Earticle

본 연구는 사이버폭력 경험이 있는 청소년들의 신체화 증상을 다루기 위해 포커싱적 태도의 관계와 영향을 알아 보고자 한다. 이를 위해 14~19세 청소년을 대상으로 설문조사를 진행하였고, 이 중 총 366명(남 84명(23%), 여 282명 (77%))의 결과를 분석에 사용하였다. 자료 분석은 빈도분석, 신뢰도분석, 상관 분석 및 다중회귀분석을 통하여 분석하였 다. 연구 결과, 사이버폭력 경험이 신체화 증상에 정적 영향을 미쳤다. 또한, 포커싱적 태도의 하위 요인 중 ‘알아차리기’ 와 ‘되새겨보기’는 신체화 증상에 정적 영향을 미치며, ‘표현하기’는 신체화 증상에 부적 영향을 미쳤다. 연구 결과를 바탕으로, 사이버폭력을 경험한 청소년들의 신체화 증상을 호소할 때 포커싱적 태도 치료적 접근의 필요성을 제시하였다.

The purpose of this study was to explore the relationship andinfluence of Focusing manner to deal with somatization symptoms of adolescents with experience of cyberbullying. For this study, we conducted on teenagers aged 14 to 19. A total of 366 of these results -84 men (23%) and 282 women(77%)- were used for the analysis. Data was analyzed through frequency analysis, reliability analysis, correlation analysis, and multiple regression analysis. As a result, cyber-bullying experiences have a positive effect on somatizaion symptoms. Among the sub-factors of focusing manner, "knowledge" and "reviewing" have a negative effect on somatizaion symptoms, and "expression" has an negative effect on somatizaion symptoms. Based on the results of the study, the need for a therapeutic approach to focusing manner was presented when appealing for somatizaion symptoms of adolescents who experienced cyberbullying.

본 연구는 고령화연구패널(KLoSA) 1차(2006년)∼6차(2016년) 자료를 이용하여 은퇴가 삶의 만족도에 미치는 영향을 다변량 다중회귀 분석(Multivariate Multiple Regression Analysis)을 이용하여 추정하였다. 우리나라 대표 표본을 가지고 국내에서 삶의 만족도에 대한 다변량 다중회귀분석을 수행하여 은퇴와 삶의 만족도에대한 분석의 정확성을 향상시키고자 하였다. 분석결과는 다음과 같다. 첫째, 은퇴는 고령자의 삶의 만족을 감소시키는 결정적인 요인이다. 특히 본 연구는 패널데이터를 분석하여 영역별 만족도의 감소를 확인할 수 있었는데은퇴이후 만족도가 가장 많이 하락하는 영역은 건강상태에 대한 만족도로 은퇴이후 약 14%의 감소를 보였으며다음은 자녀와의 관계(약 10% 감소), 배우자와의 관계(약 9% 감소), 전반적인 삶의 질에 대한 만족도(약 8% 감소)의 순으로 감소되는 것으로 나타났다. 둘째, 은퇴시기가 늦을수록, 고용상태를 유지하는 기간이 길수록 삶의 만족도는 높아진다. 이는 노동시장에서 더 오래 남아 근로를 했던 고령자의 삶의 만족이 높은 것으로, 은퇴이전 더 오랜 기간 노후준비를 할수록 은퇴이후 삶의 만족이 증진된다는 것을 시사한다. 셋째, 인구․사회적 특성에 따라 삶의 만족에 있어서 5가지 하위 요인들에 미치는 효과는 다르게 나타났다. 남자의 경우 배우자와의 관계에 대한 만족도가 증진되었고, 가구총소득이 높은 계층은 가구총소득이 낮은 계층에 비해 경제상태 만족도가 높았다. 또한, 배우자의 고용상태가 취업자일 경우 배우자와의 관계에 대한 만족도가 높았으며, 자발적 은퇴는 비자발적 은퇴에 비해 경제상태 만족도, 배우자와의 관계에 대한 만족도가 높았다. 넷째, 건강상태가 좋을수록 학력이 높아질수록 삶의 만족도는 증진되는 효과가 나타났고, 직업상태는 상용직에 비해 임시직/일용직의 삶의 만족도가 감소하였다. 자영업자는 상용직에 비해 경제상태 만족도가 줄어들었다. 본 연구는 5가지 영역별 삶의 만족도에 미치는 효과를 분석함으로써 은퇴 이후 노후준비를 위한 사회․제도적 지원과 방안을 다음과 같이 제시하였다. 첫째, 신체적 노후준비, 경제적 노후준비, 가족 간 정서 및 사회적 노후준비가 함께 이루어졌을 때 전반적인 삶의 만족도에 미치는 효과가 더 커질 수 있다고 판단되며, 둘째, 노동시장에서의 은퇴가 국가 및 기업차원의구조적인 측면에서 이루어지기 보다는 개인의 생산성 저하 및 판단에 의해 자발적인 측면에서 이루어질 수 있는노동환경이 개선되어야 한다고 생각된다.

