Fuzzy Connectedness Image Segmentation in Graph Cut Formulation: A Linear-Time Algorithm and a Comparative Analysis

A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.

A new method for calculating the convergent point of a moving group

Context. Convergent point (CP) search methods are important tools for studying the kinematic properties of open clusters and young associations whose members share the same spatial motion. Aims. We present a new CP search strategy based on proper motion data. We test the new algorithm on synthetic data and compare it with previous versions of the CP search method. As an illustration and validation of the new method we also present an application to the Hyades open cluster and a comparison with independent results. Methods. The new algorithm rests on the idea of representing the stellar proper motions by great circles over the celestial sphere and visualizing their intersections as the CP of the moving group. The new strategy combines a maximum-likelihood analysis for simultaneously determining the CP and selecting the most likely group members and a minimization procedure that returns a refined CP position and its uncertainties. The method allows one to correct for internal motions within the group and takes into account that the stars in the group lie at different distances. Results. Based on Monte Carlo simulations, we find that the new CP search method in many cases returns a more precise solution than its previous versions. The new method is able to find and eliminate more field stars in the sample and is not biased towards distant stars. The CP solution for the Hyades open cluster is in excellent agreement with previous determinations.

Advanced signal and receiver design for next generation OFDM systems

This thesis deal with the design of advanced OFDM systems. Both waveform and receiver design have been treated. The main scope of the Thesis is to study, create, and propose, ideas and novel design solutions able to cope with the weaknesses and crucial aspects of modern OFDM systems. Starting from the the transmitter side, the problem represented by low resilience to non-linear distortion has been assessed. A novel technique that considerably reduces the Peak-to-Average Power Ratio (PAPR) yielding a quasi constant signal envelope in the time domain (PAPR close to 1 dB) has been proposed.The proposed technique, named Rotation Invariant Subcarrier Mapping (RISM),is a novel scheme for subcarriers data mapping,where the symbols belonging to the modulation alphabet are not anchored, but maintain some degrees of freedom. In other words, a bit tuple is not mapped on a single point, rather it is mapped onto a geometrical locus, which is totally or partially rotation invariant. The final positions of the transmitted complex symbols are chosen by an iterative optimization process in order to minimize the PAPR of the resulting OFDM symbol. Numerical results confirm that RISM makes OFDM usable even in severe non-linear channels. Another well known problem which has been tackled is the vulnerability to synchronization errors. Indeed in OFDM system an accurate recovery of carrier frequency and symbol timing is crucial for the proper demodulation of the received packets. In general, timing and frequency synchronization is performed in two separate phases called PRE-FFT and POST-FFT synchronization. Regarding the PRE-FFT phase, a novel joint symbol timing and carrier frequency synchronization algorithm has been presented. The proposed algorithm is characterized by a very low hardware complexity, and, at the same time, it guarantees very good performance in in both AWGN and multipath channels. Regarding the POST-FFT phase, a novel approach for both pilot structure and receiver design has been presented. In particular, a novel pilot pattern has been introduced in order to minimize the occurrence of overlaps between two pattern shifted replicas. This allows to replace conventional pilots with nulls in the frequency domain, introducing the so called Silent Pilots. As a result, the optimal receiver turns out to be very robust against severe Rayleigh fading multipath and characterized by low complexity. Performance of this approach has been analytically and numerically evaluated. Comparing the proposed approach with state of the art alternatives, in both AWGN and multipath fading channels, considerable performance improvements have been obtained. The crucial problem of channel estimation has been thoroughly investigated, with particular emphasis on the decimation of the Channel Impulse Response (CIR) through the selection of the Most Significant Samples (MSSs). In this contest our contribution is twofold, from the theoretical side, we derived lower bounds on the estimation mean-square error (MSE) performance for any MSS selection strategy,from the receiver design we proposed novel MSS selection strategies which have been shown to approach these MSE lower bounds, and outperformed the state-of-the-art alternatives. Finally, the possibility of using of Single Carrier Frequency Division Multiple Access (SC-FDMA) in the Broadband Satellite Return Channel has been assessed. Notably, SC-FDMA is able to improve the physical layer spectral efficiency with respect to single carrier systems, which have been used so far in the Return Channel Satellite (RCS) standards. However, it requires a strict synchronization and it is also sensitive to phase noise of local radio frequency oscillators. For this reason, an effective pilot tone arrangement within the SC-FDMA frame, and a novel Joint Multi-User (JMU) estimation method for the SC-FDMA, has been proposed. As shown by numerical results, the proposed scheme manages to satisfy strict synchronization requirements and to guarantee a proper demodulation of the received signal.

