Time and frequency constrained sonar signal design for optimal detection of elastic objects.

PubMed

Hamschin, Brandon; Loughlin, Patrick J

2013-04-01

In this paper, the task of model-based transmit signal design for optimizing detection is considered. Building on past work that designs the spectral magnitude for optimizing detection, two methods for synthesizing minimum duration signals with this spectral magnitude are developed. The methods are applied to the design of signals that are optimal for detecting elastic objects in the presence of additive noise and self-noise. Elastic objects are modeled as linear time-invariant systems with known impulse responses, while additive noise (e.g., ocean noise or receiver noise) and acoustic self-noise (e.g., reverberation or clutter) are modeled as stationary Gaussian random processes with known power spectral densities. The first approach finds the waveform that preserves the optimal spectral magnitude while achieving the minimum temporal duration. The second approach yields a finite-length time-domain sequence by maximizing temporal energy concentration, subject to the constraint that the spectral magnitude is close (in a least-squares sense) to the optimal spectral magnitude. The two approaches are then connected analytically, showing the former is a limiting case of the latter. Simulation examples that illustrate the theory are accompanied by discussions that address practical applicability and how one might satisfy the need for target and environmental models in the real-world.

Acquisition of decision making criteria: reward rate ultimately beats accuracy.

PubMed

Balci, Fuat; Simen, Patrick; Niyogi, Ritwik; Saxe, Andrew; Hughes, Jessica A; Holmes, Philip; Cohen, Jonathan D

2011-02-01

Speed-accuracy trade-offs strongly influence the rate of reward that can be earned in many decision-making tasks. Previous reports suggest that human participants often adopt suboptimal speed-accuracy trade-offs in single session, two-alternative forced-choice tasks. We investigated whether humans acquired optimal speed-accuracy trade-offs when extensively trained with multiple signal qualities. When performance was characterized in terms of decision time and accuracy, our participants eventually performed nearly optimally in the case of higher signal qualities. Rather than adopting decision criteria that were individually optimal for each signal quality, participants adopted a single threshold that was nearly optimal for most signal qualities. However, setting a single threshold for different coherence conditions resulted in only negligible decrements in the maximum possible reward rate. Finally, we tested two hypotheses regarding the possible sources of suboptimal performance: (1) favoring accuracy over reward rate and (2) misestimating the reward rate due to timing uncertainty. Our findings provide support for both hypotheses, but also for the hypothesis that participants can learn to approach optimality. We find specifically that an accuracy bias dominates early performance, but diminishes greatly with practice. The residual discrepancy between optimal and observed performance can be explained by an adaptive response to uncertainty in time estimation.

Fuel efficient traffic signal operation and evaluation: Garden Grove Demonstration Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1983-02-01

The procedures and results of a case study of fuel efficient traffic signal operation and evaluation in the City of Garden Grove, California are documented. Improved traffic signal timing was developed for a 70-intersection test network in Garden Grove using an optimization tool called the TRANSYT Version 8 computer program. Full-scale field testing of five alternative timing plans was conducted using two instrumented vehicles equipped to measure traffic performance characteristics and fuel consumption. The field tests indicated that significant improvements in traffic flow and fuel consumption result from the use of timing plans generated by the TRANSYT optimization model. Changingmore » from pre-existing to an optimized timing plan yields a networkwide 5 percent reduction in total travel time, more than 10 percent reduction in both the number of stops and stopped delay time, and 6 percent reduction in fuel consumption. Projections are made of the benefits and costs of implementing such a program at the 20,000 traffic signals in networks throughout the State of California.« less

Direct position determination for digital modulation signals based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Yu, Wan-Ting; Yu, Hong-yi; Du, Jian-Ping; Wang, Ding

2018-04-01

The Direct Position Determination (DPD) algorithm has been demonstrated to achieve a better accuracy with known signal waveforms. However, the signal waveform is difficult to be completely known in the actual positioning process. To solve the problem, we proposed a DPD method for digital modulation signals based on improved particle swarm optimization algorithm. First, a DPD model is established for known modulation signals and a cost function is obtained on symbol estimation. Second, as the optimization of the cost function is a nonlinear integer optimization problem, an improved Particle Swarm Optimization (PSO) algorithm is considered for the optimal symbol search. Simulations are carried out to show the higher position accuracy of the proposed DPD method and the convergence of the fitness function under different inertia weight and population size. On the one hand, the proposed algorithm can take full advantage of the signal feature to improve the positioning accuracy. On the other hand, the improved PSO algorithm can improve the efficiency of symbol search by nearly one hundred times to achieve a global optimal solution.

Adaptive traffic signal control system (ACS-Lite) for Wolf Road, Albany, New York.

DOT National Transportation Integrated Search

2014-10-01

Adaptive Control Software Lite (ACS : - : Lite) is a : traffic : signal timing optimization system that : dynamically adjusts : traffic : signal timing : s : to meet current traffic demands. : The purpose of this : research project : was : to : deplo...

Development of gradient descent adaptive algorithms to remove common mode artifact for improvement of cardiovascular signal quality.

PubMed

Ciaccio, Edward J; Micheli-Tzanakou, Evangelia

2007-07-01

Common-mode noise degrades cardiovascular signal quality and diminishes measurement accuracy. Filtering to remove noise components in the frequency domain often distorts the signal. Two adaptive noise canceling (ANC) algorithms were tested to adjust weighted reference signals for optimal subtraction from a primary signal. Update of weight w was based upon the gradient term of the steepest descent equation: [see text], where the error epsilon is the difference between primary and weighted reference signals. nabla was estimated from Deltaepsilon(2) and Deltaw without using a variable Deltaw in the denominator which can cause instability. The Parallel Comparison (PC) algorithm computed Deltaepsilon(2) using fixed finite differences +/- Deltaw in parallel during each discrete time k. The ALOPEX algorithm computed Deltaepsilon(2)x Deltaw from time k to k + 1 to estimate nabla, with a random number added to account for Deltaepsilon(2) . Deltaw--> 0 near the optimal weighting. Using simulated data, both algorithms stably converged to the optimal weighting within 50-2000 discrete sample points k even with a SNR = 1:8 and weights which were initialized far from the optimal. Using a sharply pulsatile cardiac electrogram signal with added noise so that the SNR = 1:5, both algorithms exhibited stable convergence within 100 ms (100 sample points). Fourier spectral analysis revealed minimal distortion when comparing the signal without added noise to the ANC restored signal. ANC algorithms based upon difference calculations can rapidly and stably converge to the optimal weighting in simulated and real cardiovascular data. Signal quality is restored with minimal distortion, increasing the accuracy of biophysical measurement.

The fully actuated traffic control problem solved by global optimization and complementarity

NASA Astrophysics Data System (ADS)

Ribeiro, Isabel M.; de Lurdes de Oliveira Simões, Maria

2016-02-01

Global optimization and complementarity are used to determine the signal timing for fully actuated traffic control, regarding effective green and red times on each cycle. The average values of these parameters can be used to estimate the control delay of vehicles. In this article, a two-phase queuing system for a signalized intersection is outlined, based on the principle of minimization of the total waiting time for the vehicles. The underlying model results in a linear program with linear complementarity constraints, solved by a sequential complementarity algorithm. Departure rates of vehicles during green and yellow periods were treated as deterministic, while arrival rates of vehicles were assumed to follow a Poisson distribution. Several traffic scenarios were created and solved. The numerical results reveal that it is possible to use global optimization and complementarity over a reasonable number of cycles and determine with efficiency effective green and red times for a signalized intersection.

System for monitoring an industrial or biological process

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.; Vilim, Rick B.; White, Andrew M.

1998-01-01

A method and apparatus for monitoring and responding to conditions of an industrial process. Industrial process signals, such as repetitive manufacturing, testing and operational machine signals, are generated by a system. Sensor signals characteristic of the process are generated over a time length and compared to reference signals over the time length. The industrial signals are adjusted over the time length relative to the reference signals, the phase shift of the industrial signals is optimized to the reference signals and the resulting signals output for analysis by systems such as SPRT.

System for monitoring an industrial or biological process

DOEpatents

Gross, K.C.; Wegerich, S.W.; Vilim, R.B.; White, A.M.

1998-06-30

A method and apparatus are disclosed for monitoring and responding to conditions of an industrial process. Industrial process signals, such as repetitive manufacturing, testing and operational machine signals, are generated by a system. Sensor signals characteristic of the process are generated over a time length and compared to reference signals over the time length. The industrial signals are adjusted over the time length relative to the reference signals, the phase shift of the industrial signals is optimized to the reference signals and the resulting signals output for analysis by systems such as SPRT. 49 figs.

Extended Salecker-Wigner formula for optimal accuracy in reading a clock via a massive signal particle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kudaka, Shoju; Matsumoto, Shuichi

2007-07-15

In order to acquire an extended Salecker-Wigner formula from which to derive the optimal accuracy in reading a clock with a massive particle as the signal, von Neumann's classical measurement is employed, by which simultaneously both position and momentum of the signal particle can be measured approximately. By an appropriate selection of wave function for the initial state of the composite system (a clock and a signal particle), the formula is derived accurately. Valid ranges of the running time of a clock with a given optimal accuracy are also given. The extended formula means that contrary to the Salecker-Wigner formulamore » there exists the possibility of a higher accuracy of time measurement, even if the mass of the clock is very small.« less

Optimization of parameter values for complex pulse sequences by simulated annealing: application to 3D MP-RAGE imaging of the brain.

PubMed

Epstein, F H; Mugler, J P; Brookeman, J R

1994-02-01

A number of pulse sequence techniques, including magnetization-prepared gradient echo (MP-GRE), segmented GRE, and hybrid RARE, employ a relatively large number of variable pulse sequence parameters and acquire the image data during a transient signal evolution. These sequences have recently been proposed and/or used for clinical applications in the brain, spine, liver, and coronary arteries. Thus, the need for a method of deriving optimal pulse sequence parameter values for this class of sequences now exists. Due to the complexity of these sequences, conventional optimization approaches, such as applying differential calculus to signal difference equations, are inadequate. We have developed a general framework for adapting the simulated annealing algorithm to pulse sequence parameter value optimization, and applied this framework to the specific case of optimizing the white matter-gray matter signal difference for a T1-weighted variable flip angle 3D MP-RAGE sequence. Using our algorithm, the values of 35 sequence parameters, including the magnetization-preparation RF pulse flip angle and delay time, 32 flip angles in the variable flip angle gradient-echo acquisition sequence, and the magnetization recovery time, were derived. Optimized 3D MP-RAGE achieved up to a 130% increase in white matter-gray matter signal difference compared with optimized 3D RF-spoiled FLASH with the same total acquisition time. The simulated annealing approach was effective at deriving optimal parameter values for a specific 3D MP-RAGE imaging objective, and may be useful for other imaging objectives and sequences in this general class.

Symmetry breaking in optimal timing of traffic signals on an idealized two-way street.

PubMed

Panaggio, Mark J; Ottino-Löffler, Bertand J; Hu, Peiguang; Abrams, Daniel M

2013-09-01

Simple physical models based on fluid mechanics have long been used to understand the flow of vehicular traffic on freeways; analytically tractable models of flow on an urban grid, however, have not been as extensively explored. In an ideal world, traffic signals would be timed such that consecutive lights turned green just as vehicles arrived, eliminating the need to stop at each block. Unfortunately, this "green-wave" scenario is generally unworkable due to frustration imposed by competing demands of traffic moving in different directions. Until now this has typically been resolved by numerical simulation and optimization. Here, we develop a theory for the flow in an idealized system consisting of a long two-way road with periodic intersections. We show that optimal signal timing can be understood analytically and that there are counterintuitive asymmetric solutions to this signal coordination problem. We further explore how these theoretical solutions degrade as traffic conditions vary and automotive density increases.

Symmetry breaking in optimal timing of traffic signals on an idealized two-way street

NASA Astrophysics Data System (ADS)

Panaggio, Mark J.; Ottino-Löffler, Bertand J.; Hu, Peiguang; Abrams, Daniel M.

2013-09-01

Simple physical models based on fluid mechanics have long been used to understand the flow of vehicular traffic on freeways; analytically tractable models of flow on an urban grid, however, have not been as extensively explored. In an ideal world, traffic signals would be timed such that consecutive lights turned green just as vehicles arrived, eliminating the need to stop at each block. Unfortunately, this “green-wave” scenario is generally unworkable due to frustration imposed by competing demands of traffic moving in different directions. Until now this has typically been resolved by numerical simulation and optimization. Here, we develop a theory for the flow in an idealized system consisting of a long two-way road with periodic intersections. We show that optimal signal timing can be understood analytically and that there are counterintuitive asymmetric solutions to this signal coordination problem. We further explore how these theoretical solutions degrade as traffic conditions vary and automotive density increases.

Signal optimization and analysis using PASSER V-07 : training workshop: code IPR006.

DOT National Transportation Integrated Search

2011-01-01

The objective of this project was to conduct one pilot workshop and five regular workshops to teach the effective use of the enhanced PASSER V-07 arterial signal timing optimization software. PASSER V-07 and materials for conducting a one-day trainin...

Complexity in congestive heart failure: A time-frequency approach

NASA Astrophysics Data System (ADS)

Banerjee, Santo; Palit, Sanjay K.; Mukherjee, Sayan; Ariffin, MRK; Rondoni, Lamberto

2016-03-01

Reconstruction of phase space is an effective method to quantify the dynamics of a signal or a time series. Various phase space reconstruction techniques have been investigated. However, there are some issues on the optimal reconstructions and the best possible choice of the reconstruction parameters. This research introduces the idea of gradient cross recurrence (GCR) and mean gradient cross recurrence density which shows that reconstructions in time frequency domain preserve more information about the dynamics than the optimal reconstructions in time domain. This analysis is further extended to ECG signals of normal and congestive heart failure patients. By using another newly introduced measure—gradient cross recurrence period density entropy, two classes of aforesaid ECG signals can be classified with a proper threshold. This analysis can be applied to quantifying and distinguishing biomedical and other nonlinear signals.

Whole brain inhomogeneous magnetization transfer (ihMT) imaging: Sensitivity enhancement within a steady-state gradient echo sequence.

PubMed

Mchinda, Samira; Varma, Gopal; Prevost, Valentin H; Le Troter, Arnaud; Rapacchi, Stanislas; Guye, Maxime; Pelletier, Jean; Ranjeva, Jean-Philippe; Alsop, David C; Duhamel, Guillaume; Girard, Olivier M

2018-05-01

To implement, characterize, and optimize an interleaved inhomogeneous magnetization transfer (ihMT) gradient echo sequence allowing for whole-brain imaging within a clinically compatible scan time. A general framework for ihMT modelling was developed based on the Provotorov theory of radiofrequency saturation, which accounts for the dipolar order underpinning the ihMT effect. Experimental studies and numerical simulations were performed to characterize and optimize the ihMT-gradient echo dependency with sequence timings, saturation power, and offset frequency. The protocol was optimized in terms of maximum signal intensity and the reproducibility assessed for a nominal resolution of 1.5 mm isotropic. All experiments were performed on healthy volunteers at 1.5T. An important mechanism driving signal optimization and leading to strong ihMT signal enhancement that relies on the dynamics of radiofrequency energy deposition has been identified. By taking advantage of the delay allowed for readout between ihMT pulse bursts, it was possible to boost the ihMT signal by almost 2-fold compared to previous implementation. Reproducibility of the optimal protocol was very good, with an intra-individual error < 2%. The proposed sensitivity-boosted and time-efficient steady-state ihMT-gradient echo sequence, implemented and optimized at 1.5T, allowed robust high-resolution 3D ihMT imaging of the whole brain within a clinically compatible scan time. Magn Reson Med 79:2607-2619, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

A computerized traffic control algorithm to determine optimal traffic signal settings. Ph.D. Thesis - Toledo Univ.

NASA Technical Reports Server (NTRS)

Seldner, K.

1977-01-01

An algorithm was developed to optimally control the traffic signals at each intersection using a discrete time traffic model applicable to heavy or peak traffic. Off line optimization procedures were applied to compute the cycle splits required to minimize the lengths of the vehicle queues and delay at each intersection. The method was applied to an extensive traffic network in Toledo, Ohio. Results obtained with the derived optimal settings are compared with the control settings presently in use.

Artifacts in digital coincidence timing

DOE PAGES

Moses, W. W.; Peng, Q.

2014-10-16

Digital methods are becoming increasingly popular for measuring time differences, and are the de facto standard in PET cameras. These methods usually include a master system clock and a (digital) arrival time estimate for each detector that is obtained by comparing the detector output signal to some reference portion of this clock (such as the rising edge). Time differences between detector signals are then obtained by subtracting the digitized estimates from a detector pair. A number of different methods can be used to generate the digitized arrival time of the detector output, such as sending a discriminator output into amore » time to digital converter (TDC) or digitizing the waveform and applying a more sophisticated algorithm to extract a timing estimator.All measurement methods are subject to error, and one generally wants to minimize these errors and so optimize the timing resolution. A common method for optimizing timing methods is to measure the coincidence timing resolution between two timing signals whose time difference should be constant (such as detecting gammas from positron annihilation) and selecting the method that minimizes the width of the distribution (i.e. the timing resolution). Unfortunately, a common form of error (a nonlinear transfer function) leads to artifacts that artificially narrow this resolution, which can lead to erroneous selection of the 'optimal' method. In conclusion, the purpose of this note is to demonstrate the origin of this artifact and suggest that caution should be used when optimizing time digitization systems solely on timing resolution minimization.« less

Artifacts in digital coincidence timing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moses, W. W.; Peng, Q.

Digital methods are becoming increasingly popular for measuring time differences, and are the de facto standard in PET cameras. These methods usually include a master system clock and a (digital) arrival time estimate for each detector that is obtained by comparing the detector output signal to some reference portion of this clock (such as the rising edge). Time differences between detector signals are then obtained by subtracting the digitized estimates from a detector pair. A number of different methods can be used to generate the digitized arrival time of the detector output, such as sending a discriminator output into amore » time to digital converter (TDC) or digitizing the waveform and applying a more sophisticated algorithm to extract a timing estimator.All measurement methods are subject to error, and one generally wants to minimize these errors and so optimize the timing resolution. A common method for optimizing timing methods is to measure the coincidence timing resolution between two timing signals whose time difference should be constant (such as detecting gammas from positron annihilation) and selecting the method that minimizes the width of the distribution (i.e. the timing resolution). Unfortunately, a common form of error (a nonlinear transfer function) leads to artifacts that artificially narrow this resolution, which can lead to erroneous selection of the 'optimal' method. In conclusion, the purpose of this note is to demonstrate the origin of this artifact and suggest that caution should be used when optimizing time digitization systems solely on timing resolution minimization.« less

Optimal preview control for a linear continuous-time stochastic control system in finite-time horizon

NASA Astrophysics Data System (ADS)

Wu, Jiang; Liao, Fucheng; Tomizuka, Masayoshi

2017-01-01

This paper discusses the design of the optimal preview controller for a linear continuous-time stochastic control system in finite-time horizon, using the method of augmented error system. First, an assistant system is introduced for state shifting. Then, in order to overcome the difficulty of the state equation of the stochastic control system being unable to be differentiated because of Brownian motion, the integrator is introduced. Thus, the augmented error system which contains the integrator vector, control input, reference signal, error vector and state of the system is reconstructed. This leads to the tracking problem of the optimal preview control of the linear stochastic control system being transformed into the optimal output tracking problem of the augmented error system. With the method of dynamic programming in the theory of stochastic control, the optimal controller with previewable signals of the augmented error system being equal to the controller of the original system is obtained. Finally, numerical simulations show the effectiveness of the controller.

Integrating machine learning to achieve an automatic parameter prediction for practical continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Liu, Weiqi; Huang, Peng; Peng, Jinye; Fan, Jianping; Zeng, Guihua

2018-02-01

For supporting practical quantum key distribution (QKD), it is critical to stabilize the physical parameters of signals, e.g., the intensity, phase, and polarization of the laser signals, so that such QKD systems can achieve better performance and practical security. In this paper, an approach is developed by integrating a support vector regression (SVR) model to optimize the performance and practical security of the QKD system. First, a SVR model is learned to precisely predict the time-along evolutions of the physical parameters of signals. Second, such predicted time-along evolutions are employed as feedback to control the QKD system for achieving the optimal performance and practical security. Finally, our proposed approach is exemplified by using the intensity evolution of laser light and a local oscillator pulse in the Gaussian modulated coherent state QKD system. Our experimental results have demonstrated three significant benefits of our SVR-based approach: (1) it can allow the QKD system to achieve optimal performance and practical security, (2) it does not require any additional resources and any real-time monitoring module to support automatic prediction of the time-along evolutions of the physical parameters of signals, and (3) it is applicable to any measurable physical parameter of signals in the practical QKD system.

Non-stationary component extraction in noisy multicomponent signal using polynomial chirping Fourier transform.

PubMed

Lu, Wenlong; Xie, Junwei; Wang, Heming; Sheng, Chuan

2016-01-01

Inspired by track-before-detection technology in radar, a novel time-frequency transform, namely polynomial chirping Fourier transform (PCFT), is exploited to extract components from noisy multicomponent signal. The PCFT combines advantages of Fourier transform and polynomial chirplet transform to accumulate component energy along a polynomial chirping curve in the time-frequency plane. The particle swarm optimization algorithm is employed to search optimal polynomial parameters with which the PCFT will achieve a most concentrated energy ridge in the time-frequency plane for the target component. The component can be well separated in the polynomial chirping Fourier domain with a narrow-band filter and then reconstructed by inverse PCFT. Furthermore, an iterative procedure, involving parameter estimation, PCFT, filtering and recovery, is introduced to extract components from a noisy multicomponent signal successively. The Simulations and experiments show that the proposed method has better performance in component extraction from noisy multicomponent signal as well as provides more time-frequency details about the analyzed signal than conventional methods.

Optimal Control-Based Adaptive NN Design for a Class of Nonlinear Discrete-Time Block-Triangular Systems.

PubMed

Liu, Yan-Jun; Tong, Shaocheng

2016-11-01

In this paper, we propose an optimal control scheme-based adaptive neural network design for a class of unknown nonlinear discrete-time systems. The controlled systems are in a block-triangular multi-input-multi-output pure-feedback structure, i.e., there are both state and input couplings and nonaffine functions to be included in every equation of each subsystem. The design objective is to provide a control scheme, which not only guarantees the stability of the systems, but also achieves optimal control performance. The main contribution of this paper is that it is for the first time to achieve the optimal performance for such a class of systems. Owing to the interactions among subsystems, making an optimal control signal is a difficult task. The design ideas are that: 1) the systems are transformed into an output predictor form; 2) for the output predictor, the ideal control signal and the strategic utility function can be approximated by using an action network and a critic network, respectively; and 3) an optimal control signal is constructed with the weight update rules to be designed based on a gradient descent method. The stability of the systems can be proved based on the difference Lyapunov method. Finally, a numerical simulation is given to illustrate the performance of the proposed scheme.

Energy Harvesting Based Body Area Networks for Smart Health.

PubMed

Hao, Yixue; Peng, Limei; Lu, Huimin; Hassan, Mohammad Mehedi; Alamri, Atif

2017-07-10

Body area networks (BANs) are configured with a great number of ultra-low power consumption wearable devices, which constantly monitor physiological signals of the human body and thus realize intelligent monitoring. However, the collection and transfer of human body signals consume energy, and considering the comfort demand of wearable devices, both the size and the capacity of a wearable device's battery are limited. Thus, minimizing the energy consumption of wearable devices and optimizing the BAN energy efficiency is still a challenging problem. Therefore, in this paper, we propose an energy harvesting-based BAN for smart health and discuss an optimal resource allocation scheme to improve BAN energy efficiency. Specifically, firstly, considering energy harvesting in a BAN and the time limits of human body signal transfer, we formulate the energy efficiency optimization problem of time division for wireless energy transfer and wireless information transfer. Secondly, we convert the optimization problem into a convex optimization problem under a linear constraint and propose a closed-form solution to the problem. Finally, simulation results proved that when the size of data acquired by the wearable devices is small, the proportion of energy consumed by the circuit and signal acquisition of the wearable devices is big, and when the size of data acquired by the wearable devices is big, the energy consumed by the signal transfer of the wearable device is decisive.

Energy Harvesting Based Body Area Networks for Smart Health

PubMed Central

Hao, Yixue; Peng, Limei; Alamri, Atif

2017-01-01

Body area networks (BANs) are configured with a great number of ultra-low power consumption wearable devices, which constantly monitor physiological signals of the human body and thus realize intelligent monitoring. However, the collection and transfer of human body signals consume energy, and considering the comfort demand of wearable devices, both the size and the capacity of a wearable device’s battery are limited. Thus, minimizing the energy consumption of wearable devices and optimizing the BAN energy efficiency is still a challenging problem. Therefore, in this paper, we propose an energy harvesting-based BAN for smart health and discuss an optimal resource allocation scheme to improve BAN energy efficiency. Specifically, firstly, considering energy harvesting in a BAN and the time limits of human body signal transfer, we formulate the energy efficiency optimization problem of time division for wireless energy transfer and wireless information transfer. Secondly, we convert the optimization problem into a convex optimization problem under a linear constraint and propose a closed-form solution to the problem. Finally, simulation results proved that when the size of data acquired by the wearable devices is small, the proportion of energy consumed by the circuit and signal acquisition of the wearable devices is big, and when the size of data acquired by the wearable devices is big, the energy consumed by the signal transfer of the wearable device is decisive. PMID:28698501

Automated Design Tools for Integrated Mixed-Signal Microsystems (NeoCAD)

DTIC Science & Technology

2005-02-01

method, Model Order Reduction (MOR) tools, system-level, mixed-signal circuit synthesis and optimization tools, and parsitic extraction tools. A unique...Mission Area: Command and Control mixed signal circuit simulation parasitic extraction time-domain simulation IC design flow model order reduction... Extraction 1.2 Overall Program Milestones CHAPTER 2 FAST TIME DOMAIN MIXED-SIGNAL CIRCUIT SIMULATION 2.1 HAARSPICE Algorithms 2.1.1 Mathematical Background

Constant-Envelope Waveform Design for Optimal Target-Detection and Autocorrelation Performances

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sen, Satyabrata

2013-01-01

We propose an algorithm to directly synthesize in time-domain a constant-envelope transmit waveform that achieves the optimal performance in detecting an extended target in the presence of signal-dependent interference. This approach is in contrast to the traditional indirect methods that synthesize the transmit signal following the computation of the optimal energy spectral density. Additionally, we aim to maintain a good autocorrelation property of the designed signal. Therefore, our waveform design technique solves a bi-objective optimization problem in order to simultaneously improve the detection and autocorrelation performances, which are in general conflicting in nature. We demonstrate this compromising characteristics of themore » detection and autocorrelation performances with numerical examples. Furthermore, in the absence of the autocorrelation criterion, our designed signal is shown to achieve a near-optimum detection performance.« less

Optimal Window and Lattice in Gabor Transform. Application to Audio Analysis.

PubMed

Lachambre, Helene; Ricaud, Benjamin; Stempfel, Guillaume; Torrésani, Bruno; Wiesmeyr, Christoph; Onchis-Moaca, Darian

2015-01-01

This article deals with the use of optimal lattice and optimal window in Discrete Gabor Transform computation. In the case of a generalized Gaussian window, extending earlier contributions, we introduce an additional local window adaptation technique for non-stationary signals. We illustrate our approach and the earlier one by addressing three time-frequency analysis problems to show the improvements achieved by the use of optimal lattice and window: close frequencies distinction, frequency estimation and SNR estimation. The results are presented, when possible, with real world audio signals.

True logarithmic amplification of frequency clock in SS-OCT for calibration

PubMed Central

Liu, Bin; Azimi, Ehsan; Brezinski, Mark E.

2011-01-01

With swept source optical coherence tomography (SS-OCT), imprecise signal calibration prevents optimal imaging of biological tissues such as coronary artery. This work demonstrates an approach using a true logarithmic amplifier to precondition the clock signal, with the effort to minimize the noises and phase errors for optimal calibration. This method was validated and tested with a high-speed SS-OCT. The experimental results manifest its superior ability on optimization of the calibration and improvement of the imaging performance. Particularly, this hardware-based approach is suitable for real-time calibration in a high-speed system where computation time is constrained. PMID:21698036

Robust sub-shot-noise measurement via Rabi-Josephson oscillations in bimodal Bose-Einstein condensates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tikhonenkov, I.; Vardi, A.; Moore, M. G.

2011-06-15

Mach-Zehnder atom interferometry requires hold-time phase squeezing to attain readout accuracy below the standard quantum limit. This increases its sensitivity to phase diffusion, restoring shot-noise scaling of the optimal signal-to-noise ratio in the presence of interactions. The contradiction between the preparations required for readout accuracy and robustness to interactions is removed by monitoring Rabi-Josephson oscillations instead of relative-phase oscillations during signal acquisition. Optimizing the signal-to-noise ratio with a Gaussian squeezed input, we find that hold-time number squeezing satisfies both demands and that sub-shot-noise scaling is retained even for strong interactions.

Non Linear Programming (NLP) Formulation for Quantitative Modeling of Protein Signal Transduction Pathways

PubMed Central

Morris, Melody K.; Saez-Rodriguez, Julio; Lauffenburger, Douglas A.; Alexopoulos, Leonidas G.

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms. PMID:23226239

Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.

PubMed

Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Optimal causal filtering for 1 /fα-type noise in single-electrode EEG signals.

