• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.178-182
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• 2007

In this study, we evaluated current raingauge network of Soyanggang dam region applying spatial-correlation analysis and Entropy theory to recommend an optimized raingauge network. In the process of analysis, correlation distance of raingauge stations is estimated and evaluated via spatial-correlation method and entropy method. From this correlation distances, respective influencing radii of each dataset and each methods is assessed. The result of correlation and entropy analysis has estimated correlation distance of 25.546km and influence radius of 7.206km, deducing a decrease of network density from $224.53km^2$ to $122.47km^2$ which satisfy the recommended minimum densities of $250km^2$ in mountainous regions(WMO, 1994) and an increase of basin coverage from 59.3% to 86.8%. As for the elevation analysis the relative evaluation ratio increased from 0.59(current) to 0.92(optimized) resulting an obvious improvement.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.9
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• pp.45-53
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• 2006

This paper proposes a method for an effective intelligent route decision for automatic moving robots(AMR) using a 2D spatial map of a stereo camera system. In this method, information about depth and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the automatic moving robot and the obstacle is detected, and a 2D spatial map is obtained from the location coordinates. Then the relative distances between the obstacle and other objects are deduced. The robot move automatically by effective and intelligent route decision using the obtained 2D spatial map. From experiments on robot driving with 240 frames of stereo images, it was found that the error ratio of the calculated distance to the measured distance between objects was very low, 1.52[%] on average.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.54-57
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• 2016

In this paper, the method for an effective and intelligent route decision of the automatic ground vehicle (AGV) using a 2D spatial map of the stereo camera system is proposed. The depth information and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the automatic moving robot and the obstacle detected and the 2D spatial map obtained from the location coordinates, and then the relative distance between the obstacle and the other objects obtained from them. The AGV moves automatically by effective and intelligent route decision using the obtained 2D spatial map. From some experiments on robot driving with 480 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the objects is found to be very low value of 1.57% on average, respectably.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.411-418
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• 2003

The proposed system in this paper uses a camera attached to a mobile device in order to inquire a car and track its location anywhere. To do this, the system recognizes and verifies license plates on the front and back of a cu. The plates are scanned by the camera attached to a mobile device. The technology enables us to detect a car registration number and to transmit the number along with the location of the device to a server through a wireless communication network. The information of a car obtained through the terminal is encoded and transmitted to a server in a remote place through a wireless communication network also. The car registration number and its location information are decoded and transmitted as a text to the server in a remote place. In order to track a user´s location through spatial relative distance estimated in real-time, the server uses the spatial and attribute information which are the most prior to the desired data value. With this property information, the right location can be calculated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2737-2753
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• 2013

In this study, we propose a novel salient object detection strategy based on regional contrast and relative spatial compactness. Our algorithm consists of four basic steps. First, we learn color names offline using the probabilistic latent semantic analysis (PLSA) model to find the mapping between basic color names and pixel values. The color names can be used for image segmentation and region description. Second, image pixels are assigned to special color names according to their values, forming different color clusters. The saliency measure for every cluster is evaluated by its spatial compactness relative to other clusters rather than by the intra variance of the cluster alone. Third, every cluster is divided into local regions that are described with color name descriptors. The regional contrast is evaluated by computing the color distance between different regions in the entire image. Last, the final saliency map is constructed by incorporating the color cluster's spatial compactness measure and the corresponding regional contrast. Experiments show that our algorithm outperforms several existing salient object detection methods with higher precision and better recall rates when evaluated using public datasets.

• Journal of Broadcast Engineering
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• v.27 no.7
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• pp.974-984
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• 2022

In this paper, we introduce the minimum and maximum distance setting methods used in geometric distance attenuation processing, which is one of spatial sound reproduction methods. In general, sound attenuation by distance is inversely proportional to distance, that is 1/r law, but when the relative distance between the user and the audio object is very short or long, exceptional processing might be performed by setting the minimum distance or the maximum distance. While MPEG-I Immersive Audio's RM0 uses fixed values for the minimum and maximum distances, this study proposes effective methods for setting the distances considering the signal gain of an audio object. Proposed methods were verified through simulation of the proposed methods and experiments using RM0 renderer.

