• Journal of the Korean Society for Precision Engineering
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• 제21권4호
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• pp.88-94
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• 2004

Recently, vehicle simulators are widely used to evaluate driver's responses and driver assistance systems. It needs much effort to construct the virtual driving environment for a vehicle simulator. In this study, it is described how to make effectively the roads and the driving environment for a vehicle simulator. The GIS (Geographic Information System) is used to construct the roads and the environment effectively. Because the GIS is the integrated system of geographical data, it contains useful data to make virtual driving environment. First, the outline and centerline of roads is abstracted from the GIS. From the road outline, the road width is calculated. Using the centerline, the grid model of roads is constructed. The final graphic model of roads is constructed by mapping road image to the grid model according to the number of lanes and the kind of surface. Data of buildings from the GIS are abstracted. Each shape and height of buildings is determined according to kind of buildings, the final graphic model of buildings is constructed. Then, the graphic model of roadside tree is also constructed. Finally, the driving environment for driving simulator is constructed by converting the three graphic models with the graphic format of Direct-X and by joining the three graphic models.

• Journal of the Institute of Electronics Engineers of Korea CI
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• 제39권2호
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• pp.21-34
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• 2002

Different from ordinary mobile robots used in a well-structured industrial workspace, a guide mobile robot for the visually impaired should be designed in consideration of a moving obstacle, which mostly refers to pedestrians in intentional motions. Thus, the navigation of the guide robot can be facilitated if the intention of each detected obstacle can be known in advance. In this paper, we propose an inference method to understand an intention of a detected obstacle. In order to represent the environment with ultrasonic sensors, the fuzzy grid-type map is first constructed. Then, we detect the obstacle and infer the intention for collision avoidance with the CLA(Centroid of Largest Area) point of the fuzzy grid-type map. To verify the proposed method, some experiments are performed.

• International Journal of Naval Architecture and Ocean Engineering
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• 제11권2호
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• pp.679-687
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• 2019

This paper presents the autonomous swimming technology developed for an Autonomous Underwater Vehicle (AUV) operating in the underwater jacket structure environment. To prevent the position divergence of the inertial navigation system constructed for the primary navigation solution for the vehicle, we've developed kinds of marker-recognition based underwater localization methods using both of optical and acoustic cameras. However, these two methods all require the artificial markers to be located near to the cameras mounted on the vehicle. Therefore, in the case of the vehicle far away from the structure where the markers are usually mounted on, we may need alternative position-aiding solution to guarantee the navigation accuracy. For this purpose, we develop a sonar image processing based underwater localization method using a Forward Looking Sonar (FLS) mounted in front of the vehicle. The primary purpose of this FLS is to detect the obstacles in front of the vehicle. According to the detected obstacle(s), we apply an Occupancy Grid Map (OGM) based path planning algorithm to derive an obstacle collision-free reference path. Experimental studies are carried out in the water tank and also in the Pohang Yeongilman port sea environment to demonstrate the effectiveness of the proposed autonomous swimming technology.

• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2009년도 추계학술발표대회
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• pp.381-382
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• 2009

본 논문은 고령자 및 장애인의 안전한 이동을 지원하기 위한 지능형 휠체어에서의 자동 장애물 감지 및 회피 기술을 개발한다. 이때 다양한 환경에서의 장애물을 정확히 감지하고 회피하기 위하여 학습을 이용한 비전 기반의 경로 선정 방법이 제안 된다. 제안된 시스템은 배경 분류기, occupancy grid map 생성기, 경로 선정기로 구성되며, 경로 선정 시 강건한 장애물 검출을 수행하기 위해 입력 영상을 occupancy grid map으로 변환하고, K-means clustering 알고리즘을 이용하여 생성된 대표 템플릿들과 비교하여 이동 가능한 방향을 선정한다. 제안된 시스템의 효율성을 증명하기 위해 다양한 형태의 장애물을 포함하는 실내 및 실외에서 실험한 결과 81.7%의 정확도를 보였으며, 지능형 휠체어 사용자에게 안전한 이동성을 제공 할 수 있음을 증명 하였다.

• Journal of The Korean Society of Agricultural Engineers
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• 제57권2호
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• pp.15-26
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• 2015

The purpose of this paper is to develop a software tool, PGA-CC (Projection of hydrology via Grid-based Assessment for Climate Change) to evaluate the present hydrologic cycle and the future watershed hydrology by climate change. PGA-CC is composed of grid-based input data pre-processing module, hydrologic cycle calculation module, output analysis module, and output data post-processing module. The grid-based hydrological model was coded by Fortran and compiled using Compaq Fortran 6.6c, and the Graphic User Interface was developed by using Visual C#. Other most elements viz. Table and Graph, and GIS functions were implemented by MapWindow. The applicability of PGA-CC was tested by assessing the future hydrology of South Korea by HadCM3 SRES B1 and A2 climate change scenarios. For the whole country, the tool successfully assessed the future hydrological components including input data and evapotranspiration, soil moisture, surface runoff, lateral flow, base flow etc. From the spatial outputs, we could understand the hydrological changes both seasonally and regionally.

