature diversity of high-dimensional data, the representativeness of clustering features, and the precision of anomaly detection still need optimization. To address these shortcomings, this paper designs a Hybrid Clustering Deep Autoencoder (HCDAE) algorithm, which uses two nested deep autoencoders to learn normal data, extract the key features that are representative of the data, and then select the optimal cluster centers in the latent representation space through an adaptive cluster center filtering mechanism. This further enhances the significance and representativeness of the latent feature representations. Finally, this paper uses benchmark datasets for comparative experiments to evaluate the performance of HCDAE. The experimental results show that HCDAE generally performs better than other models and can effectively detect network attack anomalies, providing a new research approach for the field of network attack anomaly detection. © 2025 IEEE.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

Hybrid Deep Clustering-Based Algorithm for Anomaly Detection in Network Attacks

Hybrid Deep Clustering-Based Algorithm for Anomaly Detection...

引用

IEEE International Conference on Industrial Technology (ICIT)

作者： Mingdi Xu Wei Wang Zhaoyang Jin Zhengxiao Li Feng Cui Haipeng Fan Dept. of Computing Environment Wuhan Institute of Digital Engineering Wuhan China School of Automation China University of Geosciences Wuhan China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

关键词： High dimensional data Filtering Autoencoders Clustering algorithms Data breach Feature extraction Fraud Information technology Anomaly detection Optimization

来源：评论

学校读者我要写书评

暂无评论

Modality Representation Learning for Geometry Feature of Skeleton Based Human Action

Modality Representation Learning for Geometry Feature of Ske...

引用

2021 IEEE International Conference on Unmanned systems, ICUS 2021

作者： Qiu, Siyu Liu, Hao Tong, Hui Wuhan Digital Engineering Institute Dept. of Systems Engineering Wuhan China Wuhan Digital Engineering Institute Dept. of System Platform Wuhan China

ISBN: (纸本)9780738146577

Existing skeleton-based human action recognition has achieved enormous progress thanks to the accessible 3D skeleton capturing device and deep learning methods. One of the obstacles in action recognition lies in the cross-modal discrepancy when performing modalities fusion. Moreover, intra-modal variations in the same modality of different samples also inferior the representation learning of skeleton sequence. To address the issues, we designed five discriminative geometric representations as input of our approach. By considering the designed geometric representations as modalities, we introduce a Modality Feature Learning (MFL) framework based on Convolutional Neural Network, which is capable of automatically mines the relationships from modalities. The experimental results on the MSR Action3D dataset show that our approach achieves performance improvements over mainstream methods. © 2021 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Simulation Model of the Hydraulic Drive of the Rotary Column of the Robot Manipulator 5

Simulation Model of the Hydraulic Drive of the Rotary Column...

引用

5th International Conference on Control systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Kolpashchikov, Sergey A Terekhin, Michail A Kozlov, Evgeny V Portnov, Artem A Kalugin, Dmitry S Surguchev, Ivan V Samara State Technical University Dept. Automation and Control in Technical Systems Samara Russia Samara State University of Railway Transport Higher School of Medical Engineering Dept. Digital Technologies Institute of Innovative Development FSBEI HE SamSMU MOH Russia Samara Russia State University of Railway Transport Dept. Digital Technologies Samara Samara Russia State University of Railway Transport Institute of Innovative Development FSBEI HE SamSMU MOH Russia Dept. Digital Technologies Samara Samara Russia

ISBN: (纸本)9798350309126

The purpose of the work is to develop a simulation model of the hydraulic drive of the rotary column of the robot manipulator, which provides an adequate similarity of the proposed model with a real object. Modeling of the system was carried out with the help of modern FluidSIM Hydraulics software, which allows to intuitively reproduce and evaluate the operation of the system without using special complex mathematical structures for describing the research model. The result modeling is the transient processes hydraulic motor rotation, position value hydraulic distributor, pressure values in hydraulic lines, pushbutton state. The obtained dependences of numerical values at various time intervals, presented in the corresponding section of this work, allow us to conclude that the developed model adequately describes the nature and behavior of the object under study, corresponding to the normal mode of operation of the hydraulic system. When changing the initial data of the simulation model, it is possible to achieve other operating modes, for example, emergency ones. The developed system rotates clockwise and counterclockwise, control is carried out using a relay-contactor system. The simulation of the system was carried out taking into account the compensation of hydraulic shocks in the hydraulic lines when changing the direction of rotation in the opposite direction. Based on the results obtained, it can be concluded that the efficiency of the hydraulic drive of the rotary column of the robot manipulator depends on several main factors, such as speed, load and pressure in the hydraulic lines. Changing these parameters can affect the system both positively, leading to an increase in the efficiency of the system as a whole, and negatively and lead to a decrease in positioning accuracy, an increase in the reaction time of the system and the efficiency of power transmission. The results obtained are of interest not only for engineers of hydraulic drive systems, but also

关键词： Machine tools

来源：评论

学校读者我要写书评

暂无评论

Taxonomy of Proactive Detection Methods of Drunk Driving for Enhancing Traffic Safety 17

Taxonomy of Proactive Detection Methods of Drunk Driving for...

引用

17th IEEE International Symposium on Embedded Multicore/Many-core systems-on-Chip, MCSoC 2024

作者： Swiley, Richard Preston Alsulieman, Razan Sherif, Ahmed Elsersy, Mohamed Khalil, Kasem University of Southern Mississippi School of Computing Sciences and Computer Engineering MS United States Higher Colleges of Technology Computer and Information Systems Dept. AlAin Abu Dhabi United Arab Emirates University of Mississippi Electrical and Computer Engineering Department MS United States

ISBN: (纸本)9798331530471

Drunk driving continues to be a substantial public health issue, leading to a multitude of accidents and deaths on a global scale. Conventional techniques for identifying drunk driving, such as breathalyzers and field sobriety tests, tend to be reactive rather than proactive. This paper surveys the existing methods for detecting drunk driving to enhance traffic safety. The technologies studied can proactively detect impaired driving behaviors by combining machine learning (ML) approaches with real-time data processing. The study outlines various classifications based on measured metrics and driving behavior. © 2024 IEEE.

关键词： Artificial Intelligence Drunk Driving Detection Traffic Safety

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：