• Journal of Christian Education in Korea
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• v.72
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• pp.245-271
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• 2022

The purpose of this study is to develop a nursing clinical practice education model that applies case-based learning and co-teaching to nursing students, and to secure the validity of the developed model. To verify the validity of the nursing clinical practice education model, it was applied to the subject of 'Health Response and Nursing VI (Perception/ Cognition) Practice' in the 2nd semester of 2021 at J University in Jeonju, and the instructor's response to the model was evaluated. Surveys and focus group interviews were conducted on confidence in clinical practice and teaching and learning models. After deriving the case-based learning stage and co-teaching elements through a review of precedent literature and case studies, an initial model was devised after expert review, and the devised model was reviewed for internal validity by nursing education experts, and then modified and supplemented. As a result of the learner response evaluation conducted after applying the model to the clinical practice subject for external validation verification, the confidence in clinical performance was 4.22 points and the satisfaction with the teaching-learning model was 4.68 points. Summarizing the results of the focus group interview, the importance of prior learning and the learning of selected cases based on actual cases, learning terminology and professional knowledge, eliminated fear of the practice field, felt familiar, and learned various cases. He said that he was able to think critically through the time to organize the knowledge learned in the practice field. In addition, through co-teaching, it was found that field leaders and advisors taught the theoretical and practical aspects at the same time through examples, thereby experiencing practical education closer to practice. It is expected that the nursing clinical practice education model developed through this study, applying case-based learning and co-teaching, will be an effective teaching and learning model that can reduce the gap between theory and practice and improve the clinical performance of nursing students.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.233-246
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• 2023

In terms of understanding the water cycle and efficient water resource management, the importance of soil moisture has been highlighted. However, in Korea, the lack of qualified in-situ soil moisture data results in very limited utility. Even if satellite-based data are applied, the absence of ground reference data makes objective evaluation and correction difficult. The cosmic-ray neutron probe (CRNP) can play a key role in producing data for satellite data calibration. The installation of CRNP is non-invasive, minimizing damage to the soil and vegetation environment, and has the advantage of having a spatial representative for the intermediate scale. These characteristics are advantageous to establish an observation network in Korea which has lots of mountainous areas with dense vegetation. Therefore, this study was conducted to evaluate the applicability of the CRNP soil moisture observatory in Korea as part of the establishment of a Korean cOsmic-ray Soil Moisture Observing System (KOSMOS). The CRNP observation station was installed with the Gunup-ri observation station, considering the ease of securing power and installation sites and the efficient use of other hydro-meteorological factors. In order to evaluate the CRNP soil moisture data, 12 additional in-situ soil moisture sensors were installed, and spatial representativeness was evaluated through a temporal stability analysis. The neutrons generated by CRNP were found to be about 1,087 counts per hour on average, which was lower than that of the Solmacheon observation station, indicating that the Hongcheon observation station has a more humid environment. Soil moisture was estimated through neutron correction and early-stage calibration of the observed neutron data. The CRNP soil moisture data showed a high correlation with r=0.82 and high accuracy with root mean square error=0.02 m³/m³ in validation with in-situ data, even in a short calibration period. It is expected that higher quality soil moisture data production with greater accuracy will be possible after recalibration with the accumulation of annual data reflecting seasonal patterns. These results, together with previous studies that verified the excellence of CRNP soil moisture data, suggest that high-quality soil moisture data can be produced when constructing KOSMOS.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.97-113
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• 2023

In order to generalize the social entrepreneurship model with cooperation orientation and increase the possibility of using the model, this study developed a measurement tool and tested it with 389 executives of social enterprises. For the development of the measurement tool, preliminary measurement items were formed through review of previous studies, and a questionnaire was tentatively composed of 40 measurement items in five areas through an expert panel review of the measurement items. A total of 389 questionnaires were collected by conducting a questionnaire survey targeting Korean social enterprise managers, and exploratory and confirmatory factor analysis were conducted using 375 questionnaires that could be analyzed. Five factors for 24 items were derived through exploratory factor analysis and reliability analysis. Through a series of analysis processes including primary and secondary confirmatory factor analysis, the model fit of the newly constructed social entrepreneurship research model was confirmed, and the validity and reliability of the measurement tools were verified. As a result of this study, the model fit of the social entrepreneurship model(social value orientation; innovativeness; pro-activeness; risk-taking; cooperation orientation) is verified, thereby improving the theoretical explanatory power of social entrepreneurship research and at the same time providing the basis and basis for theoretical expansion of follow-up research. The study proved the possibility of generalizing the social entrepreneurship model with added cooperation orientation, and at the same time, the measurement tool used in this study was widely used as a tool to measure social entrepreneurship theoretically and practically. In addition, it was confirmed that the cooperation orientation is manifested in corporate decision-making and activity behaviors for resource mobilization and capacity building, opportunity and performance creation, social capital and network reinforcement, and governance establishment of social enterprises.

