• CELLMED
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• v.2 no.2
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• pp.12.1-12.11
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• 2012

Traditional Medicinal System (TMS) is one of the centuries-old practices and long-serving companions to the human kind to fight against disease and to lead a healthy life. Every indigenous people have been using their unique approaches of TMS practice where among, the Chinese, Indian and African TMSs are world-wide renowned. India has a unique Indian System of Medicines (ISM) consisting of Ayurveda, Siddha, Unani, Naturopathy and Homoeopathy. Siddhars are the saints as well as the eminent scholars, who have attained Ashta-mahasiddhi [Tamil: (Ashta-Eight; Mahasiddhi-Power)] or enlightment. They have postulated, practiced, immensely contributed and have established the concept of the Tamil medicinal system called Siddha System of Medicine (SSM). From ancient time, SSM has flourished and has been widely practiced in the southern part of India particularly in Tamil Nadu. The induction of the modern medicinal system has immensely influenced the existence of SSM and has made the SSM principles and practices undervalued/extinct. However, at present, still a considerable group of people are using the SSM as a basic health-care modality. In this context, the present scrutiny deals with the TMS history, its significance with a special reference to SSM history, Siddhars, the basic concept of SSM, its diagnostic procedures, materia medica and treatment. Conclusively, Siddha is one of the most ancient indigenous health practices despite its several thorny challenges and issues, which needs to be flagged effectively and to be preserved and revitalized in the international arena in the near future.

• The Research Journal of the Costume Culture
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• v.13 no.4 s.57
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• pp.550-563
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• 2005

These days, photoshop and illustrator program can make a fashion illustration express easily and speedily, And they can also express a feeling and sensitivity of fashion illustrator by a tool and effect more than a manual work's media. The purpose of this study was to analyze a visual expression and characteristics in fashion illustration using 2D graphics. The method of this study was to analyze the fashion illustration books using 2D graphics. The visual expressions in fashion illustration using 2D graphics were as follows: Fashion illustration was based on a sketch or photography, and used a composition, drawing, mapping, painting, and manual work's re-touching. Characteristics of visual expression were as follows: First, a image composition was showed discontinuity and heterogeneity of image, new context and composition, and allowance of reality. Second, image transform was showed image overlap, body transformation by image recomposition, and deformed transformation by vector drawing. Third, hyper-real was showed precise touching, mechanical and neutral image, omission of background and focus of an object's characteristic and information. Fourth, following a realistic expression was showed simplified color, shading, dominant view point of fashion illustrator by omission, and daily lift style. Fifth, following a pictorial expression was showed non-fixed and irregular line, natural painting, and drawing and painting by conventional pictorial media. In conclusion, a photoshop and illustrator in 2D graphics will serve as a new media far fashion illustration with a manual work. And they will not only intensify a capacity as a commercial role of fashion illustration but also present a positive motive for students learning a fashion illustration.

• School Mathematics
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• v.18 no.2
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• pp.349-373
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• 2016

Comparison of curriculum between various countries is a major research method for studying a course and content quoted on Korea's national curriculum. Therefore this research focuses on comparing and analyzing a new curriculum which Australia has announced on 2012 and conducting since 2015. From this research result, we found that Australia's curriculum achievement shows some unique characteristics. Such examples can be dealing a concept with real life context and proposing a mathematical content specifically. Also they introduce the definite integral by defining to the sum of series. There are other characteristics such as modelling motion, and numerical integration which Korea's highschool curriculum achievement doesn't deal with, and the content of vector calculus is handled more deeply. As a result of analyzing Australia's textbook, it fully deals with the supplementary notion to help understand mathematical definition. Hence further research will be needed later on to relieve the aspect of cognitive burden on Korean learners.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.02a
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• pp.16-21
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• 2004

