• Land and Housing Review
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• v.11 no.2
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• pp.33-46
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• 2020

As the fastest growing office transaction volume in Korea, there's been a need for development of indicators to accurately diagnose the office capital market. The purpose of this paper is experimentally calculate to the office price index for effective benchmark indices in Seoul. The quantitative methodology used a Case-Shiller Repeat Sales Model (1991), based on actual multiple office transaction dataset with over minimum 1,653 ㎡ from Q3 1999 to 4Q 2019 in the case of 1,536 buildings within Seoul Metropolitan. In addition, the collected historical data and spatial statistical analysis tools were treated with the SAS 9.4 and ArcGIS 10.7 programs. The main empirical results of research are briefly summarized as follows; First, Seoul office price index was estimated to be 344.3 point (2001.1Q=100.0P) at the end of 2019, and has more than tripled over the past two decades. it means that the sales price of office per 3.3 ㎡ has consistently risen more than 12% every year since 2000, which is far above the indices for apartment housing index, announced by the MOLIT (2009). Second, between quarterly and annual office price index for the two-step estimation of the MIT Real Estate Research Center (MIT/CRE), T, L, AL variables have statistically significant coefficient (Beta) all of the mode l (p<0.01). Third, it was possible to produce a more stable office price index against the basic index by using the Moore-Penrose's pseoudo inverse technique at low transaction frequency. Fourth, as an lagging indicators, the office price index is closely related to key macroeconomic indicators, such as GDP(+), KOSPI(+), interest rates (5-year KTB, -). This facts indicate that long-term office investment tends to outperform other financial assets owing to high return and low risk pattern. In conclusion, these findings are practically meaningful to presenting an new office price index that increases accuracy and then attempting to preliminary applications for the case of Seoul. Moreover, it can provide sincerely useful benchmark about investing an office and predicting changes of the sales price among market participants (e.g. policy maker, investor, landlord, tenant, user) in the future.

• Physical Therapy Korea
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• v.17 no.3
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• pp.77-86
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• 2010

The purpose of this study was to investigate the variations in gait parameters in terms of the type of arm sling used in hemiplegic patients. Ten patients with hemiplegia and ten healthy adults participated in this study and walked at self-selected speeds on a GAITRite-instrumented carpet. The activities of the opposite shoulder girdle muscle including the latissimus dorsi, anterior deltoid, and posterior deltoid were simultaneously recorded using surface EMG during gait. They were randomly assigned a condition: without an arm sling, a single strap arm sling, a Harris hemi arm sling, a Rolyan humeral cuff arm sling, and a Bobath roll arm sling. The following gait variables were analyzed: the temporo-spatial parameters of velocity, step length, stride length, swing phase, stance phase, single support, step time and toe in/toe out. The statistical analysis was one-way ANOVA with repeated measures to compare the variation of each variable. In comparison of parameters in each trial in the hemiplegia group, the non-affected side stride length, single support, and toe in/toe out resulted in statistically significantly changes (p<.05). But without an arm sling group did not show any gait parameter differences with arm slings. This study found that several arm slings varied gait patterns in patients with hemiplegia and in healthy adults. In the EMG analysis, the Rolyan humeral cuff arm sling and the Bobath roll arm sling were higher muscle activity for the latissimus dorsi muscle than did the single strap ann sling. Further study should examine the problems that appeared in patients who worn arm slings by focusing on a larger number of subjects and by studying the variety of responses in more detail using an assessment tool that measures variation.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.102-114
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• 2017

The purpose of this study was the assessment of the accuracy of Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG), a rainfall data source derived from satellite images, for evaluation of its applicability to use in ungauged or inaccessible areas. The study area was the overall area of the Korean peninsula divided into six regions. Automated Surface Observing System (ASOS) rainfall data from the Korean Meteorological Administration and IMERG satellite rainfall were used. Their average correlation coefficient was 0.46 for a 1-h temporal resolution, and it increased to 0.69 for a 24-h temporal resolution. The IMERG data quantitatively estimated less than the rainfall totals from ground gauges, and the bias decreased as the temporal resolution was decreased. The correlation coefficients of the two rainfall events, which had relatively greater rainfall amounts, were 0.68 and 0.69 for a 1-h temporal resolution. Additionally, the spatial distributions of the ASOS and IMERG data were similar to each other. The study results showed that the IMERG data were very useful in the assessment of the hydro-meteorological characteristics of ungauged or inaccessible areas. In a future study, verification of the accuracy of satellite-derived rainfall data will be performed by expanding the analysis periods and applying various statistical techniques.

