• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.175-186
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• 2019

Efforts have been made to introduce the climate smart agriculture (CSA) for adaptation to future climate conditions, which would require collection and management of site specific meteorological data. The objectives of this study were to identify requirements for construction of agricultural meteorology information service system (AMISS) using technologies that lead to the fourth industrial revolution, e.g., internet of things (IoT), artificial intelligence, and cloud computing. The IoT sensors that require low cost and low operating current would be useful to organize wireless sensor network (WSN) for collection and analysis of weather measurement data, which would help assessment of productivity for an agricultural ecosystem. It would be recommended to extend the spatial extent of the WSN to a rural community, which would benefit a greater number of farms. It is preferred to create the big data for agricultural meteorology in order to produce and evaluate the site specific data in rural areas. The digital climate map can be improved using artificial intelligence such as deep neural networks. Furthermore, cloud computing and fog computing would help reduce costs and enhance the user experience of the AMISS. In addition, it would be advantageous to combine environmental data and farm management data, e.g., price data for the produce of interest. It would also be needed to develop a mobile application whose user interface could meet the needs of stakeholders. These fourth industrial revolution technologies would facilitate the development of the AMISS and wide application of the CSA.

• Journal of Venture Innovation
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• v.6 no.4
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• pp.41-62
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• 2023

Given that SME workers are the driving force of national competitiveness and the basis and cornerstone of the industry, it is meaningful to study workers' job satisfaction and the factors that affect job satisfaction. In addition to variables related to corporate competitiveness and organizational justice, this study introduced variables such as environmental(E) activities, social(S) activities, and governance(G) activities, which th national government uses as major management evaluation indicators. Therefore, a literature study and empirical analysis were conducted on how self-efficacy affects job satisfaction when workers are faced with a changed work environment. To conduct this study, 300 copies of data were collected from workers in small and medium-sized enterprises and used for analysis. For data analysis, the SPSS statistical program (Ver. 25.0) was used. The study finds, first, that product or service quality and employee competency among corporate competitiveness had a significant positive(+) effect on job satisfaction. Secondly, among ESG management activities, social(S) activities and governance(G) activities were found to have a significant positive(+) effect on job satisfaction. Third, among organizational justice, distribution justice and procedural justice were found to have a positive(+) effect on job satisfaction. Fourth, self-efficacy was found to mediate the effect of product or service quality, employee competency, social(S) and governance(G) activities among ESG management activities, and procedural justice among organizational justice on job satisfaction. The academic value of this study is that it empirically analyzed the factors that ESG management activities affect workers' jobs,. As a result, it was confirmed that workers were satisfied with their jobs by actively showing interest in social(S) activities and governance(G) activities among ESG management activities and participating in corporate management. In addition, workers sensitive to changes in the external environment can become satisfied with their jobs through self-efficacy when SMEs actively enhance corporate competitiveness, execute ESG management activities, and provide a fair organizational culture. Finally, this study suggests that there's a possibility of improving the competitiveness of SMEs through a virtuous cycle created by a change in perception of job conversion and a decrease in turnover.

• Therapeutic Science for Rehabilitation
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• v.13 no.1
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• pp.9-21
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• 2024

Objective : The purpose of this study was to confirm the characteristics and quality of a single-subject research that conducted interventions to improve activities of daily living (ADL) in stroke patients. Methods : 'Stroke,' 'activities of daily living,' and 'single-subject studies' were searched as keywords among papers published in the last 15 years between 2009 and 2023 among Research Information Sharing Service, DBpia, and e-articles. A total of nine papers were examined for the characteristics and quality before analysis. Results : The independent variables applied to improve ADL included constraint-induced therapy, mental practice for performing functional activities, virtual reality-based task training, subjective postural vertical training without visual feedback, bilateral upper limb movement, core stability training program, traditional occupational therapy and neurocognitive rehabilitation, smooth pursuit eye movement, neck muscle vibration, and occupation-based community rehabilitation. Assessment of Motor and Process Skills was the most common evaluation tool for measuring dependent variables, with four articles, and Modified Barthel Index and Canadian Occupational Performance Measure were two articles each. As a result of confirming the qualitative level of the analyzed papers, out of a total of nine studies, seven studies were at a high level, two at a moderate level, and none were at a low level. Conclusion : Various types of rehabilitation treatments have been actively applied as intervention methods to improve the daily life activities of stroke patients; the quality level of single-subject studies applying ADL interventions was reliable.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Information Systems Review
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• v.14 no.1
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• pp.85-103
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• 2012

