• Journal of Korea Water Resources Association
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• v.36 no.1
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• pp.117-128
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• 2003

The objectives of this study are to develop the total maximum daily loads simulation system, TOLOS that is capable of estimating annual nonpoint source pollution from small watersheds, to monitor the hydrology and water quality of the Balkan HP#6 watershed, and to validate TOLOS with the field data. TOLOS consists of three subsystems: the input data processor based on a geographic information system, the models, and the post processor. Land use pattern at the tested watershed was classified from the Landsat TM data using the artificial neutral network model that adopts an error back propagation algorithm. Paddy field components were added to SWAT model to simulate water balance at irrigated paddy blocks. SWAT model parameters were obtained from the GIS data base, and additional parameters calibrated with field data. TOLOS was then tested with ungauged conditions. The simulated runoff was reasonably good as compared with the observed data. And simulated water quality parameters appear to be reasonably comparable to the field data.

• Journal of IKEEE
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• v.26 no.3
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• pp.355-363
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• 2022

Korea is pursuing a plan to switch and expand energy sources with a focus on renewable energy with the goal of becoming carbon neutral by 2050. As the instability of energy supply increases due to the intermittent nature of renewable energy, accurate prediction of the amount of renewable energy generation is becoming more important. Therefore, the government has opened a small-scale power brokerage market and is implementing a system that pays settlements according to the accuracy of renewable energy prediction. In this paper, a prediction model was implemented using a statistical model and an artificial intelligence model for the prediction of solar power generation. In addition, the results of prediction accuracy were compared and analyzed, and the revenue from the settlement amount of the renewable energy generation forecasting system was estimated.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1121-1121
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• 2001

A previous study (Berzaghi et al., 2001) evaluated the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural networks (ANN) on the prediction of the chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with reference values for moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected using 10 different Foss NIR Systems instruments, only some of which had been standardized to one master instrument. The aim of the present study was to evaluate the behaviour of these different calibration methods when predicting the same samples measured on different instruments. Twenty-two sealed samples of different kind of forages were measured in duplicate on seven instruments (one master and six slaves). Three sets of near infrared spectra (1100 to 2500nm) were created. The first set consisted of the spectra in their original form (unstandardized); the second set was created using a single sample standardization (Clone1); the third was created using a multiple sample procedure (Clone6). WinISI software (Infrasoft International Inc., Port Mathilda, PA, USA) was used to perform both types of standardization, Clone1 is just a photometric offset between a “master” instrument and the “slave” instrument. Clone6 modifies both the X-axis through a wavelength adjustment and the Y-axis through a simple regression wavelength by wavelength. The Clone1 procedure used one sample spectrally close to the centre of the population. The six samples used in Clone 6 were selected to cover the range of spectral variation in the sample set. The remaining fifteen samples were used to evaluate the performances of the different models. The predicted values for dry matter, protein and neutral detergent fibre from the master Instrument were considered as “reference Y values” when computing the statistics RMSEP, SEPC, R, Bias, Slope, mean GH (global Mahalanobis distance) and mean NH (neighbourhood Mahalanobis distance) for the 6 slave instruments. From the results we conclude that i) all the calibration techniques gave satisfactory results after standardization. Without standardization the predicted data from the slaves would have required slope and bias correction to produce acceptable statistics. ii) Standardization reduced the errors for all calibration methods and parameters tested, reducing not only systematic biases but also random errors. iii) Standardization removed slope effects that were significantly different from 1.0 in most of the cases. iv) Clone1 and Clone6 gave similar results except for NDF where Clone6 gave better RMSEP values than Clone1. v) GH and NH were reduced by half even with very large data sets including unstandardized spectra.

• Progress in Medical Physics
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• v.16 no.1
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• pp.32-38
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• 2005

Impaired processing of facial information is one of the broad ranges of cognitive deficits seen in patients with schizophrenia. The purpose of this study was to elucidate the differences in brain activities involved in the process of facial working memory between schizophrenic patients and healthy comparison subjects. Ten patients with schizophrenia were recruited along with matched healthy volunteers as a comparison group. Functional magnetic resonance imaging (fMRI) was used to assess cortical activities during the performance of a 1-back working memory paradigm using images of neutral faces as mnemonic content. The patient group performed the tasks with reduced accuracy. Group analysis revealed that left fusiform gyrus, right superior frontal gyrus, bilateral middle frontal gyri/insula, left middle temporal gyrus, precuneus and vermis of cerebellum and showed decreased cortical activities in the patient group. On the other hand, an increased level of activation in lateral prefrontal cortex and parietal lobule was observed from the patient group, all in the right hemisphere. A decreased level of activity in the left fusiform gyrus among the patient group implicates inefficient processing of facial information. An increased level of activation in prefrontal and parietal neural networks from the patient group confirms earlier findings on the impaired working memory of patients with schizophrenia.