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Modelling, control Methods and Applications of Chaotic Oscillators

Discrete Dynamics in Nature and Society 2023年第1期2023卷

作者： Vaidyanathan, Sundarapandian Sambas, Aceng Lien, Chang-Hua Mamat, Mustafa Centre for Control Systems Vel Tech University 400 Feet Outer Ring Road Chennai 600062 India Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Gong Badak 21300 Terengganu Malaysia Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Jawa Barat 46196 Indonesia Department of Marine Engineering National Kaohsiung University of Science and Technology Kaohsiung 81157 Taiwan

Some typical oscillations relate to nonlinear pendulums, population models, business cycles, and jerk systems [5]. Since the discovery of chaotic oscillations in a nonlinear weather model by Lorenz in 1963, chaotic oscillators, their modelling, and control have received much attention in the literature [1]. [...]the MATLAB simulation results of the buck converter with memristive load are shown to be in good agreement with the analog results obtained with PSIM. [...]the authors describe simulation results for an example of a remotely operated vehicle (ROV) with three degrees of freedom to demonstrate the efficacy of the suggested control approach in their research article. A unique feature of the proposed model is that the designed Chen chaotic oscillation system is integrated in a single chip with the advantages of smaller chip area, lower supply voltage, and power consumption.

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Prediction of exosomal piRNAs based on deep learning for sequence embedding with attention mechanism

Prediction of exosomal piRNAs based on deep learning for seq...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yajun Liu Yulian Ding Aimin Li Rong Fei Xie Guo Fangxiang Wu Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology Xi'an China Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Department of Computer Science Department of Mechanical Engineering Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

PIWI-interacting RNAs (piRNAs) are a type of small non-coding RNAs which bind with the PIWI proteins to exert biological effects in various regulatory mechanisms. A growing amount of evidence reveals that exosomal piRNAs are potential biomarkers for diagnosis and treatment of complex diseases. Effective methods for the prediction of exosomal piRNAs are the foundation of piRNA functional research. In this study, we propose an end-to-end deep network for identifying exosomal piRNAs based on features learned from natural language processing (NLP) models for sequence embedding with attention mechanism. First, a benchmark dataset is constructed by processing piRNA subcellular localization annotated data and sequence data. Moreover, bagging positive unlabeled learning is applied to get the reliable negative set. Finally, we treat a piRNA sequence as a sentence and its k-mer subsequence as a token. Sequence embedding models with self-attention mechanism is designed to extract features from exosome piRNA sequences, which are used for the prediction task. Compared with three competing methods, our model achieves the best performance and reveals the key factors of exosomal piRNA sequences by the attention mechanism. Our model characterizes exosomal piRNAs and could be beneficial for researchers to investigate exosomal piRNAs’ functions.

关键词： Proteins Location awareness RNA Biological system modeling Predictive models Feature extraction Natural language processing

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Inverse learning of black-box aggregator for robust Nash equilibrium

arXiv

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arXiv 2024年

作者： Chen, Guanpu Xu, Gehui He, Fengxiang Tao, Dacheng Parisini, Thomas Johansson, Karl Henrik Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden Digital Futures Stockholm100 44 Sweden Artificial Intelligence and its Applications Institute School of Informatics University of Edinburgh EdinburghEH8 9AB United Kingdom College of Computing & Data Science Nanyang Technological University Singapore639798 Singapore Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom Department of Engineering and Architecture University of Trieste Trieste34127 Italy

In this note, we investigate the robustness of Nash equilibria (NE) in multi-player aggregative games with coupling constraints. There are many algorithms for computing an NE of an aggregative game given a known aggregator. When the coupling parameters are affected by uncertainty, robust NE need to be computed. We consider a scenario where players' weight in the aggregator is unknown, making the aggregator kind of "a black box". We pursue a suitable learning approach to estimate the unknown aggregator by proposing an inverse variational inequality-based relationship. We then utilize the counterpart to reconstruct the game and obtain first-order conditions for robust NE in the worst case. Furthermore, we characterize the generalization property of the learning methodology via an upper bound on the violation probability. Simulation experiments show the effectiveness of the proposed inverse learning approach. Copyright © 2024, The Authors. All rights reserved.

