Analysis and Enlightenment of Big Data Platform for Adverse Drug Reaction Supervision in China and the United States

Objective To introduce the relevant big data platforms of FDA regulatory sciences and to provide reference for the construction of big data platform for China’s regulatory science under the“14th five-year plan”to deepen the reform of medical and health system.Methods A comparative analysis was made on China’s big data for regulatory science after studying the development process,operation mode,practical significance and characteristics of the big data platform for FDA regulatory science,which would help China to establish a perfect big database.Results and Conclusion The construction of big data platform for China’s regulatory science is not comprehensive compared with that in the United States.It is necessary to build data platforms in line with China’s national conditions through efforts in law,talents,standards,and other aspects.

Modified Buffalo Optimization with Big Data Analytics Assisted Intrusion Detection Model

Lately,the Internet of Things(IoT)application requires millions of structured and unstructured data since it has numerous problems,such as data organization,production,and capturing.To address these shortcomings,big data analytics is the most superior technology that has to be adapted.Even though big data and IoT could make human life more convenient,those benefits come at the expense of security.To manage these kinds of threats,the intrusion detection system has been extensively applied to identify malicious network traffic,particularly once the preventive technique fails at the level of endpoint IoT devices.As cyberattacks targeting IoT have gradually become stealthy and more sophisticated,intrusion detection systems(IDS)must continually emerge to manage evolving security threats.This study devises Big Data Analytics with the Internet of Things Assisted Intrusion Detection using Modified Buffalo Optimization Algorithm with Deep Learning(IDMBOA-DL)algorithm.In the presented IDMBOA-DL model,the Hadoop MapReduce tool is exploited for managing big data.The MBOA algorithm is applied to derive an optimal subset of features from picking an optimum set of feature subsets.Finally,the sine cosine algorithm(SCA)with convolutional autoencoder(CAE)mechanism is utilized to recognize and classify the intrusions in the IoT network.A wide range of simulations was conducted to demonstrate the enhanced results of the IDMBOA-DL algorithm.The comparison outcomes emphasized the better performance of the IDMBOA-DL model over other approaches.

Internet big data and capital markets:a literature review

Background:Research in various academic disciplines has undergone tremendous changes in the era of big data.Everyone is talking about big data nowadays,but how exactly is it being applied in research on financial studies?Results:This study summarizes the sources of Internet big data for research related to capital markets and the analytical methods that have been used in the literature.In addition,it presents a review of the research findings based on Internet big data in the field of capital markets and proposes suggestions for future studies in which big data can be applied to examine issues related to capital markets.Conclusion:(1)Internet big data sources related to present capital market research can be categorized into forum-type data,microblog-type data and search class data.(2)As for research about investors’sentiments on the basis of Internet big data,the main methods of sentiment analysis include building an inventory of lexical categories,using dictionaries for analysis of lexical categories,and machine learning.(3)Many studies address whether Internet big data can predict capital markets.However,they reach no consistent conclusions,which could be due to limitations of sample and analysis method used.(4)Data collection technique and analysis methods require further improvements.

Application of Big Data in Agricultural Informationization in Shandong Province under the Background of "Internet +"

This paper explains the basic concepts of " Internet + " and big data,analyzes the main problems in the application of big data technology in agricultural informationization of Shandong Province,summarizes corresponding solutions from the aspects of government guidance,financial input,open sharing of agricultural big data,big data storage and processing,data mining,etc.,and prospects the application trend of big data technology in agricultural informationization to achieve the connotative development of agriculture in Shandong Province.

Research on the Application of Energy Internet Big Data in Integrated Energy Market

Energy Internet is deeply integrated by Internet concept, information technology and energy industry, and Energy Internet Big Data are one of core technologies that achieve energy-information-economic interconnection and improve the development and evolution of Energy Internet. This paper describes the concept and characteristics of Energy Internet Big Data, and feasibility of applying Energy Internet Big Data to integrated energy market. On this basis, as for integrated energy market and multi-subjects of Energy Internet, typical application and technical system based on Energy Internet Big Data in integrated energy market is put forward, which provides a reference for the analysis and decision of integrated energy market in Energy Internet.

Discussion on the Construction of Spatiotemporal Big Data Platform for Smart City

The so-called smart city is a new form of information technology that is achieved through the integration of the contemporary advanced big data technology,Internet of Things technology,cloud computing technology,and spatial geographic information.At present,the application of this technology is important for the urban construction,planning,and services as well as management.This technology also provides great convenience in these aspects,which has allowed the cities to develop and transform towards the direction of smart cities.Based on this situation,the construction of spatiotemporal big data platforms in smart cities was analyzed in this article,and this analysis may provide a reference for the construction and development of todays smart cities.

