Physical Sciences and Mathematics Commons^™

Design And Fabrication Of A Trapped Ion Quantum Computing Testbed, Christopher A. Caron

Masters Theses

Here we present the design, assembly and successful ion trapping of a room-temperature ion trap system with a custom designed and fabricated surface electrode ion trap, which allows for rapid prototyping of novel trap designs such that new chips can be installed and reach UHV in under 2 days. The system has demonstrated success at trapping and maintaining both single ions and cold crystals of ions. We achieve this by fabricating our own custom surface Paul traps in the UMass Amherst cleanroom facilities, which are then argon ion milled, diced, mounted and wire bonded to an interposer which is placed …

Numerical Investigations Of 2-D Magnetic Nozzles On Pulsed Plasma Plumes, Joshua Daniel Burch

Masters Theses

"This research presents studies of a novel type of magnetic nozzle that allows for three-dimensional (3-D) steering of a plasma plume. Numerical simulations were performed using Tech-X's USim® software to quantify the nozzle's capabilities. A2-D planar magnetic nozzle was applied to plumes of a nominal pulsed inductive plasma (PIP) source with discharge parameters similar to those of Missouri S&T's Missouri Plasmoid Experiment (MPX). Argon and xenon plumes were considered. Simulations were verified and validated through a mesh convergence study as well as comparison with available experimental data. Periodicity was achieved over the simulation run time and phase angle samples were …

Evaluation Of Robust Deep Learning Pipelines Targeting Low Swap Edge Deployment, David Carter Cornett

Masters Theses

The deep learning technique of convolutional neural networks (CNNs) has greatly advanced the state-of-the-art for computer vision tasks such as image classification and object detection. These solutions rely on large systems leveraging wattage-hungry GPUs to provide the computational power to achieve such performance. However, the size, weight and power (SWaP) requirements of these conventional GPU-based deep learning systems are not suitable when a solution requires deployment to so called "Edge" environments such as autonomous vehicles, unmanned aerial vehicles (UAVs) and smart security cameras.

The objective of this work is to benchmark FPGA-based alternatives to conventional GPU systems that have the …

Modeling And Characterization Of Optical Metasurfaces, Mahsa Torfeh

Masters Theses

Metasurfaces are arrays of subwavelength meta-atoms that shape waves in a compact and planar form factor. During recent years, metasurfaces have gained a lot of attention due to their compact form factor, easy integration with other devices, multi functionality and straightforward fabrication using conventional CMOS techniques. To provide and evaluate an efficient metasurface, an optimized design, high resolution fabrication and accurate measurement is required. Analysis and design of metasurfaces require accurate methods for modeling their interactions with waves. Conventional modeling techniques assume that metasurfaces are locally periodic structures excited by plane waves, restricting their applicability to gradually varying metasurfaces that …

Power System Stability Assessment With Supervised Machine Learning, Mirka Mandich

Masters Theses

Power system stability assessment has become an important area of research due to the increased penetration of photovoltaics (PV) in modern power systems. This work explores how supervised machine learning can be used to assess power system stability for the Western Electricity Coordinating Council (WECC) service region as part of the Data-driven Security Assessment for the Multi-Timescale Integrated Dynamics and Scheduling for Solar (MIDAS) project. Data-driven methods offer to improve power flow scheduling through machine learning prediction, enabling better energy resource management and reducing demand on real-time time-domain simulations. Frequency, transient, and small signal stability datasets were created using the …

A Simple Background Elimination Method For Miniaturized Fiber-Optic Raman Probe, Bohong Zhang

Masters Theses

"Raman scattering is called a photonic - molecular interaction based on the kinetic model of the analytic. Due to the uniqueness of the Raman scattering technique, it can provide a unique fingerprint signal for molecular recognition. However, a serious challenge often encountered in Raman measurement comes from the requirements of fast, real-time remote sensing, background fluorescence suppression, and micro-environmental detection.

