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COVID-19 exposure notification in simulated real-world environments
April 15, 2022
Project Report
Published in:
MIT Lincoln Laboratory Report ACTA-3
Summary
Privacy-preserving contact tracing mobile applications, such as those that use the Google-Apple Exposure Notification (GAEN) service, have the potential to limit the spread of COVID-19 in communities, but the privacy-preserving aspects of the protocol make it difficult to assess the performance of the apps in real-world populations. To address this gap, we exercised the CovidWatch app on both Android and iOS phones in a variety of scripted realworld scenarios, relevant to the lives of university students and employees. We collected exposure data from the app and from the lower-level Android service, and compared it to the phones' actual distances and durations of exposure, to assess the sensitivity and specificity of the GAEN service configuration as of February 2021. Based on the app's reported ExposureWindows and alerting thresholds for Low and High alerts, our assessment is that the chosen configuration is highly sensitive under a range of realistic scenarios and conditions. With this configuration, the app is likely to capture many long-duration encounters, even at distances greater than six feet, which may be desirable under conditions with increased risk of airborne transmission.
Summary
Privacy-preserving contact tracing mobile applications, such as those that use the Google-Apple Exposure Notification (GAEN) service, have the potential to limit the spread of COVID-19 in communities, but the privacy-preserving aspects of the protocol make it difficult to assess the performance of the apps in real-world populations. To address this...
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The Simulation of Automated Exposure Notification (SimAEN) Model
April 15, 2022
Project Report
Published in:
MIT Lincoln Laboratory Report ACTA-5
Summary
Automated Exposure Notication (AEN) was implemented in 2020 to supplement traditional contact tracing for COVID-19 by estimating "too close for too long" proximities of people using the service. AEN uses Bluetooth messages to privately label and recall proximity events, so that persons who were likely exposed to SARS-CoV-2 can take the appropriate steps recommended by their health care authority. This paper describes an agent-based model that estimates the effects of AEN deployment on COVID-19 caseloads and public health workloads in the context of other critical public health measures available during the COVID-19 pandemic. We selected simulation variables pertinent to AEN deployment options, varied them in accord with the system dynamics available in 2020-2021, and calculated the outcomes of key metrics across repeated runs of the stochastic multi-week simulation. SimAEN's parameters were set to ranges of observed values in consultation with public health professionals and the rapidly accumulating literature on COVID-19 transmission; the model was validated against available population-level disease metrics. Estimates from SimAEN can help public health officials determine what AEN deployment decisions (e.g., configuration, workflow integration, and targeted adoption levels) can be most effective in their jurisdiction, in combination with other COVID-19 interventions (e.g., mask use, vaccination, quarantine and isolation periods).
Summary
Automated Exposure Notication (AEN) was implemented in 2020 to supplement traditional contact tracing for COVID-19 by estimating "too close for too long" proximities of people using the service. AEN uses Bluetooth messages to privately label and recall proximity events, so that persons who were likely exposed to SARS-CoV-2 can take...
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Adaptive stress testing: finding likely failure events with reinforcement learning
December 1, 2020
Journal Article
Published in:
J. Artif. Intell. Res., Vol. 69, 2020, pp. 1165-1201.
Summary
Finding the most likely path to a set of failure states is important to the analysis of safety critical systems that operate over a sequence of time steps, such as aircraft collision avoidance systems and autonomous cars. In many applications such as autonomous driving, failures cannot be completely eliminated due to the complex stochastic environment in which the system operates. As a result, safety validation is not only concerned about whether a failure can occur, but also discovering which failures are most likely to occur. This article presents adaptive stress testing (AST), a framework for finding the most likely path to a failure event in simulation. We consider a general black box setting for partially observable and continuous-valued systems operating in an environment with stochastic disturbances. We formulate the problem as a Markov decision process and use reinforcement learning to optimize it. The approach is simulation-based and does not require internal knowledge of the system, making it suitable for black-box testing of large systems. We present different formulations depending on whether the state is fully observable or partially observable. In the latter case, we present a modified Monte Carlo tree search algorithm that only requires access to the pseudorandom number generator of the simulator to overcome partial observability. We also present an extension of the framework, called differential adaptive stress testing (DAST), that can find failures that occur in one system but not in another. This type of differential analysis is useful in applications such as regression testing, where we are concerned with finding areas of relative weakness compared to a baseline. We demonstrate the effectiveness of the approach on an aircraft collision avoidance application, where a prototype aircraft collision avoidance system is stress tested to find the most likely scenarios of near mid-air collision.
Summary
Finding the most likely path to a set of failure states is important to the analysis of safety critical systems that operate over a sequence of time steps, such as aircraft collision avoidance systems and autonomous cars. In many applications such as autonomous driving, failures cannot be completely eliminated due...
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A quantitatively derived NMAC analog for smaller unmanned aircraft systems based on unmitigated collision risk
November 19, 2020
Journal Article
Published in:
Preprints, 19 November 2020.