关键词： Inverse problems

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Deep Learning-Based Object Pose Estimation: A Comprehensive Survey

arXiv

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arXiv 2024年

作者： Liu, Jian Sun, Wei Yang, Hui Zeng, Zhiwen Liu, Chongpei Zheng, Jin Liu, Xingyu Rahmani, Hossein Sebe, Nicu Mian, Ajmal The National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China The School of Architecture and Art Central South University Changsha410082 China The Department of Automation Tsinghua University Beijing100084 China The School of Computing and Communications Lancaster University LA1 4YW United Kingdom The Department of Information Engineering and Computer Science University of Trento Trento38123 Italy The Department of Computer Science The University of Western Australia WA6009 Australia

Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, have increasingly supplanted conventional algorithms reliant on engineered point pair features. Nevertheless, several challenges persist in contemporary methods, including their dependency on labeled training data, model compactness, robustness under challenging conditions, and their ability to generalize to novel unseen objects. A recent survey discussing the progress made on different aspects of this area, outstanding challenges, and promising future directions, is missing. To fill this gap, we discuss the recent advances in deep learning-based object pose estimation, covering all three formulations of the problem, i.e., instance-level, category-level, and unseen object pose estimation. Our survey also covers multiple input data modalities, degrees-of-freedom of output poses, object properties, and downstream tasks, providing the readers with a holistic understanding of this field. Additionally, it discusses training paradigms of different domains, inference modes, application areas, evaluation metrics, and benchmark datasets, as well as reports the performance of current state-of-the-art methods on these benchmarks, thereby facilitating the readers in selecting the most suitable method for their application. Finally, the survey identifies key challenges, reviews the prevailing trends along with their pros and cons, and identifies promising directions for future research. We also keep tracing the latest works at Awesome-Object-Pose-Estimation. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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HDiffTG: A Lightweight Hybrid Diffusion-Transformer-GCN Architecture for 3D Human Pose Estimation

arXiv

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arXiv 2025年

作者： Fu, Yajie Huang, Chaorui Li, Junwei Kong, Hui Tian, Yibin Li, Huakang Zhang, Zhiyuan College of Information Science and Electronic Engineering Zhejiang University China Faculty of Science and Technology University of Macau China College of Mechatronics and Control Engineering Shenzhen University China School of AI and Advanced Computing Xi’an Jiaotong-Liverpool University China School of Computing and Information Systems Singapore Management University Singapore

We propose HDiffTG, a novel 3D Human Pose Estimation (3DHPE) method that integrates Transformer, Graph Convolutional Network (GCN), and diffusion model into a unified framework. HDiffTG leverages the strengths of these techniques to significantly improve pose estimation accuracy and robustness while maintaining a lightweight design. The Transformer captures global spatiotemporal dependencies, the GCN models local skeletal structures, and the diffusion model provides step-by-step optimization for fine-tuning, achieving a complementary balance between global and local features. This integration enhances the model’s ability to handle pose estimation under occlusions and in complex scenarios. Furthermore, we introduce lightweight optimizations to the integrated model and refine the objective function design to reduce computational overhead without compromising performance. Evaluation results on the Human3.6M and MPI-INF-3DHP datasets demonstrate that HDiffTG achieves state-of-the-art (SOTA) performance on the MPI-INF-3DHP dataset while excelling in both accuracy and computational efficiency. Additionally, the model exhibits exceptional robustness in noisy and occluded environments. Source codes and models are available at https://***/CirceJie/HDiffTG Copyright © 2025, The Authors. All rights reserved.

