The Influence of Social Media on College Choice among Undergraduates Majoring in Big Data Management and Application in China:Taking Guilin University of Electronic Technology as an Example

This study aims to investigate the influence of social media on college choice among undergraduates majoring in Big Data Management and Application in China.The study attempts to reveal how information on social media platforms such as Weibo,WeChat,and Zhihu influences the cognition and choice process of prospective students.By employing an online quantitative survey questionnaire,data were collected from the 2022 and 2023 classes of new students majoring in Big Data Management and Application at Guilin University of Electronic Technology.The aim was to evaluate the role of social media in their college choice process and understand the features and information that most attract prospective students.Social media has become a key factor influencing the college choice decision-making of undergraduates majoring in Big Data Management and Application in China.Students tend to obtain school information through social media platforms and use this information as an important reference in their decision-making process.Higher education institutions should strengthen their social media information dissemination,providing accurate,timely,and attractive information.It is also necessary to ensure effective management of social media platforms,maintain a positive reputation for the school on social media,and increase the interest and trust of prospective students.Simultaneously,educational decision-makers should consider incorporating social media analysis into their recruitment strategies to better attract new student enrollment.This study provides a new perspective for understanding higher education choice behavior in the digital age,particularly by revealing the importance of social media in the educational decision-making process.This has important practical and theoretical implications for higher education institutions,policymakers,and social media platform operators.

Exploration and Practice of Big Data Introductory Courses for Big Data Management and Application Majors

As an introductory course for the emerging major of big data management and application,“Introduction to Big Data”has not yet formed a curriculum standard and implementation plan that is widely accepted and used by everyone.To this end,we discuss some of our explorations and attempts in the construction and teaching process of big data courses for the major of big data management and application from the perspective of course planning,course implementation,and course summary.After interviews with students and feedback from questionnaires,students are highly satisfied with some of the teaching measures and programs currently adopted.

Privacy Data Management Mechanism Based on Blockchain and Federated Learning

Due to the extensive use of various intelligent terminals and the popularity of network social tools,a large amount of data in the field of medical emerged.How to manage these massive data safely and reliably has become an important challenge for the medical network community.This paper proposes a data management framework of medical network community based on Consortium Blockchain(CB)and Federated learning(FL),which realizes the data security sharing between medical institutions and research institutions.Under this framework,the data security sharing mechanism of medical network community based on smart contract and the data privacy protection mechanism based on FL and alliance chain are designed to ensure the security of data and the privacy of important data in medical network community,respectively.An intelligent contract system based on Keyed-Homomorphic Public Key(KH-PKE)Encryption scheme is designed,so that medical data can be saved in the CB in the form of ciphertext,and the automatic sharing of data is realized.Zero knowledge mechanism is used to ensure the correctness of shared data.Moreover,the zero-knowledge mechanism introduces the dynamic group signature mechanism of chosen ciphertext attack(CCA)anonymity,which makes the scheme more efficient in computing and communication cost.In the end of this paper,the performance of the scheme is analyzed fromboth asymptotic and practical aspects.Through experimental comparative analysis,the scheme proposed in this paper is more effective and feasible.