• Atmosphere
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• v.30 no.2
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• pp.169-181
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• 2020

We conducted a study on the impact of observation station density; this was done in order to enable the accurate estimation of spatial meteorological variables. The purpose of this study is to help operate an efficient observation network by examining distributions of temperature, relative humidity, and wind speed in a test area of a three-dimensional meteorological observation project in the Yeongdong region in 2019. For our analysis, we grouped the observation stations as follows: 41 stations (for Step 4), 34 stations (for Step 3), 17 stations (for Step 2), and 10 stations (for Step 1). Grid values were interpolated using the kriging method. We compared the spatial accuracy of the estimated meteorological grid by using station density. The effect of increased observation network density varied and was dependent on meteorological variables and weather conditions. The temperature is sufficient for the current weather observation network (featuring an average distance about 9.30 km between stations), and the relative humidity is sufficient when the average distance between stations is about 5.04 km. However, it is recommended that all observation networks, with an average distance of approximately 4.59 km between stations, be utilized for monitoring wind speed. In addition, this also enables the operation of an effective observation network through the classification of outliers.

• Korean Journal of Cognitive Science
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• v.25 no.2
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• pp.109-133
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• 2014

Psychological distance refers to the perceived gap between a stimulus and a person's direct experience and its activation influences the decisions and actions that the person makes towards the stimulus. We investigated whether the level of familiarity affects the construction of psychological distance. Specifically, we hypothesized that a familiar stimulus, relative to an unfamiliar stimulus, is perceived to be psychologically closer to the observer and so its perception might be modulated by the perceived spatial distance. The familiarity of stimuli was manipulated in terms of preexposure frequency and preexposure perceptual fluency. In experiments, participants were first exposed with three nonsense words in a lexical decision task. The nonsense words were presented in nonword trials with different levels of frequency (frequent vs. rare, Experiment 1) or with different levels of visibility (less blurred vs. more blurred, Experiment 2). Participants then performed a distance Stroop task with the most familiar and the least familiar nonwords. Each of them appeared in either proximal or distant spatial locations in scenes with clear depth cues. The results showed a significant interaction between the word familiarity and the spatial distance: the familiar word was judged faster in proximal locations but slower in distant locations relative to the unfamiliar word. The current findings suggest that metacognitive evaluation of familiarity could be one of the critical factors that underlie the construction of psychological distance.

• Journal of Environmental Impact Assessment
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• v.19 no.3
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• pp.223-230
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• 2010

Trajectory dispersion models are used for the dispersion calculations in air quality assessments, Yellow-sand modeling, environmental planning and the emergency response. Meso-scale forcing and coastal circulations are calculated by trajectory model in the East Asia region. In this study the meteorological fields (GDAS and MM5) coupled to the trajectory model (HY-SPLIT) are applied to simulate the transport and the dispersion. Seoul is selected as a starting point of the HY-SPLIT. The sensitivity studies are performed by conducting an ensemble of simulations using the GDAS and the MM5 model for the same dispersion cases. The results in this study show a significant difference depending on the resolution of meteorological models. Additionally, in most cases of the compared tionally,results from MM5 and GDAS, the absolute and relative distance, shows significant difference and the difference increased with the increasing distance of HY-SPLIT. Therefore, for the case of small domai for twi d field distefbution over complex terrai, should be used only high model temporal or spatial resolution to improve the HY-SPLIT model results.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.375-383
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• 2003

Clustering in spatial mining is to group similar objects based on their distance, connectivity or their relative density in space. In the real world. there exist many physical objects such as rivers, lakes and highways, and their presence may affect the result of clustering. In this paper, we define distance to handle obstacles, and using that we propose the density based clustering algorithm called DBSCAN-O to handle obstacles. We show that DBSCAN-O produce different clustering results from previous density based clustering algorithm DBSCAN by our experiment result.