Deterministic Population Protocols for Exact Majority and Plurality

In this paper we study space-efficient deterministic population protocols for several variants of the majority problem including plurality consensus. We focus on space efficient majority protocols in populations with an arbitrary number of colours C represented by k-bit labels, where k = ceiling (log C). In particular, we present asymptotically space-optimal (with respect to the adopted k-bit representation of colours) protocols for (1) the absolute majority problem, i.e., a protocol which decides whether a single colour dominates all other colours considered together, and (2) the relative majority problem, also known in the literature as plurality consensus, in which colours declare their volume superiority versus other individual colours. The new population protocols proposed in this paper rely on a dynamic formulation of the majority problem in which the colours originally present in the population can be changed by an external force during the communication process. The considered dynamic formulation is based on the concepts studied by D. Angluin et al. and O. Michail et al. about stabilizing inputs and composition of population protocols. Also, the protocols presented in this paper use a composition of some known protocols for static and dynamic majority

Modeling, Simulation, and Hardware-in-the-Loop Implementation of Distributed Voltage Control in Power Systems with Renewable Energy Sources

This dissertation develops and analyzes distributed controllers for power systems with renewable energy sources. A comprehensive state space modeling of voltage source inverters (VSIs) is developed specifically to address the secondary voltage control. This model can be used for simulation and control design. Unlike frequency, voltage is a local phenomenon, meaning that it cannot be controlled from a far distance. Therefore, a voltage zoning matrix that relates the sensitivity of the loads to the sources is proposed. The secondary voltage control is designed by applying the eigenvalue decomposition of the voltage zoning matrix to obtain the reference generators voltages. The developed algorithm in this study has been tested on multiple IEEE case studies, and the results show its effectiveness, yet it is a centralized control algorithm. To reduce the risk of a single point of failure in the centralized controllers, distributed secondary voltage controllers have been proposed in the recent literature. However, the communication messages are still exchanged among all controllers in the system. Therefore, a fully distributed algorithm is proposed in this dissertation study through the design of a communication layer by clustering the sources based on a developed sensitivity methodology. A modified IEEE 13 bus feeder with integrating renewable energy sources shows a significant improvement in time of convergence. A real communication protocol is then applied to the system to analyze the communication effect of packet loss and latency on the given distributed control system. Furthermore, to demonstrate the voltage control problem on the hardware-in-the-loop system, the detailed steps to implement the simulation model in the OPAL-RT real-time simulator (RTS) are discussed. The results of RTS coordinate with the software modeling outcomes

The Development and Analysis of Methods Used to Evaluate American Football Facemasks

The motivation for this Ph.D. dissertation is to provide football equipment managers, coaches, parents, athletes, and relevant industry personnel with an understanding of the implication a chosen football facemask design will have on the safety of the athlete. As athletes have increased their capacity for speed, size, and strength, so too has the head injury risk increased in American football. To align with the increase in head impact injury in American football, the protective head impact community must expand its capacity to evaluate protective equipment systems. This dissertation focuses specifically on one helmet system component: the football facemask. This dissertation was completed in three steps to evaluate the mechanical characteristics of football facemasks: 1.) a review of literature regarding existing methods used to evaluate protective headgear in American football; 2.) an evaluation of the industry standard for evaluating the impact performance of a helmet system made up of a football facemask, an outer shell, and internal padding; and 3.) an isolated evaluation of the structural stiffness of existing football facemasks designs. The results demonstrated that the existing methods used to evaluate football facemask performance lack the sensitivity necessary to differentiate the performance of various facemask designs. The contribution of this dissertation to the field is a novel method, including a patented apparatus and protocol, to characterize the structural stiffness of football facemasks to set up future work examining the relationship between the stiffness and impact performance

Flexible Electronics for High-Density EMG Based Signal Acquisition for Upper Limb Myoelectric Prosthesis Control

