• Journal of Oriental Neuropsychiatry
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• v.16 no.1
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• pp.1-17
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• 2005

Objective : This empirical research is performed to recognize diagnostic concept, pattern identification, and clinical features of Hwa-byung. In other words, the aims of this research are to examine the differences of the diagnosis between Hwa-Byung and the other psychiatric disorders, and to find out pattern identification, and clinical characteristics of Hwa-Byung for prescriptions of this syndrome. Method : In the experiment, there were participated 30 patients who were met for our criterions according to HBDIS (Hwa-Byung Diagnostic interview Schedule). These patients were diagnosed as Axis1 according to criterions of DSM-IV with administering SCID-I. OMS-prime was utilized for finding out pattern identification of oriental medicine. Symptom Check List-90-Revision(SCL-90-R), Hemilton rating Scale for Depression(HRSD), Heart Rate Variability(HRV), and Digital Infrared Thermographic imaging(D.I.T.I.) were also utilized to discover clinical characteristics of Hwa-Byung Patients. Results : 1. Regarding Sex-ratio, male subjects were 3(10%), and female subjects are 27(90%). The age of subjects ranged from 22 year old to 75 $(51.87{\pm}11.04;\:Mean{\pm}SD)$ 2. In the results of diagnosis on the basis of DSM-IV, the 17(56.67%) patients were MOD (Major Depressive Disorder), the 5(16.67%) patients were USD (Undifferentiated Somatoform Disorder), the 4(13.33%) patients were Dysthymic Disorder, the 3(10%) patients were GAD (Generalized Anxiety Disorder), and the 1(3.33%) was Panic Disorder. Two of the patients who diagnosed as MOD were diagnosed as Panic Disorder too, and one of them was diagnosed as Pain Disorder too. 3. Regarding pattern identification, Hwa-Byung is positively correlated to deficiency of Heart(心). and then to stagnancy of Liver-Gall bladder. Hwa-Byung is correlated deficiency symptom-complex rather than excessiveness symptom-complex. That is also correlated positively to Pathological heat and fire. 4. In SCL90-R, the mean of PSDI was $(75.3{\pm}10.7;\:Mean{\pm}SD)$. The each mean of the other 11 factors was distributed between50-70. 5. The mean of HRSD was $(17.9{\pm}5.6;\:Mean{\pm}SD)$ in the entire subject's group. Then the group of MDD was $20.9{\pm}4.4$ and the group of USD was $12.0{\pm}4.8$ 6. In the results of HRV. the mean of TP is $972.4{\pm}1174(Mean{\pm}SD)$, this is lower than normal range 1000-200. The other factors were within normal range. Then, there were no significant differences between them (p<0.05). 7. The temperatures of each acupoint have significant differences between HNl(印堂) and PC6(內關), between CV17(顫中) and PC6(內關), between HN1(印堂) and CV8(神闕), between CV17(顫中) and CV8(神闕) in comparison with the average of body temperature in the use of D.I.T.I. (p<0.01) 8. In the analysis of correlation between SCL-90-R, HRSD, HRV. and D.I.T.I. there were no significant results. According to results that the correlation was analyzed with only the MDD group as subjects, there was negative correlation between RMSSD of HRV and HRSD, between LF of HRV and PDSIof SCL-90-R, and between LF/HF of HRV and ANX, PSY, and PDSI of SCL-90-R. Conclusion : In the observation of clinical features of 30 cases of Hwa-Byung patients by using diverse structured tests, there could make diverse diagnosis as depressive disorder, anxiety disorder, and Somatoform Disorder. Particularly. MDD was highly distributed. Considering oriental medicine's pattern identification of Hwa-Byung, this syndrome is related strongly to Heart, and there were demonstrated deficiency symptom-complex, and Pathological heat and fire. One of the limits of this study is lack of control subject's group, therefore, in the future study, it requires reexamination through a comparative research with these data to complete this study.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.77-100
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• 2009

