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Workshop 4: Bench top to the conveyor belt: Steps toward the commercialization of scientific innovations

The majority of scientific discoveries remain confined to dissertations and peer review publications where they remain hidden from their possible industrial applications. Given the challenges offered by current global events like environmental pollution, climate change effects, and diseases, the need for more rapid transmission of scientific discoveries from the realm of postgraduate dissertations and research papers to industrial applications is most critical. Hence, the need for a clear road map, allowing the connection of both pure and applied scientific discoveries to their industrial applications is obvious. Of course, for this to be achieved, a clear understanding of the constituent steps of such a process is germane. Hence, this brief workshop aims to map a possible path for achieving the aforementioned central goal, using previous experiences and examples.

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November 8, 2022
11:00 am
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Day 2
  —  
1:45 pm

A SURVEY OF NATIVE AND INVASIVE ALIEN LIVEBEARING FISH SPECIES IN JAMAICAN RIVERS

Invasive alien species (IAS) are implicated in the extinction or decline of numerous native aquatic species worldwide. Their negative impacts occur through mechanisms including habitat alteration, competition, predation, hybridisation, and the spread of disease (Strayer et al. 2006). Small island ecosystems are most susceptible to the impacts of IAS. Once established, freshwater IAS are difficult to eradicate without negatively impacting native species.

Day 3
  —  
3:30 pm

Grand Innovation Challenge

The FORECAST Grand Innovation Challenge 2022 (GIC) is to develop a feasible innovation (prototype/product/concept) that will revolutionize the management, protection, and use of water resources in the Caribbean.

Day 4
  —  
10:00 am

AN ACO-BASED ALGORITHM FOR HETEROGENEOUS COMPUTING ENVIRONMRNTS USING PRIORITY QUEUES

In parallel and distributed computing environments, task scheduling, where the basic idea is minimizing time loss and maximizing performance, is an absolutely critical component. Scheduling in these environments is NP-hard, so it is important that we continue to search and find the most efficient and effective ways of mapping tasks to processors. One such effective approach is known as Ant Colony Optimization (ACO). This popular optimization technique is inspired by the foraging behavior of ants in their colonies to find the shortest paths between their nests and food sources.

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