• ETRI Journal
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• 제31권2호
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• pp.121-128
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• 2009

In this paper, we describe a fixed-threshold sequential minimal optimization (FSMO) for structured SVM problems. FSMO is conceptually simple, easy to implement, and faster than the standard support vector machine (SVM) training algorithms for structured SVM problems. Because FSMO uses the fact that the formulation of structured SVM has no bias (that is, the threshold b is fixed at zero), FSMO breaks down the quadratic programming (QP) problems of structured SVM into a series of smallest QP problems, each involving only one variable. By involving only one variable, FSMO is advantageous in that each QP sub-problem does not need subset selection. For the various test sets, FSMO is as accurate as an existing structured SVM implementation (SVM-Struct) but is much faster on large data sets. The training time of FSMO empirically scales between O(n) and O($n^{1.2}$), while SVM-Struct scales between O($n^{1.5}$) and O($n^{1.8}$).

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2022년도 춘계학술대회
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• pp.363-364
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• 2022

The COVID-19 pandemic had substantial negative impacts and caused several disruptions to the global supply chain of the shipping industry. The key challenges identified in terms of maritime manpower are the Certificates of Competency (CoC) or the expiration and/or failure to complete refresher and/or revalidation courses, which directly hinder employment retention and lost opportunities at sea. To tackle this issue directly and swiftly, the creation of the APEC SEN Distance Learning Platform was suggested and approved by APEC as part of an official project. This paper introduces the APEC-wide accessible distance learning platform with the following key topics: the organisation and operation of the platform, the themes and content to be prioritised, the process of education, training, certification, and the ways to promote accreditation, mutual recognition on CoC, education and training videos by taking collaborative actions, and the development of content.

• 한국게임학회 논문지
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• 제19권2호
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• pp.55-66
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• 2019

본 연구는 게임콘텐츠 관련 전문가들이 지능정보시대에 콘텐츠산업의 변화를 어떻게 인식하고 있고, 콘텐츠산업 정책 중에서 어떤 평가요인에 우선순위를 두고 있는가에 대해 살펴보았다. 이를 위해 계층분석과정을 이용하여 콘텐츠산업 정책 평가요인들의 상대적 중요도와 우선순위를 분석하였다. 분석결과, '콘텐츠 기술역량 강화', '콘텐츠 전문인력 양성', '콘텐츠관련 제도개선', '콘텐츠 이용 및 소비자 안전강화'의 순으로 평가되었으며, 하위항목 분석에서는 '콘텐츠 R&D 체계구축 강화'가 가장 중요한 것으로 나타났다. 전문가집단별 분석에서는 산업계와 정책기관이 '콘텐츠기술역량 강화'를, 학계에서는 '콘텐츠 전문인력 양성'을 중요하게 평가하였다.

• Archives of Plastic Surgery
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• 제41권3호
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• pp.218-224
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• 2014

Plastic surgery training worldwide has seen a thorough restructuring over the past decade, with the introduction of formal training curricula and work-based assessment tools. Part of this process has been the introduction of revalidation and a greater use of simulation in training delivery. Simulation is an increasingly important tool for educators because it provides a way to reduce risks to both trainees and patients, whilst facilitating improved technical proficiency. Current microsurgery training interventions are often predicated on theories of skill acquisition and development that follow a 'practice makes perfect' model. Given the changing landscape of surgical training and advances in educational theories related to skill development, research is needed to assess the potential benefits of alternative models, particularly cross-training, a model now widely used in non-medical areas with significant benefits. Furthermore, with the proliferation of microsurgery training interventions and therefore diversity in length, cost, content and models used, appropriate standardisation will be an important factor to ensure that courses deliver consistent and effective training that achieves appropriate levels of competency. Key research requirements should be gathered and used in directing further research in these areas to achieve on-going improvement of microsurgery training.

• 한국사회복지학
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• 제49권
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• pp.95-128
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• 2002

The present study is designed to trace the successful reform steps taken within the vocational training system in the UK and to extract a set of instructive implications for Korea's future reform path towards an efficient vocational training system conducive to youth employment. To this end, this study focuses on three major aspects of the youth vocational training system: the government's role and partnerships between training and industry, the vocational training system, and the employment support system. Implications drawn from the comparative analysis are as follows. Vocational training reform should be made within the broad paradigm of youth employment promotion. All aspects of the youth vocational training system, such as the training program structure, program content, provider, management, so on, should be reformed, step by step, within a long-term plan. In addition to the vocational training reforms. employment support programs should be enlarged, and the service delivery system should be well structured in order to enhance the effects of the training reforms. For these reforms, it is essential to make fundamental changes in the following areas: integration of youth employment policy making and its administrative structures, reinforcement of partnerships between training and industry, nation-wide standardization of job skins, and the introduction of standardized job certificate classification on a national level.

