• Cross-Cultural Studies
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• v.46
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• pp.355-377
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• 2017

Compared with other Altaic languages, Japanese and Korean languages are much closer to each other in grammar, and also to Ryukyuan language. According to the literature, Korean people are the first foreigners to record Ryukyuan language in a written form. In the passage "pronunciation interpreting the Ryukyuan Kingdom" from A Journey to the Eastern Countries (1512), Korean people perfectly preserved the pronunciation and meanings of words and sentences in Ryukyuan language in both Korean and Chinese languages, which is an extremely valuable material. Unfortunately, the later time period witnessed stagnation after a prominent beginning. In order to clarify the language family to which Korean belongs to, it is necessary to thoroughly compare Korean language with Japanese and Ryukyuan languages. Different from lexis, grammar underwent a slow and gradual process of variation. A comparative study of the three languages can provide strong evidence for defining the language family of Korean. Based on this rationale, this paper starts from the comparison of grammar elements of these three languages, aiming at case markers including the nominative case markers and the accusative case markers, and observes the procedures and functions diachronically. Based on the examples from the medieval data, it is found that the nominative case markers and the accusative case markers of these three languages vary from each other in forms and origins. Although they show some similarities in functions, it can be conjectured that there is no cognate for the three languages in the history.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.967-971
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• 2023

Recently, a variety of AI-based platform services are available, and one of them is ChatGPT that processes a large quantity of data in the natural language and generates an answer after self-learning. ChatGPT can perform various tasks including software programming in the IT sector. Particularly, it may help generate a simple program and correct errors using C Language, which is a major programming language. Accordingly, it is expected that ChatGPT is capable of effectively using Verilog HDL, which is a hardware language created in C Language. Verilog HDL synthesis, however, is to generate imperative sentences in a logical circuit form and thus it needs to be verified whether the products are executed properly. In this paper, we aim to select small-scale logical circuits for ease of experimentation and to verify the results of circuits generated by ChatGPT and human-designed circuits. As to experimental environments, Xilinx ISE 14.7 was used for module modeling, and the xc3s1000 FPGA chip was used for module embodiment. Comparative analysis was performed on the use area and processing time of FPGA to compare the performance of ChatGPT products and Verilog HDL products.

• The Korean Society of Law and Medicine
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• v.16 no.1
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• pp.3-82
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• 2015

This paper is concerned in the theme of the liability for the breach of duty to inform(Haftungszurechnung der $Aufkl{\ddot{a}}rungspflichtverletzung$) and the malpractice of cosmetic surgery. Here, the terms, treatments for healing purposes and purely medical-technical cosmetic operations are well integrated in the category of "medical conduct(medizinische Handlung)" within the meaning of the public and administrative 'Medical Law'. In the judgment of 6. 13. 2013 Az. 2012DA94865 provides the KHGH(Korean Highest Court of Justice) to inform the patient about the prospects and risks of cosmetic surgery(Infrabrow Excision Blepharoplasty) stringent requirements, similar to the judicature of BGH(cf. BGH, Urt. v. 6. 11. 1990, Az.: VI ZR 8/90). Even in the judgment of 5. 12. 2014 Az. 2013GASO865646 the SZLG(Seoul Central Regional Court) recognizes the physician contract for 'cosmetic septoplasty' as a sort of contract for work. The medical treatment(${\ddot{a}}rztliche$ Heilbehandlung) is still regarded as a prototype of the medical activity, therefore in the meaning of the 'Civil Law(KBGB)', its term needs to be used immediately for healing purposes. The cosmetic operation, desired by a patient, differs from the healing treatment by the element of "indication" and the fact that the "healing purpose(Heilzweck)" itself is missing. In comparative context - methodically fully aware that the unreflective term transfer between different laws might contradict their legal purposes - a series of judgments BSG(BSGE 63, 83, BSGE 72, 96, BSGE, 82, 158, BSGE 93, 252 etc.) and some judgments of LSG are reviewed. In addition, also the dogmatic topic for the "legal natur of a medical treatment contract" is to reconsider by comparative introducing BGHZ 63, 306. Now in view of the current state of greater popularity of artificial cosmetic surgery still indeed is the sentences: The doctor is minister naturae, a helper of nature. A doctor promises regularly only the proper treatment of the patient, but the contractual liability for work should not be excluded in medical conditions for cosmetic surgeries altogether. "With cosmetic operations, seeking to eliminate the external deformities, the doctor may miss the medical profession entirely." - A. Laufs, Medical Law, 5th ed. P. 18.

