International Telemetering Conference Proceedings / October 22-25, 2001 / Riviera Hotel and Convention Center, Las Vegas, Nevada / The Range Instrumentation and Control System (RICS) is a network of personal computers (PCs), routers, and switches designed to transport time-space-position information (TSPI) and/or other data between multiple Test Sites and data reduction facilities. The typical use of RICS will be the transport of TSPI data from a System Under Test (SUT) to a Focus Site for real-time display and post-mission analysis of the data. This capability will be expanded to include the transport of telemetry (TM), video, and communications data via the RICS. This paper will discuss the overall hardware design of the RICS. It will further describe the programmatic issues encountered during the implementation phase of the RICS project. The paper will describe the initial design criteria, the selection of hardware to implement the design, problems encountered with the implementation of the hardware, solutions and workarounds to the problems encountered, and lessons learned during the entire process.

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published_or_final_version / abstract / Statistics and Actuarial Science / Doctoral / Doctor of Philosophy

A prime coat is defined as a low-viscosity bituminous material such as cutback, asphalt emulsions, or polymer-based chemicals applied onto the surface of road bases in order to protect the base from the penetration of moisture into the base layer. Other functions of prime coat include (1) providing good adhesion between a granular base and the bituminous surface, (2) strengthening the surface of the base by binding the fine particles, and (3) sealing against any voids along the base surface in order to reduce water absorption. To achieve these functions, a prime coat should successfully penetrate the granular base and should cure fully. In this study, field-curing data on selected prime coats was collected during March 12th-18th, 2014 and April 12th-18th, 2014. Oven-curing data was also collected in a laboratory using an adjustable oven. Identical prime coats including the four most commonly used prime coats by TxDOT ((1) Cutback MC-30, (2) asphalt emulsions and cutback mixture AEP, (3) polymer emulsions EC-30 and (4) asphalt emulsions SS-1H and CSS-1H) and base materials were divided into the two types of testing environments, one field-cured, and one in an accelerated and controlled indoor, oven-curing environment. Once the specimens were fully cured, evaluation of the engineering properties of the specimens were carried out in order to determine if oven-cured specimens can be expected to exhibit the same engineering characteristics as the field-cured specimens. Evaluation of water absorption tests, indirect indicator of relative strength, and penetration tests were performed on all specimens for both field-cured and oven-cured specimens. Importantly, a comparison of these results shows the viability of using accelerated, laboratory curing procedures. Prime coat field-testing procedures will be suggested using oven-curing rather than field-curing, reducing the amount of time required for sample preparation. Prime coat testing could conceivably be completed in a single day due to the accelerated curing rates. This advantage would reduce cost and man-hours of new prime coat material testing. / text

<p> The goal of this thesis is to study the economics of computational learning. Attention is also paid to applications of computational learning models, especially Valiant's so-called `probably approximately correctly' (PAC) learning model, in econometric situations.</p><p>Specifically, an economically reasonable stopping time model of learning is the subject of two attached papers. In the rst paper, Paper A, the economics of PAC learning are considered. It is shown how a general form of the optimal stopping time bounds can be achieved using the PAC convergence rates for a `pessimistic-rational' learner in the most standard binary case of passive supervised PAC model of finite Vapnik-Chervonenkis (VC) dimension.</p><p> </p><p>The second paper, Paper B, states precisely and improves the ideas introduced in Paper A and tests them in a specific and mathematically simple case. Using the maxmin procedure of Gilboa and Schmeidler the bounds for the stopping time are expressed in terms of the largest expected error of recall, and thus, effectively, in terms of the least expected reward. The problem of locating a real number θ by testing whether x_i ≤ θ , with x_i drawn from an calculated for a range of term rates, sample costs and rewards/penalties from a recall ae included. The standard econometric situations, such as product promotion, market research, credit risk assessment, and bargaining and tenders, where such bounds could be of interest, are pointed. </p><p>These two papers are the essence of this thesis, and form it togheter with an introduction to the subject of learning.</p> / <p>Målet med denna avhandling är att studera optimering av inlärning när det finns kostnader. Speciellt studerar jag Valiants så kallade PAC-inlärningsmodell  (Probably Approximately Correctly), ofta använd inom datavetenskap. I två artiklar behandlar jag hur länge, ur ekonomisk synvinkel, inlärningsperioden bör fortsätta.</p><p>I den första artikeln visar vi hur en generell form av begränsningar av den optimala inlärningsperioden kan fås med hjälp av PAC-konvergenshastigheten för en ’pessimistiskt rationell’ studerande (i det vanligaste binära fallet av passiv PAC-inlärningsmodell med ändlig VC-dimension).</p><p>I den andra artikeln fördjupar och förbättrar vi idéerna från den första artikeln, och testar dem i en specifik situation som är matematiskt enkel. Med hjälp av Gilboa – Schmeidlers max - minprocedur  uttrycker vi begränsningarna av den optimala inlärningsperioden som funktion av det största förväntade felet och därmed som funktion av den minsta förväntade belöningen. Vi diskuterar problemet med att hitta ett reellt tal θ genom testning av huruvida x_i ≤ θ, där x_i dras från en okänd fördelning. Här tar vi också upp exempel på begränsningar av inlärningsperioden, beräknade för en mängd av diskontovärden, stickprovskostnader och belöning/straff för erinran, samt en del vanliga ekonometriska situationer där sådana begränsningar är av intresse, såsom marknadsföring av produkter, marknadsanalys, kreditriskskattning och offertförhandling.</p><p>Avhandlingen består i huvuddel av dessa två artiklar samt en kort introduktion till ekonomiska, matematiska och datavetenskapliga inlärningsmodeller.</p><p> </p>

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