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Research on Multi-Core Processor Analysis for WCET Estimation
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作者 LUO Haoran HU Shuisong +2 位作者 WANG Wenyong TANG Yuke ZHOU Junwei 《ZTE Communications》 2024年第1期87-94,共8页
Real-time system timing analysis is crucial for estimating the worst-case execution time(WCET)of a program.To achieve this,static or dynamic analysis methods are used,along with targeted modeling of the actual hardwar... Real-time system timing analysis is crucial for estimating the worst-case execution time(WCET)of a program.To achieve this,static or dynamic analysis methods are used,along with targeted modeling of the actual hardware system.This literature review focuses on calculating WCET for multi-core processors,providing a survey of traditional methods used for static and dynamic analysis and highlighting the major challenges that arise from different program execution scenarios on multi-core platforms.This paper outlines the strengths and weaknesses of current methodologies and offers insights into prospective areas of research on multi-core analysis.By presenting a comprehensive analysis of the current state of research on multi-core processor analysis for WCET estimation,this review aims to serve as a valuable resource for researchers and practitioners in the field. 展开更多
关键词 real-time system worst-case execution time(WCET) multi-core analysis
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基于Blending-Clustering集成学习的大坝变形预测模型
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作者 冯子强 李登华 丁勇 《水利水电技术(中英文)》 北大核心 2024年第4期59-70,共12页
【目的】变形是反映大坝结构性态最直观的效应量,构建科学合理的变形预测模型是保障大坝安全健康运行的重要手段。针对传统大坝变形预测模型预测精度低、误报率高等问题导致的错误报警现象,【方法】选取不同预测模型和聚类算法集成,构... 【目的】变形是反映大坝结构性态最直观的效应量,构建科学合理的变形预测模型是保障大坝安全健康运行的重要手段。针对传统大坝变形预测模型预测精度低、误报率高等问题导致的错误报警现象,【方法】选取不同预测模型和聚类算法集成,构建了一种Blending-Clustering集成学习的大坝变形预测模型,该模型以Blending对单一预测模型集成提升预测精度为核心,并通过Clustering聚类优选预测值改善模型稳定性。以新疆某面板堆石坝变形监测数据为实例分析,通过多模型预测性能比较,对所提出模型的预测精度和稳定性进行全面评估。【结果】结果显示:Blending-Clustering模型将预测模型和聚类算法集成,均方根误差(RMSE)和归一化平均百分比误差(nMAPE)明显降低,模型的预测精度得到显著提高;回归相关系数(R~2)得到提升,模型具备更强的拟合能力;在面板堆石坝上22个测点变形数据集上的预测评价指标波动范围更小,模型的泛化性和稳定性得到有效增强。【结论】结果表明:Blending-Clustering集成预测模型对于预测精度、泛化性和稳定性均有明显提升,在实际工程具有一定的应用价值。 展开更多
关键词 大坝 变形 预测模型 Blending集成 clustering集成 模型融合
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Hybridization of Metaheuristics Based Energy Efficient Scheduling Algorithm for Multi-Core Systems
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作者 J.Jean Justus U.Sakthi +4 位作者 K.Priyadarshini B.Thiyaneswaran Masoud Alajmi Marwa Obayya Manar Ahmed Hamza 《Computer Systems Science & Engineering》 SCIE EI 2023年第1期205-219,共15页
The developments of multi-core systems(MCS)have considerably improved the existing technologies in thefield of computer architecture.The MCS comprises several processors that are heterogeneous for resource capacities,... The developments of multi-core systems(MCS)have considerably improved the existing technologies in thefield of computer architecture.The MCS comprises several processors that are heterogeneous for resource capacities,working environments,topologies,and so on.The existing multi-core technology unlocks additional research opportunities for energy minimization by the use of effective task scheduling.At the same time,the task scheduling process is yet to be explored in the multi-core systems.This paper presents a new hybrid genetic algorithm(GA)with a krill herd(KH)based energy-efficient scheduling techni-que for multi-core systems(GAKH-SMCS).The goal of the GAKH-SMCS tech-nique is to derive scheduling tasks in such a way to achieve faster completion time and minimum energy dissipation.The GAKH-SMCS model involves a multi-objectivefitness function using four parameters such as makespan,processor utilization,speedup,and energy consumption to schedule tasks proficiently.The performance of the GAKH-SMCS model has been validated against two datasets namely random dataset and benchmark dataset.The experimental outcome ensured the effectiveness of the GAKH-SMCS model interms of makespan,pro-cessor utilization,speedup,and energy consumption.The overall simulation results depicted that the presented GAKH-SMCS model achieves energy effi-ciency by optimal task scheduling process in MCS. 展开更多
关键词 Task scheduling energy efficiency multi-core systems fitness function MAKESPAN
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Shared Cache Based on Content Addressable Memory in a Multi-Core Architecture
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作者 Allam Abumwais Mahmoud Obaid 《Computers, Materials & Continua》 SCIE EI 2023年第3期4951-4963,共13页
