• 제목/요약/키워드: Device Reasoning

검색결과 45건 처리시간 0.028초

커넥티드 카를 위한 운전자 감성추론 기반의 차량 제어 및 애플리케이션/서비스 프레임워크 (The Design and Implementation of a Driver's Emotion Estimation based Application/Service Framework for Connected Cars)

  • 국중진
    • 전기학회논문지P
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    • 제67권2호
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    • pp.100-105
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    • 2018
  • In this paper, we determined the driver's stress and fatigue level through physiological signals of a driver in the connected car environment, accordingly designing and implementing the architecture of the connected cars' platforms needed to provide services to make the driving environments comfortable and reduce the driver's fatigue level. It includes a gateway between AVN and ECU for the vehicle control, a framework for native applications and web applications based on AVN, and a sensing device and an emotion estimation engine for application services. This paper will provide the element technologies for the connected car-based convergence services and their implementation methods, and reference models for the service design.

진단 수행도에 대한 지식형태의 효용에 관한 연구 (The Effects of Types of Knowledge on the Performance of Fault Diagnosis)

  • 함동한;윤완철
    • 대한산업공학회지
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    • 제22권3호
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    • pp.399-412
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    • 1996
  • With respect to the effects of types of knowledge on human diagnostic performance, the results of several experiments claimed that training with procedural knowledge is more effective than training with principle knowledge. However, more useful results would be attained by investigating when and how the principles of system dynamics is valuable for diagnosis. Accordingly, we conducted an experiment to reevaluate the value of principle knowledge in two problem situations. A simulator system, named DLD, to diagnose an electronic device was created. It is a context-free digital logic circuit which includes forty-one gates of three basic types. The experiment investigated the effects of principle knowledge over common procedural knowledge. The experimental results showed that the effects of principle knowledge is dependent on the complexity of diagnostic situations. This adds up on experimental evidence against the presumed ineffectiveness of principle knowledge and forward reasoning in fault diagnosis. The results also suggest the source of the usefulness of principle knowledge.

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Customized Resource Collaboration System based on Ontology and User Model in Resource Sharing Environments

  • Park, Jong-Hyun
    • 한국컴퓨터정보학회논문지
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    • 제23권4호
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    • pp.107-114
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    • 2018
  • Recently, various wearable personal devices such as a smart watch have been developed and these personal devices are being miniaturized. The user desires to receive new services from personal devices as well as services that have been received from personal computers, anytime and anywhere. However, miniaturization of devices involves constraints on resources such as limited input and output and insufficient power. In order to solve these resource constraints, this paper proposes a resource collaboration system which provides a service by composing sharable resources in the resource sharing environment like IoT. the paper also propose a method to infer and recommend user-customized resources among various sharable resources. For this purpose, the paper defines an ontology for resource inference. This paper also classifies users behavior types based on a user model and then uses them for resource recommendation. The paper implements the proposed method as a prototype system on a personal device with limited resources developed for resource collaboration and shows the effectiveness of the proposed method by evaluating user satisfaction.

Evaluating LIMU System Quality with Interval Evidence and Input Uncertainty

  • Xiangyi Zhou;Zhijie Zhou;Xiaoxia Han;Zhichao Ming;Yanshan Bian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제17권11호
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    • pp.2945-2965
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    • 2023
  • The laser inertial measurement unit is a precision device widely used in rocket navigation system and other equipment, and its quality is directly related to navigation accuracy. In the quality evaluation of laser inertial measurement unit, there is inevitably uncertainty in the index input information. First, the input numerical information is in interval form. Second, the index input grade and the quality evaluation result grade are given according to different national standards. So, it is a key step to transform the interval information input by the index into the data form consistent with the evaluation result grade. In the case of uncertain input, this paper puts forward a method based on probability distribution to solve the problem of asymmetry between the reference grade given by the index and the evaluation result grade when evaluating the quality of laser inertial measurement unit. By mapping the numerical relationship between the designated reference level and the evaluation reference level of the index information under different distributions, the index evidence symmetrical with the evaluation reference level is given. After the uncertain input information is transformed into evidence of interval degree distribution by this method, the information fusion of interval degree distribution evidence is carried out by interval evidential reasoning algorithm, and the evaluation result is obtained by projection covariance matrix adaptive evolution strategy optimization. Taking a five-meter redundant laser inertial measurement unit as an example, the applicability and effectiveness of this method are verified.

