• Food Science and Biotechnology
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• v.14 no.4
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• pp.554-557
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• 2005

As a device for taste sensation, an 8-channel taste evaluation system was prepared and applied for discriminant analysis of marketed liquor. The biomimetic polymer membranes for the system were prepared through a casting procedure by employing polyvinyl chloride, bis (2-ethylhexyl)sebacate as plasticizer and electroactive materials such as valinomycin in the ratio of 33:66:1, and were separately attached over the sensitive area of ion-selective electrodes to construct the corresponding taste sensor array. The sensor array in conjunction with a double junction reference electrode was connected to a high-input impedance amplifier and the amplified sensor signals were interfaced to a personal computer via an A/D converter. When the signal data from the sensor array for 3 groups of marketed liquor like Maesilju, Soju and beer were analyzed by principal component analysis after normalization, it was observed that the 1st, 2nd and 3rd principal component were responsible for most of the total data variance, and the analyzed liquor samples were discriminated well in 2 dimensional principal component planes composed of the 1st-2nd and the 1st-3rd principal component.

• Electrical & Electronic Materials
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• v.7 no.2
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• pp.107-116
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• 1994

In the manufacturing of VLSI circuits, variations of device characteristics due to the slight differences in process parameters drastically aggravate the performances of fabricated devices. Therefore, it is very important to establish optimal process conditions in order to minimize deviations of device characteristics. In this paper, we used one-dimensional process simulator, SUPREM-II, and two dimensional device simulator, MINIMOS 4.0 in order to extract optimal process parameter which can minimize changes of the device characteristics caused by process parameter variation in the case of short channel nMOSFET and pMOSFET device. From this simulation, we have derived the dependence relations between process parameters and device characteristics. Here, we have suggested a method to extract process parameters from design trend curve(DTC) obtained by these dependence relations. And we have discussed short channel effects and device limitations by scaling down MOSFET dimensions.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1486-1495
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• 2020

The analysis of digital microscopy images plays a vital role in computer-aided diagnosis (CAD) and prognosis. The main purpose of this paper is to develop a machine learning technique to predict the histological grades in prostate biopsy. To perform a multiclass classification, an AI-based deep learning algorithm, a multichannel convolutional neural network (MCCNN) was developed by connecting layers with artificial neurons inspired by the human brain system. The histological grades that were used for the analysis are benign, grade 3, grade 4, and grade 5. The proposed approach aims to classify multiple patterns of images extracted from the whole slide image (WSI) of a prostate biopsy based on the Gleason grading system. The Multichannel Convolution Neural Network (MCCNN) model takes three input channels (Red, Green, and Blue) to extract the computational features from each channel and concatenate them for multiclass classification. Stain normalization was carried out for each histological grade to standardize the intensity and contrast level in the image. The proposed model has been trained, validated, and tested with the histopathological images and has achieved an average accuracy of 96.4%, 94.6%, and 95.1%, respectively.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.141-145
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• 2015

The dynamic range of the loudness after digitalization of television broadcasting is enlarged, and the loudness difference between the broadcast channel and between the programs within the same channel is expanded. This was subjected to interfere with the television viewer's comfort. In order to improve these problems international standards for the loudness normalization was established in ITU, Europe, USA and Japan. This regulation was introduced to Korea also as technical regulation, and this will apply the broadcast service in June 2016. In this paper, ahead of the introduction of digital television technology based on loudness measurement for the major television channel and to present the results of the comparison of technical standard.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.757-770
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• 2022

Palmprint recognition has drawn increasingly attentions in the past decade due to its uniqueness and reliability. Traditional palmprint recognition methods usually use high-resolution images as the identification basis so that they can achieve relatively high precision. However, high-resolution images mean more computation cost in the recognition process, which usually cannot be guaranteed in mobile computing. Therefore, this paper proposes an improved low-resolution palmprint image recognition method based on residual networks. The main contributions include: 1) We introduce a channel attention mechanism to refactor the extracted feature maps, which can pay more attention to the informative feature maps and suppress the useless ones. 2) The ResStage group structure proposed by us divides the original residual block into three stages, and we stabilize the signal characteristics before each stage by means of BN normalization operation to enhance the feature channel. Comparison experiments are conducted on a public dataset provided by the Hong Kong Polytechnic University. Experimental results show that the proposed method achieve a rank-1 accuracy of 98.17% when tested on low-resolution images with the size of 12dpi, which outperforms all the compared methods obviously.

