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Articles 220021 - 220050 of 1327428

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Error Detection In Quantum Algorithms, Simeon R. Hanks Mar 2021

Error Detection In Quantum Algorithms, Simeon R. Hanks

Theses and Dissertations

Quantum computers need to be able to control highly entangled quantum states in the presence of environmental perturbations that lead to errors in calculations. Progress in superconducting qubits has enabled the development of computers capable of running small quantum circuits. The current era of Noise Intermediate Scale Quantum computing has a high error rate. To alleviate this error rate we apply an encoding scheme that allows us to remove results with known errors improving the quality of our results. The encoding uses multiple qubits as a single logical qubit and balances the natural tendency of state-of-the-art quantum computers to decohere …

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Ab Initio Spectroscopy Of Natural And Artificial Fire Contaminants For V/W Band Frequency Signal Absorbance, Matthew B. Husk Mar 2021

Ab Initio Spectroscopy Of Natural And Artificial Fire Contaminants For V/W Band Frequency Signal Absorbance, Matthew B. Husk

Theses and Dissertations

The rotation and vibration spectral properties including frequencies and intensities for highly concentrated molecules present in wildland and artificial fires have been studied. These properties were used to determine absorption and its effect in a link budget analysis. Absorption in link budget analyses is commonly accounted for via line-by-line methodology aided by HITRAN documented intensities. Limited, if any, customization of spectral properties is available with HITRAN and other spectral databases. Ab initio calculations with different atomic basis sets were employed to obtain structures, dipole moments, rotational-vibrational frequencies and intensities, as well as various coupling parameters. Anharmonic corrections to the vibrational …

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Application Of Artificial Neural Networks To Elemental Assay Data For Nuclear Forensics Analysis, Jason G. Seik Mar 2021

Application Of Artificial Neural Networks To Elemental Assay Data For Nuclear Forensics Analysis, Jason G. Seik

Theses and Dissertations

There is a need to quickly and accurately determine the likely physical origins of a collected sample for nuclear treaty verification purposes. The objective of this research is to prove there is a means to relate different samples (Q-values) to one another using a 'same versus not-same' artificial neural network called a Siamese network. This would provide the capability of comparing an unknown sample to a database of samples with known physical origins. Using moment transformations on current data has shown to increase the prediction capabilities of a Siamese network, and using a triplet loss function in connection with the …

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The Obstacles To The Modernization Of Common Support Equipment, J. Erik Ritschard Mar 2021

The Obstacles To The Modernization Of Common Support Equipment, J. Erik Ritschard

Theses and Dissertations

The current fleet of Common Support Equipment (CSE) is faced with a $2B funding disconnect that threatens 9 of the 12 USAF Core Functions. This research identifies the barriers to efforts to modernize CSE across the sustainment, acquisition, and maintenance communities. Using a qualitative, grounded theory methodology, the responses are explored of interviewed Support Equipment managers responsible for the sustainment and modernization of CSE. Significant barriers to current modernization efforts were exposed, resulting in expensive, duplicative, and unreliable equipment; concluding that the AF must change the way CSE is administrated, funded, and culturally understood to prevent future mission degradation.

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Defensive Counterair For Air Base Air Defense Using Directed Energy And Kinetic Energy Weapons, Andrew S. Wilson Mar 2021

Defensive Counterair For Air Base Air Defense Using Directed Energy And Kinetic Energy Weapons, Andrew S. Wilson

Theses and Dissertations

Air bases in key locations provide a strategic advantage to the countries that access them, and are at constant threat from adversaries. This research seeks to determine the optimal maneuvering of a fixed number of fighter aircraft in a combat air patrol for defensive counterair to maximally and effectively attrit the inbound cruise missile threat to a stationary high value asset such as an air base. The problem formulation identifies multiple objectives for the model: minimize the distance traveled for the fighters, minimize the time utilized to engage the incoming cruise missiles, and maximize the number of cruise missiles destroyed. …

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The Wargaming Commodity Course Of Action Automated Analysis Method, William T. Deberry Mar 2021

The Wargaming Commodity Course Of Action Automated Analysis Method, William T. Deberry

