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Author Correction: Drone-Person Tracking in Uniform Appearance Crowd: A New Dataset

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Scientific data 2025年第1期12卷 292页

作者： Mohamad Alansari Oussama Abdul Hay Sara Alansari Sajid Javed Abdulhadi Shoufan Yahya Zweiri Naoufel Werghi Department of Computer Science Khalifa University Abu Dhabi UAE. 100061914@ku.ac.ae. Department of Aerospace Engineering Khalifa University Abu Dhabi UAE. Advanced Research and Innovation Center (ARIC) Khalifa University Abu Dhabi UAE. Department of Computer Science Khalifa University Abu Dhabi UAE. Khalifa University Center for Autonomous Robotic Systems (KUCARS) Khalifa University Abu Dhabi UAE. Center for Cyber-Physical Systems (C2PS) Khalifa University Abu Dhabi UAE.

A Review on Swarm Intelligence and Evolutionary Algorithms for Solving Flexible Job Shop Scheduling Problems

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IEEE/CAA Journal of Automatica Sinica 2019年第4期6卷 904-916页

作者： Kaizhou Gao Zhiguang Cao Le Zhang Zhenghua Chen Yuyan Han Quanke Pan IEEE the Macao Institute of Systems Engineering at Macao University of Science and Technology 999078 China School of Computer at Liaocheng Univeristy Liaocheng252059China the Department of Industrial Systems Engineering and Management National University of SingaporeSingapore Centre for Maritime Studies National University of SingaporeSingapore the Institute for Infocomm Research(I2R) the Agency for ScienceTechnology and Research(A*STAR)Singapore the School of Computer at Liaocheng Univeristy Liaocheng 252059China School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200072China

Flexible job shop scheduling problems(FJSP)have received much attention from academia and industry for many *** to their exponential complexity,swarm intelligence(SI)and evolutionary algorithms(EA)are developed,employed and improved for solving *** than 60%of the publications are related to SI and *** paper intents to give a comprehensive literature review of SI and EA for solving ***,the mathematical model of FJSP is presented and the constraints in applications are ***,the encoding and decoding strategies for connecting the problem and algorithms are *** strategies for initializing algorithms?population and local search operators for improving convergence performance are ***,one classical hybrid genetic algorithm(GA)and one newest imperialist competitive algorithm(ICA)with variables neighborhood search(VNS)for solving FJSP are ***,we summarize,discus and analyze the status of SI and EA for solving FJSP and give insight into future research directions.

关键词： Evolutionary algorithm flexible job shop scheduling review swarm intelligence

Nonlinear signatures of Floquet band topology

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Physical Review B 2022年第11期105卷 115133-115133页

作者： Aleksandra Maluckov Ekaterina Smolina Daniel Leykam Sinan Gündoğdu Dimitris G. Angelakis Daria A. Smirnova Vinča Institute of Nuclear Sciences University of Belgrade National Institute of the Republic of Serbia P.O.B. 522 11001 Belgrade Serbia Institute of Applied Physics Russian Academy of Science Nizhny Novgorod 603950 Russia Centre for Quantum Technologies National University of Singapore 3 Science Drive 2 117543 Singapore Center for Theoretical Physics of Complex Systems Institute for Basic Science Daejeon 34126 Korea Department of Physics Humboldt-Universität zu Berlin Newtonstrasse 15 12489 Berlin Germany School of Electrical and Computer Engineering Technical University of Crete Chania 73100 Greece Nonlinear Physics Centre Research School of Physics Australian National University Canberra ACT 2601 Australia

We study how the nonlinear propagation dynamics of bulk states may be used to distinguish topological phases of slowly driven Floquet lattices. First, we show how instabilities of nonlinear Bloch waves may be used to populate Floquet bands and measure their Chern number via the emergence of nontrivial polarization textures in a similar manner to static (undriven) lattices. Second, we show how the nonlinear dynamics of nonstationary superposition states may be used to identify dynamical symmetry inversion points in the intracycle dynamics, thereby allowing anomalous Floquet phases to be distinguished from the trivial phase. The approaches may be readily implemented using light propagation in nonlinear waveguide arrays.

关键词： Nonlinear optics Photonics Topological materials

Adaptive folding and noise filtering for robust quantum error mitigation

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arXiv 2025年

作者： Koenig, Kathrin F. Reinecke, Finn Wellens, Thomas Fraunhofer Institute for Applied Solid State Physics Tullastr. 72 Freiburg79108 Germany Department of Sustainable Systems Engineering University of Freiburg Emmy-Noether-Str. 2 Freiburg79110 Germany Department of Computer Science University of Freiburg Georges-Köhler-Allee 51 Freiburg79110 Germany

Coping with noise in quantum computation poses significant challenges due to its unpredictable nature and the complexities of accurate modeling. This paper presents noise-adaptive folding, a technique that enhances zero-noise extrapolation (ZNE) through the use of adaptive scaling factors based on circuit error measurements. Furthermore, we introduce two filtering methods: one relies on measuring error strength, while the other utilizes statistical filtering to improve the extrapolation process. Comparing our approach with standard ZNE reveals that adaptive scaling factors can be optimized using either a noise model or direct error strength measurements from inverted circuits. The integration of adaptive scaling with filtering techniques leads to notable improvements in expectation-value extrapolation over standard ZNE. Our findings demonstrate that these adaptive methods effectively strengthen error mitigation against noise fluctuations, thereby enhancing the precision and reliability of quantum computations. © 2025, CC BY.

