• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• Journal of Nutrition and Health
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• v.55 no.1
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• pp.174-187
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• 2022

Purpose: This study was performed to evaluate an education program for housewives to reduce sodium intake based on the social cognitive theory. Methods: Housewives (n = 387) received 2 education sessions focused on food purchase and cooking, and completed a questionnaire on their perceptions of environmental, cognitive, and behavioral factors and the stages of behavioral change to reducing sodium intake both before and after the education program. Results: After the education program, the recognition of social efforts for sodium reduction and sodium labeling and experience with low-sodium products increased. Positive expectancies for the prevention of osteoporosis by the reduction of sodium were enhanced while the main barriers in practicing sodium reduction decreased, especially 'interrupting social relationships when dining with others', 'bad taste', 'preference for soup or stew', and 'limited knowledge and skills to practice'. In addition, cognition and nutrition knowledge related to reducing sodium intake were improved on all scores, but the effect on self-efficacy and dietary behavior was limited to only a few items. The percentage of participants in the pre-action stage (including pre-contemplation, contemplation, and preparation stages) for reducing sodium intake decreased from 43.2% before education to 21.5% after education, while that in the action stage increased from 19.6% before education to 43.5% after education (p < 0.001). The education program had the most significant impact on participants who were in the pre-action stage and showed improved scores in all sections. Conclusion: These results suggest that a customized education program for housewives could be an effective tool to reduce sodium intake by improving personal expectancies, cognition, and nutrition knowledge regarding sodium reduction and enabling a greater section of the population to move to the action stage of reducing sodium intake.

• Journal of Nutrition and Health
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• v.56 no.1
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• pp.97-111
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• 2023

Purpose: Childhood obesity has become a social problem due to the social distancing necessitated by the coronavirus disease 2019 pandemic. This study aimed to identify the dietary problems of obese children through various dietary assessment methods and to confirm the usefulness of each method. Methods: The subjects were 88 students in the 4th to 6th grade of elementary school who participated in the nutrition camp organised by the Busan Metropolitan Office of Education, 2020. To evaluate dietary problems and assess diet quality, 24-hour meal records, monthly food intake frequency, and Dietary Screening Test (DST) data were analyzed. Results: Of the subjects, 15.7%, 30.3%, and 53.9% were normal weight, overweight, and obese, respectively. The average age was 11.77 ± 0.77 years and the average body mass index was 23.96 ± 3.01 kg/m². It was observed from the 24-hour meal record method that the overweight and obese subject groups consumed fewer green vegetables (p < 0.001) and white vegetables (p < 0.01) than the normal weight group. In the monthly food intake frequency method, the consumption of ramen (p < 0.01), snacks (p < 0.05), and sausages (p < 0.05) were high in the obese group, and that of anchovies, broccoli, and sweet pumpkin was high in the normal group (p < 0.05). The comparative data from the DST revealed that the overweight and obese groups had less vegetable intake than the normal weight group (p < 0.01) and had higher intakes of dairy products, fast food, and sweet snacks (p < 0.05). Conclusion: The usefulness of each method in the dietary evaluation of obese children was confirmed. To address the problem of obesity, it is necessary to evaluate the dietary problem and approach it with a customized solution tailor-made for the individual subject.

• Journal of Korea Entertainment Industry Association
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• v.13 no.5
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• pp.263-271
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• 2019

