• 제목/요약/키워드: target labeling

검색결과 94건 처리시간 0.032초

A Review of the Opinion Target Extraction using Sequence Labeling Algorithms based on Features Combinations

  • Aziz, Noor Azeera Abdul;MohdAizainiMaarof, MohdAizainiMaarof;Zainal, Anazida;HazimAlkawaz, Mohammed
    • 인터넷정보학회논문지
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    • 제17권5호
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    • pp.111-119
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    • 2016
  • In recent years, the opinion analysis is one of the key research fronts of any domain. Opinion target extraction is an essential process of opinion analysis. Target is usually referred to noun or noun phrase in an entity which is deliberated by the opinion holder. Extraction of opinion target facilitates the opinion analysis more precisely and in addition helps to identify the opinion polarity i.e. users can perceive opinion in detail of a target including all its features. One of the most commonly employed algorithms is a sequence labeling algorithm also called Conditional Random Fields. In present article, recent opinion target extraction approaches are reviewed based on sequence labeling algorithm and it features combinations by analyzing and comparing these approaches. The good selection of features combinations will in some way give a good or better accuracy result. Features combinations are an essential process that can be used to identify and remove unneeded, irrelevant and redundant attributes from data that do not contribute to the accuracy of a predictive model or may in fact decrease the accuracy of the model. Hence, in general this review eventually leads to the contribution for the opinion analysis approach and assist researcher for the opinion target extraction in particular.

Labeling 방법을 이용한 Bin-Picking용 시각 기능 연구 (A study on vision algorithm for bin-picking using labeling method)

  • 최재완;박경택;정광조
    • 한국정밀공학회지
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    • 제10권4호
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    • pp.248-254
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    • 1993
  • This paper proposes the labeling method for solving bin-picking problem in robot vision. It has the processing steps such as image thresholding, region labeling, and moment computation. To determine a target object from object, the modified labeling method is used to. The moment concept applied to determine the position and orientation of target object. Finally, some experiment result are illustrated and compared with the results of conventional shrinking algorithm and collision fronts algorithm. The proposed labeling method has reduced processing time.

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A Study on Gene Detection using Non-labeling DNA

  • Choi Yong-Sung;Lee Kyung-Sup;Kwon Young-Soo
    • 한국전기전자재료학회논문지
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    • 제19권10호
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    • pp.960-965
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    • 2006
  • This research aims to develop the multiple channel electrochemical DNA chip using microfabrication technology. At first, we fabricated a high integration type DNA chip array by lithography technology. Several probe DNAs consisting of thiol group at their 5-end were immobilized on the gold electrodes. Then target DNAs were hybridized and reacted. Cyclic voltammetry showed a difference between target DNA and control DNA in the anodic peak current values. Therefore, it is able to detect a plural genes electrochemically after immobilization of a plural probe DNA and hybridization of non-labeling target DNA on the electrodes simultaneously. It suggested that this DNA chip could recognize the sequence specific genes.

Evaluation of Amplified-based Target Preparation Strategies for Toxicogenomics Study : cDNA versus cRNA

  • Nam, Suk-Woo;Lee, Jung-Young
    • Molecular & Cellular Toxicology
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    • 제1권2호
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    • pp.92-98
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    • 2005
  • DNA microarray analysis of gene expression in toxicogenomics typically requires relatively large amounts of total RNA. This limits the use of DNA microarray when the sample available is small. To confront this limitation, different methods of linear RNA amplification that generate antisense RNA (aRNA) have been optimized for microarray use. The target preparation strategy using amplified RNA in DNA microarray protocol can be divided into direct-incorporation labeling which resulted in cDNA targets (Cy-dye labeled cDNA from aRNA) and indirect-labeling which resulted in cRNA targets (i.e. Cy-dye labeled aRNA), respectively. However, despite the common use of amplified targets (cDNA or cRNA) from aRNAs, no systemic assessment for the use of amplified targets and bias in terms of hybridization performance has been reported. In this investigation, we have compared the hybridization performance of cRNA targets with cDNA targets from aRNA on a 10 K cDNA microarrays. Under optimized hybridization conditions, we found that 43% of outliers from cDNA technique and 86% from the outlier genes were reproducibly detected by both targets hybridization onto cDNA microarray. This suggests that the cRNA labeling method may have a reduced capacity for detecting the differential gene expression when compared to the cDNA target preparation. However, further validation of this discordant result should be pursued to determine which techniques possesses better accuracy in identifying truly differential genes.

ARPA 레이더 개발을 위한 물표 획득 및 추적 기술 연구 (A Study on Target Acquisition and Tracking to Develop ARPA Radar)

  • 이희용;신일식;이광일
    • 한국항해항만학회지
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    • 제39권4호
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    • pp.307-312
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    • 2015
  • ARPA(Automatic Radar Plotting Aid)는 자동레이더 플로팅 장치로써, 레이더 물표의 상대침로와 상대방위로 구성된 운동벡터에 본선의 침로와 방위로 구성되는 운동벡터를 가감 연산(벡터연산)하여, 물표의 진침로와 진방위 및 최근접점과 근접시간을 계산하는 장치를 말한다. 본 연구의 목적은 ARPA 레이더를 구현하기 위한 물표의 획득 및 추적 기술을 개발하는 것으로, 이에 관한 여러 선행 연구를 검토하여 적용 가능한 알고리듬 및 기법을 조합하여 기초적인 ARPA 기능을 개발하였다. 주요 연구내용으로, 레이더 영상에서 물표를 획득하기 위하여, 회색조 변환, 가운시안 평활 필터 적용, 이진화 및 라벨링(Labeling)과 같은 순차적 영상 처리 방법을 고안하였고, 이전 영상에서의 물표가 다음 영상에서의 어느 물표인지를 결정하는데 근접이웃탐색알고리듬을 사용하였으며, 물표의 진침로와 진방위를 계산하는 거동해석에 칼만필터를 사용하였다. 또한 이러한 기법을 전산 구현하여 실선실험을 수행하였고, 이를 통해 개발된 ARPA의 기능이 실용상 사용가능함을 검증하였다.

