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.

Uniform Representation Model for Metadata of Data Warehouse

A uniform metadata representation is introduced for heterogeneous databases, multi media information and other information sources. Some features about metadata are analyzed. The limitation of existing metadata model is compared with the new one. The metadata model is described in XML which is fit for metadata denotation and exchange. The well structured data, semi structured data and those exterior file data without structure are described in the metadata model. The model provides feasibility and extensibility for constructing uniform metadata model of data warehouse.

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.

Metadata Extended Model Based On Geological Domain Ontology

The current metadata modeling techniques can not meet the needs of knowledge conception expression, knowledge organization, and metadata semantic consistency in geological domain. This paper introduces ontology and integrates this theory to geological domain metadata modeling. It adopts the first order logic equivalent algorithm and defines the metadata extended model as a quaternion group which is consists of geological term set, geological term definition set, attribute definition set and instance set. It also provides the formal description of each set. Finally the five steps for building geological domain metadata extended model are given. The result presents that this model not only provides the content standards for geological domain knowledge representation and knowledge organization, but also provides the basis for geological domain multi-source data and historical data integration and application in semantic consistency.

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.

JPEG原图重构取证方法

数字图像已被广泛用于办理各类网上业务和作为司法证据。与此同时,利用流行的图像编辑软件,普通用户就可以对图像进行语义篡改而不留下视觉痕迹。因此,对数字图像的原始性和真实性进行辨识已成为迫切的应用需求。基于元数据的图像篡改取证方法因准确性高、计算量小而得到重视。然而,原图重构技术(例如应用MagicEXIF元数据编辑器)的出现使上述方法完全失效。针对这一问题,本文提出一种JPEG图像原图重构取证方法,用于检测图像是否受到重构攻击。通过分析原图重构的过程,以及重构前后图像的像素统计特征差异,本文对深度学习隐写分析模型SRNet(Steganalysis Residual Network)进行轻量化改进:裁剪其冗余的下采样层以减少参数,引入通道注意力机制以提高对关键特征的提取能力,并采用知识蒸馏的方法进一步提升模型的准确率。进一步地,通过分析重构对不同颜色分量的影响,采用YCbCr颜色分量作为模型输入,以提高检测性能。为测试算法的性能,我们收集了由不同品牌和型号的手机拍摄的图像数据,构建了大规模重构图像数据库。实验表明,本文提出的模型在参数量显著减少的情况下性能优于流行的模型,对512×512大小的图像可取得98%以上的检测正确率,且具有良好的跨设备泛化能力。同时,通过应用迁移学习,本文方法对不同版本的重构软件也具有较好的泛化性。

水利专业模型标准化元数据建模技术研究与应用

不同业务类型的水利专业模型在水利工程对象类型、模型静态参数、动态边界条件等输入侧存在差异,无法采用统一的构建模式进行通用化处理,影响模型的可复用性,降低了数字孪生平台的通用化水平。为此,提出了一种水利专业模型的建模技术,通过提取多类型专业模型在输入侧的类型、组织和格式特征,利用元数据的信息描述特性,建立针对水利专业模型建模过程的标准化元数据集,并基于元数据集设计和实现了通用化的建模过程接口,支撑水利专业模型的建模。该标准化元数据建模技术已成功应用于数字孪生岳城水库的预报、调度专业模型建模过程中,通过元数据屏蔽了模型各类输入数据的差异,提升了建模的效率和模型的可复用性。

角色建模工具RModeler的设计与实现

提倡在对象技术中基于角色识别对象及其协调关系,然后展开到类模型、接口模型、实体模型,同时对角色模型的形式化定义和表示方法进行了系统地研究,并在此基础上设计和实现了基于RML的可视化角色建模工具RModeler。RModeler目前完成了代码实现和测试工作,并在实际开发中使用,运行良好。RModeler支持业务过程中采用RML语言的建模,具备将RML模型转换为UML模型的功能,采用业界标准数据描述格式XMI来传递和共享建模信息。

