• Korean Journal of Acupuncture
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• v.31 no.2
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• pp.66-78
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• 2014

Objectives : The specificity of acupuncture point has been a highly controversial subject. Existing researches said that ion-distribution differences are observed on the acupuncture point. This study was conducted under the assumption that multiple ionic changes induced by muscle fatigue would be different between the acupuncture point with non-acupuncture point. Methods : To induce the identical fatigue, twenty subjects performed the knee extension/flexion exercise using the Biodex System 3. ST32 and ST33 as well as adjacent non-acupuncture points were selected. We measured blood lactate and analyzed the median frequency(MF) and peak torque. To obtain the information on the extracellular fluid(ECW), intracellular fluid(ICW) and cell membrane indirectly, we used the multi-frequency bioelectrical impedance analysis(MF-BIA) method. Results : MF, peak torque and blood lactate level of all measurement sites were gradually returned to normal. Re resistance of ST32 had a stronger response, but a non-acupuncture point adjacent to ST33 had a larger response up to 20 minutes post exercise. Ri resistances were similar for both acupoints and non-acupoints. The $C_m$ capacitance of ST32 had a stronger response after inducing fatigue, but ST33 had a smaller response than a non-acupuncture point adjacent to it. Conclusions : In comparison with before and after inducing fatigue, the specificity of acupuncture points was not clearly observed. Hence, we concluded that the body composition factors extraction method had the limitation as a method of finding the specificity of acupuncture points by inducing fatigue.

• Korean Journal of Veterinary Service
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• v.17 no.3
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• pp.227-246
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• 1994

Present investigations were undertaken in order to clarify the clinical status of Korean native cattle and dairy cattle(holstein). Blood, Feces and urine samples were collected from 247 Korean native cattle(222 adult and 25 calf), 224 dairy cattle(211 adult and 13 calf) at Chonbuk area and analyzed for clinical, serum chemical, hematological and urinary findings. In addition, we were examined the infection rate of Theileriosis, internal patasite and ring worm. The mean value for each component was calculated by statistical analysis using Excel computer program. From these investigations the following results were obtained. The mean values for RBC, PCV and etc in 433 adult cow(Korean native cattle and dairy cattle) were similar with other reports. But the mean values for MCHC of all species were lower than normal. Adult Korean native cattle and adult dairy cattle which showed hematologically normal levels were only 9.01% and 9.48%, respectively. Ahnormally high values for PCV, RBC and Hb were recorded in 7.66% of adult Korean native cattle, 20% of Korean native calf, 15.38% of dairy calf. Adult Korean native cattle and adult dairy cattle which showed hematologically anemia were 4.95% and 19.43% respectively, but all in Korean native calf and dairy calf showed normal values. Adult Korean native cattle, adult dairy cattle, Korean native calf and dairy calf which showed normal serum protein level were 84.0%, 90.8%, 50% and 44.4%, respectively. In present investigations, 50% of Korean native calf and 55.6% of dairy calf were decreased serum protein values under normal range. These abnormally decreased serum protein values mean the shortage of antibody, and these have a possibility to occrus to pneumonia and diarrhea. From these results, the economical loss caused by pneumonia was calculated as 124, 038, 833 won in the KNC and 742, 703, 430 won in the dairy calf rearing in Chonbuk area. Calculated economical loss caused by enteritis was 56, 658, 690 won in Korean native cattle. 476, 775, 799 won in dairy calf and the total loss amount to 533, 434, 488 won in Chonbuk area. Abnormally high values($21.7{\pm}4.0mg/dl) for serum calcium were recorded 49.6% in dairy cattle. The mean values of serum total cholesterol were $170.8{\pm}99.8mg/dl in Korean native cattle, $196.0{\pm}40.6mg/dl$ in Korean native calf, $202.9{\pm}86.0mg/dl$ in adult dairy cattle and $289.4{\pm}97.5mg/dl$ in dairy calf. The infection rate of internal parasite were as follows； adult Korean native cattle：21.2%, Korean native calf：80%, adult dairy cattle：67.8%. The estimated economical loss caused by internal parasites infection were 1, 120, 855, 837 won in Korean native calf, 4, 994, 959, 405 won in adult Korean native cattle, 3, 334, 751, 066 won in adult holstein, and the total loss amount to 9, 450, 566, 308 won. The infection rate of theileriosis were 1.4% in Korean native cattle and 6.6% in dairy cattle. The presumed Economical loss by T. sergenti infection were 154, 408, 482 won in Korean native cattle and 171, 577, 237 won in dairy cattle rearing at Chonbuk area. The infection rat of ringworm were 0.5% in Korean native cattle, 0.9% in adult dairy cattle and 7.7% in dairy calf. The presumed economical loss by dermatomycophyte were 12, 061, 532 won in Korean native cattle, 16, 895, 403 won in dairy cattle, and the total estimated loss amount to 28, 955, 935 won a year in Chonbuk area. The infection rate of ringworm were 0. 5% in Korean native cattle, 0.9% in adult dairy cattle and 7.7% in dairy calf. The presumed economical loss by dermatomycophyte were 12, 061, 532 won in Korean native cattle, 16, 895, 403 won in dairy cattle, and the total estimated loss amount to 28, 955, 935 won a year in Chonbuk area.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.71-89
