Fiber Bragg Gratings (FBGs) are among the most popular optical fiber sensors. FBGs are well suited for direct detection of temperature and strain and can be functionalized for pressure, humidity, and refractive index ...
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Fiber Bragg Gratings (FBGs) are among the most popular optical fiber sensors. FBGs are well suited for direct detection of temperature and strain and can be functionalized for pressure, humidity, and refractive index sensing. Commercial setups for FBG interrogation are based on white-light sources and spectrometer detectors, which are capable of decoding the spectrum of an FBG array. Low-cost spectrometers record the spectrum on a coarse wavelength grid (typically 78-156 pm), whereas wavelength shifts of 1 pm or lower are required by most of the applications. Several algorithms have been presented for detection of small wavelength shift, even with coarsewavelength sampling;most notably, the Karhunen-Loeve Transform(KLT) was demonstrated. In this paper, an improved algorithmbased on KLT is proposed, which is capable of further expanding the performances. Simulations show that, reproducing a commercial spectrometer with 156 pm grid, the algorithm estimates wavelength shift with accuracy well below 1 pm. In typical signal-to-noise ratio (SNR) conditions, the root mean square error is 22-220 fm, while the accuracy is 0.22 pm, despite the coarse sampling. Results have been also validated through experimental characterization. The proposed method allows achieving exceptional accuracy in wavelength tracking, beating the picometer level resolution proposed in most commercial and research software, and, due to fast operation (> 5 kHz), is compatible also with structural health monitoring and acoustics.
We introduced a spectral clustering algorithm based on the bipartite graph model for the Manufacturing Cell Formation problem in [Oliveira S, Ribeiro JFF, Seok SC. A spectral clustering algorithm for manufacturing cel...
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We introduced a spectral clustering algorithm based on the bipartite graph model for the Manufacturing Cell Formation problem in [Oliveira S, Ribeiro JFF, Seok SC. A spectral clustering algorithm for manufacturing cell formation. computers and Industrial Engineering. 2007 [submitted for publication]]. It constructs two similarity matrices;one for parts and one for machines. The algorithm executes a spectral clustering algorithm on each separately to find families of parts and cells of machines. The similarity measure in the approach utilized limited information between parts and between machines. This paper reviews several well-known similarity measures which have been used for Group Technology. Computational clustering results are compared by various performance measures. (C) 2008 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
We present two algorithms that are near optimal with respect to the number of inversions present in the input. One of the algorithms is a variation of insertion sort, and the other is a variation of merge sort. The nu...
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We present two algorithms that are near optimal with respect to the number of inversions present in the input. One of the algorithms is a variation of insertion sort, and the other is a variation of merge sort. The number of comparisons performed by our algorithms, on an input sequence of length n that has I inversions, is at most n log(2) (I/n + 1) + O(n) . Moreover, both algorithms have implementations that run in time O(n log(2) (I/n + 1) + n ) . All previously published algorithms require at least cn log(2) (I/n + 1) comparisons for some c > 1.
This paper presents a cyber-physical approach to optimize the semiactive control of a base-isolated structure under a suite of earthquakes. The approach uses numerical search algorithms to guide the exploration of the...
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This paper presents a cyber-physical approach to optimize the semiactive control of a base-isolated structure under a suite of earthquakes. The approach uses numerical search algorithms to guide the exploration of the design space and real-time hybrid simulation (RTHS) to evaluate candidate designs, creating a framework for real-time hybrid optimization (RHTO). By supplanting traditional numerical analysis (i.e., finite element methods) with RTHS, structural components that are difficult to model can be represented accurately while still capturing global structural performance. The efficiency of RTHO is improved for multiple design excitations with the creation of a multiinterval particle swarm optimization (MI-PSO) algorithm. As a proof-of-concept, RTHO is applied to improve the seismic performance of a base-isolated structure with supplemental control. The proposed RTHO framework with MI-PSO is a versatile technique for multivariate optimization under multiple excitations. It is well suited for the accurate and rapid evaluation of structures with nonlinear experimental substructures, in particular, those that do not undergo permanent damage such as structural control devices. The RTHO framework integrates popular optimization algorithms with advanced experimental methods, creating an exciting new cyber-physical approach to design.
Since the normal matrix is often ill-conditioned when solving Rational Function Model (RFM) for the satellite remote sensing imagery, combining with matrix orthogonal decomposition, Levenberg-Marquardt algorithm and C...
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Since the normal matrix is often ill-conditioned when solving Rational Function Model (RFM) for the satellite remote sensing imagery, combining with matrix orthogonal decomposition, Levenberg-Marquardt algorithm and Compute Unified Device Architecture high-performance computing technique, a fast and robust method directly based on the error equation coefficient matrix is proposed. The method is analysed by different parameters of control point grid and compared with the common methods, namely L-curve based ridge estimation and Iteration by Correcting Characteristic Value. The experimental results show that RFM parameters derived by ourmethod have higher fitting accuracy.
Implementation issues represent an unfamiliar challenge to most control engineers, and many techniques for controller design ignore these issues outright. Consequently, the design of controllers for smart structural s...
