Cellular Automata

Modelling and simulation are disciplines of major importance for science and engineering. There is no science without models, and simulation has nowadays become a very useful tool, sometimes unavoidable, for development of both science and engineering. The main attractive feature of cellular automata is that, in spite of their conceptual simplicity which allows an easiness of implementation for computer simulation, as a detailed and complete mathematical analysis in principle, they are able to exhibit a wide variety of amazingly complex behaviour. This feature of cellular automata has attracted the researchers' attention from a wide variety of divergent fields of the exact disciplines of science and engineering, but also of the social sciences, and sometimes beyond. The collective complex behaviour of numerous systems, which emerge from the interaction of a multitude of simple individuals, is being conveniently modelled and simulated with cellular automata for very different purposes. In this book, a number of innovative applications of cellular automata models in the fields of Quantum Computing, Materials Science, Cryptography and Coding, and Robotics and Image Processing are presented

Control of Cooperative Haptics-Enabled Teleoperation Systems with Application to Minimally Invasive Surgery

Robot-Assisted Minimally Invasive Surgical (RAMIS) systems frequently have a structure of cooperative teleoperator systems where multiple master-slave pairs are used to collaboratively execute a task. Although multiple studies indicate that haptic feedback improves the realism of tool-tissue interaction to the surgeon and leads to better performance for surgical procedures, current telesurgical systems typically do not provide force feedback, mainly because of the inherent stability issues. The research presented in this thesis is directed towards the development of control algorithms for force reflecting cooperative surgical teleoperator systems with improved stability and transparency characteristics. In the case of cooperative force reflecting teleoperation over networks, conventional passivity based approaches may have limited applicability due to potentially non-passive slave-slave interactions and irregular communication delays imposed by the network. In this thesis, an alternative small gain framework for the design of cooperative network-based force reflecting teleoperator systems is developed. Using the small gain framework, control algorithms for cooperative force-reflecting teleoperator systems are designed that guarantee stability in the presence of multiple network-induced communication constraints. Furthermore, the design conservatism typically associated with the small-gain approach is eliminated by using the Projection-Based Force Reflection (PBFR) algorithms. Stability results are established for networked cooperative teleoperator systems under different types of force reflection algorithms in the presence of irregular communication delays. The proposed control approach is consequently implemented on a dual-arm (two masters/two slaves) robotic MIS testbed. The testbed consists of two Haptic Wand devices as masters and two PA10-7C robots as the slave manipulators equipped with da Vinci laparoscopic surgical instruments. The performance of the proposed control approach is evaluated in three different cooperative surgical tasks, which are knot tightening, pegboard transfer, and object manipulation. The experimental results obtained indicate that the PBFR algorithms demonstrate statistically significant performance improvement in comparison with the conventional direct force reflection algorithms. One possible shortcoming of using PBFR algorithms is that implementation of these algorithms may lead to attenuation of the high-frequency component of the contact force which is important, in particular, for haptic perception of stiff surfaces. In this thesis, a solution to this problem is proposed which is based on the idea of separating the different frequency bands in the force reflection signal and consequently applying the projection-based principle to the low-frequency component, while reflecting the high-frequency component directly. The experimental results demonstrate that substantial improvement in transient fidelity of the force feedback is achieved using the proposed method without negative effects on the stability of the system

Detection of COVID-19 in X-Ray images using Neural Networks

Pandemie způsobena nemocí COVID-19 je velmi naléhavým problémem, který nadále ovlivňuje životy lidí po celém světě. K překonání této nemoci je nutné včas identifikovat a izolovat infikované pacienty, aby se zabránilo šíření viru. Tradiční detekční techniky založené na molekulární diagnostice, jako například RT-PCR, jsou nákladné, časově náročné a studie ukazují, že jejich spolehlivost značně kolísá. V této práci jsme zkoumali detekci nemoci COVID-19 v rentgenových snímcích hrudníku pomocí konvolučních neuronových sítí. Poznatky z provedené rešerše dále využíváme k implementaci prototypu pro provádění binární detekce a jeho následnému vyhodnocení na souboru otevřených datových repozitářů dostupných online. Tyto výsledky poté porovnáváme se stávajícími řešeními a modely. Naše navrhovaná jednoduchá architektura s názvem BaseNet dosahuje na zvolené testovací sadě dat přesnosti 95.50 % a senzitivity 93.00 %. Zmíněný BaseNet jsme dále spolu s několika dalšími vyladěnými architekturami spojili do souboru modelů, jejichž kombinovaná klasifikační přesnost je 99.50 % s naměřenou senzitivitou 98.50 %.The COVID-19 pandemic is a very pressing issue that continues to affect the lives of people around the globe. To combat and overcome the disease, it is necessary for infected patients to be quickly identified and isolated to prevent the virus from spreading. The traditional detection techniques based on molecular diagnosis, such as RT-PCR, are expensive, time-consuming, and their reliability has been shown to fluctuate. In this thesis, we research the detection of COVID-19 in chest X-ray images using convolutional neural networks. We use our findings to implement a prototype that performs binary detection of the disease, evaluate its performance on a collection of open data repositories available online, and compare its results to existing models. Our proposed light-weight architecture called the BaseNet achieves an accuracy of 95.50 % on the chosen test set, with a COVID-19 sensitivity of 93.00 %. We further assemble an ensemble of the BaseNet along with several other fine-tuned architectures, whose combined classification accuracy is 99.25 % with a measured sensitivity of 98.50 %

