Policies for Transmit Power Control in the Conditions of Jamming in Clustered Wireless System

This article presents a consistent solution of Transmit Power Control in centralized (clustered) wireless network with and without jamming. Depending on the policy assumed, solutions are applied to minimize the power used in a system or to satisfy expected Quality of Service. Because of specific nature of the system there is no optimal solution which can be applied in practice. Correctness and effectiveness of four proposed Power Control algorithms was presented in the form of computer simulation results in which the system capacity, mean power used and the number of successful links were described

Policies for Transmit Power Control in the Conditions of Jamming in Clustered Wireless System

This article presents a consistent solution of Transmit Power Control in centralized (clustered) wireless network with and without jamming. Depending on the policy assumed, solutions are applied to minimize the power used in a system or to satisfy expected Quality of Service. Because of specific nature of the system there is no optimal solution which can be applied in practice. Correctness and effectiveness of four proposed Power Control algorithms was presented in the form of computer simulation results in which the system capacity, mean power used and the number of successful links were described

Advances in approximate Bayesian computation and trans-dimensional sampling methodology

Bayesian statistical models continue to grow in complexity, driven in part by a few key factors: the massive computational resources now available to statisticians; the substantial gains made in sampling methodology and algorithms such as Markov chain Monte Carlo (MCMC), trans-dimensional MCMC (TDMCMC), sequential Monte Carlo (SMC), adaptive algorithms and stochastic approximation methods and approximate Bayesian computation (ABC); and development of more realistic models for real world phenomena as demonstrated in this thesis for financial models and telecommunications engineering. Sophisticated statistical models are increasingly proposed for practical solutions to real world problems in order to better capture salient features of increasingly more complex data. With sophistication comes a parallel requirement for more advanced and automated statistical computational methodologies. The key focus of this thesis revolves around innovation related to the following three significant Bayesian research questions. 1. How can one develop practically useful Bayesian models and corresponding computationally efficient sampling methodology, when the likelihood model is intractable? 2. How can one develop methodology in order to automate Markov chain Monte Carlo sampling approaches to efficiently explore the support of a posterior distribution, defined across multiple Bayesian statistical models? 3. How can these sophisticated Bayesian modelling frameworks and sampling methodologies be utilized to solve practically relevant and important problems in the research fields of financial risk modeling and telecommunications engineering ? This thesis is split into three bodies of work represented in three parts. Each part contains journal papers with novel statistical model and sampling methodological development. The coherent link between each part involves the novel sampling methodologies developed in Part I and utilized in Part II and Part III. Papers contained in each part make progress at addressing the core research questions posed. Part I of this thesis presents generally applicable key statistical sampling methodologies that will be utilized and extended in the subsequent two parts. In particular it presents novel developments in statistical methodology pertaining to likelihood-free or ABC and TDMCMC methodology. The TDMCMC methodology focuses on several aspects of automation in the between model proposal construction, including approximation of the optimal between model proposal kernel via a conditional path sampling density estimator. Then this methodology is explored for several novel Bayesian model selection applications including cointegrated vector autoregressions (CVAR) models and mixture models in which there is an unknown number of mixture components. The second area relates to development of ABC methodology with particular focus on SMC Samplers methodology in an ABC context via Partial Rejection Control (PRC). In addition to novel algorithmic development, key theoretical properties are also studied for the classes of algorithms developed. Then this methodology is developed for a highly challenging practically significant application relating to multivariate Bayesian $\alpha$-stable models. Then Part II focuses on novel statistical model development in the areas of financial risk and non-life insurance claims reserving. In each of the papers in this part the focus is on two aspects: foremost the development of novel statistical models to improve the modeling of risk and insurance; and then the associated problem of how to fit and sample from such statistical models efficiently. In particular novel statistical models are developed for Operational Risk (OpRisk) under a Loss Distributional Approach (LDA) and for claims reserving in Actuarial non-life insurance modelling. In each case the models developed include an additional level of complexity which adds flexibility to the model in order to better capture salient features observed in real data. The consequence of the additional complexity comes at the cost that standard fitting and sampling methodologies are generally not applicable, as a result one is required to develop and apply the methodology from Part I. Part III focuses on novel statistical model development in the area of statistical signal processing for wireless communications engineering. Statistical models will be developed or extended for two general classes of wireless communications problem: the first relates to detection of transmitted symbols and joint channel estimation in Multiple Input Multiple Output (MIMO) systems coupled with Orthogonal Frequency Division Multiplexing (OFDM); the second relates to co-operative wireless communications relay systems in which the key focus is on detection of transmitted symbols. Both these areas will require advanced sampling methodology developed in Part I to find solutions to these real world engineering problems