Theses and Dissertations

This research presents the Wargaming Commodity Course of Action Automated Analysis Method (WCCAAM), a novel approach to assist wargame commanders in developing and analyzing courses of action (COAs) through semi-automation of the Military Decision Making Process (MDMP). MDMP is a seven-step iterative method that commanders and mission partners follow to build an operational course of action to achieve strategic objectives. MDMP requires time, resources, and coordination – all competing items the commander weighs to make the optimal decision. WCCAAM receives the MDMP's Mission Analysis phase as input, converts the wargame into a directed graph, processes a multi-commodity flow algorithm on …

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Robust Scandium Aluminum Nitride Mems Resonators For L Band Operation In Orbital Environments, Israel W. Dunk Mar 2021

Robust Scandium Aluminum Nitride Mems Resonators For L Band Operation In Orbital Environments, Israel W. Dunk

Theses and Dissertations

This thesis investigates AlN alloyed with scandium in a variety of resonator architectures including WEM, overtone WEM, LEM, and SAW that have the potential to achieve high levels of electrical performance and environmental robustness. SAW resonators operating near 370 MHz are fabricated on polycrystalline Sc.37Al.63N, and AlN with the resulting devices compared and conclusions drawn as to the merits of each material. The design and fabrication of SAW devices is discussed in detail, with the operating characteristics of these resonators then tested both electrically and mechanically. Mechanical characterisation includes analysis of vibration and shock effects on …

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Improving Airfield Pavement Degradation Prediction Skill With Local Climate And Traffic, Evan M. Fortney Mar 2021

Improving Airfield Pavement Degradation Prediction Skill With Local Climate And Traffic, Evan M. Fortney

Theses and Dissertations

Airfield pavements are a critical component of the global transportation network that provide a platform for national defense. Preventative and corrective maintenance activities are founded upon accurate expectations of degradation. The leading pavement management software creates degradation predictions from pavement groups using age as the IV and current state conditions as the DV. For this work, a framework is created and implemented that utilizes a PCR model to build upon accepted practices for degradation modeling to enhance and possibly augment future prediction capabilities. The model was applied to pairs of location and pavement family and reveals several findings: the selected …

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Delayed Authentication System For Civilian Satellite, Sean M. Feschak Mar 2021

Delayed Authentication System For Civilian Satellite, Sean M. Feschak

Theses and Dissertations

This thesis presents the feasibility of a Delayed Authentication System (DAS) for civilian satellite navigation (satnav) receivers. In satnav systems, encrypted signal components are transmitted synchronously with civilian components. Hence, the civilian signals can be authenticated by detecting the presence of encrypted signal components within the received signal. To authenticate, a reference station transmits estimated encrypted signal spreading code symbols processed using a high gain antenna. In this thesis, it is shown that a 1-meter diameter dish antenna is adequate to provide a high probability of successful authentication, thereby reducing overall system complexity and cost.

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Exploring Fog Of War Concepts In Wargame Scenarios, Dillon N. Tryhorn Mar 2021

Exploring Fog Of War Concepts In Wargame Scenarios, Dillon N. Tryhorn

Theses and Dissertations

This thesis explores fog of war concepts through three submitted journal articles. The Department of Defense and U.S. Air Force are attempting to analyze war scenarios to aid the decision-making process; fog modeling improves realism in these wargame scenarios. The first article "Navigating an Enemy Contested Area with a Parallel Search Algorithm" [1] investigates a parallel algorithm's speedup, compared to the sequential implementation, with varying map configurations in a tile-based wargame. The parallel speedup tends to exceed 50 but in certain situations. The sequential algorithm outperforms it depending on the configuration of enemy location and amount on the map. The …

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Utilizing Software Defined Radios For Increased Bandwidth In Satellite Communications, Brian M. Wright Mar 2021

Utilizing Software Defined Radios For Increased Bandwidth In Satellite Communications, Brian M. Wright

Theses and Dissertations

This research explores the background and future possibilities of using cooperative satellites equipped with Software Defined Radios (SDRs) to combine their bandwidth and increase their signal reliability. Software Defined Radios are a potential solution to realize various software applications that support a reconfigurable and adaptive communication system without altering any hardware devices or features. This benefit, along with others that are offered by SDRs and the ongoing improvements in commercial digital electronics have sparked an interest in developing small satellites for advanced communications. This research effort sets out to prove if a high bandwidth signal can be generated by using …

