• Journal of Korean Home Economics Education Association
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• v.17 no.2
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• pp.49-60
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• 2005

In this study, environmental knowledge and consciousness and eco-friendly behavior related to dietary life of middle school students were examined. Male and female students in Gyeongsan and Daegu Metropolitan City were selected for the study. Total of 490 questionnaires were delivered and collected, and 445 of them were analyzed by using SPSS Win Ver 12.0. Percentages of students who checked' don't know the answer' in 20 environmental knowledge assessment questions were $14.4\~41.8\%$, and those who gave correct answer to these responded to how the answer were $40.1\~93.3\%$. The average score of environmental consciousness was 3.45 and that of eco-friendly dietary behavior was 2.9 out of 5. When dietary behavior was divided by three categories, such as food purchasing, eating. and dish washing, the score of food purchasing behavior was 2.7, those of eating behavior and dish washing behavior were 3.0, 3.1, respectively. In the relationship between environmental knowledge. consciousness. and eco-friendly dietary behavior, there was significant positive correlation between howledge and consciousness, but no significant relation between consciousness and behavior. It showed that environmental knowledge and consciousness didn't always lead to eco-friendly dietary behavior. Therefore, education for practical betlavior must be emphasized even though the knowledge and consciousness education on environment are important.

• Journal of the Korean Society of Marine Environment & Safety
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• v.15 no.2
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• pp.157-164
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• 2009

The metals such as Al, Ag, Au, Cu, Cd, Co, Fe, Ni, Pb, Zn, etc are present at very low concentration in seawater and are classified as so-called trace metals. Whiles some of them are used in metabolism of living organism as a micronutrient, they may show toxic effects on organisms in case of a limited threshold concentration of them Plenty of studies on trace metals have been performed bemuse trace metals have a persistent influence and an adverse effect on marine environment and ecosystem. For long years, when the concentration of trace metals in natural waters such as seawater and fresh water are measured with high precision and accuracy, some systematic errors have been recognized to be present in measurements. Since 1975 in US and European countries, the measured concentration of trace metals in seawater have been found to be lower by factors of 10-1,000 than the previous data of trace metals measurements and the vertical profiles of the measurements have been shown to reflect well-known biological, physical and geochemical processes. These results are attributed to great advances in analytical instrumentation and methodology for trace metals measurements. Precautions against the contamination of samples are required to be taken in the process of sampling, storage, and analysis of samples. However, in Korea, erroneous data of trace metals with regard to ocean and marine environment related survey and investigations are reported The lock of exact understanding and information regarding precautions in sampling, storage and analysis of samples lead to the deterioration of data quality, especially in the analysis of trace metals. The major procedures to obtain the accurate data of trace metals in natural waters are introduced for applying to the study and assessment of marine environments.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.207-216
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• 2013

The aim of this study is to design a classifier for sleep stage analysis and select important feature set which shows sleep stage well based on physiological signals during sleep. Sleep has a significant effect on the quality of human life. When people undergo lack of sleep or sleep-related disease, they are likely to reduced concentration and cognitive impairment affects, etc. Therefore, there are a lot of research to analyze sleep stage. In this study, after acquisition physiological signals during sleep, we do pre-processing such as filtering for extracting features. The features are used input for the new combination algorithm using genetic algorithm(GA) and neural networks(NN). The algorithm selects features which have high weights to classify sleep stage. As the result of this study, accuracy of the algorithm is up to 90.26% with electroencephalography(EEG) signal and electrocardiography(ECG) signal, and selecting features are alpha and delta frequency band power of EEG signal and standard deviation of all normal RR intervals(SDNN) of ECG signal. We checked the selected features are well shown that they have important information to classify sleep stage as doing repeating the algorithm. This research could use for not only diagnose disease related to sleep but also make a guideline of sleep stage analysis.

