• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.58-63
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• 2021

This research aims to reconsider the necessity of an alternative way(s) for contemporary actor training and acting in discussing and articulating Diderot and Suzuki's concepts and approaches for acting/training. First of all, the physical body, assumed and conceptualized by Diderot is beyond our control by means of a type of radical body/mind dualism, and is based on the concept that body and mind are separate. In contrast, Suzuki's notion of acting/training is raised by his concern about the role of an actor's body in the constitution of an actor's bodily experience against the imitation of the West-oriented theatre/acting/training. The descriptions of the two theatre artists' notion of acting/training gives us insight into the place and role of contemporary theatre as a practical root to encounter and communicate between a doer and a spectator where an actor's body must appropriately be attuned and cultivated towards the cultivation of bodily attributes which are foundation but usually neglected by actors/directors/practitioners particularly in Korea. Especially, misunderstanding of a specific training sources/approaches, namely 'scientific system' and the 'method' have taken us away from the potential possibilities of the lived oneness. Here, the 'possibility' refers to the primary bodily functions within a specific context or being in the here and now rather than attempting to copying, imitating and/or adapting a specific cultural source(s)/approaches/techniques as we have faced with through the previous century. We reconsider and argue that a potential way to correspond the nature of theatre/acting/training is that how to meet the demand of contemporary spectators which in turn intensifies an actor's stability, sustainability and hopefully professional identity in this contemporary era.

• Convergence Security Journal
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• v.16 no.3_1
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• pp.47-56
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• 2016

This study's goal is to consider deeper about the Context-Communication Study on candidates of future petty officers in community colleagues, therefore the study uses theoretical approaches of the communications based on literature research. The petty officer majors in community colleagues need to set a curriculum to achieve the goal of the Context-Communication Study. The class, which is a continuous class from freshman to sophomore year, needs to be designed as a combination class of command/discipline major classes and communication studies. This study shows the detail ways of the Context-Communication Study to bring student's interests by using simulation studies with writing papers, training interviews, and presentations which all will be checked by their instructors. Instructors will get students to the point that they have upscale communication abilities and language abilities. Finally, this study shows limitations of the Context-Communication Study and suggests the further direction of research.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.653-662
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• 2006

In ubiquitous computing that is to build computing environments to provide proper services according to user's context, human being's emotion recognition based on facial expression is used as essential means of HCI in order to make man-machine interaction more efficient and to do user's context-awareness. This paper addresses a problem of rigidly basic emotion recognition in context-sensitive facial expressions through a new Bayesian classifier. The task for emotion recognition of facial expressions consists of two steps, where the extraction step of facial feature is based on a color-histogram method and the classification step employs a new Bayesian teaming algorithm in performing efficient training and test. New context-sensitive Bayesian learning algorithm of EADF(Extended Assumed-Density Filtering) is proposed to recognize more exact emotions as it utilizes different classifier complexities for different contexts. Experimental results show an expression classification accuracy of over 91% on the test database and achieve the error rate of 10.6% by modeling facial expression as hidden context.

• Journal of Gifted/Talented Education
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• v.17 no.1
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• pp.77-98
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• 2007

It has been said that the level of teacher professionalism determines the quality of education. The same notion allies for gifted education. Therefore, exploration of teacher professionalism in gifted education may provide fundamental bases for raising the quality of gifted education. In this study, first, literature review was conducted to extract elements of teacher professionalism in gifted education and a survey instrument was developed to find out categories of those elements and differences of teacher perception to professionalism at school levels and subject areas of gifted education. Research subjects included 212 teachers who participated in 2005 KEDI teacher training program of gifted education, 60 hour-clock introductory program and 232 teachers who participated in 2005 KEDI teacher training program of gifted education, 120 hour-clock enrichment program. It was found that elements of teacher professionalism in gifted education were categorized into knowledge-based, abilitybased and context-based. It was also found that secondary school teachers' perception to knowledge-based professionalism was significantly higher than those at elementary and science teachers' perception to ability-based and context-based professionalism was significantly higher than mathematics teachers. The research findings may provide insights for better teacher training program in gifted education as well as gifted education policies.