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Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan Mar 2021

Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan

Theses and Dissertations

One of the fundamental problems of robotics and navigation is the estimation of relative pose of an external object with respect to the observer. A common method for computing the relative pose is the Iterative Closest Point (ICP) algorithm, where a reference point cloud of a known object is registered against a sensed point cloud to determine relative pose. To use this computed pose information in down-stream processing algorithms, it is necessary to estimate the uncertainty of the ICP output, typically represented as a covariance matrix. In this thesis a novel method for estimating uncertainty from sensed data is introduced. …

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Air Combat Maneuvering Via Operations Research And Artificial Intelligence Methods, James B. Crumpacker Mar 2021

Air Combat Maneuvering Via Operations Research And Artificial Intelligence Methods, James B. Crumpacker

Theses and Dissertations

Within visual range air combat requires rapid, sequential decision-making to survive and defeat the adversary. Fighter pilots spend years perfecting maneuvers for these types of engagements, yet the emergence of unmanned, autonomous vehicle technologies elicits a natural question - can an autonomous unmanned combat aerial vehicle (AUCAV) be imbued with the necessary artificial intelligence to perform air combat maneuvering tasks independently? We formulate and solve the air combat maneuvering problem to examine this question, developing a Markov decision process model to control an AUCAV seeking to destroy a maneuvering adversarial vehicle. An approximate dynamic programming (ADP) approach implementing neural network …

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Allocation Of Scarce Healthcare Resources In A Military Treatment Facility During A Pandemic: A Comparison Of Goal Programming And Portfolio Decision Analysis Methods, Donald B. Hale Mar 2021

Allocation Of Scarce Healthcare Resources In A Military Treatment Facility During A Pandemic: A Comparison Of Goal Programming And Portfolio Decision Analysis Methods, Donald B. Hale

Theses and Dissertations

In a pandemic, healthcare decisionmakers face the challenge of allocating critical, but scarce healthcare resources in a dynamic, uncertain environment. Their decisions will not only affect the patients coming to the hospital for treatment, but also the Military Treatment Facility's personnel responsible. The decisionmaker must decide how to allocate these resources to achieve multiple, conflicting objectives under multiple constraints. In response, we propose a methodology for the implementation of both Portfolio Decision Analysis and Goal Programming. The steps of this methodology provide a framework with which the decisionmaker can develop optimal allocation of resources. This framework was then applied to …

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Improving Air Battle Management Target Assignment Processes Via Approximate Dynamic Programming, Joseph M. Liles Iv Mar 2021

Improving Air Battle Management Target Assignment Processes Via Approximate Dynamic Programming, Joseph M. Liles Iv

Theses and Dissertations

Military air battle managers face many challenges when directing operations in quickly evolving combat scenarios. These scenarios require rapid decisions to engage moving and unpredictable targets. In defensive operations, the success of a sequence of air battle management decisions is reflected by the friendly force's ability to maintain air superiority by defending friendly assets. We develop a Markov decision process (MDP) model of the air battle management (ABM)problem, wherein a set of unmanned combat aerial vehicles (UCAV) is tasked to defend a central asset from cruise missiles that arrive stochastically over time.

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Bayesian Augmentation Of Cnn-Lstm For Video Classification With Uncertainty Measures, Emmie K. Swize Mar 2021

Bayesian Augmentation Of Cnn-Lstm For Video Classification With Uncertainty Measures, Emmie K. Swize

Theses and Dissertations

The success of Department of Defense (DoD) missions rely heavily on intelligence, surveillance, and reconnaissance (ISR) capabilities, which supply information about the activities and resources of an enemy or adversary. To secure this information, satellites and unmanned aircraft systems collect video data to be classified by either humans or machine learning networks. Traditional automated video classification methods lack measures of uncertainty, meaning the network is unable to identify those cases in which it predictions are made with significant uncertainty. This leads to misclassification, as the traditional network classifies each observation with same amount of certainty, no matter what the observation …

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An Examination Of Civilian Retention In The United States Air Force, William F. Wilson Mar 2021

An Examination Of Civilian Retention In The United States Air Force, William F. Wilson

