• The Journal of the Acoustical Society of Korea
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• v.21 no.4E
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• pp.146-155
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• 2002

We present a new technique for achieving source separation when given only a single charmel recording. The main idea is based on exploiting the inherent time structure of sound sources by learning a priori sets of time-domain basis functions that encode the sources in a statistically efficient manner. We derive a learning algorithm using a maximum likelihood approach given the observed single charmel data and sets of basis functions. For each time point we infer the source parameters and their contribution factors. This inference is possible due to the prior knowledge of the basis functions and the associated coefficient densities. A flexible model for density estimation allows accurate modeling of the observation, and our experimental results exhibit a high level of separation performance for simulated mixtures as well as real environment recordings employing mixtures of two different sources. We show separation results of two music signals as well as the separation of two voice signals.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.115-119
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• 2007

Huge amount of useful information is getting added to the academic digital world everyday, This digitalized information is heterogeneous and remained limited to a local domain only. How to integrate and share this scattered knowledge with simplicity remained a big challenge. In this paper, we propose a prototype of web application for accomplishing above task using web 2.0 features; it makes traditional academic digital libraries to form as a special case of collaborative environment. This application enables users to customize their own resources to form their own virtual digital library. Further users can utilize personalized information of other users working in similar research domain to form true collaborative environment. The model and framework for the new look of academic digital library is presented.

• Journal of Educational Research in Mathematics
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• v.9 no.2
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• pp.459-471
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• 1999

This study is to develop a mathematics assessment framework based on the mathematics assessment framework and content strands suggested by KEDI, NCTM, NAEP, TIMSS, Oregon State, New Zealand. According to the literature review, there has been more emphasis that students themselves 'communicate' what they 'understood' and how they 'thought' during the situation of 'solving problems'. As a result, communication ability is considered one of the most important factors in assessment situation, which always accompany the abilities of understanding, thinking, problem-solving, etc. In conclusion, the framework related to mathematical knowledge consists of content and behavior domains. The content domain is categorized into 6 content areas of the 7th mathematics curriculum, and the behavior domain is divided into computation, understanding, inference, problem-solving, and communication.

• Korean Journal of Child Studies
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• v.13 no.2
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• pp.65-81
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• 1992

The purpose of this study was to investigate children's conceptions about gender and the relation between gender conceptions and preference for gender related tasks. 130 children were interviewed about gender and gender related tasks. Data were analyzed with the component model of gender schema. Results indicated that children's gender schema in the attitudes domain was significantly different with age in all components but not different with sex. The gender schema in the knowledge domain was significantly different with age in within component and between component links, and with sex in the gender label-component and within component links. The difference between the gender inhibitory score and gender facilitative score was significantly different with age, sex, and children's gender schema. The findings that gender schema influenced the children's preferences for gender related tasks suggests a theoretical rationale of gender schema theory.

• East Asian mathematical journal
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• v.29 no.2
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• pp.207-239
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• 2013

This research is a study on student's understanding fundamental concepts of mathematical curriculum, especially in geometry domain. The goal of researching is to analyze student's concepts about that domain and get the mathematical teaching methods. We developed various questions of descriptive assessment. Then we set up the term, procedure of research for the understanding student's knowledge of geometric figures. And we analyze the student's understanding extent through investigating questions of descriptive assessment. In this research, we concluded that most of students are having difficulty with defining the fundamental concepts of mathematics, especially in geometry. Almost all the students defined the fundamental conceptions of mathematics obscurely and sometimes even missed indispensable properties. And they can't distinguish between concept definition and concept image. Prior to this study, we couldn't identify this problem. Here are some suggestions. First, take time to reflect on your previous mathematics method. And then compile some well-selected questions of descriptive assessment that tell us more about student's understanding in geometric concepts.

• Proceedings of the KSPS conference
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• 2006.11a
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• pp.24-27
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• 2006

This paper describes how a domain dependent pronunciation lexicon is generated and optimized for Korean large vocabulary continuous speech recognition(LVCSR). At the level of lexicon, pronunciation variations are usually modeled by adding pronunciation variants to the lexicon. We propose the criteria for selecting appropriate pronunciation variants in lexicon: (i) likelihood and (ii) frequency factors to select variants. Our experiment is conducted in three steps. First, the variants are generated with knowledge-based rules. Second, we generate a domain dependent lexicon which includes various numbers of pronunciation variants based on the proposed criteria. Finally, the WERs and RTFs are examined with each lexicon. In the experiment, 0.72% WER reduction is obtained by introducing the variants pruning criteria. Furthermore, RTF is not deteriorated although the average number of variants is higher than that of compared lexica.

• BMB Reports
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• v.47 no.7
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• pp.405-410
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• 2014

ZBTB3 belongs to the Zinc finger and BTB/POZ domain containing transcription factor family; however, its biological role has rarely been studied. We demonstrate for the first time, to our knowledge, that ZBTB3 is an essential factor for cancer cell growth via the regulation of the ROS detoxification pathway. Suppression of ZBTB3 using two different short hairpin RNAs in human melanoma, lung carcinoma, and breast carcinoma results in diminished cell growth. In addition, we found that suppression of ZBTB3 activates a caspase cascade, including caspase-9, -3, and PARP leading to cellular apoptosis, resulting from failed ROS detoxification. We identified that ZBTB3 plays an important role in the gene expression of ROS detoxification enzymes. Our results reveal that ZBTB3 may play a critical role in cancer cell growth via the ROS detoxification system. Therefore, therapeutic strategies that target ZBTB3 could be used in selective cancer treatments.

• Bulletin of the Society of Naval Architects of Korea
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• v.25 no.1
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• pp.56-62
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• 1988

Artificial Intelligence(AI) is that branch of computer science that deals with designing computer system that exhibit some of the characteristics associated with intelligence on human behaviors such as, understanding natural language, reasoning, solving problems, robotics and so on. The most developed component of artificial intelligence today is probably the expert system. An expert system is defined as a computer program that embodies organized knowledge concerning some specific domain of human expertise and programmed to perform convincingly as an advisory consultant in the given domain with self-explanation of reasoning on demand. This paper describes general concept of artificial intelligence and expert system and investigates applicability of expert system to ship design.

• The Journal of the Acoustical Society of Korea
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• v.21 no.4
• /
• pp.146-146
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• 2002

We present a new technique for achieving source separation when given only a single channel recording. The main idea is based on exploiting the inherent time structure of sound sources by learning a priori sets of time-domain basis functions that encode the sources in a statistically efficient manner. We derive a learning algorithm using a maximum likelihood approach given the observed single channel data and sets of basis functions. For each time point we infer the source parameters and their contribution factors. This inference is possible due to the prior knowledge of the basis functions and the associated coefficient densities. A flexible model for density estimation allows accurate modeling of the observation, and our experimental results exhibit a high level of separation performance for simulated mixtures as well as real environment recordings employing mixtures of two different sources. We show separation results of two music signals as well as the separation of two voice signals.

• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.9-17
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• 2019

As the artificial intelligence technology has developed recently, researches on chatbots that provide information and contents desired by users through an interactive interface have become active. Since chatbots require a variety of natural language processing technology and domain knowledge including typos and slang, it is currently limited to develop chatbots that can carry on daily conversations in a general-purpose domain. In this study, we propose an artificial intelligence chatbot that can provide real-time public traffic information and route information. The proposed chatbot has an advantage that it can understand the intention and requirements of the user through the conversation on the messenger platform without map application.