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The performance of Magnetized Liner Inertial Fusion (MagLIF) experiments is sensitive to the amount of laser energy coupled to the fuel during the preheat stage. 1 A significant source of energy loss in this process comes from the need to heat a laser entrance hole foil (LEH) located at the entrance to the target that is required to contain the gaseous fusion fuel. The energy lost to the LEH is a function of its thickness which can be reduced by cryogenically cooling the fuel, lowering the pressure required for a given fuel density. 2 To realize this, a cryogenically-cooled laser target platform was commissioned in the Pecos chamber that enables rapid testing of preheat configurations, 3 and a cryogenically-cooled MagLIF configuration was tested that symmetrically cools the liner from the top and bottom, minimizing temperature gradients across the target. These new capabilities were utilized to perform a cryogenically-cooled MagLIF experiment that demonstrated >2 kJ of preheat energy coupled to the fuel for the first time on Z.

The Topological Insulator (TI) BiSb, grown with a (012) film texture using molecular beam epitaxy, and coupled with a FM layer has been shown to have a very high Spin Hall Angle (SHA) > 2 and high electrical conductivity (>10 5 Ohm -1 m -1 ) in thin film stacks 1 . This makes the TI material ideally suited for spin transfer devices requiring several orders of magnitude less power consumption to operate than other traditional devices 2 . However, the practical implementation of this TI material into devices using PVD requires you overcome many severe material challenges. The BiSb material is very soft, easily damaged in ion milling or by subsequent depositions, it has a very low melting point ~ 280C, and hence possesses a very large in-plane grain size as deposited at room temperature, ~6X the targeted thickness in devices. Thermal Migration of Sb out of the TI material is also a severe problem, which is exacerbated by film roughness and large grain sizes, and all of this must be solved while growing and maintaining a non-prismatic (012) texture of BiSb with low roughness, good interfacial TI properties, at reasonable operating temperatures > 180C in actual device stacks, non-epitaxially on SiOx or ceramic substrates. We discuss here how we addressed these challenges through appropriate selection of epitaxial and non-epitaxial materials for buffer layer(s) (bottom interface), and (top interface) interlayer(s), and by using a non-uniform thickness doping of the BiSb(X) material to stabilize and grow a BiSbX(012) textured layer with low roughness, good TI properties, at elevated temperatures in FM thin film stacks.

The Global Exploration Roadmap provides a pathway for humans to leave lower Earth orbit and develop a sustained presence in cislunar space as well as the lunar surface before embarking on a long journey to Mars. During these crewed Long Duration Exploration Missions (LDEM), communication delays will limit mission control availability to support the crew during critical in-flight anomalies. In order to address this challenge, future human spaceflight operations will benefit from intelligent Virtual Assistants (VAs) capable of assisting the crew in detecting, diagnosing, and resolving emergency anomalies. This intelligent technology could increase the probability of mission success and crew safety in emergency scenarios and could improve overall crew performance while operating in the hostile environment of deep space. Daphne-AT is a VA to support crewed LDEM in the context of diagnosing and resolving in-flight anomalies related to the Environmental Control and Life Support System (ECLSS) of a spacecraft. The overall research objective is to investigate the effect of Daphne-AT on human performance, cognitive workload, situational awareness, and trust in autonomous systems. Daphne-AT will be validated using controlled laboratory experiments, and further evaluation will occur during the Human Exploration Research Analog (HERA) C6 research campaign, consisting of four 45-day missions in 2020–21. In this paper, we provide an overview of our first version of Daphne-AT (i.e., baseline version), and discuss the design of anomaly scenarios using NASA's ECLSS simulator and the experimental set up for laboratory experiments. A preliminary within-subjects (i.e., with and without Daphne-AT) experiment was conducted with five human subjects, and preliminary results indicate that the use of Daphne-AT increases performance and decreases cognitive workload in the context of ECLSS anomaly scenarios. The data also show that subjects exhibited trust in using Daphne-AT, while it improved certain aspects of their situational awareness. Our work is part of the Human Capabilities Assessments for Autonomous Missions (HCAAM) Virtual NASA Science Center of Research (VNSCOR) within the NASA Human Research Program, and the ultimate goal is to generate standards and guidelines about how to design such VAs for future LDEMs.