ISMP is a method of writing clearly the user requirements in the RFP(Request for Proposal) of the IS development projects. Unlike the conventional methods of RFP preparation that describe the user requirements of target systems in a rather superficial manner, ISMP systematically identifies the businesses needs and the status of information technology, analyzes in detail the user requirements, and defines in detail the specific functions of the target systems. By increasing the clarity of RFP, the scale and complexity of related businesses can be calculated accurately, many responding companies can prepare proposals clearly, and the level of fairness during the evaluation of many proposals can be improved, as well. Above all though, the problems that are posed as chronic challenges in this field, i.e., the misunderstanding and conflicts between the users and developers, excessive burden on developers, etc. can be resolved. This study is a case study that analyzes the execution process, execution accomplishment, problems, and the success factors of two pilot projects that introduced ISMP for the first time. ISMP performance procedures of actual site were verified, and how the user needs in the request for quote are described was examined. The satisfaction levels of ISMP RFP for quote were found to be high as compared to the conventional RFP. Although occurred were some problems such as RFP preparation difficulties, increased workload, etc. due to the lack of understanding and execution experience of ISMP, in overall, also occurred were some positive effects such as the establishment of the scope of target systems, improved information sharing and cooperation between the users and the developers, seamless communication between issuing customer corporations and IT service companies, reduction of changes in user requirements, etc. As a result of conducting action research type in-depth interviews on the persons in charge of actual work, factors were derived as ISMP success factors: prior consensus on the need for ISMP, the acquisition of execution resources resulting from the support of CEO and CIO, and the selection of specification level of the user requirements. The results of this study will provide useful site information to the corporations that are considering adopting ISMP and IT service firms, and present meaningful suggestions on the future study directions to researchers in the field of IT service competitive advantages.

• Journal of Preventive Medicine and Public Health
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• v.11 no.1
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• pp.123-127
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• 1978