Digitale Einstrahl-Holographie atmosphärischer Eiskristalle

Es wurde ein für bodengebundene Feldmessungen geeignetes System zur digital-holographischen Abbildung luftgetragener Objekte entwickelt und konstruiert. Es ist, abhängig von der Tiefenposition, geeignet zur direkten Bestimmung der Größe luftgetragener Objekte oberhalb von ca. 20 µm, sowie ihrer Form bei Größen oberhalb von ca. 100µm bis in den Millimeterbereich. Die Entwicklung umfaßte zusätzlich einen Algorithmus zur automatisierten Verbesserung der Hologrammqualität und zur semiautomatischen Entfernungsbestimmung großer Objekte entwickelt. Eine Möglichkeit zur intrinsischen Effizienzsteigerung der Bestimmung der Tiefenposition durch die Berechnung winkelgemittelter Profile wurde vorgestellt. Es wurde weiterhin ein Verfahren entwickelt, das mithilfe eines iterativen Ansatzes für isolierte Objekte die Rückgewinnung der Phaseninformation und damit die Beseitigung des Zwillingsbildes erlaubt. Weiterhin wurden mithilfe von Simulationen die Auswirkungen verschiedener Beschränkungen der digitalen Holographie wie der endlichen Pixelgröße untersucht und diskutiert. Die geeignete Darstellung der dreidimensionalen Ortsinformation stellt in der digitalen Holographie ein besonderes Problem dar, da das dreidimensionale Lichtfeld nicht physikalisch rekonstruiert wird. Es wurde ein Verfahren entwickelt und implementiert, das durch Konstruktion einer stereoskopischen Repräsentation des numerisch rekonstruierten Meßvolumens eine quasi-dreidimensionale, vergrößerte Betrachtung erlaubt. Es wurden ausgewählte, während Feldversuchen auf dem Jungfraujoch aufgenommene digitale Hologramme rekonstruiert. Dabei ergab sich teilweise ein sehr hoher Anteil an irregulären Kristallformen, insbesondere infolge massiver Bereifung. Es wurden auch in Zeiträumen mit formal eisuntersättigten Bedingungen Objekte bis hinunter in den Bereich ≤20µm beobachtet. Weiterhin konnte in Anwendung der hier entwickelten Theorie des ”Phasenrandeffektes“ ein Objekt von nur ca. 40µm Größe als Eisplättchen identifiziert werden. Größter Nachteil digitaler Holographie gegenüber herkömmlichen photographisch abbildenden Verfahren ist die Notwendigkeit der aufwendigen numerischen Rekonstruktion. Es ergibt sich ein hoher rechnerischer Aufwand zum Erreichen eines einer Photographie vergleichbaren Ergebnisses. Andererseits weist die digitale Holographie Alleinstellungsmerkmale auf. Der Zugang zur dreidimensionalen Ortsinformation kann der lokalen Untersuchung der relativen Objektabstände dienen. Allerdings zeigte sich, dass die Gegebenheiten der digitalen Holographie die Beobachtung hinreichend großer Mengen von Objekten auf der Grundlage einzelner Hologramm gegenwärtig erschweren. Es wurde demonstriert, dass vollständige Objektgrenzen auch dann rekonstruiert werden konnten, wenn ein Objekt sich teilweise oder ganz außerhalb des geometrischen Meßvolumens befand. Weiterhin wurde die zunächst in Simulationen demonstrierte Sub-Bildelementrekonstruktion auf reale Hologramme angewandt. Dabei konnte gezeigt werden, dass z.T. quasi-punktförmige Objekte mit Sub-Pixelgenauigkeit lokalisiert, aber auch bei ausgedehnten Objekten zusätzliche Informationen gewonnen werden konnten. Schließlich wurden auf rekonstruierten Eiskristallen Interferenzmuster beobachtet und teilweise zeitlich verfolgt. Gegenwärtig erscheinen sowohl kristallinterne Reflexion als auch die Existenz einer (quasi-)flüssigen Schicht als Erklärung möglich, wobei teilweise in Richtung der letztgenannten Möglichkeit argumentiert werden konnte. Als Ergebnis der Arbeit steht jetzt ein System zur Verfügung, das ein neues Meßinstrument und umfangreiche Algorithmen umfaßt. S. M. F. Raupach, H.-J. Vössing, J. Curtius und S. Borrmann: Digital crossed-beam holography for in-situ imaging of atmospheric particles, J. Opt. A: Pure Appl. Opt. 8, 796-806 (2006) S. M. F. Raupach: A cascaded adaptive mask algorithm for twin image removal and its application to digital holograms of ice crystals, Appl. Opt. 48, 287-301 (2009) S. M. F. Raupach: Stereoscopic 3D visualization of particle fields reconstructed from digital inline holograms, (zur Veröffentlichung angenommen, Optik - Int. J. Light El. Optics, 2009)

