• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.2
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• pp.46-60
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• 2001

This study proposes the Web-based GIS system based on distributed object management and conceptualise system architecture and its methods specifications through UML(unified modeling language). By using class diagram and creating prototype based on UML and reverse engineering, our conceptual shape file model is proposed to illustrate an integrated architecture. Through system analysis and software configuration management, this study enables to not only improve pliable capabilities for problematic domains and increase abilities for analytical domains when user requirements are dynamic, but also assist effective and consistent maintenances of large software systems.

• Korean Institute of Interior Design Journal
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• v.22 no.5
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• pp.207-215
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• 2013

Due to an increase in the number of large-scale and high rise buildings, the importance of indoor location information has been highlighted. As a result, seamless three-dimensional space information, linked to various indoor and outdoor services is required. The purpose of this study is to develop a system which can edit and operate indoor space information using the IndoorGML(Geography Markup Language). It provides functions such as converting and editing authoring indoor space using the IndoorGML. Based on defined schema which is the IndoorGML international standardization work, we develop the "Editor" and "Viewer" for the IndoorGML. When indoor space is modeled in an authoring tool, a variety of topologies can be created automatically. These are available to be edited and modified. Moreover, the file of model can be saved as IndoorGML, SBM and KML file. These files are viewed by the "Viewer". Indoor LBS(Location Based Service)is served with these principles.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.87-92
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• 2024

In this paper, a RAG system was implemented using an existing Large Language Model (LLM) and Langchain library to develop a dental consultation chatbot. For this purpose, we collected contents from the webpage bulletin boards of domestic dental university hospitals and constructed consultation data with the advice and supervision of dental specialists. In order to divide the input consultation data into appropriate sizes, the chunk size and the size of the overlapping text in each chunk were set to 1001 and 100, respectively. As a result of the simulation, the Retrieval Augmented LLM searched for and output the consultation content that was most similar to the user input. It was confirmed that the accessibility of dental consultation and the accuracy of consultation content could be improved through the built chatbot.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1077-1094
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• 2016

Apache Spark is a fast and general-purpose cluster computing package. It provides a new abstraction named resilient distributed dataset, which is capable of support for fault tolerance while keeping data in memory. This type of abstraction results in a significant speedup compared to legacy large-scale data framework, MapReduce. In particular, Spark framework is suitable for iterative machine learning applications such as logistic regression and K-means clustering, and interactive data querying. Spark also supports high level libraries for various applications such as machine learning, streaming data processing, database querying and graph data mining thanks to its versatility. In this work, we introduce the concept and programming model of Spark as well as show some implementations of simple statistical computing applications. We also review the machine learning package MLlib, and the R language interface SparkR.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.5
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• pp.379-387
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• 2006

The real world is spatially modelled conceptually either as discrete objects or earth surface. The generated data models are then usually represented as vector and raster respectively. Although there are limited cases where only one data model is sufficient to solve the spatial problem at hand, it is now generally accepted that GIS should be able to handle various types of data model. Recent advances in spatial technology introduced even more variety of heterogeneous data models and the need is ever growing to handle and manage efficiently these large variety of spatial data. The OGC (Open GIS Consortium), an international organization pursuing standardization in the geospatial industry. recently introduced the GMLJP2 (Geographic Mark-Up Language JP2) format which enables store and handle heterogeneous spatial data. The GMLJP2 format, which is based on the JP2 format which is an abbreviation for JPEG2000 wavelet image compression format, takes advantage of the versatility of the GML capabilities to add extra data on top of the compressed image. This study takes a close look into the GMLJP2 format to analyse and exploit its potential to handle and mange hetergeneous spatial data. Aerial image, digital map and LIDAR data were successfully transformed end archived into a single GMLJP2 file. A simple viewing program was made to view the heterogeneous spatial data from this single file.

• The Journal of the Acoustical Society of Korea
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• v.24 no.8
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• pp.498-504
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• 2005

We introduce a Korean speech recognition platform (ECHOS) developed for education and research Purposes. ECHOS lowers the entry barrier to speech recognition research and can be used as a reference engine by providing elementary speech recognition modules. It has an easy simple object-oriented architecture, implemented in the C++ language with the standard template library. The input of the ECHOS is digital speech data sampled at 8 or 16 kHz. Its output is the 1-best recognition result. N-best recognition results, and a word graph. The recognition engine is composed of MFCC/PLP feature extraction, HMM-based acoustic modeling, n-gram language modeling, finite state network (FSN)- and lexical tree-based search algorithms. It can handle various tasks from isolated word recognition to large vocabulary continuous speech recognition. We compare the performance of ECHOS and hidden Markov model toolkit (HTK) for validation. In an FSN-based task. ECHOS shows similar word accuracy while the recognition time is doubled because of object-oriented implementation. For a 8000-word continuous speech recognition task, using the lexical tree search algorithm different from the algorithm used in HTK, it increases the word error rate by $40\%$ relatively but reduces the recognition time to half.