The major objective of this research is to identify those hospital characteristics that best explain cost variation among hospitals and to formulate linear models that can predict hospital costs. Specific emphasis is placed on hospital output, that is, the identification of diagnosis related patient groups (DRGs) which are medically meaningful and demonstrate similar patterns of hospital resource consumption. A casemix index is developed based on the DRGs identified. Considering the common problems encountered in previous hospital cost research, the following study requirements are estab-lished for fulfilling the objectives of this research: 1. Selection of hospitals that exercise similar medical and fiscal practices. 2. Identification of an appropriate data collection mechanism in which demographic and medical characteristics of individual patients as well as accurate and comparable cost information can be derived. 3. Development of a patient classification system in which all the patients treated in hospitals are able to be split into mutually exclusive categories with consistent and stable patterns of resource consumption. 4. Development of a cost finding mechanism through which patient groups' costs can be made comparable across hospitals. A data set of Medicare patients prepared by the Social Security Administration was selected for the study analysis. The data set contained 27,229 record abstracts of Medicare patients discharged from all but one short-term general hospital in Connecticut during the period from January 1, 1971, to December 31, 1972. Each record abstract contained demographic and diagnostic information, as well as charges for specific medical services received. The 'AUT-OGRP System' was used to generate 198 DRGs in which the entire range of Medicare patients were split into mutually exclusive categories, each of which shows a consistent and stable pattern of resource consumption. The 'Departmental Method' was used to generate cost information for the groups of Medicare patients that would be comparable across hospitals. To fulfill the study objectives, an extensive analysis was conducted in the following areas: 1. Analysis of DRGs: in which the level of resource use of each DRG was determined, the length of stay or death rate of each DRG in relation to resource use was characterized, and underlying patterns of the relationships among DRG costs were explained. 2. Exploration of resource use profiles of hospitals; in which the magnitude of differences in the resource uses or death rates incurred in the treatment of Medicare patients among the study hospitals was explored. 3. Casemix analysis; in which four types of casemix-related indices were generated, and the significance of these indices in the explanation of hospital costs was examined. 4. Formulation of linear models to predict hospital costs of Medicare patients; in which nine independent variables (i. e., casemix index, hospital size, complexity of service, teaching activity, location, casemix-adjusted death. rate index, occupancy rate, and casemix-adjusted length of stay index) were used for determining factors in hospital costs. Results from the study analysis indicated that: 1. The system of 198 DRGs for Medicare patient classification was demonstrated not only as a strong tool for determining the pattern of hospital resource utilization of Medicare patients, but also for categorizing patients by their severity of illness. 2. The wei틴fed mean total case cost (TOTC) of the study hospitals for Medicare patients during the study years was $11,27.02 with a standard deviation of $117.20. The hospital with the highest average TOTC ($1538.15) was 2.08 times more expensive than the hospital with the lowest average TOTC ($743.45). The weighted mean per diem total cost (DTOC) of the study hospitals for Medicare patients during the sutdy years was $107.98 with a standard deviation of $15.18. The hospital with the highest average DTOC ($147.23) was 1.87 times more expensive than the hospital with the lowest average DTOC ($78.49). 3. The linear models for each of the six types of hospital costs were formulated using the casemix index and the eight other hospital variables as the determinants. These models explained variance to the extent of 68.7 percent of total case cost (TOTC), 63.5 percent of room and board cost (RMC), 66.2 percent of total ancillary service cost (TANC), 66.3 percent of per diem total cost (DTOC), 56.9 percent of per diem room and board cost (DRMC), and 65.5 percent of per diem ancillary service cost (DTANC). The casemix index alone explained approximately one half of interhospital cost variation: 59.1 percent for TOTC and 44.3 percent for DTOC. Thsee results demonstrate that the casemix index is the most importand determinant of interhospital cost variation Future research and policy implications in regard to the results of this study is envisioned in the following three areas: 1. Utilization of casemix related indices in the Medicare data systems. 2. Refinement of data for hospital cost evaluation. 3. Development of a system for reimbursement and cost control in hospitals.

• Korean Journal of Health Education and Promotion
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• v.24 no.5
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• pp.23-37
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• 2007

Background: Even though cervical cancer poses a significant global cancer burden, successful implementations for early detection offer an opportunity to prevent deaths and reduce the cancer burden. In Korea, cervical cancer is the most prevalent type of cancer among adult women, but it is one of the few cancers in which a consensus-approved screening test exists for early diagnosis, Pap test, that can be combined with highly efficacious treatment regimens for early-stage disease. Purpose: This study was carried out to identify the cognitive-behavioral factors associated with cervical cancer screening behavior among adult women, aged 40 to 59, and to develop tailored messages and to evaluate the effectiveness of stage-matched educational program. Method: A total of 283 women who aged 40 years or older was recruited in Seoul, from September, 1st to November, 14th, 2003. The intervention group (N=162) and the control group (N=121) were selected from five sub-districts in Seocho-gu, Seoul. Building on the TTM, a quasi-experimental study was conducted to test the effectiveness of stages-matched intervention addressed at the five stages of cervical cancer screening behavior. Women in the intervention group were randomly assigned to one of two conditions, internet or postal services. Results: In our results, 88.9% of participants had received a Pap test at least once in their life-time, and 65.4% had got it in the past two years. With regard to cognitive-behavioral factors, the stages-matched educational program increased attitude and process of change for cervical cancer screening. The percentage changed was the largest in maintenance stage. With regard to delivery methods for tailored messages, the print materials were more effective at increasing screening adherence than the e-mail. Whereas the postal service group showed remarkable the change of behavior stage, the internet service group did not. Also it was not shown any difference of the satisfaction with stages-matched educational program between internet and postal service groups. Conclusion: This study suggested that cervical cancer screening behavior could be changed by tailored messages which had developed with cognitive-behavioral factors. The stages-matched educational program was effective to promote the screening adherence for cervical cancer.