• Journal of the Korean Society of Radiology
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• v.12 no.1
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• pp.31-37
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• 2018

In the surface contamination test using the end-window Geiger-Muller type counter, the wrap is used as a method for protecting the detector exposed to the outside in order to measure the beta-rays. We analyze the effect of this method on the measurement rate and the correction factor, and wanted to make it clear to radiation workers that excessive use of the wrap can affect the measured value of the beta-rays. The experimental method was to compare and analyze the change of the beta-rays measurement counting rate and the calibration factor according to the wrap thickness using the beta-rays with different energy of 3 KBq, 1.5 KBq and 0.3 KBq. The subjects of this study were the end-window Geiger-Muller type counter which were held at the calibration center certified by Korea Laboratory Accreditation Scheme (KOLAS) in March 2012, Cl-36 (Chlorine) and Sr-90 (Strontium) were used as the source of beta radiation. The measurement counting rate decreased with increasing wrap thickness, and the calibration factor increased with increasing wrap thickness. Since the changes of the measurement counting rate and the calibration factors can reduce the accuracy of the instrument readings, but also have a significant impact on detector contamination and damage, so there is a need to find out what thickness of wrap is most effective. If we using a wraps with thickness that show a low rate of change of the measurement counting rate and the calibration factor, it will protect the detector and minimize the effect on the measured value of the beta-rays.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.4
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• pp.137-144
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• 2020

Delirium is among the most common mental disorders encountered in patients with a temporary cognitive impairment such as consciousness disorder, attention disorder, and poor speech, particularly among those who are older. Delirium is distressing for patients and families, can interfere with the management of symptoms such as pain, and is associated with increased elderly mortality. The purpose of this paper is to generate useful clinical knowledge that can be used to distinguish the outcomes of patients with delirium in long-term care facilities. For this purpose, we extracted the clinical classification knowledge associated with delirium using a local covering rule acquisition approach with the rough lower approximation region. The clinical applicability of the proposed method was verified using data collected from a prospective cohort study. From the results of this study, we found six useful clinical pieces of evidence that the duration of delirium could more than 12 days. Also, we confirmed eight factors such as BMI, Charlson Comorbidity Index, hospitalization path, nutrition deficiency, infection, sleep disturbance, bed scores, and diaper use are important in distinguishing the outcomes of delirium patients. The classification performance of the proposed method was verified by comparison with three benchmarking models, ANN, SVM with RBF kernel, and Random Forest, using a statistical five-fold cross-validation method. The proposed method showed an improved average performance of 0.6% and 2.7% in both accuracy and AUC criteria when compared with the SVM model with the highest classification performance of the three models respectively.

• Korean Journal of Veterinary Research
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• v.31 no.1
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• pp.109-121
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• 1991

This study was carried out to investigate the morbidity of fatty liver in cattle at the abattoir and on the farm, and to cytodiagnose fatty liver in cattle by fine needle aspiration biopsy. Incidence rates of fatty liver in cattle, detected macroscopically or based on hepatic lipid content by buoyancy, were 0.30% in Korean native cows, 4.70% in dairy cows, and 0.15% in dairy bull. Fatty liver was enlarged, swollen with round edges, light weight, and pale to yellow-orange color, but its color was not always correlated to the severity of fatty liver. The findings of fat infiltration of the hepatic lobule were large droplets around central vein, fine droplets in the periphery, and fat infiltration in the perivascular region execpt for most of normal liver and severe fatty liver. The sensitivty, specificity, and accuracy of cytological finding compared with hepatic lipid content by buoyancy were 94.4%, 95.2%, and 94.9% in normal cases, 64.3%, 100%, and 87.2% in mild cases, 100%, 83.3%, and 87.2% in moderate cases, and 100%, 100%, and 100% in sesvere cases, respectively. Cytological findings were well correlated with histological findings. Complications of fine needle aspiration biopsy were not recognized clinically. Consequently, the cytodiagnosis by fine needle aspiration biopsy is simple, rapid, safe, and economical method compared with histological techniques in the diagnosis of fatty liver in cattle.

