• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.292-305
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• 2021

The present study concerns uncertainty assessment of powering prediction from towing tank model tests, suggested by the International Towing Tank Conference (ITTC). The systematic uncertainty of towing tank tests was estimated by allowance of test setup and measurement accuracy of ITTC. The random uncertainty was varied from 0 to 8% of the measurement. Randomly generated inputs of test conditions and measurement data sets under systematic and random uncertainty are used to statistically analyze resistance and propulsive performance parameters at the full scale. The error propagation through an extrapolation procedure is investigated in terms of the sensitivity and coefficient of determination. By the uncertainty assessment, it is found that the uncertainty of resultant powering prediction was smaller than the test uncertainty.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.1187-1192
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• 2005

Approximately 25% of military establishments became superannuated to unable perform their function, and it influences on the environment by construction wastes and the waste of national budget, as there is no rational and objective standard even though old facilities have been replaced through modernization project. Therefore, it has been searched to introduce industrial building system that can cope with the new building-construction and transference for the improvement of existing military establishments. However, as there is no economical estimation standard for practical use, industrial building-construction is still remaining at the initial stage, and the study is insufficient too. So. in this study, I would like to develope LCC cost model for rational LCC comparative analysis between industrial construction system (Modular) and existing reinforced concrete structure and cage, and to evaluate economical efficiency through case analysis.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.839-846
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• 2022

Traditionally, the construction industry has shown low labor productivity and productivity growth. To improve labor productivity, it must first be accurately measured. The existing method uses work-sampling techniques through observation of workers' activities at certain time intervals on site. However, a disadvantage of this method is that the results may differ depending on the observer's judgment and may be inaccurate in the case of a large number of missed scenarios. Therefore, this study proposes a model to automate labor productivity measurement by monitoring workers' actions using a deep learning-based pose estimation method. The results are expected to contribute to productivity improvement on construction sites.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.183-187
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• 2015

The Risk Management (RM) is applied for managing uncertainty of project. In this circumstance, the competences of RM have a direct effect on the performance of its application. Especially, as the RM, one of the project management areas, is a peopleoriented management field, the individual behavioral competences are significant for a risk manager. Therefore, this paper describes the development of individual behavioral competences for construction project risk manager. For this, the research classifies the individual behavioral competences of RM. And, the Exploratory Factor Analysis (EFA) are applied to verify a validity of the competences. Likewise, a reliability analysis using Cronbach's alpha values is performed to test internal consistency. Based on the results, the authors carry out the Focus Group Interview (FGI) on expert panels of construction RM to confirm the hierarchical model of the individual behavioral competences. It is concluded that the proposed hierarchical model of individual behavioral competences helps construction companies to diagnose the competences of their project risk manager for progressing.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.445-449
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• 2015

Construction industry is one of the most significant sector in national economic, but the portion of construction has been falling regularly with the regional development. In spite of decrease in economic portion, role of construction industry does not changed irrespective of development, as the foundation of development. To distinguish each state of the maturity, countries are grouped on GDP per capita, than compared with variance of GVA in construction and GFCF per GDP as level of construction industry. GVAc% and GFCF% shows corn-shaped plotting in increase of GDP per capita, and each value converge to around 20% and 5% as GDP per capita increase. The definition of maturity is consist of 4 stages; pre-developing, ascending, stabilization, and maturement. Maturity of construction industry is a term of broad sense of construction industry that is easily to figure current state of regional construction and shows what normal condition of construction is in regional economy.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.1
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• pp.139-152
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• 2013

The purpose of this study is to claim the validity of tuning the architecture of neural network models for multi-class classification. A neural network model for multi-class classification is basically constructed by building a series of neural network models for binary classification. Building a neural network model, we are required to set the values of parameters such as number of hidden nodes and weight decay parameter in advance, which draws special attention as the performance of the model can be quite different by the values of the parameters. For better performance of the model, it is absolutely necessary to have a prior process of tuning the parameters every time the neural network model is built. Nonetheless, previous studies have not mentioned the necessity of the tuning process or proved its validity. In this study, we claim that we should tune the parameters every time we build the neural network model for multi-class classification. Through empirical analysis using wine data, we show that the performance of the model with the tuned parameters is superior to those of untuned models.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.1
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• pp.43-56
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• 2009

The Korean navy has made many efforts to apply the concepts of PLM (Product Lifecycle Management) and M&S to its naval design and production. However, most of the efforts that have being applied to some acquisition processes, focused only on the element technologies without information models and data frameworks. This study discusses an information model of naval ships for advanced naval acquisitions. We introduce a naval ship product model, and it refers to the DPD (Distributed Product Description) concept of SBA (Simulation-Based Acquisition). To realize the product model concept, we design a data architecture and develop a Product Model Management System (PMMS) based on a PDM System. It is validated through the case study of building the product model of the battle ship that the PMMS has the applicability to effectively manage the naval ship acquisition data on the basis of a 3D product model.

• Geomechanics and Engineering
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• v.9 no.1
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• pp.25-37
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• 2015

To predict the surface subsidence of salt rock storage, a new surface subsidence basin model is proposed based on the Logistic function from the phenomenological perspective. Analysis shows that the subsidence curve on the main section of the model is S-shaped, similar to that of the actual surface subsidence basin; the control parameter of the subsidence curve shape can be changed to allow for flexible adjustment of the curve shape. By using this model in combination with the MMF time function that reflects the single point subsidence-time relationship of the surface, a new dynamic prediction model of full section surface subsidence for salt rock storage is established, and the numerical simulation calculation results are used to verify the availability of the new model. The prediction results agree well with the numerical simulation results, and the model reflects the continued development of surface subsidence basin over time, which is expected to provide some insight into the prediction and visualization research on surface subsidence of salt rock storage.

• Journal of the Korean Society for Railway
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• v.14 no.2
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• pp.87-93
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• 2011

This work describes an availability model of highly available systems to achieve Five-9's availability. Modern railway systems have raised users' expectations of powerful "always on" services. The crucial characteristics of these highly available services are essential to many modern businesses area, such as telecommunications, railway systems, information operations, Web-based businesses, and so on. The architecture-based model of system availability is useful to assess the feasibility of meeting a high availability target. The Markov model approach is straightforward for relative system engineers to adapt when they model highly available system failure and the failure recovery process. This work proposed the improved availability model through UML2.0. It is shown that the architecture-based model of system availability is a good reasonable by its application of the railway systems.

• Steel and Composite Structures
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• v.32 no.4
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• pp.443-454
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• 2019

With the aim to put forward the analytical model for calculating the shear capacity of precast steel reinforced concrete (PSRC) beams, a static test on two full-scale PSRC specimens was conducted under four-point loading, and the failure modes and strain developments of the specimens were critically investigated. Based on the test results, a modified truss-arch model was proposed to analyze the shear mechanisms of PSRC and cast-in-place SRC beams. In the proposed model, the overall shear capacity of PSRC and cast-in-place SRC beams can be obtained by combining the shear capacity of encased steel shape with web concrete determined by modified Nakamura and Narita model and the shear capacity of reinforced concrete part determined by compatible truss-arch model which can consider both the contributions of concrete and stirrups to shear capacity in the truss action as well as the contribution of arch action through compatibility of deformation. Finally, the proposed model is compared with other models from JGJ 138 and AISC 360 using the available SRC beam test data consisting of 75 shear-critical PSRC and SRC beams. The results indicate that the proposed model can improve the accuracy of shear capacity predictions for shear-critical PSRC and cast-in-place SRC beams, and relatively conservative results can be obtained by the models from JGJ 138 and AISC 360.