Modern shared-memory multi-core processors typically have shared Level 2(L2)or Level 3(L3)caches.Cache bottlenecks and replacement strategies are the main problems of such architectures,where multiple cores try to acc... Modern shared-memory multi-core processors typically have shared Level 2(L2)or Level 3(L3)caches.Cache bottlenecks and replacement strategies are the main problems of such architectures,where multiple cores try to access the shared cache simultaneously.The main problem in improving memory performance is the shared cache architecture and cache replacement.This paper documents the implementation of a Dual-Port Content Addressable Memory(DPCAM)and a modified Near-Far Access Replacement Algorithm(NFRA),which was previously proposed as a shared L2 cache layer in a multi-core processor.Standard Performance Evaluation Corporation(SPEC)Central Processing Unit(CPU)2006 benchmark workloads are used to evaluate the benefit of the shared L2 cache layer.Results show improved performance of the multicore processor’s DPCAM and NFRA algorithms,corresponding to a higher number of concurrent accesses to shared memory.The new architecture significantly increases system throughput and records performance improvements of up to 8.7%on various types of SPEC 2006 benchmarks.The miss rate is also improved by about 13%,with some exceptions in the sphinx3 and bzip2 benchmarks.These results could open a new window for solving the long-standing problems with shared cache in multi-core processors. 展开更多
关键词 multi-core processor shared cache content addressable memory dual port CAM replacement algorithm benchmark program
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Fixed-Time Cluster Optimization for Multi-Agent Systems Based on Piecewise Power-Law Design
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作者 Suna Duan Xinchun Jia Xiaobo Chi 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第5期1301-1303,共3页
Dear Editor,This letter focuses on the fixed-time(FXT)cluster optimization problem of first-order multi-agent systems(FOMASs)in an undirected network,in which the optimization objective is the sum of the objective fun... Dear Editor,This letter focuses on the fixed-time(FXT)cluster optimization problem of first-order multi-agent systems(FOMASs)in an undirected network,in which the optimization objective is the sum of the objective functions of all clusters.A novel piecewise power-law control protocol with cooperative-competition relations is proposed.Furthermore,a sufficient condition is obtained to ensure that the FOMASs achieve the cluster consensus within an FXT. 展开更多
关键词 AGENT cluster OPTIMIZATION
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Cluster DetectionMethod of Endogenous Security Abnormal Attack Behavior in Air Traffic Control Network
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作者 Ruchun Jia Jianwei Zhang +2 位作者 Yi Lin Yunxiang Han Feike Yang 《Computers, Materials & Continua》 SCIE EI 2024年第5期2523-2546,共24页
In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set f... In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set for ATC cybersecurity attacks is constructed by setting the feature states,adding recursive features,and determining the feature criticality.The expected information gain and entropy of the feature data are computed to determine the information gain of the feature data and reduce the interference of similar feature data.An autoencoder is introduced into the AI(artificial intelligence)algorithm to encode and decode the characteristics of ATC network security attack behavior to reduce the dimensionality of the ATC network security attack behavior data.Based on the above processing,an unsupervised learning algorithm for clustering detection of ATC network security attacks is designed.First,determine the distance between the clustering clusters of ATC network security attack behavior characteristics,calculate the clustering threshold,and construct the initial clustering center.Then,the new average value of all feature objects in each cluster is recalculated as the new cluster center.Second,it traverses all objects in a cluster of ATC network security attack behavior feature data.Finally,the cluster detection of ATC network security attack behavior is completed by the computation of objective functions.The experiment took three groups of experimental attack behavior data sets as the test object,and took the detection rate,false detection rate and recall rate as the test indicators,and selected three similar methods for comparative test.The experimental results show that the detection rate of this method is about 98%,the false positive rate is below 1%,and the recall rate is above 97%.Research shows that this method can improve the detection performance of security attacks in air traffic control network. 展开更多
关键词 Air traffic control network security attack behavior cluster detection behavioral characteristics information gain cluster threshold automatic encoder
