• Human Ecology Research
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• 제53권5호
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• pp.489-502
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• 2015

This study identifies the relation between recognition relatively deprivation and consumption patterns. The data used were the seventh Korea Welfare Panel Study (KOWEPS). The final sample of 1,597 households was selected based on several sampling steps standard weights suggested by KOWEPS were applied. The final sample was subdivided into household recognizing relatively deprivation (51.7%) and non-household recognizing relatively deprivation (48.3%) per level of subjective income and objective income. We derived six consumption patterns from the cluster analysis as per consumption ratio: transportation dominant consumption pattern, essential consumption pattern, other dominant consumption pattern, care attention consumption pattern, private transfer consumption pattern, and education dominant consumption pattern. The results of this study are as follows. The analysis of the determinants of recognizing relatively deprivation in regards to question one found that the household was likely to be relatively deprived when: the head of a household was older, a household had a dual income, children and more total assets then those assessed 1 year ago compared to household living conditions, result of comparing the consumption patterns difference between household recognizing relatively deprivation and non-household recognizing relatively deprivation indicated that household recognizing relatively deprivation was more likely to belong to the transportation dominant consumption pattern, other dominant consumption pattern, and private transfer consumption pattern. The multinomial logistic analysis conducted to understand the determinants affecting the consumption patterns of household recognizing relatively deprivation indicated differences in demographic characteristics, household-related variables, financial variables and perception of economic conditions.

• 한국정보시스템학회지:정보시스템연구
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• 제14권3호
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• pp.82-88
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• 2005

Much information has been hierarchically organized to facilitate information browsing, retrieval, and dissemination. In practice, much information may be entered at any time, but only a small subset of the information may be classified into some categories in a hierarchy. Therefore, achieving document filtering (DF) in the course of document classification (DC) is an essential basis to develop an information center, which classifies suitable documents into suitable categories, reducing information overload while facilitating information sharing. In this paper, we present a technique ICenter, which conducts DF and DC by recognizing the context of discussion (COD) of each document and category. Experiments on real-world data show that, through COD recognition, the performance of ICenter is significantly better. The results are of theoretical and practical significance. ICenter may server as an essential basis to develop an information center for a user community, which shares and organizes a hierarchy of textual information.

• 한국수학교육학회지시리즈C:초등수학교육
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• 제19권4호
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• pp.291-311
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• 2016

연구자는 직각으로만 이루어진 계단 모양의 둘레를 구하는 과정에서 이미 알고 있는 직사각형의 둘레를 구하는 방식을 활용하지 못하고 어려움을 겪는 모습을 보았다. 이에, 평면도형의 둘레에서 학생들이 어떠한 어려움을 겪고 있는지 확인하고 어려움을 겪는 학생들을 도울 수 있는 방법을 찾고자 하였다. 이를 위해 평면도형의 둘레 문제에 관한 다수 학생의 기록지를 분석하고, 그들 중 일부를 대상으로 면담을 수행하였다. 그 결과 학생들은 둘레를 구하기 위해 주어진 정보의 인식과, 그것을 해결에 필요한 정보로 전환하는 두 측면 모두에 어려움을 겪고 있으며, 둘레가 길이의 속성을 갖는다는 선행지식도 적절히 구성되어 있지 않음을 알 수 있었다. 이러한 결과를 토대로 이 연구에서는, 평면도형의 둘레 문제해결을 돕기 위한 지도방안을 제안하였다.

• 정보관리학회지
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• 제32권3호
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• pp.1-20
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• 2015

대학에서 효과적인 연구와 학습이 이루어지기 위해서는 정보의 필요성을 인지하고, 찾아내고 평가하며, 효과적으로 사용할 수 있는 능력을 포함한 정보활용교육이 필수적이다. 본 연구는 국내 외 단체와 학자들에 의해 제시된 정보활용능력 기준 및 모형과 정보활용교육 사례를 기초로 대학생을 위한 정보활용교육 교안을 제시하고자 하였다. 정보활용교육은 1회성 교육이 갖는 한계를 극복하기 위해 정규교과목으로 운영되어야 하며, 대학도서관 정보와의 연계 및 효과적인 활용을 위해 그리고, 대학도서관 및 사서의 역할에 대한 전략적 측면의 고려를 위해 도서관 전문사서의 주도적 또는 협력적 역할이 필수적이다. 또한, 현 세대의 성향과 요구를 반영한 내용구성의 변화와 학생들의 주체적이고 자발적인 참여를 이끌어내기 위한 방법적 측면의 고려가 필요한 것으로 분석되었다.

• 제어로봇시스템학회논문지
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• 제10권9호
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• pp.763-770
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• 2004

The important issue of emotion recognition from speech is a feature extracting and pattern classification. Features should involve essential information for classifying the emotions. Feature selection is needed to decompose the components of speech and analyze the relation between features and emotions. Specially, a pitch of speech components includes much information for emotion. Accordingly, this paper searches the relation of emotion to features such as the sound loudness, pitch, etc. and classifies the emotions by using the statistic of the collecting data. This paper deals with the method of recognizing emotion from the sound. The most important emotional component of sound is a tone. Also, the inference ability of a brain takes part in the emotion recognition. This paper finds empirically the emotional components from the speech and experiment on the emotion recognition. This paper also proposes the recognition method using these emotional components and the transition probability.

