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The Philadelphia Public History Truck is a nearly two-year-old mobile museum project which creates interdisciplinary exhibitions about the history of Philadelphia neighborhoods with those who live, work, and play within the places and spaces of the city. Since I founded the project in 2013, I have navigated partnerships with both grassroots organizations and larger institutions and faced a wide-ranging gamut of experiences worthy of examination by public historians concerned with power and production of history as well as practice-based reflexivity. The first half of this thesis documents my key reflections of the first eighteen months of work and serves as a primary source on the project. This paper also places History Truck into a long historiography of both public history and mobility in the United States of America to explain the emergence of what I am calling the New Mobile History, an emerging form of practice in which community members and public historians work together from the onset of project development using ephemerality and movement as a tool for creativity and civic-driven history making. By analyzing oral history interviews with Cynthia Little and Michael Frisch, I argue firstly that Philadelphia was the birthplace of this New Mobile History. Secondly, I posit that for this New Mobile History to continue evolving, public historians must balance digital work and relationship-based process to create exhibitions which directly serve communities of memory. Lastly, I consider one possible future for History Truck, including its transformation from project to nonprofit organization manned by post-M.A. fellows who have the ability to work passionately on city streets and with new media. / History

For many years seat cushions have been investigated for their ability to reduce seating discomfort. The objective of this thesis is to examine air-inflated seat cushions to determine how seating comfort (determined by pressure change rate) is affected by changing various parameters of the cushion. To this end, a mathematical model was built using MatLab and SimuLINK to accurately represent the cushion and its response. Different aspects of the cushion, such as seating area, outlet size, cell height, and material elasticity are varied to determine how they each affect seating comfort. For each parameter three different weights are tested to see how the trends observed per parameter are affected by a person's weight. The results of this study indicate that by changing the base radius, the cell height, the outlet diameter, and the material elasticity of each cell, it is possible to improve seating comfort, as determined by pressure change rate. The study confirms that comfort levels increase with increasing seated area. The study also shows that although increasing the weight of a person decreases the comfort performance of the cushion, not all the trends observed when the cushion parameters are varied remain the same as the person's weight is changed. The trends observed when the cell height and outlet diameter are varied are not affected by the subject weight but all the other trends changed as the subject weight was changed. / Master of Science

I have developed time-varying coefficient models for recurrent event data to evaluate the temporal profiles for recurrence rate and covariate effects. There are three major parts in this dissertation. The first two parts propose a mixed Poisson process model with gamma frailties for single type recurrent events. The third part proposes a Bayesian joint model based on multivariate log-normal frailties for multi-type recurrent events. In the first part, I propose an approach based on penalized B-splines to obtain smooth estimation for both time-varying coefficients and the log baseline intensity. An EM algorithm is developed for parameter estimation. One issue with this approach is that the estimating procedure is conditional on smoothing parameters, which have to be selected by cross-validation or optimizing certain performance criterion. The procedure can be computationally demanding with a large number of time-varying coefficients. To achieve objective estimation of smoothing parameters, I propose a mixed-model representation approach for penalized splines. Spline coefficients are treated as random effects and smoothing parameters are to be estimated as variance components. An EM algorithm embedded with penalized quasi-likelihood approximation is developed to estimate the model parameters. The third part proposes a Bayesian joint model with time-varying coefficients for multi-type recurrent events. Bayesian penalized splines are used to estimate time-varying coefficients and the log baseline intensity. One challenge in Bayesian penalized splines is that the smoothness of a spline fit is considerably sensitive to the subjective choice of hyperparameters. I establish a procedure to objectively determine the hyperparameters through a robust prior specification. A Markov chain Monte Carlo procedure based on Metropolis-adjusted Langevin algorithms is developed to sample from the high-dimensional distribution of spline coefficients. The procedure includes a joint sampling scheme to achieve better convergence and mixing properties. Simulation studies in the second and third part have confirmed satisfactory model performance in estimating time-varying coefficients under different curvature and event rate conditions. The models in the second and third part were applied to data from a commercial truck driver naturalistic driving study. The application results reveal that drivers with 7-hours-or-less sleep prior to a shift have a significantly higher intensity after 8 hours of on-duty driving and that their intensity remains higher after taking a break. In addition, the results also show drivers' self-selection on sleep time, total driving hours in a shift, and breaks. These applications provide crucial insight into the impact of sleep time on driving performance for commercial truck drivers and highlights the on-road safety implications of insufficient sleep and breaks while driving. This dissertation provides flexible and robust tools to evaluate the temporal profile of intensity for recurrent events. / PHD / The overall objective of this dissertation is to develop models to evaluate the time-varying profiles for event occurrences and the time-varying effects of risk factors upon event occurrences. There are three major parts in this dissertation. The first two parts are designed for single event type. They are based on approaches such that the whole model is conditional on a certain kind of tuning parameter. The value of this tuning parameter has to be pre-specified by users and is influential to the model results. Instead of pre-specifying the value, I develop an approach to achieve an objective estimate for the optimal value of tuning parameter and obtain model results simultaneously. The third part proposes a model for multi-type events. One challenge is that the model results are considerably sensitive to the subjective choice of hyperparameters. I establish a procedure to objectively determine the hyperparameters. Simulation studies have confirmed satisfactory model performance in estimating the temporal profiles for both event occurrences and effects of risk factors. The models were applied to data from a commercial truck driver naturalistic driving study. The results reveal that drivers with 7-hours-or-less sleep prior to a shift have a significantly higher intensity after 8 hours of on-duty driving and that their driving risk remains higher after taking a break. In addition, the results also show drivers’ self-selection on sleep time, total driving hours in a shift, and breaks. These applications provide crucial insight into the impact of sleep time on driving performance for commercial truck drivers and highlights the on-road safety implications of insufficient sleep and breaks while driving. This dissertation provides flexible and robust tools to evaluate the temporal profile of both event occurrences and effects of risk factors.

