• Food Science and Preservation
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• v.12 no.6
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• pp.613-616
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• 2005

The aging degree of Kimchi fermented at $4^{\circ}C$ for 29 days was evaluated by the correlation between the flavor and the acidity analysis. The Kimchi fermentation induced a gradual reduction in pH and an increase in acidity from $0.26\%$ (initial) to $1.15\%$ (29th day). Flavor pattern of the fermented Kimchi was obtained by the electronic nose system with 12 metal oxide sensors. Electronic nose analysis could differentiate the flavor profiles of Kimchi according to the fermentation periods, making 5 group in the principal component analysis (PCA) plot Therefore, aging degree of Kimchi could be differentiated by flavor patterns analysed by electronic nose.

• Particle and aerosol research
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• v.13 no.3
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• pp.111-118
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• 2017

Electrohydrodynamic (EHD) printing with the aid of strong electric fields can generate and pattern droplets that are smaller than droplets by other printing technologies. Conventional EHD printing has created two-dimensional (2D) patterns by moving its nozzle or a substrate in X and Y directions. In this study, we aimed to develop an EHD system that can create 2D patterns using a multielectrode array (MEA) without moving a nozzle or substrate. In particular, printing ink mixtures of biodegradable polymers and model dyes was patterned on a thin film made of another biodegradable polymer. Without movement of a nozzle and substrate, stable 2D patterning of minimum $6{\mu}m$ size over a range of about 1 mm away from the nozzle position was achieved by MEA control only. We also demonstrated the possibility of denser 2D pattering of the ink mixtures by moving a target substrate relative to MEA position.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.105-110
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• 2009

Conventional TV viewing environment had provided limited numbers of channels and contents so that accessibility of contents was made user's manual change of TV channels and by manual selection of TV program contents. However, with advent of IPTV and various contents and channels available to users’ terminals, excessive numbers of TV contents become available to users’ terminals, thus leading to totally different TV viewing environments. In this TV environment, users are required to make much effort to choose their preferred TV channels or program contents, which becomes much cumbersome to the users. Therefore, in this paper, we will propose TV contents schedule recommendation by making reasoning on users’ TV viewing patterns from TV viewing history data using sequential pattern mining so that so that it increases accessibility of users to many TV program contents which may be or may not be aware of the users.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.223-236
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• 2012

We develop a video processing method that allows the more advanced human perception oriented video coding. The proposed method necessarily reflects all influences by the rate-distortion based optimization and the human visual perception that is affected by the visual saliency, the limited space-time resolution and the regional moving history. For reflecting the human perceptual effects, we devise an online moving pattern classifier using the Hedge algorithm. Then, we embed the existing visual saliency into the proposed moving patterns so as to establish a human visual perception model. In order to realize the proposed human visual perception model, we extend the conventional foveation filtering method. Compared to the conventional foveation filter only smoothing less stimulus video signals, the developed foveation filter can locally smooth and enhance signals according to the human visual perception without causing any artifacts. Due to signal enhancement, the developed foveation filter more efficiently transfers the bandwidth saved at smoothed signals to the enhanced signals. Performance evaluation verifies that the proposed video processing method satisfies the overall video quality, while improving the perceptual quality by 12%~44%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.1
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• pp.33-37
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• 2011

In the fields of display, optics, and energy, it is important to improve micropattern-machining technology for achieving small patterns, large surface areas, and low cost. Unlike flat molds, roll molds have the following advantages: they can be manufactured within a short time, larger surface areas can be obtained, and continuous molding can be achieved. In this study, we aim to investigate the causes for errors in the shapes for a micropattern-machining process, and we show that by compensating the dynamic balance of roll molds, the dimensional accuracy of machined parts can be improved. The experimental results show that dynamic-balance compensation for a roll mold reduced the mass unbalance and the vibrations of the roll mold, and as a result, the dimensional accuracy of machined micropatterns has been improved.

