• Structural Engineering and Mechanics
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• v.74 no.4
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• pp.559-565
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• 2020

This paper intends to progress models to accurately estimate the behavior of fresh concrete under vibration using artificial neural networks (ANNs). To this end, behavior of a full scale precast concrete mold was investigated numerically. Experimental study was carried out under vibration with the use of a computer-based data acquisition system. In this study measurements were taken at three points using two vibrators. Transducers were used to measure time-dependent lateral displacements at these points on mold while both mold is empty and full of fresh concrete. Modeling of empty and full mold was made using ANNs. Benefiting ANNs used in this study for modeling fresh concrete, mold design can be performed. For the modeling of ANNs: Experimental data were divided randomly into two parts such as training set and testing set. Training set was used for ANN's learning stage. And the remaining part was used for testing the ANNs. Finally, ANN modeling was compared with measured data. The comparisons show that the experimental data and ANN results are compatible.

• Journal of the Korean Society of Safety
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• v.35 no.4
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• pp.74-83
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• 2020

In Korea, about 110,000 LPG small storage tanks of less than three tons have been installed in restaurants, houses and factories, and are used as LPG supply facilities for cooking, heating and industrial use. In the case of combustible liquefied gas storage tanks, the tank may rupture due to the temperature increase of the tank steel plate (approximately 600℃) even when the safety valve is operating normally, causing large-scale damage in an instant. Therefore, in the event of a fire near the LPG small storage tank, it is necessary to accurately predict the timing of the BLEVE(Boiling Liquid Expanding Vapour Explosion) outbreak in order to secure golden time for lifesaving and safely carry out fire extinguishing activities. In this study, we have first investigated the results of a prior study on the prediction of the occurrence of BLEVE in the horizontal tanks. And we have developed thermodynamic models and simulation program on the prediction of BLEVE that can be applied to vertical tanks used in Korea, have studied the effects of the safety valve's ability to vent, heat flux strength of external fires, size of tanks, and gas remaining in tanks on the time of BLEVE occurrence and have suggested future utilization measures.

• Journal of Korean Academy of Nursing
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• v.13 no.2
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• pp.1-21
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• 1983

The purposes of this study were to(a) develop theoretical modifications of the extended gate control theory of pain using Fishbein's model and（b) test the efficacy of these modifications. Attitude, social subjective norm, personal subjective norm, habit and state anxiety were operationalized to represent internal stimuli for the cognitive-evaluative and motivational-affective dimensions of the theory. Pain expression was operationalized as sensory and affective responses to pain, and pain endurance. Sixty-two female nurses from 20 to 50 years of age participated. A semantic differential scale measured attitude and motivations to comply; a Likerty-type scale measured personal and social norms and habit. Spielberger's STAI measured state anxiety, Pain was produced using a modified submaximum effort tourniquet technique. Pair expression was measured using ratio scales of sensory intensity and unpleasantness developed by Gracely and his associates. Pain endurance was measured by subtracting time of pain threshold from pain tolerance. The first hypothesis examining whether pain endurance would be more significantly related to the affective response than to the sensory response was net rejected. Four remaining hypotheses, testing the ability of the five variables to predict the sensory and affective responses were not rejected. However, the habit of pain expression and the attitude toward pain expression contributed to the prediction of both sensory and affective responses to pain. The interaction between the cognitive-evaluative and the sensory-discriminative dimensions and the interaction between the cognitive-evaluative and motivational-affective dimensions were partially supported by the data from these two variables. The interaction between the motivational-affective and the sensory-discriminative dimensions was also supported by the relationship of sensory to affective responses. The variables which did not significantly predict pain expression appeared to have potential for prediction. Revision and testing of the tools for better reliability, validity, and clinical usuability are needed. The study contributed to theory building. The identification of variables which pre-dict pain behavior must occur before effective nursing interventions can be developed.

