• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.45-56
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• 2003

In the wireless environment, according to the development of technology, which is able to obtain location information of spatiotemporal moving object, the various application systems are developed such as vehicle tracking system, forest fire management system and digital battle field system. These application systems need the data model, which is able to represent and process the continuous change of moving object. However, if moving objects are expressed by a relational model, there is a problem which is not able to store all location information that changed per every time. Also, existing data models of moving object have a week point, which constrain the query time to the time that is managed in the database such as past or current and near future. Therefore, in this paper, we propose a data model, which is able to not only express the continuous movement of moving point and moving region but also process the operation at all query time by using shape-change process and location determination functions for past and future. In addition, we apply the proposed model to forest fire management system and evaluate the validity through the implementation result.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.307-316
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• 2009

In this paper, the spatiotemporal data mining methodology for detecting a cycle of power consumption pattern with the change of time and spatial was proposed, and applied to the power consumption data collected by GIS-AMR system with an aim to use its resulting knowledge in real world applications. First, partial clustering method was applied for cluster analysis concerned with the aim of customer's power consumption. Second, the patterns of customer's power consumption data which contain time and spatial attribute were detected by 3D cube mining method. Third, using the calendar pattern mining method for detection of cyclic patterns in the various time domains, the meanings and relationships of time attribute which is previously detected patterns were analyzed and predicted. For the evaluation of the proposed spatiotemporal data mining, we analyzed and predicted the power consumption patterns included the cycle of time and spatial feature from total 266,426 data of 3,256 customers with high power consumption from Jan. 2007 to Apr. 2007 supported by the GIS-AMR system in KEPRI. As a result of applying the proposed analysis methodology, cyclic patterns of each representative profiles of a group is identified on time and location.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

• Knowledge Management Research
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• v.21 no.2
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• pp.119-135
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• 2020

Owing to pandemic (COVID-19), the traditional face-to-face education method has been changed to the non-face-to-face real-time online education methods. Using a real time-based video conference system, synchronous education can be adopted by face-to-face class easily. Specially, it is very important to minimize the difference in learning effects between face-to-face and non-face-to-face in Entrepreneurship education. In this study, in order to derive the factors that affect the satisfaction of learners in synchronous online education, authors collected data from learners taking a synchronous entrepreneurship course. Through previous research, learned the reality of education and the composition of lessons. Spatiotemporal effectiveness, mentor ability, and educational environment influence learning satisfaction. PLS-SEM results revealed that it was confirmed that only spatiotemporal effects affect learner satisfaction. However, the education environment (fluent operation and convenience of function use of real-time based online conference system) effect teaching presence, class structure, and spatiotemporal effects. Through this research, we hope to provide theoretical and practical support for developing effective teacher activities, proper lesson structure, convenient function of the conference system, and learner-centered online learning environment when developing synchronous online classes.

• The Journal of the Acoustical Society of Korea
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• v.38 no.5
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• pp.587-592
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• 2019

ISI (Inter Symbol Interference) reduces the performance of UAComm (Underwater Acoustic Communication). This paper shows that the performance of UAComm can be improved through the spatiotemporal diversity method that is the combination of spatial diversity and temporal diversity methods. By using spatiotemporal diversity, the array aperture was reduced to increase the efficiency of the UAComm system. It is also verified using the experimental data of BLAC18 (Biomimetic Long range Acoustic Communication 18) conducted in October 2018.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.179-186
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• 2008

The converge of location-aware devices, GIS functionalities and the increasing accuracy and availability of positioning technologies pave the way to a range of new types of location-based services. The field of spatiotemporal data mining where relationships are defined by spatial and temporal aspect of data is encountering big challenges since the increased search space of knowledge. Therefore, we aim to propose algorithms for mining spatiotemporal patterns in mobile environment in this paper. Moving patterns are generated utilizing two algorithms called All_MOP and Max_MOP. The first one mines all frequent patterns and the other discovers only maximal frequent patterns. Our proposed approach is able to reduce consuming time through comparison with DFS_MINE algorithm. In addition, our approach is applicable to location-based services such as tourist service, traffic service, and so on.

