• Annals of Clinical Neurophysiology
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• v.8 no.2
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• pp.163-170
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• 2006

Backgrounds: MEG can measure the task-specific neurophysiologic activity with good spatial and time resolution. Language lateralization using noninvasive method has been a subject of interest in resective brain surgery. We purposed to develop a paradigm for language lateralization using MEG and validate its feasibility. Methods: Magnetic fields were obtained in 12 neurosurgical candidates and one volunteer for language tasks, with a 306 channel whole head MEG. Language tasks were word listening, reading and picture naming. We tested two word listening paradigms: semantic decision of meaning of abstract nouns, and recognition of repeated words. The subjects were instructed to silently name or read, and respond with pushing button or not. We decided language dominance according to the number of acceptable equivalent current dipoles (ECD) modeled by sequential single dipole, and the mean magnetic field strength by root mean square value, in each hemisphere. We collected clinical data including Wada test. Results: Magnetic fields evoked by word listening were generally distributed in bilateral temporoparietal areas with variable hemispheric dominance. Language tasks using visual stimuli frequently evoked magnetic field in posterior midline area, which made laterality decision difficult. Response during task resulted in more artifacts and different results depending on responding hand. Laterality decision with mean magnetic field strength was more concordant with Wada than the method with ECD number of each hemisphere. Conclusions: Word listening task without hand response is the most feasible paradigm for language lateralization using MEG. Mean magnetic field strength in each hemisphere is a proper index for hemispheric dominance.

• Proceedings of the Korean Society for Language and Information Conference
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• 1994.02a
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• pp.163-172
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• 1994

• Research in Mathematical Education
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• v.18 no.2
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• pp.149-170
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• 2014

The Vietnamese language has a specific property related to the zero in the name-number system. This study was conducted to examine the impact of linguistic differences and of the zero's position in a number on a transcoding task (verbal number into Arabic number). Vietnamese children and French-speaking Belgian children, from grades 3 to 6, participated in the study. The success rate and the type of errors they made varied, depending on their grade and language. At Grade 4, Vietnamese children showed performances equivalent to Grade 6 Belgian children. Our results confirmed the support provided by language to the understanding and performances in a transcoding task. Results also showed that a syntactic zero is easier to manipulate than a lexical zero for Vietnamese children. The relative influence of language and the source of errors are discussed.

• SUVANNABHUMI
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• v.14 no.1
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• pp.193-228
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• 2022

This study investigates the production and perception of Vietnamese tones by Japanese, Lao, and Taiwanese second language (L2) learners [n=30], comparing their performance in an Imitation task to that of Identification and Read-Aloud tasks. The results show that the Imitation task is generally easier for L2 speakers than the Identification and Read-Aloud tasks, suggesting that imitation is performed without some of the skills required by the other two tasks. It is also found that Lao and Taiwanese speakers outperform Japanese speakers, suggesting that prior experience with one tone language facilitates the acquisition of tone in another language. The result on speakers' tonal range show that L2 leaners have significantly narrower tonal F0 range than control Vietnamese speakers [n=11]. The results of error pattern analysis and tonal transcription also suggest that non-modal voice (glottal stop and creakiness) and contour tones (bidirectional fall-rise) are more difficult for L2 learners than modal voice tones (e.g., unidirectional contours: rising, falling, and level).

• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.19-28
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• 2010

Recently, various home appliances are inter connected in wired/wireless network to provide a single service, but their interfaces are not uniformly integrated. In order to get a service in such an environment, users have to figure out how to control each appliance and the way of combining its functions with others. Even worse to the users, many buttons are barely used to control the complicated functions of the appliances on the remote controllers, and controllers have very similar shapes in each other. In this paper, based on the definitions of a task as a unit of services provided in the environment of multi-connected appliances, we propose a markup language for home appliances, called HAML (Home Appliance Markup Language), for generating task-based user interfaces to help controlling multi-connected appliances as one pleases. The proposed method generates interfaces by gathering the buttons frequently used and necessary for tasks, and provides automatic settings of multi-connected appliances. The proposed method is verified with an analysis of scenarios and usability tests.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.81-88
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• 2022

The major educational goal of reading part, which occupies important portion in Korean language in Korean SAT, is to evaluated whether a given text can be fully understood. Therefore given questions in the exam must be able to solely solvable by given text. In this paper we developed a datatset based on Korean SAT's reading part in order to evaluate whether a deep learning language model can classify if the given question is true or false, which is a binary classification task in NLP. In result, by applying language model solely according to the passages in the dataset, we were able to acquire better performance than 59.2% in F1 score for human performance in most of language models, that KoELECTRA scored 62.49% in our experiment. Also we proved that structural limit of language models can be eased by adjusting data preprocess.

