• Title/Summary/Keyword: Sensitive data

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Robust Control of Industrial Robot Based on Back Propagation Algorithm (Back Propagation 알고리즘을 이용한 산업용 로봇의 견실 제어)

  • 윤주식;이희섭;윤대식;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2004.04a
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    • pp.253-257
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    • 2004
  • Neural networks are works are used in the framework of sensor based tracking control of robot manipulators. They learn by practice movements the relationship between PSD(an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple back propagation networks one of which is selected according to which division(corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.

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A neural network based real-time robot tracking controller using position sensitive detectors (신경회로망과 위치 검출장치를 사용한 로보트 추적 제어기의 구현)

  • 박형권;오세영;김성권
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.660-665
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    • 1993
  • Neural networks are used in the framework of sensorbased tracking control of robot manipulators. They learn by practice movements the relationship between PSD ( an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple backpropagation networks one of which is selected according to which division (corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very fast training and processing implementation required for real time control.

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Study on the physical mechanism of nonlinear gain in semiconductor lasers (반도체 레이저의 비선형 이득의 물리적인 매카니즘에 관한 연구)

  • 김창봉;엄진섭
    • Journal of the Korean Institute of Telematics and Electronics D
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    • v.34D no.9
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    • pp.72-79
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    • 1997
  • The dominant physical process repsonsible for the nonlinear gain is from spectral-hole burning with the time constant fo about 50fs and the contribution to the nonlinea rgain form hot carriers effect is determined to be about 15% of the contribution due to spectral-hole burning. To prove the above results we fit the data of hall and found that hot carriers have a profound effect on their experimental data despite the fact that the magnitude of hot carriers effect is only 15% of spectral-hole burning. We suggest that the experimenta with a pump pulse width of 180 fs is very sensitive in detecting the effect of hot carriers, but is not sensitive in detecting much faster process associated with spectral-hole burning.

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Robust Control of AM1 Robot Using PSD Sensor and Back Propagation Algorithm (PSD 센서 및 Back Propagation 알고리즘을 이용한 AM1 로봇의 견질 제어)

  • Jung, Dong-Yean;Han, Sung-Hyun
    • Journal of the Korean Society of Industry Convergence
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    • v.7 no.2
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    • pp.167-172
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    • 2004
  • Neural networks are used in the framework of sensor based tracking control of robot manipulators. They learn by practice movements the relationship between PSD(an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple back propagation networks one of which is selected according to which division (Corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.

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A Network Load Sensitive Block Placement Strategy of HDFS

  • Meng, Lingjun;Zhao, Wentao;Zhao, Haohao;Ding, Yang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.9
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    • pp.3539-3558
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    • 2015
  • This paper investigates and analyzes the default block placement strategy of HDFS. HDFS is a typical representative distributed file system to stream vast amount of data effectively at high bandwidth to user applications. However, the default HDFS block placement policy assumes that all nodes in the cluster are homogeneous, and places blocks with a simple RoundRobin strategy without considering any nodes' resource characteristics, which decreases self-adaptability of the system. The primary contribution of this paper is the proposition of a network load sensitive block placement strategy. We have implemented our algorithm and justify it through extensive simulations and comparison with similar existing studies. The results indicate that our work not only performs much better in the data distribution but also improves write performance more significantly than the others.

A Study on the Mismatch of Time and Frequency Domain for Vibration Criteria of Sensitive Equipment (고정밀 장비의 진동허용규제치에 대한 시간 및 주파수 영역에서 나타나는 불일치 문제에 관한 연구)

  • 이홍기;김강부;백재호
    • Journal of the Semiconductor & Display Technology
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    • v.1 no.1
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    • pp.1-7
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    • 2002
  • Modem technology depends on the reliability of extremely high precision equipments. In the production of semiconductor wafer, optical and electron microscopes, ion-beam, laser device must maintain their alignments within a sub-micrometer. This equipment requires a vibration free environment to provide its proper function. Therefore, this high technology equipments require very strict environmental vibration criteria because it is used as basic data for the design of building structure and structural dynamics of equipment. In this paper, the new approach is proposed to investigate the mismatch problem of time and frequency domain for vibration criteria of sensitive equipment. The proposed approach is based on a vibration measurement data and a relative transfer function which can be obtained by experiment or analysis.

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Computations of the Lyapunov exponents from time series

  • Kim, Dong-Seok;Park, Eun-Young
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.3
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    • pp.595-604
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    • 2012
  • In this article, we consider chaotic behavior happened in nonsmooth dynamical systems. To quantify such a behavior, a computation of Lyapunov exponents for chaotic orbits of a given nonsmooth dynamical system is focused. The Lyapunov exponent is a very important concept in chaotic theory, because this quantity measures the sensitive dependence on initial conditions in dynamical systems. Therefore, Lyapunov exponents can decide whether an orbit is chaos or not. To measure the sensitive dependence on initial conditions for nonsmooth dynamical systems, the calculation of Lyapunov exponent plays a key role, but in a theoretical point of view or based on the definition of Lyapunov exponents, Lyapunov exponents of nonsmooth orbit could not be calculated easily, because the Jacobian derivative at some point in the orbit may not exists. We use an algorithmic calculation method for computing Lyapunov exponents using time series for a two dimensional piecewise smooth dynamic system.

A Secure Decentralized Storage Scheme of Private Information in Blockchain Environments

  • Han, Seungjin
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.1
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    • pp.111-116
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    • 2018
  • Recently, IoT and Big Data dealing with voluminous and complex sensitive information is one of the key issues in the era of the 4th industrial revolution. There have been a lot of studies to store the collected and processed sensitive information safely in storage data. Especially biometric information, if it is leaked and becomes identity theft, is hard to be corrected and results in serious event. To fix the problem, methods such as FIDO or KFTC have been proposed. In this paper, we propose a modified method of TTAK.KO-12.0098 according to the environment of this paper and propose a method of safely storing the generated disposable template in a block chain. We show that our method is better by comparing the existing method and the security analysis.

MATE: Memory- and Retraining-Free Error Correction for Convolutional Neural Network Weights

  • Jang, Myeungjae;Hong, Jeongkyu
    • Journal of information and communication convergence engineering
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    • v.19 no.1
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    • pp.22-28
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    • 2021
  • Convolutional neural networks (CNNs) are one of the most frequently used artificial intelligence techniques. Among CNN-based applications, small and timing-sensitive applications have emerged, which must be reliable to prevent severe accidents. However, as the small and timing-sensitive systems do not have sufficient system resources, they do not possess proper error protection schemes. In this paper, we propose MATE, which is a low-cost CNN weight error correction technique. Based on the observation that all mantissa bits are not closely related to the accuracy, MATE replaces some mantissa bits in the weight with error correction codes. Therefore, MATE can provide high data protection without requiring additional memory space or modifying the memory architecture. The experimental results demonstrate that MATE retains nearly the same accuracy as the ideal error-free case on erroneous DRAM and has approximately 60% accuracy, even with extremely high bit error rates.

A Dimensionality Assessment for Polytomously Scored Items Using DETECT

  • Kim, Hae-Rim
    • Communications for Statistical Applications and Methods
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    • v.7 no.2
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    • pp.597-603
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    • 2000
  • A versatile dimensionality assessment index DETECT has been developed for binary item response data by Kim (1994). The present paper extends the use of DETECT to the polytomously scored item data. A simulation study shows DETECT performs well in differentiating multidimensional data from unidimensional one by yielding a greater value of DETECT in the case of multidimensionality. An additional investigation is necessary for the dimensionally meaningful clustering methods, such as HAC for binary data, particularly sensitive to the polytomous data.

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