• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.680-682
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• 2015

최근 스마트폰의 보급으로 소셜 네트워크 서비스를 이용하는 사용자들이 급증하였다. 그 중 트위터는 정보의 빠른 전파력과 확산성으로 인해 현실에서 발생한 이벤트를 탐지하는 도구로 활용하는 것이 가능하다. 따라서 트위터 사용자 개개인을 하나의 센서로 가정하고 그들이 작성한 트윗 텍스트를 분석한다면 이벤트 탐지의 도구로써 활용할 수 있다. 이와 관련된 연구들은 이벤트 발생 위치를 추적하기 위해 GPS좌표를 이용하지만 트위터 사용자들이 위치정보 공개에 회의적인 점을 감안하면 명확한 한계점으로 제시될 수 있다. 이에 본 논문에서는 트위터에서 제공하는 위치정보를 이용하지 않고, 트윗 텍스트에서 위치정보를 추적하는 방법을 제시하였다. 트윗 텍스트에서 키워드간의 관계를 고려하여 이벤트의 사실여부를 결정하였으며, 실험을 통해 기존 매체들보다 빠른 탐지를 보임으로써 제안된 시스템의 필요성을 보였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.113-113
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• 2018

본 연구는 다목적 입자군집최적화(Particle Swarm Optimization, PSO) 알고리즘을 SWAT(Soil and Water Assessment Tool) 모형에 적용하여 자동보정 알고리즘의 적용 가능성을 평가하고자 한다. PSO 알고리즘은 Python을 활용해 다목적 함수를 고려할 수 있도록 새롭게 개발되었다. SWAT 모형의 유출 해석은 안성천의 공도 수위 관측소 상류유역($366.5km^2$)을 대상으로 하였으며, 공도 지점의 2000년부터 2017년까지의 일 유량 자료를 이용하여 검보정하였다. 모형을 위한 기상자료는 공도유역 주변 3개 기상관측소(수원, 천안, 이천)의 일별 강수량, 최고 및 최저기온, 평균 풍속, 상대습도 및 일사량을 구축하였다. SWAT 모형의 유출 해석은 결정계수(Coefficient of determination, $R^2$), RMSE(Root mean square error), Nash-Sutcliffe 모형효율계수(NSE) 및 IOA(index of agreement) 등을 활용하여, 기존 연구 결과와 PSO 알고리즘을 활용한 결과를 비교 분석하고자 한다. 본 연구에서 개발한 다목적 PSO 알고리즘을 활용한 SWAT모형의 유출 해석은 보다 높은 정확도를 얻을 수 있을 것으로 예상되며, Python으로 개발되어 SWAT모형 이외에도 널리 적용될 수 있을 것으로 판단된다.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.1-13
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• 2005

Latent Class model has been considered recently by many researchers and practitioners as a tool for identifying heterogeneous segments or groups in a population, and grouping objects into the segments. In this paper we consider data on prostate cancer patients from Korean National Cancer Institute and propose a method for grouping prostate cancer patients by using latent class Poisson model. A Bayesian approach equipped with a Markov chain Monte Carlo method is used to overcome the limit of classical likelihood approaches. Advantages of the proposed Bayesian method are easy estimation of parameters with their standard errors, segmentation of objects into groups, and provision of uncertainty measures for the segmentation. In addition, we provide a method to determine an appropriate number of segments for the given data so that the method automatically chooses the number of segments and partitions objects into heterogeneous segments.

• Journal of Korea Water Resources Association
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• v.44 no.4
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• pp.295-304
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• 2011

For effective water quality management, it is necessary to secure reliable water quality information. There are many variables that need to be included in a comprehensive practical monitoring network : representative sampling locations, suitable sampling frequencies, water quality variable selection, and budgetary and logistical constraints are examples, especially sampling location is considered to be the most important issues. Until now, monitoring network design for water quality management was set according to the qualitative judgments, which is a problem of representativeness. In this paper, we propose network design system for optimal water quality monitoring using the scientific statistical techniques. Network design system is made based on the SAS program of version 9.2 and configured with simple input system and user friendly outputs considering the convenience of users. It applies to Excel data format for ease to use and all data of sampling location is distinguished to sheet base. In this system, time plots, dendrogram, and scatter plots are shown as follows: Time plots of water quality variables are graphed for identifying variables to classify sampling locations significantly. Similarities of sampling locations are calculated using euclidean distances of principal component variables and dimension coordinate of multidimensional scaling method are calculated and dendrogram by clustering analysis is represented and used for users to choose an appropriate number of clusters. Scatter plots of principle component variables are shown for clustering information with sampling locations and representative location.

• Journal of the military operations research society of Korea
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• v.33 no.2
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• pp.101-113
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• 2007

The period of military personnel service will be phased down by 2014 according to 'The law of National Defense Reformation' issued by the Ministry of National Defense. For this reason, the ROK army provides discrimination education to 'newly recruited privates' for more effective individual performance in the on-the-job training. For the training to be more effective, it would be essential to predict the degree of achievements by new privates in the training. Thus, we used data mining techniques to develop a classification model which classifies the new privates into one of two achievements groups, so that different skills of education are applied to each group. The target variable for this model is a binary variable, whose value can be either 'a group of general control' or 'a group of special control'. We developed four pure classification models using Neural Network, Decision Tree, Support Vector Machine and Naive Bayesian. We also built four hybrid models, each of which combines k-means clustering algorithm with one of these four mining technique. Experimental results demonstrated that the highest performance model was the hybrid model of k-means and Neural Network. We expect that various military education programs could be supported by these classification models for better educational performance.

