• The Journal of Korean Academy of Prosthodontics
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• v.36 no.2
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• pp.258-272
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• 1998

This investigation evaluated patients who received Steri-Oss implants from the Dental Hospital of Chosun University during the period from March 1989 to August 1997. 346 fixtures of 127 patients were included in this study. The results were as follows ; 1.The follow-up period was defined as the period between the surgical placement of the implants and the last follow-up examination. The mean follow-up period was $2.17{\pm}1.21$ years. 2.The period between fixture installation and second surgery was $0.71{\pm}0.44$ years in the maxilla and $0.46{\pm}0.21$ years in the mandible. 3.The number of fixtures which were installed in the upper jaw(112) was less than that in the lower jaw(234) and in the posterior region(260) was more than in the anterior region(86). 4.The length of fixture which was most frequently used was 12 mm and least was 8mm. Screw implants were installed more than cylindrical implants. 3.8mm implant was the most common implans, followed by 4.5mm and 3.25mm. 5.The number of augmentation cases was more than that of non-augmentation cases and the rate of augmentation cases in the maxilla was more than that in the mandible. 6.Implant restorations for partial edentulos patients(94cases) were more than single- tooth implant restorations(33cases) or implant restorations for complete edentulos patients(10cases). 7.Free-standing prostheses for partially edentulous patients were more commom than any other type of connection between implants and natural teeth. 8.Plaque Index($0.95{\pm}0.74$) and Gingival Index($0.31{\pm}0.52$) were very similar around the natural teeth and reflected an acceptable level of plaque and gingivitis control. Mean value for keratinized mucosa index($1.93{\pm}1.20$) remained fairly constant around level 2(1-2 mm keratinized epithelium). 9.Patients were generally satisfied with implant in terms of comfort, function, speech and esthetics. 10.There was not a statistically significant differences in overall survial rate between implants placed in the maxilla (91.5%) and those placed in the mandible (93.8%). Fourteen implants lost before the prosthetic rehabilitation and eleven implants lost following variable periods in function after the prosthetic phase of the treatment. 11.Cause of implant failures was exfoliation or removal of fixture due to non-osseointegration before the prosthetic rehabilitation or due to fracture of fixture, masticatory pain after the prosthetic rehabilitation. 12.The survival rate of Steri-Oss implants using the Kaplan-Meier statistical analysis was 93.8% at 2 year and 86.6% at 5 year, In all cases, implant losses occured predominantly in the healing period. There was a steep decline in the rate of implant loss after the first year. 13.The survival rate of Steri-Oss implants in the anterior region was 94.8% at 2 year and 94.8% at 5 year and that in the posterior region was 92.8% at 2 year and 75.9% at 5 year. In conclusion, this study revealed a number of parameters and guidelines for achieving an optimal success rate in osseointegration.

• Journal of Korean Theatre Studies Association
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• no.52
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• pp.271-317
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• 2014

This essay studied the acting theories of Diderot, Delsarte, Meyerhold, and Artaud to know the historical formation of 'sign acting' and its theoretical and aesthetic appropriateness. The sign acting so far discussed shows the repetitive patterns of idea as follows. The sign acting (1) emphasizes the physical expression such as gesture and movement, (2) assumes that the physical expression functions as a sign evoking special emotion and thought, (3) thus recommends the imitation of the outer sign, (4) uses a tableau for the effective reception of outer sign, (5) aims for the spectator oriented aesthetics as it stresses the result of outer sign rather than the creative process of a role, (6) assumes that the emotional reaction or the intellectual understanding springs from the physical experience, (7) thus emphasizes the physical language rather than speech, (8) can attain the appropriateness of physical language by the recent theories of cognitive science. Besides having such commonness, the sign acting also reveals the individual differences. For instance, the intended sign for Diderot and Delsarte was the sign of emotion, for Meyerhold the stylized sign of circus and acrobatics, and for Artaud the spiritual sign. If Diderot and Meyerhold demands the cool consciousness for the correct sign acting, Artaud's sign acting tends to pursue the state of trance. And if Diderot, Delsarte, and Meyerhold think the sign acting on the level of sensory appeal, Artaud insists that the sign acting should dismantle the spectator's sense. As such the discussion of sign acting shows both recurrent ideas and new visions, forming an unity out of diversity. Perhaps the sign acting is a matter of practice before we consider it as a theory. It is not only supposed to have been existed practically since ancient theatre, but also used by actors consciously and unconsciously in expressing certain emotion and thought. We need to study the sign acting more academically, considering its long history and aesthetic potentials. In fact the sign acting has been an essential element of acting, in spite of bad reputation judging it as a banal and worn-out style. It is true that the sign acting, in the worst case, could produce a stereotypical expression. It was this aspect of sign acting that caused a fierce negative reaction of the realists who sought the natural expression based upon psychological truth. Of course the sign acting has a serious problem when it stays banal and artificial. But we need to see this issue from a different perspective. What is the natural expression of emotion? How is it free from the learned way of expression? In some respect, we use, in reality, a learned expression of emotion that could be accepted socially. For instance, when we attend a funeral, we use the outer sign of mourning gestures learned socially. If a semiotic expression pervades various aspects of our life, the acting, being the representation of life, seems not to be free from codified expression. The sign acting could be used consciously and unconsciously in all kinds of acting.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.4
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• pp.169-178
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• 2022

