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Effects of humidity and surface on photoalignment of brilliant yellow

Summary

Controlling and optimising the alignment of liquid crystals is a crucial process for display application. Here, we investigate the effects of humidity and surface types on photoalignment of an azo-dye brilliant yellow (BY). Specifically, the effect of humidity on the photoalignment of BY was studied at the stage of substrate storage before coating, during the spin-coating process, between film coating and exposure, and after exposure. Surprising results are the drastic effect of humidity during the spin-coating process, the humidity annealing to increase the order of the BY layer after exposure and the dry annealing to stabilise the layer. Our results are interpreted in terms of the effect of water on the aggregation of BY. The type of surface studied had minimal effects. Thin BY films (about 3 nm thickness) were sensitive to the hydrophilicity of the surface while thick BY films (about 30 nm thickness) were not affected by changing the surface. The results of this paper allow for the optimisation of the BY photoalignment for liquid crystal display application as well as a better understanding of the BY photoalignment mechanism.
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Summary

Controlling and optimising the alignment of liquid crystals is a crucial process for display application. Here, we investigate the effects of humidity and surface types on photoalignment of an azo-dye brilliant yellow (BY). Specifically, the effect of humidity on the photoalignment of BY was studied at the stage of substrate...

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Use of Photoacoustic Excitation and Laser Vibrometry to Remotely Detect Trace Explosives

Summary

In this paper, we examine a laser-based approach to remotely initiate, measure, and differentiate acoustic and vibrational emissions from trace quantities of explosive materials against their environment. Using a pulsed ultraviolet laser (266 nm), we induce a significant (>100  Pa) photoacoustic response from small quantities of military-grade explosives. The photoacoustic signal, with frequencies predominantly between 100 and 500 kHz, is detected remotely via a wideband laser Doppler vibrometer. This two-laser system can be used to rapidly detect and discriminate explosives from ordinary background materials, which have significantly weaker photoacoustic response. A 100  ng/cm2 limit of detection is estimated. Photoablation is proposed as the dominant mechanism for the large photoacoustic signals generated by explosives.
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Summary

In this paper, we examine a laser-based approach to remotely initiate, measure, and differentiate acoustic and vibrational emissions from trace quantities of explosive materials against their environment. Using a pulsed ultraviolet laser (266 nm), we induce a significant (>100  Pa) photoacoustic response from small quantities of military-grade explosives. The photoacoustic signal...

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Application of a resilience framework to military installations: a methodology for energy resilience business case decisions

Published in:
MIT Lincoln Laboratory Report TR-1216

Summary

The goal of the study was to develop and demonstrate an energy resilience framework at four DoD installations. This framework, predominantly focused on developing a business case, was established for broader application across the DoD. The methodology involves gathering data from an installation on critical energy load requirements, the energy costs and usage, quantifying the cost and performance of the existing energy resilience solution at the installation, and then conducting an analysis of alternatives to look at new system designs. Improvements in data collection at the installation level, as recommended in this report, will further increase the fidelity of future analysis and the accuracy of the recommendations. And most importantly, increased collaboration between the facility personnel and the mission operators at the installation will encourage holistic solutions that improve both the life cycle costs and the resilience of the installation's energy systems and supporting infrastructure.
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Summary

The goal of the study was to develop and demonstrate an energy resilience framework at four DoD installations. This framework, predominantly focused on developing a business case, was established for broader application across the DoD. The methodology involves gathering data from an installation on critical energy load requirements, the energy...

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Crosstalk characterization and mitigation in Geiger-mode avalanche photodiode arrays

Summary

Intra focal plane array (FPA) crosstalk is a primary development limiter of large, fine-pixel Geiger-mode avalanche photodiode (Gm-APD) arrays beyond 256×256 pixels. General analysis methods and results from MIT Lincoln Laboratory (MIT/LL) InP-based detector arrays will be presented.
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Summary

Intra focal plane array (FPA) crosstalk is a primary development limiter of large, fine-pixel Geiger-mode avalanche photodiode (Gm-APD) arrays beyond 256×256 pixels. General analysis methods and results from MIT Lincoln Laboratory (MIT/LL) InP-based detector arrays will be presented.

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Biomimetic antenna array using non-foster network to enhance directional sensitivity over broad frequency band

Published in:
IEEE Trans. Antennas Propag., Vol. 64, No. 10, October 2016, pp. 4297-4305.

Summary

Biologically inspired antenna arrays that mimic the hearing mechanism of insects are called biomimetic antenna arrays (BMAAs). They are attractive for microwave applications, such as compact direction finding systems. Earlier, the BMAAs were designed for narrow frequency band phase enhancement, whereas we now propose to design them for use with a non-Foster coupling network (NFC). As the NFCs are not restricted by gain bandwidth product, their incorporation in the design can provide wideband phase enhancement. A method for designing BMAA, using a non-Foster coupling network (NFC-BMAA), and also for obtaining system stability, is presented. Simulated and measured results of the fabricated structure are also presented and discussed.
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Summary

Biologically inspired antenna arrays that mimic the hearing mechanism of insects are called biomimetic antenna arrays (BMAAs). They are attractive for microwave applications, such as compact direction finding systems. Earlier, the BMAAs were designed for narrow frequency band phase enhancement, whereas we now propose to design them for use with...