In this work, we consider collaborative unmanned aerial vehicles (UAVs) with a gimbaled sensor tracking multiple mobile surface targets, where the number of targets is greater than the number of UAVs. To this end, we have developed an efficient distributed software algorithm enabling a team of collaborative unmanned aerial vehicles to effectively detect and track multiple mobile ground targets. The software framework we present in this paper includes optimal sensor management technique to minimize the localization uncertainty of targets, efficient data association method, and a consensus decision-making algorithm to reach agreement on target assignments. Our novel strategy in this integrated framework of cooperative aerial robots effectively utilizes their sensing resources using the optimal sensor management technique as well as the consensus decision-making. Our results show that a team of n UAVs can effectively track more than 2n targets with acceptable localization uncertainties.

Board level drop impact tests to evaluate electronic package mounts on printed circuit board (PCB) solder joint reliability is critical, especially for handheld and mobile consumer products. Standard drop tests refer the JEDEC specification (JESD22-B111) for PCB design and testing conditions. There are several studies about the board level drop reliability of electronic products to focus on the solder joint failure mechanism (e.g., the crack location and characteristics) under the JEDEC standard. However, the literatures lack a study of the correlation of the PCB dynamic strain and solder joint stress during the board level drop impact and real product system level shock test. In this work, a 15x15 mm2 Quad Flat No Leads (QFN) package which is Wi-Fi module function used in industry scanner product was chosen to measure the peak acceleration and PCB strain under 1.2 meter height system level free drop. The maximum PCB strain would be used to correlate with standard board level drop tests to measure and calculate acceleration response. From the result, it shows that at similar PCB strain response the system level free drop tests peak acceleration is about 2900G and the board level drop tests peak acceleration is about 325G.Besides, the 3D transient numerical model based on the support excitation scheme was also performed to obtain thorough understanding of structural responses of the test vehicle and reliability of its solder joints under different test conditions. This model would be used to compute solder joint maximum interfacial normal and shear stresses. A fatigue reliability model that predicts the drop counts for different drop test conditions of JEDEC drop test condition: B (1500 G; 0.5 ms) and system-like condition: (325 G; 0.576 ms) was established. This study provides an accurate and reliable way to understand the correlation between system level and board level drop tests solder joint stress and to help to achieve service life improvements in early development stage.

Mass Data Collection through Facial Recognition Technology poses a threat to the personal privacy of millions, with big data companies selling and analyzing user data points without appropriate consent and having unrestricted access to said data. Personal privacy should be a right that requires protection in our interconnected society that is becoming ever more reliant on technology. We believe that as this technology progresses without proper restriction, its implementation will effectively eliminate personal privacy, effectively placing a constraint on user autonomy. This is due in part to the vagueness of current policies centered around privacy. If this does not change, personal privacy could be eliminated. FRT has many features, some of which are controversial and impede its effectiveness. Through a systems analysis approach that examines the integration of the social and technical dimensions of these privacy problems, our preliminary research examines several approaches that will be most effective in addressing this complex problem while supporting FRT development. By proposing the following solutions, we hope to prevent personal privacy infringement via FRT: Propose and pass policy similar to the Commercial Facial Recognition Privacy Act, improve data encryption for databases with sensitive personal information (such as Facial Recognition data), and change the way privacy policy is delivered to the consumer by setting maximum length standards on the policy that is written and using less legal jargon to promote the reading and understanding of these privacy policies and what they require of the user. Based on analysis of these proposed solutions, we believe that there will be an increase in security and the feeling of personal privacy across the board.

