• 한국환경과학회지
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• 제25권10호
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• pp.1433-1444
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• 2016

South Korea is a maritime nation, surrounded by water on three sides; hence, it is important to preserve in a sustainable manner. Most areas, especially those bordering the East Sea, have been suffering from severe coastal erosion. Information on the sediment yield of a river basin is an important requirement for water resources development and management. In Korea, data on suspended sediment yield are limited owing to a lack of logistic support for systematic sediment sampling activities. This paper presents an integrated approach to estimate the sediment yield for ungauged coastal basins by using a soil erosion model and a sediment delivery rate model in a geographic information system (GIS)-based platform. For applying the sediment yield model, a basin specific parameter was validated on the basis of field data, that, ranging from 0.6 to 1.2 for the 19 gauging stations. The calculated specific sediment yield ranged from 17 to $181t/km^2.yr$ in the various basin sizes of Korea. We obtained reasonable sediment yield values when comparing the measured data trends around the world with those in Korean basins.

• 한국농림기상학회지
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• 제11권3호
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• pp.118-122
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• 2009

Net Radiation ($R_N$) is the major driving force for biophysical and biogeochemical processes in the terrestrial ecosystems, which is one of the most critical variables in both measurement and modeling. Despite its importance, there are only 10 weather stations conducting $R_N$ measurements among the 544 stations operated by Korea Meteorological Administration (KMA; KMA, 2008). The measurement of incoming shortwave radiation ($R_S{\downarrow}$) is, however, conducted at 22 stations while that of sunshine duration is conducted at all the manned stations. In this context, the recent research for estimating $R_N$ using $R_S{\downarrow}$ in Korean peninsula by Kwon (2009) is of great worth. The author used a linear regression and the radiation balance methods. We generally agree with the author that, in terms of simplicity and practicality, both methods show reliable applicability for estimating $R_N$. We noted, however, that the author's experimental method and analysis need some clarification and improvement, that are addressed in the following perspectives: (1) the use of daily integrated data for regression, (2) the use of measured albedo, (3) the use of linear coefficients for whole year data, (4) methodological improvement, (5) the use of sunshine duration, and (6) the error assessment.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1152-1154
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• 2003

The needs of 3-D data have been increasing for various applications like visualization, 3-D modeling, planning and management as well as entertainment. Mobile mapping has become a quick and practical means for acquiring necessary 3-D data for above-mentioned applications. A mobile mapping system mainly consists of two main components, viz. data acquisition devices and positioning devices. The data acquisition devices consist of CCD cameras or/and laser scanners. The positioning devices consist of GPS, INS, Odometer (shaft encoder) and some other referencing devices. The overall accuracy of mobile mapping system depends on the accuracy of positioning devices and their integrated output. Though, GPS is the main input device for the position information, the signal is not available for the computation of position all the times in urban area. The GPS satellites are normally obstructed by high-rise buildings. Thus it is very important to understand the accuracy of such a system in different environments and means to solve such problems. We have developed a mobile mapping system called VLMS (Vehicle-borne Laser Mapping System), which consists of CCD Cameras, Laser scanners, GPS, INS and Odometer. In this paper, we will present and discuss the accuracy of this system with data acquired in different environments (open area, urban area, tunnel, express way etc) by analyzing the data with respect to other existing digital data.

• Advances in nano research
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• 제16권2호
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• pp.155-164
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• 2024

The rapid evolution of intelligent sports equipment and gadgets has led to the transformation of smartphones into personalized coaching devices. This transformative role is central in today's technologically advanced landscape, addressing the needs of individuals with contemporary lifestyles. The development of intelligent sports gadgets is geared towards elevating overall quality of life by facilitating sports activities, workouts, and promoting health preservation. This categorization yields two primary types of devices: smart sports devices for exercise and smart health control devices, which encompass functionalities such as blood pressure monitoring and muscle volume measurement. Illustrative examples include smart headbands, smart socks, smart wristbands, and smart shoe soles. Significantly, the global market for smart sports devices has garnered substantial popularity among enthusiasts. Moreover, the integration of sensors within these devices has instigated a revolution in group and professional sports, facilitating the calculation of impact intensity and ball speed. The utilization of various types of smart sports equipment has proliferated, encompassing applications in both sports' performance and health monitoring across diverse demographics. This article conducts an assessment of the application of nanotechnology in the continuous modeling of the magnetic electromechanical sensor integrated within smart shoe soles, with a specific emphasis on its implementation in soccer training. The exploration delves into the nuanced intersection of nanotechnology and sports equipment, elucidating the intricate mechanisms that underlie the transformative impact of these advancements.