Coordination and Control of Autonomous Mobile Robots Swarms by using Particle Swarm Optimization Algorithm and Consensus Theory

This thesis presents some different techniques designed to drive a swarm of robots in an a-priori unknown environment in order to move the group from a starting area to a final one avoiding obstacles. The presented techniques are based on two different theories used alone or in combination: Swarm Intelligence (SI) and Graph Theory. Both theories are based on the study of interactions between different entities (also called agents or units) in Multi- Agent Systems (MAS). The first one belongs to the Artificial Intelligence context and the second one to the Distributed Systems context. These theories, each one from its own point of view, exploit the emergent behaviour that comes from the interactive work of the entities, in order to achieve a common goal. The features of flexibility and adaptability of the swarm have been exploited with the aim to overcome and to minimize difficulties and problems that can affect one or more units of the group, having minimal impact to the whole group and to the common main target. Another aim of this work is to show the importance of the information shared between the units of the group, such as the communication topology, because it helps to maintain the environmental information, detected by each single agent, updated among the swarm. Swarm Intelligence has been applied to the presented technique, through the Particle Swarm Optimization algorithm (PSO), taking advantage of its features as a navigation system. The Graph Theory has been applied by exploiting Consensus and the application of the agreement protocol with the aim to maintain the units in a desired and controlled formation. This approach has been followed in order to conserve the power of PSO and to control part of its random behaviour with a distributed control algorithm like Consensus.

Decomposition Methods and Network Design Problems

Decomposition based approaches are recalled from primal and dual point of view. The possibility of building partially disaggregated reduced master problems is investigated. This extends the idea of aggregated-versus-disaggregated formulation to a gradual choice of alternative level of aggregation. Partial aggregation is applied to the linear multicommodity minimum cost flow problem. The possibility of having only partially aggregated bundles opens a wide range of alternatives with different trade-offs between the number of iterations and the required computation for solving it. This trade-off is explored for several sets of instances and the results are compared with the ones obtained by directly solving the natural node-arc formulation. An iterative solution process to the route assignment problem is proposed, based on the well-known Frank Wolfe algorithm. In order to provide a first feasible solution to the Frank Wolfe algorithm, a linear multicommodity min-cost flow problem is solved to optimality by using the decomposition techniques mentioned above. Solutions of this problem are useful for network orientation and design, especially in relation with public transportation systems as the Personal Rapid Transit. A single-commodity robust network design problem is addressed. In this, an undirected graph with edge costs is given together with a discrete set of balance matrices, representing different supply/demand scenarios. The goal is to determine the minimum cost installation of capacities on the edges such that the flow exchange is feasible for every scenario. A set of new instances that are computationally hard for the natural flow formulation are solved by means of a new heuristic algorithm. Finally, an efficient decomposition-based heuristic approach for a large scale stochastic unit commitment problem is presented. The addressed real-world stochastic problem employs at its core a deterministic unit commitment planning model developed by the California Independent System Operator (ISO).