A cashless society is an economic state which handles financial transactions not in the form of traditional mediums of currency, such as cash or coins, but by transferring digital data (usually by electronic means, such as credit cards and mobile data) between participating parties.Participants of a cashless society must Figure out a way to protect their transaction data, acknowledging the risks of organizations collecting mass amounts of said data, which result in a reduction of personal privacy. Balancing individual privacy with data security is vital in the information age, especially considering the increasing risk of data breaches and exploitation.In order to increase privacy in a cashless society, a few courses of action can be combined to produce a lasting and desirable result for users: A new kind of banking service that assigns randomized numbers to credit cards, the use of blockchain to monitor all transactions from individuals, and a campaign to educate and inform key stakeholders about security and privacy risks to provide the necessary tools and background knowledge to safeguard their own information before interaction with a foreign entity or other third parties (i.e. cybersecurity departments, IT technicians, etc). Blockchain and card number randomization are both susceptible to zero-day errors, bugs, and varied levels of social acceptance. This preliminary research draws on a systems analysis of cashless systems to identify and analyze a set of social and technical solutions to support a robust cashless system that protects users’ privacy and maintains the security of the system.The information found and analyzed will be beneficial by exposing weak points in current methods of data integrity and security. Learning about current and future methods of managing privacy and data security in the technological age would be helpful in creating preventative countermeasures. This study provides critical steps to prevent the loss of personal privacy in a cashless system.

The development and implementation of smart infrastructure raises legitimate security and privacy concerns for both the specific users of these systems as well as the public at large. The consolidation of big data through smart applications within smart infrastructure systems allows large tech companies and government entities to gather and potentially exploit the personal information of consumers. These powerful organizations collect consumer data in order to perform analysis on it, trade or sell it, or simply store it for later use. The gathering of big data or metadata, data about data, provides an opportunity for the collector to observe or predict the behaviors of specific individuals or groups. Those holding this information could use it to promote their own agendas or to otherwise exploit those from whom it has been collected without their knowledge or consent. Additionally, the current lack of legislation and policies concerning the security of smart applications or IoT devices makes the possibility of security and privacy breaches more prevalent. A breach would allow access to sensitive information which would be a threat to security and privacy at an individual and/or national scale. Due to the dynamic nature of smart infrastructure, we employed a systems analysis of this problem as a methodological approach leading to three solutions. We recommend a three-part solution-based analysis, consisting of 1.) Financial Backing 2.) Creation of Policies and Regulations and 3.) Technical Integration. This solution addresses market mitigation, data privacy for consumers, and data authentication between smart technologies and critical infrastructure. Preliminary results of this research suggest that these components are necessary for a sustainable smart infrastructure.

Smart homes are becoming increasingly common across the United States with the advent and ongoing development of new and improved IoT devices. With the increasing use of these devices, there has been exponential growth in the amount of data collected on individuals. This poses potential privacy risks that can affect the lives of these users and raises an ethical question about what information is being collected and how it is used. Much of the data collected is used to discern information about when, why, and how the device was used. It must be questioned how much information collection is necessary and at what point does it become a violation of privacy. Additionally, many devices collect data at various times when the user may not be aware of it. This information collected can be used to target specific advertisements, influence users, or be sold to third-party sources. Although much of this information is laid out in lengthy, often deceptive terms and conditions for most devices, many people do not read them or understand the implications they pose. In this paper, we present a solution that monitors data leaving the house through a device integrated within the home network with the aim of spreading awareness surrounding the potential risks associated with this issue and to work towards limiting the amount of information that is collected.

Laryngeal cancer treatments, while curative, often lead to voice impairment. Minimally invasive surgical methods that facilitate greater preservation of healthy tissue have recently emerged, but they are still limited in important ways. In this work, we describe a device that combines the advantages of the two primary minimally invasive approaches: the high quality incision and reduced post-operative pain achievable with transoral laser microsurgery and the superior visualization and tissue manipulability afforded by transoral robotic surgery. Our 11mm diameter scanning system connects to focusing optics and a fiber optic laser source and can direct a laser beam across a 18 x 10mm plane with controllable trajectories at speeds up to 7m/s. We describe its design and benchtop validation and present avenues for further development within a clinical environment. While oncological treatment is a natural first application area for this technology, we anticipate that it may also yield important benefits for the minimally invasive treatment of benign laryngeal diseases.

Three types of data were combined together to observe the evolution of the thunderstorm at the Straits of Malacca. The first data is a collection of electric field waveforms that where captured and analyzed to obtain the flash rates. Radar images from weather radar were observed in terms of their reflectivity value and cross section to locate the active regions of a thunderstorm. Next, a lightning detection system of World Wide Lightning Location Network (WLLN) capable of capturing lightning strike locations in latitudes and longitudes where used together with all the data to observe the if lightning are present at the active region. Upon overlaying the data, an observed cloud be found that the region with high reflective value (55-60 dBz) denoted with red color, have high concentration of lightning strike from WWLLN. Combination of data will help us understand further on the behavior of the thunderstorm.