A Trailblazing Framework of Security Assessment for Traffic Data Management

Connected and autonomous vehicles are seeing their dawn at this moment.They provide numerous benefits to vehicle owners,manufacturers,vehicle service providers,insurance companies,etc.These vehicles generate a large amount of data,which makes privacy and security a major challenge to their success.The complicated machine-led mechanics of connected and autonomous vehicles increase the risks of privacy invasion and cyber security violations for their users by making them more susceptible to data exploitation and vulnerable to cyber-attacks than any of their predecessors.This could have a negative impact on how well-liked CAVs are with the general public,give them a poor name at this early stage of their development,put obstacles in the way of their adoption and expanded use,and complicate the economic models for their future operations.On the other hand,congestion is still a bottleneck for traffic management and planning.This research paper presents a blockchain-based framework that protects the privacy of vehicle owners and provides data security by storing vehicular data on the blockchain,which will be used further for congestion detection and mitigation.Numerous devices placed along the road are used to communicate with passing cars and collect their data.The collected data will be compiled periodically to find the average travel time of vehicles and traffic density on a particular road segment.Furthermore,this data will be stored in the memory pool,where other devices will also store their data.After a predetermined amount of time,the memory pool will be mined,and data will be uploaded to the blockchain in the form of blocks that will be used to store traffic statistics.The information is then used in two different ways.First,the blockchain’s final block will provide real-time traffic data,triggering an intelligent traffic signal system to reduce congestion.Secondly,the data stored on the blockchain will provide historical,statistical data that can facilitate the analysis of traffic conditions according to past behavior.

Product Data Management Implementation

On the basis of PDM(product data management) definition and its connotation, the factors to ensure implementation success are analyzed. The definition phase, analysis phase, design phase, build and test phase, and post production phase during PDM implementation are described. The implementation is divided into ten processes, which consist of the above different phases. The relationships between phases and processes are illustrated. Finally, a workflow is proposed to guide the implementing at a fixed price.

Analyses on web-based product data management

This paper is concerned with the development of product data management （PDM） systems--WPDM systems based on web technologies. As a tool to integrate information, traditional PDM system has many benefits for the companies in such aspects as improving design productivity, better control over projects and so on. With the maturing of web technologies, the advantages of WPDM system are obvious. We will show these advantages in detail in Part 3. WPDM system is built on three-tier application model to provide security and flexibility, they are back-end, middle layer and front-end. The basic designs in each layer will be briefly introduced in Part 4. In the future, WPDM will be extended to integrate with other applications to provide a complete web-based engineering environment.

CifNet Network Multi-Well Data Management System

The CifNet network multi-well data management system is developed for 100MB or 1000MB local network environments which are used in Chinese oil industry. The kernel techniques of CifNet system include: 1, establishing a high efficient and low cost network multi-well data management architecture based on the General Logging Curve Theory and the Cif data format; 2, implementing efficient visit and transmission of multi-well data in C/S local network based on TCP/IP protocol; 3,ensuring the safety of multi-well data in store, visit and application based on Unix operating system security. By using CifNet system, the researcher in office or at home can visit curves of any borehole in any working area of any oilfield. The application foreground of CifNet system is also commented.

Big data management in the mining industry

The mining industry faces a number of challenges that promote the adoption of new technologies.Big data,which is driven by the accelerating progress of information and communication technology,is one of the promising technologies that can reshape the entire mining landscape.Despite numerous attempts to apply big data in the mining industry,fundamental problems of big data,especially big data management(BDM),in the mining industry persist.This paper aims to fill the gap by presenting the basics of BDM.This work provides a brief introduction to big data and BDM,and it discusses the challenges encountered by the mining industry to indicate the necessity of implementing big data.It also summarizes data sources in the mining industry and presents the potential benefits of big data to the mining industry.This work also envisions a future in which a global database project is established and big data is used together with other technologies(i.e.,automation),supported by government policies and following international standards.This paper also outlines the precautions for the utilization of BDM in the mining industry.

Blockchain for Transparent Data Management Toward 6G

The wealth of user data acts as a fuel for network intelligence toward the sixth generation wireless networks(6G).Due to data heterogeneity and dynamics,decentralized data management(DM)is desirable for achieving transparent data operations across network domains,and blockchain can be a promising solution.However,the increasing data volume and stringent data privacy-preservation requirements in 6G bring significantly technical challenge to balance transparency,efficiency,and privacy requirements in decentralized blockchain-based DM.In this paper,we investigate blockchain solutions to address the challenge.First,we explore the consensus protocols and scalability mechanisms in blockchains and discuss the roles of DM stakeholders in blockchain architectures.Second,we investigate the authentication and authorization requirements for DM stakeholders.Third,we categorize DM privacy requirements and study blockchain-based mechanisms for collaborative data processing.Subsequently,we present research issues and potential solutions for blockchain-based DM toward 6G from these three perspectives.Finally,we conclude this paper and discuss future research directions.

