• Advances in nano research
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• v.13 no.5
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• pp.499-512
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• 2022

This study investigates the efficiency of ensemble machine learning for predicting the lightweight-aggregate concrete (LWC) characteristics. A stacking ensemble (STEN) approach was proposed to estimate the dry density (DD) and 28 days compressive strength (Fc-28) of LWC using two meta-models called random forest regressor (RFR) and extra tree regressor (ETR), and two novel ensemble models called STEN-RFR and STEN-ETR, were constructed. Four standalone machine learning models including artificial neural network, gradient boosting regression, K neighbor regression, and support vector regression were used to compare the performance of the proposed models. For this purpose, a sum of 140 LWC mixtures with 21 influencing parameters for producing LWC with a density less than 1000 kg/m³, were used. Based on the experimental results with multiple performance criteria, it can be concluded that the proposed STEN-ETR model can be used to estimate the DD and Fc-28 of LWC. Moreover, the STEN-ETR approach was found to be a significant technique in prediction DD and Fc-28 of LWC with minimal prediction error. In the validation phase, the accuracy of the proposed STEN-ETR model in predicting DD and Fc-28 was found to be 96.79% and 81.50%, respectively. In addition, the significance of cement, water-cement ratio, silica fume, and aggregate with expanded glass variables is efficient in modeling DD and Fc-28 of LWC.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.848-853
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• 2004

Regarding to the project SUAV (Smart Unmanned Aerial Vehicle) in KARI (Korea Aerospace Research Institute), several engine configurations has been evaluated. However it's not an easy task to collect all the necessary data of each engine for the analysis. Usually, some kind of modeling technique is required in order to determine the unknown data. In the present paper a qualitative method for reverse engineering is proposed, in order to identify some design patterns and relationships between parameters. The method can be used to estimate several parameters that usually are not provided by the manufacturer. The method consists of modeling an existing engine and through a simulation, compare its transient behavior with its operating envelope. In the simulation several parameters such as thermodynamics, performance, safety and mechanics concerning to the definition of operation-envelope, have been discussed qualitatively. With the model, all engine parameters can be estimated with acceptable accuracy, making possible the study of dependencies among different parameters such as power-turbine total inertia, TIT, take-off time and part load, in order to check if the engine transient performance is within the design criteria. For more realistic approach and more detailed design requirements, it will be necessary to enhance the compressor map first, and more realistic estimated values must be taken into account for intake-loss, bleed-air and auxiliary power extraction. The relative importance of these “unknown” parameters must be evaluated using sensitivity analysis in the future evaluation. Moreover, fluid dynamics, thermal analysis and stress analysis necessary for the resulting life assessment of en engine, will not be addressed here but in a future paper. With the methodology presented in the paper was possible to infer the relationships between operation-envelope and engine parameters.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.12
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• pp.35-44
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• 2005

SoC(systnn-on-a-chip) requires high bandwidth system bus for performing multiple functions. Performance of the system is affected by bandwidth of the system bus. In this paper, for efficient management of the bus resource on a SoC platform, we present a latency model of the shared bus organized by multiple layers. Using the latency model, we can analyze latencies of the shared bus on a SoC. Moreover we evaluate a throughput of the bus and compare with needed throughput of the SoC platform including IPs such as MPEG or USB 2.0. And we can use the results as a criteria to find out an optimal bus architecture for the specific SoC design. For verifying accuracy of the proposed model, we compared the latencies with the simulation result from MaxSim tools. As the result of simulation, the accuracy of the IS model for a single layer and multiple layer are over $96\%\;and\;85\%$ respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.533-542
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• 2020

This study proposes the logical data model design of a spatial data model that complies with international standards for the waterworks of underground facilities. We conduct a preliminary study related to underground spatial data standards and data models, and review the status of the existing systems. Then, we defined the conceptual design direction of underground spatial data model based on the problems and issues. Next, we defined the terminology, classification, semantic relationships of waterworks. Next, for the conceptual design of the underground spatial data model, we defined the naming criteria for all data according to the waterworks classification. In addition, a logical model is drawn and described using UML (Unified Modeling Language) diagrams. Based on the results, it is expected that the accuracy related to underground facilities data will be improved.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.17 no.2
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• pp.71-76
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• 1981

In order to make a numerical modeling for the one dimensional unsteady flow which expressed by Saint Venant partial differential equations, Preissmann's implicit scheme was used, and it's stability and accuracy was mentioned. By introducing recurrence relations make it possible to use double sweep algorithm. Effective parameters to the result were the values of the $\Delta$t/$\Delta$x, $\theta$ and the chezy coefficient. In oder to get numerical solutions with enough accuracy, $\Delta$t/$\Delta$x should not be far from the value of 1, and the criteria of the $\theta$ was 0.6<$\theta$<1.0 for the stability without condition. This model should be calibrated by real field data, and expected to be developed for the simulation of the river system and to the long wave analysis for one dimensional coastal zone problem.

