The Experts below are selected from a list of 270 Experts worldwide ranked by ideXlab platform

A.m. Okamura - One of the best experts on this subject based on the ideXlab platform.

  • Techniques for Environment Parameter estimation during telemanipulation
    2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics, 2008
    Co-Authors: Tomonori Yamamoto, Michael Bernhardt, Angelika Peer, Martin Buss, A.m. Okamura
    Abstract:

    Teleoperation allows surgeons to perform an operation that is remote in distance and/or scale. Extracting information about a patient, particularly the dynamic model of tissues, during a surgical procedure may be useful for improving telemanipulator control, developing simulations, and performing automated diagnosis. This study examines automated Environment Parameter identification methods for bilateral telemanipulation, with a focus on surgical applications. We first present a multi-estimator technique and demonstrate that, in practice, it finds the best estimator for a Kelvin-Voigt material. Using a one-degree-of-freedom teleoperation system, cubes with various material properties were palpated to acquire data under three control conditions: teleoperation without persistent excitation, teleoperation in which the operator mimics persistent excitation, and autonomous control with persistent excitation. The estimation performance of three online estimation techniques (recursive least-squares, adaptive identification, and multi-estimator) are compared. Neither the cube type nor the control condition affected the estimation performance. By considering practical aspects, recursive least-squares or multi-estimator would be suitable for online estimation of the tissue property.

  • Environment Parameter Estimation during Bilateral Telemanipulation
    2006 14th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2006
    Co-Authors: S. Misra, A.m. Okamura
    Abstract:

    Accurate models of remote Environments generated during telemanipulation can be used to improve transparency, generate realistic simulations, and evaluate Environment state. This paper presents an architecture for Environment Parameter estimation during bilateral telemanipulation. Nonlinear stiffness and damping properties of the Environment are estimated using an indirect adaptive control approach. The slave-Environment contact force tracks the sum of the force applied by the human to the master and a persistent excitation force required for accurate Environment Parameter estimation. Since force feedback to the human operator should only reflect the Environment properties, several methods for force feedback are considered. Simulations confirm the validity of the proposed telemanipulation architecture for obtaining reasonable estimates of nonlinear Environment properties and providing appropriate force feedback to the operator.

  • HAPTICS - Environment Parameter Estimation during Bilateral Telemanipulation
    IEEE Virtual Reality Conference (VR'06), 2006
    Co-Authors: S. Misra, A.m. Okamura
    Abstract:

    Accurate models of remote Environments generated during telemanipulation can be used to improve transparency, generate realistic simulations, and evaluate Environment state. This paper presents an architecture for Environment Parameter estimation during bilateral telemanipulation. Nonlinear stiffness and damping properties of the Environment are estimated using an indirect adaptive control approach. The slave-Environment contact force tracks the sum of the force applied by the human to the master and a persistent excitation force required for accurate Environment Parameter estimation. Since force feedback to the human operator should only reflect the Environment properties, several methods for force feedback are considered. Simulations confirm the validity of the proposed telemanipulation architecture for obtaining reasonable estimates of nonlinear Environment properties and providing appropriate force feedback to the operator.

Neal N. Xiong - One of the best experts on this subject based on the ideXlab platform.

  • An Intelligent Adaptive Algorithm for Environment Parameter Estimation in Smart Cities
    IEEE Access, 2018
    Co-Authors: Mou Wu, Neal N. Xiong
    Abstract:

    Least mean squares (LMS) adaptive algorithms are attractive for distributed Environment Parameter estimation problems in a smart city due to the benefits of cooperation, adaptation, and rapid convergence. To obtain a reliable estimate of the network-wide Parameter vector, local results can be further fused by intermediate agents in a distributed incremental way. In this paper, we propose an intelligent variable step size incremental LMS (VSS-ILMS) algorithm to solve the dilemma between fast convergence rate and low mean-square deviation (MSD) in conventional incremental LMS (ILMS) algorithms. The main idea behind our proposal is that the local step-size is adaptively updated by minimizing the MSD in every iteration, where Tikhonov regularization and time-averaging estimation methods are adopted. A theoretical analysis of proposed algorithm is presented in terms of mean square performance and mean step size in a closed form. Simulation results show that VSS-ILMS algorithm outperforms the constant step size ILMS algorithm and several classical variable step-size LMS algorithms. The derived theoretical results shows good agreement with those based on simulated data. For a practical consideration, the proposed algorithm is also verified by the model of target localization in sensor networks.