Information Systems (IS) is an essential tool for any organizations. The last decade has seen an increasing body of knowledge on IS usage. Yet, IS often fails because of its misuse or non-use. In general, decisions regarding the selection of a system, which involve the evaluation of many IS vendors and an enormous initial investment, are made not through the consensus of employees but through the top-down decision making by top managers. In situations where the selected system does not satisfy the needs of the employees, the forced use of the selected IS will only result in their resistance to it. Many organizations have been either integrating dispersed legacy systems such as archipelago or adopting a new ERP (Enterprise Resource Planning) system to enhance employee efficiency. This study examines user resistance prior to the adoption of the selected IS or ERP system. As such, this study identifies the importance of managing organizational resistance that may appear in the pre-adoption context of an integrated IS or ERP system, explores key factors influencing user resistance, and investigates how prior experience with other integrated IS or ERP systems may change the relationship between the affecting factors and user resistance. This study focuses on organizational members' resistance and the affecting factors in the pre-adoption context of an integrated IS or ERP system rather than in the context of an ERP adoption itself or ERP post-adoption. Based on prior literature, this study proposes a research model that considers six key variables, including perceived benefit, system complexity, fitness with existing tasks, attitude toward change, the psychological reactance trait, and perceived IT competence. They are considered as independent variables affecting user resistance toward an integrated IS or ERP system. This study also introduces the concept of prior experience (i.e., whether a user has prior experience with an integrated IS or ERP system) as a moderating variable to examine the impact of perceived benefit and attitude toward change in user resistance. As such, we propose eight hypotheses with respect to the model. For the empirical validation of the hypotheses, we developed relevant instruments for each research variable based on prior literature and surveyed 95 professional researchers and the administrative staff of the Korea Photonics Technology Institute (KOPTI). We examined the organizational characteristics of KOPTI, the reasons behind their adoption of an ERP system, process changes caused by the introduction of the system, and employees' resistance/attitude toward the system at the time of the introduction. The results of the multiple regression analysis suggest that, among the six variables, perceived benefit, complexity, attitude toward change, and the psychological reactance trait significantly influence user resistance. These results further suggest that top management should manage the psychological states of their employees in order to minimize their resistance to the forced IS, even in the new system pre-adoption context. In addition, the moderating variable-prior experience was found to change the strength of the relationship between attitude toward change and system resistance. That is, the effect of attitude toward change in user resistance was significantly stronger in those with prior experience than those with no prior experience. This result implies that those with prior experience should be identified and provided with some type of attitude training or change management programs to minimize their resistance to the adoption of a system. This study contributes to the IS field by providing practical implications for IS practitioners. This study identifies system resistance stimuli of users, focusing on the pre-adoption context in a forced ERP system environment. We have empirically validated the proposed research model by examining several significant factors affecting user resistance against the adoption of an ERP system. In particular, we find a clear and significant role of the moderating variable, prior ERP usage experience, in the relationship between the affecting factors and user resistance. The results of the study suggest the importance of appropriately managing the factors that affect user resistance in organizations that plan to introduce a new ERP system or integrate legacy systems. Moreover, this study offers to practitioners several specific strategies (in particular, the categorization of users by their prior usage experience) for alleviating the resistant behaviors of users in the process of the ERP adoption before a system becomes available to them. Despite the valuable contributions of this study, there are also some limitations which will be discussed in this paper to make the study more complete and consistent.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.239-250
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• 2020

The purpose of this paper is to explore the influence of the "contextualization" effect of web celebrity live broadcast on the e-commerce platform on consumers' perception of product value, risk and purchase intention. Live in this paper, using Taobao shopping consumers as the research object, the survey method, questionnaire survey is adopted, the form through the questionnaire and distributed network, a live in order to further validation of web celebrity effect of contextualized actual influence on consumer purchase intention, questionnaire design the Likert scale, seven and recycling questionnaire analysis using the statistical software SPSS 23.0 and AMOS 22.0 after processing the data. After determining the reliability and validity of the questionnaire, the exploratory factor analysis was used to verify the hypothesis and calculate the actual adjustment degree of the "contextualization" effect of web celebrity live broadcasting on consumers' purchase intention. The research results of this paper are summarized as follows :(1) consumers' perceived value of products can significantly positively affect their purchase intention, while perceived risk has a significantly negative impact on their purchase intention; (2) consumers' trust and purchase intention to products are regulated by the "contextualization" of web celebrity live broadcast. Specifically, for web celebrity live broadcasting with good "contextualization" effect, the perceived value of consumer products has a positive impact on product trust, which is higher than that of web celebrity live broadcasting with poor "contextualization" effect. In terms of resolving consumers' perceived risks to products, web celebrity live broadcast with good "contextualization" effect is also significantly better than web celebrity live broadcast with poor "contextualization" effect. Based on empirical analysis, this paper concludes that web celebrity live broadcasting will become a new breakthrough for the sustainable growth of the e-commerce industry, and puts forward Suggestions on the e-commerce marketing mode and the transformation of web celebrity live broadcasting industry.

