• 한국컴퓨터정보학회논문지
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• 제20권12호
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• pp.21-28
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• 2015

In this paper, we propose a method of glasses detection in facial image. we develop a detection method of glasses with a weighted sum of the results that detected by facial element detection and glasses frame candidate region. Component of the face detection method detects the glasses, by defining the detection probability of the glasses according to the detection of a face component. Method using the candidate region of the glasses frame detects the glasses, by defining feature of the glasses frame in the candidate region. finally, The results of the combined weight of both methods are obtained. The proposed method in this paper is expected to increase security system's recognition on facial accessories by raising detection performance of glasses or sunglasses for using ATM.

• 동아시아식생활학회지
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• 제19권1호
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• pp.116-129
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• 2009

The study was conducted to evaluate consumer awareness of the risk elements associated with foods and their information search behavior regarding food safety. The data were collected from 504 adult consumers living in Seoul, Busan, Incheon, Daegu, Daejeon, and Gwangju through a self-administered questionnaire on August, 2006. Frequency analyses, t tests, one-way analysis of variance, and Duncan's multiple range comparison tests were conducted to analyze the responses using SPSS v. 14.0. The levels of recognition of consumers regarding each risk element were generally low. Many respondents answered that they obtained information regarding food safety from TV/radio/newspapers and family/relatives/friends/neighbors. The respondents also indicated that they had strong confidence in the information from family/relatives/friends/neighbors. Additionally, most respondents required information regarding heavy metal contamination, endoctrine disruptors, and avian influenza.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.381-384
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• 2002

In speech signal processing, it Is very important to detect the pitch exactly in speech recognition, synthesis and analysis. but, it is very difficult to pitch detection from speech signal because of formant and transition amplitude affect. therefore, in this paper, we proposed a pitch detection using the spectrum flattening techniques. Spectrum flattening is to eliminate the formant and transition amplitude affect. In time domain, positive center clipping is process in order to emphasize pitch period with a glottal component of removed vocal tract characteristic. And rough formant envelope is computed through peak-fitting spectrum of original speech signal in frequency domain. As a results, well get the flattened harmonics waveform with the algebra difference between spectrum of original speech signal and smoothed formant envelope. After all, we obtain residual signal which is removed vocal tract element The performance was compared with LPC and Cepstrum, ACF 0wing to this algorithm, we have obtained the pitch information improved the accuracy of pitch detection and gross error rate is reduced in voice speech region and in transition region of changing the phoneme.

• 복식문화연구
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• 제7권4호
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• pp.38-51
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• 1999

The purpose of this study finds that (1) history of the First birthday rite(첫돌 의례) and (2) changing process of the First birthday\`s dress and ornaments(첫돌 복식). The results of this study are as follows. The history of the first birthday rite has been continued vary long years in Korea, but it\`s origin is not clearness. The purpose and form of the first birthday rite are vary similarity in China and Korea. The rate of infant mortality was regarded that an absolute element of the first birthday rite. Making process of the first birthday\`s dress and ornaments was not definite, The adoption of that\`s form and elements act on affect local·homely·individual situation. First birthday\`s dress and ornaments was changed by changing process and convert of recognition about First birthday rite. It shows that the change of rites clothing contacted with changing process of rites.

• 전자공학회논문지A
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• 제31A권8호
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• pp.62-71
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• 1994

A novel semiconductor device is proposed to be used as a processing element for the implementation of pulse-mode neural networks which consists of alternating n' GaAs quantum wells and undoped AlGaAs barriers sandwitched between n' GaAs cathode and P' GaAs anode and in simple circuit in conjunction with a parallel capacitive and resistive load the trigger circuit generates neuron-like pulse train output mimicking the function of axon hillock of biological neuron. It showed the sigmoidal relationship between the frequency of the pulse-train and the applied input DC voltage. In conjunction with MQWIMD the various neural circuits are proposed especially a neural chip monolithically integrated with photodetectors in order to perfrom the pattern recognition.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1997년도 봄 학술발표회 논문집
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• pp.97-105
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• 1997

A methodology to identify a baseline modal model of a complicated 3-D structure using limited structural and modal information is experimentally examined. In the first part, a system's identification theory for the methodology to identify, baseline modal responses of the structure is outlined. Next, an algorithm is designed to build a generic finite element model of the baseline structure and to calibrate the model by using only a set of post-damage modal parameters. In the second part, the feasibility of the methodology is examined experimentally using a field-tested truss bridge far which only post-damaged modal responses were measured for a few vibration modes. For the complex 3-D bridge with many members, we analyzed to identify unknown stiffness parameters of the structure by using modal parameters of the initial two modes of vibration.

• 대한전기학회논문지
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• 제45권2호
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• pp.319-324
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• 1996

Using random pulse stream, a number can be transformed to the pulse stream with the probability value. So the digital value are computed by simple digital gates. Thus it will be possible to build a small and strong noise immunity processing element. We propose a faster convergence algorithm using a new methods for better performance of Random Number Generator(RNG) an the nonlinear transfer function(Sigmoid function)in this paper. And a feedback circuit were fitted for pulse stream in this paper. We proposed method is simulated with C program language and conformed by circuit implementation. Finally a system for hand written number recognition is constructed by FPGA and its performance verified.

• 한국독성학회:학술대회논문집
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• 한국독성학회 2003년도 추계학술대회
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• pp.136-136
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• 2003

Exposure of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) causes a variety of biological and toxicology effects, most of which are mediated by aryl hydrocarbon receptor (AhR). The ligand-bound AhR as a heterodimer with AhR nuclear translocator (ARNT) binds to its specific DNA recognition site, the dioxin-responsive element (DRE), and it results in increased transcription of CVP1A1 gene.(omitted)

• 한국화재소방학회:학술대회논문집
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• 한국화재소방학회 1997년도 International Symposium on Fire Science and Technology
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• pp.282-288
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• 1997

The purpose of this paper is to predict the situation of leak in closed space using an Artificial Neural Network (ANN). The existing system can't monitor the whole He situations with on/off signals. Especially the first stage of data determines the leak spot and intensity is disregarded in gas accidents. To complement these faults, a new prototype of monitoring system is proposed. Ihe system is composed of'sensing systenL data acquisition system computer, and ANN implemented in software and is capable of identifying the leak spot and intensity in closed space. The concentration of gas is measured at the 4 different places. The network has 3 layers that are composed of 4 input Processing Element (PE),24 hidden PEs, md 4 output PEs. The ANN has optimum condition through several experiments and as a consequence the recognition rate of93.75% is achieved finally

• Bulletin of the Korean Chemical Society
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• 제11권5호
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• pp.450-455
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• 1990

Fifty eight obsidian artifacts and four obsidian source samples have been analyzed by instrumental neutron activation analysis. Artifact samples have been classified into classes by unsupervised learning techniques such as eigenvector projection and nonlinear mapping. The source samples have thereafter been connected to the classes by the supervised learning techniques such as SLDA and SIMCA so as to characterize each class by possible source sites. Some difference attributable to different nonlinear mapping techniques and the elemental effects on the separation between classes have been discussed.