PubMed

Paris, Alan; Atia, George; Vosoughi, Azadeh; Berman, Stephen A

2016-08-01

Understanding the mode of generation and the statistical structure of neurological noise is one of the central problems of biomedical signal processing. We have developed a broad class of abstract biological noise sources we call hidden simplicial tissues. In the simplest cases, such tissue emits what we have named generalized van der Ziel-McWhorter (GVZM) noise which has a roughly 1/fα spectral roll-off. Our previous work focused on the statistical structure of GVZM frequency spectra. However, causality of processing operations (i.e., dependence only on the past) is an essential requirement for real-time applications to seizure detection and brain-computer interfacing. In this paper we outline the theoretical background for optimal causal time-domain filtering of deterministic signals embedded in GVZM noise. We present some of our early findings concerning the optimal filtering of EEG signals for the detection of steady-state visual evoked potential (SSVEP) responses and indicate the next steps in our ongoing research.

Sparse gammatone signal model optimized for English speech does not match the human auditory filters.

PubMed

Strahl, Stefan; Mertins, Alfred

2008-07-18

Evidence that neurosensory systems use sparse signal representations as well as improved performance of signal processing algorithms using sparse signal models raised interest in sparse signal coding in the last years. For natural audio signals like speech and environmental sounds, gammatone atoms have been derived as expansion functions that generate a nearly optimal sparse signal model (Smith, E., Lewicki, M., 2006. Efficient auditory coding. Nature 439, 978-982). Furthermore, gammatone functions are established models for the human auditory filters. Thus far, a practical application of a sparse gammatone signal model has been prevented by the fact that deriving the sparsest representation is, in general, computationally intractable. In this paper, we applied an accelerated version of the matching pursuit algorithm for gammatone dictionaries allowing real-time and large data set applications. We show that a sparse signal model in general has advantages in audio coding and that a sparse gammatone signal model encodes speech more efficiently in terms of sparseness than a sparse modified discrete cosine transform (MDCT) signal model. We also show that the optimal gammatone parameters derived for English speech do not match the human auditory filters, suggesting for signal processing applications to derive the parameters individually for each applied signal class instead of using psychometrically derived parameters. For brain research, it means that care should be taken with directly transferring findings of optimality for technical to biological systems.

A TOTP-based enhanced route optimization procedure for mobile IPv6 to reduce handover delay and signalling overhead.

PubMed

Shah, Peer Azmat; Hasbullah, Halabi B; Lawal, Ibrahim A; Aminu Mu'azu, Abubakar; Tang Jung, Low

2014-01-01

Due to the proliferation of handheld mobile devices, multimedia applications like Voice over IP (VoIP), video conferencing, network music, and online gaming are gaining popularity in recent years. These applications are well known to be delay sensitive and resource demanding. The mobility of mobile devices, running these applications, across different networks causes delay and service disruption. Mobile IPv6 was proposed to provide mobility support to IPv6-based mobile nodes for continuous communication when they roam across different networks. However, the Route Optimization procedure in Mobile IPv6 involves the verification of mobile node's reachability at the home address and at the care-of address (home test and care-of test) that results in higher handover delays and signalling overhead. This paper presents an enhanced procedure, time-based one-time password Route Optimization (TOTP-RO), for Mobile IPv6 Route Optimization that uses the concepts of shared secret Token, time based one-time password (TOTP) along with verification of the mobile node via direct communication and maintaining the status of correspondent node's compatibility. The TOTP-RO was implemented in network simulator (NS-2) and an analytical analysis was also made. Analysis showed that TOTP-RO has lower handover delays, packet loss, and signalling overhead with an increased level of security as compared to the standard Mobile IPv6's Return-Routability-based Route Optimization (RR-RO).

Sub-Optimal Choice in Pigeons Does Not Depend on Avoidance of the Stimulus Associated with the Absence of Reinforcement

ERIC Educational Resources Information Center

Stagner, Jessica P.; Laude, Jennifer R.; Zentall, Thomas R.

2011-01-01

When pigeons are given a choice between two alternatives, one leading to a stimulus 20% of the time that always signals reinforcement (S+) or another stimulus 80% of the time that signals no reinforcement (S-), and the other alternative leading to one of two stimuli each signaling reinforcement 50% of the time, they show a strong preference for…

The apparent inversion time for optimal delayed enhancement magnetic resonance imaging differs between the right and left ventricles.

PubMed

Desai, Milind Y; Gupta, Sandeep; Bomma, Chandra; Tandri, Harikrishna; Foo, Thomas K; Lima, Joao A C; Bluemke, David A

2005-01-01

Delayed post-contrast magnetic resonance (MR) imaging involves suppression of signal from myocardium using inversion times (TI) between 150-225 ms, when the myocardium appears dark and fibrotic scar appears bright. We noticed that at a TI optimized for signal suppression of the left ventricle (LV), the right ventricle (RV) appeared brighter. The purpose of this study was to evaluate the TI for signal suppression in RV compared to LV, and to try and identify the cause of this observation. Methods. We studied 31 patients (ages ranged from 17-79 years, 11 females) who had an MR scan on a 1.5 T GE scanner. Delayed post-contrast short-axis images were obtained 20 minutes after injection of 0.2 mmol/kg of intravenous gadolinium chelate. TI optimization was performed by acquiring a range of TI times within a single breath hold, in increments of 25 msec. The TI time that resulted in lowest signal for the RV arid LV was recorded. With the imaging sequence employed, the TI leading to LV signal suppression ranged from 150-225 ms. At the TI that resulted in LV signal suppression, the corrected signal from the RV was significantly higher as compared to the LV (29 +/- 13 au vs. 15 +/- 8 au, p < 0.001). The findings were similar using only the body coil. The TI required to suppress the RV was usually < or =150 msec. The observation persisted before and after gadolinium infusion. The TI for myocardial signal suppression appears to be different between LV and RV. Potential mechanisms include partial volume averaging with fat or blood pool (related to increased trabeculation) in the RV. Alternatively, increased blood pool signal (within Thebesian veins or arterioluminal communications) in RV compared to LV leads to altered TI times due to similar partial volume effects.

Optimal Design of Calibration Signals in Space-Borne Gravitational Wave Detectors

NASA Technical Reports Server (NTRS)

Nofrarias, Miquel; Karnesis, Nikolaos; Gibert, Ferran; Armano, Michele; Audley, Heather; Danzmann, Karsten; Diepholz, Ingo; Dolesi, Rita; Ferraioli, Luigi; Ferroni, Valerio;

Optimal Design of Calibration Signals in Space Borne Gravitational Wave Detectors

NASA Technical Reports Server (NTRS)

Nofrarias, Miquel; Karnesis, Nikolaos; Gibert, Ferran; Armano, Michele; Audley, Heather; Danzmann, Karsten; Diepholz, Ingo; Dolesi, Rita; Ferraioli, Luigi; Thorpe, James I.

2014-01-01

Future space borne gravitational wave detectors will require a precise definition of calibration signals to ensure the achievement of their design sensitivity. The careful design of the test signals plays a key role in the correct understanding and characterization of these instruments. In that sense, methods achieving optimal experiment designs must be considered as complementary to the parameter estimation methods being used to determine the parameters describing the system. The relevance of experiment design is particularly significant for the LISA Pathfinder mission, which will spend most of its operation time performing experiments to characterize key technologies for future space borne gravitational wave observatories. Here we propose a framework to derive the optimal signals in terms of minimum parameter uncertainty to be injected to these instruments during its calibration phase. We compare our results with an alternative numerical algorithm which achieves an optimal input signal by iteratively improving an initial guess. We show agreement of both approaches when applied to the LISA Pathfinder case.

A Danger-Theory-Based Immune Network Optimization Algorithm

PubMed Central

Li, Tao; Xiao, Xin; Shi, Yuanquan

2013-01-01

Existing artificial immune optimization algorithms reflect a number of shortcomings, such as premature convergence and poor local search ability. This paper proposes a danger-theory-based immune network optimization algorithm, named dt-aiNet. The danger theory emphasizes that danger signals generated from changes of environments will guide different levels of immune responses, and the areas around danger signals are called danger zones. By defining the danger zone to calculate danger signals for each antibody, the algorithm adjusts antibodies' concentrations through its own danger signals and then triggers immune responses of self-regulation. So the population diversity can be maintained. Experimental results show that the algorithm has more advantages in the solution quality and diversity of the population. Compared with influential optimization algorithms, CLONALG, opt-aiNet, and dopt-aiNet, the algorithm has smaller error values and higher success rates and can find solutions to meet the accuracies within the specified function evaluation times. PMID:23483853

Optimization of offsets and cycle length using high resolution signal event data.

DOT National Transportation Integrated Search

2011-01-01

Traffic signal systems represent a substantial component of the highway transportation network in the United States. It is challenging for most agencies to find engineering resources to properly update signal policies and timing plans to accommodate ...

Optimal subhourly electricity resource dispatch under multiple price signals with high renewable generation availability

DOE PAGES

Chassin, David P.; Behboodi, Sahand; Djilali, Ned

2018-01-28

This article proposes a system-wide optimal resource dispatch strategy that enables a shift from a primarily energy cost-based approach, to a strategy using simultaneous price signals for energy, power and ramping behavior. A formal method to compute the optimal sub-hourly power trajectory is derived for a system when the price of energy and ramping are both significant. Optimal control functions are obtained in both time and frequency domains, and a discrete-time solution suitable for periodic feedback control systems is presented. The method is applied to North America Western Interconnection for the planning year 2024, and it is shown that anmore » optimal dispatch strategy that simultaneously considers both the cost of energy and the cost of ramping leads to significant cost savings in systems with high levels of renewable generation: the savings exceed 25% of the total system operating cost for a 50% renewables scenario.« less

Optimal subhourly electricity resource dispatch under multiple price signals with high renewable generation availability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chassin, David P.; Behboodi, Sahand; Djilali, Ned

This article proposes a system-wide optimal resource dispatch strategy that enables a shift from a primarily energy cost-based approach, to a strategy using simultaneous price signals for energy, power and ramping behavior. A formal method to compute the optimal sub-hourly power trajectory is derived for a system when the price of energy and ramping are both significant. Optimal control functions are obtained in both time and frequency domains, and a discrete-time solution suitable for periodic feedback control systems is presented. The method is applied to North America Western Interconnection for the planning year 2024, and it is shown that anmore » optimal dispatch strategy that simultaneously considers both the cost of energy and the cost of ramping leads to significant cost savings in systems with high levels of renewable generation: the savings exceed 25% of the total system operating cost for a 50% renewables scenario.« less

Optimal filter parameters for low SNR seismograms as a function of station and event location

NASA Astrophysics Data System (ADS)

Leach, Richard R.; Dowla, Farid U.; Schultz, Craig A.

1999-06-01

Global seismic monitoring requires deployment of seismic sensors worldwide, in many areas that have not been studied or have few useable recordings. Using events with lower signal-to-noise ratios (SNR) would increase the amount of data from these regions. Lower SNR events can add significant numbers to data sets, but recordings of these events must be carefully filtered. For a given region, conventional methods of filter selection can be quite subjective and may require intensive analysis of many events. To reduce this laborious process, we have developed an automated method to provide optimal filters for low SNR regional or teleseismic events. As seismic signals are often localized in frequency and time with distinct time-frequency characteristics, our method is based on the decomposition of a time series into a set of subsignals, each representing a band with f/Δ f constant (constant Q). The SNR is calculated on the pre-event noise and signal window. The band pass signals with high SNR are used to indicate the cutoff filter limits for the optimized filter. Results indicate a significant improvement in SNR, particularly for low SNR events. The method provides an optimum filter which can be immediately applied to unknown regions. The filtered signals are used to map the seismic frequency response of a region and may provide improvements in travel-time picking, azimuth estimation, regional characterization, and event detection. For example, when an event is detected and a preliminary location is determined, the computer could automatically select optimal filter bands for data from non-reporting stations. Results are shown for a set of low SNR events as well as 379 regional and teleseismic events recorded at stations ABKT, KIV, and ANTO in the Middle East.

On the pilot's behavior of detecting a system parameter change

NASA Technical Reports Server (NTRS)

Morizumi, N.; Kimura, H.

1986-01-01

The reaction of a human pilot, engaged in compensatory control, to a sudden change in the controlled element's characteristics is described. Taking the case where the change manifests itself as a variance change of the monitored signal, it is shown that the detection time, defined to be the time elapsed until the pilot detects the change, is related to the monitored signal and its derivative. Then, the detection behavior is modeled by an optimal controller, an optimal estimator, and a variance-ratio test mechanism that is performed for the monitored signal and its derivative. Results of a digital simulation show that the pilot's detection behavior can be well represented by the model proposed here.

Real-Time Neural Signals Decoding onto Off-the-Shelf DSP Processors for Neuroprosthetic Applications.

PubMed

Pani, Danilo; Barabino, Gianluca; Citi, Luca; Meloni, Paolo; Raspopovic, Stanisa; Micera, Silvestro; Raffo, Luigi

2016-09-01

The control of upper limb neuroprostheses through the peripheral nervous system (PNS) can allow restoring motor functions in amputees. At present, the important aspect of the real-time implementation of neural decoding algorithms on embedded systems has been often overlooked, notwithstanding the impact that limited hardware resources have on the efficiency/effectiveness of any given algorithm. Present study is addressing the optimization of a template matching based algorithm for PNS signals decoding that is a milestone for its real-time, full implementation onto a floating-point digital signal processor (DSP). The proposed optimized real-time algorithm achieves up to 96% of correct classification on real PNS signals acquired through LIFE electrodes on animals, and can correctly sort spikes of a synthetic cortical dataset with sufficiently uncorrelated spike morphologies (93% average correct classification) comparably to the results obtained with top spike sorter (94% on average on the same dataset). The power consumption enables more than 24 h processing at the maximum load, and latency model has been derived to enable a fair performance assessment. The final embodiment demonstrates the real-time performance onto a low-power off-the-shelf DSP, opening to experiments exploiting the efferent signals to control a motor neuroprosthesis.

SU-E-T-247: Determinations of the Optimal Phase for Respiratory Gated Radiotherapy From Statistical Analysis Using a Visible Guidance System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oh, S; Yea, J; Kang, M

Purpose: Respiratory gated radiation therapy (RGRT) is used to minimize the radiation dose to normal tissue in lung cancer patients. Determination of the optimal point in the respiratory phase of a patient is important in RGRT but it is not easy. The goal of the present study was to see if a visible guidance system is helpful in determining the optimal phase in respiratory gated therapy. Methods: The breathing signals of 23 lung cancer patients were recorded with a Real-time Position Management (RPM) respiratory gating system (Varian, USA). The patients underwent breathing training with our visible guidance system, after whichmore » their breathing signals were recorded during 5 min of free breathing and 5 min of guided breathing. The breathing signals recorded between 3 and 5 min before and after training were compared. We performed statistical analysis of the breathing signals to find the optimal duty cycle in guided breathing for RGRT. Results: The breathing signals aided by the visible guidance system had more regular cycles over time and smaller variations in the positions of the marker block than the free breathing signals. Of the 23 lung cancer patients, 19 showed statistically significant differences by time when the values obtained before and after breathing were compared (p < 0.05); 30% and 40% of the duty cycle, respectively, was determined to be the most effective, and the corresponding phases were 30 60% (duty cycle, 30%; p < 0.05) and 30 70% (duty cycle, 40%; p < 0.05). Conclusion: Respiratory regularity was significantly improved with the use of the RPM with our visible guiding system; therefore, it would help improve the accuracy and efficiency of RGRT.« less

A high-efficiency real-time digital signal averager for time-of-flight mass spectrometry.

PubMed

Wang, Yinan; Xu, Hui; Li, Qingjiang; Li, Nan; Huang, Zhengxu; Zhou, Zhen; Liu, Husheng; Sun, Zhaolin; Xu, Xin; Yu, Hongqi; Liu, Haijun; Li, David D-U; Wang, Xi; Dong, Xiuzhen; Gao, Wei

2013-05-30

Analog-to-digital converter (ADC)-based acquisition systems are widely applied in time-of-flight mass spectrometers (TOFMS) due to their ability to record the signal intensity of all ions within the same pulse. However, the acquisition system raises the requirement for data throughput, along with increasing the conversion rate and resolution of the ADC. It is therefore of considerable interest to develop a high-performance real-time acquisition system, which can relieve the limitation of data throughput. We present in this work a high-efficiency real-time digital signal averager, consisting of a signal conditioner, a data conversion module and a signal processing module. Two optimization strategies are implemented using field programmable gate arrays (FPGAs) to enhance the efficiency of the real-time processing. A pipeline procedure is used to reduce the time consumption of the accumulation strategy. To realize continuous data transfer, a high-efficiency transmission strategy is developed, based on a ping-pong procedure. The digital signal averager features good responsiveness, analog bandwidth and dynamic performance. The optimal effective number of bits reaches 6.7 bits. For a 32 µs record length, the averager can realize 100% efficiency with an extraction frequency below 31.23 kHz by modifying the number of accumulation steps. In unit time, the averager yields superior signal-to-noise ratio (SNR) compared with data accumulation in a computer. The digital signal averager is combined with a vacuum ultraviolet single-photon ionization time-of-flight mass spectrometer (VUV-SPI-TOFMS). The efficiency of the real-time processing is tested by analyzing the volatile organic compounds (VOCs) from ordinary printed materials. In these experiments, 22 kinds of compounds are detected, and the dynamic range exceeds 3 orders of magnitude. Copyright © 2013 John Wiley & Sons, Ltd.

Dynamic facial expressions of emotion transmit an evolving hierarchy of signals over time.

PubMed

Jack, Rachael E; Garrod, Oliver G B; Schyns, Philippe G

2014-01-20

Designed by biological and social evolutionary pressures, facial expressions of emotion comprise specific facial movements to support a near-optimal system of signaling and decoding. Although highly dynamical, little is known about the form and function of facial expression temporal dynamics. Do facial expressions transmit diagnostic signals simultaneously to optimize categorization of the six classic emotions, or sequentially to support a more complex communication system of successive categorizations over time? Our data support the latter. Using a combination of perceptual expectation modeling, information theory, and Bayesian classifiers, we show that dynamic facial expressions of emotion transmit an evolving hierarchy of "biologically basic to socially specific" information over time. Early in the signaling dynamics, facial expressions systematically transmit few, biologically rooted face signals supporting the categorization of fewer elementary categories (e.g., approach/avoidance). Later transmissions comprise more complex signals that support categorization of a larger number of socially specific categories (i.e., the six classic emotions). Here, we show that dynamic facial expressions of emotion provide a sophisticated signaling system, questioning the widely accepted notion that emotion communication is comprised of six basic (i.e., psychologically irreducible) categories, and instead suggesting four. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cooperative and Integrated Vehicle and Intersection Control for Energy Efficiency (CIVIC-E²)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hou, Yunfei; Seliman, Salaheldeen M. S.; Wang, Enshu

Recent advances in connected vehicle technologies enable vehicles and signal controllers to cooperate and improve the traffic management at intersections. This paper explores the opportunity for cooperative and integrated vehicle and intersection control for energy efficiency (CIVIC-E 2) to contribute to a more sustainable transportation system. We propose a two-level approach that jointly optimizes the traffic signal timing and vehicles' approach speed, with the objective being to minimize total energy consumption for all vehicles passing through an isolated intersection. More specifically, at the intersection level, a dynamic programming algorithm is designed to find the optimal signal timing by explicitly consideringmore » the arrival time and energy profile of each vehicle. At the vehicle level, a model predictive control strategy is adopted to ensure that vehicles pass through the intersection in a timely fashion. Our simulation study has shown that the proposed CIVIC-E 2 system can significantly improve intersection performance under various traffic conditions. Compared with conventional fixed-time and actuated signal control strategies, the proposed algorithm can reduce energy consumption and queue length by up to 31% and 95%, respectively.« less

Cooperative and Integrated Vehicle and Intersection Control for Energy Efficiency (CIVIC-E²)

DOE PAGES

Hou, Yunfei; Seliman, Salaheldeen M. S.; Wang, Enshu; ...

2018-02-15

Recent advances in connected vehicle technologies enable vehicles and signal controllers to cooperate and improve the traffic management at intersections. This paper explores the opportunity for cooperative and integrated vehicle and intersection control for energy efficiency (CIVIC-E 2) to contribute to a more sustainable transportation system. We propose a two-level approach that jointly optimizes the traffic signal timing and vehicles' approach speed, with the objective being to minimize total energy consumption for all vehicles passing through an isolated intersection. More specifically, at the intersection level, a dynamic programming algorithm is designed to find the optimal signal timing by explicitly consideringmore » the arrival time and energy profile of each vehicle. At the vehicle level, a model predictive control strategy is adopted to ensure that vehicles pass through the intersection in a timely fashion. Our simulation study has shown that the proposed CIVIC-E 2 system can significantly improve intersection performance under various traffic conditions. Compared with conventional fixed-time and actuated signal control strategies, the proposed algorithm can reduce energy consumption and queue length by up to 31% and 95%, respectively.« less

An adaptive corridor-wide signal timing optimization methodology for traffic network with multiple highway-rail grade crossings.

DOT National Transportation Integrated Search

2016-06-01

Highway-rail grade crossings (HRGCs) and the intersections in their proximity are areas where potential problems in terms of safety and efficiency often arise if only simple or outdated treatments, such as normal signal timing or passive railroad war...

A TOTP-Based Enhanced Route Optimization Procedure for Mobile IPv6 to Reduce Handover Delay and Signalling Overhead

PubMed Central

Shah, Peer Azmat; Hasbullah, Halabi B.; Lawal, Ibrahim A.; Aminu Mu'azu, Abubakar; Tang Jung, Low

2014-01-01

Due to the proliferation of handheld mobile devices, multimedia applications like Voice over IP (VoIP), video conferencing, network music, and online gaming are gaining popularity in recent years. These applications are well known to be delay sensitive and resource demanding. The mobility of mobile devices, running these applications, across different networks causes delay and service disruption. Mobile IPv6 was proposed to provide mobility support to IPv6-based mobile nodes for continuous communication when they roam across different networks. However, the Route Optimization procedure in Mobile IPv6 involves the verification of mobile node's reachability at the home address and at the care-of address (home test and care-of test) that results in higher handover delays and signalling overhead. This paper presents an enhanced procedure, time-based one-time password Route Optimization (TOTP-RO), for Mobile IPv6 Route Optimization that uses the concepts of shared secret Token, time based one-time password (TOTP) along with verification of the mobile node via direct communication and maintaining the status of correspondent node's compatibility. The TOTP-RO was implemented in network simulator (NS-2) and an analytical analysis was also made. Analysis showed that TOTP-RO has lower handover delays, packet loss, and signalling overhead with an increased level of security as compared to the standard Mobile IPv6's Return-Routability-based Route Optimization (RR-RO). PMID:24688398

LOAPEX: The Long-Range Ocean Acoustic Propagation EXperiment

DTIC Science & Technology

2009-01-01

roughly 4200 m, the OBS/H packages at 5000 m received the LOAPEX transmissions. 4) Signal Processing : In general, signal processing for all receptions is...coherently in the time domain. To optimize processing , is based on the coherence time of the received signal and the resulting pro- cessing gain is . The...replica of the transmission. This process produces a triangular-shaped pulse with a time resolution of 1-b length, or 27 ms, and additional processing

Improved particle swarm optimization algorithm for android medical care IOT using modified parameters.

PubMed

Sung, Wen-Tsai; Chiang, Yen-Chun

2012-12-01

This study examines wireless sensor network with real-time remote identification using the Android study of things (HCIOT) platform in community healthcare. An improved particle swarm optimization (PSO) method is proposed to efficiently enhance physiological multi-sensors data fusion measurement precision in the Internet of Things (IOT) system. Improved PSO (IPSO) includes: inertia weight factor design, shrinkage factor adjustment to allow improved PSO algorithm data fusion performance. The Android platform is employed to build multi-physiological signal processing and timely medical care of things analysis. Wireless sensor network signal transmission and Internet links allow community or family members to have timely medical care network services.

Artifacts in Digital Coincidence Timing

PubMed Central

Moses, W. W.; Peng, Q.

2014-01-01

Digital methods are becoming increasingly popular for measuring time differences, and are the de facto standard in PET cameras. These methods usually include a master system clock and a (digital) arrival time estimate for each detector that is obtained by comparing the detector output signal to some reference portion of this clock (such as the rising edge). Time differences between detector signals are then obtained by subtracting the digitized estimates from a detector pair. A number of different methods can be used to generate the digitized arrival time of the detector output, such as sending a discriminator output into a time to digital converter (TDC) or digitizing the waveform and applying a more sophisticated algorithm to extract a timing estimator. All measurement methods are subject to error, and one generally wants to minimize these errors and so optimize the timing resolution. A common method for optimizing timing methods is to measure the coincidence timing resolution between two timing signals whose time difference should be constant (such as detecting gammas from positron annihilation) and selecting the method that minimizes the width of the distribution (i.e., the timing resolution). Unfortunately, a common form of error (a nonlinear transfer function) leads to artifacts that artificially narrow this resolution, which can lead to erroneous selection of the “optimal” method. The purpose of this note is to demonstrate the origin of this artifact and suggest that caution should be used when optimizing time digitization systems solely on timing resolution minimization. PMID:25321885

Low b-value diffusion-weighted cardiac magnetic resonance imaging: initial results in humans using an optimal time-window imaging approach.

PubMed

Rapacchi, Stanislas; Wen, Han; Viallon, Magalie; Grenier, Denis; Kellman, Peter; Croisille, Pierre; Pai, Vinay M

2011-12-01

Diffusion-weighted imaging (DWI) using low b-values permits imaging of intravoxel incoherent motion in tissues. However, low b-value DWI of the human heart has been considered too challenging because of additional signal loss due to physiological motion, which reduces both signal intensity and the signal-to-noise ratio (SNR). We address these signal loss concerns by analyzing cardiac motion during a heartbeat to determine the time-window during which cardiac bulk motion is minimal. Using this information to optimize the acquisition of DWI data and combining it with a dedicated image processing approach has enabled us to develop a novel low b-value diffusion-weighted cardiac magnetic resonance imaging approach, which significantly reduces intravoxel incoherent motion measurement bias introduced by motion. Simulations from displacement encoded motion data sets permitted the delineation of an optimal time-window with minimal cardiac motion. A number of single-shot repetitions of low b-value DWI cardiac magnetic resonance imaging data were acquired during this time-window under free-breathing conditions with bulk physiological motion corrected for by using nonrigid registration. Principal component analysis (PCA) was performed on the registered images to improve the SNR, and temporal maximum intensity projection (TMIP) was applied to recover signal intensity from time-fluctuant motion-induced signal loss. This PCATMIP method was validated with experimental data, and its benefits were evaluated in volunteers before being applied to patients. Optimal time-window cardiac DWI in combination with PCATMIP postprocessing yielded significant benefits for signal recovery, contrast-to-noise ratio, and SNR in the presence of bulk motion for both numerical simulations and human volunteer studies. Analysis of mean apparent diffusion coefficient (ADC) maps showed homogeneous values among volunteers and good reproducibility between free-breathing and breath-hold acquisitions. The PCATMIP DWI approach also indicated its potential utility by detecting ADC variations in acute myocardial infarction patients. Studying cardiac motion may provide an appropriate strategy for minimizing the impact of bulk motion on cardiac DWI. Applying PCATMIP image processing improves low b-value DWI and enables reliable analysis of ADC in the myocardium. The use of a limited number of repetitions in a free-breathing mode also enables easier application in clinical conditions.

Three component vibrational time reversal communication

DOE PAGES

Anderson, Brian E.; Ulrich, Timothy J.; Ten Cate, James A.

2015-01-01

Time reversal provides an optimal prefilter matched signal to apply to a communication signal before signal transmission. Time reversal allows compensation for wave speed dispersion and can function well in reverberant environments. Time reversal can be used to focus elastic energy to each of the three components of motion independently. A pipe encased in concrete was used to demonstrate the ability to conduct communications of information using three component time reversal. Furthermore, the ability of time reversal to compensate for multi-path distortion (overcoming reverberation) will be demonstrated and the rate of signal communication will be presented. [The U.S. Department ofmore » Energy, through the LANL/LDRD Program, is gratefully acknowledged for supporting this work.]« less

Probe-pulse optimization for nonresonant suppression in hybrid fs/ps coherent anti-Stokes Raman scattering at high temperature.

PubMed

Miller, Joseph D; Slipchenko, Mikhail N; Meyer, Terrence R

2011-07-04

Hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering (fs/ps CARS) offers accurate thermometry at kHz rates for combustion diagnostics. In high-temperature flames, selection of probe-pulse characteristics is key to simultaneously optimizing signal-to-nonresonant-background ratio, signal strength, and spectral resolution. We demonstrate a simple method for enhancing signal-to-nonresonant-background ratio by using a narrowband Lorentzian filter to generate a time-asymmetric probe pulse with full-width-half-maximum (FWHM) pulse width of only 240 fs. This allows detection within just 310 fs after the Raman excitation for eliminating nonresonant background while retaining 45% of the resonant signal at 2000 K. The narrow linewidth is comparable to that of a time-symmetric sinc2 probe pulse with a pulse width of ~2.4 ps generated with a conventional 4-f pulse shaper. This allows nonresonant-background-free, frequency-domain vibrational spectroscopy at high temperature, as verified using comparisons to a time-dependent theoretical fs/ps CARS model.

Detecting recurrence domains of dynamical systems by symbolic dynamics.

PubMed

beim Graben, Peter; Hutt, Axel

2013-04-12

We propose an algorithm for the detection of recurrence domains of complex dynamical systems from time series. Our approach exploits the characteristic checkerboard texture of recurrence domains exhibited in recurrence plots. In phase space, recurrence plots yield intersecting balls around sampling points that could be merged into cells of a phase space partition. We construct this partition by a rewriting grammar applied to the symbolic dynamics of time indices. A maximum entropy principle defines the optimal size of intersecting balls. The final application to high-dimensional brain signals yields an optimal symbolic recurrence plot revealing functional components of the signal.

