Affine Toda systems coupled to matter fields

We investigate higher grading integrable generalizations of the affine Toda systems, where the flat connections defining the models take values in eigensubspaces of an integral gradation of an affine Kac-Moody algebra, with grades varying from l to -l (l > 1). The corresponding target space possesses nontrivial vacua and soliton configurations, which can be interpreted as particles of the theory, on the same footing as those associated to fundamental fields. The models can also be formulated by a hamiltonian reduction procedure from the so-called two-loop WZNW models. We construct the general solution and show the classes corresponding to the solitons. Some of the particles and solitons become massive when the conformal symmetry is spontaneously broken by a mechanism with an intriguing topological character and leading to a very simple mass formula. The massive fields associated to nonzero grade generators obey field equations of the Dirac type and may be regarded as matter fields. A special class of models is remarkable. These theories possess a U(1 ) Noether current, which, after a special gauge fixing of the conformal symmetry, is proportional to a topological current. This leads to the confinement of the matter field inside the solitons, which can be regarded as a one-dimensional bag model for QCD. These models are also relevant to the study of electron self-localization in (quasi-)one-dimensional electron-phonon systems.

USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS

Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been conducted to solve the problems underlying the middleware services of sensor networks, such as self-deployment, self-localization, and synchronization. With the provided middleware services, sensor networks have grown into a mature technology to be used as a detection and surveillance paradigm for many real-world applications. The individual sensors are small in size. Thus, they can be deployed in areas with limited space to make unobstructed measurements in locations where the traditional centralized systems would have trouble to reach. However, there are a few physical limitations to sensor networks, which can prevent sensors from performing at their maximum potential. Individual sensors have limited power supply, the wireless band can get very cluttered when multiple sensors try to transmit at the same time. Furthermore, the individual sensors have limited communication range, so the network may not have a 1-hop communication topology and routing can be a problem in many cases. Carefully designed algorithms can alleviate the physical limitations of sensor networks, and allow them to be utilized to their full potential. Graphical models are an intuitive choice for designing sensor network algorithms. This thesis focuses on a classic application in sensor networks, detecting and tracking of targets. It develops feasible inference techniques for sensor networks using statistical graphical model inference, binary sensor detection, events isolation and dynamic clustering. The main strategy is to use only binary data for rough global inferences, and then dynamically form small scale clusters around the target for detailed computations. This framework is then extended to network topology manipulation, so that the framework developed can be applied to tracking in different network topology settings. Finally the system was tested in both simulation and real-world environments. The simulations were performed on various network topologies, from regularly distributed networks to randomly distributed networks. The results show that the algorithm performs well in randomly distributed networks, and hence requires minimum deployment effort. The experiments were carried out in both corridor and open space settings. A in-home falling detection system was simulated with real-world settings, it was setup with 30 bumblebee radars and 30 ultrasonic sensors driven by TI EZ430-RF2500 boards scanning a typical 800 sqft apartment. Bumblebee radars are calibrated to detect the falling of human body, and the two-tier tracking algorithm is used on the ultrasonic sensors to track the location of the elderly people.

Towards Mapping of Rock Walls Using a UAV-Mounted 2D Laser Scanner in GPS Denied Environments

In geotechnical engineering, the stability of rock excavations and walls is estimated by using tools that include a map of the orientations of exposed rock faces. However, measuring these orientations by using conventional methods can be time consuming, sometimes dangerous, and is limited to regions of the exposed rock that are reachable by a human. This thesis introduces a 2D, simulated, quadcopter-based rock wall mapping algorithm for GPS denied environments such as underground mines or near high walls on surface. The proposed algorithm employs techniques from the field of robotics known as simultaneous localization and mapping (SLAM) and is a step towards 3D rock wall mapping. Not only are quadcopters agile, but they can hover. This is very useful for confined spaces such as underground or near rock walls. The quadcopter requires sensors to enable self localization and mapping in dark, confined and GPS denied environments. However, these sensors are limited by the quadcopter payload and power restrictions. Because of these restrictions, a light weight 2D laser scanner is proposed. As a first step towards a 3D mapping algorithm, this thesis proposes a simplified scenario in which a simulated 1D laser range finder and 2D IMU are mounted on a quadcopter that is moving on a plane. Because the 1D laser does not provide enough information to map the 2D world from a single measurement, many measurements are combined over the trajectory of the quadcopter. Least Squares Optimization (LSO) is used to optimize the estimated trajectory and rock face for all data collected over the length of a light. Simulation results show that the mapping algorithm developed is a good first step. It shows that by combining measurements over a trajectory, the scanned rock face can be estimated using a lower-dimensional range sensor. A swathing manoeuvre is introduced as a way to promote loop closures within a short time period, thus reducing accumulated error. Some suggestions on how to improve the algorithm are also provided.