Theses and Dissertations

The backbone of the United States Air Force is undoubtedly the large civilian workforce that supplements the great work that is accomplished. Many research studies have been conducted on officer and enlisted personnel to ensure that the career fields are properly developed and managed to meet the ever growing demands of the military's varied missions, but no recent studies have focused on the civilian workforce. Striking a balance between new and experienced employees is paramount to success given the ever-changing economic and political landscapes where we find ourselves. The first part of the research uses logistic regression to determine the …

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The Effectiveness Of Image Augmentation In Deep Learning Networks For Detecting Covid-19: A Geometric Transformation Perspective, Mohamed Elgendi, Muhammad Umer Nasir, Qunfeng Tang, David Smith, John Paul Grenier, Catherine Batte, Bradley Spieler, William Donald Leslie, Carlo Menon, Richard Ribbon Fletcher, Newton Howard, Rabab Ward, William Parker, Savvas Nicolaou Mar 2021

The Effectiveness Of Image Augmentation In Deep Learning Networks For Detecting Covid-19: A Geometric Transformation Perspective, Mohamed Elgendi, Muhammad Umer Nasir, Qunfeng Tang, David Smith, John Paul Grenier, Catherine Batte, Bradley Spieler, William Donald Leslie, Carlo Menon, Richard Ribbon Fletcher, Newton Howard, Rabab Ward, William Parker, Savvas Nicolaou

School of Medicine Faculty Publications

Chest X-ray imaging technology used for the early detection and screening of COVID-19 pneumonia is both accessible worldwide and affordable compared to other non-invasive technologies. Additionally, deep learning methods have recently shown remarkable results in detecting COVID-19 on chest X-rays, making it a promising screening technology for COVID-19. Deep learning relies on a large amount of data to avoid overfitting. While overfitting can result in perfect modeling on the original training dataset, on a new testing dataset it can fail to achieve high accuracy. In the image processing field, an image augmentation step (i.e., adding more training data) is often …

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Unifying Ecosystem Responses To Disturbance Into A Single Statistical Framework, Nathan P. Lemoine Mar 2021

Unifying Ecosystem Responses To Disturbance Into A Single Statistical Framework, Nathan P. Lemoine

Biological Sciences Faculty Research and Publications

Natural ecosystems are currently experiencing unprecedented rates of anthropogenic disturbance. Given the potential ramifications of more frequent disturbances, it is imperative that we accurately quantify ecosystem responses to severe disturbance. Specifically, ecologists and managers need estimates of resistance and recovery from disturbance that are free of observation error, not biased by temporal stochasticity and that standardize disturbance magnitude among many disparate ecosystems relative to normal interannual variability. Here, I propose a statistical framework that estimates all four components of ecosystem responses to disturbance (resistance, recovery, elasticity and return time), while resolving all of the issues described above. Coupling autoregressive time …

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Building Toward A Solid Foundation: The Effect Of Thinking Concretely About The Future, Stacie F. Waites, Adam Farmer, Carol L. Esmark Jones Mar 2021

Building Toward A Solid Foundation: The Effect Of Thinking Concretely About The Future, Stacie F. Waites, Adam Farmer, Carol L. Esmark Jones

Marketing Faculty Research and Publications

According to construal level theory, consumers tend to think about their future abstractly, making it unclear and inexact. Here, a new approach is developed to help people enhance their future‐oriented outcomes by priming them to think about their future concretely. Two experiments show that priming a concrete mindset about the future leads to enhanced future‐oriented outcomes. Specifically, the studies show that participants discounted current funds in favor of future gains less when they were primed with a concrete mindset. Opportunity cost consideration is shown to be the mechanism driving this effect. Though research suggests that most consumers do not consider …

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Student Mathematical Communication In Solving Two Variable System Of Linear Equations, Fidia Lestariningsih, Tjang Daniel Chandra, Swasono Rahardjoa Mar 2021

Student Mathematical Communication In Solving Two Variable System Of Linear Equations, Fidia Lestariningsih, Tjang Daniel Chandra, Swasono Rahardjoa

Jurnal Pendidikan Sains

Communication is a basic skill for students in mathematics. This study describes students’ mathematical communication in solving mathematical problems. The results show that students with high cognitive abilities are able to consolidate and organize mathematical thinking through communication with students who have moderate and low abilities. All subjects use mathematical language to present mathematical ideas. Students with high cognitive abilities are able to communicate mathematical thinking correctly to friends, teachers, and others. However, all subjects have not been able to analyze and evaluate other mathematical ideas and strategies.

