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Articles 1 - 12 of 12
Full-Text Articles in Engineering
Investigation Of Polymer Nanocomposites With Silicon Dioxide Fillers As Helium Cooled High-Temperature Superconducting Cable Dielectrics, Jordan Thomas Cook
Investigation Of Polymer Nanocomposites With Silicon Dioxide Fillers As Helium Cooled High-Temperature Superconducting Cable Dielectrics, Jordan Thomas Cook
Theses and Dissertations
In this thesis, three polymer nanocomposite configurations are fabricated for investigation as dielectrics in helium-cooled high-temperature superconducting (HTS) cables. Polyimide, polyamide, and polymethyl methacrylate are utilized as host polymers. The composite samples are synthesized through an in situ process, dispersing silicon dioxide nanoparticles throughout the polymer hosts. Fourier transform infrared spectroscopy and scanning electron microscopy were employed to validate the synthesis of each composite configuration. Thin film samples of each configuration were also tested for their dielectric strength at both room (300 K) and cryogenic (92 K) temperatures. When going from room to cryogenic temperatures, all materials demonstrated a significant …
Low Temperature Dielectric Strength Of Polyimide-Silica Nanocomposites For Applications In High-Temperature Superconducting Cables, Michael John Mccaffrey
Low Temperature Dielectric Strength Of Polyimide-Silica Nanocomposites For Applications In High-Temperature Superconducting Cables, Michael John Mccaffrey
Theses and Dissertations
Gaseous helium is often considered as an alternative to liquid nitrogen to cool modern high-temperature superconducting cables in support of increased power capacity and/or reduction of required cable size. However, the small size of helium molecules and relatively poor dielectric strength of helium gas create challenges which limit the usefulness of modern cable dielectrics. Continuous dielectric coatings have been considered as an alternative to traditional lapped tape dielectrics to support gaseous helium refrigerants, but unmatched thermal contraction between the coating and cable components would induce failures due to mechanical stress. Composite materials have been considered as a means of matching …
A Machine Learning Framework For Automatic Speech Recognition In Air Traffic Control Using Word Level Binary Classification And Transcription, Fowad Shahid Sohail
A Machine Learning Framework For Automatic Speech Recognition In Air Traffic Control Using Word Level Binary Classification And Transcription, Fowad Shahid Sohail
Theses and Dissertations
Advances in Artificial Intelligence and Machine learning have enabled a variety of new technologies. One such technology is Automatic Speech Recognition (ASR), where a machine is given audio and transcribes the words that were spoken. ASR can be applied in a variety of domains to improve general usability and safety. One such domain is Air Traffic Control (ATC). ASR in ATC promises to improve safety in a mission critical environment. ASR models have historically required a large amount of clean training data. ATC environments are noisy and acquiring labeled data is a difficult, expertise dependent task. This thesis attempts to …
A Broad Spectrum Defense Against Adversarial Examples, Sean Mcguire
A Broad Spectrum Defense Against Adversarial Examples, Sean Mcguire
Theses and Dissertations
Machine learning models are increasingly employed in making critical decisions across a wide array of applications. As our dependence on these models increases, it is vital to recognize their vulnerability to malicious attacks from determined adversaries. In response to these adversarial attacks, new defensive mechanisms have been developed to ensure the security of machine learning models and the accuracy of the decisions they make. However, many of these mechanisms are reactionary, designed to defend specific models against a known specific attack or family of attacks. This reactionary approach does not generalize to future "yet to be developed" attacks. In this …
A Deep Learning Approach For Airport Runway Identification From Satellite Imagery, Mahmut Gemici
A Deep Learning Approach For Airport Runway Identification From Satellite Imagery, Mahmut Gemici
Theses and Dissertations
The United States lacks a comprehensive national database of private Prior Permission Required (PPR) airports. The primary reason such a database does not exist is that there are no federal regulatory obligations for these facilities to have their information re-evaluated or updated by the Federal Aviation Administration (FAA) or the local state Department of Transportation (DOT) once the data has been entered into the system. The often outdated and incorrect information about landing sites presents a serious risk factor in aviation safety. In this thesis, we present a machine learning approach for detecting airport landing sites from Google Earth satellite …
Detection Of Rotorcraft Landing Sites: An Ai-Based Approach, Abdullah Nasir
Detection Of Rotorcraft Landing Sites: An Ai-Based Approach, Abdullah Nasir
Theses and Dissertations
The updated information about the location and type of rotorcraft landing sites is an essential asset for the Federal Aviation Administration (FAA) and the Department of Transportation (DOT). However, acquiring, verifying, and regularly updating information about landing sites is not straightforward. The lack of current and correct information about landing sites is a risk factor in several rotorcraft accidents and incidents. The current FAA database of rotorcraft landing sites contains inaccurate and missing entries due to the manual updating process. There is a need for an accurate and automated validation tool to identify landing sites from satellite imagery. This thesis …
