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Strengthening network slicing for Industrial Internet with deep reinforcement learning

Digital Communications and Networks 2024年第4期10卷 863-872页

作者： Yawen Tan Jiadai Wang Jiajia Liu National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of CybersecurityNorthwestern Polytechnical UniversityXi’an710072China

Industrial Internet combines the industrial system with Internet connectivity to build a new manufacturing and service system covering the entire industry chain and value *** highly heterogeneous network structure and diversified application requirements call for the applying of network slicing *** robust network slicing is essential for Industrial Internet,but it faces the challenge of complex slice topologies caused by the intricate interaction relationships among Network Functions(NFs)composing the *** works have not concerned the strengthening problem of industrial network slicing regarding its complex network *** this end,we aim to study this issue by intelligently selecting a subset of most valuable NFs with the minimum cost to satisfy the strengthening ***-of-the-art AlphaGo series of algorithms and the advanced graph neural network technology are combined to build the *** results demonstrate the superior performance of our scheme compared to the benchmark schemes.

关键词： Industrial Internet Network slicing Deep reinforcement learning Graph neural network

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ReCSA:a dedicated sort accelerator using ReRAM-based content addressable memory

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Frontiers of Computer science 2023年第2期17卷 1-13页

作者： Huize LI Hai JIN Long ZHENG Yu HUANG Xiaofei LIAO National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabClusters and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

With the increasing amount of data,there is an urgent need for efficient sorting algorithms to process large data *** sorting algorithms have attracted much attention because they can take advantage of different hardware's *** the traditional hardware sort accelerators suffer“memory wall”problems since their multiple rounds of data transmission between the memory and the *** this paper,we utilize the in-situ processing ability of the ReRAM crossbar to design a new ReCAM array that can process the matrix-vector multiplication operation and the vector-scalar comparison in the same array *** this designed ReCAM array,we present ReCSA,which is the first dedicated ReCAM-based sort *** hardware designs,we also develop algorithms to maximize memory utilization and minimize memory exchanges to improve sorting *** sorting algorithm in ReCSA can process various data types,such as integer,float,double,and *** also present experiments to evaluate the performance and energy efficiency against the state-of-the-art sort *** experimental results show that ReCSA has 90.92×,46.13×,27.38×,84.57×,and 3.36×speedups against CPU-,GPU-,FPGA-,NDP-,and PIM-based platforms when processing numeric data *** also has 24.82×,32.94×,and 18.22×performance improvement when processing string data sets compared with CPU-,GPU-,and FPGA-based platforms.

关键词： ReCAM parallel sorting architecture design processing-in-memory

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Uncovering the Pre-Deterioration State during Disease Progression Based on Sample-Specific Causality Network Entropy(SCNE)

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Research 2025年第1期7卷 55-67页

作者： Jiayuan Zhong Hui Tang Ziyi Huang Hua Chai Fei Ling Pei Chen Rui Liu School of Mathematics and Big Data Foshan UniversityFoshan 528000China School of Biology and Biological Engineering South China University of TechnologyGuangzhou 510640China School of Mathematics South China University of TechnologyGuangzhou 510640China

Complex diseases do not always follow gradual ***,they may experience sudden shifts known as critical states or tipping points,where a marked qualitative change *** such a pivotal transition or pre-deterioration state holds paramount importance due to its association with severe disease ***,the task of pinpointing the pre-deterioration state for complex diseases remains an obstacle,especially in scenarios involving high-dimensional data with limited samples,where conventional statistical methods frequently prove *** this study,we introduce an innovative quantitative approach termed sample-specific causality network entropy(SCNE),which infers a sample-specific causality network for each individual and effectively quantifies the dynamic alterations in causal relations among molecules,thereby capturing critical points or pre-deterioration states of complex *** substantiated the accuracy and efficacy of our approach via numerical simulations and by examining various real-world datasets,including single-cell data of epithelial cell deterioration(EPCD)in colorectal cancer,influenza infection data,and three different tumor cases from The Cancer Genome Atlas(TCGA)*** to other existing six single-sample methods,our proposed approach exhibits superior performance in identifying critical signals or pre-deterioration ***,the efficacy of computational findings is underscored by analyzing the functionality of signaling biomarkers.