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Improved Data Stream Clustering Method: Incorporating KD-Tree for Typicality and Eccentricity-Based Approach
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作者 Dayu Xu Jiaming Lu +1 位作者 Xuyao Zhang Hongtao Zhang 《Computers, Materials & Continua》 SCIE EI 2024年第2期2557-2573,共17页
Data stream clustering is integral to contemporary big data applications.However,addressing the ongoing influx of data streams efficiently and accurately remains a primary challenge in current research.This paper aims... Data stream clustering is integral to contemporary big data applications.However,addressing the ongoing influx of data streams efficiently and accurately remains a primary challenge in current research.This paper aims to elevate the efficiency and precision of data stream clustering,leveraging the TEDA(Typicality and Eccentricity Data Analysis)algorithm as a foundation,we introduce improvements by integrating a nearest neighbor search algorithm to enhance both the efficiency and accuracy of the algorithm.The original TEDA algorithm,grounded in the concept of“Typicality and Eccentricity Data Analytics”,represents an evolving and recursive method that requires no prior knowledge.While the algorithm autonomously creates and merges clusters as new data arrives,its efficiency is significantly hindered by the need to traverse all existing clusters upon the arrival of further data.This work presents the NS-TEDA(Neighbor Search Based Typicality and Eccentricity Data Analysis)algorithm by incorporating a KD-Tree(K-Dimensional Tree)algorithm integrated with the Scapegoat Tree.Upon arrival,this ensures that new data points interact solely with clusters in very close proximity.This significantly enhances algorithm efficiency while preventing a single data point from joining too many clusters and mitigating the merging of clusters with high overlap to some extent.We apply the NS-TEDA algorithm to several well-known datasets,comparing its performance with other data stream clustering algorithms and the original TEDA algorithm.The results demonstrate that the proposed algorithm achieves higher accuracy,and its runtime exhibits almost linear dependence on the volume of data,making it more suitable for large-scale data stream analysis research. 展开更多
关键词 Data stream clustering TEDA KD-TREE scapegoat tree
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Formation and transformation of metastable LPSO building blocks clusters in Mg-Gd-Y-Zn-Zr alloys by spinodal decomposition and heterogeneous nucleation
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作者 Xin Zhao Zhong Yang +2 位作者 Jiachen Zhang Minxian Liang Liying Wang 《Journal of Magnesium and Alloys》 SCIE EI CAS CSCD 2024年第2期673-686,共14页
To study the formation and transformation mechanism of long-period stacked ordered(LPSO)structures,a systematic atomic scale analysis was conducted for the structural evolution of long-period stacked ordered(LPSO)stru... To study the formation and transformation mechanism of long-period stacked ordered(LPSO)structures,a systematic atomic scale analysis was conducted for the structural evolution of long-period stacked ordered(LPSO)structures in the Mg-Gd-Y-Zn-Zr alloy annealed at 300℃~500℃.Various types of metastable LPSO building block clusters were found to exist in alloy structures at different temperatures,which precipitate during the solidification and homogenization process.The stability of Zn/Y clusters is explained by the first principles of density functional theory.The LPSO structure is distinguished by the arrangement of its different Zn/Y enriched LPSO structural units,which comprises local fcc stacking sequences upon a tightly packed plane.The presence of solute atoms causes local lattice distortion,thereby enabling the rearrangement of Mg atoms in the different configurations in the local lattice,and local HCP-FCC transitions occur between Mg and Zn atoms occupying the nearest neighbor positions.This finding indicates that LPSO structures can generate necessary Schockley partial dislocations on specific slip surfaces,providing direct evidence of the transition from 18R to 14H.Growth of the LPSO,devoid of any defects and non-coherent interfaces,was observed separately from other precipitated phases.As a result,the precipitation sequence of LPSO in the solidification stage was as follows:Zn/Ycluster+Mg layers→various metastable LPSO building block clusters→18R/24R LPSO;whereas the precipitation sequence of LPSO during homogenization treatment was observed to be as follows:18R LPSO→various metastable LPSO building block clusters→14H LPSO.Of these,14H LPSO was found to be the most thermodynamically stable structure. 展开更多
关键词 LPSO Spinodal decomposition Homogenization treatment clusterS Phase transformation
