1,721,286 research outputs found
Optimal feedback control for the identification of two-wheeled mobile robot
No full textThe ability to obtain the maximum amount of information from a system while achieving the desired control performance highly depends on the applied excitation signal. In this work, a novel strategy is proposed for the parameter identification and control of two-wheeled mobile robot. The proposed method combines the nonlinear system identification paradigm and model predictive control (MPC) in a single framework in order to design the optimal feedback control algorithm. The fundamental objective of optimal input signal is to minimize the cost related to the identification experiment and provide a system model which gives the desired control performance. In the proposed strategy, Extended Kalman Filter (EKF) or Unscented Kalman filter (UKF) are proposed to be used together with an MPC strategy to yield the optimal control signal. Based on the system performance and quality of the information obtained, a comparison study is presented. The effectiveness of the proposed strategy is demonstrated on a two-wheeled mobile robot
Optimal feedback input design for dynamic nonlinear systems
No full textAn optimal feedback input design method for active parameter identification of dynamic nonlinear systems is presented. The problem is formulated in a receding horizon framework where extended Kalman filter is used for system identification and the optimal input is designed in a nonlinear model predictive control framework. Towards this end, a suitable optimality criterion related to the unknown parameters is proposed and motivated as an information measure. The aim of the optimal input design is to yield maximal information from the unknown system by minimising the cost related to the unknown parameters while maintaining some process performance and satisfying the possible constraints. Simulations are performed to show the effectiveness of the proposed algorithm
Making software architecture and agile approaches work together: foundations and approaches
No full textSoftware architecture (SA) is one of the most significant areas of research and practice in software engineering. It has been shown that getting architecture of large-scale complex systems right is not only extremely important but hugely challenging. The increasing popularity and adoption of Agile Software Development (ASD) methods have brought architecture-centric methods and practices into question as agile followers tend to perceive architecture in the context of plan-driven software development. It is widely recognized that SA needs sufficient attention for successful development and evolution of software-intensive systems and services irrespective of the software development paradigm. Given the nature of the discipline, SA methods and approaches tend to be effort-intensive and heavyweight for certain kinds of projects. There is an increasing interest in finding ways to apply architecture-centric principles and practices in an Agile fashion-Agile architecting. A good understanding of architectural principles and approaches is a prerequisite to agile architecting. The aim of this chapter is to briefly describe the fundamental concepts, principles, and practices of architecture-centric approaches. These concepts, principles, and practices are expected to provide a reader with sufficient understanding of different aspects of SA and its related methods to combine them with ASD methods. We start with a brief discussion of the points that make architecture and agile approaches seemingly incompatible. Then we present and discuss some of the key aspects of architecture-centric approaches and techniques that need to be considered for use in ASD projects. We also provide an overview of some of the key practices that have been recommended for successfully integrating architecture-centric approaches in ASD for developing large-scale, software-intensive systems. © 2014 Elsevier Inc. All rights reserved.Muhammad Ali Baba
Applying empirical software engineering to software architecture: challenges and lessons learned
Full text linkIn the last 15 years, software architecture has emerged as an important software engineering field for managing the development and maintenance of large, software-intensive systems. Software architecture community has developed numerous methods, techniques, and tools to support the architecture process (analysis, design, and review). Historically, most advances in software architecture have been driven by talented people and industrial experience, but there is now a growing need to systematically gather empirical evidence about the advantages or otherwise of tools and methods rather than just rely on promotional anecdotes or rhetoric. The aim of this paper is to promote and facilitate the application of the empirical paradigm to software architecture. To this end, we describe the challenges and lessons learned when assessing software architecture research that used controlled experiments, replications, expert opinion, systematic literature reviews, observational studies, and surveys. Our research will support the emergence of a body of knowledge consisting of the more widely-accepted and well-formed software architecture theories
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
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