Morphemes are most primitive units in a language that lose their original meaning when segmented into smaller parts. In Korean, a sentence is a sequence of eojeols (words) separated by spaces. Each eojeol comprises one or more morphemes. Korean morphological analysis (KMA) is to divide eojeols in a given Korean sentence into morpheme units. It also includes assigning appropriate part-of-speech(POS) tags to the resulting morphemes. KMA is one of the most important tasks in Korean natural language processing (NLP). Improving the performance of KMA is closely related to increasing performance of Korean NLP tasks. Recent research on KMA has begun to adopt the approach of machine translation (MT) models. MT is to convert a sequence (sentence) of units of one domain into a sequence (sentence) of units of another domain. Neural machine translation (NMT) stands for the approaches of MT that exploit neural network models. From a perspective of MT, KMA is to transform an input sequence of units belonging to the eojeol domain into a sequence of units in the morpheme domain. In this paper, we propose a deep learning model for KMA. The backbone of our model is based on the BERT-fused model which was shown to achieve high performance on NMT. The BERT-fused model utilizes Transformer, a representative model employed by NMT, and BERT which is a language representation model that has enabled a significant advance in NLP. The experimental results show that our model achieves 98.24 F1-Score.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.15-29
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• 2021

Many countries and companies are pursuing and developing Artificial intelligence as it is the core technology of the 4th industrial revolution. Global IT companies such as Apple, Microsoft, Amazon, Google and Samsung have all released their own AI assistant hardware products, hoping to increase customer loyalty and capture market share. Competition within the industry for AI agent is intense. AI assistant products that command the biggest market shares and customer loyalty have a higher chance of becoming the industry standard. This study analyzed the current status of major overseas and domestic IT companies in the field of artificial intelligence, and suggested future strategic directions for voice UI technology development and user satisfaction. In terms of B2B technology, it is recommended that IT companies use cloud computing to store big data, innovative artificial intelligence technologies and natural language technologies. Offering voice recognition technologies on the cloud enables smaller companies to take advantage of such technologies at considerably less expense. Companies also consider using GPT-3(Generative Pre-trained Transformer 3) an open source artificial intelligence language processing software that can generate very natural human-like interactions and high levels of user satisfaction. There is a need to increase usefulness and usability to enhance user satisfaction. This study has practical and theoretical implications for industry and academia.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.309-328
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• 2022

This study empirically analyzed a Korean pre-trained language models (PLMs) designed for natural language generation. The performance of two PLMs - BART and GPT - at the task of abstractive text summarization was compared. To investigate how performance depends on the characteristics of the inference data, ten different document types, containing six types of informational content and creation content, were considered. It was found that BART (which can both generate and understand natural language) performed better than GPT (which can only generate). Upon more detailed examination of the effect of inference data characteristics, the performance of GPT was found to be proportional to the length of the input text. However, even for the longest documents (with optimal GPT performance), BART still out-performed GPT, suggesting that the greatest influence on downstream performance is not the size of the training data or PLMs parameters but the structural suitability of the PLMs for the applied downstream task. The performance of different PLMs was also compared through analyzing parts of speech (POS) shares. BART's performance was inversely related to the proportion of prefixes, adjectives, adverbs and verbs but positively related to that of nouns. This result emphasizes the importance of taking the inference data's characteristics into account when fine-tuning a PLMs for its intended downstream task.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Journal of the Daesoon Academy of Sciences
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• v.43
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• pp.67-102
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• 2022

The purpose of this study is to analyze the human rights found in the North Korean Constitution and their core problem by focusing on elements of human rights suggested by Daesoon Jinrihoe's doctrine of Haewon-sangsaeng (解冤相生 the Resolution of Grievances for Mutual Beneficence). Haewon-sangsaeng is seemingly the only natural law that could resolve human resentment lingering from the Mutual Contention of the Former World while leading humans work for the betterment of one another. Haewon-sangsaeng, as a natural law, includes the right to life, the right to autonomous decision-making, and duty to act according to human dignity (physical freedom, the freedom of conscience, freedom of religion, freedom of speech, freedom of press, etc.), the right to equal treatment in one's social environment, and the right to ensure the highest level of health through treatment. The North Korean Constitution does not have a character as an institutional device to guarantee natural human rights, the fundamental principle of the Constitution, and stipulates the right of revolutionary warriors to defend dictators and dictatorships. The right to life is specified so that an individual's life belongs to the life of the group according to their socio-political theory of life. Rights to freedom are stipulated to prioritize group interests over individual interests in accordance with the principle of collectivism. The right to equality and the right to health justify discrimination through class discrimination. The right to life provided to North Koreans is not guaranteed due to the death penalty system found within the North Korean Criminal Code and the Criminal Code Supplementary Provisions. The North Korean regime deprives North Koreans of their right to die with dignity through public executions. The North Korean regime places due process under the direction of the Korea Worker's Party, recognizes religion as superstition or opium, and the Korea Worker's Party acknowledge the freedoms of bodily autonomy, religion, media, or press. North Koreans are classified according to their status, and their rights to equality are not guaranteed because they are forced to live a pre-modern lifestyle according to the patriarchal order. In addition, health rights are not guaranteed due biased availability selection and accessibility in the medical field as well as the frequent shortages of free treatments.

