• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.184-186
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• 2001

This paper describes a method of human sensibility evaluation for pleasant and unpleasant environments. Conditions of the environment are room temperature and humidity. Changing the conditions, 10-channel EEG signals for 4 subjects are collected. Linear predictor coefficients of the recorded EEGs are extracted as the feature parameter of human sensibility. A neural network-based human sensibility estimation algorithm is developed. The developed algorithm showed good performance in the pleasantness evaluation. The neural network output produced accurate states of pleasantness sensibility. Subject-independent test showed similar results with subject-dependent test.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2002년도 춘계학술대회 논문집
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• pp.215-220
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• 2002

본 연구에서는 다중채널 뇌파에서 특징 파라미터로 선형 예측기 계수(Linear predictor coefficients)를 추출하고, 패턴인식기로는 신경회로망을 이용한 쾌적성 분류 알고리즘을 개발하여 다중 템플릿 방법으로 쾌적성 분류 실험을 하고자 하였다. 뇌파 데이터는 대학생 10명으로부터 쾌적한 환경과 불쾌적한 환경에서의 데이터를 수집하였으며, 전극 위치는 Fpl, Fp2, F3, F4, T3, T4, P3, P4, O1, O2를 사용하였다. 수집된 뇌파는 전처리를 거친 후 특징 파라미터를 추출하고 패턴 분류기로 사용된 신경회로망의 입력으로 사용하였다. 쾌적성 분류 방법은 다중템플릿 방법으로 여러 명의 피검자를 각각 학습시켜 이로부터 생성되는 신경회로망의 가중치들을 템플릿에 저장한다. 그리고 테스트를 할 때에는 먼저 처음의 안정 상태의 뇌파를 이용하여 템플릿 검색을 하고 가장 가까운 템플릿을 선택한다. 그리고 선택된 템플릿을 이용하여 다른 감정에 대한 쾌적성 분류 실험을 하게 된다. 쾌적성 분류 실험 결과 평균 인식률이 약 75%의 성능을 나타내었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2690-2692
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• 2002

This paper describes a technique for human sensibility evaluation using 10-channel EEG(electroencephalogram). The proposed method uses the linear predictor coefficients as EEG feature parameters and a neural network as sensibility pattern classifier. For subject independent system, multiple templates are stored and the most similar template can be selected. EEG signals corresponding to 4 emotions such as, relaxation, joy, sadness and anger are collected from 5 armature performers. The states of relaxation and joy are considered as positive sensibility and those of sadness and anger as negative. The classification performance using the proposed method is about 72.6%. This will be promising performance in the human sensibility evaluation.

• 한국간호교육학회지
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• 제20권4호
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• pp.513-522
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• 2014

Purpose: This study identifies the influences of self-directed learning ability and metacognition on clinical competence in nursing students. Method: The subjects consisted of 290 second and third year nursing students. The data were analyzed using t-tests, ANOVA, Scheffe's test, Pearson's correlation coefficients and multiple linear regression via SPSS Statistics version 18.0. Results: On a scale of 1 (lowest) to 5 (highest), the mean self-directed learning ability score of the subjects was 3.19, mean metacognition score was 3.36 and mean clinical competence score was 3.29. A positive correlation was found between clinical competence with self-directed learning ability and metacognition. The strongest predictor of clinical competence was metacognition. Conclusion: To improve the clinical competence of nursing students, these findings indicate that increasing metacognition ability is required.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2801-2803
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• 2003

This paper describes a technique for human sensibility evaluation using personality-group templates of EEG(electroencephalogram). 10-channel EEGs of 5 extroverts and 5 introverts are collected in comfortable seat, uncomfortable seat and relaxed state. After preprocessing of EEG, the linear predictor coefficients are extracted and used as feature parameters. A neural network based sensibility classifier is designed and the output of the neural network is assumed as the sensibility index. Multiple templates of two personality-groups are stored and the most similar template can be selected by the proposed method. The proposed method showed the better performance than our previous results which have used ungrouped templates.

