• 한국정보시스템학회지:정보시스템연구
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• 제23권1호
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• pp.161-184
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• 2014

Our study measures the Digital Life Index (DLI) of baby boomers by considering the utilization of digital devices in their everyday life. The study was conducted by implementing the following three-step approach: (1) development of survey questions and data collection; (2) build Digital Life Index (DLI) model and lastly; (3) empirical analysis using the Digital Life Index (DLI). In the first stage in order to develop the survey questions to measure the digital index, two surveys were conducted. For the first preliminary survey, it was done based on the existing literatures which enabled this investigation through FGI analysis involving real professionals. The second survey was conducted by commissioning a specialized external firm. In this survey, a total of 400 data was collected to verify the validity and objectivity of the data sample. The data gathered through the survey questions was used to develop the digital index. Firstly, the appropriate factors were extracted by conducting factor analysis. This factor analysis validates and verifies the factors which are appropriate in measuring Digital Life Index (DLI). The derived factors are broadly divided into five main factors. The first factor describes the possession, purchase and use of digital device (x1). Meanwhile, the second factor describes the digital device's software (x2) and the third factor describes the participation in utilizing digital device (x3). The fourth factor describes the utilization of digital device in human personal relationship (x4) and lastly, the fifth factor describes the effect of digital device in everyday life and work environment (x5). Secondly, the digital index model was developed. The variables to represent the Digital Life Index (DLI) are ${\chi}1t,{\chi}2t,{\chi}3t,{\chi}4t$ and ${\chi}5t$. Furthermore, as experience in using the digital index grows overtime, the growth can be represented by the "S" shape. Based on the results, Digital Life Index(DLI) is distributed with the highest point at 90.3 and the lowest point at 25.9.

• Journal of Preventive Medicine and Public Health
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• 제55권5호
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• pp.444-454
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• 2022

Objectives: We aimed to identify the factors related to depression and quality of life in patients with hypertension by using multilevel regression analysis. Methods: In 2019, 229 043 participants in the Korean Community Health Survey were selected as the study group. Individual factors were identified using data from the 2019 Community Health Survey. Regional factors were identified using data from the National Statistical Office of Korea. Multilevel regression analysis was conducted to find individual and local factors affecting depression and quality of life in patients with hypertension and to determine any associated interactions. Results: As individual factors in patients with hypertension, women, those with lower education-levels, recipients of basic livelihood benefits, and those with poor dietary conditions showed stronger associations with depression and quality of life. As regional factors and individual-level variables in patients with hypertension, lower gross regional personal income, fewer doctors at medical institutions, and lower rates of participation in volunteer activities presented stronger associations with depression and quality of life. In addition, the associations of depression with gross regional personal income, the number of doctors at medical institutions, and dietary conditions were significantly stronger in patients with hypertension than in patients without hypertension. The associations of gender and employment status with quality of life were also significantly greater. Conclusions: Policy interventions are needed to adjust health behaviors, prevent depression, and improve quality of life for patients with hypertension, especially for those with the risk factors identified in this study.

• Journal of the Korean Data and Information Science Society
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• 제16권2호
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• pp.237-253
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• 2005

In Korea, the volume of insurance industry has been increased rapidly with helping the economic growth, the increment of GNP and derive of public welfare policy. But the other side of the volume increment, the life insurers have some problems, such as the high rate of turnover, lapses and surrenders, in processing of acquiring more insurance contracts. The object of this paper is the analysis of the causes and properties of the high rate of turnover, lapses and surrenders using statistical survival model. Also we hope that the insurers will use the results of analysis to reduce the rates.

• 지식경영연구
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• 제8권1호
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• pp.49-63
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• 2007

This paper presents a new methodology that allows the influence of technological obsolescence and technology composite competitiveness to estimate technology economic life. In this paper the patent citation life analysis is used to estimate technology representative life, and technology residual life analysis is employed to estimate residual life using the linear and inverse functions. The technology economic life will be determined by combining the estimation results of patent citation life analysis and technology residual life analysis. This paper includes an example of applying it to the US patent data for 5 communications areas. Therefore, this logical concept can be applied usefully to determine the technology economic life and be expected to contribute to obtain credibility of technology valuation.

• 한국정보처리학회논문지
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• 제6권5호
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• pp.1189-1202
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• 1999

As compared with VOD data, NOD article data has the following characteristics: it is created at any time, has a short life cycle, is selected as not one article but several articles by a user, and has high access locality in time. Because of these intrinsic features, user access patterns of NOD article data are different from those of VOD. Thus, building NOD system using the existing techniques of VOD system leads to poor performance. In this paper, we analysis the log file of a currently running electronic newspaper, show that the popularity distribution of NOD articles is different from Zipf distribution of VOD data, and suggest a new popularity model of NOD article data MS-Zipf(Multi-Selection Zipf) distribution and its approximate solution. Also we present a life cycle model of NOD article data, which shows changes of popularity over time. Using this life cycle model, we develop LLBF (Largest Life-cycle Based Frequency) prefetching algorithm and analysis he performance by simulation. The developed LLBF algorithm supports the similar level in hit-ratio to the other prefetching algorithms such as LRU(Least Recently Used) etc, while decreasing the number of data replacement in article prefetching and reducing the overhead of the prefetching in system performance. Using the accurate user access patterns of NOD article data, we could analysis correctly the performance of NOD server system and develop the efficient policies in the implementation of NOD server system.

