• Journal of Information Technology Applications and Management
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• 제16권3호
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• pp.113-124
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• 2009

How can action learning program promote organizational learning performance and especially project based team performance in Web-based small and medium-sized enterprises (SMEs)? This article discusses the association between project based team in action learning program and the performance of Web-based SME to be learning organization. In the case of ALPACO, action learning program that promote employee communication behavior, knowledge sharing, and organizational learning are found to be positively associated with the project based team performance and organizational learning, The results indicate that action learning program in SMEs indeed associated with greater knowledge sharing, learning communication skills and changing organizational culture. Learning organization can be, in turn, positively developed by project based team through action learning program for creating competitive advantage, Also, this study offers further support for the practical perspective on learning organization performance. The evidence from this case study suggests that the project team in action learning program playa significant role in team performance and the development of learning organization of the firm. Therefore, in the future, Web-based SMEs should consider making investments in action learning program that encourage project team's effective management in decision making, knowledge sharing, and organizational learning.

• Genomics & Informatics
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• 제17권2호
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• pp.15.1-15.7
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• 2019

Automatically detecting mentions of pharmaceutical drugs and chemical substances is key for the subsequent extraction of relations of chemicals with other biomedical entities such as genes, proteins, diseases, adverse reactions or symptoms. The identification of drug mentions is also a prior step for complex event types such as drug dosage recognition, duration of medical treatments or drug repurposing. Formally, this task is known as named entity recognition (NER), meaning automatically identifying mentions of predefined entities of interest in running text. In the domain of medical texts, for chemical entity recognition (CER), techniques based on hand-crafted rules and graph-based models can provide adequate performance. In the recent years, the field of natural language processing has mainly pivoted to deep learning and state-of-the-art results for most tasks involving natural language are usually obtained with artificial neural networks. Competitive resources for drug name recognition in English medical texts are already available and heavily used, while for other languages such as Spanish these tools, although clearly needed were missing. In this work, we adapt an existing neural NER system, NeuroNER, to the particular domain of Spanish clinical case texts, and extend the neural network to be able to take into account additional features apart from the plain text. NeuroNER can be considered a competitive baseline system for Spanish drug and CER promoted by the Spanish national plan for the advancement of language technologies (Plan TL).

• 산업경영시스템학회지
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• 제41권3호
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• pp.30-40
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• 2018

The purpose of this study is to examine the effect of project-based organizational resources on the business performance in the resource-based view (RBV) and dynamic capability one and analyze their relationship through an integrated model. The RBV argues that firms get competitive advantages when they have VRIN characterized resources but dynamic capability view argues that RBV has its limitation under volatility so it enables them to obtain competitive advantages in ever changing environments. This study analyzes data collected from 270 survey questionnaires on the project management related staff at the project-based organization among major companies in Korea. The result demonstrates that two project organizational resources on strategic and executional management with VRIN characteristics are found to bring positive effects on the organizational dynamic capabilities and also the dynamic capabilities such as integration & reconfiguration, organizational learning are verified to bring meaningful positive effects on the business performance. On the other hand, unlike previous studies, ambidexterity has quite a weak effect on the business performance. Therefore, we expect that the resources of the project-based organization with VRIN lead to strengthen the firm's business performance through organizational dynamic capabilities and produce high performance through the integrated model of RBV and dynamic capability one. The study has academic meanings that widely confirm the effects and characteristics of main elements of VRIN project organizational resources on the business performance of competitive advantage through the dynamic capabilities of the organization by the regression on the precedent studies regarding the project management resources and their relationship with the VRIO characteristics. The practical implication is that it is preferentially necessary for the organization to obtain VRIN resources and organizational dynamic capabilities, especially organizational learning to have sustainable competitive advantages.

• 한국산학기술학회논문지
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• 제8권2호
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• pp.309-323
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• 2007

최근 급격히 확산된 광역 인프라를 기반으로 탄생된 e-Learning 은 학교에서의 교육혁신 및 사회에서의 인적자원개발을 위한 새로운 수단으로 각광받고 있을 뿐만 아니라 디지털 콘텐츠 산업의 주요 핵심으로 등장하게 되었다. 본 논문에서는 e-Learning 소프트웨어의 기반 기술의 특성을 분석하고 e-Learning 소프트웨어의 품질시험 및 평가를 위한 품질특성을 분석하여 e-Learning 소프트웨어 품질 평가모델을 개발하였다. 이를 위해 관련 국제 표준을 도입하여 e-Learning 소프트웨어에 대한 품질평가 체계를 확립하고 품질평가를 위한 평가모델을 개발하였다. 이를 통해, 품질평가를 효과적으로 수행하여 경쟁력 있는 e-Learning소프트웨어 제품의 개발을 촉진할 수 있을 것이라고 사료된다.

