• Journal of the Korean Association of Geographic Information Studies
• /
• v.14 no.4
• /
• pp.182-193
• /
• 2011

In order to compare the spatio-temporal variation pattern of sea surface temperature (SST) in Korea's Southern areas of the sea according to a regional scale, this study has selected the winter and summer seasons for 31 years (1980~2010) in a period aspect and selected three areas of the sea such as the Western areas of the sea (region B) and Eastern areas of the sea (region C) around Jeju Island in addition to overall Southern areas of the sea (region A) in regional aspect. The regression analysis was applied to find out a temporal variation pattern of SST, and the weighted mean center (WMC) of SST as well as analysis of a standard deviational ellipse (SDE) was respectively applied. As a result of regression analysis of SST, it showed a rising long-term trend for all two seasons in three regions. However, though the average SST for 31 years was all similar in three regions in the summer season, the region C appeared more highly than region B in the winter season. The spatial variation pattern of SST for two seasons showed that it is respectively different from each other in three regions. The spatial variation pattern of SST appeared as E-W direction in region A, SE-NW direction in region B and SW-NE direction in region C. In addition, the relationship between the location of the WMC of SST and the average SST showed correlation in regions A and B in the winter season, whereas it appeared that there is no correlation in region C. Accordingly, it can be known that the regional scale should be considered in case of analysis of spatio-temporal variation patterns of SST.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.12
• /
• pp.8147-8156
• /
• 2015

This study analyzes the Pattern Language of Insadong-gil in street environmental design analysis for street vitalization. The urban public spaces, such as pedestrian streets, parks and plazas, have been increased with rapid urbanization and industrialization. But the fact is the satisfied spaces with the behavior patterns of users is little. This is because of the too much slanted thought toward formal supply and management of spaces without enough consideration for people and spatial quality of public spaces. The purpose of this study is to find out the factors to make the street more vital and diverse and to give the characteristic of region through the research on Insadong street with the pattern language of Christopher Alexander. So, throughout the value recognition of the changing urban street environment that has been changed by age selected spatial characteristic of public spaces. By selecting a suitable pattern language for each spatial characteristics provide the basis for street environmental design analysis. For this study, look at the relationship between pattern language focused on Insadong street, pattern language as the vitalization factor of street were analyzed 16 elements, including Pedestrian Street(100), Building Fronts(122), Activity Nodes(30) etc. This study focuses on street environmental design analysis of Insadong-gil through the Pattern Language, it propose the criteria and guidelines that will help enable street vitalization.

• Journal of Korean Society of Transportation
• /
• v.26 no.3
• /
• pp.75-84
• /
• 2008

In 2002, the 5-day workweek policy was effective in Korea. As we have expected, the 5-day workweek policy has changed people's travel behavior during weekdays and weekends. Several studies have been done to understand these changes and impacts on transportation systems. However, these studies have only focused on travel pattern changes without considering spatial factors. Said in another way, although individual travel pattern changes are usually investigated, indices adopted cannot describe travel pattern changes in a proper way due to lack of the spatial distribution measure. This study aims to analyze travel change since the 5-day work week policy in effect using a new index (i.e. Travel Vector Index) developed in this study, which can explain travel pattern changes in terms of magnitude and spatial point of views. The new index uses a GIS technology and TCS (Toll Collection System) databases in Korea. The results in this study show that the index is very useful and reliable to measure the travel patterns changes. They are applied to TCS data set and the results show that the 5-day workweek policy significantly affects on travel behaviors.

• Journal of the Korean Geographical Society
• /
• v.39 no.3
• /
• pp.457-472
• /
• 2004

The purpose of this study is to analyze spatial patterns of traffic accidents and to investigate spatial relations among neighboring spatial objects by applying GIS and spatial data mining methods. This study investigated traffic accident data in Kangnam-gu, Seoul, as a case study. As a result, four clusters were emerged based on individual attributes of traffic accidents. Each cluster showed distinctive properties. In spatial associations between individual attributes of traffic accidents and neighboring spatial objects, there were many rules according to concept hierarchy and definition of spatial relations. Although all rules were not be interesting and significant, they could be a clue to investigate more.

• Proceedings of the KAIS Fall Conference
• /
• 2010.05b
• /
• pp.630-633
• /
• 2010

입지분석은 공간 및 비공간적 특성이 중요하게 다루어져야 함에도 불구하고 공간데이터 타입(spatial data type), 공간관계(spatial relationship), 그리고 공간 자기상관성(spatial autocorrelation)의 복잡성에 기인한 처리의 어려움으로 인해 기하학적거리나 공간적 위치와 같은 단순 공간적 특성만 이용되었다. 본 연구에서는 서울시 대형할인점을 사례로하여로 GIS에 의한 공간데이터와 비공간데이터(인구통계 등)를 통합 구축한 후, 공간데이터마이닝 기법을 이용하여 입지패턴(location pattern)을 분석 추출하여 보고자 한다.