• Journal of the Korean Society of Food Culture
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• v.6 no.2
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• pp.175-184
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• 1991

To identify the eating behaviour of customers at a hotel buffet styled restaurant, a survey was conducted. The age range of the respondents was 6 through 70, but consisted mainly people in their twenties, thirties, and forties of the respondents, 65.1% were female. The occupation ranged from student 30.3%, housewife 27.2%, office worker 19.3%, professional 17.3%. 43.9% of respondents visited buffet styled restaurant 1 to 2 times every three or four months. Some respondents had a positive opinions: they had many choices in food selection, they could take and choose as much as they wanted, the appearance and the arrangement of the food was great, etc. But some also had negative attitudes(i.e. unhappy with self service and expensive prices). Of the respondents, 31.1% said they visited the buffet styled restaurant was for family parties and the average number of the party member was $9.3{\pm}4.3$. The average time period of eating was 1 hour $32{\pm}26$ minutes. The average frequency of taking food was $3.7{\pm}1.2$. The average frequency of taking food after satiety was $1.2{\pm}0.8$. The first selection of the buffet service food was soup 23.9% of the respondents and salad 23.9%. Females chose more of the soups and salads the males chose more of the meats and seafoods. The standard of food selection was 70.7% of 'my favorite'. This tells customers' low cognition level of desirable food selection and the order of a meal. 64.0% of the respondents responded overeating, from mild and extreme. We think that information on nutrition education and health problems are necessary. For better service, 82.9% wanted to lower the price by decreasing similar items. Respondent wanted; one, to increase more Korean food items and make a traditional Korean buffet styled restaurant, two, to use more seasonal food and decrease the redundant food items to reduce the price, and three, to have different price rates according to the age or gender of the grown ups.

• Journal of Service Research and Studies
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• v.5 no.1
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• pp.91-103
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• 2015

We examine the information transmission between the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index, based on the returns data offered by the Korea Exchange. The data includes daily return data from 1 January 2012 to 31 December 2014. Utilizing a dynamic analytical tool-the VAR model, Granger Causality test, Impulse Response Function and Variance Decomposition have been implemented. The results of the analysis are as follows. Firstly, results of Granger Causality test suggests the existence of mutual causality the KT Futures Index and the SK Telecom Futures Index precede and have explanatory power the KT Spot and the SK Telecom Spot However the results also identified a greater causality and explanatory power of the KT Spot and the SK Telecom Spot over the KT Futures Index and the SK Telecom Futures Index. Secondly, the results of impulse response function suggest that the KT Futures Index show immediate response to the KT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Also the SKT Futures Index show immediate response to the SKT Spot and are influenced by till time 4. From time 2, the impact gradually disappears. Lastly, the variance decomposition analysis shows that the changes of return of the KT Spot and SKT Spot are dependent on those of the KT Futures Index and the SK Telecom Futures Index. This implies that returns on the KT Spot and SKT Spot have a significant influence over returns on the KT Futures Index and the SK Telecom Futures Index. It contributes to the understanding of market price formation function through analysis of detached the KT Spot and the KT Futures Index, the SK Telecom Spot and the SK Telecom Futures Index.

• Journal of the East Asian Society of Dietary Life
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• v.27 no.4
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• pp.473-476
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• 2017

Social network service (SNS) plays an important role in food service industry consumers SNS restaurants, and other consumers review the reputations. It was assumed that bad reputation could have poor food hygiene. Therefore, this study evaluated the relation between reputations SNS and food hygiene. Restaurants were searched using web portals and 12 restaurants (six for good and six for bad reputation) were selected. Microbiological analysis (total aerobic bacteria, coliform, and Escherichia coli) for main and side dish was performed. Detection frequencies for total aerobic bacteria were not different between good and bad restaurants. However, bad restaurants had higher detection frequencies (70.8%) with mean of 3.2 log CFU/g for coliform than good restaurants (62.5%; mean of 2.3 log CFU/g). In addition, bad restaurants had higher detection frequencies (25%) of E. coli with mean of 0.8 log CFU/g than good restaurants (8.3%; mean of 0.5 log CFU/g). This result indicates that consumer reputations SNS are related to food hygiene, and the reputation data can be used for food hygiene inspection by food safety agencies.