• Journal of Preventive Medicine and Public Health
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• v.52 no.1
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• pp.1-13
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• 2019

Objectives: In recent years, serious concerns have been raised regarding the impacts of rising temperatures on health. The present study was conducted to investigate the relationship between elevated temperatures and kidney disease through a systematic review and meta-analysis. Methods: In October 2017, 2 researchers independently searched related studies in PubMed and Embase. A meta-analysis was conducted using a random-effects model, including only studies that presented odds ratios, relative risks, or percentage changes, along with 95% confidence intervals (CIs). The characteristics of each study were summarized, and the Egger test and funnel plots were used to evaluate publication bias. Results: Eleven studies that met the criteria were included in the final analysis. The pooled results suggest an increase of 30% (95% CI, 20 to 40) in kidney disease morbidity with high temperatures. In a disease-specific subgroup analysis, statistically significant results were observed for both renal colic or kidney stones and other renal diseases. In a study design-specific subgroup analysis, statistically significant results were observed in both time-series analyses and studies with other designs. In a temperature measure-specific subgroup analysis, significant results were likewise found for both studies using mean temperature measurements and studies measuring heat waves or heat stress. Conclusions: Our results indicate that morbidity due to kidney disease increases at high temperatures. We also found significant results in subgroup analyses. However, further time-series analyses are needed to obtain more generalizable evidence.

• Korean Management Science Review
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• v.22 no.1
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• pp.179-197
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• 2005

This study examines market acceptance for DMB service, one of the touted new business models in Korea's next-generation mobile communications service market, using adoption end diffusion of innovation as the theoretical framework. Market acceptance for DMB service was assessed by predicting the demand for the service using the Bass model, and the demand variability over time was then analyzed by integrating the innovation adoption model proposed by Rogers (2003). In our estimation of the Bass model, we derived the coefficient of innovation and coefficient of imitation, using actual diffusion data from the mobile telephone service market. The maximum number of subscribers was estimated based on the result of a survey on satellite DMB service. Furthermore, to test the difference in diffusion pattern between mobile phone service and satellite DMB service, we reorganized the demand data along the diffusion timeline according to Rogers' innovation adoption model, using the responses by survey subjects concerning their respective projected time of adoption. The comparison of the two demand prediction models revealed that diffusion for both took place forming a classical S-curve. Concerning variability in demand for DMB service, our findings, much in agreement with Rogers' view, indicated that demand was highly variable over time and depending on the adopter group. In distinguishing adopters into different groups by time of adoption of innovation, we found that income and lifestyle (opinion leadership, novelty seeking tendency and independent decision-making) were variables with measurable impact. Among the managerial variables, price of reception device, contents type, subscription fees were the variables resulting in statistically significant differences. This study, as an attempt to measure the market acceptance for satellite DMB service, a leading next-generation mobile communications service product, stands out from related studies in that it estimates the nature and level of acceptance for specific customer categories, using theories of innovation adoption and diffusion and based on the result of a survey conducted through one-to-one interviews. The authors of this paper believe that the theoretical framework elaborated in this study and its findings can be fruitfully reused in future attempts to predict demand for new mobile communications service products.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.85-92
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• 2019

Companies can identify user groups or consumption trends by collecting and analyzing opinions of many users on special subjects or their products as well as utilize them as various purposes such as predicting some specific trends or marketing strategies. Therefore current analyzing tools of social media have come into use as a means to measure the performances of social media marketing through network's statistical analysis. However these tools require expensive computing and network resources including burden of costs for building up and operating complex software platforms and much operating know-how. Hence, small companies or private business operators have difficulty in utilizing those social media data effectively. This paper proposes a framework applied into developing analysis system of social media. The framework could be set up and operate the system to extract necessary social media's data. Also to design the system, this study suggests a meta-model of proposed framework and to guarantee completeness and consistency, a formal specification of meta-model by using Z language is suggested. Finally, we could verify the clearness of framework's design by performing Z model checking of formal specification's output through Z-EVES tool.

• Korea Journal of Hospital Management
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• v.23 no.4
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• pp.40-52
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• 2018

The purpose of this study is to identify medical consumers' hospital selection factors in response to the rapidly changing environment of medical industry. For that purpose this study classified consumers' hospital selection factors into three categories such that human factors including expertise, reliability, empathy; system factor including, convenience, differentiation, efficiency; and facility factor including tangibility, accessibility, and location, based on the previous studies and the results of a preliminary survey of the patients of a small private hospital. The nine factors were further divided into 23 more specific attributes. Then, an online survey was conducted to measure the perceptions of the 23 attributes by the medical consumers over the age of 20. The analysis of the survey data using Kano model and Timko model indicated that 14 of the 23 attributes were classified as attractive factors, eight attributes were or classified as, one-dimensional factors, and one attribute, doctors' educational background, was classified as indifference factor. Of the 14 attractive factors, "unique and differentiated services related to medical treatment" and "distance from home to hospital" had the highest customer satisfaction coefficients. Of the eight one-dimensional factors, "kind treatment," "providing adequate explanations," "accuracy of diagnosis," and "cleanness of facilities" had the highest customer satisfaction coefficients as well as the highest dissatisfaction coefficients. The findings indicate that these six attributes are the most basic and most impactful attributes that hospitals must manage strategically to improve their service quality and attract more medical consumers to their hospitals.

