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arXiv 2025年

作者： He, Yihan Hong, Ming-Chun Ding, Qiming Lin, Chih-Sheng Lai, Chih-Ming Fang, Chao Gong, Xiao Hou, Tuo-Hung Liang, Gengchiau Department of Electrical and Computer Engineering National University of Singapore 117583 Singapore Department of Electrical Engineering Institute of Electronics National Yang-Ming Chiao Tung University Hsinchu Taiwan Electronic and Optoelectronic System Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Center on Frontiers of Computing Studies Peking University Beijing100871 China Industry Academia Innovation School National Yang-Ming Chiao Tung University Hsinchu Taiwan

Molecular docking is a critical computational strategy in drug design and discovery, but the complex diversity of biomolecular structures and flexible binding conformations create an enormous search space that challenges conventional computing methods. Although quantum computing holds promise for these challenges, it remains constrained by scalability, hardware limitations, and precision issues. Here, we report a prototype of a probabilistic computer (p-computer) that efficiently and accurately solves complex molecular docking for the first time, overcoming previously encountered challenges. At the core of the system is a p-computing chip based upon our artificial tunable probabilistic bits (p-bits), which are compatible with computing-in-memory schemes, based upon 180 nm CMOS technology and BEOL HfO2 RRAM. We successfully demonstrated the superior performance of the p-computer in practical ligand-protein docking scenarios. A 42-node molecular docking problem of lipoprotein with LolA-LolCDE complex—a key point in developing antibiotics against Gram-negative bacteria, was successfully solved. Our results align well with the Protein-Ligand Interaction Profiler tool. This work marks the first application of p-computing in molecular docking-based computational biology, which has great potential to overcome the limitations in success rate and efficiency of current technologies in addressing complex bioinformatics problems. © 2025, CC BY.

关键词： Molecular docking

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Coalition Formation for Heterogeneous Federated Learning Enabled Channel Estimation in RIS-assisted Cell-free MIMO

arXiv

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arXiv 2025年

作者： Qi, Nan Liu, Haoxuan Tsiftsis, Theodoros A. Boulogeorgos, Alexandros-Apostolos A. Zhou, Fuhui Jin, Shi Wu, Qihui Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Nanjing210016 China Department of Informatics and Telecommunications University of Thessaly Lamia35100 Greece Department of Electrical and Computer Engineering University of Western Macedonia Kozani50100 Greece National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China

Downlink channel estimation remains a significant bottleneck in reconfigurable intelligent surface-assisted cell-free multiple-input multiple-output communication systems. Conventional approaches primarily rely on centralized deep learning methods to estimate the high-dimensional and complex cascaded channels. These methods require data aggregation from all users for centralized model training, leading to excessive communication overhead and significant data privacy concerns. Additionally, the large size of local learning models imposes heavy computational demands on end users, necessitating strong computational capabilities that most commercial devices lack. To address the aforementioned challenges, a coalition-formation-guided heterogeneous federated learning (FL) framework is proposed. This framework leverages coalition formation to guide the formation of heterogeneous FL user groups for efficient channel estimation. Specifically, by utilizing a distributed deep reinforcement learning (DRL) approach, each FL user intelligently and independently decides whether to join or leave a coalition, aiming at improving channel estimation accuracy, while reducing local model size and computational costs for end users. Moreover, to accelerate the DRL-FL convergence process and reduce computational burdens on end users, a transfer learning method is introduced. This method incorporates both received reference signal power and distance similarity metrics, by considering that nodes with similar distances to the base station and comparable received signal power have a strong likelihood of experiencing similar channel fading. Massive experiments performed that reveal that, compared with the benchmarks, the proposed framework significantly reduces the computational overhead of end users by 16%, improves data privacy, and improves channel estimation accuracy by 20%. © 2025, CC BY.

关键词： Federated learning

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A new quantum-inspired pattern based on Goldner-Harary graph for automated alzheimer’s disease detection

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Cognitive Neurodynamics 2025年第1期19卷 1-19页

作者： Sercek, Ilknur Sampathila, Niranjana Tasci, Irem Ekmekyapar, Tuba Tasci, Burak Barua, Prabal Datta Baygin, Mehmet Dogan, Sengul Tuncer, Turker Tan, Ru-San Acharya, U.R. Department of Digital Forensics Engineering College of Technology Firat University Elazig Turkey Department of Biomedical Engineering Manipal Academy of Higher Education Manipal India Department of Neurology School of Medicine Firat University Elazig 23119 Turkey Department of Neurology Malatya Training and Research Hospital Malatya 44000 Turkey Vocational School of Technical Sciences Firat University Elazig 23119 Turkey School of Business (Information System) University of Southern Queensland Toowoomba Australia Department of Computer Engineering College of Engineering Erzurum Technical University Erzurum Turkey Department of Cardiology National Heart Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore School of Mathematics Physics and Computing University of Southern Queensland Springfield Australia

