• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.219-230
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• 2015

It is difficult to make plans about the production schedule and volume of seasonal products due to the huge uncertainty in the prediction of their demands, which is why the amounts of carryover seasonal products increase after the peak season. Traditional models fail to meet the important requirements of production and stock plans related to the enhanced efficiency of logistics system due to the reduced value of carryover products by the disposal based on large discounts and deterioration, which poses considerable difficulties with actual problem solving. This study examined the stages of product storage from the specialized factory warehouses during a low season through the stores and the warehouses of local distribution centers during a high season to stock disposal and carryover product warehouses after a high season. The study developed a model for logistics rationalization plans to minimize carryover products by advance selling new products by subscription during a low season in anticipation of high season demands, increasing the accuracy of demands prediction, and making stable production plans, as well as demonstrated its excellence through numerical analysis.

• Geomechanics and Engineering
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• v.20 no.2
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• pp.113-120
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• 2020

Rock damage is the main cause of accidents in underground engineering. It is difficult to predict rock damage accurately by using only one parameter. In this study, a rock failure prediction model was established by using stress, energy, and damage. The prediction level was divided into three levels according to the ratio of the damage threshold stress to the peak stress. A classification predicting model was established, including the stress, energy, damage and AE impact rate using Bayesian method. Results show that the model is good practicability and effectiveness in predicting the degree of rock failure. On the basis of this, a multi-parameter classification predicting deterioration model of rock failure was established. The results provide a new idea for classifying and predicting rockburst.

• Journal of the Korean Society of Propulsion Engineers
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• v.10 no.3
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• pp.82-89
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• 2006

Recently operation and maintenance cost of gas turbine engines has been issued as a major parameter in terms of designing and manufacturing. Accordingly, the conception that the maintenance and repair of an engine has to be conducted in assembled condition has been spreaded out. However, it is possible only if the prediction of the engine performance is clearly identified. In this study, therefore, a diagnostic code of the engine performance has been developed by using GPA(Gas Path Analysis) and Fuzzy Logic which can analyze the engine performance and estimate the health parameters. The prediction of the quantitative performance deterioration of the established model of the turbo-shaft engine for SUAV has been achieved in a satisfied level compared to that obtained by GSP code.

• International Journal of Air-Conditioning and Refrigeration
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• v.6
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• pp.93-103
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• 1998

The nucleate boiling heat transfer experiments are performed using a ternary refrigerant R407C which is a candidate of alternatives of HCFC 22. The boiling phenomena of R-32, R-125 and R-134a which are the constituent refrigerants of R407C are also investigated. The nucleate boiling heat transfer coefficients of R407C are less than those of HCFC 22 which have the similar physical and transport properties. In our experimental pressure range, which is similar to the operational pressure of air conditioning system, the deterioration of boiling heat transfer coefficients of mixture refrigerant R407C does not appear for moderate wall superheat region. Since nucleate boiling heat transfer coefficients cannot be obtained from ideal mixing law of mixture, Thome's method was used to predict. To account for the heat flux effect and system pressure in Thome's method, the correcting factor, a(P.L1T), was introduced and obtained from experiments for ternary refrigerant R407C.

• Computers and Concrete
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• v.6 no.4
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• pp.281-303
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• 2009

The lack of safety of bridge deck structures causes frequent repair and strengthening of such structures. The repair induces great loss of economy, not only due to direct cost by repair, but also due to stopping the public use of such structures during repair. The major reason for this frequent repair is mainly due to the lack of realistic and accurate assessment system for the bridge decks. The purpose of the present research was to develop a realistic expert system, called Bridge Slab-Expert which can evaluate reasonably the condition as well as the service life of concrete bridge decks, based on the deterioration models that are derived from both the structural and environmental effects. The diagnosis assessment of deck slabs due to structural and environmental effects are developed based on the cracking in concrete, surface distress and structural distress. Fuzzy logic is utilized to handle uncertainties and imprecision involved. Finally, Bridge Slab-Expert is developed for prediction of safety and remaining service life based on the chloride ions penetration and fick's second law. Proposed expert system is based on user-friendly GUI environment. The developed expert system will allow the correct diagnosis of concrete decks, realistic prediction of service life, the determination of confidence level, the description of condition and the proposed action for repair.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.87-91
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• 2019

The diagnosis of the failure for the existing electrical facilities was based on regular preventive maintenance, but this preventive maintenance was limited in preventing a lot of cost loss and sudden system failure. To overcome these shortcomings, fault prediction and diagnostic techniques are critical to increasing system reliability by monitoring electrical installations in real time and detecting abnormal conditions in the facility early. As the performance and quality deterioration problem occurs frequently due to the increase in the number of users of the motor pump, the purpose is to build an intelligent control system that can control the motor pump to maximize the performance and to improve the quality and reliability. To this end, a vibration sensor, temperature sensor, pressure sensor, and low water level sensor are used to detect vibrations, temperatures, pressures, and low water levels that can occur in the motor pump, and to build a system that can identify and diagnose information to users in real time.