A new Miniaturized Fiber-Optic Raman Probe (MFORP) for Raman spectroscopy, used especially for eliminating background fluorescence and enhancing sampling, is presented. Its main purpose is to provide an overview of excellent research on the detection of very small substances and …

A Compact Wavelength Meter Using A Multimode Fiber, Ogbole Collins Inalegwu

Masters Theses

“Wavelength meters are very important for precision measurements of both pulses and continuous-wave optical sources. Conventional wavelength meters employ gratings, prisms, interferometers, and other wavelength-sensitive materials in their design. Here, we report a simple and compact wavelength meter based on a section of multimode fiber and a camera. The concept is to correlate the multimodal interference pattern (i.e., speckle pattern) at the end-face of a multimode fiber with the wavelength of the input lightsource. Through a series of experiments, specklegrams from the end face of a multimode fiber as captured by a charge-coupled device (CCD) camera were recorded; the images …

Metric Learning Via Linear Embeddings For Human Motion Recognition, Byoungdoo Kong

Masters Theses

We consider the application of Few-Shot Learning (FSL) and dimensionality reduction to the problem of human motion recognition (HMR). The structure of human motion has unique characteristics such as its dynamic and high-dimensional nature. Recent research on human motion recognition uses deep neural networks with multiple layers. Most importantly, large datasets will need to be collected to use such networks to analyze human motion. This process is both time-consuming and expensive since a large motion capture database must be collected and labeled. Despite significant progress having been made in human motion recognition, state-of-the-art algorithms still misclassify actions because of characteristics …

A Framework To Support Automatic Certification For Self-Adaptive Systems, Ioannis Nearchou

Masters Theses

Presently, cyber-physical systems are increasingly being integrated into societies, from the economic sector to the nuclear energy sector. Cyber-physical systems are systems that combine physical, digital, human, and other components, which operate through physical means and software. When system errors occur, the consequences of malfunction could negatively impact human life. Academic studies have relied on the MAPE-K feedback loop model to develop various system components to satisfy the self-adaptive features, such that violation of the safety requirements can be minimized. Assurance of system requirement satisfaction is argued through an industrial standard form, called an assurance case, which is usually applied …

Compound Effects Of Clock And Voltage Based Power Side-Channel Countermeasures, Jacqueline Lagasse

Masters Theses

The power side-channel attack, which allows an attacker to derive secret information from power traces, continues to be a major vulnerability in many critical systems. Numerous countermeasures have been proposed since its discovery as a serious vulnerability, including both hardware and software implementations. Each countermeasure has its own drawback, with some of the highly effective countermeasures incurring large overhead in area and power. In addition, many countermeasures are quite invasive to the design process, requiring modification of the design and therefore additional validation and testing to ensure its accuracy. Less invasive countermeasures that do not require directly modifying the system …

Insar Simulations For Swot And Dual Frequency Processing For Topographic Measurements, Gerard Masalias Huguet

Masters Theses

In Earth remote sensing precise characterization of the backscatter coefficient is important to extract valuable information about the observed target. A system that eliminates platform motion during near-nadir airborne observations is presented in this thesis, showing an improvement on the accuracy of measurements for a Ka- band scatterometer previously developed at Microwave Remote Sensing Laboratory (MIRSL). These very same results are used to simulate the reflectivity of such targets as seen from a spaceborne radar and estimate height errors based on mission-specific geometry. Finally, data collected from a dual-frequency airborne interferometer com- prised by the Ka-band system and an S-band …

Application And Evaluation Of Lighthouse Technology For Precision Motion Capture, Soumitra Sitole

Masters Theses

This thesis presents the development towards a system that can capture and quantify motion for applications in biomechanical and medical fields demanding precision motion tracking using the lighthouse technology. Commercially known as SteamVR tracking, the lighthouse technology is a motion tracking system developed for virtual reality applications that makes use of patterned infrared light sources to highlight trackers (objects embedded with photodiodes) to obtain their pose or spatial position and orientation. Current motion capture systems such as the camera-based motion capture are expensive and not readily available outside of research labs. This thesis provides a case for low-cost motion capture …

