• 국제학술발표논문집
• /
• The 6th International Conference on Construction Engineering and Project Management
• /
• pp.612-613
• /
• 2015

As a construction project is recently becoming large-scaled and complex, construction process plan and management for successful performance of a construction project has become more important. Especially a reasonable estimation plan of activity duration is required because the activity duration is directly related to the determination of the entire project duration and budget. However, the activity duration is used to estimate by the experience of a construction manager and past construction records. Furthermore, the prediction of activity duration is more difficult because there is some uncertainty caused by various influencing factors in a construction project. This study suggests an estimation model of construction activity duration using neural network theory for a more systematic and objective estimation of each activity duration. Because suggested model estimates the activity duration by a reasonable schedule plan, it is expected to reduce the error between planning duration and actual duration in a construction project. And it can be a more systematic estimation method of activity duration comparing to the estimation method by experience of project manager.

• Safety and Health at Work
• /
• 제12권3호
• /
• pp.311-316
• /
• 2021

Background: The present study investigated the association between two domains of physical activity (occupational physical activity [OPA] and leisure-time physical activity [LTPA]) and sleep duration. Methods: We investigated 3,421 paid workers from the Korea National Health and Nutrition Examination Survey, 2014-2015. Sleep duration was categorized into three categories (short for less than 5 h, optimal for 5-9 h, and long for more than 9 h). OPA and LTPA were defined in terms of answers to relevant questions. Odds ratios were calculated for sleep duration according to each physical activity domain using multinomial logistic regression models. Results: There were 464 subjects (13.6%) who showed short sleep duration, and 169 subjects (4.9%) who showed long sleep duration. Prevalence of OPA and LTPA was higher in male workers than in female workers (for OPA: 3.67% and 1.76%, respectively, p = 0.0108; for LTPA: 16.14% and 6.07%, respectively, p < 0.0001). The odds ratio of OPA for long sleep duration in female workers was 3.35 (95% confidence interval, 1.37-8.21). Otherwise, LTPA was not associated with sleep duration in female paid workers, nor both physical activity domains in male paid workers. Conclusion: Female paid workers with work-related physical activity were at risk of oversleeping. These findings also suggested that physical activity has distinct associations with sleep duration according to the physical activity domains and sex.

• 한국산학기술학회논문지
• /
• 제16권5호
• /
• pp.3477-3483
• /
• 2015

공정계획 수립 시 각 공정별 작업기간 산정은 프로젝트 전체 공사기간 및 사업비용 결정과 직결되기 때문에 합리적인 산정계획이 요구된다. 그러나 일반적으로 작업기간 산정은 공사 담당자의 경험과 직관을 통해 이루어지고 있고, 다양한 영향요인에 의한 불확실성으로 인해 예측에 어려움이 있다. 이에 본 연구에서는 작업기간 산정에 영향을 미치는 다양한 요인을 고려할 수 있도록 신경망 기반 건설공사 공정별 작업기간 산정 모형을 제시하고자 한다. 본 연구에서는 정량적 및 정성적 요인을 모두 고려하여 작업기간 산정 모형을 구축하고, 사례적용을 통해 모형의 적용가능성을 검토하였다. 또한 영향요인 상관성분석을 실시하여 구축된 신경망 구조의 적합성을 판단하였다. 연구에서는 작업기간 산정 모형을 통해 합리적인 일정계획을 제공함으로써 계획공사기간과 실제공사기간의 오차율을 줄이는데 도움을 줄 수 있을 것으로 기대된다.

• 대한교통학회:학술대회논문집
• /
• 대한교통학회 1998년도 Proceedings The 4th International Transport Symposium
• /
• pp.160-167
• /
• 1998

Recent world-wide interest in activity-based travel behavior modeling has generated an entirely new perspective on how the profession views the travel demand process. This paper seeks to further promote the case of activity-based travel behavior models by providing some empirical evidence of relationship between travel time and activity duration decision for worker with transportation panel data. The travel time from home to work and from work to home, without activity involvement, is estimated by the Ordinary Least Squares (OLS) method. And, the travel time to and from the selected activity and the activity duration are modeled simultaneously by the Three Stage Least Squares (3SLS) method due to the endogenous relationship between travel time and activity duration. Two kinds of models, OLS and 3SLS, include selectivity bias corrections in a discrete/continuous framework, because of the inter-relationship between the choice of activity type/travel mode (discrete) and the travel time/activity duration (continuous). Estimation is undertaken using a sample of over 1300 household two-day trip diaries collected from the same travelers in the Seattle area in 1989. The behavioral consequences of these models provide interesting and provocative findings that should be of value to transportation policy formulation and analysis.

