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A Proposed Feature Selection Particle Swarm Optimization Adaptation for Intelligent Logistics--A Supply Chain Backlog Elimination Framework

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Computers, Materials & Continua 2024年第6期79卷 4081-4105页

作者： Yasser Hachaichi Ayman E.Khedr Amira M.Idrees College of computing and Information Technology at Khulais Department of Information SystemsUniversity of JeddahJeddah21959Saudi Arabia Faculty of Computers and Information Technology Future University in EgyptCairo11835Egypt

The diversity of data sources resulted in seeking effective manipulation and *** challenge that arises from the increasing dimensionality has a negative effect on the computation performance,efficiency,and stability of *** of the most successful optimization algorithms is Particle Swarm Optimization(PSO)which has proved its effectiveness in exploring the highest influencing features in the search space based on its fast convergence and the ability to utilize a small set of parameters in the search *** research proposes an effective enhancement of PSO that tackles the challenge of randomness search which directly enhances PSO *** the other hand,this research proposes a generic intelligent framework for early prediction of orders delay and eliminate orders backlogs which could be considered as an efficient potential solution for raising the supply chain *** proposed adapted algorithm has been applied to a supply chain dataset which minimized the features set from twenty-one features to ten significant *** confirm the proposed algorithm results,the updated data has been examined by eight of the well-known classification algorithms which reached a minimum accuracy percentage equal to 94.3%for random forest and a maximum of 99.0 for Naïve ***,the proposed algorithm adaptation has been compared with other proposed adaptations of PSO from the literature over different *** proposed PSO adaptation reached a higher accuracy compared with the literature ranging from 97.8 to 99.36 which also proved the advancement of the current research.

关键词： Optimization particle swarm optimization algorithm feature selection logistics supply chain management backlogs

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Anomalous negative magnetoresistance in quantum dot Josephson junctions with Kondo correlations

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Science China(Physics,Mechanics & Astronomy) 2024年第8期67卷 3-13页

作者： Mingtang Deng Chunlin Yu Guangyao Huang Rosa López Philippe Caroff Sepideh Ghalamestani Gloria Platero Hongqi Xu Institute for Quantum Information&State Key Laboratory of high performance computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China NanoLund and Division of Solid State Physics Lund UniversityLund S-22100Sweden China Greatwall Quantum Laboratory Changsha 410006China Institut de Física Interdisciplinària i de Sistemes Complexos IFISC Palma de Mallorca E-07122Spain Instituto de Ciencia de Materiales de Madrid Madrid 28049Spain Beijing Key Laboratory of Quantum Devices Key Laboratory for the Physics and Chemistry of Nanodevicesand Department of ElectronicsPeking UniversityBeijing 100871China Beijing Academy of Quantum Information Sciences Beijing 100193China Hefei National Laboratory Hefei 230088China

The interplay between superconductivity and the Kondo effect has stimulated significant interest in condensed matter *** compete when their critical temperatures are close and can give rise to a quantum phase transition that can mimic Majorana zero ***,we have fabricated and measured Al-InSb nanowire quantum dot-Al *** the Kondo regime,a supercurrent-induced zero-bias conductance peak *** zero-bias peak shows an anomalous negative magnetoresistance(NMR)at weak magnetic *** attribute this anomalous NMR to quasiparticle trapping at vortices in the superconductor leads as a weak magnetic field is *** trapping effect lowers the quasiparticle-caused dissipation and thus enhances the Josephson *** work connects the vortex physics and the supercurrent tunneling in Kondo regimes and can help further understand the physics of Josephson quantum dot system.

关键词： quantum dot Kondo correlation InSb nanowire quasiparticle trapping

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Quintessence anisotropic stellar models in quadratic and Born-Infeld modified teleparallel Rastall gravity

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Chinese Physics B 2024年第3期33卷 179-189页

作者： Allah Ditta 夏铁成 Irfan Mahmood Asif Mahmood department of Mathematics Shanghai University and Newtouch Center for Mathematics of Shanghai UniversityShanghai 200444China Centre for high Energy Physics University of the PunjabLahorePakistan College of Engineering Chemical Engineering DepartmentKing Saud University RiyadhSaudi Arabia

This study aims to discuss anisotropic solutions that are spherically symmetric in the quintessence field,which describe compact stellar objects in the modified Rastall teleparallel theory of *** achieve this goal,the Krori and Barua arrangement for spherically symmetric components of the line element is *** explore the field equations by selecting appropriate off-diagonal tetrad ***-Infeld function of torsion f(T)=β√λT+1-1 and power law form h(T)=δTn are *** Born-Infeld gravity was the first modified teleparallel gravity to discuss *** use the linear equation of state pr=ξρto separate the quintessence *** obtaining the field equations,we investigate different physical parameters that demonstrate the stability and physical acceptability of the stellar *** use observational data,such as the mass and radius of the compact star candidates PSRJ 1416-2230,Cen X-3,&4U 1820-30,to ensure the physical plausibility of our findings.

