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Articles 181 - 210 of 1069

Full-Text Articles in Computer Engineering

Coding Club, Nicole Livingston, Madalyn Meyer Apr 2021

Coding Club, Nicole Livingston, Madalyn Meyer

Honors Program: Expanded Learning Clubs

Lesson plans for an about 12-week club designed to introduce middle schoolers to coding using Scratch. By the end of the club, every student will have made a game they can share with the class and have learned basic coding and game creation tools. Students can also miss classes or join late and still be able to join and enjoy the club with a different focus lesson every week.


Learning Discriminative And Efficient Attention For Person Re-Identification Using Agglomerative Clustering Frameworks, Kshitij Nikhal Apr 2021

Learning Discriminative And Efficient Attention For Person Re-Identification Using Agglomerative Clustering Frameworks, Kshitij Nikhal

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Recent advancements like multiple contextual analysis, attention mechanisms, distance-aware optimization, and multi-task guidance have been widely used for supervised person re-identification (ReID), but the implementation and effects of such methods in unsupervised person ReID frameworks are non-trivial and unclear, respectively. Moreover, with increasing size and complexity of image- and video-based ReID datasets, manual or semi-automated annotation procedures for supervised ReID are becoming labor intensive and cost prohibitive, which is undesirable especially considering the likelihood of annotation errors increase with scale/complexity of data collections. Therefore, this thesis proposes a new iterative clustering framework that incorporates (a) two attention architectures that learn …


Classification Of Primary Versus Metastatic Pancreatic Tumor Cells Using Multiple Biomarkers And Whole Slide Imaging, Poupack Pooshang Baghery Apr 2021

Classification Of Primary Versus Metastatic Pancreatic Tumor Cells Using Multiple Biomarkers And Whole Slide Imaging, Poupack Pooshang Baghery

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Pancreatic cancer is a challenging cancer with a high mortality rate and a 5-year survival rate between 2% to 9%. The role of biomarkers is crucial in cancer prognosis, diagnosis, and predicting the possible responses to a specific therapy. The Discovery and development of various types of biomarkers have been studied intensively in the hope of determining the best treatment approaches, better management, and possibly cure of this deadly cancer. However, metastasis, responsible for about 90% of the deaths from cancer, is still poorly understood. A few research that have investigated the expression of a particular biomarker or a panel …


Recent Advances In Terahertz Photonic Technologies Based On Graphene And Their Applications, Tianjing Guo, Christos Argyropoulos Mar 2021

Recent Advances In Terahertz Photonic Technologies Based On Graphene And Their Applications, Tianjing Guo, Christos Argyropoulos

Department of Electrical and Computer Engineering: Faculty Publications

Graphene is a unique 2D material that has been extensively investigated due to its extraordinary photonic, electronic, thermal, and mechanical properties. Excited plasmons along its surface and other unique features are expected to play an important role in many emerging photonic technologies with drastically improved and tunable functionalities. This review is focused on presenting several recently introduced photonic phenomena based on graphene, beyond its usual linear response, such as nonlinear, active, topological, and nonreciprocal effects. The physical mechanisms and various envisioned photonic applications corresponding to these novel intriguing functionalities are also reported. The presented graphene-based technologies promise to revolutionize the …


Kegg2net: Deducing Gene Interaction Networks And Acyclic Graphs From Kegg Pathways, Sree K. Chanumolu, Mustafa Albahrani, Handan Can, Hasan H. Otu Mar 2021

Kegg2net: Deducing Gene Interaction Networks And Acyclic Graphs From Kegg Pathways, Sree K. Chanumolu, Mustafa Albahrani, Handan Can, Hasan H. Otu

Department of Electrical and Computer Engineering: Faculty Publications

The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database provides a manual curation of biological pathways that involve genes (or gene products), metabolites, chemical compounds, maps, and other entries. However, most applications and datasets involved in omics are gene or protein-centric requiring pathway representations that include direct and indirect interactions only between genes. Furthermore, special methodologies, such as Bayesian networks, require acyclic representations of graphs. We developed KEGG2Net, a web resource that generates a network involving only the genes represented on a KEGG pathway with all of the direct and indirect gene-gene interactions deduced from the pathway. KEGG2Net offers …


