Power system parameters forecasting using Hilbert-Huang transform and machine learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.

Purification, crystallization and preliminary X-ray diffraction studies of a complex between G protein-coupled receptor kinase 2 and Gbeta1gamma2.

G protein-coupled receptor kinase 2 (GRK2) phosphorylates activated G protein-coupled receptors (GPCRs), which ultimately leads to their desensitization and/or downregulation. The enzyme is recruited to the plasma membrane via the interaction of its carboxyl-terminal pleckstrin-homology (PH) domain with the beta and gamma subunits of heterotrimeric G proteins (Gbetagamma). An improved purification scheme for GRK2 has been developed, conditions under which GRK2 forms a complex with Gbeta(1)gamma(2) have been determined and the complex has been crystallized in CHAPS detergent micelles. Crystals of the GRK2-Gbetagamma complex belong to space group C2 and have unit-cell parameters a = 187.0, b = 72.1, c = 122.0 A, beta = 115.2 degrees. A complete data set has been collected to 3.2 A resolution with Cu Kalpha radiation.

Domain decomposition using a 2-level correction scheme

The PHYSICA software was developed to enable multiphysics modelling allowing for interaction between Computational Fluid Dynamics (CFD) and Computational Solid Mechanics (CSM) and Computational Aeroacoustics (CAA). PHYSICA uses the finite volume method with 3-D unstructured meshes to enable the modelling of complex geometries. Many engineering applications involve significant computational time which needs to be reduced by means of a faster solution method or parallel and high performance algorithms. It is well known that multigrid methods serve as a fast iterative scheme for linear and nonlinear diffusion problems. This papers attempts to address two major issues of this iterative solver, including parallelisation of multigrid methods and their applications to time dependent multiscale problems.

Entanglement between two superconducting qubits via interaction with nonclassical radiation

We propose a scheme to physically interface superconducting nanocircuits and quantum optics. We address the transfer of quantum information between systems having different physical natures and defined in Hilbert spaces of different dimensions. In particular, we investigate the transfer of the entanglement initially in a nonclassical state of an infinite dimensional system to a pair of superconducting charge qubits. This setup is able to drive an initially separable state of the qubits into an almost pure, highly entangled state suitable for quantum information processing.

Prediction- and simulation-error based perceptron training: Solution space analysis and a novel combined training scheme

Previous papers have noted the difficulty in obtaining neural models which are stable under simulation when trained using prediction-error-based methods. Here the differences between series-parallel and parallel identification structures for training neural models are investigated. The effect of the error surface shape on training convergence and simulation performance is analysed using a standard algorithm operating in both training modes. A combined series-parallel/parallel training scheme is proposed, aiming to provide a more effective means of obtaining accurate neural simulation models. Simulation examples show the combined scheme is advantageous in circumstances where the solution space is known or suspected to be complex. (c) 2006 Elsevier B.V. All rights reserved.

A Novel Multilocus Sequence Typing Scheme for the Opportunistic Pathogen Propionibacterium acnes and Characterisation of Type I Cell Surface-Associated Antigens.

We have developed a novel Multilocus Sequence Typing Scheme (MLST) and database (http://pubmlst.org/pacnes/) for Propionibacterium acnes based on the analysis of seven core housekeeping genes. The scheme, which was validated against previously described antibody, single locus and Random Amplification of Polymorphic DNA (RAPD) typing methods, displayed excellent resolution and differentiated 123 isolates into 37 sequence types (ST). An overall clonal population structure was detected with six eBURST groups representing the major clades I, II and III, along with two singletons. Two highly successful and global clonal lineages, ST6 (type IA) and ST10 (type IB1), representing 65% of this current MLST isolate collection were identified. The ST6 clone and closely related single locus variants (SLV), which comprise a large clonal complex CC6, dominated isolates from patients with acne, and were also significantly associated with ophthalmic infections. Our data therefore supports an association between acne and P. acnes strains from the type IA cluster and highlights the role of a widely disseminated clonal genotype in this condition. Characterisation of type I cell surface-associated antigens that are not detected in ST10 or strains of type II and III identified two dermatan-sulphate-binding proteins with putative phase/antigenic variation signatures. We propose that the expression of these proteins by type IA organisms contributes to their role in the pathophysiology of acne and helps explain the recurrent nature of the disease. The MLST scheme and database described in this study should provide a valuable platform for future epidemiological and evolutionary studies of P. acnes.

A scheme for entanglement extraction from a solid

Some thermodynamical properties of solids, such as heat capacity and magnetic susceptibility, have recently been shown to be linked to the amount of entanglement in a solid. However, this entanglement may appear a mere mathematical artefact of the typical symmetrization procedure of many-body wavefunction in solid state physics. Here we show that this entanglement is physical, demonstrating the principles of its extraction from a typical solid-state system by scattering two particles off the system. Moreover, we show how to simulate this process using present day optical lattice technology. This demonstrates not only that entanglement exists in solids but also that it can be used for quantum information processing or as a test of Bell's inequalities.

AN INJECTOR AMPLIFIER DOUBLE TARGET CONFIGURATION FOR THE NE-LIKE GE X-RAY LASER SCHEME

The XUV lasing output from one germanium slab target has been efficiently coupled into, and further amplified in, a second plasma produced by irradiation of a similar target from the opposite direction. The operation of such a double target was shown to be strongly dependent on the distance by which the two target surfaces were displaced. The line brightness peaked for a surface displacement of approximately 200-mu-m and it was observed that the pointing direction of one output beam could be controlled by the surface separation in an asymmetric geometry. Gain length products of approximately 16 with estimated output powers close to the megawatt level were achieved on both the 23.2 and 23.6 nm J=2-1 transitions for an optimised target configuration. Maximum effective coupling efficiencies of the individual outputs from double targets, comprising 2.2 and 1.4 cm length components, approached 100% for beams propagating from the shorter to the longer target.

Experimental studies of the advanced fast ignitor scheme

Guided compression offers an attractive route to explore some of the physics issues of hot electron heating and transport in the fast ignition route to inertial confinement fusion, whilst avoiding the difficulties associated with establishing the stability of the channel formation pulse. X-ray images are presented that show that the guided foil remains hydrodynamically stable during the acceleration phase, which is confirmed by two-dimensional simulations. An integrated conical compression/fast electron heating experiment is presented that confirms that this approach deserves detailed study. (C) 2000 American Institute of Physics. [S1070-664X(00)02809-3].