• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.1
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• pp.88-98
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• 1994

A new neural network architecture called the Parallel. Self-Organizing Hierarchical Neural Network (PSHNN) is presented. The new architecture involves a number of stages in which each stage can be a particular neural network (SNN). The experiments performed in comparison to multi-layered network with backpropagation training and indicated the superiority of the new architecture in the sense of classification accuracy, training time,parallelism.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.304-307
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• 2001

본 연구에서는 G7 감성공학 연구에서 발생한 231 개의 지표들을 이용자가 접근 용이하도록 분류하여 그 체계를 갖추는 작업을 수행하여 web 상에 제공함으로써 감성공학에 대해 적은 지식을 가진 이용자라 할지라도 분류체계에 따라 지표를 검색하고 이용할 수 있게 하는 것을 목표로 하고자 한다. 본 연구의 결과를 이용하면 현재 서비스 실시 중인 감성공학 인터넷 사이트(http://www.gamsung.or.kr)에서 감성지표의 검색 및 조회의 사용성을 향상 시킬 것으로 기대한다.

• Journal of Preventive Medicine and Public Health
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• v.10 no.1
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• pp.102-108
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• 1977

A study on the sickness distribution and mode of treatment in rural area was conducted during the period from July '75 to Aug. '75 using 1,225 households, 7,918 population (4,017 male, 3,901female) and 343 cases th at found during the period of survey who had beenlived in Nammyon, Hwasoongun, Chonnam. The summarized results were as follows : 1. Average family number per household was 6.5 and prevalence rate was 43.3 (21.2 for male, 22.1 for female). 2. General sickness distribution by classification of disease according to W.H.O. was highest in disease of the nervous system and sense organs (21.3%), and important others were disease of the digestive system (16.9%) and disease of the respiratory system(14.8%). In male, distribution was in order of downward disease of digestive system, disease of nervous system and sense organs, disease of skin, cellular tissue, bones and organs of movement, and disease of respiratory system. In female, distribution was in order of downward disease of nervou s system and sense organs, disease of respiratory system, disease of digestive system, and disease of skin, cellular tssue, bones and organs of movement. 5. Types of treatment in both sexes were showed that home and folkmedicine (41.1%), pharmacy(24.5%), admission to hospital or clinic (16.9%), out-patient clinic (10.8%) and herbmedicine (6.7%) in downward order. Hospital and clinic utility rate was 27.5% (31.5 for male, 24.0 for female) and it was highest in 0-4 age groups and lowest in 40-49 year age groups. 4. Hospital and clinic utility rate was highest in neoplasms, and the other hands, disease of the nervous system and sense organs and disease of the digestive system were the highest groups in the all types of treatment other than hospital and clinic. 5. On the results of treatment not, exactly replied answer was the highest (41.7%) and only 16.0% said complete recovery. In completely recovered cases, hospital and clinic using group was predominant (58.2%) and in aggravated cases, home and folkmedicine using group was highest.

• The Journal of Bigdata
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• v.5 no.1
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• pp.197-208
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• 2020

Lexical ambiguity means that a word can be interpreted as two or more meanings, such as homonym and polysemy, and there are many cases of word sense ambiguation in words expressing emotions. In terms of projecting human psychology, these words convey specific and rich contexts, resulting in lexical ambiguity. In this study, we propose an emotional classification model that disambiguate word sense using bidirectional LSTM. It is based on the assumption that if the information of the surrounding context is fully reflected, the problem of lexical ambiguity can be solved and the emotions that the sentence wants to express can be expressed as one. Bidirectional LSTM is an algorithm that is frequently used in the field of natural language processing research requiring contextual information and is also intended to be used in this study to learn context. GloVe embedding is used as the embedding layer of this research model, and the performance of this model was verified compared to the model applied with LSTM and RNN algorithms. Such a framework could contribute to various fields, including marketing, which could connect the emotions of SNS users to their desire for consumption.

• Journal of Fisheries and Marine Sciences Education
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• v.25 no.1
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• pp.246-259
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• 2013

The principal purpose of this study is to analyze school organizational culture in secondary school in Busan. This study measures background variables such as gender, teaching experience, classification of school, grade of school, and scale of school. The results of the study are as follows : First, to see the difference on the perception of organizational culture depending on gender, female teachers have a stronger sense of professionalism, community spirit and consideration than male teachers. Second, to see the difference on the perception of organizational culture in terms of teaching experience, teachers who have more than 21 years of teaching experience have a more positive perception on decision-making and consideration than those who have 11~20 years of teaching experience. Third, to see the difference on the perception of organizational culture according to classification of school, public schools have a more positive perception on every item such as professionalism, decision-making, community spirit, and consideration than private school. Fourth, to see the difference on the perception of organizational culture in terms of classification of schools, secondary schools have a more positive perception on professionalism and community spirit than high schools. Lastly, as it is seen in the difference on the perception of organizational culture depending on scale of school, schools which have 13~35 classes have a more positive perception on professionalism than others.

