• 제목/요약/키워드: Knowledge based systems

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비정형 건물일체형 태양광 발전 시스템 규칙기반 BIM설계 지원 도구 개발 (Development of a Rule-based BIM Tool Supporting Free-form Building Integrated Photovoltaic Design)

  • 홍성문;김대성;김민철;김주형
    • 한국BIM학회 논문집
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    • 제5권4호
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    • pp.53-62
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    • 2015
  • Korea has been at the forefront of green growth initiatives. In 2008, the government declared the new vision toward 'low-carbon society and green growth'. The government subsidies and Feed-in Tariff (FIT) increased domestic usage of solar power by supplying photovoltaic housing and photovoltaic generation systems. Since 2000, solar power industry has been the world's fastest growing source with the annual growth rate of 52.5%. Especially, BIPV(Building Integrated Photovoltaic) systems are capturing a growing portion of the renewable energy market due to several reasons. BIPV consists of photovoltaic cells and modules integrated into the building envelope such as a roof or facades. By avoiding the cost of conventional materials, the incremental cost of photovoltaics is reduced and its life-cycle cost is improved. When it comes to atypical building, numerous problems occur because PV modules are flat, stationary, and have its orientation determined by building surface. However, previous studies mainly focused on improving installations of solar PV technologies on ground and rooftop photovoltaic array and developing prediction model to estimate the amount of produced electricity. Consequently, this paper discusses the problem during a planning and design stage of BIPV systems and suggests the method to select optimal design of the systems by applying the national strategy and economic policies. Furthermore, the paper aims to develop BIM tool based on the engineering knowledge from experts in order for non-specialists to design photovoltaic generation systems easily.

전통한의학 연구방법론의 현대화에 대한 소고(小考) - 역사적 근거중심의학에 대한 제언 - (A Proposal for Use in Research Methodology of Traditional Medicine in East Asia - Historical Evidence-Based Medicine -)

  • 엄석기;김세현;최원철
    • 대한한의학원전학회지
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    • 제23권2호
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    • pp.89-105
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    • 2010
  • Research methodology on Traditional Medicine in East Asia refers to logical thinking system, empirical positivism system and methodology of developing these knowledge systems. Logical thinking system of abstract concepts such as analogy or abduction and positivism system of reasonable explanation such as the five elements and their characteristic theory have been used in various ways empirically or in the form of humanities and knowledge system was developed through parallel structure of empirical positivism and exegetical studies. After the 16th century, evidence was required along with the tradition of putting emphasis on rationality, logicality and empirical positivism and characteristics of medical humanities can be found in emphasizing on medical ethics. Data that can be considered as structural review paper or meta analysis from original data of research on Traditional East Asian Medicine should be evaluated as historical evidence which is equivalent to specialist opinion, descriptive disease research, single case report or case series. Historical evidence based medicine is a research method using Historical evidence to selectively support data that are faithful to traditional theory with higher possibility to be used in future traditional east Asian medicine that links between traditional knowledge and scientific research methodology. Moreover, historical evidence based medicine tries to re-evaluate the value of traditional knowledge and ultimately, guides the direction of development of traditional medicine through scientific rationality based on history and culture.

한국인 화자의 외래어 발음 변이 양상과 음절 기반 외래어 자소-음소 변환 (Pronunciation Variation Patterns of Loanwords Produced by Korean and Grapheme-to-Phoneme Conversion Using Syllable-based Segmentation and Phonological Knowledge)