This study explored the relationship between retirement and life satisfaction using Korean Longitudinal Study of Ageing(KLoSA) wave 1(2006) to wave 6(2016) data. The dependent variable of life satisfaction in this study was consisted with five dimensions of life satisfaction (satisfactions on one’s health, economic status, relationship with spouse, relationship with children, and overall life condition) as such multivariate multiple regression analyses was utilized due to the inter-relationships among the dependent variables. From the analyses from a total of 1,149(total of 2,298 observations) balanced panel showed that retirement was the major factor that influencing life satisfaction; after retirement individuals satisfactions on their own health, relationship with their spouse, relationship with their children and overall life condition were decreased. In addition, the time of retirement also influenced life satisfaction; those who stayed in workforce longer had higher levels of life satisfaction. Individuals’ background characteristics influenced each dimension of life satisfaction in different ways; men compared to women had higher levels of relationship satisfaction with spouse, those who had higher levels of household income showed higher levels of economic satisfaction. People who retired voluntarily showed higher levels of economic satisfaction and spouse relationship satisfaction. People who had higher levels of health condition and education showed higher levels of satisfaction with overall life condition. Those who work full-time had higher levels of life satisfaction compared to other working type. Based on these findings, it was suggested that when preparing for retirement all aspects of life such as health, relationship, and social condition in addition to economic and financial readiness should be considered. Retirement should be treated as individual decision making issue rather than systematic corporate issue in workforce. Future research on examining life satisfaction changes after retirement is recommended.

본 연구에서는 취약성 저감 측면에서 범죄취약계층과 범죄유형별 범죄발생건수에 대한 다중회귀분 석을 실시하여 범죄취약계층별 범죄유형에 대한 영향관계를 분석하였다. 독립변수는 선행연구 고찰 을 통해 7개의 취약계층(고령자, 아동·청소년, 외국인, 여성, 1인 가구, 다문화 가구, 기초생활수급자) 으로 선정하였으며, 범죄유형별 취약계층과의 관계를 분석하기 위해 각 유형별 발생건수를 종속변 수로 선정하였다. 범죄 유형은 활용된 데이터 유형을 반영해 강력범, 절도범, 폭력범, 지능범, 풍속범, 기타 형법범, 특별법범으로 구분하였다. 범죄취약계층 중 유의미한 상관관계를 갖는 취약계층을 분 석한 결과는 다음과 같다. 첫째, 범죄유형별로 취약계층에 따른 영향관계가 다르게 나타났다. 둘째, 모든 범죄에서 고령자와 아동·청소년은 음의 영향관계를 갖는다. 셋째, 특별법범에서는 외국인이, 절도범과 폭력범에서는 여성이, 강력범에서는 다문화가구가, 폭력범과 지능범&풍속범, 그리고 기타 형법범에서는 기초생활수급자가 양의 영향관계를 나타냈다. 본 연구의 결과는 불필요한 범죄두려움 을 없애고, 범죄유형별 취약특성에 따른 맞춤형 대책을 마련하는 데에 기여할 것으로 판단된다.

This paper identified crime vulnerable groups by crime type through performing a multiple regression analysis. Based on the review of prior studies, seven crime vulnerable groups (independent variable) were classified such as the elderly, children and youth, foreigners, female, basic livelihood security recipients, one-person households and multicultural families. Crime types (dependent variable) include heinous crime, theft crime, violent crime, intelligent crime, crime against the customs, other criminal crimes, and special crimes. The results of statistical analyses were as follows: First, crime vulnerable groups differed by crime types. Second, the elderly and children/youth showed a negative coefficient in all crime types. Third, foreigners were positively related with special crimes, while female was vulnerable to theft and violent crime. Multicultural families were vulnerable to heinous crime, while the basic livelihood security recipients were related to violent crime, intelligent crime, crime against the customs and other criminal crimes. The results of this study are expected to contribute to eliminating unnecessary fear of crime and developing customized measures based on the vulnerable characteristics of each crime type.

