• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.347-358
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• 2003

VSField-associated term is a single or compound word whose terms occur in any document, and which makes it possible to recognize a field of text by using common knowledge of human. For example, human recognizes the field of document such as or , a field name of text, when she encounters a word 'Pitcher' or 'election', respectively We Proposes an efficient construction method of field-associated terms (FTs) for specializing field to decide a field of text. We could fix document classification scheme from well-classified document database or corpus. Considering focus field we discuss levels and stability ranks of field-associated terms. To construct a balanced FT collection, we construct a single FTs. From the collections we could automatically construct FT's levels, and stability ranks. We propose a new extraction algorithms of FT's for document classification by using FT's concentration rate, its occurrence frequencies.

• Journal of the Korean Institute of Landscape Architecture
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• v.25 no.1
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• pp.47-61
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• 1997

This study was conducted to grasp the present condition of the name and the related text of the domestic laws (97 statutes, 1 examination, 1 guide, 3 ordinances, 1 leading case) in force which were connected with landscape plant and planting. Examining the general tree-planting system of America, the related foreign laws(1 constitution, 44 statutes, 31 ordinances, 6 leading cases) were arranged in the name and the text and classified by nations of regional groups and it was considered to the mutual relation with lots of laws which are scattered with the various laws. To examine the points at issue of the related domestic laws and to study the related foreign laws, the remedies for the domestic laws being at issue were proposed. That is : A change of the landscape planting concept, the introduction of the landscape planting cost compared with the total construction cost, the unification of the landscape planting ordinances as the unit of city, the clarification of the completion period for the depect of the replaced trees. putting the conservation and production of the top soil under an obligation the adoption of a licence system for the tree planting within the river area, the introduction of the allotment system for landscape architectural expenses, the encouragement of making a hedge, the settlement for the problems of the trees loss compensation, the necessity for the quality test to the landscape planting works, the intensification of the punitive rules to the illegal felling and planting of the trees in the greenzone area, the application of the Labor Standard Act to the landscape planting laborers. The laws relating to landscape plant and planting are prescribed dispersedly in the many other related laws and it is concluded to be impossible for the legislation of the singular law which is applied uniformly to the department of the tree-planting. Hereafter it should be required to analyze concretely in detail the each text of the related laws by means of the joint studies between the professional landscape architects and the lawyers.

• The Mathematical Education
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• v.46 no.4
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• pp.371-388
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• 2007

This is a case study trying to understand from the view of affordance which certain three middle school students perceive an activation of previous knowledge in the course of problem solving when they solve algebra word problems with a previous knowledge. The results of this study showed that at first, every subjects perceived the text as affordance which explaining superficial similarities, that is, a working(painting)situation rather than problem structure and then activated the related solution knowledge on the ground of the experience of previous problem solving which is similar to current situation. The subject's applying process for solving knowledge could be arranged largely into two types. The first type is a numeral information connected with the described problem situation or a symbolic representation of mathematical meaning which are the transformed solution applied process with a suitable solution formula to the current problem. This process achieved by constructing a virtual mental model that indicating mathematical situation about the problem when the solver read the problem integrating symbolized information from the described text. The second type is a case that those subjects symbolizing a formal mathematical concept which is not connected with the problem situation about the described numeral information from the applied problem or the text of mathematical meaning, which process is the case to perceive superficial phrases or words that described from the problem as affordance and then applied previously used algorithmatical formula as it was. In conclusion, on the ground of the results of this case study, it is guessed that many students put only algorithmatical knowledge in their memories through previous experiences of problem solving, and the memories are connected with the particular phrases described from the problems. And it is also recognizable when the reflection process which is the last step of problem solving carried out in the process of understanding the problem and making a plan showed the most successful in problem solving.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.189-194
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• 2019

This paper is a study on the methodology of making customized contents according to user 's tendency through the development of learning contents utilizing IT. A variety of learners around the world use mobile devices and mobile learning contents to conduct their learning activities in various fields, and foreign language learning is one of the typical mobile learning areas. Foreign language learning contents suggested in this study is constructed based on the learner's verbal and text information in accordance with the user's vocal tendency. It is necessary to find out a suitable method to translate the user's native language text into the target language and make it into user friendly content.

• Journal of Information Technology Services
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• v.20 no.5
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• pp.11-28
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• 2021

As untact travel has become a new trend in leisure culture due to the spread of COVID-19, car camping market is rapidly increasing. The sales of car camping-related goods increased by up to 600 percent, and the sales of SUV in Korea also increased by about four times. Despite the growth of the car camping market, there is a lack of research on the actual condition of the car camping market or research on the user's perspective. Therefore, in this study, a survey of actual camping users was conducted to derive factors that they consider important in camping, and through this, a car camping map was produced. As a result, two types of maps were produced: a map about the car camping site and convenience facilities closest to the car camping site in Gangwon-do, and a hash tag themed map based on keywords for each car camping site. We gathered data on portal sites and social media to obtain information related to camping sites and proceeded with analysis using text mining. In addition, we extracted keywords using network analysis techniques and selected key themes that represent them. This allows the user to choose a car camping site by selecting keywords that suit their taste. We hope that this research will help car camping researchers as a prior study and provide a foundation for leading a clean camping culture through clean camping campaign. Also, we hope that car camping users will be able to do quality trip.

