• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.27 no.1
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• pp.64-71
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• 2016

Objectives: The objective of this study was to examine the effects of osmotic-controlled release oral delivery system methylphenidate on changes in regional cerebral blood flow (rCBF) in children with attention-deficit hyperactivity disorder (ADHD) using single photon emission computed tomography (SPECT). Methods: A total of 26 children with ADHD (21 boys, mean age: $9.2{\pm}2.05$ years old) were recruited. Each ADHD participant was examined for changes in rCBF using technetium-99m-hexamethylpropylene amine oxime brain SPECT before and after 8 weeks methylphenidate medication. Brain SPECT images of pediatric normal controls were selected retrospectively. SPECT images of ADHD children taken before medication were compared with those of pediatric normal controls and those taken after medication using statistical parametric mapping analysis on a voxel-wise basis. Results: Before methylphenidate medication, significantly decreased rCBF in the cerebellum and increased rCBF in the right precuneus, left anterior cingulate, right postcentral gyrus, right inferior parietal lobule and right precentral gyrus were observed in ADHD children compared to pediatric normal controls (p-value<.0005, uncorrected). After medication, we observed significant hypoperfusion in the left thalamus and left cerebellum compared to pediatric normal controls (p-value<.0005, uncorrected). In the comparison between before medication and after medication, there was significant hyperperfusion in the superior frontal gyrus and middle frontal gyrus and significant hypoperfusion in the right insula, right caudate, right middle frontal gyrus, left subcallosal gyrus, left claustrum, and left superior temporal gyrus after methylphenidate medication (p-value<.0005, uncorrected). Conclusion: This study supports dysfunctions of fronto-striatal structures and cerebellum in ADHD. We suggest that methylphenidate may have some effects on the frontal lobe, parietal lobe, and cerebellum in children with ADHD.

• Journal of Korea Water Resources Association
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• v.39 no.12 s.173
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• pp.1043-1056
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• 2006

Our ultimate purpose is to investigate the potential change in regional surface climate due to the global warming and to produce higher quality regional surface climate information over the Korean peninsula for comprehensive impact assessment. Toward this purpose, we carried out two 30-year long experiments, one for present day conditions (covering the period 1971-2000) and one for near future climate conditions (covering the period 2021-2050) with a regional climate model (RegCM3) using a one-way double-nested system. In order to obtain the confidence in a future climate projection, we first verify the model basic performance of how the reference simulation is realistic in comparison with a fairly dense observation network. We then examine the possible future changes in mean climate state as well as in the frequency and intensity of extreme climate events to be derived by difference between climate condition as a baseline and future simulated climate states with increased greenhouse gas. Emphasis in this study is placed on the high-resolution spatial/temporal aspects of the climate change scenarios under different climate settings over Korea generated by complex topography and coastlines that are relevant on a regional scale.

• Journal of Korea Water Resources Association
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• v.36 no.2
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• pp.195-209
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• 2003

Spatial-Stochastic Neural Networks Model(SSNNM) is used to estimate long-term streamflow in the parallel reservoir groups. SSNNM employs two kinds of backpropagation algorithms, based on LMBP and BFGS-QNBP separately. SSNNM has three layers, input, hidden, and output layer, in the structure and network configuration consists of 8-8-2 nodes one by one. Nodes in input layer are composed of streamflow, precipitation, pan evaporation, and temperature with the monthly average values collected from Andong and Imha reservoir. But some temporal differences apparently exist in their time series. For the SSNNM training procedure, the training sets in input layer are generated by the PARMA(1,1) stochastic model and they covers insufficient time series. Generated data series are used to train SSNNM and the model parameters, optimal connection weights and biases, are estimated during training procedure. They are applied to evaluate model validation using observed data sets. In this study, the new approaches give outstanding results by the comparison of statistical analysis and hydrographs in the model validation. SSNNM will help to manage and control water distribution and give basic data to develop long-term coupled operation system in parallel reservoir groups of the Upper Nakdong River.

