• Title/Summary/Keyword: concept-based detection

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LATEST DEVELOPMENTS FOR FIRE DETECTION AND SUPPRESSION APPLICATIONS

  • Grant, Casey C.
    • Proceedings of the Korea Institute of Fire Science and Engineering Conference
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    • 1997.11a
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    • pp.573-581
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    • 1997
  • Much activity is occurring throughout the world with respect to the implementation of new concepts and technology for fire detection and fire suppression applications. Obvious advances include tangible detection and suppression improvements, and also new methods and approaches such as performance based codes and standards. Examples of tangible advances include addressable detection systems, wireless detection technology, halon alternatives, water mist systems, advanced sprinkler technology, and so on. Examples of new approaches and methods include a revitalized focus on disaster planning and the need for a total fire protection plan. The concept of performance based codes and standards for the design and installation fire detection and suppression systems will be explored in detail.

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A DoS Detection Method Based on Composition Self-Similarity

  • Jian-Qi, Zhu;Feng, Fu;Kim, Chong-Kwon;Ke-Xin, Yin;Yan-Heng, Liu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.5
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    • pp.1463-1478
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    • 2012
  • Based on the theory of local-world network, the composition self-similarity (CSS) of network traffic is presented for the first time in this paper for the study of DoS detection. We propose the concept of composition distribution graph and design the relative operations. The $(R/S)^d$ algorithm is designed for calculating the Hurst parameter. Based on composition distribution graph and Kullback Leibler (KL) divergence, we propose the composition self-similarity anomaly detection (CSSD) method for the detection of DoS attacks. We evaluate the effectiveness of the proposed method. Compared to other entropy based anomaly detection methods, our method is more accurate and with higher sensitivity in the detection of DoS attacks.

Image Edge Detection Applying the Toll Set and Entropy Concepts (톨연산과 엔트로피 개념에 기초한 화상의 경계선 추출)

  • Cho, Dong-Uk
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.3
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    • pp.471-477
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    • 1996
  • An image edge detection method based on the toll set concept is proposed. Initially the edge structure is established for an image following human perception n model. Then toll set membership values are computed and the toll set intersection and union operators are applied to them. The final toll set membership values are normalized to get the vagueness degrees and the thresholding operation based on entropy concept is performed on them to determine the edge of an image.

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Feasibility study of bonding state detection of explosive composite structure based on nonlinear output frequency response functions

  • Si, Yue;Zhang, Zhou-Suo;Wang, Hong-fang;Yuan, Fei-Chen
    • Steel and Composite Structures
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    • v.24 no.4
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    • pp.391-397
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    • 2017
  • With the increasing application of explosive composite structure in many engineering fields, its interface bonding state detection is more and more significant to avoid catastrophic accidents. However, this task still faces challenges due to the complexity of the bonding interface. In this paper, the concept of nonlinear output frequency response functions (NOFRFs) is introduced to detect the bonding state of explosive composite structure. The NOFRFs can describe the nonlinear characteristics of nonlinear vibrating system. Because of the presence of the bonding interface, explosive composite structure itself is a nonlinear system; when bonding interface of the structure is damaged, its dynamic characteristics show enhanced nonlinear characteristic. Therefore, the NOFRFs-based detection index is proposed as indicator to detect the bonding state of explosive composite pipes. The experimental results verify the effectiveness of the detection approach.

Photonic sensors for micro-damage detection: A proof of concept using numerical simulation

  • Sheyka, M.;El-Kady, I.;Su, M.F.;Taha, M.M. Reda
    • Smart Structures and Systems
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    • v.5 no.4
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    • pp.483-494
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    • 2009
  • Damage detection has been proven to be a challenging task in structural health monitoring (SHM) due to the fact that damage cannot be measured. The difficulty associated with damage detection is related to electing a feature that is sensitive to damage occurrence and evolution. This difficulty increases as the damage size decreases limiting the ability to detect damage occurrence at the micron and submicron length scale. Damage detection at this length scale is of interest for sensitive structures such as aircrafts and nuclear facilities. In this paper a new photonic sensor based on photonic crystal (PhC) technology that can be synthesized at the nanoscale is introduced. PhCs are synthetic materials that are capable of controlling light propagation by creating a photonic bandgap where light is forbidden to propagate. The interesting feature of PhC is that its photonic signature is strongly tied to its microstructure periodicity. This study demonstrates that when a PhC sensor adhered to polymer substrate experiences micron or submicron damage, it will experience changes in its microstructural periodicity thereby creating a photonic signature that can be related to damage severity. This concept is validated here using a three-dimensional integrated numerical simulation.

