Dynamic coast control of train movement with genetic algorithm

The railway service is now the major transportation means in most of the countries around the world. With the increasing population and expanding commercial and industrial activities, a high quality of railway service is the most desirable. Train service usually varies with the population activities throughout a day and train coordination and service regulation are then expected to meet the daily passengers' demand. Dwell time control at stations and fixed coasting point in an inter-station run are the current practices to regulate train service in most metro railway systems. However, a flexible and efficient train control and operation is not always possible. To minimize energy consumption of train operation and make certain compromises on the train schedule, coast control is an economical approach to balance run-time and energy consumption in railway operation if time is not an important issue, particularly at off-peak hours. The capability to identify the starting point for coasting according to the current traffic conditions provides the necessary flexibility for train operation. This paper presents an application of genetic algorithms (GA) to search for the appropriate coasting point(s) and investigates the possible improvement on fitness of genes. Single and multiple coasting point control with simple GA are developed to attain the solutions and their corresponding train movement is examined. Further, a hierarchical genetic algorithm (HGA) is introduced here to identify the number of coasting points required according to the traffic conditions, and Minimum-Allele-Reserve-Keeper (MARK) is adopted as a genetic operator to achieve fitter solutions.

Lateral shearing interferometry, dynamic wavefront sensing, and high-speed videokeratoscopy for noninvasive assessment of tear film surface characteristics : a comparitive study

There are several noninvasive techniques for assessing the kinetics of tear film, but no comparative studies have been conducted to evaluate their efficacies. Our aim is to test and compare techniques based on high-speed videokeratoscopy (HSV), dynamic wavefront sensing (DWS), and lateral shearing interferometry (LSI). Algorithms are developed to estimate the tear film build-up time TBLD, and the average tear film surface quality in the stable phase of the interblink interval TFSQAv. Moderate but significant correlations are found between TBLD measured with LSI and DWS based on vertical coma (Pearson's r2=0.34, p<0.01) and higher order rms (r2=0.31, p<0.01), as well as between TFSQAv measured with LSI and HSV (r2=0.35, p<0.01), and between LSI and DWS based on the rms fit error (r2=0.40, p<0.01). No significant correlation is found between HSV and DWS. All three techniques estimate tear film build-up time to be below 2.5 sec, and they achieve a remarkably close median value of 0.7 sec. HSV appears to be the most precise method for measuring tear film surface quality. LSI appears to be the most sensitive method for analyzing tear film build-up.

Development of a composite line source emission model for traffic interrupted microenvironments and its application in particle number emissions at a bus station

A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.

Structural health monitoring of bridges : source localisation in acoustic emission technique

Managing the sustainability of urban infrastructure requires regular health monitoring of key infrastructure such as bridges. The process of structural health monitoring involves monitoring a structure over a period of time using appropriate sensors, extracting damage sensitive features from the measurements made by the sensors, and analysing these features to determine the current state of the structure. Various techniques are available for structural health monitoring of structures, and acoustic emission is one technique that is finding an increasing use in the monitoring of civil infrastructures such as bridges. Acoustic emission technique is based on the recording of stress waves generated by rapid release of energy inside a material, followed by analysis of recorded signals to locate and identify the source of emission and assess its severity. This chapter first provides a brief background of the acoustic emission technique and the process of source localization. Results from laboratory experiments conducted to explore several aspects of the source localization process are also presented. The findings from the study can be expected to enhance knowledge of the acoustic emission process, and to aid the development of effective bridge structure diagnostics systems.

The dynamic processes of visual, corporate, and organisational identity : an exploratory study

The purpose of this study is to contribute to the cross-disciplinary body of literature of identity and organisational culture. This study empirically investigated the Hatch and Schultz (2002) Organisational Identity Dynamics (OID) model to look at linkages between identity, image, and organisational culture. This study used processes defined in the OID model as a theoretical frame by which to understand the relationships between actual and espoused identity manifestations across visual identity, corporate identity, and organisational identity. The linking processes of impressing, mirroring, reflecting, and expressing were discussed at three unique levels in the organisation. The overarching research question of How does the organisational identity dynamics process manifest itself in practice at different levels within an organisation? was used as a means of providing empirical understanding to the previously theoretical OID model. Case study analysis was utilised to provide exploratory data across the organisational groups of: Level A - Senior Marketing and Corporate Communications Management, Level B - Marketing and Corporate Communications Staff, and Level C - Non-Marketing Managers and Employees. Data was collected via 15 in-depth interviews with documentary analysis used as a supporting mechanism to provide triangulation in analysis. Data was analysed against the impressing, mirroring, reflecting, and expressing constructs with specific criteria developed from literature to provide a detailed analysis of each process. Conclusions revealed marked differences in the ways in which OID processes occurred across different levels with implications for the ways in which VI, CI, and OI interact to develop holistic identity across organisational levels. Implications for theory detail the need to understand and utilise cultural understanding in identity programs as well as the value in developing identity communications which represent an actual rather than an espoused position.

