• Structural Engineering and Mechanics
• /
• 제72권6호
• /
• pp.737-746
• /
• 2019

Concrete mechanical properties change constantly with age, temperature, humidity and the other environmental factors. This research studies the effects of temperature and age on the development of concrete elastic modulus by a series of prism specimens. Elastic modulus test was conducted at various temperatures and ages in the laboratory to examine the effects of temperature and age on it. The experimental results reveal that the concrete elastic modulus decreases with the rise of temperature but increases with age. Then, a temperature coefficient K is proposed to describe the effects of temperature and validated by existing studies. Finally, on the basis of K, analytical models are proposed to determine the elastic modulus of concrete at a given temperature and age. The proposed models can offer designers an approach to obtain more accurate properties of concrete structures through the elastic modulus modification based on actual age and temperature, rather than using a value merely based on laboratory testing.

• 대한치과의사협회지
• /
• 제13권5호
• /
• pp.457-461
• /
• 1975

The author observed the relationships beween the dental midline and the midsagittal plane by taking 242 cases P-A cephalo-graphy grouped by male and female 2-6 years age group, 7-15 years age group, and adult age group. The following results were obtained by the observation. 1. Generally, the median line almost coincided with dental midline ineach age group. 1. It showed som degree of deviation in each age group. 2. It showed some degree of deviation in each age group. 3. The some degree of deviation shifted in accordance with each age group. 4. In adult age group, the dental milline more coincided with median line in male than in female.

• 디지털산업정보학회논문지
• /
• 제10권4호
• /
• pp.127-132
• /
• 2014

Some laws and regulations may require internet service providers to provide services based on the age of users. Age verification in the online environment should be used as a tool to provide service that is appropriate to child based on age. Using the minimum attribute information, processes on age verification provides the proper guidance to the internet services. However, there is a lack of a globally accepted trust framework for age verification process including evaluation factors for age verification information. In this paper the federation model of user attributes were described and evaluation factors for the age verification information were suggested. Also using the suggested evaluation factors, performance evaluation of federation model of user evaluation was performed. To meet the requirements of evaluation factors, framework of federation model should consider the unlinkability pseudonym support, eavesdropping protection and cloning protection.

• 생명과학회지
• /
• 제19권10호
• /
• pp.1403-1409
• /
• 2009

본 연구에서는 중년비만여성을 대상으로 비만의 발생요인으로 예상되는 요인을 이용하여 비만의 상태를 연령 척도화하여 비만연령(Obesity Age: OA)이라는 연령 추정식을 산출함과 동시에 비만도(비만연령)를 실제의 역연령과 검토하였고 비만연령의 추정식은 다음과 같다. OAS (Obesity Age Score)=$0.106*X_1+0.035*X_2+0.048*X_3+0.041*X_4+0.003*X_5-0.037*X_6-10.66$ (1) ($X_1$: BMI, $X_2$: 체중, $X_3$: 체지방률, $X_4$: 배둘레, $X_5$: 중성지방, $X_6$: $VO_{2max}$) OA (Obesity Age)=7.3*OAS+49.6*(-1) (2) Z=(CA-49.6)(1-0.03) (3) OAc (Obesity Age corrected)=1.03*CA-7.3*OAS+1.47 (4) 그리고 역연령과 추정된 비만연령(Obesity Age corrected: OAc)의 비교에서는 유의한 차이를 나타내지 않아 타당성이 확인되었으며, 총 6개의 측정항목으로 구성된 비만연령을 통해 비만자 개개인의 비만건강도(상태)를 용이하게 평가할 수 있을 것으로 기대하며, 추후에는 다른 집단에서의 적용가능 여부를 알아보기 위해 교차타당성을 검토해야할 것이라고 사료된다.

