The goal of this project is to develop a more advanced cost-effective algorithm that can detect the road condition. The pressures signal from the pressure transducers installed on the struts of the off-road trucks are acquired and analyzed. The relationship between the road condition and pressure changes will be studied and researched. Based on the study and research, a road condition monitoring data model can be developed, and bad road condition event concept can be developed and defined. The data model can be implemented in a real-time mobile controller.
Sweet basil is a leafy, flavourful and fragrant herb commonly used many types of cooking. It has not only nutrient values but also many health benefits. Basil likes warm growing environment; therefore, it is commonly produced in greenhouses in Canada. To keep leafy vegetables fresh, right after harvesting majority of them are normally stored and transported at about 4 ºC. However, basil can quickly become black and not sellable when kept at that temperature. To store and transport basil separately is logistically difficult and costly.
Research into equine stem cells as regenerative medicine has been ongoing for over 20 years. Stem cell technologies hold promise for healing musculoskeletal tissues and wounds, fighting bacterial infections, and treating inflammatory conditions, but definitive evidence of the safety and therapeutic efficacy of these technologies have not yet been proven. A major limiting factor for conducting clinical trials to prove safety and efficacy is the lack of sufficient cell numbers with reproducible, standardized, and characterized properties.
This work will examine a novel “smart” insole that allows for the quantification of specialized running metrics and will compare the outputs with the gold-standard measure of metabolic work. The insoles work by collecting pressure data from many sensors embedded in the insole, and sending this to an phone app. We are comparing the insoles and their ability to model running power and economy both in the lab and in field conditions where factors that affect the work of running will change. This includes factors such as the running surface, grade, and external resistance.
Cyber attackers can sometimes compromise endpoint machines. They may perform malicious actions that will damage the company. As a result, it is necessary to collect forensics artifacts (Information from the endpoint machine that can be used to trace the attackers' behaviors) from the compromised machine for investigation. With the information we have, we may reconstruct malicious files, determine the goal of these attacks, or know how and when this attack happened. This project aims to automatically collect these forensics artifacts from endpoint machines and upload them to a secure portal.
Wild boars (Sus scrofa) are a highly invasive species which causes destructive damages to property and crops and poses a major threat to the Canadian pork industry because wild boars are also reservoirs for infectious diseases, including African swine virus (ASF). Current control and management of the wild boar populations have been ineffective because these animals are highly adaptive to human intervention measures such as fencing and hunting. In this proposal, we explore the feasibility of a genetics-based fertility control strategy.
Pipeline alerts are beneficial to analysts to determine where their attention is needed. However, a high false positive rate leads to a noisy stream and wastes analysts’ time. The first sub-project will aim to classify the alerts as either low or high likelihood of a false positive, allowing analysts to spend their time where it is most effective.Living-off-the-Land binaries (Lolbins) is an increasingly common technique among attackers, yet there is currently little detection for such an attack.
Fertility improvement is important in both human being and livestock industry. Increasing the oocyte competence is one of the most critical measures for fertility improvement. miRNAs are small non-coding RNAs which can regulate the estrogen production in the ovarian follicles which in turn affecting the oocyte development and competence. However, its underlying mechanism remains unknown.
Glioblastoma is the most common type of adult brain cancer. Glioblastoma tumors are very aggressive because these cells can rapidly invade deep into healthy tissue, which makes them particularly difficult to attack with current treatment options including surgery, radiotherapy, and chemotherapy.
The goal of the project is to assess the viability of current synthetic data generation systems. If the generated synthetic data is accurate enough without providing sensitive details it can be used to train machine learning models without needing to share sensitive information. The particular application of this project is to computer logs which can contain sensitive information about the computer systems themselves or the individuals using them.