• Journal of Digital Convergence
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• v.11 no.9
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• pp.289-299
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• 2013

The aim of this study was to enhance the NHI claims data-based tuberculosis classification rule of KCDC(Korea centers for disease control & prevention) for an effective TB surveillance system. 8,118 cases, 10% samples of 81,199 TB cases from NHI claims data during 2009, were subject to the Medical Record Survey about whether they are real TB patients. The final study population was 7,132 cases whose medical records were surveyed. The decision tree model was evaluated as the most superior TB patients detection model. This model required the main independent variables of age, the number of anti-tuberculosis drugs, types of medical institution, tuberculosis tests, prescription days, types of TB. This model had sensitivity of 90.6%, PPV of 96.1%, and correct classification rate of 93.8%, which was better than KCDC's TB detection model with two or more NHI claims for TB and TB drugs(sensitivity of 82.6%, PPV of 95%, and correct classification rate of 80%).

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1483-1492
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• 1996

In this paper, related on the postal business with the GIS(Geographics Information System), it discusses design and implementation of the PROS(Postal Route Optimization System) model and its main module, the shortest path generation algorithm, for supporting to postal route managements. It explains examples requirements of postal route system, and suggests the efficient PROS model using our developed shortest path generation algorithm. Because the shortest path algorithm adopts not only consider the Dijkstra algorithm of graph theory, but also the method with the direction property, PROS can be implemented with fast and efficient route search. PROS is mainly constituted of the Shortest Generator, the Isochronal Area Generator, and the Path Rearrangement Generator. It also exploits the GIS engine and the spatial DBMS (Data Base Management System) for processing coordinates in the map and geographical features. PROS can be used in the management of postal delivery business and delivery area and route, and in the rearrangement of route. In the near future, it can be also applied to commercial delivery businesses, guides of routs and traffic informations, and auto navigation system with GPS(Global Positioning System).

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.65-76
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• 2002

This study is realized using fuzzy evaluation and AHP(the analytic hierarchy process) for the optimum search of traffic route and estimated by the quantitative analysis in the vague subjective judgement. It is different from classical route search and noticed thinking method of human. Appraisal element, weight, appraisal value of route is extracted from basic of the opinion gathering fur the driving expert and example of route model was used for the finding of practice utility. Model assessment was performed attribute membership function making of estimate element, estimate value setting, weight define by the AHP, non additive presentation of weight according to $\lambda$-fuzzy measure, Choquet fuzzy integral.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.999-1008
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• 2023

Early prediction of chronic diseases such as diabetes is an important issue, and improving the accuracy of diabetes prediction is especially important. Various machine learning and deep learning-based methodologies are being introduced for diabetes prediction, but these technologies require large amounts of data for better performance than other methodologies, and the learning cost is high due to complex data models. In this study, we aim to verify the claim that DNN using the pima dataset and k-fold cross-validation reduces the efficiency of diabetes diagnosis models. Machine learning classification methods such as decision trees, SVM, random forests, logistic regression, KNN, and various ensemble techniques were used to determine which algorithm produces the best prediction results. After training and testing all classification models, the proposed system provided the best results on XGBoost classifier with ADASYN method, with accuracy of 81%, F1 coefficient of 0.81, and AUC of 0.84. Additionally, a domain adaptation method was implemented to demonstrate the versatility of the proposed system. An explainable AI approach using the LIME and SHAP frameworks was implemented to understand how the model predicts the final outcome.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.6
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• pp.599-609
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• 2008

Development of computer and electronic technology leads innovative progress in spatial informatics and successful commercialization. Geospatial information technology plays an important role in decision making in various applications. However, information display media are two-dimensional plane that limits visual perception. Understanding human visual processing mechanism to percept stereo vision makes possible to implement three-dimensional stereo image display. This paper proposes on-the-fly stereo image generation methods that are involved with various exterior and camera parameters including exposure station, viewing direction, image size, overlap and focal length. Collinearity equations and parameters related with stereo viewing conditions were solved to generate realisitc stereo imagery. In addition stereo flying simulation scenery was generated with different viewing locations and directions. The stereo viewing is based on the parallax principle of two veiwing locations. This study implemented anaglyphic stereogram, polarization and lenticular stereo display methods. Existing display technology has limitation to provide visual information of three-dimensional and dynamic nature of the real world because the 3D spatial information is projected into 2D plane. Therefore, stereo display methods developed in this study improves geospatial information and applications of GIS by realistic stereo visualization.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.387-387
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• 2022