Wireless Sensor Network Deployment

Wireless Sensor Networks (WSNs) are widely used for various civilian and military applications, and thus have attracted significant interest in recent years. This work investigates the important problem of optimal deployment of WSNs in terms of coverage and energy consumption. Five deployment algorithms are developed for maximal sensing range and minimal energy consumption in order to provide optimal sensing coverage and maximum lifetime. Also, all developed algorithms include self-healing capabilities in order to restore the operation of WSNs after a number of nodes have become inoperative. Two centralized optimization algorithms are developed, one based on Genetic Algorithms (GAs) and one based on Particle Swarm Optimization (PSO). Both optimization algorithms use powerful central nodes to calculate and obtain the global optimum outcomes. The GA is used to determine the optimal tradeoff between network coverage and overall distance travelled by fixed range sensors. The PSO algorithm is used to ensure 100% network coverage and minimize the energy consumed by mobile and range-adjustable sensors. Up to 30% - 90% energy savings can be provided in different scenarios by using the developed optimization algorithms thereby extending the lifetime of the sensor by 1.4 to 10 times. Three distributed optimization algorithms are also developed to relocate the sensors and optimize the coverage of networks with more stringent design and cost constraints. Each algorithm is cooperatively executed by all sensors to achieve better coverage. Two of our algorithms use the relative positions between sensors to optimize the coverage and energy savings. They provide 20% to 25% more energy savings than existing solutions. Our third algorithm is developed for networks without self-localization capabilities and supports the optimal deployment of such networks without requiring the use of expensive geolocation hardware or energy consuming localization algorithms. This is important for indoor monitoring applications since current localization algorithms cannot provide good accuracy for sensor relocation algorithms in such indoor environments. Also, no sensor redeployment algorithms, which can operate without self-localization systems, developed before our work.

Towards a controlled growth of self-assembled nanostructures: shaping, ordering and localization in Ge/Si heteroepitaxy.

The strain-induced self-assembly of suitable semiconductor pairs is an attractive natural route to nanofabrication. To bring to fruition their full potential for actual applications, individual nanostructures need to be combined into ordered patterns in which the location of each single unit is coupled with others and the surrounding environment. Within the Ge/Si model system, we analyze a number of examples of bottom-up strategies in which the shape, positioning, and actual growth mode of epitaxial nanostructures are tailored by manipulating the intrinsic physical processes of heteroepitaxy. The possibility of controlling elastic interactions and, hence, the configuration of self-assembled quantum dots by modulating surface orientation with the miscut angle is discussed. We focus on the use of atomic steps and step bunching as natural templates for nanodot clustering. Then, we consider several different patterning techniques which allow one to harness the natural self-organization dynamics of the system, such as: scanning tunneling nanolithography, focused ion beam and nanoindentation patterning. By analyzing the evolution of the dot assembly by scanning probe microscopy, we follow the pathway which leads to lateral ordering, discussing the thermodynamic and kinetic effects involved in selective nucleation on patterned substrates.

Self-consistent theory of localization in weakly disordered systems

An analytic treatment of localization in a weakly disordered system is presented for the case where the real lattice is approximated by a Cayley tree. Contrary to a recent assertion we find that the mobility edge moves inwards into the band as disorder increases from zero.