关键词： Three dimensional computer graphics

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Branch-and-cut-and-price for agile earth observation satellite scheduling

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European Journal of Operational Research 2025年

作者： Peng, Guansheng Wang, Jianjiang Song, Guopeng Gunawan, Aldy Xing, Lining Vansteenwegen, Pieter School of Advanced Engineering and Great Bay Institute for Advanced Study Great Bay University Dongguan523000 China Defense Innovation Institute Chinese Academy of Military Science Beijing100071 China College of Systems Engineering National University of Defense Technology Changsha410073 China National Key Laboratory of Information Systems Engineering National University of Defense Technology Changsha410073 China School of Computing and Information Systems Singapore Management University Singapore178902 Singapore Research Institute of Intelligent Control and Manufacturing System Jiangsu University of Technology Changzhou213001 China KU Leuven Institute for Mobility - CIB Leuven3001 Belgium

The Agile Earth Observation Satellite scheduling selects and sequences satellite observations of possible targets on the Earth's surface, each with a specific profit and multiple time windows. The objective is to maximize the collected profit of all observations completed under some operational constraints. The problem can be modeled as a variant of the Team Orienteering Problem with Time Windows (TOPTW). The key differences with the regular TOPTW are twofold: first, a time-dependent transition time is required for each pair of consecutive observations to adjust the camera's look angles. Second, the time windows of each target vary during different observation cycles, called "orbits". Some targets are invisible during certain orbits. We call this variant the Time-dependent Team Orienteering Problem with Variable Time Windows. In this paper, we present an efficient branch-and-cut-and-price (BCP) algorithm that exploits the problem's characteristics to solve it to optimality. Some algorithmic enhancements have been implemented, such as a Lagrangian bound, an ng-path relaxation, a primal heuristic, and subset-row inequalities. Extensive experiments on different configurations of benchmark instances demonstrate the superior performance of the proposed BCP algorithm and its algorithmic enhancements. Moreover, the primal heuristic yields a high-quality lower bound and outperforms state-of-the-art heuristics. Finally, we adopt our framework to solve the well-known TOPTW, and our algorithm is much faster than state-of-the-art exact algorithms. © 2025 Elsevier B.V.

关键词： Branch and bound method

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Quantum Entanglement Based on Two-Photon Joint Subtraction from Two-Mode Squeezed Vacuum States

Quantum Entanglement Based on Two-Photon Joint Subtraction f...

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OptoElectronics and Communications Conference, OECC

作者： Hongbin Song Heyu Huang Hao Liu Ai Zhou Guofeng Zhang Hidehiro Yonezawa The General Education Division and Guangdong Key Laboratory of Optoelectronic Materials and Chips and Shenzhen Key Lab of Semiconductor Lasers The Chinese University of Hong Kong Shenzhen Shenzhen China School of Materials Science and Engineering and National Engineering Research Center of Fiber Optic Sensing Technology and Networks Wuhan University of Technology Wuhan China National Engineering Research Center of Fiber Optic Sensing Technology and Networks Wuhan University of Technology Wuhan China Department of Applied Mathematics The Hong Kong Polytechnic University Hongkong China Optical Quantum Control Research Team RIKEN Center for Quantum Computing Saitama Japan

We present and analyze the quantum entanglement generated from two-photon joint subtraction from two-mode squeezed vacuum states (TMSV). Larger entanglement negativity than single-photon jointly subtracted TMSV, photo... 详细信息

ISBN: (数字)9798350308396

ISBN: (纸本)9798350308402

关键词： Protocols Correlation Quantum entanglement Simulation Elementary particle vacuum Quantum networks Photonics

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Performance Analysis of Cooperative Wireless-Powered NOMA System With Energy Buffer

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2024年

作者： Xie, Kengyuan Cai, Guofa Ning, Ting He, Jiguang Kaddoum, Georges Guangdong University of Technology School of Information Engineering Guangzhou510006 China Chongqing University of Posts and Telecommunications Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing400065 China Great Bay University School of Computing and Information Technology China University of Oulu Centre for Wireless Communications Oulu90014 Finland University of Quebec Electrical Engineering Department École de Technologie Supérieure MontrealQCH2L 2C4 Canada Lebanese American University Artificial Intelligence and Cyber Systems Research Center Lebanon

