1,721,041 research outputs found
A framework for stochastic scheduling of two-machine robotic rework cells with in-process inspection system
No full textAbstract not availableMehdi Foumani, Kate Smith-Miles, Indra Gunawan, Asghar Moein
Datasets for outlier detection
No full textThe zip files contains 12338 datasets for outlier detection investigated in the following papers:(1) Instance space analysis for unsupervised outlier detection Authors : Sevvandi Kandanaarachchi, Mario A. Munoz, Kate Smith-Miles (2) On normalization and algorithm selection for unsupervised outlier detection Authors : Sevvandi Kandanaarachchi, Mario A. Munoz, Rob J. Hyndman, Kate Smith-MilesSome of these datasets were originally discussed in the paper: On the evaluation of unsupervised outlier detection:measures, datasets and an empirical studyAuthors : G. O. Campos, A, Zimek, J. Sander, R. J.G.B. Campello, B. Micenkova, E. Schubert, I. Assent, M.E. Houle. </div
Gegenbauer collocation integration methods: advances in computational optimal control theory
No full textThe analytic solutions of simple optimal control problems may be found using the classical tools such as the calculus of variations, dynamic programming, or the minimum principle. However, in practice, a closed form expression of the optimal control is difficult or even impossible to determine for general nonlinear optimal control problems. Therefore such intricate optimal control problems must be solved numerically. The numerical solution of optimal control problems has been the subject of a significant amount of study since the last century; yet determining the optimal control within high precision remains very challenging in many optimal control applications. The classes of direct orthogonal collocation methods and direct pseudospectral methods are some of the most elegant numerical methods for solving nonlinear optimal control problems nowadays. These methods offer several advantages over many other popular discretization methods in the literature. The key idea of these methods is to transcribe the infinite-dimensional continuous-time optimal control problem into a finite-dimensional nonlinear programming problem. These methods are based on spectral collocation methods, which have been extensively applied and actively used in many areas. Many polynomials approximations and various discretization points have been introduced and studied in the literature for the solution of optimal control problems using control and/or state parameterizations. The commonly used basis polynomials in direct orthogonal collocation methods and direct pseudospectral methods are the Chebyshev and Legendre polynomials, and the collocation points are typically chosen to be of the Gauss or Gauss-Lobatto type of points. The integral operation in the cost functional of an optimal control problem is usually approximated by the well-known Gauss quadrature rules. The differentiation operations are frequently calculated by multiplying a constant differentiation matrix known as the spectral differentiation matrix by the matrix of the function values at a certain discretization/collocation nodes. Thus, the cost functional, the dynamics, and the constraints of the optimal control problem are approximated by a set of algebraic equations. Unfortunately, there are two salient limitations associated with the applications of typical direct orthogonal collocation methods and direct pseudospectral methods: (i) The spectral differentiation matrix, especially those of higher-orders, are widely known to be ill-conditioned; therefore, the numerical computations may be very sensitive to round-off errors. In fact, for a higher-order spectral differentiation matrix, the ill-conditioning becomes very extreme to the extent that the development of efficient preconditioners is a necessity. (ii) The popular spectral differentiation matrix employed frequently in the literature of direct orthogonal collocation methods and direct pseudospectral methods is a square and dense matrix. Therefore, to determine approximations of higher-orders, one usually has to increase the number of collocation points in a direct pseudospectral method, which in turn increases the number of constraints and the dimensionality of the resulting nonlinear programming problem. Also increasing the number of collocation points in a direct orthogonal collocation method increases the number of constraints of the reduced nonlinear programming problem. Eventually, the increase in the size of the spectral differentiation matrix leads to larger nonlinear programming problems, which may be computationally expensive to solve and time-consuming. The research goals of this dissertation are to furnish an efficient, accurate, rapid and robust optimal control solver, and to produce a significantly small-scale nonlinear programming problem using considerably few collocation points. To this end, we introduce a direct optimization method based on a novel Gegenbauer collocation integration scheme which draws upon the power of the well-developed nonlinear programming techniques and computer codes, and the well-conditioning of the numerical integration operators. This modern technique adopts two principle elements to achieve the research goals: (i) The discretization of the optimal control problem is carried out within the framework of a complete integration environment to take full advantage of the well-conditioned numerical integral operators. (ii) The integral operations included in the components of the optimal control problem are approximated through a novel optimal numerical quadrature in a certain optimality measure. The introduced numerical quadrature outperforms classical spectral quadratures in accuracy, and can be established efficiently through the Hadamard multiplication of a constant rectangular spectral integration matrix by the vector of the integrand function values at some optimal Gegenbauer-Gauss interpolation nodes, which usually differ from the employed integration/collocation nodes. The work presented in this dissertation shows clearly that the rectangular form of the developed numerical integration matrix is substantial for the achievement of very precise solutions without affecting the size of the reduced nonlinear programming problem. Chapter 1 is an introductory chapter highlighting the strengths and the weaknesses of various solution methods for optimal control problems, and provides the motivation for the present