Construction and Application Exploration of Smart Agriculture Based on Big Data Technology

Big data finds extensive application and many fields.It brings new opportunities for the development of agriculture.Using big data technology to promote the development of smart agriculture can greatly improve the effect of agricultural planting,reduce the input of manpower and material resources,and lay a solid foundation for the realization of agricultural modernization.In this regard,this paper briefly analyzes the construction and application of smart agriculture based on big data technology,hoping to provide some valuable insights for readers.

Analysis of the Impact of Big Data Technology on Environmental Pollution Control Audit

As China strives towards the second centenary goal,increasing attention is being paid to environmental pollution and other related issues.Concurrently,with the rapid development of big data technology,many big data solutions have been applied to environmental pollution control audits,exerting a significant impact.This paper presents the current situation of environmental pollution audits,summarizing the application of big data from the perspectives of both domestic and international research.In terms of data collection and data analysis for environmental pollution audits,cloud platform technology,and visualization technology are selected based on multiple data sources.The impact in the field of environmental pollution control audits is further analyzed.It is found that the environmental pollution audit cloud platform is not yet perfect,the technical skills of audit personnel are insufficient,and some technologies are not mature.Relevant suggestions are put forward to provide a reference for the future development of big data technology and its integration with environmental pollution control audits.

From Big Data to Intelligent Tutoring: Exploring the Application of Big Data Technology in the Ideological and Political Education for College Counselors

This paper explores the application of big data technology in ideological and political education for college counselors.Big data-driven personalized counseling for students,social network analysis,and public opinion monitoring can optimize the efficiency of counselor work.However,there are still challenges concerning data privacy protection,technical support,and training.By scientifically evaluating and addressing these challenges,big data technology is expected to enhance the effectiveness of college counselors and improve the quality of ideological and political education.In the future,with technological advancements,big data technology will become an essential tool for higher education management.

A Practical Study of Big Data Technology in Computer Network Information Security Processing

In recent years,China has witnessed continuous development and progress in its scientific and technological landscape,with widespread utilization of computer networks.Concurrently,issues related to computer network information security,such as information leakage and virus invasions,have become increasingly prominent.Consequently,there is a pressing need for the implementation of effective network security measures.This paper aims to provide a comprehensive summary and analysis of the challenges associated with computer network information security processing.It delves into the core concepts and characteristics of big data technology,exploring its potential as a solution.The study further scrutinizes the application strategy of big data technology in addressing the aforementioned security issues within computer networks.The insights presented in this paper are intended to serve as a valuable reference for individuals involved in the relevant fields,offering guidance on effective approaches to enhance computer network information security through the application of big data technology.

Research on the Construction of Application-Oriented Undergraduate Data Science and Big Data Technology Courses

In order to conduct research and analysis on the construction of application-oriented undergraduate data science and big data technology courses,the professional development characteristics of universities and enterprises should be taken into consideration,the development trend of the big data industry should be scrutinized,and professional application-oriented talents should be cultivated in line with job requirements.This paper expounds the demand for capacity-building professional development in application-oriented undergraduate data science and big data technology courses,conducts research and analysis on the current situation of professional development,and puts forward strategies in hope to provide reference for capacity-building professional development.

Climatic and Environmental Characteristics of Beijing Based on Rapid Processing Technology of Urban Meteorological Big Data

The meteorological big data in Beijing area are typical multi-dimensional big data containing spatiotemporal characteristics,which have important research value for researches related to urban human settlement environment.With the help of computer programming and software processing,big data crawling,integration,extraction and multi-dimensional information fusion can be realized quickly and effectively,so as to obtain the data set needed for research and realize the target of visualization.Through big data analysis of wind environment,thermal environment and total atmospheric suspended particulate pollutants in Beijing area,it was found that the average wind speed in Beijing area decreased signifi cantly in recent 40 years,while the surface temperature increased signifi cantly;urban heat island effect was signifi cant,and the phenomenon of atmospheric suspended particulate pollution was relatively common.The spatial distribution of the three climatic and environmental data was not balanced and had signifi cant regularity and correlation.Improving urban ventilation corridors and improving urban ventilation capacity is a feasible way to improve urban heat island effect and reduce urban climate issues such as atmospheric particulate pollution.

