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International Joint Conference on Neural Networks

作者： Petros Karvelis Dimitris Gavrilis George Georgoulas Chrysostomos Stylios Laboratory of Knowledge and Intelligent Computing Technological Educational Institute of Epirus Arta Greece Department of Electrical Engineering and Computer Technology University of Patras Greece Control Engineering Group Luleâ University of Technology Sweden

The ever-increasing number of electronic content stored in digital libraries requires a significant amount of effort in cataloguing and has led to self-deposit solutions where the authors submit and publish their own digital records. Even in self-deposit, going through the abstract and assigning subject terms or keywords is a time consuming and expensive process, yet crucial for the metadata quality of the record that affects retrieval. Therefore, an automatic, or even a semi-automatic process that can recommend topics for a new entry is of huge practical value. A system that can address that has to rely basically on two components, one component for efficiently representing the relevant information of the new document and one component for recommending an appropriate set of topics based on the representation of the previous stage. In this work, different candidate solutions for both components are investigated and compared. For the first stage both distributed Document to Vector (doc2vec) and conventional Bag of Words (BoW) components are employed, while for the latter two different transformation approaches from the field of multi-label classification are compared. For the comparison, a collection of Ph.D. abstracts (～19000 documents) from the MIT Libraries Dspace repository is used suggesting that different combinations can provide high quality solutions.

关键词： Feature extraction Predictive models Libraries Neural networks Classification algorithms Task analysis Training

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P2P over MANET: A review and its conceptual framework 5

P2P over MANET: A review and its conceptual framework

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5th International Conference on Parallel, Distributed and Grid computing, PDGC 2018

作者： Muchtar, Farkhana Singh, Pradeep Kumar Zawani Ahmmad, Siti Nor Ambar, Radzi Hanafi, Hafizul Fahri Fadilah, Suzi Iryanti Faculty of Computing Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Department of CSE IT JayPee University of IT Waknaghat SolanHimachal Pradesh17334 India Instrumentation Control Engineering Universiti Kuala Lumpur MITEC Bandar Seri Alam Johor81750 Malaysia Faculty of Electronic Electrical Engineering Universiti Tun Hussein Onn Batu Pahat86400 Malaysia Faculty of Art Computing and Creative Industry Universiti Pendidikan Sultan Idris Tanjung Malim Perak35900 Malaysia School of Computer Sciences Universiti Sains Malaysia Gelugor Pulau Pinang11800 Malaysia

ISBN: (纸本)9781538660263

Lately, Peer to Peer (P2P) over Mobile Ad hoc Network have become a hot topics. Thus, the main motivation of this paper is to review various techniques that have been used in previously reported research of Peer to Peer (P2P) over Mobile Ad hoc Network (MANET). From the said document, it is identified that all previously techniques used in P2P over MANET have one similarity;namely maintaining the use of TCP/IP stack as network solution, in which the source for high energy resources for their proposed solution. Hence, this paper proposed a new solution beyond the TCP/IP stack paradigms in order to improve energy efficiency in P2P over MANET, whereby through the use of Content Centric Networking (CCN). In detail, this paper has included conceptual framework of our suggested solution. It is hoped that this paper achieves its two objectives: (i) to present a literature review on the topic of P2P over MANET, and (ii) to provide conceptual framework of our suggested solution. © 2018 IEEE.

关键词： Mobile ad hoc networks

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Design of Wireless Power Charging System for Driverless Pod Application

Design of Wireless Power Charging System for Driverless Pod ...

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International Conference on Automation and computing (ICAC)

作者： Mahmoud S. Issa Ahmed Onsy Mostafa S. Hamad Amany El-Zonkoly Electrical and Control Engineering Dept. Arab Academy for Science Technology and Maritime Transport Alexandria Egypt Computing and Technology Building University of Central Lancashire Preston UK

ISBN: (纸本)9781538648919

Driverless Pods can be classified as Electric Vehicles (EVs) which possibly represent environmentally friendly transportations. However, the battery technology is the real restriction in accomplishing this concept due to its drawbacks, for example, high cost, scarce components, weak specific energy and physical contact with charging device requirements. Besides the pursuit of materials and energy density development, wireless power transfer (WPT) technology which is another technique to charge the batteries of the EVs with no physical contact has been introduced. In this paper, an overview of WPT technologies for EVs charging has been presented including classification, compensation topologies, transformer structures and different charging control techniques. Then, A MATLAB Simulink model is used to simulate the load identification method in order to validate this technique which seeks to achieve a constant voltage charging through load identification depending only on the primary-side controller.

