• Title/Summary/Keyword: 규칙기반 모델

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A Study on Analysis of Landslide Disaster Area using Cellular Automata: An Application to Umyeonsan, Seocho-Gu, Seoul, Korea (셀룰러 오토마타를 이용한 산사태 재난지역 분석에 관한 연구 - 서울특별시 서초구 우면산을 대상으로-)

  • Yoon, Dong-Hyeon;Koh, Jun-Hwan
    • Spatial Information Research
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    • v.20 no.1
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    • pp.9-18
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    • 2012
  • South Korea has many landslides caused by heavy rains during summer time recently and the landslides continue to cause damages in many places. These landslides occur repeatedly each year, and the frequency of landslides is expected to increase in the coming future due to dramatic global climate change. In Korea, 81.5% of the population is living in urban areas and about 1,055 million people are living in Seoul. In 2011, the landslide that occurred in Seocho-dong killed 18 people and about 9% of Seoul's area is under the same land conditions as Seocho-dong. Even the size of landslide occurred in a city is small, but it is more likely to cause a big disaster because of a greater population density in the city. So far, the effort has been made to identify landslide vulnerability and causes, but now, the new dem and arises for the prediction study about the areal extent of disaster area in case of landslides. In this study, the diffusion model of the landslide disaster area was established based on Cellular Automata(CA) to analyze the physical diffusion forms of landslide. This study compared the accuracy with the Seocho-dong landslide case, which occurred in July 2011, applying the SCIDDICA model and the CAESAR model. The SCIDDICA model involves the following variables, such as the movement rules and the topographical obstacles, and the CAESAR model is also applied to this process to simulate the changes of deposition and erosion.

Present the Celeb-Bot Model Using Artificial Intelligence (인공지능을 활용한 셀럽봇 모델 제시)

  • Lee, Dae-Kun;Na, Seung-Yoo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.4
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    • pp.765-776
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    • 2018
  • Artificial Intelligence is a rapidly growing technology with the latest developments in computing technology and is considered as one of the next major technologies. Chat-Bot is a system that is designed to respond to user's input according to the rules that are set up in advance and it provides more services through simple and repetitive tasks such as counseling, ordering and others. Accordingly, the study aims to present a model of a celeb-bot using Artificial Intelligence. Celeb-Bot is a combination of Celeb, which are short for Celebrity and Chat-bot. Celeb-Bot provides a Chat-Bot service that allows people to talk to a celebrity. The celeb is the best thing to build a relationship and has the advantages of being accessible to anyone. At the same time, Artificial Intelligence is a technology that can be seen as a person, not a product. Based on this, we believe that Celeb's Characteristic and Chat-bot based on artificial intelligence technologies need to be combined, so variety of products can generate synergy. It is predicted that there will be variety of derivatives that utilize this technology, and it is going to present a celeb-bot model accordingly.

Visualization of Korean Speech Based on the Distance of Acoustic Features (음성특징의 거리에 기반한 한국어 발음의 시각화)

  • Pok, Gou-Chol
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.13 no.3
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    • pp.197-205
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    • 2020
  • Korean language has the characteristics that the pronunciation of phoneme units such as vowels and consonants are fixed and the pronunciation associated with a notation does not change, so that foreign learners can approach rather easily Korean language. However, when one pronounces words, phrases, or sentences, the pronunciation changes in a manner of a wide variation and complexity at the boundaries of syllables, and the association of notation and pronunciation does not hold any more. Consequently, it is very difficult for foreign learners to study Korean standard pronunciations. Despite these difficulties, it is believed that systematic analysis of pronunciation errors for Korean words is possible according to the advantageous observations that the relationship between Korean notations and pronunciations can be described as a set of firm rules without exceptions unlike other languages including English. In this paper, we propose a visualization framework which shows the differences between standard pronunciations and erratic ones as quantitative measures on the computer screen. Previous researches only show color representation and 3D graphics of speech properties, or an animated view of changing shapes of lips and mouth cavity. Moreover, the features used in the analysis are only point data such as the average of a speech range. In this study, we propose a method which can directly use the time-series data instead of using summary or distorted data. This was realized by using the deep learning-based technique which combines Self-organizing map, variational autoencoder model, and Markov model, and we achieved a superior performance enhancement compared to the method using the point-based data.

