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Microsputterer with integrated ion-drag focusing for additive manufacturing of thin, narrow conductive lines

Published in:
J. Phys. D.: Appl. Phys., Vol. 51, 2018, 165603.

Summary

We report the design, modelling, and proof-of-concept demonstration of a continuously fed, atmospheric-pressure microplasma metal sputterer that is capable of printing conductive lines narrower than the width of the target without the need for post-processing or lithographic patterning. Ion drag-induced focusing is harnessed to print narrow lines; the focusing mechanism is modelled via COMSOL Multiphysics simulations and validated with experiments. A microplasma sputter head with gold target is constructed and used to deposit imprints with minimum feature sizes as narrow as 9 μm, roughness as small as 55 nm, and electrical resistivity as low as 1.1 mu Omega · m.
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Summary

We report the design, modelling, and proof-of-concept demonstration of a continuously fed, atmospheric-pressure microplasma metal sputterer that is capable of printing conductive lines narrower than the width of the target without the need for post-processing or lithographic patterning. Ion drag-induced focusing is harnessed to print narrow lines; the focusing mechanism...

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Next-generation embedded processors: an update

Published in:
GOMACTech Conf., 12-15 March 2018.

Summary

For mission assurance, Department of Defense (DoD) embedded systems should be designed to mitigate various aspects of cyber risks, while maintaining performance (size, weight, power, cost, and schedule). This paper reports our latest research effort in the development of a next-generation System-on-Chip (SoC) for DoD applications, which we first presented in GOMACTech 2014. This paper focuses on our ongoing work to enhance the mission assurance of its programmable processor. We will explain our updated processor architecture, justify the use of resources, and assess the processor's suitability for mission assurance.
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Summary

For mission assurance, Department of Defense (DoD) embedded systems should be designed to mitigate various aspects of cyber risks, while maintaining performance (size, weight, power, cost, and schedule). This paper reports our latest research effort in the development of a next-generation System-on-Chip (SoC) for DoD applications, which we first presented...

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SST asteroid search performance 2014-2017

Summary

From 2014 to 2017, the Lincoln Near-Earth Asteroid Research (LINEAR) program performed wide-area asteroid search using the 3.5-m Space Surveillance Telescope (SST) located on Atom Peak at White Sands Missile Range, N.M. The SST was developed by MIT Lincoln Laboratory (MIT/LL) for the Defense Advanced Research Projects Agency (DARPA) to advance the nation's capabilities in space situational awareness. LINEAR asteroid search using SST was funded by the National Aeronautics and Space Administration (NASA). During three years of asteroid search operations, the SST had more than 14 million observations accepted by the Minor Planet Center (MPC) and contributed to the discovery of 142 previously unknown near-Earth objects (NEOs). This paper provides a summary of SST asteroid search performance during the three years of operation at Atom Peak, and describes performance improvements achieved through processing software upgrades, refinements in search strategy, and hardware upgrades such as the successful installation of Wide-Field Camera 2 (WFC-2) in summer 2016.
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Summary

From 2014 to 2017, the Lincoln Near-Earth Asteroid Research (LINEAR) program performed wide-area asteroid search using the 3.5-m Space Surveillance Telescope (SST) located on Atom Peak at White Sands Missile Range, N.M. The SST was developed by MIT Lincoln Laboratory (MIT/LL) for the Defense Advanced Research Projects Agency (DARPA) to...

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Large-format Geiger-mode avalanche photodiode arrays and readout circuits

Published in:
IEEE J. Sel. Top. Quantum Electron., Vol. 24, No. 2, March/April 2018, 3800510.