• 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.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.268-278
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• 2018

The purpose of this study is to compare and analyze phonetic items such as the phonemic system, phonological rules, and pronunciation descriptions and notations incorporated in the textbooks. Based on our analysis results, we point out the problems related to pronunciation education, and suggest directions for improvement. First, the presentation order of consonants and vowels in the phonological systems sections of each textbook was different. We recommend that a standard for consonant and vowel presentation order should be prepared, but that this standard should take into consideration the specific purpose of the textbook; the learning strategies and goals, as well as the possibility of teaching and learning. Second, similar to phonemic systems, the presentation order of phonological rules was different for each textbook. To create a standard order for phonological rules, we have to standardize the order of presentation of rules and determine which rules should be presented. Furthermore, when describing phonological rules, the content should be described in common and essential terms as much as possible without the use of jargon. Third, in other matters of pronunciation, there were problems such as examples for pronunciation and lack of exercises. Regarding this, we propose to provide sentences or dialogues as examples for pronunciation, and to link these to various activities and other language functions for pronunciation practice.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.22 no.2
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• pp.191-205
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• 2000

The purpose of this study was undertaken to determine the effects of orthognathic surgery on speech. The hyposis stated herein is that functional behaviors of the dentofacial complex, such as speech production, may be adversely affected by deviations of a structural nature(especially, Class III malocclusion). Twenty adults with Class III malocclusion(13 female and 7 male) were studied preoperative, immediate postoperative and either 6 or 12 months postoperative lateral cephalograms. They had mandibular prognathism and had undergone mandible setback operation. The position of tongue, soft palate(Uvula), hyoid bone, respiratory track width, and pharyngeal depth were assessed on lateral cephalograms with 23 cephalometric variables, ANOVA, Paired t-tests and Pearson's product-moment correlation coefficient tests were used to evalute the operative changes in all cephalometric parameters. A experienced speech and language pathologists performed narrow phonetic transcriptions of tape-recorded words and sentences produced by each of the ninth patients and the recording tapes were analyzed by phonetic computer program(Computerized Speech Lab(CSL) Model 4300BI(U.S.A.)) These judges also recorded their ratings of each patient's overall consonants, hypernasality, hyponasality, and articulation proficiency. The results obtained are as follows; 1. There were significant changes in distance of posterior pharyngeal wall to tongue (TI-TW2, TS-TW3) after the surgery at 6 months postoperatively(each p<0.01 p<0.05). 2. The posterior tongue point(TI, TS, PPT) moved posteriorly after surgery and remained to its changed position at 6 months postoperatively(p<0.05). The displacement of tongue was correlated with the movement of mandibular setback amount(p<0.05). The hyoid bone moved posteriorly superiorly after immediate postoperative period. There was significant changes in hyoid bone movement after immediated postoperative period(p<0.05), but returned to its original position during the follow-up period(p>0.05) 3. The soft palate was displaced posteriorly superiorly after immediated operative period and remained to its changed position at 6 months postoperatively(p<0.05). ANS-PNS-SPT angle increasing, PPU-PPPo distance narrowing was showed after surgery, and remained its appearance 6 months postoperatively(p<0.05). 4. There were significant changes in formant value and squre diagram of vowel sound after the orthognathic surgery and the follow-up period. There were significant changes in /ㅅ/sound and posterior tongue sound. 5. The posterior movement of tongue and the posteriosuperior movement of soft palate was correlated with mandibular setback amount after orthognathic surgery. On the vowel squre diagram, the author found that the place of articulation after operation moved downward, backward, upward. 6. In assessing speech abnormalities, dental occlusion should be considered as a contributing factor. The vast majority of subjects with preoperative misarticulations eliminated or reduced their errors following orthognathic surgery. There was significant difference in speech impovement between pre- and postoperation.

