Linearized large signal modeling, analysis, and control design of phase-controlled series-parallel resonant converters using state feedback

This paper proposes a linearized large signal state-space model for the fixed-frequency phase-controlled series-parallel resonant converter. The proposed model utilizes state feedback of the output filter inductor current to perform linearization. The model combines multiple-frequency and average state-space modeling techniques to generate an aggregate model with dc state variables that are relatively easier to control and slower than the fast resonant tank dynamics. The main objective of the linearized model is to provide a linear representation of the converter behavior under large signal variation which is suitable for faster simulation and large signal estimation/calculation of the converter state variables. The model also provides insight into converter dynamics as well as a simplified reduced order transfer function for PI closed-loop design. Experimental and simulation results from a detailed switched converter model are compared with the proposed state-space model output to verify its accuracy and robustness

Pseudo-Unitary Operators and Pseudo-Unitary Quantum Dynamics

We consider pseudo-unitary quantum systems and discuss various properties of pseudo-unitary operators. In particular we prove a characterization theorem for block-diagonalizable pseudo-unitary operators with finite-dimensional diagonal blocks. Furthermore, we show that every pseudo-unitary matrix is the exponential of $i=\sqrt{-1}$ times a pseudo-Hermitian matrix, and determine the structure of the Lie groups consisting of pseudo-unitary matrices. In particular, we present a thorough treatment of $2\times 2$ pseudo-unitary matrices and discuss an example of a quantum system with a $2\times 2$ pseudo-unitary dynamical group. As other applications of our general results we give a proof of the spectral theorem for symplectic transformations of classical mechanics, demonstrate the coincidence of the symplectic group $Sp(2n)$ with the real subgroup of a matrix group that is isomorphic to the pseudo-unitary group U(n,n), and elaborate on an approach to second quantization that makes use of the underlying pseudo-unitary dynamical groups.Comment: Revised and expanded version, includes an application to symplectic transformations and groups, accepted for publication in J. Math. Phy

Towards a virtual research environment for paediatric endocrinology across Europe

Paediatric endocrinology is a medical specialty dealing with variations of physical growth and sexual development in childhood. Genetic anomalies that can cause disorders of sexual development in children are rare. Given this, sharing and collaboration on the small number of cases that occur is needed by clinical experts in the field. The EU-funded EuroDSD project (www.eurodsd.eu) is one such collaboration involving clinical centres and clinical and genetic experts across Europe. Through the establishment of a virtual research environment (VRE) supporting sharing of data and a variety of clinical and bioinformatics analysis tools, EuroDSD aims to provide a research infrastructure for research into disorders of sex development. Security, ethics and information governance are at the heart of this infrastructure. This paper describes the infrastructure that is being built and the inherent challenges in security, availability and dependability that must be overcome for the enterprise to succeed

An Efficient Automatic Mass Classification Method In Digitized Mammograms Using Artificial Neural Network

In this paper we present an efficient computer aided mass classification method in digitized mammograms using Artificial Neural Network (ANN), which performs benign-malignant classification on region of interest (ROI) that contains mass. One of the major mammographic characteristics for mass classification is texture. ANN exploits this important factor to classify the mass into benign or malignant. The statistical textural features used in characterizing the masses are mean, standard deviation, entropy, skewness, kurtosis and uniformity. The main aim of the method is to increase the effectiveness and efficiency of the classification process in an objective manner to reduce the numbers of false-positive of malignancies. Three layers artificial neural network (ANN) with seven features was proposed for classifying the marked regions into benign and malignant and 90.91% sensitivity and 83.87% specificity is achieved that is very much promising compare to the radiologist's sensitivity 75%.Comment: 13 pages, 10 figure

Hyperbolic Metamaterial Resonator-Antenna Scheme for Large, Broadband Emission Enhancement and Single Photon Collection

We model the broadband enhancement of single-photon emission from color centres in silicon carbide nanocrystals coupled to a planar hyperbolic metamaterial, HMM resonator. The design is based on positioning the single photon emitters within the HMM resonator, made of a dielectric index-matched with silicon-carbide material. The broadband response results from the successive resonance peaks of the lossy Fabry Perot structure modes arising within the high-index HMM cavity. To capture this broadband enhancement in the single photon emitters spontaneous emission, we placed a simple gold based cylindrical antenna on top of the HMM resonator. We analyzed the performance of this HMM coupled antenna structure in terms of the Purcell enhancement, quantum efficiency, collection efficiency and overall collected photon rate. For perpendicular dipole orientation relative to the interface, the HMM coupled antenna resonator leads to a significantly large spontaneous emission enhancement with Purcell factor of the order of 250 along with a very high average total collected photon rate, CPR of about 30 over a broad emission spectrum, 700 nm to 1000 nm. The peak CPR increases to about 80 at 900 nm, corresponding to the emission of silicon-carbide quantum emitters. This is a state of the art improvement considering the previous computational designs have reported a maximum average CPR of 25 across the nitrogen-vacancy centre emission spectrum, 600 nm to 800 nm with the highest value being about 40 at 650 nm