Alzheimer's disease (AD) is a common cause of dementia. We aimed to develop a computationally efficient yet accurate feature engineering model for AD detection based on electroencephalography (EEG) signal inputs. New method: We retrospectively analyzed the EEG records of 134 AD and 113 non-AD patients. To generate multilevel features, a multilevel discrete wavelet transform was used to decompose the input EEG-signals. We devised a novel quantum-inspired EEG-signal feature extraction function based on 7-distinct different subgraphs of the Goldner-Harary pattern (GHPat), and selectively assigned a specific subgraph, using a forward-forward distance-based fitness function, to each input EEG signal block for textural feature extraction. We extracted statistical features using standard statistical moments, which we then merged with the extracted textural features. Other model components were iterative neighborhood component analysis feature selection, standard shallow k-nearest neighbors, as well as iterative majority voting and greedy algorithm to generate additional voted prediction vectors and select the best overall model results. With leave-one-subject-out cross-validation (LOSO CV), our model attained 88.17% accuracy. Accuracy results stratified by channel lead placement and brain regions suggested P4 and the parietal region to be the most impactful. Comparison with existing methods: The proposed model outperforms existing methods by achieving higher accuracy with a computationally efficient quantum-inspired approach, ensuring robustness and generalizability. Cortex maps were generated that allowed visual correlation of channel-wise results with various brain regions, enhancing model explainability. © The Author(s) 2025.

关键词： Alzheimer’s disease Brain-computer interface EEG GHPat Goldner-Harary graph Signal classification

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Filtering Content Distributed via BitTorrent over Hidden Networks

Filtering Content Distributed via BitTorrent over Hidden Net...

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2019 IEEE International Conference "Quality Management, Transport and Information Security, Information Technologies" IT and QM and IS 2019

作者： Frolov, Aleksey A. Silnov, Dmitry S. Kiamov, Amir A. Department of Computer System and Technology Moscow Russia

ISBN: (纸本)9781728125954

This article addresses the problem of distributing copyrighted thematic content to increase the possibilities for restricting access to such content. The analysis of existing solutions in this area is carried out, highlighting the shortcomings of these solutions, options for applying these methods to limit the distribution of thematic content in hidden parts of the Internet. A new approach is proposed to limit access to thematic content that is distributed using the BitTorrent protocol in hidden networks. The proposed approach also uses the disadvantages and advantages of the network in which thematic content is distributed. An experiment is described for applying this approach to Darknet resources. The results of the experiment highlighted the pros and cons of the proposed approach. The final part contains conclusions about the possibility of using the proposed approach in hidden networks. © 2019 IEEE.

关键词： BitTorrent Content Filtering

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Activity-based simulation using DEVS: increasing performance by an activity model in parallel DEVS simulation

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Journal of Zhejiang University-Science C(computers and Electronics) 2014年第1期15卷 13-30页

作者： Bin CHEN Lao-bing ZHANG Xiao-cheng LIU Hans VANGHELUWE College of Information System and Management National University of Defense Technology Department of Mathematics and Computer Science University of Antwerp School of Computer Science McGill University

Improving simulation performance using activity tracking has attracted attention in the modeling field in recent *** reference to activity has been successfully used to predict and promote the simulation *** activity,however,uses only the inherent performance information contained in the *** extend activity prediction in modeling,we propose the activity enhanced modeling with an activity meta-model at the *** meta-model provides a set of interfaces to model activity in a specific *** activity model transformation in subsequence is devised to deal with the simulation difference due to the heterogeneous activity ***,the resource-aware simulation framework is implemented to integrate the activity models in activity-based *** case study shows the improvement brought on by activity-based simulation using discrete event system specification(DEVS).

关键词： Activity tracking Activity enhanced modeling Discrete event system specification(DEVS) Resource-aware simulation framework

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Improved scatter search for 4-colour mapping problem

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International Journal of Reasoning-based Intelligent systems 2012年第4期4卷 221-226页

作者： Sadiq, Ahmed T. Sagheer, Ali Makki Ibrahim, Mohammed Salah Computer Science Department University of Technology Baghdad Iraq Information System Department College of Computer University of Anbar Ramadi Iraq Computer Science Department College of Computer University of Anbar Ramadi Iraq

The paper presents an improvement to the Scatter Search algorithm. The improvement is achieved by adding some of Bees Algorithm concepts to the Scatter Search algorithm. These concepts provided Scatter Search algorithm with more of exploration for problem search space and intensification for promising solutions. The original and improved Scatter Search algorithms have been tested on local 4-Colour Mapping problem instances and the results have been reported. The computational results illustrate that the improved Scatter Search algorithm is better than the original Scatter Search algorithm. © 2012 Inderscience Enterprises Ltd.