• Journal of the Korean earth science society
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• v.45 no.2
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• pp.157-171
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• 2024

The purposes of this study were: (1) to revalidate the revised Systems Thinking Measuring Instrument (Re_STMI) reported by Lee et al. (2024) among Vietnamese high school students and (2) to investigate the differences in systems thinking abilities between Korean and Vietnamese high school students. To achieve this, data from 234 Vietnamese high school students who responded to translated Re_STMI consisting of 20 items and an Scale consisting of 20 items were used. Validity analysis was conducted through item response analysis (Item Reliability, Item Map, Infit and Outfit MNSQ, DIF between male and female) and exploratory factor analysis (principal axis factor analysis using Promax). Furthermore, structural equation modeling was employed with data from 475 Korean high school students to verify the latent mean analysis. The results were as follows: First, in the item response analysis of the 20 translated Re_STMI items in Vietnamese, the Item Reliability was .97, and the Infit MNSQ ranged from .67 to 1.38. The results from the Item Map and DIF analysis align with previous findings. In the exploratory factor analysis, all items were loaded onto intended sub-factors, with sub-factor reliabilities ranging from .662 to .833 and total reliability at .876. Confirmatory factor analysis for latent mean analysis between Korean and Vietnamese students yielded acceptable model fit indices (χ²/df: 2.830, CFI: .931, TLI: .918, SRMR: .043, RMSEA: .051). Lastly, the latent mean analysis between Korean and Vietnamese students revealed a small effect size in systems analysis, mental models, team learning, and shared vision factors, whereas a medium effect size was observed in personal mastery factors, with Vietnamese high school students showing significantly higher results in systems thinking. This study confirmed the reliability and validity of the Re_STMI items. Furthermore, international comparative studies on systems thinking using Re_STMI translated into Vietnamese, English, and other languages are warranted in the context of students' systems thinking analysis.

• Journal of Korean Dental Hygiene Science
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• v.6 no.2
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• pp.79-89
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• 2023

Background and Objectives: The prevalence of dementia is steadily increasing each year, and preceding studies continue to explore the association between dementia and oral health. Dental hygienists require specialized competencies to provide appropriate dental healthcare services, necessitating the development of a tool for the objective measurement of their knowledge levels. This study aimed to develop a knowledge assessment tool for dental hygienists concerning considerations for dental care for patients with dementia. Methods: The study constructed preliminary items based on a literature review and then conducted expert validation, a pilot survey, and the main survey. The main survey was conducted among 220 dental hygienists. Validity and reliability analyses were conducted with the collected data to select the final items, and the correctness rates for each selected item were verified. Results: As a result of the analysis of the collected data, 18 items were eliminated out of a total of 40 preliminary items, leaving a total of 6 factors and 22 items. The Cronbach's α value for the selected items was 0.791. The six factors are as follows: 'Considerations during dental treatment for dementia patients' (5 items), 'medication side effects in dementia patients' (4 items), 'oral care methods for dementia patients' (4 items), 'communication with dementia patients' (4 items), 'psychological reactions of dementia patients' (3 items), and 'guidance for dementia patients' (2 items). The item with the highest correctness rate was item 2 of the 'guidance for dementia patients' category at 98.6%, while the item with the lowest correctness rate was item 2 of the 'psychological reactions of dementia patients' category at 5.9%. Conclusion: This study validated the reliability and validity of the knowledge assessment tool, which lays the foundation for future research on dental hygienists and dementia. It contributes essential data for ongoing education, development of educational programs, and establishing operational guidelines in healthcare institutions.

• 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.

