Neural network methods for one-to-many multi-valued mapping problems

An investigation of the applicability of neural network-based methods in predicting the values of multiple parameters, given the value of a single parameter within a particular problem domain is presented. In this context, the input parameter may be an important source of variation that is related with a complex mapping function to the remaining sources of variation within a multivariate distribution. The definition of the relationship between the variables of a multivariate distribution and a single source of variation allows the estimation of the values of multiple variables given the value of the single variable, addressing in that way an ill-conditioned one-to-many mapping problem. As part of our investigation, two problem domains are considered: predicting the values of individual stock shares, given the value of the general index, and predicting the grades received by high school pupils, given the grade for a single course or the average grade. With our work, the performance of standard neural network-based methods and in particular multilayer perceptrons (MLPs), radial basis functions (RBFs), mixture density networks (MDNs) and a latent variable method, the general topographic mapping (GTM), is compared. According to the results, MLPs and RBFs outperform MDNs and the GTM for these one-to-many mapping problems

The turbulent structure of the jet in cross-flow

In this thesis the structure of the jet in cross flow in the far field was investigated experimentally using time-resolved, multi-scale and statistically independent Stereoscopic Particle Image Velocimetry measurements to reveal the mean and instantaneous three-dimensional (3D) structures. All of the measurements were performed in the Counter-rotating Vortex Pair (CVP) plane for a high velocity ratio and jet Reynolds number. Statistical measurements at various downstream locations and velocity ratios are presented. Probability density functions of the streamwise vorticity field showed that each CVP core is instantaneously made of a number of small vortex tubes rather than a single vortex core. The characteristic ‘kidney’ shape was illustrated in the rms velocity profiles and the Reynolds stress profiles exhibited a high level of organisation which showed an evolving shape with downstream distance and persisted well into the far field. Two point spatial correlations pointed to a common structure for all conditions whose mean shape generates the ‘kidney’ shape, as well as evidence of wake structures. Time-resolved measurements were carried out in a moving and stationary frame of reference, converted to 3D measurements via the use of Taylor’s hypothesis. The origin of the ‘kidney’ shape and large degree of spatial order in the far field was found to be a result of an organised ‘train’ of consecutive hairpin, roller and wake structures. Together, these structures provide a physical explanation that reconciles the statistical and instantaneous structure of the CVP.This work was supported by the EPSR

‘Healthy Eating’ and Social Media Use

Orthorexia Nervosa (ON) describes a pathological, unhealthy fixation with eating healthy food. Research concerning the symptomatology of ON, and its prevalence in numerous samples, differs as there no official measures or clear diagnostic criteria exist for this fairly new affliction. Though research on the link between the epidemiology of ON and social media is gaining traction, published evidence is scarce. This study intends to further understand ON and its possible link to the use of social media, and specifically, to test the prevalence of ON in an opportunity sample with the use of two ON measures – the ORTO-15 and the Tereul Orthorexia Scale (TOS); to use and validate a new ON measure (TOS); to examine the relationship between ON and social media use, with a focus on Instagram users; and to further understand the participants’ interpretations of the possible link between eating patterns and social media use. This study uses a convergent design and a mixed methods approach, which employs both statistical and thematic analysis (TA) to evaluate the quantitative and qualitative data generated. Data from 201 participants suggested a high prevalence of ON across the sample, and the results also reinforced the validity of the TOS measure (α = .86). ORTO 15 scores showed significant differences between age groups, genders, and Instagram users and non-Instagram users. The TA generated three overall themes: ‘The Importance of Belonging’, ‘Health as Art’ and ‘Craving’. The high prevalence in the sample may have been a result of the researcher’s recruitment method, and the ON measures may have categorised individuals on non-medically prescribed diets as ‘orthorexic’. Both the quantitative and qualitative results offer evidence to support a possible link between ON and social media use, specifically Instagram. Further research should be done to establish official criteria and measures for ON and the effect of social media on eating patterns, and to investigate the notion of ‘healthism’

Restoration of Partially Occluded Shapes of Faces using Neural Networks

One of the major difficulties encountered in the development of face image processing algorithms, is the possible presence of occlusions that hide part of the face images to be processed. Typical examples of facial occlusions include sunglasses, beards, hats and scarves. In our work we address the problem of restoring the overall shape of faces given only the shape presentation of a small part of the face. In the experiments described in this paper the shape of a face is defined by a series of landmarks located on the face outline and on the outline of different facial features. We describe the use of a number of methods including a method that utilizes a Hopfield neural network, a method that uses Multi-Layer Perceptron (MLP) neural network, a novel technique which combines Hopfield and MLP together, and a method based on associative search. We analyze comparative experiments in order to assess the performance of the four methods mentioned above. According to the experimental results it is possible to recover with reasonable accuracy the overall shape of faces even in the case that a substantial part of the shape of a given face is not visible. The techniques presented could form the basis for developing face image processing systems capable of dealing with occluded faces

