• Structural Engineering and Mechanics
• /
• v.17 no.2
• /
• pp.267-279
• /
• 2004

This paper presents an improved Monte Carlo simulation for the probabilistic determination of initial cable forces of cable-stayed bridges under dead loads using the response surfaces method. A response surface (i.e. a quadratic response surface without cross-terms) is used to approximate structural response. The use of the response surface eliminates the need to perform a deterministic analysis in each simulation loop. In addition, use of the response surface requires fewer simulation loops than conventional Monte Carlo simulation. Thereby, the computation time is saved significantly. The statistics (e.g. mean value, standard deviation) of the structural response are calculated through conventional Monte Carlo simulation method. By using Monte Carlo simulation, it is possible to use the existing deterministic finite element code without modifying it. Probabilistic analysis of a truss demonstrates the proposed method' efficiency and accuracy; probabilistic determination of initial cable forces of a cable-stayed bridge under dead loads verifies the method's applicability.

• Journal of Sasang Constitutional Medicine
• /
• v.17 no.3
• /
• pp.76-81
• /
• 2005

1. Objectives The purpose of this study is to find the difference of response to visual or auditory stimulus in Sasang Constitutional groups. 2. Methods Continuous performance test (CPT)-ADS program- was measured in 44 females in 20's. The mean and standard deviation of response time were measured and analysed statically in each group of Sasang Constitution. 3. Results There were significant results in the average of response time. The average of the response time to the auditory stimulus in Soyangin was shorter then that of in Soeumin 4. Conclusions The results suggest that there could be differences in the pattern of response to circumstantial stimulus in Sasang Constitution.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.20 no.6
• /
• pp.496-501
• /
• 2007

In order to enhance sintering characteristics on the $ZnO-Pr_6O_{11}$ based multilayer chip varistors (MLVs), a response surface analysis using central composite design method were carried out. As a result, varistor voltage($V_{1mA}$), nonlinear coefficient ($\alpha$), leakage current ($I_L$) and capacitance (C) were considered to be mainly affected by sintered temperature and holding time. MLVs sintered at $1200^{\circ}C$ and above $1200^{\circ}C$ revealed poor electrical characteristics, possibly due to the reaction between electrode materials(Pd) and $ZnO-Pr_6O_{11}$ based ceramics. On the sintering temperature range $1150{\sim}1175^{\circ}C$, nonlinear coefficient ($\alpha$) and leakage current ($I_L$) were shown to be $60{\sim}69$ and below $0.3{\mu}A$, respectively. In particular, MLVs sintered at $1175^{\circ}C$, 1.5 hr and $2^{\circ}C/hr$ (cooling speed) showed stable ESD(Electrical Static Discharge) characteristics under the condition of 10 times at 8 Kv with deviation varistor voltage, and deviation nonlinear coefficient were 0.3% and 0.33% (at positive), 0.55% (at negative), respectively.

• Journal of Sensor Science and Technology
• /
• v.12 no.6
• /
• pp.241-248
• /
• 2003

An electrochemical humidity sensor was fabricated with poly(1,5-diaminonaphthalene) film coated on a gap of two splitted gold electrodes, which were made by vacuum deposition. Response currents according to humidity were measured by the potential sweep method and chronoamperometry. The stability of the polymer film was improved by double step chronoamperometry using the applied voltage of ${\pm}0.5$ Vdc. The response time determined by the pulse technique was about ${\sim}50$ msec and the relative standard deviation of current response was within ${\pm}5.0%$. The response current of the film was intrinsically humidity dependent. The film exhibited a non-linear but reproducible response in ordinary range of relative humidity. The linear equations were $I(nA)=0.28{\times}%RH-1.01$ between 10 to 70 %RH and $I(nA)=6.05{\times}%RH-403.21$ between 70 to 90 %RH.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.4
• /
• pp.1147-1161
• /
• 2023

The Internet of Things (IoT) requires a new processing model that will allow scalability in cloud computing while reducing time delay caused by data transmission within a network. Such a model can be achieved by using resources that are closer to the user, i.e., by relying on edge computing (EC). The amount of IoT data also grows with an increase in the number of IoT devices. However, building such a flexible model within a heterogeneous environment is difficult in terms of resources. Moreover, the increasing demand for IoT services necessitates shortening time delay and response time by achieving effective load balancing. IoT devices are expected to generate huge amounts of data within a short amount of time. They will be dynamically deployed, and IoT services will be provided to EC devices or cloud servers to minimize resource costs while meeting the latency and quality of service (QoS) constraints of IoT applications when IoT devices are at the endpoint. EC is an emerging solution to the data processing problem in IoT. In this study, we improve the load balancing process and distribute resources fairly to tasks, which, in turn, will improve QoS in cloud and reduce processing time, and consequently, response time.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.16 no.6
• /
• pp.117-124
• /
• 2017

