• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.706-710
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• 2006

Recently, several studies have been carried on knowledge flow of science, technology, industry to establish STI policy. Still it is lack of studies on relationship of science-industry although there have been studied only in aspect of science-technology relationship or technology-industry relationship. This paper's purpose is to propose method to measure knowledge flow among science, technology, and industry by means of patent citation. After gathering knowledge flow data between science and technology through mapping citing patent and cited paper, it gets knowledge flows data between technology-industry by using OTC (OECD Technology Concordance), technology-industry mapping program. Basd on 2 types of knowledge flow data, it propose method to examine knowledge flow from science to industry by applying overlap function is a network link weight function.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2006.11b
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• pp.323-337
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• 2006

Recently, several studies have been carried on knowledge flow of science, technology, industry to establish STI policy. Still it is in need of studies on relationship of science-industry although there have been studied only in aspect of science-technology relationship or technology-industry relationship. This paper's purpose is to propose method to measure knowledge flow among science, technology, and industry by means of patent citation by USPTO. After gathering knowledge flow data between science and technology through mapping citing patent and cited pater, it gets knowledge flows data between technology-industry by using OTC (OECD Technology Concordance), technology-industry mapping program. Based on these knowledge flow data, it examines knowledge flow science to industry by applying overlap function that is a network link weight function.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3539-3547
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• 1999

Korean linguistic information for the generation modulo of KANT(Knowledge-based Accurate Natural language Translation) system was constructed. As KANT has a language-independent generation engine, the construction of Korean linguistic information means the development of the Korean generation module. Constructed information includes concept-based mapping rules, category-based mapping rules, syntactic lexicon, template rules, grammar rules based on the unification grammar, lexical rules and rewriting rules for Korean. With these information in sentences were successfully and completely generated from the interlingua functional structures among the 118 test set prepared by the developers of KANT system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.2
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• pp.96-103
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• 2010

This paper studies the performance of STTC with minimum Hamming distance (MHD) mapping in order to improve the bit error rate (BER) performance. Unfortunately, the MHD mapping used in trellis coded modulation (TCM) or multiple trellis coded modulation (MTCM) cannot be directly applied to STTC because the trellis structure of STTC is generally different from that of TCM or MTCM. Therefore, we need a simple modification to apply the MHD mapping concept in STTC. The core of the modification assigns information bits with a Hamming distance in proportion to the sum of the Euclidean distance to trellis branch of STTC. To the best knowledge, this combination has not been considered yet. The BER performance is examined with simulations and the performance of MHD mapping is compared to that of well known natural mapping and Gray mapping on both fast Rayleigh as well as fast Rician fading channels. It is shown that the performance of MHD mapping is much better than that of natural mapping or Gray mapping over fast Rician fading channels, especially.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.1-10
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• 2014

In recent years, the research of 3D mapping technique in urban environments obtained by mobile robots equipped with multiple sensors for recognizing the robot's surroundings is being studied actively. However, the map generated by simple integration of multiple sensors data only gives spatial information to robots. To get a semantic knowledge to help an autonomous mobile robot from the map, the robot has to convert low-level map representations to higher-level ones containing semantic knowledge of a scene. Given a 3D point cloud of an urban scene, this research proposes a method to recognize the objects effectively using 3D graph model for autonomous mobile robots. The proposed method is decomposed into three steps: sequential range data acquisition, normal vector estimation and incremental graph-based segmentation. This method guarantees the both real-time performance and accuracy of recognizing the objects in real urban environments. Also, it can provide plentiful data for classifying the objects. To evaluate a performance of proposed method, computation time and recognition rate of objects are analyzed. Experimental results show that the proposed method has efficiently in understanding the semantic knowledge of an urban environment.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.84-97
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• 2021