• Journal of Korean Academy of Nursing
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• v.26 no.4
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• pp.946-962
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• 1996

The purpose of this study was to contribute to the development of clinical instruction by students' ratings of teaching effectiveness in clinical nursing education. The subjects were comprised of graduating class 618 students from 24 nursing colleges in the nation. The instruments used in this study were "general characteristics & status of clinical nursing education" developed by the researcher and "Instrument to Measure Effectiveness of Clinical Instructors" by Reeve(1994). The 50 questions used in the questionaire were categorized into 13 components subject to factor analysis. The 13 components were interpersonal relationships, communication skills, role model, resource for students, favorable to students, encouraging to think for selves, teaching methods, evaluation, finding assignments for objectives, organization of subject matter, professional competence, knowledge of subject matter & working with agency personnel. The results of this study are as follows 1. Status of clinical nursing educaion : 1) Clinical nursing education were led by nursing professors(44.9%), a team of both nuring professor & head nurse(6.8%), instructors from specific hospital(15.1%), instuctos for a specific subject(14.6%), & head nurse(6.8%). For 3-year program students, 34.6% of the clinical nursing education were led by instructors from specific hospital & 51.4% of the education by nursing professors for Bachelor's program. 2) The contents for clinical education comprised of Conference being the most frequent of 34.5% ; a combination of Nursing skills, Orientation, Conference etc.22.0% : Nursing process 21.7% : Orientation 13.5% : Inspection(making rounds ) 6.4%, & Nursing skills of 2% being the least frequent. 3) Students' preference of clinical teachers from the highest to the lowest were instructors for a specific subject being the most desired (44.9%) followed by nursing professor, head nurse, a team of both nursing professor & head nurse, & instructors from specific hospital being the least desired. 4) Students felt that the qualification for clinical teachers should be at least a master's degree holder and 5 or more years of clinical experience. The reason they felt was because knowledge & experience are imperative for professional education. 2. Clinical teaching effectiveness : The total points for teaching effectiveness was 147.97(mean of 2.95±0.98) where the total score is considered to be an average rating. 3. Teaching effectiveness as status of clinical nursing education : 1) The score ratings for the clinical instructors from the highest to the lowest were as follows : instructors for a specific subject, instructors from specific hospitals, a team of both nursing professors & head nurses, nursing professors, head nurses, which resulted in significunt difference(F=4.53, P<0.001). 2) The rating scores based on the teaching program from the highest to the lowest were as follws ; nursing skills, nursing process, a combination of nursing skills, orientation, conference etc. , conferences, orientation, inspection, which resulted in significunt difference(F=10.97, P<0.001). 4. Based on 13 categorized components from the questionaires, questions related to communication skills scored the highest points of 3.20 where inquiries regarding resource for students scored the lowest points of 2.38. 5. Among the 13 categorial components from the questionaire, Interpersonal relationship, Communication skills, Resource for students, Encouraging to think for selves, Evaluation, Teaching method, Finding assignment for objectives, Organization of subject matter, Professional competence, & Working with agency personnel, instructors for a specific subject scored the highest points and head nurse scored the lowest, which resulted in significant difference. Favorable for students, instructors for a specific subject scored highest points and nursing professor scored the lowest, which resulted in significant deference (F=5.39, P<0.001). Role model & Professional competence, instructors for a specific subject scored the highest points and head nurse scored the lowest, with minimum variation(F=1.29, P>0.05 : F=1.64, P>0.05) 6. Based on 13 categorial components as a whole, the highest points scored among the 5 groups of clinical teachers was instructors for a specific subject and the lowest, by head nurse(F=1.94, P<0. 001). A team of both nursing professor & head nurse attained higher score in clinical education than their independent education.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.187-203
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• 2022

As the economic, social, and environmental problems of the local community reach a serious level, our society is realizing the need to foster young talents who discover opportunities in local issues through entrepreneurship education and create social values through creative challenges. However, entrepreneurship education programs are generally focused on commerciality, so customized education programs to solve regional problems are insufficient. Therefore, this study aimed to develop a community problem-solving entrepreneurship curriculum. In this study, a competency based curriculum model was applied to develop the curriculum, and regional problem-solving entrepreneurship competencies were derived through expert advice from a total of 10 people. In the process, the Delphi methodology was additionally used to reduce the possibility of errors in the competency model. As a result of the study, a total of 23 regional problem-solving entrepreneurship competencies were confirmed, and knowledge(K) - skill(S) - attitude(A) by competency consisted of 5, 9, and 9, respectively. By applying this to Dunham's problem-solving six-step model, modular learning support measures were developed in the order of phase 1(problem discovery), phase 2(problem analysis), phase 3(plan), phase 4(measure), and phase 5(evaluation). This study is meaningful in that it integrated theory and practice by developing specific entrepreneurship curriculum and learning support measures based on the theoretical model devised in social welfare. In addition, it has implications in that it developed a regional problem-solving entrepreneurship competency model based on expert advice and proposed a specific curriculum based on this.