基于耗散结构理论的政府数据治理研究

针对政府数据利用中数据的可查找、可理解、可使用等典型问题,为有效缓解高质量数据供给不平衡不充分的矛盾,综合分析政府数据治理的理论成果与目标任务,进一步研究政府数据治理的基础理论和相应的实践路径,从系统科学角度探究基于耗散结构理论的政府数据治理的内在逻辑机理,提出基于元数据管理和一体化建模的政府数据内生治理机制建设的技术方法,以期从基础层面强化数据标准、提升数据质量、促进数据利用,提升政府数据治理效能。

分类分级自动化编排方法研究

在当今数字化浪潮中,企业和组织面临的数据量呈指数级增长,其复杂性和多样性随之加剧,传统的手动数据分类分级方法已难以适应快速变化的数据环境。对此,文章通过模型训练和数据挖掘技术实现了数据的快速准确识别与分类分级,不仅能够显著提升数据管理的效率和可靠性,还能有效保护敏感数据,从而确保企业数据资产的安全。此外,相关研究成果为企业和组织提供了一种高效、智能的数据分类分级解决方案,有助于其在数字化时代中更好地管理和利用数据资源,最终实现可持续发展。

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 Novel Cross-Media Layered Semantic Mining Model

This paper presents a cross-media semantic mining model （CSMM） based on object semantic. This model obtains object-level semantic information in terms of maximum probability principle. Then semantic templates are trained and constructed with STTS （Semantic Template Training System）, which are taken as the bridge to realize the transition from various low-level media feature to object semantic. Furthermore, we put forward a kind of double layers metadata structure to efficaciously store and manage mined low-level feature and high-level semantic. This model has broad application in lots of domains such as intelligent retrieval engine, medical diagnoses, multimedia design and so on.

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.

Design and Implementation of Two-Level Metadata Server in Small-Scale Cluster File System

The reliability and high performance of metadata service is crucial to the store architecture. A novel design of a two-level metadata server file system （TTMFS） is presented, which behaves high reliability and performance. The merits both centralized management and distributed management are considered simultaneously in our design. In this file system, the advanced-metadata server is responsible for manage directory metadata and the whole namespace. The double-metadata server is responsible for maintaining file metadata. And this paper uses the Markov return model to analyze the reliability of the two-level metadata server. The experiment data indicates that the design can provide high throughput.

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.

Research on the Adaptive Object-Model Architecture Style

The rapidly changing requirements and business rules stimulate software developers to make their applications more dynamic, configurable, and adaptable. An effective way to meet such requirements is to apply an adaptive object-model (AOM). The AOM architecture style is composed of metamodel, model engine and tools. Firstly, two small patterns for building up metamodel are analyzed in detail. Then model engine for interpreting metamodel and tools for end-uses to define and configure object models are discussed. Finally, a novel platform—applicationware—is proposed.

人工智能时代的元数据方法论

元数据是关于数据的数据,随着技术的进步,元数据获取逐渐成为信息系统数据建模和实现功能的关键性步骤,发展起一套包括实体定义、关系描述、对象分析、属性提取、本体建模,以及数据清洗、消歧、对齐、映射、关联、丰富、导入、导出乃至服务部署、注册发现、运行监测等一系列操作的方法论体系,旨在帮助实现任何信息体的结构化描述、语义编码和机器理解。这些不仅是语义技术(包括关联数据)和知识图谱技术必需的应用,而且已成为信息系统建立独立的、基于知识的内容架构的基本操作和主要方案。文章把与元数据相关的一系列方法体系统称为元数据方法,相关的最佳实践基本体现于语义万维网已经制定、正在制订或正在考虑制订的各项标准规范中。元数据方法在未来基于Web 3.0的多模态元宇宙建设中会继续起到多方面的重要作用,如利用知识模型构建数字孪生,甚至支持对整个虚拟世界的建模等。当然基于人工的描述和编码显然不能适应元宇宙时代用户生产内容(UGC)和ChatGPT带来的人工智能生成内容(AIGC)的内容生产方式,必须有一套方法论帮助自动实现语义形式化。这应该是元数据方法适应未来智慧时代需求的必由之路。