• Journal of Korean Institute of Industrial Engineers
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• v.26 no.3
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• pp.200-205
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• 2000

An economic process monitoring procedure is presented using a surrogate variable for the case where performance variable is dichotomous. Every item is inspected with a surrogate variable and determined whether it should be accepted or rejected. When an item is rejected, the previous number of consecutively accepted items is compared with a predetermined number r to decide whether there is a shift in fraction nonconforming or not. The conditional distribution of the surrogate variable given the performance variable is assumed to be normal. A cost model is constructed which includes costs of inspection, misclassification, illegal signal, undetected out-of-control state, and correction. Methods of finding the optimum number r and screening limit are provided. Numerical studies on the effects of cost coefficients are also performed.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.51-60
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• 2021

Effective nonpoint source (NPS) pollution management requires frequent water quality monitoring, which is, however, often costly to be implemented in practice. Statistical techniques and machine learning methods allow us to identify and focus on fundamental environmental variables that have close relationships with NPS pollutants of interest. This study developed surrogate models to predict the concentrations of suspended sediment (SS) and total phosphorus (T-P) from turbidity and runoff discharge rates using multiple linear regression (MLR) and random forest (RF) methods. The RF models provided acceptable performance in predicting SS and T-P, especially when runoff discharge rates were high. The RF models outperformed the MLR models in all the cases. Such finding highlights the potential of RF techniques and models as a tool to identify fundamental environmental variables that are measured in relatively inexpensive ways or freely available but still able to provide information required to quantify the concentrations of NP S pollutants. The analysis of relative importance rates showed that the temporal variations of SS and T-P concentrations could be more effectively explained by that of turbidity than runoff discharge rate. This study demonstrated that the advanced statistical techniques such as machine learning could help to improve the efficiency of NPS pollutants monitoring.

• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.299-312
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• 2021

Purpose: We provide a condition-based maintenance policy where a surrogate variable is used for monitoring system performance. We constructed a risk function by taking into account the risk and losses accompanied with erroneous decisions. Methods: Assuming a unique degradation process for the performance variable and its specific relationship with the surrogate variable, the maintenance policy is determined. A risk function is developed on the basis of producer's and consumer's risks accompanied with each decision. With a strategic safety factor considered, the optimal threshold value for the surrogate variable is determined based on the risk function. Results: The condition-based maintenance is analyzed from the point of risk. With an assumed safety consideration, the optimal threshold value of the surrogate variable is provided for taking a maintenance action. The optimal solution cannot be obtained in a closed form. An illustrative numerical example and solution is provided with a source code of R program. Conclusion: The study can be applied to situation where a sensor signal is issued if the system performance begins to degrade gradually and reaches eventually its functional failure. The study can be extended to the case where two or more performance variables are connected to a same surrogate variable. Also estimation of the distribution parameters and risk coefficients should be further studied.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.1
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• pp.1-8
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• 2006

The home network system guarantees families a safe, economical, socially integrated and healthy life by using information appliances. And it provides a family with domestic safety, control of instruments, controllable energy and health monitoring by connecting to home appliances. This study designs the broadband PLC home controller using broadband PLC(Power Line Communication) technology which can save much cost at a network infrastructure by using the existing power line at home. The broadband PLC home controller consists of the broadband PLC module, the embedded main controller module and I/O module. The broadband PLC home controller can control various domestic appliances such as an auto door-lock, a boiler, an oven, etc., because it has various I/O specifications. In this study, selected home network middleware for the broadband PLC home controller is Jini surrogate using Jini technology designed by means of access to easily a home network system without a limitation of the devices. And a client application program is supported java servlet program to manage and monitor the broadband PLC home controller via web browser of a PC or a PDA, etc. Finally, for an application, we implemented and tested a home security system using one broadband PLC home controller.

• Structural Engineering and Mechanics
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• v.74 no.2
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• pp.157-173
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• 2020

In the finite element modelling of long-span cable-stayed bridges, there are a lot of uncertainties brought about by the complex structural configuration, material behaviour, boundary conditions, structural connections, etc. In order to reduce the discrepancies between the theoretical finite element model and the actual static and dynamic behaviour, updating is indispensable after establishment of the finite element model to provide a reliable baseline version for further analysis. Traditional sensitivity-based updating methods cannot support updating based on static and dynamic measurement data at the same time. The finite element model is required in every optimization iteration which limits the efficiency greatly. A convenient but accurate Kriging surrogate model for updating of the finite element model of cable-stayed bridge is proposed. First, a simple cable-stayed bridge is used to verify the method and the updating results of Kriging model are compared with those using the response surface model. Results show that Kriging model has higher accuracy than the response surface model. Then the method is utilized to update the model of a long-span cable-stayed bridge in Hong Kong. The natural frequencies are extracted using various methods from the ambient data collected by the Wind and Structural Health Monitoring System installed on the bridge. The maximum deflection records at two specific locations in the load test form the updating objective function. Finally, the fatigue lives of the structure at two cross sections are calculated with the finite element models before and after updating considering the mean stress effect. Results are compared with those calculated from the strain gauge data for verification.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.395-405
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• 2018

Seakeeping safety module in Korean e-Navigation system is one of the ship remote monitoring services that is employed to ensure the safety of ships by monitoring the ship's real time performance and providing a warning in advance when the abnormal conditions are encountered in seakeeping performance. In general, seakeeping performance has been evaluated by simulating ship motion analysis under specific conditions for its design. However, due to restriction of computation time, it is not realistic to perform simulations to evaluate seakeeping performance under real-time operation conditions. This study aims to introduce a reasonable and faster method to predict a ship's roll motion which is one of the factors used to evaluate a ship's seakeeping performance by using a machine learning-based surrogate model. Through the application of various learning techniques and sampling conditions on training data, it was observed that the difference of roll motion between a given surrogate model and motion analysis was within 1%. Therefore, it can be concluded that this method can be useful to evaluate the seakeeping performance of a ship in real-time operation.

