The Reputation Model of Multi-Stage Dynamic Game

Aim To study the implicit restriction mechanism for hidden action in multi stage dynamic game. Methods A reputation model for restriction on repeated principal agent relationship was established by using the theory on principal agent problem in information economics and the method of game theory to study the implicit restriction mechanism for hidden action. Results and Conclusion It is proved that there exists implicit restriction mechanism for the multi stage principal agent relationship, some conditions for effective restriction are derived, the design methods of implicit restriction mechanism are presented.

Research of Internet Trade Trust Based on the KMRW Reputation Model

The paper discusses the Internet trade trust problemby using KMRW reputation model in incompleteinformation limited repeated game,concluding thatin certain conditions,both Internet trade participatorswill give up short-time revenue for maximizinglong-term revenue and accordingly employ the cooperationstrategy,and the times of cooperation isvulnerable to trade price and product utility.At last,the paper proposes several policies and suggestionssuch as forming Internet honesty culture,strengtheningInternet brand and figure and protecting Internetwell-known brands.

Classification and Visualization of Surrounding Rock Mass Stability Based on Multi-Dimensional Cloud Model

The classification of the stability of surrounding rock is an uncertain system with multiple indices.The Multidimensional Cloud Model provides an advanced solution through the use of an improved model of One-dimensional Cloud Model.Setting each index as a one-dimensional attribute,the Multi-dimensional Cloud Model can set the digital characteristics of each index according to the cloud theory.The Multi-dimensional cloud generator can calculate the certainty of each grade,and then determine the stability levels of the surrounding rock according to the principle of maximum certainty.Using this model to 5 coal mine roadway surrounding rock examples and comparing the results with those of One-dimensional and Two-dimensional Cloud Models,we find that the Multi-dimensional Cloud Model can provide a more accurate solution.Since the classification results of the Multidimensional Cloud Model are difficult to be presented intuitively and visually,we reduce the Multi-dimensional Cloud Model to One-dimensional and Two-dimensional Cloud Models in order to visualize the results achieved by the Multi-dimensional Cloud Model.This approach provides a more accurate and intuitive method for the classification of the surrounding rock stability,and it can also be applied to other types of classification problems.

The Effect of Reputation to the Moral Hazard in C2C E-Market with Game Theory

It is well known that the reputation is the basis of a seller to survive and gain trust from customers in a competitive business environment. But as the existence of information asymmetry between buyer and seller, the moral hazard problem is the key obstacle that impedes the benefits of related shareholders and reduces the efficiency of total market. It is crucial to design a control mechanism to avoid the negative impact of moral hazard. This paper studies the principal and agent relationship between buyer and seller in C2C e-market;because of the influence of information asymmetry, many customers suffered from being cheated by sellers with defective products in practice. These frequent cases will deteriorate long term relationship between sellers and buyers. Here we focus on the analysis of the causes of moral risks and the effect of reputation on oral risk with repeated game theory. The purpose of this paper is to help both firms and customers effectively avoid morality risk and realize a win-win situation.

Multi-dimensional database design and implementation of dam safety monitoring system

To improve the effectiveness of dam safety monitoring database systems, the development process of a multi-dimensional conceptual data model was analyzed and a logic design wasachieved in multi-dimensional database mode. The optimal data model was confirmed by identifying data objects, defining relations and reviewing entities. The conversion of relations among entities to external keys and entities and physical attributes to tables and fields was interpreted completely. On this basis, a multi-dimensional database that reflects the management and analysis of a dam safety monitoring system on monitoring data information has been established, for which factual tables and dimensional tables have been designed. Finally, based on service design and user interface design, the dam safety monitoring system has been developed with Delphi as the development tool. This development project shows that the multi-dimensional database can simplify the development process and minimize hidden dangers in the database structure design. It is superior to other dam safety monitoring system development models and can provide a new research direction for system developers.

MULTI-DIMENSIONAL MARKOV CHAIN–BASED ANALYSIS OF CONFLICT PROBABILITY FOR SPECTRUM RESOURCE SHARING

In this paper, we consider the optimal problem of channels sharing with het-erogeneous traffic （real-time service and non-real-time service） to reduce the data conflict probability of users. Moreover, a multi-dimensional Markov chain model is developed to analyze the performance of the proposed scheme. Meanwhile, performance metrics are derived. Numerical results show that the proposed scheme can effectively reduce the forced termination probability, blocking probability and spectrum utilization.

Application Research of Multi-Dimensional Customer Behavior Analysis Model in Precision Marketing

The advent of the digital era has provided unprecedented opportunities for businesses to collect and analyze customer behavior data. Precision marketing, as a key means to improve marketing efficiency, highly depends on a deep understanding of customer behavior. This study proposes a theoretical framework for multi-dimensional customer behavior analysis, aiming to comprehensively capture customer behavioral characteristics in the digital environment. This framework integrates concepts of multi-source data including transaction history, browsing trajectories, social media interactions, and location information, constructing a theoretically more comprehensive customer profile. The research discusses the potential applications of this theoretical framework in precision marketing scenarios such as personalized recommendations, cross-selling, and customer churn prevention. Through analysis, the study points out that multi-dimensional analysis may significantly improve the targeting and theoretical conversion rates of marketing activities. However, the research also explores theoretical challenges that may be faced in the application process, such as data privacy and information overload, and proposes corresponding conceptual coping strategies. This study provides a new theoretical perspective on how businesses can optimize marketing decisions using big data thinking while respecting customer privacy, laying a foundation for future empirical research.

