• Annual Conference of KIPS
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• 2008.11a
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• pp.702-705
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• 2008

인터넷 사용자 증가에 따라 검색 엔진의 사용 또한 급격히 늘어나고 있는 추세이다. 국내외 다양한 검색 엔진들이 존재하지만 대부분의 자료들이 기본적인 카테고리별로 링크 횟수나 키워드 빈발 횟수에 따라 정렬이 되어 있다. 그러므로 사용자들은 수동적으로 정렬된 도메인들을 따라 가는 실정이다. 본 논문에서는 수동적인 서비스가 아닌 능동적인 서비스에 중점을 둔다. 특정 카테고리 내에서 접속한 사용자에게 최근 시점을 기준으로 가장 빈번하게 접속된 도메인 정보를 제공하여 시간의 단축과 유용한 서비스를 받도록 한다. 본 논문의 서비스 모델은 인터넷 사용자의 로그 데이터베이스와 도메인 데이터베이스를 기반으로 한다. 본 논문에서 제안하는 카테고리 분류 기법으로 두 데이터베이스를 통합하고 정제한다. 정제된 데이터들은 최종적으로 순차 패턴 마이닝 기법에 의해 최종 빈발 패턴을 추출 하게 되고 특정 카테고리에 접속한 사용자에게 도메인 형태로 변환 되어 서비스 하게 된다.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.191-198
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• 2017

It is needed to support intelligent customized health information service for user convenience in PHR based Personal Health Care Service Platform. In this paper, we specify an ontology-based health data model for Personal Health Care Service Platform. We also design a knowledge search algorithm that can be used to figure out similar health record by applying machine learning and data mining techniques. Axis-based mining algorithm, which we proposed, can be performed based on axis-attributes in order to improve relevance of knowledge exploration and to provide efficient search time by reducing the size of candidate item set. And K-Nearest Neighbor algorithm is used to perform to do grouping users byaccording to the similarity of the user profile. These algorithms improves the efficiency of customized information exploration according to the user 's disease and health condition. It can be useful to apply the proposed algorithm to a process of inference in the Personal Health Care Service Platform and makes it possible to recommend customized health information to the user. It is useful for people to manage smart health care in aging society.

• Journal of Practical Agriculture & Fisheries Research
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• v.22 no.1
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• pp.113-129
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• 2020

In this study we examined the topic analysis and correlation analysis by text mining to extract meaningful information or rules from the self introduction letter of freshman at Korea National College of Agriculture and Fisheries in 2020. The analysis items are described in items related to 'academic' and 'in-school activities' during high school. In the text mining results, the keywords of 'academic' items were 'study', 'thought', 'effort', 'problem', 'friend', and the key words of 'in-school activities' were 'activity', 'thought', 'friend', 'club', 'school' in order. As a result of the correlation analysis, the key words of 'thinking', 'studying', 'effort', and 'time' played a central role in the 'academic' item. And the key words of 'in-school activities' were 'thought', 'activity', 'school', 'time', and 'friend'. The results of frequency analysis and association analysis were visualized with word cloud and correlation graphs to make it easier to understand all the results. In the next study, TF-IDF(Term Frequency-Inverse Document Frequency) analysis using 'frequency of keywords' and 'reverse of document frequency' will be performed as a method of extracting key words from a large amount of documents.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.757-770
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• 2018

Foreground extraction is the most significant step in thermal imaging based surveillance systems. This step needs to be efficient in terms of time and memory consumption in order for the system to provide real time results but usually this efficiency reciprocates with the accurateness of the ROI detection. In this study, novel selective histogram bins based two background & foreground separation approaches for thermal videos processing have been proposed which exploit the temporal-consistency property of the thermal images in a given environment and can save over 80% memory than their simplest counterpart temporal median filtering.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.945-951
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• 2008

In this paper, a new high performance data cache scheme that improves exploitation of both the spatial and temporal locality is proposed. The proposed data cache consists of a hardware prefetch unit and two sub-caches such as a direct-mapped (DM) cache with a large block size and a fully associative buffer with a small block size. Spatial locality is exploited by fetching and storing large blocks into a direct mapped cache, and is enhanced by prefetching a neighboring block when a DM cache hit occurs. Temporal locality is exploited by storing small blocks from the DM cache in the fully associative buffer according to their activity in the DM cache when they are replaced. Experimental results on Spec2000 programs show that the proposed scheme can reduce the average miss ratio by $12.53%\sim23.62%$ and the AMAT by $14.67%\sim18.60%$ compared to the previous schemes such as direct mapped cache, 4-way set associative cache and SMI(selective mode intelligent) cache[8].