• Journal of Korean Medical classics
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• v.35 no.3
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• pp.41-58
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• 2022

Objectives : In this paper, the outline and overall content of the Majinhwiseong, a specialized medical text on measles written by Lee Wonpung was introduced, along with its academic historical meaning. Methods : The entire Majinhwiseong was analyzed according to content and form. In terms of form, organization, construction, cited literature, etc., were studied, while in terms of content, diagnosis of disease pattern and treatment formulas were studied. Later, based on cited medical texts and the author's social position, the academic historical meaning of this book was discussed. Results : Through the Majinhwiseong, Lee Wonpung strengthened the credibility of the text by not only providing medical knowledge on measles but listing their sources and comparing and analyzing related contents. In the diagnosis part, Lee focused on the changes in symptom, shape, color, and pulse of measles, discussing in detail its differential diagnostic methods. In the treatment part, while listing numerous formulas suggested by Ming (明) masters, Lee did not leave out treatment experiences of Joseon physicians. Meanwhile, the Majinhwiseong is indicative of measles medicine in 18th century Joseon having been progressed in the private sector rather than the official, and how the results of private sector medicine were being absorbed into the official realm through the Uiyakdongcham (議藥同參) system. Conclusions : The Majinhwiseong is a practical treatment manual written by clinician Lee Wonpung to deal measles which was widely spread at the time. The author organized existing medical knowledge on measles for clinicians while reflecting outcomes and medical situation of Joseon physicians in this book. Based on these findings, we could verify that medicine in 18th century Joseon had been progressing actively around the private medical sector.

• Dementia and Neurocognitive Disorders
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• v.23 no.3
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• pp.146-160
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• 2024

Background and Purpose: The emotions of people at various stages of dementia need to be effectively utilized for prevention, early intervention, and care planning. With technology available for understanding and addressing the emotional needs of people, this study aims to develop speech emotion recognition (SER) technology to classify emotions for people at high risk of dementia. Methods: Speech samples from people at high risk of dementia were categorized into distinct emotions via human auditory assessment, the outcomes of which were annotated for guided deep-learning method. The architecture incorporated convolutional neural network, long short-term memory, attention layers, and Wav2Vec2, a novel feature extractor to develop automated speech-emotion recognition. Results: Twenty-seven kinds of Emotions were found in the speech of the participants. These emotions were grouped into 6 detailed emotions: happiness, interest, sadness, frustration, anger, and neutrality, and further into 3 basic emotions: positive, negative, and neutral. To improve algorithmic performance, multiple learning approaches were applied using different data sources-voice and text-and varying the number of emotions. Ultimately, a 2-stage algorithm-initial text-based classification followed by voice-based analysis-achieved the highest accuracy, reaching 70%. Conclusions: The diverse emotions identified in this study were attributed to the characteristics of the participants and the method of data collection. The speech of people at high risk of dementia to companion robots also explains the relatively low performance of the SER algorithm. Accordingly, this study suggests the systematic and comprehensive construction of a dataset from people with dementia.

• Journal of the Korea Institute of Construction Safety
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• v.5 no.1
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• pp.1-8
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• 2023

The purpose of this study is to suggest a way to solve the excessive paperwork of safety managers in domestic construction sites, and to suggest a work efficiency plan that can shorten the time required to prevent safety accidents. First, a function to automatically generate a safety document and find the necessary data is applied using the RPA program. The second is document creation using mobile devices. After safety training, use the Moleil app to keep the training log. Third, to prevent omission of essential safety and health documents, the automatic warning function is activated according to the RPA submission time and sent to the person in charge by e-mail or text. Fourth, the function to find the latest data with high accuracy and speed through 'Google Cloud Search', a search function, was applied.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.509-514
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• 2020

The conventional TTS system consists of several modules, including text preprocessing, parsing analysis, grapheme-to-phoneme conversion, boundary analysis, prosody control, acoustic feature generation by acoustic model, and synthesized speech generation. But TTS system with deep learning is composed of Text2Mel process that generates spectrogram from text, and vocoder that synthesizes speech signals from spectrogram. In this paper, for the optimal Korean TTS system construction we apply Tacotron2 to Tex2Mel process, and as a vocoder we introduce the methods such as WaveNet, WaveRNN, and WaveGlow, and implement them to verify and compare their performance. Experimental results show that WaveNet has the highest MOS and the trained model is hundreds of megabytes in size, but the synthesis time is about 50 times the real time. WaveRNN shows MOS performance similar to that of WaveNet and the model size is several tens of megabytes, but this method also cannot be processed in real time. WaveGlow can handle real-time processing, but the model is several GB in size and MOS is the worst of the three vocoders. From the results of this study, the reference criteria for selecting the appropriate method according to the hardware environment in the field of applying the TTS system are presented in this paper.

• Management & Information Systems Review
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• v.37 no.4
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• pp.41-62
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• 2018

As the volume of unstructured data increases through various social media, Internet news articles, and blogs, the importance of text analysis and the studies are increasing. Since text analysis is mostly performed on a specific domain or topic, the importance of constructing and applying a domain-specific dictionary has been increased. The quality of dictionary has a direct impact on the results of the unstructured data analysis and it is much more important since it present a perspective of analysis. In the literature, most studies on text analysis has emphasized the importance of dictionaries to acquire clean and high quality results. However, unfortunately, a rigorous verification of the effects of dictionaries has not been studied, even if it is already known as the most essential factor of text analysis. In this paper, we generate three dictionaries in various ways from 39,800 news articles and analyze and verify the effect each dictionary on the accuracy of document classification by defining the concept of Intrinsic Rate. 1) A batch construction method which is building a dictionary based on the frequency of terms in the entire documents 2) A method of extracting the terms by category and integrating the terms 3) A method of extracting the features according to each category and integrating them. We compared accuracy of three artificial neural network-based document classifiers to evaluate the quality of dictionaries. As a result of the experiment, the accuracy tend to increase when the "Intrinsic Rate" is high and we found the possibility to improve accuracy of document classification by increasing the intrinsic rate of the dictionary.