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Commognitive Students’ During Discussion In Solving Skewness And Kurtosis Problems, Evi Lutviana, Toto Nusantara, Sudirman Sudirman Mar 2021

Commognitive Students’ During Discussion In Solving Skewness And Kurtosis Problems, Evi Lutviana, Toto Nusantara, Sudirman Sudirman

Jurnal Pendidikan Sains

The purpose of this study was to analyze students’ commognitive activities during discussion sessions in solving skewness and kurtosis problems. The research method used was descriptive qualitative research involving third-semester students at the State University of Malang in the 2020–2021 academic year. Based on the analysis of the completion of LKM 1 and LKM 2, all 17 groups had not yet fulfilled the commognitive components. Therefore, several groups were randomly selected, namely Group 1 and Group 15, as research subjects. The results showed that Subject Group 1 (SK1) did not interpret the final results and also failed to reflect the …

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Online Learning Impact On Students' Scientific Argumentation Ability On Thermodynamics, Dewi Priyantini, Supriyono Koes Handayanto, Eny Latifaha Mar 2021

Online Learning Impact On Students' Scientific Argumentation Ability On Thermodynamics, Dewi Priyantini, Supriyono Koes Handayanto, Eny Latifaha

Jurnal Pendidikan Sains

Scientific argumentation is a complex cognitive process that requires scientific reasoning related to theories and evidence, as well as critical thinking in constructing arguments. The purpose of this study was to analyze students’ scientific argumentation abilities on the topic of thermodynamics in online learning. The sample consisted of 100 twelfth-grade students at SMA Negeri 1 Pacitan who had studied thermodynamics through both face-to-face and online learning. Data on scientific argumentation skills were collected through 11 two-tier questions accompanied by students’ explanations and arguments, with a reliability coefficient of 0.715, categorized as high. The assessment was based on the Toulmin Argumentation …

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Preliminary Data On The Potential For Unintentional Antidoping Rule Violations By Permitted Cannabidiol (Cbd) Use., Ute Mareck, Gregor Fusshöller, Hans Geyer, Marilyn A. Huestis, Anja B Scheiff, Mario Thevis Mar 2021

Preliminary Data On The Potential For Unintentional Antidoping Rule Violations By Permitted Cannabidiol (Cbd) Use., Ute Mareck, Gregor Fusshöller, Hans Geyer, Marilyn A. Huestis, Anja B Scheiff, Mario Thevis

Institute of Emerging Health Professions Faculty Papers

According to the World Anti-Doping Agency (WADA) regulations, cannabinoids use is prohibited in competition except for cannabidiol (CBD) use. For an adverse analytical finding (AAF) in doping control, cannabinoid misuse is based on identification of the pharmacologically inactive metabolite 11-nor-delta-9-carboxy-tetrahydrocannabinol-9-carboxylic acid (carboxy-THC) in urine at a concentration greater than 180 ng/ml. All other (minor) cannabinoids are reported as AAF when identified, except for CBD that has been explicitly excluded from the class of cannabinoids on WADA's Prohibited List since 2018. However, due to the fact that CBD isolated from cannabis plants may contain additional minor cannabinoids, the permissible use of …

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General Biology 2 Laboratory Manual, Dmitry Y. Brogun, Azure N. Faucette, Kristin Polizzotto, Farshad Tamari Mar 2021

General Biology 2 Laboratory Manual, Dmitry Y. Brogun, Azure N. Faucette, Kristin Polizzotto, Farshad Tamari

Open Educational Resources

Currently, many academic institutions are using one or more variations of online modalities due to the Covid-19 pandemic, and science educators face a unique challenge with distance-learning laboratories. Many resources to engage students in virtual, interactive laboratory activities exist, but we found that high costs and/or overlooked content left gaps for several topics typically taught in a general, introductory biology course for undergraduate biology majors (e.g., organismal biology). Additionally, resources for an online lab must be identified and curated from multiple sources, requiring intense demands on the instructors’ time. To meet this need and to overcome the financial burden of …

