• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1986.04a
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• pp.119-124
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• 1986

This paper describes the development of the KORNET that may be regarded as the latest public packet-swiched computer communication network. The KORNET project included the development of the network management center (NMC), a network concentrator. For the KORNET we use the virtual circuit(VC) method, a distributed adaptive routing algorithm, and a dynamic buffer management algorithm. The NMC acts as a nerve center of the network, performing such function as network monitoring, subscriber and network management and routing management, etc. As for the NNP and NC hardware, we have implemented them with the 16-bit multitask/multiprocessor technology using MC68000 microprocessors. Softwares have been developed using C language is required for real time processing. All the network protocols we have developed comply completely with the latest CCITT recommendations including X.25, X,3 , X.28 and X.29.

• Ocean policy research
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• v.33 no.2
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• pp.123-145
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• 2018

Maritime tourism destinations need to improve image as well as enhance competitiveness through development of new marine tourism attraction due to the decrease of the number of passengers. The maritime city is trying to combine dynamic marine leisure activities as an alternative. For this purpose, it is possible to realize clear marine tourism activation policy and improve the identity of local community through the accurate analysis of the interest of the stakeholder groups of local residents in Songjeong beach in Busan. In this study, we first analyzed the language network based on the expression language related to the conflict between the stakeholders of Songjeong beach. Second, we analyzed the individual characteristics of the structure of conflict frames of stakeholders and suggested solutions by comparing the differences and similarities between perception frames of conflict parties. Third, we distinguish and compare differences of perception among the conflict parties through the detailed frame type. Based on the relationship structure between the detailed frame types of the conflict parties, we suggested an alternative for conflict resolution by restructuring the conflicts and negative perceptions among the stakeholders.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.119-126
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• 2024

In building information model (BIM), it is difficult to train an artificial intelligence (AI) model due to the lack of sufficient data about individual projects in an architecture firm. In this paper, we present a methodology to correctly train an AI neural network model based on a large language model (LLM) to predict the steel structure product weight ratios in BIM. The proposed method, with the aid of the LLM, can overcome the inherent problem of limited data availability in BIM and handle a combination of natural language and numerical data. The experimental results showed that the proposed method demonstrated significantly higher accuracy than methods based on a smaller language model. The potential for effectively applying large language models in BIM is confirmed, leading to expectations of preventing building accidents and efficiently managing construction costs.

• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.845-852
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• 2002

Electronic document processing using EDl (Electronic Data Interchange) must exchange documents using VAN (Value Added Network). However. the use of exclusive software needs alteration of a new document and the use of VAN(Value Added Network) demands an exchange of document and high cost for maintenance. Due to these problems, the existing EDI (Electronic Data Interchange) is turning into Web-based EDI (Electronic Data Interchange). This paper suggests techniques that change EDI (Electronic Data Interchange) messages which exist in two relational databases into XML (extensible Markeup Language) using the JDBC bridge. Also this paper proposes a method that recovers schema using converted XML (extensible Markeup Language) file, and a method which inserts an original record into a declared table. This solves the limitation of an original method that have to use sane database management system and also overcomes the problem in certain circumstances where the EDI (Electronic Data Interchange) exchange does not work.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.319-327
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• 2012

In this paper, we present a sign language recognition model which does not use any wearable devices for object tracking. The system design issues and implementation issues such as data representation, feature extraction and pattern classification methods are discussed. The proposed data representation method for sign language patterns is robust for spatio-temporal variances of feature points. We present a feature extraction technique which can improve the computation speed by reducing the amount of feature data. A neural network model which is capable of incremental learning is described and the behaviors and learning algorithm of the model are introduced. We have defined a measure which reflects the relevance between the feature values and the pattern classes. The measure makes it possible to select more effective features without any degradation of performance. Through the experiments using six types of sign language patterns, the proposed model is evaluated empirically.