The recent phenomenon of job "Miss Match", which is inconsistent with knowledge in the demand of educational training institutes and industries, has spread to an increase in private education costs for reeducation and employment of new hires, resulting in weak individual job competency and poor employment capability, as well as economic and material waste at the national level. To compensate for these problems, the National Competency Standards(NCS), which are available immediately in practice and look for a standard point of national job competency with the aim of fostering human resources sought by industries, were developed, and even the NCS-based qualification system was launched in line with the stream of times. This study is intended to look into the importance and priority of competency units and competency unit elements at the NCS-based qualification L3 level in the skin care field for an overall check of the NCS-based qualification level at a time when educational institutes are organizing and operating the school curriculums according to the NCS and NCS-based qualification level. And it is attempted to provide basic data for the development of curriculum in fostering professional human resources required by industries. To analyze the needs for competency units and competency unit elements at the L3 level, a survey using AHP method was carried out to a group of field experts and a group of education experts. In addition, the SPSS(Statistical Package for Social Science) ver. 21.0 and Expert Choice 2000, an AHP-only solution was used to do statistical processing through the processes of data coding and data cleaning. The findings showed that there was a partial difference of opinion between a group of field experts and a group of education experts. This indicates that the inconsistencies between educational training institutes and industrial sites should be resolved at this time of change with the aim of fostering field customized human resources with professional skills. Consequently, the solution is to combine jobs at industrial sites and standardized educations of educational institutes with human resources required at industrial sites.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.50-63
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• 2018

The rapid urbanization had led to a distortion of natural hydrological cycle system. The change in hydrological cycle structure is causing streamflow depletion, changing the existing use tendency of water resources. To manage such phenomena, a streamflow depletion impact assessment technology to forecast depletion is required. For performing such technology, it is indispensable to build GIS-based spatial data as fundamental data, but there is a shortage of related research. Therefore, this study was conducted to use the use of GIS-based time series spatial data for streamflow depletion assessment. For this study, GIS data over decades of changes on a national scale were constructed, targeting 6 streamflow depletion impact factors (weather, soil depth, forest density, road network, groundwater usage and landuse) and the data were used as the basic data for the operation of continuous hydrologic model. Focusing on these impact factors, the causes for streamflow depletion were analyzed depending on time series. Then, using distributed continuous hydrologic model based DrySAT, annual runoff of each streamflow depletion impact factor was measured and depletion assessment was conducted. As a result, the default value of annual runoff was measured at 977.9mm under the given weather condition without considering other factors. When considering the decrease in soil depth, the increase in forest density, road development, and groundwater usage, along with the change in land use and development, and annual runoff were measured at 1,003.5mm, 942.1mm, 961.9mm, 915.5mm, and 1003.7mm, respectively. The results showed that the major causes of the streaflow depletion were lowered soil depth to decrease the infiltration volume and surface runoff thereby decreasing streamflow; the increased forest density to decrease surface runoff; the increased road network to decrease the sub-surface flow; the increased groundwater use from undiscriminated development to decrease the baseflow; increased impervious areas to increase surface runoff. Also, each standard watershed depending on the grade of depletion was indicated, based on the definition of streamflow depletion and the range of grade. Considering the weather, the decrease in soil depth, the increase in forest density, road development, and groundwater usage, and the change in land use and development, the grade of depletion were 2.1, 2.2, 2.5, 2.3, 2.8, 2.2, respectively. Among the five streamflow depletion impact factors except rainfall condition, the change in groundwater usage showed the biggest influence on depletion, followed by the change in forest density, road construction, land use, and soil depth. In conclusion, it is anticipated that a national streamflow depletion assessment system to be develop in the future would provide customized depletion management and prevention plans based on the system assessment results regarding future data changes of the six streamflow depletion impact factors and the prospect of depletion progress.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.211-226
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• 2023

