• Management & Information Systems Review
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• v.36 no.5
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• pp.1-26
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• 2017

In the meantime, research on corporate informatization focuses on the completeness of information technology itself and its financial effects, so there is insufficient research on whether information technology can support business strategy. It is necessary to verify whether the management strategy implementation of the company can be led through the informatization of the enterprise and the relation between the main mechanism factors and the informatization performance. In this study, what a mechanism factor is applied in the process of result creation of informatization from three mechanism perspectives such as selecting mechanism, learning mechanism and coordinating mechanism with cases of representative domestic IT company and what an importance mechanism factors have been ascertained. This study results in 8 propositions. For a main agent of companies, securement of information capability of organizations has been selected to realize informatization results and investment of informatization has been selected to solve organizational decentralization problems as the most important factor. Additionally, as competition in the industry gets fierce, investment on informatization has been changed to a utility way of implementation of strategies and decision on investment has been made through the official process and information technology. Differentiated company capability has been made based on acquisition of technical knowledge and company information has been expanded to its whole employees through the information system. Also, informatization change management and outside subcontractor management have been acknowledged as an important adjustment factor of company. The first implication of this study is that since case studies on mechanism factors that preceding studies on informatization results did not empirically cover have directly been dealt with based on experiences of executives in charge of business and in charge of informatization, this study can provide practical views about factors that should be mainly managed for informatization results of IT companies. Secondly, since ser-M framework has been applied for IT companies for the first time, this study can academically contribute to companies in other fields about main mechanism factors for result creation of informatization based on deeper understanding and empirical cases.

• Journal of Korean Home Economics Education Association
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• v.20 no.1
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• pp.137-152
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• 2008

This study examined the organization and operation of home economics curriculum of specialized middle school in the form of regular school among alternative schools and analyzed the perceptions of teachers and students about home economics class. Interviews were conducted with teachers of 6 specialized schools in order to determine the operations and teachers' perceptions of home economics education. Students' perceptions for home economics class were gathered through surveys with students from the 3 (of the original 6) schools that authorized the questionnaire survey. The final analysis utilized 205 student responses. Survey data were analyzed using the SPSS program. The results of the research were as follows: First, home economics education within specialized middle schools was mostly conducted according to the form of the technology-home economics curriculum, which is the national common basic curriculum. Compared to the 7th national curriculum, the class of technology-home economics curriculum in 4 schools occurred 1 hour less each week. Each school incorporated various specialized curricula related to home economics. Second, as for the operation of home economics education in specialized schools, most home economics classes were conducted by teachers who had majored (or minored) in home economics. Moreover, all but 1 school, which used self-made materials, used the national textbook and dealt with the entire content of the textbook. For teaching-learning methods and instructional media, various means were utilized. For evaluation methods, most schools based grades on paper-and-pencil tests(50-60%) and performance tests(40-50%). Third, among teachers' perceptions of home economics education, the meaning of home economics education was focused on practical help and the pursuit of home happiness; the purpose was to realize the happiness of students and their homes by applying these to actual living, and increase students' ability to see the world. In regards to difficulties in educational operations, most pointed out poor conditions of practice rooms. As for differences from general schools, most teachers mentioned the active communication with students. Fourth, through the home economics class, it was found that students perceived the goal of technology-home economics curricula as lower than average. Among students' perceptions about home economics class, most were negative. Perceptions about goal of technology-home economics curricula and home economics class also showed meaningful differences according to each school. Students of the school, which had more home economics class hours and specialized curricula related to home economics, perceived more positively. Also, students who were more satisfied with school and learned from a teacher who majored in home economics tended to perceive home economics class more positively.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.119-138
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• 2017

