Transporting jobs through a two-machine open shop

We consider the two-machine open shop scheduling problem in which the jobs are brought to the system by a single transporter and moved between the processing machines by the same transporter. The purpose is to split the jobs into batches and to find the sequence of moves of the transporter so that the time by which the completed jobs are collected together on board the transporter is minimal. We present a 7/5-approximation algorithm. © 2008 Wiley Periodicals, Inc. Naval Research Logistics 2009

Single machine scheduling and due date assignment with positionally dependent processing times

We consider single machine scheduling and due date assignment problems in which the processing time of a job depends on its position in a processing sequence. The objective functions include the cost of changing the due dates, the total cost of discarded jobs that cannot be completed by their due dates and, possibly, the total earliness of the scheduled jobs. We present polynomial-time dynamic programming algorithms in the case of two popular due date assignment methods: CON and SLK. The considered problems are related to mathematical models of cooperation between the manufacturer and the customer in supply chain scheduling.

Ghost/Machine: cinema in a digital age

Cinema, with its passive cinematic apparatus and linear narrative is often characterised as a contrast to new media narrative strategies, yet from Vertov’s Man with a Movie Camera to Mike Figgis’ TimeCode and Wong Kar Wei’s 2046 cinema provides narrative strategies and spatial conceptualisations which prefigure or are contiguous with new media environments. Both our perception of what cyberspace constitutes and the technology that actualises those perceptions arise out of and are driven by fantasy and desire. This paper will explore the metaphors used to represent and understand new media aesthetics through cinematic representations of new media environments. Two key themes relevant to new media aesthetics emerge. Irigaray, Haraway, and Grosz are used to explore the de-essentialising haptic and penetrative potential of new technologies and their ability to collapse the boundary between the body and the machine. The second fantasy, of new media as a liminal space that expresses the memorialising function of technology and its relation to mourning, is analysed using Benjamin, Burgin and Rutsky. These altered spaces and perceptions of the body and memory of the post-cinematic subject are illustrated through an analysis of Gondry’s Eternal Sunshine of the Spotless Mind and Jonze’s Being John Malkovich. [From the Author]

Effect of machine dependence on wall failure property measurements, Jenike versus an annular shear tester

Annular, ring or torsional shear testers are commonly used in bulk solids handling research for the purpose of powder characterisation or equipment design. This paper reports from a DEFRA sponsored project which aims to develop an industrial powder flow-ability tester, (based on the annular shear tester) that is economic to buy and quick and easy to use in trained but unskilled hands. This paper compares the wall failure loci measured with an annular shear cell with measurements obtained using the accepted standard wall friction tester, the Jenike shear cell. These wall failure loci have been measured for several bulk solids which range from fine cohesive powders to free-flowing granular materials, on a stainless steel 304 2B wall surface.

A Competence-Based Course Authoring Concept for Learning Platforms with Legacy Assignment Tools

This paper is concerned with several of the most important aspects of Competence-Based Learning (CBL): course authoring, assignments, and categorization of learning content. The latter is part of the so-called Bologna Process (BP) and can effectively be supported by integrating knowledge resources like, e.g., standardized skill and competence taxonomies into the target implementation approach, aiming at making effective use of an open integration architecture while fostering the interoperability of hybrid knowledge-based e-learning solutions. Modern scenarios ask for interoperable software solutions to seamlessly integrate existing e-learning infrastructures and legacy tools with innovative technologies while being cognitively efficient to handle. In this way, prospective users are enabled to use them without learning overheads. At the same time, methods of Learning Design (LD) in combination with CBL are getting more and more important for production and maintenance of easy to facilitate solutions. We present our approach of developing a competence-based course-authoring and assignment support software. It is bridging the gaps between contemporary Learning Management Systems (LMS) and established legacy learning infrastructures by embedding existing resources via Learning Tools Interoperability (LTI). Furthermore, the underlying conceptual architecture for this integration approach will be explained. In addition, a competence management structure based on knowledge technologies supporting standardized skill and competence taxonomies will be introduced. The overall goal is to develop a software solution which will not only flawlessly merge into a legacy platform and several other learning environments, but also remain intuitively usable. As a proof of concept, the so-called platform independent conceptual architecture model will be validated by a concrete use case scenario.

Channel Catchments Cluster. Recent developments in tools and techniques for water quality management in the France (Channel) England region

The Channel Catchments Cluster (3C) aims to capitalise on outputs from some of the recent projects funded through the INTERREG IVa France (Channel) England programme. The river catchment basins draining into the Channel region drain an area of 137,000km2 and support a human population of over 19M. Throughout history, these catchments, rivers and estuaries have been centres of habitation, developed through commerce and industry, providing transport links to hinterland areas. These catchments also provide drinking water and food through provision of agriculture, fisheries and aquaculture. In addition, many parts of the region are also economically important now for the tourism and leisure industries. Consequently, there is a need to manage the balance of these many and varied human activities within the catchments, rivers, estuaries and marine areas to ensure that they are maintained or restored to good environmental condition . This document highlights some of the recent work carried out by projects within the INTERREG IVa programme that provide tools and techniques to assist in the achievement of these goals.

Channel Catchments Cluster: Compendium of Tools

Although the narrow stretch of water that separates England from France has seen both welcome (and occasionally less welcome) exchanges during the past thousand years, this physical challenge to the movement of people has certainly served to obstruct collaborative efforts that might establish a more sustainable economy in our part of Europe. Since 2009, the European Regional Development Fund (ERDF)-supported Interreg Programme France (Channel) England Region has actively supported efforts by organisations in France and England to work ever more closely together, to share good practice and to devise new ways to support sustainable development in the Region. The initiatives are certainly rooted in excellent research, but they have also been driven by the real needs of the Region and in all cases partners have worked to develop practical tools that can be readily applied in both France and England. The Channel Catchment Cluster (3C) builds on this growing tradition of cross-border cooperation to bring together the very best new knowledge from recent Anglo-French teamwork. The contents of this Compendium are the result of a wide variety of grass-roots initiatives that have benefitted enormously from a cross-border meeting of minds. The Cluster has brought together several of these cross-border teams to discuss their work and to share good practice in the dissemination and application of novel tools for environmental protection. This Compendium therefore not only presents a 'snapshot' of the wide variety of environmental protection and management tools that have emerged from the France (Channel) England Region, it also summarises where they stand on their 'pathway to impact'. There is clearly much more that can be achieved by future cross-border efforts in our Region, but I believe that this Compendium provides an excellent basis for future action. Professor Huw Taylor University of Brighton UK

Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species

The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.