• Magazine of the Korean Society of Agricultural Engineers
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• v.18 no.1
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• pp.4038-4051
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• 1976

This study was intended to provide the basic design creteria for the refrigerated storage, and to estimate the required optimum capacity of refrigerator for the different sizes and kinds of the existing fruit storage. The structural characteristics of the existing fruit storages in Pyungtaek-khun of Kyungki-do were surveyed. The average out-door air temperature during the expected storage life after harvesting, was obtained by analyzing the weather information. The heat transfer rates through the different models of storage walls were estimated. The refrigerating load required for different models of fruit storage was analyzed in the basis of out-door air temperature. The results obtained in this study are summarized as follows: 1. The fruit storages surveyed were constructed on-ground, under-ground and sub-ground type buildings. The majority of them being the on-ground buildings are mostly made of earth bricks with double walls. Rice hull was mostly used as the insulating materials for their walls and ceilings. About 42% of the buildings were with the horizontal ceiling, 22% with sloped ceiling, and about 36% without ceiling. About 60% of the storage buildings had floor without using insulated material. They were made of compacted earth. 2. There is no difference in heat transfer among six different types of double walls. The double wall, however, gives much less heat transfer than the single wall. Therefore, the double wall is recommended as the walls of the fruit storage on the point of heat transfer. Especially, in case of the single wall using concrete, the heat transfer is about five time of the double walls. It is evident that concrete is not proper wall material for the fruit storage without using special insulating material. 3. The heat transfer through the storage walls is in inverse proportion to the thickness of rice hull which is mostly used as the insulating material in the surveyed area. It is recommended that the thickness of rice hull used as the insulating material far storage wall is about 20cm in consideration of the decreasing rate of heat transfer and the available storage area. 4. The design refrigerating load for the on-ground storages having 20 pyung area is estimated in 4.07 to 4.16 ton refrigeration for double walls, and 5.23 to 6.97 ton refrigeration for single walls. During the long storage life, however, the average daily refrigerating load is ranged from 0.93 to 0.95 ton refrigeration for double walls, and from 1.15 to 1.47 ton refrigeration for single walls, respectively. 5. In case of single walls, 50.8 to 61.4 percent to total refrigerating load during the long storage life is caused by the heat transferred into the room space through walls, ceiling and floor. On the other hand, 39.1 to 40.7 percent is for the double walls. 6. The design and average daily refrigerating load increases in linear proportion to the size of storage area. As the size increases, the increasing rate of the refrigerating load is raised in proportion to the heat transfer rate of the wall. 7. The refrigerating load during the long storage life has close relationship to the out-door air temperature. The maximum refrigeration load is shown in later May, which is amounted to about 50 percent to the design refrigerating load. 8. It is noted that when the wall material having high heat transfer rate, such as the single wall made of concrete, is used, heating facilities are required for the period of later December to early February.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.121-137
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• 2022

The purpose of this study is to present the necessary success factors and strategies for high-tech social ventures and stakeholders in the related ecosystem by empirically identifying factors that affect their sustainable performance. Based on prior research, the dimensions of three performance factors were presented: core technology competency, core business competency, and social mission orientation. Then, such sub-dimensions such as technology innovation orientation, R&D capability, business model, customer orientation, social network, and social mission pursuit were derived. For empirical analysis, a survey was conducted on domestic high-tech social ventures, and the significance of the hypothesis was tested through PLS-structural equation analysis of the collected 243 valid data. As a result, it was found that the technology innovation orientation was embedded as an abstract organizational and cultural characteristic in the high-tech social venture, which is a research sample, and thus did not significantly affect the dependent variable. In other words, aiming for the latest cutting-edge technology alone cannot affect performance, and it is a result of proving the need for substantial influencing factors that can strengthen it. On the other hand, the business model had a significant effect only on social performance, which is presumed to be the limitation of measurement tools developed for social enterprises, and the results of additional multi-group analysis to determine the cause also supported the basis for this estimation. Excluding the previous two performance factors, R&D competency, customer orientation, social network, and social mission pursuit were all found to have a significant positive (+) effect on social and economic performance. This study laid a foundation for related research by identifying high-tech social ventures emerging in the ecosystem of a social economy and expanded empirical research models related to the performance of existing social enterprises and social ventures. However, in the research method or process, there were limitations such as factor derivation or verification for balance of dual performance, subjective measurement method, and sample representativeness. It is expected that more in-depth follow-up studies will continue by supplementing future limitations and designing improved research models.

