Getting In and Getting On? The Experiences of Young People with Visual Impairments and Hearing Impairments in Third-Level Education

Young disabled people continue to be under-represented throughout further and higher education settings. Drawing on Pierre Bourdieu’s social theory of habitus, capital and field, this paper explores the practices of domination and oppression that have made it difficult for young people with visual impairments and hearing impairments to participate in third-level education on the same basis as non-disabled people. Twenty young people with hearing impairments and visual impairments were interviewed about their educational experiences. In addition, 31 interviews were conducted with third-level education providers, policy-makers and non-governmental organisations. This article has two aims: firstly, to critically examine the experiences of young people with hearing impairments and visual impairments in accessing and engaging with support provisions in further and higher education settings; and secondly, to identify and explore the diversity of ways in which these young people have managed and responded to the practices they have encountered. This article emphasises the journey from ability to dis-ability that young people with hearing and visual impairments experience in their quest for educational achievement. The ambiguities of “inclusion”, “widening participation” and “support” are highlighted and critiqued for their extensive failure to challenge taken-for-granted discourses.

Adaptive NormalHedge for robust visual tracking

In this paper, we propose a novel visual tracking framework, based on a decision-theoretic online learning algorithm namely NormalHedge. To make NormalHedge more robust against noise, we propose an adaptive NormalHedge algorithm, which exploits the historic information of each expert to perform more accurate prediction than the standard NormalHedge. Technically, we use a set of weighted experts to predict the state of the target to be tracked over time. The weight of each expert is online learned by pushing the cumulative regret of the learner towards that of the expert. Our simulation experiments demonstrate the effectiveness of the proposed adaptive NormalHedge, compared to the standard NormalHedge method. Furthermore, the experimental results of several challenging video sequences show that the proposed tracking method outperforms several state-of-the-art methods.

Robust visual tracking using structurally random projection and weighted least squares

Sparse representation based visual tracking approaches have attracted increasing interests in the community in recent years. The main idea is to linearly represent each target candidate using a set of target and trivial templates while imposing a sparsity constraint onto the representation coefficients. After we obtain the coefficients using L1-norm minimization methods, the candidate with the lowest error, when it is reconstructed using only the target templates and the associated coefficients, is considered as the tracking result. In spite of promising system performance widely reported, it is unclear if the performance of these trackers can be maximised. In addition, computational complexity caused by the dimensionality of the feature space limits these algorithms in real-time applications. In this paper, we propose a real-time visual tracking method based on structurally random projection and weighted least squares techniques. In particular, to enhance the discriminative capability of the tracker, we introduce background templates to the linear representation framework. To handle appearance variations over time, we relax the sparsity constraint using a weighed least squares (WLS) method to obtain the representation coefficients. To further reduce the computational complexity, structurally random projection is used to reduce the dimensionality of the feature space while preserving the pairwise distances between the data points in the feature space. Experimental results show that the proposed approach outperforms several state-of-the-art tracking methods.

Visual attention to food cues in obesity: An eye‐tracking study.

Objective
Based on the theory of incentive sensitization, the aim of this study was to investigate differences in attentional processing of food-related visual cues between normal-weight and overweight/obese males and females.

Methods
Twenty-six normal-weight (14M, 12F) and 26 overweight/obese (14M, 12F) adults completed a visual probe task and an eye-tracking paradigm. Reaction times and eye movements to food and control images were collected during both a fasted and fed condition in a counterbalanced design.

Results
Participants had greater visual attention towards high-energy-density food images compared to low-energy-density food images regardless of hunger condition. This was most pronounced in overweight/obese males who had significantly greater maintained attention towards high-energy-density food images when compared with their normal-weight counterparts however no between weight group differences were observed for female participants.

Conclusions
High-energy-density food images appear to capture visual attention more readily than low-energy-density food images. Results also suggest the possibility of an altered visual food cue-associated reward system in overweight/obese males. Attentional processing of food cues may play a role in eating behaviors thus should be taken into consideration as part of an integrated approach to curbing obesity.

Attentional bias to food-related visual cues: is there a role in obesity?

The incentive sensitisation model of obesity suggests that modification of the dopaminergic associated reward systems in the brain may result in increased awareness of food-related visual cues present in the current food environment. Having a heightened awareness of these visual food cues may impact on food choices and eating behaviours with those being most aware of or demonstrating greater attention to food-related stimuli potentially being at greater risk of overeating and subsequent weight gain. To date, research related to attentional responses to visual food cues has been both limited and conflicting. Such inconsistent findings may in part be explained by the use of different methodological approaches to measure attentional bias and the impact of other factors such as hunger levels, energy density of visual food cues and individual eating style traits that may influence visual attention to food-related cues outside of weight status alone. This review examines the various methodologies employed to measure attentional bias with a particular focus on the role that attentional processing of food-related visual cues may have in obesity. Based on the findings of this review, it appears that it may be too early to clarify the role visual attention to food-related cues may have in obesity. Results however highlight the importance of considering the most appropriate methodology to use when measuring attentional bias and the characteristics of the study populations targeted while interpreting results to date and in designing future studies.

