89 resultados para haptic sensing
Resumo:
Reconstruction of biochemical reaction networks (BRN) and genetic regulatory networks (GRN) in particular is a central topic in systems biology which raises crucial theoretical challenges in system identification. Nonlinear Ordinary Differential Equations (ODEs) that involve polynomial and rational functions are typically used to model biochemical reaction networks. Such nonlinear models make the problem of determining the connectivity of biochemical networks from time-series experimental data quite difficult. In this paper, we present a network reconstruction algorithm that can deal with ODE model descriptions containing polynomial and rational functions. Rather than identifying the parameters of linear or nonlinear ODEs characterised by pre-defined equation structures, our methodology allows us to determine the nonlinear ODEs structure together with their associated parameters. To solve the network reconstruction problem, we cast it as a compressive sensing (CS) problem and use sparse Bayesian learning (SBL) algorithms as a computationally efficient and robust way to obtain its solution. © 2012 IEEE.
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We use a resistive-pulse technique to analyze molecular hybrids of single-wall carbon nanotubes (SWNTs) wrapped in either single-stranded DNA or protein. Electric fields confined in a glass capillary nanopore allow us to probe the physical size and surface properties of molecular hybrids at the single-molecule level. We find that the translocation duration of a macromolecular hybrid is determined by its hydrodynamic size and solution mobility. The event current reveals the effects of ion exclusion by the rod-shaped hybrids and possible effects due to temporary polarization of the SWNT core. Our results pave the way to direct sensing of small DNA or protein molecules in a large unmodified solid-state nanopore by using nanofilaments as carriers. © 2013 American Chemical Society.
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This paper reports on the fabrication and characterization of high-resolution strain sensors for steel based on Silicon On Insulator flexural resonators manufactured with chip-level LPCVD vacuum packaging. The sensors present high sensitivity (120 Hz/μ), very high resolution (4 n), low drift, and near-perfect reversibility in bending tests performed in both tensile and compressive strain regimes. © 2013 IEEE.
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This work investigates the feasibility of transducing molecular-recognition events into a measurable potentiometric signal. It is shown for the first time that biorecognition of acetylcholine (ACh) can be translated to conformational changes in the enzyme, acetylcholine-esterase (AChE), which in turn induces a measurable change in surface potential. Our results show that a highly sensitive detector for ACh can be obtained by the dilute assembly of AChE on a floating gate derived field effect transistor (FG-FET). A wide concentration range response is observed for ACh (10(-2)-10(-9)M) and for the inhibitor carbamylcholine CCh (10(-6)-10(-11)M). These enhanced sensitivities are modeled theoretically and explained by the combined response of the device to local pH changes and molecular dipole variations due to the enzyme-substrate recognition event.
Resumo:
We experimentally demonstrate locking of a laser frequency to a resonance line of a micro disk resonator. Achieving 1±0.1 pm shifting detection, the approach can be applied for sensing enhancement and perturbation immune NSOM measurements. © 2012 OSA.
Resumo:
We experimentally demonstrate locking of a laser frequency to a resonance line of a micro disk resonator. Achieving 1±0.1 pm shifting detection, the approach can be applied for sensing enhancement and perturbation immune NSOM measurements. © OSA 2012.
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We investigate performance bounds for feedback control of distributed plants where the controller can be centralized (i.e. it has access to measurements from the whole plant), but sensors only measure differences between neighboring subsystem outputs. Such "distributed sensing" can be a technological necessity in applications where system size exceeds accuracy requirements by many orders of magnitude. We formulate how distributed sensing generally limits feedback performance robust to measurement noise and to model uncertainty, without assuming any controller restrictions (among others, no "distributed control" restriction). A major practical consequence is the necessity to cut down integral action on some modes. We particularize the results to spatially invariant systems and finally illustrate implications of our developments for stabilizing the segmented primary mirror of the European Extremely Large Telescope. © 2013 Elsevier Ltd. All rights reserved.