关键词： Topology Batteries Magnetic resonance Inductive charging Electric vehicle charging Wireless communication Mathematical model

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Detection and Tracking of Astral Microtubules in Fluorescence Microscopy Images

Detection and Tracking of Astral Microtubules in Fluorescenc...

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IEEE International Conference on Image Processing

作者： Joshua Levine Marco Grangetto Marilena Varrecchia Gabriella Olmo Computer Science dept. Università degli Studi di Torino Torino Italy Dept. of Control and Computing Engineering Politecnico di Torino Torino Italy

In this paper we explore detection and tracking of astral micro-tubules, a sub-population of microtubules which only exists during and immediately before mitosis and aids in the spindle orientation by connecting it to the cell cortex. Its analysis can be useful to determine the presence of certain diseases, such as brain pathologies and cancer. The proposed algorithm focuses on overcoming the problems regarding fluorescence microscopy images and microtubule behaviour by using various image processing techniques and is then compared with three existing algorithms, tested on consistent sets of images.

关键词： Microscopy Standards Image segmentation Signal to noise ratio Heuristic algorithms Fluorescence Drugs

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Acoustic Source Tracking in Reverberant Environment Using A Novel PSO Particle Filter Framework

Acoustic Source Tracking in Reverberant Environment Using A ...

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Chinese Automation Congress (CAC)

作者： Jing Yang Xiuqin Shang Bin Hu Zhen Shen Gang Xiong Hui Wang College of Information Sciences and Technology Beijing University of Chemical Technology Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Cloud Computing Center Chinese Academy of Sciences Dongguan China

In this paper, several methods are combined together and applied to a Particle Filter based on Particle Swarm Optimization acoustic source tracking framework in order to solve some problems of sound source tracking. The Time Difference of Arrival (TDOA), which is extracted from the audio signal received by the microphone pair, makes observations. The Langevin Model is used to describe the speaker's motion characteristics. The pseudo-likelihood function is constructed by using the Global Coherence Field (GCF) function to update the particle weight, in order to solve problem of the phenomenon of spurious source due to noise and reverberation. According to the iterative process and particle flight conditions, the inertial weights of the particles are adjusted nonlinearly and dynamically. The concepts of superior flight speed and inferior flight speed are introduced to Particle Swarm Optimization, which helps jump out of local optimum and solves the problem of lack of particle diversity. Thus, the faster tracking of sound source is realized. In the framework, with fewer particles, the robustness of tracking is enhanced and accuracy of tracking is improved. Finally, the effectiveness of this framework for acoustic source tracking is verified through several Monte Carlo simulation experiments.

关键词： Microphones Particle filters Particle swarm optimization Tracking Coherence Reverberation

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Cost Optimal control of Microgrids Having Solar Power and Energy Storage

Cost Optimal Control of Microgrids Having Solar Power and En...

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2018 IEEE/PES Transmission and Distribution Conference and Exposition, T and D 2018

作者： Gupta, Nikhil Francis, Griffin Ospina, Juan Newaz, Alvi Collins, Emmanuel G. Faruque, Omar Meeker, Rick Harper, Mario United States Center for Intelligent Systems Control and Robotics FAMU-FSU COE United States Department of Electrical and Computer Engineering FAMU-FSU COE United States Center for Advanced Power Systems FSU United States NHU Energy Inc. TallahasseeFL United States Department of Scientific Computing FSU United States

ISBN: (纸本)9781538655832

Solar power availability is intermittent and must be accompanied by an energy storage system (ESS) so that the effect of variability can be minimized. Hence, a strategy is needed to find the optimum combination of grid power, solar power, and power from the ESS so that the total cost of energy can be minimized. A solution to this problem is proposed here as Advanced Optimal Resource Allocation (AORA). This control scheme uses the prediction of Photovoltaic (PV) power availability, the real-time price of energy, and the levelized cost of energy for both PV and ESS to optimally combine the dispatch of power sources. Simulation results are presented for a 24 h prediction window and compared with a baseline power usage scheme that is based on a fixed charging and discharging schedule for the ESS. The comparison shows that AORA results in a substantial cost savings over the baseline scheme. © 2018 IEEE.