关键词： critical states sample specific causality network entropy pre deterioration state complex diseases tipping points high dimensional data numerical simulations

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Using analytic hierarchy process to evaluate deep learning for infrared target recognition

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Multimedia Tools and Applications 2024年第38期83卷 86229-86245页

作者： Xu, Laixiang Cao, Bingxu Wei, Xinhong Li, Bei Su, Jingfeng Ning, Shiyuan Zhao, Junmin School of Computer and Data Science Henan University of Urban Construction Pingdingshan467036 China School of Information Engineering Luohe Vocational Technology College Henan University of Technology Luohe Institute of Technology Luohe462000 China School of Computer and Data Science Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Pingdingshan467036 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Henan University of Urban Construction Pingdingshan467036 China Department of Software Information China Electronics Technology Group Corporation 36-th Research Institute Jiaxing314033 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Research Center of Intelligent Campus Application Engineering of Henan Province Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Henan University of Urban Construction Pingdingshan467036 China

In order to promote the evaluation performance of deep learning infrared automatic target recognition (ATR) algorithms in the complex environment of air-to-air missile research, we proposed an analytic hierarchy process (AHP) evaluation system consisting of the target recognition ability, the generalization recognition ability, the anti-interference ability, the background suppression ability, and the cost metrics ability. According to detailed quantitative analysis and experimental results, we establish probability evaluation models and get their probability values. Compared with traditional evaluation systems, our proposed method implementation is showing high reliability. Similar superior performances are also achieved, such as quick, comprehensive, and scientific. Through the above research, the key technology of deep learning performance evaluation in automatic target recognition has been broken through, which provides some basis and guidance for the analysis of infrared imaging-guided weapon systems. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Infrared imaging

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Variable Selection for High-dimensional Cox Model with Error Rate Control

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Journal of Systems science & Complexity 2025年第3期38卷 1162-1185页

作者： HE Baihua SHI Hongwei GUO Xu ZOU Changliang ZHU Lixing International Institute of Finance School of Management University of Science and Technology of China School of Statistics Beijing Normal University School of Statistics and Data Science LPMC KLMDASR and LEBPS Nankai University Center for Statistics and Data Science Beijing Normal University at Zhuhai Department of Mathematics Hong Kong Baptist University

Simultaneously finding active predictors and controlling the false discovery rate(FDR) for high-dimensional survival data is an important but challenging statistical problem. In this paper, the authors propose a novel variable selection procedure with error rate control for the high-dimensional Cox model. By adopting a data-splitting strategy, the authors construct a series of symmetric statistics and then utilize the symmetry property to derive a data-driven threshold to achieve error rate *** authors establish finite-sample and asymptotic FDR control results under some mild *** results as well as a real data application show that the proposed approach successfully controls FDR and is often more powerful than the competing approaches.

关键词： data-splitting false discovery rate high-dimensional survival data symmetry

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Towards High-Performance Graph Processing: From a Hardware/Software Co-Design Perspective

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Journal of Computer science & technology 2024年第2期39卷 245-266页

作者：廖小飞赵文举金海姚鹏程黄禹王庆刚赵进郑龙张宇邵志远 National Engineering Research Center for Big Data Technology and System School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Services Computing Technology and System Laboratory School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Cluster and Grid Computing Laboratory School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Zhejiang Lab Hangzhou 311121China

Graph processing has been widely used in many scenarios,from scientific computing to artificial *** processing exhibits irregular computational parallelism and random memory accesses,unlike traditional ***,running graph processing workloads on conventional architectures(e.g.,CPUs and GPUs)often shows a significantly low compute-memory ratio with few performance benefits,which can be,in many cases,even slower than a specialized single-thread graph *** domain-specific hardware designs are essential for graph processing,it is still challenging to transform the hardware capability to performance boost without coupled software *** article presents a graph processing ecosystem from hardware to *** start by introducing a series of hardware accelerators as the foundation of this ***,the codesigned parallel graph systems and their distributed techniques are presented to support graph ***,we introduce our efforts on novel graph applications and hardware *** results show that various graph applications can be efficiently accelerated in this graph processing ecosystem.

关键词： graph processing hardware accelerator software system high performance ecosystem

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Helicity-Controlled Spin Hall Angle in 2D Altermagnets with Rashba Spin-Orbit Coupling

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Chinese Physics Letters 2025年第1期42卷 134-140页

作者： Weiwei Chen Longhai Zeng W.Zhu Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province College of SciencesChina Jiliang UniversityHangzhou 310018China Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province College of ScienceChina Jiliang UniversityHangzhou 310018China School of Science Westlake UniversityHangzhou 310024China

We investigated the efficiency of charge-to-spin conversion in two-dimensional Rashba altermagnets,a class of materials that combines the characteristics of both ferromagnets and *** quantum linear response theory,we quantified the longitudinal and spin Hall conductivities in this system and demonstrated a substantial enhancement in the spin Hall angle below the band crossing point through the dual effects of relativistic spin–orbit interaction and nonrelativistic altermagnetic exchange ***,the results showed that the skew scattering and intrinsic mechanisms arising from Fermi sea states are almost negligible in this system,in contrast to conventional ferromagnetic Rashba *** findings not only elucidate the spin dynamics in Rashba altermagnets but also pave the way for developing novel strategies for manipulating charge-to-spin conversion via sophisticated control of noncollinear and collinear out-of-plane spin textures.

