• Title/Summary/Keyword: Search Performance

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Performance Evaluation of DAR(Dynamic Adaptive Routing) and FSR(Flood Search Routing) Methods in a Common Channel Signaling Scheme (공통선 신호방식에서의 DAR(Dynamic Adaptive Routing)방식과 FSR(Flood Search Routing)방식의 성능평가)

  • 김재현;이종규
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.31A no.12
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    • pp.1-8
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    • 1994
  • In this paper, we hve compare the performance of DAR(Dynamic Adaptive Routing) with that of FSR(Flooding Search Routing) to select an adequate routing protocol in circuit-switched networs. As a performance factor, we have considered call setup time, which is the key factor of performance evaluation in circuit switched networks. We have evaluated the performance of two methods in grid topology circuit-switched networks using a commn channel signaling scheme, as application examples. As results, FSR method shows better performance than DAR method under light traffic load, when the number of links by which call has passed increases, but DAR method represents better performance than FSR method under heavy traffic load or large networks because of redundant packets.

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A Study of Survivable Alternate Routing Algorithm (생존성있는 대체 경로 라우팅 알고리즘 연구)

  • Park, Young-Chul
    • Journal of KIISE:Computing Practices and Letters
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    • v.13 no.7
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    • pp.535-539
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    • 2007
  • We study an degree of alternativeness and a survivability of alternate routing algorithm in mobile ad-hoc tactical communication networks. The common channel signaling scheme is used and flood search routing algorithm is used for analysis. We also study a connectivity performance for flood search routing, restricted flooding and hybrid routing. From the results we expect low blocking probabilities with alternate routing and the conventional flood search routing shows better connectivity performance which results in high survivability.

Pareto fronts-driven Multi-Objective Cuckoo Search for 5G Network Optimization

  • Wang, Junyan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.2800-2814
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    • 2020
  • 5G network optimization problem is a challenging optimization problem in the practical engineering applications. In this paper, to tackle this issue, Pareto fronts-driven Multi-Objective Cuckoo Search (PMOCS) is proposed based on Cuckoo Search. Firstly, the original global search manner is upgraded to a new form, which is aimed to strengthening the convergence. Then, the original local search manner is modified to highlight the diversity. To test the overall performance of PMOCS, PMOCS is test on three test suits against several classical comparison methods. Experimental results demonstrate that PMOCS exhibits outstanding performance. Further experiments on the 5G network optimization problem indicates that PMOCS is promising compared with other methods.

Development of A Plagiarism Detection System Using Web Search and Morpheme Analysis (인터넷 검색과 형태소분석을 이용한 표절검사시스템의 개발에 관한 연구)

  • Hwang, In-Soo
    • Journal of Information Technology Applications and Management
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    • v.16 no.1
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    • pp.21-36
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    • 2009
  • As the World Wide Web (WWW) has become a major channel for information delivery, the data accumulated in the Internet increases at an incredible speed, and it derives the advances of information search technologies. It is the search engine that solves the problem of information overloading and helps people to identify relevant information. However, as search engines become a powerful tool for finding information, the opportunities of plagiarizing have increased significantly in e-Learning. In this paper, we developed an online plagiarism detection system for detecting plagiarized documents that incorporates the functions of search engines and acts in exactly the same way of plagiarizing. The plagiarism detection system uses morpheme analysis to improve the performance and sentence-based comparison to investigate document comes from multiple sources. As a result of applying this system in e-Learning, the performance of plagiarism detection was improved.

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Analysis of Drone Target Search Performance According to Environment Change

  • Lim, Jong-Bin;Ha, Il-Kyu
    • Journal of Korea Multimedia Society
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    • v.22 no.10
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    • pp.1178-1186
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    • 2019
  • In recent years, interest in drones has grown, and many countries are developing them into a strategic industry of the future. Drones are not only used in industries such as logistics and agriculture but also in various public sectors such as life rescue, disaster investigation, traffic control, and firefighting. One of the most important tasks of a drone is to accurately identify targets in these applications. Target recognition may vary depending on the search environment of the drone. Therefore, this study tests and analyzes the drone's target recognition performance according to changes in the search environment such as the search altitude and the search angle. In addition, we propose a new algorithm that improves upon the disadvantages of the Haar cascade method, which is the existing algorithm that recognizes the target by analyzing a captured image.

