Publications
Wind turbine interference mitigation using a waveform diversity radar
April 27, 2017
Journal Article
Published in:
IEEE Trans. Aerosp. Electron. Syst., Vol. 53, No. 2, April 2017, pp. 805-15.
Summary
Interference from the proliferation of wind turbines is becoming a problem for ground-based medium-to-high pulse repetition frequency (PRF) pulsed–Doppler air surveillance radars. This paper demonstrates that randomizing some parameters of the transmit waveform from pulse to pulse, a filter can be designed to suppress both the wind turbine interference and the ground clutter. Furthermore, a single coherent processing interval (CPI) is sufficient to make an unambiguous range measurement. Therefore, multiple CPIs are not needed for range disambiguation, as in the staggered PRFs techniques. First, we consider a waveform with fixed PRF but diverse (random) initial phase applied to each transmit pulse. Second, we consider a waveform with diverse (random) PRF. The theoretical results are validated through simulations and analysis of experimental data. Clutter-plus-interference suppression and range disambiguation in a single CPI may be attractive to the Federal Aviation Administration and coastal radars.
Summary
Interference from the proliferation of wind turbines is becoming a problem for ground-based medium-to-high pulse repetition frequency (PRF) pulsed–Doppler air surveillance radars. This paper demonstrates that randomizing some parameters of the transmit waveform from pulse to pulse, a filter can be designed to suppress both the wind turbine interference and...
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Seismic barrier protection of critical infrastructure
April 25, 2017
Conference Paper
Published in:
16th Annual IEEE Int. Symp. on Technologies for Homeland Security, HST 2017, 25-26 April 2017.
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Summary
Each year, on average a major magnitude-8 earthquake strikes somewhere in the world. In addition, 10,000 earthquake related deaths occur annually, where collapsing buildings claim by far most lives. Moreover, in recent events, industry activity of oil extraction and wastewater reinjection are suspected to cause earthquake swarms that threaten high-value oil pipeline networks, U.S. oil storage reserves, and civilian homes. Earthquake engineering of building structural designs and materials have evolved over many years to minimize the destructive effects of seismic surface waves. However, even under the best engineering practices, significant damage and numbers of fatalities can still occur. In this paper, we present a novel concept and approach to redirect and attenuate the ground motion amplitudes caused by earthquakes by implementing an engineered subsurface seismic barrier – creating a form of metamaterial. The barrier is comprised of borehole array complexes and trench designs that impede and divert destructive seismic surface waves from a designated 'protection zone'. The barrier is also designed to divert not only surface waves in the aerial plane, but includes vertical 'V' shaped muffler structures composed of opposing boreholes to mitigate seismic waves from diffracting and traveling in the vertical plane. Computational 2D and 3D seismic wave propagation models developed at MIT Lincoln Laboratory suggest that borehole array and trench arrangements are critical to the redirection and self-interference reduction of broadband hazardous seismic waves in the vicinity of the structure to protect. The computational models are compared with experimental data obtained from large bench-scale physical models that contain scaled borehole arrays and trenches. These experiments are carried out at high frequencies, but with suitable material parameters and borehole dimensions. They indicate that effects of a devastating 7.0 Mw -magnitude earthquake can be reduced to those of a minor magnitude-4.5 or -5.5 Mw earthquake within a suitable protection zone. These results are very promising, and warrant validation in field scale tests.
Summary
Each year, on average a major magnitude-8 earthquake strikes somewhere in the world. In addition, 10,000 earthquake related deaths occur annually, where collapsing buildings claim by far most lives. Moreover, in recent events, industry activity of oil extraction and wastewater reinjection are suspected to cause earthquake swarms that threaten high-value...
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Effect of surface roughness and H-termination chemistry on diamond's semiconducting surface conductance
April 10, 2017
Journal Article
Published in:
Diamond Related Mater., Vol. 76, 1 June 2017, pp. 79-85.