본 연구는 선형-선형 다중회귀모형을 통해 여과속도, 탈진압력, 탈진간격, 입구농도 등의 운전조건에서 벤츄리 설치가 압력손실에 미치는 영향을 예측하여 충격기류식 여과집진장치의 효율적인 운전조건과 경제적인 설계 기초자료로 활용하 고자 하였다. 여과면적 6 m2인 파이로트형 충격기류식 여과집진장치를 이용하여 제철소 coke분진으로 여과속도, 입구농 도, 탈진압력, 탈진간격 및 벤츄리 설치 유·무의 조건에 따라 여과포 압력손실을 측정하였으며, 여과포 압력손실(P)의 변화에 기여하는 여과속도(Vf), 입구농도(Ci), 탈진압력(PP), 탈진간격(Pi), 벤츄리 설치 유·무 등에 따른 영향력을 파악하 기 위해 SAS 9.4(SAS Institute, USA) 프로그램으로 통상적인 최소자승 추정법(Ordinary Least Square; OLS)인 선형-선 형의 다중회귀모형 함수를 이용하여 벤츄리가 압력손실에 미치는 영향을 예측하였다. 예측 결과를 종합해 보면 압력손실 최소화를 위해서 벤츄리를 설치할 경우 20.3% 효율 향상이 기대되며, 압력손실에 기여하는 순서는 여과속도(Vf) > 탈진 압력(Pp) > 입구농도(Ci) > 탈진간격(Pi)임을 알 수 있었다.

The aim of this study is to predict the pressure drop due to the presence or absence of Venturi under various operating conditions such as filtration velocity, pulse pressure and interval, and dust concentration using linear-linear regression model and use it as an efficient operating condition and economic data for a shock-type filter collection system. A pilot filtration collector with a filter area of 6 m2 was used, and the filtering pressure drop was measured according to filtration velocity, inlet concentration, pulse pressure, pulse interval, and the flow and absence conditions of the Venturi installation by a steel plant. The SAS 9.4 program (SAS Institute, USA) was used to predict and to determine the effects of filtration velocity (Vf), inlet concentration (Ci), pulse pressure (Pp) and interval (Pi), presence or absence of venturi, etc. and also analyze the changes in pressure drop according to the presence of Venturi using the linear-linear multiple regression model, and the least-squares estimation method (OLS). The results re shown below. In order to minimize the pressure drop, the improvement in efficiency is expected to be 20.3% when the Venturi is installed, and the order of contributing to the pressure drop is filtration rate> pulse pressure> inlet concentration> pulse interval.

최근 상업용 통계 패키지의 발달에 힘입어 다변인 통계분석에 기초한 연구들이 양산되고 있다. 다변인 분석은 단변인 통계에 비해 복잡한 연구문제를 탐색할 수 있는 장점이 있지만, 통계분석의 복잡성으로 인하여 절차상 오류들이 더러 발견된다. 더욱이, 다변인 통계분석의 수학적 기초가 복잡하여 그 원리를 이해하기 어렵고, 분석방법 및 결과 해석이 난해할 수 있으며, 다양한 분석법들이 상반된 결과를 낳아서 결과해석이 곤란해질 수 있다. 따라서 본 연구에서는 다변인분석 적용상의 가능한 오류와 주의점들을 기술하여 이러한 오용을 줄일 수 있는 방안을 제시하고자 하였다.

Due to the recent developments in commercial statistical packages, vast amount of research articles based on multivariate statistics have been published. While the multivariate statistics have advantages over the univariate statistics in dealing with more complicated research hypothesis, abuses and misuses in it's application have been frequently noticed in many researches, due to the underlying complexities. Specifically, it is difficult to understand the basic principle due to the mathematical complexities underlying in it, henceforth making the interpretation of the analysis result be difficult. Even worse, different choice of the analysis methods sometimes result in contradicting results, making the interpretation implausible. This study tried to examine the cases of misuses in the application of multivariate statistics, and to identify the problems. Finally, several precautions for reducing the incidents was proposed.