基于通信延迟聚类和节点信誉的PBFT共识算法

针对现有基于分组策略的拜占庭容错共识算法中存在的主节点不稳定、延迟高等问题,提出一种基于通信延迟聚类和节点信誉的PBFT共识算法(CD-PBFT)。首先,设计了新的基于通信延迟的聚类算法对网络中节点进行分组,将通信延迟融合进欧氏距离公式,让系统中的节点根据混合距离进行聚类,最终使各个集群中延迟之和达到最低,减少通信开销,提升共识效率;其次,提出了基于综合评价的信誉模型,综合考虑节点延迟指数、共识行为和历史信誉,对节点进行信誉评估,依据节点行为和延迟差异进行信誉奖惩;最后,优化主节点选取方式,建立了一种基于节点稳定性和信誉模型的主节点选择机制,通过信誉模型获得节点的信誉值后,引入方差来衡量节点的信誉波动,选择信誉高且方差小的节点担任主节点,提高主节点的安全性。实验结果表明,相较于PBFT,该算法平均吞吐量提高了126.8%,平均时延降低了68.3%。同时,与现有基于聚类的PBFT算法相比,CD-PBFT具有较为明显的性能优势,能够更灵活地应用在大规模节点的联盟链场景中。

A MULTISCALE MECHANICAL MODEL FOR MATERIALS BASED ON VIRTUAL INTERNAL BOND THEORY

Only two macroscopic parameters are needed to describe the mechanical properties of linear elastic solids, i.e. the Poisson＇s ratio and Young＇s modulus. Correspondingly, there should be two microscopic parameters to determine the mechanical properties of material if the macroscopic mechanical properties of linear elastic solids are derived from the microscopic level. Enlightened by this idea, a multiscale mechanical model for material, the virtual multi-dimensional internal bonds （VMIB） model, is proposed by incorporating a shear bond into the virtual internal bond （VIB） model. By this modification, the VMIB model associates the macro mechanical properties of material with the microscopic mechanical properties of discrete structure and the corresponding relationship between micro and macro parameters is derived. The tensor quality of the energy density function, which contains coordinate vector, is mathematically proved. From the point of view of VMIB, the macroscopic nonlinear behaviors of material could be attributed to the evolution of virtual bond distribution density induced by the imposed deformation. With this theoretical hypothesis, as an application example, a uniaxial compressive failure of brittle material is simulated. Good agreement between the experimental results and the simulated ones is found.

A New Kind of Subjective Trust Model

Based on the outstanding characteristics of Cloud Model on the process of transforming a qualitative concept to a set of quantitative numerical values, a formalized model of subjective trust is introduced by which we can transform between qualitative reputation and quantitative voting data. The present paper brings forward algorithms to compute direct trust and recommender trust. Further more, an effective similarity measuring method used to distinguish two users＇ reputation on knowledge level is also proposed. The given model properly settles the uncertainty and fuzziness properties of subjective trust which is always the weakness of traditional subjective trust model, and provides a step in the direction of proper understanding and definition of human trust.

METrust: A Mutual Evaluation-based Trust Model for P2P Networks

It is necessary to construct an effective trust model to build trust relationship between peers in peer-to-peer （P2P） network and enhance the security and reliability of P2P systems. The current trust models only focus on the consumers＇ evaluation to a transaction, which may be abused by malicious peers to exaggerate or slander the provider deliberately. In this paper, we propose a novel trust model based on mutual evaluation, called METrust, to suppress the peers＇ malicious behavior, such as dishonest evaluation and strategic attack. METrust considers the factors including mutual evaluation, similarity risk, time window, incentive, and punishment mechanism. The trust value is composed of the direct trust value and the recommendation trust value. In order to inhibit dishonest evaluation, both participants should give evaluation information based on peers＇ own experiences about the transaction while computing the direct trust value. In view of this, the mutual evaluation consistency factor and its time decay function are proposed. Besides, to reduce the risk of computing the recommendation trust based on the recommendations of friend peers, the similarity risk is introduced to measure the uncertainty of the similarity computing, while similarity is used to measure credibility. The experimental results show that METrust is effective, and it has advantages in the inhibition of the various malicious behaviors.

QoS Routing Algorithm with Multi-Dimensions for Overlay Networks

Overlay networks have emerged as a useful approach to providing a general framework for new applications and services that are to be implemented without significantly changing the IP-layer network infrastructure.Overlay routing has been used as an alternative to the default best effort Internet routing for the absence of end-to-end Quality of Service(QoS). While the former has recently been investigated, the conflict of QoS restraints and resource optimization remains unsolved. Recent studies have shown that overlay paths can give better latency, loss rate and TCP throughput. In this paper, a multi-dimensional QoS objective model based on the analysis of multiple QoS constraints has been presented, and a routing algorithm to optimise the overlay resource of its nodes and links is then proposed.In fact, the algorithm obtained multiple QoS values using probability theory to achieve the routing according to the multi-dimensional QoS objective vector of the QoS objective model. Simulation results reveals that the algorithm works better than other existing algorithms in balancing the network resources, and applications with stringent QoS requirements could be run.