Application of Big Data Information Platform in Medical Equipment

The application of big data in the medical device industry mainly refers to the analysis and processing of various medical devices,so as to provide patients with better treatment and rehabilitation services.At present,our country already has a relatively mature and reliable large database system.This article studies the application of medical equipment in the big data information platform.The main methods used in this article are survey method,case analysis method,and interview method.The big data information platform and medical devices are studied from different aspects.The survey results show that 41%of people completely agree with the role of big data information platforms in medical devices.

Overview of Construction and Application of Big Data Analysis Platform

Big data technology is widely spread around the world,and is constantly developing and applying.In order to enhance the application value of big data analysis platform,it is necessary to constantly improve the data analysis and processing capacity of big data platform,so as to build a complete data analysis platform,realize resource sharing and real-time data collection.As a key point of contemporary information development,big data analysis platform is of great significance to promote social data exchange.Based on this,this paper focuses on two aspects:first,it describes the construction process and content of big data platform;second,it summarizes the relevant application and development of big data platform for reference.

A Distributed Approach of Big Data Mining for Financial Fraud Detection in a Supply Chain

Supply Chain Finance(SCF)is important for improving the effectiveness of supply chain capital operations and reducing the overall management cost of a supply chain.In recent years,with the deep integration of supply chain and Internet,Big Data,Artificial Intelligence,Internet of Things,Blockchain,etc.,the efficiency of supply chain financial services can be greatly promoted through building more customized risk pricing models and conducting more rigorous investment decision-making processes.However,with the rapid development of new technologies,the SCF data has been massively increased and new financial fraud behaviors or patterns are becoming more covertly scattered among normal ones.The lack of enough capability to handle the big data volumes and mitigate the financial frauds may lead to huge losses in supply chains.In this article,a distributed approach of big data mining is proposed for financial fraud detection in a supply chain,which implements the distributed deep learning model of Convolutional Neural Network(CNN)on big data infrastructure of Apache Spark and Hadoop to speed up the processing of the large dataset in parallel and reduce the processing time significantly.By training and testing on the continually updated SCF dataset,the approach can intelligently and automatically classify the massive data samples and discover the fraudulent financing behaviors,so as to enhance the financial fraud detection with high precision and recall rates,and reduce the losses of frauds in a supply chain.

Tobacco control challenges in China: Big data analysis of online tobacco marketing information

Objective:To develop tobacco control strategies by analyzing online tobacco marketing information in China.Methods:Using web-crawler software,this study acquired 106,485 pieces of online tobacco marketing information published on 11 different Internet platforms including Weibo,WeChat,Baidu,etc.,from January-June 2018.The data were used to investigate the characteristics and social networks of online tobacco marketing via content and social network analysis.Results:The total volume of online tobacco marketing during the study period was high,showing a positive trend.Of all the marketing subjects,those involving"flavor capsule","Marlboro",and"Esse"were the most popular.The Weibo platform had the highest volume of online tobacco marketing information as well as the largest proportion of explicit marketing information.This was followed by other social media platforms such as Baidu Search,Baidu Tieba,and Xiaohongshu,where implicit marketing information predominated.The overall network structure of tobacco websites exhibited a significant centralization feature,where traditional and novel tobacco websites formed two clusters with almost no intersections.The China Tobacco Science and Education Website(http://www.tobaccoinfo.com.cn/)and E-Cigarette Home(http://ecigm.com/)were the two nodes of the highest degree centrality within the respective"circle",while the China Tobacco Monopoly Bureau Website(http://www.tobacco.gov.cn/)was the node with the highest closeness centrality.By contrast,Baidu Tieba's overall network structure was more decentralized,and the degree of correlation between different nodes was relatively low.Conclusion:Online tobacco marketing demonstrated high volumes and wide coverage,and an intertwined network,thereby creating major obstacles for tobacco control.To address this issue,the government should strengthen network supervision of tobacco marketing and revise its current regulations.Meanwhile,Internet platforms should improve self-regulation by comprehensively removing and blocking tobacco-related information.Lastly,the media and public should advocate associated policies and support Internet platform supervision.

Research on the Relationship Between Garlic and Young GarlicShoot Based on Big Data

In view of the problems such as frequent fluctuation of garlic price, lack ofefficient forecasting means and difficulty in realizing the steady development of garlicindustry, combined with the current situation of garlic industry and the collected datainformation. Taking Big Data platform of garlic industry chain as the core, using themethods of correlation analysis, smoothness test, co-integration test, and Grangercausality test, this paper analyzes the correlation, dynamic, and causality between garlicprice and young garlic shoot price. According to the current situation of garlic industry,the garlic industry service based on Big Data is put forward. It is concluded that there is apositive correlation between garlic price and young garlic shoot price, and there is a longtermstable dynamic equilibrium relationship between young garlic shoot price and garlicprice fluctuation, and young garlic shoot price can affect garlic price. Finally, it isproposed to strengthen the infrastructure construction of garlic Big Data, increase thetechnological innovation and application of garlic Big Data technology, and promote thesafety and security ability of the whole industry to promote the development of garlicindustry.

