• Title/Summary/Keyword: 정보검색기법

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A Secure Mobile Message Authentication Over VANET (VANET 상에서의 이동성을 고려한 안전한 메시지 인증기법)

  • Seo, Hwa-Jeong;Kim, Ho-Won
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.5
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    • pp.1087-1096
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    • 2011
  • Vehicular Ad Hoc Network(VANET) using wireless network is offering the communications between vehicle and vehicle(V2V) or vehicle and infrastructure(V2I). VANET is being actively researched from industry field and university because of the rapid developments of the industry and vehicular automation. Information, collected from VANET, of velocity, acceleration, condition of road and environments provides various services related with safe drive to the drivers, so security over network is the inevitable factor. For the secure message authentication, a number of authentication proposals have been proposed. Among of them, a scheme, proposed by Jung, applying database search algorithm, Bloom filter, to RAISE scheme, is efficient authentication algorithm in a dense space. However, k-anonymity used for obtaining the accurate vehicular identification in the paper has a weak point. Whenever requesting the righteous identification, all hash value of messages are calculated. For this reason, as the number of car increases, a amount of hash operation increases exponentially. Moreover the paper does not provide a complete key exchange algorithm while the hand-over operation. In this paper, we use a Received Signal Strength Indicator(RSSI) based velocity and distance estimation algorithm to localize the identification and provide the secure and efficient algorithm in which the problem of hand-over algorithm is corrected.

Recommending Core and Connecting Keywords of Research Area Using Social Network and Data Mining Techniques (소셜 네트워크와 데이터 마이닝 기법을 활용한 학문 분야 중심 및 융합 키워드 추천 서비스)

  • Cho, In-Dong;Kim, Nam-Gyu
    • Journal of Intelligence and Information Systems
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    • v.17 no.1
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    • pp.127-138
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    • 2011
  • The core service of most research portal sites is providing relevant research papers to various researchers that match their research interests. This kind of service may only be effective and easy to use when a user can provide correct and concrete information about a paper such as the title, authors, and keywords. However, unfortunately, most users of this service are not acquainted with concrete bibliographic information. It implies that most users inevitably experience repeated trial and error attempts of keyword-based search. Especially, retrieving a relevant research paper is more difficult when a user is novice in the research domain and does not know appropriate keywords. In this case, a user should perform iterative searches as follows : i) perform an initial search with an arbitrary keyword, ii) acquire related keywords from the retrieved papers, and iii) perform another search again with the acquired keywords. This usage pattern implies that the level of service quality and user satisfaction of a portal site are strongly affected by the level of keyword management and searching mechanism. To overcome this kind of inefficiency, some leading research portal sites adopt the association rule mining-based keyword recommendation service that is similar to the product recommendation of online shopping malls. However, keyword recommendation only based on association analysis has limitation that it can show only a simple and direct relationship between two keywords. In other words, the association analysis itself is unable to present the complex relationships among many keywords in some adjacent research areas. To overcome this limitation, we propose the hybrid approach for establishing association network among keywords used in research papers. The keyword association network can be established by the following phases : i) a set of keywords specified in a certain paper are regarded as co-purchased items, ii) perform association analysis for the keywords and extract frequent patterns of keywords that satisfy predefined thresholds of confidence, support, and lift, and iii) schematize the frequent keyword patterns as a network to show the core keywords of each research area and connecting keywords among two or more research areas. To estimate the practical application of our approach, we performed a simple experiment with 600 keywords. The keywords are extracted from 131 research papers published in five prominent Korean journals in 2009. In the experiment, we used the SAS Enterprise Miner for association analysis and the R software for social network analysis. As the final outcome, we presented a network diagram and a cluster dendrogram for the keyword association network. We summarized the results in Section 4 of this paper. The main contribution of our proposed approach can be found in the following aspects : i) the keyword network can provide an initial roadmap of a research area to researchers who are novice in the domain, ii) a researcher can grasp the distribution of many keywords neighboring to a certain keyword, and iii) researchers can get some idea for converging different research areas by observing connecting keywords in the keyword association network. Further studies should include the following. First, the current version of our approach does not implement a standard meta-dictionary. For practical use, homonyms, synonyms, and multilingual problems should be resolved with a standard meta-dictionary. Additionally, more clear guidelines for clustering research areas and defining core and connecting keywords should be provided. Finally, intensive experiments not only on Korean research papers but also on international papers should be performed in further studies.