• 한국기후변화학회지
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• 제9권1호
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• pp.1-12
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• 2018

There is an emphasis on the importance of adaptation against to climate change and related natural disasters. As a result, various climate information with different time-scale can be used for science-based climate change adaptation policy. From the aspects of Global Framework for Climate Services (GFCS), various time-scaled climate information in Korea is mainly produced by Korea Meteorological Administration (KMA) However, application of weather and climate information in different application sectors has been done individually in the fields of agriculture and water resources mostly based-on weather information. Furthermore, utilization of climate information including seasonal forecast and climate change projections are insufficient. Therefore, establishment of the Cooperation Center for Application of Weather and Climate Information is necessary as an institutional platform for the UIP (User Interface Platform) focusing on multi-model ensemble (MME) based climate service, seamless climate service, and climate service based on multidisciplinary approach. In addition, APCC Integrated Modeling Solution (AIMS) was developed as a technical platform for UIP focusing on user-centered downscaling of various time-scaled climate information, application of downscaled data into impact assessment modeling in various sectors, and finally producing information can be used in decision making procedures. AIMS is expected to be helpful for the increase of adaptation capacity against climate change in developing countries and Korea through the voluntary participation of producer and user groups within in the institutional and technical platform suggested.

• Clinical and Experimental Reproductive Medicine
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• 제48권2호
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• pp.163-173
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• 2021

Objective: This study aimed to characterize a validated model for predicting oocyte retrieval in controlled ovarian stimulation (COS) and to construct model-based nomograms for assistance in clinical decision-making regarding the gonadotropin protocol and dose. Methods: This observational, retrospective, cohort study included 636 women with primary unexplained infertility and a normal menstrual cycle who were attempting assisted reproductive therapy for the first time. The enrolled women were split into an index group (n=497) for model building and a validation group (n=139). The primary outcome was absolute oocyte count. The dose-response relationship was tested using modified Poisson, negative binomial, hybrid Poisson-E_max, and linear models. The validation group was similarly analyzed, and its results were compared to that of the index group. Results: The Poisson model with the log-link function demonstrated superior predictive performance and precision (Akaike information criterion, 2,704; λ=8.27; relative standard error (λ)=2.02%). The covariate analysis included women's age (p<0.001), antral follicle count (p<0.001), basal follicle-stimulating hormone level (p<0.001), gonadotropin dose (p=0.042), and protocol type (p=0.002 and p<0.001 for short and antagonist protocols, respectively). The estimates from 500 bootstrap samples were close to those of the original model. The validation group showed model assessment metrics comparable to the index model. Based on the fitted model, a static nomogram was built to improve visualization. In addition, a dynamic electronic tool was created for convenience of use. Conclusion: Based on our validated model, nomograms were constructed to help clinicians individualize the stimulation protocol and gonadotropin doses in COS cycles.

• 산업경영시스템학회지
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• 제39권1호
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• pp.9-16
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• 2016

The project schedule risk in the engineering and facility construction industry is increasingly considered as important management factor because the risks in terms of schedule or deadline may significantly affect the project cost. Especially, the project-based operating companies attempt to find the best estimate of the project completion time for use at their proposals, and therefore, usually have much interest in accurate estimation of the duration of the projects. In general, the management of projects schedule risk is achieved by modeling project schedule with PERT/CPM techniques, and then performing risk assessment with simulation such as Monte-Carlo simulation method. However, since these approaches require the accumulated executional data, which are not usually available in project-based operating company, and, further, they cannot reflect various schedule constraints, which usually are met during the project execution, the project managers have difficulty in preparing for the project risks in advance of their occurrence in the project execution. As these constraints may affect time and cost which role as the crucial evaluation factors to the quality of the project result, they must be identified and described in advance of their occurrence in the project management. This paper proposes a Bayesian Net based methodology for estimating project schedule risk by identifying and enforcing the project risks and its response plan which may occur in storage tank engineering and construction project environment. First, we translated the schedule network with the project risks and its response plan into Bayesian Net. Second, we analyzed the integrated Bayesian Net and suggested an estimate of project schedule risk with simulation approach. Finally, we applied our approach to a storage tank construction project to validate its feasibility.

