Whole-Process Project Cost Management Based on Building Information Modeling (BIM)

The whole-process project cost management based on building information modeling(BIM)is a new management method,aiming to realize the comprehensive optimization and improvement of project cost management through the application of BIM technology.This paper summarizes and analyzes the whole-process project cost management based on BIM,aiming to explore its application and development prospects in the construction industry.Firstly,this paper introduces the role and advantages of BIM technology in engineering cost management,including information integration,data sharing,and collaborative work.Secondly,the paper analyzes the key technologies and methods of the whole-process project cost management based on BIM,including model construction,data management,and cost control.In addition,the paper also discusses the challenges and limitations of the whole-process BIM project cost management,such as the inconsistency of technical standards,personnel training,and consciousness change.Finally,the paper summarizes the advantages and development prospects of the whole-process project cost management based on BIM and puts forward the direction and suggestions for future research.Through the research of this paper,it can provide a reference for construction cost management and promote innovation and development in the construction industry.

Integrity-Management Characteristics and Efficiency Evaluation of Oil and Gas Pipelines

Pipeline integrity is a cornerstone of the operation of many industrial systems, and maintaining pipeline integrity is essential for preventing economic losses and ecological damage caused by oil and gas leaks. Based on integritymanagement data published by the US Pipeline and Hazardous Materials Safety Administration, this study applied the k-means clustering and data envelopment analysis(DEA) methods to both explore the characteristics of pipeline-integrity management and evaluate its efficiency. The k-means clustering algorithm was found to be scientifically valid for classifying pipeline companies as either low-, medium-, or high-difficulty companies according to their integrity-management requirements. Regardless of a pipeline company's classification, equipment failure was found to be the main cause of pipeline failure. In-line inspection corrosion and dent tools were the two most-used tools for pipeline inspection. Among the types of repair, 180-day condition repairs were a key concern for pipeline companies. The results of the DEA analysis indicate that only three out of 34 companies were deemed to be DEA-effective. To improve the effectiveness of pipeline integrity management, we propose targeted directions and scales of improvement for non-DEA-effective companies.

Integrated Engineering Design and Data Management

This paper describes how database information and electronic 3D models are integrated to produce power plant designs more efficiently and accurately. Engineering CAD/CAE systems have evolved from strictly 3D modeling to spatial data management tools. This paper describes how process data, commodities, and location data are disseminated to the various project team members through a central integrated database. The database and 3D model also provide a cache of information that is valuable to the constructor, and operations and maintenance Personnel.

Data Integrity and Risk

Data Integrity is a critical component of Data lifecycle management. Its importance increases even more in a complex and dynamic landscape. Actions like unauthorized access, unauthorized modifications, data manipulations, audit tampering, data backdating, data falsification, phishing and spoofing are no longer restricted to rogue individuals but in fact also prevalent in systematic organizations and states as well. Therefore, data security requires strong data integrity measures and associated technical controls in place. Without proper customized framework in place, organizations are prone to high risk of financial, reputational, revenue losses, bankruptcies, and legal penalties which we shall discuss further throughout this paper. We will also explore some of the improvised and innovative techniques in product development to better tackle the challenges and requirements of data security and integrity.

Database Management System Construction for the Evaluation Results of Intensive Land Use in the Development Areas of Hunan Province

Using spatial data integration and database technology,analyzing and integrating the assessment results in all the development zones at different time in Hunan Province,the paper is intended to construct the database and managerial system for the assessment results of land use intensity in development zones,thus formulating"one map"of Hunan Development zones and realizing the integrated management and application of the assessment results in all the development zones at any time of Hunan above the provincial level.It has been proved that the system has good application effect and promising development in land management for land management departments and development zones.

How to Implement Product Data Management

introduced are the main implementation contents and brought out is a cycle optimal PDMimplementation methodology by phases through studying requirements of enterprises' datamanagement and summarizing the existing method. The implementation contents include documentsmanagement product structure and configuration management, product classification and codingmanagement, workflow management and software encapsulation. It divides the PDM implementationinto preparing, software selechon and training, implementation plan making, concrete implementingand evaluating. By the cycle of the last two pheses, the successful implementation of PDM can beobtained. This methodology has been used in the CIMS project of two companies and proved to bepractical.

