Antipsychotic medication is associated with a constellation of metabolic abnormalities, including weight gain, an imbalance between glucose and insulin actions, and higher than normal lipid content. In particular, adolescent psychiatric patients are at increased risk for Type II Diabetes and cardiovascular disease when undergoing therapeutic treatment. Current analysis indicates that antipsychotic drugs have differing effects on body weight gain and fat content.
This research aims to develop a system that generates explainable recommendations. Mobio currently allows merchants to offer items to users, but does not employ recent advances in recommender systems. This project will allow Mobio to build on the expertise of Dr. Chiang in related relational learning problems to create such a system, and provide a real-world domain for him to advance the state-of-the-art. A core problem in recommender systems is building models of user preference that are predictive and explainable. We propose to apply and evaluate algorithms developed by Dr.
The goal of this project is to research and develop a model that is suitable for BC Hydro’s application to predict the sag of a power transmission line from its induced frequency response. Transmission lines always elongate over time due to the temperature of the conductor. The ability to monitor and obtain the shape of transmission lines is one of the most important tools in evaluating power transmission line’s effectiveness in operation, maintenance and the most important, safety.
Although there is growing awareness of the need for sports events to take account of their environmental impacts and be “greener”, few sports organizations comprehensively assess their environmental performance due to the lack of tailored methods and tools. Small events in particular have limited resources and would benefit from a simplified assessment approach that allows them to rapidly estimate impacts. Through this study, Quantis aims to develop a new tool and method, using a life cycle assessment approach, to be applied to the sport event sector.
This project involves creating a comprehensive method for developing and maintaining a Meta-model for the representation of Role and Request Modeling (R2M) constructs based on the notion of ontologies. R2M provides clear definitions and semantics for the constructs of conceptual models as well as a set of rules for guiding the modeling process. Currently, there are some challenges in evolving and maintaining R2M such as ensuring the consistency of any new rule with the set of existing rules and ensuring that a model conforms all R2M rules.
Metafor is developing a new class of IT system management solutions and as a part of this, Metafor wants a method to show differences between multiple deployed instances of an application. To implement this, Metafor requires an accurate and high-performance generalized tree differencing algorithm. Differencing algorithms are used for comparing different versions of a document or snapshots of data to find similarities and differences between them. And tree differencing algorithms perform differencing on hierarchical or treestructured data.