work. The chapter concludes with a general framework for using Gegenbauer expansions to solve optimal control problems and an overview for the remainder of the dissertation. Chapter 2 presents some preliminary mathematical background and basic concepts relevant to the solution of optimal control problems. In particular, the chapter introduces some key concepts of the calculus of variations, optimal control theory, direct optimization methods, Gegenbauer polynomials, Gegenbauer collocation, in addition to some other essential topics. Chapter 3 presents a published article in Journal of Computational and Applied Mathematics titled “Optimal Gegenbauer quadrature over arbitrary integration nodes.” In this chapter, we introduce a novel optimal Gegenbauer quadrature to efficiently approximate definite integrations numerically. The novel numerical scheme introduces the idea of exploiting the strengths of the Chebyshev, Legendre, and Gegenbauer polynomials through a unified approach, and using a unique numerical quadrature. In particular, the numerical scheme developed employs the Gegenbauer polynomials to achieve rapid rates of convergence of the quadrature for the small range of the spectral expansion terms. For a large-scale number of expansion terms, the numerical quadrature has the advantage of converging to the optimal Chebyshev and Legendre quadratures in the -norm and -norm, respectively. The developed Gegenbauer quadrature can be applied for approximating integrals with any arbitrary sets of integration nodes. Moreover, exact integrations are obtained for polynomials of any arbitrary degree if the number of columns in the developed Gegenbauer integration matrix is greater than or equal to . The error formula for the Gegenbauer quadrature is derived. Moreover, a study on the error bounds and the convergence rate shows that the optimal Gegenbauer quadrature exhibits very rapid convergence rates faster than any finite power of the number of Gegenbauer expansion terms. Two efficient computational algorithms are presented for optimally constructing the Gegenbauer quadrature, and to ideally maintain the robustness and the rapid convergence of the discrete approximations. We illustrate the high-order approximations of the optimal Gegenbauer quadrature through extensive numerical experiments including comparisons with conventional Chebyshev, Legendre, and Gegenbauer polynomial expansion methods. The present method is broadly applicable and represents a strong addition to the arsenal of numerical quadrature methods. Chapter 4 presents a published article in Advances in Computational Mathematics titled “On the optimization of Gegenbauer operational matrix of integration.” The chapter is focused on the intriguing question of “which value of the Gegenbauer parameter is optimal for a Gegenbauer integration matrix to best approximate the solution of various dynamical systems and optimal control problems?” The chapter highlights those methods presented in the literature which recast the aforementioned problems into unconstrained/constrained optimization problems, and then add the Gegenbauer parameter associated with the Gegenbauer polynomials as an extra unknown variable to be optimized. The theoretical arguments presented in this chapter prove that this naive policy is invalid since it violates the discrete Gegenbauer orthonormality relation, and may in turn produce false optimization problems analogs to the original problems with poor solution approximations. Chapter 5 presents a published article in Journal of Computational and Applied Mathematics titled “Solving boundary value problems, integral, and integro-differential equations using Gegenbauer integration matrices.” The chapter resolves the issues raised in the previous chapter through the introduction of a hybrid Gegenbauer collocation integration method for solving various dynamical systems such as boundary value problems, integral and integro-differential equations. The proposed method recasts the original problems into their integral formulations, which are then discretized into linear systems of algebraic equations using a hybridization of the Gegenbauer integration matrices developed in Chapter 3. The resulting linear systems are generally well-conditioned and can be easily solved using standard linear system solvers. A study on the error bounds of the proposed method is presented, and the spectral convergence is proven for two-point boundary-value problems. Comparisons with other competitive methods in the recent literature are included. The proposed method results in an efficient algorithm, and spectral accuracy is verified using eight test examples addressing the aforementioned classes of problems. The developed numerical scheme provides a viable alternative to other solution methods when high-order approximations are required using only a relatively small number of solution nodes. Chapter 6 presents a published article in The Proceedings of 2012 Australian Control Conference, AUCC 2012, titled “Solving optimal control problems using a Gegenbauer transcription method.” The chapter presents a novel direct orthogonal collocation method using Gegenbauer-Gauss collocation for solving continuous-time optimal control problems with nonlinear dynamics, state and control constraints, where the admissible controls are continuous functions. The framework of the novel method involves the mapping of the time domain onto the interval , and transforming the dynamical system given as a system of ordinary differential equations into its integral formulation through direct integration. In this manner, the proposed Gegenbauer transcription method unifies the process of the discretization of the dynamics and the integral cost function. The state and the control variables are then fully parameterized using Gegenbauer expansion series with some unknown Gegenbauer spectral coefficients. The proposed Gegenbauer transcription method recasts the performance index, the reduced dynamical system, and the constraints into systems of algebraic equations using the optimal Gegenbauer quadrature introduced in Chapter 3. Finally, the Gegenbauer transcription method transcribes the infinite-dimensional optimal control problem into a finite-dimensional nonlinear programming problem, which can be solved in the spectral space; thus approximating the state and the control variables along the entire time horizon. The high precision and the spectral convergence of the