Towards Self-Learning Radio-Based Localization Systems

Location-awareness indoors will be an inseparable feature of mobile services/applications in future wireless networks. Its current ubiquitous availability is still obstructed by technological challenges and privacy issues. We propose an innovative approach towards the concept of indoor positioning with main goal to develop a system that is self-learning and able to adapt to various radio propagation environments. The approach combines estimation of propagation conditions, subsequent appropriate channel modelling and optimisation feedback to the used positioning algorithm. Main advantages of the proposal are decreased system set-up effort, automatic re-calibration and increased precision.

Preferential localization of self-stimulation sites in striosomes/patches in the rat striatum

Histological sections of the mammalian striatum reveal a “matrix” that is histochemically distinguishable from patches, or “striosomes”. The latter are cross sections of a compartment that consists primarily of tube-shaped structures radiating through the matrix. As a test of the hypothesis that the function of the striosome/patch compartment includes the mediation of behaviors related to reward, the present study examined electrical self-stimulation of the caudoputamen in rats with electrodes in either of the two compartments. Rats acquired and maintained bar-pressing responses that were contingent on stimulation through electrodes making contact with striosomes/patches more reliably than animals with electrodes terminating exclusively in the matrix. The results provide in vivo evidence that the striosome/patch compartment is functionally differentiated from the matrix compartment: Stimulation centered in or around the striosome/patch compartment but not in the matrix led to rapid acquisition of a new behavior.

Robust vision-based underwater homing using self-similar landmarks

Next-generation autonomous underwater vehicles (AUVs) will be required to robustly identify underwater targets for tasks such as inspection, localization, and docking. Given their often unstructured operating environments, vision offers enormous potential in underwater navigation over more traditional methods; however, reliable target segmentation often plagues these systems. This paper addresses robust vision-based target recognition by presenting a novel scale and rotationally invariant target design and recognition routine based on self-similar landmarks that enables robust target pose estimation with respect to a single camera. These algorithms are applied to an AUV with controllers developed for vision-based docking with the target. Experimental results show that the system performs exceptionally on limited processing power and demonstrates how the combined vision and controller system enables robust target identification and docking in a variety of operating conditions.

In planta localization and interactions of impatiens necrotic spot tospovirus proteins

Impatiens necrotic spot tospovirus (INSV) is a significant pathogen of ornamentals. The tripartite negative- and ambi-sense RNA genome encodes six proteins that are involved in cytoplasmic replication, movement, assembly, insect transmission and defence. To gain insight into the associations of these viral proteins, we determined their intracellular localization and interactions in living plant cells. Nucleotide sequences encoding the nucleoprotein N, non-structural proteins NSs and NSm, and glycoproteins Gn and Gc of a Kentucky isolate of INSV were amplified by RTPCR, cloned, sequenced and transiently expressed as fusions with autofluorescent proteins in leaf epidermal cells of Nicotiana benthamiana. All proteins accumulated at the cell periphery and co-localized with an endoplasmic reticulum marker. The Gc protein fusion also localized to the nucleus. N and NSm protein self-interactions and an NSm-N interaction were observed by using bimolecular fluorescence complementation. A tospovirus NSm homotypic interaction had not been reported previously.

A probabilistic approach to the problem of electron localization in disordered systems and sharpness of the mobility edge

By applying the theory of the asymptotic distribution of extremes and a certain stability criterion to the question of the domain of convergence in the probability sense, of the renormalized perturbation expansion (RPE) for the site self-energy in a cellularly disordered system, an expression has been obtained in closed form for the probability of nonconvergence of the RPE on the real-energy axis. Hence, the intrinsic mobility mu (E) as a function of the carrier energy E is deduced to be given by mu (E)= mu 0exp(-exp( mod E mod -Ec) Delta ), where Ec is a nominal 'mobility edge' and Delta is the width of the random site-energy distribution. Thus mobility falls off sharply but continuously for mod E mod >Ec, in contradistinction with the notion of an abrupt 'mobility edge' proposed by Cohen et al. and Mott. Also, the calculated electrical conductivity shows a temperature dependence in qualitative agreement with experiments on disordered semiconductors.