(A Question Type Classifier based on a Support Vector Machine for a Korean Question-Answering System) (한국어 질의응답시스템을 위한 지지 벡터기계 기반의 질의유형분류기)

  • 김학수;안영훈;서정연
    • Journal of KIISE:Software and Applications
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    • v.30 no.5_6
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    • pp.466-475
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    • 2003
  • To build an efficient Question-Answering (QA) system, a question type classifier is needed. It can classify user's queries into predefined categories regardless of the surface form of a question. In this paper, we propose a question type classifier using a Support Vector Machine (SVM). The question type classifier first extracts features like lexical forms, part of speech and semantic markers from a user's question. The system uses $X^2$ statistic to select important features. Selected features are represented as a vector. Finally, a SVM categorizes questions into predefined categories according to the extracted features. In the experiment, the proposed system accomplished 86.4% accuracy The system precisely classifies question type without using any rules like lexico-syntactic patterns. Therefore, the system is robust and easily portable to other domains.

Personalization Recommendation Service using OWL Modeling (OWL 모델링을 이용한 개인 추천 서비스)

  • Ahn, Hyo-Sik;Jeong, Hoon;Chang, Hyo-Kyung;Choi, Eui-In
    • Journal of Digital Convergence
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    • v.10 no.1
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    • pp.309-315
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    • 2012
  • The dissemination of smartphones is being spread and supplementary services using smartphones are increasing and various as the Mobile network and device are developing rapidly, so smartphones that enables to provide a wide range of services is expected to receive the most attention. It makes users listen to music anytime, anywhere in real-time, use useful applications, and access to Internet to search for information. The service environment is changing on PC into Mobile due to the change of the circumstance mentioned above. these services are done by using just location information rather than other context, and users have to search services and use them. It is essential to have Context-aware technology for personalization recommendation services and the appropriate representation and definition of Context information for context-aware. Ontology is possible to represent knowledge freely and knowledge can be extended by inferring. In addition, design of the ontology model is needed according to the purposes of utilization. This paper used context-aware technologies to implement a user personalization recommendation service. It also defined the context through OWL modeling for user personalization recommendation service and used inference rules and inference engine for context reasoning.

Analytical Evaluation Model of the Gameplay in MMO Game - Focused on GOMS Model - (MMO 게임의 게임플레이 분석적 평가 모형 - GOMS 모형을 중심으로 -)

  • Song, Seung-Keun
    • Journal of Korea Multimedia Society
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    • v.12 no.11
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    • pp.1652-1660
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    • 2009
  • The main objective of this research is to build a behavior prediction model of gameplay for MMO (Massively Multiplayer Online) game using the GOMS analysis method. GOMS analysis is an observational approach to HCI(Human Computer Interaction) to model and predict behaviors of a human operator in a highly interactive task. In this research, a pilot experiment was previously conducted with three skilled gamers. The gamers were provided with the goals and operators through the user's guide book, and they found methods and selection rules while being observed. Based on the results obtained from the pilot study, this research was expanded and the model was further tested with 30 subjects (game experts). The new outcomes revealed that the relevance of GOMS analysis for predicting selection rules is 96.25% according to the degree of abstraction and 77.35% based on the degree of complexity. This research will provide game designers with a new testing mechanism in the early development stages, in order to improve the quality of the game product.

