• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.797-808
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• 2012

In smart work environment, a company provides employees a flexible work environment for tele-working using mobile phone or portable devices. On the other hand, such environment are exposed to the risks which the attacker can intrude into computer systems or leak personal information of smart-workers' and gain a company's sensitive information. To reduce these risks, the security administrator needs to analyze the usage patterns of employees and detect abnormal behaviors by monitoring VPN(Virtual Private Network) access log. This paper proposes a decision support system that can notify the status by using visualization and similarity measure through clustering analysis. On average, 88.7% of abnormal event can be detected by this proposed method. With this proposed system, the security administrator can detect abnormal behaviors of the employees and prevent account theft.

• IE interfaces
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• v.10 no.1
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• pp.209-222
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• 1997

The paper provides a methodology to obtain the automaticity indicator of a factory and the sequence of enabling technologies of factory automation. The automaticity indicator is the measure of the current automation status of a factory and can be used as a crucial criteria for the future automation schedule and investment. Although most industries have their own computation methods which usually consider the number of workers in the shop floor, this research covers five evaluation items of automation, such as, production facility, material transfer system, inspection and test system, information system, and flexibility. The detailed evaluation models are developed for each item. Automation sequencing prioritizes the enabling technologies of factory automation on the basis of several criteria which consist of two phases. The first phase includes the automation indicator and the second phase includes six sub-criteria such as production rate, quality, number of workers, capital investment, development duration, development difficulty. For this evaluation, AHP(Analytical Hierarchy Process) is introduced to prevent the decision maker's subject intention. As results of the automaticity indicator and automation sequence, the manager can save time and cost in building constructive and transparent automation plans.

• Journal of Chest Surgery
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• v.53 no.6
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• pp.392-399
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• 2020

Background: Surgical treatment of empyema thoracis in patients with chronic kidney disease is challenging, and few studies in the literature have evaluated this issue. In this study, we aim to report the surgical outcomes of empyema and to analyze factors predicting perioperative mortality in patients with chronic kidney disease. Methods: This retrospective study included data from 34 patients with chronic kidney disease (estimated glomerular filtration rate <60 mL/min/1.73 ㎡ for 3 or more months) who underwent surgery for empyema between 2012 and 2020. An analysis of demographic characteristics and perioperative variables, including complications, was carried out. Postoperative mortality was the primary outcome measure. Results: Patients' age ranged from 20 to 74 years with a 29-to-5 male-female ratio. The majority (n=19, 55.9%) of patients were in end-stage renal disease (ESRD) requiring maintenance hemodialysis. The mean operative time was 304 minutes and the mean intraoperative blood loss was 562 mL. Postoperative morbidity was observed in 70.5% of patients (n=24). In the subgroup analysis, higher values for operative time, blood loss, intensive care unit stay, and complications were found in ESRD patients. The mortality rate was 38.2% (n=13). In the univariate and multivariate analyses, poor performance status (Eastern Cooperative Oncology Group >2) (p=0.03), ESRD (p=0.02), and late referral (>8 weeks) (p<0.001) significantly affected mortality. Conclusion: ESRD, late referral, and poor functional status were poor prognostic factors predicting postoperative mortality. The decision of surgery should be cautiously assessed given the very high risk of perioperative morbidity and mortality in these patients.

• Journal of Korean Academy of Nursing Administration
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• v.1 no.1
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• pp.5-21
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• 1995