The research detailed in this thesis is aimed at developing flexible electrodes for high-density control of an upper limb myoelectric prosthesis. Different flexible dry electrode materials (made from doped traditionally non-conductive substrates) were used and compared to titanium (which is the industry standard for EMG electrodes). We determined that conductivity measurements alone, (the current industry standard for characterizing electrical properties of materials), are not sufficient due to their complex impedance. We measured the skin electrode complex impedance and relationship with signal to noise ratio (SNR) and settling time. We show that complex skin electrode impedance is linearly related to the SNR of signals and that complex skin electrode impedance better characterizes the electrical properties of doped, traditionally non-conductive materials for physiological signal acquisition. Next we constructed a flexible high-density array with 128- contact points arranged in an 8 x 16 configuration to cover the entire residual limb. Myoelectric signals, and its relationship to derived time domain features of all 128 channels were extracted and represented as spatio-temporal values as 8 x 16 images to represent the muscle activity map of the residual limb. Thus, a traditional signal-processing problem is converted into an image processing problem. Obtaining High Density (HD) (128 channel) spatio-temporal information has significant merits which include: ability to easily identify the optimum myoelectric recording sites on a residual limb, ability to temporally study the onset and decline of a contraction, predicting the stage of contraction and, finally, ability to implement proportional control and fine motor myoelectric control

Security, trust and cooperation in wireless sensor networks

Wireless sensor networks are a promising technology for many real-world applications such as critical infrastructure monitoring, scientific data gathering, smart buildings, etc.. However, given the typically unattended and potentially unsecured operation environment, there has been an increased number of security threats to sensor networks. In addition, sensor networks have very constrained resources, such as limited energy, memory, computational power, and communication bandwidth. These unique challenges call for new security mechanisms and algorithms. In this dissertation, we propose novel algorithms and models to address some important and challenging security problems in wireless sensor networks. The first part of the dissertation focuses on data trust in sensor networks. Since sensor networks are mainly deployed to monitor events and report data, the quality of received data must be ensured in order to make meaningful inferences from sensor data. We first study a false data injection attack in the distributed state estimation problem and propose a distributed Bayesian detection algorithm, which could maintain correct estimation results when less than one half of the sensors are compromised. To deal with the situation where more than one half of the sensors may be compromised, we introduce a special class of sensor nodes called \textit{trusted cores}. We then design a secure distributed trust aggregation algorithm that can utilize the trusted cores to improve network robustness. We show that as long as there exist some paths that can connect each regular node to one of these trusted cores, the network can not be subverted by attackers. The second part of the dissertation focuses on sensor network monitoring and anomaly detection. A sensor network may suffer from system failures due to loss of links and nodes, or malicious intrusions. Therefore, it is critical to continuously monitor the overall state of the network and locate performance anomalies. The network monitoring and probe selection problem is formulated as a budgeted coverage problem and a Markov decision process. Efficient probing strategies are designed to achieve a flexible tradeoff between inference accuracy and probing overhead. Based on the probing results on traffic measurements, anomaly detection can be conducted. To capture the highly dynamic network traffic, we develop a detection scheme based on multi-scale analysis of the traffic using wavelet transforms and hidden Markov models. The performance of the probing strategy and of the detection scheme are extensively evaluated in malicious scenarios using the NS-2 network simulator. Lastly, to better understand the role of trust in sensor networks, a game theoretic model is formulated to mathematically analyze the relation between trust and cooperation. Given the trust relations, the interactions among nodes are modeled as a network game on a trust-weighted graph. We then propose an efficient heuristic method that explores network heterogeneity to improve Nash equilibrium efficiency

Toxicity of metal debris from hip implants

Hip implants are commonly made of cobalt-chromium and titanium alloys. Once inside the body, implants wear and corrode, releasing metal particles and ions into the local tissue and blood. Metal debris can cause local adverse effects, such as bone loss and tissue necrosis, ultimately leading to implant failure. More recently, systemic cobalt toxicity has gained publicity as reports of neurotoxicity, cardiomyopathy and hypothyroidism increased among recipients of metal hip implants. Widespread dissemination of metal debris, and its accumulation in organ tissue, is of a particular concern. The aim of this thesis is to better understand how metallic implant debris affects the body, and how blood metal levels relate to any toxicity symptoms. Prevalence of neurotoxicity and cognitive decline among patients with a history of highly elevated blood cobalt was assessed, using a set of validated questionnaires. Although a number of statistically significant differences were detected between the high cobalt group and controls, clinically relevant neuro-cognitive adverse effects were not observed. Distribution and chemical speciation of cobalt, chromium and titanium deposits were investigated in cadaveric samples of organs from hip replacement patients. Though synchrotron analysis identified the presence of highly oxidised chromium, further work is needed to assess if the results can be extrapolated to the in vivo situation. Genetic factors that might predispose some patients to the adverse effects of cobalt were explored in vitro, using CRISPR/Cas9 gene editing technology. Results of the feasibility study identified several candidate genes for further investigation. Blood titanium was measured in a large group of patients with titanium-based implants, using high resolution ICP-MS. This allowed a reliable laboratory reference range to be defined for use in future patient monitoring. Results from this thesis inform on potential consequences of implant degradation, and demonstrate the clinical utility of blood metal measurements to monitor implant performance

