After an eventful decade of live-coding activities, this article seeks to explore the practice with the aim of situating it in the history of contemporary arts and music. The article introduces several key points of i...
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After an eventful decade of live-coding activities, this article seeks to explore the practice with the aim of situating it in the history of contemporary arts and music. The article introduces several key points of investigation in live-coding research and discusses some examples of how live-coding practitioners engage with these points in their system design and performances. In light of the extremely diverse manifestations of live-coding activities, the problem of defining the practice is discussed, and the question is raised whether live coding is actually necessary as an independent category.
Methods of passing through resonance zones in mechanical systems are discussed and a new method based on the speed-gradient energy control of two subsystems (rotor and support) is presented. Two typical problems of pa...
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Methods of passing through resonance zones in mechanical systems are discussed and a new method based on the speed-gradient energy control of two subsystems (rotor and support) is presented. Two typical problems of passing through resonance for one- and two-dimensional motion of the support are posed and analyzed by computer simulation. The control algorithms based on the speed-gradient method and averaging allow one to significantly reduce the required level of the controlling torque. The proposed algorithms have a small number of design parameters. Compared with the known algorithms the proposed ones are more simple for design and exhibit stronger robustness properties. (C) 2010 Elsevier Ltd. All rights reserved.
In many cases, multiple-fault diagnosis of plant-wide systems based on steady-state data is impossible. To solve this problem, a new diagnosis strategy based on neural networks has been proposed. In the suggested fram...
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In many cases, multiple-fault diagnosis of plant-wide systems based on steady-state data is impossible. To solve this problem, a new diagnosis strategy based on neural networks has been proposed. In the suggested framework, the neural network is used as the diagnoser trained by a hybrid set of steady and dynamic characteristic data of the system. The dynamic characteristic data include overshoot and undershoot values of measured variables and their corresponding occurrence times. To evaluate its performance, the proposed scheme was used in the diagnosis of the concurrent faults of the Tennessee Eastman (TE) process. Various combinations of concurrent faults were considered in this assessment. The results indicate the generality, flexibility, and accuracy of the proposed algorithm such that it is capable of diagnosing various combinations (from single to sextuple) of simultaneous faults, whereas the other diagnosing methods used for the TE process are capable of distinguishing at most three simultaneous faults.
The quadratic B-spline functions and the central difference operator for the time derivative have been used to develop a new algorithm based on the collocation method to solve modified regularized long wave equation. ...
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The quadratic B-spline functions and the central difference operator for the time derivative have been used to develop a new algorithm based on the collocation method to solve modified regularized long wave equation. A linear stability analysis of the scheme is shown to be marginally stable. The method is validated by studying solitary wave motion, two and three solitary wave interaction, the evolution of solitary waves, and undular bore development. (C) 2009 Elsevier Ltd. All rights reserved.
The identification problem of delay time as well as parameters of time-delay chaotic system is investigated in this paper. The identification problem is converted to that of parameter optimization by constructing suit...
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The identification problem of delay time as well as parameters of time-delay chaotic system is investigated in this paper. The identification problem is converted to that of parameter optimization by constructing suitable fitness function. A novel optimization method, called CAS (chaotic ant swarm), which simulates the chaotic behavior of single ant and the self-organization behavior of ant colony, is used to solve this optimization problem. Illustrative example demonstrates the effectiveness of the proposed method. Crown Copyright (C) 2008 Published by Elsevier Ltd. All rights reserved.
Genetic programming (GP) usually has a wide search space and a high flexibility. Therefore, GP may search for global optimum solution. But, in general, GPs learning speed is not so fast. An apriori algorithm is one of...
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Genetic programming (GP) usually has a wide search space and a high flexibility. Therefore, GP may search for global optimum solution. But, in general, GPs learning speed is not so fast. An apriori algorithm is one of association rule algorithms. It can be applied to a large database. But it is difficult to define its parameters without experience. We propose a rule generation technique from a database using GP combined with an association rule algorithm. It takes rules generated by the association rule algorithm as initial individual of GP. The learning speed of GP is improved by the combined algorithm. To verify the effectiveness of the proposed method, we apply it to the decision tree construction problem from the University of California at Irvine (UCI) machine-learning repository, and rule disco very problem from the occurrence of the hypertension database. We compare the results of the proposed method with prior ones.