Dirichlet Compound Multinomials Statistical Models

This contribution deals with a generative approach for the analysis of textual data. Instead of creating heuristic rules forthe representation of documents and word counts, we employ a distribution able to model words along texts considering different topics. In this regard, following Minka proposal (2003), we implement a Dirichlet Compound Multinomial (DCM) distribution, then we propose an extension called sbDCM that takes explicitly into account the different latent topics that compound the document. We follow two alternative approaches: on one hand the topics can be unknown, thus to be estimated on the basis of the data, on the other hand topics are determined in advance on the basis of a predefined ontological schema. The two possible approaches are assessed on the basis of real data.

Least squares fitting of coordinate parameters model

This paper starts with untime-diversification of the time-diversification deformation model and gives displacement distribution model of untime-diversification and simplifies further the study of deformation model. The paper discusses the problem of least squares fitting of coordinate parameters model—parameters of deformation model. During discussion, the basic means of cubic B splines and two steps of multidimensional disorder datum fitting are adopted which can make fitting function calculated mostly approximate coordinate parameters model and it can make calculation easier.

Research and implementation on multi-dimension trust evaluation method with web service

Integrating with practical e-commerce application, this paper introduces a novel multi-dimension evaluation method to depict and calculate the trust values. The multi-dimension evaluation metrics include functional and nonfunctional properties and corresponding weights. The continuous measurement values and the Markov chain mechanism are adopted to compute the trust value and detect the malicious behaviors. The current evaluation has larger influence factor on the next transaction behavior. A trust model is implemented with web service which consists of publication, filtrating, calculating and storage center. It is easily extended and the user only defines each property and its weights according to specific requirements, then the trust values are got. In order to conveniently manage and avoid the dead-lock, some constraint rules are proposed. The results show that the method based on multi-dimension can reflect objectively the dynamic change of trust values.

Application of PPE Model in Land Adaptability Appraisal in Small Basin Based on RAGA

The paper applies multi-dimension to lower technology-projection pursuit evaluation model in the conservation of water and soil discipline domain, optimizes the projection direction using the improved acceleration genetic algorithms, transforms the multi-dimensional data target to lower sub-space, and values soil adaptability of Dongdagou basin in Keshan County by searching the optimal projection direction and the projection function data. The paper provides a new notion and method for the conservation of water and soil in small basin.

基于跨链技术的食品供需网信息共享激励模式构建

随着食品种类多元化和消费者需求的提升,食品生产流程更加复杂,供应链之间交流越来越多,相关企业、食品供应链和行业机构之间的交互形成了复杂的食品供需网结构。食品供需网成员之间信息共享有利于企业之间充分合作实现长期发展,但仍有许多企业共享信息意识较弱,无法进行有效信息沟通。区块链跨链技术的应用和发展,为食品供需网信息共享提供了新思路。根据食品供需网复杂性,引入区块链技术和声誉激励机制,将声誉进行量化管理,结合区块链智能合约技术实现声誉激励机制自动化。进一步引入区块链跨链技术,打破不同行业、地区区块链之间的交易壁垒,构建基于区块链跨链技术的食品供需网信息共享声誉激励模式,以猪肉供需网为例阐述跨链信息共享声誉激励流程。该激励模式不仅保障共享信息安全性与准确性,同时保护企业隐私,最大程度保护交易方自身利益,破解信息无法共享的障碍,激发食品供需网企业参与信息共享积极性。不仅实现食品供需网内部异构区块链之间的信息交流和价值互通,还为食品供需网价值信息交流互通的发展提供新思路。

声誉对互联网医院使用意愿影响的多元路径分析——基于SEM和fsQCA的实证分析

目的:探究声誉对互联网医院使用意愿的影响,对优化互联网医院服务供给模式,提高患者就医体验,促进医院高质量发展都具有重要意义。方法:基于信息-解释-响应(I-I-R)理论构建声誉对互联网医院使用意愿影响框架模型,采用结构方程模型(SEM)和模糊集定性比较分析法(fsQCA)对互联网医院的使用意愿和组态路径进行实证分析。结果:医院社会责任、医院实力和医生声誉正向影响评估性态度,路径系数由强到弱依次为0.360、0.301和0.260;医院实力和医院社会责任正向影响情感性态度,路径系数分别为0.449和0.272;评估性态度和情感性态度正向影响使用意愿,路径系数分别为0.519和0.386。且以医院社会责任型和医生声誉+医院实力型为核心条件可构成两种模式下的六条有效路径。结论:医生声誉、医院实力和医院社会责任对提高互联网医院使用意愿最有效。医院应构建专业度高的医疗服务平台,提高知名度;应定期开展学习和培训,更新医疗设备,保持信息公开透明,积极承担社会责任,提高医院实力;医生应改善服务态度,提高线上互动性。