Journal of The Korean Society of Agricultural Engineers
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v.48
no.5
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pp.51-60
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2006
In order to examine the heat transfer characteristic of a soil warming system and effects of soil warming on the greenhouse heating load, control experiments were performed in two greenhouses covered with double polyethylene film. One treated the soil warming with an electric heat wire and the other treated a control. Inside and outside air temperature, soil temperature and heat flux, and heating energy consumption were measured under the set point of heating temperature of $5,\;10,\;15,\;and\;20^{\circ}C$, respectively. Soil temperatures in a soil warming treatment were observed $4.1\;to\;4.9^{\circ}C$ higher than a control. Heating energy consumptions decreased by 14.6 to 30.8% in a soil warming treatment. As the set point of heating temperature became lower, the rate of decrease in the heating energy consumptions increased. The percentage of soil heat flux in total heating load was -49.4 to 24.4% and as the set point of heating temperature became higher, the percentage increased. When the set point of heating temperature was low in a soil warming treatment, the soil heat flux load was minus value and it had an effect on reducing the heating load. Soil heat flux loads showed in proportion to the air temperature difference between the inside and outside of greenhouse but they showed big difference according to the soil warming treatment. So new model for estimation of the soil heat flux load should be introduced. Convective heat transfer coefficients were in proportion to the 1/3 power of temperature difference between the soil surface and the inside air. They were $3.41\;to\;12.42\;W/m^{2}^{\circ}C$ in their temperature difference of $0\;to\;10^{\circ}C$. Radiative heat loss from soil surface in greenhouse was about 66 to 130% of total heating load. To cut the radiation loss by the use of thermal curtains must be able to contribute for the energy saving in greenhouse.
Five direct/diffuse decomposition models were validated using the eight years data set of direct normal beam insolation measured in Seoul. The comparison has been performed In terms of the widely used statistical indicators such as MBE, RMSE, CV(RMSE), t-Statistic and Degree of Agreement. Result indicates that most of the correlations exhibit a tendency to underestimate the direct normal beam insolation except Bouguer's model. Most of big discrepancies between the measured and the predicted values was mainly shown in near the sunrising and the sunset period. Even though the investigated five models showed fairly large disagreement for the measured values by 34%$\sim$48% of CV(RMSE), Udagawa's correlation which includes the effect of solar altitude variation appears to performs always better in every statistical error tests.
Journal of Korean Society of Occupational and Environmental Hygiene
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v.31
no.4
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pp.378-384
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2021
Objectives: Horse trainers ensure the horses they are training and monitor horse's health, hygiene. While most of the studies on horse trainer's health focused on musculoskeletal disorders, few studies have examined the health effect of occupational exposure. This study aimed to investigate the risk of lung cancer in Korean Horse trainers. Methods: Among the largest health screening program of health screening service of the National Health Insurance Corporation, 2,246 workers were selected for study. We utilized data from the National Health Insurance Service (NHIS) National Cohort Data Base 2005-2017. We performed analyses using a Cox's proportional hazards model to identify the risk of lung cancer in Horse trainers. Results: This study found that the horse trainers group had a higher risk of lung cancer 10.07 (95% CI :2.38-42.64) compared to other occupational group. Additionally, there was 6.5 times higher risk of lung cancer in non-smoker horse trainers group. Conclusions: We, thus, verified horse trainers could have relation with increase of lung cancer risk. As lung cancer is known as a cancer with a high contribution of occupational factors compared to other cancers, it is necessary to determine the efficacy of continuous attention and active management of occupational exposure.
KSII Transactions on Internet and Information Systems (TIIS)
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v.15
no.6
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pp.1957-1980
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2021
The significant aim of this research has always been to evaluate the mechanism for efficient and inherently aware usage of vitality in-home devices, thus improving the information of smart metering systems with regard to the usage of selected homes and the time of use. Advances in information processing are commonly used to quantify gigantic building activity data steps to boost the activity efficiency of the building energy systems. Here, some smart data mining models are offered to measure, and predict the time series for energy in order to expose different ephemeral principles for using energy. Such considerations illustrate the use of machines in relation to time, such as day hour, time of day, week, month and year relationships within a family unit, which are key components in gathering and separating the effect of consumers behaviors in the use of energy and their pattern of energy prediction. It is necessary to determine the multiple relations through the usage of different appliances from simultaneous information flows. In comparison, specific relations among interval-based instances where multiple appliances use continue for certain duration are difficult to determine. In order to resolve these difficulties, an unsupervised energy time-series data clustering and a frequent pattern mining study as well as a deep learning technique for estimating energy use were presented. A broad test using true data sets that are rich in smart meter data were conducted. The exact results of the appliance designs that were recognized by the proposed model were filled out by Deep Convolutional Neural Networks (CNN) and Recurrent Neural Networks (LSTM and GRU) at each stage, with consolidated accuracy of 94.79%, 97.99%, 99.61%, for 25%, 50%, and 75%, respectively.