This study purports to investigate moral reasoning and ethical decision making among student nurses in the hypothetical moral dilemmas. The subjects consisted of 25 senior nursing students attending at a four-year college. Data were collected through self-reported questionnaires in November, 1993. The questionnaires included two kinds of tests. Rest's Defining Issues Test was adopted to measure the stage of moral development, which was classified with the stage 2 (instrumental relativist orientation), the stage 3 (interpersonal concordance), the stage 4 (law and order), the stage 5A (societal consensus), and the stage 5B (intuitional humanism). In particular, the level of principled thinking (P) was measured by summing those scores of the stages 5A, 5B, and 6. The possible range of P is 0 to 95. As for measuring the levels of morality and nursing dilemma, Crisham's Nursing Dilemma Test was adopted. This test generated the morality score(MS) and the dilemma score (DS). The data were analyzed by t-test, ANOVA, Kruskal-Wallis test, and Pearson correlation coefficients. The findings are following. 1. The mean score of P was 52.93 (SD=12.82). The mean score of the stage 5A was significantly higher than the scores of other stages (17.92, p=.0001). 2. The mean score of P was not significantly different by general characteristics of the students. Of the scores of each stage, only the mean score of the stage 3 revealed significant difference by the status of living with parents(p=.0283). The score was highest when "living with both parents"(15.22), which was followed by "living with no parents"(10.0), "living with father only"(9.0), and "living with mother only"(7.50). 3. With regard to the five dilemmas postulated such as forcing medication, performing cardiac pulmonary resuscitation, reporting a medication error, informing diagnosis to terminally ill adult, and providing new-nurse orientation, most students perceived them as moral dilemma rather than nonmoral one. Most students made a positive decision according to moral reasoning in the above situations except for providing new-nurse orientation. 4. The mean score of the MS was 3.30 and that of the DS was 3.32. These scores did not show significant difference with general characteristics of the students. 5. As for the correlations between moral reasoning and decision making, the score of the stage 5A was positively correlated with the scores of P(.74, p<.0001) and DS(.56, p<.001). Positive correlation was also observed between the scores of stage 2 and stage 4(.68, p<.0001). On the other hand, the score of P was negatively correlated with the scores of stage 3(-.47, p<.05) and of stage 4(-.55, p<.001). The score of the stage 5A was also negatively correlated with the score of the stage 6(-.42, p<.05).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.6
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• pp.689-698
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• 2009

SOLAP system integrates and complements the functions of both OLAP and GIS systems. This enables users not only to easily access geospatial data but also to analyze and extract information for decision making. In this study a SOLAP system was designed and implemented to provide urban planners with GIS information when making urban planning decisions. Rapid urbanization in Korea has brought about ill-balanced urban structure as the result of development without detailed analysis of urban plans. Systematic urban planning procedures and automated systems are crucial for detail analysis of future development plans. Data regarding the development regulations and current status of land use need to be assessed precisely and instantly. Multi-dimensional aspects of a suggested plan must be formulated instantly and examined thoroughly using 'what if' scenarios to come up with a best possible plan. The SOLAP system presented in this study designed the dimension tables and the fact tables for supplying timely geospatial information to the planners when making decisions regarding urban planning. The database was implemented using open source DBMS and was populated with necessary attribute data which was freely available from the Statistics Korea bureau homepage. It is anticipated the SOLAP system presented in this study will contribute to better urban planning decisions in Korea through more timely and accurate provision of geospatial information.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2587-2592
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• 2012

Background: Limited human papillomavirus (HPV) related knowledge might be a barrier to future vaccine acceptance. From 2008-2010, PATH conducted an HPV vaccination demonstration project in partnership with the government immunization program in Vietnam, which included awareness campaigns prior to vaccination. Objective: To assess and compare knowledge and attitudes about cervical cancer and HPV vaccines between mothers and daughters, and whether knowledge was associated with vaccination status. Methods: We analyzed HPV-related knowledge and attitude data from mother-daughter paired responses to a cross-sectional household survey. After parents completed the survey, daughters were asked the same questions. We calculated the frequency of responses for each question and devised a scaled composite measure for knowledge. Results: Participants believed they had received enough information about cervical cancer and HPV vaccines and it was sufficient to make a decision about vaccination. Fifty percent of the participants knew HPV causes cervical cancer and 80% knew the HPV vaccine prevented cervical cancer. Mothers had more knowledge about cervical cancer and HPV infection (p<0.01), compared to daughters, who had more vaccine specific knowledge (p<0.01). However, the total mean knowledge score was similar for the groups. Girls not fully vaccinated had a lower mean knowledge score than fully vaccinated girls (p<0.001). Conclusions: Our results suggest that the purpose of the HPV vaccine was clearly messaged; however, some misconceptions about cervical cancer and HPV still exist. Limited knowledge about the magnitude of cervical cancer, HPV as a cause of cervical cancer, and HPV vaccines may have contributed to incomplete vaccination.

