• Journal of Korea Multimedia Society
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• v.5 no.1
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• pp.38-46
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• 2002

In this paper, we present an adaptive contrast controller for improving the Quality of motion-picture in the video signals on the display. Using a median of image signals, we can improve the contrast according to the middle brightness, adaptively. In addition, the proposed method is useful for real-time image processing and can be composed of simpler hardware structure than other conventional methods because it does not require field and frame memory for computed data. The proposed method can be applied for video signals as well as the still image, while existing methods are confined to only the static image Also, we designed the algorithm through the VHDL, and implemented it through the FPGA. From the testing results, we see that the proposed method can effectively improve the image contrast.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.147-147
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• 2018

In this article, we use an open source software library: TensorFlow, developed for the purposes of conducting very complex machine learning and deep neural network applications. However, the system is general enough to be applicable in a wide variety of other domains as well. The proposed model based on a deep neural network model, LSTM (Long Short-Term Memory) to predict the river water level at Okcheon Station of the Guem River without utilization of rainfall - forecast information. For LSTM modeling, the input data is hourly water level data for 15 years from 2002 to 2016 at 4 stations includes 3 upstream stations (Sutong, Hotan, and Songcheon) and the forecasting-target station (Okcheon). The data are subdivided into three purposes: a training data set, a testing data set and a validation data set. The model was formulated to predict Okcheon Station water level for many cases from 3 hours to 12 hours of lead time. Although the model does not require many input data such as climate, geography, land-use for rainfall-runoff simulation, the prediction is very stable and reliable up to 9 hours of lead time with the Nash - Sutcliffe efficiency (NSE) is higher than 0.90 and the root mean square error (RMSE) is lower than 12cm. The result indicated that the method is able to produce the river water level time series and be applicable to the practical flood forecasting instead of hydrologic modeling approaches.

• Journal of Korean Society for Quality Management
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• v.49 no.2
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• pp.201-211
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• 2021

Purpose: This paper proposes a density adaptive grid algorithm for the k-NN regression model to reduce the computation time for large datasets without significant prediction accuracy loss. Methods: The proposed method utilizes the concept of the grid with centroid to reduce the number of reference data points so that the required computation time is much reduced. Since the grid generation process in this paper is based on quantiles of original variables, the proposed method can fully reflect the density information of the original reference data set. Results: Using five real-life datasets, the proposed k-NN regression model is compared with the original k-NN regression model. The results show that the proposed density adaptive grid-based k-NN regression model is superior to the original k-NN regression in terms of data reduction ratio and time efficiency ratio, and provides a similar prediction error if the appropriate number of grids is selected. Conclusion: The proposed density adaptive grid algorithm for the k-NN regression model is a simple and effective model which can help avoid a large loss of prediction accuracy with faster execution speed and fewer memory requirements during the testing phase.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.37-37
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• 2023

There is currently a high-accuracy modern forecasting method that uses machine learning algorithms or artificial neural network models to forecast river water levels or flowrate. As a result, this study aims to develop a mathematical model based on artificial neural networks to effectively forecast river water levels upstream of Tranh Culvert in North Vietnam's Bac Hung Hai irrigation system. The mathematical model was thoroughly studied and evaluated by using hydrological data from six gauge stations over a period of twenty-two years between 2000 and 2022. Furthermore, the results of the developed model were also compared to those of the long-short-term memory neural networks model. This study performs four predictions, with a forecast time ranging from 6 to 24 hours and a time step of 6 hours. To validate and test the model's performance, the Nash-Sutcliffe efficiency coefficient (NSE), mean absolute error, and root mean squared error were calculated. During the testing phase, the NSE of the model varies from 0.981 to 0.879, corresponding to forecast cases from one to four time steps ahead. The forecast results from the model are very reasonable, indicating that the model performed excellently. Therefore, the proposed model can be used to forecast water levels in North Vietnam's irrigation system or rivers impacted by tides.