• 한국간호교육학회지
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• 제19권4호
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• pp.571-579
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• 2013

Purpose: This study was done to identify the influences of ego resilience and communication ability on problem-solving ability in nursing students. Methods: The subjects consisted of 448 first and second year nursing students. The data were collected from June 10 to 21, 2013. The data were analyzed using t-test, ANOVA, Scheffe's test, Pearson's correlation coefficients and multiple linear regression with IBM SPSS Statistics version 19.0. Results: The Ego resilience score of subjects was 2.84 out of a perfect score of 4, the communication ability score of subjects was 3.51, and the problem-solving ability score of subjects was 3.44 out of a perfect score of 5. A positive correlation was found for problem-solving ability with ego resilience and communication ability. The strongest predictor of problem-solving ability was a communication ability. Conclusion: These findings indicate that there is a need to increase communication ability to improve the problem-solving ability of nursing students. The results should be reflected in the development of effective curricula.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2017년도 춘계공동학술대회
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• pp.45-45
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• 2017

On-site monitoring of vegetable growth parameters, such as leaf length, leaf area, and fresh weight, in an agricultural field can provide useful information for farmers to establish farm management strategies suitable for optimum production of vegetables. Unmanned Aerial Vehicles (UAVs) are currently gaining a growing interest for agricultural applications. This study reports on validation testing of previously developed vegetable growth estimation models based on UAV-based RGB images for white radish and Chinese cabbage. Specific objective was to investigate the potential of the UAV-based RGB camera system for effectively quantifying temporal and spatial variability in the growth status of white radish and Chinese cabbage in a field. RGB images were acquired based on an automated flight mission with a multi-rotor UAV equipped with a low-cost RGB camera while automatically tracking on a predefined path. The acquired images were initially geo-located based on the log data of flight information saved into the UAV, and then mosaicked using a commerical image processing software. Otsu threshold-based crop coverage and DSM-based crop height were used as two predictor variables of the previously developed multiple linear regression models to estimate growth parameters of vegetables. The predictive capabilities of the UAV sensing system for estimating the growth parameters of the two vegetables were evaluated quantitatively by comparing to ground truth data. There were highly linear relationships between the actual and estimated leaf lengths, widths, and fresh weights, showing coefficients of determination up to 0.7. However, there were differences in slope between the ground truth and estimated values lower than 0.5, thereby requiring the use of a site-specific normalization method.

• 한국환경보건학회지
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• 제26권2호
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• pp.97-107
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• 2000

PCBs [Polychlorinated biphenyls] are halogenated aromatic compounds with the empirical formula C12H10-nCln(n=1~10), and are a mixture of possible 209 different chlorinated congeners. PCBs were widely used as dielectric fluids for capacitors, transformers, plasticizers, lubricant inks, and paint additives. once released into the environment, PCBs persist for years because they are so resistant to degradation. In addition to their high degree of lipophilicity. In 1970s, the worldwide production of PCBs seem to be still in use. The environmental load of PCBs was prohibited since 1983 in Korea. In spite of these actions, many PCBs seem to be still in use. The environmental load of PCBs will continue to be recycled through air, land, water, and the biosphere for decades to come. This study was conducted to measure the concentrations of PCBs I the serum samples of 112 women by GC/MSD(Hewlett Packard 5897 Gas Chromatography-Mass Chromatography Detector) and CG/ECD(Hewlett Packard 5890 series-II gas chromatography-Electron capture detector, U.S.A). The main results of this study were as follows; The mean and standard deviation of serum PCBs were 3.613, 0.759 ppb, respectively and median of it was 3.828 ppb. The correlation coefficients of the concentrations of 13 PCB congeners ranged from 0.7913 to 0..9985 and were significantly correlated between each items(p=0.0001). The PCB concentrations were positively associated with age(simple linear regression; R2=0.86, =0.08023, p<0.001) and with total lipids in serums(simple linear regression; R=0.7058, =0.00486, p<0.001). The age adjusted model (Y=$\beta$0+$\beta$1age+$\beta$2X) was applied for possible predictors of PCBs levels in serum. For BMI(Body Mass Index), major residential area, and fish, meat, and dairy consumption, there was no association with PCBs levels, Also there was negative association for the number of pregnancy and lactation period with PCBs levels.