Impulse-induced optimum signal amplification in scale-free networks.

PubMed

Martínez, Pedro J; Chacón, Ricardo

2016-04-01

Optimizing information transmission across a network is an essential task for controlling and manipulating generic information-processing systems. Here, we show how topological amplification effects in scale-free networks of signaling devices are optimally enhanced when the impulse transmitted by periodic external signals (time integral over two consecutive zeros) is maximum. This is demonstrated theoretically by means of a star-like network of overdamped bistable systems subjected to generic zero-mean periodic signals and confirmed numerically by simulations of scale-free networks of such systems. Our results show that the enhancer effect of increasing values of the signal's impulse is due to a correlative increase of the energy transmitted by the periodic signals, while it is found to be resonant-like with respect to the topology-induced amplification mechanism.

Optimal pulse design for communication-oriented slow-light pulse detection.

PubMed

Stenner, Michael D; Neifeld, Mark A

2008-01-21

We present techniques for designing pulses for linear slow-light delay systems which are optimal in the sense that they maximize the signal-to-noise ratio (SNR) and signal-to-noise-plus-interference ratio (SNIR) of the detected pulse energy. Given a communication model in which input pulses are created in a finite temporal window and output pulse energy in measured in a temporally-offset output window, the SNIR-optimal pulses achieve typical improvements of 10 dB compared to traditional pulse shapes for a given output window offset. Alternatively, for fixed SNR or SNIR, window offset (detection delay) can be increased by 0.3 times the window width. This approach also invites a communication-based model for delay and signal fidelity.

How quantitative measures unravel design principles in multi-stage phosphorylation cascades.

PubMed

Frey, Simone; Millat, Thomas; Hohmann, Stefan; Wolkenhauer, Olaf

2008-09-07

We investigate design principles of linear multi-stage phosphorylation cascades by using quantitative measures for signaling time, signal duration and signal amplitude. We compare alternative pathway structures by varying the number of phosphorylations and the length of the cascade. We show that a model for a weakly activated pathway does not reflect the biological context well, unless it is restricted to certain parameter combinations. Focusing therefore on a more general model, we compare alternative structures with respect to a multivariate optimization criterion. We test the hypothesis that the structure of a linear multi-stage phosphorylation cascade is the result of an optimization process aiming for a fast response, defined by the minimum of the product of signaling time and signal duration. It is then shown that certain pathway structures minimize this criterion. Several popular models of MAPK cascades form the basis of our study. These models represent different levels of approximation, which we compare and discuss with respect to the quantitative measures.

Optimal control of the signal-to-noise ratio per unit time of a spin 1/2 particle: The crusher gradient and the radiation damping cases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lapert, M.; Glaser, S. J.; Assémat, E.

We show to which extent the signal to noise ratio per unit time of a spin 1/2 particle can be maximized. We consider a cyclic repetition of experiments made of a measurement followed by a radio-frequency magnetic field excitation of the system, in the case of unbounded amplitude. In the periodic regime, the objective of the control problem is to design the initial state of the system and the pulse sequence which leads to the best signal to noise performance. We focus on two specific issues relevant in nuclear magnetic resonance, the crusher gradient and the radiation damping cases. Optimalmore » control techniques are used to solve this non-standard control problem. We discuss the optimality of the Ernst angle solution, which is commonly applied in spectroscopic and medical imaging applications. In the radiation damping situation, we show that in some cases, the optimal solution differs from the Ernst one.« less

Adaptive photoacoustic imaging quality optimization with EMD and reconstruction

NASA Astrophysics Data System (ADS)

Guo, Chengwen; Ding, Yao; Yuan, Jie; Xu, Guan; Wang, Xueding; Carson, Paul L.

2016-10-01

Biomedical photoacoustic (PA) signal is characterized with extremely low signal to noise ratio which will yield significant artifacts in photoacoustic tomography (PAT) images. Since PA signals acquired by ultrasound transducers are non-linear and non-stationary, traditional data analysis methods such as Fourier and wavelet method cannot give useful information for further research. In this paper, we introduce an adaptive method to improve the quality of PA imaging based on empirical mode decomposition (EMD) and reconstruction. Data acquired by ultrasound transducers are adaptively decomposed into several intrinsic mode functions (IMFs) after a sifting pre-process. Since noise is randomly distributed in different IMFs, depressing IMFs with more noise while enhancing IMFs with less noise can effectively enhance the quality of reconstructed PAT images. However, searching optimal parameters by means of brute force searching algorithms will cost too much time, which prevent this method from practical use. To find parameters within reasonable time, heuristic algorithms, which are designed for finding good solutions more efficiently when traditional methods are too slow, are adopted in our method. Two of the heuristic algorithms, Simulated Annealing Algorithm, a probabilistic method to approximate the global optimal solution, and Artificial Bee Colony Algorithm, an optimization method inspired by the foraging behavior of bee swarm, are selected to search optimal parameters of IMFs in this paper. The effectiveness of our proposed method is proved both on simulated data and PA signals from real biomedical tissue, which might bear the potential for future clinical PA imaging de-noising.

Estimating the arrival times of photon-limited laser pulses in the presence of shot and speckle noise

NASA Technical Reports Server (NTRS)

Abshire, James B.; Mcgarry, Jan F.

1987-01-01

Maximum-likelihood (ML) receivers are frequently used to optimize the timing performance of laser-ranging and laser-altimetry systems in the presence of shot and speckle noise. Monte Carlo method was used to examine ML-receiver performance with return signals in the 10-5000-photoelectron (pe) range. The simulations were performed for shot noise only and for shot and speckle noise. The results agree with previous theory for signal strengths greater than about 100 pe's but show that the theory can significantly underestimate timing errors for weaker received signals. Sharp high-bandwidth features in the detected signals are shown to improve timing performance only if their signal levels are greater than 4-5 pe's.

A Sarsa(λ)-based control model for real-time traffic light coordination.

PubMed

Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

Signal intensity analysis and optimization for in vivo imaging of Cherenkov and excited luminescence

NASA Astrophysics Data System (ADS)

LaRochelle, Ethan P. M.; Shell, Jennifer R.; Gunn, Jason R.; Davis, Scott C.; Pogue, Brian W.

2018-04-01

During external beam radiotherapy (EBRT), in vivo Cherenkov optical emissions can be used as a dosimetry tool or to excite luminescence, termed Cherenkov-excited luminescence (CEL) with microsecond-level time-gated cameras. The goal of this work was to develop a complete theoretical foundation for the detectable signal strength, in order to provide guidance on optimization of the limits of detection and how to optimize near real time imaging. The key parameters affecting photon production, propagation and detection were considered and experimental validation with both tissue phantoms and a murine model are shown. Both the theoretical analysis and experimental data indicate that the detection level is near a single photon-per-pixel for the detection geometry and frame rates commonly used, with the strongest factor being the signal decrease with the square of distance from tissue to camera. Experimental data demonstrates how the SNR improves with increasing integration time, but only up to the point where the dominance of camera read noise is overcome by stray photon noise that cannot be suppressed. For the current camera in a fixed geometry, the signal to background ratio limits the detection of light signals, and the observed in vivo Cherenkov emission is on the order of 100×  stronger than CEL signals. As a result, imaging signals from depths  <15 mm is reasonable for Cherenkov light, and depths  <3 mm is reasonable for CEL imaging. The current investigation modeled Cherenkov and CEL imaging of two oxygen sensing phosphorescent compounds, but the modularity of the code allows for easy comparison of different agents or alternative cameras, geometries or tissues.

Signal intensity analysis and optimization for in vivo imaging of Cherenkov and excited luminescence.

PubMed

LaRochelle, Ethan P M; Shell, Jennifer R; Gunn, Jason R; Davis, Scott C; Pogue, Brian W

2018-04-20

During external beam radiotherapy (EBRT), in vivo Cherenkov optical emissions can be used as a dosimetry tool or to excite luminescence, termed Cherenkov-excited luminescence (CEL) with microsecond-level time-gated cameras. The goal of this work was to develop a complete theoretical foundation for the detectable signal strength, in order to provide guidance on optimization of the limits of detection and how to optimize near real time imaging. The key parameters affecting photon production, propagation and detection were considered and experimental validation with both tissue phantoms and a murine model are shown. Both the theoretical analysis and experimental data indicate that the detection level is near a single photon-per-pixel for the detection geometry and frame rates commonly used, with the strongest factor being the signal decrease with the square of distance from tissue to camera. Experimental data demonstrates how the SNR improves with increasing integration time, but only up to the point where the dominance of camera read noise is overcome by stray photon noise that cannot be suppressed. For the current camera in a fixed geometry, the signal to background ratio limits the detection of light signals, and the observed in vivo Cherenkov emission is on the order of 100×  stronger than CEL signals. As a result, imaging signals from depths  <15 mm is reasonable for Cherenkov light, and depths  <3 mm is reasonable for CEL imaging. The current investigation modeled Cherenkov and CEL imaging of two oxygen sensing phosphorescent compounds, but the modularity of the code allows for easy comparison of different agents or alternative cameras, geometries or tissues.

High time resolved electron temperature measurements by using the multi-pass Thomson scattering system in GAMMA 10/PDX.

PubMed

Yoshikawa, Masayuki; Yasuhara, Ryo; Ohta, Koichi; Chikatsu, Masayuki; Shima, Yoriko; Kohagura, Junko; Sakamoto, Mizuki; Nakashima, Yousuke; Imai, Tsuyoshi; Ichimura, Makoto; Yamada, Ichihiro; Funaba, Hisamichi; Minami, Takashi

2016-11-01

High time resolved electron temperature measurements are useful for fluctuation study. A multi-pass Thomson scattering (MPTS) system is proposed for the improvement of both increasing the TS signal intensity and time resolution. The MPTS system in GAMMA 10/PDX has been constructed for enhancing the Thomson scattered signals for the improvement of measurement accuracy. The MPTS system has a polarization-based configuration with an image relaying system. We optimized the image relaying optics for improving the multi-pass laser confinement and obtaining the stable MPTS signals over ten passing TS signals. The integrated MPTS signals increased about five times larger than that in the single pass system. Finally, time dependent electron temperatures were obtained in MHz sampling.

ECG Based Heart Arrhythmia Detection Using Wavelet Coherence and Bat Algorithm

NASA Astrophysics Data System (ADS)

Kora, Padmavathi; Sri Rama Krishna, K.

2016-12-01

Atrial fibrillation (AF) is a type of heart abnormality, during the AF electrical discharges in the atrium are rapid, results in abnormal heart beat. The morphology of ECG changes due to the abnormalities in the heart. This paper consists of three major steps for the detection of heart diseases: signal pre-processing, feature extraction and classification. Feature extraction is the key process in detecting the heart abnormality. Most of the ECG detection systems depend on the time domain features for cardiac signal classification. In this paper we proposed a wavelet coherence (WTC) technique for ECG signal analysis. The WTC calculates the similarity between two waveforms in frequency domain. Parameters extracted from WTC function is used as the features of the ECG signal. These features are optimized using Bat algorithm. The Levenberg Marquardt neural network classifier is used to classify the optimized features. The performance of the classifier can be improved with the optimized features.

Optimization of global model composed of radial basis functions using the term-ranking approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, Peng; Tao, Chao, E-mail: taochao@nju.edu.cn; Liu, Xiao-Jun

2014-03-15

A term-ranking method is put forward to optimize the global model composed of radial basis functions to improve the predictability of the model. The effectiveness of the proposed method is examined by numerical simulation and experimental data. Numerical simulations indicate that this method can significantly lengthen the prediction time and decrease the Bayesian information criterion of the model. The application to real voice signal shows that the optimized global model can capture more predictable component in chaos-like voice data and simultaneously reduce the predictable component (periodic pitch) in the residual signal.

Optimization design of urban expressway ramp control

NASA Astrophysics Data System (ADS)

Xu, Hongke; Li, Peiqi; Zheng, Jinnan; Sun, Xiuzhen; Lin, Shan

2017-05-01

In this paper, various types of expressway systems are analyzed, and a variety of signal combinations are proposed to mitigate traffic congestion. And various signal combinations are used to verify the effectiveness of the multi-signal combinatorial control strategy. The simulation software VISSIM was used to simulate the system. Based on the network model of 25 kinds of road length combinations and the simulation results, an optimization scheme suitable for the practical road model is summarized. The simulation results show that the controller can reduce the travel time by 25% under the large traffic flow and improve the road capacity by about 20%.

Attenuation of harmonic noise in vibroseis data using Simulated Annealing

NASA Astrophysics Data System (ADS)

Sharma, S. P.; Tildy, Peter; Iranpour, Kambiz; Scholtz, Peter

2009-04-01

Processing of high productivity vibroseis seismic data (such as slip-sweep acquisition records) suffers from the well known disadvantage of harmonic distortion. Harmonic distortions are observed after cross-correlation of the recorded seismic signal with the pilot sweep and affect the signals in negative time (before the actual strong reflection event). Weak reflection events of the earlier sweeps falling in the negative time window of the cross-correlation sequence are being masked by harmonic distortions. Though the amplitude of the harmonic distortion is small (up to 10-20 %) compared to the fundamental amplitude of the reflection events, but it is significant enough to mask weak reflected signals. Elimination of harmonic noise due to source signal distortion from the cross-correlated seismic trace is a challenging task since the application of vibratory sources started and it still needs improvement. An approach has been worked out that minimizes the level of harmonic distortion by designing the signal similar to the harmonic distortion. An arbitrary length filter is optimized using the Simulated Annealing global optimization approach to design a harmonic signal. The approach deals with the convolution of a ratio trace (ratio of the harmonics with respect to the fundamental sweep) with the correlated "positive time" recorded signal and an arbitrary filter. Synthetic data study has revealed that this procedure of designing a signal similar to the desired harmonics using convolution of a suitable filter with theoretical ratio of harmonics with fundamental sweep helps in reducing the problem of harmonic distortion. Once we generate a similar signal for a vibroseis source using an optimized filter, then, this filter could be used to generate harmonics, which can be subtracted from the main cross-correlated trace to get the better, undistorted image of the subsurface. Designing the predicted harmonics to reduce the energy in the trace by considering weak reflection and observed harmonics together yields the desired result (resolution of weak reflected signal from the harmonic distortion). As optimization steps proceeds forward it is possible to observe from the difference plots of desired and predicted harmonics how weak reflections evolved from the harmonic distortion gradually during later iterations of global optimization. The procedure is applied in resolving weak reflections from a number of traces considered together. For a more precise design of harmonics SA procedure needs longer computation time which is impractical to deal with voluminous seismic data. However, the objective of resolving weak reflection signal in the strong harmonic noise can be achieved with fast computation using faster cooling schedule and less number of iterations and number of moves in simulated annealing procedure. This process could help in reducing the harmonics distortion and achieving the objective of resolving the lost weak reflection events in the cross-correlated seismic traces. Acknowledgements: The research was supported under the European Marie Curie Host Fellowships for Transfer of Knowledge (TOK) Development Host Scheme (contract no. MTKD-CT-2006-042537).

Optimal space communications techniques. [discussion of video signals and delta modulation

NASA Technical Reports Server (NTRS)

Schilling, D. L.

1974-01-01

The encoding of video signals using the Song Adaptive Delta Modulator (Song ADM) is discussed. The video signals are characterized as a sequence of pulses having arbitrary height and width. Although the ADM is suited to tracking signals having fast rise times, it was found that the DM algorithm (which permits an exponential rise for estimating an input step) results in a large overshoot and an underdamped response to the step. An overshoot suppression algorithm which significantly reduces the ringing while not affecting the rise time is presented along with formuli for the rise time and the settling time. Channel errors and their effect on the DM encoded bit stream were investigated.

Optimized Signaling Method for High-Speed Transmission Channels with Higher Order Transfer Function

NASA Astrophysics Data System (ADS)

Ševčík, Břetislav; Brančík, Lubomír; Kubíček, Michal

2017-08-01

In this paper, the selected results from testing of optimized CMOS friendly signaling method for high-speed communications over cables and printed circuit boards (PCBs) are presented and discussed. The proposed signaling scheme uses modified concept of pulse width modulated (PWM) signal which enables to better equalize significant channel losses during data high-speed transmission. Thus, the very effective signaling method to overcome losses in transmission channels with higher order transfer function, typical for long cables and multilayer PCBs, is clearly analyzed in the time and frequency domain. Experimental results of the measurements include the performance comparison of conventional PWM scheme and clearly show the great potential of the modified signaling method for use in low power CMOS friendly equalization circuits, commonly considered in modern communication standards as PCI-Express, SATA or in Multi-gigabit SerDes interconnects.

Optimal Signal Processing of Frequency-Stepped CW Radar Data

NASA Technical Reports Server (NTRS)

Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

1995-01-01

An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the first two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-X510 network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

Optimal Signal Processing of Frequency-Stepped CW Radar Data

NASA Technical Reports Server (NTRS)

Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

1995-01-01

An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-851O network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

Gamma-ray detector employing scintillators coupled to semiconductor drift photodetectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iwanczyk, Jan S.; Patt, Bradley E.

Radiation detectors according to one embodiment of the invention are implemented using scintillators combined with a semiconductor drift photodetectors wherein the components are specifically constructed in terms of their geometry, dimensions, and arrangement so that the scintillator decay time and drift time in the photodetector pairs are matched in order to achieve a greater signal-to-noise ratio. The detectors may include electronics for amplification of electrical signals produced by the silicon drift photodetector, the amplification having a shaping time optimized with respect to the decay time of the scintillator and time spread of the signal in the silicon drift photodetector tomore » substantially maximize the ratio of the signal to the electronic noise.« less

Optimization of the Design of Pre-Signal System Using Improved Cellular Automaton

PubMed Central

Li, Yan; Li, Ke; Tao, Siran; Chen, Kuanmin

2014-01-01

The pre-signal system can improve the efficiency of intersection approach under rational design. One of the main obstacles in optimizing the design of pre-signal system is that driving behaviors in the sorting area cannot be well evaluated. The NaSch model was modified by considering slow probability, turning-deceleration rules, and lane changing rules. It was calibrated with field observed data to explore the interactions among design parameters. The simulation results of the proposed model indicate that the length of sorting area, traffic demand, signal timing, and lane allocation are the most important influence factors. The recommendations of these design parameters are demonstrated. The findings of this paper can be foundations for the design of pre-signal system and show promising improvement in traffic mobility. PMID:25435871

Trackside acoustic diagnosis of axle box bearing based on kurtosis-optimization wavelet denoising

NASA Astrophysics Data System (ADS)

Peng, Chaoyong; Gao, Xiaorong; Peng, Jianping; Wang, Ai

2018-04-01

As one of the key components of railway vehicles, the operation condition of the axle box bearing has a significant effect on traffic safety. The acoustic diagnosis is more suitable than vibration diagnosis for trackside monitoring. The acoustic signal generated by the train axle box bearing is an amplitude modulation and frequency modulation signal with complex train running noise. Although empirical mode decomposition (EMD) and some improved time-frequency algorithms have proved to be useful in bearing vibration signal processing, it is hard to extract the bearing fault signal from serious trackside acoustic background noises by using those algorithms. Therefore, a kurtosis-optimization-based wavelet packet (KWP) denoising algorithm is proposed, as the kurtosis is the key indicator of bearing fault signal in time domain. Firstly, the geometry based Doppler correction is applied to signals of each sensor, and with the signal superposition of multiple sensors, random noises and impulse noises, which are the interference of the kurtosis indicator, are suppressed. Then, the KWP is conducted. At last, the EMD and Hilbert transform is applied to extract the fault feature. Experiment results indicate that the proposed method consisting of KWP and EMD is superior to the EMD.

Hungry pigeons make suboptimal choices, less hungry pigeons do not.

PubMed

Laude, Jennifer R; Pattison, Kristina F; Zentall, Thomas R

2012-10-01

Hungry animals will often choose suboptimally by being attracted to reliable signals for food that occur infrequently (they gamble) over less reliable signals for food that occur more often. That is, pigeons prefer an option that 50 % of the time provides them with a reliable signal for the appearance of food but 50 % of the time provides them with a reliable signal for the absence of food (overall 50 % reinforcement) over an alternative that always provides them with a signal for the appearance of food 75 % of the time (overall 75 % reinforcement). The pigeons appear to choose impulsively for the possibility of obtaining the reliable signal for reinforcement. There is evidence that greater hunger is associated with greater impulsivity. We tested the hypothesis that if the pigeons were less hungry, they would be less impulsive and, thus, would choose more optimally (i.e., on the basis of the overall probability of reinforcement). We found that hungry pigeons choose the 50 % reinforcement alternative suboptimally but less hungry pigeons prefer the more optimal 75 % reinforcement. Paradoxically, pigeons that needed the food more received less of it. These findings have implications for how level of motivation may also affect human suboptimal choice (e.g., purchase of lottery tickets and playing slot machines).

Feature selection and classifier parameters estimation for EEG signals peak detection using particle swarm optimization.

PubMed

Adam, Asrul; Shapiai, Mohd Ibrahim; Tumari, Mohd Zaidi Mohd; Mohamad, Mohd Saberi; Mubin, Marizan

2014-01-01

Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model.

Optimizing the general linear model for functional near-infrared spectroscopy: an adaptive hemodynamic response function approach

PubMed Central

Uga, Minako; Dan, Ippeita; Sano, Toshifumi; Dan, Haruka; Watanabe, Eiju

2014-01-01

Abstract. An increasing number of functional near-infrared spectroscopy (fNIRS) studies utilize a general linear model (GLM) approach, which serves as a standard statistical method for functional magnetic resonance imaging (fMRI) data analysis. While fMRI solely measures the blood oxygen level dependent (BOLD) signal, fNIRS measures the changes of oxy-hemoglobin (oxy-Hb) and deoxy-hemoglobin (deoxy-Hb) signals at a temporal resolution severalfold higher. This suggests the necessity of adjusting the temporal parameters of a GLM for fNIRS signals. Thus, we devised a GLM-based method utilizing an adaptive hemodynamic response function (HRF). We sought the optimum temporal parameters to best explain the observed time series data during verbal fluency and naming tasks. The peak delay of the HRF was systematically changed to achieve the best-fit model for the observed oxy- and deoxy-Hb time series data. The optimized peak delay showed different values for each Hb signal and task. When the optimized peak delays were adopted, the deoxy-Hb data yielded comparable activations with similar statistical power and spatial patterns to oxy-Hb data. The adaptive HRF method could suitably explain the behaviors of both Hb parameters during tasks with the different cognitive loads during a time course, and thus would serve as an objective method to fully utilize the temporal structures of all fNIRS data. PMID:26157973

SNR-optimized phase-sensitive dual-acquisition turbo spin echo imaging: a fast alternative to FLAIR.

PubMed

Lee, Hyunyeol; Park, Jaeseok

2013-07-01

Phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo imaging was recently introduced, producing high-resolution isotropic cerebrospinal fluid attenuated brain images without long inversion recovery preparation. Despite the advantages, the weighted-averaging-based technique suffers from noise amplification resulting from different levels of cerebrospinal fluid signal modulations over the two acquisitions. The purpose of this work is to develop a signal-to-noise ratio-optimized version of the phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo. Variable refocusing flip angles in the first acquisition are calculated using a three-step prescribed signal evolution while those in the second acquisition are calculated using a two-step pseudo-steady state signal transition with a high flip-angle pseudo-steady state at a later portion of the echo train, balancing the levels of cerebrospinal fluid signals in both the acquisitions. Low spatial frequency signals are sampled during the high flip-angle pseudo-steady state to further suppress noise. Numerical simulations of the Bloch equations were performed to evaluate signal evolutions of brain tissues along the echo train and optimize imaging parameters. In vivo studies demonstrate that compared with conventional phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo, the proposed optimization yields 74% increase in apparent signal-to-noise ratio for gray matter and 32% decrease in imaging time. The proposed method can be a potential alternative to conventional fluid-attenuated imaging. Copyright © 2012 Wiley Periodicals, Inc.

Selective Data Acquisition in NMR. The Quantification of Anti-phase Scalar Couplings

NASA Astrophysics Data System (ADS)

Hodgkinson, P.; Holmes, K. J.; Hore, P. J.

Almost all time-domain NMR experiments employ "linear sampling," in which the NMR response is digitized at equally spaced times, with uniform signal averaging. Here, the possibilities of nonlinear sampling are explored using anti-phase doublets in the indirectly detected dimensions of multidimensional COSY-type experiments as an example. The Cramér-Rao lower bounds are used to evaluate and optimize experiments in which the sampling points, or the extent of signal averaging at each point, or both, are varied. The optimal nonlinear sampling for the estimation of the coupling constant J, by model fitting, turns out to involve just a few key time points, for example, at the first node ( t= 1/ J) of the sin(π Jt) modulation. Such sparse sampling patterns can be used to derive more practical strategies, in which the sampling or the signal averaging is distributed around the most significant time points. The improvements in the quantification of NMR parameters can be quite substantial especially when, as is often the case for indirectly detected dimensions, the total number of samples is limited by the time available.

Seismic signal time-frequency analysis based on multi-directional window using greedy strategy

NASA Astrophysics Data System (ADS)

Chen, Yingpin; Peng, Zhenming; Cheng, Zhuyuan; Tian, Lin

2017-08-01

Wigner-Ville distribution (WVD) is an important time-frequency analysis technology with a high energy distribution in seismic signal processing. However, it is interfered by many cross terms. To suppress the cross terms of the WVD and keep the concentration of its high energy distribution, an adaptive multi-directional filtering window in the ambiguity domain is proposed. This begins with the relationship of the Cohen distribution and the Gabor transform combining the greedy strategy and the rotational invariance property of the fractional Fourier transform in order to propose the multi-directional window, which extends the one-dimensional, one directional, optimal window function of the optimal fractional Gabor transform (OFrGT) to a two-dimensional, multi-directional window in the ambiguity domain. In this way, the multi-directional window matches the main auto terms of the WVD more precisely. Using the greedy strategy, the proposed window takes into account the optimal and other suboptimal directions, which also solves the problem of the OFrGT, called the local concentration phenomenon, when encountering a multi-component signal. Experiments on different types of both the signal models and the real seismic signals reveal that the proposed window can overcome the drawbacks of the WVD and the OFrGT mentioned above. Finally, the proposed method is applied to a seismic signal's spectral decomposition. The results show that the proposed method can explore the space distribution of a reservoir more precisely.

A Sarsa(λ)-Based Control Model for Real-Time Traffic Light Coordination

PubMed Central

Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control. PMID:24592183

Optimized signal detection and analysis methods for in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Wang, Qiyan; Zhou, Quanyu; Yang, Ping; Wang, Xiaoling; Niu, Zhenyu; Suo, Yuanzhen; He, Hao; Gao, Wenyuan; Tang, Shuo; Wei, Xunbin

2017-02-01

Melanoma is known as a malignant tumor of melanocytes, which usually appear in the blood circulation at the metastasis stage of cancer. Thus the detection of circulating melanoma cells is useful for early diagnosis and therapy of cancer. Here we have developed an in vivo photoacoustic flow cytometry (PAFC) based on the photoacoustic effect to detect melanoma cells. However, the raw signals we obtain from the target cells contain noises such as environmental sonic noises and electronic noises. Therefore we apply correlation comparison and feature separation methods to the detection and verification of the in vivo signals. Due to similar shape and structure of cells, the photoacoustic signals usually have similar vibration mode. By analyzing the correlations and the signal features in time domain and frequency domain, we are able to provide a method for separating photoacoustic signals generated by target cells from background noises. The method introduced here has proved to optimize the signal acquisition and signal processing, which can improve the detection accuracy in PAFC.

Evaluation of alternative intersections and interchanges: volume 2 -- diverging diamond interchange signal timing.

DOT National Transportation Integrated Search

2015-12-01

This report presents findings from field studies of operations at diverging diamond interchanges (DDIs) in Salt Lake City, Utah and Fort : Wayne, Indiana. These discuss optimization of signal offsets both within the DDI, and with the DDI integrated a...

When good pigeons make bad decisions: Choice with probabilistic delays and outcomes.

PubMed

Pisklak, Jeffrey M; McDevitt, Margaret A; Dunn, Roger M; Spetch, Marcia L

2015-11-01

Pigeons chose between an (optimal) alternative that sometimes provided food after a 10-s delay and other times after a 40-s delay and another (suboptimal) alternative that sometimes provided food after 10 s but other times no food after 40 s. When outcomes were not signaled during the delays, pigeons strongly preferred the optimal alternative. When outcomes were signaled, choices of the suboptimal alternative increased and most pigeons preferred the alternative that provided no food after the long delay despite the cost in terms of obtained food. The pattern of results was similar whether the short delays occurred on 25% or 50% of the trials. Shortening the 40-s delay to food sharply reduced suboptimal choices, but shortening the delay to no food had little effect. The results suggest that a signaled delay to no food does not punish responding in probabilistic choice procedures. The findings are discussed in terms of conditioned reinforcement by signals for good news. © Society for the Experimental Analysis of Behavior.

Agatha: Disentangling period signals from correlated noise in a periodogram framework

NASA Astrophysics Data System (ADS)

Feng, F.; Tuomi, M.; Jones, H. R. A.

2018-04-01

Agatha is a framework of periodograms to disentangle periodic signals from correlated noise and to solve the two-dimensional model selection problem: signal dimension and noise model dimension. These periodograms are calculated by applying likelihood maximization and marginalization and combined in a self-consistent way. Agatha can be used to select the optimal noise model and to test the consistency of signals in time and can be applied to time series analyses in other astronomical and scientific disciplines. An interactive web implementation of the software is also available at http://agatha.herts.ac.uk/.

