Canals in Milky Way radio polarization maps

Narrow depolarized canals are common in maps of the polarized synchrotron emission of the Milky Way. Two physical effects that can produce these canals have been identified: the presence of Faraday rotation measure (\RM) gradients in a foreground screen and the cumulative cancellation of polarization known as differential Faraday rotation. We show that the behaviour of the Stokes parameters $Q$ and $U$ in the vicinity of a canal can be used to identify its origin. In the case of canals produced by a Faraday screen we demonstrate that, if the polarization angle changes by 90\degr across the canal, as is observed in all fields to-date, the gradients in \RM must be discontinuous. Shocks are an obvious source of such discontinuities and we derive a relation of the expected mean separation of canals to the abundance and Mach number of supernova driven shocks, and compare this with recent observations by \citet{Haverkorn03}. We also predict the existence of less common canals with polarization angle changes other than 90\degr. Differential Faraday rotation can produce canals in a uniform magneto-ionic medium, but as the emitting layer becomes less uniform the canals will disappear. We show that for moderate differences in emissivity in a two-layer medium, of up to 1/2, and for Faraday depth fluctuations of standard deviation $\lesssim 1 \mathrm{rad}$, canals produced by differential rotation will still be visible.Comment: Accepted for publication in MNRAS Letters. 5 pages, 3 figure

Depolarization canals and interstellar turbulence

Recent radio polarization observations have revealed a plethora of unexpected features in the polarized Galactic radio background that arise from propagation effects in the random (turbulent) interstellar medium. The canals are especially striking among them, a random network of very dark, narrow regions clearly visible in many directions against a bright polarized Galactic synchrotron background. There are no obvious physical structures in the ISM that may have caused the canals, and so they have been called Faraday ghosts. They evidently carry information about interstellar turbulence but only now is it becoming clear how this information can be extracted. Two theories for the origin of the canals have been proposed; both attribute the canals to Faraday rotation, but one invokes strong gradients in Faraday rotation in the sky plane (specifically, in a foreground Faraday screen) and the other only relies on line-of-sight effects (differential Faraday rotation). In this review we discuss the physical nature of the canals and how they can be used to explore statistical properties of interstellar turbulence. This opens studies of magnetized interstellar turbulence to new methods of analysis, such as contour statistics and related techniques of computational geometry and topology. In particular, we can hope to measure such elusive quantities as the Taylor microscale and the effective magnetic Reynolds number of interstellar MHD turbulence.Comment: 20 pages, 8 figures. Contribution to the proceedings of the conference 'Polarization 2005', September 12 to 15, Orsay, France. Replaced one figure, changed three figure caption

Magnetic field tomography, helical magnetic fields and Faraday depolarization

Wide-band radio polarization observations offer the possibility to recover information about the magnetic fields in synchrotron sources, such as details of their three-dimensional configuration, that has previously been inaccessible. The key physical process involved is the Faraday rotation of the polarized emission in the source (and elsewhere along the wave's propagation path to the observer). In order to proceed, reliable methods are required for inverting the signals observed in wavelength space into useful data in Faraday space, with robust estimates of their uncertainty. In this paper, we examine how variations of the intrinsic angle of polarized emission $\psi_{0}$ with the Faraday depth $\phi$ within a source affect the observable quantities. Using simple models for the Faraday dispersion $F(\phi)$ and $\psi_{0}(\phi)$, along with the current and planned properties of the main radio interferometers, we demonstrate how degeneracies among the parameters describing the magneto-ionic medium can be minimised by combining observations in different wavebands. We also discuss how depolarization by Faraday dispersion due to a random component of the magnetic field attenuates the variations in the spectral energy distribution of the polarization and shifts its peak towards shorter wavelengths. This additional effect reduces the prospect of recovering the characteristics of the magnetic field helicity in magneto-ionic media dominated by the turbulent component of the magnetic field.Comment: Published: 2014, MNRAS 441, 2049. 9 pages, 5 figures. Major changes since previous version: added section 2.4 (Spectral dependence) and section 3.2 and appendix (Faraday dispersion

Probability distribution functions of gas in M31 and M51

We present probability distribution functions (PDFs) of the surface densities of ionized and neutral gas in the nearby spiral galaxies M31 and M51, as well as of dust emission and extinction Av in M31. The PDFs are close to lognormal and those for HI and Av in M31 are nearly identical. However, the PDFs for H2 are wider than the HI PDFs and the M51 PDFs have larger dispersions than those for M31. We use a simple model to determine how the PDFs are changed by variations in the line-of-sight (LOS) pathlength L through the gas, telescope resolution and the volume filling factor of the gas, f_v. In each of these cases the dispersion sigma of the lognormal PDF depends on the variable with a negative power law. We also derive PDFs of mean LOS volume densities of gas components in M31 and M51. Combining these with the volume density PDFs for different components of the ISM in the Milky Way (MW), we find that sigma decreases with increasing length L with an exponent of -0.76 +/- 0.06, which is steeper than expected. We show that the difference is due to variations in f_v. As f_v is similar in M31, M51 and the MW, the density structure in the gas in these galaxies must be similar. Finally, we demonstrate that an increase in f_v with increasing distance to the Galactic plane explains the decrease in sigma with latitude of the PDFs of emission measure and FUV emission observed for the MW.Comment: 15 pages, 7 figures, 7 tables, accepted for publication in Monthly Notices of the Royal Astronomical Societ