• Physical Therapy Korea
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• v.28 no.3
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• pp.177-185
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• 2021

Background: Muscle undergoes change continuously with aging. Sarcopenia, in which muscle mass decrease with aging, is associated with various diseases, the risk of falling, and the deterioration of quality of life. Obesity and sarcopenia also have a synergy effect on the disease of the older adults. Objects: This study examined the risk factors for sarcopenia, sarcopenic obesity, and sarcopenia without obesity and developed prediction models. Methods: This machine-learning study used the 2008-2011 Korea National Health and Nutrition Examination Surveys in the analysis. After data curation, 5,563 older participants were selected, of whom 1,169 had sarcopenia, 538 had sarcopenic obesity, and 631 had sarcopenia without obesity; the remaining 4,394 were normal. Decision tree and random forest models were used to identify risk factors. Results: The risk factors for sarcopenia chosen by both methods were body mass index (BMI) and duration of moderate physical activity; those for sarcopenic obesity were sex, BMI, and duration of moderate physical activity; and those for sarcopenia without obesity were BMI and sex. The areas under the receiver operating characteristic curves of all prediction models exceeded 0.75. BMI could predict sarcopenia-related disease. Conclusion: Risk factors for sarcopenia-related diseases should be identified and programs for sarcopenia-related disease prevention should be developed. Data-mining research using population data should be conducted to enhance the effectiveness of early treatment for people with sarcopenia-related diseases through predictive models.

• Journal of Korean Association for Spatial Structures
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• v.23 no.4
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• pp.81-88
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• 2023

Numerous factors contribute to the deterioration of reinforced concrete structures. Elevated temperatures significantly alter the composition of the concrete ingredients, consequently diminishing the concrete's strength properties. With the escalation of global CO2 levels, the carbonation of concrete structures has emerged as a critical challenge, substantially affecting concrete durability research. Assessing and predicting concrete degradation due to thermal effects and carbonation are crucial yet intricate tasks. To address this, multiple prediction models for concrete carbonation and compressive strength under thermal impact have been developed. This study employs seven machine learning algorithms-specifically, multiple linear regression, decision trees, random forest, support vector machines, k-nearest neighbors, artificial neural networks, and extreme gradient boosting algorithms-to formulate predictive models for concrete carbonation and thermal impact. Two distinct datasets, derived from reported experimental studies, were utilized for training these predictive models. Performance evaluation relied on metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analytical outcomes demonstrate that neural networks and extreme gradient boosting algorithms outshine the remaining five machine learning approaches, showcasing outstanding predictive performance for concrete carbonation and thermal effect modeling.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.102-110
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• 2023

PSC-I girder bridges constitute the largest proportion among highway bridges in Korea. According to the precision safety diagnosis data for the past 10 years, approximately 41.3% of the PSC-I bridges have been graded as C. Furthermore, with the increase in the aging of bridges, preemptive management is becoming more important. Damage and deterioration to the deck and girder with a long replacement cylce can have considerable impacts on the service and deterioration of a bridge. In addition, the high rate of device damages, including expansion joints and bearings, necessitates an investigation into the influence of the device damage in the structural members of the bridge. Therefore, this study defined representative PSC-I girder bridges with single and multiple spans to evaluate heterogeneous damages that incorporate the damage of the bridge member and device with the deterioration of the deck. The heterogeneous damages increased a crack area ratio compared to the individual single damage. For the single-span bridge, the occurrence of bearing damage leads to the spread of crack distribution in the girder, and in the case of multi-span bridges, expansion joint damage leads to the spread of crack distribution in the deck. The research underscores that bridge devices, when damaged, can cause subsequent secondary damage due to improper repair and replacement, which emphasizes the need for continuous observation and responsive action to the damages of the main devices.

• KIEAE Journal
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• v.3 no.1
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• pp.13-20
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• 2003

It is highly recognized that there is need for protection against indoor air pollution, as we realize environmental pollution is growing, For example, in an indoor environment, a person spends more than 80 percent of their time inside the building. Thus, concern about indoor decoration materials is growing, since they cause pollution in the rooms of an apartment, as well as in offices. As the indoor decoration materials become more diverse and lusurious, so the effect of VOCs(Volatile Organic Compounds) and HCHO(Formaldehy) is growing. The indoor decoration materials cause the Sick Building Syndrome, such as headaches, dizziness, or lack of concentraion, and they in turn cause serious deterioration in people's health. In this study, I probed the status of the indoor air pollution and carried on an investigation and analysis about the prevention technique. In doing so, I performed experimental tests and an assessment of the indoor decoration materials of an apartment. I also examined elements of the emitted and the emission. Finally, I examined the character of emissions, by changing environmental conditions, such as the temperature, humidity, and ventilation. With respect to VOCs tests, I applied the method of solid state adsorption using the adsorptive tube, based on the measurement of the American EPA TO-17, ASTM 5116-97, and the measurement of the Japanese Wall Decoration Industrial Association. The tested sample was analyzed by High Performance Liquid Chromatography, after going through the process of dissolvent extraction. As subjects of the test, Paint were selected. The process of this test is as follows; first, I figured out the character of the emission, by measuring the emitted concentration of VOCs and HOHC from the indoor decoration materials of an apartment. Second, I made a small-scale chamber and the test was processed in the chamber in order to suggest an environment-friendly prediction modlel development.