8,426 research outputs found
Oral history interview with C.J. Taylor, July 14, 2002
No full text1 electronic record(s) and derivatives. 2 audio file (wav, mp3) 1001910216 bytes. 01:34:39. 3 PDF documents (2 scans, jp2). 1.08 GB (1,163,245,328 bytes)Oral history interview with C.J. Taylor, July 14, 2002. Blackshear (Ga.). Fieldworker: Timothy C. Prizer. Audio file digitized from cassette tape. Part of the South Georgia Folklife Project at Valdosta State University Archives and Special Collections.
The contents are an occupational folklife analysis on C.J. Taylor’s life living and working in numerous turpentine camps. The interview focuses on several aspects of life in the camp, predominately on the sometimes harsh characteristics of woodsriders and bosses. Taylor is a Korean War veteran, and this is a recurrent topic as well
Advances in Intelligent Control
No full textAdvances in Intelligent Control is a collection of essays arranged in two parts. Part one contains recent contributions of artificial neural networks to modelling and control. Part two concerns itself primarily with aspects of fuzzy logic in intelligent control, guidance and estimation although some of the contributions either make direct equivalence relationships to neural networks or use hybrid methods where a neural network is used to develop the fuzzy rule base. Written by an internationally respected team of experts, contents include: Neural networks for modelling and control. Learning control with interpolative memories. Neural network model-based predictive control. Hierarchical fuzzy control. Indirect adaptive fuzzy logic control. Adaptive expert systems. Bibliography. C.J. Harris is Lucas Professor of Aerospace Systems Engineering at the University of Southampton, Southampton, UK. Index: 1. Editor's Introduction - C.J. Harris Part I - Neural Networks in Intelligent Control 2. Neural Networks for Modelling and Control: A Review - M. Brown and C.J. Harris 3. Neural Net Computing and Intelligent Control of Systems - Y.H. Pao et al. 4. Neural Networks for Nonlinear Dynamic System Modelling and Identification - S. Chen and S.A. Billings 5. Learning Control with Interpolative Memories - H. Tolle et al. 6. ASMOD: An algorithm for Adaptive Spline Modelling of Observation Data - T. Kavli 7. Adaptive Control of Nonlinear Systems - F.C. Chen and H.K. Khalil 8. Neural Network Model Based Predictive Control - J. Saint-Donat et al. Part II - Fuzzy Logic Control 9. Aspects of Fuzzy Control and Estimation: A Review - C.G. Moore and C.J. Harris 10. Hierarchical Fuzzy Control - G. Raju 11. Unified Real Time Approximate Reasoning - D. Linkens and J. Nie 12. Indirect Adaptive Fuzzy Logic Control - C.G. Moore and C.J. Harris 13. Adaptive Expert Systems - C. Batur and V. Kasparian 14. Neural Network Based Approximate Reasoning: Principles and Implementation - J. Nie and D. Linkens 15. Self-Organizing Control using Fuzzy Neural Networks - T. Yamaguchi et al. Bibliography Further information can be obtained from: Taylor & Francis Ltd Rankine Road Basingstoke Hampshire RG24 8PR UK or Taylor and Francis Inc. 1900 Frost Road Suite 101 Bristol PA 19007-1598 USA Content
C.J. Koch (1932 - )
No full textBiographical, bibliographical, and literary historiography of Australian author C.J. Koch
Anxiety Sensitivity Index 3 (ASI; Taylor, S. et al., 2007) - German version
No full textDer aus dem Englischen ins Deutsche übersetzte ASI-3 wurde zur Erfassung des Konstrukts Angstsensitivität entwickelt. Er enthält 18 Items, aus den eine Gesamtskala und die drei Subskalen (1) Bedenken somatisch (BSM), (2) Bedenken sozial (BZS) und (3) Bedenken kognitiv (BKO) gebildet werden. Reliabilität: Die internen Konsistenzen (Cronbachs Alpha) liegen zwischen Alpha = .75 und Alpha = .92. Validität: Das postulierte dreifaktorielle hierarchische Testmodell wurde belegt. Weiterhin erwies sich die faktorielle Struktur als (metrisch) invariant in Bezug auf den Erhebungsmodus und die Sprachversion. Die empirischen Validitätskoeffizienten spiegeln die aus der Literatur bekannten Beziehungen des Konstrukts im nomologischen Netzwerk angemessen wider. Die höchsten Korrelationen zeigen sich mit alternativen Maßen des Konstrukts und mit Skalen zur Erfassung von Ängstlichkeit und Körpervigilanz. Mittlere bis hohe Validitätskoeffizienten ergeben sich für Depressivität und diverse andere Symptommaße. Konvergente Korrelationen traten ebenfalls mit Neurotizismus auf. Mit den übrigen Faktoren des Fünffaktorenmodells wurden diskriminante Korrelationen gefunden. Die differentielle Validität der drei Subskalen konnte anhand unterschiedlich starker Zusammenhänge von BSM, BSO und BKO mit Validierungskriterien belegt werden. Schließlich ließen sich Personen mit unterschiedlichen klinischen Diagnosen anhand ihrer Ausprägungen auf den Subskalen differenzieren.The ASI-3 which was translated