• Journal of KIISE:Computer Systems and Theory
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• v.29 no.12
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• pp.655-664
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• 2002

In many data-parallel applications massive parallelism can be easily extracted through data distribution. But it often causes very long communication latency. This paper shows that task parallelism, which is extracted from data-parallel programs, can be exploited to hide such communication latency Unlike the most previous researches over exploitation of task parallelism which has not been considered together with data parallelism, this paper describes exploitation of task parallelism in the context of data parallelism. PCFG(Parallel Control Flow Graph) is proposed to represent a multithreaded program consisting of a few task threads each of which can include a few data-parallel loops. It is also described how a PCFG is constructed from a source data-parallel program through HDG(Hierarchical Dependence Graph) and how the multithreaded program can be constructed from the PCFG.

• Journal of Korea Multimedia Society
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• v.5 no.4
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• pp.361-371
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• 2002

An efficient access technique is one of the most Important requirements in GIS. Using level -of-detailed data, we can access spatial data efficiently, because of no access to the fully detailed spatial data. Previous spatial access methods do not access data with level of detail efficiently. To solve it, a few spatial access methods for spatial data with level of detail, are known. However these methods support only a few kinds of data with level of detail, i.e, data through selection and simplification operations. For the effects, we propose a new spatial indexing method supporting fast searching in all kinds of data with level of detail. In the proposed method, the collection of indexes in its own level are integrated into a single index structure. Experimental results show that our method offers both no data redundancy and high search performance.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.66-71
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• 2007

Isochromatics obtained from photoelastic experiment shows the stress distributions of full field of a structure under a load. Therefore stress distributions of the structure can be read at a glace through isochromatics. Many experimental data are obtained from isochromatics. And then, the various photoelastic experimental hybrid methods have been developed. Until now, monochromatic light has been used for photoelastic experimental hybrid method. Therefore the photoelastic experimental hybrid method used until now is called the photoelastic experimental hybrid method for black and white isochromatics. When stresses are analyed by photoelastic experimental hybrid method, many experimental data are needed. Therefore some fringe orders of isochromatics are needed for the photoelastic experimental hybrid method for white and black isochromatics. Therefore in this paper, the photoelastic experimental hybrid method for color isochromatics is developed. In this case, two fringe orders are enough for the experimental data of photoelastic experimental hybrid method for color isochromatics. Applying the method to stress concentration problems, its validity is confirmed. In the precision, the photoelastic experimental hybrid method for color isochromatics is better than the photoelastic experimental hybrid method for white and black isochromatics when fringe orders of isochromatics are few. When fringe orders are few, the photoelastic experimental hybrid method for color isochromatics can be used to analyze stress through few fringe orders of isochromatics.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.195-200
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• 2004

In this paper we propose effective speech recognizer through two recognition experiments. In general, SVM is classification method which classify two class set by finding voluntary nonlinear boundary in vector space and possesses high classification performance under few training data number. In this paper we compare recognition performance of HMM and SVM at training data number and investigate recognition performance of each feature parameter while changing feature space of MFCC using Independent Component Analysis(ICA) and Principal Component Analysis(PCA). As a result of experiment, recognition performance of SVM is better than 1:.um under few training data number, and feature parameter by ICA showed the highest recognition performance because of superior linear classification.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.68-74
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• 2019

Along with the deeper architecture in the deep learning approaches, the need for the data becomes very big. In the real problem, to get huge data in some disciplines is very costly. Therefore, learning on limited data in the recent years turns to be a very appealing area. Meta-learning offers a new perspective to learn a model with this limitation. A state-of-the-art model that is made using a meta-learning framework, Meta-SGD, is proposed with a key idea of learning a hyperparameter or a learning rate of the fast adaptation stage in the outer update. However, this learning rate usually is set to be very small. In consequence, the objective function of SGD will give a little improvement to our weight parameters. In other words, the prior is being a key value of getting a good adaptation. As a goal of meta-learning approaches, learning using a single gradient step in the inner update may lead to a bad performance. Especially if the prior that we use is far from the expected one, or it works in the opposite way that it is very effective to adapt the model. By this reason, we propose to add a weight term to decrease, or increase in some conditions, the effect of this prior. The experiment on few-shot learning shows that emphasizing or weakening the prior can give better performance than using its original value.

