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science China(Information sciences) 2024年第2期67卷 20-40页

作者： Peng YANG Laoming ZHANG Haifeng LIU Guiying LI Department of Statistics and data science Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and EngineeringSouthern University of Science and Technology Academy for Advanced Interdisciplinary Studies Southern University of Science and Technology Guangdong OPPO Mobile Telecommunications Corp. Ltd Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology

In recent years, various companies have started to shift their data services from traditional data centers to the cloud. One of the major motivations is to save on operational costs with the aid of cloud elasticity. This paper discusses an emerging need from financial services to reduce the incidence of idle servers retaining very few user connections, without disconnecting them from the server side. This paper considers this need as a bi-objective online load balancing problem. A neural network based scalable policy is designed to route user requests to varied numbers of servers for the required elasticity. An evolutionary multi-objective training framework is proposed to optimize the weights of the policy. Not only is the new objective of idleness reduced by over 130% more than traditional industrial solutions, but the original load balancing objective itself is also slightly improved. Extensive simulations with both synthetic and real-world data help reveal the detailed applicability of the proposed method to the emergent problem of reducing idleness in financial services.

关键词： evolutionary reinforcement learning evolutionary multi-objective optimization load balance cloud computing

Mixed convectional and chemical reactive flow of nanofluid with slanted MHD on moving permeable stretching/shrinking sheet through nonlinear radiation,energy omission

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Chinese Physics B 2024年第5期33卷 193-202页

作者： Saleem Nasir Sekson Sirisubtawee Pongpol Juntharee Taza Gul Department of Mathematics Faculty of Applied ScienceKing Mongkut's University of Technology North BangkokBangkok 10800Thailand Department of Mathematics City University of Science and Information TechnologyPeshawarPakistan

Hybrid nanofluids are remarkable functioning liquids that are intended to reduce the energy loss while maximizing the heat *** the involvement of suction and nonlinear thermal radiation effects,this study attempted to explore the energy transmission features of the inclined magnetohydrodynamic(MHD)stagnation flow of CNTs-hybrid nanofluid across the nonlinear permeable stretching or shrinking *** work also included some noteworthy features like chemical reactions,variable molecular diffusivity,quadratic convection,viscous dissipation,velocity slip and heat omission *** appropriate similarity components,the model equations were modified to ODEs and computed by using the HAM *** impact of various relevant flow characteristics on movement,heat and concentration profiles was investigated and plotted on a *** various model factors,the significance of drag friction,heat and mass transfer rate were also computed in tabular and graphical *** leads to the conclusion that such factors have a considerable impact on the dynamics of fluid as well as other engineering measurements of ***,viscous forces are dominated by increasing the values ofλ_(p),δ_(m)andδ_(q),and as a result,F(ξ)accelerates while the opposite trend is observed for M andφ.The drag friction is boosted by the augmentation M,λ_(p)andφ,but the rate of heat transfer *** to our findings,hybrid nanoliquid effects dominate that of ordinary nanofluid in terms of F(ξ),Θ(ξ)andφ(ξ)*** HAM and the numerical technique(shooting method)were found to be in good agreement.

关键词： hybrid nanofluid(SWCNT+MWCNT/H_(2)O) velocity slip conditions nonlinear thermal radiation exponential stretching/shrinking sheet inclined magnetohydrodynamic(MHD)stagnation flow

Study on the optimal incident proton energy of ^(7)Li(p,n)^(7)Be neutron source for boron neutron capture therapy

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Nuclear science and Techniques 2024年第3期35卷 170-180页

作者： Yi-Nan Zhu Zuo-Kang Lin Hai-Yan Yu Ye Dai Zhi-Min Dai Xiao-Han Yu Shanghai Institute of applied Physics Chinese Academy of SciencesShanghai 201800China University of Chinese Academy of science Beijing 100049China

Boron neutron capture therapy(BNCT)is recognized as a precise binary targeted radiotherapy technique that effectively eliminates tumors through the^(10)B(n,α)^(7)Li nuclear *** various neutron sources,accelerator-based sources have emerged as particularly promising for BNCT ***^(7)Li(p,n)^(7)Be reaction is highly regarded as a potential neutron source for BNCT,owing to its low threshold energy for the reaction,significant neutron yield,appropriate average neutron energy,and additional *** study utilized Monte Carlo simulations to model the physical interactions within a lithium target subjected to proton bombardment,including neutron moderation by an MgF_(2)moderator and subsequent BNCT dose analysis using a Snyder head *** study focused on calculating the yields of epithermal neutrons for various incident proton energies,finding an optimal energy at 2.7 ***,the Snyder head phantom was employed in dose simulations to validate the effectiveness of this specific incident energy when utilizing a^(7)Li(p,n)^(7)Be neutron source for BNCT purposes.