关键词： Qubits

Electrically Tunable Picosecond-scale Octupole Fluctuations in Chiral Antiferromagnets

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arXiv 2025年

作者： Konakanchi, Shiva T. Banerjee, Sagnik Rahman, Mohammad M. Yamane, Yuta Kanai, Shun Fukami, Shunsuke Upadhyaya, Pramey Department of Physics and Astronomy Purdue University West LafayetteIN47907 United States Elmore Family School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States Department of Chemistry and Biochemistry University of Maryland College ParkMD20742 United States Research Institute of Electrical Communication Tohoku University 2-1-1 Katahira Aoba-ku Sendai980-8577 Japan Frontier Research Institute for Interdisciplinary Sciences Tohoku University Sendai980-8578 Japan Tohoku University 2-1-1 Katahira Aoba-ku Sendai980–8577 Japan Center for Science and Innovation in Spintronics Tohoku University 2-1-1 Katahira Aoba-ku Sendai980–8577 Japan Kawaguchi332-0012 Japan Division for the Establishment of Frontier Sciences of Organization for Advanced Studies Tohoku University Tohoku University Sendai980-8577 Japan WPI-Advanced Institute for Materials Research Tohoku University 2-1-1 Katahira Aoba-ku Sendai980–8577 Japan Center for Innovative Integrated Electronic Systems Tohoku University 468-1 Aramaki Aza Aoba Aoba-ku Sendai980-0845 Japan Inamori Research Institute for Science Kyoto600-8411 Japan

We present a theory for the relaxation time of the octupole order parameter in nanoscale chiral antiferromagnets (AFMs) coupled to thermal baths and spin injection sources. Using stochastic spin dynamics simulations, we demonstrate that the octupole moment relaxes through two distinct mechanisms—escape over a barrier and precessional dephasing—as the barrier for octupole fluctuations is lowered relative to the thermal energy. Notably, the octupole moment relaxes orders of magnitude faster than the typical dipolar order parameters, reaching picosecond timescales. By combining Langer’s theory with an effective low-energy description of octupole dynamics in chiral AFMs, we derive analytical expressions for the relaxation times. We find that relaxation in chiral AFMs parallels dipole relaxation in XY magnets, with exchange fields serving the role of the dipole fields. Further, by drawing on the analogy between order parameter dynamics in XY magnets under spin injection and current-biased Josephson junctions, we propose a new scheme for electrically tuning the octupole relaxation times. Our work offers fundamental insights for the development of next-generation spintronic devices that harness octupole order parameters for information encoding, especially in octupole-based probabilistic computing. © 2025, CC BY.

关键词： Stochastic systems

Vision Transformer with Convolutions Architecture Search

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arXiv 2022年

作者： Zhang, Haichao Hao, Kuangrong Pedrycz, Witold Gao, Life Lei Tang, Xuesong Wei, Bing The College of Information Science and Technology Donghua University China The Engineering Research Center of Digitized Textile and Apparel Technology Ministry of Education Donghua University Shanghai201620 China The Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada The Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia The Systems Research Institute Polish Academy of Sciences Warsaw01-447 Poland CSIRO Waite Campus UrrbraeSA5064 Australia

Transformers exhibit great advantages in handling computer vision tasks. They model image classification tasks by utilizing a multi-head attention mechanism to process a series of patches consisting of split images. However, for complex tasks, Transformer in computer vision not only requires inheriting a bit of dynamic attention and global context, but also needs to introduce features concerning noise reduction, shifting, and scaling invariance of objects. Therefore, here we take a step forward to study the structural characteristics of Transformer and convolution and propose an architecture search method-Vision Transformer with Convolutions Architecture Search (VTCAS). The high-performance backbone network searched by VTCAS introduces the desirable features of convolutional neural networks into the Transformer architecture while maintaining the benefits of the multi-head attention mechanism. The searched block-based backbone network can extract feature maps at different scales. These features are compatible with a wider range of visual tasks, such as image classification (32 M parameters, 82.0% Top-1 accuracy on ImageNet-1K) and object detection (50.4% mAP on COCO2017). The proposed topology based on the multi-head attention mechanism and CNN adaptively associates relational features of pixels with multi-scale features of objects. It enhances the robustness of the neural network for object recognition, especially in the low illumination indoor scene. Copyright © 2022, The Authors. All rights reserved.

关键词： Convolution

Which algorithm to select in sports timetabling?

