• The Korean Journal of Nuclear Medicine
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• v.38 no.3
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• pp.233-240
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• 2004

Purpose: We developed a computer-aided classifier using artificial neural network (ANN) to discriminate the cerebral metabolic pattern of medial and lateral temporal lobe epilepsy (TLE). Materials and Methods: We studied brain F-18-FDG PET images of 113 epilepsy patients sugically and pathologically proven as medial TLE (left 41, right 42) or lateral TLE (left 14, right 16). PET images were spatially transformed onto a standard template and normalized to the mean counts of cortical regions. Asymmetry indices for predefined 17 mirrored regions to hemispheric midline and those for medial and lateral temporal lobes were used as input features for ANN. ANN classifier was composed of 3 independent multi-layered perceptrons (1 for left/right lateralization and 2 for medial/lateral discrimination) and trained to interpret metabolic patterns and produce one of 4 diagnoses (L/R medial TLE or L/R lateral TLE). Randomly selected 8 images from each group were used to train the ANN classifier and remaining 51 images were used as test sets. The accuracy of the diagnosis with ANN was estimated by averaging the agreement rates of independent 50 trials and compared to that of nuclear medicine experts. Results: The accuracy in lateralization was 89% by the human experts and 90% by the ANN classifier Overall accuracy in localization of epileptogenic zones by the ANN classifier was 69%, which was comparable to that by the human experts (72%). Conclusion: We conclude that ANN classifier performed as well as human experts and could be potentially useful supporting tool for the differential diagnosis of TLE.

• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.3
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• pp.247-256
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• 2012

Stable carbon isotope ratio of oil components are known to be unaffected by weathering processes and thus has been widely used to determine the origin of spilled oil. In this study, molecular index and composition of stable carbon isotope in 15 crude oils and petroleum product were analyzed and used as oil fingerprints to determine the discriminating power of each fingerprinting method among target crude oils. Through the fingerprints of alkane distribution only Bintulu and B-C(1%) were distinguishable from other crude oils. The pristane/phytane ratio can classify the crude oils into three groups but differentiation of crude oils within a group was impossible using the ratio. The crude oils of A.L., A.S.L., Foroozan and B-C(1%) were differentiated from the other oils using PAH source recognition indexes of C2D/C2P and C3D/C3P. The usage of 4-mD/1-mD and 2/3-mD/1-mD ratio was able to distinguish A.S.L., Bintulu and Oman from the other crude oils. However the PAH source recognition ratios in the other crude oils were similar and thus they were impractical to be used for source identification among the target crude oils. Stable carbon isotope ratios of alkanes were able to uniquely specify each crude oil in the plot of ${\delta}^{13}C_{C21}$ and ${\delta}^{13}C_{C25}$ except A.L., A.M., Qatar-Marine, B-C(1%). The oil fingerprinting method using stable carbon isotope ratios of individual alkane compounds showed more discriminating power among the target crude oils than the conventional source recognition indexes of PAHs or alkanes.

• Clinical and Experimental Pediatrics
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• v.53 no.3
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• pp.420-427
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• 2010

Purpose : Several complications can occur in patients who received bone marrow transplantation (BMT) during childhood and adolescence. This study aims to investigate endocrine dysfunctions after BMT so that better care can be provided to care for long-term survivors of BMT. Methods : One hundred patients (61 males, 39 females) were included in this study. Clinical parameters such as initial diagnosis, age at BMT, conditioning regimen, presence of graft-versus-host disease (GVHD), growth pattern, thyroid function, and pubertal status were retrospectively reviewed to evaluate risk factors associated with endocrine dysfunction. Results : Height standard deviation score (SDS) at BMT, after 1 year of BMT, and at the last visit were $0.08{\pm}1.04$, $-0.09{\pm}1.02$, and $-0.27{\pm}1.18$, respectively (P =0.001). Height SDS significantly decreased in patients who received total body irradiation (TBI) (P =0.017). One of the patients who received TBI demonstrated growth hormone deficiency. Thirty (31.9%) of 94 patients had compensated hypothyroidism. Incidence of compensated hypothyroidism was higher among those who had GVHD (odds ratio 2.82, P =0.025). Of the 32 patients (17 males, 15 females) who were over 14 years in male and 13 years in female at the last visit, 16 (3 males, 13 females) had increased luteinizing hormone (LH) or follicle-stimulating hormone (FSH). Abnormal elevation of LH or FSH was more common in females (odds ratio 30.3, P =0.001). Conclusion : The most common endocrine dysfunction was ovarian insufficiency. Regular check-up for endocrine function needs to be required due to high incidence of endocrine dysfunction in patients with BMT.