Evolutionary design optimization of traffic signals applied to Quito city.

PubMed

Armas, Rolando; Aguirre, Hernán; Daolio, Fabio; Tanaka, Kiyoshi

2017-01-01

This work applies evolutionary computation and machine learning methods to study the transportation system of Quito from a design optimization perspective. It couples an evolutionary algorithm with a microscopic transport simulator and uses the outcome of the optimization process to deepen our understanding of the problem and gain knowledge about the system. The work focuses on the optimization of a large number of traffic lights deployed on a wide area of the city and studies their impact on travel time, emissions and fuel consumption. An evolutionary algorithm with specialized mutation operators is proposed to search effectively in large decision spaces, evolving small populations for a short number of generations. The effects of the operators combined with a varying mutation schedule are studied, and an analysis of the parameters of the algorithm is also included. In addition, hierarchical clustering is performed on the best solutions found in several runs of the algorithm. An analysis of signal clusters and their geolocation, estimation of fuel consumption, spatial analysis of emissions, and an analysis of signal coordination provide an overall picture of the systemic effects of the optimization process.

Evolutionary design optimization of traffic signals applied to Quito city

PubMed Central

2017-01-01

This work applies evolutionary computation and machine learning methods to study the transportation system of Quito from a design optimization perspective. It couples an evolutionary algorithm with a microscopic transport simulator and uses the outcome of the optimization process to deepen our understanding of the problem and gain knowledge about the system. The work focuses on the optimization of a large number of traffic lights deployed on a wide area of the city and studies their impact on travel time, emissions and fuel consumption. An evolutionary algorithm with specialized mutation operators is proposed to search effectively in large decision spaces, evolving small populations for a short number of generations. The effects of the operators combined with a varying mutation schedule are studied, and an analysis of the parameters of the algorithm is also included. In addition, hierarchical clustering is performed on the best solutions found in several runs of the algorithm. An analysis of signal clusters and their geolocation, estimation of fuel consumption, spatial analysis of emissions, and an analysis of signal coordination provide an overall picture of the systemic effects of the optimization process. PMID:29236733

A stimulus-dependent spike threshold is an optimal neural coder

PubMed Central

Jones, Douglas L.; Johnson, Erik C.; Ratnam, Rama

2015-01-01

A neural code based on sequences of spikes can consume a significant portion of the brain's energy budget. Thus, energy considerations would dictate that spiking activity be kept as low as possible. However, a high spike-rate improves the coding and representation of signals in spike trains, particularly in sensory systems. These are competing demands, and selective pressure has presumably worked to optimize coding by apportioning a minimum number of spikes so as to maximize coding fidelity. The mechanisms by which a neuron generates spikes while maintaining a fidelity criterion are not known. Here, we show that a signal-dependent neural threshold, similar to a dynamic or adapting threshold, optimizes the trade-off between spike generation (encoding) and fidelity (decoding). The threshold mimics a post-synaptic membrane (a low-pass filter) and serves as an internal decoder. Further, it sets the average firing rate (the energy constraint). The decoding process provides an internal copy of the coding error to the spike-generator which emits a spike when the error equals or exceeds a spike threshold. When optimized, the trade-off leads to a deterministic spike firing-rule that generates optimally timed spikes so as to maximize fidelity. The optimal coder is derived in closed-form in the limit of high spike-rates, when the signal can be approximated as a piece-wise constant signal. The predicted spike-times are close to those obtained experimentally in the primary electrosensory afferent neurons of weakly electric fish (Apteronotus leptorhynchus) and pyramidal neurons from the somatosensory cortex of the rat. We suggest that KCNQ/Kv7 channels (underlying the M-current) are good candidates for the decoder. They are widely coupled to metabolic processes and do not inactivate. We conclude that the neural threshold is optimized to generate an energy-efficient and high-fidelity neural code. PMID:26082710

Optimization of sparse synthetic transmit aperture imaging with coded excitation and frequency division.

PubMed

Behar, Vera; Adam, Dan

2005-12-01

An effective aperture approach is used for optimization of a sparse synthetic transmit aperture (STA) imaging system with coded excitation and frequency division. A new two-stage algorithm is proposed for optimization of both the positions of the transmit elements and the weights of the receive elements. In order to increase the signal-to-noise ratio in a synthetic aperture system, temporal encoding of the excitation signals is employed. When comparing the excitation by linear frequency modulation (LFM) signals and phase shift key modulation (PSKM) signals, the analysis shows that chirps are better for excitation, since at the output of a compression filter the sidelobes generated are much smaller than those produced by the binary PSKM signals. Here, an implementation of a fast STA imaging is studied by spatial encoding with frequency division of the LFM signals. The proposed system employs a 64-element array with only four active elements used during transmit. The two-dimensional point spread function (PSF) produced by such a sparse STA system is compared to the PSF produced by an equivalent phased array system, using the Field II simulation program. The analysis demonstrates the superiority of the new sparse STA imaging system while using coded excitation and frequency division. Compared to a conventional phased array imaging system, this system acquires images of equivalent quality 60 times faster, when the transmit elements are fired in pairs consecutively and the power level used during transmit is very low. The fastest acquisition time is achieved when all transmit elements are fired simultaneously, which improves detectability, but at the cost of a slight degradation of the axial resolution. In real-time implementation, however, it must be borne in mind that the frame rate of a STA imaging system depends not only on the acquisition time of the data but also on the processing time needed for image reconstruction. Comparing to phased array imaging, a significant increase in the frame rate of a STA imaging system is possible if and only if an equivalent time efficient algorithm is used for image reconstruction.

Optimal Decentralized Protocol for Electric Vehicle Charging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gan, LW; Topcu, U; Low, SH

We propose a decentralized algorithm to optimally schedule electric vehicle (EV) charging. The algorithm exploits the elasticity of electric vehicle loads to fill the valleys in electric load profiles. We first formulate the EV charging scheduling problem as an optimal control problem, whose objective is to impose a generalized notion of valley-filling, and study properties of optimal charging profiles. We then give a decentralized algorithm to iteratively solve the optimal control problem. In each iteration, EVs update their charging profiles according to the control signal broadcast by the utility company, and the utility company alters the control signal to guidemore » their updates. The algorithm converges to optimal charging profiles (that are as "flat" as they can possibly be) irrespective of the specifications (e.g., maximum charging rate and deadline) of EVs, even if EVs do not necessarily update their charging profiles in every iteration, and use potentially outdated control signal when they update. Moreover, the algorithm only requires each EV solving its local problem, hence its implementation requires low computation capability. We also extend the algorithm to track a given load profile and to real-time implementation.« less

Optimization of a cAMP response element signal pathway reporter system.

PubMed

Shan, Qiang; Storm, Daniel R

2010-08-15

A sensitive cAMP response element (CRE) reporter system is essential for studying the cAMP/protein kinase A/cAMP response element binding protein signal pathway. Here we have tested a few CRE promoters and found one with high sensitivity to external stimuli. Using this optimal CRE promoter and the enhanced green fluorescent protein as the reporter, we have established a CRE reporter cell line. This cell line can be used to study the signal pathway by fluorescent microscope, fluorescence-activated cell analysis and luciferase assay. This cell line's sensitivity to forskolin, using the technique of fluorescence-activated cell sorting, was increased to approximately seven times that of its parental HEK 293 cell line, which is currently the most commonly used cell line in the field for the signal pathway study. Therefore, this newly created cell line is potentially useful for studying the signal pathway's modulators, which generally have weaker effect than its mediators. Our research has also established a general procedure for optimizing transcription-based reporter cell lines, which might be useful in performing the same task when studying many other transcription-based signal pathways. (c) 2010 Elsevier B.V. All rights reserved.

Long-range wind monitoring in real time with optimized coherent lidar

NASA Astrophysics Data System (ADS)

Dolfi-Bouteyre, Agnes; Canat, Guillaume; Lombard, Laurent; Valla, Matthieu; Durécu, Anne; Besson, Claudine

2017-03-01

Two important enabling technologies for pulsed coherent detection wind lidar are the laser and real-time signal processing. In particular, fiber laser is limited in peak power by nonlinear effects, such as stimulated Brillouin scattering (SBS). We report on various technologies that have been developed to mitigate SBS and increase peak power in 1.5-μm fiber lasers, such as special large mode area fiber designs or strain management. Range-resolved wind profiles up to a record range of 16 km within 0.1-s averaging time have been obtained thanks to those high-peak power fiber lasers. At long range, the lidar signal gets much weaker than the noise and special care is required to extract the Doppler peak from the spectral noise. To optimize real-time processing for weak carrier-to-noise ratio signal, we have studied various Doppler mean frequency estimators (MFE) and the influence of data accumulation on outliers occurrence. Five real-time MFEs (maximum, centroid, matched filter, maximum likelihood, and polynomial fit) have been compared in terms of error and processing time using lidar experimental data. MFE errors and data accumulation limits are established using a spectral method.

Optimization of neural network architecture for classification of radar jamming FM signals

NASA Astrophysics Data System (ADS)

Soto, Alberto; Mendoza, Ariadna; Flores, Benjamin C.

2017-05-01

The purpose of this study is to investigate several artificial Neural Network (NN) architectures in order to design a cognitive radar system capable of optimally distinguishing linear Frequency-Modulated (FM) signals from bandlimited Additive White Gaussian Noise (AWGN). The goal is to create a theoretical framework to determine an optimal NN architecture to achieve a Probability of Detection (PD) of 95% or higher and a Probability of False Alarm (PFA) of 1.5% or lower at 5 dB Signal to Noise Ratio (SNR). Literature research reveals that the frequency-domain power spectral densities characterize a signal more efficiently than its time-domain counterparts. Therefore, the input data is preprocessed by calculating the magnitude square of the Discrete Fourier Transform of the digitally sampled bandlimited AWGN and linear FM signals to populate a matrix containing N number of samples and M number of spectra. This matrix is used as input for the NN, and the spectra are divided as follows: 70% for training, 15% for validation, and 15% for testing. The study begins by experimentally deducing the optimal number of hidden neurons (1-40 neurons), then the optimal number of hidden layers (1-5 layers), and lastly, the most efficient learning algorithm. The training algorithms examined are: Resilient Backpropagation, Scaled Conjugate Gradient, Conjugate Gradient with Powell/Beale Restarts, Polak-Ribiére Conjugate Gradient, and Variable Learning Rate Backpropagation. We determine that an architecture with ten hidden neurons (or higher), one hidden layer, and a Scaled Conjugate Gradient for training algorithm encapsulates an optimal architecture for our application.

Non-linear auto-regressive models for cross-frequency coupling in neural time series

PubMed Central

Tallot, Lucille; Grabot, Laetitia; Doyère, Valérie; Grenier, Yves; Gramfort, Alexandre

2017-01-01

We address the issue of reliably detecting and quantifying cross-frequency coupling (CFC) in neural time series. Based on non-linear auto-regressive models, the proposed method provides a generative and parametric model of the time-varying spectral content of the signals. As this method models the entire spectrum simultaneously, it avoids the pitfalls related to incorrect filtering or the use of the Hilbert transform on wide-band signals. As the model is probabilistic, it also provides a score of the model “goodness of fit” via the likelihood, enabling easy and legitimate model selection and parameter comparison; this data-driven feature is unique to our model-based approach. Using three datasets obtained with invasive neurophysiological recordings in humans and rodents, we demonstrate that these models are able to replicate previous results obtained with other metrics, but also reveal new insights such as the influence of the amplitude of the slow oscillation. Using simulations, we demonstrate that our parametric method can reveal neural couplings with shorter signals than non-parametric methods. We also show how the likelihood can be used to find optimal filtering parameters, suggesting new properties on the spectrum of the driving signal, but also to estimate the optimal delay between the coupled signals, enabling a directionality estimation in the coupling. PMID:29227989

Characterization of a Raman spectroscopy probe system for intraoperative brain tissue classification

PubMed Central

Desroches, Joannie; Jermyn, Michael; Mok, Kelvin; Lemieux-Leduc, Cédric; Mercier, Jeanne; St-Arnaud, Karl; Urmey, Kirk; Guiot, Marie-Christine; Marple, Eric; Petrecca, Kevin; Leblond, Frédéric

2015-01-01

A detailed characterization study is presented of a Raman spectroscopy system designed to maximize the volume of resected cancer tissue in glioma surgery based on in vivo molecular tissue characterization. It consists of a hand-held probe system measuring spectrally resolved inelastically scattered light interacting with tissue, designed and optimized for in vivo measurements. Factors such as linearity of the signal with integration time and laser power, and their impact on signal to noise ratio, are studied leading to optimal data acquisition parameters. The impact of ambient light sources in the operating room is assessed and recommendations made for optimal operating conditions. In vivo Raman spectra of normal brain, cancer and necrotic tissue were measured in 10 patients, demonstrating that real-time inelastic scattering measurements can distinguish necrosis from vital tissue (including tumor and normal brain tissue) with an accuracy of 87%, a sensitivity of 84% and a specificity of 89%. PMID:26203368

Note: Ultrasonic gas flowmeter based on optimized time-of-flight algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, X. F.; Tang, Z. A.

2011-04-15

A new digital signal processor based single path ultrasonic gas flowmeter is designed, constructed, and experimentally tested. To achieve high accuracy measurements, an optimized ultrasound driven method of incorporation of the amplitude modulation and the phase modulation of the transmit-receive technique is used to stimulate the transmitter. Based on the regularities among the received envelope zero-crossings, different received signal's signal-to-noise ratio situations are discriminated and optional time-of-flight algorithms are applied to take flow rate calculations. Experimental results from the dry calibration indicate that the designed flowmeter prototype can meet the zero-flow verification test requirements of the American Gas Association Reportmore » No. 9. Furthermore, the results derived from the flow calibration prove that the proposed flowmeter prototype can measure flow rate accurately in the practical experiments, and the nominal accuracies after FWME adjustment are lower than 0.8% throughout the calibration range.« less

Digital signal processing for velocity measurements in dynamical material's behaviour studies.

PubMed

Devlaminck, Julien; Luc, Jérôme; Chanal, Pierre-Yves

2014-03-01

In this work, we describe different configurations of optical fiber interferometers (types Michelson and Mach-Zehnder) used to measure velocities during dynamical material's behaviour studies. We detail the algorithms of processing developed and optimized to improve the performance of these interferometers especially in terms of time and frequency resolutions. Three methods of analysis of interferometric signals were studied. For Michelson interferometers, the time-frequency analysis of signals by Short-Time Fourier Transform (STFT) is compared to a time-frequency analysis by Continuous Wavelet Transform (CWT). The results have shown that the CWT was more suitable than the STFT for signals with low signal-to-noise, and low velocity and high acceleration areas. For Mach-Zehnder interferometers, the measurement is carried out by analyzing the phase shift between three interferometric signals (Triature processing). These three methods of digital signal processing were evaluated, their measurement uncertainties estimated, and their restrictions or operational limitations specified from experimental results performed on a pulsed power machine.

Gas ultrasonic flow rate measurement through genetic-ant colony optimization based on the ultrasonic pulse received signal model

NASA Astrophysics Data System (ADS)

Hou, Huirang; Zheng, Dandan; Nie, Laixiao

2015-04-01

For gas ultrasonic flowmeters, the signals received by ultrasonic sensors are susceptible to noise interference. If signals are mingled with noise, a large error in flow measurement can be caused by triggering mistakenly using the traditional double-threshold method. To solve this problem, genetic-ant colony optimization (GACO) based on the ultrasonic pulse received signal model is proposed. Furthermore, in consideration of the real-time performance of the flow measurement system, the improvement of processing only the first three cycles of the received signals rather than the whole signal is proposed. Simulation results show that the GACO algorithm has the best estimation accuracy and ant-noise ability compared with the genetic algorithm, ant colony optimization, double-threshold and enveloped zero-crossing. Local convergence doesn’t appear with the GACO algorithm until -10 dB. For the GACO algorithm, the converging accuracy and converging speed and the amount of computation are further improved when using the first three cycles (called GACO-3cycles). Experimental results involving actual received signals show that the accuracy of single-gas ultrasonic flow rate measurement can reach 0.5% with GACO-3 cycles, which is better than with the double-threshold method.

SU-E-T-266: Development of Evaluation System of Optimal Synchrotron Controlling Parameter for Spot Scanning Proton Therapy with Multiple Gate Irradiations in One Operation Cycle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamada, T; Fujii, Y; Hitachi Ltd., Hitachi-shi, Ibaraki

2015-06-15

Purpose: We have developed a gated spot scanning proton beam therapy system with real-time tumor-tracking. This system has the ability of multiple-gated irradiation in a single synchrotron operation cycle controlling the wait-time for consecutive gate signals during a flat-top phase so that the decrease in irradiation efficiency induced by irregular variation of gate signal is reduced. Our previous studies have shown that a 200 ms wait-time is appropriate to increase the average irradiation efficiency, but the optimal wait-time can vary patient by patient and day by day. In this research, we have developed an evaluation system of the optimal wait-timemore » in each irradiation based on the log data of the real-time-image gated proton beam therapy (RGPT) system. Methods: The developed system consists of logger for operation of RGPT system and software for evaluation of optimal wait-time. The logger records timing of gate on/off, timing and the dose of delivered beam spots, beam energy and timing of X-ray irradiation. The evaluation software calculates irradiation time in the case of different wait-time by simulating the multiple-gated irradiation operation using several timing information. Actual data preserved in the log data are used for gate on and off time, spot irradiation time, and time moving to the next spot. Design values are used for the acceleration and deceleration times. We applied this system to a patient treated with the RGPT system. Results: The evaluation system found the optimal wait-time of 390 ms that reduced the irradiation time by about 10 %. The irradiation time with actual wait-time used in treatment was reproduced with accuracy of 0.2 ms. Conclusion: For spot scanning proton therapy system with multiple-gated irradiation in one synchrotron operation cycle, an evaluation system of the optimal wait-time in each irradiation based on log data has been developed. Funding Support: Japan Society for the Promotion of Science (JSPS) through the FIRST Program.« less

Performance comparison of optimal fractional order hybrid fuzzy PID controllers for handling oscillatory fractional order processes with dead time.

PubMed

Das, Saptarshi; Pan, Indranil; Das, Shantanu

2013-07-01

Fuzzy logic based PID controllers have been studied in this paper, considering several combinations of hybrid controllers by grouping the proportional, integral and derivative actions with fuzzy inferencing in different forms. Fractional order (FO) rate of error signal and FO integral of control signal have been used in the design of a family of decomposed hybrid FO fuzzy PID controllers. The input and output scaling factors (SF) along with the integro-differential operators are tuned with real coded genetic algorithm (GA) to produce optimum closed loop performance by simultaneous consideration of the control loop error index and the control signal. Three different classes of fractional order oscillatory processes with various levels of relative dominance between time constant and time delay have been used to test the comparative merits of the proposed family of hybrid fractional order fuzzy PID controllers. Performance comparison of the different FO fuzzy PID controller structures has been done in terms of optimal set-point tracking, load disturbance rejection and minimal variation of manipulated variable or smaller actuator requirement etc. In addition, multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) has been used to study the Pareto optimal trade-offs between the set point tracking and control signal, and the set point tracking and load disturbance performance for each of the controller structure to handle the three different types of processes. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Feature Selection and Classifier Parameters Estimation for EEG Signals Peak Detection Using Particle Swarm Optimization

PubMed Central

Adam, Asrul; Mohd Tumari, Mohd Zaidi; Mohamad, Mohd Saberi

2014-01-01

Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model. PMID:25243236

Signal Analysis of Helicopter Blade-Vortex-Interaction Acoustic Noise Data

NASA Technical Reports Server (NTRS)

Rogers, James C.; Dai, Renshou

1998-01-01

Blade-Vortex-Interaction (BVI) produces annoying high-intensity impulsive noise. NASA Ames collected several sets of BVI noise data during in-flight and wind tunnel tests. The goal of this work is to extract the essential features of the BVI signals from the in-flight data and examine the feasibility of extracting those features from BVI noise recorded inside a large wind tunnel. BVI noise generating mechanisms and BVI radiation patterns an are considered and a simple mathematical-physical model is presented. It allows the construction of simple synthetic BVI events that are comparable to free flight data. The boundary effects of the wind tunnel floor and ceiling are identified and more complex synthetic BVI events are constructed to account for features observed in the wind tunnel data. It is demonstrated that improved recording of BVI events can be attained by changing the geometry of the rotor hub, floor, ceiling and microphone. The Euclidean distance measure is used to align BVI events from each blade and improved BVI signals are obtained by time-domain averaging the aligned data. The differences between BVI events for individual blades are then apparent. Removal of wind tunnel background noise by optimal Wiener-filtering is shown to be effective provided representative noise-only data have been recorded. Elimination of wind tunnel reflections by cepstral and optimal filtering deconvolution is examined. It is seen that the cepstral method is not applicable but that a pragmatic optimal filtering approach gives encouraging results. Recommendations for further work include: altering measurement geometry, real-time data observation and evaluation, examining reflection signals (particularly those from the ceiling) and performing further analysis of expected BVI signals for flight conditions of interest so that microphone placement can be optimized for each condition.

Model accuracy impact through rescaled observations in hydrological data assimilation studies

USDA-ARS?s Scientific Manuscript database

Signal and noise time-series variability of soil moisture datasets (e.g. satellite-, model-, station-based) vary greatly. Optimality of the analysis obtained after observations are assimilated into the model depends on the degree that the differences between the signal variances of model and observa...

Impact of model relative accuracy in framework of rescaling observations in hydrological data assimilation studies

USDA-ARS?s Scientific Manuscript database

Soil moisture datasets (e.g. satellite-, model-, station-based) vary greatly with respect to their signal, noise, and/or combined time-series variability. Minimizing differences in signal variances is particularly important in data assimilation techniques to optimize the accuracy of the analysis obt...

Experimental optimization of directed field ionization

NASA Astrophysics Data System (ADS)

Liu, Zhimin Cheryl; Gregoric, Vincent C.; Carroll, Thomas J.; Noel, Michael W.

2017-04-01

The state distribution of an ensemble of Rydberg atoms is commonly measured using selective field ionization. The resulting time resolved ionization signal from a single energy eigenstate tends to spread out due to the multiple avoided Stark level crossings atoms must traverse on the way to ionization. The shape of the ionization signal can be modified by adding a perturbation field to the main field ramp. Here, we present experimental results of the manipulation of the ionization signal using a genetic algorithm. We address how both the genetic algorithm and the experimental parameters were adjusted to achieve an optimized result. This work was supported by the National Science Foundation under Grants No. 1607335 and No. 1607377.

A robust approach to optimal matched filter design in ultrasonic non-destructive evaluation (NDE)

NASA Astrophysics Data System (ADS)

Li, Minghui; Hayward, Gordon

2017-02-01

The matched filter was demonstrated to be a powerful yet efficient technique to enhance defect detection and imaging in ultrasonic non-destructive evaluation (NDE) of coarse grain materials, provided that the filter was properly designed and optimized. In the literature, in order to accurately approximate the defect echoes, the design utilized the real excitation signals, which made it time consuming and less straightforward to implement in practice. In this paper, we present a more robust and flexible approach to optimal matched filter design using the simulated excitation signals, and the control parameters are chosen and optimized based on the real scenario of array transducer, transmitter-receiver system response, and the test sample, as a result, the filter response is optimized and depends on the material characteristics. Experiments on industrial samples are conducted and the results confirm the great benefits of the method.

Focusing light through random photonic layers by four-element division algorithm

NASA Astrophysics Data System (ADS)

Fang, Longjie; Zhang, Xicheng; Zuo, Haoyi; Pang, Lin

2018-02-01

The propagation of waves in turbid media is a fundamental problem of optics with vast applications. Optical phase optimization approaches for focusing light through turbid media using phase control algorithm have been widely studied in recent years due to the rapid development of spatial light modulator. The existing approaches include element-based algorithms - stepwise sequential algorithm, continuous sequential algorithm and whole element optimization approaches - partitioning algorithm, transmission matrix approach and genetic algorithm. The advantage of element-based approaches is that the phase contribution of each element is very clear; however, because the intensity contribution of each element to the focal point is small especially for the case of large number of elements, the determination of the optimal phase for a single element would be difficult. In other words, the signal to noise ratio of the measurement is weak, leading to possibly local maximal during the optimization. As for whole element optimization approaches, all elements are employed for the optimization. Of course, signal to noise ratio during the optimization is improved. However, because more random processings are introduced into the processing, optimizations take more time to converge than the single element based approaches. Based on the advantages of both single element based approaches and whole element optimization approaches, we propose FEDA approach. Comparisons with the existing approaches show that FEDA only takes one third of measurement time to reach the optimization, which means that FEDA is promising in practical application such as for deep tissue imaging.

Modeling and Simulation of Bus Dispatching Policy for Timed Transfers on Signalized Networks

NASA Astrophysics Data System (ADS)

Cho, Hsun-Jung; Lin, Guey-Shii

2007-12-01

The major work of this study is to formulate the system cost functions and to integrate the bus dispatching policy with signal control. The integrated model mainly includes the flow dispersion model for links, signal control model for nodes, and dispatching control model for transfer terminals. All such models are inter-related for transfer operations in one-center transit network. The integrated model that combines dispatching policies with flexible signal control modes can be applied to assess the effectiveness of transfer operations. It is found that, if bus arrival information is reliable, an early dispatching decision made at the mean bus arrival times is preferable. The costs for coordinated operations with slack times are relatively low at the optimal common headway when applying adaptive route control. Based on such findings, a threshold function of bus headway for justifying an adaptive signal route control under various time values of auto drivers is developed.

Signal and background considerations for the MRSt on the National Ignition Facility (NIF).

PubMed

Wink, C W; Frenje, J A; Hilsabeck, T J; Bionta, R; Khater, H Y; Gatu Johnson, M; Kilkenny, J D; Li, C K; Séguin, F H; Petrasso, R D

2016-11-01

A Magnetic Recoil Spectrometer (MRSt) has been conceptually designed for time-resolved measurements of the neutron spectrum at the National Ignition Facility. Using the MRSt, the goals are to measure the time-evolution of the spectrum with a time resolution of ∼20-ps and absolute accuracy better than 5%. To meet these goals, a detailed understanding and optimization of the signal and background characteristics are required. Through ion-optics, MCNP simulations, and detector-response calculations, it is demonstrated that the goals and a signal-to background >5-10 for the down-scattered neutron measurement are met if the background, consisting of ambient neutrons and gammas, at the MRSt is reduced 50-100 times.

Time-Frequency Analysis And Pattern Recognition Using Singular Value Decomposition Of The Wigner-Ville Distribution

NASA Astrophysics Data System (ADS)

Boashash, Boualem; Lovell, Brian; White, Langford

1988-01-01

Time-Frequency analysis based on the Wigner-Ville Distribution (WVD) is shown to be optimal for a class of signals where the variation of instantaneous frequency is the dominant characteristic. Spectral resolution and instantaneous frequency tracking is substantially improved by using a Modified WVD (MWVD) based on an Autoregressive spectral estimator. Enhanced signal-to-noise ratio may be achieved by using 2D windowing in the Time-Frequency domain. The WVD provides a tool for deriving descriptors of signals which highlight their FM characteristics. These descriptors may be used for pattern recognition and data clustering using the methods presented in this paper.

Performance comparison of extracellular spike sorting algorithms for single-channel recordings.

PubMed

Wild, Jiri; Prekopcsak, Zoltan; Sieger, Tomas; Novak, Daniel; Jech, Robert

2012-01-30

Proper classification of action potentials from extracellular recordings is essential for making an accurate study of neuronal behavior. Many spike sorting algorithms have been presented in the technical literature. However, no comparative analysis has hitherto been performed. In our study, three widely-used publicly-available spike sorting algorithms (WaveClus, KlustaKwik, OSort) were compared with regard to their parameter settings. The algorithms were evaluated using 112 artificial signals (publicly available online) with 2-9 different neurons and varying noise levels between 0.00 and 0.60. An optimization technique based on Adjusted Mutual Information was employed to find near-optimal parameter settings for a given artificial signal and algorithm. All three algorithms performed significantly better (p<0.01) with optimized parameters than with the default ones. WaveClus was the most accurate spike sorting algorithm, receiving the best evaluation score for 60% of all signals. OSort operated at almost five times the speed of the other algorithms. In terms of accuracy, OSort performed significantly less well (p<0.01) than WaveClus for signals with a noise level in the range 0.15-0.30. KlustaKwik achieved similar scores to WaveClus for signals with low noise level 0.00-0.15 and was worse otherwise. In conclusion, none of the three compared algorithms was optimal in general. The accuracy of the algorithms depended on proper choice of the algorithm parameters and also on specific properties of the examined signal. Copyright © 2011 Elsevier B.V. All rights reserved.

Arterial signal timing optimization using PASSER II-87

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, E.C.P.; Messer, C.J.; Garza, R.U.

1988-11-01

PASSER is the acronym for the Progression Analysis and Signal System Evaluation Routine. PASSER II was originally developed by the Texas Transportation Institute (TTI) for the Dallas Corridor Project. The Texas State Department of Highways and Public Transportation (SDHPT) has sponsored the subsequent program development on both mainframe computers and microcomputers. The theory, model structure, methodology, and logic of PASSER II have been evaluated and well documented. PASSER II is widely used because of its ability to easily select multiple-phase sequences by adjusting the background cycle length and progression speeds to find the optimal timing plants, such as cycle, greenmore » split, phase sequence, and offsets, that can efficiently maximize the two-way progression bands.« less

n-Order and maximum fuzzy similarity entropy for discrimination of signals of different complexity: Application to fetal heart rate signals.

