Markov and Semi-markov Chains, Processes, Systems and Emerging Related Fields

This book covers a broad range of research results in the field of Markov and Semi-Markov chains, processes, systems and related emerging fields. The authors of the included research papers are well-known researchers in their field. The book presents the state-of-the-art and ideas for further research for theorists in the fields. Nonetheless, it also provides straightforwardly applicable results for diverse areas of practitioners

On the performance and programming of reversible molecular computers

If the 20th century was known for the computational revolution, what will the 21st be known for? Perhaps the recent strides in the nascent fields of molecular programming and biological computation will help bring about the ‘Coming Era of Nanotechnology’ promised in Drexler’s ‘Engines of Creation’. Though there is still far to go, there is much reason for optimism. This thesis examines the underlying principles needed to realise the computational aspects of such ‘engines’ in a performant way. Its main body focusses on the ways in which thermodynamics constrains the operation and design of such systems, and it ends with the proposal of a model of computation appropriate for exploiting these constraints. These thermodynamic constraints are approached from three different directions. The first considers the maximum possible aggregate performance of a system of computers of given volume, V, with a given supply of free energy. From this perspective, reversible computing is imperative in order to circumvent the Landauer limit. A result of Frank is refined and strengthened, showing that the adiabatic regime reversible computer performance is the best possible for any computer—quantum or classical. This therefore shows a universal scaling law governing the performance of compact computers of ~V^(5/6), compared to ~V^(2/3) for conventional computers. For the case of molecular computers, it is shown how to attain this bound. The second direction extends this performance analysis to the case where individual computational particles or sub-units can interact with one another. The third extends it to interactions with shared, non-computational parts of the system. It is found that accommodating these interactions in molecular computers imposes a performance penalty that undermines the earlier scaling result. Nonetheless, scaling superior to that of irreversible computers can be preserved, and appropriate mitigations and considerations are discussed. These analyses are framed in a context of molecular computation, but where possible more general computational systems are considered. The proposed model, the א-calculus, is appropriate for programming reversible molecular computers taking into account these constraints. A variety of examples and mathematical analyses accompany it. Moreover, abstract sketches of potential molecular implementations are provided. Developing these into viable schemes suitable for experimental validation will be a focus of future work

International Conference on Mathematical Analysis and Applications in Science and Engineering – Book of Extended Abstracts

The present volume on Mathematical Analysis and Applications in Science and Engineering - Book of Extended Abstracts of the ICMASC’2022 collects the extended abstracts of the talks presented at the International Conference on Mathematical Analysis and Applications in Science and Engineering – ICMA2SC'22 that took place at the beautiful city of Porto, Portugal, in June 27th-June 29th 2022 (3 days). Its aim was to bring together researchers in every discipline of applied mathematics, science, engineering, industry, and technology, to discuss the development of new mathematical models, theories, and applications that contribute to the advancement of scientific knowledge and practice. Authors proposed research in topics including partial and ordinary differential equations, integer and fractional order equations, linear algebra, numerical analysis, operations research, discrete mathematics, optimization, control, probability, computational mathematics, amongst others. The conference was designed to maximize the involvement of all participants and will present the state-of- the-art research and the latest achievements.info:eu-repo/semantics/publishedVersio

Dynamical Systems in Spiking Neuromorphic Hardware

Dynamical systems are universal computers. They can perceive stimuli, remember, learn from feedback, plan sequences of actions, and coordinate complex behavioural responses. The Neural Engineering Framework (NEF) provides a general recipe to formulate models of such systems as coupled sets of nonlinear differential equations and compile them onto recurrently connected spiking neural networks – akin to a programming language for spiking models of computation. The Nengo software ecosystem supports the NEF and compiles such models onto neuromorphic hardware. In this thesis, we analyze the theory driving the success of the NEF, and expose several core principles underpinning its correctness, scalability, completeness, robustness, and extensibility. We also derive novel theoretical extensions to the framework that enable it to far more effectively leverage a wide variety of dynamics in digital hardware, and to exploit the device-level physics in analog hardware. At the same time, we propose a novel set of spiking algorithms that recruit an optimal nonlinear encoding of time, which we call the Delay Network (DN). Backpropagation across stacked layers of DNs dramatically outperforms stacked Long Short-Term Memory (LSTM) networks—a state-of-the-art deep recurrent architecture—in accuracy and training time, on a continuous-time memory task, and a chaotic time-series prediction benchmark. The basic component of this network is shown to function on state-of-the-art spiking neuromorphic hardware including Braindrop and Loihi. This implementation approaches the energy-efficiency of the human brain in the former case, and the precision of conventional computation in the latter case

