Multimodal semantic-associative collateral labelling and indexing of still images

A novel framework for multimodal semantic-associative collateral image labelling, aiming at associating image regions with textual keywords, is described. Both the primary image and collateral textual modalities are exploited in a cooperative and complementary fashion. The collateral content and context based knowledge is used to bias the mapping from the low-level region-based visual primitives to the high-level visual concepts defined in a visual vocabulary. We introduce the notion of collateral context, which is represented as a co-occurrence matrix, of the visual keywords, A collaborative mapping scheme is devised using statistical methods like Gaussian distribution or Euclidean distance together with collateral content and context-driven inference mechanism. Finally, we use Self Organising Maps to examine the classification and retrieval effectiveness of the proposed high-level image feature vector model which is constructed based on the image labelling results.

The relation between content and structure in language production: an analysis of speech errors in semantic dementia

In order to explore the impact of a degraded semantic system on the structure of language production, we analysed transcripts from autobiographical memory interviews to identify naturally-occurring speech errors by eight patients with semantic dementia (SD) and eight age-matched normal speakers. Relative to controls, patients were significantly more likely to (a) substitute and omit open class words, (b) substitute (but not omit) closed class words, (c) substitute incorrect complex morphological forms and (d) produce semantically and/or syntactically anomalous sentences. Phonological errors were scarce in both groups. The study confirms previous evidence of SD patients’ problems with open class content words which are replaced by higher frequency, less specific terms. It presents the first evidence that SD patients have problems with closed class items and make syntactic as well as semantic speech errors, although these grammatical abnormalities are mostly subtle rather than gross. The results can be explained by the semantic deficit which disrupts the representation of a pre-verbal message, lexical retrieval and the early stages of grammatical encoding.

Clinical potential and design of programmable mechanical impedances for orthotic applications

A person with a moderate or severe motor disability will often use specialised or adapted tools to assist their interaction with a general environment. Such tools can assist with the movement of a person's arms so as to facilitate manipulation, can provide postural supports, or interface to computers, wheelchairs or similar assistive technologies. Designing such devices with programmable stiffness and damping may offer a better means for the person to have effective control of their surroundings. This paper addresses the possibility of designing some assistive technologies using impedance elements that can adapt to the user and the circumstances. Two impedance elements are proposed. The first, based on magnetic particle brakes, allows control of the damping coefficient in a passive element. The second, based on detuning the P-D controller in a servo-motor mechanism, allows control of both stiffness and damping. Such a mechanical impedance can be modulated to the conditions imposed by the task in hand. The limits of linear theory are explored and possible uses of programmable impedance elements are proposed.

Analysis of aluminium content and iron homeostasis in nipple aspirate fluids from healthy women and breast cancer-affected patients

Aluminium is not a physiological component of the breast but has been measured recently in human breast tissues and breast cyst fluids at levels above those found in blood serum or milk. Since the presence of aluminium can lead to iron dyshomeostasis, levels of aluminium and iron-binding proteins (ferritin, transferrin) were measured in nipple aspirate fluid (NAF), a fluid present in the breast duct tree and mirroring the breast microenvironment. NAFs were collected noninvasively from healthy women (NoCancer; n = 16) and breast cancer-affected women (Cancer; n = 19), and compared with levels in serum (n = 15) and milk (n = 45) from healthy subjects. The mean level of aluminium, measured by ICP-mass spectrometry, was significantly higher in Cancer NAF (268.4 ± 28.1 μg l−1; n = 19) than in NoCancer NAF (131.3 ± 9.6 μg l−1; n = 16; P < 0.0001). The mean level of ferritin, measured through immunoassay, was also found to be higher in Cancer NAF (280.0 ± 32.3 μg l−1) than in NoCancer NAF (55.5 ± 7.2 μg l−1), and furthermore, a positive correlation was found between levels of aluminium and ferritin in the Cancer NAF (correlation coefficient R = 0.94, P < 0.001). These results may suggest a role for raised levels of aluminium and modulation of proteins that regulate iron homeostasis as biomarkers for identification of women at higher risk of developing breast cancer. The reasons for the high levels of aluminium in NAF remain unknown but possibilities include either exposure to aluminium-based antiperspirant salts in the adjacent underarm area and/or preferential accumulation of aluminium by breast tissues.

Advanced global optimisation for mission analysis and design

This report describes the analysis and development of novel tools for the global optimisation of relevant mission design problems. A taxonomy was created for mission design problems, and an empirical analysis of their optimisational complexity performed - it was demonstrated that the use of global optimisation was necessary on most classes and informed the selection of appropriate global algorithms. The selected algorithms were then applied to the di®erent problem classes: Di®erential Evolution was found to be the most e±cient. Considering the speci¯c problem of multiple gravity assist trajectory design, a search space pruning algorithm was developed that displays both polynomial time and space complexity. Empirically, this was shown to typically achieve search space reductions of greater than six orders of magnitude, thus reducing signi¯cantly the complexity of the subsequent optimisation. The algorithm was fully implemented in a software package that allows simple visualisation of high-dimensional search spaces, and e®ective optimisation over the reduced search bounds.