Locating senior walking frame users in crowded indoor environments

University of Technology Sydney. Faculty of Engineering and Information Technology.This thesis presents a low cost indoor localization system, primarily intended for use by professional elder care supervisors for tracking elderly people in their excursions to a crowded shopping centre. The main requirement is that the system provides an approximate locations of multiple elderly people during an excursion to a crowded shopping centre. The residents are to use walking frames for locomotion, thus their motion is relatively slow and predictable. The resolution of localization is considered adequate if the care supervisor is able to locate a given person through visual contact relative to the estimated location. This thesis presents two novel localization methods that make use of these simplifying constraints and provides an industry strength implementation of one of these strategies. The first method described is an image based place recognition technique that employs the Bag of Words model for generating image descriptors and a three layer feedforward neural network for producing location estimates. Shop fronts and their corresponding neighbourhood areas are used as classes for training the neural network. The performance of this approach that was evaluated in a real shopping centre environment is presented. Although the system developed performs well, it was found to require the user cooperation in crowded areas and was deemed to have potential privacy concerns. An alternative solution, a Wi-Fi based indoor localization method is also presented. It estimates the current location of a subject using the Wi-Fi signal strengths received by a sensor module mounted on a walking frame. The environment is modelled as a collection of cells with sizes sufficiently small for locating a person through eye contact. A motion model, based on the knowledge of the floor plan of the environment is described. A probabilistic framework using the Bayes rule in combination with a Kernel Density method for estimating the probability density functions of received signal strengths at the cells is developed. The Wi-Fi based indoor localization method was implemented on a unit that measures strengths of Wi-Fi signals received from the access points present in an environment, computes the location and transmits it using the telephone network to a tablet held by a carer. An application on the tablet for visualizing the location of multiple walkers was also developed. The performance of this system was evaluated by conducting multiple trials, including a shopping centre excursion organized by a professional elder care provider named IRT. From the localization accuracies obtained through the test trials, it could be concluded that the presented Wi-Fi based localization method is adequate to fulfil the requirement of IRT, which is locating elderly people in a crowded indoor environment. It is also found that the floor plan based motion model enables the localization algorithm to produce reliable location estimates, given the relatively slow motion of elderly people

A hydrodynamic model for particle beam-driven plasmon wakefield in carbon nanotubes

Charged particles moving through a carbon nanotube may be used to excite electromagnetic modes in the electron gas produced by π and σ orbitals in the cylindrical graphene shell that makes up a nanotube wall [1]. This effect has recently been proposed as a potential novel method of short-wavelength-high-gradient particle acceleration [2, 3]. In this contribution, first we review the existing theory based on a linearised hydrodynamic model for a non-relativistic, localised point-charge propagating in a single wall nanotube (SWNT) [4]. Then we extend it to the relativistic case. In this hydrodynamic model the electron gas is treated as a plasma with additional contributions to the fluid momentum equation from specific solid- state properties of the gas. The governing set of differential equations is formed by the continuity and momentum equations for the involved species: beam charges, electrons and ions of the lattice. These equations are then coupled by Maxwell’s equations. The ions are assumed to be quasistatic and provide a neutralising background. To solve the differential equation system a modified Fourier-Bessel transform has been applied. Furthermore, a spectral analysis has been realised to determine the plasma modes able to excite a longitudinal electrical wakefield component in the SWNT to accelerate test charges. Eventually, we discuss the suitability and possible limitations of the method proposed in this study for particle acceleration

