Improving Construction Permitting Process using Predictive Analytics

In public sector, the decision making of construction permitting can have direct impacts on the ongoing urban development. The efficiency and predictability of the review process is critical for municipalities to provide timely and accurate results to the public. As the review process is managed digitally with process data available, using data analytics to develop predictive models can result in improvement of efficiency and predictability.

Application of Light Detection and Ranging in Right-of-Way Management Program

Light detection and ranging (LiDAR) is a method that uses light in the form of a pulsed laser to measure variable distances. These pulses are combined with other data (Global Navigation Satellite System (GNSS) and inertial navigation system (INS)) to precisely obtain the position of points over the shape of the earth and its surface characteristics. The capability of LiDAR to collect an enormous amount of data makes it perfect for pipeline right-of-way (ROW) management.

Relation between biometrics and traumatic brain injury risk: developing a data analysis procedure for concussion risk assessment and management

This project will attempt to uncover more insights into the importance of certain biological, situational and environmental factors that contribute to traumatic brain injuries (TBIs), especially in youth sports. By doing this, we hope to work towards better prediction, prevention, diagnosis and treatment of concussions and other TBIs.

Symbolic Model-Based Design of a Semi-Autonomous Vehicle Prototype Implementing Independent Wheel Torque Vectoring for Training an Advanced Driver Assistance System

There is a strong belief that autonomous vehicles will play a vital role in the future of the global transportation economy. There, however, exists many open challenges which need to be overcome to realize this future vision. One such challenge is the acceptance from the driver to relinquish full control of a vehicle and ultimately putting one’s safety in the hands of a computer.

Security Risk and Control Modeling for Deep Learning using the SAGETEA Methodology

SageTea Software will contribute expertise in working with Smalltalk and the SAGETEA model. This includes demonstrating the current database model and how it works. SageTea Software will also demonstrate its current implementation of Deep Learning libraries on the Python side including Tensorflow, Kibana and Elastic Search. We will provide expertise in the SAGETEA methodology and assist the researcher with developing additional mathematical analysis, software analysis design and coding. We will assist with testing and also supply infrastructure including cloud environments and software tools.

Autonomous next generation wireless communication network optimization

Since the mid 1980s, moving access points, such as Wi-Fi, closer to network devices has been the largest contributer to improved data rates and this trend continues, but its scope is more difficult for rural internet service providers. The second technique is from the choice of the assigned spectrum and how this choice relates to other techniques to improve data rates. The third technique is from a combination of advanced signal processing techniques, involving antennas, beamforming, the allocation of available bandwidth and sampling the radio channels.

Bond dependent shear behaviour of hollow core plank core plugs

Hollow core planks are used as floor systems in some structures. These planks are precast offsite of the structure and shipped to the building site for installation. They rely on the use of prestressing steel to help span large distances with minimal depth. The planks have several large voids in the interior of the concrete cross-section which results in a lower weight, more efficient structural element. These voids can cause strength problems in some circumstances, but this is mitigated by selectively filling the voids with concrete after casting of the planks.

Enhancing Reach and Penetration of Global Potato Industry Using Multi Channel Data Driven Strategies

Food Innovation Online Corp (FIO) is a New Brunswick(NB) based company that operates a website targeting the global potato industry. This website - PotatoPro.com - is the #1 website in the potato sector worldwide. As a result, the company has access to a large amount of data on the interests and information needs of this sector.

To bring this to the next level, the company has decided to move to a more formal data-driven decision model.

Advancing Strong-Scaling CFD Simulations on Manycore HPC Hardware

Science and engineering companies rely on powerful computers to simulate, in virtual space, the performance of new processes and products. The computer architectures of these systems are evolving to provide even faster virtual solutions with less energy requirements. This hardware evolution impacts software design and implementation of simulation tools such as Computational Fluid Dynamics (CFD). The intern’s project involves software design and implementation related to novel CPU/GPU parallel computers and the CFD software used by the partner organization.

Work Improvement and Data Analytics for Industrial Steel Fabrication

Work improvement is critical for performance increase in business environments. It is used to identify bottlenecks and inefficiencies in the manufacturing and other production processes, and to improve work performance by removing non-value-added activities. To conduct work improvement, the Lean Manufacturing concept is often used along with the Value Stream Mapping (VSM), a tool for visualizing the production processes and productivity metrics.

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