• Korean journal of communication and information
• /
• v.57
• /
• pp.181-201
• /
• 2012

Classic cultivation theory and research has been noted for its failure to capture subtle variation in effects by genre and to consider tangible and practical dependent variables. Redressing these limitations, this study aimed at extending cultivation theory frame to incorporating fatalistic attitudes and reality television viewing, especially with the mediator of perceived realism. We first replicated the original cultivation effect by showing the significant effect of overall TV viewing. Even controlling for overall TV viewing, reality-based program use showed positive association with fatalistic beliefs; furthermore, the effect remained significant, additionally controlling for news(fact) use and drama(fiction) use. In a nutshell, the cultivation effect of reality-based TV program on fatalistic beliefs turns out quite stable even after controlling other competing genres.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.3
• /
• pp.99-106
• /
• 2008

Recently, digital music retrieval is using in many fields (Web portal. audio service site etc). In existing fields, Meta data of music are used for digital music retrieval. If Meta data are not right or do not exist, it is hard to get high accurate retrieval result. Contents based information retrieval that use music itself are researched for solving upper problem. In this paper, we propose Same music recognition method using similarity measurement. Feature data of digital music are extracted from waveform of music using Simplified MFCC (Mel Frequency Cepstral Coefficient). Similarity between digital music files are measured using DTW (Dynamic time Warping) that are used in Vision and Speech recognition fields. We success all of 500 times experiment in randomly collected 1000 songs from same genre for preying of proposed same music recognition method. 500 digital music were made by mixing different compressing codec and bit-rate from 60 digital audios. We ploved that similarity measurement using DTW can recognize same music.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1994.06c
• /
• pp.166-171
• /
• 1994

기존의 음성인식기들은 일반적으로 간단하면서도 성능이 우수한 계층별 학습에 의해서 설계된다. 계층별 학습은 통계적 패턴인식에서의 ML 추정기법처럼 모델간의 독립성이 보장되고 무한한 양의 학습데이타가 주어진다는 가정에 기초하고 있다. 그러나, 대상어휘집합에 음운학적으로 유사한 어휘가 많이 포함되어 있는 인식문제에 있어서는 모델간의 독립성이 보장되지 못하고, 실제 주어지는 grktmqepdlk의 양도 제한되므로 기존의 합습알고리즘에는 한계가 있다. 따라서 본 논문에서는 그러한 가정상의 문제점으로 생기는 인식기의 성능저하를 개선할 수 있는 변별력 있는 학습알고리즘들을 검토하고 그의 일반적인 접근방법들에 대해서 논의한다.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1994.06c
• /
• pp.241-244
• /
• 1994

이 논문은 대어휘, 화자독립 음성인식 시스템인 KT-STOCK과 이 시스템에 대한 전화망을 통한 실험적 실용시험에 대해 기술하였다. KT-STOCK은 현재 주식시장에 상장된 712개 회사의 현재주가를 음성을 이용하여 검색할 수 있는 시스템이다. 이 시스템은 hidden markov model 기술에 기반을 둔 고립단어 인식 시스템이며 유사음소를 기본 인식단위로 사용한다. KT-STOCK은 1994년 6월 24일부터 실험적 실용시험 중에 있다. 중간 결과에 따르면 모의 실험 결과는 실제 환경에서의 시험과 차이가 있는 거승로 나타났다. 실제 환경에서 이 시스템의 인식률은 현재 61.9%이다.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1995.06a
• /
• pp.88-91
• /
• 1995

개층형 신경망은 교사신호들의 학습으로 원하는 입출력간의 매핑을 할 수 있으므로 패턴분류를 위해 사용되어왔다. 본 논문은 계층형 신경망의 일종인 RBFN 중 GPFN 과 PNN으로 한국어 음소인식을 수행하였다. RBFN 의 구조는 계층형 신경망과 유사하나 차이점으로는 은닉층에서 시그모이드 함수, 참조벡터 및 학습알고리듬의 선택이 다르다. 특히 PNN 의 시그모이드 함수는 지수를 포함한 함수들로 대체되며 학습없이 패턴을 분류하므로 계산시간이 빠르게 수행된다. 본 실험에서는 한국어 단음절에서 모음과 자음을 추출하여 음소인식을 수행하였다. 실험 결과 학습과 평가데이타에 의한 인식률은 계층형 신경망과 비교하여 향상 되었으며, Hybrid 구성에 의한 실험에서도 항상된 인식률을 얻을 수 있었다.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2000.08a
• /
• pp.233-236
• /
• 2000

최근 수많은 인쇄된 문서들이 HTML과 같은 디지털 문서로 바뀌고 있으며 이를 자동으로 변환해 주는 문자인식 기술에 대한 관심이 증가하고 있다. 본 논문에서는 그림과 글자가 공존하는 문서에서 자동으로 문자영역을 추출해서 문자를 인식하는 방법을 제안한다. 우선 입력문서는 유사한 칼라로 이루어진 영역들로 나누어진 뒤 휴리스틱 룰에 의해 문자후보 영역과 비 문자 영역으로 나누어진다. 그 다음 이들 문자후보영역들은 문자인식기를 이용하여 문자 혹은 문자의 일부분으로 인식된다. 제안된 방법으로 여러 문서들에 대하여 실험한 결과를 보이며 그 성능을 평가한다.