关键词： anisotropic spheres quintessence field modified Rastall teleparallel gravity equation of state(EoS) f(T)gravity

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Mental health in organizations from a healthcare analytics framework:taxonomic model,trends,and impact of COVID-19

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Journal of Management Analytics 2024年第1期11卷 62-86页

作者： Jorge Iván Pérez Rave Carlos Mario Zapata Jaramillo Gloria Patricia Jaramillo Álvarez IDINNOV research group IDINNOV S.A.SMedellínColombia department of computing and Decision Sciences Universidad Nacional de ColombiaMedellínColombia

Mental disorders negatively affect employee well-being and organizational *** face a challenge in terms of how to manage mental *** paper clarifies three issues(underlying patterns,trends,and impact of COVID-19)regarding the scientific study of mental health in organizations from a healthcare analytics *** framework comprises eight stages considering a text-driven approach with scientific corpora assisted by linguistic/computational and statistical *** study discovers a new taxonomic model comprising five patterns in the scientific discourse on the *** analyses reveal imbalances and concerns regarding the interests associated with the patterns,which is reinforced by examining patterns“before”and“during”*** paper complements psychological/epidemiological studies on mental health in organizations from a healthcare analytics perspective.

关键词： Healthcare analytics healthcare management analytics mental health scientific discourse text analytics taxonomy COVID-19 management analytics

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Nonlinear Extrapolation Estimates of π

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Acta Mathematicae Applicatae Sinica 2024年第1期40卷 91-108页

作者： Wen-qing Xu Sha-sha Wang Da-chuan Xu Beijing Institute for Scientific and Engineering computing Beijing University of TechnologyBeijing100124China department of Mathematics and Statistics California State UniversityLong BeachCalifornia90840USA department of Mathematics and Physics Shijiazhuang Tiedao UniversityShijiazhuang050043China

The classical Archimedean approximation of π uses the semiperimeter or area of regular polygons inscribed in or circumscribed about a unit circle in R~2 and it is well-known that by using linear combinations of these basic estimates,modern extrapolation techniques can greatly speed up the approximation ***,when n vertices are randomly selected on the circle,the semiperimeter and area of the corresponding random inscribed and circumscribing polygons are known to converge to π almost surely as n→∞,and by further applying extrapolation processes,faster convergence rates can also be achieved through similar linear combinations of the semiperimeter and area of these random *** this paper,we further develop nonlinear extrapolation methods for approximating π through certain nonlinear functions of the semiperimeter and area of such *** focus on two types of extrapolation estimates of the forms χ_n=S_n~αA_n~β and Y_n(p)=(αS_n~p+βA_n~p)~(1/p) where α+β=1,p≠0,and Sn and An respectively represents the semiperimeter and area of a random n-gon inscribed in the unit circle in R~2,and Xn may be viewed as the limit of Y_n(p) when p→*** deriving probabilistic asymptotic expansions with carefully controlled error estimates for Xn and Y_n(p),we show that the choice α=4/3,β=-1/3 minimizes the approximation error in both cases,and their distributions are also asymptotically normal.

关键词： Archimedean polygons random polygons approximations ofπ extrapolation processes asymptotic convergence

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Global Optimization for Heilbronn Problem of Convex Polygons Based on Bilinear Matrix Inequalities Solving

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Journal of Systems Science & Complexity 2024年

作者： QI Niuniu DEHBI Lydia LIU Banglong YANG Zhengfeng ZENG Zhenbing Shanghai Key Laboratory of Trustworthy computing East China Normal University department of Mathematics Shanghai University

This paper primarily focuses on solving the Heilbronn problem of convex polygons,which involves minimizing the area of a convex polygon P1P2···P_n while satisfying the condition that the areas of all triangles formed by consecutive vertices are equal to 1/*** problem is reformulated as a polynomial optimization problem with a bilinear objective function and bilinear constraints.A new method is presented to verify the upper and lower bounds for the optimization *** upper bound is obtained by the affine regular *** Bilinear Matrix Inequalities （BMI） theory and the branch-and-bound technique are used to verify the lower bound of the *** paper concludes by proving that the lower bound for the area minimization problem of a convex polygon with10 vertices is *** relative error compared to the global optimum is 0.104%.

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Nonlinear Filtering With Sample-Based Approximation Under Constrained Communication:Progress, Insights and Trends

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IEEE/CAA Journal of Automatica Sinica 2024年第07期11卷 1539-1556页

作者： Weihao Song Zidong Wang Zhongkui Li Jianan Wang Qing-Long Han IEEE the State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceCollege of Engineering Peking University the department of Computer Science Brunel University London the School of Aerospace Engineering Beijing Institute of Technology the School of Science Computing and Engineering Technologies Swinburne University of Technology

The nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical *** main objective of nonlinear filtering is to infer the states of a nonlinear dynamical system of interest based on the available noisy measurements. In recent years, the advance of network communication technology has not only popularized the networked systems with apparent advantages in terms of installation,cost and maintenance, but also brought about a series of challenges to the design of nonlinear filtering algorithms, among which the communication constraint has been recognized as a dominating concern. In this context, a great number of investigations have been launched towards the networked nonlinear filtering problem with communication constraints, and many samplebased nonlinear filters have been developed to deal with the highly nonlinear and/or non-Gaussian scenarios. The aim of this paper is to provide a timely survey about the recent advances on the sample-based networked nonlinear filtering problem from the perspective of communication constraints. More specifically, we first review three important families of sample-based filtering methods known as the unscented Kalman filter, particle filter,and maximum correntropy filter. Then, the latest developments are surveyed with stress on the topics regarding incomplete/imperfect information, limited resources and cyber ***, several challenges and open problems are highlighted to shed some lights on the possible trends of future research in this realm.

