The National Transport Data Framework

Report by Professor Peter Landshoff (Cambridge University) and Professor John Polak (Imperial College London) on a project for the Department for Transport. emails: [email protected] [email protected] NTDF is designed to be a resource for data owners to deposit descriptions into a central catalogue, so that people can search for data and find data and understand their characteristics. The value of this is to individuals, to commercial organizations, and to public bodies. For example, services that provide better information to travellers will help to make their journey less stressful and persuade them to make more use of public transport. Transport operators need very diverse information to help them plan developments to their services: demographic, geographical, economic etc. And policy makers need a similar range of information to help them decide how to divide their budget and afterwards to evaluate how valuable it has been.This work was supported by the Department for Transport (DfT)

A Study of the Relationship between CBT Developers\u27 Multiple Intelligences Dispositions and the Design of Computer-based Training

This study assessed the relationship between CBT developers\u27 multiple intelligences (MI) dispositions and their designs for computer-based training programs (CBTs). This study was based on the theoretical framework of the Theory of Multiple Intelligences (MI) and theories about instructional design (ID). Student developers in a class were surveyed using Shearer\u27s Multiple Intelligences Development Assessment Scales (MIDAS), a screening instrument that is designed to determine the students\u27 MIDAS profiles, or their intelligences. The students received instruction in using MI in their CBT design; and, after they had designed their CBTs, four professionals assessed their CBTs for inclusion of MI. Both quantitative and qualitative tests and analyses were performed on the association between students\u27 MIDAS profiles and the CBT reviewer ratings. While the findings of the correlation analysis of the quantitative data were refuted, some of the correlation and regression analyses of the observations of the qualitative data were conclusive regarding the hypothesis. CBT design was influenced by the student CBT designers MI as indicated by the MIDAS profiles, particularly in the qualitative analysis. Positive significant outcomes were reported for the linguistic spatial, intrapersonal, and kinesthetic intelligences. These findings show that knowledge of MI was influential on a few of the design variables, as the students were successful in designing CBTs that reflected inclusion of MI for tailoring to learners\u27 needs rather than to designers\u27 preferences. The information gathered in this study will make a significant contribution to the e-learning field because it sheds light on the association of MI with the development of CBTs

Common principles and best practices for engineering microbiomes

Despite broad scientific interest in harnessing the power of Earth's microbiomes, knowledge gaps hinder their efficient use for addressing urgent societal and environmental challenges. We argue hat structuring research and technology developments around a design-build-test-learn (DBTL) cycle will advance microbiome engineering and spur new discoveries on the basic scientific principles governing microbiome function. In this Review, we present key elements of an iterative DBTL cycle for microbiome engineering, focusing on generalizable approaches, including top-down and bottom-up design processes, synthetic and self-assembled construction methods, and emerging tools to analyze microbiome function. These approaches can be used to harness microbiomes for broad applications related to medicine, agriculture, energy, and the environment. We also discuss key challenges and opportunities of each approach and synthesize them into best practice guidelines for engineering microbiomes. We anticipate that adoption of a DBTL framework will rapidly advance microbiome-based biotechnologies aimed at improving human and animal health, agriculture, and enabling the bioeconomy

Fuzzy Human Reliability Analysis: Applications and Contributions Review

The applications and contributions of fuzzy set theory to human reliability analysis (HRA) are reassessed. The main contribution of fuzzy mathematics relies on its ability to represent vague information. Many HRA authors have made contributions developing new models, introducing fuzzy quantification methodologies. Conversely, others have drawn on fuzzy techniques or methodologies for quantifying already existing models. Fuzzy contributions improve HRA in five main aspects: (1) uncertainty treatment, (2) expert judgment data treatment, (3) fuzzy fault trees, (4) performance shaping factors, and (5) human behaviour model. Finally, recent fuzzy applications and new trends in fuzzy HRA are herein discussed

Learning to teach database design by trial and error

Proceedings of: 4th International Conference on Enterprise Information Systems (ICEIS 2002), Ciudad Real, Spain, April 3-6, 2002The definition of effective pedagogical strategies for coaching and tutoring students according to their needs in each moment is a high handicap in ITS design. In this paper we propose the use of a Reinforcement Learning (RL) model, that allows the system to learn how to teach to each student individually, only based on the acquired experience with other learners with similar characteristics, like a human tutor does. This technique avoids to define the teaching strategies by learning action policies that define what, when and how to teach. The model is applied to a database design ITS system, used as an example to illustrate all the concepts managed in the model