Novelty detection in video surveillance using hierarchical neural networks

Abstract. A hierarchical self-organising neural network is described for the detection of unusual pedestrian behaviour in video-based surveillance systems. The system is trained on a normal data set, with no prior information about the scene under surveillance, thereby requiring minimal user input. Nodes use a trace activation rule and feedforward connections, modified so that higher layer nodes are sensitive to trajectory segments traced across the previous layer. Top layer nodes have binary lateral connections and corresponding “novelty accumulator” nodes. Lateral connections are set between co-occurring nodes, generating a signal to prevent accumulation of the novelty measure along normal sequences. In abnormal sequences the novelty accumulator nodes are allowed to increase their activity, generating an alarm state

Maintenance Strategies to Reduce Downtime Due to Machine Positional Errors

Manufacturing strives to reduce waste and increase Overall Equipment Effectiveness (OEE). When managing machine tool maintenance a manufacturer must apply an appropriate decision technique in order to reveal hidden costs associated with production losses, reduce equipment downtime competently and similarly identify the machines’ performance. Total productive maintenance (TPM) is a maintenance program that involves concepts for maintaining plant and equipment effectively. OEE is a powerful metric of manufacturing performance incorporating measures of the utilisation, yield and efficiency of a given process, machine or manufacturing line. It supports TPM initiatives by accurately tracking progress towards achieving “perfect production.” This paper presents a review of maintenance management methodologies and their application to positional error calibration decision-making. The purpose of this review is to evaluate the contribution of maintenance strategies, in particular TPM, towards improving manufacturing performance, and how they could be applied to reduce downtime due to inaccuracy of the machine. This is to find a balance between predictive calibration, on-machine checking and lost production due to inaccuracy. This work redefines the role of maintenance management techniques and develops a framework to support the process of implementing a predictive calibration program as a prime method to supporting the change of philosophy for machine tool calibration decision making. Keywords—maintenance strategies, down time, OEE, TPM, decision making, predictive calibration

A Preliminary Study of Applying Lean Six Sigma Methods to Machine Tool Measurement

Many manufacturers aim to increase their levels of high-quality production in order to improve their market competitiveness. Continuous improvement of maintenance strategies is a key factor to be capable of delivering high quality products and services on-time with minimal operating costs. However, the cost of maintaining quality is often perceived as a non-added-value task. Improving the efficiency and effectiveness of the measurement procedures necessary to guarantee accuracy of production is a more complex task than many other maintenance functions and so deserves particular analysis. This paper investigates the feasibility of producing a concise yet effective framework that will provide a preliminary approach for integrating Lean and Six Sigma philosophies to the specific goal of reducing unnecessary downtime on manufacturing machines while maintaining its ability to machine to the required tolerance. The purpose of this study is to show how a Six Sigma infrastructure is used to investigate the root causes of complication occurring during the machine tool measurement. This work recognises issues of the uncertainty of data, and the measurement procedures in parallel with the main tools of Six Sigma’s Define-Measure-Analyse-Improve-Control (DMAIC). The significance of this work is that machine tool accuracy is critical for high value manufacturing. Over-measuring the machine to ensure accuracy potentially reduces production volume. However, not measuring them or ignoring accuracy aspects possibly lead to production waste. This piece of work aims to present a lean guidance to lessen measurement uncertainties and optimise the machine tool benchmarking procedures, while adopting the DMAIC strategy to reduce unnecessary downtime

A novel approach for ANFIS modelling based on Grey system theory for thermal error compensation

The fast and accurate modelling of thermal errors in machining is an important aspect for the implementation of thermal error compensation. This paper presents a novel modelling approach for thermal error compensation on CNC machine tools. The method combines the Adaptive Neuro Fuzzy Inference System (ANFIS) and Grey system theory to predict thermal errors in machining. Instead of following a traditional approach, which utilises original data patterns to construct the ANFIS model, this paper proposes to exploit Accumulation Generation Operation (AGO) to simplify the modelling procedures. AGO, a basis of the Grey system theory, is used to uncover a development tendency so that the features and laws of integration hidden in the chaotic raw data can be sufficiently revealed. AGO properties make it easier for the proposed model to design and predict. According to the simulation results, the proposed model demonstrates stronger prediction power than standard ANFIS model only with minimum number of training samples