• Journal of Technology Innovation
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• v.29 no.3
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• pp.1-31
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• 2021

With the growing importance of technology innovation as a key factor for firms' competitive advantage, 'innovation persistence' became also an important research subject. 'Innovation Persistence' is a concept that indicates whether or not firms' innovation activity or performance continues. However, the data used for innovation studies are carried out as cross-sectional surveys in most countries. For this reason, studies dealing with longitudinal aspect of innovation persistence are rare. In particular, there is almost no research on innovation persistence using Korean innovation survey data. This study reviews the concepts and characteristics of innovation persistence based on extant literature, and perform an empirical analysis on the status and features of Korean firms' technology innovation persistence. Based on the data of the Korean Innovation Survey (KIS) conducted every other year from 2012 to 2018, panel data on 3,379 firms which observed multiple times are constructed. As a result, only part of the firms with persistent innovation were observed (for innovation performance 10~12%, for innovation activity 15~17%), and it was found that the persistence of non-innovation was remarkable(about 52~57%). And it was confirmed that the persistence of innovation activities is stronger than that of innovation performance. Besides, some features by sub-types of innovation appeared. Product innovation showed higher persistence than process innovation, and internal R&D also showed higher persistence than joint/external R&D. As a result of additional logit analysis to identify factors, it was found that radical or gradual product innovation is the most influential factor in persisting innovation in the next period. Since the sample selection bias due to a limitations of raw data might exist in the panel data constructed in this study, it should be noted that faulty generalization of the results are not allowed. Nevertheless, this is the first study to examine the technology innovation persistence targeting Korean firms and is expected to be a starting point for follow-up studies. It is anticipated that advanced research results will be drawn through the establishment of official panel data and improved methodologies.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.5
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• pp.109-124
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• 2021

This study tried to verify the causal relationship that SMEs' organizational culture and self-efficacy would affect job crafting and job satisfaction. Unlike previous domestic studies that have been studied for organizational culture at the organizational level and self-efficacy at the individual level, this study tried to verify the interaction between job crafting and job satisfaction using different mechanisms as antecedent factors. In order to verify the research model of this study, questionnaires of 144 small and medium-sized enterprises (SMEs) workers located in Seoul and metropolitan areas were analyzed. Factor analysis and correlation analysis were performed to verify the reliability and validity of the research model on the relationship between variables, and empirical analysis was performed using regression analysis and mediation effect analysis to verify the hypothesis. The results of the study were first, that organizational culture and self-efficacy had a positive (+) effect on job crafting. On the other hand, relationship-oriented culture and hierarchical-oriented culture, which are sub-factors of organizational culture, were found to be insignificant. Second, organizational culture and self-efficacy were found to have a positive (+) effect on job satisfaction. On the other hand, it was found that market-oriented culture and hierarchical-oriented culture, which are sub-factors of organizational culture, were not significant. Third, job crafting was found to have a positive (+) effect on job satisfaction. On the other hand, it was found that the sub-factors of job crafting, disruptive job demands and social job resources, were not significant. This means that organizational culture partially affects job crafting and job satisfaction of SMEs, and job crafting also partially affects job satisfaction. The implications of this study are first, suggesting the meaning of SME organizational culture for stable and efficient human resource management for SMEs suffering from low productivity and high turnover rate. Second, it was meaningful to understand the possibility of introducing job crafting as an effective job management plan for SMEs. Third, in the current situation where there are few cases of practical introduction of job crafting, research on understanding job crafting for SMEs and improving job satisfaction is thought to be helpful in improving the productivity of SMEs.

• Journal of the Korean earth science society
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• v.42 no.3
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• pp.247-263
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• 2021

Climate change has been accelerating in coastal waters recently; therefore, the importance of coastal environmental monitoring is also increasing. Chlorophyll-a concentration, an important marine variable, in the surface layer of the global ocean has been retrieved for decades through various ocean color satellites and utilized in various research fields. However, the commonly used chlorophyll-a concentration algorithm is only suitable for application in clear water and cannot be applied to turbid waters because significant errors are caused by differences in their distinct components and optical properties. In addition, designing a standard algorithm for coastal waters is difficult because of differences in various optical characteristics depending on the coastal area. To overcome this problem, various algorithms have been developed and used considering the components and the variations in the optical properties of coastal waters with high turbidity. Chlorophyll-a concentration retrieval algorithms can be categorized into empirical algorithms, semi-analytic algorithms, and machine learning algorithms. These algorithms mainly use the blue-green band ratio based on the reflective spectrum of sea water as the basic form. In constrast, algorithms developed for turbid water utilizes the green-red band ratio, the red-near-infrared band ratio, and the inherent optical properties to compensate for the effect of dissolved organisms and suspended sediments in coastal area. Reliable retrieval of satellite chlorophyll-a concentration from turbid waters is essential for monitoring the coastal environment and understanding changes in the marine ecosystem. Therefore, this study summarizes the pre-existing algorithms that have been utilized for monitoring turbid Case 2 water and presents the problems associated with the mornitoring and study of seas around the Korean Peninsula. We also summarize the prospective for future ocean color satellites, which can yield more accurate and diverse results regarding the ecological environment with the development of multi-spectral and hyperspectral sensors.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.6
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• pp.49-62
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• 2018

