检索结果-内蒙古大学图书馆

Wi-Wheat+:Contact-free wheat moisture sensing with commodity WiFi based on entropy

Digital Communications and Networks 2023年第3期9卷 698-709页

作者： Weidong Yang Erbo Shen Xuyu Wang Shiwen Mao Yuehong Gong Pengming Hu College of Information Science and Engineering Henan University of TechnologyZhengzhou450001China Henan Key Laboratory of Grain Photoelectric Detection and Control Zhengzhou450001China College of International Education Kaifeng UniversityKaifengHenan475004China Knight Foundation School of Computing&Information Sciences Florida International UniversityMiamiFL33199USA Department of Electrical and Computer Engineering Auburn UniversityAuburnAL36849-5201USA

In this paper,we propose a contact-free wheat moisture monitoring system,termed Wi-Wheatþ,to address the several limitations of the existing grain moisture detection technologies,such as time-consuming process,expensive equipment,low accuracy,and difficulty in real-time *** proposed system is based on Commodity WiFi and is easy to *** WiFi CSI data,this paper proposes a feature extraction method based on multi-scale and multi-channel *** feasibility and stability of the system are validated through experiments in both Line-Of-Sight(LOS)and Non-Line-Of-Sight(NLOS)scenarios,where ten types of wheat moisture content are tested using multi-class Support Vector Machine(SVM).Compared with the Wi-Wheat system proposed in our prior work,Wi-Wheatþhas higher efficiency,requiring only a simple training process,and can sense more wheat moisture content levels.

关键词： Channel state information(CSI) WiFi Multi-scale entropy Multi-class support vector machine(SVM) Radio frequency(RF)sensing

来源：评论

学校读者我要写书评

暂无评论

A graph attention network integrated with gated spiking neural P systems for session-based recommendation

引用

Expert Systems with Applications 2025年 286卷

作者： Bai, Xinzhu Peng, Hong Huang, Yanping Wang, Jun Yang, Qian Ramírez-De-Arellano, Antonio School of Computer and Software Engineering Xihua University Chengdu610039 China School of Electrical Engineering and Electronic Information Xihua University Chengdu610039 China Department of Computer Science and Artificial Intelligence Research Group of Natural Computing University of Seville Sevilla41012 Spain

With the development of deep learning technology, the recommender system began to use deep neural networks for modeling, which enables the recommendation system to better capture the complex patterns and features in the data. Session-based recommendation has also gradually received attention, especially for scenarios which deal with user behavior sequences and real-time requirements in a session. However, existing session-based recommendation methods tend to ignore users’ long-term interest changes, and there are still challenges for context understanding. In addition, session-based recommendation also has drift problems (i.e., the short-term behavior of users does not necessarily represent their real interests), which will affect the accuracy of recommendations. Therefore, this paper proposes a novel graph attention network, termed GAN-GSNP. This network combines a gated spiking neural P system with an extra balancing effect (EB-GSNP) to alleviate the drift problem in session-based recommendation by processing both global and local embeddings simultaneously. In addition, the GAN-GSNP model also proposes a multi-branch feature extraction strategy, which uses Self-Attention and feedforward networks in parallel to extract the high-order features embedded globally by users, so as to capture the global dependencies within the session or between different items, and make full use of the user's contextual information. Experimental results on two real datasets demonstrate the effectiveness and accuracy of the proposed GAN-GSNP model. © 2025 Elsevier Ltd

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Guest Editorial: Special issue on computational methods and artificial intelligence applications in low-carbon energy systems

引用

IET Renewable Power Generation 2024年第3期18卷 303-305页

作者： Wang, Yishen Zhou, Fei Guerrero, Josep M. Baker, Kyri Chen, Yize Wang, Hao Xu, Bolun Xu, Qianwen Zhu, Hong Agwan, Utkarsha State Grid Laboratory of Grid Advanced Computing and Applications State Grid Smart Grid Research Institute Co. Ltd. Beijing China Department of Energy Technology Aalborg University Aalborg Denmark Department of Civil Environmental and Architectural Engineering University of Colorado-Boulder BoulderCO United States Guangzhou China Department of Data Science and AI Monash University ClaytonVIC Australia Department of Earth and Environmental Engineering Columbia University New YorkNY United States Electric Power and Energy Systems Division KTH Royal Institute of Technology Stockholm Sweden State Grid Jiangsu Electric Power Co. Ltd. Nanjing China Department of Electrical Engineering and Computer Sciences University of California - Berkeley BerkeleyCA United States

来源：评论

学校读者我要写书评

暂无评论

Enhanced Image Registration for Precise Alignment of Brain and Liver CT Images

Enhanced Image Registration for Precise Alignment of Brain a...