• Journal of Gastric Cancer
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• v.14 no.4
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• pp.259-265
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• 2014

Purpose: Survival analysis of gastric cancer patients requires knowledge about factors that affect survival time. This paper attempted to analyze the survival of patients with incomplete registered data by using imputation methods. Materials and Methods: Three missing data imputation methods, including regression, expectation maximization algorithm, and multiple imputation (MI) using Monte Carlo Markov Chain methods, were applied to the data of cancer patients referred to the cancer institute at Imam Khomeini Hospital in Tehran in 2003 to 2008. The data included demographic variables, survival times, and censored variable of 471 patients with gastric cancer. After using imputation methods to account for missing covariate data, the data were analyzed using a Cox regression model and the results were compared. Results: The mean patient survival time after diagnosis was $49.1{\pm}4.4$ months. In the complete case analysis, which used information from 100 of the 471 patients, very wide and uninformative confidence intervals were obtained for the chemotherapy and surgery hazard ratios (HRs). However, after imputation, the maximum confidence interval widths for the chemotherapy and surgery HRs were 8.470 and 0.806, respectively. The minimum width corresponded with MI. Furthermore, the minimum Bayesian and Akaike information criteria values correlated with MI (-821.236 and -827.866, respectively). Conclusions: Missing value imputation increased the estimate precision and accuracy. In addition, MI yielded better results when compared with the expectation maximization algorithm and regression simple imputation methods.

• International Journal of Ocean System Engineering
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• v.3 no.3
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• pp.116-130
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• 2013

The prediction of ocean currents in real time over the warning times of a few hours or days is required in planning many operation-related activities in the ocean. Traditionally this is done through numerical models which are targeted toward producing spatially distributed information. This paper discusses a complementary method to do so when site-specific predictions are desired. It is based on the use of a recurrent type of neural network as well as the statistical tool of model tree. The measurements made at a site in Indian Ocean over a period of 4 years were used. The predictions were made over 72 time steps in advance. The models developed were found to be fairly accurate in terms of the selected error statistics. Among the two modeling techniques the model tree performed better showing the necessity of using distributed models for different sub-domains of data rather than a unique one over the entire input domain. Typically such predictions were associated with average errors of less than 2.0 cm/s. Although the prediction accuracy declined over longer intervals, it was still very satisfactory in terms of theselected error criteria. Similarly prediction of extreme values matched with that of the rest of predictions. Unlike past studies both east-west and north-south current components were predicted fairly well.

• Advances in Computational Design
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• v.6 no.1
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• pp.55-75
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• 2021

The lightweight superstructure is beneficial for bridges in remote areas and emergency erection. In such weight-sensitive applications, the combination of fiber-reinforced polymer (FRP) as a material and box-beams as a structural system have enormous scope. This combination offers various advantages, but as a thin-walled structure, their designs are often governed by buckling criteria. FRP box-beams lose their stability either by flange or web buckling mode. In this paper, the web buckling behavior of simply supported FRP box-beam subjected to transverse load has been studied by modeling full box-beam to consider the effect of real state of stress (stress variation in length direction) and boundary conditions (rotational restraint at web-flange junction). A parametric study by varying the sectional geometry and fiber orientation is carried out by using ANSYS software. The accuracy of the FE models was ensured by verifying them against the available results provided in the literature. With the help of developed database the influential parameters (i.e., αs, βw, δw and γ) affecting the web bucklings are identified. Design trends have been developed which will be helpful to the designers in the preliminary stage. Finally, the importance of governing parameters and design trends are demonstrated through pedestrian bridge design.

• Journal of KIBIM
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• v.12 no.1
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• pp.55-61
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• 2022

Recently, demand for designing own space is increasing as the rapid growth of home furnishing market. However, there is a limitation that it is not easy to compare the style between before construction view and after view. This study aims to translate real image into another style with GAN model learned with interior images. To implement this, first we established style criteria and collected modern, natural, and classic style images, and experimented with ResNet, UNet, Gradient penalty concept to CycleGAN algorithm. As a result of training, model recognize common indoor image elements, such as floor, wall, and furniture, and suitable color, material was converted according to interior style. On the other hand, the form of furniture, ornaments, and detailed pattern expressions are difficult to be recognized by CycleGAN model, and the accuracy lacked. Although UNet converted images more radically than ResNet, it was more stained. The GAN algorithm allowed us to represent results within 2 seconds. Through this, it is possible to quickly and easily visualize and compare the front and after the interior space style to be constructed. Furthermore, this GAN will be available to use in the design rendering include interior.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.54-59
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• 2007

Recently, Apartment Reconstruction Projects are performing only with the basis of profitability without establishing either certain criteria or standard guideline. In addition, the profitability information contained in a disposal plan tends to be considered as a fixed value, and it is frequently changeable because reconstruction projects have such a long time to complete and many participants with respective interests. As mentioned above, the new approach needs to be developed which covers the limitation of the unvaried one. Consequently, this study focuses on the probability approach considering not only variances that affect the profit, but the relationship between profit and risk, and then is modeling. This study is anticipated to improve the reliability and accuracy of expected value as well as apply to the decision making criteria quantitively about potentially hidden risks in that projects.