Saudi Cultural Missions Theses & Dissertations
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Item Restricted Detecting Makeup Activities using Internet-of-Things(University of Maryland Baltimore County, 2019-07) Alqurmti, Fatimah; Roy, NirmalyaThis thesis focuses on identifying human activities for rendering make-up activities using sensors’ data and a supervised machine learning approaches. We considered five make-up activities in our work, such as, applying cream, lipsticks, blusher, eyeshadow, and mascara. We collected the data from ten participants using two smart-watch built-in sensors, accelerometer and gyroscope. We preprocessed the data and trained with different predictive machine learning models and we evaluated make-up activity prediction built on using Naïve Bayes, Simple Logistic, k-nearest neighbors’, and the random forest algorithms. We investigated the models' performance on three different datasets that differ by the environment they were collected in. The first dataset was collected from the participants using a controlled environment. In this staged setting, we provided the participants specific instructions on how to perform the five make-up activities. The second dataset was collected from the participants in an uncontrolled environment. We did not inform the participants with any prior instructions on how to perform the five activities and therefore, naturally they performed the make-up activities in their own way. Third, we synthetically generated a dataset by combining the existing datasets from the participants who were under both controlled and uncontrolled environments. Our results showed a 92.7 % accuracy for the controlled environment case given by the Gradient Boosting classifier and an 89.20 % accuracy for the uncontrolled environment case shown by the Random Forest classifier. Finally, Random Forest classifier registered the highest accuracy 92%, for the hybrid case where both the datasets from controlled and the uncontrolled environments were combined. We believe that this early work on recognizing and discovering a multitude of make-up activities has potential application in assessing and training the performance of various stakeholders in the future work of fashion industry.8 0Item Restricted IMPROVING CONTINUITY AND QUALITY ASSURANCE IN INTERNET OF THINGS INFRASTRUCTURE USING BLOCKCHAIN(Saudi Digital Library, 2022) Alshehri, Hussain Ali; Tanik, Murat; Jololian, Leon; Haider, Mohammad; Lingasubramanian, Karthik; Wells, Buren EarlIn this research I present a rigorous study on the service continuity and quality assurance using the Internet of Things (IoT). The research aims at identifying risks and improving the risk mitigation tools that are currently in use for improving the IoT performance, and for pushing forward the implementation of IoT in mission critical applications. This objective can be accomplished by identifying the impact of the strategic planning, quality assurance, performance assurance, and risk management on the IoT used in businesses. While the focus is mainly on the business continuity domain, the technical aspects of IoT solutions are also covered. The unique contributions are two folds. First, the service continuity objects are recognized and categorized with their properties. Second, several methods are proposed to mitigate the service fallbacks and reduce the risk factors in IoT service discontinuity. The contribution of the research should extend to the technical aspect of IoT. Little work has been done to assess the IoT technology risks in ultra-low power devices. The implementation of these devices is on the rise and more work has to be done to ensure that they meet the minimum continuity certification requirements with reliability, availability and responsiveness. In this research, I will try to find the optimal solution with continuity and quality assurance when we use the IoT. This is by using strategic plans based on international standard strategic foundations and theories, after obtaining the actual results from the strategic planning tools. Moreover, several factors must be taken into consideration, such as reliability, availability, speed of response, continuity, and quality. To the best of my knowledge, this work is one of the first to reflect on IoT continuity in a business assurance context. It also presents a unique approach in identifying the objects contribution to the business assurance by identifying static parameters that are persistent over time, and variable parameters that change over the course of time. In my approach I identify seven areas for IoT continuity and quality assurance: connected manufacturing, asset tracking, marketing, transportation and delivery, smart technologies, data and analytics, and security.32 0