• Journal of The Korean Society of Clinical Toxicology
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• v.2 no.1
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• pp.31-36
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• 2004

Three workers, field operators in lubricating oil processing of petroleum refinery industry were found unconscious by other worker. One of them who were exposed to an high concentration of H2S was presented with Glasgow Coma Score of 5, severe hypoxemia on arterial blood gas analysis, normal chest radiography, and normal blood pressure. On hospital day 7, his mental state became clear, and neurologic examination showed quadriparesis, profound spasticity, increased tendon reflexes, abnormal Babinski response, and bradykinesia. He was also found to have decreased memory, attention deficits and blunted affect which suggest general cognitive dysfunction, which improved soon. MRI scan showed abnormal signals in both basal ganglia and motor cortex, compatible with clinical findings of motor dysfunction. Neuropsychologic testing showed deficits of cognitive functions. SPECT showed markedly decreased cortical perfusion in frontotemporoparietal area with deep white matter. Another case was recovered completely, but the other expired the next day.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.51-57
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• 2024

This study was conducted on how to simulate runoff, which was done using existing physical models, using an LSTM (Long Short-Term Memory) model based on deep learning. Tancheon, the first tributary of the Han River, was selected as the target area for the model application. To apply the model, one water level observatory and four rainfall observatories were selected, and hourly data from 2020 to 2023 were collected to apply the model. River water level of the outlet of the Tancheon basin was simulated by inputting precipitation data from four rainfall observation stations in the basin and average preceding 72-hour precipitation data for each hour. As a result of water level simulation using 2021 to 2023 data for learning and testing with 2020 data, it was confirmed that reliable simulation results were produced through appropriate learning steps, reaching a certain mean absolute error in a short period time. Despite the short data period, it was found that the mean absolute percentage error was 0.5544~0.6226%, showing an accuracy of over 99.4%. As a result of comparing the simulated and observed values of the rapidly changing river water level during a specific heavy rain period, the coefficient of determination was found to be 0.9754 and 0.9884. It was determined that the performance of LSTM, which aims to simulate river water levels, could be improved by including preceding precipitation in the input data and using precipitation data from various rainfall observation stations within the basin.

• Korean Journal of Biological Psychiatry
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• v.14 no.1
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• pp.61-67
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• 2007

Objectives : The purpose of this study was to test stage model in Traumatic Brain Injury(TBI) patients. According to the stage model, attention deficits which is basic stage in information processing lead to memory disturbance and subsequently affect higher-order cognitive function such as memory, decision-making, abstract thinking, and judgement related to executive function. Therefore, it was hypothesized that attention affect recall(retrieval efficacy) related to executive function mostly relative to other cognitive function, in TBI patients with low executive function. Methods : Participants were referred to a TBI clinic and then was rated on K-WAIS and Executive Intelligence Test(EXIT). Participants were divided into two groups according to Executive IQ(EIQ) score, which of high function group(N=67) was more than 80(above low average) and of low function group(N=52) was under 80 (under borderline). To test the stage model, using hierarchical regression analysis, recall(retrieval efficacy) was regressed on 3 subscales(attention, verbal, visuospatial scale) after controlling for IQ according to each group. Furthermore, the mediation effect of attention between retrieval efficacy and verbal, visuospatial score was analyzed. Results : In the low function group, only attention area predicted significantly recall(retrieval efficacy), indicating that lower attention were related to lower EIQ after controlling for IQ. In the high function group, no area predicted significantly retrieval efficacy. In the low function group, verbal and visuospatial scale did not predicted significantly retrieval efficacy, indicating that there was no evidences supporting the mediation model. Conclusion : Only attention affect retrieval efficacy in TBI patients with low executive function. But, the mediation effect of attention between retrieval efficacy and verbal and visuospatial scale was not tested in the low function group. These results implied that stage model was tested partially. In treating cognitive deficit in TBI patients, it is necessary to develop cognitive rehabilitation program based on stage model. Furthermore, it is necessary to necessary to test mediation model in the future study.

• Journal of Pharmacopuncture
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• v.22 no.3
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• pp.166-170
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• 2019

