• Journal of Sasang Constitutional Medicine
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• v.4 no.1
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• pp.5-29
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• 1992

In this study, the author researched the process in which the philosophical basis of 'Sa Sang Medicine (四象醫學)' and its methodology build up the principles of Sa Sang Medicine, and then, examined how the principles were applied to the theoretical system of Sa Sang Medicine. The conclusion would be summarized as follows. 1. 'Nae Kyung Medicine (內經醫學)' was developed under the concept that the cosmos's order and its moving rule could be directly applied to that of human body, which corresponded to the 'Theory of Hwang-No (黃老之學)'. On the contrary, Sa Sang Medicine is a thoroughly human-oriented theory formed in the Confucianism system. 2. Lee Jae-Ma's Substantialism can be briefed into 'Mind 心' (Tae Keuk 太極), 'Mind-Body 心身' (Yang Eui 兩儀) and 'Activity-Mind-Body-Matter 事心身物' (Sa Sang 四象), which respectively represents one-elemented substance, two-elemented substance and four-elemented substance. Especially, Sa Sang was used as a basic framework in which he recognized all the objects and phenomena. So, most critical significance of his substantialism consists in the intention of Sa Sang type classifying. 3. By the method of Sa Sang type classifying, Lee Jae-Ma not only redefined the main concepts of confucianism and developed a unique philosophy of his own, but also, in the field of medical science, resystemized and re-explained the structure and function of human body. 4. From the recognition that Activity-Mind-body-Matter (Sa Sang) are four different existence forms of energy 氣 (or four variation types of energy), Yi Jae-Ma thinks that the viscera of human body have a vertical structure of 'four parts 四焦' (upper, mid-upper, mid-lower and lower parts) and its physiological function is operated by the rising and falling action of four energy presentations (sorrow 哀, anger 怒, joy 喜 and pleasure 樂). 5. In "Gyuk Chi Go 格致藁", Lee Jae-Ma understood the concept of joy, anger, sorrow and pleasure on the basis of nature-emotion theory 性情論 from the philosophical viewpoint. But, from the medical viewpoint of "Dong Eui Su Se Bo Won 東醫壽世保元", he understood them on the basis of vital energy theory. That is, sorrow, anger, joy and pleasure are expression of advance or reverse of nature vital-energy 性氣 and emotion vital-energy 情氣. 6. The rising and falling action principle of four energy presentations (sorrow, anger, joy and pleasure) which produces and helps each other is an identical principles of Sa Sang Medicine, distinguished from the Oh-Haeng 五行 circulating principle in Nae Kyung Medicine. Through this principle, Lee Jae-Ma explained the viscera physiology of human body, pathology & diagnosis and pharmacology.

• Journal of Sasang Constitutional Medicine
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• v.9 no.1
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• pp.127-153
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• 1997

Sasang-Medicine can classify all sympton with more simple classifying system than past Oriental-Medicine, because Sasang Byeon-Zeung(=classifying system of the sympton) separate by four clearly. The merit of this Sasang Byeon-Zeung can be seen more clearly on the part of the pathology of the expiratory-scattering and inspiratory-gathering of the Tae-Eum and Tae-Yang. On this view point, this thesis discussed the following subjects. 1. Investigate the theory of raising-falling and scattering-gathering developed in the Dongeui-Suse-Bowon. 2. Investigate the changes of the recognition of the Yang-Dog sympton and Jo-Yeol sympton argued as Interior-overheating-sympton of the Tae-Eum-In caused by liver's receiving heat. 3. Investigate the Yi-Je-Ma's view on the Eum-Yang in the argument of interior-overheating-sympton of the Tae-Eum-In caused by liver's receiving heat. As a result, the following conclusions were led to. 1. Dongeui-Suse-Bowon considers Spleen-Kidney has the couple motion of the raising Yang and falling Eum, and Liver-Lung has the couple motion of the expiratory-scattering and inspiratory-gathering. This theory of raising-falling and scattering-gathering is same as in the concept with the gathering. This theory of raising-falling and scattering-gathering is same as in the concept with the theory of raising-falling and floating-sinking of past Oriental-Medicine, but more consistently systematized in the pathology and prescription. 2. Dongeui-Suse-Bowon considers the Yang-Dog sympton and Jo-Yeol sympton as the interior-overheating-sympton of the Tae-Eum-In. As following the book, the fire of desire weeken the expiratory-scattering power of the lung, and deepen the shortage of the expiratory-scattering power comparison to the inspiratory-gathering power. Therfore the sympton can be treated by releasing ourselves from the desire and taking medicine strengthening the expiratory-scattering power. 3. In the early stage of the orintal medicine, they used prescriptions composed of So-Yang medicine and Tae-Eum medicine which can cool heat. Galgeun, Mawhang and Seungma were used in the age of Sanghanron, thereafter Jugoing's Jojung-Tang and Gongsin's Galgeunhaegi-Tang were developed as prescriptions of the interior-overheating-sympton of the Tae-Eum-In, and finally Tea-Uem-In Galgeunhaegi-Tang was settled by Yi-Je-Ma.