A multi-objective genetic algorithm optimisation using variable speed pumps in water distribution systems

Due to its practical importance and inherent complexity, the optimisation of distribution networks for supplying drinking water has been the subject of extensive study for the past 30 years. The optimization is governed by sizing the pipes in the water distribution network (WDN) and / or optimises specific parts of the network such as pumps, tanks etc. or try to analyse and optimise the reliability of a WDN. In this thesis, the author has analysed two different WDNs (Anytown City and Cabrera city networks), trying to solve and optimise a multi-objective optimisation problem (MOOP). The main two objectives in both cases were the minimisation of Energy Cost (€) or Energy consumption (kWh), along with the total Number of pump switches (TNps) during a day. For this purpose, a decision support system generator for Multi-objective optimisation used. Its name is GANetXL and has been developed by the Center of Water System in the University of Exeter. GANetXL, works by calling the EPANET hydraulic solver, each time a hydraulic analysis has been fulfilled. The main algorithm used, was a second-generation algorithm for multi-objective optimisation called NSGA_II that gave us the Pareto fronts of each configuration. The first experiment that has been carried out was the network of Anytown city. It is a big network with a pump station of four fixed speed parallel pumps that are boosting the water dynamics. The main intervention was to change these pumps to new Variable speed driven pumps (VSDPs), by installing inverters capable to diverse their velocity during the day. Hence, it’s been achieved great Energy and cost savings along with minimisation in the number of pump switches. The results of the research are thoroughly illustrated in chapter 7, with comments and a variety of graphs and different configurations. The second experiment was about the network of Cabrera city. The smaller WDN had a unique FS pump in the system. The problem was the same as far as the optimisation process was concerned, thus, the minimisation of the energy consumption and in parallel the minimisation of TNps. The same optimisation tool has been used (GANetXL).The main scope was to carry out several and different experiments regarding a vast variety of configurations, using different pump (but this time keeping the FS mode), different tank levels, different pipe diameters and different emitters coefficient. All these different modes came up with a large number of results that were compared in the chapter 8. Concluding, it should be said that the optimisation of WDNs is a very interested field that has a vast space of options to deal with. This includes a large number of algorithms to choose from, different techniques and configurations to be made and different support system generators. The researcher has to be ready to “roam” between these choices, till a satisfactory result will convince him/her that has reached a good optimisation point.

Spectral estimates and preconditioning for saddle point systems arising from optimization problems

In this thesis, we consider the problem of solving large and sparse linear systems of saddle point type stemming from optimization problems. The focus of the thesis is on iterative methods, and new preconditioning srategies are proposed, along with novel spectral estimtates for the matrices involved.

Multi-modal diffeomorphic demons registration based on point-wise mutual information

In this paper we propose a variational approach for multimodal image registration based on the diffeomorphic demons algorithm. Diffeomorphic demons has proven to be a robust and efficient way for intensity-based image registration. However, the main drawback is that it cannot deal with multiple modalities. We propose to replace the standard demons similarity metric (image intensity differences) by point-wise mutual information (PMI) in the energy function. By comparing the accuracy between our PMI based diffeomorphic demons and the B-Spline based free-form deformation approach (FFD) on simulated deformations, we show the proposed algorithm performs significantly better.

On a Microcomputer Implementation of an Intrusion-detection Algorithm

The main objective of this paper is to discuss various aspects of implementing a specific intrusion-detection scheme on a micro-computer system using fixed-point arithmetic. The proposed scheme is suitable for detecting intruder stimuli which are in the form of transient signals. It consists of two stages: an adaptive digital predictor and an adaptive threshold detection algorithm. Experimental results involving data acquired via field experiments are also included.

Bayesian change-point analysis in linear regression model with scale mixtures of normal distributions

In this thesis, we consider Bayesian inference on the detection of variance change-point models with scale mixtures of normal (for short SMN) distributions. This class of distributions is symmetric and thick-tailed and includes as special cases: Gaussian, Student-t, contaminated normal, and slash distributions. The proposed models provide greater flexibility to analyze a lot of practical data, which often show heavy-tail and may not satisfy the normal assumption. As to the Bayesian analysis, we specify some prior distributions for the unknown parameters in the variance change-point models with the SMN distributions. Due to the complexity of the joint posterior distribution, we propose an efficient Gibbs-type with Metropolis- Hastings sampling algorithm for posterior Bayesian inference. Thereafter, following the idea of [1], we consider the problems of the single and multiple change-point detections. The performance of the proposed procedures is illustrated and analyzed by simulation studies. A real application to the closing price data of U.S. stock market has been analyzed for illustrative purposes.

Walking near a conformal fixed point

We investigate the 2-d O(3) model with a q-term as a toy model for slowly walking 4-d non-Abelian gauge theories. Using the very efficient meron-cluster algorithm, an accurate investigation of the scale dependence of the renormalized coupling is carried out for different values of the vacuum angle q. Approaching q = p, the infrared dynamics of the 2-d O(3) model is determined by a non-trivial conformal fixed point. We provide evidence for a slowly walking behavior near the fixed point and we perform a finite-size scaling analysis of the mass gap.