• Journal of Environmental Health Sciences
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• v.48 no.5
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• pp.272-281
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• 2022

Background: The constant consumption of chemical products owing to expanding industrialization has led to an increase in public interest in chemical substances. As the production and disposal processes for these chemical products cause environmental problems, regional information on the hazard level of chemical substances is required considering their effects on humans and in order to ensure environmental safety. Objectives: This study aimed to identify hazard contribution and spatiotemporal characteristics by region and chemical by calculating a hazard-based result score using pollutant release and transfer register (PRTR) data. Methods: This study calculated the chemical discharge and hazard-based result score from the Risk-Screening Environmental Indicators (RSEI) model, analyzed their spatiotemporal patterns, and identified hotspot areas where chemical discharges and high hazard-based scores were concentrated. The amount of chemical discharge and hazard-based risk scores for 250 cities and counties across South Korea were calculated using PRTR data from 2011 to 2018. Results: The chemical discharge (high densities in Incheon, Daegu, and Busan) and hazard-based result scores (high densities in Incheon, Chungcheongnam-do, and some areas of Gyeongsangnam-do Province) showed varying spatial patterns. The chemical discharge (A, B) and hazard-based result score (C, D) hotspots were identified. Additionally, identification of the hazard-based result scores revealed differences in the type of chemicals contributing to the discharge. Ethylbenzene accounted for ≥80% of the discharged chemicals in the discharge hotspots, while chromium accounted for >90% of the discharged chemicals in the hazard-based result score hotspots. Conclusions: The RSEI hazard-based result score is a quantitative indicator that considers the degree of impact on human health as a toxicity-weighted value. It can be used for the management of industries discharging chemical substances as well as local environmental health management.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.95-104
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• 2018

This study has the purpose of suggesting the method to analyze the spatiotemporal change of satisfaction concerning the officially assessed land price using geostatistical analysis. Analyzing the spatial distribution characteristic of officially assessed land price using present GIS (Geographic Information System) or is staying at qualitatively suggesting the improvement method of the officially assessed land price system. Grouping the appeal strength based on the official price and opinion price of officially assessed land price, GIS DB (Database) was constructed and the time seriate satisfaction were analyzed and compared through spatial density analysis and spatial autocorrelation analysis. As a result, it was found that the difference between the official price and the applicant's price differed depending on individual land, but most of the respondents requested the increase or the reduction of the average land price, which resulted in a large number of request. Analyzing the satisfaction of the officially assessed land price by using GIS, it was known that satisfaction of officially assessed land price could be analyzed by using the difference of the opinion price and not only the officially assessed land price. Spatiotemporal change of officially assessed land price satisfaction was known to be possible through spatiotemporal pattern analysis method such as spatiotemporal auto-corelation analysis and hotspot analysis etc using GIS. In short, regionally positive or negative significant relationship was investigated through spatiotemporal analysis using annual data.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7737-7742
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• 2015

Background: Cancer is one of the common causes of disability and mortality in the world. The present study aimed to define the spatiotemporal distribution of gastrointestinal tract cancers using a geographic information system (GIS) over the time period of 2007-2012 in Kermanshah-Iran. Materials and Methods: The method of studying was descriptive-analytical as well as comparative with gastrointestinal tract cancer patients based in the City of Kermanshah over the time period covered. For data analysis, the GIS and SPSS 16.0 were applied. Results: According to the pathological reports within the space of 5 years, 283 cases of gastrointestinal tract cancer (157 in males, 156 in females) were reported. The performed tests in terms of spatial distribution in the environment of GIS indicated that the disease demonstrated a clustered pattern in the City of Kermanshah. More to the point, some loci of this disease have emerged in the City of Kermanshah that in the first level, 6 neighborhoods with 29-59 cases of this disease per square kilometer and in the second level, 15-29 cases. Conclusions: Gastrointestinal tract cancer demonstrated an ascending trend within the space of 5 years of research and the spatiotemporal distribution of cancer featured a concentrated and clustered pattern in the City of Kermanshah.

• 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.