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• 2016

Sentiment analysis is used for identifying emotions or sentiments embedded in the user generated data such as customer reviews from blogs, social network services, and so on. Various research fields such as computer science and business management can take advantage of this feature to analyze customer-generated opinions. In previous studies, the star rating of a review is regarded as the same as sentiment embedded in the text. However, it does not always correspond to the sentiment polarity. Due to this supposition, previous studies have some limitations in their accuracy. To solve this issue, the present study uses a supervised sentiment classification model to measure a more accurate sentiment polarity. This study aims to propose an advanced sentiment classifier and to discover the correlation between movie reviews and box-office success. The advanced sentiment classifier is based on two supervised machine learning techniques, the Support Vector Machines (SVM) and Feedforward Neural Network (FNN). The sentiment scores of the movie reviews are measured by the sentiment classifier and are analyzed by statistical correlations between movie reviews and box-office success. Movie reviews are collected along with a star-rate. The dataset used in this study consists of 1,258,538 reviews from 175 films gathered from Naver Movie website (movie.naver.com). The results show that the proposed sentiment classifier outperforms Naive Bayes (NB) classifier as its accuracy is about 6% higher than NB. Furthermore, the results indicate that there are positive correlations between the star-rate and the number of audiences, which can be regarded as the box-office success of a movie. The study also shows that there is the mild, positive correlation between the sentiment scores estimated by the classifier and the number of audiences. To verify the applicability of the sentiment scores, an independent sample t-test was conducted. For this, the movies were divided into two groups using the average of sentiment scores. The two groups are significantly different in terms of the star-rated scores.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.139-166
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• 2010

The supply chain management (SCM) systems have emerged as strong managerial tools for manufacturing firms in enhancing competitive strength. Despite of large investments in the SCM systems, many companies are not fully realizing the promised benefits from the systems. A review of literature on adoption, implementation and success factor of IOS (inter-organization systems), EDI (electronic data interchange) systems, shows that this issue has been examined from multiple theoretic perspectives. And many researchers have attempted to identify the factors which influence the success of system implementation. However, the existing studies have two drawbacks in revealing the determinants of systems implementation success. First, previous researches raise questions as to the appropriateness of research subjects selected. Most SCM systems are operating in the form of private industrial networks, where the participants of the systems consist of two distinct groups: focus companies and vendors. The focus companies are the primary actors in developing and operating the systems, while vendors are passive participants which are connected to the system in order to supply raw materials and parts to the focus companies. Under the circumstance, there are three ways in selecting the research subjects; focus companies only, vendors only, or two parties grouped together. It is hard to find researches that use the focus companies exclusively as the subjects probably due to the insufficient sample size for statistic analysis. Most researches have been conducted using the data collected from both groups. We argue that the SCM success factors cannot be correctly indentified in this case. The focus companies and the vendors are in different positions in many areas regarding the system implementation: firm size, managerial resources, bargaining power, organizational maturity, and etc. There are no obvious reasons to believe that the success factors of the two groups are identical. Grouping the two groups also raises questions on measuring the system success. The benefits from utilizing the systems may not be commonly distributed to the two groups. One group's