A general theory on media with randomly distributed inclusions .1. The average field behaviors

In this paper, a theory is developed to calculate the average strain field in the materials with randomly distributed inclusions. Many previous researches investigating the average field behaviors were based upon Mori and Tanaka's idea. Since they were restricted to studying those materials with uniform distributions of inclusions they did not need detailed statistical information of random microstructures, and could use the volume average to replace the ensemble average. To study more general materials with randomly distributed inclusions, the number density function is introduced in formulating the average field equation in this research. Both uniform and nonuniform distributions of inclusions are taken into account in detail.

Essex Adult Community Learning: PTLLS for distance and blended learning

Funded by the LSIS Excellence and Improvement Fund, Essex Adult Community Learning has produced a distance/blended learning resource on CD-Rom for tutors in the post-16 sector to achieve the City & Guilds PTLLS (7303 Preparing to Teach in the Lifelong Learning Sector) at Level 4. The aim of the resource is to improve teaching and learning by providing a flexible way to access initial teacher training where candidates may otherwise find it difficult or impossible to attend a taught course. It is also intended to increase tutors' own e-learning skills.

ITS Training: 'VLE - no distance too far - enhancing the learner journey and business processes'

ITS Training has undergone a revolutionary transformation in the past two years. The company has saved money, generated more business, improved recruitment, retention and achievement and expanded throughout the world because of its virtual learning environment (VLE): the ‘Student Campus'. Under its previous paper-based distance learning programme it was a hard enough task to deliver lectures to students in Liverpool. Now, the company has a classroom of learners in Tokyo, Japan.

On Best Proximity Point Theorems and Fixed Point Theorems for p-Cyclic Hybrid Self-Mappings in Banach Spaces

This paper relies on the study of fixed points and best proximity points of a class of so-called generalized point-dependent (K-Lambda)hybrid p-cyclic self-mappings relative to a Bregman distance Df, associated with a Gâteaux differentiable proper strictly convex function f in a smooth Banach space, where the real functions Lambda and K quantify the point-to-point hybrid and nonexpansive (or contractive) characteristics of the Bregman distance for points associated with the iterations through the cyclic self-mapping.Weak convergence results to weak cluster points are obtained for certain average sequences constructed with the iterates of the cyclic hybrid self-mappings.

Developing and Validating Distance Learning Awards Guidance Document (MMU)

The principal purpose of this document is to assist programme teams throughout the development process when they are considering the development or review of a route through the award where it will be delivered wholly, or primarily, via online distance learning. Please note that this document is current as of Sept 2015 but it is considered to be an evolving document and is updated/tweaked from time to time.

Outputs from the Manchester Metropolitan University distance learning think tank event

An overview of, and the emergent themes from, the Manchester Metropolitan University distance learning think tank event which took place on 10th July 2014 and aimed to provide a forum to explore and discuss some of the key issues for colleagues across the university involved in planning, setting-up and delivering such programmes at MMU.

Poster: Outputs from the Manchester Metropolitan University online distance learning think tank event

Poster from the overview of, and the emergent themes from, the Manchester Metropolitan University distance learning think tank event which took place on 10th July 2014 and aimed to provide a forum to explore and discuss some of the key issues for colleagues across the university involved in planning, setting-up and delivering such programmes at MMU.

Sampling and learning the Mallows and Generalized Mallows models under the Cayley distance

[EN]The Mallows and Generalized Mallows models are compact yet powerful and natural ways of representing a probability distribution over the space of permutations. In this paper we deal with the problems of sampling and learning (estimating) such distributions when the metric on permutations is the Cayley distance. We propose new methods for both operations, whose performance is shown through several experiments. We also introduce novel procedures to count and randomly generate permutations at a given Cayley distance both with and without certain structural restrictions. An application in the field of biology is given to motivate the interest of this model.

Sampling and learning the Mallows and Weighted Mallows models under the Hamming distance

[EN]In this paper we deal with distributions over permutation spaces. The Mallows model is the mode l in use. The associated distance for permutations is the Hamming distance.

Sampling and learning the Mallows model under the Ulam distance

[EN]In this paper we deal with probability distributions over permutation spaces. The Probability model in use is the Mallows model. The distance for permutations that the model uses in the Ulam distance.