• Smart Media Journal
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• v.9 no.1
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• pp.51-59
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• 2020

From PC communication to the development of the internet, a new term has been coined on the social media, and the social media culture has been formed due to the spread of smart phones, and the newly coined word is becoming a culture. With the advent of social networking sites and smart phones serving as a bridge, the number of data has increased in real time. The use of new words can have many advantages, including the use of short sentences to solve the problems of various letter-limited messengers and reduce data. However, new words do not have a dictionary meaning and there are limitations and degradation of algorithms such as data mining. Therefore, in this paper, the opinion of the document is confirmed by collecting data through web crawling and extracting new words contained within the text data and establishing an emotional classification. The progress of the experiment is divided into three categories. First, a word collected by collecting a new word on the social media is subjected to learned of affirmative and negative. Next, to derive and verify emotional values using standard documents, TF-IDF is used to score noun sensibilities to enter the emotional values of the data. As with the new words, the classified emotional values are applied to verify that the emotions are classified in standard language documents. Finally, a combination of the newly coined words and standard emotional values is used to perform a comparative analysis of the technology of the instrument.

• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.236-246
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• 2014

Most countries have been promoted the legislative policy for the legal employment, causing a social conflicts by illegal immigrants in any countries. Despite the efforts to alleviate the illegal aliens, there are not nearly enough successful cases, and encounter a social problem about illegal stay worker. China is no exception. At present, the issue of China's foreign illegal employment is expected to be a social problem in the present and the future. However, the legislative policy against immigration control law and illegal foreign employment in China is very neglectful. There is a lack of adjusting rule of law on illegal foreign workers in China, and the remedy is also insufficient. It is necessary to secure a legal right for the protection of the Rights of illegal foreign workers based on the international norms. For this purpose, the illegal foreign workers related law should be enacted, and based on this, administration should be strengthened. The trend of major countries of illegal aliens is centered around an employer hiring strictly regulated. There is a need to have a strengthen regulation on the employer rather than the foreign workers in China. To this end, employer who hire illegal foreign workers should be required to receive considerable disadvantages such as penalties and fines, prison sentences, as well as various kinds of burdens and repatriation costs. It is necessary to run the voluntary repatriation(Freiwillige $R\ddot{u}ckehr$) program of illegal immigrants, and there is a need to take action for illegal immigrants who voluntary return home within a certain period are exempt from penalty. In conclusion, China must push ahead with a direction of positive policy in related ministries rather than sit on its hands on the wrong choice or a confusion of an employer and foreign workers with a policy on illegal foreign residents in limbo.

• Journal of the Korean Society of Radiology
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• v.16 no.2
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• pp.123-129
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• 2022

Recently, the penetration rate of Magnetic Resonance Imaging (MRI) is higher than the average among OECD member countries, and the number of MRI scans is increasing. However, MRI scans take longer than other medical devices, and patient movement must be minimized. Therefore, patient discomfort always follows. When the examination is performed in the discomfort of the patient, it is difficult to perform an accurate examination, and it is difficult to obtain an image of diagnostic value. So, in the past, the patient was asked to read the written guide for the risk and cooperation of MRI, but it was composed of technical terms and difficult-to-understand sentences, so it was difficult to understand. The purpose of this study is to supplement these problems and increase the understanding of MRI scans to help acquire images of diagnostic value. In addition, it is intended to evaluate the excellence of leaflet education by evaluating the understanding and satisfaction of patients. As shown in the results of this study, understanding and satisfaction scores were higher after education than before leaflet education, and it was found that there was a difference in understanding according to academic background. However, there was no difference in the number of MRI scans. That is, there was no difference in the number of inspections due to leaflet education. In the future, leaflet education will be widely used for MRI examination, and it is necessary to study the qualitative evaluation of images after leaflet education in the future.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.