• Structural Engineering and Mechanics
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• v.55 no.5
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• pp.953-964
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• 2015

A model has been proposed that can predict the ultimate torsional strength of single-box multi-cell reinforced concrete box girder under combined loading of bending, shear and torsion. Compared with the single-cell box girder, this model takes the influence of inner webs on the distribution of shear flow into account. According to the softening truss theory and thin walled tube theory, a failure criterion is presented and a ultimate torsional strength calculating procedure is established for single-box multi-cell reinforced concrete box girder under combined actions, which considers the effect of tensile stress among the concrete cracks, Mohr stress compatibility and the softened constitutive law of concrete. In this paper the computer program is also compiled to speed up the calculation. The model has been validated by comparing the predicted and experimental members loaded under torsion combined with different ratios of bending and shear. The theoretical torsional strength was in good agreement with the experimental results.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.817-826
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• 2022

AI technology is being successfully introduced in many fields, and models deployed as a service are deployed with black box environment that does not expose the model's information to protect intellectual property rights and data. In a black box environment, attackers try to steal data or parameters used during training by using model output. This paper proposes a method of inferring the type of model to directly find out the composition of layer of the target model, based on the fact that there is no attack to infer the information about the type of model from the deep learning model. With ResNet, VGGNet, AlexNet, and simple convolutional neural network models trained with MNIST datasets, we show that the types of models can be inferred using the output values in the gray box and black box environments of the each model. In addition, we inferred the type of model with approximately 83% accuracy in the black box environment if we train the big and small relationship feature that proposed in this paper together, the results show that the model type can be infrerred even in situations where only partial information is given to attackers, not raw probability vectors.

• 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.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1602-1607
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• 2003

Vibration causes noise and sometimes makes structure unstable. Especially, due to the efforts of lightening, deformation of flexible structure is increased in its shape. Just a little disturbance can cause vibration and low damping ratio makes residual vibration last long time. This research is concerned with the model reference neuro-controller design for the vibration suppression of smart structures. By using a model reference neurocontroller, which is one of the algorithms of adaptive control, we performed an adaptive control of flexible cantilever plate and opened box structure with piezoelectric materials. The proposed adaptive vibration control algorithm, a model reference neuro-controller, was proved in its effectiveness by applying to an opened box structure. The model reference neuro-controller is implemented with DSP, and the real-time adaptive vibration control experiment results confirm that the model reference neuro-controller is reliable.

• Proceedings of the KSR Conference
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• 1998.11a
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• pp.39-46
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• 1998

This paper is about design for diaphragm of prestressed concrete box bridge using strut-tie model. In this paper, equivalent loads for the diaphragm are computed by considering loading conditions on continuous prestressed concrete box bridge and analyses for both longitudinal section and transverse section of the diaphragm an done by considering the equivalent loading and the prestressing. Based on principal stress trajectory obtained from the analyses, strut-tie model for each sections are constructed. By analyzing the constructed strut-tie model for each sections, the amounts and the locations of reinforcement for the diaphragm are obtained. The application of strut-tie model in this paper shows that the design by soul-tie model for the diaphragm of prestressed concrete box bridges can be rationally performed.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.359-364
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• 2005

This paper considers a specification test of conditional Poisson regression model for time series count data. Although conditional models for count data have received attention and proposed in several ways, few studies focused on checking its adequacy. Motivated by the test of martingale difference assumption, a specification test via Ljung-Box statistic is proposed in the conditional model of the time series count data. In order to illustrate the performance of Ljung- Box test, simulation results will be provided.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.11
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• pp.1112-1118
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• 2007

It was discussed to identify Thiele Small Parameters for Pseudo loudspeaker within 10mm grade microspeaker attached to closed-box using known dynamic mass of moving parts. Also, enhanced circuit model for vented-box micro speaker system was used to more accurately simulate electrical impedance curves for real vented-box microspeaker system and compared to test results. Consequently, it showed that micro speaker could be modeled by pseudo loudspeaker TS parameters similar to general loudspeaker. Vented-box microspeaker model with pseudo loudspeaker TS parameters was well suited to describe real microspeaker. Also, it was proposed to estimate volume of rear closed-box of microspeaker without design specifications.

• Steel and Composite Structures
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• v.22 no.6
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• pp.1217-1238
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• 2016

Mega composite structure systems have been widely used in high rise buildings in China. Compared to other structures, this type of composite structure systems has a larger cross-section with less weight. Concrete filled steel tubular (CFST) laced column to box-beam connections are gaining popularity, in particular for the mega composite structure system in high rise buildings. To enable a better understanding of the destruction characteristics and aseismic performance of these connections, three different connection types of specimens including single-limb bracing, cross bracing and diaphragms for core area of connections were tested under low cyclic and reciprocating loading. Hysteresis curves and skeleton curves were obtained from cyclic loading tests under axial loading. Based on these tested curves, a new trilinear hysteretic restoring force model considering rigidity degradation is proposed for CFST laced column to box-beam connections in a mega composite structure system, including a trilinear skeleton model based on calculation, law of stiffness degradation and hysteresis rules. The trilinear hysteretic restoring force model is compared with the experimental results. The experimental data shows that the new hysteretic restoring force model tallies with the test curves well and can be referenced for elastic-plastic seismic analysis of CFST laced column to composite box-beam connection in a mega composite structure system.

• Steel and Composite Structures
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• v.38 no.6
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• pp.657-670
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• 2021

This paper presents a designing method for enhancing fire resistance of steel box bridge girders (closed steel box bridge girder supporting a thin concrete slab) through taking into account such parameters namely; fire severity, type of longitudinal stiffeners (I, L, and T shaped), and number of longitudinal stiffeners. A validated 3-D finite element model, developed through the computer program ANSYS, is utilized to go over the fire response of a typical steel box bridge girder using the transient thermo-structural analysis method. Results from the numerical analysis show that fire severity and type of longitudinal stiffeners welded on bottom flange have significant influence on fire resistance of steel box bridge girders. T shaped longitudinal stiffeners applied on bottom flange can highly prevent collapse of steel box bridge girders towards the end of fire exposure. Increase of longitudinal stiffeners on bottom flange and web can slightly enhance fire resistance of steel box bridge girders. Rate of deflection-based criterion can be reliable to evaluate fire resistance of steel box bridge girders in most fire exposure cases. Thus, T shaped longitudinal stiffeners on bottom flange incorporated into bridge fire-resistance design can significantly enhance fire resistance of steel box bridge girders.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.29 no.3
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• pp.163-174
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• 2023

Though box compression strength (BCS) is commonly used as a performance criterion for shipping containers, estimating BCS remains a challenge. In this study, artificial neural networks (ANN) are implemented as a new tool, with a focus on building up ANN architectures for BCS estimation. An Artificial Neural Network (ANN) model can be constructed by adjusting four modeling factors: hidden neuron numbers, epochs, number of modeling cycles, and number of data points. The four factors interact with each other to influence model accuracy and can be optimized by minimizing model's Mean Squared Error (MSE). Using both data from the literature and "synthetic" data based on the McKee equation, we find that model estimation accuracy remains limited due to the uncertainty in both the input parameters and the ANN process itself. The population size to build an ANN model has been identified based on different data sets. This study provides a methodology guide for future research exploring the applicability of ANN to address problems and answer questions in the corrugated industry.