benefits might be realized at the expenses of the other group considering the situation where vendors participating in SCM systems are under continuous pressures from the focus companies with respect to prices, quality, and delivery time. Therefore, by combining the system outcomes of both groups we cannot measure the system benefits obtained by each group correctly. Second, the measures of system success adopted in the previous researches have shortcoming in measuring the SCM success. User satisfaction, system utilization, and user attitudes toward the systems are most commonly used success measures in the existing studies. These measures have been developed as proxy variables in the studies of decision support systems (DSS) where the contribution of the systems to the organization performance is very difficult to measure. Unlike the DSS, the SCM systems have more specific goals, such as cost saving, inventory reduction, quality improvement, rapid time, and higher customer service. We maintain that more specific measures can be developed instead of proxy variables in order to measure the system benefits correctly. The purpose of this study is to find the determinants of SCM systems success in the perspective of vendor companies. In developing the research model, we have focused on selecting the success factors appropriate for the vendors through reviewing past researches and on developing more accurate success measures. The variables can be classified into following: technological, organizational, and environmental factors on the basis of TOE (Technology-Organization-Environment) framework. The model consists of three independent variables (competition intensity, top management support, and information system maturity), one mediating variable (collaboration), one moderating variable (government support), and a dependent variable (system success). The systems success measures have been developed to reflect the operational benefits of the SCM systems; improvement in planning and analysis capabilities, faster throughput, cost reduction, task integration, and improved product and customer service. The model has been validated using the survey data collected from 122 vendors participating in the SCM systems in Korea. To test for mediation, one should estimate the hierarchical regression analysis on the collaboration. And moderating effect analysis should estimate the moderated multiple regression, examines the effect of the government support. The result shows that information system maturity and top management support are the most important determinants of SCM system success. Supply chain technologies that standardize data formats and enhance information sharing may be adopted by supply chain leader organization because of the influence of focal company in the private industrial networks in order to streamline transactions and improve inter-organization communication. Specially, the need to develop and sustain an information system maturity will provide the focus and purpose to successfully overcome information system obstacles and resistance to innovation diffusion within the supply chain network organization. The support of top management will help focus efforts toward the realization of inter-organizational benefits and lend credibility to functional managers responsible for its implementation. The active involvement, vision, and direction of high level executives provide the impetus needed to sustain the implementation of SCM. The quality of collaboration relationships also is positively related to outcome variable. Collaboration variable is found to have a mediation effect between on influencing factors and implementation success. Higher levels of inter-organizational collaboration behaviors such as shared planning and flexibility in coordinating activities were found to be strongly linked to the vendors trust in the supply chain network. Government support moderates the effect of the IS maturity, competitive intensity, top management support on collaboration and implementation success of SCM. In general, the vendor companies face substantially greater risks in SCM implementation than the larger companies do because of severe constraints on financial and human resources and limited education on SCM systems. Besides resources, Vendors generally lack computer experience and do not have sufficient internal SCM expertise. For these reasons, government supports may establish requirements for firms doing business with the government or provide incentives to adopt, implementation SCM or practices. Government support provides significant improvements in implementation success of SCM when IS maturity, competitive intensity, top management support and collaboration are low. The environmental characteristic of competition intensity has no direct effect on vendor perspective of SCM system success. But, vendors facing above average competition intensity will have a greater need for changing technology. This suggests that companies trying to implement SCM systems should set up compatible supply chain networks and a high-quality collaboration relationship for implementation and performance.