关键词： Boron neutron capture therapy ^(7)Li(p,n)7Be neutron source Incident proton energy Monte Carlo simulation

Microstructure and magnetocaloric properties of melt-extracted SmGdDyCoAl high-entropy amorphous microwires

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Rare Metals 2024年第3期43卷 1234-1242页

作者： Shi-Jie Wei Hong-Xian Shen Lun-Yong Zhang Lin Luo Xin-Xing Tang Jian-Fei Sun Xiao-Qing Li School of Materials science and Engineering Harbin Institute of TechnologyHarbin150001China applied Materials Physics Department of Materials Science and EngineeringKTH-Royal Institute of Technology10044StockholmSweden

This paper presents a systematic investigation of the microstructure and magnetocaloric properties of melt-extracted Sm_(20)Gd_(20)Dy_(20)Co_(20)Al_(20)high-entropy *** fabricated wires exhibited an amorphous structure,and the temperature interval of the undercooled liquid AT was 45 *** microwires underwent a second-order magnetic transition from a ferromagnetic to a paramagnetic state near the Curie temperature(T_(C)=52 K),The maximum magnetic entropy change(-ΔS_M^(max)),the relative cooling power and the refrigeration capacity reached 6.34 J·kg^(-1)·K^(-1).422.09 J·kg^(-1)and 332.94 J·kg^(-1),respectively,under a magnetic field change of 5 *** addition,the temperature-averaged entropy changes with two temperature lifts(3 and 10 K)were 6.32 and 6.27 J·kg^(-1)·K^(-1),*** good magnetocalorie performance highlights the significant potential for the Sm_(20)Gd_(20)Dy_(20)Co_(20)Al_(20)microwires to be used as magnetic refrigerant materials in low-temperature region *** work will serve as a valuable reference for future investigations on low-temperature high-entropy magnetocaloric materials.

关键词： Melt-extraction High-entropy amorphous microwires Magnetocaloric effect Magnetic refrigeration

Multi-Dimensional QoS Evaluation and Optimization of Mobile Edge Computing for IoT:A Survey

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Chinese Journal of Electronics 2024年第4期33卷 859-874页

作者： Jiwei HUANG Fangzheng LIU Jianbing ZHANG Beijing Key Laboratory of Petroleum data Mining China University of Petroleum Department of Computer science and Technology China University of Petroleum

With the evolvement of the Internet of things(IoT), mobile edge computing(MEC) has emerged as a promising computing paradigm to support IoT data analysis and processing. In MEC for IoT, the differentiated requirements on quality of service(QoS) have been growing rapidly, making QoS a multi-dimensional concept including several attributes, such as performance, dependability, energy efficiency, and economic factors. To guarantee the QoS of IoT applications, theories and techniques of multi-dimensional QoS evaluation and optimization have become important theoretical foundations and supporting technologies for the research and application of MEC for IoT,which have attracted significant attention from both academia and industry. This paper aims to survey the existing studies on multi-dimensional QoS evaluation and optimization of MEC for IoT, and provide insights and guidance for future research in this field. This paper summarizes the multi-dimensional and multi-attribute QoS metrics in Io T scenarios, and then several QoS evaluation methods are presented. For QoS optimization, the main research problems in this field are summarized, and optimization models as well as their corresponding solutions are elaborated. We take notice of the booming of edge intelligence in artificial intelligence-empowered Io T scenarios, and illustrate the new research topics and the state-of-the-art approaches related to QoS evaluation and optimization. We discuss the challenges and future research directions.