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Side channel authenticity discriminant analysis for device class identification

Summary

Counterfeit microelectronics present a significant challenge to commercial and defense supply chains. Many modern anti-counterfeit strategies rely on manufacturer cooperation to include additional identification components. We instead propose Side Channel Authenticity Discriminant Analysis (SICADA) to leverage physical phenomena manifesting from device operation to match suspect parts to a class of authentic parts. This paper examines the extent that power dissipation information can be used to separate unique classes of devices. A methodology for distinguishing device types is presented and tested on both simulation data of a custom circuit and empirical measurements of Microchip dsPIC33F microcontrollers. Experimental results show that power side channels contain significant distinguishing information to identify parts as authentic or suspect counterfeit.
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Summary

Counterfeit microelectronics present a significant challenge to commercial and defense supply chains. Many modern anti-counterfeit strategies rely on manufacturer cooperation to include additional identification components. We instead propose Side Channel Authenticity Discriminant Analysis (SICADA) to leverage physical phenomena manifesting from device operation to match suspect parts to a class of...

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How deep neural networks can improve emotion recognition on video data

Published in:
ICIP: 2016 IEEE Int. Conf. on Image Processing, 25-28 September 2016.

Summary

We consider the task of dimensional emotion recognition on video data using deep learning. While several previous methods have shown the benefits of training temporal neural network models such as recurrent neural networks (RNNs) on hand-crafted features, few works have considered combining convolutional neural networks (CNNs) with RNNs. In this work, we present a system that performs emotion recognition on video data using both CNNs and RNNs, and we also analyze how much each neural network component contributes to the system's overall performance. We present our findings on videos from the Audio/Visual+Emotion Challenge (AV+EC2015). In our experiments, we analyze the effects of several hyperparameters on overall performance while also achieving superior performance to the baseline and other competing methods.
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Summary

We consider the task of dimensional emotion recognition on video data using deep learning. While several previous methods have shown the benefits of training temporal neural network models such as recurrent neural networks (RNNs) on hand-crafted features, few works have considered combining convolutional neural networks (CNNs) with RNNs. In this...

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The Offshore Precipitation Capability

Summary

In this work, machine learning and image processing methods are used to estimate radar-like precipitation intensity and echo top heights beyond the range of weather radar. The technology, called the Offshore Precipitation Capability (OPC), combines global lightning data with existing radar mosaics, five Geostationary Operational Environmental Satellite (GOES) channels, and several fields from the Rapid Refresh (RAP) 13 km numerical weather prediction model to create precipitation and echo top fields similar to those provided by existing Federal Aviation Administration (FAA) weather systems. Preprocessing and feature extraction methods are described to construct inputs for model training. A variety of machine learning algorithms are investigated to identify which provides the most accuracy. Output from the machine learning model is blended with existing radar mosaics to create weather radar-like analyses that extend into offshore regions. The resulting fields are validated using land radars and satellite precipitation measurements provided by the National Aeronautics and Space Administration (NASA) Global Precipitation Measurement Mission (GPM) core observatory satellite. This capability is initially being developed for the Miami Oceanic airspace with the goal of providing improved situational awareness for offshore air traffic control.
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Summary

In this work, machine learning and image processing methods are used to estimate radar-like precipitation intensity and echo top heights beyond the range of weather radar. The technology, called the Offshore Precipitation Capability (OPC), combines global lightning data with existing radar mosaics, five Geostationary Operational Environmental Satellite (GOES) channels, and...

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Enhancing HPC security with a user-based firewall

Summary

High Performance Computing (HPC) systems traditionally allow their users unrestricted use of their internal network. While this network is normally controlled enough to guarantee privacy without the need for encryption, it does not provide a method to authenticate peer connections. Protocols built upon this internal network, such as those used in MPI, Lustre, Hadoop, or Accumulo, must provide their own authentication at the application layer. Many methods have been employed to perform this authentication, such as operating system privileged ports, Kerberos, munge, TLS, and PKI certificates. However, support for all of these methods requires the HPC application developer to include support and the user to configure and enable these services. The user-based firewall capability we have prototyped enables a set of rules governing connections across the HPC internal network to be put into place using Linux netfilter. By using an operating system-level capability, the system is not reliant on any developer or user actions to enable security. The rules we have chosen and implemented are crafted to not impact the vast majority of users and be completely invisible to them. Additionally, we have measured the performance impact of this system under various workloads.
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Summary

High Performance Computing (HPC) systems traditionally allow their users unrestricted use of their internal network. While this network is normally controlled enough to guarantee privacy without the need for encryption, it does not provide a method to authenticate peer connections. Protocols built upon this internal network, such as those used...

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High-throughput ingest of data provenance records in Accumulo

Published in:
HPEC 2016: IEEE Conf. on High Performance Extreme Computing, 13-15 September 2016.

Summary

Whole-system data provenance provides deep insight into the processing of data on a system, including detecting data integrity attacks. The downside to systems that collect whole-system data provenance is the sheer volume of data that is generated under many heavy workloads. In order to make provenance metadata useful, it must be stored somewhere where it can be queried. This problem becomes even more challenging when considering a network of provenance-aware machines all collecting this metadata. In this paper, we investigate the use of D4M and Accumulo to support high-throughput data ingest of whole-system provenance data. We find that we are able to ingest 3,970 graph components per second. Centrally storing the provenance metadata allows us to build systems that can detect and respond to data integrity attacks that are captured by the provenance system.
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Summary

Whole-system data provenance provides deep insight into the processing of data on a system, including detecting data integrity attacks. The downside to systems that collect whole-system data provenance is the sheer volume of data that is generated under many heavy workloads. In order to make provenance metadata useful, it must...

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