Browsing School of Computing and Engineering (UMKC) by Thesis Semester "2022 Fall"
Now showing items 1-6 of 6
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3D Printing of Microneedles via Embedded 3D Printing using an Associative Surfactant System
(2022)Microneedles are drug-delivery devices specially adapted to penetrate the outer-most layer of the epidermis (stratum corneum). These devices have gained popularity over the last decades because they provide non-invasive ... -
Adaptive Data-driven Optimization using Transfer Learning for Resilient, Energy-efficient, Resource-aware, and Secure Network Slicing in 5G-Advanced and 6G Wireless Systems
(2022)5G–Advanced is the next step in the evolution of the fifth–generation (5G) technology. It will introduce a new level of expanded capabilities beyond connections and enables a broader range of advanced applications and use ... -
Constant Time Sorting and Searching
(2022)To study the sorting of real numbers into a linked list on Parallel Random Access Machine model. To show that input array of n real numbers can be sorted into a linked list in constant time using n²/logᶜn processors for ... -
Human Factors in Smart and Connected Communities
(2022)The vision of Smart Connected Community (SCC) is to integrate technology to improve economy, safety, education, health and provide equity in the society. Human factor plays a vital role in the SCC in human societal, ... -
Investigating the effect of Lacunocanalicular Network Morphology Alteration Due To Aging on Osteocyte FFSS Using Computational Modeling
(2022)Exercise and physical activity exert mechanical loading on the bones, stimulating bone formation. Osteocytes are thought to be the bone cells that sense and respond to mechanical loading and that loading induces bone strains ... -
Optimization of Handover, Survivability, Multi-Connectivity and Secure Slicing in 5G Cellular Networks using Matrix Exponential Models and Machine Learning
(2022)This works proposes optimization of cellular handovers, cellular network survivability modeling, multi-connectivity and secure network slicing using matrix exponentials and machine learning techniques. We propose matrix ...