• Journal of The Korean Society of Inherited Metabolic disease
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• v.23 no.1
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• pp.25-30
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• 2023

Leigh syndrome is a rare progressive neurodegenerative mitochondrial disorder with clinical and genetic heterogeneity. Recently, balletic IARS2 variants have been identified in a number of patients presenting broad clinical phenotypes from Leigh and West syndrome to a rare syndrome CAGSSS characterized by cataracts, growth hormone deficiency, sensory neuropathy, sensorineural hearing loss, and skeletal dysplasia syndrome (OMIM#616007). We describe a child with Korean Leigh syndrome with urologic manifestations resulting from a compound heterozygote mutation in IARS2. A 5-year-old girl visited the emergency room with a complaint of abdominal pain accompanied by abdominal distension. Abdominal-pelvic CT showed a markedly distended urinary bladder without definite obstructive lesions. She was diagnosed with neurogenic bladder dysfunction based on a urodynamic study. She had global delayed development due to neurologic regression after 6 months of age and a history of bilateral cataract surgery at the age of 2 years. Her brain magnetic resonance imaging showed symmetrically increased signal intensities in the bilateral putamen and caudate nuclei with diffuse cerebral atrophy. No gene variants were identified through whole-mitochondrial genome analysis. Whole exome sequencing was performed for diagnosis, and compound heterozygous pathogenic variants were identified in IARS2: c.2446C>T (p. Arg816Ter) and c.2450G>A (p. Arg817His). To the best of our knowledge, this is the first case report of bladder dysfunction manifestation in a patient with IARS2-related Leigh syndrome. Thus, it broadens the clinical and genetic spectrum of IARS2-associated diseases.

• (The) Research of the performance art and culture
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• no.23
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• pp.37-61
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• 2011

The Noh(能) performance is a traditional drama that represents Japan. The Noh performance was approved in the background of religious thought such as Shintoism(神道), Buddhisms(佛敎), and Syugendo(修驗道). Especially, the influence from Shugendo is large. Shugendo was active in the Middle Ages. Especially, the influence from Shugendo is large. Shugendo was active in the Middle Ages. The Noh was approved while receiving a large influence from Shugendo. It can know the feature of the Shugen(修驗) culture in the Middle Ages through the consideration of . Moreover, the appearance of the training of 'Yamabusi(山伏)' can be seen. "Yamabusi" has not been paid to attention up to now in the research of . And, the focus was appropriated to Yamabusi and it researched in this text. Moreover, the problem of "Chigo(稚子)" is thought through . "Chigo culture" was general in the Middle Ages. It is thought that "Chigo culture" is reflected in . is an Noh performance for the boy named 'Wakamatsu' to enter the mountain and to train. It is because mother's sickness was cured. However, the boy gets sick while it is training. It was dropped to the valley according to the law of Shugendo, and it died. However, it revives by the Yamabusi's prayers. 'Taniko' is to drop to the valley and to bury it when the Yamabusi gets sick while lived. The title of the Noh originated in here. has elements of history, content of training of Shugendo, "Filial piety", and the Chigo culture, etc. These are features of the culture in the Middle Ages. It is not only a sad content though this is a content of the cruel remainder. It is because of the revival though waited rapidly at the end. As for the difficulty of training is drawn in the round, and the appearance of the training at that time is understood well. The essence of Shugendo is to train in the mountain. Supernatural power can be obtained through training. Moreover, it was thought that it was able to be newly reborn through training. The leading part of Shugendo is an Yamabusi. The Yamabusi took an active part in not only the mountain but also the village. The Yamabusi is ordinary people's lives and because the relation is deep, an important factor it knows the folk customs of Japan. The word 'Chigo' is not written in . However, a spectator at that time is 'Chigo' Wakamatsu and is already sure to have understood 'Chigo'. Because everyone knew the Chigo culture in the Middle Ages. A religion at that time and knowledge of the society are necessary to understand the play of Nho well.

• Sim-seong Yeon-gu
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• v.28 no.1
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• pp.50-87
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• 2013