• Journal of Korean Academy of Nursing
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• v.4 no.2
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• pp.1-16
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• 1974

This Study involved the development of a survey form and the collection of data in an effort-to provide information which can be used in the improvement of nursing curricula. The data examined were the kinds courses currently being taught in the curricula of nursing education institutions throughout Korea, credits required for course completion, and year in-which courses are taken. For the purposes of this study, curricula were classified into college, nursing school and vocational school categories. Courses were directed into the 3 major categories of general education courses, supporting science courses and professional education course, and further subdirector as. follows: 1) General education (following the classification of Philip H. phoenix): a) Symbolics, b) Empirics, c) Aesthetics. 4) Synthetics, e) Ethics, f) Synoptic. 2) Supporting science: a) physical science, b) biological science, c) social science, d) behavioral science, e) Health science, f) Educations 3) Professional Education; a) basic courses, b) courses in each of the respective fields of nursing. Ⅰ. General Education aimed at developing the individual as a person and as a member of society is relatively strong in college curricula compared with the other two. a) Courses included in the category of symbolics included Korean language, English, German. Chines. Mathematics. Statics: Economics and Computer most college curricula included 20 credits. of courses in this sub-category, while nursing schools required 12 credits and vocational school 10 units. English ordinarily receives particularly heavy emphasis. b) Research methodology, Domestic affair and women & courtney was included under the category of empirics in the college curricula, nursing and vocational school do not offer this at all. c) Courses classified under aesthetics were physical education, drill, music, recreation and fine arts. Most college curricula had 4 credits in these areas, nursing school provided for 2 credits, and most vocational schools offered 10 units. d) Synoptic included leadership, interpersonal relationship, and communications, Most schools did not offer courses of this nature. e) The category of ethics included citizenship. 2 credits are provided in college curricula, while vocational schools require 4 units. Nursing schools do not offer these courses. f) Courses included under synoptic were Korean history, cultural history, philosophy, Logics, and religion. Most college curricular 5 credits in these areas, nursing schools 4 credits. and vocational schools 2 units. g) Only physical education was given every Year in college curricula and only English was given in nursing schools and vocational schools in every of the curriculum. Most of the other courses were given during the first year of the curriculum. Ⅱ. Supporting science courses are fundamental to the practice and application of nursing theory. a) Physical science course include physics, chemistry and natural science. most colleges and nursing schools provided for 2 credits of physical science courses in their curricula, while most vocational schools did not offer t me. b) Courses included under biological science were anatomy, physiologic, biology and biochemistry. Most college curricula provided for 15 credits of biological science, nursing schools for the most part provided for 11 credits, and most vocational schools provided for 8 units. c) Courses included under social science were sociology and anthropology. Most colleges provided for 1 credit in courses of this category, which most nursing schools provided for 2 creates Most vocational school did not provide courses of this type. d) Courses included under behavioral science were general and clinical psychology, developmental psychology. mental hygiene and guidance. Most schools did not provide for these courses. e) Courses included under health science included pharmacy and pharmacology, microbiology, pathology, nutrition and dietetics, parasitology, and Chinese medicine. Most college curricula provided for 11 credits, while most nursing schools provide for 12 credits, most part provided 20 units of medical courses. f) Courses included under education included educational psychology, principles of education, philosophy of education, history of education, social education, educational evaluation, educational curricula, class management, guidance techniques and school & community. Host college softer 3 credits in courses in this category, while nursing schools provide 8 credits and vocational schools provide for 6 units, 50% of the colleges prepare these students to qualify as regular teachers of the second level, while 91% of the nursing schools and 60% of the vocational schools prepare their of the vocational schools prepare their students to qualify as school