• Title/Summary/Keyword: Clue

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Analysis of Surface Runoff in Yongdam Dam Small Basin by Using CLUE Model (토지이용변화모형을 이용한 용담댐 소유역의 지표유출량 분석)

  • Chun, Beomseok;Lee, Taehwa;Kim, Sangwoo;Jung, Younghun;Shin, Yongchul
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.170-170
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    • 2021
  • 본 연구에서는 토지이용변화 예측 모형으로 산출된 토지이용도를 사용하여 용담댐 소유역의 지표유출량을 비교 및 분석하였다. 토지이용예측모형은 DynaCLUE 모형을 사용하였으며, 토지이용 면적 시나리오는 2000년, 2007년 및 2013년 실제 중분류 토지이용도를 기반으로 회귀식을 산정하였다. 모의된 토지이용도는 실제 토지이용도와 공간적인 분포 및 면적 비교를 통해 변환 탄성계수와 변환 행렬을 수정하여 검·보정하였다. DynaCLUE 모형으로 모의된 토지이용도는 공간적인 분포에서 초지가 실제 토지이용도와 차이가 발생하였으나, 각 토지이용별 면적을 비교한 경우 모의 토지이용도와 실제 토지이용도가 매우 유사하게 나타났다. CLUE 모형으로 모의된 토지이용도에서 발생하는 공간적인 불확실성은 복잡한 용담댐 소유역의 토지이용을 반영할 Driving factor가 부족하여 발생하는 것으로 판단된다. 산출된 모의 토지이용도를 SWAT 모형의 입력 자료로 사용하여 2013년 용담댐의 소유역 지표유출량을 모의하였다. SWAT으로 산정된 유출량의 보정은 SWAT-CUP의 SUFI-2 알고리즘을 이용했으며, 보정된 모의 지표유출량과 실제 유량 측정값을 비교한 결과 유의미한 비교 결과가 나타났다. 향후 토지이용예측모형을 이용하여 토지이용 변화를 수문 분석에 반영하는 추가 연구가 필요할 것으로 판단된다.

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Algorithm for Candidate Clue Decision based on Magic Rule in Kakuro Puzzle (가꾸로 퍼즐에 관한 마법 규칙 기반 실마리 후보 결정 알고리즘)

  • Sang-Un Lee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.24 no.3
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    • pp.103-108
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    • 2024
  • Kakuro puzzles are NP-complete problems where no way to solve puzzles in polynomial time is known. Until now, a brute-force search method or a linear programming method has been applied to substitute all possible cases. This paper finds a magic rule, a rule for box sizes and unfilled numbers according to sum clues. Based on the magic rule, numbers that cannot enter empty cells were deleted from the box for row and column sum clues. Next, numbers that cannot enter the box were deleted based on the sum clue value. Finally, cells with only a single number were confirmed as clues. As a result of applying the proposed algorithm to seven benchmarking experimental data, it was shown that solutions could be obtained for all problems.

The Expectation of the Land Use and Land Cover Using CLUE-S Model and Landsat Images (CLUE-S 모델과 시계열 Landsat 자료를 이용한 토지피복 변화 예측)

  • Kim, Woo-Sun;Yun, Kong-Hyun;Heo, Joon;Jayakumar, S.
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.1
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    • pp.33-41
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    • 2008
  • Land use/land cover is very important to understand the change in the land cover between specific periods. But as there are number of factors which are responsible for the change in the land cover, it is very difficult to identify the specific factors. Therefore in the study we made an attempt to use the land use strategies quantitatively and conducted simulation study. The input data using the CLUE-S model are the satellite data of 1987 and 2001 from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) and we conducted simulations for 23 years from 1987 to 2010. As a result, the accuracy between the land use map derived from original satellite data and simulation for 2001 was 93.69% and in this reason we could expect land use and land cover in the future.

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A Probability Mapping for Land Cover Change Prediction using CLUE Model (토지피복변화 예측을 위한 CLUE 모델의 확률지도 생성)

  • Oh, Yun-Gyeong;Choi, Jin-Yong;Bae, Seung-Jong;Yoo, Seung-Hwan;Lee, Sang-Hyun
    • Journal of Korean Society of Rural Planning
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    • v.16 no.2
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    • pp.47-55
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    • 2010
  • Land cover and land use change data are important in many studies including climate change and hydrological studies. Although the various theories and models have been developed, it is difficult to identify the driving factors of the land use change because land use change is related to policy options and natural and socio-economic conditions. This study is to attempt to simulate the land cover change using the CLUE model based on a statistical analysis of land-use change. CLUE model has dynamic modeling tools from the competition among land use change in between driving force and land use, so that this model depends on statistical relations between land use change and driving factors. In this study, Yongin, Icheon and Anseong were selected for the study areas, and binary logistic regression and factor analysis were performed verifying with ROC curve. Land cover probability map was also prepared to compare with the land cover data and higher probability areas are well matched with the present land cover demonstrating CLUE model applicability.