Intrinsic Electron localization in manganites

We mention here an unusual disorder effect in manganites, namely the ubiquitous hopping behavior for electron transport observed in them over a wide range of doping. We argue that the implied Anderson localization is intrinsic to manganites, because of the existence of polarons in them which are spatially localized, generally at random sites (unless there is polaron ordering). We have developed a microscopic two fluid lb model for manganites, where l denotes lattice site localized l polarons, and b denotes band electrons. Using this, and the self-consistent theory of localization, we show that the occupied b states are Anderson localized in a large range of doping due to the scattering of b electrons from l polarons. Numerical simulations which further include the effect of long range Coulomb interactions support this, as well the existence of a novel polaronic Coulomb glass. A consequence is the inevitable hopping behaviour for electron transport observed in doped insulating manganites.

Time-resolved photoluminescence spectra of self-assembled InAs/GaAs quantum dots

Two types of InAs self-assembled Quantum dots (QDs) were prepared by Molecular beam epitaxy. Atomic force microscopy (AFM) measurements showed that, compared to QDs grown on GaAs substrate, QDs grown on InGaAs layer has a significantly enhanced density. The short spacing (several nanometer) among QDs stimulates strong coupling and leads to a large red-shift of the 1.3 mu m photoluminescence (PL) peak. We study systematically the dependence of PL lifetime on the QDs size, density and temperature (1). We found that, below 50 K, the PL lifetime is insensitive to temperature, which is interpreted from the localization effects. As T increases, the PL lifetime increases, which can be explained from the competition between the carrier redistribution and thermal emission at higher temperature. The increase of carriers in QDs migrated from barriers and wetting layer (WL), and the redistribution of carriers among QDs enhance the PL lifetime as T increases. The thermal emission and non-radiative recombination have effects to reduce the PL lifetime at higher T. As a result, the radiative recombination lifetime is determined by the wave function overlapping of electrons and holes in QDs, and QDs with different densities have different PL lifetime dependence on the QDs size. (c) 2005 Elsevier B.V. All rights reserved.

Time-resolved photoluminescence spectra of self-assembled InAs/GaAs quantum dots

Two types of InAs self-assembled Quantum dots (QDs) were prepared by Molecular beam epitaxy. Atomic force microscopy (AFM) measurements showed that, compared to QDs grown on GaAs substrate, QDs grown on InGaAs layer has a significantly enhanced density. The short spacing (several nanometer) among QDs stimulates strong coupling and leads to a large red-shift of the 1.3 mu m photoluminescence (PL) peak. We study systematically the dependence of PL lifetime on the QDs size, density and temperature (1). We found that, below 50 K, the PL lifetime is insensitive to temperature, which is interpreted from the localization effects. As T increases, the PL lifetime increases, which can be explained from the competition between the carrier redistribution and thermal emission at higher temperature. The increase of carriers in QDs migrated from barriers and wetting layer (WL), and the redistribution of carriers among QDs enhance the PL lifetime as T increases. The thermal emission and non-radiative recombination have effects to reduce the PL lifetime at higher T. As a result, the radiative recombination lifetime is determined by the wave function overlapping of electrons and holes in QDs, and QDs with different densities have different PL lifetime dependence on the QDs size. (c) 2005 Elsevier B.V. All rights reserved.

Tuning the Exciton Binding Energies in Single Self-Assembled InGaAs/GaAs Quantum Dots by Piezoelectric-Induced Biaxial Stress

We study the effect of an external biaxial stress on the light emission of single InGaAs/GaAs(001) quantum dots placed onto piezoelectric actuators. With increasing compression, the emission blueshifts and the binding energies of the positive trion (X+) and biexciton (XX) relative to the neutral exciton (X) show a monotonic increase. This phenomenon is mainly ascribed to changes in electron and hole localization and it provides a robust method to achieve color coincidence in the emission of X and XX, which is a prerequisite for the possible generation of entangled photon pairs via the recently proposed "time reordering'' scheme.