C. G. Jung believed that universal and basic condition of human's Unconscious comes out from Märchen or mythology. We can easily experience these universality of human nature in dreams. Therefore, It is very important to interpret mythogens that appear in myths and märchen in analytical psychology to understand these 'big dreams' which could be seen in clinical practice. As I was interested in interpreting myths in analytic psychology, I tried to find universality of archetypes in Korea's traditional folk tales and took note of the birth myth of Hyeokgeose, the founder of Shilla dynasty, while examining the chater of the Unsual in history in the Heritage of the Three Kingdoms. Shilla was founded earlier than two other countries, but it was located in the very south of the Korean Peninsula, and it was behind times in politically, militarily, and culturally compare to Goguryeo and Baekje. However, Shilla achieved unifying the Three Kingdoms and it lasted 1000 years, the longest unified history in Korean history. I tried to examine archetypes in the birth myth if there are any backgrounds that are related to finding a Shilla Kingdom. It is noted that myth of the founder of Korean Peninsula's small Kingdom Shilla has complete story from before the birth to birth, birth of spouse, growth, marriage, accession, governing, death, after death, and succession. Symbols such as numbers 1, 3, 5, 6, 7, 13 and 61, various azimuthes including north, west, south, east, and central, animals like tiger, white horse, hen, dragon, phoenix, and snakes, natures like main symbol egg, rock, gourd, lightening, spring water, stream, tree, forest, mountain, iron and goddess-image like seon-do Holy Mother gradually appears in the myth. These symbols could show a meaning of human experience such as birth of Conscious, growth and development of paternal and maternal love, and story of regeneration and extinction. Moreover, It could be seen as these progress eternally continues in next generation. I have found out that a word, a sentence or stories that looks meaningless in myth revealed its true symbolical meaning. In addition, interaction between Unconscious and Conscious repeats in different forms, and expressed in layered.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.63-77
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• 2011

The World Wide Web is a very large distributed digital information space. From its origins in 1991, the web has grown to encompass diverse information resources as personal home pasges, online digital libraries and virtual museums. Some estimates suggest that the web currently includes over 500 billion pages in the deep web. The ability to search and retrieve information from the web efficiently and effectively is an enabling technology for realizing its full potential. With powerful workstations and parallel processing technology, efficiency is not a bottleneck. In fact, some existing search tools sift through gigabyte.syze precompiled web indexes in a fraction of a second. But retrieval effectiveness is a different matter. Current search tools retrieve too many documents, of which only a small fraction are relevant to the user query. Furthermore, the most relevant documents do not nessarily appear at the top of the query output order. Also, current search tools can not retrieve the documents related with retrieved document from gigantic amount of documents. The most important problem for lots of current searching systems is to increase the quality of search. It means to provide related documents or decrease the number of unrelated documents as low as possible in the results of search. For this problem, CiteSeer proposed the ACI (Autonomous Citation Indexing) of the articles on the World Wide Web. A "citation index" indexes the links between articles that researchers make when they cite other articles. Citation indexes are very useful for a number of purposes, including literature search and analysis of the academic literature. For details of this work, references contained in academic articles are used to give credit to previous work in the literature and provide a link between the "citing" and "cited" articles. A citation index indexes the citations that an article makes, linking the articleswith the cited works. Citation indexes were originally designed mainly for information retrieval. The citation links allow navigating the literature in unique ways. Papers can be located independent of language, and words in thetitle, keywords or document. A citation index allows navigation backward in time (the list of cited articles) and forwardin time (which subsequent articles cite the current article?) But CiteSeer can not indexes the links between articles that researchers doesn't make. Because it indexes the links between articles that only researchers make when they cite other articles. Also, CiteSeer is not easy to scalability. Because CiteSeer can not indexes the links between articles that researchers doesn't make. All these problems make us orient for designing more effective search system. This paper shows a method that extracts subject and predicate per each sentence in documents. A document will be changed into the tabular form that extracted predicate checked value of possible subject and object. We make a hierarchical graph of a document using the table and then integrate graphs of documents. The graph of entire documents calculates the area of document as compared with integrated documents. We mark relation among the documents as compared with the area of documents. Also it proposes a method for structural integration of documents that retrieves documents from the graph. It makes that the user can find information easier. We compared the performance of the proposed approaches with lucene search engine using the formulas for ranking. As a result, the F.measure is about 60% and it is better as about 15%.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.97-117
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• 2020

