Keywords Retrieval Research Articles

Meta-Analysis of the Effect of Exercise Intervention on Improving the Executive Function of College Students

Objective To systematically evaluate the effects of different exercise styles on executive function of college students through a meta-analysis of relevant literatures at home and abroad, and to provide evidence-based reference for future studies on mental health and teaching. Method to "aerobic exercise" and "movement" executive function, "cognitive" "college students/female college students" "aerobic exercise/exercise" seven "executive function" keywords retrieval at home and abroad, such as database, retrieval time for January 2021. Literature screening was conducted, and a total of 6 relevant studies were included with high literature quality scores. Meta-analysis was performed on the fixed model. Results The combined effect size of exercise intervention on inhibition function of college students [SMD=2.73, 95%CI: 0.99 ~ 3.48, P < 0.01]. The combined effect size of exercise intervention on refresh function of college students [SMD=-82.52, 95%CI:-127.89 ~ -37.15, P < 0.01]; the combined effect size of exercise intervention on the conversion function of college students [SMD=-98.48, 95%CI:-168.56 ~ -28.39, P < 0.01]. Conclusion Aerobic exercise and bicycle can effectively improve the executive function of college students, while resistance exercise has no improvement effect. the exercise intervention of 30-50min/time has the best effect on improving the inhibition function, conversion function and refresh function of college students. The short-term intervention of 1-2 weeks or the intervention of 8 weeks can improve the inhibition function, conversion function and refresh function of college students. there is no gender difference in the improvement effect of exercise intervention on executive function of college students.

Patent Retrieval Method Based on Similarity Calculation of a Single Patent

For reverse engineering or infringement avoiding design, designers have to access relevant patents efficiently and accurately based on a specific patent (referred to “the target patent” below) in hand. A retrieval method based on a single patent is proposed. A batch of patents (referred to “the preliminary patents” below) is obtained by the keywords retrieval and retrieved again using the target patent. Then the most similar patents to the target patent are acquired by similarity calculation and sorted by the values. The effect of keyword form and its location on the similarity calculation is considered. The efficiency and accuracy of the improved algorithm are verified by tests.

Efficient Multi-keyword Ranked Search over Outsourced Cloud Data based on Homomorphic Encryption

With the development of cloud computing, more and more data owners are motivated to outsource their data to the cloud server for great flexibility and less saving expenditure. Because the security of outsourced data must be guaranteed, some encryption methods should be used which obsoletes traditional data utilization based on plaintext, e.g. keyword search. To solve the search of encrypted data, some schemes were proposed to solve the search of encrypted data, e.g. top-k single or multiple keywords retrieval. However, the efficiency of these proposed schemes is not high enough to be impractical in the cloud computing. In this paper, we propose a new scheme based on homomorphic encryption to solve this challenging problem of privacy-preserving efficient multi-keyword ranked search over outsourced cloud data. In our scheme, the inner product is adopted to measure the relevance scores and the technique of relevance feedback is used to reflect the search preference of the data users. Security analysis shows that the proposed scheme can meet strict privacy requirements for such a secure cloud data utilization system. Performance evaluation demonstrates that the proposed scheme can achieve low overhead on both computation and communication.

Knowledge System Development Based on the Primitives of Sheet Metal

Through the sheet metal digital information classification, induces the 2D graphics, 3D model, data forms, the information such as process design chart, file information is automatic extracted and meta data description information is interactively supplemented , data is stored in the database records, two kinds of query is designed for recorded data query and keywords retrieval methods.Engineering database system designed to define meta data, storage, retrieval, information coding and classification of four levels, combined with the engineering application of system requirements and function module design,interface of sheet metal unfolding system is developed.The system improve the design capability of sheet metal enterprises, reduce manufacturing cost, enhance the capacity of information management .

The Research of XML Keyword Retrieval Algorithms Based on MapReduce

In this paper, from the perspective of XML data management, first in the HDFS store large amount of data and XML data based on XML data query rewrite the traditional framework of MapReduce process, the design of large amount of data XML data set keywords retrieval algorithm, contain XML data classification and coding, index and search a four parts, solve the large amount of data of the XML document keywords retrieval problem. Then the design and implementation based on MapReduce of large amount of data XML keyword query system.

