Author

# James Taylor

Other affiliations: Institut national de la recherche agronomique, European Spallation Source, Children's Hospital of Philadelphia ...read more

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.

Topics: Laser, Fiber laser, Optical fiber, Picosecond, Photonic-crystal fiber

##### Papers published on a yearly basis

##### Papers

More filters

••

Yale University

^{1}TL;DR: The neuro-anatomical and neurochemical substrates subserving inhibitory control and motivational processes in the rodent and primate brain and their putative impact on drug seeking are considered and an integrative hypothesis for compulsive reward-seeking in drug abuse is presented.

Abstract: Drug abuse and dependence define behavioral states involving increased allocation of behavior towards drug seeking and taking at the expense of more appropriate behavioral patterns. As such, addiction can be viewed as increased control of behavior by the desired drug (due to its unconditioned, rewarding properties). It is also clear that drug-associated (conditioned) stimuli acquire heightened abilities to control behaviors. These phenomena have been linked with dopamine function within the ventral striatum and amygdala and have been described specifically in terms of motivational and incentive learning processes. New data are emerging that suggest that regions of the frontal cortex involved in inhibitory response control are directly affected by long-term exposure to drugs of abuse. The result of chronic drug use may be frontal cortical cognitive dysfunction, resulting in an inability to inhibit inappropriate unconditioned or conditioned responses elicited by drugs, by related stimuli or by internal drive states. Drug-seeking behavior may thus be due to two related phenomena: (1) augmented incentive motivational qualities of the drug and associated stimuli (due to limbic/amygdalar dysfunction) and (2) impaired inhibitory control (due to frontal cortical dysfunction). In this review, we consider the neuro-anatomical and neurochemical substrates subserving inhibitory control and motivational processes in the rodent and primate brain and their putative impact on drug seeking. The evidence for cognitive impulsivity in drug abuse associated with dysfunction of the frontostriatal system will be discussed, and an integrative hypothesis for compulsive reward-seeking in drug abuse will be presented.

1,516 citations

••

TL;DR: In this article, the authors present an up-to-date summary of the rates for all types of compact binary coalescence sources detectable by the Initial and Advanced versions of the ground-based LIGO and Virgo Astrophysical estimates for compact-binary coalescence rates depend on a number of assumptions and unknown model parameters.

Abstract: We present an up-to-date, comprehensive summary of the rates for all types of compact binary coalescence sources detectable by the Initial and Advanced versions of the ground-based gravitational-wave detectors LIGO and Virgo Astrophysical estimates for compact-binary coalescence rates depend on a number of assumptions and unknown model parameters, and are still uncertain The most confident among these estimates are the rate predictions for coalescing binary neutron stars which are based on extrapolations from observed binary pulsars in our Galaxy These yield a likely coalescence rate of 100 per Myr per Milky Way Equivalent Galaxy (MWEG), although the rate could plausibly range from 1 per Myr per MWEG to 1000 per Myr per MWEG We convert coalescence rates into detection rates based on data from the LIGO S5 and Virgo VSR2 science runs and projected sensitivities for our Advanced detectors Using the detector sensitivities derived from these data, we find a likely detection rate of 002 per year for Initial LIGO-Virgo interferometers, with a plausible range between 00002 and 02 per year The likely binary neutron-star detection rate for the Advanced LIGO-Virgo network increases to 40 events per year, with a range between 04 and 400 per year

918 citations

••

TL;DR: In this article, a comprehensive theory of risk taking in consumer behavior is presented, specifying the principal concepts involved and the interrelationships between the concepts and some of the research relevant to these concepts and interrelationship is presented.

Abstract: R AYMOND Bauer first formally proposed that consumer behavior be viewed as risk taking in 1960.1 Over a dozen years have passed since that proposal was made, and during that period a substantial body of research has been conducted and published. However, most of this research has examined relatively narrow aspects of risk taking and has been conducted without a broader, comprehensive theoretical structure. This lack of a comprehensive theory of risk taking seems to have worked to obscure the emerging picture of risk as the pivotal element in consumer behavior. Further, once perceived risk has been identified in a purchase situation, there seems to be some reasonable evidence that subsequent consumer behavior can be determined in accordance with such risk. If this view is correct, marketing managers may now have the opportunity to use the various elements of the marketing mix with considerably greater precision than has been possible in the past. This article attempts to construct a comprehensive theory of risk taking in consumer behavior by specifying the principal concepts involved and the interrelationships between the concepts. In addition, some of the research relevant to these concepts and interrelationships is presented. Finally, the author suggests how the theory might be tested and put to work in marketing decisions. The concept of theory used here is in the spirit of Baumol when he says:

759 citations

••

TL;DR: In this paper, an up-to-date compilation of the principal observed parameters of 558 pulsars, including positions, timing parameters, pulse widths, flux densities, proper motions, distances, and dispersion, rotation, and scattering measures, is presented.

Abstract: We present an up-to-date compilation of the principal observed parameters of 558 pulsars, including positions, timing parameters, pulse widths, flux densities, proper motions, distances, and dispersion, rotation, and scattering measures. We also list the orbital elements of binary pulsars and some commonly used parameters derived from the basic measurements. Uncertainties are quoted for most quantities, and references to the original literature are given. Figures are used to illustrate the sample distributions of some of the more important parameters. Machine-readable versions of the tabulated information are available, together with software designed to make the data base useful to others working in the field

683 citations

••

TL;DR: The forecasts produced by the new double seasonal Holt–Winters method outperform those from traditional Holt-Winters and from a well-specified multiplicative double seasonal ARIMA model.

Abstract: This paper considers univariate online electricity demand forecasting for lead times from a half-hour-ahead to a day-ahead. A time series of demand recorded at half-hourly intervals contains more than one seasonal pattern. A within-day seasonal cycle is apparent from the similarity of the demand profile from one day to the next, and a within-week seasonal cycle is evident when one compares the demand on the corresponding day of adjacent weeks. There is strong appeal in using a forecasting method that is able to capture both seasonalities. The multiplicative seasonal ARIMA model has been adapted for this purpose. In this paper, we adapt the Holt-Winters exponential smoothing formulation so that it can accommodate two seasonalities. We correct for residual autocorrelation using a simple autoregressive model. The forecasts produced by the new double seasonal Holt-Winters method outperform those from traditional Holt-Winters and from a well-specified multiplicative double seasonal ARIMA model.

640 citations

##### Cited by

More filters

••

[...]

TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.

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 …

33,785 citations

01 Jan 2016

TL;DR: The using multivariate statistics is universally compatible with any devices to read, allowing you to get the most less latency time to download any of the authors' books like this one.

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.

14,604 citations

•

TL;DR: 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.

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

13,333 citations

••

[...]

TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.

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.).

13,246 citations

•

01 Jan 1994

TL;DR: In this paper, the authors present a brief history of LMIs in control theory and discuss some of the standard problems involved in LMIs, such as linear matrix inequalities, linear differential inequalities, and matrix problems with analytic solutions.

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.

11,085 citations