Summary

Over the past 20 years, we have developed arrays of custom-fabricated silicon and InP Geiger-mode avalanche photodiode arrays, CMOS readout circuits to digitally count or time stamp single-photon detection events, and techniques to integrate these two components to make back-illuminated solid-state image sensors for lidar, optical communications, and passive imaging. Starting with 4 × 4 arrays, we have recently demonstrated 256 × 256 arrays, and are working to scale to megapixel-class imagers. In this paper, we review this progress and discuss key technical challenges to scaling to large format.
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Summary

Over the past 20 years, we have developed arrays of custom-fabricated silicon and InP Geiger-mode avalanche photodiode arrays, CMOS readout circuits to digitally count or time stamp single-photon detection events, and techniques to integrate these two components to make back-illuminated solid-state image sensors for lidar, optical communications, and passive imaging...

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Machine learning for medical ultrasound: status, methods, and future opportunities

Published in:
Abdom. Radiol., 2018, doi: 10.1007/s00261-018-1517-0.

Summary

Ultrasound (US) imaging is the most commonly performed cross-sectional diagnostic imaging modality in the practice of medicine. It is low-cost, non-ionizing, portable, and capable of real-time image acquisition and display. US is a rapidly evolving technology with significant challenges and opportunities. Challenges include high inter- and intra-operator variability and limited image quality control. Tremendous opportunities have arisen in the last decade as a result of exponential growth in available computational power coupled with progressive miniaturization of US devices. As US devices become smaller, enhanced computational capability can contribute significantly to decreasing variability through advanced image processing. In this paper, we review leading machine learning (ML) approaches and research directions in US, with an emphasis on recent ML advances. We also present our outlook on future opportunities for ML techniques to further improve clinical workflow and US-based disease diagnosis and characterization.
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Summary

Ultrasound (US) imaging is the most commonly performed cross-sectional diagnostic imaging modality in the practice of medicine. It is low-cost, non-ionizing, portable, and capable of real-time image acquisition and display. US is a rapidly evolving technology with significant challenges and opportunities. Challenges include high inter- and intra-operator variability and limited...

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Trust and performance in human-AI systems for multi-domain command and control

Summary

Command and Control is one of the core tenants of joint military operations, however, the nature of modern security threats, the democratization of technology globally, and the speed and scope of information flows are stressing traditional operational paradigms, necessitating a fundamental shift to better concurrently integrate and operate across multiple physical and virtual domains. In this paper, we aim to address these challenges through the proposition of three concepts that will guide the creation of integrated human-AI Command and Control systems, inspired by recent advances and successes within the commercial sector and academia. The first concept is a framework for integration of AI capabilities into the enterprise that optimizes trust and performance within the workforce. The second is an approach for facilitating multi-domain operations though realtime creation of multi-organization multi-domain task teams by dynamic management of information abstraction, teaming, and risk control. The third is a new paradigm for multi-level data security and multi-organization data sharing that will be a key enabler of joint and coalition multi-domain operation in the future. Lastly, we propose a set of recommendations towards the research, development, and instantiation of these transformative advances in Command and Control capability.
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Summary

Command and Control is one of the core tenants of joint military operations, however, the nature of modern security threats, the democratization of technology globally, and the speed and scope of information flows are stressing traditional operational paradigms, necessitating a fundamental shift to better concurrently integrate and operate across multiple...

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XLab: early indications & warning from open source data with application to biological threat

Published in:
Proc. 51st Hawaii Int. Conf. on System Sciences, HICSS 2018, pp. 944-953.

Summary

XLab is an early warning system that addresses a broad range of national security threats using a flexible, rapidly reconfigurable architecture. XLab enables intelligence analysts to visualize, explore, and query a knowledge base constructed from multiple data sources, guided by subject matter expertise codified in threat model graphs. This paper describes a novel system prototype that addresses threats arising from biological weapons of mass destruction. The prototype applies knowledge extraction analytics—including link estimation, entity disambiguation, and event detection—to build a knowledge base of 40 million entities and 140 million relationships from open sources. Exact and inexact subgraph matching analytics enable analysts to search the knowledge base for instances of modeled threats. The paper introduces new methods for inexact matching that accommodate threat models with temporal and geospatial patterns. System performance is demonstrated using several simplified threat models and an embedded scenario.
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Summary

XLab is an early warning system that addresses a broad range of national security threats using a flexible, rapidly reconfigurable architecture. XLab enables intelligence analysts to visualize, explore, and query a knowledge base constructed from multiple data sources, guided by subject matter expertise codified in threat model graphs. This paper...

