• Title/Summary/Keyword: Public Language

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Social Learning Values in the Justification Discourses for One Million-pyeong Park, Busan, South Korea (담론분석을 통한 100만평공원운동의 사회학습적 가치)

  • Lee, Sungkyung;Kim, Seung-Hwan
    • Journal of the Korean Institute of Landscape Architecture
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    • v.41 no.5
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    • pp.19-27
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    • 2013
  • This paper claims that the One Million-peyong Park(hereafter abbreviated as OMP) project is different from a typical citizen participatory park project by recognizing the exceptional leadership of the Civic Committee for the One Million-pyeong Park Construction(CCOMPC) in promoting and developing the OMP project. Since 2001 the CCOMPC has published a variety of written promotional materials to inform and educate the public about the project. In terms of approaching the promotional materials, this research focuses on the use of language on how the CCOMPC justifies the OMP project, namely the OMP justification discourse, and considers the discourse as a unique form of social document that represents the perspective of the CCOMPC in explaining the local environmental issues and values of urban parks to the public. Using a discourse analysis method, this research analyzes the justification discourses and investigates how they changed over the three main development phases of the OMP: the initiation and preliminary development phase(1999-2001.2), the development phase (2001.2-2008), and the time period after the greenbelt policy release on Dunchi Island(2008-present). In each discourse, the OMP project is rationalized as a citizen participation park project that (1) aims to enhance the quality of public green space in Busan, (2) is accompanied by various community engagement programs that emphasize the value of urban nature and environmental education to expand citizen participation, and (3) has contributed to the National Urban Park Bill. This research emphasizes the role of the discourses in helping the public gain a critical understanding about the local environment and values of urban parks. By analyzing the contents of the discourses, it explains the social learning values of the OMP expressed in the discourses.

Analysis of User′s Satisfaction to the Small Urban Spaces by Environmental Design Pattern Language (환경디자인 패턴언어를 통해 본 도심소공간의 이용만족도 분석에 관한 연구)

  • 김광래;노재현;장동주
    • Journal of the Korean Institute of Landscape Architecture
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    • v.16 no.3
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    • pp.21-37
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    • 1989
  • Environmental design pattern of the nine Small Urban Spaces at C.B.D. in City of Seoul are surveyed and analyzed for user's satisfaction and behavior under the environmental design evaluation by using Christopher Alexander's Pattern Language. Small Urban Spaces as a part of streetscape are formed by physical factors as well as visual environment and interacting user's behavior. Therefore, user's satisfaction and behavior at the nine Urban Small Spaces were investigated under the further search for some possibilities of application of those Pattern Languages. A pattern language has a structure of a network. It is used in sequence, going through the patterns, moving always from large patterns to smaller, always from the ones which create comes simply from the observation that most of the wonderful places of the city were not blade by architects but by the people. It defines the limited number of arrangements of spaces that make sense in any given culture. And it actually gives us the power to generate these coherent arrangement of space. As a results, 'Plaza', 'Seats'and 'Aecessibility' related design Patterns are highly evaluated by Pattern Frequency, Pattern Interaction and their Composition ranks, thus reconfirm Whyte's Praise of urban Small Spaces in our inner city design environments. According to the multiple regression analysis of user's evaluation, the environmental functions related to the satisfaction were 'Plaza', 'Accessibility' and 'Paving'. According to the free response, user's prefer such visually pleasing environmental design object as 'Waterscape' and 'Setting'. In addition to, the basic needs in Urban Small Spaces are amenity facilities as bench, drinking water and shade for rest.

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Aspect-Based Sentiment Analysis Using BERT: Developing Aspect Category Sentiment Classification Models (BERT를 활용한 속성기반 감성분석: 속성카테고리 감성분류 모델 개발)