Coronary artery stents: influence of adaptive statistical iterative reconstruction on image quality using 64-HDCT

OBJECTIVE: The assessment of coronary stents with present-generation 64-detector row computed tomography (HDCT) scanners is limited by image noise and blooming artefacts. We evaluated the performance of adaptive statistical iterative reconstruction (ASIR) for noise reduction in coronary stent imaging with HDCT. METHODS AND RESULTS: In 50 stents of 28 patients (mean age 64 ± 10 years) undergoing coronary CT angiography (CCTA) on an HDCT scanner the mean in-stent luminal diameter, stent length, image quality, in-stent contrast attenuation, and image noise were assessed. Studies were reconstructed using filtered back projection (FBP) and ASIR-FBP composites. ASIR resulted in reduced image noise vs. FBP (P < 0.0001). Two readers graded the CCTA stent image quality on a 4-point Likert scale and determined the proportion of interpretable stent segments. The best image quality for all clinical images was obtained with 40 and 60% ASIR with significantly larger luminal area visualization compared with FBP (+42.1 ± 5.4% with 100% ASIR vs. FBP alone; P < 0.0001) while the stent length was decreased (-4.7 ± 0.9%,

Detecting outlying studies in meta-regression models using a forward search algorithm.

When considering data from many trials, it is likely that some of them present a markedly different intervention effect or exert an undue influence on the summary results. We develop a forward search algorithm for identifying outlying and influential studies in meta-analysis models. The forward search algorithm starts by fitting the hypothesized model to a small subset of likely outlier-free studies and proceeds by adding studies into the set one-by-one that are determined to be closest to the fitted model of the existing set. As each study is added to the set, plots of estimated parameters and measures of fit are monitored to identify outliers by sharp changes in the forward plots. We apply the proposed outlier detection method to two real data sets; a meta-analysis of 26 studies that examines the effect of writing-to-learn interventions on academic achievement adjusting for three possible effect modifiers, and a meta-analysis of 70 studies that compares a fluoride toothpaste treatment to placebo for preventing dental caries in children. A simple simulated example is used to illustrate the steps of the proposed methodology, and a small-scale simulation study is conducted to evaluate the performance of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.

Developing a point-of-care electronic medical record system for TB/HIV co-infected patients: experiences from Lighthouse Trust, Lilongwe, Malawi.

BACKGROUND Implementation of user-friendly, real-time, electronic medical records for patient management may lead to improved adherence to clinical guidelines and improved quality of patient care. We detail the systematic, iterative process that implementation partners, Lighthouse clinic and Baobab Health Trust, employed to develop and implement a point-of-care electronic medical records system in an integrated, public clinic in Malawi that serves HIV-infected and tuberculosis (TB) patients. METHODS Baobab Health Trust, the system developers, conducted a series of technical and clinical meetings with Lighthouse and Ministry of Health to determine specifications. Multiple pre-testing sessions assessed patient flow, question clarity, information sequencing, and verified compliance to national guidelines. Final components of the TB/HIV electronic medical records system include: patient demographics; anthropometric measurements; laboratory samples and results; HIV testing; WHO clinical staging; TB diagnosis; family planning; clinical review; and drug dispensing. RESULTS Our experience suggests that an electronic medical records system can improve patient management, enhance integration of TB/HIV services, and improve provider decision-making. However, despite sufficient funding and motivation, several challenges delayed system launch including: expansion of system components to include of HIV testing and counseling services; changes in the national antiretroviral treatment guidelines that required system revision; and low confidence to use the system among new healthcare workers. To ensure a more robust and agile system that met all stakeholder and user needs, our electronic medical records launch was delayed more than a year. Open communication with stakeholders, careful consideration of ongoing provider input, and a well-functioning, backup, paper-based TB registry helped ensure successful implementation and sustainability of the system. Additional, on-site, technical support provided reassurance and swift problem-solving during the extended launch period. CONCLUSION Even when system users are closely involved in the design and development of an electronic medical record system, it is critical to allow sufficient time for software development, solicitation of detailed feedback from both users and stakeholders, and iterative system revisions to successfully transition from paper to point-of-care electronic medical records. For those in low-resource settings, electronic medical records for integrated care is a possible and positive innovation.