检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Gao, Can Tan, Xiaofeng Zhou, Jie Ding, Weiping Pedrycz, Witold The College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen518060 China The National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China The School of Artificial Intelligence and Computer Science Nantong University Nantong226019 China The Faculty of Data Science City University of Macau Macau999078 China The Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Systems Research Institute Polish Academy of Sciences Warsaw Poland The Department of Electrical and Computer Engineering King Abdulaziz University Jeddah Saudi Arabia The Department of Computer Engineering Istinye University Istanbul Turkey

Outlier detection refers to the identification of anomalous samples that deviate significantly from the distribution of normal data and has been extensively studied and used in a variety of practical tasks. However, most unsupervised outlier detection methods are carefully designed to detect specified outliers, while real-world data may be entangled with different types of outliers. In this study, we propose a fuzzy rough sets-based multi-scale outlier detection method to identify various types of outliers. Specifically, a novel fuzzy rough sets-based method that integrates relative fuzzy granule density is first introduced to improve the capability of detecting local outliers. Then, a multi-scale view generation method based on granular-ball computing is proposed to collaboratively identify group outliers at different levels of granularity. Moreover, reliable outliers and inliers determined by the three-way decision are used to train a weighted support vector machine to further improve the performance of outlier detection. The proposed method innovatively transforms unsupervised outlier detection into a semi-supervised classification problem and for the first time explores the fuzzy rough sets-based outlier detection from the perspective of multi-scale granular balls, allowing for high adaptability to different types of outliers. Extensive experiments carried out on both artificial and UCI datasets demonstrate that the proposed outlier detection method significantly outperforms the state-of-the-art methods, improving the results by at least 8.48% in terms of the Area Under the ROC Curve (AUROC) index. The source codes are released at https://***/Xiaofeng-Tan/MGBOD. © 2025, CC BY.

关键词： Granulation

来源：评论

学校读者我要写书评

暂无评论

GPUSecBench: Evaluating the Cache Side-Channel Resilience of a GPU Security Execution Pipeline

GPUSecBench: Evaluating the Cache Side-Channel Resilience of...

引用

Intelligent Cyber Physical systems and Internet of Things (ICoICI), International Conference on

作者： Nelson Lungu Bibhuti Bhusan Dash Manoj Ranjan Mishra Lalbihari Barik Abinash Tripathy Sudhansu Shekhar Patra Electrical and Electronic Engineering University of Zambia Lusaka Zambia School of Computer Applications KIIT Deemed to be University Bhubaneswar India Department of Information Systems Faculty of Computing and Information Technology in Rabigh King Abdul Aziz University Kingdom of Saudi Arabia

ISBN: (数字)9798331540661

ISBN: (纸本)9798331540678

Graphics processing units (GPUs) are increasingly used for security-critical workloads but remain vulnerable to cache side-channel attacks that can leak sensitive data like cryptographic keys and model parameters. Hardware-based defences incorporated into the GPU architecture, such as partitioning and randomisation, can help mitigate these risks by increasing isolation and unpredictability. However, rigorous benchmarks are imperative to evaluate the security-performance tradeoffs of potential defences. We developed GPUSecBench, a comprehensive benchmarking suite comprising timed workloads, real-world attack implementations, and rigorous analysis tools to quantify cache side-channel leakage and overhead of defences empirically. Our experiments demonstrated measurable information leakage across diverse workloads, including cryptography, machine learning, and graphics rendering. The modelled cache timing attacks succeeded in recovering secrets with over 90% success rates. At the same time, defences incurred less than 20% performance slowdown. GPUSecBench provides security insights to enable GPU hardware architects to make data-driven design decisions, guiding the development of micro architectures resilient to timing side-channel attacks with acceptable performance tradeoffs. The benchmark can also benefit system developers in building robust GPU -accelerated applications.

关键词： Protocols Pipelines Graphics processing units Side-channel attacks Machine learning Benchmark testing Rendering (computer graphics) Timing Internet of Things Resilience

来源：评论

学校读者我要写书评

暂无评论

Preliminary study on the impact of acoustic emissions on fish

Preliminary study on the impact of acoustic emissions on fis...

