• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.23-27
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• 2007

Many trials have been used to model room impulse responses, all attempting to provide efficient representations of room acoustics. The traditional model designs for room impulse response seem to fail in accuracy, controllability, or computational efficiency. In time domain, a room impulse response is generally considered as the combination of three parts having different acoustic characteristics, initial time delay, early reflection, and late reverberation. This paper introduces new learning hybrid model for the room impulse response. In this proposed model, those three parts are modeled using different models with learning algorithms that determine the length or boundary of each model in the hybrid model. By the simulation with measured room impulse responses, it was examined that the performance of proposed model shows the best efficiency in views of both the parameter numbers and modeling error.

• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.297-301
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• 2023

The study identified the various causes of odor problems, the discomfort they cause, and the importance of the public health and environmental issues associated with them. To solve the odor problem, you must identify the cause and perform an accurate analysis. Therefore, we proposed a CNN-Transformer hybrid model (CTHM) that combines CNN and Transformer and evaluated its performance. It was evaluated using a dataset consisting of 120,000 odor samples, and experimental results showed that CTHM achieved an accuracy of 93.000%, a precision of 92.553%, a recall of 94.167%, an F1 score of 92.880%, and an RMSE of 0.276. Our results showed that CTHM was suitable for odor analysis and had excellent prediction performance. Utilization of this model is expected to help address odor problems and alleviate public health and environmental concerns.

• Journal of Environmental Impact Assessment
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• v.14 no.4
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• pp.157-164
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• 2005

Existing models that predict of Daily water supply include statistical models and neural network model. The neural network model was more effective than the statistical models. Only neural network model, which predict of Daily water supply, is focused on estimation of the operational control. Neural network model takes long learning time and gets into local minimum. This study proposes Neuro Genetic hybrid model which a combination of genetic algorithm and neural network. Hybrid model makes up for neural network's shortcomings. In this study, the amount of supply, the mean temperature and the population of the area supplied with water are use for neural network's learning patterns for prediction. RMSE(Root Mean Square Error) is used for a MOE(Measure Of Effectiveness). The comparison of the two models showed that the predicting capability of Hybrid model is more effective than that of neural network model. The proposed hybrid model is able to predict of Daily water, thus it can apply real time estimation of operational control of water works and water drain pipes. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 11.81% and the average error was lower than 1.76%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.4
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• pp.1-12
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• 1999

This paper presents a DEA-AHP hybrid model to evaluate and select R&D projects. AHP collects and processes information on the weights of evaluation criteria. The processed information is used as an input for DEA/AR model. Only desirable number of projects are selected by the hybrid model. The model is examined by an example generated from a real data set.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.8
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• pp.2069-2078
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• 1993

The buoyancy-driven turbulent thermal convection is predicted using an anisotropic hybrid turbulence model, which is incorporated with a low Reynolds k-.epsilon. turbulence model and an anisotropic buoyant part of algebraic stress model(ASM). The numerical predictions are compared with the Davidson's model,(1) the full ASM and the experimental results of Cheesewright et al.(2) All the models are shown to predict good agreements with the experiments for the averaged turbulence quantities. It is found that the effect of an anisotropic part on the Reynolds stress and the turbulent heat fluxes is substantial. In this study, the present hybrid model gives a fairly reasonable prediction in terms of the computational accuracy, convergence and stability. The contribution of an anisotropic buoyant part to turbulent heat fluxes are also scrutinized over the range of Rayleigh numbers $(4.79{\times}10^{10}{\le}Ra{\le}7.46{\times}10^{10}).$

• Progress in Superconductivity and Cryogenics
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• v.12 no.1
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• pp.6-11
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• 2010

For real power system application of SFCL, it is necessary to develop an analysis model of the SFCL. In Korea, hybrid SFCL of the first half cycle non-limiting type have been jointly developed by KEPRI and LS Industrial Systems through DAPAS program. In this study, we developed a PSCAD/EMTDC analysis model of the hybrid SFCL of the first half cycle non-limiting type. The simulation results of the developed model are in agreement with the test results of the real SFCL. The developed SFCL model is tested in real power system model.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.83-98
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• 2021

This study identified the influence of employees' hybrid start-up intention (intention to start a business while maintaining a job) on the employees' self-determination motivation (intrinsic motivation, extrinsic motivation) and prior knowledge through the Model of Goal-directed Behavior (MGB). We used a PLS-SEM called SmartPLS 3.0 for 126 valid samples collected by judgement extraction for office workers throughout June 13, 2020 to July 3, 2020, and empirically evaluated the measurement model (internal consistency reliability, convergent and discriminant validity) and the structural model (multicollinearity, determination coefficient, effect size, predictive relevance, etc.). Only the intrinsic motivation for realizing the hybrid start-up goal of office workers had a significant impact on the hybrid start-up attitude and subjective norms, and the prior knowledge of hybrid start-up had a significant impact on the hybrid start-up desire and the hybrid start-up intention. In order to induce hybrid start-ups for workers with unstable employment, we need systems and programs that can inspire employees with intrinsic motivation and knowledge about hybrid start-up, so follow-up researches are necessary to analyze about government systems and consulting support that can promote hybrid start-up.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.19-26
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• 1999

This paper describes an analytical study on nonlinear hysteretic behavior of hybrid steel beam with reinforced concrete ends. Two types of analytical model, Polygonal Model[PM] and Hybrid Model[HM], were used to represent the nonlinear hysteretic behavior PM used three parameters, HM used an additional parameter to consider the initial stiffness reduction. The parameters calibrated comparing the hysteretic performance obtained from experiments. The purpose of this study is to develop an analytical model which can take into account the initial stiffness reduction of the hybrid members and to represent exactly the hysteretic performance for the hybrid structures with RC and steel. The analytical study showed PM tends to overestimate initial stiffness and strength. However, HM which is capable to consider the initial stiffness reduction gave good prediction on initial stiffness, post-yielding performance, strength, pinching response and so on.

• Korean Management Science Review
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• v.30 no.1
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• pp.25-41
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• 2013

This paper presents a supply chain framework with the ODM (Original Design Manufacturing)-OEM (Original Equipment Manufacturing) hybrid production of textile industry in FTA (Free Trade Agreements) environments between Korea and other countries. The proposed supply chain framework with ODM-OEM hybrid production is a unique supply chain that has both domestic production with non-tariff advantages in FTA environment and oversea production with low labor costs. To investigate the validity of the proposed supply chain, we first construct its strategic profit model and supply chain planning and then show that each member of supply chain network-yarn manufacturer, fabric manufacturer, and apparel manufacturer-can maximize their own profits without conflicts among the members. The efficiency of the ODM-OEM hybrid production system is analytically verified in comparison with the general OEM and ODM production model using profit models. Comprehensive numerical examples are provided to illustrate the advantages of the proposed system.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.3
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• pp.216-222
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• 2011

Recently, hybrid air-conditioning system has been proposed and applied to achieve building energy saving. One example is a system combining radiation panel with natural wind-induced cross-ventilation. However, few research works have been conducted on the non-uniformity of thermal comfort in such hybrid air-conditioning system. In this paper, both thermal environment and non-uniform thermal comfort of human thermal model under various air-conditioning system, including hybrid system, were evaluated in a typical office room using coupled simulation of computation fluid dynamics, radiation model and a human thermal model. The non-uniformity of thermal comfort was evaluated from the deviation of surface temperature of human thermal model. Flow fields and temperature distribution in each case were represented.