A web product data management system based on Simple Object Access Protocol

A new web product data management architecture is presented. The three-tier web architecture and Simple Object Access Protocol (SOAP) are combined to build the web-based product data management (PDM) system which includes three tiers: the user services tier, the business services tier, and the data services tier. The client service component uses the server-side technology, and Extensible Markup Language (XML) web service which uses SOAP as the communication protocol is chosen as the business service component. To illustrate how to build a web-based PDM system using the proposed architecture, a case PDM system which included three logical tires was built. To use the security and central management features of the database, a stored procedure was recommended in the data services tier. The business object was implemented as an XML web service so that client could use standard internet protocols to communicate with the business object from any platform. In order to satisfy users using all sorts of browser, the server-side technology and Microsoft ASP.NET was used to create the dynamic user interface.

Research on Product Data Management Based on Multi-agent System

PDM (product data management) is one kind of techniques based on software and database, which integrates information and process related to products. But it is not enough to perform the complication of PDM in enterprises. Then the mechanism to harmonize all kinds of information and process is needed. The paper introduces a novel approach to implement the intelligent monitor of PDM based on MAS (multi agent system). It carries out the management of information and process by MC (monitor center). The paper first puts forward the architecture of the whole system, then defines the structure of MC and its interoperation mode.

Statecharts for Distributed Product Data Management System Modelling

Product data management (PDM) has been accepted as an important tool for the manufacturing industries. In recent years, more and mor e researches have been conducted in the development of PDM. Their research area s include system design, integration of object-oriented technology, data distri bution, collaborative and distributed manufacturing working environment, secur ity, and web-based integration. However, there are limitations on their rese arches. In particular, they cannot cater for PDM in distributed manufacturing e nvironment. This is especially true in South China, where many Hong Kong (HK) ma nufacturers have moved their production plants to different locations in Pearl R iver Delta for cost reduction. However, they retain their main offices in HK. Development of PDM system is inherently complex. Product related data cover prod uct name, product part number (product identification), drawings, material speci fications, dimension requirement, quality specification, test result, log size, production schedules, product data version and date of release, special tooling (e.g. jig and fixture), mould design, project engineering in charge, cost spread sheets, while process data includes engineering release, engineering change info rmation management, and other workflow related to the process information. Accor ding to Cornelissen et al., the contemporary PDM system should contains manageme nt functions in structure, retrieval, release, change, and workflow. In system design, development and implementation, a formal specification is nece ssary. However, there is no formal representation model for PDM system. Theref ore a graphical representation model is constructed to express the various scena rios of interactions between users and the PDM system. Statechart is then used to model the operations of PDM system, Fig.1. Statechart model bridges the curr ent gap between requirements, scenarios, and the initial design specifications o f PDM system. After properly analyzing the PDM system, a new distributed PDM (DPDM) system is proposed. Both graphical representation and statechart models are constructed f or the new DPDM system, Fig.2. New product data of DPDM and new system function s are then investigated to support product information flow in the new distribut ed environment. It is found that statecharts allow formal representations to capture the informa tion and control flows of both PDM and DPDM. In particular, statechart offers a dditional expressive power, when compared to conventional state transition diagr am, in terms of hierarchy, concurrency, history, and timing for DPDM behavioral modeling.

STUDY ON THE BROKEN-ORE DRAWING DATA MANAGEMENT SYSTEM OF SUBLEVEL CAVING

In order to realize the modernized miningmanagementi the authors. based on the practice of a specified mine, developed the application software of the broken ore drawing data management system for sublevel caving through the study on FOXBASE computer language. This paper elabo-rates the overall conception of this system , indicates the main task which should he completed in this system and introduces its module structure and main functions.

