• Journal of Animal Science and Technology
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• 제63권3호
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• pp.651-661
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• 2021

This study aimed to investigate whether breed, sex, and age affected temperament differently (more or less neophobic) in mature horses during a novel object test. The study included Jeju crossbred (n = 12, age = 9.42 ± 4.57 y), Thoroughbred (n = 15, age = 10.73 ± 3.09 y), and Warmblood horses (n = 12, age = 13.08 ± 3.55 y) with the females (n = 22, age = 11.36 ± 4.24 y) and geldings (n = 17, age = 10.65 ± 3.66 y). Jeju crossbreds (Jeju horse × Thoroughbred) are valuable considering their popular usage in Korea, but limited studies have explored temperament of Jeju crossbred horses. A trained experimenter touched the left side of the neck with a white plastic bag (novel object). The test ended when the horse stopped escape response and heart rate (HR) dropped to baseline. Behavioral score and escape duration were measured as behavioral variables. Multiple variables related to HR and heart rate variability (HRV) were measured to reflect emotional state. These included basal HR (BHR), maximum HR (MHR), delay to reach maximum heart rate (Time to MHR), standard deviation of beat-to-beat intervals (SDNN), root mean square of successive differences (RMSSD), and ratio of low to high frequency components of a continuous series of heartbeats (LF/HF). Statistics revealed that Thoroughbreds had significantly higher behavioral scores, and lower RMSSD than Jeju crossbreds (p < 0.05), suggesting greater excitement and fear to the novel object in Thoroughbreds. None of the behavioral or cardiac parameters exhibited sex differences (p < 0.05). Age was negatively correlated with SDNN and RMSSD (p < 0.05), indicating that older horses felt more anxiety to the novelty than younger horses. Thoroughbreds and females had distinct correlations between behavioral and HRV variables in comparison with other groups (p < 0.05), implying that escape duration might be a good indicator of stress, especially in these two groups. These results are expected to improve equine welfare, safety and utility, by providing insights into the temperament of particular horse groups, to better match reactivity levels with specific functions.

• 대한의용생체공학회:의공학회지
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• 제40권2호
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• pp.62-67
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• 2019

The purpose of this study was to evaluate the performance of deep neural network model in order to determine whether there is a risk factor for coronary artery disease based on the cardiac variation parameter. The study used unidentifiable 297 data to evaluate the performance of the model. Input data consists of heart rate parameters, which are SDNN (standard deviation of the N-N intervals), PSI (physical stress index), TP (total power), VLF (very low frequency), LF (low frequency), HF (high frequency), RMSSD (root mean square of successive difference) APEN (approximate entropy) and SRD (successive R-R interval difference), the age group and sex. Output data are divided into normal and patient groups, and the patient group consists of those diagnosed with diabetes, high blood pressure, and hyperlipidemia among the various risk factors that can cause coronary artery disease. Based on this, a binary classification model was applied using Deep Neural Network of deep learning techniques to classify normal and patient groups efficiently. To evaluate the effectiveness of the model used in this study, Kernel SVM (support vector machine), one of the classification models in machine learning, was compared and evaluated using same data. The results showed that the accuracy of the proposed deep neural network was train set 91.79% and test set 85.56% and the specificity was 87.04% and the sensitivity was 83.33% from the point of diagnosis. These results suggest that deep learning is more efficient when classifying these medical data because the train set accuracy in the deep neural network was 7.73% higher than the comparative model Kernel SVM.

• Biomedical Engineering Letters
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• 제8권4호
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• pp.365-371
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• 2018

Uninterrupted monitoring of multiple subjects is required for mass causality events, in hospital environment or for sports by medical technicians or physicians. Movement of subjects under monitoring requires such system to be wireless, sometimes demands multiple transmitters and a receiver as a base station and monitored parameter must not be corrupted by any noise before further diagnosis. A Bluetooth Piconet network is visualized, where each subject carries a Bluetooth transmitter module that acquires vital sign continuously and relays to Bluetooth enabled device where, further signal processing is done. In this paper, a wireless network is realized to capture ECG of two subjects performing different activities like cycling, jogging, staircase climbing at 100 Hz frequency using prototyped Bluetooth module. The paper demonstrates removal of baseline drift using Fast Fourier Transform and Inverse Fast Fourier Transform and removal of high frequency noise using moving average and S-Golay algorithm. Experimental results highlight the efficacy of the proposed work to monitor any vital sign parameters of multiple subjects simultaneously. The importance of removing baseline drift before high frequency noise removal is shown using experimental results. It is possible to use Bluetooth Piconet frame work to capture ECG simultaneously for more than two subjects. For the applications where there will be larger body movement, baseline drift removal is a major concern and hence along with wireless transmission issues, baseline drift removal before high frequency noise removal is necessary for further feature extraction.

