• Structural Engineering and Mechanics
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• v.12 no.3
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• pp.313-328
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• 2001

A multi-span bridge has the peak value of resultant girder moment or membrane stress at the interior support. In this paper, the spline finite strip method (FSM) is modified to obtain the more appropriate solution at the interior support where the peak values of solution exist. The modification has been achieved by expressing the shape function with non-periodic B-splines which have multiple knots at the boundary. The modified B-splines have the useful feature for interpolating the curve with sudden change in curvature. Moreover, the modified spline FSM is very efficient in analyzing multi-span box girder bridges, since a bridge can be modeled by an assembly of strips extended along the entire bridge length. Numerical examples of the bridge analysis have been performed to verify the efficiency and accuracy of the new spline FSM.

• Smart Structures and Systems
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• v.28 no.6
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• pp.827-838
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• 2021

The dynamic displacement is considered to be an important indicator of structural safety, and becomes an indispensable part of Structural Health Monitoring (SHM) system for high-speed railway bridges. This paper proposes an indirect strain based dynamic displacement reconstruction methodology for high-speed railway box girders. For the typical box girders under eccentric train load, the plane section assumption and elementary beam theory is no longer applicable due to the bend-torsion coupling effects. The monitored strain was decoupled into bend and torsion induced strain, pre-trained multi-output support vector regression (M-SVR) model was employed for such decoupling process considering the sensor layout cost and reconstruction accuracy. The decoupled strained based displacement could be reconstructed respectively using box girder plate element analysis and mode superposition principle. For the transformation modal matrix has a significant impact on the reconstructed displacement accuracy, the modal order would be optimized using particle swarm algorithm (PSO), aiming to minimize the ill conditioned degree of transformation modal matrix and the displacement reconstruction error. Numerical simulation and dynamic load testing results show that the reconstructed displacement was in good agreement with the simulated or measured results, which verifies the validity and accuracy of the algorithm proposed in this paper.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1257-1270
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• 2016

This study deals with the prediction of the total number of movie audiences as a measure for the box office. Prediction is performed by classification techniques of data mining such as decision tree, multilayer perceptron(MLP) neural network model, multinomial logit model, and support vector machine over time such as before movie release, release day, after release one week, and after release two weeks. Predictors used are: online word-of-mouth(OWOM) variables such as the portal movie rating, the number of the portal movie rater, and blog; in addition, other variables include showing the inherent properties of the film (such as nationality, grade, release month, release season, directors, actors, distributors, the number of audiences, and screens). When using 10-fold cross validation technique, the accuracy of the neural network model showed more than 90 % higher predictability before movie release. In addition, it can be seen that the accuracy of the prediction increases by adding estimates of the final OWOM variables as predictors.

• Smart Media Journal
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• v.11 no.5
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• pp.38-47
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• 2022

Honey is one of the most significant ingredients in conventional food production in different regions of the world. Honey is commonly used as an ingredient in ethnic food. Beekeeping is performed in various locations as part of the local food culture and an occupation related to pollinator production. It is important to conduct beekeeping so that it generates food culture and helps regulate the regional environment in an integrated manner in preserving and improving local food culture. This study analyzes different types of environmental factors of a smart bee farm. The major goal of this study is to determine the best prediction model between the linear regression model (LM) and the support vector regression model (SVR) based on the environmental factors of a smart bee farm. The performance of prediction models is measured by R² value, root mean squared error (RMSE), and mean absolute error (MAE). From all analysis reports, the best prediction model is the support vector regression model (SVR) with a low coefficient of variation, and the R² values for Farm inside temperature, bee box inside temperature, and Farm inside humidity are 0.97, 0.96, and 0.44.

• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.37-46
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• 2010

In an IPTV system, the rights of the content and service provider can be protected by using Conditional Access System (CAS) and Digital Right Management (DRM). In case of the CAS, only the authorized user who has structured authentication keys can decrypt the encrypted content. However, since the CAS establishes a secure channel only between content provider and Smart Card (SC), it cannot protect the system against McCormac Hack attack which eavesdrops on unsecure channel between SC and Set-Top Box (STB) and SC cloning attack. In this paper, we propose a robust multi-STB assisted SC / STB authentication protocol which can protect the IPTV system against not only McCormac Hack attack, but also SC cloning attack. The previous works which bind a STB and a SC during the SC registration phase against the SC cloning attack does not support multi-STB environments. The proposed system which dynamically updates the STB information in subscriber management system using the bi-directional channel characteristic of IPTV system can support the user's multi-STB device effectively.

