The Mystery of Privity: Grand Trunk Railway Company of Canada v Robinson (1915)

This article examines a little known decision of the Judicial Committee of the Privy Council: Grand Trunk Railway Company of Canada v Robinson (1915). The examination is historical and it provides a different insight into the understanding of privity of contract, a doctrine central to contract law. The examination reveals a process of trans-Atlantic legal migration in which English law was applied to resolve an Ontario case. The nature of the resolution is surprising because it appears to conflict with the better known decision of the House of Lords, Dunlop Pneumatic Tyre Company, Limited v Selfridge and Company, Limited, which a similarly constituted panel delivered in the same week. This article argues that there was a greater malleability in the resolution of cases concerned with privity than was thought to have existed. It is also argued that the power of Canadian railway capitalism is a significant factor in understanding the legal resolution of the case. Finally, it the article considers the use of English and American precedents relevant to the case. The application of English precedents to the case led to a resolution not entirely befitting Canadian conditions.

The origins of small wars: from special operations to ideological insurgencies

This edited volume explores the origins of the term small wars and traces it to special operations. In the 17th century, such "guerrilla/petite guerre" special operations grew out of training and winter operations of the regular forces as practiced in the 16th century. In the 18th century, they fused with a tradition going back to Antiquity, of employing special ethnic groups (such as the Hungarian Hussars) for special operations. Side by side with these special operations, however, there was the even older genealogy of uprisings and insurgencies, which since the Spanish Guerrilla of 1808-1812 has been associated with this term. All three traditions have influenced each other.

Demonstrating distinction at ‘the lowest edge of the black-coated class’: the family expenditures of Edwardian railway clerks

Families at the bottom end of the Edwardian white-collar income spectrum demonstrated middle-class status through observable consumption, at the cost of squeezing other expenditures, including ‘necessities’. This had negative economic impacts, lowering living standards due to inefficiently high budget shares for positional goods. Drawing on the work of Pierre Bourdieu, we examine how railway clerks sought to demonstrate ‘distinction’ from manual workers through certain conspicuous expenditures and how this strategy was progressively undermined by falling real incomes over the Edwardian period.

Railway promotion in Victorian Britain: engineering triumph or waste of capital?

A key issue in UK railway history is whether the railway system was an efficient response to the traffic requirements of the economy. The UK railway system was constructed entirely by private enterprise with minimal state subsidies. This chapter considers whether the railway system was 'over-built' because the government ignored the advice of the Railway Committee of the Board of Trade. The chapter suggests that the system was over-built by about 35 per cent. The causes of this over-building are investigated and are found to be mainly social and political failures arising from distrust between MPs and civil servants and public pressure on local MPs to ensure that their constituencies were well served by railways.

Operations research/management science tools for integrating people with disabilities into employment. A study on Valencia`s Sheltered Work Centres for Disabled

People with disabilities have a right to a full life in every sense and one of those fundamental rights is the possibility to work. In this paper, the importance of social employment integration of disabled people is highlighted as one of the stakeholders to be satisfied by companies in the new framework that corporate social responsibility is constructing. The objective of the paper is to revise the benefits of some well-known operations research/management science tools that, if applied correctly, have a double positive impact on work accessibility and improved productivity. The responses collected from managers of Valencia`s ShelteredWork Centres for Disabled by means of a structured questionnaire are used to analyse the level of implementation of these tools and their impact depending on the type of centre, the kind of disability and other structural variables.

Simulation of Sawmill Yard Operations Using Software Agents

Bergkvist insjön AB is a sawmill yard which is capable of producing 350,000 cubic meter of timber every year this requires lot of internal resources. Sawmill operations can be classified as unloading, sorting, storage and production of timber. In the company we have trucks arriving at random they have to be unloaded and sent back at the earliest to avoid queuing up of trucks creating a problem for truck owners. The sawmill yard has to operate with two log stackers that does several tasks including transporting the logs from trucks to measurement station where the logs will be sorted into classes and dropped into pockets from pockets to the sorted timber yard where they are stored and finally from there to sawmill for final processing. The main issue that needs to be answered here is the lining up trucks that are waiting to be unload, creating a problem for both sawmill as well as the truck owners and given huge production volume, it is certain that handling of resources is top priority. A key challenge in handling of resources would be unloading of trucks and finding a way to optimize internal resources.To address this problem i have experimented on different ways of using internal resources, i have designed different cases, in case 1 we have both the log stackers working on sawmill and measurement station. The main objective of having this case is to make sawmill and measurement station to work all the time. Then in case 2, i have divided the work between both the log stackers, one log stacker will be working on sawmill and pocket_control and second log stacker will be working on measurement station and truck. Then in case 3 we have only one log stacker working on all the agents, this case was designed to reduce cost of production, as the experiment cannot be done in real-time due to operational cost, for this purpose simulation is used, preliminary investigation into simulation results suggested that case 2 is the best option has it reduced waiting time of trucks considerably when compared with other cases and it showed 50% increase in optimizing internal resources.

Multi-agent simulation of sawmill yard operations

This paper reports the findings of using multi-agent based simulation model to evaluate the sawmill yard operations within a large privately owned sawmill in Sweden, Bergkvist Insjön AB in the current case. Conventional working routines within sawmill yard threaten the overall efficiency and thereby limit the profit margin of sawmill. Deploying dynamic work routines within the sawmill yard is not readily feasible in real time, so discrete event simulation model has been investigated to be able to report optimal work order depending on the situations. Preliminary investigations indicate that the results achieved by simulation model are promising. It is expected that the results achieved in the current case will support Bergkvist-Insjön AB in making optimal decisions by deploying efficient work order in sawmill yard.

Real time video segmentation for recognising paint marks on bad wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are based on visual analysis. Machine vision based approach has been done to emulate the visual abilities of human operator to enable automation of the process. Through this process bad sleepers are identified, and a spot is marked on it with specific color (blue in the current case) on the rail so that the maintenance operators are able to identify the spot and replace the sleeper. The motive of this thesis is to help the operators to identify those sleepers which are marked by color (spots), using an “Intelligent Vehicle” which is capable of running on the track. Capturing video while running on the track and segmenting the object of interest (spot) through this vehicle; we can automate this work and minimize the human intuitions. The video acquisition process depends on camera position and source light to obtain fine brightness in acquisition, we have tested 4 different types of combinations (camera position and source light) here to record the video and test the validity of proposed method. A sequence of real time rail frames are extracted from these videos and further processing (depending upon the data acquisition process) is done to identify the spots. After identification of spot each frame is divided in to 9 regions to know the particular region where the spot lies to avoid overlapping with noise, and so on. The proposed method will generate the information regarding in which region the spot lies, based on nine regions in each frame. From the generated results we have made some classification regarding data collection techniques, efficiency, time and speed. In this report, extensive experiments using image sequences from particular camera are reported and the experiments were done using intelligent vehicle as well as test vehicle and the results shows that we have achieved 95% success in identifying the spots when we use video as it is, in other method were we can skip some frames in pre-processing to increase the speed of video but the segmentation results we reduced to 85% and the time was very less compared to previous one. This shows the validity of proposed method in identification of spots lying on wooden railway sleepers where we can compromise between time and efficiency to get the desired result.

Automating condition monitoring of vegetation on railway trackbeds and embankments

Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.