• Title/Summary/Keyword: Intelligent level

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A Natural Language Query Framework for the Semantic Web

  • Kim, Jin-Sung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.1
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    • pp.127-132
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    • 2008
  • This study proposes a Natural Language Query Framework (NLQF) for the semantic web. It supports an intelligent inference at a semantic level. Most of previous researches focused on the knowledge representation on the semantic web. However, to revitalize the intelligent e-business on the semantic web, there is a need for semantic level inference to the web information. To satisfy the need, we will review the knowledge/resource representation on the semantic web such as RDF, Ontology and Conceptual Graph (CG), and then discuss about the natural language (NL) inference. The result of this research could support a natural interface for the semantic web. Furthermore, we expect that the NLQF can be used in the semantic web-based business communications.

Intelligent Healthcare Service Provisioning Using Ontology with Low-Level Sensory Data

  • Khattak, Asad Masood;Pervez, Zeeshan;Lee, Sung-Young;Lee, Young-Koo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.11
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    • pp.2016-2034
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    • 2011
  • Ubiquitous Healthcare (u-Healthcare) is the intelligent delivery of healthcare services to users anytime and anywhere. To provide robust healthcare services, recognition of patient daily life activities is required. Context information in combination with user real-time daily life activities can help in the provision of more personalized services, service suggestions, and changes in system behavior based on user profile for better healthcare services. In this paper, we focus on the intelligent manipulation of activities using the Context-aware Activity Manipulation Engine (CAME) core of the Human Activity Recognition Engine (HARE). The activities are recognized using video-based, wearable sensor-based, and location-based activity recognition engines. An ontology-based activity fusion with subject profile information for personalized system response is achieved. CAME receives real-time low level activities and infers higher level activities, situation analysis, personalized service suggestions, and makes appropriate decisions. A two-phase filtering technique is applied for intelligent processing of information (represented in ontology) and making appropriate decisions based on rules (incorporating expert knowledge). The experimental results for intelligent processing of activity information showed relatively better accuracy. Moreover, CAME is extended with activity filters and T-Box inference that resulted in better accuracy and response time in comparison to initial results of CAME.

An intelligent control system design for autonomous underwater vehicle (무인 수중운동체를 위한 지능제어시스템 설계)

  • Lee, Dong-Ik;Kwak, Dong-Hoon;Choi, Jung-Lak
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.3
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    • pp.227-237
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    • 1997
  • Autonomous Underwater Vehicles(AUVs) have become an important tool for various purposes in subsea: inspection, recovery, construction, etc., and the development of autonomous control system is luglay desirable- thete zffe many problems associated with designing the control system for AUV due to unknown underwater envimn-Tnent, the possibility of subsystem failures, and unpredictable changes in the dynamics of the vehicle. In this paper, an autonomous control system based on the intelligent control theory to enhance operation efficiency of the ALTV is presented. The control system has a hierarchical structure which consists of mission planning level, mission control level, navigation level, and execution level. The performance of the control system is investigated by computer simulation. The results show that the proposed control system can be applied successfully to the AUV in spite of the possibility of failures in the vehicle and the collision hazard in the sea environment.

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Learning data analysis strategy in intelligent learning system (지능형 학습 시스템에서의 학습데이터 분석 전략)

  • Shin, Soo-Bum
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.37-44
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    • 2021
  • This study is about a strategy to analyze learning activities in an intelligent learning system. To this end, the conceptual definition of the intelligent learning system and the type of learning using the intelligent learning system were analyzed. The learning types were presented as individual, adaptive, competency-based, and blended learning, and although there are some differences, most of them have similar characteristics. In addition, learning activity analysis is based on data such as mouse clicks, keyboarding, and uploads generated by the system. Through this, basic analysis such as viewing time and number of uploads can be performed. However, more diverse learning analysis is needed for personalization and adaptation. It can judge not only learning attitude and achievement level, but also metacognitive level and creativity level. However, since the level of metacognition includes complex human cognitive activities, the teacher's intervention is required in the judgment of the intelligent learning system.

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Design of An Intelligent Hybrid Controller for Autonomous Mobile Robot

  • Baek, Seung-Min;Kuc, Tae-Yong
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.146.2-146
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    • 2001
  • Recently, a need of non-industrial robot, such as service, medical, entertainment and house-keeping robot, has been increased. Therefore, the capability of robot which can do intelligent behavior like interaction with men and its environment become more prominent than the capability of executing simple repetitive task. To implement an intelligent robot which provides intelligent behavior, an effective system architecture including perception, learning, reasoning and action part is necessary. Control architectures for intelligent robot can be divided into two different classes. One is deliberative type controller which is applicate to high level intelligence like environment ...

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Application of Fuzzy Algorithm with Learning Function to Nuclear Power Plant Steam Generator Level Control

  • Park, Gee-Yong-;Seong, Poong-Hyun;Lee, Jae-Young-
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1054-1057
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    • 1993
  • A direct method of fuzzy inference and a fuzzy algorithm with learning function are applied to the steam generator level control of nuclear power plant. The fuzzy controller by use of direct inference can control the steam generator in the entire range of power level. There is a little long response time of fuzzy direct inference controller at low power level. The rule base of fuzzy controller with learning function is divided into two parts. One part of the rule base is provided to level control of steam generator at low power level (0%∼30% of full power). Response time of steam generator level control at low power level with this rule base is shown generator level control at low power level with this rule base is shown to be shorter than that of fuzzy controller with direct inference.

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A Design of Intelligent Tutoring System for Mobile English Loaming (모바일 영어 학습을 위한 지능형 교육 시스템의 설계)

  • 이영석;김병규;조정원;최병욱
    • Proceedings of the IEEK Conference
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    • 2003.07d
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    • pp.1681-1684
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    • 2003
  • We propose the intelligent tutoring system for the mobile english learning. The proposed system is based on the item response theory to analyze the level of learner. We define the types of item, teaching method and item disposition according to contents modeling. The system estimates the learner level and it gives the learning contents, the evaluation results, and feedback. The system gives those by inference engine which consists of learner's level estimation value, method diagnostic value and disposition diagnostic value.

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Stock and News Application of Intelligent Agent System

  • Kim, Dae-Su
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.2
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    • pp.239-243
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    • 2003
  • Recently, there has been active research conducted on the intelligent agent in various fields. The results have been widely applied to intelligent user-friendly interfaces. In this system, we modeled, designed, and implemented an intelligent agent system that can be applied to stock and news. Some procedures such as login sequence to the web site, process to get stock information, setting stock in concern, intelligent news system module, news analysis module, and news learning module are modeled in detail and described in block diagram level. In our experiment on stock system, it showed quite a useful alarming screen avatar result and also on news system. it successfully rearranged the order of the news according to the user's preferences.