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Deep Learning and Tensor-Based Multiple Clustering Approaches for Cyber-Physical-Social Applications
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作者 Hongjun Zhang Hao Zhang +3 位作者 Yu Lei Hao Ye Peng Li Desheng Shi 《Computers, Materials & Continua》 SCIE EI 2024年第3期4109-4128,共20页
The study delves into the expanding role of network platforms in our daily lives, encompassing various mediums like blogs, forums, online chats, and prominent social media platforms such as Facebook, Twitter, and Inst... The study delves into the expanding role of network platforms in our daily lives, encompassing various mediums like blogs, forums, online chats, and prominent social media platforms such as Facebook, Twitter, and Instagram. While these platforms offer avenues for self-expression and community support, they concurrently harbor negative impacts, fostering antisocial behaviors like phishing, impersonation, hate speech, cyberbullying, cyberstalking, cyberterrorism, fake news propagation, spamming, and fraud. Notably, individuals also leverage these platforms to connect with authorities and seek aid during disasters. The overarching objective of this research is to address the dual nature of network platforms by proposing innovative methodologies aimed at enhancing their positive aspects and mitigating their negative repercussions. To achieve this, the study introduces a weight learning method grounded in multi-linear attribute ranking. This approach serves to evaluate the significance of attribute combinations across all feature spaces. Additionally, a novel clustering method based on tensors is proposed to elevate the quality of clustering while effectively distinguishing selected features. The methodology incorporates a weighted average similarity matrix and optionally integrates weighted Euclidean distance, contributing to a more nuanced understanding of attribute importance. The analysis of the proposed methods yields significant findings. The weight learning method proves instrumental in discerning the importance of attribute combinations, shedding light on key aspects within feature spaces. Simultaneously, the clustering method based on tensors exhibits improved efficacy in enhancing clustering quality and feature distinction. This not only advances our understanding of attribute importance but also paves the way for more nuanced data analysis methodologies. In conclusion, this research underscores the pivotal role of network platforms in contemporary society, emphasizing their potential for both positive contributions and adverse consequences. The proposed methodologies offer novel approaches to address these dualities, providing a foundation for future research and practical applications. Ultimately, this study contributes to the ongoing discourse on optimizing the utility of network platforms while minimizing their negative impacts. 展开更多
关键词 Network platform tensor-based clustering weight learning multi-linear euclidean
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Examining the Use of Scott’s Formula and Link Expiration Time Metric for Vehicular Clustering
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作者 Fady Samann Shavan Askar 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第3期2421-2444,共24页
Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms.K-clustering algorithms are sim... Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms.K-clustering algorithms are simplistic,with fast performance and relative accuracy.However,their implementation depends on the initial selection of clusters number(K),the initial clusters’centers,and the clustering metric.This paper investigated using Scott’s histogram formula to estimate the K number and the Link Expiration Time(LET)as a clustering metric.Realistic traffic flows were considered for three maps,namely Highway,Traffic Light junction,and Roundabout junction,to study the effect of road layout on estimating the K number.A fast version of the PAM algorithm was used for clustering with a modification to reduce time complexity.The Affinity propagation algorithm sets the baseline for the estimated K number,and the Medoid Silhouette method is used to quantify the clustering.OMNET++,Veins,and SUMO were used to simulate the traffic,while the related algorithms were implemented in Python.The Scott’s formula estimation of the K number only matched the baseline when the road layout was simple.Moreover,the clustering algorithm required one iteration on average to converge when used with LET. 展开更多
关键词 clusterING vehicular network Scott’s formula FastPAM
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Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks
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作者 Youseef Alotaibi B.Rajasekar +1 位作者 R.Jayalakshmi Surendran Rajendran 《Computers, Materials & Continua》 SCIE EI 2024年第3期4243-4262,共20页
Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effect... Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data.The communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time.Therefore,the scheme of an effectual routing protocol for reliable and stable communications is significant.Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment.Therefore,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in VANETS.The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET.To accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust level.For the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method.The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods. 展开更多
关键词 Vehicular networks communication protocol clusterING falcon optimization algorithm ROUTING
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Sparse Reconstructive Evidential Clustering for Multi-View Data
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作者 Chaoyu Gong Yang You 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第2期459-473,共15页
Although many multi-view clustering(MVC) algorithms with acceptable performances have been presented, to the best of our knowledge, nearly all of them need to be fed with the correct number of clusters. In addition, t... Although many multi-view clustering(MVC) algorithms with acceptable performances have been presented, to the best of our knowledge, nearly all of them need to be fed with the correct number of clusters. In addition, these existing algorithms create only the hard and fuzzy partitions for multi-view objects,which are often located in highly-overlapping areas of multi-view feature space. The adoption of hard and fuzzy partition ignores the ambiguity and uncertainty in the assignment of objects, likely leading to performance degradation. To address these issues, we propose a novel sparse reconstructive multi-view evidential clustering algorithm(SRMVEC). Based on a sparse reconstructive procedure, SRMVEC learns a shared affinity matrix across views, and maps multi-view objects to a 2-dimensional humanreadable chart by calculating 2 newly defined mathematical metrics for each object. From this chart, users can detect the number of clusters and select several objects existing in the dataset as cluster centers. Then, SRMVEC derives a credal partition under the framework of evidence theory, improving the fault tolerance of clustering. Ablation studies show the benefits of adopting the sparse reconstructive procedure and evidence theory. Besides,SRMVEC delivers effectiveness on benchmark datasets by outperforming some state-of-the-art methods. 展开更多
关键词 Evidence theory multi-view clustering(MVC) OPTIMIZATION sparse reconstruction
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Unsaturated bi-heterometal clusters in metal-vacancy sites of 2D MoS2 for efficient hydrogen evolution
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作者 Gonglei Shao Jie Xu +4 位作者 Shasha Gao Zhang Zhang Song Liu Xu Zhang Zhen Zhou 《Carbon Energy》 SCIE EI CAS CSCD 2024年第3期264-275,共12页
The valence states and coordination structures of doped heterometal atoms in two-dimensional(2D)nanomaterials lack predictable regulation strategies.Hence,a robust method is proposed to form unsaturated heteroatom clu... The valence states and coordination structures of doped heterometal atoms in two-dimensional(2D)nanomaterials lack predictable regulation strategies.Hence,a robust method is proposed to form unsaturated heteroatom clusters via the metal-vacancy restraint mechanism,which can precisely regulate the bonding and valence state of heterometal atoms doped in 2D molybdenum disulfide.The unsaturated valence state of heterometal Pt and Ru cluster atoms form a spatial coordination structure with Pt–S and Ru–O–S as catalytically active sites.Among them,the strong binding energy of negatively charged suspended S and O sites for H+,as well as the weak adsorption of positively charged unsaturated heterometal atoms for H*,reduces the energy barrier of the hydrogen evolution reaction proved by theoretical calculation.Whereupon,the electrocatalytic hydrogen evolution performance is markedly improved by the ensemble effect of unsaturated heterometal atoms and highlighted with an overpotential of 84 mV and Tafel slope of 68.5 mV dec^(−1).In brief,this metal vacancy-induced valence state regulation of heterometal can manipulate the coordination structure and catalytic activity of heterometal atoms doped in the 2D atomic lattice but not limited to 2D nanomaterials. 展开更多
关键词 clusterS hydrogen evolution reaction metal vacancy MOS2 unsaturated heterometal