본 연구는 청소년 가구원이 있는 저소득 가구의 청소년관련 복지서비스 이용이 청소년의 심리사회적 적응에 어떠한 영향을 미치는지 알아보았다. 이를 위해 한국복지패널 1차년도부터 4차년도까지의 자료를 사용하였으며, 4년간에 걸쳐 이용한 상담․방과후 지도․예체능교실·문화활동 중 만족도가 높은 복지서비스의 종류를 합하여 만족한 복지서비스 이용여부가 청소년의 우울 및 불안, 위축, 비행, 공격성에 미치는 영향을 측정하였다. 또한 복지서비스를 이용할 확률이 높은 집단이 복지서비스를 이용함으로써 결과적으로 복지서비스의 효과가 부정적으로 측정되는 선택편의를 줄이고자 경향점수 가중치 방법을 적용하였다. 주요 결과는 다음과 같다. 첫째, 복지서비스 이용이 청소년의 심리사회적 적응에 부정적인 영향을 미친다는 다중회귀분석 결과와 달리, 경향점수 가중치를 적용하였을 때 복지서비스 이용은 청소년의 심리사회적 적응에 아무런 영향을 미치지 않았다. 둘째, 선택편의 제거 수준에 따라 복지서비스를 이용한 청소년 집단과 그렇지 않은 청소년 집단 간에는 심리사회적 적응 수준의 차이가 발견되었으며 이는 경향점수 가중치를 통해 두 집단이 동질한 집단으로 조정되었다는 것을 보여준다. 셋째, 본 연구는 상담 서비스뿐만 아니라 방과후 지도․예체능교실․문화활동도 청소년의 심리사회적 적응에 긍정적인 영향을 미치리라는 점을 시사한다. 본 연구는 복지서비스가 전반적인 청소년발달에 미치는 영향을 알아보기 위한 기초연구로, 본 연구를 통해 도출된 연구결과와 제한점은 추후 연구에 반영될 것이다.

This study examined the effects of using welfare services for adolescents (e.g., counseling, after-school programs, art programs, and cultural activities) on the psychosocial adjustment of adolescents from low-income families. For this goal, this study used data from the Korea Welfare Panel Study from the 1st wave through the 4th wave. In addition, this study adopted propensity score weight method to reduce the distortion of the results which might result from the selection bias. The main results are as follows. First, while the result from the multiple regression analysis showed that those who used welfare services were more likely to experience lower levels of psychosocial adjustment, the result from the propensity score weight method showed that there was no significant difference in the levels of psychosocial adjustment between those who used the welfare services and those who did not. Second, depending on the levels of selection bias reduction, there were differences in the gaps of levels of psychosocial adjustment between those who used welfare services and those did not. This result shows that the adjustment using the propensity score weight method made two groups - those who used welfare services and those who did not - equivalent in terms of household head employment status, previous mental health levels of adolescents and others. Third, the research finding suggests that, in addition to counseling service, the use of after-school programs, art programs, and cultural activities has positive effects on the psychosocial adjustment of adolescents. As a preliminary study of the study which will examine the overall effects of using welfare services on all aspects of the development of adolescents from low-income families, the results as well as the limitations found in this study will be reflected in the further study.

이 연구는 탄산염암 저류층에서 석유증진회수법인 CO2-EOR(carbon dioxide enhanced oil recovery)의 효율을 신속히 평가하는 사전 경제성 평가식을 도출한다. 선행 CO2-EOR 스크리닝 연구들은 저류층 물성에 기반한 순람표등을 활용하는 정성 평가에 집중하였다. 이 연구는 CO2-EOR 효율의 정량 평가를 위해 5개의 정적 물성(저류층 압력및 온도, API 비중, 공극률, R35)과 2개의 동적 물성(CO2 돌파 시간 및 회수율)을 영향인자로 선택한 후, 영향인자 값을변화시키며 저류층 시뮬레이션을 수행하여 평가식 설계를 위한 데이터베이스를 구축하였다. 평가식은 원시석유부존량과 회수율 지표의 조합으로 구성하였다. 회수율 지표는 정적인자들을 독립변수, 동적인자들을 종속변수로 설정한 후 다중비선형회귀분석을 수행하여 계산하였다. 제안한 사전 평가 시스템은 탐사 및 개발 중인 탄산염암 저류층을위한 저렴하고 효율적인 CO2-EOR 스크리닝 도구로 활용할 수 있다.