Post-Conflict Performance, Film and Visual Arts:Cities of Memory

This book examines how contemporary theatre, performance, film and the visual arts respond to the post-conflict condition. The contents of the volume focus on a range of post-conflict cities, encouraging interdisciplinary discussion on the role of the arts and its relation to issues of testimony, witnessing, forgetting, representation, healing, reconciliation, agency, and metaphor. Contributors include: Thomas Elsaesser, Jane Taylor, Marvin Carlson, Rob Stone, Laurel Borisenko, Katarzyna Puzon, Miriam Paeslack, Emma Grey, Paula Blair, Zoran Poposki, Marija Todorova, Elena Carduro, and Paul Devlin.

A Hundred Comets: The Visual-Wavelength Observations of the Survey of Ensemble Physical Properties of Cometary Nuclei (SEPPCoN)

We present new results from SEPPCoN, a Survey of Ensemble Physical Properties of Cometary Nuclei. This project is currently surveying 100 Jupiter-family comets (JFCs) to measure the mid-infrared thermal emission and visible reflected sunlight of the nuclei. The scientific goal is to determine the distributions of radius, geometric albedo, thermal inertia, axial ratio, and color among the JFC nuclei. In the past we have presented results from the completed mid-IR observations of our sample [1]; here we present preliminary results from ongoing, broadband visible-wavelength observations of nuclei obtained from a variety of ground-based facilities (Mauna Kea, Cerro Pachon, La Silla, La Palma, Apache Point, Table Mtn., and Palomar Mtn.), including contributions from the Near Earth Asteroid Telescope project (NEAT) archive. The nuclei were observed at high heliocentric distance (usually over 4 AU) and so many comets show either no or little contamination from dust coma. While several nuclei have been observed as snapshots, we have multiepoch photometry for many of our targets. With our datasets we are building a large database of photometry, and such a database is essential to the derivation of albedo and shape of a large number of nuclei, and to the understanding of biases in the survey. Support for this work was provided by NSF and the NASA Planetary Astronomy program. Reference: [1] Fernandez, Y.R., et al. 2007, BAAS 39, 827.

Virtual Thrower Versus Real Goalkeeper: The Influence of Different Visual Conditions on Performance

In order to use virtual reality as a sport analysis tool, we need to be sure that an immersed athlete reacts realistically in a virtual environment. This has been validated for a real handball goalkeeper facing a virtual thrower. However, we currently ignore which visual variables induce a realistic motor behavior of the immersed handball goalkeeper. In this study, we used virtual reality to dissociate the visual information related to the movements of the player from the visual information related to the trajectory of the ball. Thus, the aim is to evaluate the relative influence of these different visual information sources on the goalkeeper's motor behavior. We tested 10 handball goalkeepers who had to predict the final position of the virtual ball in the goal when facing the following: only the throwing action of the attacking player (TA condition), only the resulting ball trajectory (BA condition), and both the throwing action of the attacking player and the resulting ball trajectory (TB condition). Here we show that performance was better in the BA and TB conditions, but contrary to expectations, performance was substantially worse in the TA condition. A significant effect of ball landing zone does, however, suggest that the relative importance between visual information from the player and the ball depends on the targeted zone in the goal. In some cases, body-based cues embedded in the throwing actions may have a minor influence on the ball trajectory and vice versa. Kinematics analysis was then combined with these results to determine why such differences occur depending on the ball landing zone and consequently how it can clarify the role of different sources of visual information on the motor behavior of an athlete immersed in a virtual environment.

Direct Visual Indication of pH Windows: 'Off-On-Off' Fluorescent PET (Photoinduced Electron Transfer) Sensors/Switches

1–3, which contain a fluorophore and two proton receptors with opposite PET (photoinduced electron transfer) characteristics, only display strong fluorescence within a pH window whose position and width are tunable.

Deep Salience: Visual Salience Modeling via Deep Belief Propagation

Visual salience is an intriguing phenomenon observed in biological neural systems. Numerous attempts have been made to model visual salience mathematically using various feature contrasts, either locally or globally. However, these algorithmic models tend to ignore the problem’s biological solutions, in which visual salience appears to arise during the propagation of visual stimuli along the visual cortex. In this paper, inspired by the conjecture that salience arises from deep propagation along the visual cortex, we present a Deep Salience model where a multi-layer model based on successive Markov random fields (sMRF) is proposed to analyze the input image successively through its deep belief propagation. As a result, the foreground object can be automatically separated from the background in a fully unsupervised way. Experimental evaluation on the benchmark dataset validated that our Deep Salience model can consistently outperform eleven state-of-the-art salience models, yielding the higher rates in the precision-recall tests and attaining the best F-measure and mean-square error in the experiments.