Purpose: The major objective of this study is to develop a model for the impact of franchisors' Gapjil (verbal·nonverbal Gapjil, abusing bargaining position, refusing transaction, false or exaggerated information, restrictive practices, unfair damage compensation) on franchisee's recontract intention. We also examine the mediating role of economic satisfaction and social satisfaction in the relationship between franchisors' Gapjil and franchisee's contract intention. Research design, data, and methodology: Data were collected from franchisee owners located nationwide in Korea. Out of 256 questionaires distributed, a total of 256 questionnaires were returned. After excluding 10 invalid respondent questionnaires, we coded and analyzed 246 valid questionnaires (effective response rate of 96.09%) using frequency, confirmatory factor analysis, correlations analysis, and structural equation modeling with SPSS 22.O and SmartPLS 3.0. Results: The findings of this study are summarized as follows: First, among the Gapjil of the franchisors, restrictive practices and unfair damage compensation had negative effects on economic and social satisfaction, but verbal and nonverbal Gapjil for economic and social satisfaction was not significant. Second, abusing bargaining positions and false or exaggerated information had negative effects on social satisfaction, but for economic satisfaction, found to be insignificant. Third, economic and social satisfaction had positive effects on the franchisee's recontract intention to the franchisor. Conclusion: The following implications of this study are as follows. First, the construct of Gapjil that occurs between the franchisors and the franchisees was first presented, and the franchisors' Gapjil is divided into interpersonal Gapjil and structural Gapjil. Second, the Gapjil of the franchisors can be an important predictor variable in maintaining and developing a long-term relationship between the franchisors and the franchisees. Third, solving conflict due to the Gapjil problem between franchisors and franchisees can be an important factor for franchisors and franchisees to co-survive and thrive in Korean franchise system. Fourth, this study suggest that managing the Gapjil of the franchisors was a important antecedent factor in maintaining long-term relationship between the franchisors and the franchisees. Therefore, this study will help franchisors formulate effective symbiotic marketing strategies to satisfy relationships with franchisees and consequently enhance long-term orientation.
The development of environmentally friendly products and services has become a trend, and the development and utilization of eco-friendly textiles with economic value is gaining attention as a new business model. Analyzing and identifying trends and developments in eco-friendly textiles can provide important information and insights for various stakeholders such as companies, governments, and consumers to help them achieve sustainable growth. For this study, we collected and analyzed data from newspaper articles mainly covering the textile and fashion sector from 2000 to June 2023. A total of 12,331 articles containing the keyword 'eco-friendly textiles' were collected, and after performing morphological analysis on the extracted data, Latent Dirichlet Allocation and Dynamic Topic Modeling analysis were performed to identify topics by year. The results of the study are expected to provide strategic guidance and insights for the sustainable development of the textile industry, thereby helping to promote the research, development, and commercialization of eco-friendly textiles.
The Journal of Korean Academic Society of Nursing Education
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v.5
no.1
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pp.58-71
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1999
Nursing process is an essential part for nursing practice. Nursing faculty members must focus on the clinical application for students and try to identify the possible problems that students might face in the fields. The purpose of this study is to examine the actual condition of nursing process education in curricula and to investigate the response of students in clinical experience of nursing process. From 462 students in the 6 associate programs(ADN) and the 6 baccalaureate programs (BSN) data was collected by questionnaire. The results were as followed. 1. Seven programs (58.3%) opened the nursing process in mainly sophomore (BSN) or freshman(ADN). If not opened, the nursing process was taught at the major subjects(espcially fundamental nursing or adult nursing). 2. All Students responded they we supposed to use nursing process in preparing the case report. The majority(94.6%) used NANDA lists for nursing diagnosis and 55.7% of subjects consulted the Korean terms by KNA when translating. The tutors for nursing process in clinical settings were the professor in charge of the subject (68.6) or clinical instructors (48.1%) , assistants(34%). 3. The problems in clinical application that students experienced consisted of 17 items and the mean was 2.27. The biggest problem was 'the lack of the model for RN of applying the nursing process in clinical settings'(2.97). Next the big problem was 'the lack of the competency for implementing the established nursing plans'(2.69). All items were significantly different according to the level of educational programs(ADN or BSN). ADN students had more problems in applying the each step of nursing process and BSN students perceived the NANDA as a guidance of nursing diagnosis and the inconsistency of advices from several instructors or practicum to be mere problematic. 4. The mean of merits after application of nursing process was relatively fair (2.82). The best merit was 'they can identify nursing problems more exactly'(3.07). The second high merit was 'they can study the rational of nursing action' (3.03). BSN than ADN and the subjects of second year than of one year in clinical experience perceived the use of nursing process to be better. Based on this results we need to enforce the application of nursing diagnosis in the class. The use of sample cases can be the efficient method. Students can identify the possible health problems for patient from the cases in imaginary world and discuss them each other. Also we can use the discussion session after practice every other day or as needed. All this is on the good interaction between tutor and student. We must consider to have enough time for student to seize the essence of the nursing process.
