The role of synchronization in digital communications using chaos - Part II: Chaotic modulation and chaotic synchronization.

For pt. I see ibid., vol. 44, p. 927-36 (1997). In a digital communications system, data are transmitted from one location to another by mapping bit sequences to symbols, and symbols to sample functions of analog waveforms. The analog waveform passes through a bandlimited (possibly time-varying) analog channel, where the signal is distorted and noise is added. In a conventional system the analog sample functions sent through the channel are weighted sums of one or more sinusoids; in a chaotic communications system the sample functions are segments of chaotic waveforms. At the receiver, the symbol may be recovered by means of coherent detection, where all possible sample functions are known, or by noncoherent detection, where one or more characteristics of the sample functions are estimated. In a coherent receiver, synchronization is the most commonly used technique for recovering the sample functions from the received waveform. These sample functions are then used as reference signals for a correlator. Synchronization-based coherent receivers have advantages over noncoherent receivers in terms of noise performance, bandwidth efficiency (in narrow-band systems) and/or data rate (in chaotic systems). These advantages are lost if synchronization cannot be maintained, for example, under poor propagation conditions. In these circumstances, communication without synchronization may be preferable. The theory of conventional telecommunications is extended to chaotic communications, chaotic modulation techniques and receiver configurations are surveyed, and chaotic synchronization schemes are described

Identifying sources of global contention in constraint satisfaction search

Much work has been done on learning from failure in search to boost solving of combinatorial problems, such as clause-learning and clause-weighting in boolean satisfiability (SAT), nogood and explanation-based learning, and constraint weighting in constraint satisfaction problems (CSPs). Many of the top solvers in SAT use clause learning to good effect. A similar approach (nogood learning) has not had as large an impact in CSPs. Constraint weighting is a less fine-grained approach where the information learnt gives an approximation as to which variables may be the sources of greatest contention. In this work we present two methods for learning from search using restarts, in order to identify these critical variables prior to solving. Both methods are based on the conflict-directed heuristic (weighted-degree heuristic) introduced by Boussemart et al. and are aimed at producing a better-informed version of the heuristic by gathering information through restarting and probing of the search space prior to solving, while minimizing the overhead of these restarts. We further examine the impact of different sampling strategies and different measurements of contention, and assess different restarting strategies for the heuristic. Finally, two applications for constraint weighting are considered in detail: dynamic constraint satisfaction problems and unary resource scheduling problems.

Uniformly convergent finite element and finite difference methods for singularly perturbed ordinary differential equations

This thesis is concerned with uniformly convergent finite element and finite difference methods for numerically solving singularly perturbed two-point boundary value problems. We examine the following four problems: (i) high order problem of reaction-diffusion type; (ii) high order problem of convection-diffusion type; (iii) second order interior turning point problem; (iv) semilinear reaction-diffusion problem. Firstly, we consider high order problems of reaction-diffusion type and convection-diffusion type. Under suitable hypotheses, the coercivity of the associated bilinear forms is proved and representation results for the solutions of such problems are given. It is shown that, on an equidistant mesh, polynomial schemes cannot achieve a high order of convergence which is uniform in the perturbation parameter. Piecewise polynomial Galerkin finite element methods are then constructed on a Shishkin mesh. High order convergence results, which are uniform in the perturbation parameter, are obtained in various norms. Secondly, we investigate linear second order problems with interior turning points. Piecewise linear Galerkin finite element methods are generated on various piecewise equidistant meshes designed for such problems. These methods are shown to be convergent, uniformly in the singular perturbation parameter, in a weighted energy norm and the usual L2 norm. Finally, we deal with a semilinear reaction-diffusion problem. Asymptotic properties of solutions to this problem are discussed and analysed. Two simple finite difference schemes on Shishkin meshes are applied to the problem. They are proved to be uniformly convergent of second order and fourth order respectively. Existence and uniqueness of a solution to both schemes are investigated. Numerical results for the above methods are presented.