The purpose of this study is to develop an assessment index for the selection of promising start-ups, which will enhance the efficiency of program that support start-ups. In order to develop assessment models for selecting start-ups, three major research steps were conducted. First, this study attempted to theoretically redefine the assessment index from the perspective of the Balanced Scorecard (BSC) through a literature review. Second, major assessment index were derived using Delphi technique for experts in start-up areas. Third, weights were derived by applying AHP technique to calculate the importance of each index. The results of this study are summarized as follows. First, this study attempted to apply the assessment model for selecting start-ups from the Balanced Scorecard (BSC) view through the previous study review. Second, the final major questions were derived with sufficient opinions collected and structured survey of leading start-up experts in areas related to research subjects and elicited the most representative questions. Third, the results of applying the weights of the main selected assessment index, commercialization viewpoint is the most priority, followed by market view, technology development viewpoint, and organizational capability viewpoint. In the middle section, th ability to make products in the commercialization viewpoint, market competitiveness in the market, product discrimination capacity in the technology development perspective, and the ability of the entrepreneur in the organizational capacity perspective were important. Overall important items were found to be in the order of the capabilities of entrepreneurs, market competitiveness, product fire capability, and product discrimination. The importance of small items was highest priority for comparative excellence of competing products, and the degree of marketability, capacity of entrepreneurship, ability to raise capital, desire for entrepreneurship, and passion were shown. The results of this study presented a conceptual alternative to the preceding study on the development of existing selection assessment indexes. And it provides meaningful and important implications as an attempt to develop more sophisticated indicators by overcoming the limitations of empirical research on only some of the evaluation metrics.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.55-72
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• 2021

This study aims to research the influences of the discrimination of internet media and one-person media environment, especially, the one-person media creators leading the mobile media that could be accessed and viewed anywhere, on the user attitude and continuous subscription intention. Especially, this study aimed to understand the current situation of one-person media market represented as YouTube, to explore the relationship and ecology between each subject and elements composing the media market, and also to understand the mediating effects of the characteristics of YouTube creators on the relation between contents involvement and user attitude, and the relation between user attitude and subscription intention, and the mediating effects of contents involvement on the relation between characteristics of creators and user attitude. As research methods, first, for the theoretical establishment, this study collected, conducted, and organized the published domestic/foreign theses/journal papers. For the objective validity and verification of the established research model, a survey was conducted targeting adult men and women currently watching YouTube, and then the empirical analysis was performed through the final effective samples. And the results of this study are as follows. First, the playfulness and reliability on the relation between characteristics of creators and contents involvement were not significant while the professionalism was significant. Second, the professionalism on the relation between characteristics of creators and user attitude was not significant while the playfulness and reliability were significant. Third, the relation between contents involvement and user attitude was significant. Fourth, the relation between user attitude and subscription intention was also significant. Also, in the results of verifying the mediating effects of contents involvement, the contents involvement completely mediated the relation between characteristics(playfulness, reliability, and professionalism) of creators and user attitude. And in the conclusion, this study presented the implications and suggestions for further researches in the future.

• Journal of The Korean Association For Science Education
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• v.42 no.1
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• pp.61-75
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• 2022

Recently, lifelong learning ability was newly proposed as scientific literacy, the goal of the science curriculum. To solve various science-related problems students encounter in life, lifelong learning abilities related to science beyond school science education are required, but empirical evidence shows that students can solve problems they actually face through scientific literacy. It is not easy to find in the existing science education research. In addition, there is a lack of discussion on how to cultivate lifelong learning ability suggested in the curriculum through school science education. In this study, attention was paid to SSI education as a method for students to cultivate lifelong learning ability through school science education and to develop their ability to solve science-related problems encountered in life. In this context, statements in the existing SSI education studies were reviewed to discover discourses related to lifelong learning, and their types and characteristics were distinguished. It was possible to confirm lifelong learning and its applicability with focus on science education research through this. For the study, 18 literature materials on the subject of SSI education were selected, and the discourses related to lifelong learning in the SSI education research were discovered by examining the statements revealed in the data. As a result of the study, there are four categories of discourses related to lifelong learning: 'awareness of science,' 'connection between science and everyday life', 'promotion of participatory citizenship', and 'construction of identity'. Various SSI education studies have already had lifelong learning perception in various contexts, and the four types of discourses related to lifelong learning could be linked to the four types of learning presented in the UNESCO Lifelong Learning Report. SSI education tends to view students' life experiences as part of their learning and aims to help students develop the character and capacity to make responsible decisions on social issues related to science and put them into practice. This competency can be continuously connected to the real-life of students outside of school as a lifelong learning ability. This study requires expanding the discourse related to lifelong learning in science education and operating and managing the overall educational system to foster students' lifelong learning ability.