In this study, we investigated the optimization of process conditions by using the Six Sigma process, design of experiment (DOE) method and response surface method (RSM) to resolve dimensional deviation and appearance problems arising from the shortened process time of the mobile phone rear cover. The analysis of the trivial many was performed by 2-sample T-test and cooling time, and mold temperature and packing pressure were selected as the vital fews affecting the overall width of the product. The optimal conditions of the process were then studied using the DOE and the RSM. We analyzed the improvement effects by applying the selected optimal conditions to the production process and the results showed that the difference between the mean value and target value of the overall width stood at 0.01 mm, an improvement of 88.89% compared to current process that fell within the range of standard dimension. The short-term process capability stood at $4.77{\sigma}$, which implied an excellent technology level despite a decrease by $0.22{\sigma}$ compared to the current process. The difference in process capability decreased by $2.44{\sigma}$ to $0.41{\sigma}$, showing a significant improvement in management capability. Ultimately, the process time of the product was shortened from 18.3 seconds in the current process to 13.65 seconds, resulting in a 34.07% improvement in production yield.

• Earthquakes and Structures
• /
• v.25 no.6
• /
• pp.469-479
• /
• 2023

A probabilistic seismic damage analysis is an essential procedure to identify seismically vulnerable structures, prioritize the seismic retrofit, and ultimately minimize the overall seismic risk. To assess the seismic risk of multiple structures within a region, a large number of nonlinear time-history structural analyses must be conducted and studied. As a result, each assessment requires high computing resources. To overcome this limitation, we explore a deep learning-based metamodel to enable the prediction of the mean and the standard deviation of the seismic damage distribution of track-on steel-plate girder railway bridges in Korea considering the geometric variation. For machine learning training, nonlinear dynamic time-history analyses are performed to generate 800 high-fidelity datasets on the seismic response. Through intensive trial and error, the study is concentrated on developing an optimal machine learning architecture with the pre-identified variables of the physical configuration of the bridge. Additionally, the prediction performance of the proposed method is compared with a previous, well-defined, response surface model. Finally, the statistical testing results indicate that the overall performance of the deep-learning model is improved compared to the response surface model, as its errors are reduced by as much as 61%. In conclusion, the model proposed in this study can be effectively deployed for the seismic fragility and risk assessment of a region with a large number of structures.

• Wind and Structures
• /
• v.32 no.4
• /
• pp.341-354
• /
• 2021

Articulated towers are one of the class of compliant offshore structures that freely oscillates with wind and waves, as they are designed to have low natural frequency than ocean waves. The present study deals with the dynamic response of a double-pendulum articulated tower under hydrodynamic and aerodynamic loads. The wind field is simulated by two approaches, namely, single-point and multiple-point. Nonlinearities such as instantaneous tower orientation, variable added mass, fluctuating buoyancy, and geometrical nonlinearities are duly considered in the analysis. Hamilton's principle is used to derive the nonlinear equations of motion (EOM). The EOM is solved in the time domain by using the Wilson-θ method. The maximum, minimum, mean, and standard deviation and salient power spectral density functions (PSDF) of deck displacement, bending moment, and central hinge shear are drawn for high and moderate sea states. The outcome of the analyses shows that tower response under multiple-point wind-field simulation results in lower responses when compared to that of single-point simulation.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.4
• /
• pp.382-387
• /
• 2011

In this paper, a LBCC (Latter Bank Cooling Control) for the high strength steel is proposed to obtain the desirable temperature and the property of the material along the longitudinal direction of the steel on the ROT (Run-Out Table) process. A cooling valve is modeled to analyze the response of the ROT banks. The control concept is derived from a field data, a valve model considering the valve response and a TTT (Time-Temperature Transformation) diagram. The proposed control is verified from the simulation results under the various carbon quantities. It is shown through the field test of the hot strip mill that the deviation of the CT (Coiling Temperature) is considerably decreased by the proposed temperature control.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.10a
• /
• pp.137-144
• /
• 1998

This paper proposed a optimal scale factors technique of a fuzzy-neural network for a load frequency control of two areas power system. The optimal scale factors control technique is optimize from an initial fuzzy logic control rule, and then is learned with an error back propagation learning algorithm of the fuzzy-neural network. In application two areas the load frequency control of the power system, it hopes to have response characteristic better than optimal control technique which is the conventional control technique and to show to minimize a frequency deviation and reaching and settling time of a tie line power flow deviation