• Structural Engineering and Mechanics
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• v.15 no.2
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• pp.225-238
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• 2003

In the present study, the finite strip analysis of a box girder to simulate a ship's hull model is carried out to investigate its inelastic post-buckling behavior and to predict its ultimate flexural strength. Residual stresses and initial geometrical imperfections are both considered in the combined material and geometrical nonlinear analysis. The von-Mises yield criterion and the Prandtl-Reuss flow theory of plasticity are applied in modeling the elasto-plastic behavior of material. The Newton-Raphson iterative process is also employed in the analysis to achieve convergence. The numerical results agree well with the experimental data. The effects of some material and geometrical parameters on the ultimate strength of the structure are also investigated.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.55-61
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• 2020

This study was conducted to identify the organizational commitment to health centers in the city of G from September 1, 2018 to September 29, 2018, and empowerment, which is the output of the organization, and to examine organizational diagnosis using the Six-Box Model. In the organizational diagnosis of the health center using the Six-Box Model, the support area was 3.62 points, and the attitude toward change was 3.62 points, which was higher than other areas. In the organizational diagnosis according to gender, the scores of women were higher in males than in males. In the organizational diagnosis according to the type of jobs, the purpose, relationships, rewards, and area scores of nursing jobs were higher than those of other types of jobs. In the future, the public health center is a public institution that provides health administration and medical services to residents of the community, and it is necessary to improve the capacity of the organization through continuous health center organizational diagnosis.

• Journal of Coastal Disaster Prevention
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• v.4 no.3
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• pp.111-118
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• 2017

In this study, pull box members were designed by finite element analysis of a steel plate covering a pull box to secure its safety on the landing pier dedicated to the large research survey ship. It was assumed that the maximum load is due to the 250 tonf class crane used for unloading work when the working environment in the upper part of the landing pier was considered. The safety of the pull box was evaluated by the comparison between the yield strength of the steel plate and the result of stress analysis on the steel plate due to the crane load. It was found that the stress at the plate from the crane load exceeded the yield strength of the steel(205MPa) when the upper part of the pull box was protected by a $1950{\times}1950mm$ steel plate cover. In order to compensate for this, a concrete filled steel tube(CFT) column with a diameter of 150 mm and a steel thickness of 10 mm was reinforced at the center of the plate, and the finite element analysis was carried out. However, the maximum stress at the steel plate was higher than the yield strength of the steel in some load cases so that it was tried to find appropriate thickness of the steel plate and diameter of the CFT columns. Finally, the analysis results showed that the safety of the pull box was secured when the thickness of the steel plate and the diameter of the CFT column were increased to 30mm and 180mm, respectively.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.13-22
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• 2021

The clinical decision support system uses accumulated medical data to apply an AI model learned by machine learning to patient diagnosis and treatment prediction. However, the existing black box-based AI application does not provide a valid reason for the result predicted by the system, so there is a limitation in that it lacks explanation. To compensate for these problems, this paper proposes a system model that applies XAI that can be explained in the development stage of the clinical decision support system. The proposed model can supplement the limitations of the black box by additionally applying a specific XAI technology that can be explained to the existing AI model. To show the application of the proposed model, we present an example of XAI application using LIME and SHAP. Through testing, it is possible to explain how data affects the prediction results of the model from various perspectives. The proposed model has the advantage of increasing the user's trust by presenting a specific reason to the user. In addition, it is expected that the active use of XAI will overcome the limitations of the existing clinical decision support system and enable better diagnosis and decision support.

• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.1073-1076
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• 2011

In this paper, we propose a scalable random access scheme in SVC based DASH service that enables random access support not only for base layer of SVC but also for enhancement layers. The proposed method includes extension of segment index box ('sidx') from DASH standard, as well as new RAP Synchronization Box ('raps'). Since the proposed scheme provides random access service for movie fragments with SVC encoded video layers, adaptive scalable random access service is possible.