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Research and Practice on the Construction of Professional Cluster in Application-Oriented Local Undergraduate Universities:Taking Environ-mental Chemical Engineering Professional Cluster in Pingdingshan University as an Example
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作者 Yanjiao LI Jiafei SU +5 位作者 Xiaonan HU Hongsheng QIAN Weishuang TONG Shiping CHENG Lihua XIE Zhilu ZHANG 《Asian Agricultural Research》 2024年第2期36-39,42,共5页
Based on the analysis of the importance of professional cluster construction by ecological theory,with the change of social demand for talents,this paper explores the practice of environmental chemical professional cl... Based on the analysis of the importance of professional cluster construction by ecological theory,with the change of social demand for talents,this paper explores the practice of environmental chemical professional cluster construction in Pingdingshan University,including gradually perfecting teaching conditions and reforming teaching mode,breaking through the limitations of resources,integrating the boundaries of colleges and departments,integrating multiple resources,innovating systems and mechanisms,reconstructing professional clusters,decon-structing professional connotations,reorganizing curriculum systems,etc.,in order to better build the ecological chain network of education in application-oriented colleges and universities,realize the deep integration of industry and education,train future-oriented interdisciplinary applied talents of new engineering,and realize the construction of characteristic professional cluster in application-oriented colleges. 展开更多
关键词 Professional cluster Industrial cluster Talent demand Resource integration Structural adjustment Undergraduate universities
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A Dual-Cluster-Head Based Medium Access Control for Large-Scale UAV Ad-Hoc Networks
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作者 Zhao Xinru Wei Zhiqing +3 位作者 Zou Yingying Ma Hao Cui Yanpeng Feng Zhiyong 《China Communications》 SCIE CSCD 2024年第5期123-136,共14页
Unmanned Aerial Vehicle(UAV)ad hoc network has achieved significant growth for its flexibility,extensibility,and high deployability in recent years.The application of clustering scheme for UAV ad hoc network is impera... Unmanned Aerial Vehicle(UAV)ad hoc network has achieved significant growth for its flexibility,extensibility,and high deployability in recent years.The application of clustering scheme for UAV ad hoc network is imperative to enhance the performance of throughput and energy efficiency.In conventional clustering scheme,a single cluster head(CH)is always assigned in each cluster.However,this method has some weaknesses such as overload and premature death of CH when the number of UAVs increased.In order to solve this problem,we propose a dual-cluster-head based medium access control(DCHMAC)scheme for large-scale UAV networks.In DCHMAC,two CHs are elected to manage resource allocation and data forwarding cooperatively.Specifically,two CHs work on different channels.One of CH is used for intra-cluster communication and the other one is for inter-cluster communication.A Markov chain model is developed to analyse the throughput of the network.Simulation result shows that compared with FM-MAC(flying ad hoc networks multi-channel MAC,FM-MAC),DCHMAC improves the throughput by approximately 20%~50%and prolongs the network lifetime by approximately 40%. 展开更多
关键词 dual cluster head medium access control UAV swarm
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Performance Prediction Based Workload Scheduling in Co-Located Cluster
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作者 Dongyang Ou Yongjian Ren Congfeng Jiang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第5期2043-2067,共25页
Cloud service providers generally co-locate online services and batch jobs onto the same computer cluster,where the resources can be pooled in order to maximize data center resource utilization.Due to resource competi... Cloud service providers generally co-locate online services and batch jobs onto the same computer cluster,where the resources can be pooled in order to maximize data center resource utilization.Due to resource competition between batch jobs and online services,co-location frequently impairs the performance of online services.This study presents a quality of service(QoS)prediction-based schedulingmodel(QPSM)for co-locatedworkloads.The performance prediction of QPSM consists of two parts:the prediction of an online service’s QoS anomaly based on XGBoost and the prediction of the completion time of an offline batch job based on randomforest.On-line service QoS anomaly prediction is used to evaluate the influence of batch jobmix on on-line service performance,and batch job completion time prediction is utilized to reduce the total waiting time of batch jobs.When the same number of batch jobs are scheduled in experiments using typical test sets such as CloudSuite,the scheduling time required by QPSM is reduced by about 6 h on average compared with the first-come,first-served strategy and by about 11 h compared with the random scheduling strategy.Compared with the non-co-located situation,QPSM can improve CPU resource utilization by 12.15% and memory resource utilization by 5.7% on average.Experiments show that the QPSM scheduling strategy proposed in this study can effectively guarantee the quality of online services and further improve cluster resource utilization. 展开更多