• 대한지역사회영양학회지
• /
• 제16권3호
• /
• pp.315-323
• /
• 2011

There are a few studies that reported the association of sleep duration with calorie intake and energy expenditure. Using cross-sectional data from a population-based prospective study, we evaluated the association of sleep duration with indicators of obesity including body mass index and waist circumference, calorie intake and its proportion of macronutrients, and physical activity. The study subjects were 4,226 male and female adults, who were aged 40 to 69 years and were free of diagnosed cardiovascular disease, diabetes mellitus, and dyslipidemia at baseline. Robust regression analysis was used to analyze associations. The study found that sleep duration is inversely associated with waist circumference, calorie intake, and percent of calories from fat intake and is positively associated with percent of calories from carbohydrate intake and physical activity. The inverse association between sleep duration and waist circumference was stronger among men than among women. The inverse association between sleep duration and calorie intake was stronger among women than among men and such association was also stronger among obese persons than those with a normal body mass index. The positive association between sleep duration and physical activity was strongly demonstrated regardless of sex or obesity. Physical activity is positively associated with sleep duration independent of potential confounding factors including age, sex, income, occupation, marital status, education, smoking status, waist circumference, calorie and macronutrient intake, and alcohol intake.

• 대한산업공학회지
• /
• 제43권1호
• /
• pp.1-11
• /
• 2017

Stochastic resource-constrained project scheduling problem is an extension of resource-constrained project scheduling problem such that activity duration has stochastic nature. In real situation where activity duration is not known until the activity is finished, open-loop based static policies such as activity-based policy and priority-based policy will not well cope with duration variability. Then, a dynamic policy based on closed-loop decision making will be regarded as an alternative toward achievement of minimal makespan. In this study, a dynamic policy designed to select activities to start at each decision time point is illustrated. The performance of static and dynamic policies based on variable neighborhood search is evaluated under the discrete-event simulation environment. Experiments with J120 sets in PSPLIB and several probability distributions of activity duration show that the dynamic policy is superior to static policies. Even when the variability is high, the dynamic policy provides stable and good solutions.

• 국제학술발표논문집
• /
• The 5th International Conference on Construction Engineering and Project Management
• /
• pp.397-402
• /
• 2013

In super-tall building construction projects, schedule risk factors which vertically change and are not found in the low and middle-rise building construction influence duration of a project by vertical attribute; and it makes hard to estimate activity or overall duration of a construction project. However, the existing duration estimating methods, that are based on quantity and productivity assuming activities of the same work item have the same risk and duration regardless of operation space, are not able to consider the schedule risk factors which change by the altitude of operation space. Therefore, in order to advance accuracy of duration estimation of super-tall building projects, the degree of changes of these risk factors according to altitude should be analyzed and incorporated into a duration estimating method. This research proposes a simulation model using Monte Carlo method for estimating activity duration incorporating schedule risk factors by weather conditions in a super-tall building. The research process is as follows. Firstly, the schedule risk factors in super-tall building are identified through literature and expert reviews, and occurrence of non-working days at high altitude by weather condition is identified as one of the critical schedule risk factors. Secondly, a calculating method of the vertical distributions of the weather factors such as temperature and wind speed is analyzed through literature reviews. Then, a probability distribution of the weather factors is developed using the weather database of the past decade. Thirdly, a simulation model and algorithms for estimating non-working days and duration of each activity is developed using Monte-Carlo method. Finally, sensitivity analysis and a case study are carried out for the validation of the proposed model.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
• /
• 제7권4호
• /
• pp.359-371
• /
• 2001

