• Journal of Audiology & Otology
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• v.24 no.2
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• pp.53-60
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• 2020

Several novel animal models that represent the pathophysiological process of endolymphatic hydrops (ELH) of Meniere's disease (MD) have been developed. Animal models are important to identify and characterize the pathophysiology of ELH and to corroborate molecular and genetic findings in humans. This review of the current animal models will be useful in understanding the pathophysiology of and developing proper treatments for MD. Surgical animal models will be replaced by medication-induced animal models. Study models previously developed in guinea pigs will be developed in several smaller animals for ease of conducting molecular analysis. In this review, we provided updated resources including our previous studies regarding the current and desirable animal models for MD.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.1
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• pp.111-120
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• 2020

Generative adversarial networks (GANs) achieved impressive performance on image generation and visual classification applications. However, adversarial networks meet difficulties in combining the generative model and unstable training process. To overcome the problem, we combined the deep residual network with upsampling convolutional layers to construct the generative network. Moreover, the study shows that image generation and classification performance become more prominent when the residual layers include on the generator. The proposed network empirically shows that the ability to generate images with higher visual accuracy provided certain amounts of additional complexity using proper regularization techniques. Experimental evaluation shows that the proposed method is superior to image generation and classification tasks.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1043-1050
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• 2022

Markov chains and Monte Carlo Simulation were applied to account for the probabilistic nature of pavement deterioration over time using data collected in the field. The primary purpose of this study was to evaluate pavement network performance of Western Australia (WA) by applying the existing pavement management tools relevant to WA road construction networks. Two approaches were used to analyze the pavement networks: evaluating current pavement performance data to assess WA State Road networks and predicting the future states using past and current pavement data. The Markov chains process and Monte Carlo Simulation methods were used to predicting future conditions. The results indicated that Markov chains and Monte Carlo Simulation prediction models perform well compared to pavement performance data from the last four decades. The results also revealed the impact of design, traffic demand, and climate and construction standards on urban pavement performance. This study recommends an appropriate and effective pavement engineering management system for proper pavement design and analysis, preliminary planning, future pavement maintenance and rehabilitation, service life, and sustainable pavement construction functionality.

• New & Renewable Energy
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• v.5 no.3
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• pp.40-48
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• 2009

Recovered heat has been considered as a renewable energy in Europe since 2008 because its great effect on energy saving and carbon decreasing in plant process. Energy saving and decreasing green gas are critical issue today, so various technologies to save energy and decrease carbon dioxide in plant process have been applied to many industrial area. In this paper, the feasibility of condenser heat recovery by heat pump in power plant for district heating and fuel line preheating were reviewed by verifying energy (heat) balance and mass balance of power plant model. Some ways to compose proper system to recover heat of condenser are suggested and their possibilities are also reviewed. Limitations on heat recovery in power plant are also reviewed. The results are verified by calculating input/output energy based on actual performance test data of Taean Thermal Power Plant in Korea. There is noticeable improvement of plant performance in some cases which demand low temperature (<100 C) heat like distrcit heating, fuel line heating, and so forth.

• Transactions of Materials Processing
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• v.23 no.6
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• pp.376-379
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• 2014

During roll forming a sheet metal is continuously and progressively formed into a product of the required cross-section and longitudinal shape. An example product is a circular tube with a required diameter, wall-thickness and straightness. Roll forming occurs by passing the sheet through a series of forming rolls that are arranged in tandem. Each pair of forming rolls in the roll forming line plays a particular role in obtaining the required cross-section and longitudinal shape in the product. In recent years, that process is often applied to car body parts by automotive industries. In the current study, an optimal model design and proper roll-pass sequences as well as the number of forming rolls and bending angles were used to produce a sill side. The effects of the process parameters on the final shape formed by roll forming defects were evaluated.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1222-1229
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• 1993