• Child Health Nursing Research
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• 제13권2호
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• pp.201-211
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• 2007

Purpose: This study was designed to construct a structural model to explain the quality of life of grandmothers caring for their grandchildren. Method: Data were collected by self-report questionnaires from 232 grandmothers caring for their grandchildren living in Busan. The data collection period was from June to Oct. 2006. Data analysis was done with SAS 9.13 for descriptive statistics and PC-LISREL 8.52 program for Covariance Structural analysis. Results: The findings found that the fit of the hypothetical model to the data was good, but considering theoretical implications and statistical significances of parameter estimates, paths and variables of the model were modified by excluding 2 paths. The Modified Model with 17 paths showed a good fitness to the empirical data ($X^2=15.492$ (df=11, p=.161), GFI=.985 AGFI=.940 NFI=.982 RMSR=.037 RMSEA=.042). Health status, health problems, economical status, life events, caring stress, caring efficacy and life satisfaction had significant effects on quality of life in the grandmother caring their grandchildren, but of these variables, self-esteem was the most essential factor. All predictive variables of quality of life together explained 63.9% of the variance. Conclusion: The derived model in this study was confirmed to be proper in explaining and predicting the quality of life of the grandmothers caring their grandchildren.

• 한국도로학회논문집
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• 제20권2호
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• pp.57-65
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• 2018

PURPOSES : The study aims to predict the service life of national highway asphalt pavements through deep learning methods by using maintenance history data of the National Highway Pavement Management System. METHODS : For the configuration of a deep learning network, this study used Tensorflow 1.5, an open source program which has excellent usability among deep learning frameworks. For the analysis, nine variables of cumulative annual average daily traffic, cumulative equivalent single axle loads, maintenance layer, surface, base, subbase, anti-frost layer, structural number of pavement, and region were selected as input data, while service life was chosen to construct the input layer and output layers as output data. Additionally, for scenario analysis, in this study, a model was formed with four different numbers of 1, 2, 4, and 8 hidden layers and a simulation analysis was performed according to the applicability of the over fitting resolution algorithm. RESULTS : The results of the analysis have shown that regardless of the number of hidden layers, when an over fitting resolution algorithm, such as dropout, is applied, the prediction capability is improved as the coefficient of determination ($R^2$) of the test data increases. Furthermore, the result of the sensitivity analysis of the applicability of region variables demonstrates that estimating service life requires sufficient consideration of regional characteristics as $R^2$ had a maximum of between 0.73 and 0.84, when regional variables where taken into consideration. CONCLUSIONS : As a result, this study proposes that it is possible to precisely predict the service life of national highway pavement sections with the consideration of traffic, pavement thickness, and regional factors and concludes that the use of the prediction of service life is fundamental data in decision making within pavement management systems.

• Human Ecology Research
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• 제53권3호
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• pp.331-339
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• 2015

This study investigates the effects of parental abuse and neglect on school life adjustment mediated by self-esteem in adolescents. Participants consisted of 2,259 middle school students from the Korean Children and Youth Panel Study 2012. Secondary questionnaire data on parental abuse and neglect, self-esteem, and school life adjustment are used for this study. Data were analyzed using descriptive analysis, Cronbach's a, Pearson's correlation analysis and multiple regression analysis. Baron and Kenny's method determined the mediation effect. SPSS ver 18.0 was adopted. The results were as follows. First, parental abuse and neglect were negatively correlated with the adolescent school life adjustment; however self-esteem was positively correlated with adolescent school life adjustment. Second, the results of the regression analysis revealed that adolescent school life adjustment was influenced both directly and indirectly; parental abuse had a direct effect on adolescents' school life adjustment and also had an indirect effect on mediated by self-esteem. Parental neglect had a direct effect on adolescent school life adjustment and had an indirect effect on adolescent school life adjustment mediated by self-esteem. The results indicated that self-esteem plays a crucial variable in the relationship of parental abuse and the school life adjustment. Also, self-esteem plays a crucial variable in the relationship between parental neglect and school life adjustment.

• 품질경영학회지
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• 제42권3호
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• pp.291-300
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• 2014

Purpose: The purpose of this study is to provide a statistical method from the data of ASRP's results and to apply to the reliability assessment of 155mm propelling charge, KM4A2. Methods: The accumulated data through ASRP for 155mm propelling charge were analyzed using regression analysis and MINITAB reliability analysis. The analysis methods used for this study were applied to statistical data types such as continuous data, binominal data. Results: The results of this study are as follows; The failure of 155mm propelling charge is mainly due to the broken charge bag, the decline of stabilizer content. The shelf-life(B5) regarding broken charge bag is 21.1years. The stabilizer content decrease with 0.0227%/year and safety storage period of propellant is 34.6years. Conclusion: The shelf-life of 155mm propelling charge determined by charge bag is estimated 21.1years.

• 한국안전학회지
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• 제27권4호
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• pp.115-120
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• 2012

In order to establish preventive maintenance standards through analysis & reliability prediction of about 60,000pcs of 20kindsof relays and contractors used for Seoul subway trains, several life prediction methodologies were applied. Firstly, Occurrence, Severity, Detection were defined and predicted by applying operation characteristic of EMU to the number of actions of relays & contactors which the manufacturers generally offer as the life cycle data. Secondly, failure distribution and average life of parts were analyzed through interpretation of field data based on a lot of experience which had built up in the field for a long time. Finally, using the 217PLUS standard as a reliability prediction program, comparative analysis of use reliability and inherent reliability was done through reliability prediction at the part level and system level.