• 환경생물
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• 제21권4호
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• pp.422-427
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• 2003

The spatio-temporal distribution of four coexisting acartiid species in two subgenera Acartiura (Acartia hongi and A. omorii) and Odontacartia (A. erythraea and A. pacifica) was examined at seven stations in the southwestern waters of Korea, between January to December 1998. A. hongi occurred dominantly in the northern regions from winter to spring while A. omorii predominated in the southern regions in spring and early summer when the more saline (> 33.0 psu) and high chlorophyll-$\alpha$ concentration water mass appeared. With the increase of temperature (> $20^{\circ}C$), however, both species disappeared and then replaced with A. erythraea and A. pacifica. A. erythraea (rare species), appeared in the middle regions where the high chlorophyll-$\alpha$ concentration ($3{\mu}g\; I^{-1}$) in the summer, while A. pacifica was abundant in all regions through summer and fall. It is suggested that the seasonal succession of the genus Acartia was subgenus-specifically affected by environmental factors such as temperature, salinity and chlorophyll-$\alpha$ concentration.

• 한국정보과학회논문지:데이타베이스
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• 제30권2호
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• pp.176-183
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• 2003

질의 최적화에 사용하기 위한 선택도 추정 방법은 히스토그램, 샘플링 그리고 패러미터에 의한 요약 방법 등이 제시되고 있다. 히스토그램을 이용한 선택도 추정은 상용 데이타베이스 시스템에서 가장 보편적으로 사용되는 방법이지만, 이동 객체를 위한 시공간 데이타베이스에서는 데이타 분포가 지속적으로 변화함으로써 기존의 히스토그램 방법을 이용하는 것은 제한이 많게 된다. 특히 미래 질의를 위해서는 데이타 갱신을 반영하는 동적 관리가 가능하며, 정화도를 유지할 수 있는 다른 접근 방법이 필요하다. 따라서 시공간 객체를 위한 선택도 추정 방법은 질의 술어가 요구하는 데이타 분포에 대한 히스토그램이 필요하며, 본 논문에서는 미래의 시공간 영역 질의 술어에 대하여 신속히 히스토그램을 생성할 수 있도록 쌍대성과 한계 분포 방법을 이용한 히스토그램을 제안한다. 쌍대 공간에서 이동 객체에 대한 데이타 시놉시스를 이용하여 구성된 시공간 히스토그램은 이동 궤적의 선형성이 유지하는 시간 동안 정확성을 보장하면서 빠른 시간에 생성이 가능하다. 또한 동적 갱신을 점증적으로 지원함으로써 효율적으로 갱신된 정보를 반영할 수 있고 추정 결과의 정확성을 향상시킬 수 있다.

• Transactions on Electrical and Electronic Materials
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• 제8권4호
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• pp.182-187
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• 2007

The use of the pulsed electro acoustic (PEA) method allowed us to perform the direct observations of spatio-temporal charge distributions in Electric double layer capacitors (EDLCs) based on polarizable nanoporous carbonaceous electrode. The negative charge density became the maximum, about $205C/m^3$ at the region where was near to collector layer in EDLCs for case $V_{DC}=2.5V$, while the positively charged density became the maximum, about $61.1C/m^3$ at the region where it was located around the cathode layer. The performance of the best sample was found to be better in terms of the charge density (Cs) and specific energy ($E_s$) with a maximum value of ${\sim}8.4F/g$ and 26 Wh/kg. The $C_s$ obtained from the PEA method agreed well with that from the energy conversion method. The PEA measurement used here is a very useful method to quantitively investigates the spatio-temporal charge distribution in EDLCs.

