• 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 Nutrition and Health
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• v.55 no.3
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• pp.359-375
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• 2022

Purpose: Adult Korean men belonging to the main economically active population are known to have long sedentary hours. This study was undertaken to determine the difference and relevance of sedentary hours on the nutrition, diet, and health status of adult men, and to suggest how to prevent health risk factors. Methods: Subjects (n = 1,068) were classified into 4 groups based on their sedentary hours, ranging from the first quartile (Q1) having the least hours spent sitting, to the fourth quartile (Q4) spending the longest hours. Results: Subjects belonging to Q4 had the lowest average age, the largest waist circumference, and the highest level of education. Among those engaged in economic activities, the ratio of white-collar workers was significantly higher in Q4. Accordingly, the rate of not doing high-intensity or moderate-intensity physical activity while working was also the highest in Q4. A significant difference was obtained in the drinking frequency between groups, but this was found to be associated with the average working hours rather than sedentary hours. The proportion of not doing aerobic exercise was higher with longer sitting hours. The highest diagnosis of diabetes (8.8%) was obtained in the Q4 group. Among the factors related to cardiovascular disease, only low density lipoprotein-cholesterol showed a significant difference, with Q4 being significantly higher than Q1. Considering energy and nutrient intake, vitamin B₁ and calcium intake were the lowest in the group with the longest sitting hours, as well as the least consumption of vitamin C than the recommended estimated average requirement. Conclusion: The results of this study suggest that the health and nutritional status of Korean adult men are affected by sedentary hours. This should be recognized as a health risk factor and guidelines need to be developed for sedentary lifestyle management.

• Korean Journal of Mineralogy and Petrology
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• v.36 no.4
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• pp.289-302
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• 2023

The study area was Gangnim-myeon, Hoengseong-gun, Gangwon-do, composed of the Chiaksan gneiss complex, and it was revealed that the concentrations of uranium (U) and thorium (Th) within the groundwater of the study area exceeded their water quality standards. Hence, artificial weathering experiments were conducted to elucidate mineralogically the mechanisms of their leaching using drilling cores obtained from the corresponding groundwater aquifers. First of all, the mineralogical compositions of core samples were observed, and the results indicated that the content of clinochlore, a member of the chlorite group of minerals that can form through low- and intermediate-temperature metamorphisms, was relatively higher. In addition, the Th concentration was measured ten times higher than that of U. The results of artificial weathering experiments suggested that the Th concentrations gradually increased through the dissolution of radioactive-element-bearing minerals up to the first day, and then they tended to decrease. It could be attributed to the fact that Th was leached with the dissolution of thorite, which might be a secondary mineral, and then dissolved Th was re-precipitated as the various forms of salt, such as sulfate. Even though the U content was lower than that of Th in the core samples, the U concentration was one hundred times higher than that of Th after the weathering experiments. It is likely caused by the gradual dissolution and desorption of U included in intensively weathered thorite or adsorbed as a form of UO₂²⁺ on the mineral surface. In addition, the leaching tendency of U and Th was positively correlated with the bicarbonate concentration. However, the concentrations between U and Th in groundwater exhibited a relatively lower correlation, which might result from the fact that they occurred from different sources, as aforementioned. Among various kinetic models, the parabolic diffusion and pseudo-second-order kinetic models were confirmed to best fit the dissolution kinetics of both elements. The period that would be taken for the U concentration to exceed its drinking-water standard was inferred using the regressed parameters of the best-fitted models, and the duration of 29.4 years was predicted in the neutral-pH aquifers with relatively higher concentrations of HCO₃, indicating that U could be relatively quickly leached out into groundwater.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.12
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• pp.1560-1570
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• 2007

The purpose of this study was to investigate the differences according to lifestyle in anthropometric measurement, dietary attitude, health-related behaviors and nutrient intake among the college students. The subjects were 994 nation-wide college students (male: 385, female: 609) and divided into 7 clusters (PEAO: passive economy/appearance-oriented type, NCPR: non-consumption/pursuit of relationship type, PTA: pursuit of traditional actuality type, PAT: pursuit of active health type, UO: utility-oriented type, POF: pursuit of open fashion type, PFR: pursuit of family relations type). A cross-sectional survey was conducted using a self administered questionnaire, and the data were collected via Internet or by mail. The nutrient intake data collected from food record were analyzed by the Computer Aided Nutritional Analysis Program. Data were analyzed by a SPSS 12.0 program. Average age of male and female college students were 23.7 years and 21.6 years, respectively. Most of the college students had poor eating habits. In particular, about 60% of the PEAO group has irregularity in meal time. The students in PAH and POF groups showed significantly higher consumption frequency of fruits, meat products and foods cooked with oil compared to the other groups. As for exercise, drinking and smoking, there were significant differences between PAH and the other groups. Asked for the reason for body weight control, 16.2% of NCPR group answered "for health", but 24.8% of PEAO group and 26.3% of POF group answered "for appearance". Calorie, vitamin A, vitamin $B_2$, calcium and iron intakes of all the groups were lower than the Korean DRIs. Female students in PTA group showed significantly lower vitamin $B_1$ and niacin intakes compared to the PFR group. Therefore, these results provide nation-wide information on health-related behaviors and nutrient intake according to lifestyles among Korean college students.