• 제목/요약/키워드: data labeling

검색결과 469건 처리시간 0.026초

Emotion Expressiveness and Knowledge in Preschool-Age Children: Age-Related Changes

  • Shin, Nana;Krzysik, Lisa;Vaughn, Brian E.
    • Child Studies in Asia-Pacific Contexts
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    • 제4권1호
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    • pp.1-12
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    • 2014
  • Emotion is a central feature of social interactions. In this study, we examined age-related changes in emotion expressiveness and emotion knowledge and how young children's emotion expressiveness and knowledge were related. A total of 300 children attending a daycare center contributed data for the study. Observation and interview data relevant to measures of emotion expressiveness and knowledge were collected and analyzed. Both emotion knowledge and expressed positive affect increased with age. Older preschool children expressed positive affect more frequently than did younger preschoolers. Older preschool children also labeled, recognized, and provided plausible causes mores accurately than did younger preschool children. In addition, we tested whether children's errors on the free labeling component conform to the structural model previously suggested by Bullock and Russell (1986) and found that preschool children were using systematic strategies for labeling emotion states. Relations between emotion expressiveness and emotion knowledge generally were not significant, suggesting that emotional competence is only gradually constructed by the child over the preschool years.

의류제품에 부착된 Care Label 에 관한 연구 (Care Labeling Compliance)

  • 박광희
    • 대한가정학회지
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    • 제33권2호
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    • pp.159-166
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    • 1995
  • The purpose of the present study is to investigate how closely care labels comply with the 1984 version of the Care Labeling Rule, as well as the change in degree of compliance prior to and after the 1988 IFI care label campaign. Label information was analyzed on the basis of country of origin. The information was also divided into two sets. The basis for dividing the data into two sets was the beginning of the IFI care label campaign in 1988 The data were obtained from 1147 checklists. The information for 1147 samples in six clothing categories were collected from department, specialty, and discount stores. Chi-square analyses were conducted to test hypotheses. While there was no significant difference in the number of incorrect labels on domestically produced garments compared to imported garments in set 1, there was a significant difference in set 2. Also, there was a significnat differnece in the number of incorrect labels between in set 1 and in set 2.

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의사 레이블링을 통한 레이블이 없는 데이터 보완 연구 (Research on supplementing unlabeled data through pseudo-labeling.)

  • 유민희;유헌창
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2023년도 추계학술발표대회
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    • pp.410-413
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    • 2023
  • 레이블링 작업은 데이터 분석 시 필요한 사전 작업중 하나이다. 모든 데이터들에 대해 레이블링 작업은 시간/인적 자원을 필요로 하기에, 해당 작업을 보완할 방법이 존재한다면 요구되는 리소스를 줄여 효율성을 크게 향상시킬 수 있다. 본 논문에서는 통신회사에서 적재된 데이터 셋에 대하여 레이블이 없는 데이터(Unlabeled-data)에 대해 의사 레이블링(Pseudo-labeling), SMOTE 를 통한 데이터 증강을 활용하여 기존에 활용되지 못한 데이터를 추가하여 모델에 학습시킨다. 실험을 통해 의사 레이블을 통한 모델 학습 방법이 기존 도메인 지식의 레이블 방법보다 효율적이고 성능이 우수함을 확인하였다.

호텔조리직원들의 음식점 원산지표시에 대한 지식과 수행도 관계와 교육시간 조절효과 (Moderating Effect of Education-Hours on the Relationship between Knowledge of Country-of-Origin Labeling and Performance in Hotel Culinary Staff)