This dissertation integrates the strengths of individual emergent delivery technologies with package characteristics, and rural community needs to meet the demand for equitable, accessible, and inclusive rural delivery that is also cost-effective. To find ways to meet the package delivery service needs in rural areas and to fill research gaps in rural package delivery modeling, this study introduced a novel model known as the Parallel Scheduling Vehicle Routing Problem (PSVRP) in an endeavor to revolutionize package delivery by enhancing its efficiency, accessibility, and cost-effectiveness. The PSVRP represents a state-of-the-art approach to vehicle routing problems, incorporating a diversified fleet of innovative delivery modes. The multi-modal fleet of electric vans, ADVs, drones, and truck-drone systems works in unison to minimize operational costs in various settings. A solution methodology that implemented the Adaptive Large Neighborhood Search (ALNS) algorithm was designed to solve the PSVRP in this research to produce optimal or near-optimal solutions. A variety of scenarios in a rural setting that include different quantities of customers to deliver to and different package weights are tested to evaluate if a multi-modal fleet of electric vans, ADVs, drones, and truck-drone systems can provide cost-effective, low emissions, and efficient rural delivery services from local stores. Different fleet combinations are compared to demonstrate the best combined fleet for rural package delivery. It was found that implementation of electric vans, ADVs, drones, and truck-drone systems does decrease rural package delivery cost, but it does not yet decrease cost enough for the return on investment to be high enough for industry to implement the technology. Additionally, it was found that electric technologies do significantly decrease emissions of package delivery in rural areas. However, without a carbon tax or regulation mandating reduced carbon emissions, it is unlikely that the delivery industry will quickly embrace these new delivery modes. This dissertation not only advances academic understanding and practical applications in vehicle routing problems but also contributes to social equity by researching methods to improve delivery services in underserved rural communities. The PSVRP model could benefit transportation professionals considering technology-enabled rural delivery, developing rural delivery plans, looking for cost-effective rural delivery solutions, implementing a heterogeneous fleet to optimize rural delivery, or planning to reduce rural delivery emissions. It is anticipated that these innovations will spur further research and investment into rural delivery optimization, fostering a more inclusive and accessible package delivery service landscape. / Doctor of Philosophy / This dissertation integrates the strengths of individual emergent delivery technologies with package characteristics, and rural community needs to meet the demand for equitable, accessible, and inclusive rural delivery that is also cost-effective. To find ways to meet the package delivery service needs in rural areas and to fill research gaps in rural package delivery modeling, this study introduced a novel model known as the Parallel Scheduling Vehicle Routing Problem (PSVRP) in an endeavor to revolutionize package delivery by enhancing its efficiency, accessibility, and cost-effectiveness. The PSVRP represents a state-of-the-art approach to vehicle routing problems, incorporating a diversified fleet of innovative delivery modes. The multi-modal fleet of electric vans, ADVs, drones, and truck-drone systems works in unison to minimize operational costs in various settings. A solution methodology that implemented the Adaptive Large Neighborhood Search (ALNS) algorithm was designed to solve the PSVRP in this research to produce optimal or near-optimal solutions. A variety of scenarios in a rural setting that include different quantities of customers to deliver to and different package weights are tested to evaluate if a multi-modal fleet of electric vans, ADVs, drones, and truck-drone systems can provide cost-effective, low emissions, and efficient rural delivery services from local stores. Different fleet combinations are compared to demonstrate the best combined fleet for rural package delivery. It was found that implementation of electric vans, ADVs, drones, and truck-drone systems does decrease rural package delivery cost, but it does not yet decrease cost enough for the return on investment to be high enough for industry to implement the technology. Additionally, it was found that electric technologies do significantly decrease emissions of package delivery in rural areas. However, without a carbon tax or regulation mandating reduced carbon emissions, it is unlikely that the delivery industry will quickly embrace these new delivery modes. This dissertation not only advances academic understanding and practical applications in vehicle routing problems but also contributes to social equity by researching methods to improve delivery services in underserved rural communities. The PSVRP model could benefit transportation professionals considering technology-enabled rural delivery, developing rural delivery plans, looking for cost-effective rural delivery solutions, implementing a heterogeneous fleet to optimize rural delivery, or planning to reduce rural delivery emissions. It is anticipated that these innovations will spur further research and investment into rural delivery optimization, fostering a more inclusive and accessible package delivery service landscape.