• Cross-Cultural Studies
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• v.48
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• pp.391-417
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• 2017

Southeast Asian languages are famous for having a large number of vowel sounds with an average of more than 20 vowel sounds in this certain language family. In addition, there are approximately 1,500 languages in this area, which accounts for approximately 20% of total languages in the world. For this reason, vowel systems of Southeast Asian languages should be explored to determine the nature of vowel structures of human natural languages. In this study, we analyze vowel systems of three languages, Tagalog, Malay and Thai, that have only primary or normal vowels and thus are relatively simple structures based on descriptive and analytic universals. We would also like to confirm if the six criteria of the tentative evaluation model taken from several previous literature is appropriate in applying analysis of vowel system universals under the method of the Greenbergian Universals or statistic universals. What we have found from this research are (i) the three languages have high level of universals with some exceptional cases such as three-vowel system of Tagalog, and (ii) some of the six criteria, together with some cases of analytic universals, are not quite suitable for understanding language-specific universals that are different from other languages.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.23-29
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• 2021

Recent deep learning-based natural language processing studies are conducting research to improve performance by training large amounts of data from various sources together. However, there is a possibility that the methodology of learning by combining data from various sources into one may prevent performance improvement. In the case of machine translation, data deviation occurs due to differences in translation(liberal, literal), style(colloquial, written, formal, etc.), domains, etc. Combining these corpora into one for learning can adversely affect performance. In this paper, we propose a new Corpus Weight Balance(CWB) method that considers the balance between parallel corpora in machine translation. As a result of the experiment, the model trained with balanced corpus showed better performance than the existing model. In addition, we propose an additional corpus construction process that enables coexistence with the human translation market, which can build high-quality parallel corpus even with a monolingual corpus.

• Phonetics and Speech Sciences
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• v.8 no.2
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• pp.31-39
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• 2016

In emergency dispatching at 119 Command & Dispatch Center, some inconsistencies between the 'standard emergency aid system' and 'dispatch protocol,' which are both mandatory to follow, cause inefficiency in the dispatcher's performance. If an emergency dispatch system uses automatic speech recognition (ASR) to process the dispatcher's protocol speech during the case registration, it instantly extracts and provides the required information specified in the 'standard emergency aid system,' making the rescue command more efficient. For this purpose, we have developed a Korean large vocabulary continuous speech recognition system for 400,000 words to be used for the emergency dispatch system. The 400,000 words include vocabulary from news, SNS, blogs and emergency rescue domains. Acoustic model is constructed by using 1,300 hours of telephone call (8 kHz) speech, whereas language model is constructed by using 13 GB text corpus. From the transcribed corpus of 6,600 real telephone calls, call logs with emergency rescue command class and identified major symptom are extracted in connection with the rescue activity log and National Emergency Department Information System (NEDIS). ASR is applied to emergency dispatcher's repetition utterances about the patient information. Based on the Levenshtein distance between the ASR result and the template information, the emergency patient information is extracted. Experimental results show that 9.15% Word Error Rate of the speech recognition performance and 95.8% of emergency response detection performance are obtained for the emergency dispatch system.

• Proceedings of the IEEK Conference
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• summer
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• pp.382-386
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• 2004

Recently, with the machine learning trend, most of the machine translation systems on over the world use two syntax tree sets of two relevant languages to learn syntactic tree transfer rules. However, for the English-Vietnamese language pair, this approach is impossible because until now we have not had a Vietnamese syntactic tree set which is correspondent to English one. Building of a very large correspondent Vietnamese syntactic tree set (thousands of trees) requires so much work and take the investment of specialists in linguistics. To take advantage from our available English-Vietnamese Corpus (EVC) which was tagged in word alignment, we choose the SITG (Stochastic Inversion Transduction Grammar) model to construct English- Vietnamese syntactic tree sets automatically. This model is used to parse two languages at the same time and then carry out the syntactic tree transfer. This English-Vietnamese bilingual syntactic tree set is the basic training data to carry out transferring automatically from English syntactic trees to Vietnamese ones by machine learning models. We tested the syntax analysis by comparing over 10,000 sentences in the amount of 500,000 sentences of our English-Vietnamese bilingual corpus and first stage got encouraging result $(analyzed\;about\;80\%)[5].$ We have made use the TBL algorithm (Transformation Based Learning) to carry out automatic transformations from English syntactic trees to Vietnamese ones based on that parallel syntactic tree transfer set[6].