关键词： Forecasting

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An Image Denoising Method Based on Deep Residual GAN

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Journal of Physics: Conference Series 2020年第3期1550卷

作者： Ziyuan Wang Lidan Wang Shukai Duan Yunfei Li Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing 400715 China Schoolof Electronic and information engineering Southwest University Chongqing400715 China College of Artificiall Intelligence Southwest University Chongqing 400715 China Braininspired Computing & Intelligent Control of Chongqing Key Lab Chongqing 400715 China National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715 China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715 China

As people come into contact with image data more often, high quality and clear images attract more attention. Many methods have been proposed to deal with image noise problem including deep learning (DL). However most of them is lack of capability when customers want more perceptual details of the image without information loss. In this paper, a deep residual network based on generative adversarial (GAN) network was proposed to complete the image denoising mission. Firstly, a generative-adversarial network structure based on residual blocks was designed. Secondly, a refined loss function was given to train the GAN network. The well designed loss function can help the generated image to be very close to the clear counterpart (ground truth) while enhancing more details in colours and brightness. Finally, extensive experiments show that our network is not only convincing for images denoising, but also effective for other image process tasks, such as image defogging, medical CT denoising etc., presenting impressive and competitive effects.

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A Multi-Scroll Memristive Chaotic System via Fractal Process

A Multi-Scroll Memristive Chaotic System via Fractal Process

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International Conference on Information Science and Technology (ICIST)

作者： Liquan Xiao Shukai Duan Lidan Wang College of electronic and information engineering Southwest University Chongqing China National & Local Joint Engineering Southwest University Chongqing China Brain-inspired Computing & Intelligent Control of Chongqing Key Lab Southwest University Chongqing China

Fractal theory is a leading and important branch of nonlinear science, which has been widely studied in many fields in the past few decades. Memristor is a nanoscale element with low power consumption and high integration, when it works as the nonlinear part in a chaotic system, the complexity of the chaotic system will be enhanced. Compared with single-scroll chaotic attractor, multi-scroll chaotic attractor have higher complexity and better adaptability. In this paper, the fractal process is applied to a known memristive chaotic system, which can generate multi-scroll chaotic attractor. At first, a fractal iteration is applied to the memristive chaotic system to generate new chaotic attractor. Secondly, the multi-scroll chaotic system is obtained by combining the Julia fractal and memristive chaotic system. And by changing a complex constant in the fractal process, a fractal graph with different shapes is obtained, which can also be used to generate different chaotic attractors in the generating multi-scroll memristive chaotic system. Compared with other multi-scroll chaotic attractors, the proposed multi-scroll chaotic attractors are easier to adjust the number of the scrolls. It can be seen from the simulation diagram that the size of the system phase diagram becomes smaller and smaller as the number of scrolls increases. The results show that the new system has a lot of dynamic characteristics.

关键词： Fractals Chaotic communication Memristors Complexity theory Electronic mail

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Opinion Dynamics with Stubborn Neutrals and Competitive Interactions

Opinion Dynamics with Stubborn Neutrals and Competitive Inte...

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Chinese control Conference (CCC)

作者： Shidong Zhai Wei Xing Zheng Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing China School of Computing Engineering and Mathematics Western Sydney University Sydney NSW Australia

This paper investigates a general nonlinear model of opinion dynamics with stubborn neutrals and competitive interactions. Based on Perron-Frobenius property of eventually positive matrices and LaSalle invariance principle, we conduct a comprehensive theoretical analysis of the generalized nonlinear opinion dynamics. We obtain some sufficient conditions such that the states of all agents converge into the subspace spanned by the right positive eigenvector of an eventually positive matrix. Finally, a numerical example is given to illustrate obtained results.