• Restorative Dentistry and Endodontics
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• v.24 no.4
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• pp.578-584
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• 1999

The purpose of this experiment was to determine: (1) the safe automatic apical reverse setting that prevents overinstrumentation of the root canal, using Tri Auto ZX$^{(R)}$ and (2) the effect of various irrigant on such instrumentation. The instrumentation was carried out with the automatic apical reverse setting of 0.5, 1.0, 1.5, and 2.0. The root canal irrigants used in usual manner were normal saline(0.9%), NaOCl(2.5%), and RC Prep$^{(R)}$. For each reverse setting and each irrigant, ten teeth were used with the total of 120 teeth. The distance between the file tip and the apical constriction was determined by stereomicroscope using the point that the file began to rotate in reverse direction. When the reverse setting mode was set to 0.5, 18 of 30 were overinstrumented. If these were discriminated by irrigant, 10 of 6 with 0.9% saline, 10 of 6 with NaOCl, and 10 of 6 with RC Prep$^{(R)}$ has the file tip located 0.57${\pm}$0.30mm, 0.73${\pm}$0.39mm, and 0.26${\pm}$0.25mm beyond the apical constriction respectively. In 1.0 setting 15 of 29 were over the apical constriction, and the distribution was 6 in saline, 5 in NaOCl, and 4 in RC Prep$^{(R)}$. The mean distance over the apical constriction was 0.28${\pm}$0.13mm with saline, 0.75${\pm}$0.61mm with NaOCl, and 0.25${\pm}$0.17mm with RC Prep$^{(R)}$. When the autoatic reverse mode was set to 1.5, and 2.0, 5, and 1 teeth were found to be overinstrumented in respective settings. But there were large variations in overinstrumented distances when an attempt was made to compare the effect of irrigants on this overinstrumentations and they were meaningless for the small sample size. When all of the autoreverse setting were combined to compare the number of overinstrumented teeth with each irrigant, there were no significant differences (14 for normal saline, 12 for NaOCl, 13 for RC Prep$^{(R)}$). When 0.5 or 1.0 automatic apical reverse setting mode was used the Tri Auto ZX$^{(R)}$ in clinical application, the possibility of overinstrumentation beyond the apical constriction exists in 55.9% of cases. Therefore 1.5 or 2.0 setting is safer for the preparation inside the canal but this type setting needs additional apical hand preparation of the root canal because the accuracy is lower than 0.5 or 1.0 setting.

• Journal of Navigation and Port Research
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• v.36 no.3
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• pp.205-213
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• 2012

This study focused on the supply-demand and training system of the crew for domestic coastal shipping. First of all, it forecasted the prospect and effect in the future of the crew supply-demand through the analysis to the current situation of crew employment and the internal and external environment changes. Next, it suggested the specific role and alternatives of government, industry and educational institutions after the comparison and examination of the sailor policies among Korea and major shipping countries. In regard to the demand of crew manpower in coastal shipping, it figured out the bottoms and the current circumstances of sailors, and it could anticipate the future demand by the gradational approach. According to the findings, firstly the result of this simulation by the changes of the ship numbers demonstrated that the demand over the next 10 years will be 7,890~8,025 in the case of the growth 0.4%, and 7,894~8,063 in 0.5%. Secondly, assuming the growth 0.1~1%, the result illustrated that the demand will come to 7,879~8,258. This means the fact that the additional manpower has to be input to 20~430 annually from now on. To conclude, this study showed the more rational numbers about the supply-demand than the past researches and displayed the systematic approach to supply and train the crew in domestic coastal shipping.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.89-103
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• 2020