• Journal of the Korean Institute of Gas
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• v.10 no.1 s.30
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• pp.7-12
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• 2006

The quantity of gas which can be supplied by LPG storage tank become a standard of selection. In the absence of the maximum evaporation rates from LPG storage tanks by tank capacity, continuation using time, air temperature, it is in a problem for the dissemination of LPG Storage tanks. In this paper, we showed the maximum evaporation rates from LPG storage tanks by tank capacity, air temperature, continuous using time and remaining level.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.533-538
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• 2014

Power generator is one of the most important component of electricity generation system to convert mechanical energy to electrical energy. I t designed robustly to maintain high system reliability during operation time. But unexpected failure of the power generator could happen and it cause huge amount of economic and social loss. To keep it from unexpected failure, health prognostics should be carried out In this research, We developed a health prognostic method of stator windings in power generator with statistical data analysis and degradation modeling against water absorption. We divided whole 42 windings into two groups, absorption suspected group and normal group. We built a degradation model of absorption suspected winding using Fick's second law to predict upcoming absorption data. Through the analysis of data of normal group, we could figure out the distribution of data of normal windings. After that, we can properly predict absorption data of normal windings. With data prediction of two groups, we derived upcoming Directional Mahalanobis Distance (DMD) of absorption suspected winding and time vs DMD curve. Finally we drew the probability distribution of Remaining Useful Life of absorption suspected windings.

• Journal of the Korean Geotechnical Society
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• v.39 no.4
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• pp.45-54
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• 2023

The settlement prediction during the design phase is primarily conducted using theoretical methods. However, measurement-based settlement prediction methods that predict future settlements based on measured settlement data over time are primarily used during construction due to accuracy issues. Among these methods, the hyperbolic method is commonly used. However, the existing hyperbolic method has accuracy issues and statistical limitations. Therefore, a weighted nonlinear regression hyperbolic method has been proposed. In this study, two weighting methods were applied to the weighted nonlinear regression hyperbolic method to compare and analyze the accuracy of settlement prediction. Measured settlement plate data from two sites located in Busan New Port were used. The settlement of the remaining sections was predicted by setting the regression analysis section to 30%, 50%, and 70% of the total data. Thus, regardless of the weight assignment method, the settlement prediction based on the hyperbolic method demonstrated a remarkable increase in accuracy as the regression analysis section increased. The weighted nonlinear regression hyperbolic method predicted settlement more accurately than the existing linear regression hyperbolic method. In particular, despite a smaller regression analysis section, the weighted nonlinear regression hyperbolic method showed higher settlement prediction performance than the existing linear regression hyperbolic method. Thus, it was confirmed that the weighted nonlinear regression hyperbolic method could predict settlement much faster and more accurately.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.163-179
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• 2010

Recentlythe concept of fast fashion is drawing attention as customer needs are diversified and supply lead time is getting shorter in fashion industry. It is emphasized as one of the critical success factors in the fashion industry how quickly and efficiently to satisfy the customer needs as the competition has intensified. Because the fast fashion is inherently susceptible to trend, it is very important for fashion retailers to make quick decisions regarding items to launch, quantity based on demand prediction, and the time to respond. Also the planning decisions must be executed through the business processes of procurement, production, and logistics in real time. In order to adapt to this trend, the fashion industry urgently needs supports from intelligent quick response(QR) system. However, the traditional functions of QR systems have not been able to completely satisfy such demands of the fast fashion industry. This paper proposes an intelligent quick response system for the fast fashion(IQRS-FF). Presented are models for QR process, QR principles and execution, and QR quantity and timing computation. IQRS-FF models support the decision makers by providing useful information with automated and rule-based algorithms. If the predefined conditions of a rule are satisfied, the actions defined in the rule are automatically taken or informed to the decision makers. In IQRS-FF, QRdecisions are made in two stages: pre-season and in-season. In pre-season, firstly master demand prediction is performed based on the macro level analysis such as local and global economy, fashion trends and competitors. The prediction proceeds to the master production and procurement planning. Checking availability and delivery of materials for production, decision makers must make reservations or request procurements. For the outsourcing materials, they must check the availability and capacity of partners. By the master plans, the performance of the QR during the in-season is greatly enhanced and the decision to select the QR items is made fully considering the availability of materials in warehouse as well as partners' capacity. During in-season, the decision makers must find the right time to QR as the actual sales occur in stores. Then they are to decide items to QRbased not only on the qualitative criteria such as opinions from sales persons but also on the quantitative criteria such as sales volume, the recent sales trend, inventory level, the remaining period, the forecast for the remaining period, and competitors' performance. To calculate QR quantity in IQRS-FF, two calculation methods are designed: QR Index based calculation and attribute similarity based calculation using demographic cluster. In the early period of a new season, the attribute similarity based QR amount calculation is better used because there are not enough historical sales data. By analyzing sales trends of the categories or items that have similar attributes, QR quantity can be computed. On the other hand, in case of having enough information to analyze the sales trends or forecasting, the QR Index based calculation method can be used. Having defined the models for decision making for QR, we design KPIs(Key Performance Indicators) to test the reliability of the models in critical decision makings: the difference of sales volumebetween QR items and non-QR items; the accuracy rate of QR the lead-time spent on QR decision-making. To verify the effectiveness and practicality of the proposed models, a case study has been performed for a representative fashion company which recently developed and launched the IQRS-FF. The case study shows that the average sales rateof QR items increased by 15%, the differences in sales rate between QR items and non-QR items increased by 10%, the QR accuracy was 70%, the lead time for QR dramatically decreased from 120 hours to 8 hours.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.2
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• pp.23-30
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• 2010