This study aims to derive an equation for a preliminary economic evaluation that quickly assesses the efficiency of CO2-EOR at carbonate oil reservoirs. Previous works have qualitatively analyzed the CO2-EOR efficiency by, for example, using a lookup table based on reservoir properties. This study selects a series of influential parameters on the CO2-EOR efficiency: five static (e.g., reservoir pressure and temperature, API gravity, porosity, and R35) and two dynamic properties (e.g., CO2 breakthrough time and recovery factor). A database for the derivation of the equation is built by running reservoir simulation with varying values of the influential parameters. By conducting a multiple nonlinear regression analysis, the equation is designed as a combination of oil initially in place and recovery factor. The five static properties were utilized as inputs of the equation, while the dependent variables representing the outputs were obtained by merging the two dynamic properties. The proposed economic evaluation system can be utilized as an efficient CO2-EOR screening tool for carbonate reservoirs under field exploration and development.

해기사의 높은 이직률은 기업의 측면에서 교육, 훈련 및 채용 등 인력 운용에 있 어 많은 경제적 손실을 야기하며, 국가적 차원에서도 국가의 자원으로 해기 인력을 양성하는 대한민국의 현실을 고려할 때 그 손실은 더욱 크다고 할 수 있다. 본 연구 는 최근 외항상선 해기사들의 이직률 증가 원인을 직무스트레스의 측면에서 분석하 고자 하였으며, 직무스트레스가 직무만족도 및 이직의도에 미치는 영향을 분석하여 그에 대한 개선 방안을 제시하고자 하였다. 본 연구의 목적을 달성하기 위하여 한국 형 해기사 직무스트레스 측정 도구를 개발하였으며, 이를 활용하여 재직 중인 해기 사 146명을 대상으로 설문을 수행하였다. 설문 결과를 기반으로 요인분석 및 신뢰도 검증을 수행하였으며, 직무스트레스 요인을 직무부담요인, 직무보상요인, 인간관계요 인, 고용불안요인, 조직문화요인 등 5개의 요인으로 차원 축소 및 재분류하였다. 분 석 결과 직무스트레스 요인 중 직무부담요인, 직무보상요인, 인간관계요인, 고용불안 요인, 조직문화요인이 직무만족도에 영향을 미치며, 직무부담요인, 직무보상요인, 조 직문화요인이 이직의도에 영향을 미치는 것으로 나타났다. 향후 본 연구에서 도출한 직무스트레스 요인에 따른 체계적 관리와 직무스트레스 경감 방안 개발을 통하여 해기사의 직무만족도 향상 및 이직의도 경감에 기여할 수 있을 것으로 기대한다.

As aspect of shipping companies, the high turnover rate of merchant ships’ officers causes a lot of economic and time losses in personnel management including education, training and recruitment. It is even greater loss at national level, because the Korean government has put resources and expenditures to rise officers through the maritime schools every year. In this study, the reason for the recent increase in turnover rate of the officers in shipping companies was analyzed in terms of job stress. The effect of job stress on job satisfaction and turnover intention was analyzed and the improvement plans were proposed. To achieve the purpose of this study, the stress measuring tool of KMOSS(Korean Maritime Officer’s Occupational Stress Scale) was developed and the survey was conducted on 146 officers who are on vacation. According to the survey, the job stressor factors were derived to five factors through the factor analysis and reliability verification; i.e. job burden factors, job compensation factors, human relation factors, job insecurity factors, and organizational culture factors. In addition, all stressor factors affected to job satisfaction. In case of turnover intention were found to be affected by job burden factors, job compensation factors and organizational culture factors. In the future, it is expected that the results can contribute to reduction of turnover rate and improve job satisfaction through systematic management of stressor factors which are derived in this study.

현대사회는 1인가구가 증가함에 따라 불규칙한 식습관으로 인해 영양이 불균형하게 포진되어있다. 이러한 식습 관은 위장질환, 소화기 질환 등 만성질환의 발병률을 증가시켰다. 본 논문은 위장질환 예방을 위한 다중회귀분석을 이용 한 식이지식 예측을 제안한다. 제안하는 방법은 식이지식 예측을 통해 사용자의 위장질환과 식이영양을 관리하는 방법 이다. 헬스 플랫폼에서 스마트 기기를 통해 수집된 사용자의 PHR을 통합한다. 통합된 데이터로부터 다중회귀분석을 이용하여 사용자의 식이와 활동량 변화를 분석한다. 사용자의 식이 성분과 소모 칼로리, 기초대사와 같은 상황정보를 입력으로 적절한 식이성분, 위장질환 수치의 변화를 예측하고 필요할 것으로 나타나는 영양성분을 사용자에게 권장한 다. 이를 통해 현대인들은 균형 잡힌 식사를 통해 위장질환을 관리할 수 있다.

