Scheduling and Platforming Trains at Busy Complex Stations

We consider the problem of train planning or scheduling for large, busy, complex train stations, which are common in Europe and elsewhere, though not in North America. We develop the constraints and objectives for this problem, but these are too computationally complex to solve by standard combinatorial search or integer programming methods. Also, the problem is somewhat political in nature, that is, it does not have a clear objective function because it involves multiple train operators with conflicting interests. We therefore develop scheduling heuristics analogous to those successfully adopted by train planners using ''manual'' methods. We tested the model and algorithms by applying to a typical large station that exhibits most of the complexities found in practice. The results compare well with those found by traditional methods, and take account of cost and preference trade-offs not handled by those methods. With successive refinements, the algorithm eventually took only a few seconds to run, the time depending on the version of the algorithm and the scheduling problem. The scheduling models and algorithms developed and tested here can be used on their own, or as key components for a more general system for train scheduling for a rail line or network.Train scheduling for a busy station includes ensuring that there are no conflicts between several hundred trains per day going in and out of the station on intersecting paths from multiple in-lines and out-lines to multiple platforms, while ensuring that each train is allowed at least its minimum required headways, dwell time, turnaround time and trip time. This has to be done while minimizing (costs of) deviations from desired times, platforms or lines, allowing for conflicts due to through-platforms, dead-end platforms, multiple sub-platforms, and possible constraints due to infrastructure, safety or business policy.

Time signatures of impulsively generated coronal fast wave trains

Impulsively generated short-period fast magneto-acoustic wave trains, guided by solar and stellar coronal loops, are numerically modelled. In the developed stage of the evolution, the wave trains have a characteristic quasi-periodic signature. The quasi-periodicity results from the geometrical dispersion of the guided fast modes, determined by the transverse profile of the loop. A typical feature of the signature is a tadpole wavelet Spectrum: a narrow-spectrum tail precedes a broad-band head. The instantaneous period of the oscillations in the wave train decreases gradually with time. The period and the spectral amplitude evolution are shown to be determined by the steepness of the transverse density profile and the density contrast ratio in the loop. The propagating wave trains recently discovered with the Solar Eclipse Coronal Imaging System (SECIS) instrument are noted to have similar wavelet spectral features, which strengthens the interpretation of SECIS results as guided fast wave trains.

Postoperative residuial block after intermediate-acting neuromuscular blocking drugs

Summary The frequency and duration of postoperative residual neuromuscular block on arrival of 150 patients in the recovery ward following the use of vecuronium (n = 50), atracurium (n = 50) and rocuronium (n = 50) were recorded. Residual block was defined as a train-of-four ratio of 0.8 after arrival in the recovery ward were 9.2 [1-61], 6.9 [1-24] and 14.7 [1.5-83] min for the vecuronium, atracurium and rocuronium, respectively. None of the 10 patients who did not receive neuromuscular blocking drugs had train-of-four ratios

Neostigmine antagonism of rocuronium block during anesthesia with sevoflurane, isoflurane or propofol

Purpose: To examine the influence of continuing administration of sevoflurane or isoflurane during reversal of rocuronium induced neuromuscular block with neostigmine. Methods: One hundred and twenty patients, divided into three equal groups, were randomly allocated to maintenance of anesthesia with sevoflurane, isoflurane or propofol. Neuromuscular block was induced with rocuronium and monitored using train-of-four (TOF) stimulation of the ulnar nerve and recording the force of contraction of the adductor pollicis muscle. Neostigmine was administered when the first response in TOF had recovered to 25%. At this time the volatile agent administration was stopped or propofol dosage reduced in half the patients in each group (n = 20 in each group). The times to attain TOF ratio of 0.8, and the number of patients attaining this end point within 15 min were recorded. Results: The times (mean ± SD) to recovery of the TOF ratio to 0.8 were 12.0 ± 5.5 and 6.8 ± 2.3 min in the sevoflurane continued and sevoflurane stopped groups, 9.0 ± 8.3 and 5.5 ± 3.0 min in the isoflurane continued and isoflurane stopped groups, and 5.2 ± 2.8 and 4.7 ±1.5 min in the propofol continued and propofol stopped groups (P <0.5- 01). Only 9 and 15 patients in the sevoflurane and isoflurane continued groups respectively had attained a TOF ratio of 0.8 within 15 min (P <0.001 for sevoflurane). Conclusions: The continued administration of sevoflurane, and to a smaller extent isoflurane, results in delay in attaining adequate antagonism of rocuronium induced neuromuscular block.