• Journal of Gifted/Talented Education
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• v.22 no.2
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• pp.317-332
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• 2012

We investigated brain activity during the performance of the intelligence task by a science high school student group (n=8) and a foreign language high school student group (n=5). Both groups scored in the top 1% on intelligence tests (science high school group: RAPM mean score=34.0, WAIS mean IQ=139.6; foreign language high school group: RAPM mean score=33.8, WAIS mean IQ=147.2). Analysis of brain activity during the performance of the intelligence task showed that both groups had brain activity in certain areas, including the left and right prefrontal cortex, parietal cortex, and anterior cingulate. The science high school group showed the highest activity in the right parietal cortex, which is related to visuo-spatial working memory, whereas the foreign language high school group showed the highest activity in the left prefrontal cortex, which is related to verbal working memory. The foreign language high school group showed higher brain activity than the science high school group in the left precentral gyrus which is related to the motion of the tongue and lips. These results show that the science high school group utilized the visuo-spatial area, whereas the foreign language high school group utilized the verbal area during the performance of the intelligence task. This suggests that the major thinking process differs depending on the gifted students' primary field of study, although they are doing the same task.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.100-112
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• 1996

This paper presents a design experience of a control language for coordination of a multi-robot system. To effectively program job commands, a Petrinet-type Graphical Robot Language(PGRL) is proposed, where some functions, such as concurrency and synchronization, for coordination among tasks can be easily programmed.In our system, the proposed task commands of PGRL are implemented by employing formal model languages, which are composed of three modules, sensory, data handling, and action module. It is expected that by using our proposed PGRL and formal languages, one can easily describe a job or task, and hence can effectively operate a complex real-time and concurrent system. The control system is being implemented by using VME-based 32-bit microprocessor boards for supervisory, each module controller(arm, hand, leg, sensor data processing module) and a real time multi-tasking operating system(VxWorks). (author). 17 refs., 16 figs., 2 tabs.

• Phonetics and Speech Sciences
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• v.9 no.4
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• pp.1-7
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• 2017

It was shown in speech production studies that the preparation unit of spoken word production is language particular, such as onset phonemes for English and Dutch, syllables for Mandarin Chinese, and morae for Japanese. However, there have been inconsistent results on whether the onset phoneme is a planning unit of spoken word production in Korean. In this study, two sets of experiments investigated possible influences of task demands on the phonological preparation in native Korean adults, namely, implicit priming and word naming with the form preparation paradigm. Only the word naming task, but not the implicit priming task, showed a significant onset priming effect, even though there were significant syllable priming effects in both tasks. Following the attentional theory ($O^{\prime}S{\acute{e}}aghdha$ & Frazer, 2014), these results suggest that task demands might play a role in the absence/presence of onset priming effects in Korean. Native Korean speakers could maintain their attention to the shared onset phonemes in word naming, which is not very demanding, while they have difficulties in allocating their attention to such units in a more cognitive-demanding implicit priming, even though both tasks involve accessing phonological codes. These findings demonstrate that there are cross-linguistic differences in the first selectable unit in preparation of spoken word production, but within a single language, the preparation unit might not be immutable.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.308-310
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• 2022

With the rise of the Al wave, task-oriented dialogue systems have become one of the popular research directions in academia and industry. Currently, task-oriented dialogue systems mainly adopt pipelined form, which mainly includes natural language understanding, dialogue state decision making, dialogue state tracking and natural language generation. However, pipelining is prone to error propagation, so many task-oriented dialogue systems in the market are only for single-round dialogues. Usually single- domain dialogues have relatively accurate semantic understanding, while they tend to perform poorly on multi-domain, multi-round dialogue datasets. To solve these issues, we developed a paddle-based multi-domain task-oriented Chinese dialogue system. It is based on NEZHA-base pre-training model and CrossWOZ dataset, and uses intention recognition module, dichotomous slot recognition module and NER recognition module to do DST and generate replies based on rules. Experiments show that the dialogue system not only makes good use of the context, but also effectively addresses long-term dependencies. In our approach, the DST of dialogue tracking state is improved, and our DST can identify multiple slotted key-value pairs involved in the discourse, which eliminates the need for manual tagging and thus greatly saves manpower.