Going beyond semantic image segmentation, towards holistic scene understanding, with associative hierarchical random fields

In this thesis we exploit the generality and expressive power of the Associative Hierarchical Random Field (AHRF) graphical model to take its use beyond that of semantic image segmentation, into object-classes, towards a framework for holistic scene understanding. We provide a working definition for the holistic approach to scene understanding, which allows for the integration of existing, disparate, applications into an unifying ensemble. We believe that modelling such an ensemble as an AHRF is both a principled and pragmatic solution. We present a hierarchy that shows several methods for fusing applications together with the AHRF graphical model. Each of the three; feature, potential and energy, layers subsumes its predecessor in generality and together give rise to many options for integration. With applications on street scenes we demonstrate an implementation of each layer. The first layer application joins appearance and geometric features. For our second layer we implement a things and stuff co-junction using higher order AHRF potentials for object detectors, with the goal of answering the classic questions: What? Where? and How many? A holistic approach to recognition-and-reconstruction is realised within our third layer by linking two energy based formulations of both applications. Each application is evaluated qualitatively and quantitatively. In all cases our holistic approach shows improvement over baseline methods

Embedded finite-element solver for computation of brushless permanent-magnet motors

This paper describes the theory underlying the formulation of a “minimum set” of finite-element solutions to be used in the design and analysis of saturated brushless permanent-magnet motors. The choice of finite-element solutions is described in terms of key points on the flux–MMF diagram. When the diagram has a regular shape, a huge reduction in finite-element analysis is possible with no loss of accuracy. If the loop is irregular, many more solutions are needed. This paper describes an efficient technique in which a finite-element solver is associated with a classical $d$– $q$-axis circuit model in such a way that the number of finite-element solutions in one electrical half-cycle can be varied between 1 and 360. The finite-element process is used to determine not only the average torque but also the saturated inductances as the rotor rotates

Psychometric Validation and Demographic Differences in Two Recently Developed Trait Mindfulness Measures

Although in recent years an increasingly large body of mindfulness research has accrued, there continues to be a lack of information about how to measure trait mindfulness, as well as whether it varies across demographic variables such as age and gender. Four hundred and six participants from across New Zealand completed a battery of self-report measures in order to examine demographic differences in mindfulness, as well as to look at how mindfulness predicts outcome variables such as happiness and depression. Additionally, psychometric validation was undertaken on two new trait measures of mindfulness: the Toronto Mindfulness Scale, which did not demonstrate good psychometric validity, and the Five Facet Mindfulness Questionnaire, which did demonstrate good psychometric validity. This study found that females reported higher levels of mindfulness than males, though males demonstrated a stronger mediating relationship between mindfulness and happiness. In addition, higher levels of mindfulness were reported by older individuals; however, young adults manifested the strongest negative relationship between mindfulness and depression across the lifespan. These findings are then discussed in the context of clinical utility and future research

A Numerical Method to Compute Brain Injury Associated to Concussion

This research proposes a new a numerical method to compute brain injury associated with concussion using the Peak Virtual Power method, using the THUMS 4.02 head model. The results indicate that mild and severe concussions could be prevented for lateral collisions and frontal impacts with PVP values lower than 0.928mW and 9.405mW, respectively, and no concussion would happen in the head vertical direction for a PVP value less than 1.184mW. This innovative method proposes a new paradigm to improve helmet designs, assess sports injuries and improve people's wellbeing.Comment: 12 page

A Numerical Method to Compute Brain Injury Associated to Concussion

This research proposes a new a numerical method to compute brain injury associated with concussion using the Peak Virtual Power method, using the THUMS 4.02 head model. The results indicate that mild and severe concussions could be prevented for lateral collisions and frontal impacts with PVP values lower than 0.928mW and 9.405mW, respectively, and no concussion would happen in the head vertical direction for a PVP value less than 1.184mW. This innovative method proposes a new paradigm to improve helmet designs, assess sports injuries and improve people's wellbeing.Comment: 12 page

Universal primers that amplify RNA from all three flavivirus subgroups

Background: Species within the Flavivirus genus pose public health problems around the world. Increasing cases of Dengue and Japanese encephalitis virus in Asia, frequent outbreaks of Yellow fever virus in Africa and South America, and the ongoing spread of West Nile virus throughout the Americas, show the geographical burden of flavivirus diseases. Flavivirus infections are often indistinct from and confused with other febrile illnesses. Here we review the specificity of published primers, and describe a new universal primer pair that can detect a wide range of flaviviruses, including viruses from each of the recognised subgroups

Reducing youth suicide : systems modelling and simulation to guide targeted investments across the determinants

Background: Reducing suicidal behaviour (SB) is a critical public health issue globally. The complex interplay of social determinants, service system factors, population demographics, and behavioural dynamics makes it extraordinarily difficult for decision makers to determine the nature and balance of investments required to have the greatest impacts on SB. Real-world experimentation to establish the optimal targeting, timing, scale, frequency, and intensity of investments required across the determinants is unfeasible. Therefore, this study harnesses systems modelling and simulation to guide population-level decision making that represent best strategic allocation of limited resources. Methods: Using a participatory approach, and informed by a range of national, state, and local datasets, a system dynamics model was developed, tested, and validated for a regional population catchment. The model incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and SB. Intervention scenarios were investigated to forecast their impact on SB over a 20-year period. Results: A combination of social connectedness programs, technology-enabled coordinated care, post-attempt assertive aftercare, reductions in childhood adversity, and increasing youth employment projected the greatest impacts on SB, particularly in a youth population, reducing self-harm hospitalisations (suicide attempts) by 28.5% (95% interval 26.3–30.8%) and suicide deaths by 29.3% (95% interval 27.1–31.5%). Introducing additional interventions beyond the best performing suite of interventions produced only marginal improvement in population level impacts, highlighting that ‘more is not necessarily better.’ Conclusion: Results indicate that targeted investments in addressing the social determinants and in mental health services provides the best opportunity to reduce SB and suicide. Systems modelling and simulation offers a robust approach to leveraging best available research, data, and expert knowledge in a way that helps decision makers respond to the unique characteristics and drivers of SB in their catchments and more effectively focus limited health resources

The effects of changes in the order of verbal labels and numerical values on children's scores on attitude and rating scales

Research with adults has shown that variations in verbal labels and numerical scale values on rating scales can affect the responses given. However, few studies have been conducted with children. The study aimed to examine potential differences in children’s responses to Likert-type rating scales according to their anchor points and scale direction, and to see whether or not such differences were stable over time. 130 British children, aged 9 to 11, completed six sets of Likert-type rating scales, presented in four different ways varying the position of positive labels and numerical values. The results showed, both initially and 8-12 weeks later, that presenting a positive label or a high score on the left of a scale led to significantly higher mean scores than did the other variations. These findings indicate that different arrangements of rating scales can produce different results which has clear implications for the administration of scales with children