Artificial Intelligence Model for Flowable Concrete Mixtures Used in Underwater Construction and Repair

This study explores using artificial neural networks to predict the rheological and mechanical properties of underwater concrete (UWC) mixtures and to evaluate the sensitivity of such properties to variations in mixture ingredients. Artificial neural networks (ANN) mimic the structure and operation of biological neurons and have the unique ability of self-learning, mapping, and functional approximation. Details of the development of the proposed neural network model, its architecture, training, and validation are presented in this study. A database incorporating 175 UWC mixtures from nine different studies was developed to train and test the ANN model. The data are arranged in a patterned format. Each pattern contains an input vector that includes quantity values of the mixture variables influencing the behavior of UWC mixtures (that is, cement, silica fume, fly ash, slag, water, coarse and fine aggregates, and chemical admixtures) and a corresponding output vector that includes the rheological or mechanical property to be modeled. Results show that the ANN model thus developed is not only capable of accurately predicting the slump, slump-flow, washout resistance, and compressive strength of underwater concrete mixtures used in the training process, but it can also effectively predict the aforementioned properties for new mixtures designed within the practical range of the input parameters used in the training process with an absolute error of 4.6, 10.6, 10.6, and 4.4%, respectively.

Feature Selection for Pose Invariant Lip Biometrics

For the first time in this paper the authors present results showing the effect of out of plane speaker head pose variation on a lip biometric based speaker verification system. Using appearance DCT based features, they adopt a Mutual Information analysis technique to highlight the class discriminant DCT components most robust to changes in out of plane pose. Experiments are conducted using the initial phase of a new multi view Audio-Visual database designed for research and development of pose-invariant speech and speaker recognition. They show that verification performance can be improved by substituting higher order horizontal DCT components for vertical, particularly in the case of a train/test pose angle mismatch.

Track displacement and energy loss in a railway embankment

The mainline railway track between Dublin and Belfast was constructed during the 1850s, with substantial lengths of railway embankment constructed over soft, peaty soils. In recent years Northern Ireland Railways (NIR) has noticed that the sections of the railway track constructed on these peaty soils have been deteriorating at an increasing rate. Train speeds have been reduced in response to concerns that cyclic track displacements appear to be increasing over time in response to train loading. Track maintenance has also increased significantly. The research described in this paper was undertaken to quantify the response to cyclic train loading of two portions of this track founded on peaty soils. Track displacements were recorded using a sensor system specifically created for this project. The sensor consisted of a photosensitive array, mounted on the sleepers, and a laser, which was targeted onto the photosensitive array from a location outside the area of influence of train loading. Track deflections from 5 to 20 mm were measured under train speeds from near zero to over 120 km/h. The temporal variation in track displacement was used to calibrate an analytical (Winkler) model. This analysis suggests that the deformation of the embankment under train loading was not due to dynamic excitation but rather to static deformation of the poor-quality fill and soft foundation materials. As a consequence, the analytical model highlighted that train speed has limited effect on the magnitude of the deflection of the embankment within NIR operating speeds, but has the potential to significantly reduce the power lost to the damping within the embankment and subgrade.

Neural Network Modeling of Rheological Parameters of Grouts Containing Viscosity-Modifying Agent

The development of artificial neural network (ANN) models to predict the rheological behavior of grouts is described is this paper and the sensitivity of such parameters to the variation in mixture ingredients is also evaluated. The input parameters of the neural network were the mixture ingredients influencing the rheological behavior of grouts, namely the cement content, fly ash, ground-granulated blast-furnace slag, limestone powder, silica fume, water-binder ratio (w/b), high-range water-reducing admixture, and viscosity-modifying agent (welan gum). The six outputs of the ANN models were the mini-slump, the apparent viscosity at low shear, and the yield stress and plastic viscosity values of the Bingham and modified Bingham models, respectively. The model is based on a multi-layer feed-forward neural network. The details of the proposed ANN with its architecture, training, and validation are presented in this paper. A database of 186 mixtures from eight different studies was developed to train and test the ANN model. The effectiveness of the trained ANN model is evaluated by comparing its responses with the experimental data that were used in the training process. The results show that the ANN model can accurately predict the mini-slump, the apparent viscosity at low shear, the yield stress, and the plastic viscosity values of the Bingham and modified Bingham models of the pseudo-plastic grouts used in the training process. The results can also predict these properties of new mixtures within the practical range of the input variables used in the training with an absolute error of 2%, 0.5%, 8%, 4%, 2%, and 1.6%, respectively. The sensitivity of the ANN model showed that the trend data obtained by the models were in good agreement with the actual experimental results, demonstrating the effect of mixture ingredients on fluidity and the rheological parameters with both the Bingham and modified Bingham models.

A Description of the Stationary Wave Pattern of a Marine Craft in Shallow and Intermediate Water Depths

A stationary phase model is used to study supercritical waves generated by high speed ferries. Some general relationships in terms of wave angle, propagation direction, dispersion relationship and depth wavelength relationship are explored and discussed. In particular, it is shown that the wave pattern generated by high speed craft at supercritical speeds depends mainly on the relationship of water depth and ship speed and that the wave patterns are similar in terms of location of crests and troughs for a given depth Froude number. In addition it is found that the far field wave pattern can be described adequately using a single moving point source. The theoretical model compares well with towing tank measurements and full scale data over a range of parameters and hull shapes. The paper also demonstrates that the far field wave pattern at supercritical speeds should be non-dimensionalised by water depth and not hull length unlike it is usually done for subcritical speeds.