The Human Antibody Response to Dengue Virus Infection

Dengue viruses (DENV) are the causative agents of dengue fever (DF) and dengue hemorrhagic fever (DHF). Here we review the current state of knowledge about the human antibody response to dengue and identify important knowledge gaps. A large body of work has demonstrated that antibodies can neutralize or enhance DENV infection. Investigators have mainly used mouse monoclonal antibodies (MAbs) to study interactions between DENV and antibodies. These studies indicate that antibody neutralization of DENVs is a “multi-hit” phenomenon that requires the binding of multiple antibodies to neutralize a virion. The most potently neutralizing mouse MAbs bind to surface exposed epitopes on domain III of the dengue envelope (E) protein. One challenge facing the dengue field now is to extend these studies with mouse MAbs to better understand the human antibody response. The human antibody response is complex as it involves a polyclonal response to primary and secondary infections with 4 different DENV serotypes. Here we review studies conducted with immune sera and MAbs isolated from people exposed to dengue infections. Most dengue-specific antibodies in human immune sera are weakly neutralizing and bind to multiple DENV serotypes. The human antibodies that potently and type specifically neutralize DENV represent a small fraction of the total DENV-specific antibody response. Moreover, these neutralizing antibodies appear to bind to novel epitopes including complex, quaternary epitopes that are only preserved on the intact virion. These studies establish that human and mouse antibodies recognize distinct epitopes on the dengue virion. The leading theory proposed to explain the increased risk of severe disease in secondary cases is antibody dependent enhancement (ADE), which postulates that weakly neutralizing antibodies from the first infection bind to the second serotype and enhance infection of FcγR bearing myeloid cells such as monocytes and macrophages. Here we review results from human, animal and cell culture studies relevant to the ADE hypothesis. By understanding how human antibodies neutralize or enhance DENV, it will be possible to better evaluate existing vaccines and develop the next generation of novel vaccines

Virtual Synchronous Machine-based Power Control in Active Rectifiers for Micro Grids

This dissertation presents an analytical study on virtual synchronous machine-based power control in active rectifiers for micro grids supported by prototype modelling, simulation results and discussions.Popularity and demand of the distributed energy resources and renewable energy sources are increasing due to their economic and environmental friendliness. Concept of micro grid with an active rectifier (AR) interface has been found to be promising for smart integration of such distributed generation units. Having the presence of a synchronous generator (SG) in a micro grid introduces several advantages in terms of stability and reliability in the power system. This is mainly owed to the inertia, damping and load sharing properties of SG. This in return, gives rise to the question if an AR of a micro grid can imitate the behaviour of a synchronous generator, can the stability and reliability introduced by SG be replicated in a micro grid. A research on the state-of-the-art for uninterruptible power supplies (UPS) has been carried out to identify the implementation and the control strategies of redundancy and parallel operation as UPS has been an established technology over the last decades. The theoretical study on virtual synchronous machine (VSM) concept in the fall, 2011, has been extended in developing a model with classical inner current control and outer voltage control loops based on the synchronous reference frame.The complete active rectifier model has been able to emulate the inertia, damping and load sharing properties of a SG and redundancy and expandability of parallel UPS systems. It must be emphasized that due to the flexibility of the virtual machine parameters and the absence of magnetic saturation and eddy current losses, a much improved performance have been achieved with a VSM compared to a synchronous generator.Simulations have been carried out for single and parallel operation of active rectifiers in island and grid-tied modes with satisfactory stability, damping and power sharing features.Key words Active rectifier, virtual synchronous machine, micro grid, uninterruptible power supply, load sharing, redundancy, island mode, grid-tied mode, synchronous reference fram

A Framework and an Open-Loop Method to Identify PMSM Parameters Online

A method for online adaptation of electric parameters of a rotating machine is proposed herein. The concept adopts the recursive prediction error method (RPEM) for parameter adaptation, that exploits the prediction-error gradient functions (Ψ T ) With the aim of setting a general framework for the cause, the method is systematically demonstrated for online identification of permanent magnet flux linkage (Ψ m ) and stator-winding resistance (R s ) of an interior permanent magnet synchronous machine (IPMSM). Additionally, an experiment to estimate R s at the start-up is presented. The gain-matrix is identified using the stochastic gradient algorithm (SGA). Simulation results validate the rapid convergence performance, adaptability and tuning flexibility of the proposed method