기존 홍수기시 댐 운영은 예측 강우와 실시간 관측 강우를 이용하여 댐 운영 모형을 수행하며, 예측 결과에 따라 의사결정 및 댐 운영을 실시하게 된다. 하지만 이 과정에서 반복적인 분석이 필요하며, 댐 운영 모형 수행자의 경험에 따라 예측 결과가 달라져서 반복작업에 대한 자동화, 모형 수행자에 따라 달라지지 않는 예측 결과의 일반화가 필요한 상황이다. 이에 댐 운영 모형에 AI 기법을 적용하여, 다양한 강우 상황에 따른 자동 예측 및 모형 결과의 일반화를 구현하고자 하였다. 이를 위해 수자원 분야에 적용된 국내외 129개 연구논문에서 사용된 딥러닝 기법의 활용성을 분석하였으며, 다양한 수자원 분야 AI 적용 사례 중에서 댐 운영 예측 모형에 적용한 사례는 없었지만 유사한 분야로는 장기 저수지 운영 예측과 댐 상·하류 수위, 유량 예측이 있었다. 수자원의 시계열 자료 활용을 위해서는 Long-Short Term Memory(LSTM) 기법의 적용 활용성이 높은 것으로 분석되었다. 댐 운영 모형에서 AI 적용은 2개 분야에서 진행하였다. 기존 강우관측소의 관측 강우를 활용하여 강우의 패턴분석을 수행하는 과정과, 강우에서 댐 유입량 산정시 매개변수 최적화 분야에 적용하였다. 강우 패턴분석에서는 유사한 표본끼리 묶음을 생성하는 K-means 클러스터링 알고리즘과 시계열 데이터의 유사도 분석 방법인 Dynamic Time Warping을 결합하여 적용하였다. 강우 패턴분석을 통해서 지점별로 월별, 태풍 및 장마기간에 가장 많이 관측되었던 강우 패턴을 제시하며, 이를 모형에서 직접적으로 활용할 수 있도록 구성하였다. 강우에서 댐 유입량을 산정시 활용되는 매개변수 최적화를 위해서는 3층의 Multi-Layer LSTM 기법과 경사하강법을 적용하였다. 매개변수 최적화에 적용되는 매개변수는 중권역별 8개이며, 매개변수 최적화 과정을 통해 산정되는 결과물은 실측값과 오차가 제일 적은 유량(유입량)이 된다. 댐 운영 모형에 AI 기법을 적용한 결과 기존 반복작업에 대한 자동화는 이뤘으며, 댐 운영에 따른 상·하류 제약사항 표출 기능을 추가하여 의사결정에 소요되는 시간도 많이 줄일 수 있었다. 하지만, 매개변수 최적화 부분에서 기존 댐운영 모형에 적용되어 있는 고전적인 매개변수 추정기법보다 추정시간이 오래 소요되며, 매개변수 추정결과의 일반화가 이뤄지지 않아 이 부분에 대한 추가적인 연구가 필요하다.

• Korean Journal of Construction Engineering and Management
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• v.24 no.1
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• pp.31-39
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• 2023

To reduce facility management costs and safety concerns due to aging of facilities, it is important to estimate the future facilities' condition based on facility management data and utilize predictive information for management decision making. To this end, this study proposed a methodology to estimate facility elements' condition using XGBoost. To validate the proposed methodology, this study constructed sample data for road bridges and developed a model to estimate condition grades of major elements expected in the next inspection. As a result, the developed model showed satisfactory performance in estimating the condition grades of deck, girder, and abutment/pier (average F1 score 0.869). In addition, a testbed was established that provides data management function and element condition estimation function to demonstrate the practical applicability of the proposed methodology. It was confirmed that the facility management data and predictive information in this study could help managers in making facility management decisions.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.2
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• pp.139-148
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• 2020

The most important factor affecting the berthing energy generated when a ship berths is the berthing velocity. Thus, an accident may occur if the berthing velocity is extremely high. Several ship features influence the determination of the berthing velocity. However, previous studies have mostly focused on the size of the vessel. Therefore, the aim of this study is to analyze various features that influence berthing velocity and determine their respective importance. The data used in the analysis was based on the berthing velocity of a ship on a jetty in Korea. Using the collected data, machine learning classification algorithms were compared and analyzed, such as decision tree, random forest, logistic regression, and perceptron. As an algorithm evaluation method, indexes according to the confusion matrix were used. Consequently, perceptron demonstrated the best performance, and the feature importance was in the following order: DWT, jetty number, and state. Hence, when berthing a ship, the berthing velocity should be determined in consideration of various features, such as the size of the ship, position of the jetty, and loading condition of the cargo.