• ETRI Journal
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• v.44 no.3
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• pp.413-425
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• 2022

The study of literary texts is one of the earliest disciplines practiced around the globe. Poetry is artistic writing in which words are carefully chosen and arranged for their meaning, sound, and rhythm. Poetry usually has a broad and profound sense that makes it difficult to be interpreted even by humans. The essence of poetry is Rasa, which signifies mood or emotion. In this paper, we propose a poetry classification-based approach to automatically extract similar poems from a repository. Specifically, we perform a novel Rasa-based classification of Hindi poetry. For the task, we primarily used lexical features in a bag-of-words model trained using the support vector machine classifier. In the model, we employed Hindi WordNet, Latent Semantic Indexing, and Word2Vec-based neural word embedding. To extract the rich feature vectors, we prepared a repository containing 37 717 poems collected from various sources. We evaluated the performance of the system on a manually constructed dataset containing 945 Hindi poems. Experimental results demonstrated that the proposed model attained satisfactory performance.

• The Korean Journal of Community Living Science
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• v.27 no.1
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• pp.31-47
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• 2016

This research examines the effects of consumers' moderation and simplicity, autonomy, and income level on happiness, and based on this, classifies consumer types and examines the differences in consumer happiness and life happiness in accordance with this classification. The questionnaire survey was conducted on adults in their 20's through 60's. Moreover, hierarchical regression analysis, cluster analysis, and the analysis of variance were conducted. The results of this research are as follows. First, on consumer happiness, moderation and simplicity, income level, autonomy, education level, and gender had significant effects; on life happiness, moderation and simplicity, income level, autonomy, and education level had significant effects. Second, consumers were classified into three types according to moderation and simplicity, autonomy, and income level, and when making a comparison based on these factors between consumer happiness and life happiness, both consumer happiness and life happiness showed significant differences, but the detailed aspects were different. In the case of consumer happiness, non-autonomous moderation and simplicity type were reported to have the highest sense of happiness, followed by autonomous moderation and simplicity type, and passive moderation and simplicity type, but in the case of life happiness, autonomous moderation and simplicity type were reported to have the highest sense of happiness, followed by non-autonomous moderation and simplicity type, and passive moderation and simplicity type.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1148-1157
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• 2022

In 2019, COVID-19 changed many people's lives. Among them, metaverse supports non-face-to-face services through various methods, replacing daily tasks. This phenomenon was created and formed like a culture due to the prolonged COVID-19. In this paper, the fun elements used in the existing game were organized to find out the fun factors of the metaverse, and the items and contents were reclassified according to the metaverse with five experts. Classification was classified using reproducibility, sensory fun [graphic, auditory, text, manipulation, empathy, play, perspective], challenging fun [absorbedness, challenging, discovery, thrill, reward, problem-solving], imaginative fun [new story, love, freedom, agency, expectation, change], social fun[rules, competition, social behavior, status, cooperation, participation, exchange, belonging, currency transaction], interactive fun[decision making, communication sharing, hardware, empathy, nurturing, autonomy], realistic fun[sense of unity in reality, easy of learning, adaptation, intellectual problems solving, pattern recognition, sense of reality, community], and creative fun[application, creation, customizing, virtual world].

• 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 Korean Institute of Educational Facilities
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• v.3 no.2
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• pp.25-35
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• 1996

This study is to find countermeasures of facility space according to the development of new educational program and the opening of education market from the renewal of existing facilities. The renewal is consider as the worldwide trend for enhancing added value of the facilities in economic side of educational facilities as well as educational contents. This study selects six from 94 elementary schools in Kwangju-city to examine our educational conditions, understand using conditions and recognition of existing space and possibility of the recycle. The hypothesis that recognition of existing facility space in school may be varied according to physical conditions of children is made in four sides, six elements and two trends are extracted and then life pattern, size, sense of materials and cognition of three types of passage space are analyzed. Accordingly, this study obtains such results that passage space is life space having strong place concept and there is the possibility of renewal of existing school building facilities corresponding to multipurpose of school facilities.