• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.588-593
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• 2011

The Main design parameters of ship HVAC systems are pressure drop and noise analysis of ducts. The Noise prediction for HVAC(Heating, Ventilating and Air Conditioning) systems are normally performed by empirical method suggested by NEBB(National Environmental Balancing Bureau, 1994), but NEBB's method is not suitable for the ship HVAC systems. In this paper, numerical analysis methods are used to develop a noise prediction method for the ship HVAC systems, especially for large ducts. To develop regression formula of attenuation of sound pressure level in large duct, Boundary Element Method(BEM) is used. Using dynamic loss coefficient which is suggested by ASHRAE fitting data base and numerical methods of HVAC noise analysis, integrated HVAC noise analysis of Program is developed. The developed program can present pressure drop and noise analysis of the ship HVAC systems. To verify the accuracy and convenience of the developed program, prediction of HVAC system for Semi-Submersible Drilling RIG is carried out and the results are compared with measurement of noise level during sea trial.

• Journal of KSNVE
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• v.10 no.5
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• pp.775-782
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• 2000

Being carried out a number of studies for the resilient mounting system of automobile engine than that of the studies for marine engines, many research results for the case of the resilient mounting system of the automobile engine have applied in the analysis for the case of marine engine. However, the size and the power of automobile engines are not only relatively small but also their operating conditions are quite different form those of marine engines. For the analysis of the automobile engine Wavelet shrinkage, misfire condition and unload condition have not been considered. Accordingly , it is not desirable to apply the results obtained form the case of automobile engines to the case of marine engines. In this study , exciting and damping forces working on the marine engine are formulated mathematically in order to apply to the design of a resilient mounting system of engine effectively. futhermore, some mathematical formulation for the analysis of the transmissibility of multi-body system are proposed. A new computer program which is able to calculate the free vibration, the transmissibility and the forced vibration of a resilient mounting system has been developed, As an application of this developed computer program, the dynamic behavior of resilient system with an actual rubber spring for the case of 6-degree-of-freedom system and 36-degree-of-freedom system are evaluated quantitatively.

• Journal of Sensor Science and Technology
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• v.12 no.2
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• pp.95-101
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• 2003

Ultrasonic transmitter used for scale prevention in boiler or heat exchanger is composed of the magnetostrictive material which transforms electric energy into ultrasonic wave and the horn which amplifies generated ultrasonic wave and transfers it into medium loaded. In this paper, we have performed the shape design for magnetostrictive material and analyzed a few type of horns which amplify generated ultrasonic wave and found each solution theoretically. Final length of the horn has been determined by measuring the sound pressure in medium between theoretical value and experience data. At last we have given the results of our study for the effects of ultrasonic wave irradiated by manufactured ultrasonic transmitter on preventing scale deposition on test pipe under the similar condition to boiler.

• Journal of the Korean housing association
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• v.26 no.3
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• pp.85-97
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• 2015

The Publicly Purchased Property (PPP) Program since 2004 has allowed low-income households to reside in decent housing at a reasonable expense and to live in a community they choose. With an increasing number of the housing stock, management of the properties becomes a growing concern. The purpose of this research is to find out the satisfaction of the tenants with residential environment and housing management. To collect data, a face-to-face interview survey was conducted for 310 households living in the designated properties of 8 cities in and outside the Seoul Metropolitan Area (SMA). Most of the households were a family of three headed by late middle-aged man and lived in physically sound, small-sized units at an affordable cost. Overall satisfaction with living environment was higher in non-SMA than in SMA, and influenced by building deterioration and unit size. Further, most of the respondents were in favor of housing management services provided by a nearby public housing estate. Building deterioration and regular onsite visits of management staff were determinants in the satisfaction with housing management. The results indicate that proper housing management delays building deterioration and assures decent living for low-income people, leading to high levels of residential satisfaction.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.620-625
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• 2009

The seismic slope stability is most often evaluated by the pseudo-static limit analysis, in which the earthquake loading is simplified as static inertial loads acting in horizontal and/or vertical directions. The transient loading is represented by constant acceleration via the pseudostatic coefficients. The result of a pseudostatic analysis is governed by the selection of the value of the pseudostatic coefficient. However, selection of the value is very difficult and often done in an ad hoc manner without a sound physical reasoning. In addition, the maximum acceleration is commonly estimated from the design guideline, which cannot accurately estimate the dynamic response of a slope. There is a need to perform a 2D dynamic analysis to properly define the dynamic response characteristics. This paper develops the modified one-dimensional seismic site response analysis. The modified site response analysis adjusts the density of the layers to simulate the change in mass and weight of the layers of the slope with depth. Multiple analyses are performed at various locations within the slope to estimate the change in seismic response of the slope. The calculated peak acceleration profiles with depth from the developed procedure are compared to those by the two-dimensional analyses. Comparisons show that the two methods result in remarkable match.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2821-2823
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• 2002