  • Park, Hyun-jung;Shin, Kyung-shik
    • Journal of Intelligence and Information Systems
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    • v.26 no.4
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    • pp.1-25
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    • 2020
  • Sentiment Analysis (SA) is a Natural Language Processing (NLP) task that analyzes the sentiments consumers or the public feel about an arbitrary object from written texts. Furthermore, Aspect-Based Sentiment Analysis (ABSA) is a fine-grained analysis of the sentiments towards each aspect of an object. Since having a more practical value in terms of business, ABSA is drawing attention from both academic and industrial organizations. When there is a review that says "The restaurant is expensive but the food is really fantastic", for example, the general SA evaluates the overall sentiment towards the 'restaurant' as 'positive', while ABSA identifies the restaurant's aspect 'price' as 'negative' and 'food' aspect as 'positive'. Thus, ABSA enables a more specific and effective marketing strategy. In order to perform ABSA, it is necessary to identify what are the aspect terms or aspect categories included in the text, and judge the sentiments towards them. Accordingly, there exist four main areas in ABSA; aspect term extraction, aspect category detection, Aspect Term Sentiment Classification (ATSC), and Aspect Category Sentiment Classification (ACSC). It is usually conducted by extracting aspect terms and then performing ATSC to analyze sentiments for the given aspect terms, or by extracting aspect categories and then performing ACSC to analyze sentiments for the given aspect category. Here, an aspect category is expressed in one or more aspect terms, or indirectly inferred by other words. In the preceding example sentence, 'price' and 'food' are both aspect categories, and the aspect category 'food' is expressed by the aspect term 'food' included in the review. If the review sentence includes 'pasta', 'steak', or 'grilled chicken special', these can all be aspect terms for the aspect category 'food'. As such, an aspect category referred to by one or more specific aspect terms is called an explicit aspect. On the other hand, the aspect category like 'price', which does not have any specific aspect terms but can be indirectly guessed with an emotional word 'expensive,' is called an implicit aspect. So far, the 'aspect category' has been used to avoid confusion about 'aspect term'. From now on, we will consider 'aspect category' and 'aspect' as the same concept and use the word 'aspect' more for convenience. And one thing to note is that ATSC analyzes the sentiment towards given aspect terms, so it deals only with explicit aspects, and ACSC treats not only explicit aspects but also implicit aspects. This study seeks to find answers to the following issues ignored in the previous studies when applying the BERT pre-trained language model to ACSC and derives superior ACSC models. First, is it more effective to reflect the output vector of tokens for aspect categories than to use only the final output vector of [CLS] token as a classification vector? Second, is there any performance difference between QA (Question Answering) and NLI (Natural Language Inference) types in the sentence-pair configuration of input data? Third, is there any performance difference according to the order of sentence including aspect category in the QA or NLI type sentence-pair configuration of input data? To achieve these research objectives, we implemented 12 ACSC models and conducted experiments on 4 English benchmark datasets. As a result, ACSC models that provide performance beyond the existing studies without expanding the training dataset were derived. In addition, it was found that it is more effective to reflect the output vector of the aspect category token than to use only the output vector for the [CLS] token as a classification vector. It was also found that QA type input generally provides better performance than NLI, and the order of the sentence with the aspect category in QA type is irrelevant with performance. There may be some differences depending on the characteristics of the dataset, but when using NLI type sentence-pair input, placing the sentence containing the aspect category second seems to provide better performance. The new methodology for designing the ACSC model used in this study could be similarly applied to other studies such as ATSC.

A Research in the Characteristic of Arthritis Patienth (관절염환자(關節炎患者)의 특성(特性)에 대한 조사(調査) 연구(硏究))