• English Language & Literature Teaching
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• v.11 no.3
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• pp.113-137
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• 2005

The purpose of this research is to introduce a new pedagogy for developing English education in the university. It is based on the favorable results of the application of Network English, which is a method that has been used in three classes at Y University for a period of one semester. Network English is a kind of integrated teaching method of offline and online education, and can be a learner-oriented educational method. The online aspect gives learners easier access to the text, regardless of time and place. And in addition to the characteristic of online itself, the various contents in conformity with the learning ability of learners are provided in the text, in order that the learners can get and maintain a desire for study without losing their interest in English. Although the offline part is not much different from traditional classes, the offline education can complement the deficiency of the online and also offer the learners the opportunity for questions and answers. From the results of application of Network English in three classes, the students were satisfied with the method and have more interest in English, which resulted in better grades.

• Language and Information
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• v.10 no.1
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• pp.47-69
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• 2006

Recently, there has been a surge of interests concerning the construction and utilization of a Korean thesaurus. In this paper, a semi-automatic method for generating a lexical-semantic network of Korean '-ha' verbs is presented through an analysis of the lexical definitions of these verbs. Initially, through the use of several tools that can filter out and coordinate lexical data, pairs constituting a word and a definition were prepared for treatment in a subsequent step. While inspecting the various definitions of each verb, we extracted and coordinated the head words from the sentences that constitute the definition of each word. These words are thought to be the main conceptual words that represent the sense of the current verb. Using these head words and related information, this paper shows that the creation of a thesaurus could be achieved without any difficulty in a semi-automatic fashion.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.32-41
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• 2000

In this paper, we proposed a method which predict the verb by using the neural network in order to enhance communication rate in augmentative communication system for Korean language disorders. Each word is represented by an information vector according to syntax and semantics, and is positioned at the state space by being partitioned into various regions different from a dictionary-like lexicon. Conceptual similarity is realized through position in state space. When a symbol was pressed, we could find the word for the symbol at the position in the state space. In order to prevent verb prediction's redundancy according to input units, we predicted the verb after separating class using the neural network. In the result we can enhance $20\% communication rate in the restricted space

• Journal of the Korean Society of Earth Science Education
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• v.9 no.1
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• pp.65-87
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• 2016

The purpose of this study is to examine Korean journals related to science education in order to analyze research trends into Nature of science in Korea. The subject of the study is the level of Korean Citation Index (KCI-listed, KCI listing candidates), that can be searched by the key phrase, "Nature of science" in Korean language through the RISS service. In this study, the Descriptive Statistical Analysis Method is utilized to discover the number of research articles, classifying them by year and by journal. Also, the Sementic Network Analysis was conducted to Word Cloud Analysis the frequency of key words, Centrality Analysis, co-occurrence and Cluster Dendrogram Analysis throughout a variety of research articles. The results show that 91 research papers were published in 25 journals from 1991 to 2015. Specifically, the 2 major journals published more than 50% of the total papers. In relation to research fields., In addition, key phrases, such as 'Analysis', 'recognition', 'lessons', 'science textbook', 'History of Science' and 'influence' are the most frequently used among the research studies. Finally, there are small language networks that appear concurrently as below: [Nature of science - high school student - recognize], [Explicit - lesson - effect], [elementary school - science textbook - analysis]. Research topic have been gradually diversified. However, many studies still put their focus on analysis and research aspects, and there have been little research on the Teaching and learning methods.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.87-96
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• 2023

ChatGPT, a leader in generative AI, can use natural expressions like humans based on large-scale language models (LLM). The ability to grasp the context of the language and provide more specific answers by algorithms is excellent. It also has high-quality conversation capabilities that have significantly developed from past Chatbot services to the level of human conversation. In addition, it is expected to change the operation method of the tourism industry and improve the service by utilizing ChatGPT, a generative AI in the tourism sector. This study was conducted to explore ChatGPT trends and paradigms in tourism. The results of the study are as follows. First, keywords such as tourism, utilization, creation, technology, service, travel, holding, education, development, news, digital, future, and chatbot were widespread. Second, unlike other keywords, service, education, and Mokpo City data confirmed the results of a high degree of centrality. Third, due to CONCOR analysis, eight keyword clusters highly relevant to ChatGPT in the tourism sector emerged.