Subimage Detection of Window Image Using AdaBoost (AdaBoost를 이용한 윈도우 영상의 하위 영상 검출)

  • Gil, Jong In;Kim, Manbae
    • Journal of Broadcast Engineering
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    • v.19 no.5
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    • pp.578-589
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    • 2014
  • Window image is displayed through a monitor screen when we execute the application programs on the computer. This includes webpage, video player and a number of applications. The webpage delivers a variety of information by various types in comparison with other application. Unlike a natural image captured from a camera, the window image like a webpage includes diverse components such as text, logo, icon, subimage and so on. Each component delivers various types of information to users. However, the components with different characteristic need to be divided locally, because text and image are served by various type. In this paper, we divide window images into many sub blocks, and classify each divided region into background, text and subimage. The detected subimages can be applied into 2D-to-3D conversion, image retrieval, image browsing and so forth. There are many subimage classification methods. In this paper, we utilize AdaBoost for verifying that the machine learning-based algorithm can be efficient for subimage detection. In the experiment, we showed that the subimage detection ratio is 93.4 % and false alarm is 13 %.

Trends Analysis on Research Articles of the Sharing Economy through a Meta Study Based on Big Data Analytics (빅데이터 분석 기반의 메타스터디를 통해 본 공유경제에 대한 학술연구 동향 분석)

  • Kim, Ki-youn
    • Journal of Internet Computing and Services
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    • v.21 no.4
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    • pp.97-107
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    • 2020
  • This study aims to conduct a comprehensive meta-study from the perspective of content analysis to explore trends in Korean academic research on the sharing economy by using the big data analytics. Comprehensive meta-analysis methodology can examine the entire set of research results historically and wholly to illuminate the tendency or properties of the overall research trend. Academic research related to the sharing economy first appeared in the year in which Professor Lawrence Lessig introduced the concept of the sharing economy to the world in 2008, but research began in earnest in 2013. In particular, between 2006 and 2008, research improved dramatically. In order to grasp the overall flow of domestic academic research of trends, 8 years of papers from 2013 to the present have been selected as target analysis papers, focusing on titles, keywords, and abstracts using database of electronic journals. Big data analysis was performed in the order of cleaning, analysis, and visualization of the collected data to derive research trends and insights by year and type of literature. We used Python3.7 and Textom analysis tools for data preprocessing, text mining, and metrics frequency analysis for key word extraction, and N-gram chart, centrality and social network analysis and CONCOR clustering visualization based on UCINET6/NetDraw, Textom program, the keywords clustered into 8 groups were used to derive the typologies of each research trend. The outcomes of this study will provide useful theoretical insights and guideline to future studies.

Development of water cycle analysis systems and evaluation of Urbanization for the Gap river basin using SWAT (SWAT 모델을 이용한 갑천 유역 물수지 분석 및 도시화 영향 평가)