引用

IEEE Recent Advances in Intelligent Computational Systems (RAICS)

作者： Adithya Gokulan S Mahati Reddy Varshith M Afnaan K Tripty Singh Mansi Sharma Department of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India Cloud Computing SW Artificial Intelligence Research Laboratory Electronics and Telecommunications Research Institute (ETRI) South Korea

ISBN: (数字)9798350381689

ISBN: (纸本)9798350381696

This study aims to assess improved methods of image registration to obtain accurate alignment of CT scans of the liver and brain. A collection of more than 1600 CT scans of the brain and liver is used in our research. We employ a variety of techniques, such as FFT-based registration with frequency domain analysis, Cv2 (OpenCV) for complete computer vision capabilities including picture alignment, and PystackReg, a Python package with a variety of registration algorithms. While Cv2 enables feature detection and geometric transformations, PystackReg offers a variety of transformation models. FFT uses spectral shifts to align images by taking advantage of frequency domains. By addressing particular aspects of the image, these techniques allow for accurate alignment of CT images throughout the registration process. As our CT dataset consists of two different anatomic data (Brain and Liver), we will divide the outcomes of each approach into two sections. To conclude our findings, we employ a variety of evaluation measures, including the Euclidean distance, Mean Square Error, Sum of Absolute Differences, and Jaccard Index. The FFT model is found to be more accurate in the dataset including brain CT scans, as evidenced by its higher Jaccard Index value (0.909) in comparison to the other models (0.439-PystackReg, 0.866-Cv2) and its lower Mean Square Error (0.090) in comparison to the other models (37.708-PystackReg, 0.130-Cv2). However, with the lowest Euclidean Measure (0.5974) and mean square error (0.0050) as compared to PystackReg (14.9810, 0.0386) and FFT (5.3996, 0.5727) models, respectively, the Cv2 Model performs better on liver CT images. These advancements could lead to better therapeutic evaluation, diagnostic capabilities, and personalized healthcare. They might also bring about a paradigm shift towards the analysis and interpretation of medical pictures that is more successful and efficient.

关键词： Image registration Accuracy Computed tomography Frequency-domain analysis Computational modeling Measurement uncertainty Liver Mean square error methods Brain modeling Indexes

来源：评论

学校读者我要写书评

暂无评论

AModified Search and Rescue Optimization Based Node Localization Technique inWSN

引用

computers, Materials & Continua 2022年第1期70卷 1229-1245页

作者： Suma Sira Jacob K.Muthumayil M.Kavitha Lijo Jacob Varghese M.Ilayaraja Irina V.Pustokhina Denis A.Pustokhin Department of Computer Science and Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Information Technology PSNA College of Engineering and TechnologyDindigul624622India Department of Electronics and Communication Engineering K.Ramakrishnan College of TechnologyTiruchirappalli621112India Department of Electrical and Electronics Engineering Christian College of Engineering and TechnologyOddanchatram624619India School of Computing Kalasalingam Academy of Research and EducationKrishnankoil626128India Department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia Department of Logistics State University of ManagementMoscow109542Russia

Wireless sensor network(WSN)is an emerging technology which find useful in several application areas such as healthcare,environmentalmonitoring,border surveillance,*** issues that exist in the designing of WSN are node localization,coverage,energy efficiency,security,and so *** spite of the issues,node localization is considered an important issue,which intends to calculate the coordinate points of unknown nodes with the assistance of *** efficiency of the WSN can be considerably influenced by the node localization ***,this paper presents a modified search and rescue optimization based node localization technique(MSRONLT)*** major aim of theMSRO-NLT technique is to determine the positioning of the unknown nodes in *** the traditional search and rescue optimization(SRO)algorithm suffers from the local optima problemwith an increase in number of iterations,MSRO algorithm is developed by the incorporation of chaotic maps to improvise the diversity of the *** application of the concept of chaotic map to the characteristics of the traditional SRO algorithm helps to achieve better exploration ability of the MSRO *** order to validate the effective node localization performance of the MSRO-NLT algorithm,a set of simulations were performed to highlight the supremacy of the presented model.A detailed comparative results analysis showcased the betterment of the MSRO-NLT technique over the other compared methods in terms of different measures.

