• 제목/요약/키워드: Recognition and Understanding

검색결과 938건 처리시간 0.03초

Transfer RNA Acceptor Stem Determinants for Specific Aminoacylation by Class II Aminoacyl-tRNA Synthetases

  • Musier, Karin
    • BMB Reports
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    • 제31권6호
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    • pp.525-535
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    • 1998
  • A critical step in the faithful translation of genetic information is specific tRNA recognition by aminoacyl-tRNA synthetases. These enzymes catalyze the covalent attachment of particular amino acids to the terminal adenosine of cognate tRNA substrates. In general, there is one synthetase for each of the twenty amino acids and each enzyme must discriminate against all of the cellular tRNAs that are specific for the nineteen noncognate amino acids. Primary sequence information combined with structural data have resulted in the division of the twenty synthetases into two classes. In recent years, several high-resolution co-crystal structures along with biochemical data have led to an increased understanding of tRNA recognition by synthetases of both classes. The anticodon sequence and the amino acid acceptor stem are the most common locations for critical recognition elements. This review will focus on acceptor stem discrimination by class II synthetases. In particular, the results of in vitro aminoacylation assays and site-directed and atomic group mutagenesis studies will be discussed. These studies have revealed that even subtle atomic determinants can provide signals for specific tRNA aminoacylation.

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분산 메모리 다중프로세서 환경에서의 병렬 음성인식 모델 (A Parallel Speech Recognition Model on Distributed Memory Multiprocessors)

  • 정상화;김형순;박민욱;황병한
    • 한국음향학회지
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    • 제18권5호
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    • pp.44-51
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    • 1999
  • 본 논문에서는 음성과 자연언어의 통합처리를 위한 효과적인 병렬계산모델을 제안한다. 음소모델은 연속 Hidden Markov Model(HMM)에 기반을 둔 문맥종속형 음소를 사용하며, 언어모델은 지식베이스를 기반으로 한다. 또한 지식베이스를 구성하기 위해 계층구조의 semantic network과 병렬 marker-passing을 추론 메카니즘으로 쓰는 memory-based parsing 기술을 사용한다. 본 연구의 병렬 음성인식 알고리즘은 분산메모리 MIMD(Multiple Instruction Multiple Data) 구조의 다중 Transputer 시스템을 이용하여 구현되었다. 실험결과, 본 연구의 지식베이스 기반 음성인식 시스템의 인식률이 word network 기반 음성인식 시스템보다 높게 나타났으며 code-phoneme 통계정보를 활용하여 인식성능의 향상도 얻을 수 있었다. 또한, 성능향상도(speedup) 관련 실험들을 통하여 병렬 음성인식 시스템의 실시간 구현 가능성을 확인하였다.

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인간의 움직임 추출을 이용한 감정적인 행동 인식 시스템 개발 (Emotional Human Body Recognition by Using Extraction of Human Body from Image)

  • 송민국;주영훈;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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    • pp.214-216
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    • 2006
  • Expressive face and human body gestures are among the main non-verbal communication channels in human-human interaction. Understanding human emotions through body gesture is one of the necessary skills both for humans and also for the computers to interact with their human counterparts. Gesture analysis is consisted of several processes such as detecting of hand, extracting feature, and recognizing emotions. Skin color information for tracking hand gesture is obtained from face detection region. We have revealed relationships between paricular body movements and specific emotions by using HMM(Hidden Markov Model) classifier. Performance evaluation of emotional human body recognition has experimented.

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On the Use Of Speech Recognition Technology for Foreign Language Pronunciation Teaching

  • Hirose, Keikichi;Ishi, Caries-T.;Kawai, Goh
    • 대한음성학회지:말소리
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    • 제42호
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    • pp.37-46
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    • 2001
  • Recently speech technologies have shown notable advancements and they now play major roles in computer-aided language learning systems. In the current paper, use of speech recognition technologies is viewed with our system for teaching English pronunciation to Japanese speakers.

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Construction Site Scene Understanding: A 2D Image Segmentation and Classification

  • Kim, Hongjo;Park, Sungjae;Ha, Sooji;Kim, Hyoungkwan
    • 국제학술발표논문집
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    • The 6th International Conference on Construction Engineering and Project Management
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    • pp.333-335
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    • 2015
  • A computer vision-based scene recognition algorithm is proposed for monitoring construction sites. The system analyzes images acquired from a surveillance camera to separate regions and classify them as building, ground, and hole. Mean shift image segmentation algorithm is tested for separating meaningful regions of construction site images. The system would benefit current monitoring practices in that information extracted from images could embrace an environmental context.