• Spatial Information Research
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• v.20 no.4
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• pp.47-55
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• 2012

Normalized Difference Vegetation Index (NDVI) has been used to measure and monitor plant growth, vegetation cover, and biomass from multispectral satellite data. It is also a valuable index in forest applications, providing forest resource information. In this research, an approach for monitoring forest change using MODIS NDVI time series data is explored. NDVI difference-based approaches for a specific point in time have possible accuracy problems and are lacking in monitoring long-term forest cover change. It means that a multi-time NDVI pattern change needs to be considered. In this study, an efficient methodology to consider long-term NDVI pattern is suggested using a harmonic model. The suggested method reconstructs MODIS NDVI time series data through application of the harmonic model, which corrects missing and erroneous data. Then NDVI pattern is analyzed based on estimated values of the harmonic model. The suggested method was applied to 49 NDVI time series data from Aug. 21, 2009 to Sep. 6, 2011 and its usefulness was shown through an experiment.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.277-285
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• 2004

We present a new hybrid stereo matching technique in terms of the co-operation of area-based stereo and feature-based stereo. The core of our technique is that feature matching is carried out by the reference of the disparity evaluated by area-based stereo. Since the reference of the disparity can significantly reduce the number of feature matching combinations, feature matching error can be drastically minimized. One requirement of the disparity to be referenced is that it should be reliable to be used in feature matching. To measure the reliability of the disparity, in this paper, we employ the self-consistency of the disunity Our suggested technique is applied to the detection of 3D line segments by 2D line matching using our hybrid stereo matching, which can be efficiently utilized in the generation of the rooftop model from urban imagery. We carry out the experiments on our hybrid stereo matching scheme. We generate synthetic images by photo-realistic simulation on Avenches data set of Ascona aerial images. Experimental results indicate that the extracted 3D line segments have an average error of 0.5m and verify our proposed scheme. In order to apply our method to the generation of 3D model in urban imagery, we carry out Preliminary experiments for rooftop generation. Since occlusions are occurred around the outlines of buildings, we experimentally suggested multi-image hybrid stereo system, based on the fusion of 3D line segments. In terms of the simple domain-specific 3D grouping scheme, we notice that an accurate 3D rooftop model can be generated. In this context, we expect that an extended 3D grouping scheme using our hybrid technique can be efficiently applied to the construction of 3D models with more general types of building rooftops.

• Journal of Environmental Science International
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• v.18 no.12
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• pp.1417-1426
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• 2009

As the damages due to natural disasters continue to increase, a growing interest is being witnessed in such studies that focus on preventive measures to reduce damages rather than on their recovery. As such, the U.S. has been actively conducting projects to develop new models that can forecast potential damages due to natural disasters and widely employing them in actual cases. With no specific models developed in Korea yet, this study aimed to introduce an overseas typhoon model as part of the advanced efforts and apply it the actual cases occurring across the nation. This model estimates wind loads by measuring the impact of a strong wind upon buildings, and measurements require a number of parameters. Those parameters should include the types and dimensions of buildings and the type of the roofs. As for the FPHLM(Florida Public Hurricane Loss Model), a precedent model for our study, we were able to take advantage of number of the statistics and detailed categorizations on the residential buildings in the U.S., which enabled us to select the representative building types and produce their wind loads. With no sufficient relevant statistics available for the nation, however, we may not be able to readily measure the wind loads on the nation's residential buildings. Therefore, this study tried to choose the representative types, heights and dimensions of the buildings for the measurement of wind loads. We consequently came up with a representative house having an area between 62.81 and $95.56m^2$, either a flat roof or hip roof, a height of 2.6 m, an side ratio of 1.5, and the width and length of the mean $85m^2$ sized house being 11,300 mm and 7,530 mm, respectively.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.40-51
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• 2012

Online discussion bulletin in Korea is not only a specific place where user exchange opinions but also a public sphere through which users discuss and form public opinion. Sometimes, there is a heated debate on a topic and any article becomes a political or sociological issue. In this paper, we propose how to analyze the popularity of articles by collecting the information of articles obtained from two well-known discussion forums such as AGORA and SEOPRISE. And we propose a prediction model for the article popularity by applying the characteristics of subject articles. Our experiment shown that the popularity of 87.52% articles have been saturated within a day after the submission in AGORA, but the popularity of 39% articles is growing after 4 days passed in SEOPRISE. And we observed that there is a low correlation between the period of popularity and the hit count. The steady increase of the hit count of an article does not necessarily imply the final hit count of the article at the saturation point is so high. In this paper, we newly propose a new prediction model called 'baseline'. We evaluated the predictability for popular articles using three models (SVM, similar matching and baseline). Through the results of performance evaluation, we observed that SVM model is the best in F-measure and precision, but baseline is the best in running time.