3,146 research outputs found
T.J. Stiles: “The Commodore’s Patriotism: Cornelius Vanderbilt’s Path to the Founding of Vanderbilt University”
No full textIncludes descriptive metadata provided by producer in MP4 file: "Chancellor's Lecture Series - Videos - T.J. Stiles: 'The Commodore’s Patriotism: Cornelius Vanderbilt’s Path to the Founding of Vanderbilt University'." By Vanderbilt University. T.J. Stiles, Pulitzer Prize-winning author and historian, speaks Sept. 29, 2010 as part of the Chancellor's Lecture Series. Stiles wrote the 2009 biography The First Tycoon: The Epic Life of Cornelius Vanderbilt. Chancellor Nicholas Zeppos introduces Stiles. Stiles takes questions after his lecture
Cwbr Author Interview: Custer\u27s Trials: A Life On The Frontier Of A New America
No full textInterview with T.J. Stiles, author of Custer\u27s Trials: A Life on the Frontier of a New America Interviewed by Tom Barber
Civil War Book Review (CWBR): The Civil War Book Review is pleased to speak with T.J. Stiles, winner of multiple awards for biography and author of Jesse James: Last Rebel of the Civil War and The First Tycoon: The Epic Life of Cornelius Vanderbilt. Today we get to discuss his most recent work Custer\u27s Trials: A Life on the Frontier of a New America. Mr. Stiles, thank you for joining us today. T.J. Stiles: Thanks very much for interviewing me...
Prior distribution elicitation
No full textAn overview of key issues associated with the elicitation of a prior probability distribution is provided. The nature of subjective probability is discussed, and the main causes of biased assessments are identified. Evidence is presented suggesting that people can improve their probability assessments under the correct conditions. The ways in which the elicitation of a prior distribution can be embedded within a process to minimize the impact of bias are examined. More advanced issues, namely validation of a prior distribution and reducing the cognitive burden on experts, are described
Carmen sµculare for the year 1700 [electronic resource] : to the King.
No full textIn verse.A celebration of the arrival of William III from Holland. Cf. Oxford Companion to English literature.Attributed to Matthew Prior. Cf. Wing.First ed. Cf. BM.Advertisement ([2] p.) at end.Reproduction of original in Princeton University Library.WingWise, T.J. Ashley lib.Electronic reproduction
Electrostatic wear monitoring of rolling element bearings
No full textResearch and development work at the University of Southampton using an electrostatic condition monitoring system developed by Smiths Aerospace Information Systems has shown that electrostatic charge signals can be used to detect the onset of wear in lubricated tribo-contacts. Preliminary investigations have already demonstrated the viability of this system when tested on a laboratory-based pin-on-disc rig, a reciprocating laboratory wear rig and in an FZG gear scuffing rig. These preliminary experiments have indicated several charging mechanisms may be involved, namely—tribo-charging, localised surface charge variations, exo-emissions and debris generation.The electrostatic monitoring system has now been implemented on a taper-roller bearing test rig. The electrostatic system employed comprises three wear-site sensors (WSS) and an oil-line sensor (OLS). The WSS are mounted close to the bearing in order to monitor the earliest stages of component surface breakdown and wear, whereas the OLS is placed in the re-circulation oil-line to monitor debris generated and transported from the deteriorating component. For the present tests, taper-roller bearing wear was monitored using electrostatic sensors as well as vibration and lubricant temperature measurements; also two additional oil-line monitoring devices, supplied by Macom Technology Ltd., using Eddy current technology and ferromagnetism to sense debris entrained in the lubricant recirculating system were employed.The experimental data shows that the electrostatic monitoring systems detected bearing deterioration up to 4 h prior to complete failure (seizure) during a seeded fault test. The electrostatic wear-site and oil-line sensors detected changes in charge that coincided with increases in vibration, temperature and debris generation detected by the two Macom units
The future of battlefield micro air vehicle systems
No full textThe most recent survey of Unmanned Aerial Vehicle (UAV) adoption rates shows that the area of small, man-portable systems (generally defined as Micro Air Vehicles or MAVs of maximum take-off weight between 1-5 kg) has one of the highest growth rates of any of the market sectors. There is a growing realisation by military planners that to win the insurgency wars of the present and future, forward units will have to operate within the close confines of urban conurbations and for prolonged periods of time without support. Real-time information and intelligence on enemy strength, dispositions and tactics is therefore essential for battlefield succes
Quantitative characterization of solute transport processes in the laboratory using electrical resistivity tomography
No full textThe shallow subsurface is an important zone from a social, economical, and environmental point of view. The increased use of the shallow subsurface together with the call for its protection and sustainable exploitation have increased the need for tools to monitor and characterize the subsurface, as well as for an improved understanding of the hydrogeological processes taking place in this zone. The limitations of traditional point sampling techniques have led to the field of hydrogeophysics, in which geophysical methods are employed to characterize the subsurface at a relatively high spatial resolution but with minimal disturbance. A common geophysical method used for hydrogeological characterization is electrical resistivity tomography (ERT). ERT uses the injection of electrical currents and the measurement of the resulting voltages to obtain a spatial distribution of the electrical conductivity, which is related, among other things, to volumetric moisture content and ionic strength of the pore water. Although ERT is an established tool for qualitative visualization of hydrogeological processes in the subsurface, its quantitative application is relatively new and constitutes an active area of research. The main aim of this study is to explore the quantitative characterization of solute transport processes in porous media in the laboratory using ERT. For this