Digital management technology and its application to investment casting enterprises

With the advent of Industry 4.0, more and more investment casting enterprises are implementing production manufacturing systems, especially in the last two years. This paper summarizes three new common requirements of the digital management aspect in precision casting enterprises, and puts forward three corresponding techniques. They are: the production process tracking card technology based on the main-sub card mode; the workshop site production process processing technology based on the barcode; and the equipment data integration technology. Then, this paper discusses in detail the principle, application and effect of these technologies; to provide the reference for enterprises to move towards digital casting and intelligent casting.

Reliability Management for Information System

An integrated intelligent management is presented to help organizations manage many heterogeneous resources in their information system. A general architecture of management for information system reliability is proposed, and the architecture from two aspects, process model and hierarchical model, described. Data mining techniques are used in data analysis. A data analysis system applicable to real-time data analysis is developed by improved data mining on the critical processes. The framework of the integrated management for information system reliability based on real-time data mining is illustrated, and the development of integrated and intelligent management of information system discussed.

Web-services-based Integration Design of PDM and DNC Systems

In a networked manufacturing environment, product data integration is the foundation of collaborative manufacturing among manufacturing enterprises. It is very important to build an effective integration mechanism for product data sharing of manufacturing enterprises in geographically dispersed, heterogeneous system platform. In order to integrate enterprise level product data management (PDM) system and shop floor level distributed numerical control (DNC) system, based on the description of Web services technology, a Web-services-based integration approach is presented for facilitating seamless sharing of product data between PDM and DNC systems in a networked manufacturing environment. In order to verify the validity of the proposed approach, an example-based integration development has been implemented with Java 2 Software Development Kit and Java Web Services Developer Pack in Windows 2000 Professional environment.

Trust Management in Grid-Trust Assessment and Trust Degree Calculation of a Resource—A Novel Approach

Grid Computing is concerned with the sharing and coordinated use of diverse resources in distributed Virtual Organizations. This introduces various challenging security issues. Among these trusting, the resources to be shared and coordinated with the dynamic and multi-institutional virtual organization environment becomes a challenging security issue. In this paper, an approach for trust assessment and trust degree calculation using subjective logic is suggested to allocate the Data Grid or Computational Grid user a reliable, trusted resource for maintaining the integrity of the data with fast response and accurate results. The suggested approach is explained using an example scenario and also from the simulation results. It is observed that there is an increase in the resource utilization of a trusted resource in contrast to the resource which is not trusted.

Intelligent Biometric Information Management

We advance here a novel methodology for robust intelligent biometric information management with inferences and predictions made using randomness and complexity concepts. Intelligence refers to learning, adap- tation, and functionality, and robustness refers to the ability to handle incomplete and/or corrupt adversarial information, on one side, and image and or device variability, on the other side. The proposed methodology is model-free and non-parametric. It draws support from discriminative methods using likelihood ratios to link at the conceptual level biometrics and forensics. It further links, at the modeling and implementation level, the Bayesian framework, statistical learning theory (SLT) using transduction and semi-supervised lea- rning, and Information Theory (IY) using mutual information. The key concepts supporting the proposed methodology are a) local estimation to facilitate learning and prediction using both labeled and unlabeled data;b) similarity metrics using regularity of patterns, randomness deficiency, and Kolmogorov complexity (similar to MDL) using strangeness/typicality and ranking p-values;and c) the Cover – Hart theorem on the asymptotical performance of k-nearest neighbors approaching the optimal Bayes error. Several topics on biometric inference and prediction related to 1) multi-level and multi-layer data fusion including quality and multi-modal biometrics;2) score normalization and revision theory;3) face selection and tracking;and 4) identity management, are described here using an integrated approach that includes transduction and boosting for ranking and sequential fusion/aggregation, respectively, on one side, and active learning and change/ outlier/intrusion detection realized using information gain and martingale, respectively, on the other side. The methodology proposed can be mapped to additional types of information beyond biometrics.