引用

OCEANS

作者： Fausto Ferreira Roee Diamant Ilan Shachar Alexia Badi Nikola Mišković Danny Morick Laboratory for Underwater Systems and Technologies (LABUST) Faculty of Electrical Engineering and Computing University of Zagreb Croatia Charney School of Marine Sciences University of Haifa Israel CESI CFA SUP Nice France

Anthropogenic underwater acoustic noise is known to affect marine life from mammals to sea birds. Due to the intense use of acoustics for communication and navigation by mammals (especially whales), there is a significant body of research devoted to the impact of underwater noise in this type of animals. On the contrary, studies on the impact on fish are much less common. This work presents a preliminary study on the impact of acoustic emissions in fish. Results obtained in a tank are presented both for biological parameters and speed estimation through camera. Differences in stress levels have been found as well as in speed that may suggest physical deficiencies. However, future work is needed to corroborate these results.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Resilience-oriented Operation of Power Distribution Networks with Line Hardening and Comprehensive Reconfiguration Measures

Resilience-oriented Operation of Power Distribution Networks...

引用

IEEE International Conference on Smart Grid Communications (SmartGridComm)

作者： Zhengmao Li Zhao Shi Guangchun Ruan Yuzhang Lin Jin Zhao School of Electrical Engineering Aalto University Espoo Finland School of Electrical and Electronic Engineering Nanyang Technological University Singapore Laboratory for Information & Decision Systems Massachusetts Institute of Technology Boston The USA Department of Electrical and Computer Engineering New York University New York the USA Department of Electronic and Electrical Engineering Trinity College Dublin Dublin Ireland

With the frequent occurrence of extreme events like natural disasters and man-made attacks, the resilience concept is attracting worldwide research attention. Thus, this paper proposes a resilient operation model for the power distribution network (PDN) to recover load and limit economic loss to the greatest possible extent. First, the line hardening measure is applied to strengthen the PDN to avoid the serious breakdown of distribution lines. In addition, a comprehensive single commodity flow-based reconfiguration approach is used which not only sets the buses connecting generation sources but also those at the end of broken lines as the slack buses. Then, the radiality of PDNs can still be guaranteed after reconfiguration. The resilience-oriented operation problem can be originally formulated as a nonlinear programming one while efficient linearization methods are applied to reduce computational burdens. Hence, the operation problem is reformulated as a mixed-integer linear programming one which will enjoy favorable solution performances. Finally, case studies on an IEEE 33 PDN including comparison cases with traditional benchmarks are done to show the effectiveness of our method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

AgileWatts: An Energy-Efficient CPU Core Idle-State Architecture for Latency-Sensitive Server Applications 22

AgileWatts: An Energy-Efficient CPU Core Idle-State Architec...

引用

Proceedings of the 55th Annual IEEE/ACM International Symposium on Microarchitecture

作者： Jawad Haj Yahya Haris Volos Davide B. Bartolini Georgia Antoniou Jeremie S. Kim Zhe Wang Kleovoulos Kalaitzidis Tom Rollet Zhirui Chen Ye Geng Onur Mutlu Yiannakis Sazeides Rivos Inc Mountain View California United States Computer Architecture Laboratory Department of Computer Science University of Cyprus Computing Systems Lab Huawei Zurich Research Center Department of Information Technology and Electrical Engineering ETH Zurich Switzerland

ISBN: (纸本)9781665462723

User-facing applications running in modern datacenters exhibit irregular request patterns and are implemented using a multitude of services with tight latency requirements (30--250μs). These characteristics render existing energy-conserving techniques ineffective when processors are idle due to the long transition time (order of 100μs) from a deep CPU core idle power state (C-state). While prior works propose management techniques to mitigate this inefficiency, we tackle it at its root with AgileWatts (AW): a new deep CPU core C-state architecture optimized for datacenter server processors targeting latency-sensitive *** drastically reduces the transition latency from deep CPU core idle power states while retaining most of their power savings based on three key ideas. First, AW eliminates the latency (several microseconds) of saving/restoring the core context when powering-off/-on the core in a deep idle state by i) implementing medium-grained power-gates, carefully distributed across the CPU core, and ii) retaining context in the power-ungated domain. Second, AW eliminates the flush latency (several tens of microseconds) of the L1/L2 caches when entering a deep idle state by keeping L1/L2 content power-ungated. A small control logic also remains ungated to serve cache coherence traffic. AW implements cache sleep-mode and leakage reduction for the power-ungated domain by lowering a core's voltage to the minimum operational level. Third, using a state-of-the-art power efficient all-digital phase-locked loop (ADPLL) clock generator, AW keeps the PLL active and locked during the idle state, cutting microseconds of wake-up latency at negligible power *** evaluation with an accurate industrial-grade simulator calibrated against an Intel Skylake server shows that AW reduces the energy consumption of Memcached by up to 71% (35% on average) with <1% end-to-end performance degradation. We observe similar trends for other evaluated services (MySQL and Kafka).