Recently, SNS has become an important channel for marketing as well as personal communication. However, cybercrime has also evolved with the development of information and communication technology, and illegal advertising is distributed to SNS in large quantity. As a result, personal information is lost and even monetary damages occur more frequently. In this study, we propose a method to analyze which sentences and documents, which have been sent to the SNS, are related to financial fraud. First of all, as a conceptual framework, we developed a matrix of conceptual characteristics of cybercriminality on SNS and emergency management. We also suggested emergency management process which consists of Pre-Cybercriminality (e.g. risk identification) and Post-Cybercriminality steps. Among those we focused on risk identification in this paper. The main process consists of data collection, preprocessing and analysis. First, we selected two words 'daechul(loan)' and 'sachae(private loan)' as seed words and collected data with this word from SNS such as twitter. The collected data are given to the two researchers to decide whether they are related to the cybercriminality, particularly financial fraud, or not. Then we selected some of them as keywords if the vocabularies are related to the nominals and symbols. With the selected keywords, we searched and collected data from web materials such as twitter, news, blog, and more than 820,000 articles collected. The collected articles were refined through preprocessing and made into learning data. The preprocessing process is divided into performing morphological analysis step, removing stop words step, and selecting valid part-of-speech step. In the morphological analysis step, a complex sentence is transformed into some morpheme units to enable mechanical analysis. In the removing stop words step, non-lexical elements such as numbers, punctuation marks, and double spaces are removed from the text. In the step of selecting valid part-of-speech, only two kinds of nouns and symbols are considered. Since nouns could refer to things, the intent of message is expressed better than the other part-of-speech. Moreover, the more illegal the text is, the more frequently symbols are used. The selected data is given 'legal' or 'illegal'. To make the selected data as learning data through the preprocessing process, it is necessary to classify whether each data is legitimate or not. The processed data is then converted into Corpus type and Document-Term Matrix. Finally, the two types of 'legal' and 'illegal' files were mixed and randomly divided into learning data set and test data set. In this study, we set the learning data as 70% and the test data as 30%. SVM was used as the discrimination algorithm. Since SVM requires gamma and cost values as the main parameters, we set gamma as 0.5 and cost as 10, based on the optimal value function. The cost is set higher than general cases. To show the feasibility of the idea proposed in this paper, we compared the proposed method with MLE (Maximum Likelihood Estimation), Term Frequency, and Collective Intelligence method. Overall accuracy and was used as the metric. As a result, the overall accuracy of the proposed method was 92.41% of illegal loan advertisement and 77.75% of illegal visit sales, which is apparently superior to that of the Term Frequency, MLE, etc. Hence, the result suggests that the proposed method is valid and usable practically. In this paper, we propose a framework for crisis management caused by abnormalities of unstructured data sources such as SNS. We hope this study will contribute to the academia by identifying what to consider when applying the SVM-like discrimination algorithm to text analysis. Moreover, the study will also contribute to the practitioners in the field of brand management and opinion mining.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• (The)Study of the Eastern Classic
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• no.73
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• pp.9-33
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• 2018

This paper examines the literary theory of Gollyun(昆侖) Choe, Changdae(崔昌大, 1669-1720). He has authored a variety of works, and his works have been recognized in many literatures. Because of this, studying his literature is a meaningful. The theory of poem creation is as follows. It is the basic poem creationism that expresses the feelings that I experienced and felt as it is. The utility is to multiply and control the artist's feelings through his poem. However, the creative theory of being the best writer is different from this. It must be premised on finding from the heart and studying various books. If these qualities was provided, the words are clear and the meaning is condensed. He distinguished between general works and the best works, and presented their own creative theory and discussed their utility. The theory of prose utility is as follows. He emphasizes the importance of communicating with contemporaries and establishing important things of the day and making them easier to understand, without specifying the morality. This is a thoroughly realistic utility theory. In the classical chinese prose's history, 'Sadal(辭達)' and 'Susa(修辭)' were issues. He transcends the recognition of 'Sadal(辭達)' and 'Susa(修辭)' as zero-sum. In addition, he gives priority to the meaning of the writer and emphasizes self-realization, which is in common with other political soron(少論) writers' theories. When creating prose, simplicity and bizarreness were issues. He emphasizes concise writing. However, it can be realized when a writer with high opinion is aware of the reason and raises the core. Through various sources, he has completely rejected Ming(明) dynasty's former and latter seven master(前後七子). However, he did not exclude their work unilaterally, and recognized the work of Chin-Han dynasty(秦漢) and Dang-Song dynasty(唐宋). This is the same as his father Choiseokjung(崔錫鼎). He recognized Chin-Han dynasty(秦漢) and Dang-Song dynasty(唐宋) equally, and sought a simplified and summarized style.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.6
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• pp.49-63
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• 2021