In this paper we propose the Multi-FNN (Fuzzy-Neural Networks) for optimal identification modeling of complex system. The proposed Multi-FNNs is based on a concept of FNNs and exploit linear inference being treated as generic inference mechanisms. In the networks learning, backpropagation(BP) algorithm of neural networks is used to updata the parameters of the network in order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM(Hard C-Means)clustering algorithm which carry out the input-output dat a preprocessing function and Genetic Algorithm which carry out optimization of model The HCM clustering method is utilized to determine the structure of Multi-FNNs. The parameters of Multi-FNN model such as apexes of membership function, learning rates, and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization abilities of the model. NOx emission process data of gas turbine power plant is simulated in order to confirm the efficiency and feasibility of the proposed approach in this paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.489-491
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• 2013

In this paper, Electronic Drum based on Arduino and Processing language to communicate with a computer is implemented. First, we made a drum pad by using piezoelectric sensors. The drum pads prevent damage to the sensor and new mechanism was fabricated to mitigate the impact structure. Arduino connected to the pad, the sensor detects a signal when the shock sends it to Arduino. The received signal of Arduino sends a signal to the computer, and the signal received is stored in the computer to output sound of the drum. Through this structure, the micro-controller, the computer and communications technology can be combined and applicable to a many system.

• Proceedings of the KWS Conference
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• 1996.10a
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• pp.139-141
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• 1996

Among various welding parameters, the welding current which is inversely proportional to the tip-to-workpiece distance in GMAW is an essential parameter to monitor the GMAW process of horizontal fillet joints. For the case of weld defect such as overlap in horizontal fillet welding, therefore, the signal processing for process monitoring or automatic seam tracking should be modified by considering the weld pool surface geometry including the corresponding weld defect. In other words, the adequate signal processing algorithm is indispensible to improve the performance of the arc sensor. However, arc sensor algorithm already developed usually focus on weld seam tracing but do not considering the weld qualities. In this paper, various experiments were carried out to investigate the tendencies of the weld defects when weaving motion is added, and the experimental method based on 2$^n$ factorial design was proposed for deriving the mathematical model between the leg length and the various welding conditions. Moreover, a signal processing method based on the artificial neural network(Adaptive Resonance Theory) was proposed far discriminating the current signal of sound weld beads from that of weld beads with overlap. Finally, the algorithm for weld seam tracking combined with the mathematical modeling and the signal processing method was carried out to track the weld line in conjunction with the improvement of the weld qualities. The reliability of the proposed algorithms were evaluated through various experiments, which showed that the proposed algorithms could be effectively used for arc welding automation.

• Korean Management Science Review
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• v.21 no.2
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• pp.145-165
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• 2004

Frequently. lots of organizations have experienced the value discrepancy between the expected value and the realized value from IS (information systems) investments. Being positive or negative the difference is. however, the existence of discrepancy itself is an evidence of less-than-sound management and measurement of IS projects. Analyzing the factors that cause such discrepancy has become an issue of scrutiny both in academia and in practice. We model which factors. as predictors, will affect the value discrepancy, as dependent variables. in IS investment. This research will establish and examine the research model. the validity of category classification of value discrepancy factors and the perceptual level of IS value discrepancy by survey research. As a result of the survey research. the strategic alignment. the proper system design for staffs. the project planning capability. and interdepartmental task cooperation are perceived as the factors that significantly affect the value discrepancy. And known as IS success factors such as the managerial support, the change management, the standardized process. and the competitive investment are not significant factors. The research findings will provide and emphasize useful implications which factors should be deliberately investigated in IS investment both for practices considering IS deployment and for academia.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.47-50
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• 2000

In this paper, an optimal identification method using Multi-FNN(Fuzzy-Neural Network) is proposed for model ins of nonlinear complex system. In order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM clustering algorithm which carry out the input-output data preprocessing function and Genetic Algorithm which carry out optimization of model. The proposed Multi-FNN is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. HCM clustering method which carry out the data preprocessing function for system modeling, is utilized to determine the structure of Multi-FNN by means of the divisions of input-output space. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model, To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.