  • Kang Jeam-Dug;Nam Chul-Hyun;Kim Gi-Yeol
    • Journal of Society of Preventive Korean Medicine
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    • v.1 no.1
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    • pp.149-165
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    • 1997
  • In order that, investigating the feature of patients suffering arthritis, analysing its contents, and grasping a Primary factor affecting it, I might offerbasic datas which could help to plan and perform healthy affairs to thake precautions beforehand, I have investigated, analysed, and studied a total of 320 patients suffering arthritis, who have received physiotherapy in hospital located in Teaegu area for five months, from November 1 1995 to March 30 1996, of which summary and conclusion is this. 1. The general feature of patients in investigative objects In the distribution of the distinction of sex, men accounted for 26.9% and women, for 73.1%, and, in the fistribution of age, 60-year-old or more, most for 27.2% and from 20 to 29 years old, least for 14.0%. In the distinction of a vocation, housewives most accounted for 34.7% and students(jobless men), least for 19.3%. In the distinction of a matrimonial state, married persons most accounted for 76.7% and people living alone(divorce, separation by death, separation), least for 11.4%. In the distinction of an economic state, the middle classes most accounted for 73.5% and the upper classes, least for 2.9%. In the distinction of their academic careers, graduates of a primary school most accounted for 26.9% and graduates of university, for 14.1%, of which patients, having the ability to decode the national language, reached to 11.3%. In the distinction of the house form, people living in independent houses most accounted for 76.4% and residents in apartment(having an elevator), least for 9.4%. 2. In the distribution of the recurring state in the distinction of the feature, the recurring group was more than the group of patients falling that ill at first as 62.2% and in the distinction of the feature of the recurring group, the recurring group turned high in case of men being from 50s to 60s years old or more, people living alone (divorce, separation by death, separation), students (joblessmen), people working in farming, stockbeeding, forestry, fisheries, a simple labour, graduates of a primary school I having the ability to decode the national language, the upper classes, people part two years since they begined to suffer arthritis, people who had members having ever experienced arthritis among families. 3. In the distribution of arthritis on the distinction of bodily pars, a knee articulation most accounted for 50.2% and the articulation of fingers, for 8.8%, wile the simultaneous, several parts (multiple) accounted for 35.1%. In the distinction of the feature, arthritis of a knee turned high in case of men being from 20s to 30s years old, unmarried persons, people having academic careers of university, the middle classes, residents in apartment (having stairs). In the dictnction of a feature the case of several parts (multiple) turned high in case of women being from 50s to 60s years old or more, people living alone (divorce, separation by death, separation), people having the ability to decode th. national language, the graduates of a primary school, the upper classes, residents in apartment (having elevator). 4. In the distribution of arthritis on e distinction of a contracting term, two years or more most accounted for 51.6% and the case of contacting from one year to two years, for 15.3%. Analysing the distinction of the feature, the case of two years or more turned high in case of women being from 50s to 60s years old or more, people living alone (divorce separation by death, separation), the upper classes, people having the ability to decode the national language, residents in apartment (having elevator). 5. In the distribution of an treatment institution before patients came to help, their not curing most accounted for 39.1%, general, orthopedic, neurological surgery (physical therapy), for. 20.0%, and th. therapy of Chinese medicine (acupuncture, moxacautery, Chinese medicine), for 17.5%, and a pharmacy (medical therapy), for 13.4%. The case of patients not curing, in the distinction of a feature, turned high in case of men 20s years old, unmarried, the lower classes, people having academic careers of university, residents in apartment (having elevator). 6. In e distribution of the extent of satisfaction with treatment, common most accounted for 54.4% and some satisfaction, for 32.8%. The case of common, in the distinction of a feature, turned high, in case of men living alone from 50s to 60s years old (divorce, separation by death, separation), married persons, the upper classes, people having academic careers of university, residents in independent house, residents in apartment (having elevator), 7. In the distribution of the degree of knowledge of the cause of arthritis, patients knowing that the cause is to use very much a articulation in normal times most accounts for 60.1%, and patients knowing the state of short nutrition as a cause, for 2.5%. The case of patients knowing that the cause is to use very much in normal times, in the distinction of a feature, turned high in·case of ment being 20s and 60s years old or more, unmarried persons, e lower classes, people having the ability to decode. the national language, people having academic careers of university, residents in apartment (having stairs), 8. In the distribution of the state of physical exercise before arthritis contracted, patients exercising very much on the whole most accpimend for 40.3%, and patients not exercising, for 34.7%. The case of patients exercising very much on the whole, in the distinction of the feature, turned high in case of men being from 50s to 60s years old or more, people living alone(divorce, separation by death, separation), the lower classes, people having the ability to decode the national language, graduates of a primary school, residents in apartment (having elevator). 9. In the taste of patients suffering from arthritis, while the group of patients falling that ill at first and the recurring group didn't smoke cigarets, during alcohol and coffee on the whole, and the group of patients falling once again that ill drank a cup of distilled linquor and three cup of coffee or more on the whole per one day, and the group of patients falling that ill at first liked sort of vegetables and the recurring group liked very much sons of vegetables and fresh and meat in their loving food normal times. 10. Analysing the distribution on the dining table used by patients and the structure of a powder room, at first, in the structure of a powder room, the group of patients filling that ill have a toilet stool using as their sits, and a Bush toilet on the whole, and the recurring group, a toilet stool using as their sits and conventional type, and in the structure of a dinning table, the group of patients falling that ill at first and the recurring group turned high, each as 66.9% and 6.3%, who have a dining table carring here and there. 11. In the distribution of patients of arthritis in relation to stress, the case that they feeled severly symptoms of arthritis when thay got stress, turned high, each, as 78.6% in the recurring poop, and the case not knowing, as 61.5% in the first group. In the extent of stress normal times, the case that they got much stress on the whole turned high, each, as 72.4% in e recurring group, and the care that got less stress on the whole, as 60.0%. 12. In the distribution on the distinction of symptoms and impedimental extent, the recurring group turned high in each variable. Analysing the feature of the recurring group, in the distinction of symptoms, the case that they fooled much that the node of an articulation is stiff, turned high, as 71.6, and in the distinction of treatment before. patients came to helpk, the theraphy of Chinese medicine (physical theraphy), as 84.4%, the theraphy of Chinese medicine (acupuncture, moxacautery, Chinese medicine), as 73.2%, and in the distinction of the satisfing extent on treatment, the case of comman, as 72.3%, and in the cause of arthritis, the case not recruiting their health after a birth, as 68.5%, and the case not recovering wholely an articulation having got hurt, as 62.8%, and in the state of physical exercise before they begined suffering from arthritis, the case exercising very much on the whole, (as 74.2%), and in the extent of subjective impediment, the case of not being able to act almost, as 66.7%, the case of acting but feeling some hard, as 66.3%. 13. The correlation in variables in relation to arthritis Analysing realted variables, the recurring frequency showed correlation with such as the extent that patients got stress normal times, and the exercising state before suffering arthritis, and showed contra-correlation with academic careers, the wights, coffee. The cigaret, e loving food of taste, showed corralation with the weight, stature, alcohole as the loving food of taste. On the basis of this result medical members of heal, who are related to the regular education, public education or development of this program, should be concerned to prevent orthris.

