• Ocean and Polar Research
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• v.30 no.1
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• pp.79-87
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• 2008

Hydroacoustic technique was used to analyze spatiotemporal stability and distribution of demersal fish aggregations in the coastal region to overcome some limitations of the existing methods such as net and diving. The survey was carried out in the Baekeum Bay on the south coast of Korea in January 2007. The bottom depth in the study site ranges from 7 to 25 m. In order to outline aggregations of demersal fish initial scanning using 200 kHz split-beam transducer was randomly conducted over the large area. Having detected fish aggregation in the specific region, intensive acoustic survey of irregular star pattern was carried out along 14 transects across the area in question. The results of the acoustic survey show that all demersal fish aggregations are concentrated about 5 m from sea bottom having a slight slope and remain steady with no spatial or temporal variations during acoustic survey. The hydroacoustic method used in this study offers a new approach to understand vertical and horizontal distribution, spatiotemporal stability, and biomass estimate of demersal fish aggregations in coastal regions. Additionally, the number of individual fish estimated from in situ acoustic target strength data can be used to understand the standing stock of demersal fish aggregation.

• Information Systems Review
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• v.11 no.1
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• pp.181-196
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• 2009

New domains in the analysis of the behavior of moving objects, particularly within human social settings, are generating research interest due to significant advances in the accuracy and production cost of global positioning system (GPS) devices. However, although potential applications have been described in multiple research areas, practical and viable business implementations of GPS technology remain challenging. This paper combines the potential of GPS capabilities with the analytical power of OLAP and data visualization to examine data on the movements of visitors in a zoological garden. Based on this example, the benefits and limitations of the application of GPS technology to the analysis of human spatial behavior are discussed.

• Spatial Information Research
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• v.14 no.2 s.37
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• pp.223-234
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• 2006

In order to examine spatio-temporal characteristics of coastal water quality, we applied GIS spatial analysis to the water quality data collected from observation points located on Korean coastal area during 1997$\sim$2004. The water quality parameters measured included: chlorophyll-a, pH, DO, COD, SS, dissolved inorganic nitrogen, dissolved inorganic phosphorous, salinity, temperature. The water quality data used in this paper was obtained only at selected sites even though they are potentially available at any location in a continuous surface. Thus, it is necessary to estimate the values at unsampled locations so as to analyze spatial distribution patterns of coastal water quality, Owing to this reason, we applied IDW(inverse distance weighted) interpolation method to water quality data and evaluated the usefulness of IDW method. After IDW interfolation method was applied, we divided the Korean coastal area into 46 sections and examined spatio-temporal patterns of each section using GIS visualization technique. As a result of evaluation, we can blow that IDW interpolation and GIS are useful for understanding spatial and temporal distribution characteristics of coastal water quality data which is collected from a wide area far many years.

• Phonetics and Speech Sciences
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• v.7 no.1
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• pp.151-163
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• 2015

In this study, we aim to describe kinematic characteristics of Korean /l/-flapping in two speech rates (fast vs. comfortable). Production data was collected from seven native speakers of Seoul Korean (four females and three males) using electromagnetic midsagittal articulometry (EMMA), which provided two dimensional data on the x-y plane. We examined kinematic properties of the vertical/horizontal tongue tip gesture, the vertical/horizontal (rear) tongue body gesture, and the jaw gesture in an /i/-/i/ context. Gestural landmarks of the vertical tongue tip gesture are directly measured. This serves as the actual anchoring time points to which relevant measures of other trajectories referred. The study focuses on velocity profiles, closing/opening spatiotemporal properties, constriction duration, and constriction minima were analyzed. The results are summarized as follows. First, gradiently distributed spatiotemporal values of the vertical tongue tip gesture were on a continuum. This shows more of a reduction in fast speech rate, but no single instance of categorical reduction (deletion). Second, Korean /l/-flapping predominantly exhibited a backward sliding tongue tip movement, in 83% of production, which is apparently distinguished from forward sliding movement in English. Lastly, there was an indication of vocalic reduction in fast rate, truncating spatial displacement of the jaw and the tongue body, although we did not observe positional variations with speech rate. The present study shows that Korean /l/-flapping is characterized by mixed articulatory properties with respect to flapping sounds of other languages such as English and Xiangxiang Chinese. Korean /l/ flapping demonstrates a language-universal property, such as the gradient nature of its flapping sounds that is compatible with other languages. On the other hand, Korean /l/-flapping also shows a language-particular property, particularly distinguished from English, in that a backward gliding movement occurs during the tongue tip closing movement. Although, there was no vocalic reduction in V2 observed in terms of jaw and tongue body height, spatial displacement of these articulators still suggests truncation in fast speech rate.