Algorithm for Clue Combination Number Intersection of Number Clue Sujiko Puzzle (숫자 실마리 수지코 퍼즐에 관한 실마리 숫자 조합 교집합 알고리즘)

  • Sang-Un Lee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.24 no.5
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    • pp.159-168
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    • 2024
  • In a grid board with 9 cells of 3X3, the Sujiko puzzle with 4 sum clues and C number clues as one block is an NP-complete problem with no known way to solve the puzzle in polynomial time. To solve this puzzle (9-C)! in all possible cases, a brute-force method should be applied to substitute the number. This paper confirmed the clue of the unique number cell by reducing the number of candidates that can enter empty cells. When the unique number cell no longer exists, a method of selecting the intersection combination numbers between the sum clue blocks has been proposed. Applying the proposed algorithm to 52 benchmarking experimental data showed that puzzles can be solved in polynomial time for all problems.

Prediction of Land-Use Change based on Urban Growth Scenario in South Korea using CLUE-s Model (도시성장 시나리오와 CLUE-s 모형을 이용한 우리나라의 토지이용 변화 예측)

  • LEE, Yong-Gwan;CHO, Young-Hyun;KIM, Seong-Joon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.3
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    • pp.75-88
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    • 2016
  • In this study, we used the CLUE-s model to predict the future land-use change based on the urban growth scenario in South Korea. The land-use maps of six classes (water, urban, rice paddy, upland crop, forest, and grass) for the year 2008 were obtained from the Ministry of Environment (MOE), and the land-use data for 5-year intervals between 1980 and 2010 were obtained from the Water Resources Management Information System (WAMIS), South Korea. For predicting the future land-use change, the MOE environmental conservation value assessment map (ECVAM) was considered for identifying the development-restricted areas, and various driving factors as location characteristics were prepared for the model. The predicted results were verified by comparing them with the land-use statistics of urban areas in each province for the year 2008. The prediction error rates were 9.47% in Gyeonggi, 9.96% in Gangwon, 10.63% in Chungbuk, 7.53% in Chungnam, 9.48% in Jeonbuk, 6.92% in Jeonnam, 2.50% in Gyeongbuk, and 8.09% in Gyeongnam. The sources of error might come from the gaps between the development of political decisions in reality with spatio-temporal variation and the mathematical model for urban growth rate in CLUE-s model for future scenarios. Based on the land-use scenario in 2008, the land-use predictions for the year 2100 showed that the urban area increased by 28.24%, and the rice paddy, upland crop, and forest areas decreased by 8.27, 6.72, and 1.66%, respectively, in South Korea.

A Topic Classification System Based on Clue Expressions for Person-Related Questions and Passages (단서표현 기반의 인물관련 질의-응답문 문장 주제 분류 시스템)

  • Lee, Gyoung Ho;Lee, Kong Joo
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.12
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    • pp.577-584
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    • 2015
  • In general, Q&A system retrieves passages by matching terms of a question in order to find an answer to the question. However it is difficult for Q&A system to find a correct answer because too many passages are retrieved and matching using terms is not enough to rank them according to their relevancy to a question. To alleviate this problem, we introduce a topic for a sentence, and adopt it for ranking in Q&A system. We define a set of person-related topic class and a clue expression which can indicate a topic of a sentence. A topic classification system proposed in this paper can determine a target topic for an input sentence by using clue expressions, which are manually collected from a corpus. We explain an architecture of the topic classification system and evaluate the performance of the components of this system.

