Inverse Design of Three-Dimensional Frequency Selective Structures and Metamaterials using Multi-Objective Lazy Ant Colony Optimization

With the rise of big data and the “internet of things,” wireless signals permeate today’s environment more than ever before. As the demand for information and security continues to expand, the need for filtering a crowded signal space will become increasingly important. Although existing devices can achieve this with additional components, such as in-line filters and low noise amplifiers, these approaches introduce additional bulk, cost and complexity. An alternative, low-cost solution to filtering these signals can be achieved through the use of Frequency Selective Surfaces (FSSs), which are commonly used in antennas, polarizers, radomes, and intelligent architecture. FSSs typically consist of a doubly-periodic array of unit cells, which acts as a spatial electromagnetic filter that selectively rejects or transmits electromagnetic waves, based on the unit cell’s geometry and material properties. Unlike traditional analog filters, spatial filters must also account for the polarization and incidence angle of signals; thus, an ideal FSS maintains a given frequency response for all polarizations and incidence angles. Traditional FSS designs have ranged from planar structures with canonical shapes to miniaturized and multi-layer designs using fractals and other space-filling geometries. More recently, FSS research has expanded into three-dimensional (3D) designs, which have demonstrated enhanced fields of view over traditional planar and multi-layer designs. To date, nearly all FSSs still suffer from significant shifts in resonant frequencies or onset of grating lobes at incidence angles beyond 60 degrees in one or more polarizations. Additionally, while recent advances in additive manufacturing techniques have made fully 3D FSS designs increasingly popular, design tools to exploit these fabrication methods to develop FSSs with ultra-wide Fields of View (FOV) do not currently exist. In this dissertation, a Multi-Objective Lazy Ant Colony Optimization (MOLACO) scheme will be introduced and applied to the problem of 3D FSS design for extreme FOVs. The versatility of this algorithm will further be demonstrated through application to the design of meander line antennas, optical antennas, and phase-gradient metasurfaces

Source localization within a uniform circular sensor array

Traditional source localization problems have been considered with linear and planar antenna arrays. In this research work, we assume that the sources are located within a uniformly spaced circular sensor array. Using a modified Metropolis algorithm and Polak-Ribière conjugate gradients, a hybrid optimization algorithm is proposed to localize sources within a two dimensional uniform circular sensor array, which suffers from far field attenuation. The developed algorithm is capable of accurately locating the position of a single, stationary source within 1% of a wavelength and 1° of angular displacement. In the single stationary source case, the simulated Cramer-Rao Lower Bound has also shown low noise susceptibility for a reasonable signal to noise ratio. Additionally, the localization of multiple stationary sources within the array is presented and tracking capabilities for a slowly moving non-stationary source is also demonstrated. In each case, results are presented, analyzed and discussed. Furthermore, the proposed algorithm has also been validated through hardware experimentation. The design and construction of four microstrip patch antennas and a wire antenna have been completed to emulate a circular sensor array and the enclosed source, respectively. Within this array, data has been collected at the four sensors from several fixed source positions and fitted into the proposed algorithm for source localization. The convergence of the algorithm with both simulated data and data collected from hardware are compared and sources of error and potential improvements are proposed

Integrating Data Science into a General Education Information Technology Course: An Approach to Developing Data Savvy Undergraduates

The National Academies recommend academic institutions foster a basic understanding of data science in all undergraduates. However, data science education is not currently a graduation requirement at most colleges and universities. As a result, many graduates lack even basic knowledge of data science. To address the shortfall, academic institutions should incorporate introductory data science into general education courses. A general education IT course provides a unique opportunity to integrate data science education. Modules covering databases, spreadsheets, and presentation software, already present in many survey IT courses, teach concepts and skills needed for data science. As a result, a survey IT course can provide comprehensive introductory data science education by adding a data science module focused on modeling and evaluation, two key steps in the data science process. The module should use data science software for application, avoiding the complexities of programming and advanced math, while enabling an emphasis on conceptual understanding. We implemented a course built around these ideas and found that the course helps develop data savvy in students

GCL: Gradient-Guided Contrastive Learning for Medical Image Segmentation with Multi-Perspective Meta Labels

Since annotating medical images for segmentation tasks commonly incurs expensive costs, it is highly desirable to design an annotation-efficient method to alleviate the annotation burden. Recently, contrastive learning has exhibited a great potential in learning robust representations to boost downstream tasks with limited labels. In medical imaging scenarios, ready-made meta labels (i.e., specific attribute information of medical images) inherently reveal semantic relationships among images, which have been used to define positive pairs in previous work. However, the multi-perspective semantics revealed by various meta labels are usually incompatible and can incur intractable "semantic contradiction" when combining different meta labels. In this paper, we tackle the issue of "semantic contradiction" in a gradient-guided manner using our proposed Gradient Mitigator method, which systematically unifies multi-perspective meta labels to enable a pre-trained model to attain a better high-level semantic recognition ability. Moreover, we emphasize that the fine-grained discrimination ability is vital for segmentation-oriented pre-training, and develop a novel method called Gradient Filter to dynamically screen pixel pairs with the most discriminating power based on the magnitude of gradients. Comprehensive experiments on four medical image segmentation datasets verify that our new method GCL: (1) learns informative image representations and considerably boosts segmentation performance with limited labels, and (2) shows promising generalizability on out-of-distribution datasets