• English Language & Literature Teaching
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• v.12 no.4
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• pp.253-276
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• 2006

The purpose of this study is to compare and analyze the aspects of task-based materials in high school English textbooks for first year students in Korea. Based on the theoretical backgrounds for designing communicative tasks and the basic contents of the 7th national curriculum for English, a total of six different qualitative evaluation categories of task-based materials are constructed. The six categories include input data, settings, activity types, language skills, activity themes, and communicative functions. The results of the data analysis showed that the regulations of the 7th national English curriculum, which were aimed at improving the students' communicative abilities, were properly reflected in the materials of task-based activities of all textbooks. On the other hand, a few problems were found in some textbooks: too many individual tasks; being out of proportion in presenting task types and themes; non-systematic introduction of language skills, etc. To conclude, a few suggestions are made to provide some meaningful considerations for the text material developers in order to produce better textbooks in the future: task goals and rationale that encourage the learner's positive motivation; authenticity of input data based on the real-world context; a collaborative learning environment that enhances communicative interaction; a proportional representation of the various activity types including creative problem-solving procedures; systematic introduction of integrated language skills, etc.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.1
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• pp.88-99
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• 2003

The body changes of the elderly women are the forward tilt of the neck and shoulder point shrinkage of the spinal column, and protrusive abdomen. Unfortunately, few data based on body measurements for elderly women existed and a few studies are limited to the body figure of the elderly women. If these changes are not applied to the manufacturing of the clothing, almost of the elderly women will be unfitted with their clothing. So to improve the fitting of the elderly women, it is necessary to use the standard size systems for elderly women. This report is the first study to develop the standard tables of body measurements to be used for improving the fit of garments and patterns for women aged 60 and older. This study drew from anthropometric measurements of 337 and photographic measurements of 276 women aged 60 and older. It described the protocol of anthropometric measurement, the comparison between the measured data and the data on which National anthropometric survey of Korea 1997 is based, and the development of body measurement standard tables for elderly women. And we also considered the regional difference of body dimensions in order to develop the national size standards for elderly women. Further study would include the classification of body dimensions and description of each figure type for sizing apparel of women aged 60 and older.

• Journal of Information Science Theory and Practice
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• v.8 no.3
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• pp.77-90
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• 2020

This study analyzes N=181 social media rumors from Bangladesh to find out the most popular themes, sources, and aims. The result shows that social media rumors have seven popular themes: political, health & education, crime & human rights, religious, religiopolitical, entertainment, and other. Also, online media and mainstream media are the two main sources of social media rumors, along with three tentative aims: positive, negative, and unknown. A few major findings of this research are: Political rumors dominate social media, but its percentage is decreasing, while religion-related rumors are increasing; most of the social media rumors are negative and emerge from online media, and social media itself is the dominant online source of social media rumors; and, most of the health-related rumors are negative and surge during a crisis period, such as the COVID-19 pandemic. This paper identifies some of its limitations with the data collection period, data source, and data analysis. Providing a few research directions, this study also elucidates the contributions of its results in academia and policymaking.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.664-671
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• 2023

최근 다양한 거대 언어모델(Large Language Model)들이 개발되면서 프롬프트 엔지니어링의 대한 다양한 연구가 진행되고 있다. 본 논문에서는 퓨삿 학습 환경에서 개체명 인식의 성능을 높이기 위해서 제안된 템플릿이 필요 없는 프롬프트 튜닝(Template-free Prompt Tuning) 방법을 이용하고, 이 방법에서 사용된 라벨 단어 집합 생성 방법에 Maximal Marginal Relevance 알고리즘을 적용하여 해당 개체명에 대해 보다 다양하고 구체적인 라벨 단어 집합을 생성하도록 개선하였다. 실험 결과, 'LOC' 타입을 제외한 나머지 개체명 타입에서 'PER' 타입은 0.60%p, 'ORG' 타입은 4.98%p, 'MISC' 타입은 1.38%p 성능이 향상되었고, 전체 개체명 인식 성능은 1.26%p 향상되었다. 이를 통해 본 논문에서 제안한 라벨 단어 집합 생성 기법이 개체명 인식 성능 향상에 도움이 됨을 보였다.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.88-92
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• 2007

In this paper, an SS-RRA protocol that is based on Code Division Multiple Access is proposed and analyzed under the integrated voice and data traffic load. The backward logical channels consist of slotted time division frames with multiple spreading codes per slot. The protocol uses a reservation mechanism for the voice traffic, and a random access scheme for the data traffic. A discrete-time, discrete-state Markov chain is used to evaluate the performance. The numerical results show that the performance can be significantly improved by a few distinct spreading codes.