Research on the Application of Computer Network Technology in Electronic Information Engineering

Computer network technology has a very important role in electronic information engineering.The application of this technology not only enriches the traditional information engineering functions,but also effectively guarantees the efficiency and quality.At present,due to the wide variety of external information that Chinese citizens are exposed to,in addition to the variegated and mixed content,it is easy for information to be leaked or stolen.In order to avoid similar situations,it is necessary for people to pay more attention to network system security,so as to ensure that the quality of life of citizens can be guaranteed.In view of that,this paper discusses and analyzes the application of computer network technology in electronic information engineering.

New directions of digitally driven S&T evaluation

Science and Technology(S&T)evaluation plays a baton role in developing science and technology innovation.However,traditional S&T evaluation indicators and methods are difficult to apply effectively in S&T evaluation practice.This paper analyzes the transformation of the S&T evaluation paradigm in the digital environment.Theories,methods,and tools of S&T evaluation research are continuously innovated and optimized;big data becomes the driving force of S&T evaluation development;the role played by S&T evaluation is shifting from a provider of statistical data and information to a participant in S&T decision-making activities.S&T evaluation research should focus on improving data retrieval and organization,knowledge mining and knowledge discovery,and intelligent evaluation models.Moreover,we suggest that scientists carry out S&T evaluation in agreement with the needs of S&T development:1)monitoring and sensing the development of science and technology in real-time with the help of emerging digital technologies;2)exploring solutions to major concerns such as technical project management mechanisms,utilizing advanced data science and digital technologies to identify important scientific frontiers,and leveraging big data in science of science to reveal patterns and characteristics of scientific structures and activities;3)carrying out problem-oriented evaluation research practice focused on four aspects,including intelligent project evaluation,evaluation of the critical technology competitiveness,talent assessment,and diagnostic evaluation of the research entity competitiveness.

A citation iteration method for publications and scientists evaluation

In the last decades many methods have been developed for the evaluation of the quality and impact of both the scientific research papers and scientists.Effectively identifying,discovering,and evaluating high-impact papers using scientometric methods,and adopting reasonable evaluation procedures and methods are vital to stimulating scientists’creative vitality.Examples of methods used for evaluating impact are:h-index and the cited frequency of articles and the number of highly cited papers.Here we propose a new method to assess the scientist impact based on citation iteration.The method was inspired in the Page Rank algorithm.In the present study,both the number of citations and the citing publications after each citation were considered.According to the obtained results,the proposal allows a more accurate measurement of the impact of scientific papers.Also,the application of this method,it can greatly improve the judgment efficiency of high-impact scientists.We have also conducted an empirical study at three levels in the discipline of mathematics,namely the comparisons of two publications,two scientists and eight scientists.Results show that indexes proposed in this dissertation designed for the publications’impacts evaluation and scientists’impact evaluation can be used to find the cause behind the number of cited frequencies resulting in the impact difference.The Q-index for publications’impacts evaluation and F-index for scientists’impacts evaluation proposed in this article can be used more accurately to check and evaluate the impact of scientists.Additionally,these new indexes can be used in the research management of departments at all levels,and can be useful by the states to find leading scientists in several fields.

The scientific applications of big data in science of science

The value of big data in science of science for knowledge discovery is that it can reveal deeper information and knowledge, promote knowledge integration in the whole process of scientific research, guide interdisciplinary integration, and provide new ideas and new methods for knowledge discovery research. This paper discusses the value and role of big data in science of science in knowledge discovery from five aspects, including exploring the laws of scientific research, revealing scientific structure, analyzing scientific research activities, supporting technical recognition and prediction, and serving science and technology evaluation.