检索结果-内蒙古大学图书馆

computational Optical Sensing and Imaging, COSI 2024 - Part of Optica Imaging Congress

作者： Atibi, Arash Alqahtani, Abdulaziz Preza, Chrysanthe Computational Imaging Research Laboratory Department of Electrical and Computer Engineering The University of Memphis MemphisTN38152 United States

We investigated the use of Plug-and-Play methods in structured illumination microscopy using a 2D-processing approach and information from multiple 2D defocused PSFs. The achieved resolution in results from noisy simu... 详细信息

关键词： Illumination meters

来源：评论

学校读者我要写书评

暂无评论

Mutual Information-Guided GA for Bayesian Network Structure Learning (Extended Abstract) 40

Mutual Information-Guided GA for Bayesian Network Structure ...

引用

40th IEEE International Conference on Data engineering, ICDE 2024

作者： Yan, Kefei Fang, Wei Lu, Hengyang Zhang, Xin Sun, Jun Wu, Xiaojun Jiangnan University Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence Department of Computer Science and Technology Wuxi214122 China

ISBN: (纸本)9798350317152

Bayesian network structure learning (BNSL) from data is an NP-hard problem. Genetic algorithms are powerful for solving combinatorial optimization problems, but the lack of effective guidance results in slow convergence and low accuracy regarding BNSL. To address this problem, we propose a mutual information (MI) guided genetic algorithm (MIGA) for BNSL in this paper, which uses MI to effectively search BN structures. In the initialization phase of MIGA, the population is generated by adding additional constraints based on MI to reach a higher score without losing diversity. By employing normalized MI and defining the population support, the potential dominance in the population can be identified and then used to design a novel crossover operator in order to preserve the dominant genes with a higher probability. Moreover, with the guidance of MI for removing loops from the structures, infeasible solutions can be handled in a straightforward and practical way. The proposed MIGA is evaluated on eleven well-known benchmark datasets and compared with four GA-based methods and four other state-of-the-art BNSL algorithms. Experimental results show that MIGA outperforms the compared algorithms in convergence and learning accuracy. © 2024 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

An overview on IRS-enabled sensing and communications for 6G: architectures, fundamental limits, and joint beamforming designs

引用

Science China(Information Sciences) 2025年第5期68卷 170-193页

作者： Xianxin SONG Yuan FANG Feng WANG Zixiang REN Xianghao YU Ye ZHANG Fan LIU Jie XU Derrick Wing Kwan NG Rui ZHANG Shuguang CUI School of Science and Engineering (SSE) Shenzhen Future Network of Intelligence Institute (FNii-Shenzhen)and Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Department of Electrical Engineering City University of Hong Kong School of Information Engineering Guangdong University of Technology Key Laboratory of Wireless-Optical Communications Chinese Academy of Sciences School of Information Science and Technology University of Science and Technology of China Computer School Beijing Information Science and Technology University National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University School of Electrical Engineering and Telecommunications University of New South Wales School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Department of Electrical and Computer Engineering National University of Singapore

This study presents an overview on intelligent reflecting surface(IRS)-enabled sensing and communication for the forthcoming sixth-generation(6G) wireless networks, in which IRSs are strategically deployed to proactively reconfigure wireless environments to improve both sensing and communication(S&C) performance. First, we exploit a single IRS to enable wireless sensing in the base station's(BS's) non-line-of-sight(NLoS) area. In particular, we present three IRS-enabled NLoS target sensing architectures with fully-passive, semi-passive, and active IRSs, respectively. We compare their pros and cons by analyzing the fundamental sensing performance limits for target detection and parameter estimation. Next, we consider a single IRS to facilitate integrated sensing and communication(ISAC), in which the transmit signals at the BS are used for achieving both S&C functionalities, aided by the IRS through reflective beamforming. We present joint transmit signal and receiver processing designs for realizing efficient ISAC, and jointly optimize the transmit beamforming at the BS and reflective beamforming at the IRS to balance the fundamental performance tradeoff between S&C. Furthermore, we discuss multi-IRS networked ISAC, by particularly focusing on multi-IRS-enabled multi-link ISAC, multi-region ISAC, and ISAC signal routing, respectively. Finally, we highlight various promising research topics in this area to motivate future work.

关键词： integrated sensing and communication (ISAC) intelligent reflecting surface (IRS) non-line-of-sight (NLoS) sensing sensing and communication tradeoff

来源：评论

学校读者我要写书评

暂无评论

Software engineering Research in a World with Generative Artificial intelligence 24

Software Engineering Research in a World with Generative Art...