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Summary
The H-terminated surface of diamond when activated with NO2 produces a surface conduction layer that has been used to make FETs. Variations in processing can significantly affect this conduction layer. This article discusses the effect of diamond surface preparation and H termination procedures on surface conduction. Surface preparations that generate a rough surface result in a more conductive surface with the conductivity increasing with surface roughness. We hypothesize that the increase in conductance with roughness is the result of an increase of reactive sites that generate the carriers. Roughening the diamond surface is just one way to generate these sites and the rough surface is believed to be a separate property from the density of surface reactive sites. The presence of C in the H2 plasma used for H termination decreases surface conductance. A simple procedure for NO2 activation is demonstrated. Interpretation of electrical measurements and possible alternatives to activation with NO2 are discussed. Using Kasu's oxidation model for surface conductance as a guide, compounds other than NO2 have been found to activate the diamond surface as well.
Summary
The H-terminated surface of diamond when activated with NO2 produces a surface conduction layer that has been used to make FETs. Variations in processing can significantly affect this conduction layer. This article discusses the effect of diamond surface preparation and H termination procedures on surface conduction. Surface preparations that generate...
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Twitter language identification of similar languages and dialects without ground truth
April 3, 2017
Conference Paper
Published in:
Proc. 4th Workshop on NLP for Similar Languages, Varieties and Dialects, 3 April 2017, pp. 73-83.
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Summary
We present a new method to bootstrap filter Twitter language ID labels in our dataset for automatic language identification (LID). Our method combines geolocation, original Twitter LID labels, and Amazon Mechanical Turk to resolve missing and unreliable labels. We are the first to compare LID classification performance using the MIRA algorithm and langid.py. We show classifier performance on different versions of our dataset with high accuracy using only Twitter data, without ground truth, and very few training examples. We also show how Platt Scaling can be use to calibrate MIRA classifier output values into a probability distribution over candidate classes, making the output more intuitive. Our method allows for fine-grained distinctions between similar languages and dialects and allows us to rediscover the language composition of our Twitter dataset.
Summary
We present a new method to bootstrap filter Twitter language ID labels in our dataset for automatic language identification (LID). Our method combines geolocation, original Twitter LID labels, and Amazon Mechanical Turk to resolve missing and unreliable labels. We are the first to compare LID classification performance using the MIRA...
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Bounded-collusion attribute-based encryption from minimal assumptions
March 28, 2017
Conference Paper
Published in:
IACR 20th Int. Conf. on Practice and Theory of Public Key Cryptography, PKC 2017, 28-31 March 2017.
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Summary
Attribute-based encryption (ABE) enables encryption of messages under access policies so that only users with attributes satisfying the policy can decrypt the ciphertext. In standard ABE, an arbitrary number of colluding users, each without an authorized attribute set, cannot decrypt the ciphertext. However, all existing ABE schemes rely on concrete cryptographic assumptions such as the hardness of certain problems over bilinear maps or integer lattices. Furthermore, it is known that ABE cannot be constructed from generic assumptions such as public-key encryption using black-box techniques. In this work, we revisit the problem of constructing ABE that tolerates collusions of arbitrary but a priori bounded size. We present two ABE schemes secure against bounded collusions that require only semantically secure public-key encryption. Our schemes achieve significant improvement in the size of the public parameters, secret keys, and ciphertexts over the previous construction of bounded-collusion ABE from minimal assumptions by Gorbunov et al. (CRYPTO 2012). In fact, in our second scheme, the size of ABE secret keys does not grow at all with the collusion bound. As a building block, we introduce a multidimensional secret-sharing scheme that may be of independent interest. We also obtain bounded-collusion symmetric-key ABE (which requires the secret key for encryption) by replacing the public-key encryption with symmetric-key encryption, which can be built from the minimal assumption of one-way functions.
