In this study we present the fabrication, the optical characterization and the electrical operation of a high quality, nanometer-sized, silicon-based light modulator made of nematic liquid crystals (LC) encapsulated i...
In this study we present the fabrication, the optical characterization and the electrical operation of a high quality, nanometer-sized, silicon-based light modulator made of nematic liquid crystals (LC) encapsulated into porous silicon (PSi) multilayer matrix. We first demonstrate the infiltration procedure and characterize the cell's reflectance and photoluminescence (PL) before and after infiltration. Then we examine the LC molecular alignment, and show that their long axis is positioned along the pore walls. Therefore, the electrical control of an interference filter is achieved by applying a field horizontal to the pore's directionality. We also demonstrate that by applying up to 10 V the molecules reorient, the effective refractive index is modulated by as much as Δ n = 0.15, and the reflectance spectra is red shifted.
作者：
Bryant, REFlynn, JERussell Bryant:is the leader for future decoy development in the Surface Electronic Warfare Systems Program Office
Program Executive Office for Theater Surface Combatants. Previously he served as CVN Ship Life Cycle Manager in the Aircraft Carrier Program Office Naval Sea Systems Command. He is a retired reserve Lieutenant Commander with surface warfare nuclear power and naval control of shipping/convoy qualifications. He was commissioned 1976 from the Rensselaer Polytechnic Institute NROTC program with a bachelor of engineering degree in nuclear engineering and minor in history and political science. His active duty service includes USS Mississippi (CGN 40) USS South Carolina (CGN 37)USS Texas (CGN 39)Commander Naval Surface Force
Atlantic Fleet (Readiness and Training) staff and
Commander Naval Air Force Pacific Fleet (Ship's Material) staff. He graduated in 1997 from the Naval War College College of Naval Command and Staff through the Non-Resident Seminar Program. He graduated in 1998 from the USDA Graduate School Leadership Development Academy Executive Potential Program. John Flynn:is the battle force operations and engineering leader for PEO Theater Surface Combatant participation in service and joint war games
exercises and experiments. Previously he was the first head of modeling and simulation (M&S) in the AEGIS Program Office where he pioneered the use of distributed M&S. He previously served at NSWC White Oak as head of system design and technical direction agent groups for the MK 116 Mod 7 ASW Control System. He graduated from Villanova University and was commissioned via NROTC in 1974. He served on sea duty aboard USS Forrestal (CV 59) and USS Coontz (DDG 40). He is a Captain in the Naval Reserve serving a third command tour. He has a BS in computer science from the University of Maryland graduated with highest distinction from the Naval War College and completed the Strategic Studies Program at Old Dominion University. He is a graduate of The Catholic University Columbus School
Many discussions and articles address the business and military changes supporting implementation of Joint Vision 2010 and its system-of-systems approach. The dynamics of international military operations and commitme...
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Many discussions and articles address the business and military changes supporting implementation of Joint Vision 2010 and its system-of-systems approach. The dynamics of international military operations and commitments, coupled with accelerating information technologies, can lead to confusion and uncertainty Customary rules recommend caution, even stopping, when confusion and uncertainty are present, yet the needed changes counsel toward accelerated efforts. Currently, systems engineering does not completely address delivering "operational war fighting capabilities," or foster commanders' confidence to fully exploit those capabilities upon delivery. Acquisition reform supports accelerating delivery of systems. likewise, accelerated delivery of "war fighting capabilities" within any opponents' fielding and deployment cycle is imperative. Technical advances in modeling and simulation, utilization concepts, and innovative evaluation methods create an opportunity to facilitate codevelopment of doctrine, operations, and training prior to producing hardware systems. On-line simulation and evaluation tools can overcome the need for physical systems. Specifically, this paper lays out the opportunity to evolve systems engineering to another level, operational engineering, which leverages from the modeling and simulation environment, prior to hardware production. That modeling and simulation paired with coevolution of procedures and on-line analysis will produce a trained customer base, fully prepared for deliveries of "operational war fighting capabilities".
