Distributed Matching Theory-Based Task Re-Allocating for Heterogeneous Multi-UAV Edge Computing

Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge computing.However,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not been fully considered yet.Moreover,most existing works neglect the fact that a task can only be executed on the UAV equipped with its desired service function(SF).In this backdrop,this paper formulates the task scheduling problem as a multi-objective task scheduling problem,which aims at maximizing the task execution success ratio while minimizing the average weighted sum of all tasks’completion time and energy consumption.Optimizing three coupled goals in a realtime manner with the dynamic arrival of tasks hinders us from adopting existing methods,like machine learning-based solutions that require a long training time and tremendous pre-knowledge about the task arrival process,or heuristic-based ones that usually incur a long decision-making time.To tackle this problem in a distributed manner,we establish a matching theory framework,in which three conflicting goals are treated as the preferences of tasks,SFs and UAVs.Then,a Distributed Matching Theory-based Re-allocating(DiMaToRe)algorithm is put forward.We formally proved that a stable matching can be achieved by our proposal.Extensive simulation results show that Di Ma To Re algorithm outperforms benchmark algorithms under diverse parameter settings and has good robustness.

Two-Sided Stable Matching Decision-Making Method Considering Matching Intention under a Hesitant Fuzzy Environment

In this paper,a stable two-sided matching(TSM)method considering the matching intention of agents under a hesitant fuzzy environment is proposed.The method uses a hesitant fuzzy element(HFE)as its basis.First,the HFE preference matrix is transformed into the normalized HFE preference matrix.On this basis,the distance and the projection of the normalized HFEs on positive and negative ideal solutions are calculated.Then,the normalized HFEs are transformed into agent satisfactions.Considering the stable matching constraints,a multiobjective programming model with the objective of maximizing the satisfactions of two-sided agents is constructed.Based on the agent satisfaction matrix,the matching intention matrix of two-sided agents is built.According to the agent satisfaction matrix and matching intention matrix,the comprehensive satisfaction matrix is set up.Furthermore,the multiobjective programming model based on satisfactions is transformed into a multiobjective programming model based on comprehensive satisfactions.Using the G-S algorithm,the multiobjective programming model based on comprehensive satisfactions is solved,and then the best TSM scheme is obtained.Finally,a terminal distribution example is used to verify the feasibility and effectiveness of the proposed method.

Two-Sided Matching Decision Making with Multi-Attribute Probabilistic Hesitant Fuzzy Sets

In previous research on two-sided matching(TSM)decision,agents’preferences were often given in the form of exact values of ordinal numbers and linguistic phrase term sets.Nowdays,the matching agent cannot perform the exact evaluation in the TSM situations due to the great fuzziness of human thought and the complexity of reality.Probability hesitant fuzzy sets,however,have grown in popularity due to their advantages in communicating complex information.Therefore,this paper develops a TSM decision-making approach with multi-attribute probability hesitant fuzzy sets and unknown attribute weight information.The agent attribute weight vector should be obtained by using the maximum deviation method and Hamming distance.The probabilistic hesitancy fuzzy information matrix of each agent is then arranged to determine the comprehensive evaluation of two matching agent sets.The agent satisfaction degree is calculated using the technique for order preference by similarity to ideal solution(TOPSIS).Additionally,the multi-object programming technique is used to establish a TSM method with the objective of maximizing the agent satisfaction of two-sided agents,and the matching schemes are then established by solving the built model.The study concludes by providing a real-world supply-demand scenario to illustrate the effectiveness of the proposed method.The proposed method is more flexible than prior research since it expresses evaluation information using probability hesitating fuzzy sets and can be used in scenarios when attribute weight information is unclear.

Color Matching of Pre-colored Fiber Blends Based on Two-Constant Kubelka-Munk Theory

Some modifications of two-constant Kubelka-Munk theory has been made for the color matching of pre-colored fiber blends. The scattering coefficients of three primaries are averaged and taken as initial coefficients in each wavelength. The unit sums of concentration in E-Allen’s Algorithm were removed in the case of pre-colored fiber blends. Predicted blend ratios and reflectance curves agree very well with measured ones and color differences are within the tolerant limit, showing satisfactory matching results.