As we transition into the post-COVID era, economic activities that were stagnant are regaining momentum. In particular, there is a growing trend of technology entrepreneurship driven by the opportunities of digital transformation in the Fourth Industrial Revolution. However, entrepreneurship education content is struggling to keep up with the rapid pace of technological change. This study aims to emphasize the importance of entrepreneurship mentoring as a crucial component of entrepreneurship education content that requires adaptation and advancement due to the increasing demand for technology entrepreneurship. This study redefines startup mentoring, which is differentiated from general mentoring, at the present time when the demand for startups, which increases with the declining employment rate, increases, and the development of quality startup education contents and securing professional startup mentors are required. According to the start-up stage, it is divided into preliminary entrepreneurs and early entrepreneurs, and the effect of entrepreneurship knowledge and self-efficacy among start-up mentoring functions on entrepreneurial will and mentoring satisfaction is improved by empirically researching the effects of start-up mentoring functions in the case of initial entrepreneurs as a moderating effect. To confirm the importance of entrepreneurship mentoring effect for. To this end, among the mentoring functions, entrepreneurship knowledge and self-efficacy were set as independent variables, and entrepreneurial will and mentoring satisfaction were set as dependent variables. The research model was designed and hypotheses were established. In addition, empirical analysis was conducted by conducting a questionnaire survey on trainees who received entrepreneurship mentoring education at ICCE Startup School and Opus Startup School. To summarize the results of the empirical analysis, first, among the entrepreneurship mentoring functions, entrepreneurship knowledge and self-efficacy were analyzed to have a significant positive (+) effect on entrepreneurial will. Second, among the entrepreneurship mentoring functions, entrepreneurship knowledge and self-efficacy were analyzed to have a significant positive (+) effect on mentoring satisfaction. Third, it was analyzed that entrepreneurship had no significant moderating effect on entrepreneurial knowledge and entrepreneurial will. Fourth, it was analyzed that entrepreneurship had no significant moderating effect on mentoring satisfaction. Fifth, it was found that entrepreneurship had a significant moderating effect between self-efficacy and will to start a business. As a result of the research analysis, the first implication is that the mentoring function in start-up education is analyzed to produce meaningful results for both the initial entrepreneurs and the prospective entrepreneurs in the will to start a business and satisfaction. . Second, it was analyzed that there was no significant relationship between whether a business was started and the mentoring function and effect. However, it was analyzed that the will to start a business through improvement of self-efficacy through mentoring was significantly related to whether or not to start a business. turned out to be helpful. Many start-up education programs currently conducted in Korea educate both early-stage entrepreneurs and prospective entrepreneurs at the same time for reasons such as convenience. However, through the results of this study, even in small-scale entrepreneurship mentoring, it is suggested that customized mentoring through detailed classification such as whether the mentee has started a business can be a method for successful entrepreneurship and high satisfaction of the mentee.

• Journal of Nutrition and Health
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• v.48 no.5
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• pp.429-440
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• 2015

Purpose: The purpose of this study was to examine sodium-related nutrition knowledge, eating attitudes, eating behaviors, and self-efficacy by stages of behavioral change in reducing sodium intake among childcare center foodservice employees. Methods: Subjects (n = 333) were categorized according to two groups based on the stages of change; Pre-action stage (PA group: precontemplation/contemplation/preparation stage), Action stage (A group: action/maintenance stage). Results: A major source of sodium-related nutrition information was TV/radio (56.6%) and only 166 people (49.8%) have experienced nutrition education specific to sodium. Although the A group showed slightly higher scores for nutrition knowledge than the PA group, the difference was not significant. The percentages of correct answers for 'daily goal of sodium intake for adults (27.0%)', 'calculation of sodium content in nutrition labeling (30.3%)' were low for both groups. The A group (total score: 40.3) had more desirable eating attitudes regarding reducing sodium intake than the PA group (36.6, p < 0.001). The total score for eating behaviors was slightly higher in the A group (49.6) than in the PA group (48.5), but without statistical significance. The A group (total score: 58.2) also received higher scores for self-efficacy regarding reducing sodium intake than the PA group (52.5, p < 0.001). Conclusion: This study suggests that nutrition education for childcare center foodservice employees should be expanded and customized education should be implemented according to the stages in reducing sodium intake. It is also suggested that food companies make efforts to develop low-sodium products.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.1
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• pp.285-301
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• 2020