• Journal of Korean Society for Quality Management
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• v.27 no.1
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• pp.35-45
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• 1999

A process monitoring procedure using a correlated variable is presented when a lower specification limit is given on the performance variable. Every item is inspected with a variable correlated with the performance variable. When an item is rejected in the screening inspection, the process is checked for change using the mean and variance of measurements of the correlated variable for n preceding items including the rejected one. The performance variable is assumed to be normally distributed. A linear relationship between the performance and surrogate variables is assumed with normally distributed error term. The monitoring procedure is designed so that the prespecified outgoing quality can be attained.

• New & Renewable Energy
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• v.20 no.1
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• pp.79-87
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• 2024

This study introduces a method for estimating Aerosol Optical Depth (AOD) using Broadband Aerosol Optical Depth (BAOD) derived from direct normal irradiance and meteorological factors observed between 2016 and 2017. Through correlation analyses between BAOD and atmospheric components such as Rayleigh scattering, water vapor, and tropospheric nitrogen dioxide, significant relationships were identified, enabling accurate AOD estimation. The methodology demonstrated high correlation coefficients and low Root Mean Square Errors (RMSE) compared to actual AOD₅₀₀ measurements, indicating that the attenuation effects of water vapor and the direct impact of tropospheric nitrogen dioxide concentration are crucial for precise aerosol optical depth estimation. The application of BAOD for estimating AOD₅₀₀ across various time scales-hourly, daily, and monthly-showed the approach's robustness in understanding aerosol distributions and their optical properties, with a high coefficient of determination (0.96) for monthly average AOD₅₀₀ estimates. This study simplifies the aerosol monitoring process and enhances the accuracy and reliability of AOD estimations, offering valuable insights into aerosol research and its implications for climate modeling and air quality assessment. The findings underscore the viability of using BAOD as a surrogate for direct AOD₅₀₀ measurements, presenting a promising avenue for more accessible and accurate aerosol monitoring practices, crucial for improving our understanding of aerosol dynamics and their environmental impacts.

• The Korean Journal of Physiology and Pharmacology
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• v.15 no.2
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• pp.67-81
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• 2011

Epilepsy is a chronic disease occurring in approximately 1.0% of the world's population. About 30% of the epileptic patients treated with availably antiepileptic drugs (AEDs) continue to have seizures and are considered therapy-resistant or refractory patients. The ultimate goal for the use of AEDs is complete cessation of seizures without side effects. Because of a narrow therapeutic index of AEDs, a complete understanding of its clinical pharmacokinetics is essential for understanding of the pharmacodynamics of these drugs. These drug concentrations in biological fluids serve as surrogate markers and can be used to guide or target drug dosing. Because early studies demonstrated clinical and/or electroencephalographic correlations with serum concentrations of several AEDs, It has been almost 50 years since clinicians started using plasma concentrations of AEDs to optimize pharmacotherapy in patients with epilepsy. Therefore, validated analytical method for concentrations of AEDs in biological fluids is a necessity in order to explore pharmacokinetics, bioequivalence and TDM in various clinical situations. There are hundreds of published articles on the analysis of specific AEDs by a wide variety of analytical methods in biological samples have appears over the past decade. This review intends to provide an updated, concise overview on the modern method development for monitoring AEDs for pharmacokinetic studies, bioequivalence and therapeutic drug monitoring.

• Biomolecules & Therapeutics
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• v.20 no.6
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• pp.562-568
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• 2012

Cytochrome P450 BM3 (CYP102A1) from Bacillus megaterium is a self-sufficient monooxygenase that consists of a heme domain and FAD/FMN-containing reductase domain (BMR). In this report, the reduction of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) by BMR was evaluated as a method for monitoring BMR activity. The electron transfer proceeds from NADPH to BMR and then to BMR substrates, MTT and CTC. MTT and CTC are monotetrazolium salts that form formazans upon reduction. The reduction of MTT and CTC followed classical Michaelis-Menten kinetics ($k_{cat}=4120\;min^{-1}$, $K_m=77{\mu}M$ for MTT and $k_{cat}=6580\;min^{-1}$, $K_m=51{\mu}M$ for CTC). Our continuous assay using MTT and CTC allows the simple, rapid measurement of BMR activity. The BMR was able to metabolize mitomycin C and doxorubicin, which are anticancer drug substrates for CPR, producing the same metabolites as those produced by CPR. Moreover, the BMR was able to interact with CYP1A2 and transfer electrons to promote the oxidation reactions of substrates by CYP1A2 and CYP2E1 in humans. The results of this study suggest the possibility of the utilization of BMR as a surrogate for mammalian CPR.