A Study On Modelling Spatial-Temporal Human Mobility Patterns For Improving Personalized Weather Warning, Yue Xu

Masters Theses

Understanding human mobility patterns is important for severe weather warning since these patterns can help identify where people are in time and in space when flash floods, tornados, high winds and hurricanes are occurring or are predicted to occur. A GIS (Geographic Information Science) data model was proposed to describe the spatial-temporal human activity. Based on this model, a metric was designed to represent the spatial-temporal activity intensity of human mobility, and an index was generated to quantitatively describe the change in human activities. By analyzing high-resolution human mobility data, the paper verified that human daily mobility patterns could be …

Explorations Into Machine Learning Techniques For Precipitation Nowcasting, Aditya Nagarajan

Masters Theses

Recent advances in cloud-based big-data technologies now makes data driven solutions feasible for increasing numbers of scientific computing applications. One such data driven solution approach is machine learning where patterns in large data sets are brought to the surface by finding complex mathematical relationships within the data. Nowcasting or short-term prediction of rainfall in a given region is an important problem in meteorology. In this thesis we explore the nowcasting problem through a data driven approach by formulating it as a machine learning problem.

State-of-the-art nowcasting systems today are based on numerical models which describe the physical processes leading to …

Time Domain Sar Processing With Gpus For Airborne Platforms, Dustin Lagoy

Masters Theses

A time-domain backprojection processor for airborne synthetic aperture radar (SAR) has been developed at the University of Massachusetts’ Microwave Remote Sensing Lab (MIRSL). The aim of this work is to produce a SAR processor capable of addressing the motion compensation issues faced by frequency-domain processing algorithms, in order to create well focused SAR imagery suitable for interferometry. The time-domain backprojection algorithm inherently compensates for non-linear platform motion, dependent on the availability of accurate measurements of the motion. The implementation must manage the relatively high computational burden of the backprojection algorithm, which is done using modern graphics processing units (GPUs), programmed …

Classification Of Basal Cell Carcinoma Using Telangiectatic Vessels And Machine Learning, Hemanth Yadav Aradhyula

Masters Theses

“Basal cell carcinoma (BCC) is one of the most common types of skin cancer in the United States. Early detection of BCC by noninvasive techniques can decrease delay in treatment and save cost. A recent study estimated that 5.4 million cases of non-melanocytic skin cancer (NMSC) occur each year in the US. BCC accounts for 50% of NMSC cases. Telangiectasia, which appears in most BCCs is an important feature for identification of BCC for an automatic diagnostic system. In this thesis, three methods for detection of telangiectasia present in dermoscopy lesion image (DI) were proposed. Detected telangiectasia in DI was …

A Haptic Surface Robot Interface For Large-Format Touchscreen Displays, Mark Price

Masters Theses

This thesis presents the design for a novel haptic interface for large-format touchscreens. Techniques such as electrovibration, ultrasonic vibration, and external braked devices have been developed by other researchers to deliver haptic feedback to touchscreen users. However, these methods do not address the need for spatial constraints that only restrict user motion in the direction of the constraint. This technology gap contributes to the lack of haptic technology available for touchscreen-based upper-limb rehabilitation, despite the prevalent use of haptics in other forms of robotic rehabilitation. The goal of this thesis is to display kinesthetic haptic constraints to the touchscreen user …

Intensity Control Of Dielectric Barrier Discharge Filaments, Matthew Crawford Paliwoda

Masters Theses

"When operated in a filamentary mode, a volume dielectric barrier discharge (DBD) is known to produce patterned plasma structures. These structures are currently being explored for reconfigurable metamaterial applications. In this work the presence and intensity of a single filament, within an array of filaments, was controlled by adjusting the voltage to that filament's individual needle electrode. The current, voltage, and time-averaged normalized light intensity were measured while varying the voltage of the needle through a self-biasing resistance. For a 7.5 kV, 3.2 kHz DBD in air, the needle-controlled filament intensity varies from that of the surrounding filaments to zero …