关键词： Internet of things Mobile edge computing Quality of service Quality of service evaluation Quality of service optimization PERFORMANCE EVALUATION RESOURCE-ALLOCATION SERVICE MIGRATION DELAY CLOUD DEPENDABILITY MECHANISM INTERNET SYSTEM THINGS

Classification and Comprehension of Software Requirements Using Ensemble Learning

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Computers, Materials & Continua 2024年第8期80卷 2839-2855页

作者： Jalil Abbas Arshad Ahmad Syed Muqsit Shaheed Rubia Fatima Sajid Shah Mohammad Elaffendi Gauhar Ali School of Computer science and Technology Anhui UniversityHefei230039China School of Computing sciences Pak Austria FachhochschuleInstitute of Applied Sciences and TechnologyHaripur22620Pakistan Department of Computer science and IT University of LahoreLahore55150Pakistan Department of Computer science Emerson UniversityPunjabMultan60000Pakistan EIAS(Emerging Intelligent Autonomous Systems)data science Lab Prince Sultan UniversityRiyad12435Saudi Arabia

The software development process mostly depends on accurately identifying both essential and optional ***,user needs are typically expressed in free-form language,requiring significant time and human resources to translate these into clear functional and non-functional *** address this challenge,various machine learning(ML)methods have been explored to automate the understanding of these requirements,aiming to reduce time and human ***,existing techniques often struggle with complex instructions and large-scale *** our study,we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier(FNRC).By combining the traditional random forest algorithm with the Accuracy Sliding Window(ASW)technique,we develop optimal sub-ensembles that surpass the initial classifier’s accuracy while using fewer *** results demonstrate that our FNRC methodology performs robustly across different datasets,achieving a balanced Precision of 75%on the PROMISE dataset and an impressive Recall of 85%on the CCHIT *** datasets consistently maintain an F-measure around 64%,highlighting FNRC’s ability to effectively balance precision and recall in diverse *** findings contribute to more accurate and efficient software development processes,increasing the probability of achieving successful project outcomes.

关键词： Ensemble learning machine learning non-functional requirements requirement engineering accuracy sliding window

Complementary-Label Adversarial Domain Adaptation Fault Diagnosis Network under Time-Varying Rotational Speed and Weakly-Supervised Conditions

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Computers, Materials & Continua 2024年第4期79卷 761-777页

作者： Siyuan Liu Jinying Huang Jiancheng Ma Licheng Jing Yuxuan Wang School of data science and Technology North University of ChinaTaiyuan030051China School of Mechanical Engineering North University of ChinaTaiyuan030051China

Recent research in cross-domain intelligence fault diagnosis of machinery still has some problems,such as relatively ideal speed conditions and sample *** engineering practice,the rotational speed of the machine is often transient and time-varying,which makes the sample annotation increasingly ***,the number of samples collected from different health states is often *** deal with the above challenges,a complementary-label(CL)adversarial domain adaptation fault diagnosis network(CLADAN)is proposed under time-varying rotational speed and weakly-supervised *** the weakly supervised learning condition,machine prior information is used for sample annotation via cost-friendly complementary label learning.A diagnosticmodel learning strategywith discretized category probabilities is designed to avoidmulti-peak distribution of prediction *** adversarial training process,we developed virtual adversarial regularization(VAR)strategy,which further enhances the robustness of the model by adding adversarial perturbations in the target *** experiments on two case studies validated the superior performance of the proposed method.

关键词： Time-varying rotational speed weakly-supervised fault diagnosis domain adaptation

A review of understanding electrocatalytic reactions in energy conversion and energy storage systems via scanning electrochemical microscopy

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Journal of Energy Chemistry 2024年第4期91卷 155-177页

作者： Jihye Park Jong Hwan Lim Jin-Hyuk Kang Jiheon Lim Ho Won Jang Hosun Shin Sun Hwa Park Interdisciplinary Materials Measurement Institute Korea Research Institute of Standards and ScienceDaejeon 34113Republic of Korea Department of Material science and Engineering Seoul National UniversitySeoul 08826Republic of Korea Department of applied Measurement science University of Science and TechnologyDaejeon 34113Republic of Korea

To address climate change and promote environmental sustainability,electrochemical energy conversion and storage systems emerge as promising alternative to fossil fuels,catering to the escalating demand for *** optimal energy efficiency and cost competitiveness in these systems requires the strategic design of electrocatalysts,coupled with a thorough comprehension of the underlying mechanisms and degradation behavior occurring during the electrocatalysis *** electrochemical microscopy(SECM),an analytical technique for studying surface electrochemically,stands out as a powerful tool offering electrochemical *** possesses remarkable spatiotemporal resolution,enabling the visualization of the localized electrochemical activity and surface *** review compiles crucial research findings and recent breakthroughs in electrocatalytic processes utilizing the SECM methodology,specifically focusing on applications in electrolysis,fuel cells,and metal–oxygen batteries within the realm of energy conversion and storage *** with an overview of each energy system,the review introduces the fundamental principles of SECM,and aiming to provide new perspectives and broadening the scope of applied research by describing the major research categories within SECM.

