• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.90-103
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• 2012

Mallipo is a representative beach contaminated by Hebei Spirit oil spill accident in December 2007. This study aims to compare the differences of two seasons (winter and summer) for the spatio-temporal variation patterns of oiling status in the whole area and divided five regions of Mallipo beach. In the whole area, the decreasing rate of average TPH (total petroleum hydrocarbon) in winter was twice greater than summer during four years. According to the spatial variation pattern analysis of oiling status using weighted mean center and weighted standard distance, the oil concentration was clustered on southwestern region in winter, however, the TPH was dispersed in the whole area in summer. Temporal variation pattern of TPH in each of Mallipo's five regions showed that TPH had been consistently decreased in winter, but oil concentration had not been changed in summer since 2009 except the southwestern region. Therefore, in order to evaluate and predict the progress of oiling status, it is needed to analyze the spatio-temporal variation pattern of TPH using spatial analysis after separating data into seasons (e.g., winter and summer). In addition, time series analysis is useful in the regional scales through spatial partitioning rather than the whole beach area for the understanding of temporal variation pattern.

• Journal of the Korean Society of Physical Medicine
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• v.13 no.3
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• pp.19-25
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• 2018

PURPOSE: Most gait assessment tools are expensive and require controlled laboratory environments. Tri-axial accelerometers have been used in gait analysis as an alternative to laboratory assessments. Many smartphones have added an accelerometer, making it possible to assess spatio-temporal gait parameters. This study was conducted to confirm the reliability and validity of a smartphone-based accelerometer at quantifying spatio-temporal gait parameters of stroke patients when attached to the body. METHODS: We measured gait parameters using a smartphone accelerometer and gait parameters through the GAITRite analysis system and the reliability and validity of the smartphone-based accelerometer for quantifying spatio-temporal gait parameters for stroke patients were then evaluated. Thirty stroke patients were asked to walk at self-selected comfortable speeds over a 10 m walkway, during which time gait velocity, cadence and step length were computed from smartphone-based accelerometers and validated with a GAITRite analysis system. RESULTS: Smartphone data was found to have excellent reliability ($ICC2,1{\geq}.98$) for measuring the tested parameters, with a high correlation being observed between smartphone-based gait parameters and GAITRite analysis system-based gait parameters (r = .99, .97, .41 for gait velocity, cadence, step length, respectively). CONCLUSION: The results suggest that specific opportunities exist for smartphone-based gait assessment as an alternative to conventional gait assessment. Moreover, smartphone-based gait assessment can provide objective information about changes in the spatio-temporal gait parameters of stroke subjects.

• Journal of KIISE:Databases
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• v.32 no.2
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• pp.129-141
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• 2005

Although spatio-temporal databases have received considerable attention recently, there has been little work on processing range sum queries on the historical records of moving objects despite their importance. Since to answer range sum queries, the direct access to a huge amount of data incurs prohibitive computation cost, materialization techniques based on existing index structures are recently suggested. A simple but effective solution is to apply the materialization technique to the MVR-tree known as the most efficient structure for window queries with spatio-temporal conditions. However, the MVR-tree has a difficulty in maintaining pre-aggregated results inside its internal nodes due to cyclic paths between nodes. Aggregate structures based on other index structures such as the HR-tree and the 3DR-tree do not provide satisfactory query performance. In this paper, we propose a new indexing technique called the Adaptive Partitioned Aggregate R-Tree (APART) and query processing algorithms to efficiently process range sum queries in many situations. Experimental results show that the performance of the APART is typically above 2 times better than existing aggregate structures in a wide range of scenarios.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.2
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• pp.20-41
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• 2023

Recently, urban shrinkage due to low birth rate and aging population and the decline of local cities are causing a new urban problem of empty houses. This study examines the distribution of vacant homes using spatial panel data collected from 2015 to 2019 at local administraitve districts and estimates the factors of vacant house occurrence using a spatial panel model considering spatio-temporal dependency. As a result, the spatio-temporal dependence of vacant houses was identified and it was estimated using spatial panel model not OLS model. Based on the spatial panel model, it was found that the most influential factor in the occurrence of vacant houses was the housing-related factor. This result shows that policy considerations for housing supply are necessary for the management of vacant housing as well as population movement and poor infrastructure.