关键词：

来源：评论

学校读者我要写书评

暂无评论

Skeleton-Based Multi-Stream Adaptive Graph Convolutional Network for Indoor Scene Action Recognition

Skeleton-Based Multi-Stream Adaptive Graph Convolutional Net...

引用

2023 China Automation Congress, CAC 2023

作者： Li, Jiazhuo Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru The School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China The Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada The Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland The Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey The Tokyo Institute of Technology Tokyo226-8502 Japan

ISBN: (纸本)9798350303759

With the rapid advances in computer vision, human action recognition has gradually received attention, but the current methods still exhibit some problems in indoor environments. The human skeleton, as the framework of human motion, contains high-quality actional feature information, and the skeleton-based action recognition method effectively avoid the interference of interior background noise and has advantages in indoor action recognition. The outstanding effect of graph convolutional networks on graph structure data processing has led to its rapid development and wide application in skeleton-based action recognition. Second-order skeletal information also contains a large number of actional features but is not effectively utilized. The artificial predefined topology of the human skeleton map has limitations, and cannot reflect the interaction between limbs. To solve the above problems, this article designs an adaptive weighted multi-stream graph convolutional network (AM-GCN) based on skeletal information, using an attention mechanism to enhance the network's ability to extract actional features, and an adaptive layer to make the construction graph more flexible, incorporating second-order skeletal features through a dual-stream architecture. In this article, the NTU-RGB+D dataset has been used for the experiments, the results show that the method in this article has good results. © 2023 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

SSRN

引用

SSRN 2024年

作者： Ren, Yingying Li, Qiuli Guo, Yangyang Pedrycz, Witold Xing, Lining Liu, Anfeng Song, Yanjie School of Computer Electronics and Information Guangxi University Nannig China Guangxi Key Laboratory of Multimedia Communications and Network Technology China China School of Systems Science Beijing Jiaotong University Beijing China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Systems Research Institute Polish Academy of Sciences Poland Faculty of Engineering and Natural Sciences Department of Computer Engineering Sariyer Istanbul Turkey School of Electronic Engineering Xidian University Xian China School of Electronic Engineering Central South University Changsha China College of Systems Engineering National University of Defense Technology Changsha China

With the rapid development of the satellite industry, the information transmission network based on communication satellites has gradually become a major and important part of the future satellite ground integration network. However, the low transmission efficiency of the satellite data relay back mission has become a problem that is currently constraining the construction of the system and needs to be solved urgently. Effectively planning the task of satellite ground networking by reasonably scheduling resources is crucial for the efficient transmission of task data. In this paper, we hope to provide a task execution scheme that maximizes the profit of the networking task for satellite ground network planning considering feeding mode (SGNPFM). To solve the SGNPFM problem, a mixed-integer planning model with the objective of maximizing the gain of the link-building task is constructed, which considers various constraints of the satellite in the feed-switching mode. Based on the problem characteristics, we propose a distance similarity-based genetic optimization algorithm (DSGA), which considers the state characteristics between the tasks and introduces a weighted Euclidean distance method to determine the similarity between the tasks. To obtain more high-quality solutions, different similarity evaluation methods are designed to assist the algorithm in intelligently screening individuals. The DSGA also uses an adaptive crossover strategy based on similarity mechanism, which guides the algorithm to achieve efficient population search. In addition, a task scheduling algorithm considering the feed-switching mode is designed for decoding the algorithm to generate a high-quality scheme. The results of simulation experiments show that the DSGA can effectively solve the SGNPFM problem. Compared to other algorithms, the proposed algorithm not only obtains higher quality planning schemes but also has faster algorithm convergence speed. The proposed algorithm improves data tra