Summary
Attribute-based encryption (ABE) enables encryption of messages under access policies so that only users with attributes satisfying the policy can decrypt the ciphertext. In standard ABE, an arbitrary number of colluding users, each without an authorized attribute set, cannot decrypt the ciphertext. However, all existing ABE schemes rely on concrete...
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Predicting exploitation of disclosed software vulnerabilities using open-source data
March 24, 2017
Conference Paper
Published in:
3rd ACM Int. Workshop on Security and Privacy Analytics, IWSPA 2017, 24 March 2017.
Summary
Each year, thousands of software vulnerabilities are discovered and reported to the public. Unpatched known vulnerabilities are a significant security risk. It is imperative that software vendors quickly provide patches once vulnerabilities are known and users quickly install those patches as soon as they are available. However, most vulnerabilities are never actually exploited. Since writing, testing, and installing software patches can involve considerable resources, it would be desirable to prioritize the remediation of vulnerabilities that are likely to be exploited. Several published research studies have reported moderate success in applying machine learning techniques to the task of predicting whether a vulnerability will be exploited. These approaches typically use features derived from vulnerability databases (such as the summary text describing the vulnerability) or social media posts that mention the vulnerability by name. However, these prior studies share multiple methodological shortcomings that infl ate predictive power of these approaches. We replicate key portions of the prior work, compare their approaches, and show how selection of training and test data critically affect the estimated performance of predictive models. The results of this study point to important methodological considerations that should be taken into account so that results reflect real-world utility.
Summary
Each year, thousands of software vulnerabilities are discovered and reported to the public. Unpatched known vulnerabilities are a significant security risk. It is imperative that software vendors quickly provide patches once vulnerabilities are known and users quickly install those patches as soon as they are available. However, most vulnerabilities are...
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High-efficiency large-angle Pancharatnam phase deflector based on dual-twist design
March 20, 2017
Journal Article
Published in:
Opt. Express, Vol. 25, No. 6, 20 March 2017.
Summary
We have previously shown through simulation that an optical beam deflector based on the Pancharatnam (geometric) phase can provide high efficiency with up to 80° deflection using a dual-twist structure for polarization-state control [Appl. Opt. 54, 10035 (2015)]. In this report, we demonstrate that its optical performance is as predicted and far beyond what could be expected for a conventional diffractive optical device. We provide details about construction and characterization of a ± 40° beam-steering device with 90% diffraction efficiency based on our dual-twist design at a 633nm wavelength.
Summary
We have previously shown through simulation that an optical beam deflector based on the Pancharatnam (geometric) phase can provide high efficiency with up to 80° deflection using a dual-twist structure for polarization-state control [Appl. Opt. 54, 10035 (2015)]. In this report, we demonstrate that its optical performance is as predicted...
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Wind information requirements for NextGen applications phase 4 final report
March 6, 2017
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-431
Summary
The success of many NextGen applications with time-based control elements, such as Required Time of Arrival (RTA) at a meter fix under 4D-Trajectory Based Operations (4D-TBO/Time of Arrival Control (TOAC) procedures or compliance to an Assigned Spacing Goal (ASG) between aircraft under Interval Management (IM) procedures, are subject to the quality of the atmospheric forecast utilized by participating aircraft. Erroneous information derived from provided forecast data, such as the magnitude of future headwinds relative to the headwinds actually experienced during flight, or forecast data that is insufficient to fully describe the forthcoming atmospheric conditions, can significantly degrade the performance of an attempted procedure. The work described in this report summarizes the major activities conducted in Fiscal Year 2015.
Summary
The success of many NextGen applications with time-based control elements, such as Required Time of Arrival (RTA) at a meter fix under 4D-Trajectory Based Operations (4D-TBO/Time of Arrival Control (TOAC) procedures or compliance to an Assigned Spacing Goal (ASG) between aircraft under Interval Management (IM) procedures, are subject to the...