Objectives: Attentional and memory functions are important aspects of neural plasticity that, theoretically, should be amenable to pharmacopuncture treatments. A previous study from our laboratory suggested that quantitative electroencephalographic (qEEG) measurements of theta/beta ratio (TBR), an index of attentional control, may be indicative of academic performance in a first-semester medical school course. The present study expands our prior report by extracting and analyzing data on frontal theta and beta asymmetries. We test the hypothesis that the amount of frontal theta and beta asymmetries (fTA, fBA), are correlated with TBR and academic performance, thereby providing novel targets for pharmacopuncture treatments to improve cognitive performance. Methods: Ten healthy male volunteers were subjected to 5-10 min of qEEG measurements under eyes-closed conditions. The qEEG measurements were performed 3 days before each of first two block examinations in anatomy-physiology, separated by five weeks. Amplitudes of the theta and beta waveforms, expressed in ${\mu}V$, were used to compute TBR, fTA and fBA. Significance of changes in theta and beta EEG wave amplitude was assessed by ANOVA with post-hoc t-testing. Correlations between TBR, fTA, fBA and the raw examination scores were evaluated by Pearson's product-moment coefficients and linear regression analysis. Results: fTA and fBA were found to be negatively correlated with TBR (P<0.03, P<0.05, respectively) and were positively correlated with the second examination score (P<0.03, P=0.1, respectively). Conclusion: Smaller fTA and fBA were associated with lower academic performance in the second of two first-semester medical school anatomy-physiology block examination. Future studies should determine whether these qEEG metrics are useful for monitoring changes associated with the brain's cognitive adaptations to academic challenges, for predicting academic performance and for targeting phamacopuncture treatments to improve cognitive performance.

• Journal of Korean Neurosurgical Society
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• v.64 no.1
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• pp.125-135
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• 2021

Objective : This study aimed to validate the Korean version of the Repeatable Battery for the Assessment of Neuropsychological Status Update (K-RBANS). Methods : We performed a retrospective analysis of 283 psychiatric and neurosurgery patients. To investigate the convergent validity of the K-RBANS, correlation analyses were performed for other intelligence and neuropsychological test results. Confirmatory factor analysis was used to test a series of alternative plausible models of the K-RBANS. To analyze the various capabilities of the K-RBANS, we compared the area under the receiver operating characteristic (ROC) curves (AUC). Results : Significant correlations were observed, confirming the convergent validity of the K-RBANS among the Total Scale Index (TSI) and indices of the K-RBANS and indices of intelligence (r=0.47-0.81; p<0.001) and other neuropsychological tests at moderate and above significance (r=0.41-0.63; p<0.001). Additionally, the results testing the construct validity of the K-RBANS showed that the second-order factor structure model (model 2, similar to an original factor structure of RBANS), which includes a first-order factor comprising five index scores (immediate memory, visuospatial capacity, language, attention, delayed memory) and one higher-order factor (TSI), was statistically acceptable. The comparative fit index (CFI) (CFI, 0.949) values and the goodness of fit index (GFI) (GFI, 0.942) values higher than 0.90 indicated an excellent fit. The root mean squared error of approximation (RMSEA) (RMSEA, 0.082) was considered an acceptable fit. Additionally, the factor structure of model 2 was found to be better and more valid than the other model in χ2 values (Δχ2=7.69, p<0.05). In the ROC analysis, the AUCs of the TSI and five indices were 0.716-0.837, and the AUC of TSI (AUC, 0.837; 95% confidence interval, 0.760-0.896) was higher than the AUCs of the other indices. The sensitivity and specificity of TSI were 77.66% and 78.12%, respectively. Conclusion : The overall results of this study suggest that the K-RBANS may be used as a valid tool for the brief screening of neuropsychological patients in Korea.

• Korean Journal of Forensic Psychology
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• v.11 no.1
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• pp.1-20
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• 2020

Witnesses will be exposed to a variety of misinformation after the witnessing of the event and state at the scene of the investigation after the delay period. This study was conducted to promote correct recall reporting without being affected by factors that against correct recall. Self-Administered Interview(SAI) is known to obtain eyewitness accounts quickly and accurately. Therefore, we performed a SAI to see if it reported more information than the control group that did not perform the SAI. Also, it also performed that correct information was maintained without being affected by misinformation and delay. Eighty-eight participants were asked to perform SAI or game after showing a video of mock crime. Misinformation was presented in the first or second session to see if it affected recall. An analysis of responses from the final test conducted in the second session by participants showed that groups that conducted SAI after a four-week delay reported more correct information than control groups, while there was no difference between incorrect- and confabulation information. In particular, the timing of presenting misinformation did not affect the amount of recall. This suggests that conducting the SAI immediately after witnessing the event protects correct information even after four weeks. Finally, the significance and limitations of this study, and subsequent studies were discussed.