This paper proposes an energy buffer aided cooperative wireless-powered non-orthogonal multiple access (NOMA) system, which includes a base station (BS), a near user (NU), and a far user (FU). To consider a more general case and improve the system performance as much as possible, both the NU and FU are equipped with energy buffers. Two different energy management policies are considered at the NU and FU, namely the best-effort policy (BEP) and on-off policy (OOP). In the proposed system, the NU and FU first collect and store radio frequency based energy from the BS. Then, the FU uses the stored energy to transmit its signal to both the BS and NU. The NU decodes the received signal from the FU and uses the stored energy to transmit the superimposed signal that consists of its own signal and the decoded FU signal to the BS. The outage probability and throughput expressions of the proposed system with BEP and OOP are derived over Rayleigh fading channels. Results reveal that the proposed system can significantly improve the performance of FU compared to the energy buffer aided non-cooperative wireless-powered NOMA system, and can outperform the buffer-less cooperative wireless-powered NOMA system. © 2017 IEEE.

关键词： Fading channels

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Redundant-Manipulator Minimal Motion via Different-Precision Discrete-Time Zhang Neural Dynamics Algorithms Especially Ten-Instant One

Redundant-Manipulator Minimal Motion via Different-Precision...

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2021 China Automation Congress, CAC 2021

作者： Tang, Zanyu Guo, Jinjin Chen, Jianrong Zhang, Yunong School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Jishou University Jishou China Guangdong Key Laboratory of Modern Control Technology Guangzhou China School of Public Health and Management Youjiang Medical University for Nationalities Baise China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangzhou China

ISBN: (纸本)9781665426473

As a significant and basic robotic sub-topic, the problem of optimal MPC (motion planning & control) of ordinarily redundant manipulator widely exists in many fields, such as industry and daily-life applications. Following previous work, the aim of this paper is at solving the problem of velocity-level minimal joint motion planning & control (VLMJMPC) in a way of discrete time. Firstly, the VLMJMPC problem is introduced and analyzed using Zhang neural dynamics (ZND) method, and the motion scheme is then given. Secondly, by using ZND and Lagrange-multiplier methods, a continuous-time (CT) model for real-time solving the problem is established. In order to realize on digital computers, we use a ten-instant Zhang time discretization (abbreviated as ZTD) general formula with the fifth-order precision to discretize the model, and a special algorithm with high precision is derived, developed and analyzed. Finally, five discrete-time ZND (DTZND) algorithms are further acquired by adopting this ten-instant ZTD formula and other ZTD formulas, and the corresponding theoretical analyses are given. Computer experiment results numerically verify the online effectiveness and correctness of the developed five DTZND algorithms. © 2021 IEEE

关键词： Redundant manipulators

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Explaining to a Computer: Enhancing Student Assessment with Programming and Simulating Execution 4th

Explaining to a Computer: Enhancing Student Assessment wit...

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4th BenchCouncil International Symposium on Intelligent Computers, Algorithms, and Applications, IC 2024

作者： Du, Yu Li, Zhenying Xu, Zhiwei Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Beijing Institute of Control Engineering Beijing100190 China Great Bay University Guangdong Dongguan523000 China

ISBN: (纸本)9789819663095

Accurately assessing students’ understanding of knowledge is essential in the teaching process. Traditional assessment methods rely on static and standardized questions, which often lack personalization and diversity. This makes these methods susceptible to plagiarism or cheating with tools such as large language models (LLMs). Inspired by Donald Knuth, the Knuth Test is an assessment method designed to address these limitations. We formulate the definition of "explaining to a computer" in the Knuth Test, requiring students to transform the knowledge they have learned into computational processes that can be executed on computing systems. Under this refined definition, the Knuth Test includes both programming and simulating execution, aligning more closely with real-world teaching scenarios. We collected data from over 1,300 students enrolled in the CS101 course over the past four years. The results demonstrate that both programming and simulating execution methods exhibit comparable effectiveness in assessing student performance, and their performance surpasses that of non-Knuth Test methods. These findings suggest that our refined assessment approach can enhance the evaluation of student understanding in introductory computer science education, providing valuable insights for the development of more effective teaching strategies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Students

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