关键词： Communication constraints maximum correntropy filter networked nonlinear filtering particle filter sample-based approximation unscented Kalman filter

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More Than Lightening:A Self-Supervised Low-Light Image Enhancement Method Capable for Multiple Degradations

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 622-637页

作者： Han Xu Jiayi Ma Yixuan Yuan Hao Zhang Xin Tian Xiaojie Guo the Electronic Information School Wuhan UniversityWuhan 430072China IEEE the department of Electronic Engineering Chinese University of Hong KongHong Kong 999077China the College of Intelligence and computing Tianjin UniversityTianjin 300350China

Low-light images suffer from low quality due to poor lighting conditions,noise pollution,and improper settings of *** enhance low-light images,most existing methods rely on normal-light images for guidance but the collection of suitable normal-light images is *** contrast,a self-supervised method breaks free from the reliance on normal-light data,resulting in more convenience and better *** self-supervised methods primarily focus on illumination adjustment and design pixel-based adjustment methods,resulting in remnants of other degradations,uneven brightness and *** response,this paper proposes a self-supervised enhancement method,termed as *** can handle multiple degradations including illumination attenuation,noise pollution,and color shift,all in a self-supervised *** attenuation is estimated based on physical principles and local neighborhood *** removal and correction of noise and color shift removal are solely realized with noisy images and images with color ***,the comprehensive and fully self-supervised approach can achieve better adaptability and *** is applicable to various low light conditions,and can reproduce the original color of scenes in natural *** experiments conducted on four public datasets demonstrate the superiority of SLIE to thirteen state-of-the-art *** code is available at https://***/hanna-xu/SLIE.

关键词： Color correction low-light image enhancement self-supervised learning.

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Multi-Smart Meter Data Encryption Scheme Basedon Distributed Differential Privacy

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Big Data Mining and Analytics 2024年第1期7卷 131-141页

作者： Renwu Yan Yang Zheng Ning Yu Cen Liang School of Electronic Electrical Engineering and PhysicsFujian University of TechnologyFuzhou 350118China department of computing Sciences at The College at Brockport State University of New YorkNew YorkNY 14420USA

Under the general trend of the rapid development of smart grids,data security and privacy are facing serious challenges;protecting the privacy data of single users under the premise of obtaining user-aggregated data has attracted widespread *** this study,we propose an encryption scheme on the basis of differential privacy for the problem of user privacy leakage when aggregating data from multiple smart ***,we use an improved homomorphic encryption method to realize the encryption aggregation of users’***,we propose a double-blind noise addition protocol to generate distributed noise through interaction between users and a cloud platform to prevent semi-honest participants from stealing data by colluding with one ***,the simulation results show that the proposed scheme can encrypt the transmission of multi-intelligent meter data under the premise of satisfying the differential privacy *** if an attacker has enough background knowledge,the security of the electricity information of one another can be ensured.

关键词： smart grid homomorphic encryption data aggregation differential privacy cloud computing

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FDSC-YOLOv8:Advancements in Automated Crack Identification for Enhanced Safety in Underground Engineering

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 3035-3049页

作者： Rui Wang Zhihui Liu Hongdi Liu Baozhong Su Chuanyi Ma Key Laboratory of computing Power Network and Information Security Ministry of EducationShandong Computer Science Center(National Supercomputer Center in Jinan)Qilu University of Technology(Shandong Academy of Sciences)Jinan250353China School of Qilu Transportation Shandong UniversityJinan250100China Geotechnical and Structural Engineering Center Shandong UniversityJinan250061China Shandong Lairong high-Speed Railway Co. Ltd.Weihai264200China Shandong high-Speed Group Co. Ltd.Jinan250014China

In underground engineering,the detection of structural cracks on tunnel surfaces stands as a pivotal task in ensuring the health and reliability of tunnel ***,the dim and dusty environment inherent to under-ground engineering poses considerable challenges to crack *** paper proposes a crack segmentation algorithm termed as Focused Detection for Subsurface Cracks YOLOv8(FDSC-YOLOv8)specifically designed for underground engineering structural ***,to improve the extraction of multi-layer convolutional features,the fixed convolutional module is replaced with a deformable convolutional ***,the model’s receptive field is enhanced by introducing a multi-branch convolutional module,improving the extraction of shallow features for small ***,the Dynamic Snake Convolution module is incorporated to enhance the extraction capability for slender and weak ***,the Convolutional Block Attention Module(CBAM)module is employed to achieve better target *** FDSC-YOLOv8s algorithm’s mAP50 and mAP50-95 reach 96.5%and 66.4%,according to the testing data.

关键词： Crack segmentation improved YOLOv8 engineering applications feature extraction

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