자원제약 하에서의 프로젝트 스케줄링 문제는 많은 불확실성의 요소들을 내포하고 있으며 스케줄의 구성은 전문가에 의한 자의적 판단에 따르는 것이 일반적 현상이다. 전문가는 스케줄을 구성하기 위해 자신의 경험을 토대로 프로젝트 진행을 위한 작업(activity)들을 식별하고 이 작업들 사이의 선행관계를 규정하여 각 작업들에 대한 예상 시간을 이용하여 스케줄을 작성한다. 이 때 대부분의 스케줄링 방법들은 비용과 작업기간 두 요소들 중 한 요소에 집중하게 된다. 또한 스케줄 작성의 중요한 요소인 작업기간 결정이 전문가의 경험에 의존하여 결정됨으로써 결정된 작업기간의 불확실성을 초래할 수 있으며 따라서 이 불확실한 작업기간을 이용하여 구성된 스케줄의 불확실성이 증대되는 문제를 내포하고 있다. 이와 같은 문제 즉 스케줄 구성에 있어 작업기간의 불확실성과 작업비용을 함께 고려하지 못하는 문제를 해결하기 위해 이 논문에서는 Fuzzy 개념을 이용한 작업기간의 정형화를 시도하며 아울러 정형된 퍼지 작업 기간과 결합 가능한 퍼지 작업비용을 도입하여 작업기간과 작업비용을 함께 고려하는 Fuzzy-MOEH 스케줄링 알고리즘을 제안한다. 아울러 이 논문에서 제안한 Fuzzy-MOEH 알고리즘과 기존 MOEH 알고리즘의 수행 결과에 대한 비교를 통해 Fuzzy-MOEH 알고리즘의 효용성 및 특성을 분석한다.

• Journal of Nutrition and Health
• /
• 제29권9호
• /
• pp.1003-1012
• /
• 1996

We examined the relationship among riboflavin intake, work activity, erythrocyte glutathione reductase activity coefficient(EGR AC)and urinary riboflavin excretion. We also attempted to determine factors affecting seasonal riboflavin status of rural women. All information about nutrient intake, work activity and riboflavin biochemical status was repeatly collected in three seasons ; farming season(June), harvest season(October), nonfarming season(February). EGR AC was negatively correlated with riboflavin intake(P<0.005) and positively correlated with the duration(min) of farming activity(P<0.005) and the percentage of lean body mass(LBM) (%) representing long term physical activity(P<0.05) in harvestseason. Urinary riboflavin excretion was positively correlated with the ratio of riboflavin intake to 1,000kcal of energy expenditure (P<0.05) in farming season and negatively correlated with the duration(min) of farming activity (P<0.05) and crude nitrogen balance(P<0.005) in harvest season. It appeared that EGR AC seems to increase and urinary riboflavin excretion seems to decrease as work activity increase. Therefore work activity would be expected to deteriorate riboflavin status. Multiple regression analysis of variables showed that in general EGR AC was affected by riboflavin and energy intakes, energy expenditure, energy balance, the duration(min) of farming activity, LBM (%). Urinary riboflavin excretion was affected by riboflavin and protein intakes, LBM(kg) and crude nitrogen balance. Crude nitrogen balance affected urinary riboflavin excretion in all seasons. The result indicated that work activity as well as nutrient intake seemed to affect riboflavin status, especially EGR AC was affected preferentially be work activity in all seasons.

• 한국경영과학회지
• /
• 제30권3호
• /
• pp.137-149
• /
• 2005

This study proposes a framework enhancing the accuracy of estimation for project duration by combining linear Bayesian updating scheme with the learning curve effect. Activities in a particular project might share resources in various forms and might be affected by risk factors such as weather Statistical dependence stemming from such resource or risk sharing might help us learn about the duration of upcoming activities in the Bayesian model. We illustrate, using a Monte Carlo simulation, that for partially repetitive projects a higher degree of statistical dependence among activity duration results in more variation in estimating the project duration in total, although more accurate forecasting Is achievable for the duration of an individual activity.