• Journal of Korea Water Resources Association
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• v.47 no.11
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• pp.1039-1050
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• 2014

The goal of this study is to demonstrate the diversity of model performance for various climatic elements and indicators. We evaluated the skills of the most advanced 17 General Circulation Models (GCMs) i.e., CMIP5 (Climate Model Inter-comparison project, phase 5) climate models in reproducing retrospective climatology from 1950 to 2000 over the Southeast US for the key climatic elements important in the hydrological and agricultural perspectives (i.e., precipitation, maximum and minimum temperature, and wind speed). The biases of raw CMIP5 GCMs were estimated for 16 different climatic indicators that imply mean climatology, temporal variability, extreme frequency, etc. using a grid-based observational dataset as reference. Based on the error (RMSE) and correlation (R) of GCM outputs, the error-based GCM ranks were assigned on average over the indicators. Overall, the GCMs showed much better accuracy in representing mean climatology of temperature comparing to other elements whereas few GCM showed acceptable skills for precipitation. It was also found that the model skills and ranks would be substantially different by the climatic elements, error statistics applied for evaluation, and indicators as well. This study presents significance of GCM uncertainty and the needs of considering rational strategies for climate model evaluation and selection.

• Journal of Korea Water Resources Association
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• v.47 no.1
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• pp.25-35
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• 2014

The objective of this study is to evaluate TOPLATS land surface model performance through comparison of results of water and energy balance analysis. The study area is selected Nakdong river basin and high resolution hydrometeorological components of which spatio-temporal resolution is 1 hr and 1 km are simulated during 2003 to 2013. The simulated daily and monthly depth of flows are well fitted with the observed one on Andong and Hapcheon dam basin. In results of diurnally analysis of energy components, change pattern throughout the day of net radiation, latent heat, sensible heat, and ground heat under energy balance analysis have higher accuracy than ones under water balance analysis at C3 and C4 sites. Especially, root mean square errors of net radiation and latent heat at C4 site are shown very low as 22.18 $W/m^2$ and 7.27 $W/m^2$, respectively. Mean soil moisture and evapotranspiration in summer and winter are simulated as 36.80%, 33.08% and 222.40 mm, 59.95 mm, respectively. From this result, when we need high resolution hydrometeorological components, energy balance analysis is more reasonable than water balance analysis. And this results will be used for monitor and forecast of weather disaster like flood and draught using spatial hydrometeorological information.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.1
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• pp.82-89
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• 2016

And by entering into an aging society with economic growth "beautiful and healthy desire to live', aesthetics industry as promote interest in 'Anti-aging' is emerging as a promising business increased significantly the skin care market. However, the management of the hospital or the temporal order to receive professional care providers, spatial, and cost constraints caused many companies to solve this problem began to approach the Home Care Area. Global trends in personal skin care market has been activated, the domestic has been activated at low cost, private market due to the recession. We have performed this test in order to develop a skin care device for home in order to compensate for this point.In this paper, we develop a low-level laser to create a personal skin care products and sought to incorporate them into the skin cosmetic.Expand the pores by using the low-level laser to the skin by to the dermal layer of the skin was penetrated aim experiment the ampoule, and by a comparison of the medical low-level laser reliability and determine the effectiveness or absence of the performance and efforts to commercialize.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1066-1072
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• 2011