• 전기전자학회논문지
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• 제23권1호
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• pp.1-8
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• 2019

본 논문에서는 18650 원통형 NCA 리튬이온 배터리로 구성된 고출력 직렬 배터리로 다양한 C-rate의 전기적 특성을 테스트한다. 테스트를 통해 추출한 14S1P 배터리 팩의 방전 용량 데이터와 4S1P 배터리 팩의 EV cycle 데이터를 통해 C-rate의 변화에 따른 전기적 특성을 분석한다. 분석을 통해 얻은 데이터를 기반으로 C-rate에 따른 방전용량 실험의 셀 간 전압 편차와 EV cycle 실험의 셀 간 전압 편차를 다중선형회귀 모델로 추정하여 선형적인 특징을 가진 데이터와 비선형적인 특징을 가진 데이터에 대한 각각의 추정성능을 검증한다. 모델의 추정성능을 검증하기 위해 추정 데이터와 실제 데이터의 RMSE를 구해 알고리즘의 정확성을 평가한다. 논문의 결과는 14S1P 배터리 팩의 방전 용량의 셀 간 전압 불균형과 4S1P 배터리 팩의 EV cycle의 셀 간 전압 불균형 중 선형적인 데이터인 방전 용량의 셀 간 불균형 데이터의 추정 성능이 더 뛰어난 것을 검증하는데 기여한다.

• 고신대학교 의과대학 학술지
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• 제33권3호
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• pp.369-379
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• 2018

Objectives: Analysis of heart rate variability (HRV) has been used as a measure of cardiac autonomic function. According to the pNN50 statistic, the percentage of differences between successive normal RR intervals (RRI) that exceed 50 ms, has been known to reflect cardiac vagal modulation. Relatively little is known about the validity of pNN50 during general anesthesia (GA). Therefore, we evaluated the correlation of pNN50 with other variables such as HF, RMSSD, SD1 of HRV reflecting the vagal tone, and examined the validity of pNN50 in anesthetized patients. Methods: We assessed changes in RRI, pNN50, root mean square of successive differences of RRI (RMSSD), high frequency (HF) and standard deviation 1 (SD1) of $Poincar{\acute{e}}$ plots after GA using sevoflurane anesthesia. We also calculated the probability distributions for the family of pNNx statistics (x: 2-50 ms). Results: All HRV variables were significantly decreased during GA. HF power was not correlated with pNN50 during GA (r = 0.096, P = 0.392). Less than pNN47 was shown to have a correlation with other variables. Conclusions: These data suggest that pNN50 can not reflect the level of vagal tone during GA.

• 상하수도학회지
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• 제35권1호
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• pp.83-91
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• 2021

The increased turbidity in rivers during flood events has various effects on water environmental management, including drinking water supply systems. Thus, prediction of turbid water is essential for water environmental management. Recently, various advanced machine learning algorithms have been increasingly used in water environmental management. Ensemble machine learning algorithms such as random forest (RF) and gradient boosting decision tree (GBDT) are some of the most popular machine learning algorithms used for water environmental management, along with deep learning algorithms such as recurrent neural networks. In this study GBDT, an ensemble machine learning algorithm, and gated recurrent unit (GRU), a recurrent neural networks algorithm, are used for model development to predict turbidity in a river. The observation frequencies of input data used for the model were 2, 4, 8, 24, 48, 120 and 168 h. The root-mean-square error-observations standard deviation ratio (RSR) of GRU and GBDT ranges between 0.182~0.766 and 0.400~0.683, respectively. Both models show similar prediction accuracy with RSR of 0.682 for GRU and 0.683 for GBDT. The GRU shows better prediction accuracy when the observation frequency is relatively short (i.e., 2, 4, and 8 h) where GBDT shows better prediction accuracy when the observation frequency is relatively long (i.e. 48, 120, 160 h). The results suggest that the characteristics of input data should be considered to develop an appropriate model to predict turbidity.

• 한국자기공명학회논문지
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• 제24권4호
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• pp.136-142
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• 2020

Apolipoprotein B-100 (apo B-100), the main protein component that makes up LDL (Low density lipoprotein), consists of 4,536 amino acids and serves to combine with the LDL receptor. The oxidized LDL peptides by malondialdehyde (MDA) or acetylation in vivo were act as immunoglobulin (Ig) antigens and peptide groups were classified into 7 peptide groups with subsequent 20 amino acids (P1-P302). The biomimetic peptide P99 (KGTYG LSCQR DPNTG RLNGE) out of B-group peptides carrying the highest value of IgM antigens were selected for structural studies that may provide antigen specificity. Circular Dichroism (CD) spectra were measured for peptide secondary structure in the range of 190-260 nm. Experimental results show that P99 has pseudo α-helice and random coil structure. Homonuclear (COSY, TOCSY, NOESY) 2D-NMR experiments were carried out for NMR signal assignments and structure determination for P99. On the basis of these completely assigned NMR spectra and proton distance information, distance geometry (DG) and molecular dynamic (MD) were carried out to determine the structures of P99. The proposed structure was selected by comparisons between experimental NOE spectra and back-calculated 2D NOE results from determined structure showing acceptable agreement. The total Root-Mean-Square-Deviation (RMSD) value of P99 obtained upon superposition of all atoms were in the set range. The solution state P99 has mixed structure of pseudo α-helix and β-turn(Gln[9] to Thr[13]). These NMR results are well consistent with secondary structure from experimental results of circular dichroism. Structural studies based on NMR may contribute to the prevent oxidation studies of atherosclerosis and observed conformational characteristics of apo B-100 in LDL using monoclonal antibodies.