The research presents moisture content measuring and calibration method of road pavement, especially asphalt concrete pavement for performance evaluation or remaining life prediction using Time Domain Reflectometry(TDR) sensor, CS616 made by campbell INC. Before calibration test of CS616, accomplished a sensor verification tests. Verification test items were covering depth and interference effect of two CS616 sensors, temperature effects between $5^{\circ}C\sim25^{\circ}C$ and compaction ratio effects. Covering depth and interference effects between two CS616 sensors were just small and the effects of temperature and compaction ratio effected a Volumetric Moisture Contents at $\pm6%$ under disregard appeared with the fact that was possible. Also, obtained the calibration equation of the subgrade and subbase course, $R^2$ showed above of all 0.9.

• Asian Spine Journal
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• v.12 no.6
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• pp.1069-1077
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• 2018

Study Design: A case study. Purpose: To assess the chronological changes of the disease-related kyphosis after chemotherapy alone, secondly to clarify the role of growth cartilage in the healed lesion on kyphosis change, and to define the accurate prediction time in assessing residual kyphosis. Overview of Literature: None of the previous papers up to now dealt with the residual kyphosis, stability and remodeling processes of the affected segments. Methods: One hundred and one spinal tuberculosis children with various stages of disease processes, age 2 to 15 years, were the subject materials, between 1971 to 2010. They were treated with two different chemotherapy formula: before 1975, 18 months of triple chemotherapy (isoniazid [INH], para-aminosalicylic acid, streptomycin); and since 1976, 12 months triple chemotherapy (INH, rifampicin, ethambutol, or pyrazinamide). The first assessment at post-chemotherapy one year and at the final discharge time from the follow-up (36 months at minimum and 20 years at maximum) were analyzed by utilizing the images effect of the remaining growth plate cartilage on chronological changes of kyphosis after initiation of chemotherapy. Results: Complete disc destruction at the initial examination were observed in two (5.0%) out of 40 cervical spine, eight (26.7%) out of 30 dorsal spine, and six (19.4%) out of 31 lumbosacral spine. In all those cases residual kyphosis developed inevitably. In the remainders the discs were partially preserved or remained intact. Among 101 children kyphosis was maintained without change in 20 (19.8%), while kyphosis decreased in 14 children (13.7%), and increased in 67 children (66.3%) with non-recoverably damaged growth plate, respectively. Conclusions: It could tentatively be possible to predict the deformity progress or non-progress and spontaneous correction at the time of initial treatment, but it predictive accuracy was low. Therefore, assessment of the trend of kyphotic change is recommended at the end of chemotherapy. In children with progressive curve change, the deformity assessment should be continued till the maturity.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.2
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• pp.70-76
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• 2014

In industrial situation, electronic and electro-mechanical systems have been using different type of batteries in rapidly increasing numbers. These systems commonly require high reliability for long periods of time. Wider application of battery for low-power design as a prime power source requires us knowledge of failure mechanism and reliability of batteries in terms of load condition, environment condition and other explanatory variables. Battery life is an important factor that affects the reliability of such systems. There is need for us to understand the mechanism leading to the failure state of battery with performance characteristic and develop a method to predict the life of such battery. The purpose of this paper is to develope the methodology of monitoring the health of battery and determining the condition or fate of such systems through the performance reliability to predict the remaining useful life of primary battery with load condition, operating condition, environment change in light of battery life variation. In order to evaluate on-going performance of systems and subsystems adopting primary batteries as energy source, The primitive prototype for performance reliability analysis device was developed and related framework explained.