Looking at the problem of aging in the nation from a demographic perspective, it is not a problem of the overall population, but of the structure of the population. It is the baby boomer and post-baby boomers, the largest population in the country. Baby boomers were born between 1955 and 1963, and currently have a population of 7001,333, which is 13.6 percent (as of 2015). The Post-Baby Boomer generation was born between 1964 and 1974, with a total population of 9,567,171, accounting for 18.8 percent of the total population. In particular, baby boomers and post-baby boomers (32.4% of the total population) have begun to retire or will retire soon. The average life expectancy continues to increase due to the development of medical technology, and the falling birth rate of newborns and the declining population of the production population are darkening the domestic economy. In a policy proposal aimed at easing the nation's falling economic growth rate, women's participation rate is as high as Sweden and men's efforts to increase it as high as Japan's, while the elderly rate is desirable to maintain Korea's high level. This is because the expansion of the elderly generation's participation in economic activities could ease a sharp drop in economic growth and reduce the burden of supporting the elderly population. The study, based on this social problem awareness and problem solving plan, looks at the relationship between career orientation and satisfaction in start-up education based on the diverse career base of active seniors, and also suggests the importance of customized start-up education on the diversity of active seniors by clarifying the relationship between them, and suggests the desirable direction of senior start-up policy design, funding, and start-up education. Based on the theoretical background, the concept of five factors was defined: active senior, career-oriented, satisfaction level of start-up education, willingness to start a business, and the concept definition of an active senior, which is particularly key to the baby boomers in their 50s and 60s, is generally regarded as a source of consumption or welfare benefits, but in this study, the concept of active start-up is reflected in the domestic start-up market by young people in their 40s, 50s and 60s. As a result of a hypothesis test. Hypothesis 1 and Hypothesis 5: Career orientation has been verified to affect the willingness to start a business and the behavior of preparation for a start-up. Hypothesis 3: The willingness to start a business has been verified as having an effect between startup preparation actions. Hypothesis 4: The satisfaction level of start-up education has been verified to affect start-up preparation behavior. However, hypothesis 2: The satisfaction level of education for start-ups does not affect the willingness to start a business. Such results can be inferred that satisfaction in start-up education does not have a direct effect on the will to start a business and increases the will to start a business through the influence of personal career orientation.

• Journal of Nutrition and Health
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• v.50 no.2
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• pp.171-179
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• 2017

Purpose: We conducted comparative analysis of dietary behavior and food and nutrient intakes of Korean elderly in urban and rural areas using the 2014 Korea National Health and Nutrition Examination Survey (KNHANES). Methods: This study was conducted on 1,239 participants (urban elderly: 867, rural elderly: 372) aged 65 years and over who participated in the health examination and nutrition survey in the 6th 2014 KNHANES. Dietary behaviors, including skipping meals, eating out frequencies, and food and nutrient intakes were analyzed using 24-hour recall data. Analysis of complex sample design data through SPSS 19.0 was used for the analysis. Results: The rate of skipping dinner was higher in urban (6.5%) than in rural elderly (3.6%) (p < 0.05), and the frequency of eating out per week of urban elderly (1.73) was higher than that of rural elderly (1.35) (p < 0.001). The rural elderly consumed a greater amount of grain compared to urban elderly, whereas consumption of water, seaweed food, and dairy products was lower in rural than in urban areas (p < 0.05). The rural elderly consumed significantly less highly unsaturated fatty acids, n-6 fatty acids, phosphorus, iron, vitamin A, carotene, niacin, and vitamin C in comparison with elderly in urban areas. Comparison of the percentages of Dietary Reference Intakes for Koreans (KDRIs) between the two groups showed that intakes of vitamin A and vitamin C were significantly lower in the rural elderly than in urban elderly. Conclusion: The elderly in rural areas showed unbalanced food and nutrient intakes compared to the elderly in urban areas. Therefore, customized nutrition education according to residential areas should be developed and provided to rural elderly to improve their health and nutritional status.