Thesis (M. Comm.)--University of South Africa, 2002.

Thesis (M. Comm.)--University of South Africa, 2002.

Approved for public release, distribution is unlimited / The Marine Corps is fielding the MTVR Truck as a replacement for its aging fleet of five-ton cargo trucks. The MTVR is an Acquisition Category II program that was a multi-service Army-Marine Corps program. The purpose of this thesis is to examine the effectiveness of having an Army Product Office execute a Marine Corps Program. The study analyzes the effectiveness of the timing of the program's transition from the Army to the Marine Corps. A detailed literature search, as well as information gathered from attending various IPRs and conducting interviews with program officials and contractors, provided the basis for the in-depth background study presented. Analysis of the data gathered led to a justification for multi-service managed programs, as well as to recommendations on the timing of the MTVR program transition. / Civilian, United States Army

Cette thèse CIFRE est le fruit d’une collaboration entre Renault Trucks et le LMFA dans la perspective d’une évaluation de la pertinence du contrôle actif pour la réduction de traînée de véhicule industriel. Les deux principaux objectifs de ces travaux expérimentaux consistent à l’analyse de l’influence de l’écoulement de soubassement sur la dynamique du sillage et l’étude d’une stratégie de contrôle d’écoulement combinant des volets déflecteurs (positionnés sur les bords supérieurs et latéraux du culot) à des actionneurs de type jets pulsés dans l’optique d’une réduction de la traînée aérodynamique d’un corps non profilé à culot droit. Le développement du sillage pour différentes vitesses de soubassement évoluant de 10% à plus de 80% de la vitesse de l’écoulement infini amont est étudié sur une maquette simplifiée de véhicule poids lourd à l’échelle 1/43e. Des mesures de pression au culot permettent d’identifier quatre classes d’écoulement associées à des structures de sillage différentes mises en évidence par des mesures PIV 2D-3C. Le sillage de la première classe d’écoulement obtenu pour les très faibles vitesses de soubassement ressemble au sillage derrière une marche 3D. Pour des vitesses de soubassement plus élevées, l’écoulement de soubassement décolle au niveau du sol et impacte soit le culot ou soit la couche de cisaillement supérieure favorisant le développement des instabilités de type Kelvin-Helmoltz dans ce dernier cas. Enfin, la dernière classe est caractérisée par un sillage comparable à celui d’un corps d’Ahmed. L’ajout de volets déflecteurs à l’arrière du culot engendre une augmentation de la pression au culot pour l’ensemble des classes d’écoulement. Cette augmentation réside principalement dans l’effet de vectorisation de l’écoulement. Un système de contrôle actif est intégré sur une maquette 1/8e géométriquement identique à celle à l’échelle 1/43e et équipée de volets déflecteurs. Deux angles de volet supérieur sont testés afin d’obtenir en moyenne (i) un écoulement naturel attaché à la paroi du volet et (ii) un écoulement naturel détaché du volet. Par rapport au cas sans contrôle actif, des gains sur la traînée sont obtenus pour une certaine gamme de fréquence d’actionnement uniquement dans le cas (ii). Ces gains sont obtenus suite au recollement de l’écoulement sur le volet. Enfin, la robustesse des gains sur la pression au culot est testée avec succès en mettant la maquette en dérapage pour simuler un vent de travers. / This PhD thesis was realized in the scope of a collaboration with Renault Trucks and the LMFA in view of an evaluation of the relevance of active flow control for the drag reduction industrial vehicle. The two main objectives of this experimental work are to analyze the impact of the underbody flow on the wake dynamics and to study a flow control strategy combining inclined flaps (located on the upper and lateral edges of the rear base) with pulsed jet actuators for reducing the aerodynamic drag of a square-back bluff body. The wake development for several underbody velocities ranging from 10% to more than 80% of the free-stream velocity is studied on a simplified truck model at scale 1 :43. Rear base pressure measurements lead to the identification of four flow classes associated with different wake structures highlighted by 2D-3C PIV measurements. The wake of the first flow class obtained for very low underbody velocities looks like that of the wake of a 3D backward facing step. For higher underbody velocities, the underbody flow is separated from the ground impaging either the rear base or the upper shear layer triggering Kelvin-Helmoltz instabilities for this last case. Finally, the fourth class is characterized by a wake comparable to that of the Ahmed body. The implementation of inclined flaps at the rear base increases the base pressure for all classes. This increase is mainly due to the vectoring effect of the flow. An active control system is integrated to a 1 :8 scale model geometrically identical to that of the 1 :43 scale model with flaps. Two upper flap angles are tested to have (i) a natural flow attached to the flap and (ii) a natural flow detached from the flap. In comparison to the case without active flow control, drag reductions are obtained only for a specific range of actuation frequencies only in case (ii). These gains are associated with the reattachment of the flow on the flap. Finally, the robustness of the pressure gains is successfully tested in crosswind conditions.