The Forest Visitor Centers for Little Children who means preschoolers is an educational facility that achieves holistic growth by experiencing forests, and it should not be completed by installing specific facilities in the forest environment, but should be a space where preschoolers can play freely in the forest environment themselves. This study comprehensively evaluated the current status of Seoul Forest Visitor Centers for Little Children and suggested space improvement measures to enhance the effectiveness of forest experience. Through the theoretical review, seven spatial elements that enhance the effect of forest experience and six areas composing outdoor play areas were derived to prepare an analysis table for current status evaluation, and field survey studies were conducted on 24 centers in Seoul. Through expert interviews, the physical status was examined from the perspective of childhood education and the experiences of the users were summarized. As a result of the study, the Seoul Forest Visitor Center for Little Children is classified into six types according to the location characteristics and spatial structure, and has the characteristics of each type. The effectiveness of forest experience can be enhanced by identifying and revealing the environmental strengths of individual centers. In the case of outdoor experience learning zones, the proportion of exercise play areas was very large. By evenly organizing the forest experience space for each area, it will be possible to provide more diverse experiences to preschoolers. However, the status of uniform facility-oriented cannot be viewed as a fragmentary factor that lowers the effect of forest experience. The key to increasing the effect of forest experience by inducing creative activities is the spatial composition that considers the surrounding natural environment. Facilities should be a medium to help preschoolers' interest move into the forest. This study prepared data to understand the average physical status of the Seoul Forest Visitor Center for Little Children and suggested space improvement measures to increase the effectiveness of forest experience. This can be used as basic data for research to improve the quality level of the Seoul Forest Visitor Center for Little Children about 10 years after the project was implemented.

• Journal of The Korean Association For Science Education
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• v.43 no.2
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• pp.139-150
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• 2023

This study started with the awareness of the need to explore various aspects of science education and was conducted according to the necessity of practical research on science cultural activities targeting adults. Accordingly, adults' book discussions of science fiction were selected as research cases, and science-related attitudes in science cultural activities were explored. There are four participants in the study, all of whom have engaged in a book club and have not majored or are working in science disciplines. Three science fictions were selected after establishing specific standards for the selection discussed with participants. For four months, a total of three unstructured book discussions of science fiction, post-interviews for each discussion, and in-depth individual interviews after the end of the entire activity were conducted. Various data such as recorded and transcribed reading discussion discourse, post- and in-depth individual interviews, researchers' observation records, and participants' book journals were collected and analyzed using a continuous comparison method. As a result of the study, as scientific thinking is illustrated in SF, the participants also demonstrated scientific attitudes during their discussions. In addition, the textual feature(storytelling) of science fiction was found to lessen cognitive overload and the burden of understanding science by providing scientific knowledge with context. Finally they demonstrated a shift in attitude toward science, valuing science cultural activities in themselves, rather than simply viewing science as a subject of understanding and learning. The conclusions and meanings of this study based on the above results are presented to enhance a positive attitude toward science for adults even after school education.

• Journal of Korea Entertainment Industry Association
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• v.13 no.2
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• pp.27-36
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• 2019

Today, the Korean wave headed by K-pop is newly named as 'New Korean Wave' in that it has been extended to United States, Europe and Russia. K-POP, the main player of the new Korean wave, has been successful in SNS marketing channels. Furthermore, the content of K-pop has attracted the attention of the global audience. The media and public attention on the Korean Wave is meaningful because it is not merely a cultural export. It also makes Korean people feel national pride, seeing the mental influence of its culture on other regions. Moreover, the development of the cultural industry in our society, which is different from industrial or material development, is a proof that Korean society is at the center of globalization. Until the 20th century, Korean culture had been rather receptive than dominant. In other words, it was focused more on acceptance of other cultures than active creation or outflow of its own. Now, however, K-POP is not anymore copying Western culture. It is creating its own unique characters, which makes K-pop very competitive. Korean culture has been formed for a long time in Korea's unique historical background. Korean popular culture also has to establish a solid foothold in world markets through its distinctive and traditional feature. The positive consumer response to Korean pop culture will create the added value of Korean contents and their derivatives, which will heighten Korea's national image also. In other words, if traditional art and K-POP are converged and equipped with our own unique and highly artistic culture, they will take the lead in the global cultural art market. In this study, we will recognize the possibility, growth and development of K-pop culture and analyze the cases of combining K-pop and Korean traditional art. First, we have to blend traditional art and other various genres to create diverse contents, and we have to actively utilize media channels. Second, we must improve people's awareness of the copyrights of traditional art. Also, we have to mitigate the copyrights of creative dance to expand the disclosure of contents which can be utilized. Third, we have to learn about traditional arts from younger age. Fourth, we will expand traditional arts to the whole of Korean cultural policies, which can enhance the nation's cultural value and create economic benefits. These four are expected to be effective ways to preserve the identity of traditional art and at the same time, globalize Korean culture.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.35-44
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• 2024