• 해양환경안전학회지
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• 제19권3호
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• pp.290-301
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• 2013

The docking analysis of a global ship structure is requested to evaluate its structural safety against the reaction forces at supports during docking works inside a dry dock. That problem becomes more important recently as the size of ships is getting larger and larger. The docking supports are appropriately arranged in a dock to avoid their excessive reaction forces which primarily cause the structural damages in docking a ship and, up to now, the structural safety has been assessed against the support arrangement by the finite element analysis (FEA) of a global ship structure. However, it is complicated to establish the finite element model of the ship in the current structural design environment of a shipyard and it takes over a month to finish the work. This paper investigates a simple and fast approach to carry out a ship docking analysis by a simplified grillage model and to assign the docking supports position on the model. The grillage analysis was considered from the motivation that only the reaction forces at supports are sufficient to assess their arrangement. Since the simplified grillage model of the ship cannot guarantee its accuracy quantitatively, modeling strategies are proposed to improve the accuracy. In this paper, comparisons between the proposed approach and three-dimensional FEA for typical types of ships show that the results from the present grillage model have reasonably good agreement with the FEA model. Finally, an integrated program developed for docking supports planning and its evaluation by the proposed approach is briefly described.

• Advances in Computational Design
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• 제5권2호
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• pp.127-146
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• 2020

Building Information Modeling (BIM) is increasingly used throughout the facility's life cycle for various applications, such as design, construction, facility management, and maintenance. For existing buildings, the geometry of as-built BIM is often constructed using dense, three dimensional (3D) point clouds data obtained with laser scanners. Traditionally, as-built BIM systems do not contain the material and textural information of the buildings' elements. This paper presents a semi-automatic method for generation of material and texture rich as-built BIM. The method captures and integrates material and textural information of building elements into as-built BIM using thermal infrared sensing (TIS). The proposed method uses TIS to capture thermal images of the interior walls of an existing building. These images are then processed to extract the interior walls using a segmentation algorithm. The digital numbers in the resulted images are then transformed into radiance values that represent the emitted thermal infrared radiation. Machine learning techniques are then applied to build a correlation between the radiance values and the material type in each image. The radiance values were used to extract textural information from the images. The extracted textural and material information are then robustly integrated into the as-built BIM providing the data needed for the assessment of building conditions in general including energy efficiency, among others.

• 한국물환경학회지
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• 제29권5호
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• pp.681-690
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• 2013

Watershed models have been increasingly used to support an integrated management of land and water, non-point source pollutants, and implement total daily maximum load policy. However, these models demand a great amount of input data, process parameters, a proper calibration, and sometimes result in significant uncertainty in the simulation results. For this reason, uncertainty analysis is necessary to minimize the risk in the use of the models for an important decision making. The objectives of this study were to evaluate three different uncertainty analysis algorithms (SUFI-2: Sequential Uncertainty Fitting-Ver.2, GLUE: Generalized Likelihood Uncertainty Estimation, ParaSol: Parameter Solution) that used to analyze the sensitivity of the SWAT(Soil and Water Assessment Tool) parameters and auto-calibration in a watershed, evaluate the uncertainties on the simulations of runoff and sediment load, and suggest alternatives to reduce the uncertainty. The results confirmed that the parameters which are most sensitive to runoff and sediment simulations were consistent in three algorithms although the order of importance is slightly different. In addition, there was no significant difference in the performance of auto-calibration results for runoff simulations. On the other hand, sediment calibration results showed less modeling efficiency compared to runoff simulations, which is probably due to the lack of measurement data. It is obvious that the parameter uncertainty in the sediment simulation is much grater than that in the runoff simulation. To decrease the uncertainty of SWAT simulations, it is recommended to estimate feasible ranges of model parameters, and obtain sufficient and reliable measurement data for the study site.