• Journal of Convergence for Information Technology
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• v.8 no.4
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• pp.247-253
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• 2018

This study was designed to analyze the difference in attendance and academic achievement based on spatio-temporal data relate to e-Learning patterns of university e-Learning learners. This study collected e-Learning data from 68 e-Learning classes, 13,611 learners during 3 years. Collected data were analyzed by t-test and two-way ANOVA. Major study findings were as follows. Firstly, e-Learning learners in school received higher than those of learners outside school both in attendance and academic achievement, while that academic achievement showed statistical significance. Secondly, the attendance and academic achievement by the day was in the order of e-Learning learners mainly in the morning, those in the afternoon and those at night, in addition there was statistical significance. Lastly e-Learning learners in the weekdays appeared higher than those of learners in the weekends both in attendance and academic achievement, also both of them showed statistical significance.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.81-91
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• 2007

In this paper, we have proposed the non-duplication loading method for supporting spatio-temporal analysis in spatial data warehouse. SDW(Spatial Data Warehouse) extracts spatial data from SDBMS that support various service of different machine. In proposed methods, it extracts updated parts of SDBMS that is participated to source in SDW. And it removes the duplicated data by spatial operation, then loads it by integrated forms. By this manner, it can support fast analysis operation for spatial data and reduce a waste of storage space. Proposed method loads spatial data by efficient form at application of analysis and prospect by time like spatial mining.

• Advances in environmental research
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• v.6 no.2
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• pp.83-94
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• 2017

Air quality planning and management requires accurate and consistent records of the air quality parameters. Limited number of monitoring stations and inconsistent measurements of the air quality parameters is a very serious problem in many parts of India. It becomes difficult for the authorities to plan proactive measures with such a limited data. Estimation models can be developed using soft computing techniques considering the physics behind pollution dispersion as they can work very well with limited data. They are more realistic and can present the complete picture about the air quality. In the present case study spatio-temporal models using Linear Genetic Programming (LGP) have been developed for estimation of air quality parameters. The air quality data from four monitoring stations of an Indian city has been used and LGP models have been developed to estimate pollutant concentration of the fifth station. Three types of models are developed. In the first type, models are developed considering only the pollutant concentrations at the neighboring stations without considering the effect of distance between the stations as well the significance of the prevailing wind direction. Second type of models are distance based models based on the hypothesis that there will be atmospheric interactions between the two stations under consideration and the effect increases with decrease in the distance between the two. In third type the effect of the prevailing wind direction is also considered in choosing the input stations in wind and distance based models. Models are evaluated using Band Error and it was observed that majority of the errors are in +/-1 band.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.141-146
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• 2011

The GIS service has to provide latest spatio-temporal data for the effective service. The two-way synchronization scheme collects updated spatio-temporal data in the field and synchronizes with a server by using the wireless network. However, since the two-way synchronization scheme processes sequentially synchronizing work of clients, it has the problem that the synchronization of multiple clients takes long time. In this paper, we propose the concurrent synchronizations scheme based on the multi-queue in order to reduce the waiting time of multiple clients. We also build both schemes and evaulate the performance test. The results show that the proposed scheme reduce the waiting time by 31%.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.36-40
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• 2008

SIMS manages data for various spatial and non-spatial as integral management system to support space information administration environment and support several application works. Without being limited to spatial data that existent spatial Data Mining question language advances handling in this paper, did so that can find useful information from various data connected with automatically data collection, artificial satellite side upside service, remote sensing, GPS. Mobile Computing and data about Spatio-Temporal. Also, we designed spatial Data Mining query language that support a spatial Data Mining exclusive use system based on SIMS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.588-591
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• 2009

In ubiquitous computing GIS services, it is possible to use the spatio-temporal data anytime through the mobile device. GIS services regularly update use the latest spatio-temporal data to provide the most suitable services. For this situation, update data is distributed to CD or wired networks update services. However, this method has problem to propagate update data to users as taking long time. In this paper, suggests a synchronization system which propagate update data to users for reducing processing time efficiently. This synchronization system collects update data in the field and synchronizes server with collected data to use mobile devices by real time. For this system, I design and materialize synchronization module which updates update data and wireless network module.