Digital twins are one of the promising digital technologies used to facilitate digital transformation. Therefore, it needs to continually be developed remain relevant in industry and academia. Consolidation of research is required to create a common understanding of the topic and to ensure that future research is built upon a solid foundation. Based on a bibliometric review and a thematic analysis of 217 publications on digital twins from the past two decades, this paper creates and analyzes a visual knowledge map and proposes areas for further research. To comprehensively analyze the development trends and research trends of digital twins, we performed statistical analysis of the relevant literature on digital twins within the core collection database of Web of Science. Through our research, we have shown that the current situation, trends, and hotspots of digital twin research were analyzed via CiteSpace. This study demonstrates that research on digital twins is rapidly growing in popularity, that the output of the research depends largely on the core group of authors conducting it, and that digital twins warrant cross-domain and cross-disciplinary research pathways.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.77-89
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• 2022

In this paper, we propose a system which automatically generates SHACL schemas to describe and validate RDF knowledge graphs constructed by RML mappings. Unlike existing studies, the proposed system generates the schemas based on not only RML mapping rules but also metadata extracted from RML mapping input data in various formats such as CSV, JSON, XML or databases. Therefore, our schemas include the constraints on data type, string length, value range and cardinality, which were not present in the existing schemas. And we solves the problem with "repeated properties" which overlooked in existing studies. Through a conformance test consisting of 297 cases, we show that the proposed system generates correct constraints for the graphs. The proposed system can contribute to automation of the tedious and error-prone existing manual validation processes.

• English Language & Literature Teaching
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• v.7 no.1
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• pp.137-160
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• 2001

This paper is to suggest the way to improve EFL reading skill through semantic mapping by leveled group activities. Semantic mapping is a categorical structuring of information in graphic forms or diagrams. It can be used to activate and organize background knowledge on topics in classrooms. For small group activities, the class is divided into higher leveled groups and lower leveled groups of four members based on their grades. The teaching process has three stages: Pre-reading, while-reading, and post-reading. In the pre-reading stage, students discuss what they know about the topic. They map ideas with a brainstorming technique. In the while-reading stage, they read the text about the topic. While they are reading, they could ask some questions they might have and discuss the information in the text and categorize them with semantic mapping. In the post-reading stage, they discuss what they thought of the topic and add some information about the topic with semantic mapping. For the subjects of this study, third grade, middle school students were selected: 41 students for the experimental group and 35 students for the control group. The experimental period covered almost one semester from March to August, 2000. The results were as follows: 1) The students in the experimental group had higher scores in reading comprehension than those in the control group when semantic mapping was used; 2) The use of semantic mapping in reading comprehension was found to be much more effective in the higher leveled group than in the lower leveled group; 3) The results of questionnaires showed that many students became more interested and motivated in English, and semantic mapping helped them to participate positively in reading the English text. Thus, using semantic mapping by leveled group activities can be an effective alternative to traditional teaching methods for teachers who desire to improve reading skill in middle school students' English classes.

• Journal of the Korea Society of Computer and Information
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• v.25 no.10
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• pp.23-34
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• 2020

In this paper, we proposes a method to automatically construct SHACL schemas for RDF knowledge graphs(KGs) generated by Direct Mapping(DM). DM and SHACL are all W3C recommendations. DM consists of rules to transform the data in an RDB into an RDF graph. SHACL is a language to describe and validate the structure of RDF graphs. The proposed method automatically translates the integrity constraints as well as the structure information in an RDB schema into SHACL. Thus, our SHACL schemas are able to check integrity instead of RDBMSs. This is a consideration to assure database consistency even when RDBs are served as virtual RDF KGs. We tested our results on 24 DM test cases, published by W3C. It was shown that they are effective in describing and validating RDF KGs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.236-239
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• 2021

With the growth of AI technology, the scale of Knowledge Graphs continues to be expanded. Knowledge Graphs are mainly expressed as RDF representations that consist of connected triples. Many RDF storages compress and transform RDF triples into the condensed IDs. However, if we try to transform a large scale of RDF triples, it occurs the high processing time and memory overhead because it needs to search the large ID mapping table. In this paper, we propose the method of converting RDF triples using Hash-based ID mapping tables with MapReduce, which is the software framework with a parallel, distributed algorithm. Our proposed method not only transforms RDF triples into Integer-based IDs, but also improves the conversion speed and memory overhead. As a result of our experiment with the proposed method for LUBM, the size of the dataset is reduced by about 3.8 times and the conversion time was spent about 106 seconds.