Analysis and Modeling of Mobile Phone Activity Data Using Interactive Cyber-Physical Social System

Mobile networks possess significant information and thus are considered a gold mine for the researcher’s community.The call detail records(CDR)of a mobile network are used to identify the network’s efficacy and the mobile user’s behavior.It is evident from the recent literature that cyber-physical systems(CPS)were used in the analytics and modeling of telecom data.In addition,CPS is used to provide valuable services in smart cities.In general,a typical telecom company hasmillions of subscribers and thus generatesmassive amounts of data.From this aspect,data storage,analysis,and processing are the key concerns.To solve these issues,herein we propose a multilevel cyber-physical social system(CPSS)for the analysis and modeling of large internet data.Our proposed multilevel system has three levels and each level has a specific functionality.Initially,raw Call Detail Data(CDR)was collected at the first level.Herein,the data preprocessing,cleaning,and error removal operations were performed.In the second level,data processing,cleaning,reduction,integration,processing,and storage were performed.Herein,suggested internet activity record measures were applied.Our proposed system initially constructs a graph and then performs network analysis.Thus proposed CPSS system accurately identifies different areas of internet peak usage in a city(Milan city).Our research is helpful for the network operators to plan effective network configuration,management,and optimization of resources.

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.

Research on the J2EE-based product database management system

The basic frame and the design idea of J2EE-based Product Data Management (PDM) system are presented. This paper adopts the technology of Object-Oriented to realize the database design and builds the information model of this PDM system. The integration key technology of PDM and CAD systems are discussed, the isomerous interface characteristics between CAD and PDM systems are analyzed, and finally, the integration mode of the PDM and CAD systems is given. Using these technologies, the integration of PDM and CAD systems is realized and the consistence of data in PDM and CAD systems is kept. Finally, the Product Data Management system is developed, which has been tested on development process of the hydraulic generator. The running process is stable and safety.

Systematic review of data-centric approaches in artificial intelligence and machine learning

Artificial intelligence(AI)relies on data and algorithms.State-of-the-art(SOTA)AI smart algorithms have been developed to improve the performance of AI-oriented structures.However,model-centric approaches are limited by the absence of high-quality data.Data-centric AI is an emerging approach for solving machine learning(ML)problems.It is a collection of various data manipulation techniques that allow ML practitioners to systematically improve the quality of the data used in an ML pipeline.However,data-centric AI approaches are not well documented.Researchers have conducted various experiments without a clear set of guidelines.This survey highlights six major data-centric AI aspects that researchers are already using to intentionally or unintentionally improve the quality of AI systems.These include big data quality assessment,data preprocessing,transfer learning,semi-supervised learning,machine learning operations(MLOps),and the effect of adding more data.In addition,it highlights recent data-centric techniques adopted by ML practitioners.We addressed how adding data might harm datasets and how HoloClean can be used to restore and clean them.Finally,we discuss the causes of technical debt in AI.Technical debt builds up when software design and implementation decisions run into“or outright collide with”business goals and timelines.This survey lays the groundwork for future data-centric AI discussions by summarizing various data-centric approaches.

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.

Management Procedures for Data Collected via Intelligent Transportation Systems

Addressing transportation planning, operation and investment challenges requires increasingly sophisticated data and information management strategies. ITS （intelligent transportation systems） and CV （connected vehicle） technologies represent a new approach to capturing and using needed transportation data in real time or near real time. In the case of Michigan, several ITS programs have been launched successfully, but independently of each other. The objective of this research is to evaluate and assess all important factors that will influence the collection, management and use of ITS data, and recommend strategies to develop integrated, dynamic and adaptive data management systems for state transportation agencies.

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.

Comparison of R and Excel in the Field of Data Analysis

This research paper compares Excel and R language for data analysis and concludes that R language is more suitable for complex data analysis tasks.R language’s open-source nature makes it accessible to everyone,and its powerful data management and analysis tools make it suitable for handling complex data analysis tasks.It is also highly customizable,allowing users to create custom functions and packages to meet their specific needs.Additionally,R language provides high reproducibility,making it easy to replicate and verify research results,and it has excellent collaboration capabilities,enabling multiple users to work on the same project simultaneously.These advantages make R language a more suitable choice for complex data analysis tasks,particularly in scientific research and business applications.The findings of this study will help people understand that R is not just a language that can handle more data than Excel and demonstrate that r is essential to the field of data analysis.At the same time,it will also help users and organizations make informed decisions regarding their data analysis needs and software preferences.

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.

Using Python to Analyze Financial Big Data

As technology and the internet develop,more data are generated every day.These data are in large sizes,high dimensions,and complex structures.The combination of these three features is the“Big Data”[1].Big data is revolutionizing all industries,bringing colossal impacts to them[2].Many researchers have pointed out the huge impact that big data can have on our daily lives[3].We can utilize the information we obtain and help us make decisions.Also,the conclusions we drew from the big data we analyzed can be used as a prediction for the future,helping us to make more accurate and benign decisions earlier than others.If we apply these technics in finance,for example,in stock,we can get detailed information for stocks.Moreover,we can use the analyzed data to predict certain stocks.This can help people decide whether to buy a stock or not by providing predicted data for people at a certain convincing level,helping to protect them from potential losses.

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.

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.

CAD-VR geometry and meta data synchronization for design review applications

In this paper we present the MEMPHIS middleware framework for the integration of CAD geometries and assemblies with derived Virtual Reality (VR) models and its specific meta data and attributes. The goal of this work is to connect real time VR applications, especially for the Design Review, with enterprise software storing and managing CAD models (Product Data Man- agement—PDM). The preparation of VR models requires expert knowledge, is time consuming, and includes selection of required CAD data, tessellation, healing of unwanted gaps, applying materials and textures, and special surface and light effects. During the Design Review process, decisions are made concerning the choice of materials and surface forms. While materials can be switched directly on the VR model, the modification of part geometries must be made on the CAD model. Our system synchronizes modi- fications of the original CAD geometries and of attributes that are relevant for the realistic rendering using the PLM Services standard. Thus, repeated work for the VR preparation can be avoided.