  • 류혁수;나민수;정민화
    • 말소리와 음성과학
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    • 제7권3호
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    • pp.139-149
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    • 2015
  • This paper aims to analyze pronunciation variations of loanwords produced by Korean and improve the performance of pronunciation modeling of loanwords in Korean by using syllable-based segmentation and phonological knowledge. The loanword text corpus used for our experiment consists of 14.5k words extracted from the frequently used words in set-top box, music, and point-of-interest (POI) domains. At first, pronunciations of loanwords in Korean are obtained by manual transcriptions, which are used as target pronunciations. The target pronunciations are compared with the standard pronunciation using confusion matrices for analysis of pronunciation variation patterns of loanwords. Based on the confusion matrices, three salient pronunciation variations of loanwords are identified such as tensification of fricative [s] and derounding of rounded vowel [ɥi] and [$w{\varepsilon}$]. In addition, a syllable-based segmentation method considering phonological knowledge is proposed for loanword pronunciation modeling. Performance of the baseline and the proposed method is measured using phone error rate (PER)/word error rate (WER) and F-score at various context spans. Experimental results show that the proposed method outperforms the baseline. We also observe that performance degrades when training and test sets come from different domains, which implies that loanword pronunciations are influenced by data domains. It is noteworthy that pronunciation modeling for loanwords is enhanced by reflecting phonological knowledge. The loanword pronunciation modeling in Korean proposed in this paper can be used for automatic speech recognition of application interface such as navigation systems and set-top boxes and for computer-assisted pronunciation training for Korean learners of English.

Design of A Personalized Classifier using Soft Computing Techniques and Its Application to Facial Expression Recognition

  • Kim, Dae-Jin;Zeungnam Bien
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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    • pp.521-524
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    • 2003
  • In this paper, we propose a design process of 'personalized' classification with soft computing techniques. Based on human's thinking way, a construction methodology for personalized classifier is mentioned. Here, two fuzzy similarity measures and ensemble of classifiers are effectively used. As one of the possible applications, facial expression recognition problem is discussed. The numerical result shows that the proposed method is very useful for on-line learning, reusability of previous knowledge and so on.

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Some new similarity based approaches in approximate reasoning and their applications to pattern recognition

  • Swapan Raha;Nikhil R. Pal;Ray, Kumar-Sankar
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.719-724
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    • 1998
  • This paper presents a systematic developement of a formal approach to inference in approximate reasoning. We introduce some measures of similarity and discuss their properties. Using the concept of similarity index we formulate two methods for inferring from vague knowledge. In order to illustrate the effectiveness of the proposed technique we use it to develop a vowel recognition system.

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An Extended Version of the CPT-based Estimation for Missing Values in Nominal Attributes

  • Ko, Song;Kim, Dae-Won
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제10권4호
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    • pp.253-258
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    • 2010
  • The causal network represents the knowledge related to the dependency relationship between all attributes. If the causal network is available, the dependency relationship can be employed to estimate the missing values for improving the estimation performance. However, the previous method had a limitation in that it did not consider the bidirectional characteristic of the causal network. The proposed method considers the bidirectional characteristic by applying prior and posterior conditions, so that it outperforms the previous method.

Process Control Using n Neural Network Combined with the Conventional PID Controllers

  • Lee, Moonyong;Park, Sunwon
    • Transactions on Control, Automation and Systems Engineering
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    • 제2권3호
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    • pp.196-200
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    • 2000
  • A neural controller for process control is proposed that combines a conventional multi-loop PID controller with a neural network. The concept of target signal based on feedback error is used fur on-line learning of the neural network. This controller is applied to distillation column control to illustrate its effectiveness. The result shows that the proposed neural controller can cope well with disturbance, strong interactions, time delays without any prior knowledge of the process.

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Database & Knowledge Based Approaches to Information Retrieval; A Comparative Study

  • Kim, Dong-Hyung;Sri
    • 한국정보시스템학회지:정보시스템연구
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    • 제3권
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    • pp.171-201
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    • 1994
  • I wish to acknowledge the people who inspired me to believe that a machine can have intelligence. They are the ones who envisioned the future of mankind. I specially appreciate to my advisor Dr. Srivasan raghunathan, who was always supportive and encouraged to finish this research. I also sincerely thank for my parents who are always concerned of my well-being. Without them, what I achived here cannot be possible.

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Human Robot Interaction via Evolutionary Network Intelligence

  • Yamaguchi, Toru
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2002년도 ICCAS
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    • pp.49.2-49
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    • 2002
  • This paper describes the configuration of a multi-agent system that can recognize human intentions. This system constructs ontologies of human intentions and enables knowledge acquisition and sharing between intelligent agents operating in different environments. This is achieved by using a bi-directional associative memory network. The process of intention recognition is based on fuzzy association inferences. This paper shows the process of information sharing by using ontologies. The purpose of this research is to create human-centered systems that can provide a natural interface in their interaction with people.

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