FREQUENCY DOMAIN CHARACTERIZATION OF OPTIC FLOW AND VISION-BASED OCELLAR SENSING FOR ROTATIONAL MOTION

The structure of an animal’s eye is determined by the tasks it must perform. While vertebrates rely on their two eyes for all visual functions, insects have evolved a wide range of specialized visual organs to support behaviors such as prey capture, predator evasion, mate pursuit, flight stabilization, and navigation. Compound eyes and ocelli constitute the vision forming and sensing mechanisms of some flying insects. They provide signals useful for flight stabilization and navigation. In contrast to the well-studied compound eye, the ocelli, seen as the second visual system, sense fast luminance changes and allows for fast visual processing. Using a luminance-based sensor that mimics the insect ocelli and a camera-based motion detection system, a frequency-domain characterization of an ocellar sensor and optic flow (due to rotational motion) are analyzed. Inspired by the insect neurons that make use of signals from both vision sensing mechanisms, advantages, disadvantages and complementary properties of ocellar and optic flow estimates are discussed.

Dynamic Resource Allocation in Wireless Heterogeneous Networks

Deployment of low power basestations within cellular networks can potentially increase both capacity and coverage. However, such deployments require efficient resource allocation schemes for managing interference from the low power and macro basestations that are located within each other’s transmission range. In this dissertation, we propose novel and efficient dynamic resource allocation algorithms in the frequency, time and space domains. We show that the proposed algorithms perform better than the current state-of-art resource management algorithms. In the first part of the dissertation, we propose an interference management solution in the frequency domain. We introduce a distributed frequency allocation scheme that shares frequencies between macro and low power pico basestations, and guarantees a minimum average throughput to users. The scheme seeks to minimize the total number of frequencies needed to honor the minimum throughput requirements. We evaluate our scheme using detailed simulations and show that it performs on par with the centralized optimum allocation. Moreover, our proposed scheme outperforms a static frequency reuse scheme and the centralized optimal partitioning between the macro and picos. In the second part of the dissertation, we propose a time domain solution to the interference problem. We consider the problem of maximizing the alpha-fairness utility over heterogeneous wireless networks (HetNets) by jointly optimizing user association, wherein each user is associated to any one transmission point (TP) in the network, and activation fractions of all TPs. Activation fraction of a TP is the fraction of the frame duration for which it is active, and together these fractions influence the interference seen in the network. To address this joint optimization problem which we show is NP-hard, we propose an alternating optimization based approach wherein the activation fractions and the user association are optimized in an alternating manner. The subproblem of determining the optimal activation fractions is solved using a provably convergent auxiliary function method. On the other hand, the subproblem of determining the user association is solved via a simple combinatorial algorithm. Meaningful performance guarantees are derived in either case. Simulation results over a practical HetNet topology reveal the superior performance of the proposed algorithms and underscore the significant benefits of the joint optimization. In the final part of the dissertation, we propose a space domain solution to the interference problem. We consider the problem of maximizing system utility by optimizing over the set of user and TP pairs in each subframe, where each user can be served by multiple TPs. To address this optimization problem which is NP-hard, we propose a solution scheme based on difference of submodular function optimization approach. We evaluate our scheme using detailed simulations and show that it performs on par with a much more computationally demanding difference of convex function optimization scheme. Moreover, the proposed scheme performs within a reasonable percentage of the optimal solution. We further demonstrate the advantage of the proposed scheme by studying its performance with variation in different network topology parameters.

Resilience to Climate Change: An Ethnographic Approach

Global projections for climate change impacts produce a startling picture of the future for low-lying coastal communities. The United States’ Chesapeake Bay region and especially marginalized and rural communities will be severely impacted by sea level rise and other changes over the next one hundred years. The concept of resilience has been theorized as a measure of social-ecological system health and as a unifying framework under which people can work together towards climate change adaptation. But it has also been critiqued for the way in which it does not adequately take into account local perspective and experiences, bringing into question the value of this concept as a tool for local communities. We must be sure that the concerns, weaknesses, and strengths of particular local communities are part of the climate change adaptation, decision-making, and planning process in which communities participate. An example of this type of planning process is the Deal Island Marsh and Community Project (DIMCP), a grant funded initiative to build resilience within marsh ecosystems and communities of the Deal Island Peninsula area of Maryland (USA) to environmental and social impacts from climate change. I argue it is important to have well-developed understandings of vulnerabilities and resiliencies identified by local residents and others to accomplish this type of work. This dissertation explores vulnerability and resilience to climate change using an engaged and ethnographic anthropological perspective. Utilizing participant observation, semi-structured and structured interviews, text analysis, and cultural domain analysis I produce an in-depth perspective of what vulnerability and resilience means to the DIMCP stakeholder network. Findings highlight significant vulnerabilities and resiliencies inherent in the local area and how these interface with additional vulnerabilities and resiliencies seen from a nonlocal perspective. I conclude that vulnerability and resilience are highly dynamic and context-specific for the local community. Vulnerabilities relate to climate change and other social and environmental changes. Resilience is a long-standing way of life, not a new concept related specifically to climate change. This ethnographic insight into vulnerability and resilience provides a basis for stronger engagement in collaboration and planning for the future.