• 한국환경과학회지
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• 제27권7호
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• pp.499-507
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• 2018

Agricultural meteorological information is an important resource that affects farmers' income, food security, and agricultural conditions. Thus, such data are used in various fields that are responsible for planning, enforcing, and evaluating agricultural policies. The meteorological information obtained from automatic weather observation systems operated by rural development agencies contains missing values owing to temporary mechanical or communication deficiencies. It is known that missing values lead to reduction in the reliability and validity of the model. In this study, the hierarchical Bayesian spatio-temporal model suggests replacements for missing values because the meteorological information includes spatio-temporal correlation. The prior distribution is very important in the Bayesian approach. However, we found a problem where the spatial decay parameter was not converged through the trace plot. A suitable spatial decay parameter, estimated on the bias of root-mean-square error (RMSE), which was determined to be the difference between the predicted and observed values. The latitude, longitude, and altitude were considered as covariates. The estimated spatial decay parameters were 0.041 and 0.039, for the spatio-temporal model with latitude and longitude and for latitude, longitude, and altitude, respectively. The posterior distributions were stable after the spatial decay parameter was fixed. root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and bias were calculated for model validation. Finally, the missing values were generated using the independent Gaussian process model.

• 산업경영시스템학회지
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• 제46권3호
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• pp.251-258
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• 2023

This study (1) explored spatio-temporal population distribution patterns in Jeonju by using emerging hot spot analysis and (2) identified the influential factors to determine the spatio-temporal patterns by using multinomial logit model. The major findings are as follows. First, the results of emerging hot spot analysis indicated that the 100*100m grid in the urban area of Jeonju was found to have a category of hot spots, whereas most of the cold spot series was concentrated in the outskirts of the city. Also, new towns such as Jeonju Eco City, Jeonbuk Innovation City, and Hyocheon District were persistent or intensifying hot spots, Third, the results of multinomial logit model revealed that the factors influencing deterrmining the spatio-temporal patterns were accessibility to schools, hospitals, parks, and walfare services. This study offered a deeper understanding of urbanization and regional changes in Jeonju, and important information for urban planning.

• 한국해양학회지:바다
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• 제8권3호
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• pp.243-250
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• 2003

본 연구는 경기만 동물플랑크톤 군집의 시공간적 분포 특성을 파악하기 위하여 2001년 2월부터 2001년 12월까지 인천 연안에서 선갑도에 이르는 수역에서 5개 정점을 대상으로 월별 조사가 실시되었다. 연구 기간중 출현한 동물플랑크톤 개체수는 월평균 1,100∼404,200 indiv./㎥의 범위로 2월에 가장 적은 개체수가 출현하였고 8월에 가장 많은 개체수가 출현하였으며 연구 기간 평균 개체수는 55,000 indiv./㎥였다. 정점별 평균 개체수는 인천 연안 수역에서 114,600 indiv./㎥로 가장 많았고 외해쪽으로 갈수록 감소하여 선갑도 부근 수역에서 16,500 indiv./㎥가 출현하였다. 경기만에서 우점하여 출현한 동물플랑크톤은 Noctiluca scintillans, Acartia hongi, Oithona davisae, Paracalanus crassirostris, Paracalanus indicus, Oikopluera spp. 였으며 이들에 의해 전체 평균 동물플랑크톤 개체수의 94.9％가 점유되었다 대부분의 우점종들은 경기만에서 연중 넓게 분포하지만 계절에 따른 개체수의 대량 증가 현상은 내만 수역에서 집중되는 현상이 나타났으며 이러한 시, 공간적 분포 특성은 수온과 식물플랑크톤 현존량에 의해 크게 영향을 받는 것으로 판단된다.

