• Spatial Information Research
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• v.8 no.1
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• pp.141-153
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• 2000

The purpose of this study is to develop and apply spatial landslide information system using Geographic information system (GIS) in concerned with spatial data. Landslide locations detected from interpretation of aerial photo and field survey, and topographic , soil , forest , and geological maps of the study area, Yongin were collected and constructed into spatial database using GIS. As landslide occurrence factors, slope, aspect and curvature of topography were calculated from the topographic database. Texture, material, drainage and effective thickness of soil were extracted from the soil database, and type, age, diameter and density of wood were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM satellite image. In addition, landslide damageable objects such as building, road, rail and other facility were extracted from the topographic database. Landslide susceptibility was analyzed using the landslide occurrence factors by probability, logistic regression and neural network methods. The spatial landslide information system was developed to retrieve the constructed GIS database and landslide susceptibility . The system was developed using Arc View script language(Avenue), and consisted of pull-down and icon menus for easy use. Also, the constructed database can be retrieved through Internet World Wide Web (WWW) using Internet GIS technology.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.199-206
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• 1999

본 연구에서는 웹기반의 화물차량위치추적시스템의 개발과 관련된 문제를 다루고 있다. 화물위치추적 시스템이란 이동하는 화물차량으로부터 위치데이터 및 관련 정보를 수신하여 중앙관제센터에서 이 정보를 데이터베이스에 저장하여 두고 화물위치 정보를 지도 위에 표시하는 시스템으로 화주, 운송회사 등 육상물류관련 기관에서 화물위치추적, 공동수배송, 화물차량 통제 등 다양한 목적으로 사용될 수 있다. 화물차량위치추적시스템은 AVLS(Automatic Vehicle Location System)라 불리우면서 산업계에서 활용되고 있으며 위치획득 방법의 종류에 따라 다양한 유형의 AVLS모델이 등장하고 있다. 예를 들면 전통적인 GPS(Global Positioning System) 위성 수신, DGPS(Differential GPS) 기지국, PCS(Personal Communication System) Cell, 도로기반 시설에 포함되는 비콘 등의 방법에 의해 AVLS는 구현되고 있다. AVLS는 정보통신 요소 기술과 정보통신 기반 시설로 구성되는데, 정보통신 요소기술로는 위치획측의 매개체인 AVL단말기와 관제시스템 S/W. 그리고 GIS(Geographic Information System)가 있고, 정보통신 기반 시설로는 차량의 단말기와 관제시스템 사이의 데이터 중계를 담당하는 네트워크가 있다. 화물차량위치추적시스템을 구성하기 위한 구비요건으로 중계망의 안정성과 신뢰성, 획득한 위치데이터의 정확성, 관제시스템의 완성도와 AVL단말기의 사용자 인터페이스, GIS S/W개발을 위한 Map API(Application Program Interface)등을 들 수 있다. 본 연구에서는 PCS Cell 방식에 의한 위치결정방식을 채택하였는데, 이것은 PCS망을 기반으로 데이터를 주고받이며 인터넷 단말기로 확장 가능한 PCS 단말기를 사용해서 위치추적을 하는 시스템이다. 이러한 시스템을 선정하게된 배경은 단말기아 망 이용료의 가격이 저렴하여 현실적으로 트럭이 쉽게 부착할 수 있다는 장점이 있으며 나아가 인터넷 단말기를 활용하여 차량과 관제센터사이에 메시지 전송 등 부가적인 서비스가 가능하기 때문이다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.95-105
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• 2019

In recent years, image processing techniques for detecting road surface damaged spot have been actively researched. Especially, it is mainly used to acquire images through a smart phone or a black box that can be mounted in a vehicle and recognize the road surface damaged region in the image using several algorithms. In addition, in conjunction with the GPS module, the exact damaged location can be obtained. The most important technology is image processing algorithm. Recently, algorithms based on artificial intelligence have been attracting attention as research topics. In this paper, we will also discuss artificial intelligence image processing algorithms. Among them, an object detection method based on an region-based convolution neural networks method is used. To improve the recognition performance of road surface damage objects, 600 road surface damaged images and 1500 general road driving images are added to the learning database. Also, supervised learning using background object recognition method is performed to reduce false alarm and missing rate in road surface damage detection. As a result, we introduce a new method that improves the recognition performance of the algorithm to 8.66% based on average value of mAP through the same test database.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.82-92
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• 2007

This paper describes a novel global shape (GS) feature based on radial basis function network (RBFN) and the extraction method of the proposed feature for 3D face recognition. RBFN is the weighted sum of RBfs, it well present the non-linearity of a facial shape using the linear combination of RBFs. It is the proposed facial feature that the weights of RBFN learned by the horizontal profiles of a face. RBFN based feature expresses the locality of the facial shape even if it is GS feature, and it reduces the feature complexity like existing global methods. And it also get the smoothing effect of the facial shape. Through the experiments, we get 94.7% using the proposed feature and hidden markov model (HMM) to match the features for 100 gallery set with those for 300 test set.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.958-963
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• 2023

