The evolution of human beings is marked by adaptation. The ability to adapt to and manipulate our environment is one definer of intelligence, and ours is unique among life on Earth. Since moving off of the African Continent, humans have migrated to inhabit every part of the Earth. Human existence and perpetuity in the universe depends upon the success of this adaptation, and inevitably, migrating off of this planet. The technological advances being developed today will change our way of life, and enable people to travel to and live permanently on the Moon and Mars. This study involves the architectural design and construction of a completely programmable permanent Martian settlement in the year 2050. Previous studies and proposals for Martian architecture rely mostly on existing technology. The first people are not expected to reach Mars until 2030, and new and emerging technologies will radically affect the designs being considered today. Technical challenges constrain designers of space architecture today, and scientific developments will solve many of these. This study seeks to explore how new technology can positively affect the architecture of the future, affording more comfortable and livable space on Mars. With a construction date of 2050, this project differs from others by benefitting from the next four decades of profound technological advancement. Leading Futurist Raymond Kurzweil predicts that the technological singularity is within this time frame, and that the 21st Century will, “Witness on the order of 20,000 years of progress (at today’s rate of progress) (Kurzweil, Law of Accelerating Change).” This thesis theorizes that nanotechnology will enable the deployment of a completely self-constructing and programmable permanent Martian settlement designed from a series of spatial modules. The anticipated results include a modular system of architectural spaces, and an increased awareness of the architectural benefits of emerging technologies as they relate to future space architecture.

Blight and the elimination thereof have profoundly impacted urban areas. In Colony Park/Lakeside (Austin, Texas), community leaders and members of the local neighborhood association have come together to mitigate and reverse social, economic, and physical symptoms of blight in their neighborhood. Following the approval of a HUD Community Challenge Planning Grant application that was submitted by the Austin Neighborhood Housing and Community Development (NHCD) department, these individuals utilized the media attention surrounding the grant to campaign for code enforcement, landlord-tenant accountability, policing, and the clean-up of illegal dumping in the area. Moreover, after much ado between residents and City workers, the neighborhood association devised a community-focused partnership with the City to ensure that current residents would reap the benefits of the planning process and help define the collective will and interests of the community. Utilizing publicly available data and first-hand knowledge from one City code compliance investigator and local residents, this report attempts to provide a blight indicator analysis of the Colony Park/Lakeside planning area as defined by NHCD. In other words, this report uses quantitative data to create descriptive maps of current neighborhood conditions with particular attention to code violations and community discussions surrounding them. The results of this work are intended to shed light on where resources should be directed to further research in the area and to resolve issues that threaten the health, safety, and viability of the neighborhood today. / text

published_or_final_version / Comparative Literature / Doctoral / Doctor of Philosophy

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Vehicular Ad hoc Networks (VANET) exhibit highly dynamic behavior with high mobility and random network topologies. The performance of Transmission Control Protocols in such wireless ad hoc networks is plagued by a number of problems: frequent link failures, scalability, multi-hop data transmission and data loss. To address these VANET routing issues, I have used the ideas from swarm intelligence. The Ant Colony Optimization (ACO), which is a branch of swarm intelligence, is the main source of my inspiration. I have designed an ant-based routing algorithm which addresses routing issues prevalent in VANETs: adaptivity, robustness and scalability. One attractive feature of ACO is that they provide multiple routes from source to destination, resulting in more robust network. In this work, together with ACO, I have used the ideas from zone routing protocols to develop my algorithm: Mobility Aware Zone based Ant Colony Optimization Routing for VANET that exhibits locality and scalability.

Network resiliency pertains to the vulnerability of telecommunication networks in the case of failures and malicious attacks. With the increasing capacity catering of network for the booming multi-services in Next Generation Networks (NGNs), reducing recovery time and improving capacity efficiency while providing high quality and resiliency of services has become increasingly important for the future network development. Providing network resiliency means to rapidly and accurately reroute the traffic via diversely routed spare capacity in the network when a failure takes down links or nodes in the working path. Planning and optimization for NGNs require an efficient algorithm for spare capacity allocation (SCA) that assures restorability with a minimum of total capacity. This dissertation aims to understand and advance the state of knowledge on spare capacity allocation in network resiliency for telecommunication core networks. Optimal network resiliency design for restorability requires considering: network topology, working and protection paths routing and spare capacity allocation. Restorable networks should be highly efficient in terms of total capacity required for restorability and be able to support any target level of restorability. The SCA strategy is to decide how much spare capacity should be reserved on links and to pre-plan protection paths to protect traffic from a set of failures. This optimal capacity allocation problem for survivable routing is known as NP-complete. To expose the problem structure, we propose a model of the SCA problem using a matrix-based framework, named Distributed Resilience Matrix (DRM) to identify the dependencies between the working and protection capacities associated with each pair of links and also to capture the local capacity usage information in a distributed control environment. In addition, we introduce a novel ant-based heuristic algorithm, called Friend-or-Foe Resilient (FoF-R) ant-based routing algorithm to find the optimal protection cycle (i.e., two node-disjoint paths between a source-destination node pair) and explore the sharing ability among protection paths using a capacity headroom-dependent attraction and repulsion function. Simulation results based on the OMNeT++ and AMPL/CPLEX tools show that the FoF-R scheme with the DRM structure is a promising approach to solving the SCA problem for survivable routing and it gives a good trade off between solution optimality and computation speed. Furthermore, for the SCA studies of survivable networks, it is also important to be able to differentiate between network topologies by means of a robust numerical measure that indicates the level of immunity of these topologies to failures of their nodes and links. Ideally, such a measure should be sensitive to the existence of nodes or links, which are more important than others, for example, if their failure causes the network’s disintegration. Another contribution in this dissertation is to introduce an algebraic connectivity metric, adopted from the spectral graph theory, namely the 2nd smallest eigenvalue of the Laplacian matrix of the network topology, instead of the average nodal degree, to characterize network robustness in studies of the SCA problem. Extensive simulation studies confirm that this metric is a more informative parameter than the average nodal degree for characterizing network topologies in network resiliency studies.

This thesis presents an application of the Ant Colony algorithm for optimizing filter placement and sizing on a radial distribution system to reduce power losses and keep the effective harmonic voltage values and the total harmonic distortion (THD) within prescribed limits. First, a harmonic load flow (HLF) algorithm is performed to demonstrate the effect of harmonic sources on total power loss. Then the Ant Colony algorithm is used in conjunction with HLF to place a selection of filter sizes available at each possible location so that both power loss and THD are minimized. As a result the optimal adjustment of location and size of the filter are determined. Results of computational experiments on standard test systems are presented to demonstrate improvement and effectiveness of using the filters at the optimal location. The methodology used can be easily extended to different distribution network configurations. / Master Thesis