Concept Drift Based on CNN Probability Vector in Data Stream Environment

  • Kim, Tae Yeun;Bae, Sang Hyun
    • Journal of Integrative Natural Science
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    • v.13 no.4
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    • pp.147-151
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    • 2020
  • In this paper, we propose a method to detect concept drift by applying Convolutional Neural Network (CNN) in a data stream environment. Since the conventional method compares only the final output value of the CNN and detects it as a concept drift if there is a difference, there is a problem in that the actual input value of the data stream reacts sensitively even if there is no significant difference and is incorrectly detected as a concept drift. Therefore, in this paper, in order to reduce such errors, not only the output value of CNN but also the probability vector are used. First, the data entered into the data stream is patterned to learn from the neural network model, and the difference between the output value and probability vector of the current data and the historical data of these learned neural network models is compared to detect the concept drift. The proposed method confirmed that only CNN output values could be used to reduce detection errors compared to how concept drift were detected.

A Study on the Fault Detection of an Integrated Servo Actuator (통합 서보 액츄에이터의 고장 감지시스템 연구)

  • 신기현;임광호
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.11a
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    • pp.306-312
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    • 1996
  • The performance of the failure detection algorithm may be greatly influenced by the model uncertainty. It is very important to design a robust failure detection system to the model uncertainty. In this paper, a design procedure to generate failure detection algorithm is proposed. The design procedure suggested is based on the concept of the‘threshold selector[1]’. The H$\infty$ control algorithm is used to derive a threshold selector which is robust to the model uncertainty, The threshold selector derived can be used to develop a failure detection system together with the weighted cumulative sum algorithm[3]. Computer simulation study showed that the failure detection system designed for an ISA(Integrated Servo Actuator) system by using the proposed method is robust to the model uncertainty.

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Implementation of a Change Detection System based on OGC Grid Coverage Specification (OGC Grid Coverage 기반 다기능 변화탐지 시스템의 구현)

  • Lim, Young-Jae;Jeong, Soo;Kim, Kyung-Ok
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2003.10a
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    • pp.379-384
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    • 2003
  • In this paper, we introduce a change detection system that can extract and analyze change elements from high-resolution satellite imagery as well as low- or middle-resolution satellite imagery. The developed system provides not only 7 pixel-based methods that can be used to detect change from low- or middle-resolution satellite images but also a float window concept that can be used in manual change detection from high-resolution satellite images. This system enables fast process of the very large image, because it is constituted by OGC grid coverage components. Also new change detection algorithms can be easily added into this system if once they are made into grid coverage components.

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Combined burst synchronization/error detection systems maximizing bit slip correction ranges (최대 비트슬립 정정범위를 가지는 복합 버스트 동기/에러 검출 시스템)

  • 최양호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.7
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    • pp.1477-1486
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    • 1997
  • Conventioally the decoding methods and the design of coset codes for burst synchronization and error detection have been based on the concept that slips occuring to the right or to the left with respect to a reference timing are corrected. In this paper we newly approach to the design of coset codes relying on the condition that only a single code word can exists in an observation interval, which provides an extentended view on the conventional approach. A theorem concerning the condition is presented. A combined burst synchronization and error detection system with maximum slip correction capability have been devised based on the theorem and a detection method is falsely accepted in the presented of channel errors. The false acceptance probabilities of the system are derived and its performance is analyzed through computer computation using the derived results.

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A Model-based Study on the Expansion of Measured Data and the Damage Detection (모델기반의 계측데이터 확장 및 손상 추정에 관한 연구)

  • Kang, Taik-Seon;Lee, Byeong-Hyeon;Eun, Hee-Chang
    • Journal of the Architectural Institute of Korea Structure & Construction
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    • v.34 no.3
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    • pp.3-10
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    • 2018
  • It's not practical to collect all information at the entire degrees of freedom of finite element model. The incomplete measurements should be expanded for subsequent analysis and damage detection. This work presents the analytical methods to expand the incomplete static or dynamic response data. Using the expanded data, introducing the concept of residual force, and minimizing the performance index expressed as the stiffness matrix and its difference before and after damage, the variation in stiffness matrix is derived. Based on the difference in the stiffness matrix, the damage detection method of structures is also provided. The validity of the proposed methods is illustrated in a numerical application, the numerical results are analyzed for applications, and the applicability of both methods is investigated.