Augmenting Heads-Up Displays With Intelligent Agents: A Human Factors Approach, Grant Edward Morfitt
Augmenting Heads-Up Displays With Intelligent Agents: A Human Factors Approach, Grant Edward Morfitt
Theses and Dissertations
Situational awareness, both tactical and strategic, is essential for humans engaged in complex tasks in civilian and military theaters of operation. Previous work has shown that heads-up displays are effective tools for providing critical information to operators in such situations. Hitherto, heads-up displays have been designed to relay instrument and sensor information to the operator in a topical, timely, and accurate manner. There is a large body of complementary work in the area of human factors that deals with presenting information to a user without detracting from the primary mission. This thesis investigates, measures, and validates the effectiveness of a …
Student Modeling And Analysis In Adaptive Instructional Systems, Jing Liang, Ryan Hare, Tianyu Chang, Fangli Xu, Ying Tang, Fei-Yue Wang, Shimeng Peng
Student Modeling And Analysis In Adaptive Instructional Systems, Jing Liang, Ryan Hare, Tianyu Chang, Fangli Xu, Ying Tang, Fei-Yue Wang, Shimeng Peng
Henry M. Rowan College of Engineering Faculty Scholarship
There is a growing interest in developing and implementing adaptive instructional systems to improve, automate, and personalize student education. A necessary part of any such adaptive instructional system is a student model used to predict or analyze learner behavior and inform adaptation. To help inform researchers in this area, this paper presents a state-of-the-art review of 11 years of research (2010-2021) in student modeling, focusing on learner characteristics, learning indicators, and foundational aspects of dissimilar models. We mainly emphasize increased prediction accuracy when using multidimensional learner data to create multimodal models in real-world adaptive instructional systems. In addition, we discuss …
Sub-Nyquist Optical Pulse Sampling For Photonic Blind Source Separation, Taichu Shi, Yang Qi, Weipeng Zhang, Paul Prucnal, Jie Li, Ben Wu
Sub-Nyquist Optical Pulse Sampling For Photonic Blind Source Separation, Taichu Shi, Yang Qi, Weipeng Zhang, Paul Prucnal, Jie Li, Ben Wu
Henry M. Rowan College of Engineering Faculty Scholarship
We propose and experimentally demonstrate an optical pulse sampling method for photonic blind source separation. The photonic system processes and separates wideband signals based on the statistical information of the mixed signals, and thus the sampling frequency can be orders of magnitude lower than the bandwidth of the signals. The ultra-fast optical pulses collect samples of the signals at very low sampling rates, and each sample is short enough to maintain the statistical properties of the signals. The low sampling frequency reduces the workloads of the analog to digital conversion and digital signal processing systems. In the meantime, the short …
Image Processing Algorithms For Detection Of Anomalies In Orthopedic Surgery Implants, Alexander William Wiese
Image Processing Algorithms For Detection Of Anomalies In Orthopedic Surgery Implants, Alexander William Wiese
Theses and Dissertations
Orthopedic implant procedures for hip implants are performed on 300,000 patients annually in the United States, with 22.3 million procedures worldwide. While most such operations are successfully performed to relieve pain and restore joint function for the duration of the patient's life, advances in medicine have enabled patients to outlive the life of their implant, increasing the likelihood of implant failure. There is significant advantage to the patient, the surgeon, and the medical community in early detection of implant failures.The research work presented in this thesis demonstrates a non-invasive digital image processing technique for the automated detection of specific arthroplasty …
Malware Binary Image Classification Using Convolutional Neural Networks, John Kiger, Shen-Shyang Ho, Vahid Heydari
Malware Binary Image Classification Using Convolutional Neural Networks, John Kiger, Shen-Shyang Ho, Vahid Heydari
Faculty Scholarship for the College of Science & Mathematics
The persistent shortage of cybersecurity professionals combined with enterprise networks tasked with processing more data than ever before has led many cybersecurity experts to consider automating some of the most common and time-consuming security tasks using machine learning. One of these cybersecurity tasks where machine learning may prove advantageous is malware analysis and classification. To evade traditional detection techniques, malware developers are creating more complex malware. This is achieved through more advanced methods of code obfuscation and conducting more sophisticated attacks. This can make the manual process of analyzing malware an infinitely more complex task. Furthermore, the proliferation of malicious …
Technical Analysis Of Thanos Ransomware, Ikuromor Ogiriki, Christopher Beck, Vahid Heydari
Technical Analysis Of Thanos Ransomware, Ikuromor Ogiriki, Christopher Beck, Vahid Heydari
Faculty Scholarship for the College of Science & Mathematics
Ransomware is a developing menace that encrypts users’ files and holds the decryption key hostage until the victim pays a ransom. This particular class of malware has been in charge of extortion hundreds of millions of dollars every year. Adding to the problem, generating new variations is cheap. Therefore, new malware can detect antivirus and intrusion detection systems and evade them or manifest in ways to make themselves undetectable. We must first understand the characteristics and behavior of various varieties of ransomware to create and construct effective security mechanisms to combat them. This research presents a novel dynamic and behavioral …