Systematic delay-driven power optimisation and power-driven delay optimisation of combinational circuits

With the proliferation of mobile wireless communication and embedded systems, the energy efficiency becomes a major design constraint. The dissipated energy is often referred as the product of power dissipation and the input-output delay. Most of electronic design automation techniques focus on optimising only one of these parameters either power or delay. Industry standard design flows integrate systematic methods of optimising either area or timing while for power consumption optimisation one often employs heuristics which are characteristic to a specific design. In this work we answer three questions in our quest to provide a systematic approach to joint power and delay Optimisation. The first question of our research is: How to build a design flow which incorporates academic and industry standard design flows for power optimisation? To address this question, we use a reference design flow provided by Synopsys and integrate in this flow academic tools and methodologies. The proposed design flow is used as a platform for analysing some novel algorithms and methodologies for optimisation in the context of digital circuits. The second question we answer is: Is possible to apply a systematic approach for power optimisation in the context of combinational digital circuits? The starting point is a selection of a suitable data structure which can easily incorporate information about delay, power, area and which then allows optimisation algorithms to be applied. In particular we address the implications of a systematic power optimisation methodologies and the potential degradation of other (often conflicting) parameters such as area or the delay of implementation. Finally, the third question which this thesis attempts to answer is: Is there a systematic approach for multi-objective optimisation of delay and power? A delay-driven power and power-driven delay optimisation is proposed in order to have balanced delay and power values. This implies that each power optimisation step is not only constrained by the decrease in power but also the increase in delay. Similarly, each delay optimisation step is not only governed with the decrease in delay but also the increase in power. The goal is to obtain multi-objective optimisation of digital circuits where the two conflicting objectives are power and delay. The logic synthesis and optimisation methodology is based on AND-Inverter Graphs (AIGs) which represent the functionality of the circuit. The switching activities and arrival times of circuit nodes are annotated onto an AND-Inverter Graph under the zero and a non-zero-delay model. We introduce then several reordering rules which are applied on the AIG nodes to minimise switching power or longest path delay of the circuit at the pre-technology mapping level. The academic Electronic Design Automation (EDA) tool ABC is used for the manipulation of AND-Inverter Graphs. We have implemented various combinatorial optimisation algorithms often used in Electronic Design Automation such as Simulated Annealing and Uniform Cost Search Algorithm. Simulated Annealing (SMA) is a probabilistic meta heuristic for the global optimization problem of locating a good approximation to the global optimum of a given function in a large search space. We used SMA to probabilistically decide between moving from one optimised solution to another such that the dynamic power is optimised under given delay constraints and the delay is optimised under given power constraints. A good approximation to the global optimum solution of energy constraint is obtained. Uniform Cost Search (UCS) is a tree search algorithm used for traversing or searching a weighted tree, tree structure, or graph. We have used Uniform Cost Search Algorithm to search within the AIG network, a specific AIG node order for the reordering rules application. After the reordering rules application, the AIG network is mapped to an AIG netlist using specific library cells. Our approach combines network re-structuring, AIG nodes reordering, dynamic power and longest path delay estimation and optimisation and finally technology mapping to an AIG netlist. A set of MCNC Benchmark circuits and large combinational circuits up to 100,000 gates have been used to validate our methodology. Comparisons for power and delay optimisation are made with the best synthesis scripts used in ABC. Reduction of 23% in power and 15% in delay with minimal overhead is achieved, compared to the best known ABC results. Also, our approach is also implemented on a number of processors with combinational and sequential components and significant savings are achieved.

Networking protocols for long life wireless sensor networks

My original contribution to knowledge is the creation of a WSN system that further improves the functionality of existing technology, whilst achieving improved power consumption and reliability. This thesis concerns the development of industrially applicable wireless sensor networks that are low-power, reliable and latency aware. This work aims to improve upon the state of the art in networking protocols for low-rate multi-hop wireless sensor networks. Presented is an application-driven co-design approach to the development of such a system. Starting with the physical layer, hardware was designed to meet industry specified requirements. The end system required further investigation of communications protocols that could achieve the derived application-level system performance specifications. A CSMA/TDMA hybrid MAC protocol was developed, leveraging numerous techniques from the literature and novel optimisations. It extends the current art with respect to power consumption for radio duty-cycled applications, and reliability, in dense wireless sensor networks, whilst respecting latency bounds. Specifically, it provides 100% packet delivery for 11 concurrent senders transmitting towards a single radio duty cycled sink-node. This is representative of an order of magnitude improvement over the comparable art, considering MAC-only mechanisms. A novel latency-aware routing protocol was developed to exploit the developed hardware and MAC protocol. It is based on a new weighted objective function with multiple fail safe mechanisms to ensure extremely high reliability and robustness. The system was empirically evaluated on two hardware platforms. These are the application-specific custom 868 MHz node and the de facto community-standard TelosB. Extensive empirical comparative performance analyses were conducted against the relevant art to demonstrate the advances made. The resultant system is capable of exceeding 10-year battery life, and exhibits reliability performance in excess of 99.9%.