关键词： Mathematical model Eigenvalues and eigenfunctions Jacobian matrices Electronic mail Social network services Null space Complex systems

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Foundation models and intelligent decision-making: Progress, challenges, and perspectives

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Innovation 2025年第6期6卷 100948页

作者： Huang, Jincai Xu, Yongjun Wang, Qi Wang, Qi [Cheems] Liang, Xingxing Wang, Fei Zhang, Zhao Wei, Wei Zhang, Boxuan Huang, Libo Chang, Jingru Ma, Liantao Ma, Ting Liang, Yuxuan Zhang, Jie Guo, Jian Jiang, Xuhui Fan, Xinxin An, Zhulin Li, Tingting Li, Xuefei Shao, Zezhi Qian, Tangwen Sun, Tao Diao, Boyu Yang, Chuanguang Yu, Chenqing Wu, Yiqing Li, Mengxian Zhang, Haifeng Zeng, Yongcheng Zhang, Zhicheng Zhu, Zhengqiu Lv, Yiqin Li, Aming Chen, Xu An, Bo Xiao, Wei Bai, Chenguang Mao, Yuxing Yin, Zhigang Gui, Sheng Su, Wentao Zhu, Yinghao Gao, Junyi He, Xinyu Li, Yizhou Jin, Guangyin Ao, Xiang Zhai, Xuehao Tan, Haoran Yun, Lijun Shi, Hongquan Li, Jun Fan, Changjun Huang, Kuihua Harrison, Ewen Leung, Victor C.M. Qiu, Sihang Dong, Yanjie Zheng, Xiaolong Wang, Gang Zheng, Yu Wang, Yuanzhuo Guo, Jiafeng Wang, Lizhe Cheng, Xueqi Wang, Yaonan Yang, Shanlin Fu, Mengyin Fei, Aiguo Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Department of Automation Tsinghua University Beijing100084 China Huazhong University of Science and Technology Wuhan430074 China School of Automation Beijing Institute of Technology Beijing100081 China School of Information Science and Engineering Dalian Polytechnic University Dalian116034 China National Engineering Research Center for Software Engineering Peking University Beijing100871 China Department of Oral Implantology Peking University School and Hospital of Stomatology Beijing100081 China Guangzhou511453 China College of Information and Electrical Engineering China Agricultural University Beijing100083 China IDEA Research International Digital Economy Academy Shenzhen518057 China Institute of Automation Chinese Academy of Sciences Beijing100190 China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China College of Science National University of Defense Technology Changsha410073 China Center for Systems and Control College of Engineering Peking University Beijing100871 China Gaoling School of Artificial Intelligence Renmin University of China Beijing100872 China College of Systems Engineering National University of Defense Technology Changsha410073 China Laboratory for Big Data and Decision National University of Defense Technology Changsha410073 China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore School of Electrical Engineering Chongqing University Chongqing400044 China Department of Mathematics The University of Hong Kong Hong Kong SAR999077 China School of Food Science and Technology Dalian Polytechnic University Dalian116034 China Centre for Medical Informatics University of Edinburgh EdinburghEH16 4UX United Kingdom Department of Stomatology Peking Union Medical College Hospital Chinese Academ

Intelligent decision-making (IDM) is a cornerstone of artificial intelligence (AI) designed to automate or augment decision processes. Modern IDM paradigms integrate advanced frameworks to enable intelligent agents to make effective and adaptive choices and decompose complex tasks into manageable steps, such as AI agents and high-level reinforcement learning. Recent advances in multimodal foundation-based approaches unify diverse input modalities—such as vision, language, and sensory data—into a cohesive decision-making process. Foundation models (FMs) have become pivotal in science and industry, transforming decision-making and research capabilities. Their large-scale, multimodal data-processing abilities foster adaptability and interdisciplinary breakthroughs across fields such as healthcare, life sciences, and education. This survey examines IDM's evolution, advanced paradigms with FMs and their transformative impact on decision-making across diverse scientific and industrial domains, highlighting the challenges and opportunities in building efficient, adaptive, and ethical decision systems. © 2025 The Authors

关键词： Reinforcement learning

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