Comparing different classifiers for automatic age estimation

We describe a quantitative evaluation of the performance of different classifiers in the task of automatic age estimation. In this context we generate a statistical model of facial appearance, which is subsequently used as the basis for obtaining a compact parametric description of face images. The aim of our work is to design classifiers that accept the model-based representation of unseen images and produce an estimate of the age of the person in the corresponding face image. For this application we have tested different classifiers: a classifier based on the use of quadratic functions for modeling the relationship between face model parameters and age, a shortest distance classifier and artificial neural network based classifiers. We also describe variations to the basic method where we use age-specific and/or appearance specific age estimation methods. In this context we use age estimation classifiers for each age group and/or classifiers for different clusters of subjects within our training set. In those cases part of the classification procedure is devoted to choosing the most appropriate classifier for the subject/age range in question, so that more accurate age estimates can be obtained. We also present comparative results concerning the performance of humans and computers in the task of age estimation. Our results indicate that machines can estimate the age of a person almost as reliably as humans

A case of Meigs syndrome mimicking metastatic breast carcinoma

<p>Abstract</p> <p>Background</p> <p>Adnexal masses are not uncommon in patients with breast cancer. Breast cancer and ovarian malignancies are known to be associated. In patients with breast cancer and co-existing pleural effusions, ascites and adnexal masses, the probability of disseminated disease is high. Nevertheless, benign ovarian masses can mimic this clinical picture when they are associated with Meigs' syndrome making the work-up and management of these patients challenging. To our knowledge, there are no similar reports in the literature and therefore we present this case to highlight this entity.</p> <p>Case presentation</p> <p>A 56-year old woman presented with a 4 cm, grade 2, invasive ductal carcinoma of her left breast. Pre-treatment staging investigations showed a 13.5 cm mass in her left ovary, a small amount of ascites and a large right pleural effusion. Serum tumour markers showed a raised CA125 supporting the malignant nature of the ovarian mass. The cytology from the pleural effusion was indeterminate but thoracoscopic biopsy failed to show malignancy. The patient was strongly against mastectomy and she was commenced on neo-adjuvant Letrozole 2.5 mg daily with a view to perform breast conserving surgery. After a good response to the hormone manipulation, the patient had breast conserving surgery, axillary sampling and laparoscopic excision of the ovarian mass which was eventually found to be a benign ovarian fibroma.</p> <p>Conclusion</p> <p>Despite the high probability of disseminated malignancy when an ovarian mass associated with ascites if found in a patient with a breast cancer and pleural effusion, clinicians should be aware about rare benign syndromes, like Meigs', which may mimic a similar picture and mislead the diagnosis and management plan.</p

The Cost-effectiveness of Pixantrone for Third/Fourth-line Treatment of Aggressive Non-Hodgkin's Lymphoma

PURPOSE: Aggressive non-Hodgkin's lymphoma (aNHL) is associated with poor long-term survival after relapse, and treatment is limited by a lack of consensus regarding standard of care. Pixantrone was studied in a randomized trial in patients with relapsed or refractory aNHL who had failed ≥ 2 lines of therapy, demonstrating a significant improvement in complete or unconfirmed complete response and progression-free survival (PFS) compared with investigators' choice of single-agent therapy. The objective of this study was to assess the health economic implications of pixantrone versus current clinical practice (CCP) in the United Kingdom for patients with multiply relapsed or refractory aNHL receiving their third or fourth line of treatment. METHODS: A semi-Markov partition model based on overall survival and PFS was developed to evaluate the lifetime clinical and economic impact of treatment of multiply relapsed or refractory aNHL with pixantrone versus CCP. The empirical overall survival and PFS data from the PIX301 trial were extrapolated to a lifetime horizon. Resource use was elicited from clinical experts, and unit costs and utilities were obtained from published sources. The analysis was conducted from the perspective of the United Kingdom's National Health Service and personal social services. Outcomes evaluated were total costs, life-years, quality-adjusted life-years (QALYs), and cost per QALY gained. Deterministic and probabilistic sensitivity analyses were conducted to assess uncertainty around the results. FINDINGS: Pixantrone was estimated to increase life expectancy by a mean of 10.8 months per patient compared with CCP and a mean gain of 0.56 discounted QALYs. The increased health gains were associated with an increase in discounted costs of approximately £18,494 per patient. The incremental cost-effectiveness ratio of pixantrone versus CCP was £33,272 per QALY gained. Sensitivity and scenario analyses suggest that the incremental cost-effectiveness ratio was sensitive to uncertainty in the PFS and overall survival estimates and the utility values associated with each health state. IMPLICATIONS: Pixantrone may be considered both clinically effective and cost-effective for patients with multiply relapsed or refractory aNHL who currently have a high level of unmet need