In recent years, the importance of geospatial data have been emphasized not only for the national GIS programs and but also in the value added commercial and industry markets. There is no doubt that GIS, GPS, aerial and satellite imagery data were provided powerful tools to support national information infrastructure for geospatial database. While great emphasis has been laid on the geospatial data, there has been little analysis or evaluation of how to maximize the benefits of using these information sources. Also, with the proliferation of geographic data and information sources such as satellite imagery, digital aerial photography, digital topographic and vector data, there is a great need to inform professionals from all disciplines as to the benefits of these information sources and how to best put them to use within any given application. From the first publication of KSGPC(Korean Society of Geodesy, Photogrammetry and Cartography) papers in 1981, our objective was, and is, to help develop the wider spectrum of GIS in the academy and industry by exposing new users to the benefits of GIS, remote sensing, mapping, GPS and photogrammetry. In this presentation, we will introduce KSGPC works and will evaluate GIS-related governmental policies and programs in Korea for the past and the future to present different status between Korea and Russia. It is now important to investigate lessons learnt from two countries' experiences and developed an empirical framework to combine outcomes from GIS-related researches in Korea and Russia. This may enable GIS professionals to gain a wider range of experiences in the international context, and consequently, help them to develop new markets for GIS. Therefore, we arranged the possible action items and interesting points to corporate and to promote the academic growth in the practice of GIS.

• Asia-Pacific Journal of Business
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• v.12 no.1
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• pp.209-223
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• 2021

Purpose - The purpose of this study was to investigate the relationship between Korea agricultural productions and Greenhouse Gas (GHG) emissions based on Environmental Kuznets Curve (EKC) hypothesis. Design/methodology/approach - This study utilized time series data of economic growth, greenhouse gas, agricultural productions, trade dependency, and energy usages. In order to econometric procedure of EKC hypothesis, this study utilized unit root test and cointegration test to check staionarity of each variable and also adopted Vector Error Correction Model (VECM) and Ordinary Least Square (OLS) to analyze the short and long run relationships. Findings - In the short run, greenhouse gas emissions resulting from economic growth show an inverse U-shape relationship, and an increase in agricultural production and energy consumption led to increase in greenhouse gas emission. In the long run, total GHG emissions and CO2 emissions show an N-shaped relationship with economic growth, and an increase in agricultural production has resulted in a decrease in total GHG and CO2 emissions. However, methane (CH4) and nitrous oxide (N2O) emissions showed an inverse U-shape relationship with economic growth, which indicated the environment and production process of agricultural production. Research implications or Originality - Korea agricultural production has different effects on the GHG emission sources, and in particular, methane (CH4) and nitrous oxide (N2O) emissions show to increase as the agricultural production expansions, so policy or technological development in related sector is required. Especially, in the context of the 2030 GHG reduction road-map, if GHG-related reduction technologies or policies are spread, national GHG emission reduction targets can be achieved and this is possible to predict the decline in production in the sector and damage to the related industries.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.33-38
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• 2018

Recently, we are trying to predict the emotion from various information and to convey the emotion information that the supervisor wants to inform the audience. In addition, audiences intend to understand the flow of emotions through various information of non-dialogue parts, such as cinematography, scene background, background sound and so on. In this paper, we propose to extract emotions by mixing not only the context of scripts but also the cinematography information such as color, background sound, composition, arrangement and so on. In other words, we propose an emotional prediction system that learns and distinguishes various emotional expression techniques into dialogue and non-dialogue regions, contributes to the completeness of the movie, and quickly applies them to new changes. The precision of the proposed system is improved by about 5.1% and 0.4%, and the recall is improved by about 4.3% and 1.6%, respectively, when compared with the modified n-gram and morphological analysis.

• Smart Media Journal
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• v.10 no.1
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• pp.39-46
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• 2021

This study is about a method of extracting a summary from a news article in consideration of the importance of each sentence constituting the article. We propose a method of calculating sentence importance by extracting the probabilities of topic sentence, similarity with article title and other sentences, and sentence position as characteristics that affect sentence importance. At this time, a hypothesis is established that the Topic Sentence will have a characteristic distinct from the general sentence, and a deep learning-based classification model is trained to obtain a topic sentence probability value for the input sentence. Also, using the pre-learned ELMo language model, the similarity between sentences is calculated based on the sentence vector value reflecting the context information and extracted as sentence characteristics. The topic sentence classification performance of the LSTM and BERT models was 93% accurate, 96.22% recall, and 89.5% precision, resulting in high analysis results. As a result of calculating the importance of each sentence by combining the extracted sentence characteristics, it was confirmed that the performance of extracting the topic sentence was improved by about 10% compared to the existing TextRank algorithm.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.333-335
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• 2022

