• Journal of KIISE:Software and Applications
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• v.29 no.7
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• pp.510-520
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• 2002

This paper proposes a transformation-based approach to design constraint-based analyses for Java at a coarser granularity. In this approach, we design a less or equally precise but more efficient version of an original analysis by transforming the original construction rules into new ones. As applications of this rule transformation, we provide two instances of analysis design by rule-transformation. The first one designs a sparse version of class analysis for Java and the second one deals with a sparse exception analysis for Java. Both are designed based on method-level, and the sparse exception analysis is shown to give the same information for every method as the original analysis.

• The Journal of the Acoustical Society of Korea
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• v.31 no.1
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• pp.39-50
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• 2012

A voice transformation (VT) method that can make the utterance of a source speaker mimic that of a target speaker is described. Speaker individuality transformation is achieved by altering three feature parameters, which include the LPC cepstrum, pitch period and gain. The main objective of this study involves construction of an optimal sequence of features selected from a target speaker's database, to maximize both the correlation probabilities between the transformed and the source features and the likelihood of the transformed features with respect to the target model. A set of two-pass conversion rules is proposed, where the feature parameters are first selected from a database then the optimal sequence of the feature parameters is then constructed in the second pass. The conversion rules were developed using a statistical approach that employed a maximum likelihood criterion. In constructing an optimal sequence of the features, a hidden Markov model (HMM) was employed to find the most likely combination of the features with respect to the target speaker's model. The effectiveness of the proposed transformation method was evaluated using objective tests and informal listening tests. We confirmed that the proposed method leads to perceptually more preferred results, compared with the conventional methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.63-70
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• 2013

In previous research, we suggested a business process structured query language(BPSQL) for information extraction and retrieval in the business process framework, and used an existing query language with the tablization for each layer within the framework, but still had a problem to manually build with the specification of each layer information of BFP. To solve this problem, we suggest automatically to build the schema based business process model with model-to-text conversion technique. This procedure consists of 1) defining each meta-model of the entire structure and of database schema, and 2) also defining model transformation rules for it. With this procedure, we can automatically transform from defining through meta-modeling of an integrated information system designed to the schema based model information table specification defined of the entire layer each layer specification with model-to-text conversion techniques. It is possible to develop the efficiently integrated information system.

• Journal of architectural history
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• v.8 no.3 s.20
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• pp.75-89
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• 1999

Under the WTO system, global standardization of professionalism in architecture practice calls for transformation of curriculum in architectural education in Korea. This paper compares the curriculum standards of international accrediting authorities such as NAAB and RIBA based on UIA accord which defines fundamental knowledge and abilities of an architect. As a result this paper extracts 51 achievement oriented criteria of architectural education in Korea. It can be categorized as communication, design, cultural context(history and theory, human behavior and social aspects), technical systems(structural systems, environmental control systems, construction material and assemblies) and practice(project process, project economics and business management, laws and regulations). Based on this recommended Korean curriculum standards, current curriculum is analyzed focusing on the 5 architectural programs in Seoul. Through this analysis, it became clear that some area - social and economic aspects in architecture, sustainability in architecture, understanding and selection of construction material, assemblies and environmental control system, recycling of existing building, professional liability, professional rules of conduct, project economics and project management - need to be covered and emphasized to meet the international standards in professional education in architecture. The result in this paper will be used as a basic data in the process of finding the direction of restructuring curriculum for professional architectural education in Korea.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.381-386
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• 2023

Many existing test case generation researchers extract test cases from models. However, research on generating test cases from natural language requirements is required in practice. For this purpose, the combination of natural language analysis and requirements engineering is very necessary. However, Requirements analysis written in Korean is difficult due to the diverse meaning of sentence expressions. We research test case generation through natural language requirement definition analysis, C3Tree model, cause-effect graph, and decision table steps as one of the test case generation methods from Korean natural requirements. As an intermediate step, this paper generates test cases from C3Tree model-based decision tables using meta-modeling. This method has the advantage of being able to easily maintain the model-to-model and model-to-text transformation processes by modifying only the transformation rules. If an existing model is modified or a new model is added, only the model transformation rules can be maintained without changing the program algorithm. As a result of the evaluation, all combinations for the decision table were automatically generated as test cases.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.865-872
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• 2013

Two-level morphology analysis method is one of rule-based morphological analysis method. This approach handles morphological transformation using rules and analyzes words with morpheme connection information in a lexicon. It is independent of language and Korean Two-level system was also developed. But, it was limited in practical use, because of using very small set of lexicon built manually. And it has also a over-generation problem. In this paper, we propose an automatic construction method of Korean Two-level lexicon for PC-KIMMO from morpheme tagged corpus. We also propose a method to solve over-generation problem using lexical information and sub-tags. The experiment showed that the proposed method reduced over-generation by 68% compared with the previous method, and the performance increased from 39% to 65% in f-measure.

• Journal for History of Mathematics
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• v.24 no.1
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• pp.15-29
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• 2011

This study was carrying out research on the geometry of Sulbas${\={u}}$tras as parts of looking for historical roots of oriental mathematics, The Sulbas${\={u}}$tras(rope's rules), a collection of Hindu religious documents, was written between Vedic period(BC 1500~600). The geometry of Sulbas${\={u}}$tras in ancient India was studied to construct or design for sacrificial rite and fire altars. The Sulbas${\={u}}$tras contains not only geometrical contents such as simple statement of plane figures, geometrical constructions for combination and transformation of areas, but also algebraic contents such as Pythagoras theorem and Pythagorean triples, irrational number, simultaneous indeterminate equation and so on. This paper examined the key features of the geometry of Sulbas${\={u}}$tras and the geometry of Sulbas${\={u}}$tras for the construction of the sacrificial rite and the fire altars. Also, in this study we compared geometry developments in ancient India with one of the other ancient civilizations.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.403-421
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• 2021

Most of the urban tunnels in Korea, which are represented by the 1st to 3rd subways, use the drainage tunnel by NATM. Recently, when a construction project that actively utilizes large-scale urban space is promoted, negative effects that do not conform to the existing empirical rules of urban tunnels may occur. In particular, there is a high possibility that groundwater fluctuations and hydrodynamic behavior will occur owing to the practice of tunnel technology in Korea, which has mainly applied the drainage tunnel. In order to solve the problem of the drainage tunnel, attempts are being made to control groundwater fluctuations. For this, the establishment of tunnel groundwater management standard concept and the analysis of the tunnel hydraulic behavior were performed. To prevent the problem of groundwater fluctuations caused by the construction of large-scale tunnels in urban areas, it was suggested that the conceptual transformation of the empirical technical practice, which is applied only in the underground safety impact assessment stage, to the direction of controlling the inflow in the tunnel, is required. And the relationship between the groundwater level and the inflow of the tunnel required for setting the allowable inflow when planning the tunnel was derived. The introduction of a tunnel groundwater management concept is expected to help solve problems such as groundwater fluctuations, ground settlement, depletion of groundwater resources, and decline of maintenance performance in various urban deep tunnel construction projects to be promoted in the future.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.