discrete solutions are verified through two optimal control test problems with nonlinear dynamics and some inequality constraints. In particular, we investigate the application of the proposed method for finding the best path in 2D of an unmanned aerial vehicle moving in a stationary risk environment. Moreover, we compare the performance of the proposed Gegenbauer transcription method with another classical variational technique to demonstrate the efficiency and the accuracy of the proposed method. Chapter 7 presents a published article in Journal of Computational and Applied Mathematics titled “Fast, accurate, and small-scale direct trajectory optimization using a Gegenbauer transcription method.” This chapter extends the Gegenbauer transcription method introduced in the preceding chapter to deal further with continuous-time optimal control problems including different orders time derivatives of the states by solving the continuous-time optimal control problem directly for the control and the highest-order time derivative . The state vector and its derivatives up to the th-order derivative can then be stably recovered by successive integration. Moreover, we present our solution method for solving linear quadratic regulator problems as we aim to cover a wider collection of continuous-time optimal control problems with the concrete aim of comparing the efficiency of the current work with other classical discretization methods in the literature. The advantages of the proposed direct Gegenbauer transcription method over other traditional discretization methods are shown through four well-studied optimal control test examples. The present work is a major breakthrough in the area of computational optimal control theory as it delivers significantly accurate solutions using considerably small numbers of collocation points, states and controls expansions terms. Moreover, the Gegenbauer transcription method produces very small-scale nonlinear programming problems, which can be solved very quickly using modern nonlinear programming software. The Gegenbauer collocation integration scheme adopted in this dissertation allows for the solution of continuous-time optimal control problems governed by various types of dynamical systems; thus encompassing a wider collection of problems than standard optimal control solvers. Moreover, the method is simple and very suitable for digital computations. Chapter 8 presents some concluding remarks on the works developed in this dissertation including some suggestions for future research
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Visually appealing and intelligent projection with natural interaction
No full textProjectors satisfy our natural urge to interact with the virtual world with large, human-sized surfaces. We develop novel techniques to create realistic and appealing projection, using a single projector, on ad hoc but ubiquitous Lambertian dual-planar surfaces, and demonstrate support for a range of meaningful interactions with natural interaction. Deploying projectors in such environments creates several image artifacts resulting in degradation of observed imagery by end-users. Several artifacts due to global illumination, defocus blur, geometry distortion, and ambient light can occur in such environments. To correct these artifacts the projector is coupled with a camera that senses the environment thereby forming a closed loop system. In these environments interreflection of light results in global illumination effects. Our method to compensate for these effects is based on the systematic adaptation and interpretation of the classical radiosity equation in the image domain. Our method does not assume prior knowledge of 3D scene geometry. Our algorithm achieves compensation in real time. The output of our method has better contrast and is thus more appealing to the viewer. Projectors can create bright and crisp images on a single planar surface. The large aperture lenses used in projectors to create displays restricts their depth of field, thereby resulting in defocus blur artifacts when projectors are used in ad hoc environments. We advance the state of the art by demonstrating defocus correction in a non-parametric setting. Our method differs from prior methods in that (a) the luminance and chrominance channels are holistically considered, and (b) a sparse sampling of the surface is used to discover the spatially varying defocus kernel. Certain area of the large display surface could be non-projectable due to the presence of undesirable characteristics (like running wires, saturated color patches, etc.). This causes the projected content to distort and/or occlude making it unreadable. This leads us to the problem of projection in limited area on a single planar surface that we call as the re-targeting problem. We explore some of the research challenges involved in solving this problem and develop a content based re-targeting (CBR) solution for re-targeting content of presentation slides. CBR along with natural user interaction has been used to develop an intelligent application called SmartPro. It allows dynamic control of projection area and intensity. This allows us to support a range of interactions like dynamic annotation of the projected content on the display surface, holistic movement of the projected content to unoccluded parts, etc. Traditionally one or more external sensors observe the projection environment and user interaction is extracted and interpreted from the observed data. This requires appropriate instrumentation and configuration of the environment. Further a lot of data (in addition to the interactions) are captured. We propose a different approach wherein the sensor is associated with the interaction, called sensor on activity. The task of interaction extraction is now simplified. This paradigm has been effectively demonstrated through a virtual shooting range application where the sensor (camera) is mounted on the weapon and is directly associated with the shooting activity. Tracking and inferring position and orientation of weapon, as in traditional setups, to determine if a fire has been successful is not required any more. This system is able to support firing at video frame rates.Thesis submitted in partial fulfillment of the requirements of the degree of Doctor of Philosophy of the Indian Institute of Technology Bombay, India and Monash University, Australia
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