This study presents a simple but high performance vector quantisation (VQ) codebook search algorithm for line spectral frequency quantisation in ITU-T G.729 speech codec, designated as the binary search space-structur...
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This study presents a simple but high performance vector quantisation (VQ) codebook search algorithm for line spectral frequency quantisation in ITU-T G.729 speech codec, designated as the binary search space-structured VQ (BSS-VQ) algorithm. This is done through a combined use of a fast locating technique and lookup tables, such that an input vector, ahead of VQ encoding, is assigned efficiently to a subspace where merely a small number of codeword searches are required to be performed. As a consequence, the computational load is reduced remarkably. A trade-off can be made easy to meet a user's requirement when performing VQ encoding. It is experimentally validated that a search accuracy is well maintained at 99% approximately for a threshold of quantisation accuracy of 0.99. More importantly, with a full search algorithm as a benchmark for search load comparison, this proposal provides a 85% search load reduction, a figure far beyond 43% in multiple triangular inequality elimination approach, 47% in TIE with dynamic and intersection rules and 59% in quasi-binary search VQ algorithm.
A novel improved particle swarm algorithm named competition particle swarm optimization (CPSO) is proposed to calibrate the Underwater Transponder coordinates. To improve the performance of the algorithm, TVAC algorit...
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A novel improved particle swarm algorithm named competition particle swarm optimization (CPSO) is proposed to calibrate the Underwater Transponder coordinates. To improve the performance of the algorithm, TVAC algorithm is introduced into CPSO to present an extension competition particle swarm optimization (ECPSO). The proposed method is tested with a set of 10 standard optimization benchmark problems and the results are compared with those obtained through existing PSO algorithms, basic particle swarm optimization (BPSO), linear decreasing inertia weight particle swarm optimization (LWPSO), exponential inertia weight particle swarm optimization (EPSO), and time-varying acceleration coefficient (TVAC). The results demonstrate that CPSO and ECPSO manifest faster searching speed, accuracy, and stability. The searching performance for multimodulus function of ECPSO is superior to CPSO. At last, calibration of the underwater transponder coordinates is present using particle swarm algorithm, and novel improved particle swarm algorithm shows better performance than other algorithms.
作者：
Samareh, JANASA
Langley Res Ctr Multidisciplinary Optimizat Branch Hampton VA 23665 USA
A multidisciplinary shape parameterization approach is presented. The approach consists of two basic concepts: 1) parameterizing the shape perturbations rather than the geometry itself and 2) performing the shape defo...
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A multidisciplinary shape parameterization approach is presented. The approach consists of two basic concepts: 1) parameterizing the shape perturbations rather than the geometry itself and 2) performing the shape deformation by means of the soft object animation algorithms used in computer graphics. Because the formulation presented is independent of grid topology, we can treat computational fluid dynamics and finite element grids in the same manner. The proposed approach is simple, compact, and efficient. Also, the analytical sensitivity derivatives are easily computed for use in a gradient-based optimization. This algorithm is suitable for low-fidelity, for example, linear aerodynamics and equivalent laminated plate structures, and high-fidelity, for example, nonlinear computational fluid dynamics and detailed finite element modeling, analysis tools. The implementation details of parameterizing for planform, twist, dihedral, thickness, camber, and free-form surface are given. Results are presented for a multidisciplinary application consisting of nonlinear computational fluid dynamics, detailed computational structural mechanics, and a simple performance module.
This paper presents real-time control characteristics of an electrorheological (ER) suspension system via a fuzzy sliding mode control algorithm which is formulated in a discrete-time manner by considering the samplin...
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This paper presents real-time control characteristics of an electrorheological (ER) suspension system via a fuzzy sliding mode control algorithm which is formulated in a discrete-time manner by considering the sampling rate of an electronic control unit for a vehicle system. A quarter-vehicle system consisting of sprung mass, spring, tire and a cylindrical ER damper (shock absorber) is constructed for the real-time control. After deriving the governing equation of motion of the proposed system, a discrete-time control model with system uncertainties is formulated. A stable sliding surface is then designed and followed by the formulation of the discrete-time sliding mode controller which consists of a discontinuous part and an equivalent part. In the controller formulation, the fuzzy control algorithm is also adopted to enhance system robustness to the mass variation and reaching time to the sliding surface. The controller is then experimentally realized for the manufactured quarter-vehicle ER suspension system. Control performances such as vertical acceleration are evaluated under various road conditions and presented in both time and frequency domains.
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