• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1995년도 가을 학술발표회 논문집
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• pp.334-338
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• 1995

In recent years, the prediction of the deterioration rate of concrete structures has become major research interest. However, there are still many uncertain factors in the deterioration process and the relation between deterioration and durability of structures. This is mainly due to various uncertainties involved in the construction process and the environmental conditions which affect the rate of deterioration of concrete structures. In this study a limit state model in terms of random crack width due to applied dead and live loads is proposed for the assessment of crack damage of reinforced concrete structures. The AFOSM reliability method is used for the reliability evaluation of the crack durability of concrete bridges. The proposed model for crack durability of concrete bridges is applied to the Seoul interior circuit elevated expressway. The sensitivity analyses are performed for the proposed model.

• 대한임베디드공학회논문지
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• 제13권4호
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• pp.215-223
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• 2018

Recently, as interest of wearable devices has increased, commercially available smart wristbands and applications have been used as a tool for personal healthy management. However most previous studies have focused on evaluating the accuracy and reliability of the technical problems of wearable devices, especially step counts, walking distance, and energy consumption measured from the smart wristbands. In this study, we propose a physical activity evaluation model using classification rules, induced from the associative classification mining approach. These rules associated with five physical activities were generated by considering activities and walking times in target heart rate zones such as 'Out-of Zone', 'Fat Burn Zone', 'Cardio Zone', and 'Peak Zone'. In the experiment, we evaluated the prediction power of classification rules and verified its effectiveness by comparing classification accuracies between the proposed model and support vector machine.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2007년도 제29회 추계학술대회논문집
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• pp.27-30
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• 2007

In recent years, scientific community has found renewed interest in hypersonic flight research. These hypersonic vehicles undergo severe aero-thermal environments during their flight regimes. One of the most important topics of research in hypersonic aerodynamics is to find a reasonable way of calculating either the surface temperature or the heat flux to surface when its temperature is held fixed. This requires modeling of physical and chemical processes. Hyperbolic system of equations with stiff relaxation method are being identified in recent literature as a novel method of predicting long time behavior of systems such as gas at high temperatures. In present work, Energy Relaxation Method (ERM) has been considered to simulate the real gas flow over a 2-D cylinder. Present heat flux results over the cylinder compared well with the experiment. Thus, real gas effects in hypersonic flows can be modeled through energy relaxation method.

• Communications for Statistical Applications and Methods
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• 제16권5호
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• pp.851-858
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• 2009

In the last decades, there has been much interest in climate variability because its change has dramatic effects on humanity. Especially, the precipitation data are measured over space and their spatial association is so complicated. So we should take into account such a spatial dependency structure while analyzing the data. However, in linear models for analyzing the data, data sets show severely skewed distribution. In the paper, we consider the Box-Cox transformation to satisfy the normal distribution prior to the analysis, and employ a Bayesian hierarchical framework to investigate the spatial patterns. The data set we considered is monthly average precipitation of the third quarter of 2007 obtained from 347 automated monitoring stations in Contiguous South Korea.

• 상하수도학회지
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• 제26권4호
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• pp.547-554
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• 2012

As a national river remediation project has been completed, this study has a special interest on the capabilities to predict water levels at various points of the Geum River. To be endowed with intelligent forecasting capabilities, the author formulate the neuro-genetic algorithm associated with the short-term water level prediction model. The results show that neuro-genetic algorithm has considerable potentials to be practically used for water level forecasting, revealing that (1) model optimization can be obtained easily and systematically, and (2) validity in predicting one- or two-day ahead water levels can be fully proved at various points.

• 전기학회논문지
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• 제65권6호
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• pp.918-922
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• 2016

As the number of wind farms operating has increased, the interest of the central unit commitment and dispatch for wind power has increased as well. Wind power forecast is necessary for effective power system management and operation with high wind power penetrations. This paper presents the centralized wind power forecasting method, which is a forecast to combine all wind farms in the area into one, using time series models. Also, this paper proposes a prediction model modified with wind forecast error compensation. To demonstrate the improvement of wind power forecasting accuracy, the proposed method is compared with persistence model and new reference model which are commonly used as reference in wind power forecasting using Jeju Island data. The results of case studies are presented to show the effectiveness of the proposed wind power forecasting method.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.1021-1026
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• 2003

The problem of predicting the fracture strength behavior in orthotropic plate with a crack inclined with respect to the principal material axes is analyzed. Both the load to cause fracture and the crack direction of crack growth arc of interest. The theoretical results based on the normal stress ration theory show significant effects of biaxial loading and the fiber orientation on the crack growth angle and the critical stress. The additional term in the asymptotic expansion of the crack tip stress field appears to provide more accurate critical stress prediction.

• KIEAE Journal
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• 제12권1호
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• pp.127-132
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• 2012

The energy consumption in the world is growing rapidly. And the environmental issues of climate become a important task. The interest in renewable energy like wind and solar is increasing now. Especially, by reducing power transmission loss, a small wind power is getting attention at the residential areas and campus of university. In this study, we attempted to estimate and compare the wind energy density using wind data of AWS (Automatic Weather Station) of H University. In this case of a campus, the weibull distribution parameter C is 2.27, and K is 0.88. According to the data, the energy density of the small wind power is 12.7 W/m2. We did CFD(Computational Fluid Dynamics) simulations at H University campus by 7 wind directions(ENE, ESE, SE, NW, WNW, W, WSW). In the results, we suggest 4 small wind powers. The small wind power generating system can produce 4,514kWh annually.

• 한국유체기계학회 논문집
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• 제4권2호
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• pp.7-14
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• 2001

Design and development of a propeller fan for a cooling tower have been accomplished by both numerical prediction of performance and experimental validation with a wind tunnel. Main interest lies on blade geometry of a fan for optimal design of aerodynamic performance. A commercial program, Fine/Turbo used for the present numerical estimation, gives us engineering information such as flow details near the blades and flow rate of the system. The numerical results are compared with precise experimental output and show good agreement in comparison between the two data. Also new proposed model of a blade shows improved performance relative to present running model in market.

• 품질경영학회지
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• 제7권2호
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• pp.22-28
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• 1979

The problem considered in this paper is to select the vital factor effect to the product quality through the experimental design and analysis of response surface, so as to control the quality improvement of industrial product. In this time, even through the mathematical model is unknown it could be applicable to control the quality of industrial products and to determine optimum operating condition for many technical fields, particulary, for industrial manufacturing process. When a set of data is available from an experimental design, it is often of interest 1:0 fit polynominal repression model in independent variables (eg, time, temperature, pressure, etc) the optimize the response variable (eg. yield, strength etc). This paper proposes a method known to obtain the optimum operating condition, and how to find the condition by using table of orthogonal array experiments, and optimization methodology of statistical model. A criterion can be applied determining to optimum operating conditions in manufacturing industry and improving the fit of response surface which may be used for prediction of responses and quality control of industrial products.