• Journal of the Korean Vacuum Society
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• v.18 no.6
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• pp.468-473
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• 2009

Selective area epitaxy of multiple-stacked InP/InGaAs structures were grown by chemical beam epitaxy. The width of top of the multiple-stacked InP/InGaAs layer which were selectively grown on the stripe lines parallel to the <011> direction was narrowed, while the width of top of the multiple-stacked InP/InGaAs layer on the stripe lines parallel to the <01-1> was widen. This difference according to the <011> and <01-1> direction was explained by the growth of InGaAs <311>A and B faces on the (100) InP surface on the stripe lines parallel to the <01-1> direction. Under growth rate of $1\;{\mu}m/h$, top of the multiple-stacked InP/InGaAs was flattened as the pressure of group V gas was decreased. This phenomenon was understood by the saturation of group V element on the surface.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.216-224
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• 2010

A RAM-based Neural Network(RNN) has the advantages of processing speed and hardware implementation. In spite of these advantages, it has a saturation problem, weakness of repeated learning and extract of a generalized pattern. To resolve these problems of RNN, the 3DNS model using cumulative multi discriminator was proposed. But that model does not solve the saturation problem yet. In this paper, we proposed a adaptive weight cumulative neural net(AWCNN) using the adaptive weight neuron (AWN) for solving the saturation problem. The proposed nets improved a recognition rate and the saturation problem of 3DNS. We experimented with the MNIST database of NIST without preprocessing. As a result of experimentations, the AWCNN was 1.5% higher than 3DNS in a recognition rate when all input patterns were used. The recognition rate using generalized patterns was similar to that using all input patterns.

• Journal of Wetlands Research
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• v.19 no.4
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• pp.423-432
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• 2017

This study used SSARR model to predict the flood hydrograph for the Miho stream in the Geum river basin. First, we performed the sensitivity analysis on the parameters of SSARR model to know the characteristics of the parameters and set the range. For the parameter calibration, optimization methods such as genetic algorithm, pattern search and SCE-UA were used. WSSR and SSR were applied as objective functions, and the results of optimization method and objective function were compared and analyzed. As a result of this study, flood prediction was most accurate when using pattern search as an optimization method and WSSR as an objective function. If the parameters are optimized based on the results of this study, it can be helpful for decision making such as flood prediction and flood warning.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.27-34
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• 2010

This paper proposes an efficient method for verifying palmprint which is captured at the natural interface without any physical restriction. The location and orientation of the region of interest (ROI) in palm images are variously appeared due to the translation and rotation of hand. Therefore, it is necessary to extract the ROI stably for palmprint recognition. This paper presents a method that can extract the ROI, which is based on the reference points that are located at the center of the crotch segments between index finger and middle finger and between ring finger and little finger. It also proposes a palmprint recognition method using the histogram of local binary patterns (LBP). Experiments for evaluating the performance of the proposed method were performed on 1,597 palmprint images acquired from 100 different persons. The experimental results showed that ROI was correctly extracted at the rate of 99.5% and the equal error rate (EER) and the decidability index d' indicating the performance of palmprint verification were 0.136 and 3.539, respectively. These results demonstrate that the proposed method is robust to the variations of the translation and rotation of hand.

• Journal of the Korean Geographical Society
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• v.45 no.3
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• pp.319-341
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• 2010

The purposes of this study are to classify heavy snowfall types in the Republic of Korea based on fresh snowfall data and atmospheric circulation data during the last 36(1973/74-2008/09) snow seasons and to identify typical surface synoptic climate patterns that characterize each heavy snowfall type. Four synoptic climate categories and seventeen regional heavy snowfall types are classified based on sea level pressure/surface wind vector patterns in East Asia and frequent spatial clustering patterns of heavy snowfall in the Republic of Korea, respectively. Composite analyses of multiple surface synoptic weather charts demonstrate that the locations and intensity of pressure/wind vector mean and anomaly cores in East Asia differentiate each regional heavy snowfall type in Korea. These differences in synoptic climatic fields are primarily associated with the surge of the Siberian high pressure system and the appearance of low pressure systems over the Korean Peninsula. In terms of hemispheric atmospheric circulation, synoptic climatic patterns in the negative mode of winter Arctic Oscillation (AO) are also associated with frequent heavy snowfall in the Republic of Korea at seasonal scales. These results from long-term synoptic climatic data could contribute to improvement of short-range or seasonal prediction of regional heavy snowfall.