We have determined single crystal structures of an A‐DNA decamer and a B‐DNA dodecamer at 0.83 and 0.95 Å, respectively. The resolution of the former is the highest reported thus far for any right‐handed nucle...
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During the training of self-organizing maps (SOMs), there is a conflict between the twin goals of topology preservation between input and output and the minimization of quantization error (QE). This is especially obvi...
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During the training of self-organizing maps (SOMs), there is a conflict between the twin goals of topology preservation between input and output and the minimization of quantization error (QE). This is especially obvious when the dimension of the input data (the dimension of the codebook vectors) is higher than the dimension of the output network (the dimension of the map grid). The standard SOM training algorithm usually achieves a reasonable balance between the two requirements but, in the end, the need for a low QE overrides the desire for optimal topology preservation. However, one can easily think of applications for which topology preservation should be given relatively greater weight than the standard algorithm allows. The paper describes three modifications to the incremental SOM learning algorithm that enhance its ability to preserve topological relationships without increasing the dimensionality of the network, but usually necessarily at the expense of QE. Experiments are described which demonstrate the new algorithms and compare their performance to that of the standard SOM training.
A variety of alternate training strategies for implementing the dual heuristic programming (DHP) method of approximate dynamic programming in the neurocontrol context are explored. The DHP method of controller trainin...
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A variety of alternate training strategies for implementing the dual heuristic programming (DHP) method of approximate dynamic programming in the neurocontrol context are explored. The DHP method of controller training has been successfully demonstrated by a number of authors on a variety of control problems in recent years, but no unified view of the implementation details of the method has yet emerged. A number of options are described for sequencing the training of the controller and critic networks in DHP implementations. Results are given about their relative efficiency and the quality of the resulting controllers for two benchmark control problems.
We apply the modal distribution, a high-resolution time-frequency distribution, to the study of sung musical passages. Evidence is presented comparing the modal distribution with the spectrogram for a set of synthetic...
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We have proposed for the task of hourly electric load forecasting a hybrid neural system combining unsupervised and supervised learning. The system consists of a recurrent neural gas (RNG) network and many Elman neura...
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We have proposed for the task of hourly electric load forecasting a hybrid neural system combining unsupervised and supervised learning. The system consists of a recurrent neural gas (RNG) network and many Elman neural networks (ENs). RNG is a modification we introduced in the neural gas (NG) network in order to enable it to do clustering using a sequence of input data. For verifying the RNG's performance, many architectures are compared in the learning of global and local models. In a global model only one supervised network is trained and in a local model the training examples are grouped by a clustering algorithm and each one of these groups is sent to different supervised networks. These architectures use different clustering algorithms (NG and RNG) or different supervised networks for prediction (ENs that are trained by backpropagation or backpropagation through time, and feedforward networks).
An integrated multichannel wavelength monitoring circuit using specially designed phased-array waveguide grating and detector arrays, which monitors all wavelength-division multiplexing channels in real-time (sixteen ...
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ISBN:
(纸本)155752582X
An integrated multichannel wavelength monitoring circuit using specially designed phased-array waveguide grating and detector arrays, which monitors all wavelength-division multiplexing channels in real-time (sixteen channels at 200-GHz spacing), has been demonstrated with /spl sim/0.02 nm accuracy.
Spiking neural networks have been shown to have powerful computation capability, but most results have been restricted to theoretical work. In this paper, we apply a spiking neural network to a time-series prediction ...
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Spiking neural networks have been shown to have powerful computation capability, but most results have been restricted to theoretical work. In this paper, we apply a spiking neural network to a time-series prediction problem, i.e., laser amplitude fluctuation data. We formulate the time-series problem as a spatio-temporal pattern recognition problem and present a learning method in which spatio-temporal patterns are recorded as synaptic delays. Experimental results show that the presented model is useful for temporal pattern recognition.
We developed an alternate method for density-based load estimation and applied it to estimate hip joint load distributions for two femora. Two-dimensional finite element models were constructed from single energy quan...
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