Governing network evolution in the quest for identity

This paper provides a managerial account of network governance by exploring how initially non-powerful agents, driven by the quest for distinctive identity, shape the governance of their networks over time. The research design is that of a longitudinal comparative case study of the trajectories of three renowned, Oscar-winning Spanish filmmakers. It scrutinizes data coming from original interviews, as well as from multiple secondary data sources, in order to illustrate the propositions advanced. The paper's contribution is sought: 1) in proposing a micro-level framework for systematic thinking about network governance evolution, distinguishing four dimensions (co-governance, structure, strategy, and pace) and their respective sub-categories; 2) in advancing three peculiar identity profiles with different implications for the evolution of network governance (i.e., a maverick, an integrated professional, and a broker); 3) in bringing together two bodies of literature that have not conversed frequently (i.e., network governance and identity) in a largely overlooked cultural and historical context, that of Spain after the transition to democracy in 1975.Network governance; Management

Use of soft computing and numerical analysis in design, analysis and management of pavement systems

There are a number of components of pavement engineering, including pavement management, pavement analysis and design, and pavement materials. Historically, the field of pavement management has been interested in monitoring post-construction condition, timing of preventive maintenance and rehabilitation treatments, and economic analysis of alternatives. On the other hand, the field of pavement analysis and design has dealt with optimizing pavement structure; with optimum structure, a pavement system is expected to survive during its service life for given traffic and climate conditions. The performance of pavement materials has been improved to achieve the long-lasting and lower-maintenance pavement systems. A data-driven comprehensive approach considering all aspects of pavement engineering together could be a future direction for advancing pavement engineering practices. In order to achieve a data-driven comprehensive approach considering all aspects of pavement engineering together as outlined above, a data-driven and efficient pavement design, analysis and management concept has been proposed in this study. To serve as elements of this concept, several models related to pavement structural response models, pavement performance prediction models, and pavement remaining service life (RSL) models have been developed. First, to enable faster three-dimensional finite element (3D-FE) computations of design stresses, artificial neural network (ANN)-based surrogate computational pavement structural response models were developed. These models produce an estimate of the top-down bending stress close to that computed by 3D-FE analysis in rigid airport pavements in a fraction of the time. Second, longitudinal cracking mechanisms of widened jointed plain concrete pavements (JPCP) were demonstrated and their longitudinal cracking potential was evaluated using numerical analysis. Third, the Federal Aviation Administration’s (FAA) current rigid airfield pavement design methodology has been evaluated in great detail to better identify research gaps and remaining needs with respect to cracking failure models so that recommendations could be made as to how current methodology could be improved to accommodate top-down and bottom-up cracking failure modes. Fourth, a detailed step-by-step methodology for the development of a framework for pavement performance and RSL prediction models was explained using real pavement performance data obtained from the Iowa Department of Transportation (DOT)’s Pavement Management Information System (PMIS) database

Causal Inference Using Variation In Treatment Over Time

This thesis and related research is motivated by my interest in understanding the use of time-varying treatments in causal inference from complex longitudinal data, which play a prominent role in public health, economics, and epidemiology, as well as in biological and medical sciences. Longitudinal data allow the direct study of temporal changes within individuals and across populations, therefore give us the edge to utilize time this important factor to explore causal relationships than static data. There are also a variety challenges that arise in analyzing longitudinal data. By the very nature of repeated measurements, longitudinal data are multivariate in various dimensions and have completed random-error structures, which make many conventional causal assumptions and related statistical methods are not directly applicable. Therefore, new methodologies, most likely data-driven, are always encouraged and sometimes necessary in longitudinal causal inference, as will be seen throughout this thesis As a result of the various topics explored, this thesis is split into four parts corresponding to three dierent patterns of variation in treatment. The rst pattern is the one-directional change of a binary treatment assignment, meaning that each study participant is only allowed to experience the change from untreated to treated at the staggered time. Such pattern is observed in a novel cluster-randomized design called the stepped-wedge. The second pattern is the arbitrary switching of a binary treatment caused by changes in person-specic characteristics and general time trend. The patterns is the most common thing one would observe in longitudinal data and we develop a method utilizing trends in treatment to account for unmeasured confounding. The third pattern is that the underlying treatment, outcome, covariates are time-continuous, yet are only observed at discrete time points. Instead of modeling cross-sectional and pooled longitudinal data, we take a mechanistic view by modeling reactions among variables using stochastic dierential equations and investigate whether it is possible to draw sensible causal conclusions from discrete measurements

User Participation in Infrastructuring: Exploring the Space for Action

This paper addresses the concept of participation in the context of design and transformation of a health information infrastructure. Recent work on transformation of health information infrastructures shows that bottom-up user-driven processes are preferred, however, the role of the user in infrastructuring remains under-researched. We investigate user representatives\u27 space for participation in design of an infrastructure, based on the Scandinavian tradition of Participatory Design. We take a user perspective to infrastructuring, investigating the work of user representatives (health workers) who engage in technology design, requiring engagement with local practices in shaping data practices. We have conducted a longitudinal case study on the design and development of a data platform for patient handover in a large Norwegian municipality. We contribute with an understanding of participation in the transformation of infrastructures as user representatives engage local organizations as both facilitators for their own design process, i.e. designers preparing and transforming their local services, as well as participants into design of the infrastructure, i.e. designers shaping technology. We contribute to literature on infrastructuring by showing how user representatives explore possbilities for action, shaping the infrastructuring process