关键词 Co-located cluster workload scheduling online service batch jobs data center
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Coupling Au with BO_(x) matrix induced by Closo-boron cluster for electrochemical synthesis of ammonia
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作者 Wenjing Liu Nan Yang +10 位作者 Yuao Wei Yingjie Yu Jie Chen Mo Wei Yuting Huang Xiaohan Li Linghai Zhang Faisal Saleem Weina Zhang Haibo Zhang Fengwei Huo 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2024年第6期471-477,I0012,共8页
Au is considered as one of the most promising catalysts for nitrogen reduction reaction(NRR),however maximizing the activity utilization rate of Au and understanding the synergistic effects between Au and carriers pos... Au is considered as one of the most promising catalysts for nitrogen reduction reaction(NRR),however maximizing the activity utilization rate of Au and understanding the synergistic effects between Au and carriers pose ongoing challenges.Herein,we systematically explore the synergistic catalytic effect of incorporating Au with boron clusters for accelerating NRR kinetics.An in-situ abinitio strategy is employed to construct B-doped Au nanoparticles(2-6 nm in diameter)loaded on BO_(x) substrates(AuBO_(x)),in which B not only modulates the surface electronic structure of Au but also forms strong coupling interactions to stabilize the nanoparticles.The electrochemical results show that Au-BO_(x) possesses excellent NRR activity(NH_(3) yield of 48.52μg h^(-1)mg_(cat)^(-1),Faraday efficiency of 56.18%),and exhibits high stability and reproducibility throughout the electrocatalytic NRR process.Theoretical calculations reveal that the introduction of B induces the formation of both Au dangling bond and Au-B coupling bond.which considerably facilitates the hydrogenation of~*N_(2)^(-)~*NH_(3).The present work provides a new avenue for the preparation of metal-boron materials achieved by one-step reduction and doping process,utilizing boron clusters as reducing and stabilizing agents. 展开更多
关键词 Boron clusters Nitrogen reduction reaction Au–B coupling
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ARHCS (Automatic Rainfall Half-Life Cluster System): A Landslides Early Warning System (LEWS) Using Cluster Analysis and Automatic Threshold Definition
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作者 Cassiano Antonio Bortolozo Luana Albertani Pampuch +8 位作者 Marcio Roberto Magalhães De Andrade Daniel Metodiev Adenilson Roberto Carvalho Tatiana Sussel Gonçalves Mendes Tristan Pryer Harideva Marturano Egas Rodolfo Moreda Mendes Isadora Araújo Sousa Jenny Power 《International Journal of Geosciences》 CAS 2024年第1期54-69,共16页
A significant portion of Landslide Early Warning Systems (LEWS) relies on the definition of operational thresholds and the monitoring of cumulative rainfall for alert issuance. These thresholds can be obtained in vari... A significant portion of Landslide Early Warning Systems (LEWS) relies on the definition of operational thresholds and the monitoring of cumulative rainfall for alert issuance. These thresholds can be obtained in various ways, but most often they are based on previous landslide data. This approach introduces several limitations. For instance, there is a requirement for the location to have been previously monitored in some way to have this type of information recorded. Another significant limitation is the need for information regarding the location and timing of incidents. Despite the current ease of obtaining location information (GPS, drone images, etc.), the timing of the event remains challenging to ascertain for a considerable portion of landslide data. Concerning rainfall monitoring, there are multiple ways to consider it, for instance, examining accumulations over various intervals (1 h, 6 h, 24 h, 72 h), as well as in the calculation of effective rainfall, which represents the precipitation that actually infiltrates the soil. However, in the vast majority of cases, both the thresholds and the rain monitoring approach are defined manually and subjectively, relying on the operators’ experience. This makes the process labor-intensive and time-consuming, hindering the establishment of a truly standardized and rapidly scalable methodology on a large scale. In this work, we propose a Landslides Early Warning System (LEWS) based on the concept of rainfall half-life and the determination of thresholds using Cluster Analysis and data inversion. The system is designed to be applied in extensive monitoring networks, such as the one utilized by Cemaden, Brazil’s National Center for Monitoring and Early Warning of Natural Disasters. 展开更多