• Journal of The Korean Association For Science Education
• /
• v.40 no.4
• /
• pp.359-374
• /
• 2020

This study is a complex type consisting of survey study and self-study. The former investigated elementary teachers' epistemological beliefs on convergence knowledge and teaching. As a representative of the result of survey study I, as a teacher as well as a researcher, was the participant of the self-study, which investigated my epistemological belief on convergence knowledge and teaching and my execution of convergent science teaching based on family resemblance of mathematics, science, and physical education. A set of open-ended written questionnaires was administered to 28 elementary teachers. Participating teachers considered convergent teaching as discipline-using or multi-disciplinary teaching. They also have epistemological beliefs in which they conceived convergence knowledge as aggregation of diverse disciplinary knowledge and students could get it through their own problem solving processes. As a teacher and researcher I have similar epistemological belief as the other teachers. During the self-study, I tried to apply convergence knowledge system based on the family resemblance analysis among math, science, and PE to my teaching. Inter-disciplinary approach to convergence teaching was not easy for me to conduct. Mathematical units, ratio and rate were linked to science concept of velocity so that it was effective to converge two disciplines. Moreover PE offered specific context where the concepts of math and science were connected convergently so that PE facilitated inter-disciplinary convergent teaching. The gaps between my epistemological belief and inter-disciplinary convergence knowledge based on family resemblance and the cases of how to bridge the gap by my experience were discussed.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.7 no.6
• /
• pp.1318-1324
• /
• 2003

There are two problems in the conventional ART1 algorithm. One is in similarity testing method of the conventional ART1 between input patterns and stored patterns. The other is that vigilance threshold of conventional ART1 influences the number of clusters and the rate of recognition. In this paper, new similarity testing method and dynamical vigilance threshold method are proposed to solve these problems. The former is similarity test method using the rate of norm of exclusive-NOR between input patterns and stored patterns and the rate of nodes have equivalence value, and the latter method dynamically controls vigilance threshold to similarity using fuzzy operations and the sum operation of Yager. To check the performance of new methods, we used 26 alphabet characters and nosed characters. In experiment results, the proposed methods are better than the conventional methods in ART1, because the proposed methods are less sensitive than the conventional methods for initial vigilance and the recognition rate of the proposed methods is higher than that of the conventional methods.

• Cartoon and Animation Studies
• /
• s.40
• /
• pp.477-496
• /
• 2015

Emotional awareness is the image of a person is represented by different tendencies. Currently, the emotion computing to objectively evaluate the emotion recognition research is being actively studied. However, existing emotional computing research has many problems to run. First, the non-objective in emotion recognition if it is inaccurate. Second, the correlation between the emotion recognition is unclear points. So to test the regularity of image sensitivity to the need of the present study is to control emotions in the computing system. In addition, the screen number of the emotion recognized for the purpose of this study, applying the method of objective image emotional computing system and compared with a similar degree of emotion of the person. The key features of the image emotional computing system calculates the emotion recognized as numbered digital form. And to study the background of emotion computing is a key advantage of the effect of the James A. Russell for digitization of emotion (Core Affect). Pleasure emotions about the core axis (X axis) of pleasure and displeasure, tension (Y-axis) axis of tension and relaxation of emotion, emotion is applied to the computing research. Emotional axis with associated representative sensibility very happy, excited, elated, happy, contentment, calm, relaxing, quiet, tired, helpless, depressed, sad, angry, stress, anxiety, pieces 16 of tense emotional separated by a sensibility ComputingIt applies. Course of the present study is to use the color of the color key elements of the image computing formula sensitivity, brightness, and saturation applied to the sensitivity property elements. Property and calculating the rate sensitivity factors are applied to the importance weight, measured by free-level sensitivity score (X-axis) and the tension (Y-axis). Emotion won again expanded on the basis of emotion crossed point, and included a representative selection in Sensibility size of the top five ranking representative of the main emotion. In addition, measuring the emotional image of a person with 16 representative emotional score, and separated by a representative of the top five senses. Compare the main representative of the main representatives of Emotion and Sensibility people aware of the sensitivity of the results to verify the similarity degree computing emotion emotional emotions depending on the number of representative matches. The emotional similarity computing results represent the average concordance rate of major sensitivity was 51%, representing 2.5 sensibilities were consistent with the person's emotion recognition. Similar measures were the degree of emotion computing calculation and emotion recognition in this study who were given the objective criteria of the sensitivity calculation. Future research will need to be maintained weight room and the study of the emotional equation of a higher concordance rate improved.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2010.04a
• /
• pp.433-436
• /
• 2010

최근 한국어 문서에는 한국어뿐만 아니라 외래어 표기 등이 혼합되어 사용되고 있다. 외래어 표기는 한 단어에 대해 한 개만 존재하는 것이 아니라 여러 개의 다른 표기로 사용되고 있다. 이러한 표기상 불일치는 하나의 단어가 다른 개념으로 인식되어 정보검색 시스템의 성능 저하의 원인이 된다. 따라서 정보검색 시스템의 성능 향상을 위해 여러 외래어 표기를 같은 개념으로 인식하는 시스템이 필요하다. 본 논문에서는 한국어 자모 혼동행렬을 기반으로 한 유사 외래어 표기 검출 기법을 제안한다. 제안한 기법에 따라 유사 외래어 표기를 검출해줌으로써 정보검색 시스템의 성능을 향상할 수 있다.