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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Optimizing Keyboard Layouts For English Text, David Sommerfield
Optimizing Keyboard Layouts For English Text, David Sommerfield
Research & Creative Achievement Day
QWERTY has been the de facto layout for English text input since its invention in 1874. Its continued usage has led to concerns about its ergonomic shortcomings. Previous attempts at layout creation have usually relied on manual observations of typing data rather than a predictive model. To address this issue, we propose a methodology that incorporates both corpus data from 22 million English websites and 8,228 hours of real-world typing data from participants. The corpus data is processed into bigrams and their number of occurrences. The typing data is preprocessed to exclude user-made typos, and then each bigram is tabulated …
Genetic Association In Entylia Carinata Using Random Forest Classification, Caden J. Harper
Genetic Association In Entylia Carinata Using Random Forest Classification, Caden J. Harper
Research & Creative Achievement Day
The goal of this research was to identify locations in the genome of the Entylia carinata, known as the treehopper, that are associated with anomalous behavior exhibited by the species. Treehoppers are phytophagous insects and are shown to feed, reproduce, and rear their young on specific aster species. Observation has shown that the insects will disregard potential mates in close proximity in favor of those that originate from the same plant species as themselves. This behavior suggests genetic separation in the species based on plant nativity and warrants genetic analysis. Machine learning offers an effective genetic association technique due to …
Enhancing R2l Intrusion Detection Using Decision Trees, Stephen Sommer
Enhancing R2l Intrusion Detection Using Decision Trees, Stephen Sommer
Research & Creative Achievement Day
In the age of advancing technology, artificial intelligence, and big data, Remote to Local (R2L) attacks are increasingly threatening cloud computing environments, heightening concerns about security and privacy. Intrusion detection systems (IDS) using Artificial Intelligence play a role in safeguarding data integrity within databases by swiftly identifying and isolating suspicious records. Furthermore, machine learning techniques enhance the effectiveness of these IDS by continuously adapting to new attack patterns and improving accuracy. This research investigates the use of Decision Tree, a Machine Learning Algorithm for enhancing Remote to Local (R2L) intrusion detection capabilities, utilizing the KDD Cup 1999 dataset and the …