nurse. g) The majority of colleges start supporting science courses in the first year and complete them by the second year. Nursing schools and vocational schools usually complete them in the first year. Ⅲ. Professional Education courses are designed to develop professional nursing knowledge, attitudes and skills in the students. a) Basic courses include social nursing, nursing ethics, history of nursing professional control, nursing administration, social medicine, social welfare, introductory nursing, advanced nursing, medical regulations, efficient nursing, nursing english and basic nursing, College curricula devoted 13 credits to these subjects, nursing schools 14 credits, and vocational schools 26 units indicating a severe difference in the scope of education provided. b) There was noticeable tendency for the colleges to take a unified approach to the branches of nursing. 60% of the schools had courses in public health nursing, 80% in pediatric nursing, 60% in obstetric nursing, 90% in psychiatric nursing and 80% in medical-surgical nursing. The greatest number of schools provided 48 crudites in all of these fields combined. in most of the nursing schools, 52 credits were provided for courses divided according to disease. in the vocational schools, unified courses are provided in public health nursing, child nursing, maternal nursing, psychiatric nursing and adult nursing. In addition, one unit is provided for one hour a week of practice. The total number of units provided in the greatest number of vocational schools is thus Ⅲ units double the number provided in nursing schools and colleges. c) In th leges, the second year is devoted mainly to basic nursing courses, while the third and fourth years are used for advanced nursing courses. In nursing schools and vocational schools, the first year deals primarily with basic nursing and the second and third years are used to cover advanced nursing courses. The study yielded the following conclusions. 1. Instructional goals should be established for each courses in line with the idea of nursing, and curriculum improvements should be made accordingly. 2. Course that fall under the synthetics category should be strengthened and ways should be sought to develop the ability to cooperate with those who work for human welfare and health. 3. The ability to solve problems on the basis of scientific principles and knowledge and understanding of man society should be fostered through a strengthening of courses dealing with physical sciences, social sciences and behavioral sciences and redistribution of courses emphasizing biological and health sciences. 4. There should be more balanced curricula with less emphasis on courses in the major There is a need to establish courses necessary for the individual nurse by doing away with courses centered around specific diseases and combining them in unified courses. In addition it is possible to develop skill in dealing with people by using the social setting in comprehensive training. The most efficient ratio of the study experience should be studied to provide more effective, interesting education Elective course should be initiated to insure a man flexible, responsive educational program. 5. The curriculum stipulated in the education law should be examined.

• Journal of Korean Academy of Nursing
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• v.20 no.2
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• pp.153-173
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• 1990

One of the important tasks for new parents. especially mothers, is to establish warm, mutually affirming interpersonal relationships with the new baby in the family, with the purpose of promoting the healthy development of the child and the wellbeing of the whole family. Nurses assess the quality of the behavioral characteristics of the maternal-infant interaction. This study examined the relationships between primiparas pereptions of their delivery experience and their maternal infant interaction. It compared to delivery experience of mothers having a normal vaginal delivery with those having a casearean section. The purpose was to explore the relationships between the mother's perceptions of her delivery experience with her maternal infant interaction. The aim was to contribute to the development of theoretical understanding on which to base care toward promoting the quality of maternal-infant interaction. Data were collected directly by the investigator and a trained associate from Dec. 1, 1987 to March 8, 1988. Subjects were 3 random sample of 62 mothers, 32 who had a normal vaginal delivery and 30 who had a non-elective cesarean section (but without other perinatal complications) at three general hospitals in Seoul. Instruments used were the Stainton Parent -infant Interaction Scale(1981) and the Marut and Mercer Perception of Birth Scale(1979). The first observations were made in the delivery room (for vaginally delivered mothers only), followed by day 1, day 2, day 3, and 2 weeks, 4 weeks, 6 weeks and 8 weeks after birth, for a total of 7-8 contacts(Cesarean section mothers were observed on days 4 and 5 but the data not used for analysis). Observations in the hospital were made during the hour prior to scheduled feedings. The infant was placed beside the mother. Later contacts were made at home. Data analysis was done by computer using as SPSS program and indulded X² test, paired t-test, t-test, and Pearson Correlation coefficient ; the results were as follows. 