关键词： Scanning electrochemical microscopy Electrocatalyst Electrocatalysis Water splitting Fuel cell Metal-oxygen battery

Phase Behaviour and Physical Properties of Alkane Solvent（s）/CO2/N2/DME/Water/Heavy Oil Systems under Reservoir Conditions

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油气地质与采收率 2024年第2期 175-208页

作者： YANG Daoyong LI Yunlong HUANG Desheng Energy Systems Engineering Faculty of Engineering and Applied Science University of Regina

The hybrid steam-solvent injection has been considered as a promising technique for enhancing heavy oil/bitumen recov‐ery,while its main mechanisms including the heat transferred and dissolution of solvents (e.g.,CH4,C2H6,C3H8,C4H10,CO2,N2,and DME) into heavy oil/bitumen to reduce its viscosity and swell it are closely related to the phase behaviour of the solvents/water/heavy oil *** allow the seamless integration with the existing reservoir simulators,the traditional cubic equations of state （i.e.,SRK EOS and PR EOS） have been modified and improved to accurately quantify the phase behaviour and physical prop‐erties of the aforementioned systems under equilibrium and nonequilibrium ***,a huge database has been built to de‐velop the corresponding alpha functions by minimizing the deviation between the measured and calculated vapour pressures for wa‐ter as well as non-hydrocarbon and hydrocarbon compounds available from the public *** obtained alpha functions are fur‐ther validated with enthalpy of vaporization for pure substances,and then the reduced temperature has been optimized and the ec‐centric factor has been ***,a pressure-implicit strategy has been developed to optimize the binary interaction param‐eters （BIPs） by treating heavy oil as one pseudocomponent （PC） or multiple ***,the contributions of each solvent to the aforementioned systems have been compared and analyzed within a consistent and unified *** addition to new alpha func‐tions for hydrocarbons and water,respectively,the reduced temperature is found to have its optimum value of 0.59 for the two equa‐tions of state （EOSs）,while 0.60 is recommended for practical *** improved EOSs have been further employed to reproduce the experimentally measured multiphase boundaries （or pseudo-bubble-point pressures）,density,viscosity,（mutual） solubility,and preferential mass transfer for the aforementioned mixtures under equilibrium and nonequilibrium

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Robust zero-watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 40-53页

作者： Yiyi Yuan Jingbing Li Jing Liu Uzair Aslam Bhatti Zilong Liu Yen-wei Chen School of Information and Communication Engineering Hainan UniversityHaikouChina Research Center for Healthcare data science Zhejiang LabHangzhouChina Graduate School of Information science and Engineering Ritsumeikan University ShigaJapan

In the intricate network environment,the secure transmission of medical images faces challenges such as information leakage and malicious tampering,significantly impacting the accuracy of disease diagnoses by medical *** address this problem,the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi-stage discrete wavelet transform(DWT),Daisy descriptor,and discrete cosine transform(DCT).The algorithm initially encrypts the original medical image through DWT-DCT and Logistic ***,a 3-stage DWT transformation is applied to the encrypted medical image,with the centre point of the LL3 sub-band within its low-frequency component serving as the sampling *** Daisy descriptor matrix for this point is then ***,a DCT transformation is performed on the Daisy descriptor matrix,and the low-frequency portion is processed using the perceptual hashing algorithm to generate a 32-bit binary feature vector for the medical *** scheme utilises cryptographic knowledge and zero-watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image,which meets the basic re-quirements of medical image *** embedding and extraction of water-marks are accomplished in a mere 0.160 and 0.411s,respectively,with minimal computational *** results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks,with a notable performance in resisting rotation attacks.

关键词： daisy descriptor DCT DWT encryption domain medical image zero-watermarking