Game-Theory Analysis for High Satisfaction Matchingon Strategic Decision

In any group,the project’s members want to create the highest value for the common goal,and how to choose project’s members could be a game.This study investigated the cooperating with education institutions.Analysis of the players’strategic choices and relative outcomes was conducted.The researchers would organize a simple tree model and sort to payoff matrix.The results revealed that the strategy of each player is different finally.There were two strategies for selecting a member-'Choosing Good Friendship player'and'Choosing Good Ability player'.Furthermore,this study also analyzed the influencing factors and stable matching possibility among the factors.

Resource Allocation in D2D-Aided High-Speed Railway Wireless Communication Systems： A Matching Theory Approach

With the rapid deployment of high speed railway(HSR) worldwide,both safety operation and comfort experience can be desired to evolve into a future era of intelligent transportation system.To eliminate boredom and provide entertainment for passengers,an intranet for internal communications among passengers named as onboard social network system(SNS) is needed.In this paper,the latest progress in HSR network architectures and technology building blocks are discussed to enable the implementation of the SNS.Meanwhile,based on the device-to-device(D2 D) communication technology for proximal information interaction,SNS can be efficiently facilitated.A dynamic resource allocation algorithm is proposed to maximize the total utility of the onboard SNS,which is solved with the matching theory method.Simulation results verify the convergence and efficiency of the proposed algorithm.

Exploring Channel Diversity in HF Communication Systems： A Matching-Potential Game Approach

This paper investigates the channel diversity problem in high frequency(HF) communication systems. Due to the limited HF spectrum resources, a HF communication system with shared channels is considered, where each user equipment(UE) has individual communication demand. In order to maximize the communication probability of the whole system, a matching-potential game framework is designed. In detail, the channel diversity problem is decomposed into two sub-problems. One is channel-transmitter matching problem, which can be formulated as a many-to-one matching game. The other is the transmitter allocation problem which decides the transmission object that each transmitter communicates with under channel-transmitter matching result, and this sub-problem can be modeled as a potential game. A multiple round stable matching algorithm(MRSMA) is proposed, which obtains a stable matching result for the first sub-problem, and a distributed BR-based transmitter allocation algorithm(DBRTAA) is designed to reach Nash Equilibrium(NE) of the second sub-problem. Simulation results verify the effectiveness and superiority of the proposed method.

Automatic Web services composition algorithm based on optimal matching

A novel layered method was proposed to solve the problem of Web services composition.In this method,services composition problem was formally transformed into the optimal matching problem of every layer,then optimal matching problem was modeled based on the hypergraph theory,and solved by computing the minimal transversals of the hypergraph.Meanwhile,two optimization algorithms were designed to discard some useless states at the intermediary steps of the composition algorithm.The effectiveness of the composition method was tested by a set of experiments,in addition,an example regarding the travel services composition was also given.The experimental results show that this method not only can automatically generate composition tree whose leaf nodes correspond to services composition solutions,but also has better performance on execution time and solution quality by adopting two proposed optimization algorithms.

An Automata-Based Approach to Pattern Matching

Due to its importance in security, syntax analysis has found usage in many high-level programming languages. The Lisp language has its share of operations for evaluating regular expressions, but native parsing of Lisp code in this way is unsupported. Matching on lists requires a significantly more complicated model, with a different programmatic approach than that of string matching. This work presents a new automata-based approach centered on a set of functions and macros for identifying sequences of Lisp S-expressions using finite tree automata. The objective is to test that a given list is an element of a given tree language. We use a macro that takes a grammar and generates a function that reads off the leaves of a tree and tries to parse them as a string in a context-free language. The experimental results indicate that this approach is a viable tool for parsing Lisp lists and expressions in the abstract interpretation

IMPROVED MODE-MATCHING AND NETWORK ANALYSIS OF E-PLANE WAVEGUIDE BRANCH DIRECTIONAL COUPLERS

The E-plane waveguide branch directional couplers are analyzed by a method which combines the multimode network theory with rigorous mode-matching approach. The electromagnetic field components are expanded by the superposition of LSEx modes rather than TE and TM modes in the mode-matching procedure. Meanwhile, the electromagnetic problem is transferred into the network problem through the mode-matching treatment. It is shown that the present method has the advantages of simplicity and less computation without affecting the accuracy of the calculation.