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Association Between Preterm-Birth Phenotypes And Differential Morbidity, Growth, And Neurodevelopment At Age 2 Years: Results From The Interbio-21st Newborn Study, Jose Villar, María C. Restrepo-Méndez, Rose Mcgready, Fernando C. Barros, Cesar G. Victora, Shama Munim, Aris T. Papageorghiou, Roseline Ochieng, Rachel Craik, Zulfiqar Ahmed Bhutta Mar 2021

Association Between Preterm-Birth Phenotypes And Differential Morbidity, Growth, And Neurodevelopment At Age 2 Years: Results From The Interbio-21st Newborn Study, Jose Villar, María C. Restrepo-Méndez, Rose Mcgready, Fernando C. Barros, Cesar G. Victora, Shama Munim, Aris T. Papageorghiou, Roseline Ochieng, Rachel Craik, Zulfiqar Ahmed Bhutta

Department of Obstetrics & Gynaecology

Importance: The etiologic complexities of preterm birth remain inadequately understood, which may impede the development of better preventative and treatment measures.
Objective: To examine the association between specific preterm-birth phenotypes and clinical, growth, and neurodevelopmental differences among preterm newborns compared with term newborns up to age 2 years.
Design, setting, and participants: The INTERBIO-21st study included a cohort of preterm and term newborn singletons enrolled between March 2012 and June 2018 from maternity hospitals in 6 countries worldwide who were followed up from birth to age 2 years. All pregnancies were dated by ultrasonography. Data were analyzed from November 2019 …

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Developing Guided Inquiry-Based Ecosystem Modules Based On Fish Pond Learning, Vilda Rima Aulia Zahroh, Sueb Sueb, Mimien Henie Irawati Al Muhdharb Mar 2021

Developing Guided Inquiry-Based Ecosystem Modules Based On Fish Pond Learning, Vilda Rima Aulia Zahroh, Sueb Sueb, Mimien Henie Irawati Al Muhdharb

Jurnal Pendidikan Sains

The aim of this research was to develop a guided inquiry-based ecosystem module using fish ponds as a learning resource that met valid and practical criteria. This research employed the ADDIE development model proposed by Branch. The results showed that the module validation score reached 98.78%, which indicated that the module was categorized as very valid, while the validation result from subject experts reached 100%. The practicality result was 98%, indicating that the module was categorized as very practical. In addition, the average result of students’ responses was 91.65%, showing that students gave positive responses to the module. Based on …

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Deep Learning For Anisoplanatic Optical Turbulence Mitigation In Long-Range Imaging, Matthew A. Hoffmire, Russell C. Hardie, Michael A. Rucci, Richard Van Hook, Barry K. Karch Mar 2021

Deep Learning For Anisoplanatic Optical Turbulence Mitigation In Long-Range Imaging, Matthew A. Hoffmire, Russell C. Hardie, Michael A. Rucci, Richard Van Hook, Barry K. Karch

Electrical and Computer Engineering Faculty Publications

We present a deep learning approach for restoring images degraded by atmospheric optical turbulence. We consider the case of terrestrial imaging over long ranges with a wide field-of-view. This produces an anisoplanatic imaging scenario where turbulence warping and blurring vary spatially across the image. The proposed turbulence mitigation (TM) method assumes that a sequence of short-exposure images is acquired. A block matching (BM) registration algorithm is applied to the observed frames for dewarping, and the resulting images are averaged. A convolutional neural network (CNN) is then employed to perform spatially adaptive restoration. We refer to the proposed TM algorithm as …

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Can Millennials Deliver On Equal Pay? Why The Time Is Finally Right For Pay Transparency, Susan R. Fiorentino, Sandra M. Tomkowicz Mar 2021

Can Millennials Deliver On Equal Pay? Why The Time Is Finally Right For Pay Transparency, Susan R. Fiorentino, Sandra M. Tomkowicz

Hofstra Labor & Employment Law Journal

No abstract provided.

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"I Know It When I See It": The Nlrb's Glaring Inconsistencies When Classifying Workers, Hunter Igoe Mar 2021

"I Know It When I See It": The Nlrb's Glaring Inconsistencies When Classifying Workers, Hunter Igoe

Hofstra Labor & Employment Law Journal

No abstract provided.

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