• 한국수산과학회지
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• 제56권4호
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• pp.558-568
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• 2023

The spatio-temporal distribution of the sand crab Ovalipes punctatus larvae was investigated in the Korean waters in 2019. Sea surface temperature (SST) was the lowest in February and highest in September. Sea surface salinity (SSS) was the lowest in September and highest in March. Further, sea surface chlorophyll a (SSC) was the highest in September. Larvae were distributed in the South Sea and coastal area of Jeju Island from April to June, and the abundance was the highest in May. The spatio-temporal distribution analysis suggested that larval groups showed a tendency to be dispersed over a wider area as the larvae developed, due to the increase in their swimming ability. The correlation analysis between environmental factors and larval density suggested that larvae appeared in the SST range 11.8-20.9℃ and SSS range 31.5-35.3 psu. The Megalopal stage appeared in a wider range of SST and SSS than other larval stages, possibly due to the increased environmental tolerance before settlement. Results of redundancy analysis (RDA) and Spearman's rank correlation analysis between the larval density by developmental stages and the environmental factors suggested that SST showed a positive correlation and SSC showed a negative correlation in the later stage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권10호
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• pp.2632-2649
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• 2012

Most approaches to human action recognition is limited due to the use of simple action datasets under controlled environments or focus on excessively localized features without sufficiently exploring the spatio-temporal information. This paper proposed a framework for recognizing realistic human actions. Specifically, a new action representation is proposed based on computing a rich set of descriptors from keypoint trajectories. To obtain efficient and compact representations for actions, we develop a feature fusion method to combine spatial-temporal local motion descriptors by the movement of the camera which is detected by the distribution of spatio-temporal interest points in the clips. A new topic model called Markov Semantic Model is proposed for semantic feature selection which relies on the different kinds of dependencies between words produced by "syntactic " and "semantic" constraints. The informative features are selected collaboratively based on the different types of dependencies between words produced by short range and long range constraints. Building on the nonlinear SVMs, we validate this proposed hierarchical framework on several realistic action datasets.

• Ocean Science Journal
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• 제43권4호
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• pp.209-222
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• 2008

To understand physical structures in the Korean waters, we investigated the spatio-temporal distribution of Pontella species known as indicator species of water mass using a David-Hempel neuston net from April 2002 to March 2003. Five Pontella species (P. chierchiae Giesbrecht, P. fera Dana, P. latifurca Chen and Zhang, P. securifer Brady and P. sinica Chen and Zhang) were found. Their abundance increased from May to October with increasing the surface water temperature. Pontella chierchiae predominantly appeared in the whole areas while P. latifurca scarcely occurred in coastal waters. The other three species (P. fera, P. securifer and P. sinica) were rarely found in the South Sea of Korea on August to September. We suggest that P. securifer and P. fera as oceanic species can play a role in an indicator species of the Tsushima Warm Current while P. sinica as Chinese coastal species is affected by the diluted waters of the Yantze River. We also provide re-description of the three species (P. chierchiae, P. fera and P. latifurca) insufficiently described and discuss their zoogeography.

• 대한토목학회논문집
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• 제31권1B호
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• pp.13-20
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• 2011

강수량은 시공간적으로 변화하는 수문변량으로서 강수량의 시간적인 특성 또한 강수량의 특성을 정의하는데 매우 중요한 요소이다. 본 연구에서는 극치강수량의 지역빈도해석을 위한 범주화 과정에서 기존의 강수량과 관측소 위치좌표만을 이용한 범주화를 통해 해결할 수 없는 강우 발생의 계절적 변화와 집중에 대한 고려를 반영하기 위하여, 기존의 양적 범주화 과정에 시간적인 영향을 고려할 수 있는 요소로서 극치강수량 발생 시기 통계치를 활용할 수 있는 범주화 과정을 제시하였다. 본 연구에서는 극치강수량의 발생 시기에 대한 정량적인 분석이 가능한 순환통계기법을 이용하여 관측 지점별 시간 통계량을 산정하고, 이를 극치강수량과 결합하여 시 공간적인 특성자료를 생성한 후 수정 K-means 방법을 이용하여 군집화 해석을 수행하였으며, 전국을 다섯 개의 군집으로 분류하였다. 기존의 양적 범주화 결과와의 비교를 통해 발생 시간 통계치를 결합한 범주화 결과가 지형 및 권역을 반영하는 결과를 보임을 확인하였다.