Managing Risks Of Market Price Uncertainty For A Microgrid Operation, Sriram Raghavan

Masters Theses

"After deregulation of electricity in the United States, the day-ahead and real-time markets allow load serving entities and generation companies to bid and purchase/sell energy under the supervision of the independent system operator (ISO). The electricity market prices are inherently uncertain, and can be highly volatile. The main objective of this thesis is to hedge against the risk from the uncertainty of the market prices when purchasing/selling energy from/to the market. The energy manager can also schedule distributed generators (DGs) and storage of the microgrid to meet the demand, in addition to energy transactions from the market. The risk measure …

Design And Implementation Of Digital Information Security For Physical Documents, Pengcheng Wang

Masters Theses

The objective of this thesis is to improve the security for physical paper documents. Providing information security has been difficult in environments that rely on physical paper documents to implement business processes. Our work presents the design of a digital information security system for paper documents, called "CryptoPaper", that uses 2-dimensional codes to represent data and its security properties on paper. A special scanner system is designed for "CryptoPaper" which uses image recognition techniques and cloud-based access control to display plaintext of encrypted and encoded data to authorized users.

Steam Flooding Screening And Eor Prediction By Using Clustering Algorithm And Data Visualization, Na Zhang

Masters Theses

"Enhanced Oil Recovery (EOR) techniques are vitally important in the oil industry because these techniques could not only extend the life of wells, but also produce 10% to 30% additional oil from the reservoir. However, selecting the most suitable EOR techniques for unknown reservoirs is not easy for decision making. Based on literature, EOR screening criteria could help to find the best candidates for unknown projects, which is classified into two categories: conventional EOR screening and advanced EOR screening. In this research, an artificial intelligent (AI) method, hierarchical clustering algorithm, is adapted to analyze both steam flooding projects and worldwide …

Microwave Assisted Reconstruction Of Optical Interferograms For Distributed Fiber Optics Sensing & Characterization Of Pcb Dielectric Properties Using Two Striplines On The Same Board, Lei Hua

Masters Theses

"A new concept, the microwave-assisted reconstruction of an optical interferogram for distributed sensing, was developed to resolve both the position and reflectivity of each sensor along an optical fiber. This approach involves sending a microwave-modulated optical signal through cascaded fiber optic interferometers. The optical spectrum of each sensor can be reconstructed by sweeping the optical wavelength and detecting the modulation signal. A series of cascaded fiber optic extrinsic Fabry-Perot interferometric sensors was used to prove the concept. The microwave-reconstructed interferogram matched well with those recorded individually from a traditional optical spectrometer. The application of distributed strain measurement was also investigated. …

Cervical Cancer Histology Image Feature Extraction And Classification, Peng Guo

Masters Theses

"Cervical cancer, the second most common cancer affecting women worldwide and the most common in developing countries can be cured if detected early and treated. Expert pathologists routinely visually examine histology slides for cervix tissue abnormality assessment. In previous research, an automated, localized, fusion-based approach was investigated for classifying squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN) based on image analysis of 62 digitized histology images obtained through the National Library of Medicine. In this research, CIN grade assessments from two pathologists are analyzed and are used to facilitate atypical cell concentration feature development …

Cytongrasp: Cyton Alpha Controller Via Graspit! Simulation, Nicholas Wayne Overfield

Masters Theses

This thesis addresses an expansion of the control programs for the Cyton Alpha 7D 1G arm. The original control system made use of configurable software which exploited the arm’s seven degrees of freedom and kinematic redundancy to control the arm based on desired behaviors that were configured off-line. The inclusions of the GraspIt! grasp planning simulator and toolkit enables the Cyton Alpha to be used in more proactive on-line grasping problems, as well as, presenting many additional tools for on-line learning applications. In short, GraspIt! expands what is possible with the Cyton Alpha to include many machine learning tools and …