• Journal of Distribution Research
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• v.17 no.1
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• pp.37-63
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• 2012

In franchise business, exclusive sales territory (sometimes EST in table) protection is a very important issue from an economic, social and political point of view. It affects the growth and survival of both franchisor and franchisee and often raises issues of social and political conflicts. When franchisee is not familiar with related laws and regulations, franchisor has high chance to utilize it. Exclusive sales territory protection by the manufacturer and distributors (wholesalers or retailers) means sales area restriction by which only certain distributors have right to sell products or services. The distributor, who has been granted exclusive sales territories, can protect its own territory, whereas he may be prohibited from entering in other regions. Even though exclusive sales territory is a quite critical problem in franchise business, there is not much rigorous research about the reason, results, evaluation, and future direction based on empirical data. This paper tries to address this problem not only from logical and nomological validity, but from empirical validation. While we purse an empirical analysis, we take into account the difficulties of real data collection and statistical analysis techniques. We use a set of disclosure document data collected by Korea Fair Trade Commission, instead of conventional survey method which is usually criticized for its measurement error. Existing theories about exclusive sales territory can be summarized into two groups as shown in the table below. The first one is about the effectiveness of exclusive sales territory from both franchisor and franchisee point of view. In fact, output of exclusive sales territory can be positive for franchisors but negative for franchisees. Also, it can be positive in terms of sales but negative in terms of profit. Therefore, variables and viewpoints should be set properly. The other one is about the motive or reason why exclusive sales territory is protected. The reasons can be classified into four groups - industry characteristics, franchise systems characteristics, capability to maintain exclusive sales territory, and strategic decision. Within four groups of reasons, there are more specific variables and theories as below. Based on these theories, we develop nine hypotheses which are briefly shown in the last table below with the results. In order to validate the hypothesis, data is collected from government (FTC) homepage which is open source. The sample consists of 1,896 franchisors and it contains about three year operation data, from 2006 to 2008. Within the samples, 627 have exclusive sales territory protection policy and the one with exclusive sales territory policy is not evenly distributed over 19 representative industries. Additional data are also collected from another government agency homepage, like Statistics Korea. Also, we combine data from various secondary sources to create meaningful variables as shown in the table below. All variables are dichotomized by mean or median split if they are not inherently dichotomized by its definition, since each hypothesis is composed by multiple variables and there is no solid statistical technique to incorporate all these conditions to test the hypotheses. This paper uses a simple chi-square test because hypotheses and theories are built upon quite specific conditions such as industry type, economic condition, company history and various strategic purposes. It is almost impossible to find all those samples to satisfy them and it can't be manipulated in experimental settings. However, more advanced statistical techniques are very good on clean data without exogenous variables, but not good with real complex data. The chi-square test is applied in a way that samples are grouped into four with two criteria, whether they use exclusive sales territory protection or not, and whether they satisfy conditions of each hypothesis. So the proportion of sample franchisors which satisfy conditions and protect exclusive sales territory, does significantly exceed the proportion of samples that satisfy condition and do not protect. In fact, chi-square test is equivalent with the Poisson regression which allows more flexible application. As results, only three hypotheses are accepted. When attitude toward the risk is high so loyalty fee is determined according to sales performance, EST protection makes poor results as expected. And when franchisor protects EST in order to recruit franchisee easily, EST protection makes better results. Also, when EST protection is to improve the efficiency of franchise system as a whole, it shows better performances. High efficiency is achieved as EST prohibits the free riding of franchisee who exploits other's marketing efforts, and it encourages proper investments and distributes franchisee into multiple regions evenly. Other hypotheses are not supported in the results of significance testing. Exclusive sales territory should be protected from proper motives and administered for mutual benefits. Legal restrictions driven by the government agency like FTC could be misused and cause mis-understandings. So there need more careful monitoring on real practices and more rigorous studies by both academicians and practitioners.

• Journal of Global Scholars of Marketing Science
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• v.17 no.2
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• pp.31-54
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• 2007