Energy Efficient and Cooperative Solutions for Next-Generation Wireless Networks

Energy efficiency is increasingly important for next-generation wireless systems due to the limited battery resources of mobile clients. While fourth generation cellular standards emphasize low client battery consumption, existing techniques do not explicitly focus on reducing power that is consumed when a client is actively communicating with the network. Based on high data rate demands of modern multimedia applications, active mode power consumption is expected to become a critical consideration for the development and deployment of future wireless technologies. Another reason for focusing more attention on energy efficient studies is given by the relatively slow progress in battery technology and the growing quality of service requirements of multimedia applications. The disproportion between demanded and available battery capacity is becoming especially significant for small-scale mobile client devices, where wireless power consumption dominates within the total device power budget. To compensate for this growing gap, aggressive improvements in all aspects of wireless system design are necessary. Recent work in this area indicates that joint link adaptation and resource allocation techniques optimizing energy efficient metrics can provide a considerable gain in client power consumption. Consequently, it is crucial to adapt state-of-the-art energy efficient approaches for practical use, as well as to illustrate the pros and cons associated with applying power-bandwidth optimization to improve client energy efficiency and develop insights for future research in this area. This constitutes the first objective of the present research. Together with energy efficiency, next-generation cellular technologies are emphasizing stronger support for heterogeneous multimedia applications. Since the integration of diverse services within a single radio platform is expected to result in higher operator profits and, at the same time, reduce network management expenses, intensive research efforts have been invested into design principles of such networks. However, as wireless resources are limited and shared by clients, service integration may become challenging. A key element in such systems is the packet scheduler, which typically helps ensure that the individual quality of service requirements of wireless clients are satisfied. In contrastingly different distributed wireless environments, random multiple access protocols are beginning to provide mechanisms for statistical quality of service assurance. However, there is currently a lack of comprehensive analytical frameworks which allow reliable control of the quality of service parameters for both cellular and local area networks. Providing such frameworks is therefore the second objective of this thesis. Additionally, the study addresses the simultaneous operation of a cellular and a local area network in spectrally intense metropolitan deployments and solves some related problems. Further improving the performance of battery-driven mobile clients, cooperative communications are sought as a promising and practical concept. In particular, they are capable of mitigating the negative effects of fading in a wireless channel and are thus expected to enhance next-generation cellular networks in terms of client spectral and energy efficiencies. At the cell edges or in areas missing any supportive relaying infrastructure, client-based cooperative techniques are becoming even more important. As such, a mobile client with poor channel quality may take advantage of neighboring clients which would relay data on its behalf. The key idea behind the concept of client relay is to provide flexible and distributed control over cooperative communications by the wireless clients themselves. By contrast to fully centralized control, this is expected to minimize overhead protocol signaling and hence ensure simpler implementation. Compared to infrastructure relay, client relay will also be cheaper to deploy. Developing the novel concept of client relay, proposing simple and feasible cooperation protocols, and analyzing the basic trade-offs behind client relay functionality become the third objective of this research. Envisioning the evolution of cellular technologies beyond their fourth generation, it appears important to study a wireless network capable of supporting machine-to-machine applications. Recent standardization documents cover a plethora of machine-to-machine use cases, as they also outline the respective technical requirements and features according to the application or network environment. As follows from this activity, a smart grid is one of the primary machine-to-machine use cases that involves meters autonomously reporting usage and alarm information to the grid infrastructure to help reduce operational cost, as well as regulate a customer's utility usage. The preliminary analysis of the reference smart grid scenario indicates weak system architecture components. For instance, the large population of machine-to-machine devices may connect nearly simultaneously to the wireless infrastructure and, consequently, suffer from excessive network entry delays. Another concern is the performance of cell-edge machine-to-machine devices with weak wireless links. Therefore, mitigating the above architecture vulnerabilities and improving the performance of future smart grid deployments is the fourth objective of this thesis. Summarizing, this thesis is generally aimed at the improvement of energy efficient properties of mobile devices in next-generation wireless networks. The related research also embraces a novel cooperation technique where clients may assist each other to increase per-client and network-wide performance. Applying the proposed solutions, the operation time of mobile clients without recharging may be increased dramatically. Our approach incorporates both analytical and simulation components to evaluate complex interactions between the studied objectives. It brings important conclusions about energy efficient and cooperative client behaviors, which is crucial for further development of wireless communications technologies