Assessing and training standing balance in older adults: A novel approach using the 'Nintendo Wii' Balance Board

Older adults, deemed to be at a high risk of falling, are often unable to participate in dynamic exercises due to physical constraints and/or a fear of falling. Using the Nintendo 'Wii Balance Board' (WBB) (Nintendo, Kyoto, Japan), we have developed an interface that allows a user to accurately calculate a participant's centre of pressure (COP) and incorporate it into a virtual environment to create bespoke diagnostic or training programmes that exploit real-time visual feedback of current COP position. This platform allows researchers to design, control and validate tasks that both train and test balance function. This technology provides a safe, adaptable and low-cost balance training/testing solution for older adults, particularly those at high-risk of falling.

The Government – Voluntary Sector Compacts: Governance, Governmentality and Civil Society

In 1998 government and the main representatives of the voluntary sector in each of the four countries in the United Kingdom published "compacts" on relations between government and the voluntary sector. These were joint documents, carrying forward ideas expressed by the Labor Party when in opposition, and directed at developing a new relationship for partnership with those "not-for-profit organizations" that are involved primarily in the areas of policy and service delivery. This article seeks to use an examination of the compacts, and the processes that produced them and that they have now set in train, to explore some of the wider issues about the changing role of government and its developing relationships with civil society. In particular, it argues that the new partnership builds upon a movement from welfarism to economism which is being developed further through the compact process. Drawing upon a governmentality approach, and illustrating the account with interview material obtained from some of those involved in compact issues from within both government and those umbrella groups which represent the voluntary sector, an argument is made that this overall process represents the beginning of a new reconfiguration of the state that is of considerable constitutional significance.

Temporal characterization of attosecond pulses emitted from solid-density plasmas

The generation of high harmonics from solid-density plasmas promises the production of attosecond (as) pulses orders of magnitude brighter than those from conventional rare gas sources. However, while spatial and spectral emission of surface harmonics has been characterized in detail in many experiments proof that the harmonic emission is indeed phase locked and thus bunched in as-pulses has only been delivered recently (Nomura et al 2009 Nat. Phys. 5 124-8). In this paper, we discuss the experimental setup of our extreme ultraviolet (XUV) autocorrelation (AC) device in detail and show the first two-photon ionization and subsequent AC experiment using solid target harmonics. In addition, we describe a simple analytical model to estimate the chirp between the individual generated harmonics in the sub- and mildly relativistic regime and validate it using particle-in-cell (PIC) simulations. Finally, we propose several methods applicable to surface harmonics to extend the temporal pulse characterization to higher photon energies and for the reconstruction of the spectral phase between the individual harmonics. The experiments described in this paper prove unambiguously that harmonic emission from solid-density plasmas indeed occurs as a train of sub- femtosecond pulses and thus fulfills the most important property for a next-generation as-pulse source of unprecedented brightness.

Generation and control of ultrafast pulse trains for quasi-phase-matching high-harmonic generation

Two techniques are demonstrated to produce ultrashort pulse trains capable of quasi-phase-matching high-harmonic generation. The first technique makes use of an array of birefringent crystals and is shown to generate high-contrast pulse trains with constant pulse spacing. The second technique employs a grating-pair stretcher, a multiple-order wave plate, and a linear polarizer. Trains of up to 100 pulses are demonstrated with this technique, with almost constant inter-pulse separation. It is shown that arbitrary pulse separation can be achieved by introducing the appropriate dispersion. This principle is demonstrated by using an acousto-optic programmable dispersive filter to introduce third-and fourth-order dispersions leading to a linear and quadratic variation of the separation of pulses through the train. Chirped-pulse trains of this type may be used to quasi-phase-match high-harmonic generation in situations where the coherence length varies through the medium. (C) 2010 Optical Society of America

Simple technique for generating trains of ultrashort pulses

A simple method for generating trains of high-contrast femtosecond pulses is proposed and demonstrated: a linearly polarized, frequency-chirped laser pulse is passed through a multiple-order wave plate and a linear polarizer. It is shown theoretically that this arrangement forms a train of laser pulses, and in experiments the production of a train of approximately 100 pulses, each of 200 fs duration, is demonstrated. In combination with an acousto-optic programmable dispersive filter this technique could be used to generate and control pulse trains with chirped spacing. Pulse trains of this type have widespread applications in ultrafast optics. (C) 2007 Optical Society of America.

Automatic detection and classification of football players

Color segmentation of images usually requires a manual selection and classification of samples to train the system. This paper presents an automatic system that performs these tasks without the need of a long training, providing a useful tool to detect and identify figures. In real situations, it is necessary to repeat the training process if light conditions change, or if, in the same scenario, the colors of the figures and the background may have changed, being useful a fast training method. A direct application of this method is the detection and identification of football players.