from English into German was developed to measure the construct fear sensitivity. It contains 18 items, from which a total scale and the three subscales (1) somatic concerns (BSM), (2) social concerns (BZS) and (3) cognitive concerns (BKO). Reliability: The internal consistencies (Cronbach's alpha) lie between alpha = .75 and alpha = .92. Validity: The postulated three-factor hierarchical test model was proven. Furthermore, the factorial structure proved to be (metrically) invariant with respect to the survey mode and the language version. The empirical validity coefficients adequately reflect the relationships of the construct in the nomological network known from the literature. The highest correlations can be found with alternative measures of the construct and with scales to measure anxiety and body vigilance. Medium to high validity coefficients result for depressivity and various other symptom measures. Convergent correlations also occurred with neuroticism. Discriminant correlations were found with the other factors of the five-factor model. The differential validity of the three subscales could be proven with validation criteria on the basis of different strong correlations of BSM, BSO and BKO. Finally, persons with different clinical diagnoses could be differentiated on the basis of their expressions on the subscales.reviewedpublishedVersio
Inertial Taylor rules: the benefit of signaling future policy
No full textWe trace the consequences of an energy shock on the economy under two different monetary policy rules: a standard Taylor rule where the Fed responds to inflation and the output gap; and a Taylor rule with inertia where the Fed moves slowly to the rate predicted by the standard rule. We show that with both sticky wages and sticky prices, the outcome of an inertial Taylor rule is superior to that of the standard rule, in the sense that inflation is lower and output is higher following an adverse energy shock. However, if prices alone are sticky, things are less clear and the standard rule delivers substantially less inflation than the inertial rule in the short run.Monetary policy ; Interest rates ; Inflation (Finance)
Numerical simulation of bubble dispersion in turbulent Taylor-Couette flow
No full textWe investigate bubble dispersion in turbulent Taylor-Couette flow. The aim of this study is to describe the main mechanisms yielding preferential bubble accumulation in near-wall structures of the flow. We first proceed to direct numerical simulation of Taylor-Couette flows for three different geometrical configurations (three radius ratios η = R 1/R 2: η = 0.5, η = 0.72, and η = 0.91 with the outer cylinder at rest) and Reynolds numbers corresponding to turbulent regime ranging from 3000 to 8000. The statistics of the flow are discussed using two different averaging procedures that permit to characterize the mean azimuthal velocity, the Taylor vortices contribution and the small-scale turbulent fluctuations. The simulations are compared and validated with experimental and numerical data from literature. The second part of this study is devoted to bubble dispersion. Bubble accumulation is analyzed by comparing the dispersion obtained with the full turbulent flow field to bubble dispersion occurring at lower Reynolds numbers in previous works. Several patterns of preferential accumulation of bubbles have been observed depending on bubble size and the effect of gravity. For the smaller size considered, bubbles disperse homogeneously throughout the gap, while for the larger size they accumulate along the inner wall for the large gap width (η = 0.5). Varying the intensity of buoyancy yields complex evolution of the bubble spatial distribution. For low gravity effect, bubble entrapment is strong leading to accumulation along the inner wall in outflow regions (streaks of low wall shear stress). When buoyancy effect dominates on vortex trapping, bubbles rise through the vortices, while spiral patterns stretched along the inner cylinder are clearly identified. Force balance is analyzed to identify dominating forces leading to this accumulation and accumulation patterns are compared with previous experiments
Audio Interview with Mr. C.J. Rayner Whiteley
No full textAudio - Mr. Whiteley recounts the story of delivering the message of the flood of 1904. He took seventeen hours by horse to travel from Perryvale to Edmonton. Billy Loutit took the same message by foot arriving in Edmonton about the same time. Mr. Whiteley discusses early settlers, farming, homesteading and businesses. He has many anecdotes about life and people living in Athabasca at the start of the twentieth century. He freighted for ten years with the Hudson's Bay Company and also discusses early farming prices and technology extensivelyInformative Interview of Mr. C.J. Raymor Whitely In April 1961 on a Reel to Reel tape recorded onto cassette by R. Tanhas March 198