Analysis of Cultural Context of Image Search with Deep Transfer Learning (심층 전이 학습을 이용한 이미지 검색의 문화적 특성 분석)

  • Kim, Hyeon-sik;Jeong, Jin-Woo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.5
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    • pp.674-677
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    • 2020
  • The cultural background of users utilizing image search engines has a significant impact on the satisfaction of the search results. Therefore, it is important to analyze and understand the cultural context of images for more accurate image search. In this paper, we investigate how the cultural context of images can affect the performance of image classification. To this end, we first collected various types of images (e.g,. food, temple, etc.) with various cultural contexts (e.g., Korea, Japan, etc.) from web search engines. Afterwards, a deep transfer learning approach using VGG19 and MobileNetV2 pre-trained with ImageNet was adopted to learn the cultural features of the collected images. Through various experiments we show the performance of image classification can be differently affected according to the cultural context of images.

Implementation of A Set-based POI Search Algorithm Supporting Classifying Duplicate Characters (중복글자 구분을 지원하는 집합 기반 POI 검색 알고리즘 구현)

  • Ko, Eunbyul;Lee, Jongwoo
    • Journal of Digital Contents Society
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    • v.14 no.4
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    • pp.463-469
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    • 2013
  • The set-based POI search algorithm showed better performance than the existing hard matching search when inaccurate queries are entered. In the set-based POI search algorithm, however, there is a problem that can't classify duplicate characters within a record. This is due to it's 'set-based' search property. To solve this problem, we improve the existing set-based POI search algorithm. In this paper, we propose and implement an improved set-based POI search algorithm that is able to deal duplicate characters properly. From the experimental results, we can find that our technique for duplicate characters improves the performance of the existing set based POI search algorithm.

The Vocabulary Recognition Optimize using Acoustic and Lexical Search (음향학적 및 언어적 탐색을 이용한 어휘 인식 최적화)

  • Ahn, Chan-Shik;Oh, Sang-Yeob
    • Journal of Korea Multimedia Society
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    • v.13 no.4
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    • pp.496-503
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    • 2010
  • Speech recognition system is developed of standalone, In case of a mobile terminal using that low recognition rate represent because of limitation of memory size and audio compression. This study suggest vocabulary recognition highest performance improvement system for separate acoustic search and lexical search. Acoustic search is carry out in mobile terminal, lexical search is carry out in server processing system. feature vector of speech signal extract using GMM a phoneme execution, recognition a phoneme list transmission server using Lexical Tree Search algorithm lexical search recognition execution. System performance as a result of represent vocabulary dependence recognition rate of 98.01%, vocabulary independence recognition rate of 97.71%, represent recognition speed of 1.58 second.

A Study on the Performance Evaluation of Semantic Retrieval Engines (시맨틱검색엔진의 성능평가에 관한 연구)

  • Noh, Young-Hee
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.22 no.2
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    • pp.141-160
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    • 2011
  • This study suggested knowledge base and search engine for the libraries that have the largescaled data. For this purpose, 3 components of knowledge bases(triple ontology, concept-based knowledge base, inverted file) were constructed and 3 search engines(search engine JENA for rule-based reasoning, Concept-based search engine, keyword-based Lucene retrieval engine) were implemented to measure their performance. As a result, concept-based retrieval engine showed the best performance, followed by ontology-based Jena retrieval engine, and then by a normal keyword search engine.

Performance Improvement of BLAST using Grid Computing and Implementation of Genome Sequence Analysis System (그리드 컴퓨팅을 이용한 BLAST 성능개선 및 유전체 서열분석 시스템 구현)

  • Kim, Dong-Wook;Choi, Han-Suk
    • The Journal of the Korea Contents Association
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    • v.10 no.7
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    • pp.81-87
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    • 2010
  • This paper proposes a G-BLAST(BLAST using Grid Computing) system, an integrated software package for BLAST searches operated in heterogeneous distributed environment. G-BLAST employed 'database splicing' method to improve the performance of BLAST searches using exists computing resources. G-BLAST is a basic local alignment search tool of DNA Sequence using grid computing in heterogeneous distributed environment. The G-BLAST improved the existing BLAST search performance in gene sequence analysis. Also G-BLAST implemented the pipeline and data management method for users to easily manage and analyze the BLAST search results. The proposed G-BLAST system has been confirmed the speed and efficiency of BLAST search performance in heterogeneous distributed computing.