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Effect of the Influential Factors on Brand Equity (브랜드 자산가치의 형성에 미치는 영향요인에 관한 연구)

  • Kang, Seuk-Jung
    • Journal of Global Scholars of Marketing Science
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    • v.8
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    • pp.233-267
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    • 2001
  • The management environment in Korea today is undergoing rapid changes; in particular, domestic corporations and businesses are confronting formidable adversity with IMF crisis and WTO. Though cost cutback, higher quality, rapid production, and diversification of products were accepted as important requirements for competitiveness in the past, they have been replaced by brand power. Consumption patterns have changed their focus from function to image orientation. This is why managers in corporations have invested enormous amounts of resources into producing powerful brands, which can attract consumers' attention greatly enough to improve the image of their products. Brands are regarded as a vital vehicle for marketing strategies and thus as a legal asset. Brands with remarkable and favorable image can secure a loyal consumer groups stable revenues. M & A, currently active between corporations, makes brand equity all the more important. The purpose of the present study was to investigate the effect of internal marketing and increased brand diversification on brand equity by combining them as influential factors with marketing mix factor. For this purpose, literature review was make on previous fragmented studies of influential factors on brand equity build-up. Based on the findings of this study, some operational implications were suggested for marketing managers. The findings and implications of the present study are as follows; First, efficient communication among organization members was found to have a significant effect on product quality. Second, job satisfaction and efficient communication among members was shown to significantly influence price policies. Thirdly, efficient communication among organization workers proved to have a significant effect on distribution strategies. Forth, efficient communication among members was demonstrated to significantly influence advertisement and other public-relations activities. Fifth, opacity of market environment appeared to have a significant effect on product quality, prior market entrance as perceived by organization members turned to be of negative influence on product quality. Sixth, opacity of market environment was found to have a significant effect on price policies. Seventh, opacity of market environment was shown to be of significant effect on distribution strategies. Eighth, grater opacity of market environment proved to improve advertisement and other public-relations activities. Ninth, price policies, distribution strategies, advertisement and public-relations activities were found to have a significant effect on brand equity value. To sum up these findings, in order for corporations and businesses to cope with consumers' needs that are increasingly segmented, internal marketing strategies and brand diversification should be implemented so as to generate greater synergy effect. It is also important to stress that differentiated, higher competitiveness should be secured for Korean corporations and businesses to survive in the drastically changing, globalized market environment. In this regard, continuous and long-term management strategies for brand equity build-up should be ensured and is essential in the present unlimited competition. The last but not least important point to notice is that to increase brand equity value, intensive investment and constant emphasis should be made on internal marketing management on intra-organizational members before strengthening external marketing.

