Data Scale, Data Scope and Platform Enterprise Performance: Insights from Digital Platform M&As

Data is a key asset for digital platforms,and mergers and acquisitions(M&As)are an important way for platform enterprises to acquire it.The types of data obtained from intra-industry and cross-sector M&As differ,as does the extent to which they interact within or between platforms.The impact of such data on corporate market performance is an important question to consider when selecting strategies for digital platform M&As.Based on our research on advertising-driven platforms,we developed a two-stage Hotelling game model for comparing the market performance effects of intra-industry M&As and cross-sector M&As for digital platforms.We carried out an empirical test using relevant data from advertising-driven digital platforms between 2009 and 2021,as well as a case study on Baidu’s M&A activities.Our research discovered that intra-industry M&As driven by“data economies of scale”and cross-sector M&As driven by“data economies of scope”are both beneficial to the market performance of platform enterprises.Intra-industry M&As have a more significant positive effect on the market performance of platform enterprises because the same types of data are easier to integrate and develop the“network effect of data scale”.From a data factor perspective,this paper reveals the inherent economic logic by which different types of M&As influence the market performance of digital platforms,as well as policymaking recommendations for all digital platforms to select M&A strategies based on data scale,data scope,and the network effect of data.

Digital twin intelligent system for industrial internet of things-based big data management and analysis in cloud environments

This work surveys and illustrates multiple open challenges in the field of industrial Internet of Things(IoT)-based big data management and analysis in cloud environments.Challenges arising from the fields of machine learning in cloud infrastructures,artificial intelligence techniques for big data analytics in cloud environments,and federated learning cloud systems are elucidated.Additionally,reinforcement learning,which is a novel technique that allows large cloud-based data centers,to allocate more energy-efficient resources is examined.Moreover,we propose an architecture that attempts to combine the features offered by several cloud providers to achieve an energy-efficient industrial IoT-based big data management framework(EEIBDM)established outside of every user in the cloud.IoT data can be integrated with techniques such as reinforcement and federated learning to achieve a digital twin scenario for the virtual representation of industrial IoT-based big data of machines and room tem-peratures.Furthermore,we propose an algorithm for determining the energy consumption of the infrastructure by evaluating the EEIBDM framework.Finally,future directions for the expansion of this research are discussed.

Application of Data Governance Models in the Context of the Digital Economy

In the context of the digital economy,the volume of data is growing exponentially,the types of data are becoming more diverse,and its value is increasing,often providing critical support for decision-making by enterprises and government institutions.Effective data governance is a crucial tool for maximizing data value and mitigating data risks.This article examines the application of data governance models in the digital economy,aiming to offer technical insights and guidance for data-driven enterprises and governments in China.By elevating their data governance standards in the new era,this approach will comprehensively enhance their ability to harness digital value and ensure security in the digital economy,ultimately driving the continued growth of both the digital economy and society.

Digital Transformation of Enterprise Human Resource Management Enabled by Big Data

With the continuous development of big data technology,the digital transformation of enterprise human resource management has become a development trend.Human resources is one of the most important resources of enterprises,which is crucial to the competitiveness of enterprises.Enterprises need to attract,retain,and motivate excellent employees,thereby enhancing the innovation ability of enterprises and improving competitiveness and market share in the market.To maintain advantages in the fierce market competition,enterprises need to adopt more scientific and effective human resource management methods to enhance organizational efficiency and competitiveness.At the same time,this paper analyzes the dilemma faced by enterprise human resource management,points out the new characteristics of enterprise human resource management enabled by big data,and puts forward feasible suggestions for enterprise digital transformation.

Research on the Innovativeness and Characteristic of Digital Media under the Environment of Internet and Big Data

In this paper, we conduct survey and research on the innovativeness and characteristic of digital media under the environment of Internet and big data. Under the background of the era of rapid change, the current education system is more severe impact and challenge. Creative industry is the product of cultural industry development to a new stage, is the most creative cultural industry and the origin of the core part of the new economic era of creativity industry is the condition of globalization. The research indicates that the combination of the big data with digital media is necessary and needed. In the future, we will test more related combination and creativeness.

Digital/Data Curation的概念与翻译研究

数字资料的长期保存、复用和增值日益受到学界重视。该文在对国内外Digital/Data Curation概念进行综述的基础上,提出了Digital/Data Curation的一般概念,即Digital/Data Curation是为实现数字资料的复用、共享和增值,数字资料生产者、管理者、消费者和其相关人员主动介入并对数字资料全生命周期进行管理的活动,并建议以"数字/数据理用"作为"Digital/Data Curation"的中文翻译。

Research of data architecture in digital ocean

The characters of marine data, such as multi-source, polymorphism, diversity and large amount, determine their differences from other data. How to store and manage marine data rationally and effectively to provide powerful data support for marine management information system and ＂Digital Ocean＂ prototype system construction is an urgent problem to solve. Different types of system planning data, such as marine resource, marine environment, marine econotny and marine management, and establishing marine data architecture frame with uniform standard are to realize the effective management of all level marine data, such as national marine data, the provincial （municipal） marine data, and meet the need of fundamental information-platform construction.