• Journal of Environmental Science International
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• 제20권1호
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• pp.93-106
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• 2011

Physically-based resampling scheme for roughness coefficient of surface runoff considering the spatial landuse distribution was suggested for the purpose of effective operational application of recent grid-based distributed rainfall runoff model. Generally grid scale(mother scale) of hydrologic modeling can be greater than the scale (child scale) of original GIS thematic digital map when the objective basin is wide or topographically simple, so the modeler uses large grid scale. The resampled roughness coefficient was estimated and compared using 3 different schemes of Predominant, Composite and Mosaic approaches and total runoff volume and peak streamflow were computed through distributed rainfall-runoff model. For quantitative assessment of biases between computational simulation and observation, runoff responses for the roughness estimated using the 3 different schemes were evaluated using MAPE(Mean Areal Percentage Error), RMSE(Root-Mean Squared Error), and COE(Coefficient of Efficiency). As a result, in the case of 500m scale Mosaic resampling for the natural and urban basin, the distribution of surface runoff roughness coefficient shows biggest difference from that of original scale but surface runoff simulation shows smallest, especially in peakflow rather than total runoff volume.

• Journal of the Korean Institute of Telematics and Electronics A
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• 제32A권8호
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• pp.1-10
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• 1995

We have analyzed the reliability of failure models in circuit-switched networks. These models are grid topology circuit-switched networks, and each node transmits a packet to a destination node using a Flooding routing method. We have assumed that the failure of each link and node is independent. We have considered two method to analyze reliability in these models : The Karnaugh Map method and joint probability method. In this two method, we have analyzed the reliability in a small grid topology circuit switched network by a joint probability method, and comared analytic results with simulated ones. For a large grid enormous. So, we have evaluated the reliability of the network by computer simulation techniques. As results, we have found that the analytic results are very close to simulated ones in a small grid topology circuit switched network. And, we have found that network reliability decreases exponentially, according to increment of link or node failure, and network reliability is almost linearly decreased according to increment of the number of links, by which call has passed. Finally, we have found an interesting result that nodes in a center of the network are superior to the other nodes from the reliability point of view.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제38권5호
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• pp.407-414
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• 2020

SVM (Support vector machine) analysis was performed after applying a deep learning technique based on an Inception-based model (GoogLeNet). The accuracy of automatic image classification was analyzed using an SVM with multiple virtual grid sizes. Six classes were selected from a standard land cover map. Cars were added as a separate item to increase the classification accuracy of roads. The virtual grid size was 2-5 m for natural areas, 5-10 m for traffic areas, and 10-15 m for building areas, based on the size of items and the resolution of input images. The results demonstrate that automatic classification accuracy can be increased by adopting an integrated approach that utilizes weighted virtual grid sizes for different classes.

• Communications for Statistical Applications and Methods
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• 제29권1호
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• pp.65-83
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• 2022

Although various statistical methods have been developed to map time-dependent genetic factors, most identified genetic variants can explain only a small portion of the estimated genetic variation in longitudinal traits. Gene-gene and gene-time/environment interactions are known to be important putative sources of the missing heritability. However, mapping epistatic gene-gene interactions is extremely difficult due to the very large parameter spaces for models containing such interactions. In this paper, we develop a Gaussian process (GP) based nonparametric Bayesian variable selection method for longitudinal data. It maps multiple genetic markers without restricting to pairwise interactions. Rather than modeling each main and interaction term explicitly, the GP model measures the importance of each marker, regardless of whether it is mostly due to a main effect or some interaction effect(s), via an unspecified function. To improve the flexibility of the GP model, we propose a novel grid-based method for the within-subject dependence structure. The proposed method can accurately approximate complex covariance structures. The dimension of the covariance matrix depends only on the number of fixed grid points although each subject may have different numbers of measurements at different time points. The deviance information criterion (DIC) and the Bayesian predictive information criterion (BPIC) are proposed for selecting an optimal number of grid points. To efficiently draw posterior samples, we combine a hybrid Monte Carlo method with a partially collapsed Gibbs (PCG) sampler. We apply the proposed GP model to a mouse dataset on age-related body weight.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제33권4호
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• pp.221-229
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• 2015

The urban crimes that threat individual's safety are parts of the serious social problems. However. the information of crime in Korea has only been provided by forms of hot spots around place of crime, or forms of crime statistics without positional information. Those could not provide enough information to users in identifying the vulnerable areas for substantive crimes. Therefore, this study suggested a methodology of extraction in criminal vulnerable areas by using the spatial information, the statistical information and the public sector information. The crime vulnerable areas were extracted through the grid-based spatial analysis and the overlapping analysis from each of the information. In fact, the extracted areas were able to provide detailed vulnerability information than the traditional hot spot-based crime information. Following the study, the extracted results in crime vulnerable areas have displayed highly coincide with Korea safety map, provided by national disaster management institute, which regards to be able to provide crime risk rating in terms of administrative business in future.