High bandwidth voltage and current control design for voltage source converters

In this paper, two different high bandwidth converter control strategies are discussed. One of the strategies is for voltage control and the other is for current control. The converter, in each of the cases, is equipped with an output passive filter. For the voltage controller, the converter is equipped with an LC filter, while an output has an LCL filter for current controller. The important aspect that has been discussed the paper is to avoid computation of unnecessary references using high-pass filters in the feedback loop. The stability of the overall system, including the high-pass filters, has been analyzed. The choice of filter parameters is crucial for achieving desirable system performance. In this paper, the bandwidth of achievable performance is presented through frequency (Bode) plot of the system gains. It has been illustrated that the proposed controllers are capable of tracking fundamental frequency components along with low-order harmonic components. Extensive simulation results are presented to validate the control concepts presented in the paper.

Channel-aware routing in MANETs with route handoff

In wireless mobile ad hoc networks (MANETs), packet transmission is impaired by radio link fluctuations. This paper proposes a novel channel adaptive routing protocol which extends the Ad-hoc On-Demand Multipath Distance Vector routing protocol (AOMDV) to accommodate channel fading. Specifically, the proposed Channel Aware AOMDV (CA-AOMDV) uses the channel average non-fading duration as a routing metric to select stable links for path discovery, and applies a preemptive handoff strategy to maintain reliable connections by exploiting channel state information. Using the same information, paths can be reused when they become available again, rather than being discarded. We provide new theoretical results for the downtime and lifetime of a live-die-live multiple path system, as well as detailed theoretical expressions for common network performance measures, providing useful insights into the differences in performance between CA-AOMDV and AOMDV. Simulation and theoretical results show that CA-AOMDV has greatly improved network performance over AOMDV.

Source apportionment of fine particles at a suburban site in Queensland, Australia

Airborne fine particles were collected at a suburban site in Queensland, Australia between 1995 and 2003. The samples were analysed for 21 elements, and Positive Matrix Factorisation (PMF), Preference Ranking Organisation METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA) were applied to the data. PROMETHEE provided information on the ranking of pollutant levels from the sampling years while PMF provided insights into the sources of the pollutants, their chemical composition, most likely locations and relative contribution to the levels of particulate pollution at the site. PROMETHEE and GAIA found that the removal of lead from fuel in the area had a significant impact on the pollution patterns while PMF identified 6 pollution sources including: Railways (5.5%), Biomass Burning (43.3%), Soil (9.2%), Sea Salt (15.6%), Aged Sea Salt (24.4%) and Motor Vehicles (2.0%). Thus the results gave information that can assist in the formulation of mitigation measures for air pollution.

Source of concern for IT purchasing decisions

The open source juggernaut seems to be gaining pace. The open source model certainly has appeal - cutting costs, while at the same time potentially increasing staff and system efficiencies. However, open source poses a number of significant legal challenges and risks for those that incorporate it. Clients need to look carefully before leaping.

Fixed-wing attitude estimation using temporal tracking of the horizon and optical flow

In this paper, a method has been developed for estimating pitch angle, roll angle and aircraft body rates based on horizon detection and temporal tracking using a forward-looking camera, without assistance from other sensors. Using an image processing front-end, we select several lines in an image that may or may not correspond to the true horizon. The optical flow at each candidate line is calculated, which may be used to measure the body rates of the aircraft. Using an Extended Kalman Filter (EKF), the aircraft state is propagated using a motion model and a candidate horizon line is associated using a statistical test based on the optical flow measurements and the location of the horizon. Once associated, the selected horizon line, along with the associated optical flow, is used as a measurement to the EKF. To test the accuracy of the algorithm, two flights were conducted, one using a highly dynamic Uninhabited Airborne Vehicle (UAV) in clear flight conditions and the other in a human-piloted Cessna 172 in conditions where the horizon was partially obscured by terrain, haze and smoke. The UAV flight resulted in pitch and roll error standard deviations of 0.42◦ and 0.71◦ respectively when compared with a truth attitude source. The Cessna flight resulted in pitch and roll error standard deviations of 1.79◦ and 1.75◦ respectively. The benefits of selecting and tracking the horizon using a motion model and optical flow rather than naively relying on the image processing front-end is also demonstrated.

Persistent ocean monitoring with underwater gliders : towards accurate reconstruction of dynamic ocean processes

Ocean processes are dynamic and complex events that occur on multiple different spatial and temporal scales. To obtain a synoptic view of such events, ocean scientists focus on the collection of long-term time series data sets. Generally, these time series measurements are continually provided in real or near-real time by fixed sensors, e.g., buoys and moorings. In recent years, an increase in the utilization of mobile sensor platforms, e.g., Autonomous Underwater Vehicles, has been seen to enable dynamic acquisition of time series data sets. However, these mobile assets are not utilized to their full capabilities, generally only performing repeated transects or user-defined patrolling loops. Here, we provide an extension to repeated patrolling of a designated area. Our algorithms provide the ability to adapt a standard mission to increase information gain in areas of greater scientific interest. By implementing a velocity control optimization along the predefined path, we are able to increase or decrease spatiotemporal sampling resolution to satisfy the sampling requirements necessary to properly resolve an oceanic phenomenon. We present a path planning algorithm that defines a sampling path, which is optimized for repeatability. This is followed by the derivation of a velocity controller that defines how the vehicle traverses the given path. The application of these tools is motivated by an ongoing research effort to understand the oceanic region off the coast of Los Angeles, California. The computed paths are implemented with the computed velocities onto autonomous vehicles for data collection during sea trials. Results from this data collection are presented and compared for analysis of the proposed technique.

Multi-objective four-dimensional vehicle motion planning in large dynamic environments

This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.