3d Printing Of Human Microbiome Constituents To Understand Spatial Relationships And Shape Parameters In Bacteriology, Jacques Izard, Teklu Kuru Gerbaba, Shara R. P. Yumul Mar 2021

3d Printing Of Human Microbiome Constituents To Understand Spatial Relationships And Shape Parameters In Bacteriology, Jacques Izard, Teklu Kuru Gerbaba, Shara R. P. Yumul

Department of Food Science and Technology: Faculty Publications

Effective laboratory and classroom demonstration of microbiome size and shape, diversity, and ecological relationships is hampered by a lack of high-resolution, easy-to-use, readily accessible physical or digital models for use in teaching. Three-dimensional (3D) representations are, overall, more effective in communicating visuospatial information, allowing for a better understanding of concepts not directly observable with the unaided eye. Published morphology descriptions and microscopy images were used as the basis for designing 3D digital models, scaled at 20,000×, using computer-aided design software (CAD) and generating printed models of bacteria on mass-market 3D printers. Sixteen models are presented, including rod-shaped, spiral, flask-like, vibroid, …


Exploring The Efficiency Of Self-Organizing Software Teams With Game Theory, Clay Stevens, Jared Soundy, Hau Chan Feb 2021

Exploring The Efficiency Of Self-Organizing Software Teams With Game Theory, Clay Stevens, Jared Soundy, Hau Chan

School of Computing: Conference and Workshop Papers

Over the last two decades, software development has moved away from centralized, plan-based management toward agile methodologies such as Scrum. Agile methodologies are founded on a shared set of core principles, including self-organizing software development teams. Such teams are promoted as a way to increase both developer productivity and team morale, which is echoed by academic research. However, recent works on agile neglect to consider strategic behavior among developers, particularly during task assignment–one of the primary functions of a self-organizing team. This paper argues that self-organizing software teams could be readily modeled using game theory, providing insight into how agile …


Plasmonic Waveguides To Enhance Quantum Electrodynamic Phenomena At The Nanoscale, Ying Li, Christos Argyropoulos Feb 2021

Plasmonic Waveguides To Enhance Quantum Electrodynamic Phenomena At The Nanoscale, Ying Li, Christos Argyropoulos

Department of Electrical and Computer Engineering: Faculty Publications

The emerging field of plasmonics can lead to enhanced light-matter interactions at extremely nanoscale regions. Plasmonic (metallic) devices promise to efficiently control both classical and quantum properties of light. Plasmonic waveguides are usually used to excite confined electromagnetic modes at the nanoscale that can strongly interact with matter. The analysis of these nanowaveguides exhibits similarities with their low frequency microwave counterparts. In this article, we review ways to study plasmonic nanostructures coupled to quantum optical emitters from a classical electromagnetic perspective. These quantum emitters are mainly used to generate single-photon quantum light that can be employed as a quantum bit …


Laser Vibrational Excitation Of Radicals To Prevent Crystallinity Degradation Caused By Boron Doping In Diamond, L Fan, L Constantin, Z P. Wu, K A. Mcelveen, X G. Chen, F Wang, C Debiemme-Chouvy, B Cui, R Y. Lai, X Li, J F. Silvain, Y F. Lu Jan 2021

Laser Vibrational Excitation Of Radicals To Prevent Crystallinity Degradation Caused By Boron Doping In Diamond, L Fan, L Constantin, Z P. Wu, K A. Mcelveen, X G. Chen, F Wang, C Debiemme-Chouvy, B Cui, R Y. Lai, X Li, J F. Silvain, Y F. Lu

Department of Electrical and Computer Engineering: Faculty Publications

Pursuing high-level doping without deteriorating crystallinity is prohibitively difficult but scientifically crucial to unleashing the hidden power of materials. This study demonstrates an effective route for maintaining lattice integrity during the combustion chemical vapor deposition of highly conductive boron-doped diamonds (BDDs) through laser vibrational excitation of a growth-critical radical, boron dihydride (BH2). The improved diamond crystallinity is attributed to a laser-enabled, thermal nonequilibrium suppression of the relative abundance of boron hydrides (BH), whose excessive presence induces boron segregation and disturbs the crystallization. The BDDs show a boron concentration of 4.3 × 1021 cm−3, a film …


