• Journal of Information Processing Systems
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• 제19권4호
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• pp.554-562
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• 2023

This research offers a sports video action recognition approach based on the fish swarm algorithm in light of the low accuracy of existing sports video action recognition methods. A modified fish swarm algorithm is proposed to construct invariant features and decrease the dimension of features. Based on this algorithm, local features and global features can be classified. The experimental findings on the typical sports action data set demonstrate that the key details of sports action can be successfully retained by the dimensionality-reduced fusion invariant characteristics. According to this research, the average recognition time of the proposed method for walking, running, squatting, sitting, and bending is less than 326 seconds, and the average recognition rate is higher than 94%. This proves that this method can significantly improve the performance and efficiency of online sports video motion recognition.

• 한국조리학회지
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• 제17권2호
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• pp.126-139
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• 2011

본 연구는 조리 관련 학과를 전공하고 있는 일부 4년제 대학생을 대상으로 조리 실습 교육에 대한 인식 수준을 조사하여 조리교육의 발전 방안을 모색하고자 하는 목적으로 수행되었다. 성과 학년, 졸업학교 유형에 따른 조리 실습 교육에 대한 인식 수준은 다음과 같다. 조리 실습 교육의 흥미도와 필요성은 매우 높으나, 조리 실습 교육의 실시 정도에 대해서는 부족하다고 느끼고 있었다. 효과적인 조리 실습 교육을 위해서는 이론 교육과 실습시연이 필요하다고 인식하고 있었으며, 호텔요리와 기능사요리에 중점을 두기를 희망하고 있었다. 또한 교사의 자세한 실습 시연과 보충실습을 할 수 있는 장소가 제공되기를 희망하였다. 변인에 따라서는 남학생과 고학년, 전문계고 출신 학생들이 긍정적인 응답을 하였다. 결론적으로 교육과정에서 실습의 비중을 높이고, 다양한 프로그램의 개발 및 적용, 열린 실습실의 운영, 사회 변화를 반영한 교육과정 편성 등을 통해 자기 주도적으로 성취 욕구를 발산할 수 있는 기회가 제공된다면 조리 실습 교육은 더욱 활성화될 수 있을 것으로 사료된다.

• 융합정보논문지
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• 제9권10호
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• pp.254-263
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• 2019

본 연구는 DISC행동유형을 통해 미용 전공 대학생들의 미용교육 전공인식과 만족도, 직업 선호도에 대하여 파악하고자 하였으며, DISC행동유형을 통한 개인별 성향을 고려하여 맞춤형 진로 및 미용교육 자료로써 활용하고자 하였다. 2017년 9월 20일부터 10월 11일까지 충남과 경기도에 거주하는 미용교육 대학생을 대상으로 최종 설문지 225부를 분석하였다. 연구 대상자들의 전공에 대한 만족도가 D, I, S, C 순으로 확인되었고, 전공인식과 직업 선호도는 유형별로 유의한 차이가 확인되었다. 본 연구를 통하여 미용 교육 대학생들의 전공인식과 만족도, 직업 선호도를 파악하여, 미용 교육 후 진로 결정에 도움이 될 수 있는 기초자료로써 활용이 가능할 것으로 사료되어진다.

• Journal of information and communication convergence engineering
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• 제12권4호
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• pp.263-270
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• 2014

Corner detection and feature extraction are essential aspects of computer vision problems such as object recognition and tracking. Feature detectors such as Scale Invariant Feature Transform (SIFT) yields high quality features but computationally intensive for use in real-time applications. The Features from Accelerated Segment Test (FAST) detector provides faster feature computation by extracting only corner information in recognising an object. In this paper we have analyzed the efficient object detection algorithms with respect to efficiency, quality and robustness by comparing characteristics of image detectors for corner detector and feature extractors. The simulated result shows that compared to conventional SIFT algorithm, the object recognition system based on the FAST corner detector yields increased speed and low performance degradation. The average time to find keypoints in SIFT method is about 0.116 seconds for extracting 2169 keypoints. Similarly the average time to find corner points was 0.651 seconds for detecting 1714 keypoints in FAST methods at threshold 30. Thus the FAST method detects corner points faster with better quality images for object recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권8호
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• pp.3488-3500
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• 2020

At the present time, the economy continues to flourish, and private cars have become the means of choice for most people. Therefore, the license plate recognition technology has become an indispensable part of intelligent transportation, with research and application value. In recent years, the convolution neural network for image classification is an application of deep learning on image processing. This paper proposes a strategy to improve the YOLO model by studying the deep learning convolutional neural network (CNN) and related target detection methods, and combines the OpenCV and TensorFlow frameworks to achieve efficient recognition of license plate characters. The experimental results show that target detection method based on YOLO is beneficial to shorten the training process and achieve a good level of accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4510-4526
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• 2017