• 보건교육건강증진학회지
• /
• 제13권1호
• /
• pp.128-162
• /
• 1996

Using Random Sampling, the authors measured the body heights and weights of 31,151 persons - 17,102 in males and 14,049 in females from metropolitan, urban and rural areas between 6 to over 80 year old - for the purpose of investigating the type and the actual condition of the Korean's growth and development. At first, on the basis of the results, the authors measured the growth and development, various kinds of physiques, nutritional index of the 6 to 20s age group. Second, the authors presented the standard body weight of males and females by their body height, who were in the end of their growth (20-29 age group). Third, the authors calculated and presented the normal adapted body weight of the age group who were over 30 age after the growth had been completed. Forth, the author presented the obesity rate of the adults over 20 years old by body mass index. Finally, the authors compared chronological change of the Koreans' body heights and body weights with the results of other researchers. 1. Body Measurement Rapid growth, in terms of body height, which is described by a straight line on a growth curve has been observed among males in the ages 6-13 and among females 6-14. That growth curve turned out to be slower among the people of higher ages by both sexes. The cross-over occurred in both sexes at 11-14. The highest growth rate for a year is at 13-16 for males and 11-13 for females. This indicates that females enter a rapidly growing stage 2 years earlier than males. 2. Various Physiques and Nutritional Index Rapid growth, in terms of Relative Body Weight Index, which is described by a straight line, has been observed among males in the ages 6-16 and females in the ages 6-14. The cross-over occurred in both sexes 12.5-14.5 age in the adolescencent period. Whereupon females outgrow males. The Roher Index displayed more good value in case of females than male and in the adolescent period, the level of fullness is lower than after the completion of development. The Kaup Indices of both sexes increase with age. The index is less than 2.0 for males in 6-14 age group and for females in 6-13 age group and with this, it appeared that development of horizontal axis to long axis is poor. The index is more than 2.0 after 15 age group in males and 14 age group in females and developmental state4 age group and for females in 6-13 age group and with this, it appeared that development of horizontal axis to long axis is poor. The index is more than 2.0 after 15 age group in males and 14 age group in females and developmental state Body Mass Index is less than 20 for males 6-14 age group and for females in 6-13 age group. In the case of the higher age group, that index maintains a normal state.

• 한국지역지리학회지
• /
• 제3권1호
• /
• pp.35-50
• /
• 1997

경기지역의 성별 연령구조의 공간적 분포양상은 서울과 인접한 서울주변지역과 경수축, 경인축, 경춘축, 고양-파주축, 의정부-동두천축, 하남 방향 등 각종 교통노선에 의해 서울과의 접근성이 양호한 지역에 상대적으로 젊은 연령층이 다수 거주하고 있음이 확인된다. 이들 지역은 기동성이 큰 젊은 연령층이 거주교외 화를 주도하여 집중적으로 살고 있는 거주교외지역과 중복된다. 이 지역에서는 교통체계가 개선되어 대중교통 및 자가용에 의해 기동성이 크게 증가되었고, 주택신도시 건설 등 정책적 변수가 작용하여 인구유입이 가속화되고 있으며, 경기지역으로의 공장이전, 본사 및 지사설립, 연구단지조성 등으로 취업기회가 확대되고 있을 뿐만 아니라, 서울주변지역의 쾌적성과 발전성이 예견되고 있기 때문에 사람들이 주거지를 선택하고 있다고 판단된다. 그리고 서울에서 멀어질수록 농촌적 기능이 많을수록 상대적으로 노년층의 연령구조물 보여준다. 경기지역의 성별 연령구조의 공간적 분포에서는 여성의 연령구조가 남성에 비해 현저하게 노령화구조률 나타내고 있음이 확인된다. 이것은 남성 연령구조지수의 평균치가 1592인데 비해 여성연령구조지수가 1386로 집계되어 상대적으로 노령화되어 있는 점에서도 드러난다.