关键词： Node localization WSN chaotic map search and rescue optimization algorithm localization error

来源：评论

学校读者我要写书评

暂无评论

Advancing Proactive Producer Mobility Management in Named Data Networking: A Conceptual Model 7

Advancing Proactive Producer Mobility Management in Named Da...

引用

7th International Conference on Internet Applications, Protocols, and Services, NETAPPS 2024

作者： Zukri, Nurul Hidayah Ahmad Arif, Ahmad Suki Che Mohamed Alsamman, Mohammed Abrar, Ahmad Fazea, Yousef Universiti Teknologi MARA Cawangan Perlis Kampus Arau Perlis Malaysia School of Computing Universiti Utara Malaysia Kedah Malaysia InterNetWorks Research Lab Universiti Utara Malaysia Kedah Malaysia Department of Computer Science and Electrical Engineering Marshall University One John Marshall Dr. HuntingtonWV25755 United States

ISBN: (纸本)9798331519513

In recent years, the Named Data Networking (NDN) paradigm has emerged as a promising candidate for future Internet architecture. Underpinned by the notion of a data-centric forwarding philosophy, NDN is purported to offer seamless network communication for mobile users. However, while it provides inherent support for consumer mobility, viable solutions for producer mobility remain insufficient. Therefore, this study aims to highlight the mobility issues in NDN, particularly concerning high latency, Interest packet loss, and Interest retransmission, with a focus on producer mobility. In this paper, we critically review previous works based on proactive and reactive approaches. Furthermore, we propose a mobility management model that adopts a proactive approach, estimating the producer's handoff time from the connected access point. The proposed model leverages this information to notify consumers about the moving producer, aiming to prevent consumers from sending Interest to the mobile producer during handoff and thereby overcome the associated challenges. © 2024 IEEE.

关键词： Named Data Network Proactive Producer Mobility

来源：评论

学校读者我要写书评

暂无评论

Two-Stage Robust Optimization Under Decision Dependent Uncertainty

引用

IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

来源：评论

学校读者我要写书评

暂无评论

Understanding wide field-of-view flat lenses:an analytical solution[Invited]

引用

Chinese Optics Letters 2023年第2期21卷 111-118页

作者：杨帆安森松 Mikhail Y.Shalaginov 张华亮胡崛隽古田 Department of Materials Science&Engineering Massachusetts Institute of TechnologyCambridgeMassachusetts 02139USA Department of Electrical&Computer Engineering University of Massachusetts LowellLowellMassachusetts 01854USA Materials Research Laboratory Massachusetts Institute of TechnologyCambridgeMassachusetts 02139USA

Wide field-of-view(FOV)optics are widely used in various imaging,display,and sensing *** wide FOV optics rely on complicated lens assembly comprising multiple elements to suppress coma and other Seidel *** emergence of flat optics exemplified by metasurfaces and diffractive optical elements(DOEs)offers a promising route to expand the FOV without escalating complexity of optical *** date,design of large FOV flat lenses has been relying upon iterative numerical ***,we derive,for the first time,to the best of our knowledge,an analytical solution to enable computationally efficient design of flat lenses with an ultra-wide FOV approaching 180°.This analytical theory further provides critical insights into working principles and otherwise non-intuitive design trade-offs of wide FOV optics.

