Zugl.: Bremen, Universiẗat, Diss., 2006.

Thesis (Ph.D.)--Cornell University, 2002. / Adviser: Eva Tardos. Includes bibliographical references.

Thesis (M.S.)--Baylor University, 2006. / Includes bibliographical references (p. 50-52).

Universiẗat, Diss., 2005--St. Gallen.

Today's product managers must quickly determine viable avenues for innovation while carefully balancing the costs and benefits involved. Agile methodologies are highly incremental and often seen as lacking in rigour and due diligence. This thesis explores the relationship between processes and tools that are commonplace for product managers versus those that tend to be reserved for researchers. A case study reveals key opportunities for the practices in each domain to inform each other, and further identifies the need for gaps in the tooling to be addressed. The study uses Think Together, a collaborative mobile application for interactive presentations with rich media content. The application supports individual action layers for each user and session replay, creating several challenging bottlenecks that jeopardize the scalability of the original implementation. A proposal for an alternative network configuration for communication to address these bottlenecks is examined from both a product management viewpoint and from a more traditional research perspective. A simulator is used as a means to analyze and evaluate the proposed configuration, revealing essential trade-o s in terms of efficiency and productivity. Unlike testing on real devices, the simulator is much more in line with agile processes, enabling more power and flexibility without the limitations of physical resources. However, the extent to which simulated results are practical in the real world, in particular to product managers, is an open question. We demonstrate how a lifecycle involving both traditional approaches to research and incremental implementation strategies in agile environments complements each other, and further identify current obstacles involved. / Graduate

Pollination networks summarize interactions between plants and pollinators, providing insight into ecosystem stability. An unplanned fire provided the opportunity to assess network structure following disturbance in the Tall Grass Prairie Preserve in southern Manitoba. I established transects in sites burned <1 year, 5-6 years, or 10+ years ago. I assessed species richness, diversity, abundance, and phenology of insects and flowering plants. I created interaction matrices by recording plant-insect interactions, and sampled pollen loads from insects. Network structure was assessed by connectance, nestedness, and interaction strength. Flowers were more abundant and bloomed two weeks earlier in newly burned sites in 2010. Bees showed responses to fire based on nesting habitat, however visits by syrphids were related to precipitation. Network structure showed that tall grass prairie pollination networks were resilient to disturbance and variable environmental conditions, and management of prairie by fire did not negatively impact plant-pollinator interactions within the community overall. / February 2016

The ability to probe many-particle systems on a microscopic level has revolutionized the way we do statistical physics. As computational capabilities continue to grow exponentially, larger and more complex systems come within reach of microscopic analysis. In the field of network growth, the classical model has given way to competitive processes, in which networks are guided by some criteria at every step of their formation. We develop and analyze a new competitive growth process that permits intervention on growing networks using only local properties of the network when evaluating how to add new connections. We establish the critical behavior of this new method and explore potential uses in guiding the development of real-world networks. The classical system of electrons diffusing within a conductor similarly permits a microscopic analysis where, to date, studies of the macroscopic properties have dominated the literature. In order to extend our understanding of the theory that governs this diffusion—the fluctuation-dissipation theorem—we construct a physical model of the Johnson-Nyquist system of electrons embedded in the bulk of a conductor. Constructing the model involves deriving how the motion of each individual electron comes about via scattering processes in the conductor, then connecting this collective motion to the macroscopic observables of voltage and current that define Johnson-Nyquist noise. Once the equilibrium properties have been fully realized, an external perturbation can be applied in order to probe the behavior of the model as it deviates away from equilibrium. In much the same way that competitive network growth revolutionized classical network theory, we aim to establish a model which can guide future research into nonequilibrium fluctuation-dissipation by providing a method for interacting with the system in a precise and well-controlled manner as it evolves over time. This model is presented in its present form in Chapter 3. Chapter 2, which covers this work, has been published in Physical Review E as a Rapid Communication [1]. The writing and analysis were performed by me as the primary author. Eric Corwin and Georgios Tsekenis are listed as co-authors for their contribution to the analysis and for advisement on the work. This dissertation includes previously published and unpublished co-authored material.

Network analysis techniques have been used for planning purposes in the construction industry for over a decade. They have been used with various degrees of success by the client to control the progress of his job; by the architect (or consultant) to plan the design phase of the project; and finally by the contractor to prepare his pre-tender and contract programmes. This study is concerned about the factors which contribute to higher success in the use of network analysis techniques in contracting organizations.