유비쿼터스 환경에서 자원 공유를 위한 상황인지 기반 개인화 추천 (Personalized Recommendation based on Context-Aware for Resource Sharing in Ubiquitous Environments)

  • 박종현;강지훈
    • 한국컴퓨터정보학회논문지
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    • 제16권9호
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    • pp.19-26
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    • 2011
  • 최근 스마트 폰과 같은 다양한 모바일 장치들의 개발과 함께 사용자는 자신의 모바일 단말을 이용하여 개인화된 서비스를 제공받기를 원한다. 이러한 요구사항을 만족하기 위하여 모바일 장치들은 많은 기능을 제공해야하지만 모바일 장치가 소형화됨에 따라 작은 디스플레이 장치, 제한적인 입력 장치 그리고 부족한 파워와 같은 자원 제약성을 갖는다. 본논문은이러한자원의제약성을해결하고사용자에게개인화된서비스를제공하기위하여유비쿼터스환경에서 컴퓨팅 자원을 공유하여 사용자에게 서비스를 제공하기 위한 환경을 제안한다. 또한 다양한 자원들 가운데 사용자의 상황과 개인 선호도를 기반으로 최적의 자원을 추천하기 위한 방법을 제안한다. 이러한 자원 추천을 위하여 본 논문에서는 사용자의 사용 이력으로부터 행동 유형을 분석하고 이를 기반으로 개인화된 자원을 추천하기위한 방법을 사용한다. 또한 논문은 제안한 방법을 구현하고 만족도를 평가하여 유효성을 보인다.

Knowledge- Evolutionary Intelligent Machine-Tools - Part 1 : Design of Dialogue Agent based on Standard Platform

  • Kim, Dong-Hoon;Song, Jun-Yeob
    • Journal of Mechanical Science and Technology
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    • 제20권11호
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    • pp.1863-1872
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    • 2006
  • In FMS (Flexible Manufacturing System) and CIM (Computer Integrated Manufacturing), machine-tools have been the target of integration in the last three decades. The conventional concept of integration is being changed into the autonomous manufacturing device based on the knowledge evolution by applying advanced information technology in which an open architecture controller, high-speed network and internet technology are included. In the advanced environment, the machine-tools is not the target of integration anymore, but has been the key subject of cooperation. In the near future, machine-tools will be more improved in the form of a knowledge-evolutionary intelligent device. The final goal of this study is to develop an intelligent machine having knowledge-evolution capability and a management system based on internet operability. The knowledge-evolutionary intelligent machine-tools is expected to gather knowledge autonomically, by producing knowledge, understanding knowledge, reasoning knowledge, making a new decision, dialoguing with other machines, etc. The concept of the knowledge-evolutionary intelligent machine is originated from the machine control being operated by human experts' sense, dialogue and decision. The structure of knowledge evolution in M2M (Machine to Machine) and the scheme for a dialogue agent among agent-based modules such as a sensory agent, a dialogue agent and an expert system (decision support agent) are presented in this paper, with intent to develop the knowledge-evolutionary machine-tools. The dialogue agent functions as an interface for inter-machine cooperation. To design the dialogue agent module in an M2M environment, FIPA (Foundation of Intelligent Physical Agent) standard platform and the ping agent based on FIPA are analyzed in this study. In addition, the dialogue agent is designed and applied to recommend cutting conditions and thermal error compensation in a tapping machine. The knowledge-evolutionary machine-tools are expected easily implemented on the basis of this study and shows a good assistance to sensory and decision support agents.