A 3d Point Cloud Deep Learning Approach Using Lidar To Identify Ancient Maya Archaeological Sites, Heather Richards-Rissetto, David Newton, Aziza Al Zadjali Jan 2021

A 3d Point Cloud Deep Learning Approach Using Lidar To Identify Ancient Maya Archaeological Sites, Heather Richards-Rissetto, David Newton, Aziza Al Zadjali

Department of Anthropology: Faculty Publications

Airborne light detection and ranging (LIDAR) systems allow archaeologists to capture 3D data of anthropogenic landscapes with a level of precision that permits the identification of archaeological sites in difficult to reach and inaccessible regions. These benefits have come with a deluge of LIDAR data that requires significant and costly manual labor to interpret and analyze. In order to address this challenge, researchers have explored the use of state-of-the-art automated object recognition algorithms from the field of deep learning with success. This previous research, however, has been limited to the exploration of deep learning processes that work with only 2D …


End-Effector Contact And Force Detection For Miniature Autonomous Robots Performing Lunar And Expeditionary Surgery, Eric T. Psota, Jay Carlson, Priscila Rodrigues Armijo, Laura Flores, Ka-Chun Siu, Dmitry Oleynikov, Shane Farritor, Nathan Bills Jan 2021

End-Effector Contact And Force Detection For Miniature Autonomous Robots Performing Lunar And Expeditionary Surgery, Eric T. Psota, Jay Carlson, Priscila Rodrigues Armijo, Laura Flores, Ka-Chun Siu, Dmitry Oleynikov, Shane Farritor, Nathan Bills

Department of Electrical and Computer Engineering: Faculty Publications

Introduction: The U.S. Space Force was stood up on December 20, 2019 as an independent branch under the Air Force consisting of about 16,000 active duty and civilian personnel focused singularly on space. In addition to the Space Force, the plans by NASA and private industry for exploration-class long-duration missions to the moon, near-earth asteroids, and Mars makes semi-independent medical capability in space a priority. Current practice for space-based medicine is limited and relies on a “life-raft” scenario for emergencies. Discussions by working groups on military space-based medicine include placing a Role III equivalent facility in a lunar surface station. …


Recent Advances In Terahertz Photonic Technologies Based On Graphene And Their Applications, Tianjing Guo, Christos Argyropoulos Jan 2021

Recent Advances In Terahertz Photonic Technologies Based On Graphene And Their Applications, Tianjing Guo, Christos Argyropoulos

Department of Electrical and Computer Engineering: Faculty Publications

Graphene is a unique 2D material that has been extensively investigated due to its extraordinary photonic, electronic, thermal, and mechanical properties. Excited plasmons along its surface and other unique features are expected to play an important role in many emerging photonic technologies with drastically improved and tunable functionalities. This review is focused on presenting several recently introduced photonic phenomena based on graphene, beyond its usual linear response, such as nonlinear, active, topological, and nonreciprocal effects. The physical mechanisms and various envisioned photonic applications corresponding to these novel intriguing functionalities are also reported. The presented graphene-based technologies promise to revolutionize the …


A Routine Electroencephalography Monitoring System For Automated Sports-Related Concussion Detection, Amirsalar Mansouri, Patrick Ledwidge, Khalid Sayood, Dennis L. Molfese Jan 2021

A Routine Electroencephalography Monitoring System For Automated Sports-Related Concussion Detection, Amirsalar Mansouri, Patrick Ledwidge, Khalid Sayood, Dennis L. Molfese

Department of Electrical and Computer Engineering: Faculty Publications

Cases of concussions in the United States keep increasing and are now up to 2 million to 3 million incidents per year. Although concussions are recoverable and usually not life-threatening, the degree and rate of recovery may vary depending on age, severity of the injury, and past concussion history. A subsequent concussion before full recovery may lead to more-severe brain damage and poorer outcomes. Electroencephalography (EEG) recordings can identify brain dysfunctionality and abnormalities, such as after a concussion. Routine EEG monitoring can be a convenient method for reducing unreported injuries and preventing long-term damage, especially among groups with a greater …