This dissertation is concerned with the management and performance issues of those register-insertion (R-I) ring type local area networks (LANs) which employ the message removal by destination node protocol. A typical example of such a network is the Distributed Loop Computer Network (DLCN). developed by Liu et al for fundamental research in the field of distributed computing. After considering the management issues of low cost R-J LANs. the research deals with performance analysis of the dynamically reconfigurable register-insertion (DRR) network. In the first part of this research. a set of management functions is identified which are desirable and can be provided economically by a low cost LAN. A unique feature of the DLCN is that messages are removed from the network by the destination node. that is. messages do not travel whole of the loop. Therefore. it is not possible for a special control node to monitor the data traffic on the network without providing support functionality in each network access unit (NAU). The minimum functionality which must be provided in each NAU is identified in the thesis. A skeleton network was implemented to verify the feasibility of the proposed scheme. A paper describing the findings of this research was published and is reproduced as appendix A. In the second part of this research. a new feature of the DLCN network is introduced. namely. that the performance of a network employing removal by destination protocol can be improved by reconfiguring the network in a particular way. A methodology to find the optimal configuration is developed and is shown. by worked examples. to lead to improved performance. The findings of this research are particularly applicable to the dynamically reconfigurable register-insertion (DRR) network. A paper dealing with the optimisation of a hypothetical fully connected DRR network has been accepted for publication. Another paper. which considers the general case of less than fully connected DRR networks. is to be published. Both papers are reproduced as append ices Band C. Finally. a performance study of the ORR network is undertaken. As there seems to be no published attempt at formal analysis or simulation of a ORR network. a survey of literature dealing with performance study of the basic OLeN is performed. A simulation model of the DRR was then developed and implemented to verify the results arrived at in the previous section. Later. a queueing model of the DRR network. based on the work of Bux and Schlatter [7] is developed and analysed. Both simulation and analysis support the claim that the performance of a DRR network can be improved by adopting the configuration strategy developed in this thesis.

In this study a dynamic assignment model is developed which estimates travellers' route and departure time choices and the resulting time varying traffic patterns during the morning peak. The distinctive feature of the model is that it does not restrict the geometry of the network to specific forms. The proposed framework of analysis consists of a travel time model, a demand model and a demand adjustment mechanism. Two travel time models are proposed. The first is based on elementary relationships from traffic flow theory and provides the framework for a macroscopic simulation model which calculates the time varying flow patterns and link travel times given the time dependent departure rate distributions; the second is based on queueing theory and models roads as bottlenecks through which traffic flow is either uncongested or fixed at a capacity independent of traffic density. The demand model is based on the utility maximisation decision rule and defines the time dependent departure rates associated with each reasonable route connecting, the O-D pairs of the network, given the total utility associated with each combination of departure time and route. Travellers' choices are assumed to result from the trade-off between travel time and schedule delay and each individual is assumed to first choose a departure time t, and then select a reasonable route, conditional on the choice of t. The demand model has therefore the form of a nested logit. The demand adjustment mechanism is derived from a Markovian model, and describes the day-to-day evolution of the departure rate distributions. Travellers are assumed to modify their trip choice decisions based on the information they acquire from recent trips. The demand adjustment mechanism is used in order to find the equilibrium state of the system, defined as the state at which travellers believe that they cannot increase their utility of travel by unilaterally changing route or departure time. The model outputs exhibit the characteristics of real world traffic patterns observed during the peak, i. e., time varying flow patterns and travel times which result from time varying departure rates from the origins. It is shown that increasing the work start time flexibility results in a spread of the departure rate distributions over a longer period and therefore reduces the level of congestion in the network. Furthermore, it was shown that increasing the total demand using the road network results in higher levels of congestion and that travellers tend to depart earlier in an attempt to compensate for the increase in travel times. Moreover, experiments using the queueing theory based travel time model have shown that increasing the capacity of a bottleneck may cause congestion to develop downstream, which in turn may result in an increase of the average travel time for certain O-D pairs. The dynamic assignment model is also applied to estimate the effects that different road pricing policies may have on trip choices and the level of congestion; the model is used to demonstrate the development of the shifting peak phenomenon. Furthermore, the effect of information availability on the traffic patterns is investigated through a number of experiments using the developed dynamic assignment model and assuming that guided drivers form a class of users characterised by lower variability of preferences with respect to route choice.