• Journal of Life Science
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• v.18 no.6
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• pp.796-803
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• 2008

Mutations in the APP gene lead to enhanced cleavage by ${\beta}-$ and ${\gamma}-secretase$, and increased $A{\beta}$ formation, which are closely associated with Alzheimer's disease (AD)-like neuropathological changes. Recent studies have shown that exercise training can ameliorate pathogenic phenotypes ($A{\beta}-42$, BDNF, GLUT-1 and HSP70) in experimental models of Alzheimer's disease. Here, we have used NSE/APPsw transgenic mice to investigate directly whether exercise training ameliorates pathogenic phenotypes within Alzheimer's brains. Sixteen weeks of exercise training resulted in a reduction of $A{\beta}-42$ peptides and also facilitated improvement of cognitive function. Furthermore, GLUT -1 and BDNF proteins produced by exercise training may protect brain neurons by inducing the concomitant expression of genes that encode proteins (HSP-70) which suppress stress induced neuron cell damages from APPsw transgenic mice. Thus, the improved cognitive function by exercise training may be mechanistically linked to a reduction of $A{\beta}-42$ peptides, possibly via activation of BDNF, GLUT-1, and HSP-70 proteins. On the basis of the evidences presented in this study, exercise training may represent a practical therapeutic management strategy for human subjects suffering from Alzheimer's disease.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Journal of Science Education
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• v.32 no.2
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• pp.71-86
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• 2008

The purpose of this study was to apply After-school programs related to sub-chapter 'The Change of Weather', and thereby to investigate the effect of After-school program on science-related attitude and learning achievement of students, and interaction between treatment methods and students' learning ability. The subjects of study consisted of 2nd grade students of sixty four students in high school. Sixty four students were divided into two categories by experimental and control groups on the basis of midterm examination before teaching treatment. The experimental groups have received four After-school programs including making models of a weather front, measurement of wind, measurement of temperature and the dew point, making a three-dimensional weather chart which were developed by researcher for six times. The control groups have received the instruction through the conventional teaching methods. Seventy questions within seven frameworks of TOSRA have been used in this study as an evaluation instrument of science-related attitude. Learning achievement has been evaluated using an instrument developed by researcher. The scores of both pre-test and post-test were estimated by ANCOVA. The results of this study can be summarized as follows. (1) After-school programs were more effective in progressing the three categories of science related attitude of high school students i.e. pleasure of science class(p<.05), reception of scientific attitude(p<.01), attitude about a science research(p<.05) than conventional teaching methods. (2) Experimental groups showed statistically significant improvement on learning achievement than control groups(p<.05). (3) The effect of treatment methods on students' learning ability has been improved in experimental groups more positively than control groups(p<.05). High level students in experimental groups showed significant improvement on learning achievement than low level students according to the representing profile plot. But there were no significant interaction between treatment methods and students' learning ability(p>.05) In conclusion, the After-school programs have positive effect on the improvement of science related attitude and learning achievement.

• 한국노년학
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• v.41 no.2
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• pp.271-284
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• 2021

This study was conducted to derive factors that affect the satisfaction of home visiting health care services and to develop effective community care models by using the results of Seoul's outreach service which is the basis for Korean community care. The population of the study was the elderly aged 65 and 70 who participated in the Seoul's outreach community services 3rd stage (July 2017 - June 2018) and 4th stage (July 2018 to June 2019). 2,200 people were extracted by the proportional allocation method and home visit interviews were conducted on them. Subjects were divided into sub-groups based on chronic disease prevalence, and logistic regression was conducted to derive factors that affect the satisfaction of home visiting health care services. The results demonstrated that the elderly without chronic diseases were more satisfied when they received health education and counseling services, the elderly with one chronic disease were more satisfied when they received Community resource-linked services. In the case of elderly people with two or more chronic diseases, the service satisfaction level is increased when health condition assessment and Community resource-linked services are provided. Regardless of whether or not they have chronic diseases, service delivery time was a factor that increased satisfaction in home visiting health care. And the degree of explanation understanding was a factor that increased satisfaction for both single and complex chronic patients. Home Visiting health care services based on the community is a key component of the ongoing community care. In order to increase the sustainability and effectiveness of community care in the future, Community-oriented health care services based on the degree of chronic diseases of the elderly should be provided. In order to provide more effective services, however, it is necessary (1) to establish a linkage system to share health information of the subject held by the National Health Insurance Service to local governments and (2) to provide capacity-building education for visiting nurses to improve the quality of home visiting health care services. It is hoped that this study will be us ed as bas ic data for the successful settlement of community care.