Photovoltaic Panels Tilt Angle Optimization, Kerry A. Sado, Lokman H. Hassan, Shivan Sado Jan 2021

Photovoltaic Panels Tilt Angle Optimization, Kerry A. Sado, Lokman H. Hassan, Shivan Sado

Department of Electrical and Computer Engineering: Faculty Publications

The tilt angle of solar panels is significant for capturing solar radiation that reaches the surface of the panel. Photovoltaic (PV) performance and efficiency are highly affected by its angle of tilt with respect to the horizontal plane. The amount of radiation reaching the surface of a PV panel changes with the changes in its tilt angle, hence adding a solar tracking system will maximize the amount of solar radiation reaching the surface of a PV panel at any time during the day, however, integrating solar tracking system will increase the total cost and maintenance of any PV system. Thus, …


Near-Unity Broadband Omnidirectional Emissivity Via Femtosecond Laser Surface Processing, Andrew Reicks, Alfred Tsubaki, Mark Anderson, Jace Wieseler, Larousse Khosravi Khorashad, Jeffrey E. Shield, George Gogos, Dennis Alexander, Christos Argyropoulos, Craig Zuhlke Jan 2021

Near-Unity Broadband Omnidirectional Emissivity Via Femtosecond Laser Surface Processing, Andrew Reicks, Alfred Tsubaki, Mark Anderson, Jace Wieseler, Larousse Khosravi Khorashad, Jeffrey E. Shield, George Gogos, Dennis Alexander, Christos Argyropoulos, Craig Zuhlke

Department of Electrical and Computer Engineering: Faculty Publications

It is very challenging to achieve near perfect absorption or emission that is both broadband and omnidirectional while utilizing a scalable fabrication process. Femtosecond laser surface processing is an emerging low-cost and large-scale manufacturing technique used to directly and permanently modify the surface properties of a material. The versatility of this technique to produce tailored surface properties has resulted in a rapidly growing number of applications. Here, we demonstrate near perfect, broadband, omnidirectional emissivity from aluminum surfaces by tuning the laser surface processing parameters including fluence, pulse count, and the ambient gas. Full-wave simulations and experimental results prove that the …


Game-Theoretic Analysis Of Effort Allocation Of Contributors To Public Projects, Jared Soundy, Chenhao Wang, Clay Stevens, Hau Chan Jan 2021

Game-Theoretic Analysis Of Effort Allocation Of Contributors To Public Projects, Jared Soundy, Chenhao Wang, Clay Stevens, Hau Chan

School of Computing: Conference and Workshop Papers

Public projects can succeed or fail for many reasons such as the feasibility of the original goal and coordination among contributors. One major reason for failure is that insufficient work leaves the project partially completed. For certain types of projects anything short of full completion is a failure (e.g., feature request on software projects in GitHub). Therefore, project success relies heavily on individuals allocating sufficient effort. When there are multiple public projects, each contributor needs to make decisions to best allocate his/her limited effort (e.g., time) to projects while considering the effort allocation decisions of other strategic contributors and his/her …


Targeted Metabolomics Analysis Of Postoperative Delirium, Bridget A. Tripp, Simon T. Dillon, Min Yuan, John M. Asara, Sarinnapha M. Vasunilashorn, Tamara G. Fong, Eran D. Metzger, Sharon K. Inouye, Zhongcong Xie, Long H. Ngo, Edward R. Marcantonio, Towia A. Libermann, Hasan H. Otu Jan 2021

Targeted Metabolomics Analysis Of Postoperative Delirium, Bridget A. Tripp, Simon T. Dillon, Min Yuan, John M. Asara, Sarinnapha M. Vasunilashorn, Tamara G. Fong, Eran D. Metzger, Sharon K. Inouye, Zhongcong Xie, Long H. Ngo, Edward R. Marcantonio, Towia A. Libermann, Hasan H. Otu

