Browsing by Subject "ranking"

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    Ranking and Visualizing Clusters of the US States by Adversity Childhood Experiences
    (2023) Do, Anh Phuong; Rashid, Mamunur; Sarkar, Jyotirmoy; Rashid, Maieasha Shifa; Mathematical Sciences, School of Science
    Adverse Childhood Experiences (ACEs) refer to traumatic childhood events like emotional, physical, sexual abuse, and other forms of household dysfunction. ACEs are associated with biomarkers for chronic diseases resulting in early mortality and increased morbidity. According to the Centers for Disease Control and Prevention, ACEs are common: Around 61% of adults across 25 US states reported having experienced at least one type of ACE. Ranking and finding clusters of the US states on ACEs provide a better understanding of the situation and helps prevent or reduce the occurrence of ACEs. The paper aims to apply a Multiple Criteria Decision-Making Model called the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method and calculate the overall Composite Index‘ to rank the states. Furthermore, the study uses the K-Means Cluster algorithm to identify and visualize clusters of states experiencing similar ACEs. The BRFSS 2019 data set was used for all analyses. The TOPSIS method suggested that Tennessee had the worst status of ACEs (ranked first) and North Dakota performed the best (ranked last). The elbow method determined that four clusters were present out of the 21 states. Many states ranked with the highest ACEs were clustered together: Tennessee, Florida, Pennsylvania, New Mexico, Delaware, Michigan. To better understand the current performance of the US regarding ACEs, it would be best to collect data from all states. Diagnostic studies, such as this study, can create the foundation for addressing and eradicating child maltreatment and ensuring healthy and nurturing childhoods.
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    Ranking of Android Apps based on Security Evidences
    (2020-12) Maharjan, Ayush; Raje, Rajeev R.; Tuceryan, Mihran; Zou, Xukai
    With the large number of Android apps available in app stores such as Google Play, it has become increasingly challenging to choose among the apps. The users generally select the apps based on the ratings and reviews of other users, or the recommendations from the app store. But it is very important to take the security into consideration while choosing an app with the increasing security and privacy concerns with mobile apps. This thesis proposes different ranking schemes for Android apps based on security apps evaluated from the static code analysis tools that are available. It proposes the ranking schemes based on the categories of evidences reported by the tools, based on the frequency of each category, and based on the severity of each evidence. The evidences are gathered, and rankings are generated based on the theory of Subjective Logic. In addition to these ranking schemes, the tools are themselves evaluated against the Ghera benchmark. Finally, this work proposes two additional schemes to combine the evidences from difference tools to provide a combined ranking.