引用

44th ACM/IEEE International Conference on Software engineering, ICSE 2024

作者： Rinard, Martin Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science CambridgeMA United States

Generative artificial intelligence systems such as large language models (LLMs) exhibit powerful capabilities that many see as the kind of flexible and adaptive intelligence that previously only humans could exhibit. ... 详细信息

ISBN: (纸本)9798400702174

关键词： Software engineering

来源：评论

学校读者我要写书评

暂无评论

Hyperautomation for Air Quality Evaluations: A Perspective of Evidential Three-way Decision-making

引用

Cognitive Computation 2024年第5期16卷 2437-2453页

作者： Ding, Juanjuan Zhang, Chao Li, Deyu Sangaiah, Arun Kumar School of Computer and Information Technology Shanxi University Shanxi Taiyuan030006 China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Shanxi Taiyuan030006 China International Graduate Institute of Artificial Intelligence National Yunlin University of Science and Technology Douliou64002 Taiwan Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

Hyperautomation acts as a real digital transformation with the support of several cutting-edge cognitive computation methods that include robotic process automation, natural language processing, artificial intelligence, and other emerging ones, which is conducive to processing complex industrial processes via extending the range of various data-driven cognitive decision-making algorithms. The study of air quality evaluations (AQE) plays a significant role in ensuring healthy atmospheric environments. In view of the objective existence of uncertainties, AQE can be modeled and addressed by a typical data-driven automated decision-making problem, and hyperautomation can provide a reasonable solution via associating with a variety of techniques. This article explores hyperautomation for AQE via evidential three-way large-scale group decision-making (LSGDM) in an intuitionistic fuzzy (IF) setting. First, the notion of intuitionistic fuzzy sets (IFSs) is incorporated into the paradigm of multi-granularity (MG) three-way decisions (TWD), and the model of adjustable MG IF probabilistic rough sets (PRSs) is developed. Second, an IF clustering analysis with the improved technique for order preference by similarity to ideal solution (TOPSIS) method is conducted to affirm representative members within a decision group. Third, a novel IF LSGDM method is built via adjustable MG IF PRSs and the evidence reasoning (ER) method. Finally, a case study in the setting of AQE is studied by using the presented evidential three-way LSGDM method. Corresponding experimental analyses are carried out for illustrating the efficiency of hyperautomation for AQE. In general, the proposed method improves the performance of information fusion by virtue of adjustable MG IF PRSs, and the TOPSIS method avoids the influence of subjective factors on decision results. Meanwhile, the evaluation information of decision-makers (DMs) is fully analyzed by means of the ER method, which can provide more explaina

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Incomplete multi-view clustering via local and global co-regularization

引用

Science China(Information Sciences) 2022年第5期65卷 96-111页

作者： Jiye LIANG Xiaolin LIU Liang BAI Fuyuan CAO Dianhui WANG Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education School of Computer and Information Technology Shanxi University Artificial Intelligence Research Institute China University of Mining and Technology Department of Computer Science and Computer Engineering La Trobe University

The incompleteness of multi-view data is a phenomenon associated with real-world data mining applications, which brings a huge challenge for multi-view clustering. Although various types of clustering methods, which try to obtain a complete and consensus clustering result from a latent subspace, have been developed to overcome this problem, most methods excessively rely on views-public instances to bridge the connection with view-private instances. When lacking sufficient views-public instances, existing methods fail to transmit the information among incomplete views effectively. To overcome this limitation, we propose an incomplete multi-view clustering algorithm via local and global co-regularization(IMVC-LG). In this algorithm, we define a new objective function that is composed of two terms: local clustering from each view and global clustering from multiple views, which constrain each other to exploit the local clustering information from different incomplete views and determine a global consensus clustering result, ***, an iterative optimization method is proposed to minimize the objective function. Finally, we compare the proposed algorithm with other state-of-the-art incomplete multi-view clustering methods on several benchmark datasets to illustrate its effectiveness.

关键词： incompleteness multi-view clustering local clustering global clustering co-regularization

来源：评论

学校读者我要写书评

暂无评论

Anomaly Detection and Classification in Streaming PMU Data in Smart Grids

引用

computer Systems Science & engineering 2023年第9期46卷 3387-3401页

作者： A.L.Amutha R.Annie Uthra J.Preetha Roselyn R.Golda Brunet Department of Computational Intelligence SRM Institute of Science and TechnologyChennai603203India Department of Electrical and Electronics Engineering SRM Institute of Science and TechnologyChennai603203India Department of Computer Science and Engineering Government College of EngineeringSalem636011India

The invention of Phasor Measurement Units(PMUs)produce synchronized phasor measurements with high resolution real time monitoring and control of power system in smart grids that make *** are used in transmitting data to Phasor Data Concentrators(PDC)placed in control centers for monitoring purpose.A primary concern of system operators in control centers is maintaining safe and efficient operation of the power *** can be achieved by continuous monitoring of the PMU data that contains both normal and abnormal *** normal data indicates the normal behavior of the grid whereas the abnormal data indicates fault or abnormal conditions in power *** a result,detecting anomalies/abnormal conditions in the fast flowing PMU data that reflects the status of the power system is critical.A novel methodology for detecting and categorizing abnormalities in streaming PMU data is presented in this *** proposed method consists of three modules namely,offline Gaussian Mixture Model(GMM),online GMM for identifying anomalies and clustering ensemble model for classifying the *** significant features of the proposed method are detecting anomalies while taking into account of multivariate nature of the PMU dataset,adapting to concept drift in the flowing PMU data without retraining the existing model unnecessarily and classifying the *** proposed model is implemented in Python and the testing results prove that the proposed model is well suited for detection and classification of anomalies on the fly.