Throughout scientific history, overarching theoretical frameworks have allowed researchers to grow beyond personal intuitions and culturally biased theories. They allow to verify and replicate existing findings, and to link disconnected results. The notion of self-play, albeit often cited in multiagent Reinforcement Learning, has never been grounded in a formal model. We present a formalized framework, with clearly defined assumptions, which encapsulates the meaning of self-play as abstracted from various existing self-play algorithms. This framework is framed as an approximation to a theoretical solution concept for multiagent training. On a simple environment, we qualitatively measure how well a subset of the captured self-play methods approximate this solution when paired with the famous PPO algorithm. The results indicate that throughout training the trained policies exhibit cyclic evolutions, showing that self-play research is still at an early stage.

A hybrid manufacturing process combining abrasive jet and laser micromaching enables the creation of living hinges in nitinol that retain the superelastic properties of the bulk material. The former selectively etches through the thickness of a workpiece and the latter defines the part’s final geometry. Because the majority of the material removal is done with the room-temperature mechanical etching procedure, thermal damage to the part is minimized. Processing parameters to achieve desired geometries are described, a bending stiffness model for the living hinges is provided, and validation experiments are presented. Lastly, to demonstrate the usefulness of these components to millimeter-sized robotic systems and medical devices, we show their integration in two prototype devices: an endoscopic camera wrist and a simple laser beam steering system.

In visual object recognition problems essential to surveillance and navigation problems in a variety of military and civilian use cases, low-resolution and low-quality images present great challenges to this problem. Recent advancements in deep learning based methods like EDSR/VDSR have boosted pixel domain image super-resolution (SR) performances significantly in terms of signal to noise ratio(SNR)/ mean square error(MSE) metrics of the super-resolved image. However, these pixel domain signal quality metrics may not directly correlate to the machine vision tasks like key points detection and object recognition. In this work, we develop a machine vision tasks-friendly super-resolution technique which enhances the gradient images and associated features from the low-resolution images that benefit the high level machine vision tasks. Here, a residual learning deep neural network based gradient image super-resolution solution is developed with scale space adaptive network depth, and simulation results demonstrate the performance gains in both gradient image quality as well as key points repeatability.

In recent years, increasing interest in distributed sensing networks has led to a demand for robust multi-sensor multi-object tracking (MOT) methods that can take advantage of large quantities of gathered data. However, distributed sensing has unique challenges stemming from limited computational resources, limited bandwidth, and complex network topology that must be considered within a given tracking method. Several recently developed methods that are based upon the random finite set (RFS) have shown promise as statistically rigorous approaches to the distributed MOT problem. Among the most desirable qualities of RFS-based approaches is that they are derived from a common mathematical framework, finite set statistics, which provides a basis for principled fusion of full multi-object probability distributions. Yet, distributed labeled RFS tracking is a still-maturing field of research, and many practical considerations must be addressed before large-scale, real-time systems can be implemented. For example, methods that use label-based fusion require perfect label consistency of objects across sensors, which is impossible to guarantee in scalable distributed systems. This paper provides a survey of the challenges inherent in distributed tracking using labeled RFS methods. An overview of labeled RFS filtering is presented, the distributed MOT problem is characterized, and recent approaches to distributed labeled RFS filtering are examined. The problems that currently prevent implementation of distributed labeled RFS trackers in scalable real-time systems are identified and demonstrated within the scope of several exemplar scenarios.

As the number of distributed energy resources (DERs) continues to increase, the DER response during a fault is becoming critical to power system stability. In the near future, DERs are expected to provide advanced functions such as voltage ride through and dynamic voltage support to maintain stable power system operation. In this context, an aggregated model of dynamic DERs that includes these advanced functions has been developed previously under the composite load model structure. In order to provide model parameters appropriate for an actual distribution system, however, dynamic simulations based on a detailed feeder model are required. Therefore, the purpose of this study is to evaluate the dynamic voltage response of a detailed feeder model incorporating modern DERs. In experiments on data from an actual circuit in California, the dynamic simulations reveal the partial loss behaviors of the DERs for several voltage sags, along with reactive current output induced by the dynamic voltage support.