• Journal of Information Technology Services
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• v.11 no.1
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• pp.197-210
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• 2012

This paper presents the ways that can improve the Software Cost Estimation Guidelines in order to replace those that are expected to be abolished at February, 2012, and solve the problems that are being occurred in the current Software Cost Estimation Guidelines. By using multidimensional modeling of OLAP(On-Line Analytical Processing), this paper does three dimensional modeling that considers the product/service view, process view and skill view. Also, it presents the identification method of cost estimation data through the view of each dimension. Furthermore, it defines the software cost estimation process and adapts them into the bottom up estimation and the top down estimation. Finally, it proposes the access of cost estimation data by the multidimensional analysis of OLAP.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1266-1271
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• 2009

Formwork layout is perceived as important due to its strong tie to site works. But, most formwork is done manually and influenced by worker's skill and thus, a lot of construction errors occur. The introduction of BIM (Building Information Modeling) enables acquiring more precise information on the building shape, dimension, structure, etc. than 2D-based drawings and thus, the increased productivity, such as reduction of workload and work times, and the economic efficiency, such as reduction of formwork types and form dimensions with the consideration of constructability, are expected. This study reviewed the previous studies and formwork layout systems to derive this study's differentiations and factors to be first considered for formwork planning were derived by analyzing priorities against consideration factors. Last, a flow chart and algorithm were developed to apply the derived factors to the formwork layout module.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.365-373
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• 1999

Recently, numerous studies have demonstrated that artificial intelligence such as neural networks can be an alternative methodology for classification problems to which traditional statistical methods have long been applied. In building neural network model, the selection of independent and dependent variables should be approached with great care and should be treated as a model construction process. Irrespective of the efficiency of a learning procedure in terms of convergence, generalization and stability, the ultimate performance of the estimator will depend on the relevance of the selected input variables and the quality of the data used. Approaches developed in statistical methods such as correlation analysis and stepwise selection method are often very useful. These methods, however, may not be the optimal ones for the development of neural network models. In this paper, we propose a genetic algorithms approach to find an optimal or near optimal input variables for neural network modeling. The proposed approach is demonstrated by applications to bankruptcy prediction modeling. Our experimental results show that this approach increases overall classification accuracy rate significantly.

• Korean Journal of Childcare and Education
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• v.16 no.1
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• pp.115-143
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• 2020

Objective: The purpose of this study was to examine underlying types of developmental trajectories of adaptation to child care among infants and toddlers. This study also aimed to identify latent classes in their child care adaptation types in order to find predictors that account for individual differences. Methods: Participants were 420 mothers of infants and toddlers and 123 teachers. The levels of child care adaptation of participating infants and toddlers were rated monthly from early April to June, 2019. The collected data were analyzed using growth mixture modeling, latent class analysis and multinominal logistic analysis. Results: The results of growth trajectories of child care adaptation showed there were two to four latent groups by dimension of child care adaptation. Also, the groups of individual dimensions of child care adaptation were classified into three latent classes, which were 'complying and positive group', 'negative group', and 'individualized group. Multinominal logistic analysis revealed that children's age, gender, and temperament differentiated the three latent classes of adaptation to child care. Conclusion/Implications: The results show individual characteristics that infants and toddlers possess should be prudently considered in order for successful adaptation to child care.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.146-151
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• 2001

This study is an investigation for the ADS optimum design by using FEM. We write out program which express ADS perfectly and reduce the required time for correcting of model to the minimum in solution and manufacture result. We complete algorithm which can plan optimum forming of model by feedback error information in CAE. For that, we draw up ADS program which modeling rachet wheel by using visual LISP and telegraph to ANSYS, structural solution program, we can solve stress solution. Then we correct model by feedback date obtaining in solution process, repeat course following stress solution again and do modeling rachet wheel for optimum forming. That is our aim. As a result of experience, we can develope automatic design program using Visual LISP and exhibit ADS as modeling third dimension CAD for optimum design. Also, we develop optimum design algorithm using ADS and FEM. In rachet wheel, greatest equivalence stress originates in key groove comer and KS standard is proved the design for security.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.47 no.3
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• pp.257-266
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• 2011

Recently, the manufacturers of life-jacket are very interested in the acquisition of USCG(US Coast Guard) approval because the acquisition of USCG approval has an important role in the purchasing decision of the buyer's. Be based on criterion of USCG, we studied how to predict the change of floating position of human model with life-jacket to verify the backside restore. For this, in this study, the human model and the lifejacket was modeled in three dimension, the application program for prediction of floating position was developed, and plugged-in commercial program.