Summary
The capability to avoid other air traffic is a fundamental component of the layered conflict management system to ensure safe and efficient operations in the National Airspace System. The evaluation of systems designed to mitigate the risk of midair collisions of manned aircraft are based on large-scale modeling and simulation efforts and a quantitative volume defined as a near midair collision (NMAC). Since midair collisions are difficult to observe in simulation and are inherently rare events, basing evaluations on NMAC enables a more robust statistical analysis. However, an NMAC and its underlying assumptions for assessing close encounters with manned aircraft do not adequately consider the different characteristics of smaller UAS-only encounters. The primary contribution of this paper is to explore quantitative criteria to use when simulating two or more smaller UASs in sufficiently close proximity that a midair collision might reasonably occur and without any mitigations to reduce the likelihood of a midair collision. The criteria assumes a historically motivated upper bound for the collision likelihood and subsequently identify the smallest possible NMAC analogs. We also demonstrate the NMAC analogs can be used to support modeling and simulation activities.
Summary
The capability to avoid other air traffic is a fundamental component of the layered conflict management system to ensure safe and efficient operations in the National Airspace System. The evaluation of systems designed to mitigate the risk of midair collisions of manned aircraft are based on large-scale modeling and simulation...
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Predicting cognitive load and operational performance in a simulated marksmanship task
July 3, 2020
Conference Paper
Published in:
Front. Human Neurosci., 3 July 2020.
Summary
Modern operational environments can place significant demands on a service member's cognitive resources, increasing the risk of errors or mishaps due to overburden. The ability to monitor cognitive burden and associated performance within operational environments is critical to improving mission readiness. As a key step toward a field-ready system, we developed a simulated marksmanship scenario with an embedded working memory task in an immersive virtual reality environment. As participants performed the marksmanship task, they were instructed to remember numbered targets and recall the sequence of those targets at the end of the trial. Low and high cognitive load conditions were defined as the recall of three- and six-digit strings, respectively. Physiological and behavioral signals recorded included speech, heart rate, breathing rate, and body movement. These features were input into a random forest classifier that significantly discriminated between the low- and high-cognitive load conditions (AUC=0.94). Behavioral features of gait were the most informative, followed by features of speech. We also showed the capability to predict performance on the digit recall (AUC = 0.71) and marksmanship (AUC = 0.58) tasks. The experimental framework can be leveraged in future studies to quantify the interaction of other types of stressors and their impact on operational cognitive and physical performance.
Summary
Modern operational environments can place significant demands on a service member's cognitive resources, increasing the risk of errors or mishaps due to overburden. The ability to monitor cognitive burden and associated performance within operational environments is critical to improving mission readiness. As a key step toward a field-ready system, we...
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Vector antenna and maximum likelihood imaging for radio astronomy
March 5, 2016
Conference Paper
Published in:
2016 IEEE Aerospace Conf., 5-12 March 2016.
Topic:
R&D area:
Summary
Radio astronomy using frequencies less than ~100 MHz provides a window into non-thermal processes in objects ranging from planets to galaxies. Observations in this frequency range are also used to map the very early history of star and galaxy formation in the universe. Much effort in recent years has been devoted to highly capable low frequency ground-based interferometric arrays such as LOFAR, LWA, and MWA. Ground-based arrays, however, cannot observe astronomical sources below the ionospheric cut-off frequency of ~10 MHz, so the sky has not been mapped with high angular resolution below that frequency. The only space mission to observe the sky below the ionospheric cut-off was RAE-2, which achieved an angular resolution of ~60 degrees in 1973. This work presents alternative sensor and algorithm designs for mapping the sky both above and below the ionospheric cutoff. The use of a vector sensor, which measures the full electric and magnetic field vectors of incoming radiation, enables reasonable angular resolution (~5 degrees) from a compact sensor (~4 m) with a single phase center. A deployable version of the vector sensor has been developed to be compatible with the CubeSat form factor.
Summary
Radio astronomy using frequencies less than ~100 MHz provides a window into non-thermal processes in objects ranging from planets to galaxies. Observations in this frequency range are also used to map the very early history of star and galaxy formation in the universe. Much effort in recent years has been...
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Model of turn-on characteristics of InP-based Geiger-mode avalanche photodiodes suitable for circuit simulations
April 22, 2015
Conference Paper
Published in:
SPIE, Vol. 9492, Advanced Photon Counting Techniques IX, 28 May 2015.
Topic:
R&D area:
Summary
A model for the turn-on characteristics of separate-absorber-multiplier InP-based Geiger-mode Avalanche Photodiodes (APDs) has been developed. Verilog-A was used to implement the model in a manner that can be incorporated into circuit simulations. Rather than using SPICE elements to mimic the voltage and current characteristics of the APD, Verilog-A can represent the first order nonlinear differential equations that govern the avalanche current of the APD. This continuous time representation is fundamentally different than the piecewise linear characteristics of other models. The model is based on a driving term for the differential current, which is given by the voltage overbias minus the voltage drop across the device?s space-charge resistance RSC. This drop is primarily due to electrons transiting the separate absorber. RSC starts off high and decreases with time as the initial breakdown filament spreads laterally to fill the APD. With constant bias voltage, the initial current grows exponentially until space charge effects reduce the driving function. With increasing current the driving term eventually goes to zero and the APD current saturates. On the other hand, if the APD is biased with a capacitor, the driving term becomes negative as the capacitor discharges, reducing the current and driving the voltage below breakdown. The model parameters depend on device design and are obtained from fitting the model to Monte-Carlo turn-on simulations that include lateral spreading of the carriers of the relevant structure. The Monte-Carlo simulations also provide information on the probability of avalanche, and jitter due to where the photon is absorbed in the APD.