• Journal of Korea Spatial Information System Society
• /
• v.10 no.2
• /
• pp.63-79
• /
• 2008

With the recent development of advanced GIS and complex spatial analysis technologies, the more sophisticated technologies are being required to support the advanced knowledge for solving geographical or spatial problems in various decision support systems. In addition, necessity for research on scientific crime investigation and forensic science is increasing particularly at law enforcement agencies and investigation institutions for efficient investigation and the prevention of crimes. There are active researches on geographic profiling to predict the base location such as criminals' residence by analyzing the spatial patterns of serial crimes. However, as previous researches on geographic profiling use simply statistical methods for spatial pattern analysis and do not apply a variety of spatial and temporal analysis technologies on serial crimes, they have the low prediction accuracy. Therefore, this paper identifies the typology the spatio-temporal patterns of serial crimes according to spatial distribution of crime sites and temporal distribution on occurrence of crimes and proposes STA-BLP(Spatio-Temporal Analysis based Base Location Prediction) algorithm which predicts the base location of serial crimes more accurately based on the patterns. STA-BLP improves the prediction accuracy by considering of the anisotropic pattern of serial crimes committed by criminals who prefer specific directions on a crime trip and the learning effect of criminals through repeated movement along the same route. In addition, it can predict base location more accurately in the serial crimes from multiple bases with the local prediction for some crime sites included in a cluster and the global prediction for all crime sites. Through a variety of experiments, we proved the superiority of the STA-BLP by comparing it with previous algorithms in terms of prediction accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.4A
• /
• pp.558-565
• /
• 2000

While research of ATPG(automatic test pattern generation) for combinational circuits almost reaches a satisfiable level, one for sequential circuits still requires more research. In this paper, we propose new algorithm for sequential ATPG based on state information learning. By efficiently storing the information of the state searched during the process of test pattern generation and using the state information that has been already stored, test pattern generation becomes more efficient in time, fault coverage, and the number of test patterns. Through some experiments with ISCAS '89 benchmark circuits, the efficiency of the proposed method is shown.

• Journal of Korean Society for Geospatial Information Science
• /
• v.23 no.1
• /
• pp.39-45
• /
• 2015

The housing market is transformed by a variety of socio-economic characteristics, also appeared differently according to regional characteristics. This study aims to draw out the change factors influencing on the housing market structure and to analyze the drawn factors' distribution pattern by area. For this purpose, First, targeting 251 areas in the units of city, county and districts nationwide, this study drew out demographic, socio-economic variables influencing on the housing market structure for 5 years ranging 2005 to 2010. For that, the factor analysis was conducted. Second, this study grasped the change factors of the housing market structure's spatial patterns using the kriging method, a spatial statistical method. Third, this study used the Moran I, one of spatial autocorrelation analysis methods in order to grasp whether the factors had statistically significant concentration or dispersion or showed a random distribution pattern.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.1
• /
• pp.199-206
• /
• 2018

This study was to investigate the Influence of smart phone use on gait in healthy adults. Twenty healthy adults were recruited in this study. All subjects performed twice for each normal gait and smart phone gait. The normal gait walked at their chosen speed, and the smart phone gait walked while watching the video. GAITRite system was used to identify the temporal and spatial variables related to the gait pattern during walking. Statistical analysis was analyzed by paired t-test. In comparison of temporal variables, smart phone gait was significantly lower in gait speed and cadence than in normal gait(p<.05), and was significantly longer in single support time and double support time(p<.05). In comparison of spatial variables, smart phone gait was significantly shorter in step length and stride length than in normal gait(p<.05) and significantly longer in step width(p<.05). The results of this study demonstrated that smartphone use can negatively affect the correct gait patterns during walking.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.12
• /
• pp.5015-5022
• /
• 2010

Most of the existing pattern mining techniques are capable of searching patterns according to the continuous change of the spatial information of an object but there is no constraint on the spatial information that must be included in the extracted pattern. Thus, the existing techniques are not applicable to the optimal path search between specific nodes or path prediction considering the nodes that a moving object is required to round during a unit time. In this paper, the precision of the path search according to the spatial hierarchy is analyzed using the Spatial-Temporal Optimal Moving Pattern(with Frequency & Weight) (STOPM(FW)) algorithm which searches for the optimal moving path by considering the most frequent pattern and other weighted factors such as time and cost. The result of analysis shows that the database retrieval time is minimized through the reduction of retrieval range applying with the spatial constraints. Also, the optimal moving pattern is efficiently obtained by considering whether the moving pattern is included in each hierarchical spatial scope of the spatial hierarchy or not.