PubMed

Zaylaa, Amira; Oudjemia, Souad; Charara, Jamal; Girault, Jean-Marc

2015-09-01

This paper presents two new concepts for discrimination of signals of different complexity. The first focused initially on solving the problem of setting entropy descriptors by varying the pattern size instead of the tolerance. This led to the search for the optimal pattern size that maximized the similarity entropy. The second paradigm was based on the n-order similarity entropy that encompasses the 1-order similarity entropy. To improve the statistical stability, n-order fuzzy similarity entropy was proposed. Fractional Brownian motion was simulated to validate the different methods proposed, and fetal heart rate signals were used to discriminate normal from abnormal fetuses. In all cases, it was found that it was possible to discriminate time series of different complexity such as fractional Brownian motion and fetal heart rate signals. The best levels of performance in terms of sensitivity (90%) and specificity (90%) were obtained with the n-order fuzzy similarity entropy. However, it was shown that the optimal pattern size and the maximum similarity measurement were related to intrinsic features of the time series. Copyright © 2015 Elsevier Ltd. All rights reserved.

Real-Time Noise Reduction for Mossbauer Spectroscopy through Online Implementation of a Modified Kalman Filter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abrecht, David G.; Schwantes, Jon M.; Kukkadapu, Ravi K.

2015-02-01

Spectrum-processing software that incorporates a gaussian smoothing kernel within the statistics of first-order Kalman filtration has been developed to provide cross-channel spectral noise reduction for increased real-time signal-to-noise ratios for Mossbauer spectroscopy. The filter was optimized for the breadth of the gaussian using the Mossbauer spectrum of natural iron foil, and comparisons between the peak broadening, signal-to-noise ratios, and shifts in the calculated hyperfine parameters are presented. The results of optimization give a maximum improvement in the signal-to-noise ratio of 51.1% over the unfiltered spectrum at a gaussian breadth of 27 channels, or 2.5% of the total spectrum width. Themore » full-width half-maximum of the spectrum peaks showed an increase of 19.6% at this optimum point, indicating a relatively weak increase in the peak broadening relative to the signal enhancement, leading to an overall increase in the observable signal. Calculations of the hyperfine parameters showed no statistically significant deviations were introduced from the application of the filter, confirming the utility of this filter for spectroscopy applications.« less

An enhanced multi-channel bacterial foraging optimization algorithm for MIMO communication system

NASA Astrophysics Data System (ADS)

Palanimuthu, Senthilkumar Jayalakshmi; Muthial, Chandrasekaran

2017-04-01

Channel estimation and optimisation are the main challenging tasks in Multi Input Multi Output (MIMO) wireless communication systems. In this work, a Multi-Channel Bacterial Foraging Optimization Algorithm approach is proposed for the selection of antenna in a transmission area. The main advantage of this method is, it reduces the loss of bandwidth during data transmission effectively. Here, we considered the channel estimation and optimisation for improving the transmission speed and reducing the unused bandwidth. Initially, the message is given to the input of the communication system. Then, the symbol mapping process is performed for converting the message into signals. It will be encoded based on the space-time encoding technique. Here, the single signal is divided into multiple signals and it will be given to the input of space-time precoder. Hence, the multiplexing is applied to transmission channel estimation. In this paper, the Rayleigh channel is selected based on the bandwidth range. This is the Gaussian distribution type channel. Then, the demultiplexing is applied on the obtained signal that is the reverse function of multiplexing, which splits the combined signal arriving from a medium into the original information signal. Furthermore, the long-term evolution technique is used for scheduling the time to channels during transmission. Here, the hidden Markov model technique is employed to predict the status information of the channel. Finally, the signals are decoded and the reconstructed signal is obtained after performing the scheduling process. The experimental results evaluate the performance of the proposed MIMO communication system in terms of bit error rate, mean squared error, average throughput, outage capacity and signal to interference noise ratio.

Digital signal processing the Tevatron BPM signals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cancelo, G.; James, E.; Wolbers, S.

2005-05-01

The Beam Position Monitor (TeV BPM) readout system at Fermilab's Tevatron has been updated and is currently being commissioned. The new BPMs use new analog and digital hardware to achieve better beam position measurement resolution. The new system reads signals from both ends of the existing directional stripline pickups to provide simultaneous proton and antiproton measurements. The signals provided by the two ends of the BPM pickups are processed by analog band-pass filters and sampled by 14-bit ADCs at 74.3MHz. A crucial part of this work has been the design of digital filters that process the signal. This paper describesmore » the digital processing and estimation techniques used to optimize the beam position measurement. The BPM electronics must operate in narrow-band and wide-band modes to enable measurements of closed-orbit and turn-by-turn positions. The filtering and timing conditions of the signals are tuned accordingly for the operational modes. The analysis and the optimized result for each mode are presented.« less

Mass Spectrometry Parameters Optimization for the 46 Multiclass Pesticides Determination in Strawberries with Gas Chromatography Ion-Trap Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Fernandes, Virgínia C.; Vera, Jose L.; Domingues, Valentina F.; Silva, Luís M. S.; Mateus, Nuno; Delerue-Matos, Cristina

2012-12-01

Multiclass analysis method was optimized in order to analyze pesticides traces by gas chromatography with ion-trap and tandem mass spectrometry (GC-MS/MS). The influence of some analytical parameters on pesticide signal response was explored. Five ion trap mass spectrometry (IT-MS) operating parameters, including isolation time (IT), excitation voltage (EV), excitation time (ET), maximum excitation energy or " q" value (q), and isolation mass window (IMW) were numerically tested in order to maximize the instrument analytical signal response. For this, multiple linear regression was used in data analysis to evaluate the influence of the five parameters on the analytical response in the ion trap mass spectrometer and to predict its response. The assessment of the five parameters based on the regression equations substantially increased the sensitivity of IT-MS/MS in the MS/MS mode. The results obtained show that for most of the pesticides, these parameters have a strong influence on both signal response and detection limit. Using the optimized method, a multiclass pesticide analysis was performed for 46 pesticides in a strawberry matrix. Levels higher than the limit established for strawberries by the European Union were found in some samples.

Optimized linear motor and digital PID controller setup used in Mössbauer spectrometer

NASA Astrophysics Data System (ADS)

Kohout, Pavel; Kouřil, Lukáš; Navařík, Jakub; Novák, Petr; Pechoušek, Jiří

2014-10-01

Optimization of a linear motor and digital PID controller setup used in a Mössbauer spectrometer is presented. Velocity driving system with a digital PID feedback subsystem was developed in the LabVIEW graphical environment and deployed on the sbRIO real-time hardware device (National Instruments). The most important data acquisition processes are performed as real-time deterministic tasks on an FPGA chip. Velocity transducer of a double loudspeaker type with a power amplifier circuit is driven by the system. Series of calibration measurements were proceeded to find the optimal setup of the P, I, D parameters together with velocity error signal analysis. The shape and given signal characteristics of the velocity error signal are analyzed in details. Remote applications for controlling and monitoring the PID system from computer or smart phone, respectively, were also developed. The best setup and P, I, D parameters were set and calibration spectrum of α-Fe sample with an average nonlinearity of the velocity scale below 0.08% was collected. Furthermore, the width of the spectral line below 0.30 mm/s was observed. Powerful and complex velocity driving system was designed.

Optimized tracking of RF carriers with phase noise, including Pioneer 10 results

NASA Technical Reports Server (NTRS)

Vilnrotter, V. A.; Hurd, W. J.; Brown, D. H.

1987-01-01

The ability to track very weak signals from distant spacecraft is limited by the phase instabilities of the received signal and of the local oscillator employed by the receiver. These instabilities ultimately limit the minimum loop bandwidth that can be used in a phase-coherent receiver, and hence limit the ratio of received carrier power to noise spectral density which can be tracked phase coherently. A method is presented for near real time estimation of the received carrier phase and additive noise spectrum, and optimization of the phase locked loop bandwidth. The method was used with the breadboard Deep Space Network (DSN) Advanced Receiver to optimize tracking of very weak signals from the Pioneer 10 spacecraft, which is now more distant that the edge of the solar system. Tracking with bandwidths of 0.1 Hz to 1.0 Hz reduces tracking signal threshold and increases carrier loop signal to noise ratio (SNR) by 5 dB to 15 dB compared to the 3 Hz bandwidth of the receivers now used operationally in the DSN. This will enable the DSN to track Pioneer 10 until its power sources fails near the end of the century.

The frequencies of calcium oscillations are optimized for efficient calcium-mediated activation of Ras and the ERK/MAPK cascade.

PubMed

Kupzig, Sabine; Walker, Simon A; Cullen, Peter J

2005-05-24

Ras proteins are binary switches that, by cycling through inactive GDP- and active GTP-bound conformations, regulate multiple cellular signaling pathways, including those that control growth and differentiation. For some time, it has been known that receptor-mediated increases in the concentration of intracellular free calcium ([Ca(2+)](i)) can modulate Ras activation. Increases in [Ca(2+)](i) often occur as repetitive Ca(2+) spikes or oscillations. Induced by electrical or receptor stimuli, these repetitive Ca(2+) oscillations increase in frequency with the amplitude of receptor stimuli, a phenomenon critical for the induction of selective cellular functions. Here, we show that Ca(2+) oscillations are optimized for Ca(2+)-mediated activation of Ras and signaling through the extracellular signal-regulated kinase (ERK)/mitogen-activated protein kinase (MAPK) cascade. We present additional evidence that Ca(2+) oscillations reduce the effective Ca(2+) threshold for the activation of Ras and that the oscillatory frequency is optimized for activation of Ras and the ERK/MAPK pathway. Our results describe a hitherto unrecognized link between complex Ca(2+) signals and the modulation of the Ras/ERK/MAPK signaling cascade.

Optimality study of a gust alleviation system for light wing-loading STOL aircraft

NASA Technical Reports Server (NTRS)

Komoda, M.

1976-01-01

An analytical study was made of an optimal gust alleviation system that employs a vertical gust sensor mounted forward of an aircraft's center of gravity. Frequency domain optimization techniques were employed to synthesize the optimal filters that process the corrective signals to the flaps and elevator actuators. Special attention was given to evaluating the effectiveness of lead time, that is, the time by which relative wind sensor information should lead the actual encounter of the gust. The resulting filter is expressed as an implicit function of the prescribed control cost. A numerical example for a light wing loading STOL aircraft is included in which the optimal trade-off between performance and control cost is systematically studied.

Construction of large signaling pathways using an adaptive perturbation approach with phosphoproteomic data.

PubMed

Melas, Ioannis N; Mitsos, Alexander; Messinis, Dimitris E; Weiss, Thomas S; Rodriguez, Julio-Saez; Alexopoulos, Leonidas G

2012-04-01

Construction of large and cell-specific signaling pathways is essential to understand information processing under normal and pathological conditions. On this front, gene-based approaches offer the advantage of large pathway exploration whereas phosphoproteomic approaches offer a more reliable view of pathway activities but are applicable to small pathway sizes. In this paper, we demonstrate an experimentally adaptive approach to construct large signaling pathways from phosphoproteomic data within a 3-day time frame. Our approach--taking advantage of the fast turnaround time of the xMAP technology--is carried out in four steps: (i) screen optimal pathway inducers, (ii) select the responsive ones, (iii) combine them in a combinatorial fashion to construct a phosphoproteomic dataset, and (iv) optimize a reduced generic pathway via an Integer Linear Programming formulation. As a case study, we uncover novel players and their corresponding pathways in primary human hepatocytes by interrogating the signal transduction downstream of 81 receptors of interest and constructing a detailed model for the responsive part of the network comprising 177 species (of which 14 are measured) and 365 interactions.

Fault feature extraction of planet gear in wind turbine gearbox based on spectral kurtosis and time wavelet energy spectrum

NASA Astrophysics Data System (ADS)

Kong, Yun; Wang, Tianyang; Li, Zheng; Chu, Fulei

2017-09-01

Planetary transmission plays a vital role in wind turbine drivetrains, and its fault diagnosis has been an important and challenging issue. Owing to the complicated and coupled vibration source, time-variant vibration transfer path, and heavy background noise masking effect, the vibration signal of planet gear in wind turbine gearboxes exhibits several unique characteristics: Complex frequency components, low signal-to-noise ratio, and weak fault feature. In this sense, the periodic impulsive components induced by a localized defect are hard to extract, and the fault detection of planet gear in wind turbines remains to be a challenging research work. Aiming to extract the fault feature of planet gear effectively, we propose a novel feature extraction method based on spectral kurtosis and time wavelet energy spectrum (SK-TWES) in the paper. Firstly, the spectral kurtosis (SK) and kurtogram of raw vibration signals are computed and exploited to select the optimal filtering parameter for the subsequent band-pass filtering. Then, the band-pass filtering is applied to extrude periodic transient impulses using the optimal frequency band in which the corresponding SK value is maximal. Finally, the time wavelet energy spectrum analysis is performed on the filtered signal, selecting Morlet wavelet as the mother wavelet which possesses a high similarity to the impulsive components. The experimental signals collected from the wind turbine gearbox test rig demonstrate that the proposed method is effective at the feature extraction and fault diagnosis for the planet gear with a localized defect.

Conditions for NIR fluorescence-guided tumor resectioning in preclinical lung cancer model (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kim, Minji; Quan, Yuhua; Choi, Byeong Hyun; Choi, Yeonho; Kim, Hyun Koo; Kim, Beop-Min

2016-03-01

Pulmonary nodule could be identified by intraoperative fluorescence imaging system from systemic injection of indocyanine green (ICG) which achieves enhanced permeability and retention (EPR) effects. This study was performed to evaluate optimal injection time of ICG for detecting cancer during surgery in rabbit lung cancer model. VX2 carcinoma cell was injected in rabbit lung under fluoroscopic computed tomography-guidance. Solitary lung cancer was confirmed on positron emitting tomography with CT (PET/CT) 2 weeks after inoculation. ICG was administered intravenously and fluorescent intensity of lung tumor was measured using the custom-built intraoperative color and fluorescence merged imaging system (ICFIS) for 15 hours. Solitary lung cancer was resected through thoracoscopic version of ICFIS. ICG was observed in all animals. Because Lung has fast blood pulmonary circulation, Fluorescent signal showed maximum intensity earlier than previous studies in other organs. Fluorescent intensity showed maximum intensity within 6-9 hours in rabbit lung cancer. Overall, Fluorescent intensity decreased with increasing time, however, all tumors were detectable using fluorescent images until 12 hours. In conclusion, while there had been studies in other organs showed that optimal injection time was at least 24 hours before operation, this study showed shorter optimal injection time at lung cancer. Since fluorescent signal showed the maximum intensity within 6-9 hours, cancer resection could be performed during this time. This data informed us that optimal injection time of ICG should be evaluated in each different solid organ tumor for fluorescent image guided surgery.

Heuristic and optimal policy computations in the human brain during sequential decision-making.

PubMed

Korn, Christoph W; Bach, Dominik R

2018-01-23

Optimal decisions across extended time horizons require value calculations over multiple probabilistic future states. Humans may circumvent such complex computations by resorting to easy-to-compute heuristics that approximate optimal solutions. To probe the potential interplay between heuristic and optimal computations, we develop a novel sequential decision-making task, framed as virtual foraging in which participants have to avoid virtual starvation. Rewards depend only on final outcomes over five-trial blocks, necessitating planning over five sequential decisions and probabilistic outcomes. Here, we report model comparisons demonstrating that participants primarily rely on the best available heuristic but also use the normatively optimal policy. FMRI signals in medial prefrontal cortex (MPFC) relate to heuristic and optimal policies and associated choice uncertainties. Crucially, reaction times and dorsal MPFC activity scale with discrepancies between heuristic and optimal policies. Thus, sequential decision-making in humans may emerge from integration between heuristic and optimal policies, implemented by controllers in MPFC.

Regulation of Dynamical Systems to Optimal Solutions of Semidefinite Programs: Algorithms and Applications to AC Optimal Power Flow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall'Anese, Emiliano; Dhople, Sairaj V.; Giannakis, Georgios B.

2015-07-01

This paper considers a collection of networked nonlinear dynamical systems, and addresses the synthesis of feedback controllers that seek optimal operating points corresponding to the solution of pertinent network-wide optimization problems. Particular emphasis is placed on the solution of semidefinite programs (SDPs). The design of the feedback controller is grounded on a dual e-subgradient approach, with the dual iterates utilized to dynamically update the dynamical-system reference signals. Global convergence is guaranteed for diminishing stepsize rules, even when the reference inputs are updated at a faster rate than the dynamical-system settling time. The application of the proposed framework to the controlmore » of power-electronic inverters in AC distribution systems is discussed. The objective is to bridge the time-scale separation between real-time inverter control and network-wide optimization. Optimization objectives assume the form of SDP relaxations of prototypical AC optimal power flow problems.« less

Controlling the high frequency response of H2 by ultra-short tailored laser pulses: A time-dependent configuration interaction study

NASA Astrophysics Data System (ADS)

Schönborn, Jan Boyke; Saalfrank, Peter; Klamroth, Tillmann

2016-01-01

We combine the stochastic pulse optimization (SPO) scheme with the time-dependent configuration interaction singles method in order to control the high frequency response of a simple molecular model system to a tailored femtosecond laser pulse. For this purpose, we use H2 treated in the fixed nuclei approximation. The SPO scheme, as similar genetic algorithms, is especially suited to control highly non-linear processes, which we consider here in the context of high harmonic generation. Here, we will demonstrate that SPO can be used to realize a "non-harmonic" response of H2 to a laser pulse. Specifically, we will show how adding low intensity side frequencies to the dominant carrier frequency of the laser pulse and stochastically optimizing their contribution can create a high-frequency spectral signal of significant intensity, not harmonic to the carrier frequency. At the same time, it is possible to suppress the harmonic signals in the same spectral region, although the carrier frequency is kept dominant during the optimization.

An Optimal Image-Based Method for Identification of Acoustic Emission (AE) Sources in Plate-Like Structures Using a Lead Zirconium Titanate (PZT) Sensor Array.

PubMed

Yan, Gang; Zhou, Li

2018-02-21

This paper proposes an innovative method for identifying the locations of multiple simultaneous acoustic emission (AE) events in plate-like structures from the view of image processing. By using a linear lead zirconium titanate (PZT) sensor array to record the AE wave signals, a reverse-time frequency-wavenumber (f-k) migration is employed to produce images displaying the locations of AE sources by back-propagating the AE waves. Lamb wave theory is included in the f-k migration to consider the dispersive property of the AE waves. Since the exact occurrence time of the AE events is usually unknown when recording the AE wave signals, a heuristic artificial bee colony (ABC) algorithm combined with an optimal criterion using minimum Shannon entropy is used to find the image with the identified AE source locations and occurrence time that mostly approximate the actual ones. Experimental studies on an aluminum plate with AE events simulated by PZT actuators are performed to validate the applicability and effectiveness of the proposed optimal image-based AE source identification method.

Controlling the high frequency response of H{sub 2} by ultra-short tailored laser pulses: A time-dependent configuration interaction study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schönborn, Jan Boyke; Saalfrank, Peter; Klamroth, Tillmann, E-mail: klamroth@uni-potsdam.de

2016-01-28

We combine the stochastic pulse optimization (SPO) scheme with the time-dependent configuration interaction singles method in order to control the high frequency response of a simple molecular model system to a tailored femtosecond laser pulse. For this purpose, we use H{sub 2} treated in the fixed nuclei approximation. The SPO scheme, as similar genetic algorithms, is especially suited to control highly non-linear processes, which we consider here in the context of high harmonic generation. Here, we will demonstrate that SPO can be used to realize a “non-harmonic” response of H{sub 2} to a laser pulse. Specifically, we will show howmore » adding low intensity side frequencies to the dominant carrier frequency of the laser pulse and stochastically optimizing their contribution can create a high-frequency spectral signal of significant intensity, not harmonic to the carrier frequency. At the same time, it is possible to suppress the harmonic signals in the same spectral region, although the carrier frequency is kept dominant during the optimization.« less

An Optimal Image-Based Method for Identification of Acoustic Emission (AE) Sources in Plate-Like Structures Using a Lead Zirconium Titanate (PZT) Sensor Array

PubMed Central

Zhou, Li

2018-01-01

This paper proposes an innovative method for identifying the locations of multiple simultaneous acoustic emission (AE) events in plate-like structures from the view of image processing. By using a linear lead zirconium titanate (PZT) sensor array to record the AE wave signals, a reverse-time frequency-wavenumber (f-k) migration is employed to produce images displaying the locations of AE sources by back-propagating the AE waves. Lamb wave theory is included in the f-k migration to consider the dispersive property of the AE waves. Since the exact occurrence time of the AE events is usually unknown when recording the AE wave signals, a heuristic artificial bee colony (ABC) algorithm combined with an optimal criterion using minimum Shannon entropy is used to find the image with the identified AE source locations and occurrence time that mostly approximate the actual ones. Experimental studies on an aluminum plate with AE events simulated by PZT actuators are performed to validate the applicability and effectiveness of the proposed optimal image-based AE source identification method. PMID:29466310

Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

NASA Astrophysics Data System (ADS)

Raskovic, Dejan

Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

A Novel Feature Optimization for Wearable Human-Computer Interfaces Using Surface Electromyography Sensors

PubMed Central

Zhang, Xiong; Zhao, Yacong; Zhang, Yu; Zhong, Xuefei; Fan, Zhaowen

2018-01-01

The novel human-computer interface (HCI) using bioelectrical signals as input is a valuable tool to improve the lives of people with disabilities. In this paper, surface electromyography (sEMG) signals induced by four classes of wrist movements were acquired from four sites on the lower arm with our designed system. Forty-two features were extracted from the time, frequency and time-frequency domains. Optimal channels were determined from single-channel classification performance rank. The optimal-feature selection was according to a modified entropy criteria (EC) and Fisher discrimination (FD) criteria. The feature selection results were evaluated by four different classifiers, and compared with other conventional feature subsets. In online tests, the wearable system acquired real-time sEMG signals. The selected features and trained classifier model were used to control a telecar through four different paradigms in a designed environment with simple obstacles. Performance was evaluated based on travel time (TT) and recognition rate (RR). The results of hardware evaluation verified the feasibility of our acquisition systems, and ensured signal quality. Single-channel analysis results indicated that the channel located on the extensor carpi ulnaris (ECU) performed best with mean classification accuracy of 97.45% for all movement’s pairs. Channels placed on ECU and the extensor carpi radialis (ECR) were selected according to the accuracy rank. Experimental results showed that the proposed FD method was better than other feature selection methods and single-type features. The combination of FD and random forest (RF) performed best in offline analysis, with 96.77% multi-class RR. Online results illustrated that the state-machine paradigm with a 125 ms window had the highest maneuverability and was closest to real-life control. Subjects could accomplish online sessions by three sEMG-based paradigms, with average times of 46.02, 49.06 and 48.08 s, respectively. These experiments validate the feasibility of proposed real-time wearable HCI system and algorithms, providing a potential assistive device interface for persons with disabilities. PMID:29543737

Error-based analysis of optimal tuning functions explains phenomena observed in sensory neurons.

PubMed

Yaeli, Steve; Meir, Ron

2010-01-01

Biological systems display impressive capabilities in effectively responding to environmental signals in real time. There is increasing evidence that organisms may indeed be employing near optimal Bayesian calculations in their decision-making. An intriguing question relates to the properties of optimal encoding methods, namely determining the properties of neural populations in sensory layers that optimize performance, subject to physiological constraints. Within an ecological theory of neural encoding/decoding, we show that optimal Bayesian performance requires neural adaptation which reflects environmental changes. Specifically, we predict that neuronal tuning functions possess an optimal width, which increases with prior uncertainty and environmental noise, and decreases with the decoding time window. Furthermore, even for static stimuli, we demonstrate that dynamic sensory tuning functions, acting at relatively short time scales, lead to improved performance. Interestingly, the narrowing of tuning functions as a function of time was recently observed in several biological systems. Such results set the stage for a functional theory which may explain the high reliability of sensory systems, and the utility of neuronal adaptation occurring at multiple time scales.

Data analysis of gravitational-wave signals from spinning neutron stars. III. Detection statistics and computational requirements

NASA Astrophysics Data System (ADS)

Jaranowski, Piotr; Królak, Andrzej

2000-03-01

We develop the analytic and numerical tools for data analysis of the continuous gravitational-wave signals from spinning neutron stars for ground-based laser interferometric detectors. The statistical data analysis method that we investigate is maximum likelihood detection which for the case of Gaussian noise reduces to matched filtering. We study in detail the statistical properties of the optimum functional that needs to be calculated in order to detect the gravitational-wave signal and estimate its parameters. We find it particularly useful to divide the parameter space into elementary cells such that the values of the optimal functional are statistically independent in different cells. We derive formulas for false alarm and detection probabilities both for the optimal and the suboptimal filters. We assess the computational requirements needed to do the signal search. We compare a number of criteria to build sufficiently accurate templates for our data analysis scheme. We verify the validity of our concepts and formulas by means of the Monte Carlo simulations. We present algorithms by which one can estimate the parameters of the continuous signals accurately. We find, confirming earlier work of other authors, that given a 100 Gflops computational power an all-sky search for observation time of 7 days and directed search for observation time of 120 days are possible whereas an all-sky search for 120 days of observation time is computationally prohibitive.

19F Magnetic resonance imaging of perfluorooctanoic acid encapsulated in liposome for biodistribution measurement.

PubMed

Kimura, Atsuomi; Narazaki, Michiko; Kanazawa, Yoko; Fujiwara, Hideaki

2004-07-01

The tissue distribution of perfluorooctanoic acid (PFOA), which is known to show unique biological responses, has been visualized in female mice by (19)F magnetic resonance imaging (MRI) incorporated with the recent advances in microimaging technique. The chemical shift selected fast spin-echo method was applied to acquire in vivo (19)F MR images of PFOA. The in vivo T(1) and T(2) relaxation times of PFOA were proven to be extremely short, which were 140 (+/- 20) ms and 6.3 (+/- 2.2) ms, respectively. To acquire the in vivo (19)F MR images of PFOA, it was necessary to optimize the parameters of signal selection and echo train length. The chemical shift selection was effectively performed by using the (19)F NMR signal of CF(3) group of PFOA without the signal overlapping because the chemical shift difference between the CF(3) and neighbor signals reaches to 14 kHz. The most optimal echo train length to obtain (19)F images efficiently was determined so that the maximum echo time (TE) value in the fast spin-echo sequence was comparable to the in vivo T(2) value. By optimizing these parameters, the in vivo (19)F MR image of PFOA was enabled to obtain efficiently in 12 minutes. As a result, the time course of the accumulation of PFOA into the mouse liver was clearly pursued in the (19)F MR images. Thus, it was concluded that the (19)F MRI becomes the effective method toward the future pharmacological and toxicological studies of perfluorocarboxilic acids.

Data compression and information retrieval via symbolization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, X.Z.; Tracy, E.R.

Converting a continuous signal into a multisymbol stream is a simple method of data compression which preserves much of the dynamical information present in the original signal. The retrieval of selected types of information from symbolic data involves binary operations and is therefore optimal for digital computers. For example, correlation time scales can be easily recovered, even at high noise levels, by varying the time delay for symbolization. Also, the presence of periodicity in the signal can be reliably detected even if it is weak and masked by a dominant chaotic/stochastic background. {copyright} {ital 1998 American Institute of Physics.}

PAPR-Constrained Pareto-Optimal Waveform Design for OFDM-STAP Radar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sen, Satyabrata

We propose a peak-to-average power ratio (PAPR) constrained Pareto-optimal waveform design approach for an orthogonal frequency division multiplexing (OFDM) radar signal to detect a target using the space-time adaptive processing (STAP) technique. The use of an OFDM signal does not only increase the frequency diversity of our system, but also enables us to adaptively design the OFDM coefficients in order to further improve the system performance. First, we develop a parametric OFDM-STAP measurement model by considering the effects of signaldependent clutter and colored noise. Then, we observe that the resulting STAP-performance can be improved by maximizing the output signal-to-interference-plus-noise ratiomore » (SINR) with respect to the signal parameters. However, in practical scenarios, the computation of output SINR depends on the estimated values of the spatial and temporal frequencies and target scattering responses. Therefore, we formulate a PAPR-constrained multi-objective optimization (MOO) problem to design the OFDM spectral parameters by simultaneously optimizing four objective functions: maximizing the output SINR, minimizing two separate Cramer-Rao bounds (CRBs) on the normalized spatial and temporal frequencies, and minimizing the trace of CRB matrix on the target scattering coefficients estimations. We present several numerical examples to demonstrate the achieved performance improvement due to the adaptive waveform design.« less

Signal and background considerations for the MRSt on the National Ignition Facility (NIF)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wink, C. W., E-mail: cwink@mit.edu; Frenje, J. A.; Gatu Johnson, M.

2016-11-15

A Magnetic Recoil Spectrometer (MRSt) has been conceptually designed for time-resolved measurements of the neutron spectrum at the National Ignition Facility. Using the MRSt, the goals are to measure the time-evolution of the spectrum with a time resolution of ∼20-ps and absolute accuracy better than 5%. To meet these goals, a detailed understanding and optimization of the signal and background characteristics are required. Through ion-optics, MCNP simulations, and detector-response calculations, it is demonstrated that the goals and a signal-to background >5–10 for the down-scattered neutron measurement are met if the background, consisting of ambient neutrons and gammas, at the MRStmore » is reduced 50–100 times.« less

Signal and background considerations for the MRSt on the National Ignition Facility (NIF)

DOE PAGES

Wink, C. W.; Frenje, J. A.; Hilsabeck, T. J.; ...