• Korean Journal of Construction Engineering and Management
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• v.20 no.4
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• pp.22-33
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• 2019

The government has steadily revised and developed laws and systems for activating remodeling of apartments in response to the problems of aged apartments. However, despite such efforts, remodeling has yet to be activated. For many reasons, this study noted that there were no tools for reasonable profitability judgements and decision making in the preliminary stages of the remodeling project. Thus, the feasibility evaluation model was developed. Generally, the profitability judgements are made after the conceptual design. However, decisions to drive remodeling projects are made at the preliminary stage. So a feasibility evaluation model is required at the preliminary stage. Accordingly, In this study, a feasibility evaluation model was developed for determining preliminary stage profitability. Construction costs, business expenses, financial expenses, and generally sales revenue were calculated using the initial available information and remodeling variables derived through the existing cases. Through this process, we developed an algorithm that can give an overview of the return on investment. In addition, the preliminary stage feasibility evaluation model developed was applied to three cases to verify the applicability of the model. Although applied in three cases, the difference between the model's forecast and actual case values is less than 5%, which is considered highly applicable. If cases are expanded in the future, it will be a useful tool that can be used in actual work. The feasibility evaluation model developed in this study will support decision making by union members, and if the model is applied in different regions, it will be expected to help local governments to understand the size of possible remodeling projects.

• Journal of the Korean Institute of Navigation
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• v.18 no.3
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• pp.1-9
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• 1994

종래(從來)의 내비게이션시스템은 주로 선박(船舶)을 대상(對象)으로 이용되어왔으나, 최근(最近)에는 각종(各種) 이동(移動)로보트 및 자동차(自動車)에 대한 적용사례(適用事例)가 증가(增加)하고 있다. 내비게이션시스템은 기계적(機械的)인 이동(移動)시스템뿐만 아니라, 이동(移動)이라는 행동(行動)을 취하는 인간(人間)시스템 즉, 시각(視覺) 부자유자(不自由者를) 대상(對象)으로 적용(適用)될 수 있다. 종래(從來)의 기계적(機械的)인 맹인용(盲人用) 가이딩시스템으로서 맹도견(盲導犬)로보트가 있으나 계단(階段)등의 복잡(複雜)한 환경하(環境下에)서는 안내(案內)가 불가능(不可能)한 점과 맹인(盲人)의 의사(意思)가 반영(反映)되기 어렵다는 점 등의 많은 문제점(問題點)을 안고 있다. 현실적(現實的)으로 요구(要求)되는 안내(案內)시스템은, 단지 환경(環境)에 관한 각종정보(各種情報)를 제공(提供)하고 의사결정(意思決定)과 행동(行動)은 맹인(盲人)이 실시(實施)하는 시스템의 형태(形態)이다. 본논문(本論文)에서는, 맹인용(盲人用) 내비게이션시스템의 구축(構築)을 목표(目標)로 하는 중간과제(中間課題)로서, 화상(畵像)을 이용(利用)한 언어적(言語的) 가이드시스템을 제안(提案)한다. 당해(當該)시스템 구축(構築)에 있어서 중요(重要)한 과제(課題)는, 주어진 환경(環境)에 관한 화상정보(畵像情報)를 언어(言語)로 변환(變換)시키는 일이다 본연구(本硏究)에서는, 가이드를 위한 언어지원(言語指元) 생성(生成)에, 정성적(定性的), 정량적(定量的)인 속성(屬性)을 가지고 언어적(言語的) 표현(表現)에 유효(有效)한 퍼지이론(理論)을 이용(利用)한다. 구체적(具體的)인 일례(一例)로서, 공원(公園)에서 벤치까지 맹인(盲人)을 가이드하는 상황(狀況)을 설정하고 언어지원(言語指元)을 생성(生成)하는 알고리즘을 제안(提案)한다.