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A Word Spacing System based on Syllable Patterns for Memory-constrained Devices (메모리 제약적 기기를 위한 음절 패턴 기반 띄어쓰기 시스템)

  • Kim, Shin-Il;Yang, Seon;Ko, Young-Joong
    • Journal of KIISE:Software and Applications
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    • v.37 no.8
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    • pp.653-658
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    • 2010
  • In this paper, we propose a word spacing system which can be performed with just a small memory. We focus on significant memory reduction while maintaining the performance of the system as much as the latest studies. Our proposed method is based on the theory of Hidden Markov Model. We use only probability information not adding any rule information. Two types of features are employed: 1) the first features are the spacing patterns dependent on each individual syllable and 2) the second features are the values of transition probability between the two syllable-patterns. In our experiment using only the first type of features, we achieved a high accuracy of more than 91% while reducing the memory by 53% compared with other systems developed for mobile application. When we used both types of features, we achieved an outstanding accuracy of more than 94% while reducing the memory by 76% compared with other system which employs bigram syllables as its features.

Modeling of Multi-Boom Floating Crane for Lifting Analysis of Offshore Wind Turbine (해상 풍력 발전기 리프팅 해석을 위한 해상 크레인 멀티 붐 모델링)

  • Park, Kwang-Phil;Cha, Ju-Hwan;Lee, Kyu-Yeul
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.35 no.1
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    • pp.115-120
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    • 2011
  • The dynamic responses of a 5 MW wind turbine lifted by a floating crane with two elastic booms are analyzed. Dynamic equations of motions of a multibody system that consists of a floating crane, two elastic booms, and a wind turbine are derived. The six-degree-of-freedom (DOF) motions for the floating crane and the wind turbine are considered in the equations of motions. The hydrostatic force, the hydrodynamic force due to a regular wave, the mooring force, the wire rope force, and the gravitational force are considered as external forces. By solving the equations numerically, the dynamic responses of cargo are simulated. The simulation results are compared with those in the case of one elastic boom. Finally, the dynamic responses of the wind turbine lifted by the floating crane are analyzed under regular wave condition.

Decision Rule using Confidence Based Anti-phone Model and Interrupt-Polling Method for Distributed Speech Recognition DSP Networking System (분산형 음성인식 DSP 네트워킹 시스템을 위한 반음소 모델기반의 신뢰도를 사용한 결정규칙과 인터럽트-폴링)

  • Song, Ki-Chang;Kang, Chul-Ho
    • Journal of Korea Multimedia Society
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    • v.13 no.7
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    • pp.1016-1022
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    • 2010
  • Far-talking recognition and distributed speech recognition networking techniques are essential to control various and complex home services conveniently with voices. It is possible to control devices everywhere at home by using only voices. In this paper, we have developed the server-client DSP module for distributed speech recognition network system and proposed a new decision rule to decide intelligently whether to accept the recognition results or not by the transferred confidence rate. Simulation results show that the proposed decision rule delivers better performances than the conventional decision by majority rule or decision by first-arrival. Also, we have proposed the new interrupt-polling technique to remedy the defect of existing delay technique which always has to wait several clients' results for a few seconds. The proposed technique queries all client's status after first-arrival and decides whether to wait or not. It can remove unnecessary delay-time without any performance degradation.

Strength Prediction Model of Rapid Prototyping Parts - Fused Deposition Modeling (FDM) (쾌속조형재료의 강도예측모델 - Fused Deposition Modeling (FDM))

  • 안성훈;이선영;백창일;추원식
    • Composites Research
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    • v.15 no.6
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    • pp.38-43
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    • 2002
  • Rapid Prototyping(RP) technologies provide the ability to fabricate initial prototypes from various model materials. Stratasys' Fused Deposition Modeling(FDM) is a typical RP process that can fabricate prototypes out of plastic materials, and the parts made from FDM were often used as load-carrying elements. Because FDM deposits materials in about 300$\mu$m thin filament with designated orientation, parts made from FDM show anisotropic material properties. In this paper an analytic model was proposed to predict the tensile strength of FDM parts. Applying the Classical Lamination Theory, which was developed for laminated composite materials, a computer code was implemented. Tsai-Wu failure criterion was added to the code to predict the failure of the FDM parts. The tensile strengths predicted by the analytic model were compared with experimental data. The data and prediction agreed reasonably well to prove the validity of the model. In addition, a web-based advisory service(FDMAS) was developed to provide strength prediction and design rules for FDM parts.