Department of Electrical and Computer Engineering: Faculty Publications

Postoperative delirium is the most common complication among older adults undergoing major surgery. The pathophysiology of delirium is poorly understood, and no blood-based, predictive markers are available. We characterized the plasma metabolome of 52 delirium cases and 52 matched controls from the Successful Aging after Elective Surgery (SAGES) cohort (N= 560) of patients ≥ 70 years old without dementia undergoing scheduled major non-cardiac surgery. We applied targeted mass spectrometry with internal standards and pooled controls using a nested matched case-control study preoperatively (PREOP) and on postoperative day 2 (POD2) to identify potential delirium risk and disease markers. Univariate analyses identifed …


The Anisotropic Quasi-Static Permittivity Of Single-Crystal Β-Ga2O3 Measured By Terahertz Spectroscopy, Prashanth Gopalan, Sean Knight, Ashish Chanana, Megan Stokey, Praneeth Ranga, Michael A. Scarpulia, Sriram Krishnamoorthy, Vanya Darakchieva, Zbigniew Galazka, Klaus Irmscher, Andreas Fiedler, Steve Blair, Mathias Schubert, Berardi Sensale-Rodriguez Jan 2021

The Anisotropic Quasi-Static Permittivity Of Single-Crystal Β-Ga2O3 Measured By Terahertz Spectroscopy, Prashanth Gopalan, Sean Knight, Ashish Chanana, Megan Stokey, Praneeth Ranga, Michael A. Scarpulia, Sriram Krishnamoorthy, Vanya Darakchieva, Zbigniew Galazka, Klaus Irmscher, Andreas Fiedler, Steve Blair, Mathias Schubert, Berardi Sensale-Rodriguez

Department of Electrical and Computer Engineering: Faculty Publications

The quasi-static anisotropic permittivity parameters of electrically insulating beta gallium oxide (β-Ga2O3) were determined by terahertz spectroscopy. Polarization-resolved frequency domain spectroscopy in the spectral range from 200 GHz to 1 THz was carried out on bulk crystals along different orientations. Principal directions for permittivity were determined along crystallographic axes c and b and reciprocal lattice direction a*. No significant frequency dispersion in the real part of dielectric permittivity was observed in the measured spectral range. Our results are in excellent agreement with recent radio frequency capacitance measurements as well as with extrapolations from recent infrared measurements …


A Novel Spatiotemporal Prediction Method Of Cumulative Covid-19 Cases, Junzhe Cai Dec 2020

A Novel Spatiotemporal Prediction Method Of Cumulative Covid-19 Cases, Junzhe Cai

School of Computing: Dissertations, Theses, and Student Research

Prediction methods are important for many applications. In particular, an accurate prediction for the total number of cases for pandemics such as the Covid-19 pandemic could help medical preparedness by providing in time a sufficient supply of testing kits, hospital beds and medical personnel. This thesis experimentally compares the accuracy of ten prediction methods for the cumulative number of Covid-19 pandemic cases. These ten methods include two types of neural networks and extrapolation methods based on best fit linear, best fit quadratic, best fit cubic and Lagrange interpolation, as well as an extrapolation method from Revesz. We also consider the …


Suffix Tree, Minwise Hashing And Streaming Algorithms For Big Data Analysis In Bioinformatics, Sairam Behera Dec 2020

Suffix Tree, Minwise Hashing And Streaming Algorithms For Big Data Analysis In Bioinformatics, Sairam Behera

School of Computing: Dissertations, Theses, and Student Research

In this dissertation, we worked on several algorithmic problems in bioinformatics using mainly three approaches: (a) a streaming model, (b) sux-tree based indexing, and (c) minwise-hashing (minhash) and locality-sensitive hashing (LSH). The streaming models are useful for large data problems where a good approximation needs to be achieved with limited space usage. We developed an approximation algorithm (Kmer-Estimate) using the streaming approach to obtain a better estimation of the frequency of k-mer counts. A k-mer, a subsequence of length k, plays an important role in many bioinformatics analyses such as genome distance estimation. We also developed new methods that use …


Representational Learning Approach For Predicting Developer Expertise Using Eye Movements, Sumeet Maan Dec 2020

Representational Learning Approach For Predicting Developer Expertise Using Eye Movements, Sumeet Maan