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arXiv 2023年

作者： Van Bulck, David Goossens, Dries Clarner, Jan-Patrick Dimitsas, Angelos Fonseca, George H.G. Lamas-Fernandez, Carlos Lester, Martin Mariusz Pedersen, Jaap Phillips, Antony E. Rosati, Roberto Maria Faculty of Economics and Business Administration Ghent University Tweekerkenstraat 2 Ghent9000 Belgium Core lab CVAMO FlandersMake@UGent Belgium Applied Algorithmic Intelligence Methods Department Zuse Institute Berlin Takustrase 7 Berlin14195 Germany Department of Informatics University of Ioannina University of Ioannina Greece Computing and Systems Department Federal University of Ouro Preto R. Diogo de Vasconcelos 122 Ouro Preto Brazil Southampton Business School University of Southampton United Kingdom Department of Computer Science University of Reading Reading United Kingdom 7bridges *** 23 Meard St London United Kingdom DPIA University of Udine via delle Scienze 206 Udine33100 Italy

Any sports competition needs a timetable, specifying when and where teams meet each other. The recent International Timetabling Competition (ITC2021) on sports timetabling showed that, although it is possible to develop general algorithms, the performance of each algorithm varies considerably over the problem instances. This paper provides a problem type analysis for sports timetabling, resulting in powerful insights into the strengths and weaknesses of eight state-of-the-art algorithms. Based on machine learning techniques, we propose an algorithm selection system that predicts which algorithm is likely to perform best based on the type of competition and constraints being used (i.e., the problem type) in a given sports timetabling problem instance. Furthermore, we visualize how the problem type relates to algorithm performance, providing insights and possibilities to further enhance several algorithms. Finally, we assess the empirical hardness of the instances. Our results are based on large computational experiments involving about 50 years of CPU time on more than 500 newly generated problem instances. © 2023, CC BY-NC-ND.

关键词： Scheduling algorithms

Hybrid Reinforcement Learning-based Sustainable Multi-User Computation Offloading for Mobile Edge-Quantum Computing

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arXiv 2025年

作者： Xu, Minrui Niyato, Dusit Kang, Jiawen Xiong, Zehui Chen, Mingzhe Kim, Dong In Shen, Xuemin College of Computing and Data Science Nanyang Technological University Singapore School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore487372 Singapore Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

Exploiting quantum computing at the mobile edge holds immense potential for facilitating large-scale network design, processing multimodal data, optimizing resource management, and enhancing network security. In this paper, we propose a pioneering paradigm of mobile edge quantum computing (MEQC) that integrates quantum computing capabilities into classical edge computing servers that are proximate to mobile devices. To conceptualize the MEQC, we first design an MEQC system, where mobile devices can offload classical and quantum computation tasks to edge servers equipped with classical and quantum computers. We then formulate the hybrid classical-quantum computation offloading problem whose goal is to minimize system cost in terms of latency and energy consumption. To solve the offloading problem efficiently, we propose a hybrid discrete-continuous multi-agent reinforcement learning algorithm to learn long-term sustainable offloading and partitioning strategies. Finally, numerical results demonstrate that the proposed algorithm can reduce the MEQC system cost by up to 30% compared to existing baselines. © 2025, CC BY.

关键词： Qubits

Multi-granularity ensemble sample selection and label correction for classification with noisy labels

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Applied Soft Computing 2025年 180卷

作者： Kecan Cai Hongyun Zhang Witold Pedrycz Duoqian Miao Chaofan Chen Department of Computer Science and Technology Tongji University Shanghai 201804 PR China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 PR China Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6G 2R3 Canada Systems Research Institute Polish Academy of Sciences 00-901 Warsaw Poland Istinye University Faculty of Engineering and Natural Sciences Department of Computer Engineering Sariyer/Istanbul Turkiye

Sample selection is crucial in classification tasks with noisy labels, yet most existing sample selection methods rely on a single criterion. These approaches often face challenges, including low purity of selected clean samples, and underfitting due to an insufficient number of selected clean training samples. To address these challenges, this paper proposes GNet-SSLC, a novel multi-granularity network framework that integrates multiple criteria ensemble sample selection (SS) and multiple views label correction (LC). In the SS phase, this paper proposes a metric learning-based dual k-Nearest Neighbor (k-NN) sample selection method. This method first uses corrected soft labels from the initial k-NN round to guide the selection of clean samples in the subsequent k-NN round. To further enhance selection accuracy, we combine this dual k-NN approach with a small loss sample selection technique through a voting mechanism. This multiple criteria ensemble method addresses the issues of low purity and instability inherent in single criterion approaches. In the LC phase, this paper designs a multiple views label correction framework that generates high-quality pseudo-labels for selected noisy samples. A key innovation of the framework is the design of a regularized contrastive learning loss, which optimizes the semi-supervised learning process by leveraging multiple views of training samples. The additional inclusion of training samples with high-quality pseudo-labels can effectively mitigate underfitting caused by a limited number of clean training samples. Experimental results on both synthetic and real-world noisy datasets indicate that GNet-SSLC enhances the purity and stability of the selected clean samples, and significantly improves classification performance. The enhancement is particularly notable with high noise rate dataset, such as CIFAR-100 dataset with 80% noise rate, achieving a 19.3% increase in classification accuracy compared to the baseline method.

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