• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.1
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• pp.82-88
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• 2024

As the modern maritime industry rapidly progresses through technological advancements, data processing technology is emphasized as a key driver of this development. Natural language processing is a technology that enables machines to understand and process human language. Through this methodology, we aim to develop a model that predicts the proportions of outcomes when entering new written judgments by analyzing the rulings of the Marine Safety Tribunal and learning the cause-providing ratios of previously adjudicated ship collisions. The model calculated the cause-providing ratios of the accident using the navigation applied at the time of the accident and the weight of key keywords that affect the cause-providing ratios. Through this, the accuracy of the developed model could be analyzed, the practical applicability of the model could be reviewed, and it could be used to prevent the recurrence of collisions and resolve disputes between parties involved in marine accidents.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.13-23
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• 2022

In this study we leveraged a probing method to evaluate how a pre-trained L2 LSTM language model represents sentences with relative and coordinate clauses. The probing experiment employed adapted models based on the pre-trained L2 language models to trace the syntactic properties of sentence embedding vector representations. The dataset for probing was automatically generated using several templates related to different sentence structures. To classify the syntactic properties of sentences for each probing task, we measured the adaptation effects of the language models using syntactic priming. We performed linear mixed-effects model analyses to analyze the relation between adaptation effects in a complex statistical manner and reveal how the L2 language models represent syntactic features for English sentences. When the L2 language models were compared with the baseline L1 Gulordava language models, the analogous results were found for each probing task. In addition, it was confirmed that the L2 language models contain syntactic features of relative and coordinate clauses hierarchically in the sentence embedding representations.

• 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.

• Korean Journal of Radiology
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• v.24 no.10
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• pp.1038-1041
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• 2023

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.711-715
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• 2023

본 연구는 대부분의 언어 모델이 사용하고 있는 서브워드 토큰화 과정을 거치지 않고, 바이트 단위의 인코딩을 그대로 다룰 수 있는 토큰-프리 사전학습 언어모델에 대한 것이다. 토큰-프리 언어모델은 명시적인 미등록어 토큰이 존재하지 않고, 전 처리 과정이 단순하며 다양한 언어 및 표현 체계에 대응할 수 있는 장점이 있다. 하지만 관련 연구가 미흡, 서브워드 모델에 대비해 학습이 어렵고 낮은 성능이 보고되어 왔다. 본 연구에서는 한국어를 중심으로 토큰-프리 언어 이해-생성 모델을 사전 학습 후, 서브워드 기반 모델과 비교하여 가능성을 살펴본다. 또한, 토큰 프리 언어모델에서 지적되는 과도한 연산량을 감소시킬 수 있는 그래디언트 기반 서브워드 토크나이저를 적용, 처리 속도를 학습 2.7배, 추론 1.46배 개선하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.270-273
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• 2001

In this paper, we proposed the intelligent navigation agent model for successive electronic commerce management. For allowing intelligence, we used fuzzy theory. Fuzzy theory is very useful method where keywords have vague conditions and system must process that conditions. So, using theory, we proposed the model that can process the vague keywords effectively. Through the this, we verified that we can get the more appropriate navigation result than any other crisp retrieval keywords condition.

• Language and Information
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• v.2 no.1
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• pp.79-105
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• 1998

This paper aims to describe a German-Korean machine translation system for nominal phrases. Besides, we have two subgoals. First, we are going to revea linguistic differences between two languages and propose a language-informational method fo overcome the differences. The method is based on an integrated model of translation knowledge, efficient information structure, and concordance selection. Then, we will show the statistical results about translation experiment and its evaluation as an evidence for the adequacy of our linguistic method and translation system itself.

• ETRI Journal
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• v.42 no.1
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• pp.101-107
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• 2020

For Korean language processing, morphological analysis is a critical component that requires extensive work. This morphological analysis can be conducted in an end-to-end manner without requiring a complicated feature design using a sequence-to-sequence model. However, the sequence-to-sequence model has a time complexity of O(n²) for an input length n when using the attention mechanism technique for high performance. In this study, we propose a linear-time Korean morphological analysis model using a local monotonic attention mechanism relying on monotonic alignment, which is a characteristic of Korean morphological analysis. The proposed model indicates an extreme improvement in a single threaded environment and a high morphometric F1-measure even for a hard attention model with the elimination of the attention mechanism formula.

• Korean Management Science Review
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• v.11 no.2
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• pp.43-63
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• 1994

A new model management framework is proposed to accommodate wide-spreading algebraic modeling languages (AMLs), and to facilitate a full range of model manipulation functions. To incorporate different modeling conventions of the leading AMLs (AMPL, GAMS, and SML) homogeneously, generic model concepts are introduced as a conceptual basis and are embodied by the structural and operational constructs of an Object-Oriented Database Management System(ODBMS), enabling the framework to consolidate components of DSSs(database, modelbase, and associated solvers) in a single formalism effectively. Empowered by a database query language, the new model management framework can provide uniform model management commands to models represented in different AMLs, and effectively facilitate integration of the DSS components. A prototype system of the framework has been developed on a commercial ODBMS, ObjectStore, and a C++ programming language.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2175-2184
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• 2009

This paper describes operational analysis results of the DC micro-grid using detailed model of distributed generation. Detailed model of wind power generation, photo-voltaic generation, fuel-cell generation was implemented with the user-defined model of PSCAD/EMTDC software that is coded with C-language. The operation analysis was carried out using PSCAD/EMTDC software, in which the power circuit is implemented by built-in model and the controller is modelled by user-defined model that is also coded with C-language. Various simulation results confirm that the DC micro-grid can operate without any problem in both the interconnected mode and the islanded mode. The operation analysis result confirms that the DC micro-grid make it feasible to provide power to the load stably. And it can be utilize to develop the actual system design and building.