Development and psychometric evaluation of the spirituality instrument (SpI-27) in a sample of people with chronic illness

Background: Spirituality is fundamental to all human beings, existing within a person, and developing until death. This research sought to operationalise spirituality in a sample of individuals with chronic illness. A review of the conceptual literature identified three dimensions of spirituality: connectedness, transcendence, and meaning in life. A review of the empirical literature identified one instrument that measures the three dimensions together. Yet, recent appraisals of this instrument highlighted issues with item formulation and limited evidence of reliability and validity. Aim: The aim of this research was to develop a theoretically-grounded instrument to measure spirituality – the Spirituality Instrument-27 (SpI-27). A secondary aim was to psychometrically evaluate this instrument in a sample of individuals with chronic illness (n=249). Methods: A two-phase design was adopted. Phase one consisted of the development of the SpI-27 based on item generation from a concept analysis, a literature review, and an instrument appraisal. The second phase established the psychometric properties of the instrument and included: a qualitative descriptive design to establish content validity; a pilot study to evaluate the mode of administration; and a descriptive correlational design to assess the instrument’s reliability and validity. Data were analysed using SPSS (Version 18). Results: Results of exploratory factor analysis concluded a final five-factor solution with 27 items. These five factors were labelled: Connectedness with Others, Self-Transcendence, Self-Cognisance, Conservationism, and Connectedness with a Higher Power. Cronbach’s alpha coefficients ranged from 0.823 to 0.911 for the five factors, and 0.904 for the overall scale, indicating high internal consistency. Paired-sample t-tests, intra-class correlations, and weighted kappa values supported the temporal stability of the instrument over 2 weeks. A significant positive correlation was found between the SpI-27 and the Spirituality Index of Well-Being, providing evidence for convergent validity. Conclusion: This research addresses a call for a theoretically-grounded instrument to measure spirituality.

Physical function, psychosocial adaptation, and hardiness post stroke

Introduction: Stroke is a chronic condition that significantly impacts on morbidity and mortality (Balanda et al. 2010). Globally, the complexity of stroke is well documented and more recently, in Ireland, as part of the National Survey of Stroke Survivors (Horgan et al. 2014). There are a number of factors that are known to influence adaptation post stroke. However, there is a lack of research to explain the variability in how survivors adapt post stroke. Hardiness is a broad personality trait that leads to better outcome. This study investigated the influence of hardiness and physical function on psychosocial adaptation post stroke. Methods: A quantitative cross-sectional, correlational, exploratory study was conducted between April and November 2013. The sample consisted of stroke survivors (n=100) who were recruited from three hospital outpatient departments and completed a questionnaire package. Results: The mean age of participants was 76 years (range 70-80), over half (56%) of the participants achieved the maximum score of 20 on the Barthel Index indicating independence in activities of daily living. The median number of days since stroke onset was 91 days (range 74-128). The total mean score and standard deviation for hardiness was 1.89 (0.4) as measured by the Dispositional Resilience Scale, indicating medium hardiness (possible range 0-3). Psychosocial adaptation was measured using the Psychosocial Adjustment to Illness Scale, the total weighted mean and standard deviation was 0.54 (0.3) indicating a satisfactory level of psychosocial adaptation (possible range 0-3). A hierarchical multiple linear regression was performed which contained 6 independent variables (hardiness, living arrangement, and length of hospital stay, number of days since stroke onset, physical function and self-rated recovery). Findings demonstrated that physical function (p<0.001) and hardiness (p=0.008) were significantly related to psychosocial adaptation. Altogether, 65% of the variation in psychosocial adaptation can be explained by the combined effect of the independent variables. Physical functioning had the highest unique contribution (11%) to explain the variance in psychosocial adaptation while self-rated recovery, hardiness, and living arrangements contributed 3% each. Conclusion: This research provides important information regarding factors that influence psychosocial adaptation post stroke at 3 months. Physical function significantly contributed to psychosocial adaptation post stroke. The personality trait of hardiness provides insight into how behaviour influenced adaptation post stroke. While hardiness also had a strong relationship with psychosocial adaptation, further research is necessary to fully comprehend this process.