Research on Intelligent Information Retrieval Based on Semantic Web Technology

According to the rapid development of the Internet and the increase of the network resources, it was very important to search the information resources for meeting the need of large ground of users. The key words were used as the indexes for retrieval with traditional method. But it couldnt reflect the real purposes and intentions of the users precisely. An improved information retrieval method based on the semantic web technology was proposed for carrying out the information retrieval work precisely and effectively. The mew retrieval system was not just recognizing the words simply, but it could comprehend the semantic ingredients of the words and sentences. The semantic web retrieval system was constructed eventually. Comparing to the traditional keywords retrieval method, the similarity degree was calculated in the simulation, simulation result shows that the retrieval precision ratio of new method increases by 15%, then the intelligent, efficient and accurate information retrieval system is realized successfully.

Based on Wavelet Multi-Resolution Analysis of Image Retrieval and Reviewed

Multimedia technology development and the implementation of the Internet technology leading to a large number of image information appear, based on keywords retrieval methods of traditional text can not meet the requirement of image information retrieval, this makes the content-based image retrieval technology gradually become the focus of research. Based on the content retrieval technology of the key step is necessary in the extraction of image features, which can be used to extract the features such as color, texture and shape. However, because of the image characteristics can only hold each image similarity of a certain aspects, therefore how to better image will be based on content said image retrieval one of the important research direction. This article reviews some content-based image retrieval comparison, such as color features and the texture characteristics and the extraction of the kind of method, each have their own advantages is in.

XML keywords retrieval by integrating semantics of document and user inquiries

XML keywords retrieval by integrating semantics of document and user inquiries

XSTAR: XML 질의의 SQL 변환 알고리즘

XML이 다양한 분야에 널지 이용되면서 대용량의 XML을 효과적으로 관리하는 여러 가지 방법들이 연구되고 있다. 특히 지금가지 상업적, 기술적으로 성공적인 데이터 모델인 관계형 데이터베이스를 기반으로 한 여러 가지 방법들이 연구되고 있다. 본 논문은 관계형 DBMS를 사용하여 XML 질의어인 XQuery를 SQL로 변환하는 알고리즘인 XSTAR(XQuery to SQL Translation Algorithms on RDBMS)를 설계 및 구현한다. 본 연구의 XSTAR 알고리즘은 기본적인 XPath 뿐만 아니라 XQuery FLWOR 표현식, XQuery함수, 그리고 전문 검색(Fulltext 검색[8])과 관련된 몇몇 특수한 기능을 효율적으로 지원할 수 있으며, 질의의 결과 값을 XML 형태로 재생성하여 사용자에게 반환한다. 본 논문에서 제안하는 XSTAR 알고리즘은 현재 웹 상에서 공개적으로 시범 운용되고 있는 XML 문서의 관리 및 질의 처리 시스템인 XPERT(XML Query Processing Engine using Relational Technologies, http://dblab.kmu.ac.kr/project.jsp")의 질의 처리 엔진으로 사용되고 있다. There have been several researches to manipulate XML Queries efficiently since XML has been accepted in many areas. Among the many of the researches majority of them adopt relational databases as underlying systems because relational model which is used the most widely for managing large data efficiently. In this paper we develop XQuery to SQL Translation Algorithms called XSTAR that can efficiently handle XPath, XQuery FLWORs with nested iteration expressions, element constructors and keywords retrieval on relational database as well as constructing XML fragments from the transformed SQL results. The entire algorithms mentioned in XSTAR have been implemented as the XQuery processor engine in XML management system, XPERT, and we can test and confirm it's prototype from "http ://dblab.kmu.ac.kr/project.jsp".

Research and application on Web information retrieval based on improved FP-growth algorithm

A kind of single linked lists named aggregative chain is introduced to the algorithm, thus improving the architecture of FP tree. The new FP tree is a one-way tree and only the pointers that point its parent at each node are kept. Route information of different nodes in a same item are compressed into aggregative chains so that the frequent patterns will be produced in aggregative chains without generating node links and conditional pattern bases. An example of Web key words retrieval is given to analyze and verify the frequent pattern algorithm in this paper.