The challenge of high cube ISO containers for British rail freight operations

Rail freight activity in Britain has increased by almost 50% in the last ten years, with the movement of deep sea ISO containers between ports and inland terminals being a significant growth sector, with considerable further growth potential. High cube ISO containers have become more prevalent, posing a considerable challenge for rail freight operators since much of the rail network has insufficient loading gauge clearance to carry them on standard wagons. This paper investigates the extent to which rail currently handles high cube container movements to/from ports through the analysis of a representative survey of container trains in 2007. The incidence of high cube containers carried by services on gauge-cleared and non-gauge-cleared routes is identified to assess the extent to which a lack of gauge enhancement affects the movement by rail of high cube containers and to identify the impacts of the lack of gauge clearance on operating efficiency. The paper concludes with an evaluation of the likely consequences of the gauge enhancement schemes for which funding is now committed, assessing the extent to which they will reduce or remove the barriers associated with carrying high cube containers between ports and their hinterlands.

Water jet based autonomous surface vehicle for coastal waters operations

This paper presents the design of low cost, small autonomous surface vehicle for missions in the coastal waters and specifically for the challenging surf zone. The main objective of the vehicle design described in this paper is to address both the capability of operation at sea in relative challenging conditions and maintain a very low set of operational requirements (ease of deployment). This vehicle provides a first step towards being able to perform general purpose missions (such as data gathering or patrolling) and to at least in a relatively short distances to be able to be used in rescue operations (with very low handling requirements) such as carrying support to humans on the water. The USV is based on a commercially available fiber glass hull, it uses a directional waterjet powered by an electrical brushless motor for propulsion, thus without any protruding propeller reducing danger in rescue operations. Its small dimensions (1.5 m length) and weight allow versatility and ease of deployment. The vehicle design is described in this paper both from a hardware and software point of view. A characterization of the vehicle in terms of energy consumption and performance is provided both from test tank and operational scenario tests. An example application in search and rescue is also presented and discussed with the integration of this vehicle in the European ICARUS (7th framework) research project addressing the development and integration of robotic tools for large scale search and rescue operations.

Greener Golf Operations: A Comparative Case Study of Ontario Golf Courses Engaged in Environmental Sustainability Initiatives

This research explored environmental sustainability (ES) initiatives at five top-ranked Ontario golf courses that were members of the Audubon Cooperative Sanctuary Program for Golf (ACSP). Research Questions: (1) How are golf courses adapting to safeguard the natural environment? (2) Why or why not are golf courses moving to ES? and (3) What are the arising barriers to ES in golf and how can they be overcome; what role does communication play? Overall, the research was framed with an adaptation of the dimensions of convergence by Houlihan (2012), including the motives, inputs, implementation, momentum, and impact. Additionally, impression management and message framing constructs were utilized to address the issue of communicating ES initiatives. Data collection involved in-depth interviews, observations, and unobtrusive document collection. Environmental aspects of the examination were guided by the Canadian Standards Association (CSA) Requirements and Guidance for Organizers of Sustainable Events and Sustainable Sport and Event Toolkit (SSET).

Summary of Research Conducted by the Manufacturing Systems Team 1994-2002

The Manufacturing Systems team was one of the research teams within the Lean Aerospace Initiative (LAI) whose goal was to document, analyze and communicate the design attributes and relationships that lead to significant performance improvements in manufacturing systems in the defense aerospace industry. This report will provide an integrated record of this research using the Production Operations Transition to Lean Roadmap as its organizing framework.

From architecturology to architecturological research

This paper presents a genesis of the French research field of Architecturology, from its creation to the current researches developed from it, at ARIAM-LAREA (National School of Architecture of Paris-la-Villette Laboratory of modeling for computer aids of cognitive activity of conception). Architecturology has been thought at the creation of French Schools of Architecture that has been initiated with the French movement of 1968 May. Its major aim is to build specific knowledge on architecture for learning architecture. The first book of the beginnings of this scientific field is ���Sur l���espace architectural��� written by Ph. Boudon and published in 1971. It���s currently constituted with a scientific systemic language and a paradigm that help to explain cognitive activity of design named by it, conception. This scientific language has been published in ���Enseigner la conception architecturale: cours d���architecturologie��� written by Ph. Boudon, Ph. Deshayes, F. Pousin and F. Shatz, and published in 1994 and in 2000, in ���Echelle(s)��� published in 2002 and which gathers different articles of Ph. Boudon and, in different articles of the team of LAREA - Ph. Boudon, Ph. Deshayes, F. Pousin, F. Shatz and C. Lecourtois. From this scientific language and the paradigm of Architecturology, I develop methods for extending the field of knowledge of this point of view by doing researches in architecture. These methods are gathered into the concept of Applied Architecturology. In 2005, LAREA has merged with a research team interested in Computer Aided Design, named ARIAM. To create ARIAM-LAREA, we have built a new research program on Computer Aided Conception where we use Applied Architecturology for 1) producing new knowledge on implications of Computer in cognitive activity of design and 2) developing new software to Support some operations of conception. This paper exposes my current research work and three theses that I co-lead at ARIAMLAREA on this object.

Storm prediction research and its application to the oil/gas industry

The accurate prediction of storms is vital to the oil and gas sector for the management of their operations. An overview of research exploring the prediction of storms by ensemble prediction systems is presented and its application to the oil and gas sector is discussed. The analysis method used requires larger amounts of data storage and computer processing time than other more conventional analysis methods. To overcome these difficulties eScience techniques have been utilised. These techniques potentially have applications to the oil and gas sector to help incorporate environmental data into their information systems

MI(R,)G(R) and British Covert Operations, 1939-42

The Military Intelligence (Research) Department of the British War Office was tasked in 1940 with encouraging and supporting armed resistance in occupied Europe and the Axis-controlled Middle East. The major contention of this paper is that, in doing so, MI(R) performed a key role in British strategy in 1940-42 and in the development of what are now known as covert operations. MI(R) developed an organic, but coherent doctrine for such activity which was influential upon the Special Operations Executive (SOE) and its own sub-branch, G(R), which applied this doctrine in practice in East Africa and the Middle East in 1940-41. It was also here that a number of key figures in the development of covert operations and special forces first cut their teeth, the most notable being Major Generals Colin Gubbins and Orde Wingate.

Final report on research project PS2010, proof of concept of automated mapping of weeds in arable fields

Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).