Product evaluation criteria is an indicator describing attributes or values of products, which enable users or manufacturers measure and understand the products. When companies analyze their products or compare them with competitors, appropriate criteria must be selected for objective evaluation. The criteria should show the features of products that consumers considered when they purchased, used and evaluated the products. However, current evaluation criteria do not reflect different consumers' opinion from product to product. Previous studies tried to used online reviews from e-commerce sites that reflect consumer opinions to extract the features and topics of products and use them as evaluation criteria. However, there is still a limit that they produce irrelevant criteria to products due to extracted or improper words are not refined. To overcome this limitation, this research suggests LDA-k-NN model which extracts possible criteria words from online reviews by using LDA and refines them with k-nearest neighbor. Proposed approach starts with preparation phase, which is constructed with 6 steps. At first, it collects review data from e-commerce websites. Most e-commerce websites classify their selling items by high-level, middle-level, and low-level categories. Review data for preparation phase are gathered from each middle-level category and collapsed later, which is to present single high-level category. Next, nouns, adjectives, adverbs, and verbs are extracted from reviews by getting part of speech information using morpheme analysis module. After preprocessing, words per each topic from review are shown with LDA and only nouns in topic words are chosen as potential words for criteria. Then, words are tagged based on possibility of criteria for each middle-level category. Next, every tagged word is vectorized by pre-trained word embedding model. Finally, k-nearest neighbor case-based approach is used to classify each word with tags. After setting up preparation phase, criteria extraction phase is conducted with low-level categories. This phase starts with crawling reviews in the corresponding low-level category. Same preprocessing as preparation phase is conducted using morpheme analysis module and LDA. Possible criteria words are extracted by getting nouns from the data and vectorized by pre-trained word embedding model. Finally, evaluation criteria are extracted by refining possible criteria words using k-nearest neighbor approach and reference proportion of each word in the words set. To evaluate the performance of the proposed model, an experiment was conducted with review on '11st', one of the biggest e-commerce companies in Korea. Review data were from 'Electronics/Digital' section, one of high-level categories in 11st. For performance evaluation of suggested model, three other models were used for comparing with the suggested model; actual criteria of 11st, a model that extracts nouns by morpheme analysis module and refines them according to word frequency, and a model that extracts nouns from LDA topics and refines them by word frequency. The performance evaluation was set to predict evaluation criteria of 10 low-level categories with the suggested model and 3 models above. Criteria words extracted from each model were combined into a single words set and it was used for survey questionnaires. In the survey, respondents chose every item they consider as appropriate criteria for each category. Each model got its score when chosen words were extracted from that model. The suggested model had higher scores than other models in 8 out of 10 low-level categories. By conducting paired t-tests on scores of each model, we confirmed that the suggested model shows better performance in 26 tests out of 30. In addition, the suggested model was the best model in terms of accuracy. This research proposes evaluation criteria extracting method that combines topic extraction using LDA and refinement with k-nearest neighbor approach. This method overcomes the limits of previous dictionary-based models and frequency-based refinement models. This study can contribute to improve review analysis for deriving business insights in e-commerce market.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.33 no.3
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• pp.38-49
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• 2015

This study aims to contemplated spatial recognition in Soswaewon Garden through garden visitors poetry. It was content analysis in poetry and extract frequency from words based on relationship of author. The results were as follows. First, relationship of authors who wrote Soswaewon Garden poetry was formed in companionship. In the Yang, San-Bo(梁山甫), poetry was written by Song, Soon(宋純), Kim, Un-Geo(金彦据) and Kim, In-Hu(金麟厚) as the central figure. Especially Kim, In-Hu was playing an important role in Soswaewon Garden poetry. He was wrote many of poetry and keep friends with Yang, Ja-Jeong(梁子渟) too. In the Yang, Ja-Jung, relationship of previous generation was sustained. In addition, Ko, Gyeong-Myeong(高敬命) and Kim, Seong-Won and Jeong, Chul(鄭澈) is more closely related than others. Because blood relationship by marriage. In the Yang, Jin-Tae(梁晋泰), He formed a relationship with a celebrity and attend to international activity. Since then Yang, Jin-Tae periord, Yang, Gyeong-Ji(梁敬之) and Yang, Chae-Ji(梁采之) formed relationship of previous generation was sustained. And surrounding people was written poetry as hold a banquet. Second, plant and ornament is a popular object for writing poetry. Bamboo grove and Fine tree with a high frequency of plant element in poetry. Bamboo grove is a typical species of trees in Soswaewon Garden. It was enclosed the Soswaewon Garden. Fine tree was often used target of poetry as a single tree. Meanwhile, ornament of the wall has been used most frequently. Descendants wrote a poem to see it because Kim, In-Hu's poetry was left. This phenomenon is involves respect for the ancient sages with high frequency. In addition, behavior of viewing the landscape was mainly appeared. Third, spatial recognition of Soswaewon Garden can be divided into landscape cognition, behavior cognition and emotional cognition. In a aspect of landscape cognition, early Soswaewon Garden was recognized as a pavilion. That was used garden name to 'Soswaewon Garden' since Yang, Ja-Jung's period. That is to say, Soswaewon Garden expanded from pavilion area surrounded by trees into the whole appearance is equipped garden area. Behavior cognition was consisting drink and enjoys a landscape. In the Yang, San-Bo, authors enjoyed drinking and viewing a landscape besides walking, writing poetry, viewing the moon. But after Yang, San-Bo's period other than drinking and enjoy a landscape has appeared a low frequency. These results were changed from internal place to blood relationship into external place to companionship. In the Yang, San-Bo's emotional cognition was sorrow and yearning about leave to Soswaewon Garden with an idly atmosphere. Pleasant emotion was sustained all generation. And emotion of respect for the ancient sages was appeared since Yang, Cheon-un.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.137-152
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• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.