• Journal of Mechanical Science and Technology
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• v.19 no.7
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• pp.1393-1404
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• 2005

Fatigue crack growth and life have been estimated based on established empirical equations. In this paper, an alternative method using artificial neural network (ANN) -based model developed to predict fatigue damages simultaneously. To learn and generalize the ANN, fatigue crack growth rate and life data were built up using in-plane bending fatigue test results. Single fracture mechanical parameter or nondestructive parameter can't predict fatigue damage accurately but multiple fracture mechanical parameters or nondestructive parameters can. Existing fatigue damage modeling used this merit but limited real-time damage monitoring. Therefore, this study shows fatigue damage model using backpropagation neural networks on the basis of X -ray half breadth ratio B / $B_o$, fractal dimension $D_f$ and fracture mechanical parameters can estimate fatigue crack growth rate da/ dN and cycle ratio N / $N_f$ at the same time within engineering limit error ($5\%$).

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.158-158
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• 2019

Recent studies show the possibility of more frequent extreme events as a result of the changing climate. These weather extremes, such as excessive rainfall, result to debris flow, river overflow and urban flooding, which post a substantial threat to the community. Therefore, an effective flood model is a crucial tool in flood disaster mitigation. In recent years, a number of flood models has been established; however, the major challenge in developing effective and accurate inundation models is the inconvenience of running multiple models for separate conditions. Among the solutions in recent researches is the development of the combined 1D-2D flood modeling. The coupled 1D-2D river flood modeling allows channel flows to be represented in 1D and the overbank flow to be modeled over two-dimension. To test the efficiency of this approach, this research aims to assess the capability of HEC-RAS model's implementation of the combined 1D-2D hydraulic simulation of river overflow inundation, and compare with the results of GERIS and FLUMENS 2D flood model. Results show similar output to the flood models that had used different methods. This proves the applicability of the HEC-RAS 1D-2D coupling method as a powerful tool in simulating accurate inundation for flood events.

• The Journal of Information Systems
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• v.31 no.2
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• pp.239-261
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• 2022

Purpose The purpose of this study is to explore and compare changes in tourist opinion during the COVID-19 pandemic. Since the COVID-19 outbreak has caused changes in all areas of our lives, the conditions related to confinement during a lockdown have led to changes in tourists' habits and behaviors. Design/methodology/approach To analyze opinion changes about tourist attractions, this study performed topic modeling by summarizing topics into five dimensions: management, scenery, price, suggestion, and safety; then, based on the topic modeling results, sentiment analysis and emotion analysis were conducted to explore the change of tourists' opinion during the COVID-19 pandemic. Findings According to the results, this study confirmed the pandemic's positive effect on tourists' opinions about attractions after the COVID 19 outbreak. Presumably due to the absence of lines and crowed. Moreover, the dimension 'Safety' started to appear in US tourists' attractions reviews only in the period after the outbreak and during the mass vaccination. These results mean that tourists started to care more about safety due to the impact of the COVID-19 pandemic.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.5
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• pp.381-387
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• 2017

Fiber-reinforced composites not only have a direction of thermal expansion coefficient, but also inevitably suffer thermal stress effects due to the difference between the manufacturing process temperature and the actual use temperature. The damage caused by thermal stress is more prominent in the case of thick composite laminates, which are increasingly applied in the aerospace industry, and have a great influence on the mechanical function and fracture strength of the laminates. In this study, the dimensional reduction and thermal stress recovery theory of composite beam structure having high slenderness ratio is introduced and show the efficiency and accuracy of the thermal stress comparison results between the 3-D finite element model and the dimension reduction beam model. Efficient recovery analysis study will be introduced by reconstructing the thermal stress of the composite beam section applied to the thermal environment by constructing the dimensional reduction modeling and recovery relations.