采用DDN接入INTERNET的3种配置方法

详细讲解了采用DDN接入internet的 3种配置方法 :直接通过路由器访问internet ;通过代理服务器访问internet;采用直接访问与间接访问并存的方式访问internet。并分析了各自的利弊 ,提出采用 2种方式并存的方法为最佳方案。

THE SCHEME FOR THE DATABASE BUILDING AND UPDATING OF 1∶10 000 DIGITAL ELEVATION MODELS

The National Bureau of Surveying and Mapping of China has planned to speed up the development of spatial data infrastructure (SDI) in the coming few years.This SDI consists of four types of digital products,i.e.,digital orthophotos,digital elevation models, digital line graphs and digital raster graphs.For the DEM,a scheme for the database building and updating of 1∶10 000 digital elevation models has been proposed and some experimental tests have also been accomplished.This paper describes the theoretical (and/or technical) background and reports some of the experimental results to support the scheme.Various aspects of the scheme such as accuracy,data sources,data sampling,spatial resolution,terrain modeling,data organization,etc are discussed.

“Deep-time Digital Basin” Based on Big Data and Artificial Intelligence

1 Introduction Information technology has been playing an ever-increasing role in geoscience.Sphisicated database platforms are essential for geological data storage,analysis and exchange of Big Data(Feblowitz,2013;Zhang et al.,2016;Teng et al.,2016;Tian and Li,2018).The United States has built an information-sharing platform for state-owned scientific data as a national strategy.

Digital Continuity Guarantee Approach of Electronic Record Based on Data Quality Theory

Since the British National Archive put forward the concept of the digital continuity in 2007,several developed countries have worked out their digital continuity action plan.However,the technologies of the digital continuity guarantee are still lacked.At first,this paper analyzes the requirements of digital continuity guarantee for electronic record based on data quality theory,then points out the necessity of data quality guarantee for electronic record.Moreover,we convert the digital continuity guarantee of electronic record to ensure the consistency,completeness and timeliness of electronic record,and construct the first technology framework of the digital continuity guarantee for electronic record.Finally,the temporal functional dependencies technology is utilized to build the first integration method to insure the consistency,completeness and timeliness of electronic record.

Source parameters of the Gonghe,Qinghai Province,China,earthquake from inversion of digital broadband waveform data

An earthquake of M S=6.9 occurred in Gonghe County, Qinghai Province, China on April 26, 1990.This earthquake was followed by three larger aftershocks of M S=5.5 on May 7, 1990, M S=6.0 on Jan.3, 1994, and M S=5.7 on Feb.16, 1994, consecutively. The moment tensors of these earthquakes as function of time were obtained by the technique of moment tensor inversion in frequency domain . The results inverted indicate that these earthquakes had a very similar focal mechanism of predominantly reverse faulting on a plane striking NWW, dipping to SSW.The scalar seismic moments of these earthquakes are M 0=9.4×10 18 Nm for the M S=6.9 event, 8.0×10 16 Nm for the M S=5.5 event, 4.9×10 17 Nm for the M S =6.0 event and 2.9×10 17 Nm for the M S=5.7 event, respectively. The results inverted also show that the source processes of these events were significantly different. The main shock had a very complex process, consisting of two distinct sub events with comparable sizes. The first sub event occurred in the first 12s, having a seismic moment of 4.7×10 18 Nm, and the second one continued from 31s to 41s, having a seismic moment of 2.5×10 18 Nm. In addition, a much smaller sub event, having a seismic moment of about 2.1×10 18 Nm, may exist in the interval of 12 s and 31 s, In contrast, the source processes of the three aftershocks are quite simple. The source time function of each of aftershocks is a single impulse, suggestting that each of aftershocks consists of a mainly uninterrupted rupture. The rise times and total rupture durations are 4 s and 11 s for the M S=5.5 event, 6 s and 16 s for the M S= 6.0 event and 6 s and 13 s for the M S=5.7 event, respectively.

Digital Coal Mine Integrated Automation System Based on ControlNet

A three-layer model for digital communication in a mine is proposed. Two basic platforms are discussed: A uniform transmission network and a uniform data warehouse. An actual,ControlNet based,transmission network plat-form suitable for the Jining No.3 coal mine is presented. This network is an information superhighway intended to inte-grate all existing and new automation subsystems. Its standard interface can be used with future subsystems. The net-work,data structure and management decision-making all employ this uniform hardware and software. This effectively avoids the problems of system and information islands seen in traditional mine-automation systems. The construction of the network provides a stable foundation for digital communication in the Jining No.3 coal mine.

Digital Watermark-based Security Technology for Geo-spatial Graphics Data

The paper presents a set of techniques of digital watermarking by which copyright and user rights messages are hidden into geo-spatial graphics data,as well as techniques of compressing and encrypting the watermarked geo-spatial graphics data.The technology aims at tracing and resisting the illegal distribution and duplication of the geo-spatial graphics data product,so as to effectively protect the data producer＇s rights as well as to facilitate the secure sharing of geo-spatial graphics data.So far in the CIS field throughout the world,few researches have been made on digital watermarking.The research is a novel exploration both in the field of security management of geo-spatial graphics data and in the applications of digital watermarking technique.An application software employing the proposed technology has been developed.A number of experimental tests on the 1：500,000 digital bathymetric chart of the South China Sea and 1：10,000 digital topographic map of Jiangsu Province have been conducted to verify the feasibility of the proposed technology.