• Journal of Broadcast Engineering
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• v.21 no.5
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• pp.770-781
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• 2016

As a result of reducing color information and edge information, object distinction in haze image occurs with difficulty. One of the famous defogging algorithm is haze removal by using 'Dark Channel Prior(DCP)', which is used to predict for transmission rate using color information of an image and eliminates haze from the image. But, In case that haze rate is estimated under color information, there is a miscalculated issue which is posed by haze rate and transmission in area with high brightness such as a white object or a light source. In this paper, We deal with a miscalculated issue by correcting from around haze rate, after application of color normalization used by main white part of image haze. Moreover, We calculation improved transmission based on the result of improved haze rate estimation. And then haze image quality is developed through refining transmission.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.1
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• pp.36-39
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• 1980

Studies have been perfor mad on the normalization of V-I characteristics, the dependence of current runaway on the applied step voltage and the analysis of the current channet in the sintered 5Fe$_2$O$_3$-5Bi$_2$O$_3$. From the measurement of snitching Properties of the sintered 5Fe$_2$O$_3$-5Bi$_2$O$_3$, it is exe]twined that the electrical switching mechanism is that of thermal ionic breakolown.

• The Journal of the Acoustical Society of Korea
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• v.21 no.1E
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• pp.3-11
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• 2002

Broadcast news transcription is one of the hardest tasks in speech recognition because broadcast speech signals have much variability in speech quality, channel and background conditions. We developed a Korean broadcast news speech recognizer. We used a morpheme-based dictionary and a language model to reduce the out-of·vocabulary (OOV) rate. We concatenated the original morpheme pairs of short length or high frequency in order to reduce insertion and deletion errors due to short morphemes. We used a lexicon with multiple pronunciations to reflect inter-morpheme pronunciation variations without severe modification of the search tree. By using the merged morpheme as recognition units, we achieved the OOV rate of 1.7% comparable to European languages with 64k vocabulary. We implemented a hidden Markov model-based recognizer with vocal tract length normalization and online speaker adaptation by maximum likelihood linear regression. Experimental results showed that the recognizer yielded 21.8% morpheme error rate for anchor speech and 31.6% for mostly noisy reporter speech.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.453-456
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• 1997

In this paper, we present the developement of Biofeedback system. Biofeedback is a method for learned control of physiological response of the body. It can be used to control certain biological response that cause health problems. Over the past 2 decades, biofeedback has received much attention from medicine as a cure-all for a variety of disease. It has been heralded as a technique that can provide normalization of disturbed physiology without the need for drugs or surgery and their attendant negative side effects. Biofeedback system has been implemented by using PIC microprocessor. We have displayed 5-channel value on PC and managed patient information by using Delphi.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.205-208
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• 2001

According to the IMT-2000 specification of 3GPP(3rd Generation Partnership Project) and 3GPP2, Turbo codes is selected as a FEC(forward error correction) code for even higher reliable data communication. In 3GPP complied IMT-2000 system, channel coding under consideration is the selective use of convolutional coding and Turbo codes of 1/3 code rate with 4 constraint length. Suggesting a new path metric normalization method, we achieved a low complexity and high performance SOVA decoder for Turbo Codes, Further more, we analyze the decoding performance with respect to update depth and find out the optimal value of it by using computer simulation. Based on the simulation result, we designed a SOVA decoder using VHDL and implemented it into the Altera EPF10K100GC503FPGA.