As we face an aging society, the demand for personal mobility for disabled and aged people is increasing. In fact, as of 2017, the number of electric wheelchair in the country continues to increase to 90,000. However, people with disabilities and seniors are more likely to have accidents while driving, because their judgment and coordination are inferior to normal people. One of the causes of the accident is the interference of personal vehicle steering control due to unbalanced road surface conditions. In this paper, we introduce a encoder type semantic segmentation algorithm that can recognize road conditions at high speed to prevent such accidents. To this end, more than 1,500 training data and 150 test data including road surface damage were newly secured. With the data, we proposed a deep neural network composed of encoder stages, unlike the Auto-encoding type consisting of encoder and decoder stages. Compared to the conventional method, this deep neural network has a 4.45% increase in mean accuracy, a 59.2% decrease in parameters, and an 11.9% increase in computation speed. It is expected that safe personal transportation will be come soon by utilizing such high speed algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.238-240
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• 2006

네트워크상에서 발생하는 다양한 형태의 대량의 데이터를 정확하고 효율적으로 분석하기 위해 설계되고 있는 마이닝 시스템들은 목표지향적으로 훈련데이터들을 어떻게 구축하여 다룰 것인지에 대한 문제보다는 대부분 얼마나 많은 데이터 마이닝 기법을 지원하고 이를 적용할 수 있는지 등의 기법에 초점을 두고 있다. 따라서, 점점 더 에이전트화, 분산화, 자동화 및 은닉화 되는 최근의 보안공격기법을 정확하게 탐지하기 위한 방법은 미흡한 실정이다. 본 연구에서는 유비쿼터스 환경 내에서 발생 가능한 문제 중 복잡하고 지능화된 침입패턴의 탐지를 위해 데이터 마이닝 기법과 결함허용방법을 이용하는 개선된 학습알고리즘과 후처리 방법에 의한 RTPID(Refinement Training and Post-processing for Intrusion Detection)시스템을 제안한다. 본 논문에서의 RTPID 시스템은 active learning과 post-processing을 이용하여, 네트워크 내에서 발생 가능한 침입형태들을 정확하고 효율적으로 다루어 분석하고 있다. 이는 기법에만 초점을 맞춘 기존의 데이터마이닝 분석을 개선하고 있으며, 특히 제안된 분석 프로세스를 진행하는 동안 능동학습방법의 장점을 수용하여 학습효과는 높이며 비용을 감소시킬 수 있는 자가학습방법(self learning)방법의 효과를 기대할 수 있다. 이는 관리자의 개입을 최소화하는 학습방법이면서 동시에 False Positive와 False Negative 의 오류를 매우 효율적으로 개선하는 방법으로 기대된다. 본 논문의 제안방법은 분석도구나 시스템에 의존하지 않기 때문에, 유사한 문제를 안고 있는 여러 분야의 네트웍 환경에 적용될 수 있다.더욱 높은성능을 가짐을 알 수 있다.의 각 노드의 전력이 위험할 때 에러 패킷을 발생하는 기법을 추가하였다. NS-2 시뮬레이터를 이용하여 실험을 한 결과, 제안한 기법이 AOMDV에 비해 경로 탐색 횟수가 최대 36.57% 까지 감소되었음을 알 수 있었다.의 작용보다 더 강력함을 시사하고 있다.TEX>로 최고값을 나타내었으며 그 후 감소하여 담금 10일에는 $1.61{\sim}2.34%$였다. 시험구간에는 KKR, SKR이 비교적 높은 값을 나타내었다. 무기질 함량은 발효기간이 경과할수록 증하였고 Ca는 $2.95{\sim}36.76$, Cu는 $0.01{\sim}0.14$, Fe는 $0.71{\sim}3.23$, K는 $110.89{\sim}517.33$, Mg는 $34.78{\sim}122.40$, Mn은 $0.56{\sim}5.98$, Na는 $0.19{\sim}14.36$, Zn은 $0.90{\sim}5.71ppm$을 나타내었으며, 시험구별로 보면 WNR, BNR구가 Na만 제외한 다른 무기성분 함량이 가장 높았다.O to reduce I/O cost by reusing data already present in the memory of other nodes. Finally, chunking and on-line compression mechanisms are included in both models. We demonstrate that we can obtain significantly high-performanc