The exchange between buyers and sellers in the industrial market is changing from short-term to long-term relationships. Long-term relationships are governed mainly by formal contracts or informal agreements, but many scholars are now asserting that controlling relationship by using formal contracts under environmental dynamism is inappropriate. In this case, partners will depend on each other's flexibility or interdependence. The former, flexibility, provides a general frame of reference, order, and standards against which to guide and assess appropriate behavior in dynamic and ambiguous situations, thus motivating the value-oriented performance goals shared between partners. It is based on social sacrifices, which can potentially minimize any opportunistic behaviors. The later, interdependence, means that each firm possesses a high level of dependence in an dynamic channel relationship. When interdependence is high in magnitude and symmetric, each firm enjoys a high level of power and the bonds between the firms should be reasonably strong. Strong shared power is likely to promote commitment because of the common interests, attention, and support found in such channel relationships. This study deals with environmental dynamism in high-tech industry. Firms in the high-tech industry regard it as a key success factor to successfully cope with environmental changes. However, due to the lack of studies dealing with environmental dynamism and supply chain commitment in the high-tech industry, it is very difficult to find effective strategies to cope with them. This paper presents the results of an empirical study on the relationship between environmental dynamism and supply chain commitment in the high-tech industry. We examined the effects of consumer, competitor, and technological dynamism on supply chain commitment. Additionally, we examined the moderating effects of flexibility and dependence of supply chains. This study was confined to the type of high-tech industry which has the characteristics of rapid technology change and short product lifecycle. Flexibility among the firms of this industry, having the characteristic of hard and fast growth, is more important here than among any other industry. Thus, a variety of environmental dynamism can affect a supply chain relationship. The industries targeted industries were electronic parts, metal product, computer, electric machine, automobile, and medical precision manufacturing industries. Data was collected as follows. During the survey, the researchers managed to obtain the list of parts suppliers of 2 companies, N and L, with an international competitiveness in the mobile phone manufacturing industry; and of the suppliers in a business relationship with S company, a semiconductor manufacturing company. They were asked to respond to the survey via telephone and e-mail. During the two month period of February-April 2006, we were able to collect data from 44 companies. The respondents were restricted to direct dealing authorities and subcontractor company (the supplier) staff with at least three months of dealing experience with a manufacture (an industrial material buyer). The measurement validation procedures included scale reliability; discriminant and convergent validity were used to validate measures. Also, the reliability measurements traditionally employed, such as the Cronbach's alpha, were used. All the reliabilities were greater than.70. A series of exploratory factor analyses was conducted. We conducted confirmatory factor analyses to assess the validity of our measurements. A series of chi-square difference tests were conducted so that the discriminant validity could be ensured. For each pair, we estimated two models-an unconstrained model and a constrained model-and compared the two model fits. All these tests supported discriminant validity. Also, all items loaded significantly on their respective constructs, providing support for convergent validity. We then examined composite reliability and average variance extracted (AVE). The composite reliability of each construct was greater than.70. The AVE of each construct was greater than.50. According to the multiple regression analysis, customer dynamism had a negative effect and competitor dynamism had a positive effect on a supplier's commitment. In addition, flexibility and dependence had significant moderating effects on customer and competitor dynamism. On the other hand, all hypotheses about technological dynamism had no significant effects on commitment. In other words, technological dynamism had no direct effect on supplier's commitment and was not moderated by the flexibility and dependence of the supply chain. This study makes its contribution in the point of view that this is a rare study on environmental dynamism and supply chain commitment in the field of high-tech industry. Especially, this study verified the effects of three sectors of environmental dynamism on supplier's commitment. Also, it empirically tested how the effects were moderated by flexibility and dependence. The results showed that flexibility and interdependence had a role to strengthen supplier's commitment under environmental dynamism in high-tech industry. Thus relationship managers in high-tech industry should make supply chain relationship flexible and interdependent. The limitations of the study are as follows; First, about the research setting, the study was conducted with high-tech industry, in which the direction of the change in the power balance of supply chain dyads is usually determined by manufacturers. So we have a difficulty with generalization. We need to control the power structure between partners in a future study. Secondly, about flexibility, we treated it throughout the paper as positive, but it can also be negative, i.e. violating an agreement or moving, but in the wrong direction, etc. Therefore we need to investigate the multi-dimensionality of flexibility in future research.

• 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 Food Hygiene and Safety
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• v.34 no.1
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• pp.22-29
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• 2019

Validamycin A is an aminoglycoside fungicide produced by Streptomyces hygroscopicus that inhibits trehalase. The purpose of this study was to develop a method for detecting validamycin A in agricultural samples to establish MRL values for use in Korea. The validamycin A residues in samples were extracted using methanol/water (50/50, v/v) and purified with a hydrophilic-lipophilic balance (HLB) cartridges. The analyte was quantified and confirmed by liquid chromatograph-tandem mass spectrometer (LC-MS/MS) in positive ion mode using multiple reaction monitoring (MRM). Matrix-matched calibration curves were linear over the calibration ranges (0.005~0.5 ng) into a blank extract with $R^2$ > 0.99. The limits of detection and quantification were 0.005 and 0.01 mg/kg, respectively. For validation validamycin A, recovery studies were carried out three different concentration levels (LOQ, $LOQ{\times}10$, $LOQ{\times}50$, n = 5) with five replicates at each level. The average recovery range was from 72.5~118.3%, with relative standard deviation (RSD) less than 10.3%. All values were consistent with the criteria ranges requested in the Codex guidelines (CAC/GL 40-1993, 2003) and the NIFDS (National Institute of Food and Drug Safety) guideline (2016). Therefore, the proposed analytical method is accurate, effective and sensitive for validamycin A determination in agricultural commodities.