Most available methods of facial gender recognition work well under a constrained situation, but the performances of these methods have decreased significantly when they are implemented under unconstrained environments. In this paper, a method via low-rank and collaborative representation is proposed for facial gender recognition in the wild. Firstly, the low-rank decomposition is applied to the face image to minimize the negative effect caused by various corruptions and dynamical illuminations in an unconstrained environment. And, we employ the collaborative representation to be as the classifier, which using the much weaker $l_2-norm$ sparsity constraint to achieve similar classification results but with significantly lower complexity. The proposed method combines the low-rank and collaborative representation to an organic whole to solve the task of facial gender recognition under unconstrained environments. Extensive experiments on three benchmarks including AR, CAS-PERL and YouTube are conducted to show the effectiveness of the proposed method. Compared with several state-of-the-art algorithms, our method has overwhelming superiority in the aspects of accuracy and robustness.

• 보건의료산업학회지
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• 제14권1호
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• pp.103-110
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• 2020

Objectives: In this paper, we propose the ethical education direction by analyzing the personal information recognition and practice of music therapists. Methods: For the analyses, we selected 60 music therapists who answered a questionnaire from members of K Music Therapy Association, and analyzed task recognition and practice ask performance using IPA method. Results: In the IPA table, the areas of high recognition and practice (1) are the areas of personal information protection information management. In the IPA table, the areas of low awareness and high practice (2) are areas of privacy communication for those who have completed ethics education. In the IPA table, the areas of low awareness and low practice (3) are areas of privacy communication when ethics education is not completed. In the IPA table, areas of high awareness and low levels of practice (4) are areas of privacy protection. Conclusions: Continuing education should be provided to improve the curriculum on the protection of personal information for music therapists, thereby raising the awareness and practice of privacy.

• 한국식생활문화학회지
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• 제38권6호
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• pp.373-380
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• 2023

In this study, 294 housewives in Siheung, Gyeonggi-do, were surveyed to evaluate the differences in the recognition and use of nutrition labeling according to age and to present data for nutrition education. The younger the age, the more aware the consumer was of the information on the nutrition label. Housewives who were younger than 60 years were more likely to check the nutrition labels. The lower the age, the higher the reliance on the nutritional labeling content of the food, and the higher the recognition level of nutritional labeling. It was found that the lower the age, the easier it was for the consumer to understand the nutritional labeling. Among housewives in their 30s and younger, 89.5 percent said they believed checking nutrition labels would help their health. In the younger age group knowledge and information on nutrition labeling was acquired from the internet, and in the older age group, knowledge was acquired from television, radio, and newspapers. Research conducted on housewives in other regions in the future could provide more detailed information suitable for the population of each region. This would serve as data for nutrition education on the recognition and use of nutrition labeling for a healthy diet.

• 영어어문교육
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• 제5호
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• pp.191-218
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• 1999

The purpose of this study is to investigate the actual conditions of preschool English education, and teachers' and parents' recognition of preschool early English education in Cheonan-city. Recently the importance of English education as an essential means for communication in the whole world is emphasized in our society. That atmosphere makes the elementary schools offer English as a subject in their curriculums, and also many preschool education institutes begin to teach English in their education courses. However before we begin to teach English as a subject in the preschool education, we need to survey the actual conditions of preschools and recognition of teachers and parents. The first part of this study is to survey the theoretical foundations of early English education; 1) the definition of early English education. 2) the situation of early foreign language education in foreign countries. 3) the relationship between the language acquisition and the cognitive development. The second part is to analyze the results of the Questionnaire which was distributed among 86 teachers and 103 parents in Cheonan-city preschools. As a conclusion, some suggestions will be given for the development of early English education in the near future.

• 정보교육학회논문지
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• 제25권6호
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• pp.927-934
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• 2021

인공지능은 우리의 삶에 점차 많은 부분을 차지하고 있으며, 발전하는 속도도 빨라지고 있다. 학생들의 컴퓨팅 사고력을 인공지능이 학습하는 방법대로 길러주는 것을 ACT(AI based Computational Thinking)라고 한다. ACT 중 패턴 인식은 문제를 효율적으로 해결하기 위해 필수적인 요소이다. 패턴 분석은 패턴 인식 과정의 일부로 볼 수 있다. 실제로 넷플릭스의 개인 맞춤 영화 추천, 반복된 증상을 분석하여 코로나 바이러스로 명명하는 것 등이 모두 패턴 분석의 결과이다. 패턴인식을 포함한 ACT의 중요성이 부각되는 것에 반면, 유치원과 초등학교 저학년을 대상으로 한 소프트웨어 교육은 국외에 비해 많이 부족한 실정이다. 따라서 본 연구에서는 유치원 학생들을 대상으로 하여 패턴 분석을 통한 인공지능 기반 컴퓨팅 사고력 계발을 위한 교재를 설계하고 개발하였다.