Modern society is undergoing nutritional imbalance according to the diet as the number of one person increases. This is increasing the incidence of chronic diseases such as gastrointestinal diseases and digestive diseases. This study suggests the prediction of dietary knowledge using multiple regression analysis for preventing chronic stomach diseases. The proposed method manages user’s stomach diseases and dietary nutrition through the prediction of nutrition knowledge. It collects user's PHR through smart device and integrates in the health platform. The integrated data analyzes the dietary and activity of the user through multiple regression analysis. It predicts the required nutrients and provides services to users through applications. Therefore, it suggests recommended dietary components and consumed calories, appropriate dietary components based on the user's basal metabolism, and gastrointestinal levels. With the personalized health management, modern people can manage gastrointestinal diseases through a balanced diet.

In the ALC(Autoclaved lightweight concrete) manufacturing process, if the pre-cured semi-cake is removed after proper time is passed, it will be hard to retain the moisture and be easily cracked. Therefore, in this research, we took the research by multiple regression analysis to find relationship between variables for the prediction the hardness that is the control standard of the removal time. We study the relationship between Independent variables such as the V/T(Vibration Time), V/T movement, expansion height, curing time, placing temperature, Rising and C/S ratio and the Dependent variables, the hardness by multiple regression analysis. In this study, first, we calculated regression equation by the regression analysis, then we tried phased regression analysis, best subset regression analysis and residual analysis. At last, we could verify curing time, placing temperature, Rising and C/S ratio influence to the hardness by the estimated regression equation.

This paper is an empirical study on the impact of organizational culture upon employee satisfaction based on the survey data of a logistics company. Robert Levering's organizational culture model, which categorizes cultural aspects into five major areas( credibility, respect, fairness, pride, and fun), was adopted as the basis for nominating independent variables of the multiple regression analysis model. 803 data sets were collected from the questionnaire survey. Statistical test of hypothesis upon the multiple regression model indicated that 'respect', 'fairness', and 'pride' play significant role on employee satisfaction. Whereas the remaining two cultural aspects, i.e., 'credibility' and 'fun,' do not play any significant role. However, care must be given so that this result might not be generalized for other organizations in the defense industry.

본 연구에서는 다항식 회귀분석(Polynomial regression analysis) 방법을 이용하여 비선형 특성을 갖는 전자저울 의 질량 추정 모델 개발이 이루어 졌다. 전자저울에 사용되는 로드셀의 출력 단자 전압을 기준 질량 추를 사용하여 직접 측정하였고 이 데이터를 이용하여 MS Office 엑셀의 행렬식 계산과 데이터 추세선 분석 기능을 이용하여 다항식 회귀 모델을 구하였다. 5kg까지 측정 가능한 로드셀 전자저울을 사용하여 100g단위로 질량을 측정하였고 다항식 회귀분석 (Multiple regression analysis) 모델을 구하였으며, 단순(1차), 2차, 3차 다항식 회귀분석에 대한 오차를 구하였다. 각 모델에 대한 회귀 방정식의 적합도 분석을 위해 결정계수(Coefficient of determination)를 제시하여 추정 질량과 측정 데이터와의 상관관계를 나타내었다. 본 연구에서 제안하는 3차 다항식 모델을 이용하여 추정 값의 표준편차가 10g, 결정계 수 1.0으로 상당히 정확한 모델을 얻었다. 본 연구에 사용된 선형 회귀 분석 이론을 바탕으로 최근 인공지능 분야에서 많이 사용되고 있는 로지스틱 회귀 분석(Logistic regression analysis)을 활용하여 기상예측, 신약개발, 경제지표 분석 등의 분야에 대한 다양한 연구를 수행할 수 있을 것으로 생각된다.

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple(1st), 2nd and 3rd order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.