Estimation of Fractional Vegetation Cover Based on Digital Camera Survey Data and a Remote Sensing Model

The objective of this paper is to improve the monitoring speed and precision of fractional vegetation cover (fc). It mainly focuses on fc estimation when fcmax and fcmin are not approximately equal to 100% and 0%, respectively due to using remote sensing image with medium or low spatial resolution. Meanwhile, we present a new method of fc estimation based on a random set of fc maximum and minimum values from digital camera (DC) survey data and a di- midiate pixel model. The results show that this is a convenient, efficient and accurate method for fc monitoring, with the maximum error -0.172 and correlation coefficient of 0.974 between DC survey data and the estimated value of the remote sensing model. The remaining DC survey data can be used as verification data for the precision of the fc estimation. In general, the estimation of fc based on DC survey data and a remote sensing model is a brand-new development trend and deserves further extensive utilization.

Review on status of groundwater database and application prospect in deep-time digital earth plan

Groundwater is an important water resource.The total amount of active groundwater in a hydrological cycle is about 3.5 times that of the total amount of surface water.The information in the deep groundwater records the material exchange and dynamics in the earth’s evolution,which is an important aspect of the Deep-Time Digital Earth(DDE)plan.In recent years,scientists have discussed the distribution of transboundary aquifers and the environmental significance of groundwater resources through groundwater databases established by international organizations,such as the Global Groundwater Information System and the chronicles consortium,and national institutes,such as national geological surveys.The application of the groundwater database in the DDE plan,however,has been limited by the management,interactivity,and monitoring method of the groundwater data.The ability to further integrate data that are private and scattered across research institutions and individuals,while establishing an open,unified,and shared groundwater data platform,is essential to enhance our understanding of groundwater,ranging from shallow to deep water,which is a goal of the DDE plan.In this study,we introduced the current situation of groundwater database operations in domestic and international research and provided frontier research with groundwater big data.Considering the related objectives of the DDE plan and the limitations of existing groundwater databases,we proposed an improvement plan and new prospects for applying groundwater databases in the research of the deep earth.

Smart Data for Digital Humanities

The emergence of ＂Big Data＂ has been a dramatic development in recent years. Alongside it, a lesser-known but equally important set of concepts and practices has also come into being--＂Smart Data.＂ This paper shares the author＇s understanding of what, why, how, who, where, and which data in relation to Smart Data and digital humanities. It concludes that, challenges and opportunities co-exist, but it is certain that Smart Data, the ability to achieve big insights from trusted, contextualized, relevant, cognitive, predictive, and consumable data at any scale, will continue to have extraordinary value in digital humanities.

Performance of digital data acquisition system in gamma-ray spectroscopy

A newly developed digital data acquisition system,which is based on the digital pulse processor Pixie-16 modules by XIA LLC,was tested with the c-ray detector array of the China Institute of Atomic Energy using the cray source and in-beam c-rays.A comparison between this digital data acquisition system and the conventional analog data acquisition system was made.At a low count rate,both systems exhibit good and comparable energy resolutions.At a high count rate above 8.8 k/s,while the energy resolution obtained by the analog system deteriorates significantly,the energy resolution obtained by the digital system is nearly unchanged.Meanwhile,experimental data with higher statistics can be collected by the digital system.The advantage of this digital system over the conventional analog system can be ascribed to its excellent capability of handling pile-up pulses at higher count rates,and the fact that it has nearly no dead time in data transmission and conversion.

Data Security Storage Model of the Internet of Things Based on Blockchain

With the development of information technology,the Internet of Things(IoT)has gradually become the third wave of the worldwide information industry revolution after the computer and the Internet.The application of the IoT has brought great convenience to people’s production and life.However,the potential information security problems in various IoT applications are gradually exposed and people pay more attention to them.The traditional centralized data storage and management model of the IoT is easy to cause transmission delay,single point of failure,privacy disclosure and other problems,and eventually leads to unpredictable behavior of the system.Blockchain technology can effectively improve the operation and data security status of the IoT.Referring to the storage model of the Fabric blockchain project,this paper designs a data security storage model suitable for the IoT system.The simulation results show that the model is not only effective and extensible,but also can better protect the data security of the Internet of Things.

Digital Forensics and Cyber Crime Datamining

Digital forensics is the science of identifying, extracting, analyzing and presenting the digital evidence that has been stored in the digital devices. Various digital tools and techniques are being used to achieve this. Our paper explains forensic analysis steps in the storage media, hidden data analysis in the file system, network forensic methods and cyber crime data mining. This paper proposes a new tool which is the combination of digital forensic investigation and crime data mining. The proposed system is designed for finding motive, pattern of cyber attacks and counts of attacks types happened during a period. Hence the proposed tool enables the system administrators to minimize the system vulnerability.