Browsing The University of Oklahoma by Author "MacDonald, Gregory"
Now showing items 1-12 of 12
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Adaptive Distributed Source Coding Based on Bayesian Inference
Chen, Feng (2015-08-14)Distributed Source Coding (DSC) is an important topic for both in information theory and communication. DSC utilizes the correlations among the sources to compress data, and it has the advantages of being simple and easy ... -
AI BASED FAULT DIAGNOSIS IN EMERGING CELLULAR NETWORKS
Bothe, Shruti (2019-08)Mobile cellular network operators spend nearly a quarter of their revenue on network management and maintenance. A significant portion of that budget, is spent on resolving faults diagnosed in the system that degrade or ... -
THE APPLICATION OF MULTIVARIATE DISTANCE MATRIX REGRESSION IN TRANSPORTATION FOR TRAFFIC ANALYSIS
SHAB KALEIA, MUHANAD (2017-12)A critical function of intelligent transportation systems is studying and analyzing the effects of road condition variables (e.g. construction, severe weather, and the like) on traffic to aid in improving road designs, ... -
BIG DATA ANALYTICS SOLUTION FOR SMALL CELLS DEPLOYMENT USING MACHINE LEARNING TECHNIQUES
Daware, Sachin (2016-12)This thesis presents a “Novel Small Cell Planning Solution using Machine learning”. The Telecom service providers are interested in estimating various trends in order to plan future upgrades and deployments driven by real ... -
DETECTING EAVESDROPPING ACTIVITY IN FIBER OPTIC NETWORKS
MacDonald, Gregory (2012)The secure transmission of data is critical to governments, military organizations, financial institutions, health care providers and other enterprises. The primary method of securing in-transit data is though data ... -
Energy Efficient Machine Learning-Based Classification of ECG Heartbeat Types
Hartmann, Morghan (2018-12-05)To meet the accuracy, latency and energy efficiency requirements during real-time collection and analysis of health data, a distributed edge computing environment is the answer, combined with 5G speeds and modern computing ... -
Enhanced Capsule-based Networks and Their Applications
Zhao, Zhihao (2022-12)Current deep models have achieved human-like accuracy in many computer vision tasks, even defeating humans sometimes. However, these deep models still suffer from significant weaknesses. To name a few, it is hard to interpret ... -
HAND GESTURES FOR DRONE CONTROL USING DEEP LEARNING
Hadri, Soubhi (2018-12)Commercial drones, also known as unmanned aerial vehicles (UAVs), are rapidly becoming more prevalent and are used in many different applications, such as surveillance for sporting events, transportation for emergency ... -
Online closed-loop tACS-fMRI for brain modulation
Mulyana, Beni (2022-07-20)Recent studies suggest that transcranial electrical stimulation (tES) can be performed during functional magnetic resonance imaging (fMRI). The novel approach of using concurrent tES-fMRI to modulate and measure targeted ... -
Potential Application of Machine Learning in Optical Communication Systems
Elgrew, Mohamed (2017-07-07)In this work, we will examine practically encoding information in the state of polarization using M- POLSK. We employ polarization-shift keying (POLSK) to generate an expected pattern of changing states of polarization ... -
SON: PREDICTING THE NATURE OF SERVICE DISRUPTIONS IN CELLULAR NETWORKS
Madabushi, Hemanth (2016-12)An important aspect of communication is involved in its cellular network. To meet the demands, communication requires the next generation cellular network, i.e., self organizing networks (SON). In order to implement a ... -
THEORETICAL STUDIES OF MULTI-MODE NOON STATES FOR APPLICATIONS IN QUANTUM METROLOGY AND PROPOSALS OF EXPERIMENTAL SETUPS FOR THEIR GENERATION
Zhang, Lu (2018-05)Quantum entanglement is a fascinating physical resource that is central to the field of quantum information processing with important applications in such areas as quantum computing, quantum communication, quantum metrology, ...