The purpose of this report is to discuss the obtained findings gathered from ultrasound screenings of the liver. After running diagnostic tests health, screens were then conducted to analyze and compare the gained results. This data was then charted and used to strengthen our theorized hypothesis. From January 2013 to June 2013 a recorded 2906 people over the age of 20 visited Health Promotion Centers in various areas throughout Daejeon. Of those 2906 participants 1789 underwent screenings for abdominal ultrasonography; these participants as well as their ultrasound results were used as the bases of our study. For the establishment of our baseline and the comparison of our results, we gathered case-controlled studies from various reputable sources. Both the control and the experimental groups were tested to measure the following liver enzymes (AST, ALT, r-GTP, ALP, and etc.). Kidney functions were measured as well enzymes such as BUN, Creatinine, and Uric Acids levels were analyzed and recorded to see if any relationships existed between the levels documented in the liver and those in the kidneys. It was shown that the two primary causes of fat build up within the liver were significantly connected to obesity BMI(OR=4.14) and waist circumference(OR=3.88).

An observation of the mortality rate in the construction industry by age for the past five years shows that the mortality rate of those 50 years of age and older is consistently increasing. As the number of middle and old aged workers is continuously increasing, their hazard rate is also increasing so hazard prevention efforts for them are being urgently demanded. In particular, with regard to middle and old aged workers, there are many experienced in construction so wrong work methods or habits adopted in the past can cause hazards so safety education that can allow middle and old aged workers to adopt proper work methods or habits is urgently needed. At this, this study proposes a safety education model for middle and old aged workers that takes into consideration the characteristics of middle and old aged workers. The accuracy of the developed model was evaluated and its applicability was reviewed based on data. Verification of this proposed model was made by conducting a likelihood ratio test and correction rate test and likelihood ratio test results showed that all safety education elements were significant at a significance level of 0.1% and they also had a goodness of fit of 83%, so their potential for applicability in actual construction sites was verified. The accuracy of this model will increase as more data accumulates in the future.

The multiple linear regression model contains more than one predictor variable and it shows the relationship among multiple variables. In the existing research field of rural-urban income disparity, the method of multiple regression analysis is mainly employed. But the linear relationship among variables is estimated mainly depending on principal component analysis. Principal component analysis is used to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. The principal component analysis is widely used for feature extraction to reveal the most main factors from the multiple aspects. A multiply linear regression model integrating principal components analysis is proposed to address on the income gap between the city and country. The influential factors are given and the analysis results are discussed in this paper. The experimental results on income data from 1990 to 2013 show that the proposed method is effective in predicting the income ratio and analyzing the influential factors.

Different festivals are being held following the implementation of the local autonomy system. These festivals are having significant influences on the image enhancement of the regions holding the festivasl as well as the local economic stimulation. In terms of economic, social, and cultural perspectives, festivals have positive effects on the local society and are acting as resources for new opportunities in area development. In order for the festivals to be successful, preparation and efforts are needed to enhance the satisfaction of the festival spectators. This paper derived the evaluation factors which have influence on the festival satisfaction of spectators from the planning stage and constructed a study model. Then, regression analysis was applied for suggestion to be made on the evaluation of festival satisfaction.

The relationship between the gas chromatographic (GC) patterns of sauce made of barley bran and ranked order in sensory analysis was investigated by multiple regression analysis (MRA). Most of the 42 barley bran sauce samples comprised about 34 peaks, in which the content of 9, 12-octadecanoic acid methyl ester was the highest, followed by those of 2-furanmethanol and 2-furancarboxaldehyde. It is difficult to estimate the aroma quality of barley bran sauce samples on the basis of only one peak. The 34 aroma compounds of the 42 samples were analyzed by an MRA model featuring six transformations. The most precise fit was calculated from the absolute value transformed with the root square of each peak, and the multiple determination coefficient showed that 91.6% of the variation in the sensory score could be explained on the basis of GC data.

Forecasting quality of complex products is a major concern for quality engineers and enterprises' decision-makers. But only a few researchers have investigated how multiple linear regression analysis can improve forecasts. This article presents a predictive control model for personalized forecasting system of complex product quality using multiple linear regression analysis. First, this paper compares the performance of personalized forecasting system for product quality which leads to a better understanding of the applicability of the forecasting model. Second, this paper identifies the effect of predictive control model of multiple linear regression analysis on forecasting accuracy. Then, an example shows the feasibility of using predictive control model in complex product quality personalized forecasting. Finally, it makes a conclusion that the approved prediction system embraces superiority over the prediction of the quality factors and manufacturing resources.