2016-08-03

A Magnetic Recoil Spectrometer (MRSt) has been conceptually designed for time-resolved measurements of the neutron spectrum at the National Ignition Facility. Using the MRSt, the goals are to measure the time-evolution of the spectrum with a time resolution of ~20-ps and absolute accuracy better than 5%. To meet these goals, a detailed understanding and optimization of the signal and background characteristics are required. Through ion-optics, MCNP simulations, and detector-response calculations, we demonstrate that the goals and a signal-to background >5-10 for the down-scattered neutron measurement are met if the background, consisting of ambient neutrons and gammas, at the MRSt ismore » reduced 50-100 times.« less

SNR Improvement of QEPAS System by Preamplifier Circuit Optimization and Frequency Locked Technique

NASA Astrophysics Data System (ADS)

Zhang, Qinduan; Chang, Jun; Wang, Zongliang; Wang, Fupeng; Jiang, Fengting; Wang, Mengyao

2018-06-01

Preamplifier circuit noise is of great importance in quartz enhanced photoacoustic spectroscopy (QEPAS) system. In this paper, several noise sources are evaluated and discussed in detail. Based on the noise characteristics, the corresponding noise reduction method is proposed. In addition, a frequency locked technique is introduced to further optimize the QEPAS system noise and improve signal, which achieves a better performance than the conventional frequency scan method. As a result, the signal-to-noise ratio (SNR) could be increased 14 times by utilizing frequency locked technique and numerical averaging technique in the QEPAS system for water vapor detection.

Alternatives to Pyrotechnic Distress Signals; Additional Signal Evaluation

DTIC Science & Technology

2017-06-01

conducted a series of laboratory experiments designed to determine the optimal signal color and temporal pattern for identification against a variety of...practice” trials at approximately 2030 local time and began the actual Test 1 observation trials at approximately 2130. The series of trials finished at...Lewandowski , 860-271-2692, email: M.J.Lewandowski@uscg.mil 16. Abstract (MAXIMUM 200 WORDS) This report is the fourth in a series that details work

A Space Affine Matching Approach to fMRI Time Series Analysis.

PubMed

Chen, Liang; Zhang, Weishi; Liu, Hongbo; Feng, Shigang; Chen, C L Philip; Wang, Huili

2016-07-01

For fMRI time series analysis, an important challenge is to overcome the potential delay between hemodynamic response signal and cognitive stimuli signal, namely the same frequency but different phase (SFDP) problem. In this paper, a novel space affine matching feature is presented by introducing the time domain and frequency domain features. The time domain feature is used to discern different stimuli, while the frequency domain feature to eliminate the delay. And then we propose a space affine matching (SAM) algorithm to match fMRI time series by our affine feature, in which a normal vector is estimated using gradient descent to explore the time series matching optimally. The experimental results illustrate that the SAM algorithm is insensitive to the delay between the hemodynamic response signal and the cognitive stimuli signal. Our approach significantly outperforms GLM method while there exists the delay. The approach can help us solve the SFDP problem in fMRI time series matching and thus of great promise to reveal brain dynamics.

Optimal Control for Aperiodic Dual-Rate Systems With Time-Varying Delays

PubMed Central

Salt, Julián; Guinaldo, María; Chacón, Jesús

2018-01-01

In this work, we consider a dual-rate scenario with slow input and fast output. Our objective is the maximization of the decay rate of the system through the suitable choice of the n-input signals between two measures (periodic sampling) and their times of application. The optimization algorithm is extended for time-varying delays in order to make possible its implementation in networked control systems. We provide experimental results in an air levitation system to verify the validity of the algorithm in a real plant. PMID:29747441

Optimal Control for Aperiodic Dual-Rate Systems With Time-Varying Delays.

PubMed

Aranda-Escolástico, Ernesto; Salt, Julián; Guinaldo, María; Chacón, Jesús; Dormido, Sebastián

2018-05-09

In this work, we consider a dual-rate scenario with slow input and fast output. Our objective is the maximization of the decay rate of the system through the suitable choice of the n -input signals between two measures (periodic sampling) and their times of application. The optimization algorithm is extended for time-varying delays in order to make possible its implementation in networked control systems. We provide experimental results in an air levitation system to verify the validity of the algorithm in a real plant.

Fuzzy logic control and optimization system

DOEpatents

Lou, Xinsheng [West Hartford, CT

2012-04-17

A control system (300) for optimizing a power plant includes a chemical loop having an input for receiving an input signal (369) and an output for outputting an output signal (367), and a hierarchical fuzzy control system (400) operably connected to the chemical loop. The hierarchical fuzzy control system (400) includes a plurality of fuzzy controllers (330). The hierarchical fuzzy control system (400) receives the output signal (367), optimizes the input signal (369) based on the received output signal (367), and outputs an optimized input signal (369) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.

Effect of Pulse Shape on Spall Strength

NASA Astrophysics Data System (ADS)

Smirnov, V. I.; Petrov, Yu. V.

2018-03-01

This paper analyzes the effect of the time-dependent shape of a load pulse on the spall strength of materials. Within the framework of a classical one-dimensional scheme, triangular pulses with signal rise and decay portions and with no signal rise portions considered. Calculation results for the threshold characteristics of fracture for rail steel are given. The possibility of optimization of fracture by selecting a loading time with the use of an introduced characteristic of dynamic strength (pulse fracture capacity) is demonstrated. The study is carried out using a structure-time fracture criterion.

Optimization of wide-angle seismic signal-to-noise ratios and P-wave transmission in Kenya

USGS Publications Warehouse

Jacob, A.W.B.; Vees, R.; Braile, L.W.; Criley, E.

1994-01-01

In previous refraction and wide-angle reflection experiments in the Kenya Rift there were problems with poor signal-noise ratios which made good seismic interpretation difficult. Careful planning and preparation for KRISP 90 has substantially overcome these problems and produced excellent seismic sections in a difficult environment. Noise levels were minimized by working, as far as possible, at times of the day when conditions were quiet, while source signals were optimized by using dispersed charges in water where it was available and waterfilled boreholes in most cases where it was not. Seismic coupling at optimum depth in water has been found to be more than 100 times greater than it is in a borehole in dry loosely compacted material. Allowing for the source coupling, a very marked difference has been found between the observation ranges in the rift and those on the flanks, where the observation ranges are greater. These appear to indicate a significant difference in seismic transmission through the two types of crust. ?? 1994.

The New Year Wave: Generation, Propagation, Kinematics and Dynamics - Registered in a Seakeeping Basin

NASA Astrophysics Data System (ADS)

Clauss, Günther; Klein, Marco

2010-05-01

In the past years the existence of freak waves has been affirmed by observations, registrations, and severe accidents. One of the famous real world registrations is the so called 'New Year wave,' recorded in the North Sea at the Draupner jacket platform on January 1st, 1995. Since there is only a single point registration available, it is not possible to draw conclusions on the spatial development in front of and behind the point of registration, which is indispensable for a complete understanding of this phenomenon. This paper presents the temporal and spatial development of the New Year Wave generated in a model basin. To simulate the recorded New Year wave in the wave tank, an optimization approach for the experimental generation of wave sequences with predefined characteristics is used. The method is applied to generate scenarios with a single high wave superimposed to irregular seas. During the experimental optimization special emphasis is laid on the exact reproduction of the wave height, crest height, wave period, as well as the vertical and horizontal asymmetries of the New Year Wave. The fully automated optimization process is carried out in a small wave tank. At the beginning of the optimization process, the scaled real-sea measured sea state is transformed back to the position of the piston type wave generator by means of linear wave theory and by multiplication with the electrical and hydrodynamic transfer functions in the frequency domain. As a result a preliminary control signal for the wave generator is obtained. Due to nonlinear effects in the wave tank, the registration of the freak wave at the target position generated by this preliminary control signal deviates from the predefined target parameters. To improve the target wave in the tank only a short section of the control signal in time domain has to be adapted. For these temporally limited local changes in the control signal, the discrete wavelet transformation is introduced into the optimization process which samples the signal into several decomposition levels where each resulting coefficient describes the control signal in a specific time range and frequency bandwidth. To improve the control signal, the experimental optimization routine iterates until the target parameters are satisfied by applying the subplex optimization method. The resulting control signal in the small wave tank is then transferred to a large wave tank considering the electrical and hydrodynamic RAOs of the respective wave generator. The extreme sea state with the embedded New Year Wave obtained with this method is measured at different locations in the tank, in a range from 2163 m (full scale) ahead of to 1470 m behind the target position-520 registrations altogether. The focus lies on the detailed description of a possible evolution of the New Year Wave over a large area and time interval. The analysis of the registrations reveals freak waves occurring at three different positions in the wave tank and the observed freak waves are developing from a wave group of three waves, which travels with constant speed along the wave tank up to the target position. The group velocity, wave propagation, and the energy flux of this wave group are analyzed within this paper.

Adaptive near-optimal neuro controller for continuous-time nonaffine nonlinear systems with constrained input.

PubMed

Esfandiari, Kasra; Abdollahi, Farzaneh; Talebi, Heidar Ali

2017-09-01

In this paper, an identifier-critic structure is introduced to find an online near-optimal controller for continuous-time nonaffine nonlinear systems having saturated control signal. By employing two Neural Networks (NNs), the solution of Hamilton-Jacobi-Bellman (HJB) equation associated with the cost function is derived without requiring a priori knowledge about system dynamics. Weights of the identifier and critic NNs are tuned online and simultaneously such that unknown terms are approximated accurately and the control signal is kept between the saturation bounds. The convergence of NNs' weights, identification error, and system states is guaranteed using Lyapunov's direct method. Finally, simulation results are performed on two nonlinear systems to confirm the effectiveness of the proposed control strategy. Copyright © 2017 Elsevier Ltd. All rights reserved.

RAPID COMMUNICATION: A novel time frequency-based 3D Lissajous figure method and its application to the determination of oxygen saturation from the photoplethysmogram

NASA Astrophysics Data System (ADS)

Addison, Paul S.; Watson, James N.

2004-11-01

We present a novel time-frequency method for the measurement of oxygen saturation using the photoplethysmogram (PPG) signals from a standard pulse oximeter machine. The method utilizes the time-frequency transformation of the red and infrared PPGs to derive a 3D Lissajous figure. By selecting the optimal Lissajous, the method provides an inherently robust basis for the determination of oxygen saturation as regions of the time-frequency plane where high- and low-frequency signal artefacts are to be found are automatically avoided.

Inferring neural activity from BOLD signals through nonlinear optimization.

PubMed

Vakorin, Vasily A; Krakovska, Olga O; Borowsky, Ron; Sarty, Gordon E

2007-11-01

The blood oxygen level-dependent (BOLD) fMRI signal does not measure neuronal activity directly. This fact is a key concern for interpreting functional imaging data based on BOLD. Mathematical models describing the path from neural activity to the BOLD response allow us to numerically solve the inverse problem of estimating the timing and amplitude of the neuronal activity underlying the BOLD signal. In fact, these models can be viewed as an advanced substitute for the impulse response function. In this work, the issue of estimating the dynamics of neuronal activity from the observed BOLD signal is considered within the framework of optimization problems. The model is based on the extended "balloon" model and describes the conversion of neuronal signals into the BOLD response through the transitional dynamics of the blood flow-inducing signal, cerebral blood flow, cerebral blood volume and deoxyhemoglobin concentration. Global optimization techniques are applied to find a control input (the neuronal activity and/or the biophysical parameters in the model) that causes the system to follow an admissible solution to minimize discrepancy between model and experimental data. As an alternative to a local linearization (LL) filtering scheme, the optimization method escapes the linearization of the transition system and provides a possibility to search for the global optimum, avoiding spurious local minima. We have found that the dynamics of the neural signals and the physiological variables as well as the biophysical parameters can be robustly reconstructed from the BOLD responses. Furthermore, it is shown that spiking off/on dynamics of the neural activity is the natural mathematical solution of the model. Incorporating, in addition, the expansion of the neural input by smooth basis functions, representing a low-pass filtering, allows us to model local field potential (LFP) solutions instead of spiking solutions.

A robust algorithm for optimisation and customisation of fractal dimensions of time series modified by nonlinearly scaling their time derivatives: mathematical theory and practical applications.

PubMed

Fuss, Franz Konstantin

2013-01-01

Standard methods for computing the fractal dimensions of time series are usually tested with continuous nowhere differentiable functions, but not benchmarked with actual signals. Therefore they can produce opposite results in extreme signals. These methods also use different scaling methods, that is, different amplitude multipliers, which makes it difficult to compare fractal dimensions obtained from different methods. The purpose of this research was to develop an optimisation method that computes the fractal dimension of a normalised (dimensionless) and modified time series signal with a robust algorithm and a running average method, and that maximises the difference between two fractal dimensions, for example, a minimum and a maximum one. The signal is modified by transforming its amplitude by a multiplier, which has a non-linear effect on the signal's time derivative. The optimisation method identifies the optimal multiplier of the normalised amplitude for targeted decision making based on fractal dimensions. The optimisation method provides an additional filter effect and makes the fractal dimensions less noisy. The method is exemplified by, and explained with, different signals, such as human movement, EEG, and acoustic signals.

A Robust Algorithm for Optimisation and Customisation of Fractal Dimensions of Time Series Modified by Nonlinearly Scaling Their Time Derivatives: Mathematical Theory and Practical Applications

PubMed Central

2013-01-01

Standard methods for computing the fractal dimensions of time series are usually tested with continuous nowhere differentiable functions, but not benchmarked with actual signals. Therefore they can produce opposite results in extreme signals. These methods also use different scaling methods, that is, different amplitude multipliers, which makes it difficult to compare fractal dimensions obtained from different methods. The purpose of this research was to develop an optimisation method that computes the fractal dimension of a normalised (dimensionless) and modified time series signal with a robust algorithm and a running average method, and that maximises the difference between two fractal dimensions, for example, a minimum and a maximum one. The signal is modified by transforming its amplitude by a multiplier, which has a non-linear effect on the signal's time derivative. The optimisation method identifies the optimal multiplier of the normalised amplitude for targeted decision making based on fractal dimensions. The optimisation method provides an additional filter effect and makes the fractal dimensions less noisy. The method is exemplified by, and explained with, different signals, such as human movement, EEG, and acoustic signals. PMID:24151522

Autaptic pacemaker mediated propagation of weak rhythmic activity across small-world neuronal networks

NASA Astrophysics Data System (ADS)

Yilmaz, Ergin; Baysal, Veli; Ozer, Mahmut; Perc, Matjaž

2016-02-01

We study the effects of an autapse, which is mathematically described as a self-feedback loop, on the propagation of weak, localized pacemaker activity across a Newman-Watts small-world network consisting of stochastic Hodgkin-Huxley neurons. We consider that only the pacemaker neuron, which is stimulated by a subthreshold periodic signal, has an electrical autapse that is characterized by a coupling strength and a delay time. We focus on the impact of the coupling strength, the network structure, the properties of the weak periodic stimulus, and the properties of the autapse on the transmission of localized pacemaker activity. Obtained results indicate the existence of optimal channel noise intensity for the propagation of the localized rhythm. Under optimal conditions, the autapse can significantly improve the propagation of pacemaker activity, but only for a specific range of the autaptic coupling strength. Moreover, the autaptic delay time has to be equal to the intrinsic oscillation period of the Hodgkin-Huxley neuron or its integer multiples. We analyze the inter-spike interval histogram and show that the autapse enhances or suppresses the propagation of the localized rhythm by increasing or decreasing the phase locking between the spiking of the pacemaker neuron and the weak periodic signal. In particular, when the autaptic delay time is equal to the intrinsic period of oscillations an optimal phase locking takes place, resulting in a dominant time scale of the spiking activity. We also investigate the effects of the network structure and the coupling strength on the propagation of pacemaker activity. We find that there exist an optimal coupling strength and an optimal network structure that together warrant an optimal propagation of the localized rhythm.

Focusing of light through turbid media by curve fitting optimization

NASA Astrophysics Data System (ADS)

Gong, Changmei; Wu, Tengfei; Liu, Jietao; Li, Huijuan; Shao, Xiaopeng; Zhang, Jianqi

2016-12-01

The construction of wavefront phase plays a critical role in focusing light through turbid media. We introduce the curve fitting algorithm (CFA) into the feedback control procedure for wavefront optimization. Unlike the existing continuous sequential algorithm (CSA), the CFA locates the optimal phase by fitting a curve to the measured signals. Simulation results show that, similar to the genetic algorithm (GA), the proposed CFA technique is far less susceptible to the experimental noise than the CSA. Furthermore, only three measurements of feedback signals are enough for CFA to fit the optimal phase while obtaining a higher focal intensity than the CSA and the GA, dramatically shortening the optimization time by a factor of 3 compared with the CSA and the GA. The proposed CFA approach can be applied to enhance the focus intensity and boost the focusing speed in the fields of biological imaging, particle trapping, laser therapy, and so on, and might help to focus light through dynamic turbid media.

Correcting for Blood Arrival Time in Global Mean Regression Enhances Functional Connectivity Analysis of Resting State fMRI-BOLD Signals.

PubMed

Erdoğan, Sinem B; Tong, Yunjie; Hocke, Lia M; Lindsey, Kimberly P; deB Frederick, Blaise

2016-01-01

Resting state functional connectivity analysis is a widely used method for mapping intrinsic functional organization of the brain. Global signal regression (GSR) is commonly employed for removing systemic global variance from resting state BOLD-fMRI data; however, recent studies have demonstrated that GSR may introduce spurious negative correlations within and between functional networks, calling into question the meaning of anticorrelations reported between some networks. In the present study, we propose that global signal from resting state fMRI is composed primarily of systemic low frequency oscillations (sLFOs) that propagate with cerebral blood circulation throughout the brain. We introduce a novel systemic noise removal strategy for resting state fMRI data, "dynamic global signal regression" (dGSR), which applies a voxel-specific optimal time delay to the global signal prior to regression from voxel-wise time series. We test our hypothesis on two functional systems that are suggested to be intrinsically organized into anticorrelated networks: the default mode network (DMN) and task positive network (TPN). We evaluate the efficacy of dGSR and compare its performance with the conventional "static" global regression (sGSR) method in terms of (i) explaining systemic variance in the data and (ii) enhancing specificity and sensitivity of functional connectivity measures. dGSR increases the amount of BOLD signal variance being modeled and removed relative to sGSR while reducing spurious negative correlations introduced in reference regions by sGSR, and attenuating inflated positive connectivity measures. We conclude that incorporating time delay information for sLFOs into global noise removal strategies is of crucial importance for optimal noise removal from resting state functional connectivity maps.

Quantification of glutathione transverse relaxation time T2 using echo time extension with variable refocusing selectivity and symmetry in the human brain at 7 Tesla

NASA Astrophysics Data System (ADS)

Swanberg, Kelley M.; Prinsen, Hetty; Coman, Daniel; de Graaf, Robin A.; Juchem, Christoph

2018-05-01

Glutathione (GSH) is an endogenous antioxidant implicated in numerous biological processes, including those associated with multiple sclerosis, aging, and cancer. Spectral editing techniques have greatly facilitated the acquisition of glutathione signal in living humans via proton magnetic resonance spectroscopy, but signal quantification at 7 Tesla is still hampered by uncertainty about the glutathione transverse decay rate T2 relative to those of commonly employed quantitative references like N-acetyl aspartate (NAA), total creatine, or water. While the T2 of uncoupled singlets can be derived in a straightforward manner from exponential signal decay as a function of echo time, similar estimation of signal decay in GSH is complicated by a spin system that involves both weak and strong J-couplings as well as resonances that overlap those of several other metabolites and macromolecules. Here, we extend a previously published method for quantifying the T2 of GABA, a weakly coupled system, to quantify T2 of the strongly coupled spin system glutathione in the human brain at 7 Tesla. Using full density matrix simulation of glutathione signal behavior, we selected an array of eight optimized echo times between 72 and 322 ms for glutathione signal acquisition by J-difference editing (JDE). We varied the selectivity and symmetry parameters of the inversion pulses used for echo time extension to further optimize the intensity, simplicity, and distinctiveness of glutathione signals at chosen echo times. Pairs of selective adiabatic inversion pulses replaced nonselective pulses at three extended echo times, and symmetry of the time intervals between the two extension pulses was adjusted at one extended echo time to compensate for J-modulation, thereby resulting in appreciable signal-to-noise ratio and quantifiable signal shapes at all measured points. Glutathione signal across all echo times fit smooth monoexponential curves over ten scans of occipital cortex voxels in nine subjects. The T2 of glutathione was calculated to be 145.0 ± 20.1 ms (mean ± standard deviation); this result was robust within one standard deviation to changes in metabolite fitting baseline corrections and removal of individual data points on the signal decay curve. The measured T2 of NAA (222.1 ± 24.7 ms) and total creatine (153.0 ± 19.9 ms) were both higher than that calculated for GSH. Apparent glutathione concentration quantified relative to both reference metabolites increased by up to 32% and 6%, respectively, upon correction with calculated T2 values, emphasizing the importance of considering T2 relaxation differences in the spectroscopic measurement of these metabolites, especially at longer echo times.

Quantification of glutathione transverse relaxation time T2 using echo time extension with variable refocusing selectivity and symmetry in the human brain at 7 Tesla.

PubMed

Swanberg, Kelley M; Prinsen, Hetty; Coman, Daniel; de Graaf, Robin A; Juchem, Christoph

2018-05-01

Glutathione (GSH) is an endogenous antioxidant implicated in numerous biological processes, including those associated with multiple sclerosis, aging, and cancer. Spectral editing techniques have greatly facilitated the acquisition of glutathione signal in living humans via proton magnetic resonance spectroscopy, but signal quantification at 7 Tesla is still hampered by uncertainty about the glutathione transverse decay rate T 2 relative to those of commonly employed quantitative references like N-acetyl aspartate (NAA), total creatine, or water. While the T 2 of uncoupled singlets can be derived in a straightforward manner from exponential signal decay as a function of echo time, similar estimation of signal decay in GSH is complicated by a spin system that involves both weak and strong J-couplings as well as resonances that overlap those of several other metabolites and macromolecules. Here, we extend a previously published method for quantifying the T 2 of GABA, a weakly coupled system, to quantify T 2 of the strongly coupled spin system glutathione in the human brain at 7 Tesla. Using full density matrix simulation of glutathione signal behavior, we selected an array of eight optimized echo times between 72 and 322 ms for glutathione signal acquisition by J-difference editing (JDE). We varied the selectivity and symmetry parameters of the inversion pulses used for echo time extension to further optimize the intensity, simplicity, and distinctiveness of glutathione signals at chosen echo times. Pairs of selective adiabatic inversion pulses replaced nonselective pulses at three extended echo times, and symmetry of the time intervals between the two extension pulses was adjusted at one extended echo time to compensate for J-modulation, thereby resulting in appreciable signal-to-noise ratio and quantifiable signal shapes at all measured points. Glutathione signal across all echo times fit smooth monoexponential curves over ten scans of occipital cortex voxels in nine subjects. The T 2 of glutathione was calculated to be 145.0 ± 20.1 ms (mean ± standard deviation); this result was robust within one standard deviation to changes in metabolite fitting baseline corrections and removal of individual data points on the signal decay curve. The measured T 2 of NAA (222.1 ± 24.7 ms) and total creatine (153.0 ± 19.9 ms) were both higher than that calculated for GSH. Apparent glutathione concentration quantified relative to both reference metabolites increased by up to 32% and 6%, respectively, upon correction with calculated T 2 values, emphasizing the importance of considering T 2 relaxation differences in the spectroscopic measurement of these metabolites, especially at longer echo times. Copyright © 2018 Elsevier Inc. All rights reserved.

Sliding window denoising K-Singular Value Decomposition and its application on rolling bearing impact fault diagnosis

NASA Astrophysics Data System (ADS)

Yang, Honggang; Lin, Huibin; Ding, Kang

2018-05-01

The performance of sparse features extraction by commonly used K-Singular Value Decomposition (K-SVD) method depends largely on the signal segment selected in rolling bearing diagnosis, furthermore, the calculating speed is relatively slow and the dictionary becomes so redundant when the fault signal is relatively long. A new sliding window denoising K-SVD (SWD-KSVD) method is proposed, which uses only one small segment of time domain signal containing impacts to perform sliding window dictionary learning and select an optimal pattern with oscillating information of the rolling bearing fault according to a maximum variance principle. An inner product operation between the optimal pattern and the whole fault signal is performed to enhance the characteristic of the impacts' occurrence moments. Lastly, the signal is reconstructed at peak points of the inner product to realize the extraction of the rolling bearing fault features. Both simulation and experiments verify that the method could extract the fault features effectively.

Real Time Phase Noise Meter Based on a Digital Signal Processor

NASA Technical Reports Server (NTRS)

Angrisani, Leopoldo; D'Arco, Mauro; Greenhall, Charles A.; Schiano Lo Morille, Rosario

2006-01-01

A digital signal-processing meter for phase noise measurement on sinusoidal signals is dealt with. It enlists a special hardware architecture, made up of a core digital signal processor connected to a data acquisition board, and takes advantage of a quadrature demodulation-based measurement scheme, already proposed by the authors. Thanks to an efficient measurement process and an optimized implementation of its fundamental stages, the proposed meter succeeds in exploiting all hardware resources in such an effective way as to gain high performance and real-time operation. For input frequencies up to some hundreds of kilohertz, the meter is capable both of updating phase noise power spectrum while seamlessly capturing the analyzed signal into its memory, and granting as good frequency resolution as few units of hertz.

Optimization of spin-torque switching using AC and DC pulses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dunn, Tom; Kamenev, Alex; Fine Theoretical Physics Institute, University of Minnesota, Minneapolis, Minnesota 55455

2014-06-21

We explore spin-torque induced magnetic reversal in magnetic tunnel junctions using combined AC and DC spin-current pulses. We calculate the optimal pulse times and current strengths for both AC and DC pulses as well as the optimal AC signal frequency, needed to minimize the Joule heat lost during the switching process. The results of this optimization are compared against numeric simulations. Finally, we show how this optimization leads to different dynamic regimes, where switching is optimized by either a purely AC or DC spin-current, or a combination AC/DC spin-current, depending on the anisotropy energies and the spin-current polarization.

Detection of epileptiform activity in EEG signals based on time-frequency and non-linear analysis

PubMed Central

Gajic, Dragoljub; Djurovic, Zeljko; Gligorijevic, Jovan; Di Gennaro, Stefano; Savic-Gajic, Ivana

2015-01-01

We present a new technique for detection of epileptiform activity in EEG signals. After preprocessing of EEG signals we extract representative features in time, frequency and time-frequency domain as well as using non-linear analysis. The features are extracted in a few frequency sub-bands of clinical interest since these sub-bands showed much better discriminatory characteristics compared with the whole frequency band. Then we optimally reduce the dimension of feature space to two using scatter matrices. A decision about the presence of epileptiform activity in EEG signals is made by quadratic classifiers designed in the reduced two-dimensional feature space. The accuracy of the technique was tested on three sets of electroencephalographic (EEG) signals recorded at the University Hospital Bonn: surface EEG signals from healthy volunteers, intracranial EEG signals from the epilepsy patients during the seizure free interval from within the seizure focus and intracranial EEG signals of epileptic seizures also from within the seizure focus. An overall detection accuracy of 98.7% was achieved. PMID:25852534

Parallel optimization of signal detection in active magnetospheric signal injection experiments

NASA Astrophysics Data System (ADS)

Gowanlock, Michael; Li, Justin D.; Rude, Cody M.; Pankratius, Victor

2018-05-01

Signal detection and extraction requires substantial manual parameter tuning at different stages in the processing pipeline. Time-series data depends on domain-specific signal properties, necessitating unique parameter selection for a given problem. The large potential search space makes this parameter selection process time-consuming and subject to variability. We introduce a technique to search and prune such parameter search spaces in parallel and select parameters for time series filters using breadth- and depth-first search strategies to increase the likelihood of detecting signals of interest in the field of magnetospheric physics. We focus on studying geomagnetic activity in the extremely and very low frequency ranges (ELF/VLF) using ELF/VLF transmissions from Siple Station, Antarctica, received at Québec, Canada. Our technique successfully detects amplified transmissions and achieves substantial speedup performance gains as compared to an exhaustive parameter search. We present examples where our algorithmic approach reduces the search from hundreds of seconds down to less than 1 s, with a ranked signal detection in the top 99th percentile, thus making it valuable for real-time monitoring. We also present empirical performance models quantifying the trade-off between the quality of signal recovered and the algorithm response time required for signal extraction. In the future, improved signal extraction in scenarios like the Siple experiment will enable better real-time diagnostics of conditions of the Earth's magnetosphere for monitoring space weather activity.

Influence of infectious disease seasonality on the performance of the outbreak detection algorithm in the China Infectious Disease Automated-alert and Response System

PubMed Central

Wang, Ruiping; Jiang, Yonggen; Guo, Xiaoqin; Wu, Yiling; Zhao, Genming

2017-01-01

Objective The Chinese Center for Disease Control and Prevention developed the China Infectious Disease Automated-alert and Response System (CIDARS) in 2008. The CIDARS can detect outbreak signals in a timely manner but generates many false-positive signals, especially for diseases with seasonality. We assessed the influence of seasonality on infectious disease outbreak detection performance. Methods Chickenpox surveillance data in Songjiang District, Shanghai were used. The optimized early alert thresholds for chickenpox were selected according to three algorithm evaluation indexes: sensitivity (Se), false alarm rate (FAR), and time to detection (TTD). Performance of selected proper thresholds was assessed by data external to the study period. Results The optimized early alert threshold for chickenpox during the epidemic season was the percentile P65, which demonstrated an Se of 93.33%, FAR of 0%, and TTD of 0 days. The optimized early alert threshold in the nonepidemic season was P50, demonstrating an Se of 100%, FAR of 18.94%, and TTD was 2.5 days. The performance evaluation demonstrated that the use of an optimized threshold adjusted for seasonality could reduce the FAR and shorten the TTD. Conclusions Selection of optimized early alert thresholds based on local infectious disease seasonality could improve the performance of the CIDARS. PMID:28728470

Influence of infectious disease seasonality on the performance of the outbreak detection algorithm in the China Infectious Disease Automated-alert and Response System.