Soo Hyung Jeon;In Seon Lee;Gyoo yong Chi;Jong Won Kim;Chang Wan Kang;Yong Tae Lee
Journal of Physiology & Pathology in Korean Medicine
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v.37
no.6
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pp.172-177
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2023
In order to deduce the pathogenic factor(PF) diagnosis logic of underlying in pattern identification of Korean medicine, 2,072 cases of DSOM(Diagnosis System of Oriental Medicine) data from May 2005 to April 2022 were collected and analyzed by means of decision tree model(DTM). The entire data were divided into training data and validation data at a ratio of 7:3. The CHAID algorithm was used for analysis of DTM, and then validity was tested by applying the validation data. The decision rules of items and pathways determined from the diagnosis data of Qi Deficiency, Blood Deficiency, Yin Deficiency and Yang Deficiency Pathogenic Factor of DSOM were as follows. Qi Deficiency PF had 7 decision rules and used 5 questions: Q124, Q116a, Q119, Q119a, Q55. The primary indicators(PI) were 'lack of energy' and 'weary of talking'. Blood deficiency PF had 7 decision rules and used 6 questions: Q113, Q84, Q85, Q114, Q129, Q130. The PI were 'numbness in the limbs', 'dizziness when standing up', and 'frequent cramps'. Yin deficiency PF had 3 decision rules and used 2 questions: Q144 and Q56. The PI were 'subjective heat sensation from the afternoon to night' and 'heat sensation in the limbs'. Yang deficiency PF had 3 decision rules and used 3 questions: Q55, Q10, and Q102. The PI were 'sweating even with small movements' and 'lack of energy'. Conclusively, these rules and symptom information to decide the Qi·Blood·Yin·Yang Deficiency PF would be helpful for Korean medicine diagnostics.
The purpose of this paper is to obtain reliable rainfall data for runoff simulation and other hydrological analysis by the calibration of gauge rainfall. The calibrated gauge rainfall could be close to the actual value with rainfall on the ground. In order to analyze the wind effect of ground rain gauge, we selected the rain gauge sites with and without a windshield and standard rain gauge data from Chupungryeong weather station installed by standard of WMO. Simple linear regression model and artificial neural networks were used for the calibration of rainfalls, and we verified the reliability of the calibrated rainfalls through the runoff analysis using $Vflo^{TM}$. Rainfall calibrated by linear regression is higher amount of rainfall in 5%~18% than actual rainfall, and the wind remarkably affects the rainfall amount in the range of wind speed of 1.6~3.3m/s. It is hard to apply the linear regression model over 5.5m/s wind speed, because there is an insufficient wind speed data over 5.5m/s and there are also some outliers. On the other hand, rainfall calibrated by neural networks is estimated lower rainfall amount in 10~20% than actual rainfall. The results of the statistical evaluations are that neural networks model is more suitable for relatively big standard deviation and average rainfall. However, the linear regression model shows more suitable for extreme values. For getting more reliable rainfall data, we may need to select the suitable model for rainfall calibration. We expect the reliable hydrologic analysis could be performed by applying the calibration method suggested in this research.
Kim, Yeon-Joong;Kim, Tae-Woo;Yoon, Jong-Sung;Kim, Myong-Kyu
Journal of Ocean Engineering and Technology
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v.33
no.6
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pp.590-596
/
2019
Numerous deaths and substantial property damage have occurred recently due to frequent disasters of the highest intensity according to the abnormal climate, which is caused by various problems, such as global warming, all over the world. Such large-scale disasters have become an international issue and have made people aware of the disasters so they can implement disaster-prevention measures. Extensive information on disaster prevention actively has been announced publicly to support the natural disaster reduction measures throughout the world. In Japan, diverse developmental studies on disaster prevention systems, which support hazard map development and flood control activity, have been conducted vigorously to estimate external forces according to design frequencies as well as expected maximum frequencies from a variety of areas, such as rivers, coasts, and ports based on broad disaster prevention data obtained from several huge disasters. However, the current reduction measures alone are not sufficiently effective due to the change of the paradigms of the current disasters. Therefore, in order to obtain the synergy effect of reduction measures, a study of the establishment of an integrated system is required to improve the various disaster prevention technologies and the current disaster prevention system. In order to develop a similar typhoon search system and establish a disaster prevention infrastructure, in this study, techniques will be developed that can be used to forecast typhoons before they strike by using artificial intelligence (AI) technology and offer primary disaster prevention information according to the direction of the typhoon. The main function of this model is to predict the most similar typhoon among the existing typhoons by utilizing the major typhoon information, such as course, central pressure, and speed, before the typhoon directly impacts South Korea. This model is equipped with a combination of AI and DNN forecasts of typhoons that change from moment to moment in order to efficiently forecast a current typhoon based on similar typhoons in the past. Thus, the result of a similar typhoon search showed that the quality of prediction was higher with the grid size of one degree rather than two degrees in latitude and longitude.
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