• Journal of Korean language education
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• v.28 no.2
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• pp.61-88
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• 2017

This paper seeks to use case studies of training programs for teachers at US K-12 schools to provide a model for developing training programs in South Korea for Korean language teachers overseas, and to consider directions for the future. Toward the end, we review examples of professional development programs for Korean language instructors at US K-12 schools that we have developed and conducted between 2011 and 2016. By comparing these programs with the results of post-program assessments, we explore ways of improving those programs. To respect teachers' wishes, these training programs have attempted to strike a balance between cultural and linguistic education while focusing more on workshops, debates, and field trips than on theoretical lectures. The difficulty of operating such programs is the difference in the teachers' individual circumstances and educational context, which necessitates giving teachers an opportunity to discuss the content of the program and find ways to apply it to their own circumstances. To resolve such difficulties, the training programs that we develop should avoid predetermined curriculums and should not be focused on simple drills or the trainer. Instead, these programs should take the approach of proactively incorporating contents desired by the participating teachers by starting with the situations, needs, and tasks of each of those teachers.

• Journal of Korean language education
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• v.29 no.4
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• pp.255-294
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• 2018

The Buckwheat Season, evaluated as the best of Lee Hyo-seok's literature, is one of the short stories that represent Korean literature. However, vivid literary expressions such as lyrical and beautiful depictions, figurative expressions and dialects, which show the Korean beauty, rather make learners have difficulty and become a factor that fails in reading comprehension. Thus, it is necessary to revise and present the text modified for the learners' language level. The methods of revising a literary text include the revision of linguistic elements such as cryptic vocabulary or sentence structure and the revision of the composition of the text, e.g. suggestion of characters or plot, or insertion of illustration. The methods of revising the language of the text can be divided into methods of simplification and detailing. However, in the process of revising the text, many depend on the adapter's subjective perception, not revising it with objective criteria. This paper revised the text, utilizing by the Academy of Korean Studies, , and the by the National Institute of Korean Language to secure objectivity in revising the text.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.1
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• pp.29-34
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• 2021

The real-time video education is used as an effective method of operating classes that replaces face-to-face education of instructors and learners in remote areas. However, the existing video call and video conferences system is mainly used, and this is effective in linguistic education because it focuses on lecture through video, but it is not utilized in other education. In this paper, we propose a design model of real-time video system that can improve the effectiveness of science curriculum and mathematics education by providing the functions that can be utilized during class by improving limitations of image - oriented image education.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3390-3405
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• 2022

Long Short-Term Memory (LSTM) combined with attention mechanism is extensively used to generate semantic sentences of images in image captioning models. However, features of salient regions and spatial information are not utilized sufficiently in most related works. Meanwhile, the LSTM also suffers from the problem of underutilized information in a single time step. In the paper, two innovative approaches are proposed to solve these problems. First, the Synergy-Gated Attention (SGA) method is proposed, which can process the spatial features and the salient region features of given images simultaneously. SGA establishes a gated mechanism through the global features to guide the interaction of information between these two features. Then, the Recurrent Fusion LSTM (RF-LSTM) mechanism is proposed, which can predict the next hidden vectors in one time step and improve linguistic coherence by fusing future information. Experimental results on the benchmark dataset of MSCOCO show that compared with the state-of-the-art methods, the proposed method can improve the performance of image captioning model, and achieve competitive performance on multiple evaluation indicators.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2718-2731
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• 2023

This paper presents a method of using syntax and shallow semantic analysis for Vietnamese question generation (QG). Specifically, our proposed technique concentrates on investigating both the syntactic and shallow semantic structure of each sentence. The main goal of our method is to generate questions from a single sentence. These generated questions are known as factoid questions which require short, fact-based answers. In general, syntax-based analysis is one of the most popular approaches within the QG field, but it requires linguistic expert knowledge as well as a deep understanding of syntax rules in the Vietnamese language. It is thus considered a high-cost and inefficient solution due to the requirement of significant human effort to achieve qualified syntax rules. To deal with this problem, we collected the syntax rules in Vietnamese from a Vietnamese language textbook. Moreover, we also used different natural language processing (NLP) techniques to analyze Vietnamese shallow syntax and semantics for the QG task. These techniques include: sentence segmentation, word segmentation, part of speech, chunking, dependency parsing, and named entity recognition. We used human evaluation to assess the credibility of our model, which means we manually generated questions from the corpus, and then compared them with the generated questions. The empirical evidence demonstrates that our proposed technique has significant performance, in which the generated questions are very similar to those which are created by humans.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.99-107
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• 2024

In AI image generation tools, most general users must use an effective prompt to craft queries or statements to elicit the desired response (image, result) from the AI model. But we are software engineers who focus on software processes. At the process's early stage, we use informal and formal requirement specifications. At this time, we adapt the natural language approach into requirement engineering and toon engineering. Most Generative AI tools do not produce the same image in the same query. The reason is that the same data asset is not used for the same query. To solve this problem, we intend to use informal requirement engineering and linguistics to create a toon. Therefore, we propose a sequence diagram and image generation mechanism by analyzing and applying key objects and attributes as an informal natural language requirement analysis. Identify morpheme and semantic roles by analyzing natural language through linguistic methods. Based on the analysis results, a sequence diagram and an image are generated through the diagram. We expect consistent image generation using the same image element asset through the proposed mechanism.

