Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images

Mixture models implemented via the expectation-maximization (EM) algorithm are being increasingly used in a wide range of problems in pattern recognition such as image segmentation. However, the EM algorithm requires considerable computational time in its application to huge data sets such as a three-dimensional magnetic resonance (MR) image of over 10 million voxels. Recently, it was shown that a sparse, incremental version of the EM algorithm could improve its rate of convergence. In this paper, we show how this modified EM algorithm can be speeded up further by adopting a multiresolution kd-tree structure in performing the E-step. The proposed algorithm outperforms some other variants of the EM algorithm for segmenting MR images of the human brain. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Right ventricle extraction by low level and model-based algorithm

In this paper we present an algorithm as the combination of a low level morphological operation and model based Global Circular Shortest Path scheme to explore the segmentation of the Right Ventricle. Traditional morphological operations were employed to obtain the region of interest, and adjust it to generate a mask. The image cropped by the mask is then partitioned into a few overlapping regions. Global Circular Shortest Path algorithm is then applied to extract the contour from each partition. The final step is to re-assemble the partitions to create the whole contour. The technique is deemed quite reliable and robust, as this is illustrated by a very good agreement between the extracted contour and the expert manual drawing output.

The relationship between extra-role behaviours and job burnout for primary school teachers: A preliminary model and development of an organisational citizenship behaviour scale

Recent research on teacher stress in primary schools (e.g. Leonard, Bourke & Schofield, 1999) has shown that higher levels of teacher exhaustion are associated with higher levels of student satisfaction. This paper seeks to explain this surprising finding by considering a construct discussed widely in the organisational literature known as extra-role or organisational citizenship behaviour (OCB). Teacher OCB may include extra efforts to make lessons enjoyable and interesting, organising extra-curricular activities and spending personal time talking with students. The proposed model of analysis also draws on literature relating to job burnout (Maslach, 1982), which generally suggests that the three components of chronic occupational stress - exhaustion, depersonalisation and reduced accomplishment - occur together. However, this paper proposes that although teachers who engage in more OCB experience more exhaustion, they may simultaneously increase their feelings of personal accomplishment and work identification, which may in turn help to avert burnout. It is argued that only with this particular set of job attitudes are the effects of exhaustion caused by high levels of OCB sufficiently buffered to avoid job burnout, and thus positively affect students' quality of school life. The development and piloting of an instrument to measure teachers' OCB will be discussed. The preliminary findings reported herein are part of a larger ongoing study investigating the consequences of stress and OCB in primary school teachers.

Knowledge-based development in leading regions across the globe:an exploratory analysis of the co-evolution of resources, capabilities, and outputs

It is widely observed that the global geography of innovation is rapidly evolving. This paper presents evidence concerning the contemporary evolution of the globe's most productive regions. The paper uncovers the underlying structure and co-evolution of knowledge-based resources, capabilities and outputs across these regions. The analysis identifies two key trends by which the economic evolution and growth patterns of these regions are differentiated-namely, knowledge-based growth and labour market growth. The knowledge-based growth factor represents the underlying commonality found between the growth of economic output, earnings and a range of knowledge-based resources. The labour market growth factor represents the capability of regions to draw on their human capital. Overall, spectacular knowledge-based growth of leading Chinese regions is evident, highlighting a continued shift of knowledge-based resources to Asia. It is concluded that regional growth in knowledge production investment and the capacity to draw on regional human capital reserves are neither necessarily traded-off nor complementary to each other. © 2012 Urban Studies Journal Limited.

Towards agility in design in global component-based development

The potential benefits of implementing Component-Based Development (CBD) methodologies in a globally distributed environment are many. Lessons from the aeronautics, automotive, electronics and computer hardware industries, in which Component-Based (CB) architectures have been successfully employed for setting up globally distributed design and production activities, have consistently shown that firms have managed to increase the rate of reused components and sub-assemblies, and to speed up the design and production process of new products.

Nootropia : a user profiling model based on a self-organising term network

Artificial Immune Systems are well suited to the problem of using a profile representation of an individual’s or a group’s interests to evaluate documents. Nootropia is a user profiling model that exhibits similarities to models of the immune system that have been developed in the context of autopoietic theory. It uses a self-organising term network that can represent a user’s multiple interests and can adapt to both short-term variations and substantial changes in them. This allows Nootropia to drift, constantly following changes in the user’s multiple interests, and, thus, to become structurally coupled to the user.