Innovative Projects Realized

GIS-based Wildfire Catastrophic Risk Economic Capital Modelling

Models used for Wildfire catastrophe insurance as of today are not considering substantial information, such as geographic information and environmental constraints. The objective of the project is to establish a theoretical framework and an empirical process to enhance Aviva Canada’s current Wildfire Economic Capital (EC) model, to be able to determine the amount of capital needed to be allocated to ensure the company remains solvent, in case of occurrence of risks. The new model will incorporate spatial Geographic Information System (GIS)-based information and other non-spatial information and it will cater for the nature of the heavy-tailed data. It is expected that this approach can be adapted and extended to Aviva Canada’s other natural and man-made Catastrophe risk EC models with similar needs.

An examination of post-compulsory education for migrant children in urban China

Migrant workers are an important source of labor, becoming the engine of rapid development in urban areas in China. Despite the fact they have made a significant contribution to China’s economic prosperity, they and their children have limited access to social welfares in the host cities due to their lack of local urban hukou (household registration). This study aims to investigate migrant children’s access to senior secondary education in urban areas. I will conduct the study in Suzhou which is an economically-developed city on China’s east coast that offers job prospects and therefore appeals to the migrant population. I intend to conduct individual interviews with five migrant children and five teachers working with this group of children in junior high school. This project will make policy recommendations to the municipal and central governments to increase migrant children’s participation in high school in urban areas.

Smart TECHnology for better shared decision making about prenatal testing for pregnant WomEn (TECH4WE)

Whether or not to undergo prenatal screening to assess the risk of certain genetic conditions in the fetus, and if so deciding among available prenatal screening tests, is a difficult decision faced by all pregnant women and their partners. However, few are aware of the implications of the various options. With shared decision making (SDM), patients and doctors share health decisions based on the pros and cons of all the options and on what matters most to the patient, so decisions reflect this knowledge and the preferences of those involved. SDM reduces decision regret and reduces overuse of diagnostic testing. A mobile app could be a cost-effective, and efficient way to help patients make decisions. My research (Rahimi.2017,PMID:28838306) found little evidence of the use of mobile apps to support SDM, and none that support prenatal testing decisions. I plan to: (a)assess the needs and preferences of pregnant women regarding using smartphones for information seeking and decision making; (b)develop an analytical decision making model that incorporates and processes information, preferences and choices (e.g. screening options, decision criteria and weighting of decision criteria); (c)with my technological partner, Greybox Solutions, develop an analytical app and pilot test it. TBC

Évaluation de l’effet d’un éventail de traitements sylvicoles sur la régénération desprincipales essences feuillues dans les érablières en Estrie afin de développer un modèlede prédiction de la régéné

Ce projet de stage s’inscrit dans un projet de recherche plus vaste

ayant pour objectif de compléter, pour les érablières de l’Estrie (Québec), l’étalonnage du

modèle de simulation de la dynamique forestière SORTIE-ND. Ce dernier est un modèle

spatialement explicite qui sera utilisé pour évaluer et comparer l’effet d’un large éventail

de traitements sylvicoles susceptibles d’être utilisés dans un contexte d’aménagement

écosystémique (AÉ) des forêts de feuillus tolérants. Le présent stage a pour objectif de

déterminer comment la densité de la régénération (semis de 1 à 5 ans) des principales

essences feuillues de la région varie selon i) le traitement sylvicole utilisé; ii) le nombre

d’années écoulées depuis la coupe; et en fonction iii) des conditions lumineuses; iv) des

lits de germination; et v) des semenciers présents dans le peuplement résiduel. Ces

résultats permettront d’obtenir i) une meilleure connaissance de l’effet des traitements

sylvicoles utilisés au cours des dernières années sur l’établissement de la régénration dans

les secteurs d’étude; ii) une meilleure…………………

.

Development of a helmet grading system based on linear and rotational acceleration

Helmets are currently tested and certified based on appropriate standards using a pass/fail criteria. All helmets that are available in the market have passed this standard testing. Unfortunately, the pass/fail threshold is well above known head injury threshold. Other than by comparing the price, consumers do not have a quantitative way to determine whether one helmet is better than another. In this project, a user-friendly helmet grading system will be developed for different types of helmet. The grading system takes into account different aspects of impact such as peak and duration of measured acceleration pulse. Shield-X Technology Inc. has been looking for such comprehensive helmet grading system to evaluate their products. The grading system will also help Shield-X with its product development and communications with the third party companies in regards to how well its technologies enhance helmet performanc

An Evaluation of the Reliability of Forensic Case Formulation in the Risk Assessment of Intimate Partner Violence

Intimate partner violence (IPV), also known as spousal assault and domestic violence, is the most common form of violence experienced by women worldwide. Fortunately, IPV risk assessment tools, training, and practices have improved immensely over the last 20 years. One of the areas that can still be improved is training those using violence risk assessments for evaluations to better understand the root causes of violence at the individual level. The process of determining root causes of violence is an advanced skill now considered necessary for the comprehensive assessment of violence risk and determining risk management strategies. This study will develop and test a training program to improve aspects of risk assessment training and increase the utility of the training process. Improving the training around the root causes of violence within risk assessment is one of the last frontiers to improving risk assessment practices and training and ultimately reducing the incidence of IPV.