• Quality Improvement in Health Care
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• v.3 no.1
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• pp.78-93
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• 1996

Background : The goal of this study was to establish the QA items and guidelines for preventing and improving of safety management. Therefore we investigated the nurses' recognition and knowledge of the safety and risk procedures and policies, and the agreement between the nurses beliefs on the degree of importance of those procedures and policies, with actual implementation in hospitals. Method : The subjects of this study were 201 nurses who participated in a program called continuing education for nurses, which held in December, 1993. Result: The results of this study were as follows: 1. Among 18 types of hospital risks, the items that scored highest or the need of closer attention in safety management was the needle stick, medication errors, falling, and bed sores. 2. In most questions of the 18 incidences, the nurses showed that the estimated result would have positive signs except for hospital infections, burns, and bed sores. 3. Even though the survey shows that incidences and types of occurences varies according to the person's age and the time of incident, they mostly occur between midnight to 6AM. Falls and bed sores can be seen more in the elderly. Medications errors, hospital infections and burns are frequently found between the ages of one through twenty. 4. There was a higher mean score for recognizing the importance of those items than the importance of implementing them. Conclusion : In summary, nurses did perceive the need of safety management but the hospital policy for proper safety management was not established. So we recommended that the hospital administration would undertake an early detection and proper management system for hospital precautions, based on QA items & guidelines presented in this study.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.325-340
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• 2022

Amid the unprecedented situation of COVID-19 around the world, online education has established itself as an essential element in the era of zero contact and the importance of various content and changes of the system that are appropriate for the era of the 4^th industrial revolution has increased. Although universities are making their efforts to combine ICT technologies and design and achieve new systems, the recognition and atmosphere for establishing the cloud computing system are falling short. The purpose of this research importance of success factors of "Building a cloud computing system of cyber university in Korea" by classifying the work characteristics and scale, and to derive and analyze the importance cloud rankings considering the organization and individual dimension. Therefore, this study has drawn 14 major factors in the previous researches and models through the survey on experts with knowledge related to the cloud computing. The analysis was conducted to see what differences there are in factors for the successful establishment of the cloud computing system using AHP. It is expected that the factors for success presented through this study would be used as systemic strategies and tools for the purpose of drawing factors for the success of establishing the private cloud computing system for the higher education institutions and public information systems.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.123-132
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• 2013

As the smartphones are equipped with various sensors such as the accelerometer, GPS, gravity sensor, gyros, ambient light sensor, proximity sensor, and so on, there have been many research works on making use of these sensors to create valuable applications. Human activity recognition is one such application that is motivated by various welfare applications such as the support for the elderly, measurement of calorie consumption, analysis of lifestyles, analysis of exercise patterns, and so on. One of the challenges faced when using the smartphone sensors for activity recognition is that the number of sensors used should be minimized to save the battery power. When the number of sensors used are restricted, it is difficult to realize a highly accurate activity recognizer or a classifier because it is hard to distinguish between subtly different activities relying on only limited information. The difficulty gets especially severe when the number of different activity classes to be distinguished is very large. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we take to dealing with this ten-class problem is to use the ensemble of nested dichotomy (END) method that transforms a multi-class problem into multiple two-class problems. END builds a committee of binary classifiers in a nested fashion using a binary tree. At the root of the binary tree, the set of all the classes are split into two subsets of classes by using a binary classifier. At a child node of the tree, a subset of classes is again split into two smaller subsets by using another binary classifier. Continuing in this way, we can obtain a binary tree where each leaf node contains a single class. This binary tree can be viewed as a nested dichotomy that can make multi-class predictions. Depending on how a set of classes are split into two subsets at each node, the final tree that we obtain can be different. Since there can be some classes that are correlated, a particular tree may perform better than the others. However, we can hardly identify the best tree without deep domain knowledge. The END method copes with this problem by building multiple dichotomy trees randomly during learning, and then combining the predictions made by each tree during classification. The END method is generally known to perform well even when the base learner is unable to model complex decision boundaries As the base classifier at each node of the dichotomy, we have used another ensemble classifier called the random forest. A random forest is built by repeatedly generating a decision tree each time with a different random subset of features using a bootstrap sample. By combining bagging with random feature subset selection, a random forest enjoys the advantage of having more diverse ensemble members than a simple bagging. As an overall result, our ensemble of nested dichotomy can actually be seen as a committee of committees of decision trees that can deal with a multi-class problem with high accuracy. The ten classes of activities that we distinguish in this paper are 'Sitting', 'Standing', 'Walking', 'Running', 'Walking Uphill', 'Walking Downhill', 'Running Uphill', 'Running Downhill', 'Falling', and 'Hobbling'. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window of the last 2 seconds, etc. For experiments to compare the performance of END with those of other methods, the accelerometer data has been collected at every 0.1 second for 2 minutes for each activity from 5 volunteers. Among these 5,900 ($=5{\times}(60{\times}2-2)/0.1$) data collected for each activity (the data for the first 2 seconds are trashed because they do not have time window data), 4,700 have been used for training and the rest for testing. Although 'Walking Uphill' is often confused with some other similar activities, END has been found to classify all of the ten activities with a fairly high accuracy of 98.4%. On the other hand, the accuracies achieved by a decision tree, a k-nearest neighbor, and a one-versus-rest support vector machine have been observed as 97.6%, 96.5%, and 97.6%, respectively.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.