• Journal of KIISE:Software and Applications
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• v.35 no.9
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• pp.554-561
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• 2008

Prediction technique of user's intention can be used as a post-processing method for reducing the search space of an automatic speech recognizer. Prediction technique of system's intention can be used as a pre-processing method for generating a flexible sentence. To satisfy these practical needs, we propose a statistical model to predict speakers' intentions that are generalized into pairs of a speech act and a concept sequence. Contrary to the previous model using simple n-gram statistic of speech acts, the proposed model represents a dialogue history of a current utterance to a feature set with various linguistic levels (i.e. n-grams of speech act and a concept sequence pairs, clue words, and state information of a domain frame). Then, the proposed model predicts the intention of the next utterance by using the feature set as inputs of CRFs (Conditional Random Fields). In the experiment in a schedule management domain, The proposed model showed the precision of 76.25% on prediction of user's speech act and the precision of 64.21% on prediction of user's concept sequence. The proposed model also showed the precision of 88.11% on prediction of system's speech act and the Precision of 87.19% on prediction of system's concept sequence. In addition, the proposed model showed 29.32% higher average precision than the previous model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.1
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• pp.59-73
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• 2003

As a means of overcoming the linguistic barrier between different languages in the Internet, a new sign-language communication system with CG animation techniques has been developed and proposed. In the system, the joint angles of the arms and the hands corresponding to the gesture as a non-verbal communication tool have been considered. The emotional expression, however, could as play also an important role in communicating each other. Especially, a comic expression is more efficient than real facial expression, and the movements of the cheeks and the jaws are more important AU's than those of the eyebrow, eye, mouth etc. Therefore, in this paper, we designed a 3D emotion editor using 2D model, and we extract AU's (called as PAU, here) which play a principal function in expressing emotions. We also proposed a method of generating the universal emotional expression with Avatar models which have different vertex structures. Here, we employed a method of dynamically adjusting the AU movements according to emotional intensities. The proposed system is implemented with Visual C＋＋ and Open Inventor on windows platforms. Experimental results show a possibility that the system could be used as a non-verbal communication means to overcome the linguistic barrier.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.426-436
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• 2022

This study aimed to explore the role of models and reformulations as feedback to English writing in L2 learners' noticing and their writing. 92 participants were placed into three groups; a models group (MG), a reformulations group (RG), a control group (CG), involved in a three-stage writing task. In stage 1, they were asked to perform a 1st draft of writing, while taking notes on the problems they experienced. In stage 2, the MG was asked to compare their writing with a model text and the RG with a reformulated version of it. They were instructed to write down whatever they noticed in their comparison. The CG was asked to just read their writing. In stage 3, all the participants attempted subsequent revisions. The results indicated that all the participants noticed problematic linguistic features the most in a lexical category, and models and reformulations led to higher rate of noticing the problematic linguistic features reported in stage 1 and contributed to subsequent revisions. It was also revealed that the MG and RG significantly improved with their writings of MG and RG on the post-writing test. The findings imply that models and reformulations result in better performance in L2 writing and should be promoted in an English writing class.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.36 no.1
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• pp.54-59
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• 2000

This paper presents a control system that uses a fuzzy algorithm in controlling the depth of a model midwater trawl net, and experimental results carried out in the circulating water channel by using a model trawl winch system.The fuzzy controller calculates the length of the warp to be changed, based on the depth error between the desired depth and actual depth of the model trawl net and the ratio of change in the depth error. The error and the error change are calculated every sampling time. Then the control input, i.e. desirable length of the warp, is determined by inference from the linguistic control rules which an experienced captain or navigator uses in controlling the depth of the trawl winch controller and the length of the warp is changed. Two kinds of fuzzy control rules were tested, one was obtained from the actual operations used by a skilled skipper or navigator, and the other was a modified from the former by considering the hydrodynamic characteristics of the model trawl system.Two kinds of fuzzy control were tested, one was obtained fro the actual operations used by a skilled skipper or navigator, and the other was a modified from the former by considering the hydrodynamic characteristics of the model trawl system.The results of these model experiments indicate that the proposed fuzzy controllers rapidly follow the desired depth without steady-state error although the desired depth was given in one step, and show robustness properties against changes in the parameters such as the change of the towing sped. Especially, a modified rule shows smaller depth fluctuations and faster setting times than those obtained by a field oriented rule.