• International conference on construction engineering and project management
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• 2015.10a
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• pp.612-613
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• 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
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• v.12 no.3
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• pp.311-316
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• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3477-3483
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• 2015

A reasonable process for the activity duration estimation is required for the successful construction management because it directly affects the entire construction duration and budget. However, the activity duration is being generally estimated by the experience of the construction manager. This study suggests an estimation model of construction activity duration using neural network theory. This model estimates the activity duration by considering both the quantitative and qualitative elements, and the model is verified by a case study. Because the 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.

• Proceedings of the KOR-KST Conference
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• 1998.09a
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• pp.160-167
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• 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.

• Korean Journal of Community Nutrition
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• v.16 no.3
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• pp.315-323
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• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.1
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• pp.1-11
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• 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.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.397-402
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• 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.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.4
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• pp.359-371
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• 2001

Project scheduling under resource constraint conditions have contained to many uncertain factors and it is perfonned by human experts. The expert identifies the activities of the project, decides the precedent relationships between these activities, and then construct the schedule using expected activity's duration. At this time, most of the scheduling methods concentrate on one of scheduling factor between activity duration and cost. And the activity duration, which is the most important factor in scheduling, is decided by heuristic of expert. Therefore it may cause uncertainty of activity duration decision and the use of this activity duration may increase the uncertainty of constructed schedule. This paper proposes Fuzzy-MOEH scheduling algorithm, which is the aggregation of the fuzzy number for deciding activity duration and applies the cost function for solving the problems of previous scheduling methods. This paper also analyze the utility and property of Fuzzy-MEOH algorithm through the comparison between Fuzzy-MEOH algorithm and existing MEOH algorithm.

• Journal of Nutrition and Health
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• v.29 no.9
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• pp.1003-1012
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• 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.3
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• pp.137-149
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• 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.