School of Engineering and Technology (SET) Researches

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    Comparison of COVID-19 Severity Between Tropical and Non-Tropical Countries
    (International Journal of Infection., 2020-06-13) flor, Tushabe
    Abstract Coronavirus disease 2019 (COVID-19) has affected the whole world. However, it is not clear whether the disease affects all countries equally. This paper analyzes the severity of COVID-19 in tropical and temperate countries by comparing the data of infections and deaths registered four months after the onset of the disease. Data were segregated, summarized, visualized, and interpreted. The severity of the disease was quantified in each country and recommendations were made for both categories of countries. The re search found that the severity of the disease in terms of infection or death was six times more in countries located in the temperate region. Keywords: Coronavirus, COVID-19, Tropics, Tropical Countries, Temperate, Temperate Countries
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    Motion Prediction with Gaussian processes for Safe Human-Robot Interaction in Virtual Environments
    (IEEE, 2023) STANLEY, MUGISHA; VAMSI, KRISHNA GUDA; CHRISTINE, CHEVALLEREAU; DAMIEN, CHABLAT; MATTEO, ZOPPI
    ABSTRACT Humans use collaborative robots as tools for accomplishing various tasks. The interaction between humans and robots happens in tight shared workspaces. However, these machines must be safe to operate alongside humans to minimize the risk of accidental collisions. Ensuring safety imposes many constraints, such as reduced torque and velocity limits during operation, increasing the time to accomplish manytasks.However,forapplicationssuchasusingcollaborativerobotsashapticinterfaceswithintermittent contacts, speed limitations result in poor user experiences. This research aims to improve the efficiency of a collaborative robot while improving the safety of the human user. We used Gaussian process models to predict human hand motion and developed strategies for human intention detection to improve the time for the robot while improving human security in a virtual environment. We then studied the effect of prediction. Results from comparisons show that the strategies with prediction model improved robot time by 3% and safety by 17%. When used alongside gaze for prediction, the strategy based on the Gaussian process model resulted into an improvement of the robot time by 2% and the safety by 13%.
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    Prevalence of Aflatoxin Contamination Across the Food Value Chain for Maize and Groundnuts in Uganda
    (Acta Scientific AGRICULTURE, 2023-04-11) Florence, Tushabe; Samuel, Mwesige; Okoth, Thomas; Ivan, Kasamba; Areu, David
    Abstract Background: Maize and groundnuts are some of the most highly contaminated foods on the Ugandan market. Since 2006 there have been some scattered studies on the prevalence of aflatoxin contamination among these grains. However, there were no recent studies of 2022 to highlight the status of aflatoxin contamination. Methods: Grain samples were collected from two highest producing districts that is Masindi and Soroti districts; and across the value chain, from farmers to wholesalers, retailers, processors and restaurants/homes. The samples were tested using ELISA method and the prevalence calculated. Results: Aflatoxins were detected in 45% and 30% of maize and groundnuts, respectively. Contamination increases over the value chain from 31% at farm level, to 42% at table level. In general, contamination was highest among processors at 43%, followed by restaurants (42%), wholesalers (40%), farmers (31%) and retailers at 29%. Keywords: Aflatoxins; Prevalence; Maize; Corn; Groundnuts; Gnuts; Uganda; Value Chain