Resumo:
A time multiplexed rectangular Zernike modal wavefront sensor based on a nematic phase-only liquid crystal spatial light modulator and specially designed for a high power two-electrode tapered laser diode which is a compact and novel free space optical communication source is used in an adaptive beam steering free space optical communication system, enabling the system to have 1.25 GHz modulation bandwidth, 4.6° angular coverage and the capability of sensing aberrations within the system and caused by atmosphere turbulence up to absolute value of 0.15 waves amplitude and correcting them in one correction cycle. Closed-loop aberration correction algorithm can be implemented to provide convergence for larger and time varying aberrations. Improvement of the system signal-to-noise-ratio performance is achieved by aberration correction. To our knowledge, it is first time to use rectangular orthonormal Zernike polynomials to represent balanced aberrations for high power rectangular laser beam in practice. © 2014 IEEE.
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Using holographic techniques and a tapered laser, an optical wireless communication system with 4.6 degree angular coverage, 1.25GHz modulation bandwidth and the capability of sensing and correcting aberrations within system and from atmosphere is reported. © OSA 2013.
Resumo:
BACKGROUND: Despite the widespread use of sensors in engineering systems like robots and automation systems, the common paradigm is to have fixed sensor morphology tailored to fulfill a specific application. On the other hand, robotic systems are expected to operate in ever more uncertain environments. In order to cope with the challenge, it is worthy of note that biological systems show the importance of suitable sensor morphology and active sensing capability to handle different kinds of sensing tasks with particular requirements. METHODOLOGY: This paper presents a robotics active sensing system which is able to adjust its sensor morphology in situ in order to sense different physical quantities with desirable sensing characteristics. The approach taken is to use thermoplastic adhesive material, i.e. Hot Melt Adhesive (HMA). It will be shown that the thermoplastic and thermoadhesive nature of HMA enables the system to repeatedly fabricate, attach and detach mechanical structures with a variety of shape and size to the robot end effector for sensing purposes. Via active sensing capability, the robotic system utilizes the structure to physically probe an unknown target object with suitable motion and transduce the arising physical stimuli into information usable by a camera as its only built-in sensor. CONCLUSIONS/SIGNIFICANCE: The efficacy of the proposed system is verified based on two results. Firstly, it is confirmed that suitable sensor morphology and active sensing capability enables the system to sense different physical quantities, i.e. softness and temperature, with desirable sensing characteristics. Secondly, given tasks of discriminating two visually indistinguishable objects with respect to softness and temperature, it is confirmed that the proposed robotic system is able to autonomously accomplish them. The way the results motivate new research directions which focus on in situ adjustment of sensor morphology will also be discussed.
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It has been shown that sensory morphology and sensory-motor coordination enhance the capabilities of sensing in robotic systems. The tasks of categorization and category learning, for example, can be significantly simplified by exploiting the morphological constraints, sensory-motor couplings and the interaction with the environment. This paper argues that, in the context of sensory-motor control, it is essential to consider body dynamics derived from morphological properties and the interaction with the environment in order to gain additional insight into the underlying mechanisms of sensory-motor coordination, and more generally the nature of perception. A locomotion model of a four-legged robot is used for the case studies in both simulation and real world. The locomotion model demonstrates how attractor states derived from body dynamics influence the sensory information, which can then be used for the recognition of stable behavioral patterns and of physical properties in the environment. A comprehensive analysis of behavior and sensory information leads to a deeper understanding of the underlying mechanisms by which body dynamics can be exploited for category learning of autonomous robotic systems. © 2006 Elsevier Ltd. All rights reserved.
Resumo:
In this paper, we propose a low complexity and reliable wideband spectrum sensing technique that operates at sub-Nyquist sampling rates. Unlike the majority of other sub-Nyquist spectrum sensing algorithms that rely on the Compressive Sensing (CS) methodology, the introduced method does not entail solving an optimisation problem. It is characterised by simplicity and low computational complexity without compromising the system performance and yet delivers substantial reductions on the operational sampling rates. The reliability guidelines of the devised non-compressive sensing approach are provided and simulations are presented to illustrate its superior performance. © 2013 IEEE.