• 한국치위생학회지
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• 제24권1호
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• pp.69-77
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• 2024

Objectives: The purpose of this study was to explore the general public's perception and status of oral muscle strength training, to develop age-appropriate educational media and training methods, and to promote the need for oral muscle strength training. Methods: Data were collected from 15 individuals across different age groups (young, middle-aged, and elderly) from December 2022 to February 2023 through focus group interviews, and they were conducted twice for each group in a face-to-face manner. Results: Four key categories were identified: lack of information, effectiveness of training, need for promotion, and factors necessary for implementation. The following themes emerged: lack of information, need for training, age-specific characteristics, need for repetition, age at which training is needed, lack of promotion, need for promotion, number of practitioners, willingness to practice, and appropriate media for training. Conclusions: Awareness of oral muscle strength training was found to be very low, and it is necessary to improve awareness through continuous information and appropriate education on its need among the public. Additionally, quality content or media that can be easily applied for effective training should be developed, and personnel who can perform training efficiently should be trained.

• 한국컴퓨터그래픽스학회논문지
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• 제26권3호
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• pp.111-121
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• 2020

가상현실의 높은 몰입감을 활용한 실감형 훈련 콘텐츠가 산업, 교육, 의료 등 다양한 분야에서 활용되고 있다. 특히 현실에서 실시하기 힘든 고위험, 고비용이 발생하는 교육훈련을 최신 가상현실 기술을 적용하여 현실과 비슷한 환경에서 효율적이고 안전하게 체험하여 교육효과를 높일 수 있다. 본 논문은 실감형 가상훈련 콘텐츠를 체계적으로 관리하고 정의된 평가요소를 기반으로 훈련 결과를 도식화된 그림으로 가시화하는 관리 시스템을 소개한다. 관리 시스템은 콘텐츠에서 생성되는 정보를 데이터베이스에 저장하여 각 훈련생의 훈련 기록을 실용적으로 관리할 수 있다. 또한 콘텐츠 기반 시나리오 생성 방법으로 훈련 목표, 참여인원, 평가요소 등을 설정하여 하나의 콘텐츠를 여러 시나리오로 생성할 수 있다. 본 논문은 관리 시스템의 제작 방법과 그 결과를 적용 사례인 가상현실 훈련 콘텐츠 기반으로 설명한다.

• Asian-Australasian Journal of Animal Sciences
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• 제6권4호
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• pp.509-514
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• 1993

The experiment was conducted to determine the effect of different fiber levels on milk production of crossbred Holstein milking cows fed urea-treated rice straw (UTS) as a roughage. Eight cows were allotted into 2 squares of 4 cows each with 4 treatments by a balanced design. The treatments were 17%, 22%, and 24% crude fiber (CF) diets and Thai feeding system (free choice of roughage and 1 kg of concentrates/2 kg of milk) as a control. Body weight change was not significantly different among the treatments during the experiment. Milk production (4% FCM) and milk protein content wee not different among the treatments, but milk fat content was low in the 17% CF group and high in the control group. Cows fed the 17% CF diet consumed less UTS and more concentrates than the others, and consequently total DM intake was not different among the treatments. The feed conversion ratio was significantly higher in the control. Feed cost per kg milk was lowest in the control and highest in the 17% CF diet. The fiber content of the diet would be more than 17%, preferably 22-24% for normally producing Thai crossbred Holstein cows when the UTS was fed as a main roughage source.

• 농촌지도와개발
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• 제22권4호
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• pp.435-444
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• 2015

This study analyzes the structural relationship between attitudes and learning more properties in agricultural college education programs. The results were as follows. first, The model was accepted according to the some goodness of fit statistics such as ${\chi}^2$(84.28, p>.05), RMR(.036), RMSEA(.041), GFI(.927), NFI(.945), CFI(.985), IFI(985). seconds, Learning attitude(.31) and content validity(.47) in the structural relationship between variables is a direct impact on satisfaction. thirds, Perceived Usefulness(.34) and Content validity(.36) has direct effect of factor on learning attitude. Finally Perceived Usefulness was found to direct effect all Content validity(.64) and easy of use(.27). Finally, considering of duties required in the agriculture. increase the satisfaction of learners should have provide field learning based Learning materials, practices, instructional media. As a result, it will enhance the performance of field learning agricultural education programs.

• ETRI Journal
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• 제39권5호
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• pp.643-651
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• 2017

Human age estimation is one of the key factors in the field of Human-Robot Interaction/Human-Computer Interaction (HRI/HCI). Owing to the development of deep-learning technologies, age recognition has recently been attempted. In general, however, deep learning techniques require a large-scale database, and for age learning with variations, a conventional database is insufficient. For this reason, we propose an age estimation method using artificially generated data. Image data are artificially generated through 3D information, thus solving the problem of shortage of training data, and helping with the training of the deep-learning technique. Augmentation using 3D has advantages over 2D because it creates new images with more information. We use a deep architecture as a pre-trained model, and improve the estimation capacity using artificially augmented training images. The deep architecture can outperform traditional estimation methods, and the improved method showed increased reliability. We have achieved state-of-the-art performance using the proposed method in the Morph-II dataset and have proven that the proposed method can be used effectively using the Adience dataset.