Solving Functional Constraints by Variable Substitution

Functional constraints and bi-functional constraints are an important constraint class in Constraint Programming (CP) systems, in particular for Constraint Logic Programming (CLP) systems. CP systems with finite domain constraints usually employ CSP-based solvers which use local consistency, for example, arc consistency. We introduce a new approach which is based instead on variable substitution. We obtain efficient algorithms for reducing systems involving functional and bi-functional constraints together with other non-functional constraints. It also solves globally any CSP where there exists a variable such that any other variable is reachable from it through a sequence of functional constraints. Our experiments on random problems show that variable elimination can significantly improve the efficiency of solving problems with functional constraints

Hybrid energy sources for electric and fuel cell vehicle propulsion

Given the energy (and hence range) and performance limitations of electro-chemical batteries, hybrid systems combining energy and power dense storage technologies have been proposed for electric vehicle propulsion. The paper will discuss the application of electro-chemical batteries, supercapacitors and fuel cells in single and hybrid source configurations for electric vehicle drive-train applications. Simulation models of energy sources are presented and used to investigate the design optimisation of electric vehicle on-board energy source in terms of energy efficiency and storage mass/volume. Results from a case study considering a typical small urban electric vehicle are presented, illustrating the benefits of hybrid energy sources in terms of system mass and vehicle range. The models and approach can be applied to other vehicles and driving regimes

A H2 PEM fuel cell and high energy dense battery hybrid energy source for an urban electric vehicle

Electric vehicles are set to play a prominent role in addressing the energy and environmental impact of an increasing road transport population by offering a more energy efficient and less polluting drive-train alternative to conventional internal combustion engine (ICE) vehicles. Given the energy (and hence range) and performance limitations of electro-chemical battery storage systems, hybrid systems combining energy and power dense storage technologies have been proposed for vehicle applications. The paper discusses the application of a hydrogen fuel cell as a range extender for an urban electric vehicle for which the primary energy source is provided by a high energy dense battery. A review of fuel cell systems and automotive drive-train application issues are discussed, together with an overview of the battery technology. The prototype fuel cell and battery component simulation models are presented and their performance as a combined energy/power source assessed for typical urban and sub-urban driving scenario

Effect of Thermal and Mechanical Deformation of Metamaterial FDM Components

At Lancaster University, research is currently investigating the use of rapid manufacturing (RM) to realise metamaterials, although key to the success of this project is the development of an understanding of how coated RM parts deform under thermal and mechanical stress. The research in this paper presents a comparison of the thermal and mechanical deformation behaviour of RM coated metamaterials components from a numerical context. The research uses the design of a simple metamaterial unit cell as a test model for both the experimental and finite element method (FEM). The investigation of deformation behaviour of sample Fused Deposition Modelling (FDM) parts manufactured in different orientations and simulated using commercial FEM code means that the FEM analysis can be utilized for design verification of FDM parts. This research contributes to further research into the development of RM metamaterials, specifically design analysis and verification tools for RM materials

Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores

Modern business applications and scientific databases call for inherently dynamic data storage environments. Such environments are characterized by two challenging features: (a) they have little idle system time to devote on physical design; and (b) there is little, if any, a priori workload knowledge, while the query and data workload keeps changing dynamically. In such environments, traditional approaches to index building and maintenance cannot apply. Database cracking has been proposed as a solution that allows on-the-fly physical data reorganization, as a collateral effect of query processing. Cracking aims to continuously and automatically adapt indexes to the workload at hand, without human intervention. Indexes are built incrementally, adaptively, and on demand. Nevertheless, as we show, existing adaptive indexing methods fail to deliver workload-robustness; they perform much better with random workloads than with others. This frailty derives from the inelasticity with which these approaches interpret each query as a hint on how data should be stored. Current cracking schemes blindly reorganize the data within each query's range, even if that results into successive expensive operations with minimal indexing benefit. In this paper, we introduce stochastic cracking, a significantly more resilient approach to adaptive indexing. Stochastic cracking also uses each query as a hint on how to reorganize data, but not blindly so; it gains resilience and avoids performance bottlenecks by deliberately applying certain arbitrary choices in its decision-making. Thereby, we bring adaptive indexing forward to a mature formulation that confers the workload-robustness previous approaches lacked. Our extensive experimental study verifies that stochastic cracking maintains the desired properties of original database cracking while at the same time it performs well with diverse realistic workloads.Comment: VLDB201

Hotel housekeeping occupational stressors in Norway

Stress is evident in the Norwegian hotel industry and requires urgent attention as portrayed in Annbjørg’s housekeeping managerial occupation. Annbjørg’s occupational stressors derived from weak control of and support for demanding jobs in the housekeeping department and possibly under-reward in comparison to her tireless efforts. Hence, this case study provides a platform for educators, trainers, managers, students and learners to critically examine, discuss and argue managerial occupational stress and interventions set within the Norwegian hotel housekeeping context

Organic food consumers in Hong Kong

Asian organic foods consumers’ behaviour is worth investigating to sustain the continuous growth of organic foods consumption. Hence, Fiona has the ambition to employ the innovation diffusion theory to profile and understand organic foods consumers in Hong Kong in her research proposal. The process of writing an acceptable research proposal is challenging, tedious and time consuming as depicted in Fiona’s experience. Hence, this case study provides the opportunity for educators, students, and organic foods sellers and retailers to discuss and address Fiona’s challenges