• 한국연소학회:학술대회논문집
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• 2003.05a
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• pp.195-199
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• 2003

The stoichiometric methan/air premixed turbulent flames at the axisymmetric Bunsen burner situation are numerically investigated. To account for the chemistry-turbulence interaction in the turbulent premixed flames, the steady laminar flamelet library method has been adopted. The flame front is tracked by using the Level-Set Approach. Turbulence is represented by the ${\kappa}-{\varepsilon}$ modeling with a Pope's correction. The detailed comparison between prediction and measurement has made for the flame field in terms of velocity, turbulent kinetic energy, and normarlized temperature.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2787-2790
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• 2003

In this paper, we predict tracking performance of the multiple hypothesis tracking (MHT) algorithm. The MHT algorithm is known to be an optimal Bayesian approach and is superior to asly other tracking filters because it takes into account the events that the measurements can be originated from new targets and false alarms 3s well as interesting targets. In the MHT algorithm, a number of candidate hypotheses are generated and evaluated later as more data are received. The probability of each candidate hypotheses is approximately evaluated by using the hybrid conditional average approach (HYCA). We performed numerical experiments to show the validity of our performance prediction.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.73-75
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• 1987

The paper proposes a class of discrete-time adaptive controller which may be applicable without sufficient a priori information. Against choices of the Information, GPC algorithm may seem to be more robust than any other methods reported, but it is the method based on Indirect approach. It is, therefore, reasonable to propose an algorithm via the zero-gain prediction, in which the control parameters are directly estimated and calculated.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.146-153
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• 1998

NC machines with 4 or 5 axes are capable of various tool approach motions, which makes interference-free and high machinablity machining possible. This paper deals with how to integrate these two advantages (interference-free and high machinability machining) in multi-axes NC machining with a ball-end mill. Feasible tool approach region at a point on a surface is first computed, then among which an approach direction is determined so as to minimize the cutting force required. Tool and spindle volumes are considered in computing the feasible tool approach region, and the computing time is improved by trans-forming surface patches into minimal enclosing spheres. A cutting force prediction model is used for estimating the cutting force. The algorithm is developed so as to be applied to 4- or 5-axes NC machining in common.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.12
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• pp.1090-1097
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• 2000

Predicting building energy use can be useful to evaluate its energy performance. This study proposed empirical approach for predicting building energy use with regression analysis. For the empirical analysis, simple regression models were developed based on the historical energy consumption data as a function of daily outside temperature, the predicting equations were derived for different operational modes and day types, then the equations were applied for predicting energy use in a building. BY selecting a real building as a case study, the feasibilities of the empirical approach for predicting building energy use were examined. The results showed that empirical approach with regression analysis was fairly reliable by demonstrating prediction accuracy of $pm10%$ compared with the actual energy consumption data. It was also verified that the prediction by regression models could be simple and fairly accurate. Thus, it is anticipated that the empirical approach will be useful and reliable tool for many purposes: retrofit savings analysis by estimating energy usage in an existing building or the diagnosis of the building operational problems with real time analysis.

• Journal of electromagnetic engineering and science
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• v.11 no.3
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• pp.220-226
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• 2011

We have proposed a new method to accurately predict the resonance of Fabry-Perot Cavity (FPC) antennas enclosed with conducting side walls. When lateral directions of an FPC antenna are not blocked with metallic walls, the conventional technique is accurate enough to predict the resonance of the FPC antenna. However, when the FPC antenna has side walls, especially for case with only a short distance between the walls, the conventional prediction method yields an inaccurate result, inevitably requiring a tedious, time-consuming tuning process to determine the correct resonant height to provide the maximum antenna gain in a target frequency band using three-dimensional full-wave computer simulations. To solve that problem, we have proposed a new resonance prediction method to provide a more accurate resonant height calculation of FPC antennas by using the well-known resonance behavior of a rectangular resonant cavity. For a more physically insightful explanation of the new prediction formula, we have reinvestigated our proposal using a wave propagation characteristic in a hollow rectangular waveguide, which clearly confirms our approach. By applying the proposed technique to an FPC antenna covered with a partially reflecting superstrate consisting of continuously tapered meander loops, we have proved that our method is very accurate and readily applicable to various types of FPC antennas with lateral walls. Experimental result confirms the validness of our approach.