Lately, there has been increasing research on the prediction of motion performance using artificial intelligence for the safe design and operation of ships. However, compared to conventional ships, research on small fishing boats is insufficient. In this paper, we propose a model that estimates the motion response essential for calculating the motion performance of small fishing boats using a deep neural network. Hydrodynamic analysis was conducted on 15 small fishing boats, and a database was established. Environmental conditions and main particulars were applied as input data, and the response amplitude operators were utilized as the output data. The motion response predicted by the trained deep neural network model showed similar trends to the hydrodynamic analysis results. The results showed that the high-frequency motion responses were predicted well with a low error. Based on this study, we plan to extend existing research by incorporating the hull shape characteristics of fishing boats into a deep neural network model.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.4
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• pp.85-98
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• 2003

There has recently been an increasing interest of the watershed management as a solution to a wide range of problems related water environment, therefore this study attempted to construct the environment information system to monitor the Geumho River watershed, and to evaluate the impacts of the watershed characteristics on stream water quality. A detailed GIS database to analyze the environmental characteristics at the subwatershed units, including 1:25,000 scale topographical maps, detailed soil maps, land use, 10m-resolution DEMs, roads, streams, vegetation index(NDVI) calculated from Landsat TM imagery, rainfall, and soil loss using RUSLE, is compiled for the study area. The set of variables representing watershed urbanization or industrialization, residential and commercial landuse, industrial landuse, and road area have significantly negative(-) relationship with water quality variables(BOD, COD, SS, T-N, T-P). On the other hand, watershed indicators related to natural environmental conditions, forest cover and vegetation index(NDVI) in each subwatershed were significantly positive(+) relationship with water quality. Three other variables, agricultural landuse, amount of fertilizer and pesticides, and potential soil loss, were not significant in explaining the correlations between watershed environment and stream water quality.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.378-382
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• 2006

This paper presents an approach to detect premature ventricular contractions(PVC) using the neural network with weighted fuzzy membership functions(NEWFM). NEWFM classifies normal and PVC beats by the trained weighted fuzzy membership functions using wavelet transformed coefficients extracted from the MIT-BIH PVC database. The two most important coefficients are selected by the non-overlap area distribution measurement method to minimize the classification rules that show PVC classification rate of 99.90%. By Presenting locations of the extracted two coefficients based on the R wave location, it is shown that PVC can be detected using only information of the two portions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.32-36
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• 2002

심리상담의 영역이 확대되어 감에 따라 오프라인 상담뿐만 아니라 온라인 형태의 상담이 급속히 발전하고 있다. 인터넷의 활용도가 증가함에 따라 컴퓨터를 의사소통의 매개로 활용한 사이버상담 형태를 통한 상담도 체계적으로 개발되어야 할 필요성이 있다. 그러나 현재 개설되어 운영되고 있는 사이버상담은 내담자에게 적합한 맞춤상담이 불가능하며 또한 자가치유가 가능한 자가치유시스템이 없는 실정이다. 따라서 본 논문에서는 지능형 에이전트를 이용하여 내담자에게 적합한 맞춤상담이 가능한 방법을 제안함과 동시에 과거 상담사레 데이터베이스를 바탕으로 이전의 상담사레들을 신경망의 BP학습알고리즘을 이용하여 학습을 시킨 후 자가치유가 가능한 자가치유시스템을 설계하는 방법을 제안한다.

• Journal of the Korea Safety Management & Science
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• v.9 no.5
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• pp.97-101
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• 2007

As the use of vehicle route application and LBS(location based service) are fast grew, the importance of maintaining road network data is also increased. To maintain road data accuracy, we can collect road data by driving real roads with probe vehicle, or using digital image processing for the extraction of roads from aerial imagery. After compare the new road data to current database, we can update the road database, but that job is mostly time and money consuming or can be inaccurate. In this paper, an updating method of using GPS(global positioning system) enabled cell phone is proposed. By using GPS phone, we can update road database easily and sufficiently accurately.

• Prospectives of Industrial Chemistry
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• v.22 no.4
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• pp.13-19
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• 2019

최근 가공할만한 성능의 슈퍼컴퓨터에 머신 러닝 기법을 연동한 인공 지능형 소재 정보학이 과학 기술 및 산업계에 새로운 연구개발 패러다임으로 급속히 확산되고 있다. 본 기고문에서는 이 기법의 성공에 핵심적 요소인 정확한 데이터베이스 구축을 위해 제일원리 전산을 적용하는 것과 이를 기반으로 소재를 구성하는 원소 간 인공 신경망 포텐셜을 만드는 방법을 소개하고자 한다. 이 연구 방법론은 나노 스케일 신소재 개발에 적용할 경우, 양자역학 수준의 정밀도로 순수 제일원리 전산 대비 100배 이상의 빠른 결과를 도출할 가능성이 있음을 예시한다. 이는 향후 다양한 산업계에 막대한 파급효과를 가져올 것으로 예상된다.