The Influence of Built Environment on the Spatial Distribution of Housing Price:Based on Multiple Big Data and Hedonic Model

In recent years,more and more researches focus on the self characteristics and spatial location of housing,and explore the influencing factors of urban housing price from the micro perspective.As representative of big cities,spatial distribution pattern of housing price in national central cities has attracted much attention.In order to return the spatial distribution pattern of housing price to the research on influencing factors of housing price,the reasons behind the spatial distribution pattern of housing price in three national central cities:Beijing,Wuhan and Chongqing are explored.The results show that①urban housing price is affected by many factors.Due to different social and economic conditions in each city,there are differences in the influence direction of the proximity to expressways,city squares,universities and living facilities,characteristics of companies and enterprises on Beijing,Wuhan and Chongqing.②Various factors have different value-added effects on housing price in different cities.The location of ring line in Beijing and Wuhan has the greatest increase effect on housing price,while metro station of Chongqing has the greatest increase effect on housing price.

Improving Performance of Cloud Computing and Big Data Technologies and Applications

Cloud computing technology is changing the development and usage patterns of IT infrastructure and applications. Virtualized and distributed systems as well as unified management and scheduling has greatly im proved computing and storage. Management has become easier, andOAM costs have been significantly reduced. Cloud desktop technology is develop ing rapidly. With this technology, users can flexibly and dynamically use virtual ma chine resources, companies＇ efficiency of using and allocating resources is greatly improved, and information security is ensured. In most existing virtual cloud desk top solutions, computing and storage are bound together, and data is stored as im age files. This limits the flexibility and expandability of systems and is insufficient for meetinz customers＇ requirements in different scenarios.

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.

Research on the Teaching Reform of “Big Data Analysis and Visualization” Course for College Students

Under the background of the big data era,the education of big data majors is undergoing a profound teaching reform and innovation.With the increasing role of big data technology in analysis and decision-making,updating and expanding the teaching content of big data majors has become particularly important.In the era of big data,modern enterprises have put forward new and higher demands for big data talents,which not only include traditional data analysis skills but also knowledge of data visualization and information technology.To address these challenges,big data education needs to reform and innovate in the development and utilization of teaching content,methods,and resources.This paper proposes teaching models and reform methods for big data majors and analyzes corresponding teaching reforms and innovations to meet the requirements of the new development of big data majors.The traditional classroom teaching method is no longer sufficient to meet the learning needs of students,and more dynamic and interactive teaching methods,such as case studies,flipped classrooms,and project-based learning,are becoming increasingly essential.These innovative teaching methods can more effectively cultivate students’practical operation skills and independent thinking while allowing them to better learn advanced knowledge in a real big-data environment.In addition,the paper also discusses the construction of big data processing and analysis platforms,as well as innovative teaching management and evaluation systems to improve teaching quality.

The Influence of Financial Technology on the Business of Commercial Banks and Measure Suggestions

With the continuous development and improvement of financial technology,commercial banks are facing huge impacts and challenges brought about by financial technology,but what follows is a huge opportunity for the transformation of commercial banks.Therefore,this research analyzes the four aspects of the impact of financial technology on commercial banks,and explores the challenges that financial technology brings to commercial banks’development strategies,traditional businesses,and business processes.For the measures taken,commercial banks need to improve the financial technology-related infrastructure,and improve the main functions of supervision technology and the transformation of cultural values.This research provides theoretical basis and implementation suggestions for the transformation of commercial banks through theoretical research.