  • Kim, Jeong-Kon;Son, Kyong-Ho;Noh, Jun-Woo;Jang, Chang-Lae;Ko, Ich-Hwan
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.130-134
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    • 2006
  • 본 연구의 목적은 하천 복원과 관리에 필수적인 하천의 특성 분석 및 물순환 분석시스템 구축에 있다. 연구 대상지역으로 최근 하천의 생태 기능 회복을 위해 도심생태하천조성 사업이 추진되고 있는 대전 3대 하천유역을 선정하였다. 대전 3대 하천 유역의 물수지와 도시화에 따른 영향을 파악하기 위하여 SWAT을 이용한 물순환 분석시스템을 구축하였다. 모형적용 결과, 유출량과 지하수 수위 변화 등 대전 3대 하천 유역의 특성을 관측치에 가깝게 모의할 수 있었다. 모델의 검보정 실시결과에서 나타난 모델의 계산 값들의 관측된 유출량뿐 아니라 기저유출량 및 지하수 수위와의 높은 상관관계는 본 연구에서 구축한 모델의 구조나 변수의 유효성에 많은 신뢰도를 제공한다고 판단된다. SWAT을 이용하여 대전 3대 하천 유역의 물수지 분석 및 도시화에 따른 영향을 평가하였다. 물수지 분석결과에 의하면, 전체적으로 총 유출량 중 지하수 유출량이 47%정도, 중간 유출량이 31% 그리고 지표유출량이 22%이다. 각 소유역의별 유출 성분 분석결과는 각 소유역의 토지 이용도, 토양 그리고 지형적 특징에 따른 유출 특성을 확인하였다. 도시화 영향 분석 결과 전체적으로 1975년에서 2000년까지 갑천 유역의 약 5%가량의 도시화는 총 유출량의 변화에 있어서는 현저한 차이를 보이지 않았으나, 각 유출 성분의 경우에는 많은 영향이 있는 것으로 나타났다. 특히 지표유출량은 45% 가량의 증가를 보였고, 전체 유역의 지하수함양 량이 5%정도 감소한 반면, 도시화가 31%정도 진행된 소유역의 경우에는 17%정도의 현저한 감소를 나타냈다. 본 연구에서 수행한 물수지 분석 및 도시화 영향분석 결과는 향후 대천 3대 하천의 생태하천복원을 위한 물순환 정상화 대책마련 및 하천의 유량확보방안 마련에 기초자료를 제공할 수 있을 것이다.득증대를 꾀함으로 농촌문제 해결에 도움이 될 것으로 기대된다. 본 연구를 통해 GIS 와 RS의 기술이 농촌분야에 더 효율적으로 적용될 것으로 기대되며, 농업기술센터를 통한 정보제공을 함으로써 대농민 서비스 및 농업기관의 위상이 제고 될 것으로 기대된다.여 전자파의 공간적인 가시화를 수행할 수 있었다. 본 전자파 시뮬레이션 기법이 실무에 이용될 경우, 일반인이 전자파의 분포에 대한 전문지식을 습득할 필요 없이, 검색하고자 하는 지역과 송전선, 전철 등 각종 전자파의 발생 공간 객체를 선택하여 실생활과 관련된 전자파 정보에 예측할 수 있어, 대민 환경정보 서비스 질의 개선측면에서 획기적인 계기를 마련할 것으로 사료된다.acid$(C_{18:3})$가 대부분을 차지하였다. 야생 돌복숭아 과육 중의 지방산 조성은 포화지방산이 16.74%, 단불포화지방산 17.51% 및 다불포화지방산이 65.73%의 함유 비율을 보였는데, 이 중 다불포화지방산인 n-6계 linoleic acid$(C_{18:2})$와 n-3계 linolenic acid$(C_{18:3})$가 지질 구성 총 지방산의 대부분을 차지하는 함유 비율을 나타내었다.했다. 하강하는 약 4일간의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에 있어서 시장수익률을 평균적으로 초과할 수 있는 거래전략은 존재하므로 이러한 전

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A Dominant Discharge Estimate for Channel Characteristics Quantity Survey (하도특성량 조사를 위한 지배유량의 산정)