Numerical simulations of drag modulation by microbubbles in a turbulent Taylor-Couette flow
No full textThe aim of our study is to investigate numerically the interaction between a dispersed phase composed of microbubbles and a turbulent Taylor-Couette flow (flow within the gap between two cylinders). We use the Euler-Lagrange approach based on Direct Numerical Simulation of the continuous phase flow equations and a Lagrangian tracking for the dispersed phase. Each bubble trajectory is calculated by integrating the force balance equation accounting for buoyancy, drag, added-mass, pressure gradient, and the lift forces. The numerical method has been adapted in order to take into account the feed-back effect of the dispersed bubbles on the carrying flow. Our approach is based on local volume average of the two-phase Navier-Stokes equations. Local and temporal variations of the bubble concentration and momentum source terms are accounted for in mass and momentum balance equations. A number of reference cases have been tested to validate the modelling approach and its numerical implementation. Then, our previous study of bubble dispersion has been extended to two-way coupling simulations of turbulent Taylor-Couette flows (only inner cylinder is rotating). Modulation of the drag will be discussed for different geometries, Reynolds numbers and bubble sizes. The results show that near-wall turbulent structures are modified by the presence of bubbles.The aim of our study is to investigate numerically the interaction between a dispersed phase composed of microbubbles and a turbulent Taylor-Couette flow (flow within the gap between two cylinders). We use the Euler-Lagrange approach based on Direct Numerical Simulation of the continuous phase flow equations and a Lagrangian tracking for the dispersed phase. Each bubble trajectory is calculated by integrating the force balance equation accounting for buoyancy, drag, added-mass, pressure gradient, and the lift forces. The numerical method has been adapted in order to take into account the feed-back effect of the dispersed bubbles on the carrying flow. Our approach is based on local volume average of the two-phase Navier-Stokes equations. Local and temporal variations of the bubble concentration and momentum source terms are accounted for in mass and momentum balance equations. A number of reference cases have been tested to validate the modelling approach and its numerical implementation. Then, our previous study of bubble dispersion has been extended to two-way coupling simulations of turbulent Taylor-Couette flows (only inner cylinder is rotating). Modulation of the drag will be discussed for different geometries, Reynolds numbers and bubble sizes. The results show that near-wall turbulent structures are modified by the presence of bubbles
Kernel ellipsoidal trimming
No full textEllipsoid estimation is important in many practical areas such as control, system identification, visual/audio tracking, experimental design, data mining, robust statistics and statistical outlier or novelty detection. A new method, called kernel minimum volume covering ellipsoid (KMVCE) estimation, that finds an ellipsoid in a kernel-defined feature space is presented. Although the method is very general and can be applied to many of the aforementioned problems, the main focus is on the problem of statistical novelty/outlier detection. A simple iterative algorithm based on Mahalanobis-type distances in the kernel-defined feature space is proposed for practical implementation. The probability that a non-outlier is misidentified by our algorithms is analyzed using bounds based on Rademacher complexity. The KMVCE method performs very well on a set of real-life and simulated datasets, when compared with standard kernel-based novelty detection methods
Kernel ellipsoidal trimming
No full textEllipsoid estimation is an issue of primary importance in many practical areas such as control, system identification, visual/audio tracking, experimental design, data mining, robust statistics and novelty/outlier detection. This paper presents a new method of kernel information matrix ellipsoid estimation (KIMEE) that finds an ellipsoid in a kernel defined feature space based on a centered information matrix. Although the method is very general and can be applied to many of the aforementioned problems, the main focus in this paper is the problem of novelty or outlier detection associated with fault detection. A simple iterative algorithm based on Titterington's minimum volume ellipsoid method is proposed for practical implementation. The KIMEE method demonstrates very good performance on a set of real-life and simulated datasets compared with support vector machine methods
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