Planning of electric vehicle charging infrastructure under the Background of Big Data

Today, the problems of power consumption and environmental pollution caused by road trafficare very serious. Automobiles produce large amounts of carbon monoxide and nitrogen, dust,and particles, which are the primary user of the fuel. Unconventional design methods will preventthe international process of replacing fuel-filled vehicles with electric vehicles. The promotionand adoption of electric vehicles can effectively alleviate these problems, but the planning ofelectric vehicle charging facilities needs to be resolved as soon as possible. The state-of-the-artmodeand power model of public charging equipment proposed in this paper can solve the problemof positioning charging equipment in large-scale transmission networks and research onrelated charging materials and location planning and energy model design methods that arebeneficial to the future development.

Call for Papers Special Issue of Tsinghua Science and Technology on Cloud Computing and Big Data

The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenting the state-of-art scientific achievements in computer science and other IT fields. One paper on Cloud Computing published in Vol. 18, Issue. 1, 2013, has been ranked the top of IEEE download list continuously for five months：

Call for Papers Special Issue of Tsinghua Science and Technology on Cloud Computing and Big Data

The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenting the state-of-art scientific achievements in computer science and other IT fields. One paper on Cloud Computing published in Vol. 18, Issue 1, 2013, has been ranked No. 1 of IEEE download list continuously for five months： http：//ieeexplore.ieee.org/xpl/browsePopular.jsp？topArticlesDate=August＋2013.

Location correction technique based on mobile communication base station for earthquake population heat map

China has mobile phone penetration rate of over 96.2%.Mobile phone has become the largest Internet terminal for Chinese Internet users.Population geographic distribution in earthquake zones can be got based on mobile phone positioning and map matching.For reducing earthquake black-box stage,we propose a real-time collection,correction and schedule algorithm of population position data by four stream processing environments(Redis,Hbase,Kafka,and Spark Streaming)in this paper.For labeling precisely population geographic distribution on the network map,matching of population geographic coordinates and map coordinates are optimized by sample comparison based on location data of mobile communication base stations and prefecture level cities.The test result shows the proposed system is high efficient and can rapidly respond to any emerging parallel tasks during the earthquake.A high-precision heat map of affected population can be produced and published on-line within 2 min after the devastating earthquake happened.

Realization and application of geological cloud platform

In recent years,with the progress of computer technology,some traditional industries such as geology are facing changes in industrial structure and application mode.So we try to apply big data and virtualization technology in the field of geoscience.This study aims at addressing the existing problems in geological applications,such as data sharing,data processing and computing performance.A Geological Cloud Platform has been designed and realized preliminarily with big data and virtualization technology.The application of the Geological Cloud Platform can be divided into two parts:1)to nest the geological computing model in cloud platform and visualize the results and 2)to use relevant software to conduct data analysis and processing in virtual machines of Windows or Linux system.Finally,we prospect Carlin-type deposits in Nevada by using the spatial data model ArcSDM in the virtual machine.

Credit Risk Analysis of Chinese Companies by Applying the CAFÉApproach

It is known that the current Credit Rating in financial markets of China is facing at least three problems:1)the rating is falsely high;2)the differentiation of credit rating is insufficient;and 3)the poor performance of predicting early warning,thus we must consider how to create a reasonable new credit risk analysis approach to deal with issues for financial markets in China for those listed companies’performance.This report shows that by using a newmethod called the“Hologram approach”as a tool,we are able to establish a so-called“CAFÉRisk Analysis System”(in short,“CAFÉApproach”,or“CAFÉ”)to resolve three issues for credit rating in China.In particular,the main goal in this paper is to give a comprehensive report for credit risk assessments for eight selected list companies by applying our“CAFÉ”from different industry sectors against actual market performance with the time period from the past one to three years through our one-by-one interpretation for event screening and true occurrence and related events.In this way,we show how“CAFÉ”is able to resolve current three major problems of“rating is falsely high,the differentiation of credit rating grades is insufficient,and the poor performance of predicting early warning”in the current credit market in China’s financial industry in practice.