  • Im, Chang-Su;Lee, Joon-Ho;Kim, Tae-Hee;Lee, Jae-Chul;Yoon, Sei-Eui
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.66-71
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    • 2006
  • 최근에 하도계획의 주된 과제는 하천환경의 보전과 창조를 위한 비용의 최소화이며, 침식과 세굴에 대한 하천관리 시설의 안정성을 확보하기 위한 질적 안전도의 최대화에 있다. 이를 위해 하도의 변화를 전제로 이동상 현상을 고려하고 저수로의 특성을 파악하여 하도계획에 반영하는 것이 필요하다. 이러한 하도계획과 관리를 위한 주요한 도구로서 하도특성조사가 제시되고 있다. 우리나라에서는 수변 생태환경의 기능회복으로의 하천환경에 관심을 기울이기 시작한 단계에 머물러 있다. 국내에서도 일본 등 선진 외국과 같이 홍수시 재해를 크게 경감하고, 자연환경을 실질적이고 체계적으로 배려하면서 경제적 하도계획 및 관리에 역점을 두어야 할 시점에 이르렀다. 이를 위해서는 우선적으로 하천이 갖고 있는 고유 특성인 하도특성에 대한 조사가 선행되어야 한다. 본 연구에서는 대상하천을 선정하고 측량, 하상재료 채취 및 분석, 유사량 채취 등의 기초조사를 수행하였으며, 이에 따른 하도특성량을 분석하였다. 대상하천은 금강유역의 지천 하류부의 약 2km 구간을 선정하였으며, 2003년${\sim}$2004년에 3회에 걸쳐 측량을 실시하고, 구간내 구룡수위표에서 유량 몇 유사량을 측정하였다. 또한 대상구간내 14개 지점에서 하상토를 채취하여 입도분석을 실시하였으며, 구룡수위표 자료를 이용하여 수문자료를 구축하였다. 수집된 기초자료를 이용하여 대상구간의 강턱유량, 특정재현기간유량, 유효유량을 산정하여 지배유량을 결정하였다. 산정된 지배유량을 이용하여 하상경사, 대표입경, 저수로내 평균수심, 에너지 경사, 마찰속도, 무차원소류력, 하폭-수심비, 수심-입경비 등의 하도특성량을 산출하여 하천환경정비를 위한 기초자료로서 활용 될 수 있도록 하였다.구에 맞는 작물 생산 및 농촌관광단지 조성을 통해 부가가치증대 및 소득증대를 꾀함으로 농촌문제 해결에 도움이 될 것으로 기대된다. 본 연구를 통해 GIS 와 RS의 기술이 농촌분야에 더 효율적으로 적용될 것으로 기대되며, 농업기술센터를 통한 정보제공을 함으로써 대농민 서비스 및 농업기관의 위상이 제고 될 것으로 기대된다.여 전자파의 공간적인 가시화를 수행할 수 있었다. 본 전자파 시뮬레이션 기법이 실무에 이용될 경우, 일반인이 전자파의 분포에 대한 전문지식을 습득할 필요 없이, 검색하고자 하는 지역과 송전선, 전철 등 각종 전자파의 발생 공간 객체를 선택하여 실생활과 관련된 전자파 정보에 예측할 수 있어, 대민 환경정보 서비스 질의 개선측면에서 획기적인 계기를 마련할 것으로 사료된다.acid$(C_{18:3})$가 대부분을 차지하였다. 야생 돌복숭아 과육 중의 지방산 조성은 포화지방산이 16.74%, 단불포화지방산 17.51% 및 다불포화지방산이 65.73%의 함유 비율을 보였는데, 이 중 다불포화지방산인 n-6계 linoleic acid$(C_{18:2})$와 n-3계 linolenic acid$(C_{18:3})$가 지질 구성 총 지방산의 대부분을 차지하는 함유 비율을 나타내었다.했다. 하강하는 약 4일간의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행

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Elicitation of Collective Intelligence by Fuzzy Relational Methodology (퍼지관계 이론에 의한 집단지성의 도출)

  • Joo, Young-Do
    • Journal of Intelligence and Information Systems
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    • v.17 no.1
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    • pp.17-35
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    • 2011
  • The collective intelligence is a common-based production by the collaboration and competition of many peer individuals. In other words, it is the aggregation of individual intelligence to lead the wisdom of crowd. Recently, the utilization of the collective intelligence has become one of the emerging research areas, since it has been adopted as an important principle of web 2.0 to aim openness, sharing and participation. This paper introduces an approach to seek the collective intelligence by cognition of the relation and interaction among individual participants. It describes a methodology well-suited to evaluate individual intelligence in information retrieval and classification as an application field. The research investigates how to derive and represent such cognitive intelligence from individuals through the application of fuzzy relational theory to personal construct theory and knowledge grid technique. Crucial to this research is to implement formally and process interpretatively the cognitive knowledge of participants who makes the mutual relation and social interaction. What is needed is a technique to analyze cognitive intelligence structure in the form of Hasse diagram, which is an instantiation of this perceptive intelligence of human beings. The search for the collective intelligence requires a theory of similarity to deal with underlying problems; clustering of social subgroups of individuals through identification of individual intelligence and commonality among intelligence and then elicitation of collective intelligence to aggregate the congruence or sharing of all the participants of the entire group. Unlike standard approaches to similarity based on statistical techniques, the method presented employs a theory of fuzzy relational products with the related computational procedures to cover issues of similarity and dissimilarity.

