• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2004.11a
• /
• pp.575-578
• /
• 2004

Since a construction project is a series of works that utilizes resources to accomplish the project goal for a given time period, efficient resource management is a prerequisite for the success of the project. Two major areas of resource management are resource constrained scheduling focusing on the limited resource availability and resource leveling focusing on smoothing resource usage pattern on the fixed project completion time. It is not available, however, to apply both techniques to a project at the same time. This paper proposes a model to enhance the minimum moment algorithm of resource leveling, aiming to find an efficient usage of resources and an appropriate project completion time. A survey is performed to evaluate the major five factors using the AHP.

• Journal of Climate Change Research
• /
• v.9 no.1
• /
• pp.31-45
• /
• 2018

This study implemented the prediction of drought properties (number of drought events, intensity, duration) using the user-oriented systematical procedures of downscaling climate change scenarios based the multiple global climate models (GCMs), AIMS (APCC Integrated Modeling Solution) program. The drought properties were defined and estimated with Effective Drought Index (EDI). The optimal 10 models among 29 GCMs were selected, by the estimation of the spatial and temporal reproducibility about the five climate change indices related with precipitation. In addition, Simple Quantile Mapping (SQM) as the downscaling technique is much better in describing the observed precipitation events than Spatial Disaggregation Quantile Delta Mapping (SDQDM). Even though the procedure was systematically applied, there are still limitations in describing the observed spatial precipitation properties well due to the offset of spatial variability in multi-model ensemble (MME) analysis. As a result, the farther into the future, the duration and the number of drought generation will be decreased, while the intensity of drought will be increased. Regionally, the drought at the central regions of the Korean Peninsula is expected to be mitigated, while that at the southern regions are expected to be severe.

• Korean Journal of Construction Engineering and Management
• /
• v.5 no.5 s.21
• /
• pp.126-134
• /
• 2004

Since a construction project is a series of works that utilizes resources to accomplish the project goal for a given time period, efficient resource management is a prerequisite for the success of the project. Two major areas of resource management are resource constrained scheduling focusing on the limited resource availability and resource leveling focusing on smoothing resource usage pattern on the fixed project completion time. It is not available, however, to apply both techniques to a project at the same time. This paper proposes a model to enhance the minimum moment algorithm of resource leveling, aiming to find an efficient usage of resources and an appropriate project completion time. A survey was performed to evaluate the major five factors in the model. A case study demonstrates the value of the proposed resource leveling technique.

• Korean Journal of Remote Sensing
• /
• v.33 no.5_2
• /
• pp.741-750
• /
• 2017

The objective of this study was to estimate corn and soybean yield in Illinois and Iowa in USA using satellite and meteorological data. MODIS products for NDVI were downloaded from a NASA website. Each layer was processed to convert projection and extract layers for NDVI. Relations of NDVI from 2002 to 2012 with corn and soybean yield were investigated to find informative days for rice yield estimation. Weather data for the county of study state duration from 2002 to 2012 to correlate crop yield. Multiple regression models based on MODIS NDVI and rainfall were made to estimate corn and soybean yields in study site. Corn yields estimated for 2013 were $10.17ton\;ha^{-1}$ in Illinois, $10.21ton\;ha^{-1}$ in Iowa and soybean yields estimated were $3.11ton\;ha^{-1}$ in Illinois, $2.58ton\;ha^{-1}$ in Iowa, respectively. Corn and Soybean yield distributions in 2013 were mapped to show spatial variability of crop yields of the Illinois and Iowa state.