关键词： interaction magnets Rashba

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Structural insights, synthesis, and electrocatalysis of high entropy nanoparticles for fuel cell, metal-air battery, and water-splitting applications

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Progress in Natural science:Materials International 2024年第3期34卷 512-523页

作者： Xin Tong Hao Ye Yunrou Wu Xinxing Zhan Manqi Gu Shixia Luo Jiangning Gong Juan Tiana Yadian Xie School of Chemistry and Material Science Guizhou Normal University Center for the Physics of Low-Dimensional Materials School of Physics and Electronics School of Future Technology Henan University Key Laboratory of Low-Dimensional Materials and Big Data Guizhou Minzu University

High-entropy alloy nanoparticles(HEA-NPs) have recently sparked great interest in materials science. Their solidsolution states, derived from distinct HEA configurations, make them promising candidates for catalysts with exceptional activity, stability, and tunable performance. However, a comprehensive understanding of the underlying mechanisms governing their electrocatalytic behavior is still lacking, hindering the rational design of HEA electrocatalysts. This review summarizes the fundamental knowledge of HEA-NPs, including the structureactivity correlations of HEA-NPs, diverse synthesis strategies, and applications in electrochemical catalysis. The design strategies for guiding improvements in tunable performance were highlighted. The article concludes with insights, perspectives, and future directions, encapsulating the state-of-the-art knowledge and paving the way for further exploration in this dynamic field.

关键词： High-entropy alloy nanoparticles Structure-activity correlations Synthesis strategies Electrochemical catalysis

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Design of Adaptive Global Barrier-Function PID-Type Finite Time Tracking Control Method for Uncertain Systems

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3693-3706页

作者： Mobayen, Saleh National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliou640301 Taiwan

This article presents a novel adaptive control methodology for achieving robust and accurate tracking control of uncertain nonlinear systems using a combination of barrier functions, global sliding mode control, proportional-integral-derivative (PID) controllers, and finite time control techniques. The proposed adaptive barrier-function global PID-type control method is designed to handle both matched and unmatched uncertainties and adjust the control parameters in real time to account for changes in system dynamics and perturbations. It efficiently handles both matched and mismatched uncertainties, ensuring precise tracking performance even amid uncertain dynamics and disturbances. The methodology dynamically adjusts control parameters in real time to accommodate changes in system dynamics, enhancing adaptability and performance. The globality of the suggested controller ensures the absence of a reaching phase and establishes the presence of the sliding mode around the surface right from the beginning. The proposed method has also been expanded to address uncertain dynamic systems with both matched and unmatched disturbances, while accounting for actuator faults and input saturation. The efficacy of the proposed methodology is demonstrated through simulation studies and experimental results on a rotary inverted pendulum (RIP) system, showcasing rapid convergence and exceptional tracking capabilities in practical scenarios. The contributions of this research lie in presenting a novel methodology that significantly contributes to the field of nonlinear control systems, offering a robust framework capable of addressing uncertainties in complex nonlinear systems. The results show that the method achieves fast convergence and excellent tracking performance in the presence of uncertainties and disturbances. The proposed adaptive control methodology stands as a promising approach for overcoming the complexities involved in controlling uncertain nonlinear systems, paving t

关键词： Sliding mode control

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A Fair Scheduling Algorithm and Schedulability Analysis for Performance Asymmetric Multiprocessors 25

A Fair Scheduling Algorithm and Schedulability Analysis for ...

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25th IEEE International Conference on Industrial technology, ICIT 2024

作者： Wu, Peng Jin, Feihang Yan, Tao Institute of Big Data Science and Industry Shanxi University Taiyuan China School of Computer and Information Technology Shanxi University Taiyuan China Institute of Big Data Science and Industry School of Computer and Information Technology Taiyuan China

We propose a new scheduling policy for performance asymmetric multiprocessors that have identical instruction sets but different processing speeds. The difference between it and the original Pfair scheduling is that when selecting scheduling parameters such as the pseudo deadline of the subtask and selecting the processor when running the highest priority subtask, it can be aware of the performance asymmetry of the underlying processor. In addition, we also propose a sufficient schedulability test for Pfair scheduling on performance asymmetric multiprocessors. © 2024 IEEE.

关键词： Real time systems

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