关键词 Landslides Early Warning System (LEWS) cluster Analysis LANDSLIDES Brazil
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Building Fe atom–cluster composite sites using a site occupation strategy to boost electrochemical oxygen reduction
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作者 Tingyi Zhou Yi Guan +9 位作者 Changjie He Lei Zhang Xueliang Sun Zhongxin Song Qianling Zhang Chuanxin He Xiantao Jiang Zhaoyan Luo Wei Xing Xiangzhong Ren 《Carbon Energy》 SCIE EI CAS CSCD 2024年第3期276-286,共11页
The high-temperature pyrolysis process for preparing M–N–C single-atom catalyst usually results in high heterogeneity in product structure concurrently contains multiscale metal phases from single atoms(SAs),atomic ... The high-temperature pyrolysis process for preparing M–N–C single-atom catalyst usually results in high heterogeneity in product structure concurrently contains multiscale metal phases from single atoms(SAs),atomic clusters to nanoparticles.Therefore,understanding the interactions among these components,especially the synergistic effects between single atomic sites and cluster sites,is crucial for improving the oxygen reduction reaction(ORR)activity of M–N–C catalysts.Accordingly,herein,we constructed a model catalyst composed of both atomically dispersed FeN4 SA sites and adjacent Fe clusters through a site occupation strategy.We found that the Fe clusters can optimize the adsorption strength of oxygen reduction intermediates on FeN4 SA sites by introducing electron-withdrawing–OH ligands and decreasing the d-band center of the Fe center.The as-developed catalyst exhibits encouraging ORR activity with halfwave potentials(E1/2)of 0.831 and 0.905 V in acidic and alkaline media,respectively.Moreover,the catalyst also represents excellent durability exceeding that of Fe–N–C SA catalyst.The practical application of Fe(Cd)–CNx catalyst is further validated by its superior activity and stability in a metalair battery device.Our work exhibits the great potential of synergistic effects between multiphase metal species for improvements of singleatom site catalysts. 展开更多
关键词 d-band center metal clusters oxygen reduction reaction single-atom catalyst site occupations strategy
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Heat-inducible SlWRKY3 confers thermotolerance by activating the SlGRXS1 gene cluster in tomato
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作者 Ying Wang Wenxian Gai +9 位作者 Liangdan Yuan Lele Shang Fangman Li Zhao Gong Pingfei Ge Yaru Wang Jinbao Tao Xingyu Zhang Haiqiang Dong Yuyang Zhang 《Horticultural Plant Journal》 SCIE CAS CSCD 2024年第2期515-531,共17页
High temperature stress is one of the major environmental factors that affect the growth and development of plants. Although WRKY transcription factors play a critical role in stress responses, there are few studies o... High temperature stress is one of the major environmental factors that affect the growth and development of plants. Although WRKY transcription factors play a critical role in stress responses, there are few studies on the regulation of heat stress by WRKY transcription factors,especially in tomato. Here, we identified a group I WRKY transcription factor, SlWRKY3, involved in thermotolerance in tomato. First, SlWRKY3 was induced and upregulated under heat stress. Accordingly, overexpression of SlWRKY3 led to an increase, whereas knock-out of SlWRKY3 resulted in decreased tolerance to heat stress. Overexpression of SlWRKY3 accumulated less reactive oxygen species(ROS), whereas knock-out of SlWRKY3 accumulated more ROS under heat stress. This indicated that SlWRKY3 positively regulates heat stress in tomato. In addition,SlWRKY3 activated the expression of a range of abiotic stress-responsive genes involved in ROS scavenging, such as a SlGRXS1 gene cluster.Further analysis showed that SlWRKY3 can bind to the promoters of the SlGRXS1 gene cluster and activate their expression. Collectively, these results imply that SlWRKY3 is a positive regulator of thermotolerance through direct binding to the promoters of the SlGRXS1 gene cluster and activating their expression and ROS scavenging. 展开更多
关键词 TOMATO WRKY transcription factor SlWRKY3 THERMOTOLERANCE SlGRXS1 Gene cluster Abiotic stress
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