Probabilistic Image Generation from Layout

Despite significant recent progress on generative models, controlled generation of images depicting multiple and complex object
layouts is still a difficult problem. Among the core challenges are the diversity of appearance a given object may possess and, as
a result, exponential set of images consistent with a specified layout. In this project, we propose to address these challenges by a
probabilistic generative model, which can generate a set of realistic images by giving the coarse spatial layout (bounding boxes +
object categories). To further increase the controllability of the image generation, attributes or textual description of each object in
the layout may also be provided. A probabilistic generative model will be designed to better model the uncertainty the target
image. It will compose distributions based on given information and decodes samples from these distributions into realistic
images. The expected outcomes include the source code of the proposed model, one research paper to be published at a top-tier
international conference or journal, and one patent of the proposed algorithm.

Design and Exploration of a General Purpose Stochastic Computing Processor

The rise of Internet of Things (IoT) with millions of edge devices created per year drives the need for computing platforms that have lower power, better fault tolerance and greater computing flexibility. With more and more novel applications and algorithms being rapidly deployed, the traditional approach of using custom hardware to achieve a low power budget will not scale. This project explores the design of an ultra low power, fault tolerant stochastic computing general purpose processor that satisfies the key metrics that IoT edge devices care about while being able to support the rapid shift in applications. Not only will the realization of a stochastic general purpose processor be able to maintain a low power envelope and be resilient through bit-flip errors, stochastic computing’s ability to provide progressive precision (i.e. compute results that start as a rough approximation and become more accurate over time) is often a desirable property for many of the applications in this space (e.g. machine learning).

Day and night location planning for general practitioners

Primary care plays a vital role in the health care system. Challenges in accessing primary care is a growing area of concern globally, with demonstrated negative patient and health system outcomes. Patient and physician preferences for both location and daytime/afterhours access differ. Determining the location of primary care practices that meet the needs of both patients and physicians is a complex optimization problem with multiple criteria.

The specific objectives of the project are to develop a framework to measure and evaluate how well primary care practices cover a population. This will be considered from the physician and patient perspectives and differentiated by daytime versus afterhours needs. Using this framework, we will develop an Operations Research model to recommend an optimal practice network.

The proposed research builds upon collaborations between Dalhousie University and KIT. This project will support applied case studies based on German and Nova Scotia primary care networks.

Optimal spatial movement strategies in foraging among free-ranging Japanese macaques (Macaca fuscata)

Choices allow us to navigate through physical space, to literally or figuratively problem-solve, to achieve goals. While this behavioural phenomenon is common across time and space for our human species, many other species make movement choices as well. The objective of my research is to assess how individual and social factors influence route choice decisions in foraging within a group of free-ranging Japanese macaques (Macaca fuscata). Specifically, I will explore how factors such as life-stage, sex, physical disability, and/or competition impact individual decision-making in a foraging experiment. This study promises to positively contribute to the gap in knowledge surrounding motivations underlying optimal route strategies adopted by Japanese macaques, as well as, providing insight into individual variation and compensatory behaviours adopted in foraging strategies.

Pharmacological properties of selective MT1 receptor partial agonists in an animal model of bipolar disorder.

Preliminary data suggest a possible involvement of the melatonin MT1 but not MT2 receptor in the pathophysiology of bipolar disorder. The main objective of this short project is therefore to investigate at preclinical level whether the first selective MT1 receptor partial agonist to be synthesized (UCM871) can improve the bipolar symptomatology of the mice genetically modified for the Clock gene. This genetically modified mouse model is the one that today best represents the human bipolar pathology in mice. Furthermore, we will start to explore the possible neuronal mechanism of action of the novel drugs. For this purpose, we will use behavioral pharmacology tests that will allow us to evaluate the pharmacological effects of the novel drug on symptoms of mania measured as increased locomotor activity in the open field test. TO BE CONT’D

Using fractal analysis to determine if physical impairment in Japanese macaques (Macaca fuscata) reduces behavioural movement complexity

Free ranging and wild animals sometimes experience challenges of physical wellbeing and optimal movement ability, but assessing if they are stressed in these situations can prove difficult. My research will be focusing on a population of Japanese macaques on Awaji Island, Japan that are born with very high incidences of limb malformations that cause physical impairment. This circumstance provides a rare opportunity to observe behavioural responses to disabilities. Previous work suggests that disabled individuals in the population spend a similar amount of time engaged in locomotion compared to non-disabled individuals since they live within social groups. However, fully understanding and quantifying the costs of these disabilities remains a challenge. Fractal Analysis is a non-invasive method for quantifying subtle variations in the complexity of movement behaviour patterns and sequences. Using Fractal Analysis, I plan to test the hypothesis that impairment caused by congenital limb malformations will alter the complexity of movement behaviours for disabled monkeys under free-ranging conditions; either becoming more stereotypical or conversely more random in their behaviour patterns. This research will potentially reveal whether animals are experiencing subtle difficulties without disturbing them in their natural environments.