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    A Distributed Navigation Strategy for Mobile Sensor Networks With the Probabilistic Wireless Links 

    Source: Journal of Dynamic Systems, Measurement, and Control:;2017:;volume( 139 ):;issue: 003:;page 31004
    Author(s): Madhag, Aqeel; Choi, Jongeun
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Mobile sensor networks have been widely used to predict the spatio-temporal physical phenomena for various scientific and engineering applications. To accommodate the realistic models of mobile sensor networks, we incorporated ...
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    Special Issue on Stochastic Models, Control, and Algorithms in Robotics 

    Source: Journal of Dynamic Systems, Measurement, and Control:;2015:;volume( 137 ):;issue: 003:;page 30201
    Author(s): Milutinoviؤ‡, Dejan; Choi, Jongeun
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: We invited authors to submit their original contributions with the focus on theory, applications, or both. The response from the dynamic systems and control community was impressive, and we are glad for the opportunity to ...
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    Tips on Stochastic Optimal Feedback Control and Bayesian Spatiotemporal Models: Applications to Robotics 

    Source: Journal of Dynamic Systems, Measurement, and Control:;2015:;volume( 137 ):;issue: 003:;page 30801
    Author(s): Choi, Jongeun; Milutinoviؤ‡, Dejan
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This tutorial paper presents the expositions of stochastic optimal feedback control theory and Bayesian spatiotemporal models in the context of robotics applications. The presented material is selfcontained so that readers ...
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    Vision-Based Uncertainty-Aware Lane Keeping Strategy Using Deep Reinforcement Learning 

    Source: Journal of Dynamic Systems, Measurement, and Control:;2021:;volume( 143 ):;issue: 008:;page 084503-1
    Author(s): Kim, Myounghoe; Seo, Joohwan; Lee, Mingoo; Choi, Jongeun
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Recent deep learning techniques promise high hopes for self-driving cars while there are still many issues to be addressed such as uncertainties (e.g., extreme weather conditions) in learned models. In this work, for the ...
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    Guaranteed Performance State Feedback Gain Scheduling Control With Uncertain Scheduling Parameters 

    Source: Journal of Dynamic Systems, Measurement, and Control:;2016:;volume( 138 ):;issue: 001:;page 14502
    Author(s): Al; Zhu, Guoming G.; Choi, Jongeun
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Statefeedback gainscheduling controller synthesis with guaranteed performance is considered in this brief. Practical assumption has been considered in the sense that scheduling parameters are assumed to be uncertain. The ...
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    Computational Growth and Remodeling of Abdominal Aortic Aneurysms Constrained by the Spine 

    Source: Journal of Biomechanical Engineering:;2015:;volume( 137 ):;issue: 009:;page 91008
    Author(s): Farsad, Mehdi; Zeinali; Choi, Jongeun; Baek, Seungik
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Abdominal aortic aneurysms (AAAs) evolve over time, and the vertebral column, which acts as an external barrier, affects their biomechanical properties. Mechanical interaction between AAAs and the spine is believed to alter ...
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    Prior Distributions of Material Parameters for Bayesian Calibration of Growth and Remodeling Computational Model of Abdominal Aortic Wall 

    Source: Journal of Biomechanical Engineering:;2015:;volume( 137 ):;issue: 010:;page 101001
    Author(s): Seyedsalehi, Sajjad; Zhang, Liangliang; Choi, Jongeun; Baek, Seungik
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: For the accurate prediction of the vascular disease progression, there is a crucial need for developing a systematic tool aimed toward patientspecific modeling. Considering the interpatient variations, a prior distribution ...
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    Distributed Gaussian Process Regression Under Localization Uncertainty 

    Source: Journal of Dynamic Systems, Measurement, and Control:;2015:;volume( 137 ):;issue: 003:;page 31007
    Author(s): Choi, Sungjoon; Jadaliha, Mahdi; Choi, Jongeun; Oh, Songhwai
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In this paper, we propose distributed Gaussian process regression (GPR) for resourceconstrained distributed sensor networks under localization uncertainty. The proposed distributed algorithm, which combines Jacobi ...
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    Linear Matrix Inequalities Approach to Input Covariance Constraint Control With Application to Electronic Throttle 

    Source: Journal of Dynamic Systems, Measurement, and Control:;2015:;volume( 137 ):;issue: 009:;page 91010
    Author(s): Khudhair Al; White, Andrew; Zhang, Shupeng; Zhu, Guoming; Choi, Jongeun
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In this paper, the input covariance constraint (ICC) control problem is solved by convex optimization subject to linear matrix inequalities (LMIs) constraints. The ICC control problem is an optimal control problem that is ...
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    Appearance-Based Localization of Mobile Robots Using Group LASSO Regression 

    Source: Journal of Dynamic Systems, Measurement, and Control:;2018:;volume( 140 ):;issue: 009:;page 91016
    Author(s): Do, Huan N.; Choi, Jongeun; Young Lim, Chae; Maiti, Tapabrata
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Appearance-based localization is a robot self-navigation technique that integrates visual appearance and kinematic information. To analyze the visual appearance, we need to build a regression model based on extracted visual ...
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    DSpace software copyright © 2002-2015  DuraSpace
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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