关键词： Profitability

来源：评论

学校读者我要写书评

暂无评论

A Survey on Deep Learning for Polyp Segmentation: Techniques, Challenges and Future Trends

arXiv

引用

arXiv 2023年

作者： Mei, Jiaxin Zhou, Tao Huang, Kaiwen Zhang, Yizhe Zhou, Yi Wu, Ye Fu, Huazhu Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China School of Computer Science and Engineering Southeast University Nanjing China Institute of High Performance Computing A*STAR Singapore

Early detection and assessment of polyps play a crucial role in the prevention and treatment of colorectal cancer (CRC). Polyp segmentation provides an effective solution to assist clinicians in accurately locating and segmenting polyp regions. In the past, people often relied on manually extracted lower-level features such as color, texture, and shape, which often had problems capturing global context and lacked robustness to complex scenarios. With the advent of deep learning, more and more medical image segmentation algorithms based on deep learning networks have emerged, making significant progress in the field. This paper provides a comprehensive review of polyp segmentation algorithms. We first review some traditional algorithms based on manually extracted features and deep segmentation algorithms, and then describe benchmark datasets related to the topic. Specifically, we carry out a comprehensive evaluation of recent deep learning models and results based on polyp size, taking into account the focus of research topics and differences in network structures. Finally, we discuss the challenges of polyp segmentation and future trends in the field. Copyright © 2023, The Authors. All rights reserved.

关键词： Medical imaging

来源：评论

学校读者我要写书评

暂无评论

Toward Democratized Generative AI in Next-Generation Mobile Edge Networks

arXiv

引用

arXiv 2024年

作者： Zhang, Ruichen He, Jiayi Luo, Xiaofeng Niyato, Dusit Kang, Jiawen Xiong, Zehui Li, Yonghui Sikdar, Biplab The College of Computing and Data Science Nanyang Technological University Singapore The School of Automation Guangdong University of Technology Guangzhou510006 China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The School of Electrical and Information Engineering University of Sydney SydneyNSW2006 Australia The Department of Electrical and Computer Engineering College of Design and Engineering National University of Singapore Singapore

The rapid development of generative AI technologies, including large language models (LLMs), has brought transformative changes to various fields. However, deploying such advanced models on mobile and edge devices remains challenging due to their high computational, memory, communication, and energy requirements. To address these challenges, we propose a model-centric framework for democratizing generative AI deployment on mobile and edge networks. First, we comprehensively review key compact model strategies, such as quantization, model pruning, and knowledge distillation, and present key performance metrics to optimize generative AI for mobile deployment. Next, we provide a focused review of mobile and edge networks, emphasizing the specific challenges and requirements of these environments. We further conduct a case study demonstrating the effectiveness of these strategies by deploying LLMs on real mobile edge devices. Experimental results highlight the practicality of democratized LLMs, with significant improvements in generalization accuracy, hallucination rate, accessibility, and resource consumption. Finally, we discuss potential research directions to further advance the deployment of generative AI in resource-constrained environments. © 2024, CC BY.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Robust Voltage Regulation for DC Microgrids via Passivity-Based Sliding Mode Control

Robust Voltage Regulation for DC Microgrids via Passivity-Ba...

引用

International Workshop on Variable Structure systems, VSS

作者： Edoardo Vacchini Michele Cucuzzella Pablo Borja Antonella Ferrara Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy Jan C. Willems Center for Systems and Control Engineering and Technology Institute Groningen (ENTEG) Faculty of Science and Engineering University of Groningen Groningen The Netherlands School of Engineering Computing and Mathematics University of Plymouth Plymouth U.K.

ISBN: (数字)9798350353686

ISBN: (纸本)9798350353693

This paper proposes a decentralized sliding mode control approach to the voltage regulation problem in a DC microgrid consisting of distributed generation units interconnected with each other through resistive-inductive power lines and supplying unknown nonlinear loads. In particular, the port-Hamiltonian structure of the system suggests the design of a suitable sliding manifold such that the system on this manifold exhibits desired passivity properties. This approach simplifies the control design and relaxes some restrictive assumptions required by other controllers proposed in the literature, while offering satisfactory performance.

关键词： Manifolds Variable structure systems Power transmission lines Microgrids Power system stability Stability analysis Robustness Reduced order systems Voltage control Sliding mode control

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：