基于Data Fabric的多模数据管理方法

随着政府和企业在信息化向数字化演进历程中信息化程度的加深,各类应用系统生成的数据日益多模化、多源化、海量化,这对数据管理造成了新的挑战.为了解决这些挑战,数据管理领域涌现出了许多新的技术和理念,其中Data Fabric (数据编织)便是一种新兴的数据管理技术和方法,它将分布式数据存储、处理和应用整合为一个整体,并提供了一套可视化的接口进行管理.本文首先分析了Data Fabric的技术架构、技术特点、技术价值和对多模数据进行管理与应用的完整流程.其次,提出了基于时序指标的多模多源数据的异常监测方法、基于日志数据的多模多源数据的异常监测方法,它们通过Data Fabric技术的使用,处理速度分别提高了33.3%和42.2%, F1-score分别提高12.2个和14.8个百分点,进一步说明了Data Fabric技术和本文新提出方法的高效性和应用价值.

大数据应用技术课程本研一体化教学体系建设

大数据应用技术课程对于数据科学的研究和发展、数据科学学科的建设、培育新型数据人才具有重要意义。本研一体化教学有助于提高本研学生的学习效率和创新能力,增强课程体系的延续性和实践性,重视学科交叉融合发展。从教学大纲修订、教学管理模式改革、教学评价方式三个方面探讨本研一体化教学体系建设的重点问题,全面阐述大数据应用技术课程本研一体化教学改革的路径选择和实践,致力于培养学生长期内驱力和创新能力,为国家和社会发展培育高质量数据人才。

“多元基础、分路径培养”的物流大数据应用型人才培养创新与实践

该文从人才培养模式创新、产教融合提升人才培养质量视角,对大数据本科专业应用型人才培养的多元学科专业基础和培养路径做出分析,进而以物流大数据专业群应用型人才培养为例,通过实施文理文工融合改革思路构建物流大数据复合知识体系,建设“多专业+多课程+多层次+多要求”的大数据实践实训平台、多学科专业融合互促的泛在化教学体系和深化产教研融合,形成多元基础分路径培养的人才培养思路并应用实践。通过物流大数据人才培养改革创新与实践,2021—2023年文理文工融合人才培养模式获得认可,教学成果突出,促进学科专业资源整合,形成“资源-名师-成果”互促上升的发展路径,人才培养质量显著提升,社会认可度提高。

科学数据出版在我国的实践研究——以《图书馆杂志》为例

通过对《图书馆杂志》科学数据出版实践进行分析,为我国科学数据出版发展提供参考和借鉴。文章梳理科学数据出版的发展历程,归纳科学数据出版的三种主要模式:独立数据出版、论文辅助资料数据出版、数据论文出版。文章深入分析《图书馆杂志》科学数据出版模式、科学数据出版流程和数据出版管理平台的服务功能,对《图书馆杂志》科学数据出版业务的未来进行展望,认为《图书馆杂志》数据出版尚处于探索阶段,还需对标国际知名出版机构的科学数据出版经验,完善科学数据出版的各个环节,以期更好地服务科研群体,助力我国学术期刊科学数据出版高质量发展。

智慧校园背景下高校多业务系统数据集成与共享应用研究

随着高校智慧校园建设的持续推进,各类业务信息系统和Web应用不断完善,产生了数据类型和数据访问方式多样的海量业务数据,实现多源数据集成与共享,成为当前高校智慧校园建设的必然趋势。文章就高校数据资源现状进行分析,提出公共数据中心的建设框架、实现海量数据交互共享的策略以及相对应的数据管理办法。

基于虚实结合的任务信息引接系统设计与实现

为满足训练的信息化需求,设计了灵活通用的数据协议和虚实结合的信息引接系统。基于中间件的分层设计思路,实现了外部信息接收、对内信息转发、通信协议解析与转换、信息对接联调、数据文件记录、配置管理以及信息流量统计等功能;采用了MVC软件架构模式,选用Visual Studio 2015作为开发工具,以Oracle数据库作为底层支撑,构建了实装信息及虚拟目标信息接收模块、建立数据映射关系模块、读取数据库方案模块、基础通信接收内部航迹模块、数据包发送模块。实际应用效果表明,该系统能够屏蔽外部装备系统、仿真系统和网络协议之间的差异,提供互联互通,适应虚实结合的训练任务,提高保障能力。该系统具有良好的适应性和可扩展性,可以满足信息化条件下系统的应用和发展需要。