Seeded Self-Modulation of Elliptical Beams in Plasma Wakefields

This thesis is concerned with investigating the effects of ellipticity on the seeded self-modulation process of long particle beams in plasma accelerators, and the implications for accelerated beams, using theoretical and computational models. Proton-driven plasma wakefield acceleration is a novel approach to plasma-based particle acceleration pioneered by the AWAKE experiment at CERN. The use of high-energy-content proton beams allows sustained high gradient (gigavolts per meter) plasma wakefields, allowing in principle, acceleration of witness beams over 10s or even 100s of meters. The scheme used at AWAKE relies on the seeded self-modulation (SSM) of long particle bunches, where the stability of the microbunch trains produced by SSM over tens or hundreds of meters is crucial for extrapolating this scheme as proposed for use in several high energy plasma-based linear colliders. Further, the uniformity and reproducibility of the resultant wakefields is essential for determining injection parameters and preservation of phase-space quality for witness beams during acceleration. Transverse asymmetry is often characteristic of synchrotron-generated beams. However, aside from the competing hosing instability, few works have examined other effects of transverse asymmetry in this process. In this thesis, analytical modelling and 3D particle-in-cell (PIC) simulations are used to characterise the impact on the SSM growth process and resultant wakefields due to elliptical transverse asymmetry in the beam. Metrics are constructed for quantifying the asymmetry of the evolving transverse beam profile in PIC simulations. Using these it is found that while beam asymmetry undergoes an order-of-magnitude increase during saturation of the SSM, the initial azimuthal complexity remains low and increases only slightly during the SSM growth stage. This allows the construction of a new analytical model for asymmetric SSM growth, from which a scaling for the reduction of the SSM growth rate with aspect ratio of the initial beam profile is obtained. A new method for estimating the SSM growth rate from simulations is developed, which allows these to be quantitatively verified. Finally, using heuristic knowledge of witness beam behaviour, the impact of azimuthal asymmetry of the longitudinal component of the wakefield on the final energy spread of an accelerated witness beam is estimated and found to be at most a few percent of the energy spread due to variation in a symmetric wakefield

Gauss-Newton: A prediction-error-gradient based algorithm to track PMSM parameters online

Online adaptation of temperature-sensitive motor parameters is of significance for the electric drives in reliability-critical applications. Recursive prediction error method (RPEM) is widely used for this purpose. Gauss-Newton Algorithm (GNA), a prediction-error-gradients based algorithm, is adopted in this paper to find RPEM-gains for the parameter identification. This paper first investigates the simultaneous identifiability of permanent magnet flux linkage ( Ψm), and stator resistance (Rs) of interior permanent magnet synchronous machine (IPMSM) using both nonlinear observability theorem and RPEM. Subsequently, GNA is analyzed for its tracking capability, speed of convergence, need of gain-scheduling and computational demand in comparison to stochastic gradient (SGA), another algorithm of the same class, using steady and dynamic state simulations

A Recursive Prediction Error Method with Effective Use of Gradient-Functions to Adapt PMSM-Parameters Online

This paper proposes a method for online estimation of electrical parameters of interior permanent magnet synchronous machines (IPMSM) based on the recursive prediction error method (RPEM). The parameter-sensitivity functions (herein known as the gradient functions, Ψ T ) both in dynamic and steady -states are exploited for this purpose. The RPEM has been computed using the stochastic gradient algorithm (SGA). The scalar Hessian matrix, r[k] appearing in the algorithm has been analyzed for both its steady and dynamic states. Different combinations of Ψ T and r[k] -states have been simulated and compared with respect to performance when used for parameter adaptation

Full Speed Range Sensorless IPMSM Drive Enhanced with Online Parameter Identification

This paper aims to combine the state-of-the-art parameter-adaptation and state-estimation techniques to realize an adaptive and sensorless interior permanent magnet synchronous machine (IPMSM) drive that offers robust performance across the full speed range even in the presence of temperature-variations. Recursive prediction error based Online Parameter Estimator (OPE) accompanied by a gain-scheduler adapts temperature-sensitive motor parameters, i.e. the stator resistance (R s ) and permanent magnet flux linkage ( Ψm) in the lower and higher speed regions respectively. The Active Flux Observer (AFO) and the Pulsating sqUare-wave Voltage Injection (PUVI) based saliency tracking method are adopted to estimate the rotor position in the higher and lower speed regions respectively. The OPE augments the performance of the AFO across a large part of the speed-range and the use of PUVI-based technique eliminates the potential precision-compromise of the estimated position due to the gain-scheduler in the low-speed region. Zynq System on Chip (SoC) based Embedded Real-Time Simulator (ERTS) is used to demonstrate the concepts, in which the drive control and estimation algorithms are programmed in its processor system and the drive hardware is modeled in its Field-Programmable Gate Array (FPGA)