Affective Computing

This book provides an overview of state of the art research in Affective Computing. It presents new ideas, original results and practical experiences in this increasingly important research field. The book consists of 23 chapters categorized into four sections. Since one of the most important means of human communication is facial expression, the first section of this book (Chapters 1 to 7) presents a research on synthesis and recognition of facial expressions. Given that we not only use the face but also body movements to express ourselves, in the second section (Chapters 8 to 11) we present a research on perception and generation of emotional expressions by using full-body motions. The third section of the book (Chapters 12 to 16) presents computational models on emotion, as well as findings from neuroscience research. In the last section of the book (Chapters 17 to 22) we present applications related to affective computing

Photoactive Materials: Synthesis, Applications and Technology

This book presents a collection of 13 original research articles that focus on the science of light–matter interaction. This area of science has been led to some the greatest accomplishments of the past 100 years, with the discovery of materials that perform useful operations by collecting light or generating light from an outside stimulus. These materials are at the center of a multitude of technologies that have permeated our daily life; every day we rely on quantum well lasers for telecommunication, organic light emitting diodes for our displays, complementary metal–oxide–semiconductors for our camera detectors, and of course a plethora of new photovoltaic cells that harvest sunlight to satisfy our energy needs. In this book, top-rated researchers present their latest findings in the field of nano-particles, plasmonics, semi-conductors, magneto-optics, and holography

The design and analysis of novel integrated phase-change photonic memory and computing devices

The current massive growth in data generation and communication challenges traditional computing and storage paradigms. The integrated silicon photonic platform may alleviate the physical limitations resulting from the use of electrical interconnects and the conventional von Neuman computing architecture, due to its intrinsic energy and bandwidth advantages. This work focuses on the development of the phase-change all-photonic memory (PPCM), a device potentially enabling the transition from the electrical to the optical domain by providing the (previously unavailable) non-volatile all-photonic storage functionality. PPCM devices allow for all-optical encoding of the information on the crystal fraction of a waveguide-implemented phase-change material layer, here Ge2Sb2Te5, which in turn modulates the transmitted signal amplitude. This thesis reports novel developments of the numerical methods necessary to emulate the physics of PPCM device operation and performance characteristics, illustrating solutions enabling the realization of a simulation framework modelling the inherently three-dimensional and self-influencing optical, thermal and phase-switching behaviour of PPCM devices. This thesis also depicts an innovative, fast and cost-effective method to characterise the key optical properties of phase-change materials (upon which the performance of PPCM devices depend), exploiting the reflection pattern of a purposely built layer stack, combined with a smart fit algorithm adapting potential solutions drawn from the scientific literature. The simulation framework developed in the thesis is used to analyse reported PPCM experimental results. Numerous sources of uncertainty are underlined, whose systematic analysis reduced to the peculiar non-linear optical properties of Ge2Sb2Te5. Yet, the data fit process validates both the simulation tool and the remaining physical assumptions, as the model captures the key aspects of the PPCM at high optical intensity, and reliably and accurately predicts its behaviour at low intensity, enabling to investigate its underpinning physical mechanisms. Finally, a novel PPCM memory architecture, exploiting the interaction of a much-reduced Ge2Sb2Te5 volume with a plasmonic resonant nanoantenna, is proposed and numerically investigated. The architecture concept is described and the memory functionality is demonstrated, underlining its potential energy and speed improvement on the conventional device by up to two orders of magnitude.Engineering and Physical Sciences Research Council (EPSRC

Advanced Mobile Robotics: Volume 3

Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective

Proceedings of the Scientific-Practical Conference "Research and Development - 2016"

talent management; sensor arrays; automatic speech recognition; dry separation technology; oil production; oil waste; laser technolog