Land Cover Change Prediction Based on Climate Change Scenarios using CLUE Model (CLUE 모형과 기후변화 시나리오를 이용한 토지피복 변화 예측)

  • Oh, Yun-Gyeong;Choi, Jin-Yong;Lee, Sang-Hyun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2010.05a
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    • pp.1546-1550
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    • 2010
  • 최근 IPCC에서는 제 4차 평가보고서를 통해 대기 속 이산화탄소 농도가 산업혁명 이전에 비해 2005년 기준 약 35% 증가하였으며, 지난 1세기 동안 지구 평균기온이 $0.74^{\circ}C$ 증가하였다고 발표하였다. 이러한 기후변화로 인해 야기된 홍수, 가뭄, 사막화, 생태계 혼란 등의 심각한 환경문제를 해결하고자 UN에서는 1992년 세계 환경 개발에 관한 리우 데 자네이로 정상회의에서 기후변화에 관한 기본협약을 체결하여 국제적인 대책을 마련하기 위해 노력하고 있다. 이 중 토지이용변화에 관한 연구는 기후변화를 야기하는 주요한 요인에 관한 연구로서 온실가스 증가와 생물종다양성, 수문학적인 변화 등을 파악하는 데 활용되고 있다. 따라서 기후변화에 대응하고 지속가능한 개발 정책을 수립하기 위해서는 다양한 경제학적, 사회학적인 시나리오 조건에서 미래의 토지이용변화 양상을 살펴볼 필요가 있다. 이에 본 연구에서는 토지이용변화에 영향을 미치는 사회 경제적 요인과 과거의 토지이용변화 패턴을 고려하여 토지이용변화를 모델링 할 수 있는 CLUE(The Conversion of Land Use and its Effects) 모델을 이용하여 SRES(Special Report on Emissions Scenarios) 시나리오에 기초한 토지피복 변화를 살펴보고자 한다. 이는 향후 기후변화를 최소화하기위한 개발전략 수립에 있어서 정책방향을 결정하는 데 기초자료로 활용될 수 있을 것이다.

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The Relationship Between Young Children's Executive Function and Arithmetic Story Problem Solving Abilities (유아의 실행기능과 수학이야기문제해결력 간의 관계)

  • Cheung, Eun Jin
    • Korean Journal of Childcare and Education
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    • v.15 no.1
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    • pp.37-55
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    • 2019
  • Objective: This study investigated whether executive function has a significant relationship to concrete, picture, and language clue tasks of the arithmetic story problem-solving ability, and its effects. Methods: The participants in the study were 112 young children at childcare centers. The following methods were used to evaluate executive function: Day-Night/Flag-Raising tasks, DCCS tasks, and digit span-reverse digit span methods. To measure the arithmetic story problem-solving ability concrete, picture, and language clue tasks were evaluated. Results: First, the higher the child's age, the higher their executive function and arithmetic story problem-solving abilities were. Second, there is a significant positive correlation between a young child's executive function and arithmetic story problem-solving ability. Third, when the task presentation method varied for concrete, picture, and language clue tasks, the effect of the subordinate factor of the execution function of the arithmetic story problem-solving ability also varied. Conclusion/Implications: Analysis confirmed the relationship between young children's executive function and arithmetic story problem-solving ability. The results are meaningful in showing that the sub-factors of the executive function have different influences on concrete, picture, and language clue tasks of the arithmetic story problem-solving ability.

Comparative Analysis of Land Use Change Model at Gapcheon Watershed (갑천 유역을 대상으로 토지이용예측모델 비교 분석)

  • Kwon, PilJu;Ryu, Jichul;Lee, Dong Jun;Han, Jeongho;Sung, Yunsoo;Lim, Kyoung Jae;Kim, Ki-Sung
    • Journal of Korean Society on Water Environment
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    • v.32 no.6
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    • pp.552-561
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    • 2016
  • For the prediction of hydrologic phenomenon, predicting future land use change is a very important task. This study aimed to compare and analyze the two land use change models, CLUE-S and SLEUTH3-R. The analysis of two models were performed based on the MSR value such that the model with more reliable MSR value can be recommended as an appropriate land use change prediction model. The model performance was examined by applying to the Gapcheon A watershed. Land use map of the study area of 2007 obtained from the Ministry of Environment was compared with the predicted land use map obtained from each of the two models. The result from both models showed somewhat similar results. The MSR value obtained from CLUE-S was 0.564, while that from SLEUTH3-R was 0.586. However, when land use map of 2010 was compared with predicted land use map obtained from the two models in same manner, the MSR value obtained from CLUE-S' was 0.500 while that from SLEUTH3-R was decreased to 0.397, an approximately 32.3% decrease from previous value of 2007. Moreover, SLEUTH3-R showed more sensitivity in conversion of urban areas, as compared to other land use types. Therefore, for the prediction of future land use change, CLUE-S model is more reliable than SLEUTH3-R.