PubMed

Wang, Ruiping; Jiang, Yonggen; Guo, Xiaoqin; Wu, Yiling; Zhao, Genming

2018-01-01

Objective The Chinese Center for Disease Control and Prevention developed the China Infectious Disease Automated-alert and Response System (CIDARS) in 2008. The CIDARS can detect outbreak signals in a timely manner but generates many false-positive signals, especially for diseases with seasonality. We assessed the influence of seasonality on infectious disease outbreak detection performance. Methods Chickenpox surveillance data in Songjiang District, Shanghai were used. The optimized early alert thresholds for chickenpox were selected according to three algorithm evaluation indexes: sensitivity (Se), false alarm rate (FAR), and time to detection (TTD). Performance of selected proper thresholds was assessed by data external to the study period. Results The optimized early alert threshold for chickenpox during the epidemic season was the percentile P65, which demonstrated an Se of 93.33%, FAR of 0%, and TTD of 0 days. The optimized early alert threshold in the nonepidemic season was P50, demonstrating an Se of 100%, FAR of 18.94%, and TTD was 2.5 days. The performance evaluation demonstrated that the use of an optimized threshold adjusted for seasonality could reduce the FAR and shorten the TTD. Conclusions Selection of optimized early alert thresholds based on local infectious disease seasonality could improve the performance of the CIDARS.

Adaptive filtering in biological signal processing.

PubMed

Iyer, V K; Ploysongsang, Y; Ramamoorthy, P A

1990-01-01

The high dependence of conventional optimal filtering methods on the a priori knowledge of the signal and noise statistics render them ineffective in dealing with signals whose statistics cannot be predetermined accurately. Adaptive filtering methods offer a better alternative, since the a priori knowledge of statistics is less critical, real time processing is possible, and the computations are less expensive for this approach. Adaptive filtering methods compute the filter coefficients "on-line", converging to the optimal values in the least-mean square (LMS) error sense. Adaptive filtering is therefore apt for dealing with the "unknown" statistics situation and has been applied extensively in areas like communication, speech, radar, sonar, seismology, and biological signal processing and analysis for channel equalization, interference and echo canceling, line enhancement, signal detection, system identification, spectral analysis, beamforming, modeling, control, etc. In this review article adaptive filtering in the context of biological signals is reviewed. An intuitive approach to the underlying theory of adaptive filters and its applicability are presented. Applications of the principles in biological signal processing are discussed in a manner that brings out the key ideas involved. Current and potential future directions in adaptive biological signal processing are also discussed.

Producing >60,000-fold room-temperature 89Y NMR signal enhancement

NASA Astrophysics Data System (ADS)

Lumata, Lloyd; Jindal, Ashish; Merritt, Matthew; Malloy, Craig; Sherry, A. Dean; Kovacs, Zoltan

2011-03-01

89 Y in chelated form is potentially valuable in medical imaging because its chemical shift is sensitive to local factors in tumors such as pH. However, 89 Y has a low gyromagnetic ratio γn thus its NMR signal is hampered by low thermal polarization. Here we show that we can enhance the room-temperature NMR signal of 89 Y up to 65,000 times the thermal signal, which corresponds to 10 % nuclear polarization, via fast dissolution dynamic nuclear polarization (DNP). The relatively long spin-lattice relaxation time T1 (~ 500 s) of 89 Y translates to a long polarization lifetime. The 89 Y NMR enhancement is optimized by varying the glassing matrices and paramagnetic agents as well as doping the samples with a gadolinium relaxation agent. Co-polarization of 89 Y-DOTA with a 13 C sample shows that both nuclear spin species acquire the same spin temperature Ts , consistent with thermal mixing mechanism of DNP. The high room-temperature NMR signal enhancement places 89 Y, one of the most challenging nuclei to detect by NMR, in the list of viable magnetic resonance imaging (MRI) agents when hyperpolarized under optimized conditions. This work is supported in part by the National Institutes of Health grant numbers 1R21EB009147-01 and RR02584.

Characteristics of official and experimental GRACE time series by GFZ and CSR - with applications to polar signals

NASA Astrophysics Data System (ADS)

Horvath, Alexander; Horwath, Martin; Pail, Roland

2014-05-01

The Release-05 monthly solutions by the three centers of the GRACE Science and Data System are a significant improvement with respect to the previous Release 4. Meanwhile, previous assessments have revealed different noise levels between the solutions by CSR, GFZ and JPL, and also different amplitudes of interannual signal in the solutions by GFZ as compared to the two other centers. Encouraged by the science community, GFZ and CSR have kindly provided additional sets of time series. GFZ has reprocessed the RL05 monthly solutions (up to degree and order 90) with revised processing. CSR has made available monthly solutions with standard processing up to degree and order 96, in addition to their solutions up to degree and order 60. We compare these different time series with respect to their signal and noise content and analyze them on global and regional scale. For the regional scale our special interest is paid on Antarctica and on revealing polar signals such as ice mass trends and GIA. Following the necessity of destriping, an optimal choice for the setup of the Swenson & Wahr filter approach is evaluated to adapt to the specific signal and noise level in Antarctica. Furthermore we analyze the potential benefit of mixed time series solutions in order to combine the strengths of the solutions available. Concerning the question for an optimal maximum degree we suggest that for resolving large polar ice mass changes, it would be beneficial to provide gravity field variations even beyond degree 90.

Developing Fast Fluorescent Protein Voltage Sensors by Optimizing FRET Interactions

PubMed Central

Sung, Uhna; Sepehri-Rad, Masoud; Piao, Hong Hua; Jin, Lei; Hughes, Thomas; Cohen, Lawrence B.; Baker, Bradley J.

2015-01-01

FRET (Förster Resonance Energy Transfer)-based protein voltage sensors can be useful for monitoring neuronal activity in vivo because the ratio of signals between the donor and acceptor pair reduces common sources of noise such as heart beat artifacts. We improved the performance of FRET based genetically encoded Fluorescent Protein (FP) voltage sensors by optimizing the location of donor and acceptor FPs flanking the voltage sensitive domain of the Ciona intestinalis voltage sensitive phosphatase. First, we created 39 different “Nabi1” constructs by positioning the donor FP, UKG, at 8 different locations downstream of the voltage-sensing domain and the acceptor FP, mKO, at 6 positions upstream. Several of these combinations resulted in large voltage dependent signals and relatively fast kinetics. Nabi1 probes responded with signal size up to 11% ΔF/F for a 100 mV depolarization and fast response time constants both for signal activation (~2 ms) and signal decay (~3 ms). We improved expression in neuronal cells by replacing the mKO and UKG FRET pair with Clover (donor FP) and mRuby2 (acceptor FP) to create Nabi2 probes. Nabi2 probes also had large signals and relatively fast time constants in HEK293 cells. In primary neuronal culture, a Nabi2 probe was able to differentiate individual action potentials at 45 Hz. PMID:26587834

Optimization of a double inversion recovery sequence for noninvasive synovium imaging of joint effusion in the knee.

PubMed

Jahng, Geon-Ho; Jin, Wook; Yang, Dal Mo; Ryu, Kyung Nam

2011-05-01

We wanted to optimize a double inversion recovery (DIR) sequence to image joint effusion regions of the knee, especially intracapsular or intrasynovial imaging in the suprapatellar bursa and patellofemoral joint space. Computer simulations were performed to determine the optimum inversion times (TI) for suppressing both fat and water signals, and a DIR sequence was optimized based on the simulations for distinguishing synovitis from fluid. In vivo studies were also performed on individuals who showed joint effusion on routine knee MR images to demonstrate the feasibility of using the DIR sequence with a 3T whole-body MR scanner. To compare intracapsular or intrasynovial signals on the DIR images, intermediate density-weighted images and/or post-enhanced T1-weighted images were acquired. The timings to enhance the synovial contrast from the fluid components were TI1 = 2830 ms and TI2 = 254 ms for suppressing the water and fat signals, respectively. Improved contrast for the intrasynovial area in the knees was observed with the DIR turbo spin-echo pulse sequence compared to the intermediate density-weighted sequence. Imaging contrast obtained noninvasively with the DIR sequence was similar to that of the post-enhanced T1-weighted sequence. The DIR sequence may be useful for delineating synovium without using contrast materials.

Data mining for water resource management part 2 - methods and approaches to solving contemporary problems

USGS Publications Warehouse

Roehl, Edwin A.; Conrads, Paul

2010-01-01

This is the second of two papers that describe how data mining can aid natural-resource managers with the difficult problem of controlling the interactions between hydrologic and man-made systems. Data mining is a new science that assists scientists in converting large databases into knowledge, and is uniquely able to leverage the large amounts of real-time, multivariate data now being collected for hydrologic systems. Part 1 gives a high-level overview of data mining, and describes several applications that have addressed major water resource issues in South Carolina. This Part 2 paper describes how various data mining methods are integrated to produce predictive models for controlling surface- and groundwater hydraulics and quality. The methods include: - signal processing to remove noise and decompose complex signals into simpler components; - time series clustering that optimally groups hundreds of signals into "classes" that behave similarly for data reduction and (or) divide-and-conquer problem solving; - classification which optimally matches new data to behavioral classes; - artificial neural networks which optimally fit multivariate data to create predictive models; - model response surface visualization that greatly aids in understanding data and physical processes; and, - decision support systems that integrate data, models, and graphics into a single package that is easy to use.

Increased bioassay sensitivity of bioactive molecule discovery using metal-enhanced bioluminescence

NASA Astrophysics Data System (ADS)

Golberg, Karina; Elbaz, Amit; McNeil, Ronald; Kushmaro, Ariel; Geddes, Chris D.; Marks, Robert S.

2014-12-01

We report the use of bioluminescence signal enhancement via proximity to deposited silver nanoparticles for bioactive compound discovery. This approach employs a whole-cell bioreporter harboring a plasmid-borne fusion of a specific promoter incorporated with a bioluminescence reporter gene. The silver deposition process was first optimized to provide optimal nanoparticle size in the reaction time dependence with fluorescein. The use of silver deposition of 350 nm particles enabled the doubling of the bioluminescent signal amplitude by the bacterial bioreporter when compared to an untouched non-silver-deposited microtiter plate surface. This recording is carried out in the less optimal but necessary far-field distance. SEM micrographs provided a visualization of the proximity of the bioreporter to the silver nanoparticles. The electromagnetic field distributions around the nanoparticles were simulated using Finite Difference Time Domain, further suggesting a re-excitation of non-chemically excited bioluminescence in addition to metal-enhanced bioluminescence. The possibility of an antiseptic silver effect caused by such a close proximity was eliminated disregarded by the dynamic growth curves of the bioreporter strains as seen using viability staining. As a highly attractive biotechnology tool, this silver deposition technique, coupled with whole-cell sensing, enables increased bioluminescence sensitivity, making it especially useful for cases in which reporter luminescence signals are very weak.

Optimal wavelets for biomedical signal compression.

PubMed

Nielsen, Mogens; Kamavuako, Ernest Nlandu; Andersen, Michael Midtgaard; Lucas, Marie-Françoise; Farina, Dario

2006-07-01

Signal compression is gaining importance in biomedical engineering due to the potential applications in telemedicine. In this work, we propose a novel scheme of signal compression based on signal-dependent wavelets. To adapt the mother wavelet to the signal for the purpose of compression, it is necessary to define (1) a family of wavelets that depend on a set of parameters and (2) a quality criterion for wavelet selection (i.e., wavelet parameter optimization). We propose the use of an unconstrained parameterization of the wavelet for wavelet optimization. A natural performance criterion for compression is the minimization of the signal distortion rate given the desired compression rate. For coding the wavelet coefficients, we adopted the embedded zerotree wavelet coding algorithm, although any coding scheme may be used with the proposed wavelet optimization. As a representative example of application, the coding/encoding scheme was applied to surface electromyographic signals recorded from ten subjects. The distortion rate strongly depended on the mother wavelet (for example, for 50% compression rate, optimal wavelet, mean+/-SD, 5.46+/-1.01%; worst wavelet 12.76+/-2.73%). Thus, optimization significantly improved performance with respect to previous approaches based on classic wavelets. The algorithm can be applied to any signal type since the optimal wavelet is selected on a signal-by-signal basis. Examples of application to ECG and EEG signals are also reported.

Reversals and collisions optimize protein exchange in bacterial swarms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amiri, Aboutaleb; Harvey, Cameron; Buchmann, Amy

Swarming groups of bacteria coordinate their behavior by self-organizing as a population to move over surfaces in search of nutrients and optimal niches for colonization. Many open questions remain about the cues used by swarming bacteria to achieve this self-organization. While chemical cue signaling known as quorum sensing is well-described, swarming bacteria often act and coordinate on time scales that could not be achieved via these extracellular quorum sensing cues. Here, cell-cell contact-dependent protein exchange is explored as amechanism of intercellular signaling for the bacterium Myxococcus xanthus. A detailed biologically calibrated computational model is used to study how M. xanthusmore » optimizes the connection rate between cells and maximizes the spread of an extracellular protein within the population. The maximum rate of protein spreading is observed for cells that reverse direction optimally for swarming. Cells that reverse too slowly or too fast fail to spread extracellular protein efficiently. In particular, a specific range of cell reversal frequencies was observed to maximize the cell-cell connection rate and minimize the time of protein spreading. Furthermore, our findings suggest that predesigned motion reversal can be employed to enhance the collective behavior of biological synthetic active systems.« less

Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design.

PubMed

Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

2018-04-01

This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.

An Evaluation of Signal Annoyance for a Head-Mounted Tactile Display

DTIC Science & Technology

2015-03-01

the burden, to Department of Defense , Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215... the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the ...be used on the finger, torso, and arm, and currently, vibrotactile signals are optimized for use on those areas. Thus, integrating BC

Resource allocation for error resilient video coding over AWGN using optimization approach.

PubMed

An, Cheolhong; Nguyen, Truong Q

2008-12-01

The number of slices for error resilient video coding is jointly optimized with 802.11a-like media access control and the physical layers with automatic repeat request and rate compatible punctured convolutional code over additive white gaussian noise channel as well as channel times allocation for time division multiple access. For error resilient video coding, the relation between the number of slices and coding efficiency is analyzed and formulated as a mathematical model. It is applied for the joint optimization problem, and the problem is solved by a convex optimization method such as the primal-dual decomposition method. We compare the performance of a video communication system which uses the optimal number of slices with one that codes a picture as one slice. From numerical examples, end-to-end distortion of utility functions can be significantly reduced with the optimal slices of a picture especially at low signal-to-noise ratio.

On optimal infinite impulse response edge detection filters

NASA Technical Reports Server (NTRS)

Sarkar, Sudeep; Boyer, Kim L.

1991-01-01

The authors outline the design of an optimal, computationally efficient, infinite impulse response edge detection filter. The optimal filter is computed based on Canny's high signal to noise ratio, good localization criteria, and a criterion on the spurious response of the filter to noise. An expression for the width of the filter, which is appropriate for infinite-length filters, is incorporated directly in the expression for spurious responses. The three criteria are maximized using the variational method and nonlinear constrained optimization. The optimal filter parameters are tabulated for various values of the filter performance criteria. A complete methodology for implementing the optimal filter using approximating recursive digital filtering is presented. The approximating recursive digital filter is separable into two linear filters operating in two orthogonal directions. The implementation is very simple and computationally efficient, has a constant time of execution for different sizes of the operator, and is readily amenable to real-time hardware implementation.

Optimizing signal recycling for detecting a stochastic gravitational-wave background

NASA Astrophysics Data System (ADS)

Tao, Duo; Christensen, Nelson

2018-06-01

Signal recycling is applied in laser interferometers such as the Advanced Laser Interferometer Gravitational-Wave Observatory (aLIGO) to increase their sensitivity to gravitational waves. In this study, signal recycling configurations for detecting a stochastic gravitational wave background are optimized based on aLIGO parameters. Optimal transmission of the signal recycling mirror (SRM) and detuning phase of the signal recycling cavity under a fixed laser power and low-frequency cutoff are calculated. Based on the optimal configurations, the compatibility with a binary neutron star (BNS) search is discussed. Then, different laser powers and low-frequency cutoffs are considered. Two models for the dimensionless energy density of gravitational waves , the flat model and the model, are studied. For a stochastic background search, it is found that an interferometer using signal recycling has a better sensitivity than an interferometer not using it. The optimal stochastic search configurations are typically found when both the SRM transmission and the signal recycling detuning phase are low. In this region, the BNS range mostly lies between 160 and 180 Mpc. When a lower laser power is used the optimal signal recycling detuning phase increases, the optimal SRM transmission increases and the optimal sensitivity improves. A reduced low-frequency cutoff gives a better sensitivity limit. For both models of , a typical optimal sensitivity limit on the order of 10‑10 is achieved at a reference frequency of Hz.

Human-in-the-loop Bayesian optimization of wearable device parameters

PubMed Central

Malcolm, Philippe; Speeckaert, Jozefien; Siviy, Christoper J.; Walsh, Conor J.; Kuindersma, Scott

2017-01-01

The increasing capabilities of exoskeletons and powered prosthetics for walking assistance have paved the way for more sophisticated and individualized control strategies. In response to this opportunity, recent work on human-in-the-loop optimization has considered the problem of automatically tuning control parameters based on realtime physiological measurements. However, the common use of metabolic cost as a performance metric creates significant experimental challenges due to its long measurement times and low signal-to-noise ratio. We evaluate the use of Bayesian optimization—a family of sample-efficient, noise-tolerant, and global optimization methods—for quickly identifying near-optimal control parameters. To manage experimental complexity and provide comparisons against related work, we consider the task of minimizing metabolic cost by optimizing walking step frequencies in unaided human subjects. Compared to an existing approach based on gradient descent, Bayesian optimization identified a near-optimal step frequency with a faster time to convergence (12 minutes, p < 0.01), smaller inter-subject variability in convergence time (± 2 minutes, p < 0.01), and lower overall energy expenditure (p < 0.01). PMID:28926613

Using Differential Evolution to Optimize Learning from Signals and Enhance Network Security

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harmer, Paul K; Temple, Michael A; Buckner, Mark A

2011-01-01

Computer and communication network attacks are commonly orchestrated through Wireless Access Points (WAPs). This paper summarizes proof-of-concept research activity aimed at developing a physical layer Radio Frequency (RF) air monitoring capability to limit unauthorizedWAP access and mprove network security. This is done using Differential Evolution (DE) to optimize the performance of a Learning from Signals (LFS) classifier implemented with RF Distinct Native Attribute (RF-DNA) fingerprints. Performance of the resultant DE-optimized LFS classifier is demonstrated using 802.11a WiFi devices under the most challenging conditions of intra-manufacturer classification, i.e., using emissions of like-model devices that only differ in serial number. Using identicalmore » classifier input features, performance of the DE-optimized LFS classifier is assessed relative to a Multiple Discriminant Analysis / Maximum Likelihood (MDA/ML) classifier that has been used for previous demonstrations. The comparative assessment is made using both Time Domain (TD) and Spectral Domain (SD) fingerprint features. For all combinations of classifier type, feature type, and signal-to-noise ratio considered, results show that the DEoptimized LFS classifier with TD features is uperior and provides up to 20% improvement in classification accuracy with proper selection of DE parameters.« less

Array signal recovery algorithm for a single-RF-channel DBF array

NASA Astrophysics Data System (ADS)

Zhang, Duo; Wu, Wen; Fang, Da Gang

2016-12-01

An array signal recovery algorithm based on sparse signal reconstruction theory is proposed for a single-RF-channel digital beamforming (DBF) array. A single-RF-channel antenna array is a low-cost antenna array in which signals are obtained from all antenna elements by only one microwave digital receiver. The spatially parallel array signals are converted into time-sequence signals, which are then sampled by the system. The proposed algorithm uses these time-sequence samples to recover the original parallel array signals by exploiting the second-order sparse structure of the array signals. Additionally, an optimization method based on the artificial bee colony (ABC) algorithm is proposed to improve the reconstruction performance. Using the proposed algorithm, the motion compensation problem for the single-RF-channel DBF array can be solved effectively, and the angle and Doppler information for the target can be simultaneously estimated. The effectiveness of the proposed algorithms is demonstrated by the results of numerical simulations.

Signal design and courtship presentation coincide for highly biased delivery of an iridescent butterfly mating signal

PubMed Central

White, Thomas E; Zeil, Jochen; Kemp, Darrell J; Rodriguez, R; Lenormand, T

2015-01-01

Sensory drive theory contends that signaling systems should evolve to optimize transmission between senders and intended receivers, while minimizing visibility to eavesdroppers where possible. In visual communication systems, the high directionality afforded by iridescent coloration presents underappreciated avenues for mediating this trade-off. This hypothesis predicts functional links between signal design and presentation such that visual conspicuousness is maximized only under ecologically relevant settings and/or to select audiences. We addressed this prediction using Hypolimnas bolina, a butterfly in which males possess ultraviolet markings on their dorsal wing surfaces with a narrow angular reflectance function. Males bearing brighter dorsal markings are increasingly attractive to females, but also likely more conspicuous to predators. Our data indicate that, during courtship (and given the ritualized wingbeat dynamics at these times), males position themselves relative to females in such a way as to simultaneously maximize three components of known or putative signal conspicuousness: brightness, area, and iridescent flash. This suggests that male signal design and display have coevolved for the delivery of an optimally conspicuous signal to courted females. More broadly, these findings imply a potential signaling role for iridescence itself, and pose a novel example for how signal design may coevolve with the behavioral context of display. PMID:25328995

A simple analytical model for signal amplification by reversible exchange (SABRE) process.

PubMed

Barskiy, Danila A; Pravdivtsev, Andrey N; Ivanov, Konstantin L; Kovtunov, Kirill V; Koptyug, Igor V

2016-01-07

We demonstrate an analytical model for the description of the signal amplification by reversible exchange (SABRE) process. The model relies on a combined analysis of chemical kinetics and the evolution of the nuclear spin system during the hyperpolarization process. The presented model for the first time provides rationale for deciding which system parameters (i.e. J-couplings, relaxation rates, reaction rate constants) have to be optimized in order to achieve higher signal enhancement for a substrate of interest in SABRE experiments.

Time-Gated Raman Spectroscopy for Quantitative Determination of Solid-State Forms of Fluorescent Pharmaceuticals.

PubMed

Lipiäinen, Tiina; Pessi, Jenni; Movahedi, Parisa; Koivistoinen, Juha; Kurki, Lauri; Tenhunen, Mari; Yliruusi, Jouko; Juppo, Anne M; Heikkonen, Jukka; Pahikkala, Tapio; Strachan, Clare J

2018-04-03

Raman spectroscopy is widely used for quantitative pharmaceutical analysis, but a common obstacle to its use is sample fluorescence masking the Raman signal. Time-gating provides an instrument-based method for rejecting fluorescence through temporal resolution of the spectral signal and allows Raman spectra of fluorescent materials to be obtained. An additional practical advantage is that analysis is possible in ambient lighting. This study assesses the efficacy of time-gated Raman spectroscopy for the quantitative measurement of fluorescent pharmaceuticals. Time-gated Raman spectroscopy with a 128 × (2) × 4 CMOS SPAD detector was applied for quantitative analysis of ternary mixtures of solid-state forms of the model drug, piroxicam (PRX). Partial least-squares (PLS) regression allowed quantification, with Raman-active time domain selection (based on visual inspection) improving performance. Model performance was further improved by using kernel-based regularized least-squares (RLS) regression with greedy feature selection in which the data use in both the Raman shift and time dimensions was statistically optimized. Overall, time-gated Raman spectroscopy, especially with optimized data analysis in both the spectral and time dimensions, shows potential for sensitive and relatively routine quantitative analysis of photoluminescent pharmaceuticals during drug development and manufacturing.

Functional Near Infrared Spectroscopy: Watching the Brain in Flight

NASA Technical Reports Server (NTRS)

Harrivel, Angela; Hearn, Tristan A.

2012-01-01

Functional Near Infrared Spectroscopy (fNIRS) is an emerging neurological sensing technique applicable to optimizing human performance in transportation operations, such as commercial aviation. Cognitive state can be determined via pattern classification of functional activations measured with fNIRS. Operational application calls for further development of algorithms and filters for dynamic artifact removal. The concept of using the frequency domain phase shift signal to tune a Kalman filter is introduced to improve the quality of fNIRS signals in real-time. Hemoglobin concentration and phase shift traces were simulated for four different types of motion artifact to demonstrate the filter. Unwanted signal was reduced by at least 43%, and the contrast of the filtered oxygenated hemoglobin signal was increased by more than 100% overall. This filtering method is a good candidate for qualifying fNIRS signals in real time without auxiliary sensors.

Real-time radar signal processing using GPGPU (general-purpose graphic processing unit)

NASA Astrophysics Data System (ADS)

Kong, Fanxing; Zhang, Yan Rockee; Cai, Jingxiao; Palmer, Robert D.

2016-05-01

This study introduces a practical approach to develop real-time signal processing chain for general phased array radar on NVIDIA GPUs(Graphical Processing Units) using CUDA (Compute Unified Device Architecture) libraries such as cuBlas and cuFFT, which are adopted from open source libraries and optimized for the NVIDIA GPUs. The processed results are rigorously verified against those from the CPUs. Performance benchmarked in computation time with various input data cube sizes are compared across GPUs and CPUs. Through the analysis, it will be demonstrated that GPGPUs (General Purpose GPU) real-time processing of the array radar data is possible with relatively low-cost commercial GPUs.

High-Resolution DCE-MRI of the Pituitary Gland Using Radial k-Space Acquisition with Compressed Sensing Reconstruction.

PubMed

Rossi Espagnet, M C; Bangiyev, L; Haber, M; Block, K T; Babb, J; Ruggiero, V; Boada, F; Gonen, O; Fatterpekar, G M

2015-08-01

The pituitary gland is located outside of the blood-brain barrier. Dynamic T1 weighted contrast enhanced sequence is considered to be the gold standard to evaluate this region. However, it does not allow assessment of intrinsic permeability properties of the gland. Our aim was to demonstrate the utility of radial volumetric interpolated brain examination with the golden-angle radial sparse parallel technique to evaluate permeability characteristics of the individual components (anterior and posterior gland and the median eminence) of the pituitary gland and areas of differential enhancement and to optimize the study acquisition time. A retrospective study was performed in 52 patients (group 1, 25 patients with normal pituitary glands; and group 2, 27 patients with a known diagnosis of microadenoma). Radial volumetric interpolated brain examination sequences with golden-angle radial sparse parallel technique were evaluated with an ROI-based method to obtain signal-time curves and permeability measures of individual normal structures within the pituitary gland and areas of differential enhancement. Statistical analyses were performed to assess differences in the permeability parameters of these individual regions and optimize the study acquisition time. Signal-time curves from the posterior pituitary gland and median eminence demonstrated a faster wash-in and time of maximum enhancement with a lower peak of enhancement compared with the anterior pituitary gland (P < .005). Time-optimization analysis demonstrated that 120 seconds is ideal for dynamic pituitary gland evaluation. In the absence of a clinical history, differences in the signal-time curves allow easy distinction between a simple cyst and a microadenoma. This retrospective study confirms the ability of the golden-angle radial sparse parallel technique to evaluate the permeability characteristics of the pituitary gland and establishes 120 seconds as the ideal acquisition time for dynamic pituitary gland imaging. © 2015 by American Journal of Neuroradiology.

High-Resolution DCE-MRI of the Pituitary Gland Using Radial k-Space Acquisition with Compressed Sensing Reconstruction

PubMed Central

Rossi Espagnet, M.C.; Bangiyev, L.; Haber, M.; Block, K.T.; Babb, J.; Ruggiero, V.; Boada, F.; Gonen, O.; Fatterpekar, G.M.

2015-01-01

BACKGROUNDANDPURPOSE The pituitary gland is located outside of the blood-brain barrier. Dynamic T1 weighted contrast enhanced sequence is considered to be the gold standard to evaluate this region. However, it does not allow assessment of intrinsic permeability properties of the gland. Our aim was to demonstrate the utility of radial volumetric interpolated brain examination with the golden-angle radial sparse parallel technique to evaluate permeability characteristics of the individual components (anterior and posterior gland and the median eminence) of the pituitary gland and areas of differential enhancement and to optimize the study acquisition time. MATERIALS AND METHODS A retrospective study was performed in 52 patients (group 1, 25 patients with normal pituitary glands; and group 2, 27 patients with a known diagnosis of microadenoma). Radial volumetric interpolated brain examination sequences with golden-angle radial sparse parallel technique were evaluated with an ROI-based method to obtain signal-time curves and permeability measures of individual normal structures within the pituitary gland and areas of differential enhancement. Statistical analyses were performed to assess differences in the permeability parameters of these individual regions and optimize the study acquisition time. RESULTS Signal-time curves from the posterior pituitary gland and median eminence demonstrated a faster wash-in and time of maximum enhancement with a lower peak of enhancement compared with the anterior pituitary gland (P < .005). Time-optimization analysis demonstrated that 120 seconds is ideal for dynamic pituitary gland evaluation. In the absence of a clinical history, differences in the signal-time curves allow easy distinction between a simple cyst and a microadenoma. CONCLUSIONS This retrospective study confirms the ability of the golden-angle radial sparse parallel technique to evaluate the permeability characteristics of the pituitary gland and establishes 120 seconds as the ideal acquisition time for dynamic pituitary gland imaging. PMID:25953760

EEG/ERP adaptive noise canceller design with controlled search space (CSS) approach in cuckoo and other optimization algorithms.