• Advances in robotics research
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• 제2권1호
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• pp.59-68
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• 2018

Autonomous mobile service medical robots (AMSMRs) are one of the promising developments in contemporary medical robotics. In this study, we consider the essential technical and intellectual abilities needed by AMSMRs. Based on expert analysis of the behavior exhibited by AMSMRs in clinics under basic scenarios, these robots can be classified as intellectual dynamic systems acting according to a situation in a multi-object and multi-agent environment. An AMSMR should identify different objects that define the presented territory (rooms and paths), different objects between and inside rooms (doors, tables, and beds, among others), and other robots. They should also identify the means for interacting with these objects, people and their speech, different information for communication, and small objects for transportation. These are included in the minimum set required to form the internal world model in an AMSMR. Recognizing door handles and opening doors are some of the most difficult problems for contemporary AMSMRs. The ability to recognize the meaning of human speech and actions and to assist them effectively are other problems that need solutions. These unresolved issues indicate that AMSMRs will need to pass through some learning and training programs before starting real work in hospitals.

• 한국통신학회논문지
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• 제28권9C호
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• pp.860-867
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• 2003

본 논문에서는 방향 패턴 레이블링을 이용하여 지문 영상의 중심점을 검출하는 방법을 제안하였다. 중심점은 지문영상에서의 특이점들 중의 하나이며 대부분의 지문 인식 시스템에서 기준점으로 사용되고 있다. 중심점의 검출은 지문 인식 시스템에서 반드시 수행되어야할 중요한 단계로 전체 시스템의 성능에 큰 영향을 준다. 제안된 방법에서는 ridge의 분포로부터 얻어낸 방향 성분에 레이블링 방법과 중심점의 위치를 결정하는 알고리즘을 적용하여 중심점의 위치를 검출할 수 있었다. 모의 실험 결과 제안한 방법이 Poincare index와 Sine map 방법들에 비해 수행시간과 검출률 모두에서 좀더 나은 성능을 보임을 확인하였다. 특히 제안한 방법은 arch 형의 중심점 검출에 있어 Poincare index 방법의 낮은 검출률과 Sine map 방법의 긴 수행 시간이라는 단점들을 모두 극복하였다.

• 한국정보교육학회:학술대회논문집
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• 한국정보교육학회 2021년도 학술논문집
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• pp.315-320
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• 2021

미래사회 변화에 대비하기 위하여 SW·AI 교육은 필수적이다. 본 논문에서는 예비교사를 대상으로 비대면 SW·AI 교육을 실시한 후 SW 기초교육 효과성 측정도구를 사용하여 교육 전과 후의 SW 교육 효과성을 측정하였다. 분석 결과, 전체 평균과 '컴퓨팅 사고력', 'SW 문해력' 영역의 평균이 유의미하게 증가하였고, '컴퓨팅 사고력' 영역의 분해, 패턴인식, 추상화, 알고리즘 하위영역에서도 모두 교육 전과 후의 평균의 차이가 통계적으로 유의미하게 나타났다. 학생들은 SW·AI 교육을 통해 SW 교육의 필요성과 컴퓨팅 사고력의 중요성을 인식할 뿐만 아니라 정보를 분해하고 패턴을 인식하고 추출하며 문제해결과정을 표현하는 과정을 이해함을 알 수 있었다. 이는 비대면 SW·AI 교육도 SW가 중요함을 인식시키는 것을 넘어 컴퓨팅 사고력, SW 문해력을 향상시키는 효과를 나타내고 있음을 알 수 있다.

• 한국언어정보학회지:언어와정보
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• 제18권2호
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• pp.141-168
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• 2014

Recognizing spatial information associated with events expressed in natural language text is essential not only for the interpretation of such events and but also for the understanding of the relations among them. However, spatial information is rarely mentioned as compared to events and the association between event and spatial expressions is also highly implicit in a text. This would make it difficult to automate the extraction of spatial information associated with events from the text. In this paper, we give a linguistic analysis of how spatial expressions are associated with event expressions in a text. We first present issues in annotating narrative texts with reference relations between event and spatial expressions, and then discuss surface-level linguistic characteristics of such relations based on the annotated corpus to give a helpful insight into developing an automated recognition method.

• 전자공학회논문지B
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• 제30B권2호
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• pp.69-77
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• 1993

Automatic image recognition system is essential for a better man-to machine interaction. Because of the noise and deformation due to the sensor operation, it is not simple to build an image recognition system even for the fixed images. In this paper neural network which has been reported to be adequate for pattern recognition task is applied to the fixed and variational(rotation, size, position variation for the fixed image)recognition with a hope that the problems of conventional pattern recognition techniques are overcome. At fixed image recognition system. ART model is trained with face images obtained by camera. When recognizing an matching score. In the test when wigilance level 0.6 - 0.8 the system has achievel 100% correct face recognition rate. In the variational image recognition system, 65 invariant moment features sets are taken from thirteen persons. 39 data are taken to train multi-layer perceptron and other 26 data used for testing. The result shows 92.5% recognition rate.