• 한국산학기술학회논문지
• /
• 제20권8호
• /
• pp.331-343
• /
• 2019

본 연구는 Framingham Heart Study의 심장나이 예측 모형을 활용하여 심장나이의 추이를 관찰하여 한국인 심혈관질환 발생 위험을 평가해보고자 하였다. 연구대상은 2005년~2013년 국민건강영양조사 자료를 이용하여 30세~74세 대상자 중 심혈관질환 기왕력이 없고, 모형의 결정요인에 해당하는 자료의 결손이 없는 20,012명을 연구대상으로 하였다. 이들에 대해 Framingham Heart Study 비실험실 자료를 이용하는 심장나이 산정 모형을 적용하여 심장나이를 계산하였으며 성별로 심장나이와 실제나이와의 차이, 연령대별 차이, 10년 이상 초과율, 지역별 차이에 대해 연도별 추이를 관찰하였다. 자료분석은 SAS 9.3으로 수행하였으며 가중치를 적용한 복합표본설계분석을 수행하였다. 연구 결과 심장나이와 실제나이의 평균 차이는 남성은 2005년에 7.8세, 2013년 7.7세, 여성은 2005년 1.2세 2013년 1.2세로 남성이 여성보다 컸고, 연령대가 증가할수록 나이차이가 많아졌으며, 연도별로 뚜렷한 추이 변화는 없었다. 심장나이가 실제 나이보다 10년 이상 초과한 비율은 남성은 2005년에 35.0%, 2013년에 34.8%, 여성은 2005년에 17.7%, 2013년에 18.7%로 남성이 여성보다 거의 두 배 정도 높았으며 연령대가 증가할수록 차이가 많이 났다. 지역별로 차이를 보였으며 남녀 차이가 많았다. 본 연구결과로 볼 때 한국인의 10년 내 심혈관질환 발생 가능성은 상당히 높은 수준이었다. 본 연구에서 사용한 심장나이는 미래의 심혈관질환 발병 위험을 간단하고 편리하게 예측할 수 있는 유용한 종합 지표로 사용될 수 있으며, 이를 한국인 심혈관질환 예방을 위한 경고효과와 계도목적으로 현장에서 공중보건 관리에 활용되기를 제안한다. 한국형 심장나이 예측 모형의 개발을 위한 심층 연구도 필요하다.