• Proceedings of the KSPS conference
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• 2006.05a
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• pp.37-40
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• 2006

In this paper, we propose a VQ codebook design of speech recognition feature parameters in order to improve the performance of a distributed speech recognition system. For the context-dependent HMMs, a VQ codebook should be correlated with phonetic distributions in the training data for HMMs. Thus, we focus on a selection method of training data based on phonetic distribution instead of using all the training data for an efficient VQ codebook design. From the speech recognition experiments using the Aurora 4 database, the distributed speech recognition system employing a VQ codebook designed by the proposed method reduced the word error rate (WER) by 10% when compared with that using a VQ codebook trained with the whole training data.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.1
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• pp.91-102
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• 2015

In connection with biodiversity that has recently become the topic, competition to secure biological genetic resources is being heightened all over the world. Korea also has a variety of efforts to secure and preserve plant genetic resources, and has recognized the importance of the function and role of arboretums. Arboretums in Korea, however, have the problems in terms of quality due to the rapid increase. One of the problems is shortages in experts who are essential for the proper functioning of arboretums. To solve the problem, the State introduced Gardener Training Program certification system and started to train gardeners. However, gardeners who have actually employed at arboretums are less than 20% and thus the problem of shortages in experts still exists. In this context, this study examined 44 registered arboretums in Korea to find out the current situation of experts; analyzed arboretum experts and the program certification system in view of relevant laws; and investigated the current situation of training programs being operated in three Gardener Training Program certification organizations. Finally, this study conducted a survey of 68 gardeners who completed the training program at Chollipo Arboretum and tried to suggest a plan for securing experts from the gardener training programs. The plan for utilizing the trained gardeners as experts in arboretums is as follows: First, legal standards for the employment of experts in arboretums should be strengthened. Second, it is necessary to evaluate training programs, in order to raise the reliability of arboretum experts' expertise. Third, official validity that can be honored in all arboretums should be granted to a certificate of program completion. Finally, networks of gardeners who completed the programs should be formed through follow-up management of them.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2839-2852
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• 2013

Context-awareness is an essential part of ubiquitous computing, and over the past decade video based activity recognition (VAR) has emerged as an important component to identify user's context for automatic service delivery in context-aware applications. The accuracy of VAR significantly depends on the performance of the employed human body segmentation algorithm. Previous human body segmentation algorithms often engage modeling of the human body that normally requires bulky amount of training data and cannot competently handle changes over time. Recently, active contours have emerged as a successful segmentation technique in still images. In this paper, an active contour model with the integration of Chan Vese (CV) energy and Bhattacharya distance functions are adapted for automatic human body segmentation using depth cameras for VAR. The proposed technique not only outperforms existing segmentation methods in normal scenarios but it is also more robust to noise. Moreover, it is unsupervised, i.e., no prior human body model is needed. The performance of the proposed segmentation technique is compared against conventional CV Active Contour (AC) model using a depth-camera and obtained much better performance over it.

• Informatization Policy
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• v.30 no.3
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• pp.49-68
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• 2023

This study presented a framework for re-conceptualized data literacy that consists of three domains-knowledge, skills, and contexts- and elements that are emphasized by each domain. In addition to the existing concept of data literacy that mainly emphasized the skills to handle data, the context domain of data was considered including the elements of scope, time, and value orientation. Based on the re-conceptualized data literacy, it is expected to be usable as reference material in the development of curriculum and educational programs in the fields of informatization, manpower training, and administration.

• The Journal of the Acoustical Society of Korea
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• v.17 no.4E
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• pp.11-16
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• 1998

For large vocabulary speech recognition using HMMs, context-dependent subword units have been often employed. However, when context-dependent phone models are used, they result in a system which has too may parameters to train. The problem of too many parameters and too little training data is absolutely crucial in the design of a statistical speech recognizer. Furthermore, when building large vocabulary speech recognition systems, unseen triphone problem is unavoidable. In this paper, we propose the modified phonetic decision tree algorithm for the automatic prediction of unseen triphones which has advantages solving these problems through following two experiments in Japanese contexts. The baseline experimental results show that the modified tree based clustering algorithm is effective for clustering and reducing the number of states without any degradation in performance. The task experimental results show that our proposed algorithm also has the advantage of providing a automatic prediction of unseen triphones.

• Speech Sciences
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• v.10 no.1
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• pp.71-84
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• 2003

In the acoustic modeling for large vocabulary speech recognition, a sparse data problem caused by a huge number of context-dependent (CD) models usually leads the estimated models to being unreliable. In this paper, we develop a new clustering method based on the C45 decision-tree learning algorithm that effectively encapsulates the CD modeling. The proposed scheme essentially constructs a supervised decision rule and applies over the pre-clustered triphones using the C45 algorithm, which is known to effectively search through the attributes of the training instances and extract the attribute that best separates the given examples. In particular, the data driven method is used as a clustering algorithm while its result is used as the learning target of the C45 algorithm. This scheme has been shown to be effective particularly over the database of low unknown-context ratio in terms of recognition performance. For speaker-independent, task-independent continuous speech recognition task, the proposed method reduced the percent accuracy WER by 3.93% compared to the existing rule-based methods.