• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.1
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• pp.22-31
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• 2008

The operating window method is a novel approach in quality improvement. But it has not received deserved attention in academic research. If a critical factor for competing failure modes can be identified, the probability of failure can be reduced by widening the operating window of this factor. Traditional SN ratio for the operating window advocated by Taguchi has a critical shortcoming, which has been derived under the assumption that failure rates are determined by the operating window factor only. A new metric for robustness is given for the operating window method, which has relaxed the restrictive assumption of Taguchi's SN ratio. And procedures for determining optimal conditions based on the new metric is presented. The effectiveness of the proposed approach over the traditional practice is tested with the aid of a wave soldering process.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.138-144
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• 2015

Digital filters are extensively used in the world of communication. In order to design a digital finite impulse response (FIR) filter that satisfies all the required conditions is challenging. In this paper, design techniques of digital low pass FIR filters using Rectangular window method, Hamming window, Hanning window, and Optimal Parks McClellan method are presented. The stability, number of components required and filter coefficients are demonstrated for different design techniques. It is demonstrated that filter design using hamming window is comparatively better than rectangular and hanning window though the components required for all of the windowing technique are same, hamming shows higher stability. The stability is shown with the help of magnitude and phase spectrum of each window. Simulation is carried out using MATLAB and comparisons are made entirely based on the output of the simulation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.10 no.4
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• pp.73-79
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• 2000

We show how to reduce the number of multiplications required for an exponentiation by using a window method and a factor method. This method requires 599 multiplications for a 512-bit integer exponent while the window method with window size 5 requires 607 multiplications. This method requires fewest multiplications among practical exponentiation algo- rithms.

• Spatial Information Research
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• v.18 no.5
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• pp.13-26
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• 2010

In this paper, a dynamic variable window-based topographical classification method is proposed which has the changeable classification units depending on topographical properties. In the proposed scheme, to im prove the classification efficiency, the unit of topographical classification can be changeable dynamically according to the topographical properties and repeated patterns. Also, in this paper, the classification efficiency and accuracy of the proposed method are analyzed in order to find an optimal maximum decision window-size through the experiment. According to the experiment results, the proposed dynamic variable window-based topographical classification method maintains similar accuracy but remarkably reduce computing time than that of a fixed window-size based one, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5A
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• pp.426-432
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• 2007

The MAP algorithm is designed and implemented through the sliding window method for turbo decoding. First, the implementation issues, which are the length of the sliding window and the normalization method of state metrics are reviewed, and their optimal values are obtained by the simulation. All component schemes of the decoder including the branch metric evaluator are also presented. The proposed MAP architecture can be easily redesigned according to the size of sliding window, that is, sub-frame length because of its simplicity on buffer control.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.109-111
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• 1989

In this paper, we propose a new method of parameter est mat ion which modifies the exponentially weighted RLS (WRLS) method using asliding window. It can be used in adaptive control for a class of linear tine varying system. Computer simulations show that our new method tracts rapidly time varying parameters more effectively than WRLS.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.4 no.2
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• pp.82-95
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• 1992

It has been known that the application of an airflow window system reduces the energy consumption compared with conventional double pane window in a building. But how to analyze thermal load in a building with an airflow window system has not been well known. so two kinds of method (Mode 1 and Mode 2) to analyze time dependent thermal load of the building with an airflow window system are presented in this study. The results of load analysis about the model building(total area : $4521m^2$, 3 floors) by Mode 2 show that the maximum cooling and heating load in a building with an airflow window system are decreased about 12-17% and about 19.5% than with double pane glass window, and yearly energy consumption with an airflow window system is saved about about 20% than with double pane glass window.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.557-560
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• 2008

Window system is an essential component for ventilation, lighting, and thermal environment in buildings. However, window system has the lowest insulation performance and may cause high energy consumptions, if it is not properly designed. Thus, performance of window systems play an important role in built environment. This study proposes a new window systems for balcony, which has double vents and analyses the thermal performance using an intergrated simulation method with Therm 6.1 and Widow 6.1. The result shows higher U-factor than conventional window systems. It is expected that the double vent window system can increase thermal performance and save energy in apartment houses.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.601-607
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• 2018

Median filtering is a nonlinear method which is known to be effective in removing impulse noise while preserving local image structure relatively well. However, it could still suffer the smearing phenomena of edges and fine details into neighbors due to undesirable influence from the pixels whose values are far off from the true value of the pixel at hand. This drawback mainly comes from the fact that median filters typically employ a regular shape window for collecting the pixels used in the filtering operation. In this paper, we propose a median filtering method which employs an irregular shape filter window in collecting neighboring pixels around the pixel to be denoised. By employing an irregular shape window, we can achieve good noise suppression while preserving image details. Experimental results have shown that our approach is superior to regular window-based methods.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.156-161
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• 2003

It is an interest problem to predict substance distributions in three-dimensional space. Recently, a research field as Geostatistics is advanced. It is a kind of inter- or extrapolation mathematically. Some useful means for the inter- and extrapolation are known, in which slide window method with neural networks is hopeful one. We propose multi-dimensional extrapolation using multi-layer neural networks and the slide-window method. The multi-dimensional extrapolation is not similar to one-dimension. It has plural algorithms. We researched line predictors and local-plain predictors I two-dimensional space. The both predictors are equivalent; however, in multi-dimensional extrapolation, it is very important to find the direction of predictions. Especially, since the slide window method requires information to predict the future in sampling data, if they are not ordered appropriately in the direction, the predictor cannot operate. We tested the extrapolation for typical two-dimensional functions, and found an excellent character of slide-window method based on local-plain. By using the method, we can extrapolate the function until twice-outer regions of the definitions.