서모그래피 기법을 적용한 하이브리드 대형 커빅기어 신뢰성 평가 (Evaluation of Reliability of Large Hybrid Curvic Gear Using Thermography)

  • 이경일;김재열
    • 한국기계가공학회지
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    • 제16권3호
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    • pp.146-152
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    • 2017
  • Stabilizing the operation of dual fuel diesel engines is very important. The shipbuilding industry is rapidly growing, but gear components requiring reliability are still imported from other countries. The reasoning for this is three-fold. Firstly, it is compulsory that all ships must use devices that meet the performance standards specified in the Safety of Life at Sea (SOLAS) and the convention of MARine POLlution (MAPOL) to prevent pollution caused by ships. Secondly, most ships must comply with the ship classifications specified by ship owners. Therefore, it is specified that key engine gear components must be inspected and authorized for the quality and performance specified by the Ship Register Authority. Thirdly, it is essential that devices (engine gear) for human safety in ships comply with quality standards specified in the regulations and rules by the government. The Ship Register Authority's strict quality standards and approval requirements contribute to the reduction of motivation towards new investment and technology development by device component manufacturers. Therefore, this study aims to develop a method for using infrared thermography to examine gear reliability in order to ensure gear component reliability and national competitiveness in the global market.

Study of Switching and Kirk Effects in InAlAs/InGaAs/InAlAs Double Heterojunction Bipolar Transistors

  • Mohiuddin, M.;Sexton, J.;Missous, M.
    • JSTS:Journal of Semiconductor Technology and Science
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    • 제13권5호
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    • pp.516-521
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    • 2013
  • This paper investigates the two dominant but intertwined current blocking mechanisms of Switching and Kirk Effect in pure ternary InAlAs/InGaAs/InAlAs Double Heterojunction Bipolar Transistors (DHBTs). Molecular Beam Epitaxy (MBE) grown, lattice-matched samples have been investigated giving substantial experimental results and theoretical reasoning to explain the interplay between these two effects as the current density is increased up to and beyond the theoretical Kirk Effect limit for devices of emitter areas varying from $20{\times}20{\mu}m^2$ to $1{\times}5{\mu}m^2$. Pure ternary InAlAs/InGaAs/InAlAs DHBTs are ideally suited for such investigations because, unless corrective measures are taken, these devices suffer from appreciable current blocking effect due to their large conduction band discontinuity of 0.5 eV and thus facilitating the observation of the two different physical phenomena. This enhanced understanding of the interplay between the Kirk and Switching effect makes the DHBT device design and optimization process more effective and efficient.

D-F-M 기반의 생체신호측정기 개발 (Development of a Bio-Signal Measuring System Based on D-F-M)

  • 채용웅;홍동권
    • 한국전자통신학회논문지
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    • 제13권4호
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    • pp.897-902
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    • 2018
  • 본 연구는 D-F-M(Diagnose Fure Funktionelle Medizine) 이론을 기반으로 하여 신체 7부위에 13Hz의 양과 음의 임펄스전압을 인가함으로서 생성된 출력 파형을 이용하여 환자의 건강상태를 진단하는 생체신호 측정기의 개발에 관한 것이다. 측정기에서 취득한 데이터는 인공지능을 기반으로 한 귀납적 추론을 통하여 간엽조직 뿐만 아니라 신체기관의 상태를 진단하는 기기로서의 역할을 수행할 것으로 기대된다. 본 논문에서는 생체신호를 취득하고 관리하는 시스템 하드웨어에 주제를 한정할 것이다.

CNN 모델을 이용한 위해 식품 알림 애플리케이션의 개발 (Development of Hazardous Food Notification Application Using CNN Model)

  • 윤동언;이효상;오암석
    • 한국멀티미디어학회논문지
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    • 제25권3호
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    • pp.461-467
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    • 2022
  • This research is to raise awareness of food safety by designing and supporting a hazard food information notification platform for consumers. To this end, the design was carried out by dividing the process into a data extraction process, an application screen design process, and a CNN-based food inference process. Data was collected through public data APIs and crawling, and it was sent to each activity screen designed for Android studios so that it could be output. As a result, when the platform is executed, information on hazardous food names, registration dates, food classification, manufacturing dates, recovery grades, recovery reasons, recovery methods, company names, barcode numbers, and packaging units can be intuitively and conveniently checked. In addition, CNN-based food inference processes allowed mobile cameras to infer harmful food and applied various quantization techniques such as Dynamic Range, Integer, and Float16 to compare the degree of improvement in inference performance. As a result, the group that applied basic quantization and treated device resources with GPU showed the greatest improvement in inference performance. Through this platform, it is expected that the reliability of food safety will be improved by making it more convenient for consumers to recognize food risks.