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Implementation issues represent an unfamiliar challenge to most control engineers, and many techniques for controller design ignore these issues outright. Consequently, the design of controllers for smart structural systems usually proceeds without regard for their eventual implementation, thus resulting either in serious performance degradation or in hardware requirements that squander power, complicate integration, and drive up cost. The level of integration assumed by the smart patch further exacerbates these difficulties, and any design inefficiency may render the realization of a single-package sensor-controller-actuator system infeasible. The goal of this research is to automate the controller implementation process and to relieve the design engineer of implementation concerns like quantization, computational efficiency, and device selection. Field programmable gate arrays (FPGA) are specifically targeted as a hardware platform because these devices are highly flexible, power efficient, and reprogrammable. The current study develops an automated implementation sequence that minimizes hardware requirements while maintaining controller performance. Beginning with a state space representation of the controller, the sequence automatically generates a configuration bitstream for a suitable FPGA implementation. MATLAB functions optimize and simulate the control algorithm before translating it into the VHSIC hardware description language (VHDL). These functions improve power efficiency and simplify integration in the final implementation by performing a linear transformation that renders the controller computationally friendly. The transformation favors sparse matrices in order to reduce multiply operations and the hardware necessary to support them;simultaneously, the remaining matrix elements take on values that minimize limit cycles and parameter sensitivity. The proposed controller design methodology is implemented on a simple cantilever beam test structure using
The application of sliding mode control to permanent-magnet synchronous motors (DC brushless motors), wound-rotor synchronous motors, and asynchronous motors is presented. A unified approach to the control problem of ...
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The application of sliding mode control to permanent-magnet synchronous motors (DC brushless motors), wound-rotor synchronous motors, and asynchronous motors is presented. A unified approach to the control problem of AC machines reveals that a simple control algorithm which effectively solves the problem can be derived using variable-structure system theory. Selection of the control variable (angular position, speed, acceleration, or torque) leaves the basic control structure unchanged, and even current limiting can easily be included. The theoretical results are verified by experiments. The design procedure and experimental results show that this approach provides good behavior of the system in both transient and steady-state operation.
External memory (EM) algorithms are designed for computational problems in which the size of the internal memory of the computer is only a small fraction of the problem size. Blockwise access to data is a central them...
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External memory (EM) algorithms are designed for computational problems in which the size of the internal memory of the computer is only a small fraction of the problem size. Blockwise access to data is a central theme in the design of efficient EM algorithms, A similar requirement arises in the transmission of data between processors in high performance parallel computation systems, for which blockwise communication is a crucial issue. We consider multisearch problems, where a large number of queries are to be simultaneously processed and satisfied by navigating through large data structures on parallel computers, Our examples originate as algorithms for parallel machines, and we adapt them to the EM situation where the queries and data structure are considered to be much larger than the size of the available internal memory. This paper presents techniques to achieve blocking for I/O as well as for communication in multisearch on the BSP and EM-BSP models. We describe improvements to the 1-optimal BSP* multisearch algorithm of [8] which permit larger search trees to be handled. In the area of EM algorithms new algorithms for multisearch in balanced trees are described. For search trees of size O (n log n) where n is the number of queries, we obtain a work-optimal, parallel, randomized EM multisearch algorithm whose I/O and communication time are smaller, asymptotically, than the computation time. We obtain a deterministic version via a similar technique. These algorithms are obtained via the simulation techniques of [12], [17], [13], [14], and [24]. For larger trees we describe a parallel, EM algorithm which is I-optimal considering computation, communication, and I/O (for suitable parameter constellations) plus I/O-optimal. We give a lower bound to the number of I/O operations required for filtering n queries through a binary or multiway search tree of size m when m greater than or equal to n(2 + epsilon) for a constant epsilon > 0.
In this paper we demonstrate techniques for increasing the node-level parallelism of a deterministic discrete ordinates neutral particle transport algorithm on a structured mesh to exploit many-core technologies. Tran...
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In this paper we demonstrate techniques for increasing the node-level parallelism of a deterministic discrete ordinates neutral particle transport algorithm on a structured mesh to exploit many-core technologies. Transport calculations form a large part of the computational workload of physical simulations and so good performance is vital for the simulations to complete in reasonable time. We will demonstrate our approach utilizing the SNAP mini-app, which gives a simplified implementation of the full transport algorithm but remains similar enough to the real algorithm to act as a useful proxy for research purposes. We present an OpenCL implementation of our improved algorithm which achieves a speedup of up to 2.5 x on a many-core GPGPU device compared to a state-of-the-art multi-core node for the transport sweep, and up to 4 x compared to the multi-core CPUs in the largest GPU enabled supercomputer;the first time this scale of speedup has been achieved for algorithms of this class. We then discuss ways to express our scheme in OpenMP 4.0 and demonstrate the performance on an Intel Knights Corner Xeon Phi compared to the original scheme.
This paper presents a modified barebones particle swarm optimization (OBPSO) to solve constrained nonlinear optimization problems. The proposed approach OBPSO combines barebones particle swarm optimization (BPSO) and ...
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This paper presents a modified barebones particle swarm optimization (OBPSO) to solve constrained nonlinear optimization problems. The proposed approach OBPSO combines barebones particle swarm optimization (BPSO) and opposition-based learning (OBL) to improve the quality of solutions. A novel boundary search strategy is used to approach the boundary between the feasible and infeasible search region. Moreover, an adaptive penalty method is employed to handle constraints. To verify the performance of OBPSO, a set of well-known constrained benchmark functions is used in the experiments. Simulation results show that our approach achieves a promising performance.
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