• The Journal of Korean Academy of Sensory Integration
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• v.15 no.2
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• pp.46-65
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• 2017

Objective : The purpose of this research is to find clinical effects of application of weighted vest during task-oriented training focused on gross motor performance and balance abilities of children with spastic diplegia. Methods : 34 subjects were divided by simple random sampling into two groups; experimental group (male : 9, female : 8, average age : 8.12) and placebo group (male : 9, female : 9, average age : 7.53). Both two groups underwent to 40 minute intervention, twice a week for 12 weeks. The intervention was task-oriented training focused on facilitating closed kinematic chain and multi-joint functional movement pattern. During the training, the experimental group received loaded-resistance weighted vest and placebo group also received weighted vest but without loaded-resistance. Participants in both groups underwent 8 to 10 reps of the task-oriented training and there were 3 minutes break time between tasks. There were pre-test of gross motor performance and balance abilities, and two times of post-tests were performed upon 6 weeks and 12 weeks after the intervention completed. And in final, an additional follow-up test was performed 12 weeks after the evaluation was finished in order to find any difference between the two groups over time. Results : There was significant difference in Gross Motor Performance Measure (GMPM) between two groups. It is found that average score of the experimental group increased more than the placebo group after 6 weeks and 12 weeks intervention (p<.05). There was significant difference in Pediatric Berg's Balance Scale (PBS) between two groups. It is found that average score of the experimental group increased more than the placebo group after 6 weeks and 12 weeks intervention (p<.05). Conclusion : Based on the results in this study, it is proposed that application of weighted vest into task-oriented training to facilitating closed kinematic chain and multi-joint movement can improve gross motor performance and balance abilities of children with cerebral palsy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.558-569
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• 2020

This study examined the frequency of a broiler's stay in each area as stock density using an ICT-based image analysis technique from the perspective of precision livestock farming (PLF) according to the increase in the domestic broiler farms to understand the normal behavior patterns of broilers by age. The broiler was used in the experimental box (3.3×2.7 m) in a poultry house in Gyeonggi province. The stock densities were 9.5 birds/㎡ (n=85) and 19 birds/㎡ (n=170), respectively, and the frequency of stay by feeding, water, and rest area was monitored using a top-view camera. The image data of three-colored-specific broilers identified as the stock density were acquired by age (12, 16, 22, 27, and 29 days) for six hours. In the collected image data, the object tracking technique was used to record the cumulative movement path by connecting approximately 640,000 frames at 30 fps to quantify the frequency of stay in each area. In each stock density, it was significant in the order of the rest area, feeding, and water area (p<0.001). In 9.5 birds/㎡, it was at 57.9, 24.2, and 17.9 %, and 73.2, 16.8, and 10 % in 19 birds/㎡. The frequency of a broiler's stay could be evaluated in each area as the stock density using an ICT-based image analysis technique that minimizes stress. This method is expected to be used to provide basic material for developing an ICT-based management system through real-time monitoring.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1095-1105
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• 2021

The advancement of dam operation is further required due to the upcoming rainy season, typhoons, or torrential rains. Besides, physical models based on specific rules may sometimes have limitations in controlling the release discharge of dam due to inherent uncertainty and complex factors. This study aims to forecast the water level of the nearest station to the dam multi-timestep-ahead and evaluate the availability when it makes a decision for a release discharge of dam based on LSTM (Long Short-Term Memory) of deep learning. The LSTM model was trained and tested on eight data sets with a 1-hour temporal resolution, including primary data used in the dam operation and downstream water level station data about 13 years (2009~2021). The trained model forecasted the water level time series divided by the six lead times: 1, 3, 6, 9, 12, 18-hours, and compared and analyzed with the observed data. As a result, the prediction results of the 1-hour ahead exhibited the best performance for all cases with an average accuracy of MAE of 0.01m, RMSE of 0.015 m, and NSE of 0.99, respectively. In addition, as the lead time increases, the predictive performance of the model tends to decrease slightly. The model may similarly estimate and reliably predicts the temporal pattern of the observed water level. Thus, it is judged that the LSTM model could produce predictive data by extracting the characteristics of complex hydrological non-linear data and can be used to determine the amount of release discharge from the dam when simulating the operation of the dam.