• Nuclear Engineering and Technology
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• v.42 no.4
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• pp.414-425
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• 2010

In this paper, a procedure is developed for identifying a number of representative solutions manageable for decision-making in a multiobjective optimization problem concerning the test intervals of the components of a safety system of a nuclear power plant. Pareto Front solutions are identified by a genetic algorithm and then clustered by subtractive clustering into "families". On the basis of the decision maker's preferences, each family is then synthetically represented by a "head of the family" solution. This is done by introducing a scoring system that ranks the solutions with respect to the different objectives: a fuzzy preference assignment is employed to this purpose. Level Diagrams are then used to represent, analyze and interpret the Pareto Fronts reduced to the head-of-the-family solutions.

• IE interfaces
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• v.24 no.1
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• pp.40-50
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• 2011

We develop a nonlinear integer programming model which minimizes the total cost with the optimal number of operators to hire and their optimal allocation to the tasks under the diverse constraints such as the weekly, daily, and hourly maximum allowable abandonment rates for the time-varying inbound call volume. We present a case study based on actual data at a call center, in order to prove the validity of applying the optimization method proposed. By the one-sample two-tailed t-test, we confirm that the expected abandonment rates resulting from the optimization method are identical with the ones from the discrete-event simulation within specified confidence intervals.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.120-127
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• 2011

Checkpointing is one of common methods of realizing fault-tolerance for real-time systems. This paper presents a scheme to determine checkpoint intervals using probabilistic optimization. The considered real-time systems comprises multiple tasks in which transient faults can happen with a Poisson distribution. Also, multi-tasks are scheduled by the non-preemptive Rate Monotonic (RM) algorithm. In this paper, we present an optimization problem where the probability of task completion is described by checkpoint numbers. The solution to this problem is the optimal set of checkpoint numbers and intervals that maximize the probability. The probability computation includes schedulability test for the non-preemptive RM algorithm with respect to given numbers of checkpoint re-execution. A case study is given to show the applicability of the proposed scheme.

• Corrosion Science and Technology
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• v.15 no.4
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• pp.189-197
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• 2016

It is a common practice to conduct periodic washes at designated intervals in order to prevent the atmospheric corrosion of aircraft. The wash interval depends on the atmospheric conditions, but the wash intervals set by the U.S. Air Force were widely adopted in Korea without detailed knowledge of the background data. Therefore, it is necessary to determine our own wash intervals representing the atmospheric and geographical conditions in Korea. This study analyzed previous wash interval algorithms and atmospheric data in Korea. New wash intervals are then proposed based on the corrosion rate equation in ISO-9223:2012. Atmospheric corrosion testing was conducted using 7075 and 1050 aluminum alloy specimens to verify the accuracy of the corrosion rate equation in ISO-9223:2012. Test results showed a reasonable agreement with the corrosion rates predicted by the equation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.148-154
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• 2012

For a successful checkpointing strategy, we should place checkpoints so as to optimize fault-tolerance capability of real-time systems. This paper presents a novel scheme of checkpoint placement for real-time systems with periodic multi-tasks. Under the influence of transient faults, multi-tasks are scheduled by the Rate Monotonic (RM) algorithm. The optimal checkpoint intervals are derived to maximize the probability of task completion. In particular, this paper is concerned about the general case that the deadline of a task is longer than the period. Compared with the special condition that the deadline is equal to or less than the period, this general case causes a more complicate test procedure for schedulability of the RM algorithm with respect to a given set of checkpoint re-execution vectors. The probability of task completion is also derived in a more complex form. A case study is given to show the applicability of the proposed scheme.

• Journal of Environmental Health Sciences
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• v.43 no.1
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• pp.77-86
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• 2017

Objectives: The purpose of this study was to compare permeation characteristics in three skin types using oil-soluble benzoic acid and water-soluble caffeine after method condition optimization based on OECD guideline 428. Methods: A Franz diffusion cell, a reliable alternative method for skin permeation, was used. One-milliliter samples were taken and immediately replaced with fresh solution in the receptor chamber at regular time intervals (1, 2, 4, 7, 10 and 24 hr). The amount of test substances was measured by LC-MS/MS. Results: The permeation rate increased dose-dependently, and the permeation orders were $KeraSkin^{TM}$ > hairless mouse full skin > human cadaver epidermis for skin types, and benzoic acid solution > caffeine solution > benzoic acid cream > caffeine cream for type of test materials. Conclusion: According to the definitions of Marzulli, benzoic acid and caffeine would be classified as 'fast' and 'moderate' compared with the permeation of other chemical species. The setting conditions and permeation characteristics performed in this study are expected to contribute to future permeation studies.