purpose a flexible, high-speed, and modular ERT measurement system was developed in collaboration with the Electronic and Mechanical Support Division. The new system can perform measurements with a much higher temporal resolution than commercially available field equipment. The ERT system uses a pulsed direct current source and eight channels for simultaneous voltage measurement, and can be connected to a total of 128 electrodes. An error analysis for the ERT system shows that the measurement noise of a transfer resistance measurement (the ratio of injected current and measured voltage) in the used laboratory setup is described by a Gaussian probability distribution with e ? N(e ?,se ). The standard deviation of the measurement errors (se ) can be estimated from repeatability measurements, while the mean (e ?, representing systematic errors) can be estimated from reciprocity measurements. The ERT setup (ERT measurement system, electrodes, and experimental tank) has been used to perform a set of relatively simple, well-defined, static experiments. For these experiments the experimental tank was filled with an aqueous solution into which a solid plastic cylinder was placed. The collected ERT measurements have been used in uncoupled as well as coupled inverse approaches to estimate parameters such as the location and radius of the plastic cylinder. The statistical inversion algorithm DREAM(ZS), based on the Markov Chain Monte Carlo method, was used to estimate the model parameters. The reconstructed electrical conductivity images required in the uncoupled inversion were obtained using an algorithm based on Occam’s inversion. The model parameters estimated with the uncoupled inverse approach are corrupted due to the regularization bias introduced into the reconstructed electrical conductivity image. This bias particularly affects the estimates of the plastic cylinder’s electrical conductivity and radius. The poor performance of the uncoupled inverse approach is mainly caused by the use of a smoothness prior in the image reconstruction. Obviously, such a prior is not in agreement with the sharp conductivity contrast between the plastic cylinder and the aqueous solution. Conversely, the model parameters estimated in the coupled inverse approach are in close agreement with the measured values. The residual between the measured and simulated transfer resistances in the coupled inversion suggest that the model errors are larger than the measurement noise. The model errors are mainly attributed to errors in electrode position or shape and errors in the shape of the experimental tank. Even though the model errors are statistically significant, the total data errors are too small to significantly affect the estimated parameters values. The results show that when accurate forward models are used in a coupled inverse approach, ERT measurements can provide accurate and precise parameter estimates. Subsequently, the feasibility of ERT to quantitatively characterize solute transport processes in our laboratory setup was explored. For this purpose, a straightforward solute transport experiment was performed, consisting of a series of three single-step tracer injections into a saturated homogeneous sand column. The use of ERT to quantify processes in porous media introduces additional uncertainty since a petrophysical relationship is required to relate the bulk electrical conductivity modelled with ERT to the properties of the porous medium. In addition, the solute transport model is subject to uncertainty in porous medium parameters as well as petrophysical parameters, uncertainty in boundary and initial conditions, and model structural errors (e.g. caused by assuming a homogeneous porous medium while in reality the medium is heterogeneous). The reconstructed electrical conductivity images for the tracer injection experiments clearly were affected by the spatially variable resolution of the smoothness-constrained image reconstruction as well as by inversion artefacts. The applied smoothing primarily caused overestimation of the dispersion of the tracer front. The reconstructed electrical conductivities could be improved by the use of a process-based prior which includes specific information about the solute transport process in the regularized inversion. However, the success of this prior is dependent on the accuracy of the solute transport model and petrophysical relationship used to generate the set of feasible electrical conductivity models. The ERT measurements collected during the tracer injections were also used to estimate the parameters of a one-dimensional solute transport model in an uncoupled as well as a coupled inverse approach. In both inverse approaches, the solute transport parameters could be estimated to a high precision. Moreover, the estimated values were physically realistic and agreed relatively well with the expected values. Surprisingly, the results obtained in the uncoupled and coupled inversions were comparable, despite the fact that the reconstructed electrical conductivities were clearly affected by regularization. An explanation for this observation was found in the variable sizes of the elements used in the ERT mesh. The smaller elements near the electrodes, where ERT spatial resolution was high, relatively contributed more to the objective function in the uncoupled inversion than the larger elements towards the centre of the domain, where ERT spatial resolution was low. As a result, the uncoupled inversion was biased towards areas with good data quality. Although the solute transport parameters estimated with the coupled inversion are physically realistic and agree relatively well with the expected values, the (mis)fit between the observed and simulated transfer resistances suggests that significant model errors in the solute transport and/or petrophysical model must have been present. These model errors likely are the result of heterogeneities in the solute transport caused by small-scale preferential flow (cm or less). Possible causes for small-scale preferential flow are unsaturated conditions in the sand column, the periodic invasive sampling of water at the sampling ports, or non-uniform tracer injection at the sand column’s bottom boundary. Overall, the results presented in this thesis show that ERT can be used to quantitatively characterize a solute transport process in a laboratory sand column, given that a coupled inverse framework is used and the forward models are accurate enough representations