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Sentiment Analysis of Korean Reviews Using CNN: Focusing on Morpheme Embedding (CNN을 적용한 한국어 상품평 감성분석: 형태소 임베딩을 중심으로)

  • Park, Hyun-jung;Song, Min-chae;Shin, Kyung-shik
    • Journal of Intelligence and Information Systems
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    • v.24 no.2
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    • pp.59-83
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    • 2018
  • With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

A Symbolic Characteristic of Mimetic Words in Published Cartoon: Focusing on Works of Heo, Young Man (허영만의 작품에서 나타난 효과태의 상징어적 특징과 활용)

  • O, Yul Seok;Yoon, Ki Heon
    • Cartoon and Animation Studies
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    • s.30
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    • pp.169-199
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    • 2013
  • In various directions of cartoon, vertical stroll direction is opposite to the page direction of existing published cartoon with the popularity of webtoon and established new genre. Lots of studies on published cartoon focus on the cut direction by page, but webtoon doesn't have any concept of page. The pivot of cartoon oriented people is changed from paper to computer monitor as times go by, characteristics of media are changed and media is gradually diversified. Like the strengthening of mobile caused by smart phone's popularity, tablet PC's propagation in public education, etc. cartoon is included to the environment of media which is rapidly changed. In this situation, one of cartoon's unchanged important identities can be the direction made by harmony between picture and text. This thesis analyzed symbolic characteristics and effective value of hyogwatae, mimetic words of cartoon, focusing on works of Heo, Young Man. Hyogwatae just delivers not only sound but also shape, feeling, status, etc. and has significant characteristics by invoking the imaginary structure of literature. Strengths of modern Korean, various linguistic expressions and syllabic systems, let people feel minute feeling of language and difference of emotion and remember the memory through the direct and indirect experiences, so it makes it nuance. Because of the characteristics, representative works of Heo, Young Man have commercialization and writer characteristics, have communicated with people for a long time and have plentiful knowledge of Korean cartoon. The characteristics of hyogwatae in Heo, Young Man's cartoon make a lot of effects for the expression and delivery of cartoon more than the general expectation. When conducting the study focusing on the symbolic process of language, uncertainty and vague standard of judgement caused by the wide factors of study on the direction of general cartoon could be endured. And, through the Heo, Young Man's deep analysis on hyogwatae's direction, readers enjoy the process while inferring actually and intellectually between pictures and sentences. In the process, the equipment stimulating imagination more than pictures, effects and dialogues is hyogwatae. It's reader's equipment of active participation and its strength is symbolic structure.

Performance Evaluation of a Dynamic Bandwidth Allocation Algorithm with providing the Fairness among Terminals for Ethernet PON Systems (단말에 대한 공정성을 고려한 이더넷 PON 시스템의 동적대역할당방법의 성능분석)

  • Park Ji-won;Yoon Chong-ho;Song Jae-yeon;Lim Se-youn;Kim Jin-hee
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.11B
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    • pp.980-990
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    • 2004
  • In this paper, we propose the dynamic bandwidth allocation algorithm for the IEEE802.3ah Ethernet Passive Optical Network(EPON) system to provide the fairness among terminals, and evaluate the delay-throughput performance by simulation. For the conventional EPON systems, an Optical Line Termination (OLT) schedules the upstream bandwidth for each Optical Network Unit (ONU), based on its buffer state. This scheme can provide a fair bandwidth allocation for each ONU. However, it has a critical problem that it does not guarantee the fair bandwidth among terminals which are connected to ONUs. For an example, we assume that the traffic from a greedy terminal increases at a time. Then, the buffer state of its ONU is instantly reported to the OLT, and finally the OW can get more bandwidth. As a result, the less bandwidth is allocated to the other ONUs, and thus the transfer delay of terminals connected to the ONUs gets inevitably increased. Noting that this unfairness problem exists in the conventional EPON systems, we propose a fair bandwidth allocation scheme by OLT with considering the buffer state of ONU as welt as the number of terminals connected it. For the performance evaluation, we develop the EPON simulation model with SIMULA simulation language. From the result of the throughput-delay performance and the dynamics of buffer state along time for each terminal and ONU, respectively, one can see that the proposed scheme can provide the fairness among not ONUs but terminals. Finally, it is worthwhile to note that the proposed scheme for the public EPON systems might be an attractive solution for providing the fairness among subscriber terminals.