1. Mothers who had a normal vaginal delivery tended to perceive the delivery experience more positively than cesarean section mothers(p＝0.002). The finding supported the hypothesis I that perception of delivery would vary according to the method of delivery. Mothers' perceptions of birth were classified into three dimensions, labor, delivery and the bady. There was a significantly different and positive perception by the vaginally delivered mothers to the delivery experience(p＝0.000) but no differences for labor or the bady according to the delivery method(p＝0.096, p＝0.389), 2. Mothers who had a normal vaginal delivery had higher average maternal-infant interaction scores(p＝0.029) than mothers who had a cesarean section. There were similar higher scores for the 1st day(p＝0.042), 2nd day (p＝0.009), and the 3rd day(p＝0.006) after delivery but not for later times. The findings supported the hypothesis Ⅱ that there would be differences in maternal-infant interaction for mothers having vaginal and cesarean section deliveries. However these differences deccreased section deliveries. However these differences decreased over time . by eight weeks the scores for vaginal delivery mothers averaged 8.1 and for cesarean section mothers, 7.9. 3. The more highly positive the pereption of the delivery experience, the higher the maternal-infant interaction score for all subjects(F＝.3206, p＝.006). The findings supported the hypothesis Ⅲ that there would be correlations between perceptions of delivery and maternal-infant interaction. The maternal infant interaction was highest when the perception of the bady and deliery was positive(r＝.4363, p＝.000, r＝.2881, p＝.012). No correlations between perceptions of labor and maternal-infant interaction were found(p＝0.062). 4. The daily maternal-infant interaction score for the initial contact after birth to 8 weeks postpartum had the lowest average score 5.20 and the highest 7.98(in a range of 0-10). This subjects group of mothers needed nursing intervention to promote their maternal- infant interaction. The daily scores for the maternal-infant over the period of eight weeks. However, there were significantly different increases in maternal-infant interaction only from the first to second day(p＝0.000) and from the fourth to sixth weeks after birth(P＝0.000). 5. When the eight items of maternal-infant interaction were evaluated separately, “Expresses feelings about her role as mother” had the highest average score, 1.64(ina range of 0-3)and “Speaks to baby” the lowest, 0.9. All items, with the possible exception of “Expresses feelings about her role as mother”, suggested the subjects' need of nursing intervention to promote maternal-infant interaction. 6. There were positive correlations between certain general charateristis, namely, both a higher economic status(p＝0.002) and breast feeding(p＝0.202) and maternal - infant interaction. There were positive correlations between a mother's confidence in her role as a mother and the perception of the birth experience(p＝0.004). For mothers who had a cesarean section, a positive perception of the birth experience was related to the duration of her marriage(p＝0.010), a wanted pregnancy (P＝0.030) and her confidence in her role as a mother(p＝0.000). Pereptions of birth for mothers who had a normal vaginal delivery were positive than those for mothers who had a cesarean section. The level of maternalinfant interaction for mothers delivered vaginally was higher than for cesarean section mothers. The relationship between perception of birth and materanalinfant interaction was confirmed. Cesarean section has an impact on the mother's perceived experience of birth which, in turn, is positively related to maternal-infant in turn, is positively related to maternal-infant interaction. Nursing intervention to enhance maternal-infant interaction should begin in prenatal classes with an exploration of the potential impact of cesarean section on the perceptions of the birth experience and continue throughout the perinatal and post-natal periods to promote the mother's ability to control with this crisis experience and to mobilize social support. Nursing should help transform a relatively negatively perceived experience into an accepted, positively perceived and self affirming experience which enhances the maternal-infant relationship.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.191-207
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• 2021

Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.