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.3
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• pp.55-62
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• 2000

This paper presents an analysis of the chaotic behavior in the discrete-time voltage mode chaotic generator fabricated using 0.8${\mu}{\textrm}{m}$ single poly CMOS technology. An approximated empirical equation is extracted from the measurement data of a nonlinear function block. Then the bifurcation diagram is simulated according to input variables and Lyapunov exponent λ which represent a dependence on an initial value is calculated. We show the interrelations among time waveforms, state transition, and power spectra for the state condition of chaotic circuit, such as equilibrium, periodic, and chaotic state. And results of experiments in the chaotic circuit with the $\pm$2.5V power supply and sampling clock frequency of 10KHz are shown and compared with the simulated results.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.465-465
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• 2012

본 연구는 우리나라 전국 기상관측소 중 1973년부터 2011년까지 시 강수 자료가 구축되어 있는 기상관측소 61개 지점에 대해서 지속시간별(1, 2, 3, 6, 12, 24, 48, 72 시간) 연 최대 강수량의 발생특성 즉 발생 시기 및 정량적 특성의 변화를 지역특성에 따라 분석 제시하였다. 대상 기간을 전기(1973년-1992년)와 후기(1993년-2011년)로 나누어 극치 강수량과 발생시점의 변화를 비교하였으며, 지역 특성별 변화를 분석하기 위하여 고도별, 위도별, 경도별, 내륙/해안별, 유역별, 도시화별로 변화 특성을 분석하였다. 분석결과, 전체적으로 짧은 지속시간의 연 최대 강수량의 빈도는 대부분 7월에서 8월로 옮겨가는 추세를 나타났으며 장마철에 발생하던 짧은 지속기간 극치 강수현상이 태풍과 장마이후 집중호우 시 발생하는 것으로 판단되며 지속시간이 24시간 이상일 경우에는 8월에서 7월로 변하는 결과는 긴 지속시간의 극치 강수가 장마기간에 강수량 증가와 연관되어 나타나는 것으로 판단된다. 경도가 130도 이상인 지역에서는 7월과 8월에만 강수량이 편중되어 있지 않고 다양하게 나타났다. 또한 각 지점의 위치적 특성에 따라 분석한 결과에서는 지속시간별 강수량은 통계적 유의성을 가지지는 않지만 대체적으로 전기에 비해서 후기에 연 최대 강수량이 증가하는 경향을 보였다. 또한 각 월별 지역특성에 따른 연 최대 강수량의 평균에 대한 분석 결과에서도 일반적으로 7월과 8월에 연 최대 강수량이 다른 기간에 비해 큰 것으로 나타났다. 또한 전기 대비 후기에 양도 증가하는 지역들이 나타났으며, 전기에는 7월에 많은 강수량이 나타난 반면, 후기에는 8월에 많은 강수량이 나타나는 지역들이 나타남을 보였고 오히려 전기에는 8월에 많이 내리는 것으로 나타났으나 후기에는 7월에 많이 내리는 지역도 나타났다. 이러한 지역 특성별 극치 강수 발생 특성 분석 결과는 수자원 관리 및 수재해 예방을 위한 계획 수립 시 도움을 줄 것으로 판단된다.

• The Journal of Korean Association of Computer Education
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• v.17 no.2
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• pp.31-38
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• 2014

This paper reveals continuity of related events which are occurred and changing from moment to moment accident/events collected from various social media channels. Among them, we especially define the events which have big social influence as "issue event" and investigate the type and characteristics of continuous issue event for each domain. We also introduce a automatic issue detection system in social media text. Based on the extracted issue event results in a particular domain, we analyse the continuity of those events by illustrating in time and place-axis. Furthermore, we identify the relationship between social media in terms of issue events propagation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2371-2379
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• 2017

For the drone that is active in a wide search area, the time to grasp the target in the field of applications such as searching for emergency patients, monitoring of natural disasters requiring prompt warning and response, that is, the speediness of target detection is very important. In the actual operation of drone, the time for target detection is highly related to collaboration between drones and search algorithm to efficiently search the navigation area. In this research, we will provide a search method with cooperation of drone based on target existence probability to solve the problem of quickness in drone target search. In particular, the proposed method increases the probability of finding a target and shorten the search time by transmitting high-altitude drone search results to a low-altitude drone after searching first and performing more precise search. We verify the performance of the proposed method through several simulations.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.157-165
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• 2011

It is challenging to detect foreground objects when background includes an illumination variation, shadow or structural variation due to its motion. Basically pixel-based background models including codebook-based modeling suffer from statistical randomness of each pixel. This paper proposes an algorithm that incorporates Markov random field model into pixel-based background modeling to achieve more accurate foreground detection. Under the assumptions the distance between the pixel on the input imaging and the corresponding background model and the difference between the scene estimates of the spatio-temporally neighboring pixels are exponentially distributed, a recursive approach for estimating the MRF regularizing parameters is proposed. The proposed method alternates between estimating the parameters with the intermediate foreground detection and estimating the foreground detection with the estimated parameters, after computing it with random initial parameters. Extensive experiment is conducted with several videos recorded both indoors and outdoors to compare the proposed method with the standard codebook-based algorithm.