• Journal of The Association for Neo Medicine
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• v.2 no.1
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• pp.35-54
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• 1997

We tried to observe the features of ancient medical practice by analysing the records related to medicine in the book, ${\ulcorner}$the Historical Records of the Three Kingdom${\lrcorner}$ of which content includes the features of medicine in mythology, plague, delivery of twins, drugs, medical system, shamanism, constitutional medicine, psychiatry, forensic medicine, deformity, a spa, medical phrase, health and welfare work, religion, death. physiological anatomy, Taoist medicine, acupuncture, the occult af of transformation and etc. Our initial concern was about where to draw line as of medical field and we defined medicine in more broad meaning. The book ${\ulcorner}$the Historical Records of the Three Kingdoms${\lrcorner}$ describes the world of mythology by way of medicine which is not clearly a conventional one. There appears records of birth of multiple offsprings 7 times in which cases are of triplets or more. Delivering multiple offsprings were rare phenomenon though such fertility was highly admired. This shows one aspect of ancient country having more population meant more power of the nation. Of those medical records conveyed in that book includes stories of childbirth such as giving birth to a son after praying, giving birth to Kim Yoo-shin after 20 months after mother's dream of conception, and a song longing for getting a laudable child. Plagues were prevalent throughout winter to spring season and one can observe various symptoms of plagues in the record. Of these epidemic diseases, cold type might have been more common than the heat one. Appearance of epidemic diseases frequently coincided with that of natural disasters that this suggests a linkage between plague and underlying doctrine on five elements' motion and six kinds of natural factors. There exists only a few names of diseases such as epidemic disease, wind disease, and syndrome characterized by dyspnea. Otherwise there appeared only afflictions that were not specified therefore it remains cluless to keep track of certain diseases of prevalence. Since this ${\ulcorner}$Historical Records of the Three Kingdoms'${\lrcorner}$ wasn't any sort of medical book, words and terms used were not technical kind and most were the ones used generally among lay people. Therefore any mechanisms of the diseases were hardly mentioned. Some of medicinal substances such as Calculus Bovis, Radix Ginseng, Gaboderma Luciderm, magnetitum were also in use in those days. 53 kinds of dietary supplies appears in the records and some of these might have been used as medicinal purpose. Records concerning dicipline of one's body includes activities such as hunting, archery, horseback riding etc. In Shilla dynasty there were positions such as professor of medicine, Naekongbong(內供奉), Kongbong's doctor(供奉醫師), Kongbong's diviner(供奉卜師). As an educational facility, medical school was built at the first year of King Hyoso's reign and it's curricula included various subjects as ${\ulcorner}$Shin Nong's Herbal classic${\lrcorner}$, ${\ulcorner}$Kabeul classic of acupuncture and moxbustion${\lrcorner}$, ${\ulcorner}$The Plain Questions of the Yellow Emperor's Classic of Internal Medicine${\lrcorner}$, ${\ulcorner}$Classic of Acupuncturer${\lrcorner}$, ${\ulcorner}$The Pulse Classic${\lrcorner}$, ${\ulcorner}$Classic of Channels and Acupuncture Points${\lrcorner}$ and ${\ulcorner}$Difficult Classic${\lrcorner}$. There were 2 medical professors who were in charge of education. To establish pharmacopoeia, 2 Shaji(舍知), 6 Sha(史), 2 Jongshaji(從舍知) were appointed. In Baekje dynasty, Department of Herb was maintained. Doing praying for the sake of health, doing phrenology also can be extended to medical arena. Those who survived over 100 years of age appear 3 times in the record, while 98 appears once. The earliest psychiatrist Nokjin differentiated symptoms to apply either therapies using acupuncture and drug or psychotherapy. There appears a case of rape, a case of burying alive with the dead, 8 cases of suicide that can characterize a prototype of forensic medicine. Deformity-related records include phrases as follow: 'there seems protrudent bone behind the head', 'a body which has two heads, two trunks, four arms.', 'a body equipped with two heads' In those times spa can be said to be used as a place for he리ing, convalescence, and relaxation seeing the records describing a person pretended illness and went to spa to enjoy with his friends. Priest doctors and millitary surgeons were in charge of the medical sevice in the period of the Three Kingdoms by the record written by Mookhoja(墨胡子) and Hoonkyeom(訓謙). Poor diet and regimen makes people more vulnerable to diseases. So there existed charity services for those poor people who couldn't live with one's own capacity such as single parents, orphans, the aged people no one to take care and those who are ill. The cause of affliction was frequently coined with human relation. There appeared the phenomenon of releasing prisoners and allowing people to become priests at the time of king's suffering. Besides, as a healing procedure, sutra-chanting was peformed. There appears 10 cases of death related records which varies from death by drowning, or by freezing, death from animals, death from war, death from wightloss and killing oneself at the moment of spouse's death and etc. There also exist certain records which suggest the knowledge of physiology and anatomy in those times. Since the taoist books such as ${\ulcorner}$Book of the Way and Its Power(老子道德經)${\lrcorner}$ were introduced in the period of Three Kingdoms, it can be considered that medicine was also influenced by taoism. Records of higher level of acupuncture, records which links the medicine and occult art of transformation existed. Although limited, we could figure out the medical state of ancient society.