• Journal of Korea Water Resources Association
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• v.47 no.9
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• pp.825-838
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• 2014

The stationary Markov chain model has been widely used as a daily rainfall simulation model. A main assumption of the stationary Markov model is that statistical characteristics do not change over time and do not have any trends. In other words, the stationary Markov chain model for daily rainfall simulation essentially can not incorporate any changes in mean or variance into the model. Here we develop a Non-stationary hidden Markov chain model (NHMM) based stochastic downscaling scheme for simulating the daily rainfall sequences, using general circulation models (GCMs) as inputs. It has been acknowledged that GCMs perform well with respect to annual and seasonal variation at large spatial scale and they stand as one of the primary sources for obtaining forecasts. The proposed model is applied to daily rainfall series at three stations in Nakdong watershed. The model showed a better performance in reproducing most of the statistics associated with daily and seasonal rainfall. In particular, the proposed model provided a significant improvement in reproducing the extremes. It was confirmed that the proposed model could be used as a downscaling model for the purpose of generating plausible daily rainfall scenarios if elaborate GCM forecasts can used as a predictor. Also, the proposed NHMM model can be applied to climate change studies if GCM based climate change scenarios are used as inputs.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.5-23
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• 2020

According to the Korean Statistical Information Service(2019), the number of public land in Korea is 10,734,439parcels and 33,395㎢, accounting for 33.2% of the land area. In the meantime, the central government and local governments have been promoting the efficiency of public land management through annexation, but if the scale of cadastral record is different or the public land is registered in different types of cadastral maps, it is impossible to annexation and it is a major obstacle to the efficiency of public land management. As a way to solve these problems, the annexation method accompanied by survey was presented and the effect was analyzed. As a result, the number of parcels to be managed decreased by 91.7% and 99.6% of the actual survey cost was reduced despite the expenditure of only 54.9% of the existing method. It was found that the annexation survey of the public land, which are clustered by connection, can ultimately contribute to the efficiency of the public land management by newly establishing the indication of the public land. In the future, we hope that follow-up research on the public land management based on cadastral surveys will be conducted in various and in-depth ways.

• Journal of the Korean earth science society
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• v.30 no.2
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• pp.210-222
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• 2009

Lightning data, observed from total lightning detection system (TLDS) of KMA, for the recent five years (2002-2006) have been analyzed for temporal and spatial characteristics of frequency, intensity, duration, and flash rate. Lightning frequency varies largely with years (most frequent in 2006) and the lightning during the summer accounts for 75% of total flashes and only 0.6% of lightnings strike in cold season. In rainy season (JJAS), the ratio of positive flashes to negative ones is as low as 0.15, but it increases up to 0.98 in February. The seasonal variation of lightning duration is strongly linked with lightning occurrences, whereas flashes rates show weak seasonal variability. In a daily scale, lightning, on average, occurs more often at dawn (2 am, 5-7 am) and in the mid-afternoon (15 pm), and the lightning at dawn (around 5 am) is most intense during the day. The western inland areas md the West/South Sea show high lightning density during JJAS, whereas eastern part and the East Sea exhibit a low density of lightning. Considering the low ratio of positive flashes (0.15) for the whole analysis domain during summer period, Chungnam and Jeonbuk areas have a high ratio of flashes over 0.4. However, these should be analyzed with much caution because weak positive cloud-to-cloud discharges can be regarded as cloud-to-ground flashes. The western inland also exhibits long annual flash hours (15-24). And the W3st Sea has high flash rates as a result of large density and low flash hours. The most frequent time of lightning occurrence over most inland areas lies between mid-afternoon and early-evening, whereas mountainous and coastal areas, and the northern Kyoungki and Hwanghae provinces show the maximum lightning strikes in the morning and at dawn, respectively.

• Journal of KIISE:Databases
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• v.35 no.1
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• pp.54-66
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• 2008

A spatio-temporal join is an expensive operation that is commonly used in spatio-temporal database systems. In order to generate an efficient query plan for the queries involving spatio-temporal join operations, it is crucial to estimate accurate selectivity for the join operations. Given two dataset $S_1,\;S_2$ of discrete data and a timestamp $t_q$, a spatio-temporal join retrieves all pairs of objects that are intersected each other at $t_q$. The selectivity of the join operation equals the number of retrieved pairs divided by the cardinality of the Cartesian product $S_1{\times}S_2$. In this paper, we propose aspatio-temporal histogram to estimate selectivity of spatio-temporal join by extending existing geometric histogram. By using a wide spectrum of both uniform dataset and skewed dataset, it is shown that our proposed method, called Spatio-Temporal Histogram, can accurately estimate the selectivity of spatio-temporal join. Our contributions can be summarized as follows: First, the selectivity estimation of spatio-temporal join for discrete data has been first attempted. Second, we propose an efficient maintenance method that reconstructs histograms using compression of spatial statistical information during the lifespan of discrete data.