An advanced design environment , which is based on adaptive and knowledge -based finite elements (INTELMESH), has been developed. Unlike other approaches, INTEMMESH incorporates the information about the object geometry as well as the boundary and loading conditions to generate an ${\alpha}$-priori finite element mesh which is more refined around the critical regions of the problem domain. INTEMMESH is designed for planar domains and axisymmetric 3-D structures of elasticity and heat transfer subjected to mechanical and thermal loading . It intelligently identifies the critical regions/points in the problem domain and utilize the new concepts of substructuring and wave propagation to choose the proper mesh size for them. INTEMMESH generates well-shaped triangular elements by applying trangulartion and Laplacian smoothing procedures. The adaptive analysis involves the intial finite elements analyze and an efficient ${\alpha}$-posteriori error analysis involves the initial finite element anal sis and an efficient ${\alpha}$-posteriori error analysis and estimation . Once a problem is defined , the system automatically builds a finite element model and analyzes the problem though automatic iterative process until the error reaches a desired level. It has been shown that the proposed approach which initiates the process with an ${\alpha}$-priori, and near optimum mesh of the object , converges to the desired accuracy in less time and at less cost. Such an advanced design/analysis environment will provide the capability for rapid product development and reducing the design cycle time and cost.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.05a
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• pp.224-228
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• 2007

It is focused on a methodology to establish a optimal inspection cycle of electrical facility of railroad Decision method of optimal inspection cycle is a process which establishes maintenance plan for facilities' immanent function as using reliability theory in operation term In order to ensure normal operation in a given condition, the decision method is logical for selecting effective maintenance plan to consider characteristic of system In estimation of failure rate, critical facility is selected firstly. After that, proper distribution function on each facility is decided to investigate distribution function for extraction of failure rate. Next, cost produced by the case that facility's failure is occurred is surveyed. Finally, maintenance method developed until now is investigated, before suitable model for the facility applying maintenance method is developed, and that maintenance decision is made. Therefore, this process is the method to find optimal inspection cycle for reasonable cost and effective reliability on facility.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.6
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• pp.434-440
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• 2007

One of the cold start problems of a FCV is the freezing of the water in the water tank when a FCV is not in operation and the surrounding temperature drops below $0^{\circ}C$. The ice in the tank should be melted as quickly as possible for a satisfactory operation of fuel cell vehicles. In this study, the melting process for the constant heat fluxes of the plate heaters was numerically calculated in the 2-D model of the tank and plate heaters. The enthalpy method and FVM code was used for this analysis. The changes of the temperature with heat fluxes and the heat transfer area could be investigated. The energy balance error was found to increase with the heat flux. From this numerical analysis, the proper heat flux value and some important design factors relating local overheating and pressurization of the water tank could be examined.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.43-48
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• 2002

This paper discusses the application of fuzzy-ARTMAP neural network to compensate the nonlinearity of satellite communication channel. The fuzzy-ARTMAP is the class of ART(adaptive resonance theory) architectures designed fur supervised loaming. It has capabilities not fecund in other neural network approaches, that includes a small number of parameters, no requirements fur the choice of initial weights, automatic increase of hidden units, and capability of adding new data without retraining previously trained data. By a match tracking process with vigilance parameter, fuzzy-ARTMAP neural network achieves a minimax teaming rule that minimizes predictive error and maximizes generalization. Thus, the system automatically leans a minimal number of recognition categories, or hidden units, to meet accuracy criteria. As a input-converting process for implementing fuzzy-ARTMAP equalizer, the sigmoid function is chosen to convert actual channel output to the proper input values of fuzzy-ARTMAP. Simulation studies are performed over satellite nonlinear channels. QPSK signals with Gaussian noise are generated at random from Volterra model. The performance of proposed fuzzy-ARTMAP equalizer is compared with MLP equalizer.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.3
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• pp.79-94
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• 2012

According to the higher dependence of contemporary firms on data digitalization and the information technology, the role and importance of Information Security Management (ISM) is getting higher. Thus, there is a need to arrange proper procedure and a series of device within the organization in order to reduce diverse security risks, which take place from the inside and the outside of firm. In other words, prior examination for reinforcing recognition of ISM, and of a systematic performance method in the refined form is important. This study investigate the key variables influencing the ISM. Thus, this study suggests firm environmental factors that include four exogenous variables, market volatility, task interdependence, perceived benefits, and coordination mechanism affecting awareness of ISM. In addition, it proposes a concept of the ISM process with awareness, development, and performance, and examines the moderating effects of regulatory influence. The research model was tested by using Structural Equation Modeling, via SmartPLS 2.0 analysis on a sample collected from 186 employees in various industries. The research results provide the evidence that supports the tested hypotheses except significance of coordination mechanism. The implications of the findings suggest a new theoretical framework of the ISM and offers important solutions for the practical application guidelines.