James Taylor

Bio: James Taylor is an academic researcher from Newcastle University. The author has contributed to research in topics: Laser & Fiber laser. The author has an hindex of 95, co-authored 1161 publications receiving 39945 citations. Previous affiliations of James Taylor include Institut national de la recherche agronomique & European Spallation Source.

Mode-locking by nanotubes of a Raman laser based on a highly doped GeO 2 fiber

Abstract: A mode-locked Raman laser, using 25 m of a GeO 2 doped fiber as the gain medium, is reported employing carbon nanotubes. The oscillator generates 850 ps chirped pulses, which are externally compressed to 185 ps.

A framework for the development of a global standardised marine taxon reference image database (SMarTaR-ID) to support image-based analyses

Abstract: Video and image data are regularly used in the field of benthic ecology to document biodiversity. However, their use is subject to a number of challenges, principally the identification of taxa within the images without associated physical specimens. The challenge of applying traditional taxonomic keys to the identification of fauna from images has led to the development of personal, group, or institution level reference image catalogues of operational taxonomic units (OTUs) or morphospecies. Lack of standardisation among these reference catalogues has led to problems with observer bias and the inability to combine datasets across studies. In addition, lack of a common reference standard is stifling efforts in the application of artificial intelligence to taxon identification. Using the North Atlantic deep sea as a case study, we propose a database structure to facilitate standardisation of morphospecies image catalogues between research groups and support future use in multiple front-end applications. We also propose a framework for coordination of international efforts to develop reference guides for the identification of marine species from images. The proposed structure follows the Darwin Core standard to allow integration with existing databases. We suggest a management framework where high-level taxonomic groups are curated by a regional team, consisting of both end users and taxonomic experts. We identify a mechanism by which overall quality of data within a common reference guide could be raised over the next decade. Finally, we discuss the role of a common reference standard in advancing marine ecology and supporting sustainable use of this ecosystem.

Study of the within-plant spatial variability of stomatal conductance on a young 'Arbequina' olive orchard under drip-irrigated and semi-arid conditions

Abstract: Para olivos regados por goteo, el monitoreo del estado hidrico de la planta es una herramienta fundamental para la gestion del riego, ya que influencia directamente el rendimiento final de fruta y de aceite. Sin embargo, el monitoreo del estado hidrico de la planta utilizando mediciones fisiologicas tales como el potencial hidrico y la conductancia estomatica (gs), implican un desafio tecnico importante en la seleccion del sitio de medicion dentro del dosel, el cual debe ser representativo de toda la planta. Por lo tanto, el objetivo de la presente investigacion fue estudiar la variabilidad espacial de la conductancia estomatica dentro de la planta, en un huerto joven de olivos regados por goteo creciendo en condiciones semi-aridas. Se realizo un ensayo de campo en un huerto comercial joven de olivos (Olea europea L. 'Arbequina') regado por goteo, ubicado en el valle de Pencahue, Region del Maule, Chile (35° 23' S; 71° 44' O; WGS 84; 96 m.s.n.m.). Las mediciones de gs se realizaron en cuatro fechas utilizando un analizador infrarrojo de gases (LI-COR, LI-6400, EE.UU.) durante la temporada de crecimiento 2011-2012. Los resultados mostraron que en condiciones de restriccion hidrica de leve a moderada (-1,5 a -2,2 MPa), la variabilidad intraplanta de la conductancia estomatica fue alta, permitiendo identificar dos zonas distintas dentro del follaje, las cuales fueron observadas en ambos niveles de expresion vegetativa. Por el contrario, en condiciones de restriccion hidrica de moderada a fuerte (< -2,2 a -3,5 MPa), la variabilidad intraplanta de la conductancia estomatica fue baja para ambos niveles de expresion vegetativa, sin detectar sectores distintos al interior de la planta. Los resultados anteriores son relevante para la seleccion del sitio mas apropiado de muestreo dentro del dosel de la planta para las mediciones de potencial hidrico y/o intercambio gaseoso.

Skeuomorphism in digital archaeological practice : A barrier to progress, or a vital cog in the wheels of change?

Abstract: Drawing upon the author’s combined experiences of developing digital field workflows at the sites of Catalhoyuk in Turkey and Kampinge in Sweden, this paper will discuss the role of skeuomorphism within the context of digital archaeological practice, and specifically, it will focus upon the ways that the use of digital technology affects the epistemological processes associated with fieldwork. In doing so it will examine whether common trends towards skeuomorphism in digital structure and practice may actually form an essential part of the process of ‘getting to grips’ with new digital technologies and shape a conceptual framework for this process. This framework will be discussed within the context of wider disciplinary trends and theory and ultimately a case will me made that skeuomorphism may need to be embraced if, as a discipline, we are going to explore the potential of emergent digital technologies to transform our digital practice in the long term (Less)

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Using Multivariate Statistics

Abstract: Thank you for downloading using multivariate statistics. As you may know, people have look hundreds times for their favorite novels like this using multivariate statistics, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some harmful bugs inside their laptop. using multivariate statistics is available in our digital library an online access to it is set as public so you can download it instantly. Our books collection saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the using multivariate statistics is universally compatible with any devices to read.

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Linear Matrix Inequalities in System and Control Theory

Abstract: Preface 1. Introduction Overview A Brief History of LMIs in Control Theory Notes on the Style of the Book Origin of the Book 2. Some Standard Problems Involving LMIs. Linear Matrix Inequalities Some Standard Problems Ellipsoid Algorithm Interior-Point Methods Strict and Nonstrict LMIs Miscellaneous Results on Matrix Inequalities Some LMI Problems with Analytic Solutions 3. Some Matrix Problems. Minimizing Condition Number by Scaling Minimizing Condition Number of a Positive-Definite Matrix Minimizing Norm by Scaling Rescaling a Matrix Positive-Definite Matrix Completion Problems Quadratic Approximation of a Polytopic Norm Ellipsoidal Approximation 4. Linear Differential Inclusions. Differential Inclusions Some Specific LDIs Nonlinear System Analysis via LDIs 5. Analysis of LDIs: State Properties. Quadratic Stability Invariant Ellipsoids 6. Analysis of LDIs: Input/Output Properties. Input-to-State Properties State-to-Output Properties Input-to-Output Properties 7. State-Feedback Synthesis for LDIs. Static State-Feedback Controllers State Properties Input-to-State Properties State-to-Output Properties Input-to-Output Properties Observer-Based Controllers for Nonlinear Systems 8. Lure and Multiplier Methods. Analysis of Lure Systems Integral Quadratic Constraints Multipliers for Systems with Unknown Parameters 9. Systems with Multiplicative Noise. Analysis of Systems with Multiplicative Noise State-Feedback Synthesis 10. Miscellaneous Problems. Optimization over an Affine Family of Linear Systems Analysis of Systems with LTI Perturbations Positive Orthant Stabilizability Linear Systems with Delays Interpolation Problems The Inverse Problem of Optimal Control System Realization Problems Multi-Criterion LQG Nonconvex Multi-Criterion Quadratic Problems Notation List of Acronyms Bibliography Index.