Sonic utopia and social dystopia in the music of Hendrix, Reznor and Deadmau5

Twentieth-century popular music is fundamentally associated with electronics in its creation and recording, consumption, modes of dissemination, and playback. Traditional musical analysis, placing primacy on notated music, generally focuses on harmony, melody, and form, with issues of timbre and postproduction effects remaining largely unstudied. Interdisciplinary methodological practices address these limitations and can help broaden the analytical scope of popular idioms. Grounded in Jacques Attali's critical theories about the political economy of music, this dissertation investigates how the subversive noise of electronic sound challenges a controlling order and predicts broad cultural realignment. This study demonstrates how electronic noise, as an extra-musical element, creates modern soundscapes that require a new mapping of musical form and social intent. I further argue that the use of electronics in popular music signifies a technologically-obsessed postwar American culture moving rapidly towards an online digital revolution. I examine how electronic music technology introduces new sounds concurrent with generational shifts, projects imagined utopian and dystopian futures, and engages the tension between automated modern life and emotionally validating musical communities in real and virtual spaces. Chapter One synthesizes this interdisciplinary American studies project with the growing scholarship of sound studies in order to construct theoretical models for popular music analysis drawn from the fields of musicology, history, and science and technology studies. Chapter Two traces the emergence of the electronic synthesizer as a new sound that facilitated the transition of a technological postwar American culture into the politicized counterculture of the 1960s. The following three chapters provide case studies of individual popular artists' use of electronic music technology to express societal and political discontent: 1) Jimi Hendrix's application of distortion and stereo effects to narrate an Afrofuturist consciousness in the 1960s; 2) Trent Reznor's aggressive industrial rejection of Conservatism in the 1980s; and 3) Deadmau5's mediation of online life through computer-based production and performance in the 2000s. Lastly, this study extends existing discussions within sound studies to consider the cultural implications of music technology, noise politics, electronic timbre, multitrack audio, digital analytical techniques and online communities built through social media

A Statistical Evaluation of Risk Priority Numbers in Failure Modes and Effects Analysis Applied to the Prediction of Complex Systems

Complex systems such as military aircraft and naval ships are difficult to cost effectively maintain. Frequently, large-scale maintenance of complex systems (i.e., a naval vessel) is based on the reduction of the system to its base subcomponents and the use of manufacturer-suggested, time-directed, preventative maintenance, which is augmented during the systems lifecycle with predictive maintenance which assesses the system\u27s ability to perform its mission objectives. While preventative maintenance under certain conditions can increase reliability, preventative maintenance systems are often costly, increase down time, and allow for maintenance-induced failures, which may decrease the reliability of the system (Ebeling, 1997). This maintenance scheme ignores the complexity of the system it tries to maintain. By combining the base components or subsystems into a larger system, and introducing human interaction with the system, the complexity of the system creates a unique entity that cannot be completely understood by basing predictability of the system to perform tasks on the reduction of the system to its subcomponents. This study adds to the scholarly literature by developing a model, based on the traditional failure modes and effects analysis commonly used for research and development projects, to capture the effects of the human interaction with the system. Based on the ability of personnel assigned to operate and maintain the system, the severity of the system failure on the impact on the metasystems ability to perform its mission and the likelihood of the event of the failure to occur. Findings of the research indicate that the human interaction with the system, in as far as the ability of the personnel to repair and maintain the system, is a vital component in the ability to predict likelihood of the system failure and the prioritization of the risk of system failure, may be adequately captured for analysis through use of expert opinion elicitation. The use of the expert\u27s opinions may provide additional robustness to the modeling and analysis of system behavior in the event that failure occurs