• Clinical and Experimental Pediatrics
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• 제54권2호
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• pp.64-68
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• 2011

Purpose: The normal values for lung resistance and lung capacity of children, as determined by impulse oscillometry (IOS), are different for children of different ethnicities. However, reference values there is no available reference value for Korean preschool children have yet to be determined. The aim of the present study was to determine the normal ranges of IOS parameters in Korean preschool children. Methods: A total of 133 healthy Korean preschool children were selected from 639 children (aged 3 to 6 years) who attended kindergarten in Seongnam, Gyeonggi province, Korea. Healthy children were defined according to the European Respiratory Society (ERS) criteria. All subjects underwent lung function tests using IOS. The relationships between IOS value (respiratory resistance (Rrs) and reactance (Xrs) at 5 and 10 Hz and resonance frequency (RF)) and age, height, and weight were analyzed by simple linear and multiple linear regression analyses. Results: The IOS success rate was 89.5%, yielding data on 119 children. Linear regression identified height as the best predictor of Rrs and Xrs. Using stepwise multiple linear regressions based on age, height, and weight, we determined regression equations and coefficients of determination ($R^2$) for boys ($Rrs_5=1.934-0.009{\times}Height$, $R^2$=12.1%; $Xrs_5=0.774+0.006{\times}Height-0.002{\times}Age$, $R^2$=20.2% and for girls $(Rrs_5=2.201-0.012{\times}Height$, $R^2$=18.2%; $Xrs_5=-0.674+0.004{\times}Height$, $R^2$=10.5%). Conclusion: This study provides reference values for IOS measurements of normal Korean preschool children. These provide a basis for the diagnosis and monitoring of preschool children with a variety of respiratory diseases.

• 원예과학기술지
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• 제30권3호
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• pp.270-277
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• 2012

Greenhouse industry has been growing in many countries due to both the advantage of stable year-round crop production and increased demand for fresh vegetables. In greenhouse cultivation, $CO_2$ concentration plays an essential role in the photosynthesis process of crops. Continuous and accurate monitoring of $CO_2$ level in the greenhouse would improve profitability and reduce environmental impact, through optimum control of greenhouse $CO_2$ enrichment and efficient crop production, as compared with the conventional management practices without monitoring and control of $CO_2$ level. In this study, a mathematical model was developed to estimate the $CO_2$ emission from soil as affected by environmental factors in greenhouses. Among various model types evaluated, a linear regression model provided the best coefficient of determination. Selected predictor variables were solar radiation and relative humidity and exponential transformation of both. As a response variable in the model, the difference between $CO_2$ concentrations at the soil surface and 5-cm depth showed are latively strong relationship with the predictor variables. Segmented regression analysis showed that better models were obtained when the entire daily dataset was divided into segments of shorter time ranges, and best models were obtained for segmented data where more variability in solar radiation and humidity were present (i.e., after sun-rise, before sun-set) than other segments. To consider time delay in the response of $CO_2$ concentration, concept of time lag was implemented in the regression analysis. As a result, there was an improvement in the performance of the models as the coefficients of determination were 0.93 and 0.87 with segmented time frames for sun-rise and sun-set periods, respectively. Validation tests of the models to predict $CO_2$ emission from soil showed that the developed empirical model would be applicable to real-time monitoring and diagnosis of significant factors for $CO_2$ enrichment in a soil-based greenhouse.