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Improving security at the system-call boundary in a type-safe operating system

Published in:
Thesis (M.E.)--Massachusetts Institute of Technology, 2018.

Summary

Historically, most approaches to operating sytems security aim to either protect the kernel (e.g., the MMU) or protect user applications (e.g., W exclusive or X). However, little study has been done into protecting the boundary between these layers. We describe a vulnerability in Tock, a type-safe operating system, at the system-call boundary. We then introduce a technique for providing memory safety at the boundary between userland and the kernel in Tock. We demonstrate that this technique works to prevent against the aforementioned vulnerability and a class of similar vulnerabilities, and we propose how it might be used to protect against simliar vulnerabilities in other operating systems.
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Summary

Historically, most approaches to operating sytems security aim to either protect the kernel (e.g., the MMU) or protect user applications (e.g., W exclusive or X). However, little study has been done into protecting the boundary between these layers. We describe a vulnerability in Tock, a type-safe operating system, at the...

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Classifier performance estimation with unbalanced, partially labeled data

Published in:
Proc. Machine Learning Research, Vol. 88, 2018, pp. 4-16.

Summary

Class imbalance and lack of ground truth are two significant problems in modern machine learning research. These problems are especially pressing in operational contexts where the total number of data points is extremely large and the cost of obtaining labels is very high. In the face of these issues, accurate estimation of the performance of a detection or classification system is crucial to inform decisions based on the observations. This paper presents a framework for estimating performance of a binary classifier in such a context. We focus on the scenario where each set of measurements has been reduced to a score, and the operator only investigates data when the score exceeds a threshold. The operator is blind to the number of missed detections, so performance estimation targets two quantities: recall and the derivative of precision with respect to recall. Measuring with respect to error in these two metrics, simulations in this context demonstrate that labeling outliers not only outperforms random labeling, but often matches performance of an adaptive method that attempts to choose the optimal data for labeling. Application to real anomaly detection data confirms the utility of the approach, and suggests direction for future work.
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Summary

Class imbalance and lack of ground truth are two significant problems in modern machine learning research. These problems are especially pressing in operational contexts where the total number of data points is extremely large and the cost of obtaining labels is very high. In the face of these issues, accurate...

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Key Challenges and Prospects for Optical Standoff Trace Detection of Explosives

Published in:
Trends in Analytical Chemistry, vol. 100

Summary

Sophisticated improvised explosive devices (IEDs) challenge the capabilities of current sensors, particularly in areas away from static checkpoints. This security gap could be filled by standoff chemical sensors that detect IEDs based on external trace explosive residues. Unfortunately, previous efforts have not led to widely deployed capabilities. Crucially, the physical morphology of trace explosive residues and chemical “clutter” present unique challenges to the operational performance of standoff sensors. In this review, an overview of standoff trace explosive detection systems is provided in the context of these unique challenges. Tradespace analysis is performed for two popular standoff detection methods: longwave infrared hyperspectral imaging and deep-UV Raman spectroscopy. The tradespace analysis method described in this review incorporates realistic trace explosive residues and background clutter into the technology development process. The review predicts system performance and areas where additional research is needed for these two technologies to optimize performance.
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Summary

Sophisticated improvised explosive devices (IEDs) challenge the capabilities of current sensors, particularly in areas away from static checkpoints. This security gap could be filled by standoff chemical sensors that detect IEDs based on external trace explosive residues. Unfortunately, previous efforts have not led to widely deployed capabilities. Crucially, the physical...

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