• International Journal of Automotive Technology
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• v.7 no.5
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• pp.571-577
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• 2006

This paper deals with dynamic tensile characteristics for the polypropylene used in an IP(Instrument Panel). The polypropylene is adopted in the dash board of a car, especially PAB(Passenger Air Bag) module. Its dynamic tensile characteristics are important because the PAB module undergoes high speed deformation during the airbag expansion. Since the operating temperature of a car varies from $-40^{\circ}C$ to $90^{\circ}C$ according to the specification, the dynamic tensile tests are performed at a low temperature($-30^{\circ}C$), the room temperature($21^{\circ}C$) and a high temperature($85^{\circ}C$). The tensile tests are carried out at strain rates of six intervals ranged from 0.001/sec to 100/sec in order to obtain the strain rate sensitivity. The flow stress decreases at the high temperature while the strain rate sensitivity increases. Tensile tests of polymers are rather tricky since polymer does not elongate uniformly right after the onset of yielding unlike the conventional steel. A new method is suggested to obtain the stress-strain curve accurately. A true stress-strain curve was estimated from modification of the nominal stress-strain curves obtained from the experiment. The modification was carried out with the help of an optimization scheme accompanied with finite element analysis of the tensile test with a special specimen. The optimization method provided excellent true stress-strain curves by enforcing the load response coincident with the experimental result. The material properties obtained from this paper will be useful to simulate the airbag expansion at the normal and harsh operating conditions.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.113-123
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• 2011

Traffic signal control is one of the most cost-effective means of improving urban mobility. With the recent progress of ITS (Intelligent Transportation System) and the installation of the real time traffic control systems, traffic signal control is conducted in online and real time. Normally, time-of-day (TOD) signal control is used with the system, but no definite methodology has yet been available for efficient TOD signal planing designing. Such method and process are in need to optimize the traffic signal timing plan. This paper proposes the optimization of TOD signal timings on arterials. The effects of the signal timings from the proposed method were assessed in the field. The proposed includes the methods determining the separation of the TOD break points and the TOD intervals. Those were tested on an arterial consisting of ten coordinated signalized intersections. It was found from the test results that the proposed TOD signal timing plans outperformed the previous signal timings.

• Journal of Periodontal and Implant Science
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• v.48 no.2
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• pp.114-123
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• 2018

Purpose: The aim of the current study was to develop a computer-assisted detection system based on a deep convolutional neural network (CNN) algorithm and to evaluate the potential usefulness and accuracy of this system for the diagnosis and prediction of periodontally compromised teeth (PCT). Methods: Combining pretrained deep CNN architecture and a self-trained network, periapical radiographic images were used to determine the optimal CNN algorithm and weights. The diagnostic and predictive accuracy, sensitivity, specificity, positive predictive value, negative predictive value, receiver operating characteristic (ROC) curve, area under the ROC curve, confusion matrix, and 95% confidence intervals (CIs) were calculated using our deep CNN algorithm, based on a Keras framework in Python. Results: The periapical radiographic dataset was split into training (n=1,044), validation (n=348), and test (n=348) datasets. With the deep learning algorithm, the diagnostic accuracy for PCT was 81.0% for premolars and 76.7% for molars. Using 64 premolars and 64 molars that were clinically diagnosed as severe PCT, the accuracy of predicting extraction was 82.8% (95% CI, 70.1%-91.2%) for premolars and 73.4% (95% CI, 59.9%-84.0%) for molars. Conclusions: We demonstrated that the deep CNN algorithm was useful for assessing the diagnosis and predictability of PCT. Therefore, with further optimization of the PCT dataset and improvements in the algorithm, a computer-aided detection system can be expected to become an effective and efficient method of diagnosing and predicting PCT.

• The Journal of Engineering Geology
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• v.30 no.3
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• pp.269-278
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• 2020

In this study, the effects of groundwater artificial recharge through vertical wells in the upper small basin are preliminarily evaluated by using field injection test and a 3-D numerical model. The injection rate per well in a model is set to 20, 37.5, 60, and 75 ㎥/day based on the results of field injection test, groundwater levels, and hydraulic conductivities estimated from particle size analysis, and a numerical model using MODFLOW is conducted for 28 cases, which have diverse injection intervals, in order to estimated the changes of groundwater level and water balance after injection. Groundwater level after injection does not show a linear relationship with the injection rate per well, and the cumulative effect of artificial recharge decreases and the timing of maximum water level rise is shortened as the injection interval becomes longer. In four cases of continuous injection with total injection rate of 1,200 ㎥, it is revealed that the recharge effect is analyzed as 36.5~65.3% of the original injection rate. However, it will be more effective if the artificial recharge system combined with underground barrier is introduced for the longer pumping during a long and severe drought. Additionally, it will be possible to build a stable artificial recharge system by an establishment of efficient scenario from recharge to pumping as well as an optimization of recharge facilities.