Establishment of Person and Enterprise Process Model in Product Data Management System

Before the implementation of product data management (PDM) system, person model and enterprise process model (EPM) must be firstly established. For the convenience of project management, all the related users must be allocated to the “Person User Role Group” net. Based on the person model and the direction of information flow, the EPM is established subsequently. The EPM consists of several release levels, in which the access controls are defined. The EPM procedure shows the blueprint of the workflow process structure. The establishment of person model and EPM in an enterprise has been instanced at the end of this paper.

Organizational Data Management： Proposing a Metadata-Driven Data Warehouse （DW） Model

Discussing the matter of organizational data management implies, almost automatically, the concept of data warehousing as one of the most important parts of decision support system （DSS）, as it supports the integration of information management by aggregating all data formats and provisioning external systems with consistent data content and flows, together with the metadata concept, as one of the easiest ways of integration for software and database systems. Since organizational data management uses the metadata channel for creating a bi-directional flow, when correctly managed, metadata can save both time and resources for organizations. This paperI will focus on providing theoretical aspects of the two concepts, together with a short brief over a proposed model of design for an organizational management tool.

Best Practices and Innovative Scenarios of Integrated Patient Data Management to Improve Continuity of Care and Scientific Research

Clinical data have strong features of complexity and multi-disciplinarity. Clinical data are generated both from the documentation of physicians＇ interactions with the patient and by diagnostic systems. During the care process, a number of different actors and roles （physicians, specialists, nurses, etc.） have the need to access patient data and document clinical activities in different moments and settings. Thus, data sharing and flexible aggregation based on different users＇ needs have become more and more important for supporting continuity of care at home, at hospitals, at outpatient clinics. In this paper, the authors identify and describe needs and challenges for patient data management at provider level and regional- （or inter-organizational-） level, because nowadays sharing patient data is needed to improve continuity and quality of care. For each level, the authors describe state-of-the-art Information and Communication Technology solutions to collect, manage, aggregate and share patient data. For each level some examples of best practices and solution scenarios being implemented in the Italian Healthcare setting are described as well.

The Istituto Nazionale di Geofisica e Vulcanologia Data Management System for the Arctic Sciences

The brokering approach can be successfully used to overcome the crucial question of searching among enormous amount of data （raw and/or processed） produced and stored in different information systems. In this paper, authors describe the Data Management System the DMS （Data Management System） developed by INGV （Istituto Nazionale di Geofisica e Vulcanologia） to support the brokering system GEOSS （Global Earth Observation System of Systems） adopted for the ARCA （Arctic Present Climate Change and Past Extreme Events） project. This DMS includes heterogeneous data that contributes to the ARCA objective （www.arcaproject.it） focusing on multi-parametric and multi-disciplinary studies on the mechanism （s） behind the release of large volumes of cold and fresh water from melting of ice caps. The DMS is accessible directly at the www.arca.rm.ingv.it, or through the IADC （Italian Arctic Data Center） at http：//arcticnode.dta.cnr.it/iadc/gi-portal/index.jsp that interoperates with the GEOSS brokering system （http：//www.geoportal.org0 making easy and fast the search of specific data set and its URL.

Automated Performance Tuning of Data Management Systems with Materializations and Indices

Automated performance tuning of data management systems offer various benefits such as improved performance, declined administration costs, and reduced workloads to database administrators (DBAs). Currently, DBAs tune the performance of database systems with a little help from the database servers. In this paper, we propose a new technique for automated performance tuning of data management systems. Firstly, we show how to use the periods of low workload time for performance improvements in the periods of high workload time. We demonstrate that extensions of a database system with materialised views and indices when a workload is low may contribute to better performance for a successive period of high workload. The paper proposes several online algorithms for continuous processing of estimated database workloads and for the discovery of the best plan for materialised view and index database extensions and of elimination of the extensions that are no longer needed. We present the results of experiments that show how the proposed automated performance tuning technique improves the overall performance of a data management system.

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.

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.