关键词： Learning algorithms

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Transfer function adaptation for effective feature selection with the side-blotched lizard algorithm

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Multimedia Tools and Applications 2024年 1-21页

作者： Eisa, Mohamed Abdel-lah, Marwa Farouk, Fifi Abdel-aal, Amr System and Information Technology Department Faculty of Management Technology and Information System Port Said University Port Said Egypt Department of Computer Science Faculty of Computer and Informatics Zagazig University Zagazig Egypt

Feature selection is a crucial preprocessing step in data mining and machine learning, enhancing model performance and computational efficiency. This paper investigates the effectiveness of the Side-Blotched Lizard Optimization Algorithm (SBLA) for feature selection by developing six novel variants: Sbla-s1, Sbla-s2, Sbla-s3, Sbla-v1, Sbla-v2, and Sbla-v3, each employing distinct S-shaped or V-shaped transfer functions to convert the continuous search space to a binary format. These variants were rigorously evaluated on nineteen benchmark datasets from the UCI repository, comparing their performance based on average classification accuracy, average number of selected features, and average fitness value. The results demonstrated the superiority of Sbla-s3, achieving an average classification accuracy of 92.8% across all datasets, a mean number of selected features of 20, and an average fitness value of 0.08. Furthermore, Sbla-s3 consistently outperformed six other state-of-the-art metaheuristic algorithms, achieving the highest average accuracy on sixteen out of nineteen datasets. These findings establish Sbla-s3 as a promising and effective approach for feature selection, capable of identifying relevant features while maintaining high classification accuracy, potentially leading to improved model performance in various machine learning applications. © The Author(s) 2024.

关键词： Heuristic algorithms

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Concurrent Competitive Wave Approach toHyper-Distributed Hyper-Parallel AIProcessing

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Journal of computer Science & technology 1997年第6期12卷 543-554页

作者：帅典勋 Department of Computer Science East China University of Science and Technology Shanghai State Key Laboratory of Intelligence Technology and System Tsinghua University Beijing

This paper preseflts a new approach of the synchronous homogeneous concurrent propagation of competitive waves for the purpose of hyper-distributed hyper-parallel heuristic problem-solving. The concurrent algorithm, mechanism and their properties are given. In comparison with the traditional AI algorithms, the approach is featured by the knowledge-based problem-solving in the distributed parallel environment, the feasibility for hardware implementation and the various applications.

关键词： Hyper-distributed hyper-parallel processing synchronous homogeneous competitive wave heuristic search implicit AND/OR graph concurrent algorithm

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Hyper-Distributed Hyper-Parallel Implementation of Heuristic Search ofImplicit AND/OR Graph

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Journal of computer Science & technology 1997年第6期12卷 532-542页

作者：帅典勋 Department of Computer Science East China University of Science and Technology Shanghai State Key Laboratory of Intelligence Technology and System Tsinghua University Beijing

This paper presents the hierarchic chaotic cellular networks for the hardware implementation of hyper-distributed hyper-parallel intelligent problem solving based on competitive wave propagation. By using the bifurcation and the synchronization of distributed chaotic dynamic systems, and by improving the Chua's circuit, the mechanism and the algorithms of heuristic search of an implicit AND/OR graph are realized in a hyper-distributed hyper-parallel environment. This paper's approach has many advantages in comparison with other traditional systolic structures based on symbolic logic algorithms.

关键词： Chaos Chua's circuit synchronization bifurcation heuristic search Petri network

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SwiftArray: Accelerating Queries on Multidimensional Arrays

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Tsinghua Science and technology 2014年第5期19卷 521-530页

作者： Yifeng Geng Xiaomeng Huang Guangwen Yang Department of Computer Science and Technology Tsinghua University Ministry of Education Key Laboratory for Earth System Modeling Tsinghua University

Scientific instruments and simulation programs are generating large amounts of multidimensional array data. Queries with value and dimension subsetting conditions are commonly used by scientists to find useful information from big array data, and data storage and indexing methods play an important role in supporting queries on multidimensional array data efficiently. In this paper, we propose SwiftArray, a new storage layout with indexing techniques to accelerate queries with value and dimension subsetting conditions. In SwiftArray, the multidimensional array is divided into blocks and each block stores sorted values. Blocks are placed in the order of a Hilbert space-filling curve to improve data locality for dimension subsetting queries. We propose a 2-D-Bin method to build an index for the blocks＇ value ranges, which is an efficient way to avoid accessing unnecessary blocks for value subsetting queries. Our evaluations show that SwiftArray surpasses the NetCDF-4 format and FastBit indexing technique for queries on multidimensional arrays.

关键词： multidimensional array indexing space-filling curve

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