• Korean Journal of Food Science and Technology
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• v.36 no.4
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• pp.580-585
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• 2004

Respiration of 'Fuyu' persimmon (Diospyros kaki) fruits were measured in terms of oxygen consumption rate and carbon dioxide evolution by closed system experiments at 0, 5, and $20^{\circ}C$. Enzyme kinetics-based respiration model was used to describe respiration rate as function of $O_2\;and\;CO_2$ gas concentrations $(R=V_m[O_2]/K_m+(1+[CO_2]/K_i)[O_2])$, and Arrhenius equation was applied to analyze temperature effect. $V_m\;and\;K_m$ increased, while $K_i$ decreased, with increasing temperature. $K_m\;of\;O_2$ consumption was greater than that of $CO_2$ evolution at equal temperature. Inhibitory effect of reduced $O_2$ level on $O_2$ consumption was more prominent than that on $CO_2$ evolution. Activation energy of respiration decreased with reduced $O_2$ and elevated $CO_2$ concentrations. Activation energy of $CO_2$ evolution was greater than that of $O_2$ consumption. Permeable package experiments verified respiration model parameters by showing good agreement between predicted and experimental gas concentrations in package.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.12
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• pp.2175-2185
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• 2000

Respiration rate should be a reasonable state variable for the activated sludge and could be used to simulate the performance of the activated sludge process. Toxic materials are classified into three groups, competitive, noncompetitive and uncompetitive. They increase/decrease the half saturation coefficient or specific growth rate. that means decreasing of the substrate removal capacity. In this research, a pilot-scale activated sludge process was operated under extended aeration method, and a representative noncompetitive inhibitor, acidic wastewater was applied to establish a respirometry-based toxicity model. Using this model. the correlation coefficient between measured and calculated respiration rate was 0.96 when acidic wastewater(pH 3.9~5.5) was introduced continuously to the aeration tank. Even though respiration rate was decreased by toxic effect of acidic wastewater, effluent substrate concentration represented to COD was deteriorated just a little bit. It might be caused by the low ratio of readily biodegradable substrate in the input substrate. Reduction of respiration rate by decreasing of input substrate concentration was much lower than that by acidic wastewater, and hence it was estimated that the possibility of false toxic alarm caused by decreasing of substrate concentration should be low.

• Annual Conference of KIPS
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• 2023.11a
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• pp.641-643
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• 2023

Deep Learning(DL)을 사용한 호흡음의 자동 분석은 폐 질환의 조기 진단에 중추적인 역할을 한다. 그러나 현재의 DL 방법은 종종 호흡음의 공간적 및 시간적 특성을 분리하여 검사하기 때문에 한계가 있다. 본 연구는 컨볼루션 연산을 통해 공간적 특징을 캡처하고 시간 컨볼루션 네트워크를 사용하여 이러한 특징의 공간적-시간적 상관 관계를 활용하는 새로운 DL 프레임워크를 제한한다. 제안된 프레임워크는 앙상블 학습 접근법 내에 컨볼루션 네트워크를 통합하여 폐음 녹음에서 호흡 이상 및 질병을 검출하는 정확도를 크게 향상시킨다. 잘 알려진 ICBHI 2017 챌린지 데이터 세트에 대한 실험은 제안된 프레임워크가 호흡 이상 및 질병 검출을 위한 4-Class 작업에서 비교모델 성능보다 우수함을 보여준다. 특히 민감도와 특이도를 나타내는 점수 메트릭 측면에서 최대 45.91%와 14.1%의 개선이 이진 및 다중 클래스 호흡 이상 감지 작업에서 각각 보여준다. 이러한 결과는 기존 기술보다 우리 방법의 두드러진 이점을 강조하여 호흡기 의료 기술의 미래 혁신을 주도할 수 있는 잠재력을 보여준다.

• Food Science and Preservation
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• v.9 no.3
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• pp.261-266
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• 2002

A transpiration model was selected and tested experimentally to predict transpiration into of Fuji apple stored in a normal air and controlled atmospheres (l∼3% O$_2$+ l∼3% CO$_2$) at 0$\^{C}$ and 98% RH for 6weeks. CA storage decreased the respiration rate of Fuji apple by 50% when compared with normal air storage. The transpiration rates of apple showed 50∼70% higher in normal air storage than those in CA storage and were decreased by increasing CO$_2$concentration under same concentration of O$_2$. The transpiration rates estimated by the selected model were in good agreement with experimental data for Fuji apples under controlled atmosphere conditions and normal air. When the respiratory heat generation rate u of Fuji apple increased with storage conditions, the evaporating surface temperature and transpiration rate also increased. But since some portion of respiratory heat was used as latent heat in the evaporating surface, the change of u value had a little effect on the determination of the evaporation temperature and the transpiration rate.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.53-62
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• 2004