• The Korean Journal of Air & Space Law and Policy
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• v.30 no.2
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• pp.427-468
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• 2015

To date, we have considered the theoretical views, the standpoint of states and the discourse within the international community such as the UN Committee on the Peaceful Uses of Outer Space(COPUOS) regarding the Air/Outer Space Boundary Question which is one of the first issues of UN COPUOS established in line with marking the starting point of Outer Space Area. As above mentioned, discussions in the United Nations and among scholars of within each state regarding the delimitation issue often saw a division between those in favor of a functional approach (the functionalists) and those seeking the delineation of a boundary (the spatialists). The spatialists emphasize that the boundary between air and outer space should be delimited because the status of outer space is a type of public domain from which sovereign jurisdiction is excluded, as stated in Article 2 of Outer Space Treaty. On the contrary art. I of Chicago Convention is evidence of the acknowledgement of sovereignty over airspace existing as an international customary law, has the binding force of which exists independently of the Convention. The functionalists, backed initially by the major space powers, which viewed any boundary demarcation as possibly restricting their access to space, whether for peaceful or non-military purposes, considered it insufficient or inadequate to delimit a boundary of outer space without obvious scientific and technological evidences. Last more than 50 years there were large development in the exploration and use of outer space. But a large number states including those taking the view of a functionalist have taken on a negative attitude. As the element of location is a decisive factor for the choice of the legal regime to be applied, a purely functional approach to the regulation of activities in the space above the Earth does not offer a solution. It seems therefore to welcome the arrival of clear evidence of a growing recognition of and national practices concerning a spatial approach to the problem is gaining support both by a large number of States as well as by publicists. The search for a solution to the problem of demarcating the two different legal regimes governing the space above Earth has undoubtedly been facilitated and a number of countries including Russia have already advocated the acceptance of the lowest perigee boundary of outer space at a height of 100km. As a matter of fact the lowest perigee where space objects are still able to continue in their orbiting around the earth has already been imposed as a natural criterion for the delimitation of outer space. This delimitation of outer space has also been evidenced by the constant practice of a large number of States and their tacit consent to space activities accomplished so far at this distance and beyond it. Of course there are still numerous opposing views on the delineation of a outer space boundary by space powers like U.S.A., England, France and so on. Therefore, first of all to solve the legal issues faced by the international community in outer space activities like delimitation problem, there needs a positive and peaceful will of international cooperation. From this viewpoint, President John F. Kennedy once described the rationale behind the outer space activities in his famous "Moon speech" given at Rice University in 1962. He called upon Americans and all mankind to strive for peaceful cooperation and coexistence in our future outer space activities. And Kennedy explained, "There is no strife, ${\ldots}$ nor any international conflict in outer space as yet. But its hazards are hostile to us all: Its conquest deserves the best of all mankind, and its opportunity for peaceful cooperation may never come again." This speech seems to even present us in the contemporary era with ample suggestions for further peaceful cooperation in outer space activities including the delimitation of outer space.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Korean Journal of Cognitive Science
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• v.22 no.1
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• pp.57-78
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• 2011

Paraphrasing is the act of writing a text using other words without altering the meaning. Paraphrases can be used in many fields of natural language processing. In particular, paraphrases can be incorporated in machine translation in order to improve the coverage and the quality of translation. Recently, the approaches on paraphrase extraction utilize bilingual parallel corpora, which consist of aligned sentence pairs. In these approaches, paraphrases are identified, from the word alignment result, by pivot phrases which are the phrases in one language to which two or more phrases are connected in the other language. However, the word alignment is itself a very difficult task, so there can be many alignment errors. Moreover, the alignment errors can lead to the problem of selecting incorrect pivot phrases. In this study, we propose a method in paraphrase extraction that discriminates good pivot phrases from bad pivot phrases. Each pivot phrase is weighted according to its reliability, which is scored by considering the lexical and part-of-speech information. The experimental result shows that the proposed method achieves higher precision and recall of the paraphrase extraction than the baseline. Also, we show that the extracted paraphrases can increase the coverage of the Korean-English machine translation.