关键词： Smart Grid PMU data incremental learning classifying anomalies artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Improved resolution in 3D structured illumination microscopy using a 3D-based U-Net

Improved resolution in 3D structured illumination microscopy...

引用

2023 Imaging Systems and Applications, IS 2023 in Optica Imaging Congress - Part of Imaging and Applied Optics Congress 2023

作者： Kebede, Bereket E. Preza, Chrysanthe Computational Imaging Research Laboratory Department of Electrical and Computer Engineering The University of Memphis United States

ISBN: (纸本)9781957171289

Recent developments using deep learning (DL) super-resolution in structured-illumination microscopy (SIM) have improved speed in two-dimensional (2D) image restoration and minimized the impact of noise. We explore extending this 2D DL technique to 3D by augmenting the 2D-convolutional layers to 3D in a U-Net DL network. We demonstrate experimentally that this extension improves lateral and axial resolution in the final 3D restoration compared to the resolution achieved by axially stacking the outputs of the 2D U-Net. © 2023 The Author(s).

关键词： Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

A review on simulation models of cascading failures in power systems

引用

iEnergy 2023年第4期2卷 284-296页

作者： Zhenping Guo Kai Sun Xiaowen Su Srdjan Simunovic Department of Electrical Engineering and Computer Science University of TennesseeKnoxvilleTNUSA Department of Electrical and Computer Engineering University of Texas at San AntonioSan AntonioTXUSA Computational Sciences&Engineering Division Oak Ridge National LaboratoryOak RidgeTNUSA

Among various power system disturbances,cascading failures are considered the most serious and extreme threats to grid operations,potentially leading to significant stability issues or even widespread power *** power systems’behaviors during cascading failures is of great importance to comprehend how failures originate and propagate,as well as to develop effective preventive and mitigative control *** intricate mechanism of cascading failures,characterized by multi-timescale dynamics,presents exceptional challenges for their *** paper provides a comprehensive review of simulation models for cascading failures,providing a systematic categorization and a comparison of these *** challenges and potential research directions for the future are also discussed.

关键词： Cascading failures power systems security and reliability simulation models

来源：评论

学校读者我要写书评

暂无评论

A Classifier-Ensemble-Based Surrogate-Assisted Evolutionary Algorithm for Distributed Data-Driven Optimization

引用

IEEE Transactions on Evolutionary Computation 2025年第3期29卷 711-725页

作者： Guo, Xiao-Qi Wei, Feng-Feng Zhang, Jun Chen, Wei-Neng South China University of Technology School of Computer Science and Engineering Guangzhou510006 China South China University of Technology State Key Laboratory of Subtropical Building of Big Data and Computational Intelligence Guangzhou510006 China Hanyang University ERICA School of Electrical and Engineering Ansan15588 Korea Republic of Nankai University College of Artificial Intelligence Tianjin300071 China

Surrogate-assisted evolutionary algorithms (SAEAs) have achieved effective performance in solving complex data-driven optimization problems. In the Internet of Things environment, the data of many problems are collected and processed in distributed network nodes and cannot be transmitted. As each local node can only access and build surrogate models based on partial data, local models are usually not accurate and even conflicting. To address these challenges, this article proposes a classifier-ensemble-based surrogate-assisted evolutionary algorithm (CESAEA) with the following features. First, the local nodes in CESAEA train classifiers as surrogate models based on their own data to classify candidates into several levels according to their fitness quality. The classifiers are less sensitive to the partial and biased data than regression models in local nodes. Second, the central node in CESAEA ensembles the local surrogates to form a global classifier with a relaxation condition to guide the evolutionary optimizer to generate promising candidates. The relaxation condition helps to overcome the problem of local model inconsistency. Overall, CESAEA is composed of local classifier construction, global classifier ensemble, classifier-assisted evolutionary optimization and local regression-assisted selection. As only classifiers are allowed to transmit from local nodes to the central node, the mapping relationship between decision vector and objective is hidden and thus data privacy is protected. The experimental results on benchmark functions as well as distributed feature selection problems verify the effectiveness of CESAEA compared to several state-of-the-art approaches. © 1997-2012 IEEE.

关键词： Linear programming

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：