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A Comparative Study of Recognition Rate of Color QR Code Printed on Tyvek and Cotton Material

  • Park, Suhrin
    • 패션비즈니스
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    • 제21권3호
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    • pp.14-28
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    • 2017
  • This purpose of this study to analyze effect material properties have on change in QR code recognition rate according to change of materials by comparing recognition rate of color QR code. QR code applied to textile materials has the advantage of being washable and being applicable to lost child prevention goods or clothes or a person with dementia through record of information relating to the material or input of additional information, differently from QR code printed on the conventional paper. An effective method of entering QR code in textile materials is Digital Textile Printing(DTP), that facilitates printing by rapidly applying diverse information, and small quantity production. It is possible to tailor various QR codes according to use. Regarding samples to use, cotton material used in clothing products and Tyvek material recently applied to clothing and related products were selected. Reactive dyes were used for cotton, pigment was used for Tyvek, and QR code was printed with an inkjet printer by direct printing method. Printing methods and surface textures are different between cotton and Tyvek. It was revealed that consequent print results and results of recognition rate were different. Regarding color to be printed, 2015 S/S - 2017 S/S color presented by Pantone was used. Color combination affected recognition rate of color QR code. Understanding color combination, material properties and print characteristics may be helpful in increasing recognition rate of color QR code, and may contribute to usability of color QR code applied to textile materials in the future.

샤머니즘에 대한 간호학적 탐색 (A Study on Shamanism from a standpoint of Nursing)

  • 심형화
    • 대한간호학회지
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    • 제30권2호
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    • pp.498-513
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    • 2000
  • The purpose of this study is to construct the nursing-policy and nursing-theory of Korean style by understanding the type of recognition and attitude immanent in Korean people through of Korean people to the Shamanism(巫敎). And this paper is using Q methodology by operant definition. Because individual recognition and attitude to Shammanism is very subjective and individualistic and many-sided. Q statements in this paper are ultimately 38 statements divided into 5 regions, which are abstracted from 285 Q samples. 38 persons in all are objects of P-population. The results of analyses on the characters of each type are as follows. The men who belong to type I is positive to the Shamanism in recognition and attitude at the same time. The men who belong to type II are negative the analysis of the recognition and attitude to Shamanism in recognition, but positive to Shamanism in practical attitude. The men who belong to type III are evidently negative to Shamanism in recognition and attitude at the same time. The men who belong to type IV are positive to Shamanism, but negative or reservative to it in attitude. In conclusion, we could affirm that shamanic care-act which modern medicine discard as only superstition is very deeply rooted in the Korean people'need. In short, Korean people is already and always related to Shamnism, whether positively or negatively. I dare to think this paper might contribute the other disciplines of sciences as basic data.

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Object Recognition of Robot Using 3D RFID System

  • Roh, Se-Gon;Park, Jin-Ho;Lee, Young-Hoon;Choi, Hyouk-Ryeol
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.62-67
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    • 2005
  • Object recognition in the field of robotics generally has depended on a computer vision system. Recently, RFID(Radio Frequency IDentification) technology has been suggested to support recognition and has been rapidly and widely applied. This paper introduces the more advanced RFID-based recognition. A novel tag named 3D tag, which facilitates the understanding of the object, was designed. The previous RFID-based system only detects the existence of the object, and therefore, the system should find the object and had to carry out a complex process such as pattern match to identify the object. 3D tag, however, not only detects the existence of the object as well as other tags, but also estimates the orientation and position of the object. These characteristics of 3D tag allows the robot to considerably reduce its dependence on other sensors required for object recognition the object. In this paper, we analyze the 3D tag's detection characteristic and the position and orientation estimation algorithm of the 3D tag-based RFID system.

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도면을 이용한 3D 모델링 CAD 시스템 (CAD system for 3D modeling using engineering drawings)

  • 이창조;김창헌;황종선
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 1995년도 춘계공동학술대회논문집; 전남대학교; 28-29 Apr. 1995
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    • pp.891-895
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    • 1995
  • This paper describes a solid modeling system based on a systematic description of techniques for analyzing and understanding on engineering drawings. Main stress is placed on clarifying the difference between the drawing understanding and the drawing recognition. The former, in which we feel major interest, is intrinsically a difficult problem because it inherent contains combinatorial search to require more than polynomial time. Actually, understanding drawings is regarded as a process to recover the information lost in projection 3-D objects to 2-D drawings. But, solid modeling by automatic understanding of the given drawings is one of the promising approach, which is described precisely in the text. Reviewing the studies performed so far, we summarize the future direction of the project and inevitable open problems left.

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Image Understanding for Visual Dialog

  • Cho, Yeongsu;Kim, Incheol
    • Journal of Information Processing Systems
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    • 제15권5호
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    • pp.1171-1178
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    • 2019
  • This study proposes a deep neural network model based on an encoder-decoder structure for visual dialogs. Ongoing linguistic understanding of the dialog history and context is important to generate correct answers to questions in visual dialogs followed by questions and answers regarding images. Nevertheless, in many cases, a visual understanding that can identify scenes or object attributes contained in images is beneficial. Hence, in the proposed model, by employing a separate person detector and an attribute recognizer in addition to visual features extracted from the entire input image at the encoding stage using a convolutional neural network, we emphasize attributes, such as gender, age, and dress concept of the people in the corresponding image and use them to generate answers. The results of the experiments conducted using VisDial v0.9, a large benchmark dataset, confirmed that the proposed model performed well.