The Roles of 5G Mobile Broadband in the Development of IoT, Big Data, Cloud and SDN

The fast technology development of 5G mobile broadband (5G), Internet of Things (IoT), Big Data Analytics (Big Data), Cloud Computing (Cloud) and Software Defined Networks (SDN) has made those technologies one after another and created strong interdependence among one another. For example, IoT applications that generate small data with large volume and fast velocity will need 5G with characteristics of high data rate and low latency to transmit such data faster and cheaper. On the other hand, those data also need Cloud to process and to store and furthermore, SDN to provide scalable network infrastructure to transport this large volume of data in an optimal way. This article explores the technical relationships among the development of IoT, Big Data, Cloud, and SDN in the coming 5G era and illustrates several ongoing programs and applications at National Chiao Tung University that are based on the converging of those technologies.

Data Resource Management Platform of Paper-making Mill Equipment Operation based on Hadoop

Aiming at the ″Made in China 2025″ strategy proposed by the state and combining with the popular the Internet, Internet of things, big data, machine learning and other technologies, Hadoop-based open source framework is adopted to realize the equipment data resource management platform of paper-making mill equipment. In this paper, the main function module of the platform is introduced, and some of operational effect map from the C paper-making mill are shown, and the key technologies in the platform construction is studied. It proposal to combine the internet, the internet of things, big data and machine learning to improve the informatization of the paper-making mill equipment, and ensure production safety, optimize technological process, improve product competitiveness, and also provide the theoretical guidance and practical basis for constructing the similar projects.

Design and Implementation of the Sense Egypt Platform for Real-Time Analysis of IoT Data Streams

Nowadays, we experience an abundance of Internet of Things middleware solutions that make the sensors and the actuators are able to connect to the Internet. These solutions, referred to as platforms to gain a widespread adoption, have to meet the expectations of different players in the IoT ecosystem, including devices [1]. Low cost devices are easily able to connect wirelessly to the Internet, from handhelds to coffee machines, also known as Internet of Things (IoT). This research describes the methodology and the development process of creating an IoT platform. This paper also presents the architecture and implementation for the IoT platform. The goal of this research is to develop an analytics engine which can gather sensor data from different devices and provide the ability to gain meaningful information from IoT data and act on it using machine learning algorithms. The proposed system is introducing the use of a messaging system to improve the overall system performance as well as provide easy scalability.

Analysis on the Impact of Big Data on Management Accounting

In recent years,big data has developed rapidly,and it would have a specific impact on the development of management accounting.In order to ensure the smooth development of management accounting,it is necessary to recognize the influence of big data on it and scientifically use the essential advantages of big data.By exploring and analyzing the main characteristics of big data,the article describes the impact of big data on management accounting and puts forward effective strategies to efficiently carry out management accounting under the environment of big data.

Foundation Treatment in Urban Underground Engineering Using Big Data Analysis for Smart City Applications

A core element of the sustainable approach to global living quality improvement can now become the intensive and organized usage of underground space.There is a growing interest in underground building and growth worldwide.The reduced consumption of electricity,effective preservation of green land,sustainable wastewater and sewage treatment,efficient reverse degradation of the urban environment,and reliable critical infrastructure management can improve the quality of life.At the same time,technological innovations such as artificial intelligence(AI),cloud computing(CC),the internet of things(IoT),and big data analytics(BDA)play a significant role in improved quality of life.Hence,this study aims to integrate the technological innovations in urban underground engineering to ensure a high quality of life.Thus,this study uses big data analytics to carry out the status quo of foundation treatment and proposes a conceptual framework named the BDA with IoT on urban underground engineering(BI0T-UUE).This framework connects hidden features with various high-level sensing sources and practical predictive model characterization to lower building costs,productive infrastructure management,preparedness for disasters,and modern community smart services.The IoT integration gives an optimum opportunity to work towards the functionality of‘‘digital doubles’’of secret infrastructure,both economical and scalable,with the increasing sophistication and tooling of the underworld.The simulation analysis ensures the highest efficiency and cost-effectiveness of the underground engineering with a value of 96.54%and 97.46%.

Preliminary build and application of a data analysis platform for coiled tubing steel strips

To solve the problems in the quality control and improvement of coiled tubing steel strips production, such as scattered and inefficient production data, difficult performance fluctuation factor analysis, complex multivariate statistical analysis, and low accuracy and difficulty in mechanical property prediction, an industrial data analysis platform for coiled tubing steel strips production has been preliminarily developed.As the premise and foundation of analysis, industrial data collection, storage, and utilization are realized by using multiple big data technologies.With Django as the agile development framework, data visualization and comprehensive analyses are achieved.The platform has functions including overview survey, stability analysis, comprehensive analysis(such as exploratory data analysis, correlation analysis, and multivariate statistics),precise steel strength prediction, and skin-passing process recommendation.The platform is helpful for production overviewing and prompt responding, laying a foundation for an in-depth understanding of product characteristics and improving product performance stability.