Stand-off runaway electron beam termination by tungsten particulates for tokamak disruption mitigation

Stand-off runaway electron termination by injected tungsten particulates offers a plausible option in the toolbox of disruption mitigation. Tungsten is an attractive material choice for this application due to large electron stopping power and high melting point. To assess the feasibility of this scheme, we simulate runaway collisions with tungsten particulates using the MCNP program for incident runaway energies ranging from 1 to 10 MeV. We assess runaway termination from energetics and collisional kinematics perspectives. Energetically, the simulations show that 99% of runaway beam energy is removed by tungsten particulates on a timescale of 4-9 $\mu$s. Kinematically, the simulations show that 99% of runaways are terminated by absorption or backscattering on a timescale of 3-4 $\mu$s. By either metric, the runaway beam is effectively terminated before the onset of particulate melting. Furthermore, the simulations show that secondary radiation emission by tungsten particulates does not significantly impact the runaway termination efficacy of this scheme. Secondary radiation is emitted at lower particle energies than the incident runaways and with a broad angular distribution such that the majority of secondary electrons emitted will not experience efficient runaway re-acceleration. Overall, the stand-off runaway termination scheme is a promising concept for last-ditch runaway mitigation in ITER, SPARC, and other future burning-plasma tokamaks.Comment: Submitted to: Nuclear Fusion - 16 pages (4 supplementary), 11 figures (5 supplementary), 4 table

Inverse Design of Three-Dimensional Nanoantennas for Metasurface Applications

Recent advances in manufacturing techniques have been made to match the demand for high performance optical devices. To this end, tremendous research activity has been focused on optical metasurfaces as they offer a unique potential to achieve disruptive designs when paired with innovative fabrication techniques and inverse design tools. However, most metasurface designs have revolved around canonical geometries. While these elements are relatively easy to fabricate, they represent only a small portion of the design space, and rarely offer peak performance in transmission, phase range or field of view. In this work, a Lazy Ant Colony Optimization (LACO) technique is applied in conjunction with a full-wave solver using the Periodic Finite Element Boundary Integral (PFEBI) method to reveal high performing three-dimensional nanoantenna designs with potential applications for a variety of optical devices

Information Seeking by Under-Represented Communities

Final project for INST490: Integrative Capstone (Fall 2019). University of Maryland, College Park.Prince George's County Parks and Recreation offers recreation programs, facilities, and services throughout the entire county to its residents and visitors. The county operates and maintains more than 27,000 acres of parkland for parks, picnic areas, athletic fields, historic sites, community centers, and recreation facilities. The county also seeks to preserve parts of this parkland as buffers and natural open space. Parks and Recreation services include art and nature programs, fitness and sports programs, live performances, more than 90 miles of hiker/biker/equestrian trails, outdoor festivals, self-improvement classes, summer camps, teen and senior activities, and trips. While the county offers these various services and programs, more initiatives are needed to understand how Prince George's County residents are using these programs and services, or even if they are using them. Understanding how members of underrepresented communities use these services will allow the Department to better tailor what they offer for the benefit of all its residents. Through this project, the Parks and Recreation Department seeks to better understand how its residents, in particular how underrepresented communities, use its services and programs. The Department wants to know their information seeking behavior, whether different groups use the parks differently, and if certain parks features are being used more or less. To gather this information, an online and in-person survey, developed by the team member authors, was administered at various events, beginning in September 2019 and finishing in December 2019. The main point of contact throughout this project was Edith Michel, a certified Parks and Recreation Professional with more than 20 years of experience in local government within the Maryland-National Capital Park and Planning Commission. Other key Parks and Recreation staff who we worked with are Alex Teaff, the Community Outreach Manager and Kira Lewis, the Acting Chief of the Public Affairs & Marketing Division.Prince George’s Count

The human PAF complex coordinates transcription with events downstream of RNA synthesis.

The yeast PAF (yPAF) complex interacts with RNA polymerase II and coordinates the setting of histone marks associated with active transcription. We report the isolation and functional characterization of the human PAF (hPAF) complex. hPAF shares four subunits with yPAF (hCtr9, hPaf1, hLeo1, and hCdc73), but contains a novel higher eukaryotic-specific subunit, hSki8. RNAi against hSki8 or hCtr9 reduces the cellular levels of other hPAF subunits and of mono- and trimethylated H3-Lys 4 and dimethylated H3-Lys 79. The hSki8 subunit is also a component of the human SKI (hSKI) complex. Yeast SKI complex is cytoplasmic and together with Exosome mediates 3\u27-5\u27 mRNA degradation. However, hSKI complex localizes to both nucleus and cytoplasm. Immunoprecipitation experiments revealed that hPAF and hSKI complexes interact, and ChIP experiments demonstrated that hSKI associates with transcriptionally active genes dependent on the presence of hPAF. Thus, in addition to coordinating events during transcription (initiation, promoter clearance, and elongation), hPAF also coordinates events in RNA quality control