基于AIGC的用户个性化需求服务匹配模型研究

目的为解决网购推送内容相关度较低、信息滞后而造成的用户疲劳等问题,优化推送系统的个性化推荐能力,对AIGC推荐算法下的交互模式进行可行性探索。方法基于扎根理论获取用户关联属性并对其排序,进而利用AIGC大模型分别对用户需求信息和产品特征图文进行处理,最终建立基于AIGC的“用户-产品点对点匹配”(User-Product Point-To-Point Matching)推送模型。结果以水杯网购过程为例,通过对比实验进行验证。实验结果表明,该模式在用户选择信息层和深度搜索等方面可提升用户满意度。结论将AIGC引入推送服务行业,通过“预训练语言模型+微调”的模式实现推荐,能够进一步完善“用户-产品”的个性化推送服务,在电子商务、社交媒体、在线教育服务等领域具有重要意义。

基于动态哈夫模型及双边匹配的电动汽车充电引导策略

由于充电站中充电桩数目有限且电动汽车充电耗时长,陆续产生充电需求的各电动汽车用户存在对充电站资源的竞争。这不仅增加了用户排队概率,降低了充电站收益和利用率,而且使得用户在充电站规模、价格、评价等方面的个性化需求得不到充分满足。为此,提出了一种动态哈夫模型与双边匹配方法相结合的电动汽车充电引导策略。首先,对充电站客流、充电订单和充电桩详情等真实数据集进行大数据挖掘,分析公共充电站用户的充电站选择偏好和充电行为特征;然后,基于动态哈夫模型,结合用户充电站选择偏好量化不同区域用户前往不同充电站的概率,并生成充电站推荐列表;最后,将前景理论与双边匹配策略相结合,进行充电引导。算例分析表明,所提策略大幅降低了用户的排队概率,在满足用户个性化充电需求的同时,保障了充电站利益。

信息资源管理学科期刊年度选题指南与发表论文的匹配度

探究期刊的年度选题指南与所发表论文之间的匹配度及其影响因素有利于提高期刊办刊质量,提升学术引领力。文章选取信息资源管理学科13种期刊2017-2021年间的选题指南及2017-2022年间发表论文11,836篇,分别构建年度选题指南关键词数据集和论文关键词数据集,利用Python编写相应程序探究两者之间的匹配度;基于计划行为理论构建影响因素,利用SPSS软件分析这些因素对匹配度的影响。研究发现:信息资源管理学科期刊当年选题指南与相邻两年内发表论文的匹配度较低,均在0.5以下;当年选题指南与相邻两年间发表论文的匹配度存在差异,第一年的匹配度高于第二年的匹配度;以下因素与匹配度呈显著的相关关系,按影响程度由大到小依次为办刊时间、基金论文比、载文量,而期刊栏目数、复合影响因子、出版周期及论文年均篇幅长度与匹配度无关。

借势生财还是深度共创?创业生态系统中新创企业成长绩效组态研究

随着创业生态系统逐渐成为新创企业创业的重要基础设施,如何有效利用生态系统资源成为其成长道路上的主要挑战。基于资源编排理论与战略匹配理论,采用fsQCA研究方法对创业园区、孵化器内27家示范企业一手访谈调查数据进行分析,从组态视角探究创业生态系统情境下新创企业主体与资源情境对企业成长绩效的作用机制。结果发现:环境和主体层面的单一要素均不是促使新创企业成长绩效提升的必要条件,高成长绩效是资源情境特征与资源管理行为有效匹配的结果。存在3条高成长绩效实现路径,可归纳为借势生财型和深度共创型;2条非高成长绩效路径分别为雪上加霜型和眼高手低型。资源能力化、资源杠杆化组合与创业生态导向存在替代关系,说明在不同战略导向下新创企业可以采取不同资源管理方法获得高成长绩效。从复杂观与整体观视角解构创业生态系统情境下新创企业成长绩效差异化实现路径,有助于新创企业转变思维方式,提高资源利用效率。结论可为引导各类要素向创业生态系统集聚,提升创业生态系统资源配置水平提供理论支撑。