In this study, an improved post-processing technique for correcting MRI artifact due to the unknown respiratory motion in the imaging plane is presented. Respiratory motion is modeled by a two-Dimensional linear expending-shrinking movement. Assuming that the body tissues are incompressible fluid like materials, the proton density per unit volume of the imaging object is kept constant. According to the introduced model, respiratory motion imposes phase error, non-uniform sampling and amplitude modulation distortions on the acquired MRI data. When the motion parameters are known or can be estimatead a reconstruction algorithm based on biliner superposition method was used to correct the MRI artifact. In the case of motion parameters are unknown, first, the spectrum shift method is applied to find the respiratory fluctuation function, x directional expansion coefficient and x directional expansion center. Next, y directional expansion coefficient and y directional expansion center are estimated by using the minimum energy method. Finally, the validity of this proposed method is shown to be effective by using the simulated motion images.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.21-31
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• 2021

As the COVID-19 pandemic rapidly changes healthcare around the globe, the need for smart healthcare that allows for remote diagnosis is increasing. The current classification of respiratory diseases cost high and requires a face-to-face visit with a skilled medical professional, thus the pandemic significantly hinders monitoring and early diagnosis. Therefore, the ability to accurately classify and diagnose respiratory sound using deep learning-based AI models is essential to modern medicine as a remote alternative to the current stethoscope. In this study, we propose a deep learning-based respiratory sound classification model using data collected from medical experts. The sound data were preprocessed with BandPassFilter, and the relevant respiratory audio features were extracted with Log-Mel Spectrogram and Mel Frequency Cepstral Coefficient (MFCC). Subsequently, a Parallel CNN network model was trained on these two inputs using stacking ensemble techniques combined with various machine learning classifiers to efficiently classify and detect abnormal respiratory sounds with high accuracy. The model proposed in this paper classified abnormal respiratory sounds with an accuracy of 96.9%, which is approximately 6.1% higher than the classification accuracy of baseline model.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2002.04a
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• pp.117-118
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• 2002

본 연구에서는 지하수로부터 방출된 실내라돈오염을 해석하기 위한 수학적 모델에서 모델인자들의 불확실성을 고려하고 인체축적량을 정량적으로 해석하는 PBPK모델을 사용하여 호흡을 통한 라돈의 인체축적량을 보다 현실적으로 평가하려고 한다. 우선, 전에 사용한 3 구역모델을 샤워실과 화장실을 구분하는 경계가 없다는 국내실정을 감안하여 보다 현실적으로 개량한 2-구역 모델을 개발하였다. (중략)

• Aerospace Engineering and Technology
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• v.8 no.1
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• pp.207-214
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• 2009

The purpose of this study was to examine the influence of hypoxic exercise at head down tilt (HDT) on cardiovascular responses. Eight men ($23{\pm}2$ yrs, $176{\pm}4$ cm, and $75{\pm}8$ kg) underwent four separate exercise testing sessions; seated normoxia (SN), seated hypoxia (SH), HDT normoxia (HN), and HDT hypoxia (HH). Each participant performed the leg cycling at predetermined 40% of maximal aerobic capacity relevant to each posture for 15 min. Heart rate was higher in SH than SN and higher also in HH than SH (p<0.05). Blood oxygen saturation was lower in SH than SN (p<0.05). During resting, diastolic blood pressure and mean arterial pressure was significantly lower in HDT than seated posture (p<0.05). No differences were found between conditions in hemoglobin and hematocrit and electrolytes including, sodium, potassium, and chloride. Lactate was higher in SH than SN. In conclusion, there was no effect for cardiovascular responses to duplicate stimuli both hypoxia and posture.

• Sleep Medicine and Psychophysiology
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• v.12 no.1
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• pp.68-71
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• 2005

We report a case of obstructive sleep apnea syndrome, which occurred primarily during the REM sleep stage. A 55-year-old female patient who complained of chronic insomnia on the initial visit turned out to have obstructive sleep apnea syndrome of a mild degree (respiratory disturbance index (RDI) of 13.8/hour, %time spent below 90% of SaO2=5.0%) on nocturnal polysomnography. Interestingly, apnea episodes and desaturations mainly occurred during REM sleep stage. And RDI and destaturations during REM sleep stage were found to be severe enough to classify as a severe degree of obstructive sleep apnea syndrome. These findings suggest that severe obstructive sleep apnea syndrome might be masked under the symptom of chronic insomnia and that apneas can be predominantly localized within REM sleep epochs. In terms of treatment, "REM sleep-dependent" apneas may call for different methods of treatment, especially REM sleep-specific pharmacological intervention.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.4
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• pp.409-413
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• 2005

A method to estimate the autotrophic maximum specific growth rate is presented in this paper. First of all, the concentration of nitrifier is simulated based on the amount of N nitrified, the sludge age and the default value for the decay coefficient. Secondly the OUR of the sludge with access of ammonia is measured. The maximum specific growth rate can be calculated as ${\mu}_{max,A}\;=\;OUR_{max,A}/Y_A$. It was demonstrated that the maximum specific growth rate of autotrophic biomass is not a constants but a time variable parameter. It is concluded that using $OUR_{max,A}$ for dynamic estimating maximum specific growth rate is a good approach and that using a constant value for the maximum specific growth rate over a longer period of time could not predict the performance of activated sludge plants.