School of Computing: Dissertations, Theses, and Student Research

The thesis analyzes an existing eye-tracking dataset collected while software developers were solving bug fixing tasks in an open-source system. The analysis is performed using a representational learning approach namely, Multi-layer Perceptron (MLP). The novel aspect of the analysis is the introduction of a new feature engineering method based on the eye-tracking data. This is then used to predict developer expertise on the data. The dataset used in this thesis is inherently more complex because it is collected in a very dynamic environment i.e., the Eclipse IDE using an eye-tracking plugin, iTrace. Previous work in this area only worked on …


Strain And Stress Relationships For Optical Phonon Modes In Monoclinic Crystals With Β-Ga2O3 As An Example, Rafal Korlacki, Megan Stokey, A. Mock, Sean Knight, A. Papamichail, V. Darakchieva, Mathias Schubert Nov 2020

Strain And Stress Relationships For Optical Phonon Modes In Monoclinic Crystals With Β-Ga2O3 As An Example, Rafal Korlacki, Megan Stokey, A. Mock, Sean Knight, A. Papamichail, V. Darakchieva, Mathias Schubert

Department of Electrical and Computer Engineering: Faculty Publications

Strain-stress relationships for physical properties are of interest for heteroepitaxial material systems, where strain and stress are inherent due to thermal expansion and lattice mismatch. We report linear perturbation theory strain and stress relationships for optical phonon modes in monoclinic crystals for strain and stress situations which maintain the monoclinic symmetry of the crystal. By using symmetry group analysis and phonon frequencies obtained under various deformation scenarios from density-functional perturbation theory calculations on β-Ga2O3, we obtain four strain and four stress potential parameters for each phonon mode. We demonstrate that these parameters are sufficient to …


Strain And Stress Relationships For Optical Phonon Modes In Monoclinic Crystals With Β-Ga2O3 As An Example, Rafal Korlacki, Megan Stokey, A. Mock, Sean Knight, Alexis Papamichail, Vanya Darakchieva, Mathias Schubert Nov 2020

Strain And Stress Relationships For Optical Phonon Modes In Monoclinic Crystals With Β-Ga2O3 As An Example, Rafal Korlacki, Megan Stokey, A. Mock, Sean Knight, Alexis Papamichail, Vanya Darakchieva, Mathias Schubert

Department of Electrical and Computer Engineering: Faculty Publications

Strain-stress relationships for physical properties are of interest for heteroepitaxial material systems, where strain and stress are inherent due to thermal expansion and lattice mismatch. We report linear perturbation theory strain and stress relationships for optical phonon modes in monoclinic crystals for strain and stress situations which maintain the monoclinic symmetry of the crystal. By using symmetry group analysis and phonon frequencies obtained under various deformation scenarios from density-functional perturbation theory calculations on β-Ga2O3, we obtain four strain and four stress potential parameters for each phonon mode. We demonstrate that these parameters are sufficient to …


Formal Concept Analysis Applications In Bioinformatics, Sarah Roscoe Nov 2020

Formal Concept Analysis Applications In Bioinformatics, Sarah Roscoe

School of Computing: Dissertations, Theses, and Student Research

Bioinformatics is an important field that seeks to solve biological problems with the help of computation. One specific field in bioinformatics is that of genomics, the study of genes and their functions. Genomics can provide valuable analysis as to the interaction between how genes interact with their environment. One such way to measure the interaction is through gene expression data, which determines whether (and how much) a certain gene activates in a situation. Analyzing this data can be critical for predicting diseases or other biological reactions. One method used for analysis is Formal Concept Analysis (FCA), a computing technique based …


Investigating Factors Predicting Effective Learning In A Cs Professional Development Program For K–12 Teachers, Patrick Morrow Oct 2020

Investigating Factors Predicting Effective Learning In A Cs Professional Development Program For K–12 Teachers, Patrick Morrow

School of Computing: Dissertations, Theses, and Student Research

The demand for K-12 Computer Science (CS) education is growing and there is not an adequate number of educators to match the demand. Comprehensive research was carried out to investigate and understand the influence of a summer two-week professional development (PD) program on teachers’ CS content and pedagogical knowledge, their confidence in such knowledge, their interest in and perceived value of CS, and the factors influencing such impacts. Two courses designed to train K-12 teachers to teach CS, focusing on both concepts and pedagogy skills were taught over two separate summers to two separate cohorts of teachers. Statistical and SWOT …