• 한국지구과학회지
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• 제42권6호
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• pp.605-622
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• 2021

Seasonal forecasting has numerous socioeconomic benefits because it can be used for disaster mitigation. Therefore, it is necessary to diagnose and improve the seasonal forecast model. Moreover, the model performance is partly related to the ocean model. This study evaluated the hindcast performance in the upper ocean of the Global Seasonal Forecasting System version 5-Global Couple Configuration 2 (GloSea5-GC2) using a multivariable integrated evaluation method. The normalized potential temperature, salinity, zonal and meridional currents, and sea surface height anomalies were evaluated. Model performance was affected by the target month and was found to be better in the Pacific than in the Atlantic. An increase in lead time led to a decrease in overall model performance, along with decreases in interannual variability, pattern similarity, and root mean square vector deviation. Improving the performance for ocean currents is a more critical than enhancing the performance for other evaluated variables. The tropical Pacific showed the best accuracy in the surface layer, but a spring predictability barrier was present. At the depth of 301 m, the north Pacific and tropical Atlantic exhibited the best and worst accuracies, respectively. These findings provide fundamental evidence for the ocean forecasting performance of GloSea5.

• The Journal of Advanced Prosthodontics
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• 제14권2호
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• pp.122-132
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• 2022

PURPOSE. This in-vitro analysis aimed to compare the intaglio trueness, the antagonist's wear volume loss, and fracture load of various single-unit zirconia prostheses fabricated by different manufacturing techniques. MATERIALS AND METHODS. Zirconia crowns were prepared into four different groups (n = 14 per group) according to the manufacturing techniques and generations of the materials. The intaglio surface trueness (root-mean-square estimates, RMS) of the crown was measured at the marginal, axial, occlusal, and inner surface areas. Half of the specimens were artificially aged in the chewing simulator with 120,000 cycles, and the antagonist's volume loss after aging was calculated. The fracture load for each crown group was measured before and after hydrothermal aging. The intaglio trueness was evaluated with Welch's ANOVA and the antagonist's volume loss was assessed by the Kruskal-Wallis tests. The effects of manufacturing and aging on the fracture resistance of the tested zirconia crowns were determined by two-way ANOVA. RESULTS. The trueness analysis of the crown intaglio surfaces showed surface deviation (RMS) within 50 ㎛, regardless of the manufacturing methods (P = .053). After simulated mastication, no significant differences in the volume loss of the antagonists were observed among the zirconia groups (P = .946). The manufacturing methods and simulated chewing had statistically significant effects on the fracture resistance (P < .001). CONCLUSION. The intaglio surface trueness, fracture resistance, and antagonist's wear volume of the additively manufactured 3Y-TZP crown were clinically acceptable, as compared with those of the 4Y- or 5Y-PSZ crowns produced by subtractive milling.

• The Journal of Advanced Prosthodontics
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• 제14권3호
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• pp.173-181
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• 2022

PURPOSE. This analysis aimed to evaluate the intaglio surface trueness, antagonist's wear volume loss, and fracture resistance of full-contour crowns of (Y, Nb)-stabilized fully-sintered zirconia (FSZ), 4 mol% or 5 mol% yttria-stabilized partially sintered zirconia (4YZ or 5YZ) with high-speed sintering. MATERIALS AND METHODS. A total of 42 zirconia crowns were separated into three groups: FSZ, 4YZ, and 5YZ (n = 14). The intaglio surface trueness of the crowns was evaluated at the inner surface, occlusal, margin, and axial areas and reported as root-mean-square, positive and negative average deviation. Half of the specimens were aged for 120,000 cycles in the chewing simulator, and the wear volume loss of antagonist was measured. Before and after chewing, the fracture load was measured for each group. The trueness values were analyzed with Welch's ANOVA, and the wear volume loss with the Kruskal-Wallis tests. Effect of the zirconia type and aging on fracture resistance of crowns was tested using two-way ANOVA. RESULTS. The intaglio surface trueness measured at four different areas of the crown was less than 50 ㎛, regardless of the type of zirconia. No significant P in wear volume loss of antagonists were detected among the groups (P > .05). Both the type of zirconia and aging showed statistically significant effects on fracture resistance (P < .05). CONCLUSION. The full-contour crowns of FSZ as well as 4YZ or 5YZ with high-speed sintering were clinically acceptable, in terms of intaglio surface trueness, antagonist's wear volume loss, and fracture resistance after simulated mastication.