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.19-29
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• 2008

The main purpose of this study is to introduce Hauer's(2004) approach that overcomes current accident prediction models' limitation and to apply this approach to Korean situation using fatal accident data on motorways. After developing accident prediction models according to this approach, it is found that AADT and vertical grade could improve fitness of the model, whereas a radius of roads is not related to the number of accidents. The advantage of Hauer's approach is to reduce possibility to eliminate critical variables and to keep uncritical variables when we consider many variables to develop accident prediction models.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.5
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• pp.631-638
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• 2013

The probabilistic fatigue life analysis is one of the common methods to account the uncertainty of parameters on the structural failure. Frequently, the Bayesian approach has been demonstrated as a proper method to show the uncertainty of parameters. In this work, the application of probabilistic fatigue life prediction method for the aircraft structure was studied. This effort was conducted by using the PoF(Probability of Failure) based on Bayesian approach. Furthermore, numerical example was carried out to confirm the validation of the suggested approach. In conclusion, it was shown that the Bayesian approach can calculate the probabilistic fatigue lives and the quantitative value of PoF effectively for the aircraft structural component. Moreover the calculated probabilistic fatigue lives can be utilized to determine the optimized inspection period of aircraft structures.

• Corrosion Science and Technology
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• v.3 no.3
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• pp.87-97
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• 2004

This paper presents a new approach with meso scale structure models to express mechanical property, such as stress - strain relationships, of concrete. This approach is successful to represent both uniaxial tension and uniaxial compression stress - strain relationship, which is in macro scale. The meso scale approach is also applied to predict degraded mechanical properties of frost-damaged concrete. The degradation of mechanical properties with frost-damaged concrete was carefully observed. Strength and stiffness in both tension and compression decrease with freezing and thawing cycles (FTC), while stress-free crack opening in tension softening increases. First attempt shows that the numerical simulation can express the experimentally observed degradation by introducing changes in the meso scale structure in concrete, which are assumed based on observed damages in the concrete subjected to FTC. At the end applicability of the meso scale approach to prediction of the degradation by combined effects of salt attack and FTC is discussed. It is shown that clarification of effects of frost damage in concrete on corrosion progress and on crack development in the damaged cover concrete due to corrosion is one of the issues for which the meso scale approach is useful.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.434-442
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• 2023

The relationship between acute kidney injury (AKI) prediction and nephrotoxic drugs, or drugs that adversely affect kidney function, is one that has yet to be explored in the critical care setting. One contributing factor to this gap in research is the limited investigation of drug modalities in the intensive care unit (ICU) context, due to the challenges of processing prescription data into the corresponding drug representations and a lack in the comprehensive understanding of these drug representations. This study addresses this gap by proposing a novel approach that leverages patient prescription data as a modality to improve existing models for AKI prediction. We base our research on Electronic Health Record (EHR) data, extracting the relevant patient prescription information and converting it into the selected drug representation for our research, the extended-connectivity fingerprint (ECFP). Furthermore, we adopt a unique multimodal approach, developing machine learning models and 1D Convolutional Neural Networks (CNN) applied to clinical drug representations, establishing a procedure which has not been used by any previous studies predicting AKI. The findings showcase a notable improvement in AKI prediction through the integration of drug embeddings and other patient cohort features. By using drug features represented as ECFP molecular fingerprints along with common cohort features such as demographics and lab test values, we achieved a considerable improvement in model performance for the AKI prediction task over the baseline model which does not include the drug representations as features, indicating that our distinct approach enhances existing baseline techniques and highlights the relevance of drug data in predicting AKI in the ICU setting.