• 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.

• 한국사회복지학회:학술대회논문집
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• 2003.10a
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• pp.185-216
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• 2003

This study was aimed at investigating important factors influencing career success among regular workers. The current researcher scrutinized the degree to which variables and factors affect the career success and occupational turnover rates of the research participants. At the same tune, two hypothetical path models established by the researcher were examined using linear multiple regression methods and the LISREL. After examining the differences among the factors of career success, a comparison was made between the disabled worker group and the non-disabled worker group. A questionnaire using the 5-point Likert scale was distributed to a group of 374 workers with disabilities and 463 workers without disabilities. For the data analysis purpose, the structural equation model, factor analysis, correlation analysis, and multiple regression analysis were carried out. The results of this study ran be summarized as follows. First, the results of factor analysis showed important categories of conceptual themes of career success. The initial conceptual factor model did not accord with the empirical one. A three-factorial model revealed categories of personal, family, and organizational factor respectively. The personal factor was composed of the self-esteem and self-efficiency. The family factor was consisted of the multi-roles stress and the number of children. Finally, the organizational factor was composed of the capacity for utilizing resources, networking, and the frequency of mentoring. In addition, the total 10 sub areas of career success were divided by two important aspects; the subjective career success and the objective career success. Second, both research participant groups seemed to be influenced by their occupational types. However, all predictive variables excluding the wage rate and the average length of work years had significant impact on job success for the disabled work group, while all the variables excluding the frequency of advice and length of working years had significant impact on job success for the non-disabled worker group. Third, the turnover rate was significantly influenced by the age and the experience of turnover of the research participants. However, the number of co-workers was the strongest predictive variable for the worker group with disabilities, but the occupation choice variable for the worker group without disabilities. For the disabled worker group, the turnover rate was differently influenced by the type of occupation, the length of working years, while multi-role stress and the average working years at the time of turnover for the worker group without disabilities. Fifth, as a result of verifying the hypothetical path model, it showed that the first model was somewhat proper and could predict the career success on both research participant groups. In the second model, the Chi-square, the degree of freedom (($x^2=64.950$, df=61, P=0.341), and the adjusted Goodness of Fit Index (AGFI) were .964, and the Comparative Fit Index (CFI) were .997, and the Root Mean Squared Residual (RMR) was respectively. .038. The model was best fitted and could predict the career success more highly because the goodness of fit index in the whole models was within the allowed range. In conclusion, the following research implications can be suggested. First, the occupational type of research participants was one of the most important variables to predict the career success for both research participant groups. It means that people with disabilities require human development services including education. They need to improve themselves in this knowledge-based society. Furthermore, for maintaining the career success, people with disabilities should be approached by considering the subjective career success aspects including wages and the promotion opportunities than the objective career success aspects.