• Spatial Information Research
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• v.20 no.2
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• pp.129-136
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• 2012

Recently international organizations such as ISO/TC211, OGC, INSPIRE (Infrastructure for Spatial Information in Europe) make an effort to share geospatial data using semantic web technologies. In addition, smart phone and social networking services enable community-based opportunities for participants to share issues of a social phenomenon based on geographic area, and many researchers try to find a method of extracting issues from that. However, serviceable spatial ontologies are still insufficient at application level, and studies of spatial information extraction from SNS were focused on user's location finding or geocoding by text mining. Therefore, a study of extracting spatial phenomenon from social media information and converting it into geosemantic knowledge is very usable. In this paper, we propose a framework for extracting keywords from micro-blog, one of the social media services, finding their relationships using data mining technique, and converting it into spatiotemopral knowledge. The result of this study could be used for implementing a related system as a procedure and ontology model for constructing geoseem antic issue. And from this, it is expected to improve the effectiveness of finding, publishing and analysing spatial issues.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.148-148
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• 2022

Spatiotemporal precipitation data is one of the primary quantities in hydrological as well as climatological studies. Despite the fact that the estimation of these data has made considerable progress owing to advances in remote sensing, the discrepancy between satellite-derived precipitation product (SPP) data and observed data is still remarkable. This study aims to propose an effective deep learning model (DLM) for bias correction of SPPs. In which TRMM (The Tropical Rainfall Measuring Mission), CMORPH (CPC Morphing technique), and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) are three SPPs with a spatial resolution of 0.25o exploited for bias correction, and APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) data is used as a benchmark to evaluate the effectiveness of DLM. We selected the Mekong River Basin as a case study area because it is one of the largest watersheds in the world and spans many countries. The adjusted dataset has demonstrated an impressive performance of DLM in bias correction of SPPs in terms of both spatial and temporal evaluation. The findings of this study indicate that DLM can generate reliable estimates for the gridded satellite-based precipitation bias correction.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.77-81
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• 2015

The unit price contracting is the standard contracting method for highway projects in the U.S. As a result, state highway agencies have collected a large amount of historical bid data that they can use to determine engineer's estimates for future projects. The estimator must carefully consider various characteristics of a new project such as its location to determine an engineer's estimate as accurate as possible before bid letting. Higher cost estimates can result in the loss of the available budget and lower cost estimates may lead to deferral and delay of projects. The study uses the historical bid data obtained from Iowa Department of Transportation and develops a Geographic Information System (GIS) tool to visually show the variation of unit prices over the map using a spatial interpolation technique. The interpolation map can be used to estimate the unit price of the item at any location across Iowa. This noble method allows the estimator to effectively and fully utilize the historical bid data in a very time efficient manner and determine more accurate cost estimation.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.119-121
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• 2008

Pattern matching is increasingly being employed in various researches as health care service, RFID-based system, facility management, and surveillance. Geosensor filter correlates a data stream to match specific patterns in distribution environments. In this paper, we present a geosensor query language to represent efficiently declarative geosensor query. Geosensor operators are proposed to use for fast query processing in terms of spatial and temporal area in distribution environments. We also propose a geosensor filter to match new query predicates into incoming stream predicates. Our filter can reduce the volume of transmission data and save power consumption of sensors. It can be utilized the stream data mining system to process in real-time various data as location, time, and geosensor information in distribution environments.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.250-252
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• 2004

In this paper we apply several variations of independent component analysis( ICA) methods, such as spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA), to yeast cell cycle datasets, and compare their performance in finding components that result in gene clusters coherent with annotations and in extract ins meaningful temporal modes. It turns out that the results of tICA are superior to those of PCA, sICA, and stICA in terms of gene clustering and the temporal modes extracted by stICA highlights particular cellular processes.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.609-626
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• 2020

Satellite-based land surface temperature (LST) has been used as one of the major parameters in various climate and environmental models. Especially, Moderate Resolution Imaging Spectroradiometer (MODIS) LST is the most widely used satellite-based LST product due to its spatiotemporal coverage (1 km spatial and sub-daily temporal resolutions) and longevity (> 20 years). However, there is an increasing demand for LST products with finer spatial resolution (e.g., 10-250 m) over regions such as urban areas. Therefore, various methods have been proposed to produce high-resolution MODIS-like LST less than 250 m (e.g., 100 m). The purpose of this review is to provide a comprehensive overview of recent research trends and challenges for the downscaling of MODIS LST. Based on the recent literature survey for the past decade, the downscaling techniques classified into three groups-kernel-driven, fusion-based, and the combination of kernel-driven and fusion-based methods-were reviewed with their pros and cons. Then, five open issues and challenges were discussed: uncertainty in LST retrievals, low thermal contrast, the nonlinearity of LST temporal change, cloud contamination, and model generalization. Future research directions of LST downscaling were finally provided.