A classification of emerging and traditional grid systems

The grid has evolved in numerous distinct phases. It started in the early ’90s as a model of metacomputing in which supercomputers share resources; subsequently, researchers added the ability to share data. This is usually referred to as the first-generation grid. By the late ’90s, researchers had outlined the framework for second-generation grids, characterized by their use of grid middleware systems to “glue” different grid technologies together. Third-generation grids originated in the early millennium when Web technology was combined with second-generation grids. As a result, the invisible grid, in which grid complexity is fully hidden through resource virtualization, started receiving attention. Subsequently, grid researchers identified the requirement for semantically rich knowledge grids, in which middleware technologies are more intelligent and autonomic. Recently, the necessity for grids to support and extend the ambient intelligence vision has emerged. In AmI, humans are surrounded by computing technologies that are unobtrusively embedded in their surroundings. However, third-generation grids’ current architecture doesn’t meet the requirements of next-generation grids (NGG) and service-oriented knowledge utility (SOKU).4 A few years ago, a group of independent experts, arranged by the European Commission, identified these shortcomings as a way to identify potential European grid research priorities for 2010 and beyond. The experts envision grid systems’ information, knowledge, and processing capabilities as a set of utility services.3 Consequently, new grid systems are emerging to materialize these visions. Here, we review emerging grids and classify them to motivate further research and help establish a solid foundation in this rapidly evolving area

Assessing the quality of a student-generated question repository

We present results from a study that categorizes and assesses the quality of questions and explanations authored by students, in question repositories produced as part of the summative assessment in introductory physics courses over the past two years. Mapping question quality onto the levels in the cognitive domain of Bloom's taxonomy, we find that students produce questions of high quality. More than three-quarters of questions fall into categories beyond simple recall, in contrast to similar studies of student-authored content in different subject domains. Similarly, the quality of student-authored explanations for questions was also high, with approximately 60% of all explanations classified as being of high or outstanding quality. Overall, 75% of questions met combined quality criteria, which we hypothesize is due in part to the in-class scaffolding activities that we provided for students ahead of requiring them to author questions.Comment: 24 pages, 5 figure

Early Determinants of Women in the IT Workforce: A Model of Girls’ Career Choices

Purpose – To develop a testable model for girls’ career choices in technology fields based on past research and hypotheses about the future of the information technology (IT) workforce. Design/Methodology/Approach – Review and assimilation of literature from education, psychology, sociology, computer science, IT, and business in a model that identifies factors that can potentially influence a girl’s choice towards or against IT careers. The factors are categorized into social factors (family, peers, and media), structural factors (computer use, teacher/counselor influence, same sex versus coeducational schools), and individual differences. The impact of culture on these various factors is also explored. Findings – The model indicates that parents, particularly fathers, are the key influencers of girls’ choice of IT careers. Teachers and counselors provide little or no career direction. Hypotheses propose that early access to computers may reduce intimidation with technology and that same-sex education may serve to reduce career bias against IT. Research Limitations/Implications – While the model is multidisciplinary, much of research from which it draws is five to eight years old. Patterns of career choices, availability of technology, increased independence of women and girls, offshore/nearshore outsourcings of IT jobs are just some of the factors that may be insufficiently addressed in this study. Practical Implications – A “Recommendations” section provides some practical steps to increase the involvement of girls in IT-related careers and activities at an early age. The article identifies cultural research as a limitation and ways to address this. Originality/value – The paper is an assimilation of literature from diverse fields and provides a testable model for research on gender and IT

Image analysis and statistical modelling for measurement and quality assessment of ornamental horticulture crops in glasshouses

Image analysis for ornamental crops is discussed with examples from the bedding plant industry. Feed-forward artificial neural networks are used to segment top and side view images of three contrasting species of bedding plants. The segmented images provide objective measurements of leaf and flower cover, colour, uniformity and leaf canopy height. On each imaging occasion, each pack was scored for quality by an assessor panel and it is shown that image analysis can explain 88.5%, 81.7% and 70.4% of the panel quality scores for the three species, respectively. Stereoscopy for crop height and uniformity is outlined briefly. The methods discussed here could be used for crop grading at marketing or for monitoring and assessment of growing crops within a glasshouse during all stages of production

Who do you talk to about your teaching?' Networking activities among university teachers

As the higher education environment changes, there are calls for university teachers to change and enhance their teaching practices to match. Networking practices are known to be deeply implicated in studies of change and diffusion of innovation, yet academics’ networking activities in relation to teaching have been little studied. This paper extends the current limited understanding, building on Roxå and Mårtensson’s work (2009) and extending it from Sweden to the UK and USA. It is based on two separate studies, one from the Share Project led by the University of Kent, and one from Glasgow Caledonian University, exploring the composition of personal networks, and the characteristics of interactions in order to understand the networking practices which may support change of teaching practice. We conclude that academics’ personal teaching networks are mainly discipline-specific and strongly localised. This contrasts with the research networks found by Becher and Trowler (2001) and may reduce innovation, although about half the respondents also had external contacts that might support creativity

Skills Assessment for Business Services: Final Report

No abstract available