Summary
A model for the turn-on characteristics of separate-absorber-multiplier InP-based Geiger-mode Avalanche Photodiodes (APDs) has been developed. Verilog-A was used to implement the model in a manner that can be incorporated into circuit simulations. Rather than using SPICE elements to mimic the voltage and current characteristics of the APD, Verilog-A can...
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Advisory services for user composition tools
February 7, 2015
Conference Paper
Published in:
9th IEEE Int. Conf. on Semantic Computing, IEEE ICSC 2015, 7-9 February 2015.
Summary
We have developed an ontology based framework that evaluates compatibility between processing modules within an end user development framework, using MIT Lincoln Laboratory's Composable Analytics environment as a test case. In particular, we focus on inter-module semantic compatibility as well as compatibility between data and modules. Our framework includes a core ontology that provides an extendible vocabulary that can describe module attributes, module input and output requirements and preferences, and data characteristics that are pertinent to selecting appropriate modules in a given situation. Based on the ontological description of the modules and data, we first present a framework that takes a rule based approach in measuring semantic compatibility. Later, we extend the rule based approach to a flexible fuzzy logic based semantic compatibility evaluator. We have built an initial simulator to test module compatibility under varying situations. The simulator takes in the ontological description of the modules and data and calculates semantic compatibility. We believe the framework and simulation environment together will help both the developers test new modules they create as well as support end users in composing new capabilities. In this paper, we describe the details of the framework, the simulation environment, and our iterative process in developing the module ontology.
Summary
We have developed an ontology based framework that evaluates compatibility between processing modules within an end user development framework, using MIT Lincoln Laboratory's Composable Analytics environment as a test case. In particular, we focus on inter-module semantic compatibility as well as compatibility between data and modules. Our framework includes a...
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Wideband antenna array for simultaneous transmit and receive (STAR) applications
July 6, 2014
Conference Paper
Published in:
2014 IEEE Int. Symp. on Antennas and Propagation & USNC/URSI National Radio Science Meeting, 6-11 July 2014.
Summary
A wideband antenna array for Simultaneous Transmit and Receive (STAR) applications is presented. The design is comprised of a ring array of TEM horns, and a monocone at the array's center. When the array is phased with the first order circular mode, it is isolated from the monocone. Thus, the array may be used in reception while the monocone is used in transmission, or vice versa. The array and monocone both produce quasi-omnidirectional patterns in the azimuthal planes. Simulations suggest that the design operates across an 8.4 : 1 bandwidth. This wide bandwidth is possible through the use of a novel capacitive feed employed in the TEM horn array.
Summary
A wideband antenna array for Simultaneous Transmit and Receive (STAR) applications is presented. The design is comprised of a ring array of TEM horns, and a monocone at the array's center. When the array is phased with the first order circular mode, it is isolated from the monocone. Thus, the...
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TCAS multiple threat encounter analysis
October 22, 2009
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-359
Topic:
R&D area:
R&D group:
Summary
The recent development of high-fidelity U.S. airspace encounter models at Lincoln Laboratory has motivated a simulation study of the Traffic Alert and Collision Avoidance System (TCAS) multiple threat logic. We observed from archived radar data that while rarer than single-threat encounters, multiple threat encounters occur more frequently than originally expected. The multithreat logic has not been analyzed in the past using encounter models. To generate multi-threat encounters, this report extends the statistical techniques used to develop pairwise correlated encounters. We generated and simulated a large number of multi-threat encounters using the TCAS logic implemented in Lincoln Laboratory's Collision Avoidance System Safety Assessment Tool. Near mid-air collision (NMAC) count indicates how often close encounters are resolved, unresolved, or induced by TCAS. Change in vertical miss distance shows the effect of the additional threat on the vertical separation between the first two aircraft. Risk ratio measures how the probability of an NMAC changes when an aircraft is equipped with TCAS versus being unequipped. Study results indicate that in multi-threat encounters, the TCAS logic results in a more than twofold increase in unresolved NMACs and approximately five times more induced NMACs than one-on-one encounters. TCAS provides a safety benefit in multi-threat encounters by issuing resolution advisories that result in increased vertical separation between the equipped aircraft and the first intruder.
Summary
The recent development of high-fidelity U.S. airspace encounter models at Lincoln Laboratory has motivated a simulation study of the Traffic Alert and Collision Avoidance System (TCAS) multiple threat logic. We observed from archived radar data that while rarer than single-threat encounters, multiple threat encounters occur more frequently than originally expected...
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