Analytical Computation Of Proper Orthogonal Decomposition Modes And N-Width Approximations For The Heat Equation With Boundary Control, Tasha N. Fernandez

Masters Theses

Model reduction is a powerful and ubiquitous tool used to reduce the complexity of a dynamical system while preserving the input-output behavior. It has been applied throughout many different disciplines, including controls, fluid and structural dynamics. Model reduction via proper orthogonal decomposition (POD) is utilized for of control of partial differential equations. In this thesis, the analytical expressions of POD modes are derived for the heat equation. The autocorrelation function of the latter is viewed as the kernel of a self adjoint compact operator, and the POD modes and corresponding eigenvalues are computed by solving homogeneous integral equations of the …

Improving Query Efficiency Of Multiresolution Data Aggregation For Analytical Exploration Of Large Relational Dataset, Yu-Ting Huang

Masters Theses

Tree structures are developed to organize the data more efficiently by using fewer resources for searching records. This thesis investigates the tree's actual structure on the hard disk to see the influence of different kinds of structures on the tree building time and query execution time. In order to improve efficiency, one multi-file structure and two reorganization structures, BFS and DFS, are examined to achieve this goal. The results indicate that two reorganization structures on KDB-tree structure can significantly improve the query execution time in large data sets and multi-file structure can slightly improve the TPIE lover level building time.

Universal Geometric Camera Calibration With Statistical Model Selection, Chistopher Paul Broaddus

Masters Theses

We propose a new universal camera calibration approach that uses statistical information criteria for automatic camera model selection. It requires the camera to observe a planar pattern from different positions, and then closed-form estimates for the intrinsic and extrinsic parameters are computed followed by nonlinear optimization. In lieu of modeling radial distortion, the lens projection of the camera is modeled, and in addition we include decentering distortion. This approach is particularly advantageous for wide angle (fisheye) camera calibration because it often reduces the complexity of the model compared to modeling radial distortion. We then apply statistical information criteria to automatically …

Middle Terminal Cell Models For Efficient Over-The-Cell Routing, Siddharth Bhingarde

Masters Theses

In this thesis, we introduce a new class of cell models called Middle Terminal Models (MTM) which combines the advantages of existing cell models: BTM and CTM. This class contains the models 2MTM, 3MTM-V, and 3MTM+V depending on the number of metal layers and the permissibility of vias in over-the-cell areas. In MTM, two rows of terminals are located in the middle of the cell. This partitions over-the-cell area into three regions and allows allocation of more nets to over-the-cell area in congested channels. We prove that when vias are allowed over-the-cell, in "almost all" cases the MTM based layouts …

On Planar Routing Of Multi-Terminal Nets In Vlsi Physical Design, Jahangir A. Hashmi

Masters Theses

In this thesis, we study two problems related to the physical design of VLSI circuits. One problem is related to the VLSI global routing and the other is related to the detailed routing in a bounded region.

We consider the routing of multiple multi-terminal nets on a single layer. We suggest a new approach for this problem. Our approach is based on simultaneously finding a forest of k non-intersecting spanning trees. We present an O(n^3) algorithm for finding two spanning trees corresponding to two nets on a single layer.

We also study the problem of finding a minimum Steiner tree …

Inhibited Spontaneous Emission By Photonic Band Gaps In A Square Lattice Of Periodic Dielectric Medium, Abdullah Al-Ghamdi

Masters Theses

The concepts of band theory for electrons can be employed to describe the behavior of electromagnetic waves propagating in two-dimensional, periodic dielectric structures. These two-dimensional, periodic structures can produce photonic band gaps in which the spontaneous emission by atoms embedded in the structure is prohibited and as a result the performance of many semiconductor devices can be enhanced. The calculations are based on finding the eigenvalues of the algebraic equation for the frequencies of electromagnetic waves moving in a square lattice composed of square dielectric rods with different dielectric constants.