• 한국노년학
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• v.30 no.1
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• pp.81-91
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• 2010

The purpose of this study was to test a validity and reliability of Cognitive Performance Scale(CPS), a cognitive measure generated from 5 items(comatose status, decision making, short-term memory, making self understood, and eating). Method: 393 patients in 2 hospitals for the elderly with dementia were measured with CPS by two nurses independently. The inter-rater agreement was tested by comparing two scores. The CPS score was compared with GDS, which was measured by doctors and nurses, and MMSE score which was drawn from the claim data of Health Insurance Review & Assessment Service. Result: The correlation coefficient between CPS and GDS was 0.742(p<0.0001), CPS and MMSE was -0.794(p<0.0001). The Cronbach's coefficient alpha of CPS was 0.742, Kappa value was 0.772~1.000. The CPS showed high validity and reliability in long term care hospitals of Korea.

• Journal of Distribution Science
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• v.13 no.11
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• pp.69-77
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• 2015

Purpose - Economic status at an early stage of life after one's retirement is often determined by the long-term sacrifice of one's earlier consumption tendencies. In general, the first and foremost way to secure income after retirement is through annuity savings. People sign up for personal annuity savings in order to guarantee a stable economic life upon retirement, and such actions may be heavily influenced by self-efficacy. Confidence in current economic activity is a source of rational decision-making. Inability to achieve self-control can lead to reckless spending and the eventual hindering of proper investment for the future. This paper examines how self-efficacy and self-control affect the intention and action of enrolling in an annuity savings plan in relation to one's level of financial literacy. Research design, data, and methodology - To analyze the proposed model, this study investigates financial consumers over the age of 20. The data were collected from 511 respondents and analyzed with SPSS 21.0 and AMOS 21.0. First, for the one-dimensional test and to measure the convergent validity of each structure, we use the scale purification process. The results of the test and the confirmatory factor analysis ensure the focus of the validity of the single dimension for each structure. In addition, the validity of the measurement was guaranteed from the results of correlation analysis. Results - First, self-efficacy and self-control have positive effects on the purchasing intention of the personal annuity savings plan. Second, purchasing intention positively affects purchasing behavior. Lastly, self-control has a positive effect on purchasing intention among the low financial literacy group, whereas self-efficacy does not have this effect in the high financial literacy one. Conclusions - The time of product benefit is different with age. The younger group would be granted the savings after several decades once they enroll, whereas the older group would wait for a relatively shorter period of time. Therefore, further research should be conducted in order to verify such a difference. However, this study has value through its confirmation that the roles of self-efficacy and self-control play a part in leading to the enrollment in annuity savings plans and by verifying different effects based on levels of financial literacy. Such results suggest a number of implications in a real life setting. First, banks need to put greater emphasis on the stability of annuity savings in general. Second, customers with relatively low levels of financial literacy are able to control their finances through annuity savings, but find self-efficacy difficult due to a lack of financial understanding. Therefore, such customers should be approached from an invest-effectiveness comparison method. Third, customers with high financial literacy tend to put more value in rational economic decision-making and behavior than in self-efficacy. Therefore, such customers should be approached by promoting the reliability of annuity savings and the excellence of the specific bank's annuity savings plan in comparison to those of other financial institutions.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.99-104
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• 2021

In this paper, we propose health risk management using feature extraction and cluster analysis considering time flow. The proposed method proceeds in three steps. The first is the pre-processing and feature extraction step. It collects user's lifelog using a wearable device, removes incomplete data, errors, noise, and contradictory data, and processes missing values. Then, for feature extraction, important variables are selected through principal component analysis, and data similar to the relationship between the data are classified through correlation coefficient and covariance. In order to analyze the features extracted from the lifelog, dynamic clustering is performed through the K-means algorithm in consideration of the passage of time. The new data is clustered through the similarity distance measurement method based on the increment of the sum of squared errors. Next is to extract information about the cluster by considering the passage of time. Therefore, using the health decision-making system through feature clusters, risks able to managed through factors such as physical characteristics, lifestyle habits, disease status, health care event occurrence risk, and predictability. The performance evaluation compares the proposed method using Precision, Recall, and F-measure with the fuzzy and kernel-based clustering. As a result of the evaluation, the proposed method is excellently evaluated. Therefore, through the proposed method, it is possible to accurately predict and appropriately manage the user's potential health risk by using the similarity with the patient.