• 보험의학회지
• /
• 제4권1호
• /
• pp.44-76
• /
• 1987

Present study was undertaken to establish the modified Broca's indices to estimate standard body weight by using a total of 5,496 insured persons who were medically examined at the Honam Medical Room of Dong Bang Life Insurance Company Ltd. from January, 1983 to January, 1986. The results were as follows: 1. The linear regression equations of body weight to $height^3$ to estimate standard body weight were as follows: In male, for $18{\sim}19$ age group $y=7.272{\times}10^{-6}{\times}x^3+23.560$ for $20{\sim}29$ age group $y=8.187{\times}10^{-6}{\times}x^3+22.031$ for $30{\sim}39$ age group $y=8.627{\times}10^{-6}{\times}x^3+23.169$ for $40{\sim}49$ age group $y=9.561{\times}10^{-6}{\times}x^3+20.994$ for $50{\sim}59$ age group $y=8.604{\times}10^{-6}{\times}x^3+23.081$ and for all ages group $y=7.778{\times}10^{-6}{\times}x^3+25.929$ In female, for $18{\sim}19$ age group $y=8.252{\times}10^{-6}{\times}x^3+18.920$ for $20{\sim}29$ age group $y=7.715{\times}10^{-6}{\times}x^3+22.409$ for $30{\sim}39$ age group $y=8.808{\times}10^{-6}{\times}x^3+21.440$ for $40{\sim}49$ age group $y=9.691{\times}10^{-6}{\times}x^3+21.940$ for $50{\sim}59$ age group $y=12.550{\times}10^{-6}{\times}x^3+11.031$ and for all ages group $y=7.300{\times}10^{-6}{\times}x^3+26.601$ In both sexes, for all ages group $y=8.342{\times}10^{-6}{\times}x^3+22.998$ 2. The modified Broca's index is expressed by formula $\{height(cm)-100\}{\times}K(kg)$. K is obtained from the following formula standard weight to average height estimated $\frac{by\;means\;of\;linear\;regression\;equation(kg)}{\{Average\;height(cm)-100\}{\times}K(kg)}$=1 Author's modified Broca's indices are as follows: In male, for $18{\sim}19$ age group $\{height(cm)-100\}{\times}0.85(kg)$ for $20{\sim}29$ age group $\{height(cm)-100\}{\times}0.90(kg)$ for $30{\sim}39$ age group $\{height(cm)-100\}{\times}0.95(kg)$ for $40{\sim}49$ age group $\{height(cm)-100\}{\times}1.00(kg)$ for $50{\sim}59$ age group $\{height(cm)-100\}{\times}0.95(kg)$ and for all ages group $\{height(cm)-100\}{\times}0.95(kg)$ In female, for $18{\sim}19$ age group $\{height(cm)-100\}{\times}0.90(kg)$ for $20{\sim}29$ age group $\{height(cm)-100\}{\times}0.90(kg)$ for $30{\sim}39$ age group $\{height(cm)-100\}{\times}1.00(kg)$ for $40{\sim}49$ age group $\{height(cm)-100\}{\times}1.05(kg)$ for $50{\sim}59$ age group $\{height(cm)-100\}{\times}1.05(kg)$ and for all ages group $\{height(cm)-100\}{\times}1.00(kg)$ In both sexes, for all age group $\{height(cm)-100\}{\times}0.95(kg)$ 3. Several types of modified Broca's index recommended by author are as follows: I. In male, for $18{\sim}29$ age group $\{height(cm)-100\}{\times}0.90(kg)$ and for $30{\sim}59$ age group $\{height(cm)-100\}{\times}0.95(kg)$ In female, for $18{\sim}29$ age group $\{height(cm)-100\}{\times}0.90(kg)$ and for $30{\sim}39$ age group $\{height(cm)-100\}{\times}1.00(kg)$ II. In male, for all ages group $\{height(cm)-100\}{\times}0.95(kg)$ In female, for all ages group $\{height(cm)-100\}{\times}1.00(kg)$ III. In both sexes, for all ages group $\{height(cm)-100\}{\times}0.95(kg)$ Note: The first type of modified Broca's index is the most precise one in estimating standard body weight among several types established by author. 4. Error of estimated standard body weight appearing by applying modified Broca's indices is generally greater in short build persons than in tall build persons and is more dominant especially in female group.

• 한국디자인학회:학술대회논문집
• /
• 한국디자인학회 2003년도 봄 학술발표대회논문집
• /
• pp.84-85
• /
• 2003

• 대한한방소아과학회지
• /
• 제28권1호
• /
• pp.43-51
• /
• 2014

Objectives The purpose of this study is to find out the relationship between mid parental height (MPH), birth weight, current growth condition of children (height, weight, BMI, body fat percentage, bone age) and final height of the future. Methods The study was conducted with 237 children, who were 12 - 14 years old. They were analyzed to find out the relationship between MPH, birth weight, height, current weight, BMI, body fat percentage, bone age and predicted height. Results 1. As MPH was increased, height and predicted height were also increased. As MPHs in girls were increased, 'bone age - chronological age' were decreased. As MPHs in girls were increased, body fat percentages were decreased. 2. As birth weights were increased, height, weight, BMI and body fat percentages were also increased in boys. 3. As body fat percentage was increased, predicted height was decreased. As 'bone age - chronological age' was increased, predicted height was decreased. As BMI was increased, 'bone age - chronological age' was increased. As body fat percentages in boys were increased, heights were decreased. As body fat percentages in girls were increased, 'bone age - chronological age' were increased. Conclusions MPH, birth weight, current growth condition (height, weight, BMI, body fat percentage, bone age) and predicted height are correlated to each other. There are some differences between boys and girls in these relationships.