The influence of piezoceramic stack location on nonlinear behavior of langevin transducers

Power ultrasonic applications such as cutting, welding, and sonochemistry often use Langevin transducers to generate power ultrasound. Traditionally, it has been proposed that the piezoceramic stack of a Langevin transducer should be located in the nodal plane of the longitudinal mode of vibration, ensuring that the piezoceramic elements are positioned under a uniform stress during transducer operation, maximizing element efficiency and minimizing piezoceramic aging. However, this general design rule is often partially broken during the design phase if features such as a support flange or multiple piezoceramic stacks are incorporated into the transducer architecture. Meanwhile, it has also been well documented in the literature that power ultrasonic devices driven at high excitation levels exhibit nonlinear behaviors similar to those observed in Duffing-type systems, such as resonant frequency shifts, the jump phenomenon, and hysteretic regions. This study investigates three Langevin transducers with different piezoceramic stack locations by characterizing their linear and nonlinear vibrational responses to understand how the stack location influences nonlinear behavior

The influence of urban form on car travel following residential relocation : a current and retrospective study in Scottish urban areas

Spatial planning and spatial policy continues to be used as a tool to bring about changes in travel behaviour. Policy suggests that by creating particular urban forms, demand for travel by car can be reduced. This paper uses data collected in 2006 from 280 households in Glasgow and Edinburgh to analyse the relationships between urban form and vehicle miles driven, with an emphasis on those who had recently relocated. Population densities, housing type, distance to urban centre and measures of mix were collected for the current residential location and previous, for those who had relocated in the previous three years. An ordinal regression model of change in urban form showed significant associations with reported change in miles driven, although the effect was small compared with the effects of socio-economic factors and car ownership. While the results give some weight to intensification as a policy to bring about a reduction in average distance driven, there may be an increase in distance driven in the intensified area. Whether or not such intensification can be enacted against a backdrop of preferences towards suburban, car oriented living is contentious. As such, this study calls into question the use of planning policy as a means to reduce car use in Scottish cities

A state-of-the-art review on torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains

© 2019, Levrotto and Bella. All rights reserved. Electric vehicles are the future of private passenger transportation. However, there are still several technological barriers that hinder the large scale adoption of electric vehicles. In particular, their limited autonomy motivates studies on methods for improving the energy efficiency of electric vehicles so as to make them more attractive to the market. This paper provides a concise review on the current state-of-the-art of torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains (FEVIADs). Starting from the operating principles, which include the "control allocation" problem, the peculiarities of each proposed solution are illustrated. All the existing techniques are categorized based on a selection of parameters deemed relevant to provide a comprehensive overview and understanding of the topic. Finally, future concerns and research perspectives for FEVIAD are discussed

The Mechanical Behavior of a 25Cr Super Duplex Stainless Steel at Elevated Temperature

Peer reviewedPostprin

Longitudinal vehicle dynamics : a comparison of physical and data-driven models under large-scale real-world driving conditions

Mathematical models of vehicle dynamics will form essential components of future autonomous vehicles. They may be used within inverse or forward control loops, or within predictive learning systems. Often, nonlinear physical models are used in this context, which, though conceptually simple (especially for decoupled, longitudinal dynamics), may be computationally costly to parameterise and also inaccurate if they omit vehicle-specific dynamics. In this study we sought to determine the relative merits of a commonly used nonlinear physical model of vehicle dynamics versus data-driven models in large-scale real-world driving conditions. To this end, we compared the performance of a standard nonlinear physical model with a linear state-space model and a neural network model. The large-scale experimental data was obtained from two vehicles; a Lancia Delta car and a Jeep Renegade sport utility vehicle. The vehicles were driven on regular, public roads, during normal human driving, across a range of road gradients. Both data-driven models outperformed the physical model. The neural network model performed best for both vehicles; the state-space model performed almost as well as the neural network for the Lancia Delta, but fell short for the Jeep Renegade whose dynamics were more strongly nonlinear. Our results suggest that the linear data-driven model gives a good trade-off in accuracy and simplicity, whilst the neural network model is most accurate and is extensible to more nonlinear operating conditions, and finally that the widely used physical model may not be the best choice for control design

Laser Wire Scanner Compton Scattering Techniques for the Measurement of the Transverse Beam Size of Particle Beams at Future Linear Colliders

This archive summarizes a working paper and conference proceedings related to laser wire scanner development for the Future Linear Collider (FLC) in the years 2001 to 2006. In particular the design, setup and data taking for the laser wire experiments at PETRA II and CT2 are described. The material is focused on the activities undertaken by Royal Holloway University of London (RHUL).Comment: 61 page