of reality. In general, the success of quantitative characterization using ERT measurements is highly dependent on the information available in addition to the ERT measurements, such as information about the dominant flow and transport processes, porous medium properties, heterogeneities, and initial and boundary conditions. When little or no information is available, ERT is best used in a standard image reconstruction using a smoothness prior or other general prior. Although the resulting images will only provide qualitative information, this information could still be beneficial for the construction of an appropriate hydrogeological model. Once a hydrogeological model is constructed, its unknown parameters could be estimated using the ERT measurements in a coupled inverse approach. In a controlled laboratory experiment additional information is readily available, which increases the feasibility of ERT for quantitative characterization. Additional information may come from imposed boundary and initial conditions and the experimental design, as well as from independent measurements of the soil’s properties (e.g., porosity, water content) and petrophysical parameters. Alternatively, additional information may come from other geophysical datatypes as well as hydrological measurements. Since the success of quantitative characterization of hydrogeological processes using ERT is highly dependent on the information available in addition to the ERT measurements, future research should focus on the integration of multiple types of geophysical data (e.g., electrical resistivity tomography, ground-penetrating radar, induced potential, self potential, electromagnetics, time-domain reflectometry) and local hydrological data (e.g., concentration, hydraulic head, flowrates).Geoscience & EngineeringCivil Engineering and Geoscience
Flow patterns around longitudinal training dams
No full textWith the intention to reduce the negative effects of ongoing bed erosion, as well as to improve several other river functions such as protection against floods, provision of safe and efficient navigation and ecology, a ‘pilot project longitudinal training dams’ was initiated. The training dams have recently been implemented in the Waal between Tiel and Sind Andries. In this project, river groynes have been completely removed and replaced by dams that lie parallel to the river bank. With help of the longitudinal training dams, a two-channel river system is created in which the river is divided into a main and side channel. The dams are placed in a continuous manner with openings in between that are relatively small compared to the dam length. At the beginning and end of the dam an inlet and outlet region is situated, as shown in Fig. 1. The combination of inlet and openings allows for water and sediment to be divided between the main and the side channel. Both inlet and openings are constructed with the help of a porous rock-layer. The crest heights can be altered by adding or removing stones. This is expected to influence the amount of water and sediment entering the side channel and can therefore be used as a regulation tool. A.J.F. Hoitink, T.V. de Ruijsscher, T.J. Geertsema, B. Makaske, J. Wallinga, J.H.J. Candel, J. Poelman (Eds.) NCR days 2017, Febr. 1-3, 2017. Book of abstracts, NCR publication 41-2017.Rivers, Ports, Waterways and Dredging EngineeringHydraulic Structures and Flood RiskEnvironmental Fluid Mechanic
Mixtures of g-priors for Bayesian model averaging with economic applications
No full textWe examine the issue of variable selection in linear regression
modeling, where we have a potentially large amount of possible covariates
and economic theory offers insufficient guidance on how to select the ap-
propriate subset. Bayesian Model Averaging presents a formal Bayesian
solution to dealing with model uncertainty. Our main interest here is the
effect of the prior on the results, such as posterior inclusion probabilities
of regressors and predictive performance. We combine a Binomial-Beta
prior on model size with a g-prior on the coefficients of each model. In
addition, we assign a hyperprior to g, as the choice of g has been found
to have a large impact on the results. For the prior on g, we examine
the Zellner-Siow prior and a class of Beta shrinkage priors, which covers
most choices in the recent literature. We propose a benchmark Beta prior,
inspired by earlier findings with fixed g, and show it leads to consistent
model selection. Inference is conducted through a Markov chain Monte
Carlo sampler over model space and g. We examine the performance of the
various priors in the context of simulated and real data. For the latter, we
consider two important applications in economics, namely cross-country
growth regression and returns to schooling. Recommendations to applied
users are provided
Mixtures of g-priors for Bayesian Model Averaging with economic application
No full textThis paper examines the issue of variable selection in linear regression modeling, where there is a potentially large amount of possible covariates and economic theory offers insufficient guidance on how to select the appropriate subset. In this context, Bayesian Model Averaging presents a formal Bayesian solution to dealing with model uncertainty. The main interest here is the effect of the prior on the results, such as posterior inclusion probabilities of regressors and predictive performance. The authors combine a Binomial-Beta prior on model size with a g-prior on the coefficients of each model. In addition, they assign a hyperprior to g, as the choice of g has been found to have a large impact on the results. For the prior on g, they examine the Zellner-Siow prior and a class of Beta shrinkage priors, which covers most choices in the recent literature. The authors propose a benchmark Beta prior, inspired by earlier findings with fixed g, and show it leads to consistent model selection. Inference is conducted through a Markov chain Monte Carlo sampler over model space and g. The authors examine the performance of the various priors in the context of simulated and real data. For the latter, they consider two important applications in economics, namely cross-country growth regression and returns to schooling. Recommendations for applied users are provided.Educational Technology and Distance Education,Arts&Music,Geographical Information Systems,Information Security&Privacy,Statistical&Mathematical Sciences
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