J Du - One of the best experts on this subject based on the ideXlab platform.

  • channel modeling and simulation in satellite mobile communication systems
    IEEE Journal on Selected Areas in Communications, 1992
    Co-Authors: Branka Vucetic, J Du
    Abstract:

    An analog model describing signal amplitude and phase variations on shadowed satellite mobile channels is proposed. A linear combination of log-normal, Rayleigh, and Rice models is used to describe signal variations over an area with constant Environment attributes while an M-state Markov chain is applied to represent Environment Parameter variations. Channel Parameters are evaluated from the experimental data and utilized to verify a simulation model. Results, presented in the form of signal waveforms, probability density functions, fade durations, and average bit and block error rates, show close agreement with measurements. >

Ahmad Bashawir Abdul Ghani - One of the best experts on this subject based on the ideXlab platform.

  • Environmental sustainability practices among palm oil millers
    Clean Technologies and Environmental Policy, 2019
    Co-Authors: Halima Begum, A. C. Er, A. S. A. Ferdous Alam, Ahmad Bashawir Abdul Ghani
    Abstract:

    Considering the global palm oil production, it can be identified as the second largest vegetable oil. Palm oil is a natural resource that is favorable for the Malaysian climate. In 2017, Malaysia had a total of 454 palm oil mills with a production capacity of approximately 112 million tonnes of fresh fruit bunches. A sustainable Environment denotes high income, value addition and zero waste. Nonetheless, palm oil mills are being associated with the discharge of untreated effluent water stream pollution, solid wastes, air pollution, etc. The important objective of this study is to measure the level of sustainable Environmental practices Parameters and awareness of millers. The primary data were collected through questionnaire survey and interviews from 71 millers in Malaysia. This study used confirmatory factor analysis to describe the relationships between the Environmental Parameters for measuring Environment sustainability. This study found that most of the millers employ positive practices for Environmental sustainability, and the highest Environment Parameter is disposal of solid wastes. However, this study can be implemented in Malaysian palm oil mills for identifying the lowest Parameters. This study suggested to the industries that the new national sustainable policies for palm oil mills, especially for small and medium players, may enhance the Environmental Parameters.

Mou Wu - One of the best experts on this subject based on the ideXlab platform.

  • An Intelligent Adaptive Algorithm for Environment Parameter Estimation in Smart Cities
    IEEE Access, 2018
    Co-Authors: Mou Wu, Neal N. Xiong
    Abstract:

    Least mean squares (LMS) adaptive algorithms are attractive for distributed Environment Parameter estimation problems in a smart city due to the benefits of cooperation, adaptation, and rapid convergence. To obtain a reliable estimate of the network-wide Parameter vector, local results can be further fused by intermediate agents in a distributed incremental way. In this paper, we propose an intelligent variable step size incremental LMS (VSS-ILMS) algorithm to solve the dilemma between fast convergence rate and low mean-square deviation (MSD) in conventional incremental LMS (ILMS) algorithms. The main idea behind our proposal is that the local step-size is adaptively updated by minimizing the MSD in every iteration, where Tikhonov regularization and time-averaging estimation methods are adopted. A theoretical analysis of proposed algorithm is presented in terms of mean square performance and mean step size in a closed form. Simulation results show that VSS-ILMS algorithm outperforms the constant step size ILMS algorithm and several classical variable step-size LMS algorithms. The derived theoretical results shows good agreement with those based on simulated data. For a practical consideration, the proposed algorithm is also verified by the model of target localization in sensor networks.