A novel parallel algorithm for surface editing and its FPGA implementation

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophySurface modelling and editing is one of important subjects in computer graphics. Decades of research in computer graphics has been carried out on both low-level, hardware-related algorithms and high-level, abstract software. Success of computer graphics has been seen in many application areas, such as multimedia, visualisation, virtual reality and the Internet. However, the hardware realisation of OpenGL architecture based on FPGA (field programmable gate array) is beyond the scope of most of computer graphics researches. It is an uncultivated research area where the OpenGL pipeline, from hardware through the whole embedded system (ES) up to applications, is implemented in an FPGA chip. This research proposes a hybrid approach to investigating both software and hardware methods. It aims at bridging the gap between methods of software and hardware, and enhancing the overall performance for computer graphics. It consists of four parts, the construction of an FPGA-based ES, Mesa-OpenGL implementation for FPGA-based ESs, parallel processing, and a novel algorithm for surface modelling and editing. The FPGA-based ES is built up. In addition to the Nios II soft processor and DDR SDRAM memory, it consists of the LCD display device, frame buffers, video pipeline, and algorithm-specified module to support the graphics processing. Since there is no implementation of OpenGL ES available for FPGA-based ESs, a specific OpenGL implementation based on Mesa is carried out. Because of the limited FPGA resources, the implementation adopts the fixed-point arithmetic, which can offer faster computing and lower storage than the floating point arithmetic, and the accuracy satisfying the needs of 3D rendering. Moreover, the implementation includes Bézier-spline curve and surface algorithms to support surface modelling and editing. The pipelined parallelism and co-processors are used to accelerate graphics processing in this research. These two parallelism methods extend the traditional computation parallelism in fine-grained parallel tasks in the FPGA-base ESs. The novel algorithm for surface modelling and editing, called Progressive and Mixing Algorithm (PAMA), is proposed and implemented on FPGA-based ES’s. Compared with two main surface editing methods, subdivision and deformation, the PAMA can eliminate the large storage requirement and computing cost of intermediated processes. With four independent shape parameters, the PAMA can be used to model and edit freely the shape of an open or closed surface that keeps globally the zero-order geometric continuity. The PAMA can be applied independently not only FPGA-based ESs but also other platforms. With the parallel processing, small size, and low costs of computing, storage and power, the FPGA-based ES provides an effective hybrid solution to surface modelling and editing

On the Combination of Game-Theoretic Learning and Multi Model Adaptive Filters

This paper casts coordination of a team of robots within the framework of game theoretic learning algorithms. In particular a novel variant of fictitious play is proposed, by considering multi-model adaptive filters as a method to estimate other players’ strategies. The proposed algorithm can be used as a coordination mechanism between players when they should take decisions under uncertainty. Each player chooses an action after taking into account the actions of the other players and also the uncertainty. Uncertainty can occur either in terms of noisy observations or various types of other players. In addition, in contrast to other game-theoretic and heuristic algorithms for distributed optimisation, it is not necessary to find the optimal parameters a priori. Various parameter values can be used initially as inputs to different models. Therefore, the resulting decisions will be aggregate results of all the parameter values. Simulations are used to test the performance of the proposed methodology against other game-theoretic learning algorithms.</p

Astrophysics in 2006

The fastest pulsar and the slowest nova; the oldest galaxies and the youngest stars; the weirdest life forms and the commonest dwarfs; the highest energy particles and the lowest energy photons. These were some of the extremes of Astrophysics 2006. We attempt also to bring you updates on things of which there is currently only one (habitable planets, the Sun, and the universe) and others of which there are always many, like meteors and molecules, black holes and binaries.Comment: 244 pages, no figure

Project X: Physics Opportunities

Part 2 of "Project X: Accelerator Reference Design, Physics Opportunities, Broader Impacts". In this Part, we outline the particle-physics program that can be achieved with Project X, a staged superconducting linac for intensity-frontier particle physics. Topics include neutrino physics, kaon physics, muon physics, electric dipole moments, neutron-antineutron oscillations, new light particles, hadron structure, hadron spectroscopy, and lattice-QCD calculations. Part 1 is available as arXiv:1306.5022 [physics.acc-ph] and Part 3 is available as arXiv:1306.5024 [physics.acc-ph]

Angioplasty, Various Techniques and Challenges in Treatment of Congenital and Acquired Vascular Stenoses

The field of performing transcatheter interventions to treat vascular lesions has exploded over the past 20 years. Not only has the technology changed, especially in the arena of balloon/stent devices, but the techniques of approaching complex lesions has evolved over the past decade. Lesions that no one would have imagined treating back in the 1990's are now being done routinely in the catheterization suite. This book provides an update on the current techniques and devices used to treat a wide variety of lesions. Though, at first, the outward appearance of the topics appears to be varied, they are all related by the common thread of treating vascular lesions. We hope, by publishing this book, to accomplish two things: First, to offer insight from experts in their field to treat, both medically and procedurally, complex vascular lesions that we frequently encounter. Secondly, we hope to promote increased communication between areas of medicine that frequently don't communicate, between adult interventional cardiologists, pediatric interventional cardiologists, interventional radiologists, and neurosurgeons. Much can be learned from our respective colleagues in these areas which can further our own world of interventions