• Journal of the Korean Geographical Society
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• v.41 no.3 s.114
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• pp.245-266
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• 2006

This study aims to explain the emergence of Gangnam Region of Seoul as a new cluster of the Korean film industry in the context of its history of growth, recent development characteristics, and its production system. Statistical analyses of Korean industries and in-depth interview surveys to film producers were conducted. The results of the analyses show that there has been obvious tendency of film makers' move from Chungmuro, a traditional cluster of the Korean film industry, to Gangnam and many births of new film makers in Gangnam. This new cluster, however, is operating on informal networking between film makers and related personnel, not on formalized production system composed of specialized functions and labor market. Therefore, it can be called as loosely-articulated cluster. This form of cluster has much to do with production milieu of Gangnam, such as advantages of obtaining information and consumer trend, diverse atmosphere which makes it easier to meet diverse people, favorable environment to embed creativity and fresh idea, etc. This trend of the film industry to orient a specific area can be explained in conjunction with the uniqueness of the film industry, such as uncertainty, project-based work, generation gap between film makers, participation of large companies or increasing size of investment.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.513-521
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• 2015

In the processing of ocean color remote sensing data, spatio-temporal binning is crucial for securing effective observation area. The validity determination for given source data refers to the information in Level-2 flag. For minimizing the stray light contamination, NASA OBPG's standard algorithm suggests the use of large filtering window but it results in the loss of effective observation area. This study is aimed for quality improvement of ocean color remote sensing data by recovering/extending the portion of effective observation area. We analyzed the difference between MODIS/Aqua standard and modified product in terms of chlorophyll-a concentration, spatial and temporal coverage. The recovery fractions in Level-2 swath product, Level-3 daily composite product, 8-day composite product, and monthly composite product were $13.2({\pm}5.2)%$, $30.8({\pm}16.3)%$, $15.8({\pm}9.2)%$, and $6.0({\pm}5.6)%$, respectively. The mean difference between chlorophyll-a concentrations of two products was only 0.012%, which is smaller than the nominal precision of the geophysical parameter estimation. Increase in areal coverage also results in the increase in temporal density of multi-temporal dataset, and this processing gain was most effective in 8-day composite data. The proposed method can contribute for the quality enhancement of ocean color remote sensing data by improving not only the data productivity but also statistical stability from increased number of samples.

• Journal of Environmental Health Sciences
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• v.47 no.5
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• pp.486-495
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• 2021

Background: Particulate matter (PM) is one of the leading causes of premature death worldwide. Previous studies in South Korea have applied a relative risk calculated from Western populations when estimating the disease burden attributable to PM. However, the relative risk of PM on health outcomes may not be the same across different countries or regions. Objectives: This study aimed to estimate the premature deaths and socioeconomic costs attributable to long-term exposure to PM in South Korea. We considered not only the difference in PM concentration between regions, but also the difference in relative risk. Methods: National monitoring data of PM concentrations was obtained, and missing values were imputed using the AERMOD model and linear regression model. As a surrogate for relative risk, hazard ratios (HRs) of PM for cardiovascular and respiratory mortality were estimated using the National Health Insurance Service-National Sample Cohort. The nation was divided into five areas (metropolitan, central, southern, south-eastern, and Gangwon-do Province regions). The number of PM attributable deaths in 2018 was calculated at the district level. The socioeconomic cost was derived by multiplying the number of deaths and the statistical value of life. Results: The average PM₁₀ concentration for 2014~2018 was 45.2 ㎍/m³. The association between long-term exposure to PM₁₀ and mortality was heterogeneous between areas. When applying area-specific HRs, 23,811 premature deaths from cardiovascular and respiratory disease in 2018 were attributable to PM₁₀ (reference level 20 ㎍/m³). The corresponding socioeconomic cost was about 31 trillion won. These estimated values were higher than that when applying nationwide HRs. Conclusions: This study is the first research to estimate the premature mortality caused by long-term exposure to PM using relative risks derived from the national population. This study will help precisely identify the national and regional health burden attributed to PM and establish the priorities of air quality policy.