  • 권기완;정유경
    • 한국조리학회지
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    • 제22권4호
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    • pp.37-50
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    • 2016
  • 본 연구는 호텔 조리직원들을 대상으로 음식점 원산지표시에 대해 어느 정도 지식을 가지고 있는지, 그 지식 정도가 조리업무 중 하나인 원산지 표시 업무 수행에 어느 정도 영향을 미치는지를 파악하고자 하였다. 또한, 원산지표시에 대한 교육시간에 따라 지식의 차이 정도를 알아보고자하며, 교육시간이 지식과 수행도 관계에 어떠한 조절효과가 있는지를 파악하는 데 목적이 있다. 본 연구는 서울소재 특급호텔 10곳에 재직 중인 조리직원들을 대상으로 2014년 11월 14일부터 11월 27일까지 14일 동안 총 250부의 자기기입식 설문지를 배포하여 응답이 불성실한 설문지 4부를 제외한 246부(98.4%)를 사용하였다. 수집된 자료를 바탕으로 연구에 필요한 모든 자료의 분석은 SPSS 18.0 통계 프로그램을 활용하여 빈도분석, 신뢰성을 검증, 탐색적 요인분석, 단순회귀분석, t-test, 조절회귀분석을 하였다. 연구결과, 호텔 조리직원들의 음식점 원산지표시에 대한 지식은 업무 수행도에 유의한 정(+)의 영향을 미치며, 교육시간은 1~2시간 받는 그룹의 지식정도가 더 높아, 교육시간에 따라 지식이 차이를 보이고, 지식과 수행도 관계에 교육시간이 조절하는 것으로 조사되었다. 따라서 호텔조리직원들의 음식점 원산지표시 지식을 높이고 수행정도를 높이기 위해서는 교육시간을 늘려 조리직원들이 더 많은 지식을 학습하여 실제 업무에 사용하도록 하여야 할 것이다. 연구의 한계 및 향후 연구방향에 대해 논의 하였다.

GAN을 활용한 분류 시스템에 관한 연구 (A Study on Classification System using Generative Adversarial Networks)

  • 배상중;임병연;정지학;나철훈;정회경
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2019년도 춘계학술대회
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    • pp.338-340
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    • 2019
  • 최근 네트워크의 발달로 인해 데이터가 축적되는 속도와 크기가 증가되고 있다. 이 데이터들을 분류하는데 많은 어려움이 있는데 그 어려움 중에 하나가 라벨링의 어려움이다. 라벨링은 보통 사람이 진행하게 되는데 모든 사람이 같은 방식으로 데이터를 이해를 하는데 무리가 있어 동일한 기준으로 라벨링하는 것은 매우 어렵다는 문제가 있다. 이를 해결하기 위해 본 논문에서는 GAN을 이용하여 입력 이미지를 기반으로 새로운 이미지를 생성하고 이를 학습을 하는 데 사용을 하여 입력 데이터를 간접적으로 학습할 수 있게 구현하였다. 이를 통해 학습 데이터의 개수를 늘려 분류의 정확도를 높일 수 있을 것으로 사료된다.

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건설 인공지능 개발사례로 보는 전공교육 인력의 중요성 (The Importance of Manpower in Major Education as an Example of Artificial Intelligence Development in Construction)

  • 허석재;이상현;이성원;김명훈;정란
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2021년도 가을 학술논문 발표대회
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    • pp.223-224
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    • 2021
  • The process before the model learning stage in AI R&D can be subdivided into data collection/cleansing-data purification-data labeling. After that, according to the purpose of development, it goes through a stage of verifying the model by performing learning by using the algorithm of the artificial intelligence model. Several studies describe an important part of AI research as the learning stage, and try to increase the accuracy by changing the structure and layer of the AI model. However, if the refinement and labeling process of the learning data is tailored only to the model format and is not made for the purpose of development, the desired AI model cannot be obtained. The latest research reveals that most AI research failures are the failure of the learning data rather than the structure of the AI model. analyzed.

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Towards Improved Performance on Plant Disease Recognition with Symptoms Specific Annotation

  • Dong, Jiuqing;Fuentes, Alvaro;Yoon, Sook;Kim, Taehyun;Park, Dong Sun
    • 스마트미디어저널
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    • 제11권4호
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    • pp.38-45
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    • 2022
  • Object detection models have become the current tool of choice for plant disease detection in precision agriculture. Most existing research improves the performance by ameliorating networks and optimizing the loss function. However, the data-centric part of a whole project also needs more investigation. In this paper, we proposed a systematic strategy with three different annotation methods for plant disease detection: local, semi-global, and global label. Experimental results on our paprika disease dataset show that a single class annotation with semi-global boxes may improve accuracy. In addition, we also studied the noise factor during the labeling process. An ablation study shows that annotation noise within 10% is acceptable for keeping good performance. Overall, this data-centric numerical analysis helps us to understand the significance of annotation methods, which provides practitioners a way to obtain higher performance and reduce annotation costs on plant disease detection tasks. Our work encourages researchers to pay more attention to label quality and the essential issues of labeling methods.