财政资助能否提升人力资本?——基于CEPS数据的实证分析

义务教育阶段的财政资助是中国特色重大专项转移支付。基于新人力资本理论,运用倾向得分匹配的固定效应模型,依据中国教育追踪调查数据(CEPS),考量财政资助对人力资本的影响。结果显示:财政资助有助于提升人力资本,具体表现在对个人非认知能力及其外向性、尽责性与开放性的提升。同时,自我教育期望和父母陪伴在财政资助与人力资本中起到部分中介作用。鉴于此,应进一步深化财政资助工作的育人属性,注重人力资本积累,因人施策提升财政资助绩效。

速调管放大器输入腔的匹配理论和模拟研究

基于输入微波与腔体耦合的等效电路模型,对于任意的腔体和电子束参数,建立了任意的输入微波与腔体耦合的速调管放大器输入腔的两种匹配状态的理论。建立了带有互感和电子束等效电阻和电容等参数的输入腔等效电路模型,推导了入射功率与反射功率的表达式,以及输入微波与带有电子束的输入腔耦合的完全匹配状态和任意的耦合这两种情形时输入功率和间隙电压关系的公式。推导了完全匹配状态时输入微波工作频率与输入腔有载品质因数的表达式。推导了复耦合系数等于1时输入腔外观品质因数与热腔品质因数的表达式,得出了当工作频率等于输入腔谐振频率,输入腔外观品质因数与热腔品质因数相等,且满足电子束等效电容远小于1时接近达到匹配状态,与传统理论基本一致。通过对比两种状态时的入射功率,得出了匹配状态时的入射功率小于复耦合系数等于1时入射功率的结论。通过对比复耦合系数等于1时新理论和传统理论的入射功率,得出不考虑电子束等效电容情况下两者相等的结论。采用二维粒子模拟的模型与匹配理论进行了对比,粒子模拟与理论基本一致。根据匹配理论找到了接近匹配状态的工作频率与有载品质因数以及较小的输入功率。

双元工作压力情境下如何促进员工产生创新行为--基于模糊集的定性比较分析

基于组态视角与个人—环境匹配理论,以152名企业员工为研究对象,运用CiteSpace和fsQCA方法对企业中促进员工产生创新行为的影响因素进行组态分析。探究不同压力情境下变革型领导、知识共享和心理授权在员工创新行为产生过程中的差异机制。结果表明,当员工感知的压力为挑战性压力且非阻碍性压力时,企业管理者应采用变革型领导的方式,并且鼓励员工之间知识共享;当员工既感知到挑战性压力又感知到阻碍性压力时,企业管理者应采用变革型领导的方式,并且提高员工的心理授权。

Damage failure of cemented backfill and its reasonable match with rock mass

In order to study the failure mechanism of backfill and the reasonable matches between backfill and rock mass, and to achieve the object of safe and efficient mining in metal mine, four types of backfills were tested under uniaxial compression loading, with cement?tailing ratios of 0.250:1, 0.125:1, 0.100:1 and 0.083:1, respectively. With the help of the stress?strain curves, the deformation and failure characteristics of different backfills with differing cement?tailing ratios were analyzed. Based on the experimental results, the damage constitutive equations of cemented backfills with four cement?tailing ratios were proposed on the basis of damage mechanics. Moreover, comparative analysis of constitutive model and experimental results were made to verify the reliability of the damage model. In addition, an energy model using catastrophe theory to obtain the instability criteria of system was established to study the interaction between backfill and rock mass, and then the system instability criterion was deduced. The results show that there are different damage characteristics for different backfills, backfills with lower cement?tailing ratio tend to have a lower damage value when stress reaches peak value, and damage more rapidly and more obviously in failure process after peak value of stress; the stiffness and elastic modulus of rock mass with lower strength are more likely to lead to system instability. The results of this work provide a scientific basis for the rational strength design of backfill mine.