• Korean Journal of Microbiology
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• v.43 no.3
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• pp.210-216
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• 2007

The principal objective of this study was to analyze 16S rDNA-ARDRA of the humus forest soil via an improved manual method and an ISOIL kit on the basis of the UPGMA clustering of the 16S rDNA combined profile, 44 ARDRA clusters of 76 clones via the ISOIL kit method and 45 ARDRA clusters of 136 clones via the improved manual method. On the basis of the 16S rDNA sequences, 44 clones from the ARDRA clusters by the ISOIL kit were classified into 3 phyla : ${\alpha}-,\;{\beta}-,\;{\gamma}-,\;{\delta}-Proteobacteria$, Acidobacteria and Actinobacteria. Using the improved manual method, the specimens were classified into 6 phyla : the ${\alpha}-,\;{\beta}-,\;{\gamma}-,\;{\delta}-Proteobacteria$, Acidobacteria, Bacteroides, Verrucomicrobia, Planctomycetes and Gemmatomonadetes. As a result, the modified manual method indicated greater phylogenetic diversity than was detected by the ISOIL kit. Approximately 40 percent of the total clones were identified as ${\alpha}-Proteobacteria$ and 30 percent of the total clones were ${\gamma}-Proteobacteria$ and assigned to dominant phylogenetic groups using the ISOIL kit. Using the modified manual method, 41 percent of the total clones were identified as Acidobacteria and 28 percent of total clones were identified as ${\alpha}-proteobacteria$ and assigned to dominant phylogenetic groups.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.709-716
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• 2004

This paper describes an intelligent real-time monitoring system of a semiconductor processing equipment, which determines normal or not for a wafer in processing, using multiple time-series pattern recognition. The proposed system consists of three phases, initialization, learning and real-time prediction. The initialization phase sets the weights and tile effective steps for all parameters of a monitoring equipment. The learning phase clusters time series patterns, which are producted and fathered for processing wafers by the equipment, using LBG algorithm. Each pattern has an ACI which is measured by a tester at the end of a process The real-time prediction phase corresponds a time series entered by real-time with the clustered patterns using Dynamic Time Warping, and finds the best matched pattern. Then it calculates a predicted ACI from a combination of the ACI, the difference and the weights. Finally it determines Spec in or out for the wafer. The proposed system is tested on the data acquired from etching device. The results show that the error between the estimated ACI and the actual measurement ACI is remarkably reduced according to the number of learning increases.

• Land and Housing Review
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• v.15 no.2
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• pp.107-124
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• 2024

Based on Muan-gun, Jeollanam-do, this study explores how to mitigate the disappearance of rual areas. The study surveyed 95 young farmers in Muan-gun to assess their farming practices and the challenges they face. We further employ factor analysis and cluster analysis classify young farmers in Muan-gun, facilitating the identification of tailored policies or initiatives aimed at fostering and supporting young farmers. The results are summarized as follows. First, Muan County does not have any ordinances or original projects specifically designed to support young farmers. Second, the succession rate of farmland among young farmers in Muan County is 41.1%, which is comparable to the national rate of 43.7%. This indicates that approximately 40% of young farmers in Korea have inherited farmland, a critical foundation for agricultural activities. Third, despite accumulating farming experience, young farmers have not seen any improvement in local living conditions, and rather their difficulties have intensified. Fourth, this study conducted a factor analysis using 21 variables, resulting in the selection of seven common factors for cluster analysis. Consequently, young farmers in Muan County were categorized into three groups. The multinomial logit analysis revealed that the typology of young farmers is influenced by indicators such as cultivated area, farming experience, demand for smart farms, farm income, and farming type (rice cultivation or other). Therefore, to attract young farmers and prevent the decline of rural areas, policy efforts should focus on minimizing entry barriers to farming infrastructure, such as access to farmland, and improving local settlement conditions.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.443-449
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• 2017

Swarm of low-cost UAVs for search mission has benefit in the sense of rapid search compared to use of single high-end UAV. As the number of UAVs forming swarm increases, not only the time for the mission planning increases, but also the system to operate UAVs has excessive burden. This paper addresses a decentralized area search algorithm adequate for multiple UAVs which takes advantages of flexibility, robustness, and simplicity. To down the cost, it is assumed that each UAV has limited ability: close-communication, basic calculation, and limited memory. In close-communication, heath conditions and search information are shared. And collision avoidance and consensus of next search direction are then done. To increase weight on un-searched area and to provide overlapped search, the score function is introduced. Performance and operational characteristics of the proposed search algorithm and mission planning logic are verified via numerical simulations.

• Korean Journal of Construction Engineering and Management
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• v.6 no.2 s.24
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• pp.102-110
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• 2005

After the IMF bailout, the Environment of Domestic Construction Industry had changed dramatically. Before the IMF, Domestic Construction Firms are secured by the government regulations and some traditional practices. However, due to the following reasons: a decrease in public works, an increase in uncertainty of market prediction, the change of bid system, and increase in construction firms, recently the competition among construction firms has became keen. Under the serious competition, in order that medium-size construction firms survive in the construction market, it is need to establish the strategy that could increase productivity. In order to establish the strategy, firstly, construction firms should set up an appraisal standard of construction firms. Consequently, This study will introduce companies' objective appraisal in domestic construction market as well as basal data for setting-up strategy through adaptation industry structure analysis of business administration for strategic group analysis and a company which has lagged behind competitive power among the competitive companies can choose a target strategic group which should be pursued it in the future through being classified according to a group taken analogical strategy.