Doctoral supervision of colleagues: peeling off the veneer of satisfaction and competence

The nexus of teaching, administration and research activities engaged in by academic staff in higher education means that each individual plays a multitude of roles in relation to colleagues, producing inevitable tensions. One role relationship that epitomizes this extraordinary juggling task is that of doctoral supervisor/supervisee, when both are academic staff in the same institution. The last 10 years has seen an upsurge of research interest in doctoral research students, and government and funding bodies have imposed ever more stringent requirements on supervisors. However, staff pairings have been ignored in this literature and research. This article reports on an exploration that seeks to redress this omission by giving voice to the participants (colleague supervisor or research student), allowing them to articulate constructs about what may be unique in the interaction, thus highlighting factors that support or impede success in the enterprise.

Uneven playing field or falling standards? Chinese students' competence in English.

This paper explores student and teacher perspectives of challenges relating to the levels of competence in English of Chinese students studying overseas from the perspective of critical pedagogy. It draws on two complementary studies undertaken by colleagues at the University of Reading. The first—a research seminar attended by representatives from a wide range of UK universities—presents the views of teachers and administrators; the second draws on four case studies of the language learning of Chinese postgraduate students during their first year of study in the UK, and offers the student voice. Interview and focus group data highlight the limitations of current tests of English used as part of the requirements for university admission. In particular, university teachers expressed uncertainty about whether the acceptance of levels of written English which fall far short of native-speaker competence is an ill-advised lowering of standards or a necessary and pragmatic response to the realities of an otherwise uneven playing field. In spite of this ambivalence, there is evidence of a growing willingness on the part of university teachers and support staff to find solutions to the language issues facing Chinese students, some of which require a more strategic institutional approach, while others rely on greater flexibility on the part of individuals. Although the studies reported in this paper were based on British universities, the findings will also be of interest to those involved in tertiary education in other English-speaking countries which are currently attracting large numbers of Chinese students.

Doctoral supervision of colleagues: peeling off the veneer of satisfaction and competence

The nexus of teaching, administration and research activities engaged in by academic staff in higher education means that each individual plays a multitude of roles in relation to colleagues, producing inevitable tensions. One role relationship that epitomizes this extraordinary juggling task is that of doctoral supervisor/supervisee, when both are academic staff in the same institution. The last 10 years has seen an upsurge of research interest in doctoral research students, and government and funding bodies have imposed ever more stringent requirements on supervisors. However, staff pairings have been ignored in this literature and research. This article reports on an exploration that seeks to redress this omission by giving voice to the participants (colleague supervisor or research student), allowing them to articulate constructs about what may be unique in the interaction, thus highlighting factors that support or impede success in the enterprise.

Investigation of support vector machine for the detection of architectural distortion in mammographic images

This paper investigates detection of architectural distortion in mammographic images using support vector machine. Hausdorff dimension is used to characterise the texture feature of mammographic images. Support vector machine, a learning machine based on statistical learning theory, is trained through supervised learning to detect architectural distortion. Compared to the Radial Basis Function neural networks, SVM produced more accurate classification results in distinguishing architectural distortion abnormality from normal breast parenchyma.

Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms

Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.

Finding the point on Bezier Curves with the normal vector passing an external point

Two algorithms for finding the point on non-rational/rational Bezier curves of which the normal vector passes through a given external point are presented. The algorithms are based on Bezier curves generation algorithms of de Casteljau's algorithm for non-rational Bezier curve or Farin's recursion for rational Bezier curve, respectively. Orthogonal projections from the external point are used to guide the directional search used in the proposed iterative algorithms. Using Lyapunov's method, it is shown that each algorithm is able to converge to a local minimum for each case of non-rational/rational Bezier curves. It is also shown that on convergence the distance between the point on curves to the external point reaches a local minimum for both approaches. Illustrative examples are included to demonstrate the effectiveness of the proposed approaches.

Speed sensorless vector control of induction machines

A novel rotor velocity estimation scheme applicable to vector controlled induction motors has been described. The proposed method will evaluate rotor velocity, ωr, on-line, does not require any extra transducers or injection of any signals, nor does it employ complicated algorithms such as MRAS or Kalman filters. Furthermore, the new scheme will operate at all velocities including zero with very little error. The procedure employs motor model equations, however all differential and integral terms have been eliminated giving a very fast, low-cost, effective and practical alternative to the current available methods. Simulation results verify the operation of the scheme under ideal and PWM conditions.

A vector approach to the assessment of undergraduate engineering courses

In any undergraduate engineering programme there is a need to assess the balance and flavour of the various educational strands. In order for a quality assurance of these programmes to be met there is a need to evaluate the course load, academic content and the assessment marks of each course in the undergraduate programme. The existing ranges of QA methods for these programmes are focused on one or two of these issues and do not provide a comprehensive assessment procedure. Following a review of the existing QA methods, this paper will define a three-dimensional approach to the assessment of the educational aspects of an undergraduate course. Various features of this method will be described and potential benefits explained.