시판 포장가공 식품의 영양표시 현황에 관한 조사연구 (A Study on the Current Nutritin Labeling Practices for the Processed Foods Retailed in the Supermarket in Korea)

  • 장순옥
    • Journal of Nutrition and Health
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    • 제30권1호
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    • pp.100-108
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    • 1997
  • Our current food hygiene law mandates nutrition label (NL) for the special nutrition foods, health support foods, instant foods, and foods with certain nutrient emphasized note, only. Currently more processed foods are bearing nutrition labels though the format is quite inconsistant. This study examined the status on current nutrition labeling practices for the processed foods that are retailed in the supermarket. The obtained information was assessed in the aspects of numerical data presentation on nutrients content, descriptive terms, health claim, and the format. The results are summarized as follows. 1) Foods with NL are limited to the food category specified by current hygiene law while voluntary nutition labeling is few. 2) Descriptive terms such as free, low, and sufficient are not substantiated with quantitative data. The efficacy of microelements which has not been clalified yet are overemphasized but major nutrients are ignored. 3) The regulations for the descriptive terms are set on the base of the nutrient content per 100g or 100ml under current nutrition labeling act. It would mislead consumers thus the definition for these descriptor be better set on the unit of the amount of food customary eaten at one time. For this the standard serving size should be set officially. 4) Quantitative nutrition information given on food products is difficult to compare because of the lack in formality. The title of NL, load and kinds of nutritents, order of nutrients listed, the unit of expression, RDA comparision, and reference RDA are inconsistant among the foods similar in dietary property. Uniform format is needed to give NL the credibility and usefulness. Proividing nutrition information to the consumers with NL is a worldwide practice though its efficacy has been controversial. Under newly legistered health promotion law in Korean nutrition education is esxpected to take part in to improve national nutrition condition and NL would education is expected to take part in to improve national nutrition condition and NL would be a potent tool for public nutritions education. It appears to be the time to mandate NL to all the processed foods in the market. The result of present study would initiate further consumer experiments related to NL. Various interest groups such as food and nutrition professions, public health organizations, government regulatory agencies, food producers and marketers, and consumer groups need to particepate and communicate for the legislation of NL and the development of NL format.

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다중 가변 문턱값을 이용한 복셀 칼라링 기법에 관한 연구 (A Study on the Voxel Coloring using Multi-variable Thresholding)

  • 김효성;이상욱;남기곤
    • 한국정보통신학회논문지
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    • 제9권5호
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    • pp.1102-1110
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    • 2005
  • 본 논문에서는 기존 복셀 칼라링 기법에서의 색상 일관성에 대한 문턱값 문제를 해결하기 위한 개선된 복셀 칼라링 기법을 제안하였다. 제안 기법에서는 표면 복셀에 대한 색상 일관성의 문턱값을 내부 복셀의 색상 일관성 값으로 대체함으로써 복셀 칼라링의 반복 회수가 증가함에 따라 개별 표면 복셀에 대한 최적의 문턱값을 찾아가도록 하였다. 또한 그래프 절단 기법을 적용하여 주위 복셀을 제거 판단에 함께 고려함으로써 표면 잡음을 감소시켰다.

해양사고 예방을 위한 사전학습 언어모델의 순차적 레이블링 기반 복수 인과관계 추출 (Sequence Labeling-based Multiple Causal Relations Extraction using Pre-trained Language Model for Maritime Accident Prevention)

  • 문기영;김도현;양태훈;이상덕
    • 한국안전학회지
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    • 제38권5호
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    • pp.51-57
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    • 2023
  • Numerous studies have been conducted to analyze the causal relationships of maritime accidents using natural language processing techniques. However, when multiple causes and effects are associated with a single accident, the effectiveness of extracting these causal relations diminishes. To address this challenge, we compiled a dataset using verdicts from maritime accident cases in this study, analyzed their causal relations, and applied labeling considering the association information of various causes and effects. In addition, to validate the efficacy of our proposed methodology, we fine-tuned the KoELECTRA Korean language model. The results of our validation process demonstrated the ability of our approach to successfully extract multiple causal relationships from maritime accident cases.