• International journal of advanced smart convergence
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• 제8권4호
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• pp.75-81
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• 2019

Though recent advancement of deep learning methods have provided satisfactory results from large data domain, somehow yield poor performance on few-shot classification tasks. In order to train a model with strong performance, i.e. deep convolutional neural network, it depends heavily on huge dataset and the labeled classes of the dataset can be extremely humongous. The cost of human annotation and scarcity of the data among the classes have drastically limited the capability of current image classification model. On the contrary, humans are excellent in terms of learning or recognizing new unseen classes with merely small set of labeled examples. Few-shot learning aims to train a classification model with limited labeled samples to recognize new classes that have neverseen during training process. In this paper, we increase the backbone depth of the embedding network in orderto learn the variation between the intra-class. By increasing the network depth of the embedding module, we are able to achieve competitive performance due to the minimized intra-class variation.

• International Journal of Costume and Fashion
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• 제9권2호
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• pp.1-18
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• 2009

Since the 1990s, the domestic fashion industry has been changing rapidly and has become more competitive. Due to these circumstances, the roles of Shop masters were intensified and a training course to acquire a certificate of qualification as a Shop master was in great demand. The 1st Shop master certification exam took place in the year 2001. The purpose of this study was to research the formality of Shop master certificate training courses via e-learning, which is a hot topic in 21st century education, and to provide a development example. First, an analysis was made of the definition and basic characteristics needed of a Shop-master. Next, we noted the problems of former Shop master training facilities and their training process. Thirdly, we did a research on the definition of e-learning and the elements to embody the system. Based on the information obtained through this research, we provided a development example on Shop-master certificate training courses via e-learning that overcame the problems of courses that are currently provided.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권2호
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• pp.84-88
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• 2011

In this paper, a new competition strategy for learning vector quantization is proposed. The simple competitive strategy used for learning vector quantization moves the winning prototype which is the closest to the newly given data pattern. We propose a new learning strategy based on k-nearest neighbor prototypes as the winning prototypes. The selection of several prototypes as the winning prototypes guarantees that the updating process occurs more frequently. The design is illustrated with the aid of numeric examples that provide a detailed insight into the performance of the proposed learning strategy.

• Journal of the Korean Data and Information Science Society
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• 제23권4호
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• pp.825-832
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• 2012

We propose a novel way of forecasting the market shares of several brands simultaneously in a multiplicative competitive interaction model, which uses kernel regression technique incorporated with kernel machine technique applied in support vector machines and other machine learning techniques. Traditionally, the estimations of the market share attraction model are performed via a maximum likelihood estimation procedure under the assumption that the data are drawn from a normal distribution. The proposed method is shown to be a good candidate for forecasting method of the market share attraction model when normal distribution is not assumed. We apply the proposed method to forecast the market shares of 4 Korean car brands simultaneously and represent better performances than maximum likelihood estimation procedure.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2005년도 춘계학술대회 발표 논문집
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• pp.409-424
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• 2005

Today, many universities are confronted with the changing education paradigm such as e-Learning, Distance Education, Virtual University. This IT-based learning paradigm shift is certainly a new opportunity or a threat to our universities. The Local University Community e-Learning Centers that support the demand of e-Learning for their community are recommended. Tn order to operate these centers efficiently, the strategic roles of the e-Learning center should first be defined. To define the strategic roles, We classified the strategic roles of the e-Learning center into four dimensions, (1) to improve management efficiency, (2) to enhance educational service, (3) to acquire competitive advantages, (4) to build new education infrastructure, and each dimension has S or 6 measurement items. As result, to enhance the educational service was considered as the most significant factor among the four dimensions of strategic roles, and the infrastructure building was the next. Through the strategic roles definition and analysis of expected role ratings, we could have recommended the direction and operation policies of the e-Learning centers.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제9권1호
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• pp.69-96
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• 2005

Motivation for learning is important for positive learning outcomes as well as for measured achievement levels. When students come to our classes, they bring with them learning histories in which we as individual teachers, most likely, did not have an input. Our students do not only bring with them different levels of prerequisite leanings but also different levels of affect for what they will be learning. If we leave their final learning at the mercy of these entry characteristics, a test given the first day before the course will have almost isomorphic results with their achievement levels on the last day. The ones who had 'it' on the first day will be the ones who in the future will also have 'it', not too different from what the present situation is all over the world. These circumstances will tend to be the case ad infinitum, unless of course, we want to change the situation. This research clearly shows that effective instructional methodologies coupled with cooperative peer interactions not only have an impact on achievement but also on positive attitudes toward one's learning.