Evaluation Criteria for Appropriateness of Bicycle Riding Path Considering Cyclist's Trip Purposes (자전거 이용자의 통행목적을 고려한 주행경로 적정성 평가지표 개발)

  • Kim, Eui-Jin;Kim, Dong-Kyu
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.4
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    • pp.12-25
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    • 2016
  • The purpose of this study is providing an evaluation criteria for appropriateness of bicycle riding path considering trip purpose based on cyclist's response of importance and satisfaction. The survey presents a quantified criteria of evaluating appropriateness of the bicycle path by investigating difference of impotance and satisfaction between two purposes among 5 selected influence factors about bicycle lane and bicycle parking facility, and in case of commuting purpose, information of destination is additionally considered. All the influence factors are analyzed by Analytical Hierarchy Process (AHP) which yields importance. For the factors which have a huge difference between two purposes, evaluation criteria using a GIS Data of respondent's path and satisfaction of each factors is developed, and other factors are made it by reviewing literature. The importance analyzed by AHP and evaluation criteria can provide a path based LOS for cyclist, and this information can be improved through user's response from app or search engine in the future. and by considering individual's evaluation, it can provide individually specified information.

Real time Storage Manager to store very large datausing block transaction (블록 단위 트랜잭션을 이용한 대용량 데이터의 실시간 저장관리기)

  • Baek, Sung-Ha;Lee, Dong-Wook;Eo, Sang-Hun;Chung, Warn-Ill;Kim, Gyoung-Bae;Oh, Young-Hwan;Bae, Hae-Young
    • Journal of Korea Spatial Information System Society
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    • v.10 no.2
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    • pp.1-12
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    • 2008
  • Automatic semiconductor manufacture system generating transaction from 50,000 to 500,000 per a second needs storage management system processing very large data at once. A lot of storage management systems are researched for storing very large data. Existing storage management system is typical DBMS on a disk. It is difficult that the DBMS on a disk processes the 500,000 number of insert transaction per a second. So, the DBMS on main memory appeared to use memory. But it is difficultthat very large data stores into the DBMS on a memory because of limited amount of memory. In this paper we propose storage management system using insert transaction of a block unit that can process insert transaction over 50,000 and store data on low storage cost. A transaction of a block unit can decrease cost for a log and index per each tuple as transforming a transaction of a tuple unit to a block unit. Besides, the proposed system come cost to decompress all block of data because the information of each field be loss. To solve the problems, the proposed system generates the index of each compressed block to prevent reducing speed for searching. The proposed system can store very large data generated in semiconductor system and reduce storage cost.

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Multiple Cause Model-based Topic Extraction and Semantic Kernel Construction from Text Documents (다중요인모델에 기반한 텍스트 문서에서의 토픽 추출 및 의미 커널 구축)

  • 장정호;장병탁
    • Journal of KIISE:Software and Applications
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    • v.31 no.5
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    • pp.595-604
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    • 2004
  • Automatic analysis of concepts or semantic relations from text documents enables not only an efficient acquisition of relevant information, but also a comparison of documents in the concept level. We present a multiple cause model-based approach to text analysis, where latent topics are automatically extracted from document sets and similarity between documents is measured by semantic kernels constructed from the extracted topics. In our approach, a document is assumed to be generated by various combinations of underlying topics. A topic is defined by a set of words that are related to the same topic or cooccur frequently within a document. In a network representing a multiple-cause model, each topic is identified by a group of words having high connection weights from a latent node. In order to facilitate teaming and inferences in multiple-cause models, some approximation methods are required and we utilize an approximation by Helmholtz machines. In an experiment on TDT-2 data set, we extract sets of meaningful words where each set contains some theme-specific terms. Using semantic kernels constructed from latent topics extracted by multiple cause models, we also achieve significant improvements over the basic vector space model in terms of retrieval effectiveness.