Research in dam inflow prediction has actively explored the utilization of data-driven machine learning and deep learning (ML&DL) tools across diverse domains. Enhancing not just the inherent model performance but also accounting for model characteristics and preprocessing data are crucial elements for precise dam inflow prediction. Particularly, existing rainfall data, derived from snowfall amounts through heating facilities, introduces distortions in the correlation between snow accumulation and rainfall, especially in dam basins influenced by snow accumulation, such as Soyang Dam. This study focuses on the preprocessing of rainfall data essential for the application of ML&DL models in predicting dam inflow in basins affected by snow accumulation. This is vital to address phenomena like reduced outflow during winter due to low snowfall and increased outflow during spring despite minimal or no rain, both of which are physical occurrences. Three machine learning models (SVM, RF, LGBM) and two deep learning models (LSTM, TCN) were built by combining rainfall and inflow series. With optimal hyperparameter tuning, the appropriate model was selected, resulting in a high level of predictive performance with NSE ranging from 0.842 to 0.894. Moreover, to generate rainfall correction data considering snow accumulation, a simulated snow accumulation algorithm was developed. Applying this correction to machine learning and deep learning models yielded NSE values ranging from 0.841 to 0.896, indicating a similarly high level of predictive performance compared to the pre-snow accumulation application. Notably, during the snow accumulation period, adjusting rainfall during the training phase was observed to lead to a more accurate simulation of observed inflow when predicted. This underscores the importance of thoughtful data preprocessing, taking into account physical factors such as snowfall and snowmelt, in constructing data models.

• The Korean Society of Law and Medicine
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• v.24 no.4
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• pp.67-101
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• 2023

The utilization of generative AI in the medical field is also being rapidly researched. Access to vast data sets reduces the time and energy spent in selecting information. However, as the effort put into content creation decreases, there is a greater likelihood of associated issues arising. For example, with generative AI, users must discern the accuracy of results themselves, as these AIs learn from data within a set period and generate outcomes. While the answers may appear plausible, their sources are often unclear, making it challenging to determine their veracity. Additionally, the possibility of presenting results from a biased or distorted perspective cannot be discounted at present on ethical grounds. Despite these concerns, the field of generative AI is continually advancing, with an increasing number of users leveraging it in various sectors, including biomedical and life sciences. This raises important legal considerations regarding who bears responsibility and to what extent for any damages caused by these high-performance AI algorithms. A general overview of issues with generative AI includes those discussed above, but another perspective arises from its fundamental nature as a large-scale language model ('LLM') AI. There is a civil law concern regarding "the memorization of training data within artificial neural networks and its subsequent reproduction". Medical data, by nature, often reflects personal characteristics of patients, potentially leading to issues such as the regeneration of personal information. The extensive application of generative AI in scenarios beyond traditional AI brings forth the possibility of legal challenges that cannot be ignored. Upon examining the technical characteristics of generative AI and focusing on legal issues, especially concerning the protection of personal information, it's evident that current laws regarding personal information protection, particularly in the context of health and medical data utilization, are inadequate. These laws provide processes for anonymizing and de-identification, specific personal information but fall short when generative AI is applied as software in medical devices. To address the functionalities of generative AI in clinical software, a reevaluation and adjustment of existing laws for the protection of personal information are imperative.