Research on ITB Contract Terms Classification Model for Risk Management in EPC Projects: Deep Learning-Based PLM Ensemble Techniques (EPC 프로젝트의 위험 관리를 위한 ITB 문서 조항 분류 모델 연구: 딥러닝 기반 PLM 앙상블 기법 활용)

  • Hyunsang Lee;Wonseok Lee;Bogeun Jo;Heejun Lee;Sangjin Oh;Sangwoo You;Maru Nam;Hyunsik Lee
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.11
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    • pp.471-480
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    • 2023
  • The Korean construction order volume in South Korea grew significantly from 91.3 trillion won in public orders in 2013 to a total of 212 trillion won in 2021, particularly in the private sector. As the size of the domestic and overseas markets grew, the scale and complexity of EPC (Engineering, Procurement, Construction) projects increased, and risk management of project management and ITB (Invitation to Bid) documents became a critical issue. The time granted to actual construction companies in the bidding process following the EPC project award is not only limited, but also extremely challenging to review all the risk terms in the ITB document due to manpower and cost issues. Previous research attempted to categorize the risk terms in EPC contract documents and detect them based on AI, but there were limitations to practical use due to problems related to data, such as the limit of labeled data utilization and class imbalance. Therefore, this study aims to develop an AI model that can categorize the contract terms based on the FIDIC Yellow 2017(Federation Internationale Des Ingenieurs-Conseils Contract terms) standard in detail, rather than defining and classifying risk terms like previous research. A multi-text classification function is necessary because the contract terms that need to be reviewed in detail may vary depending on the scale and type of the project. To enhance the performance of the multi-text classification model, we developed the ELECTRA PLM (Pre-trained Language Model) capable of efficiently learning the context of text data from the pre-training stage, and conducted a four-step experiment to validate the performance of the model. As a result, the ensemble version of the self-developed ITB-ELECTRA model and Legal-BERT achieved the best performance with a weighted average F1-Score of 76% in the classification of 57 contract terms.

Analysis of the Impact of Generative AI based on Crunchbase: Before and After the Emergence of ChatGPT (Crunchbase를 바탕으로 한 Generative AI 영향 분석: ChatGPT 등장 전·후를 중심으로)

  • Nayun Kim;Youngjung Geum
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.19 no.3
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    • pp.53-68
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    • 2024
  • Generative AI is receiving a lot of attention around the world, and ways to effectively utilize it in the business environment are being explored. In particular, since the public release of the ChatGPT service, which applies the GPT-3.5 model, a large language model developed by OpenAI, it has attracted more attention and has had a significant impact on the entire industry. This study focuses on the emergence of Generative AI, especially ChatGPT, which applies OpenAI's GPT-3.5 model, to investigate its impact on the startup industry and compare the changes that occurred before and after its emergence. This study aims to shed light on the actual application and impact of generative AI in the business environment by examining in detail how generative AI is being used in the startup industry and analyzing the impact of ChatGPT's emergence on the industry. To this end, we collected company information of generative AI-related startups that appeared before and after the ChatGPT announcement and analyzed changes in industry, business content, and investment information. Through keyword analysis, topic modeling, and network analysis, we identified trends in the startup industry and how the introduction of generative AI has revolutionized the startup industry. As a result of the study, we found that the number of startups related to Generative AI has increased since the emergence of ChatGPT, and in particular, the total and average amount of funding for Generative AI-related startups has increased significantly. We also found that various industries are attempting to apply Generative AI technology, and the development of services and products such as enterprise applications and SaaS using Generative AI has been actively promoted, influencing the emergence of new business models. The findings of this study confirm the impact of Generative AI on the startup industry and contribute to our understanding of how the emergence of this innovative new technology can change the business ecosystem.

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