On Distributed Estimation for Resource Constrained Wireless Sensor Networks

We study Distributed Estimation (DES) problem, where several agents observe a noisy version of an underlying unknown physical phenomena (which is not directly observable), and transmit a compressed version of their observations to a Fusion Center (FC), where collective data is fused to reconstruct the unknown. One of the most important applications of Wireless Sensor Networks (WSNs) is performing DES in a field to estimate an unknown signal source. In a WSN battery powered geographically distributed tiny sensors are tasked with collecting data from the field. Each sensor locally processes its noisy observation (local processing can include compression, dimension reduction, quantization, etc) and transmits the processed observation over communication channels to the FC, where the received data is used to form a global estimate of the unknown source such that the Mean Square Error (MSE) of the DES is minimized. The accuracy of DES depends on many factors such as intensity of observation noises in sensors, quantization errors in sensors, available power and bandwidth of the network, quality of communication channels between sensors and the FC, and the choice of fusion rule in the FC. Taking into account all of these contributing factors and implementing a DES system which minimizes the MSE and satisfies all constraints is a challenging task. In order to probe into different aspects of this challenging task we identify and formulate the following three problems and address them accordingly: 1- Consider an inhomogeneous WSN where the sensors\u27 observations is modeled linear with additive Gaussian noise. The communication channels between sensors and FC are orthogonal power and bandwidth-constrained erroneous wireless fading channels. The unknown to be estimated is a Gaussian vector. Sensors employ uniform multi-bit quantizers and BPSK modulation. Given this setup, we ask: what is the best fusion rule in the FC? what is the best transmit power and quantization rate (measured in bits per sensor) allocation schemes that minimize the MSE? In order to answer these questions, we derive some upper bounds on global MSE and through minimizing those bounds, we propose various resource allocation schemes for the problem, through which we investigate the effect of contributing factors on the MSE. 2- Consider an inhomogeneous WSN with an FC which is tasked with estimating a scalar Gaussian unknown. The sensors are equipped with uniform multi-bit quantizers and the communication channels are modeled as Binary Symmetric Channels (BSC). In contrast to former problem the sensors experience independent multiplicative noises (in addition to additive noise). The natural question in this scenario is: how does multiplicative noise affect the DES system performance? how does it affect the resource allocation for sensors, with respect to the case where there is no multiplicative noise? We propose a linear fusion rule in the FC and derive the associated MSE in closed-form. We propose several rate allocation schemes with different levels of complexity which minimize the MSE. Implementing the proposed schemes lets us study the effect of multiplicative noise on DES system performance and its dynamics. We also derive Bayesian Cramer-Rao Lower Bound (BCRLB) and compare the MSE performance of our porposed methods against the bound. As a dual problem we also answer the question: what is the minimum required bandwidth of the network to satisfy a predetermined target MSE? 3- Assuming the framework of Bayesian DES of a Gaussian unknown with additive and multiplicative Gaussian noises involved, we answer the following question: Can multiplicative noise improve the DES performance in any case/scenario? the answer is yes, and we call the phenomena as \u27enhancement mode\u27 of multiplicative noise. Through deriving different lower bounds, such as BCRLB,Weiss-Weinstein Bound (WWB), Hybrid CRLB (HCRLB), Nayak Bound (NB), Yatarcos Bound (YB) on MSE, we identify and characterize the scenarios that the enhancement happens. We investigate two situations where variance of multiplicative noise is known and unknown. We also compare the performance of well-known estimators with the derived bounds, to ensure practicability of the mentioned enhancement modes

Two Phase Flow, Phase Change and Numerical Modeling

The heat transfer and analysis on laser beam, evaporator coils, shell-and-tube condenser, two phase flow, nanofluids, complex fluids, and on phase change are significant issues in a design of wide range of industrial processes and devices. This book includes 25 advanced and revised contributions, and it covers mainly (1) numerical modeling of heat transfer, (2) two phase flow, (3) nanofluids, and (4) phase change. The first section introduces numerical modeling of heat transfer on particles in binary gas-solid fluidization bed, solidification phenomena, thermal approaches to laser damage, and temperature and velocity distribution. The second section covers density wave instability phenomena, gas and spray-water quenching, spray cooling, wettability effect, liquid film thickness, and thermosyphon loop. The third section includes nanofluids for heat transfer, nanofluids in minichannels, potential and engineering strategies on nanofluids, and heat transfer at nanoscale. The forth section presents time-dependent melting and deformation processes of phase change material (PCM), thermal energy storage tanks using PCM, phase change in deep CO2 injector, and thermal storage device of solar hot water system. The advanced idea and information described here will be fruitful for the readers to find a sustainable solution in an industrialized society