비수식화 바이오칩 및 유전자 검출 (Genome Detection Using an DNA Chip Array and Non-labeling DNA)

  • 최용성;이경섭
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2006년도 하계학술대회 논문집 Vol.7
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    • pp.402-403
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    • 2006
  • This research aims to develop the multiple channel electrochemical DNA chip using microfabrication technology. At first, we fabricated a high integration type DNA chip array by lithography technology. Several probe DNAs consisting of thiol group at their 5-end were immobilized on the gold electrodes. Then target DNAs were hybridized and reacted. Cyclic voltammetry showed a difference between target DNA and control DNA in the anodic peak current values. Therefore, it is able to detect a plural genes electrochemically after immobilization of a plural probe DNA and hybridization of non-labeling target DNA on the electrodes simultaneously. It suggested that this DNA chip could recognize the sequence specific genes.

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Site-Specific Labeling of Proteins Using Unnatural Amino Acids

  • Lee, Kyung Jin;Kang, Deokhee;Park, Hee-Sung
    • Molecules and Cells
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    • 제42권5호
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    • pp.386-396
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    • 2019
  • Labeling of a protein with a specific dye or tag at defined positions is a critical step in tracing the subtle behavior of the protein and assessing its cellular function. Over the last decade, many strategies have been developed to achieve selective labeling of proteins in living cells. In particular, the site-specific unnatural amino acid (UAA) incorporation technique has gained increasing attention since it enables attachment of various organic probes to a specific position of a protein in a more precise way. In this review, we describe how the UAA incorporation technique has expanded our ability to achieve site-specific labeling and visualization of target proteins for functional analyses in live cells.

음식점 원산지 표시제 시행에 따른 소비자의 인식 및 요구도 조사 - 서울시 거주하는 성인 대상 - (Consumer Awareness and Demand for Country-of-Origin Labeling at Restaurants - For Adults Who Live in Seoul -)

  • 안희진;박상현;주나미
    • 대한영양사협회학술지
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    • 제16권3호
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    • pp.255-269
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    • 2010
  • The purpose of this study was to investigate consumer awareness and demand related to country-of-origin labeling at restaurants, and to provide basic data to reexamine the need for current policies and to determine problems. The study found that 70% of the respondents thought that the implemented representation policy had improved food quality, and 81.3% of the respondents checked country-of-origin labeling at restaurants. In addition, 74.7% of the respondents answered that "reward for accusation" was appropriate policy. Regarding the degree of recognition of the meat importers, the respondents were well aware of the importing countries, but did not recognize the importing country of chicken. In terms of preference for meat importers, Australian beef was rated highest, but beef from the U.S. was ranked seventh. However, in preferences for pork and chicken, U.S. products were rated highest. According to the survey, in a question regarding the perception toward country-of-origin labeling, the respondents recognized that rice, beef, pork, and chicken were the targeted items. In addition, the respondents suggested that other food ingredients at restaurants should be designated as target items for country-of-origin labeling.

집적형 DNA칩 미소 전극 어레이 및 비수식화 표적 DNA를 이용한 유전자 검출 (Genome Detection Using an Integrated type DNA Chip Microelectrode-array and Non-labeling Target DNA)

  • 최용성;이혜연;전중유행;전중수화;권영수;천합지이
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 추계학술대회 논문집 전기물성,응용부문
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    • pp.274-276
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    • 2001
  • This research aims to develop the multiple channel electrochemical DNA chip using microfabrication technology. At first, we fabricated a high integration type DNA chip array by lithography technology. Several probe DNAs consisting of thiol group at their 5-end were immobilized on the sold electrodes. Then target DNAs were hybridized and reacted. Cyclic voltammetry showed a difference between target DNA and control DNA in the anodic peak current values. Therefore, it is able to detect a plural genes electrochemically after immobilization of a plural probe DNA and hybridization of non-labeling target DNA on the electrodes simultaneously. It suggested that this DNA chip could recognize the sequence specific genes.

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Domain-Adaptation Technique for Semantic Role Labeling with Structural Learning

  • Lim, Soojong;Lee, Changki;Ryu, Pum-Mo;Kim, Hyunki;Park, Sang Kyu;Ra, Dongyul
    • ETRI Journal
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    • 제36권3호
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    • pp.429-438
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    • 2014
  • Semantic role labeling (SRL) is a task in natural-language processing with the aim of detecting predicates in the text, choosing their correct senses, identifying their associated arguments, and predicting the semantic roles of the arguments. Developing a high-performance SRL system for a domain requires manually annotated training data of large size in the same domain. However, such SRL training data of sufficient size is available only for a few domains. Constructing SRL training data for a new domain is very expensive. Therefore, domain adaptation in SRL can be regarded as an important problem. In this paper, we show that domain adaptation for SRL systems can achieve state-of-the-art performance when based on structural learning and exploiting a prior model approach. We provide experimental results with three different target domains showing that our method is effective even if training data of small size is available for the target domains. According to experimentations, our proposed method outperforms those of other research works by about 2% to 5% in F-score.