关键词： metasurface metalens field-of-view

来源：评论

学校读者我要写书评

暂无评论

Organic-inorganic hybrid piezotronic bipolar junction transistor for pressure sensing

引用

Microsystems & Nanoengineering 2024年第3期10卷 229-244页

作者： Emad Iranmanesh Zihao Liang Weiwei Li Congwei Liao Shunyu Jin Chuan Liu Kai Wang Shengdong Zhang Charalampos Doumanidis Gehan A.J.Amaratunga Hang Zhou Guangdong Provincial Key Laboratory of In-Memory Computing Chips School of Electronic and Computer EngineeringPeking University Shenzhen Graduate SchoolShenzhen 518055P.R.China School of Mechanical Engineering Guangdong Technion-Israel Institute of TechnologyShantou 515063P.R.China State Key Laboratory of Microelectronics Device and Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029P.R.China Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of ChinaHefei 23000PR China School of Electronics and Information Technology Sun Yat-sen UniversityNo.132 East Waihuan RoadGuangzhou 510006P.R.China Department of Mechanical Aerospaceand Biomedical EngineeringUniversity of South AlabamaShelby Hall3128MobileAL 36688USA Electrical Engineering Division Department of EngineeringUniversity of Cambridge9 JJ Thomson AvenueCambridge CB30FAUnited Kingdom Zhejiang University International CampusHainingChina

With the rapid development of the Internet of Things(IoTs),wearable sensors are playing an increasingly important role in daily monitoring of personal health and *** signal-to-noise-ratio has become the most critical performance factor to *** enhance it,on the one hand,good sensing materials/devices have been employed;on the other hand,signal amplification and noise reduction circuits have been ***,most of these devices and circuits work in an active sampling mode,requiring frequent data acquisition and hence,entailing high-power *** this scenario,a flexible and wearable event-triggered sensor with embedded signal amplification without an external power supply is of great ***,we report a flexible two-terminal piezotronic n-p-n bipolar junction transistor(PBJT)that acts as an autonomous and highly sensitive,current-and/or voltage-mediated pressure *** PBJT is formed by two back-to-back piezotronic diodes which are defined as emitter-base and collectorbase *** force exertion on the emitter side,as a result of the piezoelectric effect,the emitter-base diode is forward biased while the collector-base diode is reverse *** to the inherent BJT amplification effect,the PBJT achieves record-high sensitivities of 139.7 kPa^(-1)(current-based)and 88.66 kPa^(-1)(voltage-based)in sensing *** PBJT also has a fast response time of<110 ms under exertion of dynamic stimuli ranging from a flying butterfly to a gentle finger ***,the PBJT advances the state of the art not only in terms of sensitivity but also in regard to being self-driven and autonomous,making it promising for pressure sensing and other IoT applications.

关键词： bipolar transistor IoT

来源：评论

学校读者我要写书评

暂无评论

PierGuard: A Planning Framework for Underwater Robotic Inspection of Coastal Piers

引用

IEEE Transactions on Automation science and engineering 2025年 22卷 15941-15952页

作者： Wang, Pengyu Lin, Hin Wang Li, Jialu Wang, Jiankun Shi, Ling Meng, Max Q.-H Southern University of Science and Technology Shenzhen Key Laboratory of Robotics Perception and Intelligence Department of Electronic and Electrical Engineering Shenzhen China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Southern University of Science and Technology Jiaxing Research Institute Jiaxing China Hong Kong University of Science and Technology Department of Chemical and Biological Engineering Hong Kong The Chinese University of Hong Kong Department of Electronic Engineering Hong Kong University of Alberta Canada Department of Electrical and Computer Engineering Canada

Using underwater robots instead of humans for the inspection of coastal piers can enhance efficiency while reducing risks. A key challenge in performing these tasks lies in achieving efficient and rapid path planning within complex environments. Sampling-based path planning methods, such as Rapidly-exploring Random Tree* (RRT*), have demonstrated notable performance in high-dimensional spaces. In recent years, researchers have begun designing various geometry-inspired heuristics and neural network-driven heuristics to further enhance the effectiveness of RRT*. However, the performance of these general path planning methods still requires improvement when applied to highly cluttered underwater environments. In this paper, we propose PierGuard, which combines the strengths of bidirectional search and neural network-driven heuristic regions. We design a specialized neural network to generate high-quality heuristic regions in cluttered maps, thereby improving the performance of the path planning. Through extensive simulation and real-world ocean field experiments, we demonstrate the effectiveness and efficiency of our proposed method compared with previous research. Our method achieves approximately 2.6 times the performance of the state-of-the-art geometric-based sampling method and nearly 4.9 times that of the state-of-the-art learning-based sampling method. Our results provide valuable insights for the automation of pier inspection and the enhancement of maritime safety. (Video1). © 2004-2012 IEEE.

关键词： Motion planning

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：