In the method to analyze the relationship in the system call orders, the normal system call orders are divided into a certain size of system call orders to generates gene and use them as the detectors. In the method to consider the system call parameters, the mean and standard deviation of the parameter lengths are used as the detectors. The attack of which system call order is normal but the parameter values are changed, such as the format string attack, cannot be detected by the method that considers only the system call orders, whereas the model that considers only the system call parameters has the drawback of high positive defect rate because of the information obtained from the interval where the attack has not been initiated, since the parameters are considered individually. To solve these problems, it is necessary to develop a more efficient learning and detecting method that groups the continuous system call orders and parameters as the approach that considers various characteristics of system call related to attacking simultaneously. In this article, we detected the anomaly of the system call orders and parameters by applying the temporal concept to the system call orders and parameters in order to improve the rate of positive defect, that is, the misjudgment of anomaly as normality. The result of the experiment where the DARPA data set was employed showed that the proposed method improved the positive defect rate by 13% in the system call order model where time was considered in comparison with that of the model where time was not considered.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.11
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• pp.790-796
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• 2011

In this study, we measured the concentrations of volatile organic compounds (VOCs) in Shiwha area by using active and passive sampler. We did a comparative analysis of the characteristics of the active sampler and passive sampler. In the case of the passive sampler, the average TVOC concentration of the industrial area was 1.86 times higher than that of the residential area. In the case of the active sampler, the average TVOC concentration of the industrial area was 1.07 times higher than that of the residential area. When using the passive sampler, the concentration of VOCs in the industrial area was noted to be higher than the concentration found in the residential area. However, when we used the thermal desorption tube, the concentration of residential area was higher rather than that of industrial area in some substances such as trichloroethylene, toluene, ethylbenzene, and xylene. Toluene was a larger percentage of the overall BTEX ratio. In case of the passive sampler, the relative ratio of toluene, ethylbenzene, and xylene was higher in the industrial area than in the residential area. In contrast in case of the thermal desorption tube, the ratio of these substances was higher in the residential area rather than in the industrial area. The passive sampling in this study showed an appropriate method to analyze the temporal and spatial concentrations of air contaminants. This assessment would prove to be useful for its observance of standards or epidemical study.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.2
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• pp.53-62
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• 2012

Demand for high resolution weather data grows in the agriculture and forestry fields. Local Analysis and Prediction System (LAPS) can be used to analyze the local weather at high spatial and temporal resolution, utilizing the data from various sources including numerical weather prediction models, wind or temperature profilers, Automated Weather Station (AWS) networks, radars, and satellites. LAPS has been set to analyze weather elements such as air temperature, relative humidity, wind speed, and wind direction every hour at the spatial resolution of $100m{\times}100m$ for Gyeonggi-do on near real-time basis. The AWS data were revised by adding the agricultural field AWS data (33 stations) in addition to the KMA data. The analysis periods were from 1 to 31 August 2009 and from 15 to 21 February 2010. The comparison of the LAPS output showed the smaller errors when using the agricultural AWS observation data together with the KMA data as its input data than using only either the agricultural or KMA AWS data. The accuracy of the current system needs improvement by further optimization of analyzing options of the system. However, the system is highly applicable to various fields in agriculture and forestry because it can provide site specific data with reasonable time intervals.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1107-1115
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• 2019

Satellite data play a major role in supporting knowledge about forest fire by delivering rapid information to map areas damaged. This study, we used 7 Sentinel-2A images to detect change area in forests of Sokcho on April 4, 2019. The process of classify forest fire severity used 7 levels from Sentinel-2A dNBR(differenced Normalized Burn Ratio). In the process of classifying forest fire damage areas, the study selected three areas with high regrowth of vegetation level and conducted a detailed spatial analysis of the areas concerned. The results of dNBR analysis, regrowth of coniferous forest was greater than broad-leaf forest, but NDVI showed the lowest level of vegetation. This is the error of dNBR classification of dNBR. The results of dNBR time series, an area of forest fire damage decreased to a large extent between April 20th and May 3rd. This is an example of the regrowth by developing rare-plants and recovering broad-leaf plants vegetation. The results showed that change area was detected through the change detection of danage area by forest category and the classification errors of the coniferous forest were reached through the comparison of NDVI and dNBR. Therefore, the need to improve the precision Korean forest fire damage rating table accompanied by field investigations was suggested during the image classification process through dNBR.