본 논문에서는 기존에 두 가지 모델이 필요했던 작업을 하나의 모델로 처리할 수 있는 자연어 처리 아키텍처를 제안한다. 단일 모델로 알츠하이머 환자의 언어패턴과 대화맥락을 분석하고 두 가지 결과인 환자분류와 챗봇의 대답을 도출한다. 일상생활에서 챗봇으로 환자의 언어특징을 파악한다면 의사는 조기진단을 위해 더 정밀한 진단과 치료를 계획할 수 있다. 제안된 모델은 전문가가 필요했던 질문지법을 대체하는 챗봇 개발에 활용된다. 모델이 수행하는 자연어 처리 작업은 두 가지이다. 첫 번째는 환자가 병을 가졌는지 여부를 확률로 표시하는 '자연어 분류'이고 두 번째는 환자의 대답에 대한 챗봇의 다음 '대답을 생성'하는 것이다. 전반부에서는 셀프어탠션 신경망을 통해 환자 발화 특징인 맥락벡터(context vector)를 추출한다. 이 맥락벡터와 챗봇(전문가, 진행자)의 질문을 함께 인코더에 입력해 질문자와 환자 사이 상호작용 특징을 담은 행렬을 얻는다. 벡터화된 행렬은 환자분류를 위한 확률값이 된다. 행렬을 챗봇(진행자)의 다음 대답과 함께 디코더에 입력해 다음 발화를 생성한다. 이 구조를 DementiaBank의 쿠키도둑묘사 말뭉치로 학습한 결과 인코더와 디코더의 손실함수 값이 유의미하게 줄어들며 수렴하는 양상을 확인할 수 있었다. 이는 알츠하이머병 환자의 발화 언어패턴을 포착하는 것이 향후 해당 병의 조기진단과 종단연구에 기여할 수 있음을 보여준다.

• Land and Housing Review
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• v.14 no.4
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• pp.95-102
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• 2023

Numerous investigations have explored the integration of machine leaning algorithms with high-resolution drone image for object detection in urban settings. However, a prevalent limitation in vehicle extraction studies involves the reliance on bounding boxes rather than instance segmentation. This limitation hinders the precise determination of vehicle direction and exact boundaries. Instance segmentation, while providing detailed object boundaries, necessitates labour intensive labelling for individual objects, prompting the need for research on automating unsupervised instance segmentation in vehicle extraction. In this study, a novel approach was proposed for vehicle extraction utilizing unsupervised SVM classification applied to vehicle bounding boxes in drone images. The method aims to address the challenges associated with bounding box-based approaches and provide a more accurate representation of vehicle boundaries. The study showed promising results, demonstrating an 89% accuracy in vehicle extraction. Notably, the proposed technique proved effective even when dealing with significant variations in spectral characteristics within the vehicles. This research contributes to advancing the field by offering a viable solution for automatic and unsupervised instance segmentation in the context of vehicle extraction from image.

• Science of Emotion and Sensibility
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• v.11 no.4
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• pp.461-480
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• 2008

There are innumerable studies on technology adoption and usage continuance; most examine cognitive factors while affective factors or the feelings of users are left relatively unexplored. Although attitude and user satisfaction are factors commonly considered in Information Systems(IS) research, they represent only some aspects of feelings. In contrast, researchers in diverse fields have begun to note the importance of feelings in understanding and predicting human behavior. Feelings are anticipated to be essential particularly in the context of modern applications, such as mobile internet(M-internet) services, where users are not simply technology users but also service consumers. Drawing on the support of consumer research, social psychology and computer science, this study proposes a balanced cognition-affect model of IS continuance. Prior works in relation to IS research have already considered the emotional factors. The common factors are enjoyment, anxiety, affect and satisfaction. The main difference in our study is that the factors that we used are the primary dimensions of affect according to Circumplex Model of Affect. The horizontal axis of the model represents the pleasure dimension and the vertical represents the arousal dimension. Other emotional factors such as enjoyment and anxiety can be viewed as a combination of these two dimensions, and they can be placed in the vector space formed by these two primary dimensions. Affect has been defined as the enjoyment a person derives from using computers. Satisfaction has different conceptualizations. It has been conceptualized as judgment based on the expectation disconfirmation theory. Thus, while prior works considered the direct and indirect effects of "feeling-related constructs"(enjoyment and anxiety) on usage behavior, our study proposes effects of "feeling-based constructs"(pleasure and arousal). The balanced cognition-affect model is tested in a survey of, M-internet service users. The results establish the validity of the model.