Cross-Domain Identification For Thermal-To-Visible Face Recognition, Cedric Nimpa Fondje, Shuowen Hu, Nathaniel J. Short, Benjamin S. Riggan Aug 2020

Cross-Domain Identification For Thermal-To-Visible Face Recognition, Cedric Nimpa Fondje, Shuowen Hu, Nathaniel J. Short, Benjamin S. Riggan

Department of Electrical and Computer Engineering: Faculty Publications

Recent advances in domain adaptation, especially those applied to heterogeneous facial recognition, typically rely upon restrictive Euclidean loss functions (e.g., L2 norm) which perform best when images from two different domains (e.g., visible and thermal) are co-registered and temporally synchronized. This paper proposes a novel domain adaptation framework that combines a new feature mapping sub-network with existing deep feature models, which are based on modified network architectures (e.g., VGG16 or Resnet50). This framework is optimized by introducing new cross-domain identity and domain invariance loss functions for thermal-to-visible face recognition, which alleviates the requirement for precisely co-registered and synchronized imagery. We …


Routing Optimization In Heterogeneous Wireless Networks For Space And Mission-Driven Internet Of Things (Iot) Environments, Sara El Alaoui Aug 2020

Routing Optimization In Heterogeneous Wireless Networks For Space And Mission-Driven Internet Of Things (Iot) Environments, Sara El Alaoui

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

As technological advances have made it possible to build cheap devices with more processing power and storage, and that are capable of continuously generating large amounts of data, the network has to undergo significant changes as well. The rising number of vendors and variety in platforms and wireless communication technologies have introduced heterogeneity to networks compromising the efficiency of existing routing algorithms. Furthermore, most of the existing solutions assume and require connection to the backbone network and involve changes to the infrastructures, which are not always possible -- a 2018 report by the Federal Communications Commission shows that over 31% …


Enhanced Control Algorithms In Permanent Magnet Synchronous Machines, Haibo Li Aug 2020

Enhanced Control Algorithms In Permanent Magnet Synchronous Machines, Haibo Li

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Permanent magnet synchronous machines (PMSMs) are gaining increasing popularity in various applications due to their advantages, such as high efficiency, high power density, and superior control performance. A well-designed machine control algorithm is indispensable for a PMSM system to secure its good performance.

In this work, enhanced control algorithms in PMSMs are developed. Online machine current trajectory tracking, source power management, hardware overcurrent regulation, and machine current sensor fault detection and isolation (FDI) are included in the developed algorithms. The online machine current trajectory tracking ensures the maximum torque per ampere (MTPA) or maximum torque per voltage (MTPV) control in …


An End-To-End Trainable Method For Generating And Detecting Fiducial Markers, J. Brennan Peace Aug 2020

An End-To-End Trainable Method For Generating And Detecting Fiducial Markers, J. Brennan Peace

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Existing fiducial markers are designed for efficient detection and decoding. The methods are computationally efficient and capable of demonstrating impressive results, however, the markers are not explicitly designed to stand out in natural environments and their robustness is difficult to infer from relatively limited analysis. Worsening performance in challenging image capture scenarios - such as poorly exposed images, motion blur, and off-axis viewing - sheds light on their limitations. The method introduced in this work is an end-to-end trainable method for designing fiducial markers and a complimentary detector. By introducing back-propagatable marker augmentation and superimposition into training, the method learns …


A Novel Path Loss Forecast Model To Support Digital Twins For High Frequency Communications Networks, James Marvin Taylor Jr. Jul 2020

A Novel Path Loss Forecast Model To Support Digital Twins For High Frequency Communications Networks, James Marvin Taylor Jr.

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The need for long-distance High Frequency (HF) communications in the 3-30 MHz frequency range seemed to diminish at the end of the 20th century with the advent of space-based communications and the spread of fiber optic-connected digital networks. Renewed interest in HF has emerged as an enabler for operations in austere locations and for its ability to serve as a redundant link when space-based and terrestrial communication channels fail. Communications system designers can create a “digital twin” system to explore the operational advantages and constraints of the new capability. Existing wireless channel models can adequately simulate communication channel conditions with …