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Detecting virus exposure during the pre-symptomatic incubation period using physiological data
March 3, 2017
Journal Article
Published in:
Science Translational Medicine (submitted), 3 March 2017.
Summary
Early pathogen exposure detection allows better patient care and faster implementation of public health measures (patient isolation, contact tracing). Existing exposure detection most frequently relies on overt clinical symptoms, namely fever, during the infectious prodromal period. We have developed a robust machine learning method to better detect asymptomatic states during the incubation period using subtle, sub-clinical physiological markers. Using high-resolution physiological data from non-human primate studies of Ebola and Marburg viruses, we pre-processed the data to reduce short-term variability and normalize diurnal variations, then provided these to a supervised random forest classification algorithm. In most subjects detection is achieved well before the onset of fever; subject cross-validation lead to 52±14h mean early detection (at >0.90 area under the receiver-operating characteristic curve). Cross-cohort tests across pathogens and exposure routes also lead to successful early detection (28±16h and 43±22h, respectively). We discuss which physiological indicators are most informative for early detection and options for extending this capability to lower data resolution and wearable, non-invasive sensors.
Summary
Early pathogen exposure detection allows better patient care and faster implementation of public health measures (patient isolation, contact tracing). Existing exposure detection most frequently relies on overt clinical symptoms, namely fever, during the infectious prodromal period. We have developed a robust machine learning method to better detect asymptomatic states during...
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Characterization of nitrated sugar alcohols by atmospheric-pressure chemical-ionization mass spectrometry
February 28, 2017
Journal Article
Published in:
Rapid Commun. Mass Spectrom., Vol. 33, 2017, pp. 333-43.
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Summary
RATIONALE: The nitrated sugar alcohols mannitol hexanitrate (MHN), sorbitol hexanitrate (SHN) and xylitol pentanitrate (XPN) are in the same class of compounds as the powerful military-grade explosive pentaerythritol tetranitrate (PETN) and the homemade explosive erythritol tetranitrate (ETN) but, unlike for PETN and ETN, ways to detect MHN, SHN and XPN by mass spectrometry (MS) have not been fully investigated. METHODS: Atmospheric-pressure chemical-ionization mass spectrometry (APCI-MS) was used to detect ions characteristic of nitrated sugar alcohols. APCI time-of-flight mass spectrometry (APCI-TOF MS) and collision-induced dissociation tandem mass spectrometry (CID MS/MS) were used for confirmation of each ion assignment. In addition, the use of the chemical ionization reagent dichloromethane was investigated to improve sensitivity and selectivity for detection of MHN, SHN and XPN. RESULTS: All the nitrated sugar alcohols studied followed similar fragmentation pathways in the APCI source. MHN, SHN and XPN were detectable as fragment ions formed by the loss of NO2, HNO2, NO3, and CH2NO2 groups, and in the presence of dichloromethane chlorinated adduct ions were observed. It was determined that in MS/MS mode, chlorinated adducts of MHN and SHN had the lowest limits of detection (LODs), while for XPN the lowest LOD was for the [XPN-NO2]- fragment ion. Partially nitrated analogs of each of the three compounds were also present in the starting materials, and ions attributable to these compounds versus those formed from in-source fragmentation of MHN, SHN, and XPN were distinguished and assigned using liquid chromatography APCI-MS and ESI-MS. CONCLUSIONS: The APCI-MS technique provides a selective and sensitive method for the detection of nitrated sugar alcohols. The methods disclosed here will benefit the area of explosives trace detection for counterterrorism and forensics.
Summary
RATIONALE: The nitrated sugar alcohols mannitol hexanitrate (MHN), sorbitol hexanitrate (SHN) and xylitol pentanitrate (XPN) are in the same class of compounds as the powerful military-grade explosive pentaerythritol tetranitrate (PETN) and the homemade explosive erythritol tetranitrate (ETN) but, unlike for PETN and ETN, ways to detect MHN, SHN and XPN...
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