PubMed

Ahirwal, M K; Kumar, Anil; Singh, G K

2013-01-01

This paper explores the migration of adaptive filtering with swarm intelligence/evolutionary techniques employed in the field of electroencephalogram/event-related potential noise cancellation or extraction. A new approach is proposed in the form of controlled search space to stabilize the randomness of swarm intelligence techniques especially for the EEG signal. Swarm-based algorithms such as Particles Swarm Optimization, Artificial Bee Colony, and Cuckoo Optimization Algorithm with their variants are implemented to design optimized adaptive noise canceler. The proposed controlled search space technique is tested on each of the swarm intelligence techniques and is found to be more accurate and powerful. Adaptive noise canceler with traditional algorithms such as least-mean-square, normalized least-mean-square, and recursive least-mean-square algorithms are also implemented to compare the results. ERP signals such as simulated visual evoked potential, real visual evoked potential, and real sensorimotor evoked potential are used, due to their physiological importance in various EEG studies. Average computational time and shape measures of evolutionary techniques are observed 8.21E-01 sec and 1.73E-01, respectively. Though, traditional algorithms take negligible time consumption, but are unable to offer good shape preservation of ERP, noticed as average computational time and shape measure difference, 1.41E-02 sec and 2.60E+00, respectively.

RHODES-ITMS Tempe field test project : implementation and field testing of RHODES, a real-time traffic adaptive control system

DOT National Transportation Integrated Search

2001-09-01

RHODES is a traffic-adaptive signal control system that optimally controls the traffic that is observed in real time. The RHODES-ITMS Program is the application of the RHODES strategy for the two intersections of a freeway-arterial diamond interchang...

Distributed Optimization for a Class of Nonlinear Multiagent Systems With Disturbance Rejection.

PubMed

Wang, Xinghu; Hong, Yiguang; Ji, Haibo

2016-07-01

The paper studies the distributed optimization problem for a class of nonlinear multiagent systems in the presence of external disturbances. To solve the problem, we need to achieve the optimal multiagent consensus based on local cost function information and neighboring information and meanwhile to reject local disturbance signals modeled by an exogenous system. With convex analysis and the internal model approach, we propose a distributed optimization controller for heterogeneous and nonlinear agents in the form of continuous-time minimum-phase systems with unity relative degree. We prove that the proposed design can solve the exact optimization problem with rejecting disturbances.

Multi-objective LQR with optimum weight selection to design FOPID controllers for delayed fractional order processes.

PubMed

Das, Saptarshi; Pan, Indranil; Das, Shantanu

2015-09-01

An optimal trade-off design for fractional order (FO)-PID controller is proposed with a Linear Quadratic Regulator (LQR) based technique using two conflicting time domain objectives. A class of delayed FO systems with single non-integer order element, exhibiting both sluggish and oscillatory open loop responses, have been controlled here. The FO time delay processes are handled within a multi-objective optimization (MOO) formalism of LQR based FOPID design. A comparison is made between two contemporary approaches of stabilizing time-delay systems withinLQR. The MOO control design methodology yields the Pareto optimal trade-off solutions between the tracking performance and total variation (TV) of the control signal. Tuning rules are formed for the optimal LQR-FOPID controller parameters, using median of the non-dominated Pareto solutions to handle delayed FO processes. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal reference polarization states for the calibration of general Stokes polarimeters in the presence of noise

NASA Astrophysics Data System (ADS)

Mu, Tingkui; Bao, Donghao; Zhang, Chunmin; Chen, Zeyu; Song, Jionghui

2018-07-01

During the calibration of the system matrix of a Stokes polarimeter using reference polarization states (RPSs) and pseudo-inversion estimation method, the measurement intensities are usually noised by the signal-independent additive Gaussian noise or signal-dependent Poisson shot noise, the precision of the estimated system matrix is degraded. In this paper, we present a paradigm for selecting RPSs to improve the precision of the estimated system matrix in the presence of both types of noise. The analytical solution of the precision of the system matrix estimated with the RPSs are derived. Experimental measurements from a general Stokes polarimeter show that accurate system matrix is estimated with the optimal RPSs, which are generated using two rotating quarter-wave plates. The advantage of using optimal RPSs is a reduction in measurement time with high calibration precision.

Optimal Hotspots of Dynamic Surfaced-Enhanced Raman Spectroscopy for Drugs Quantitative Detection.

PubMed

Yan, Xiunan; Li, Pan; Zhou, Binbin; Tang, Xianghu; Li, Xiaoyun; Weng, Shizhuang; Yang, Liangbao; Liu, Jinhuai

2017-05-02

Surface-enhanced Raman spectroscopy (SERS) as a powerful qualitative analysis method has been widely applied in many fields. However, SERS for quantitative analysis still suffers from several challenges partially because of the absence of stable and credible analytical strategy. Here, we demonstrate that the optimal hotspots created from dynamic surfaced-enhanced Raman spectroscopy (D-SERS) can be used for quantitative SERS measurements. In situ small-angle X-ray scattering was carried out to in situ real-time monitor the formation of the optimal hotspots, where the optimal hotspots with the most efficient hotspots were generated during the monodisperse Au-sol evaporating process. Importantly, the natural evaporation of Au-sol avoids the nanoparticles instability of salt-induced, and formation of ordered three-dimensional hotspots allows SERS detection with excellent reproducibility. Considering SERS signal variability in the D-SERS process, 4-mercaptopyridine (4-mpy) acted as internal standard to validly correct and improve stability as well as reduce fluctuation of signals. The strongest SERS spectra at the optimal hotspots of D-SERS have been extracted to statistics analysis. By using the SERS signal of 4-mpy as a stable internal calibration standard, the relative SERS intensity of target molecules demonstrated a linear response versus the negative logarithm of concentrations at the point of strongest SERS signals, which illustrates the great potential for quantitative analysis. The public drugs 3,4-methylenedioxymethamphetamine and α-methyltryptamine hydrochloride obtained precise analysis with internal standard D-SERS strategy. As a consequence, one has reason to believe our approach is promising to challenge quantitative problems in conventional SERS analysis.

A Deep Machine Learning Method for Classifying Cyclic Time Series of Biological Signals Using Time-Growing Neural Network.

PubMed

Gharehbaghi, Arash; Linden, Maria

2017-10-12

This paper presents a novel method for learning the cyclic contents of stochastic time series: the deep time-growing neural network (DTGNN). The DTGNN combines supervised and unsupervised methods in different levels of learning for an enhanced performance. It is employed by a multiscale learning structure to classify cyclic time series (CTS), in which the dynamic contents of the time series are preserved in an efficient manner. This paper suggests a systematic procedure for finding the design parameter of the classification method for a one-versus-multiple class application. A novel validation method is also suggested for evaluating the structural risk, both in a quantitative and a qualitative manner. The effect of the DTGNN on the performance of the classifier is statistically validated through the repeated random subsampling using different sets of CTS, from different medical applications. The validation involves four medical databases, comprised of 108 recordings of the electroencephalogram signal, 90 recordings of the electromyogram signal, 130 recordings of the heart sound signal, and 50 recordings of the respiratory sound signal. Results of the statistical validations show that the DTGNN significantly improves the performance of the classification and also exhibits an optimal structural risk.

Implementation and optimization of ultrasound signal processing algorithms on mobile GPU

NASA Astrophysics Data System (ADS)

Kong, Woo Kyu; Lee, Wooyoul; Kim, Kyu Cheol; Yoo, Yangmo; Song, Tai-Kyong

2014-03-01

A general-purpose graphics processing unit (GPGPU) has been used for improving computing power in medical ultrasound imaging systems. Recently, a mobile GPU becomes powerful to deal with 3D games and videos at high frame rates on Full HD or HD resolution displays. This paper proposes the method to implement ultrasound signal processing on a mobile GPU available in the high-end smartphone (Galaxy S4, Samsung Electronics, Seoul, Korea) with programmable shaders on the OpenGL ES 2.0 platform. To maximize the performance of the mobile GPU, the optimization of shader design and load sharing between vertex and fragment shader was performed. The beamformed data were captured from a tissue mimicking phantom (Model 539 Multipurpose Phantom, ATS Laboratories, Inc., Bridgeport, CT, USA) by using a commercial ultrasound imaging system equipped with a research package (Ultrasonix Touch, Ultrasonix, Richmond, BC, Canada). The real-time performance is evaluated by frame rates while varying the range of signal processing blocks. The implementation method of ultrasound signal processing on OpenGL ES 2.0 was verified by analyzing PSNR with MATLAB gold standard that has the same signal path. CNR was also analyzed to verify the method. From the evaluations, the proposed mobile GPU-based processing method has no significant difference with the processing using MATLAB (i.e., PSNR<52.51 dB). The comparable results of CNR were obtained from both processing methods (i.e., 11.31). From the mobile GPU implementation, the frame rates of 57.6 Hz were achieved. The total execution time was 17.4 ms that was faster than the acquisition time (i.e., 34.4 ms). These results indicate that the mobile GPU-based processing method can support real-time ultrasound B-mode processing on the smartphone.

Functional Description of Read-out Electronics for Time-Domain Multiplexed Bolometers for Millimeter and Sub-millimeter Astronomy

NASA Astrophysics Data System (ADS)

Battistelli, E. S.; Amiri, M.; Burger, B.; Halpern, M.; Knotek, S.; Ellis, M.; Gao, X.; Kelly, D.; Macintosh, M.; Irwin, K.; Reintsema, C.

2008-05-01

We have developed multi-channel electronics (MCE) which work in concert with time-domain multiplexors developed at NIST, to control and read signals from large format bolometer arrays of superconducting transition edge sensors (TESs). These electronics were developed as part of the Submillimeter Common-User Bolometer Array-2 (SCUBA2 ) camera, but are now used in several other instruments. The main advantages of these electronics compared to earlier versions is that they are multi-channel, fully programmable, suited for remote operations and provide a clean geometry, with no electrical cabling outside of the Faraday cage formed by the cryostat and the electronics chassis. The MCE is used to determine the optimal operating points for the TES and the superconducting quantum interference device (SQUID) amplifiers autonomously. During observation, the MCE execute a running PID-servo and apply to each first stage SQUID a feedback signal necessary to keep the system in a linear regime at optimal gain. The feedback and error signals from a ˜1000-pixel array can be written to hard drive at up to 2 kHz.

Optimizing the feedback control of Galvo scanners for laser manufacturing systems

NASA Astrophysics Data System (ADS)

Mirtchev, Theodore; Weeks, Robert; Minko, Sergey

2010-06-01

This paper summarizes the factors that limit the performance of moving-magnet galvo scanners driven by closed-loop digital servo amplifiers: torsional resonances, drifts, nonlinearities, feedback noise and friction. Then it describes a detailed Simulink® simulator that takes into account these factors and can be used to automatically tune the controller for best results with given galvo type and trajectory patterns. It allows for rapid testing of different control schemes, for instance combined position/velocity PID loops and displays the corresponding output in terms of torque, angular position and feedback sensor signal. The tool is configurable and can either use a dynamical state-space model of galvo's open-loop response, or can import the experimentally measured frequency domain transfer function. Next a drive signal digital pre-filtering technique is discussed. By performing a real-time Fourier analysis of the raw command signal it can be pre-warped to minimize all harmonics around the torsional resonances while boosting other non-resonant high frequencies. The optimized waveform results in much smaller overshoot and better settling time. Similar performance gain cannot be extracted from the servo controller alone.

Determining the Ocean's Role on the Variable Gravity Field and Earth Rotation

NASA Technical Reports Server (NTRS)

Ponte, Rui M.; Frey, H. (Technical Monitor)

2000-01-01

A number of ocean models of different complexity have been used to study changes in the oceanic angular momentum (OAM) and mass fields and their relation to the variable Earth rotation and gravity field. Time scales examined range from seasonal to a few days. Results point to the importance of oceanic signals in driving polar motion, in particular the Chandler and annual wobbles. Results also show that oceanic signals have a measurable impact on length-of-day variations. Various circulation features and associated mass signals, including the North Pacific subtropical gyre, the equatorial currents, and the Antarctic Circumpolar Current play a significant role in oceanic angular momentum variability. The impact on OAM values of an optimization procedure that uses available data to constrain ocean model results was also tested for the first time. The optimization procedure yielded substantial changes, in OAM, related to adjustments in both motion and mass fields,as well as in the wind stress torques acting on the ocean. Constrained OAM values were found to yield noticeable improvements in the agreement with the observed Earth rotation parameters, particularly at the seasonal timescale.

An optimized time varying filtering based empirical mode decomposition method with grey wolf optimizer for machinery fault diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Xin; Liu, Zhiwen; Miao, Qiang; Wang, Lei

2018-03-01

A time varying filtering based empirical mode decomposition (EMD) (TVF-EMD) method was proposed recently to solve the mode mixing problem of EMD method. Compared with the classical EMD, TVF-EMD was proven to improve the frequency separation performance and be robust to noise interference. However, the decomposition parameters (i.e., bandwidth threshold and B-spline order) significantly affect the decomposition results of this method. In original TVF-EMD method, the parameter values are assigned in advance, which makes it difficult to achieve satisfactory analysis results. To solve this problem, this paper develops an optimized TVF-EMD method based on grey wolf optimizer (GWO) algorithm for fault diagnosis of rotating machinery. Firstly, a measurement index termed weighted kurtosis index is constructed by using kurtosis index and correlation coefficient. Subsequently, the optimal TVF-EMD parameters that match with the input signal can be obtained by GWO algorithm using the maximum weighted kurtosis index as objective function. Finally, fault features can be extracted by analyzing the sensitive intrinsic mode function (IMF) owning the maximum weighted kurtosis index. Simulations and comparisons highlight the performance of TVF-EMD method for signal decomposition, and meanwhile verify the fact that bandwidth threshold and B-spline order are critical to the decomposition results. Two case studies on rotating machinery fault diagnosis demonstrate the effectiveness and advantages of the proposed method.

A new fast and fully automated software based algorithm for extracting respiratory signal from raw PET data and its comparison to other methods.

PubMed

Kesner, Adam Leon; Kuntner, Claudia

2010-10-01

Respiratory gating in PET is an approach used to minimize the negative effects of respiratory motion on spatial resolution. It is based on an initial determination of a patient's respiratory movements during a scan, typically using hardware based systems. In recent years, several fully automated databased algorithms have been presented for extracting a respiratory signal directly from PET data, providing a very practical strategy for implementing gating in the clinic. In this work, a new method is presented for extracting a respiratory signal from raw PET sinogram data and compared to previously presented automated techniques. The acquisition of respiratory signal from PET data in the newly proposed method is based on rebinning the sinogram data into smaller data structures and then analyzing the time activity behavior in the elements of these structures. From this analysis, a 1D respiratory trace is produced, analogous to a hardware derived respiratory trace. To assess the accuracy of this fully automated method, respiratory signal was extracted from a collection of 22 clinical FDG-PET scans using this method, and compared to signal derived from several other software based methods as well as a signal derived from a hardware system. The method presented required approximately 9 min of processing time for each 10 min scan (using a single 2.67 GHz processor), which in theory can be accomplished while the scan is being acquired and therefore allowing a real-time respiratory signal acquisition. Using the mean correlation between the software based and hardware based respiratory traces, the optimal parameters were determined for the presented algorithm. The mean/median/range of correlations for the set of scans when using the optimal parameters was found to be 0.58/0.68/0.07-0.86. The speed of this method was within the range of real-time while the accuracy surpassed the most accurate of the previously presented algorithms. PET data inherently contains information about patient motion; information that is not currently being utilized. We have shown that a respiratory signal can be extracted from raw PET data in potentially real-time and in a fully automated manner. This signal correlates well with hardware based signal for a large percentage of scans, and avoids the efforts and complications associated with hardware. The proposed method to extract a respiratory signal can be implemented on existing scanners and, if properly integrated, can be applied without changes to routine clinical procedures.

Automatic threshold optimization in nonlinear energy operator based spike detection.

PubMed

Malik, Muhammad H; Saeed, Maryam; Kamboh, Awais M

2016-08-01

In neural spike sorting systems, the performance of the spike detector has to be maximized because it affects the performance of all subsequent blocks. Non-linear energy operator (NEO), is a popular spike detector due to its detection accuracy and its hardware friendly architecture. However, it involves a thresholding stage, whose value is usually approximated and is thus not optimal. This approximation deteriorates the performance in real-time systems where signal to noise ratio (SNR) estimation is a challenge, especially at lower SNRs. In this paper, we propose an automatic and robust threshold calculation method using an empirical gradient technique. The method is tested on two different datasets. The results show that our optimized threshold improves the detection accuracy in both high SNR and low SNR signals. Boxplots are presented that provide a statistical analysis of improvements in accuracy, for instance, the 75th percentile was at 98.7% and 93.5% for the optimized NEO threshold and traditional NEO threshold, respectively.

Noise Tolerance of Attractor and Feedforward Memory Models

PubMed Central

Lim, Sukbin; Goldman, Mark S.

2017-01-01

In short-term memory networks, transient stimuli are represented by patterns of neural activity that persist long after stimulus offset. Here, we compare the performance of two prominent classes of memory networks, feedback-based attractor networks and feedforward networks, in conveying information about the amplitude of a briefly presented stimulus in the presence of gaussian noise. Using Fisher information as a metric of memory performance, we find that the optimal form of network architecture depends strongly on assumptions about the forms of nonlinearities in the network. For purely linear networks, we find that feedforward networks outperform attractor networks because noise is continually removed from feedforward networks when signals exit the network; as a result, feedforward networks can amplify signals they receive faster than noise accumulates over time. By contrast, attractor networks must operate in a signal-attenuating regime to avoid the buildup of noise. However, if the amplification of signals is limited by a finite dynamic range of neuronal responses or if noise is reset at the time of signal arrival, as suggested by recent experiments, we find that attractor networks can out-perform feedforward ones. Under a simple model in which neurons have a finite dynamic range, we find that the optimal attractor networks are forgetful if there is no mechanism for noise reduction with signal arrival but nonforgetful (perfect integrators) in the presence of a strong reset mechanism. Furthermore, we find that the maximal Fisher information for the feedforward and attractor networks exhibits power law decay as a function of time and scales linearly with the number of neurons. These results highlight prominent factors that lead to trade-offs in the memory performance of networks with different architectures and constraints, and suggest conditions under which attractor or feedforward networks may be best suited to storing information about previous stimuli. PMID:22091664

Energy Efficient GNSS Signal Acquisition Using Singular Value Decomposition (SVD).

PubMed

Bermúdez Ordoñez, Juan Carlos; Arnaldo Valdés, Rosa María; Gómez Comendador, Fernando

2018-05-16

A significant challenge in global navigation satellite system (GNSS) signal processing is a requirement for a very high sampling rate. The recently-emerging compressed sensing (CS) theory makes processing GNSS signals at a low sampling rate possible if the signal has a sparse representation in a certain space. Based on CS and SVD theories, an algorithm for sampling GNSS signals at a rate much lower than the Nyquist rate and reconstructing the compressed signal is proposed in this research, which is validated after the output from that process still performs signal detection using the standard fast Fourier transform (FFT) parallel frequency space search acquisition. The sparse representation of the GNSS signal is the most important precondition for CS, by constructing a rectangular Toeplitz matrix (TZ) of the transmitted signal, calculating the left singular vectors using SVD from the TZ, to achieve sparse signal representation. Next, obtaining the M-dimensional observation vectors based on the left singular vectors of the SVD, which are equivalent to the sampler operator in standard compressive sensing theory, the signal can be sampled below the Nyquist rate, and can still be reconstructed via ℓ 1 minimization with accuracy using convex optimization. As an added value, there is a GNSS signal acquisition enhancement effect by retaining the useful signal and filtering out noise by projecting the signal into the most significant proper orthogonal modes (PODs) which are the optimal distributions of signal power. The algorithm is validated with real recorded signals, and the results show that the proposed method is effective for sampling, reconstructing intermediate frequency (IF) GNSS signals in the time discrete domain.

Energy Efficient GNSS Signal Acquisition Using Singular Value Decomposition (SVD)

PubMed Central

Arnaldo Valdés, Rosa María; Gómez Comendador, Fernando

2018-01-01

A significant challenge in global navigation satellite system (GNSS) signal processing is a requirement for a very high sampling rate. The recently-emerging compressed sensing (CS) theory makes processing GNSS signals at a low sampling rate possible if the signal has a sparse representation in a certain space. Based on CS and SVD theories, an algorithm for sampling GNSS signals at a rate much lower than the Nyquist rate and reconstructing the compressed signal is proposed in this research, which is validated after the output from that process still performs signal detection using the standard fast Fourier transform (FFT) parallel frequency space search acquisition. The sparse representation of the GNSS signal is the most important precondition for CS, by constructing a rectangular Toeplitz matrix (TZ) of the transmitted signal, calculating the left singular vectors using SVD from the TZ, to achieve sparse signal representation. Next, obtaining the M-dimensional observation vectors based on the left singular vectors of the SVD, which are equivalent to the sampler operator in standard compressive sensing theory, the signal can be sampled below the Nyquist rate, and can still be reconstructed via ℓ1 minimization with accuracy using convex optimization. As an added value, there is a GNSS signal acquisition enhancement effect by retaining the useful signal and filtering out noise by projecting the signal into the most significant proper orthogonal modes (PODs) which are the optimal distributions of signal power. The algorithm is validated with real recorded signals, and the results show that the proposed method is effective for sampling, reconstructing intermediate frequency (IF) GNSS signals in the time discrete domain. PMID:29772731

1 Tbit/inch2 Recording in Angular-Multiplexing Holographic Memory with Constant Signal-to-Scatter Ratio Schedule

NASA Astrophysics Data System (ADS)

Hosaka, Makoto; Ishii, Toshiki; Tanaka, Asato; Koga, Shogo; Hoshizawa, Taku

2013-09-01

We developed an iterative method for optimizing the exposure schedule to obtain a constant signal-to-scatter ratio (SSR) to accommodate various recording conditions and achieve high-density recording. 192 binary images were recorded in the same location of a medium in approximately 300×300 µm2 using an experimental system embedded with a blue laser diode with a 405 nm wavelength and an objective lens with a 0.85 numerical aperture. The recording density of this multiplexing corresponds to 1 Tbit/in.2. The recording exposure time was optimized through the iteration of a three-step sequence consisting of total reproduced intensity measurement, target signal calculation, and recording energy density calculation. The SSR of pages recorded with this method was almost constant throughout the entire range of the reference beam angle. The signal-to-noise ratio of the sampled pages was over 2.9 dB, which is higher than the reproducible limit of 1.5 dB in our experimental system.

Adaptive Detector Arrays for Optical Communications Receivers

NASA Technical Reports Server (NTRS)

Vilnrotter, V.; Srinivasan, M.

2000-01-01

The structure of an optimal adaptive array receiver for ground-based optical communications is described and its performance investigated. Kolmogorov phase screen simulations are used to model the sample functions of the focal-plane signal distribution due to turbulence and to generate realistic spatial distributions of the received optical field. This novel array detector concept reduces interference from background radiation by effectively assigning higher confidence levels at each instant of time to those detector elements that contain significant signal energy and suppressing those that do not. A simpler suboptimum structure that replaces the continuous weighting function of the optimal receiver by a hard decision on the selection of the signal detector elements also is described and evaluated. Approximations and bounds to the error probability are derived and compared with the exact calculations and receiver simulation results. It is shown that, for photon-counting receivers observing Poisson-distributed signals, performance improvements of approximately 5 dB can be obtained over conventional single-detector photon-counting receivers, when operating in high background environments.

Brain-computer interface using wavelet transformation and naïve bayes classifier.

PubMed

Bassani, Thiago; Nievola, Julio Cesar

2010-01-01

The main purpose of this work is to establish an exploratory approach using electroencephalographic (EEG) signal, analyzing the patterns in the time-frequency plane. This work also aims to optimize the EEG signal analysis through the improvement of classifiers and, eventually, of the BCI performance. In this paper a novel exploratory approach for data mining of EEG signal based on continuous wavelet transformation (CWT) and wavelet coherence (WC) statistical analysis is introduced and applied. The CWT allows the representation of time-frequency patterns of the signal's information content by WC qualiatative analysis. Results suggest that the proposed methodology is capable of identifying regions in time-frequency spectrum during the specified task of BCI. Furthermore, an example of a region is identified, and the patterns are classified using a Naïve Bayes Classifier (NBC). This innovative characteristic of the process justifies the feasibility of the proposed approach to other data mining applications. It can open new physiologic researches in this field and on non stationary time series analysis.

Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.

PubMed

Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping

2018-06-01

This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.

Short-time fractional Fourier methods for the time-frequency representation of chirp signals.

PubMed

Capus, Chris; Brown, Keith

2003-06-01

The fractional Fourier transform (FrFT) provides a valuable tool for the analysis of linear chirp signals. This paper develops two short-time FrFT variants which are suited to the analysis of multicomponent and nonlinear chirp signals. Outputs have similar properties to the short-time Fourier transform (STFT) but show improved time-frequency resolution. The FrFT is a parameterized transform with parameter, a, related to chirp rate. The two short-time implementations differ in how the value of a is chosen. In the first, a global optimization procedure selects one value of a with reference to the entire signal. In the second, a values are selected independently for each windowed section. Comparative variance measures based on the Gaussian function are given and are shown to be consistent with the uncertainty principle in fractional domains. For appropriately chosen FrFT orders, the derived fractional domain uncertainty relationship is minimized for Gaussian windowed linear chirp signals. The two short-time FrFT algorithms have complementary strengths demonstrated by time-frequency representations for a multicomponent bat chirp, a highly nonlinear quadratic chirp, and an output pulse from a finite-difference sonar model with dispersive change. These representations illustrate the improvements obtained in using FrFT based algorithms compared to the STFT.

Time-Frequency Analysis of Non-Stationary Biological Signals with Sparse Linear Regression Based Fourier Linear Combiner.

PubMed

Wang, Yubo; Veluvolu, Kalyana C

2017-06-14

It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC). In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976) ratio and outperforms existing methods such as short-time Fourier transfrom (STFT), continuous Wavelet transform (CWT) and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.

Compressive sensing using optimized sensing matrix for face verification

NASA Astrophysics Data System (ADS)

Oey, Endra; Jeffry; Wongso, Kelvin; Tommy

2017-12-01

Biometric appears as one of the solutions which is capable in solving problems that occurred in the usage of password in terms of data access, for example there is possibility in forgetting password and hard to recall various different passwords. With biometrics, physical characteristics of a person can be captured and used in the identification process. In this research, facial biometric is used in the verification process to determine whether the user has the authority to access the data or not. Facial biometric is chosen as its low cost implementation and generate quite accurate result for user identification. Face verification system which is adopted in this research is Compressive Sensing (CS) technique, in which aims to reduce dimension size as well as encrypt data in form of facial test image where the image is represented in sparse signals. Encrypted data can be reconstructed using Sparse Coding algorithm. Two types of Sparse Coding namely Orthogonal Matching Pursuit (OMP) and Iteratively Reweighted Least Squares -ℓp (IRLS-ℓp) will be used for comparison face verification system research. Reconstruction results of sparse signals are then used to find Euclidean norm with the sparse signal of user that has been previously saved in system to determine the validity of the facial test image. Results of system accuracy obtained in this research are 99% in IRLS with time response of face verification for 4.917 seconds and 96.33% in OMP with time response of face verification for 0.4046 seconds with non-optimized sensing matrix, while 99% in IRLS with time response of face verification for 13.4791 seconds and 98.33% for OMP with time response of face verification for 3.1571 seconds with optimized sensing matrix.

Design of a surface-scanning coil detector for direct bacteria detection on food surfaces using a magnetoelastic biosensor

NASA Astrophysics Data System (ADS)

Chai, Yating; Wikle, Howard C.; Wang, Zhenyu; Horikawa, Shin; Best, Steve; Cheng, Zhongyang; Dyer, Dave F.; Chin, Bryan A.

2013-09-01

The real-time, in-situ bacteria detection on food surfaces was achieved by using a magnetoelastic biosensor combined with a surface-scanning coil detector. This paper focuses on the coil design for signal optimization. The coil was used to excite the sensor's vibration and detect its resonant frequency signal. The vibrating sensor creates a magnetic flux change around the coil, which then produces a mutual inductance. In order to enhance the signal amplitude, a theory of the sensor's mutual inductance with the measurement coil is proposed. Both theoretical calculations and experimental data showed that the working length of the coil has a significant effect on the signal amplitude. For a 1 mm-long sensor, a coil with a working length of 1.3 mm showed the best signal amplitude. The real-time detection of Salmonella bacteria on a fresh food surface was demonstrated using this new technology.

Optimal time points sampling in pathway modelling.

PubMed

Hu, Shiyan

2004-01-01

Modelling cellular dynamics based on experimental data is at the heart of system biology. Considerable progress has been made to dynamic pathway modelling as well as the related parameter estimation. However, few of them gives consideration for the issue of optimal sampling time selection for parameter estimation. Time course experiments in molecular biology rarely produce large and accurate data sets and the experiments involved are usually time consuming and expensive. Therefore, to approximate parameters for models with only few available sampling data is of significant practical value. For signal transduction, the sampling intervals are usually not evenly distributed and are based on heuristics. In the paper, we investigate an approach to guide the process of selecting time points in an optimal way to minimize the variance of parameter estimates. In the method, we first formulate the problem to a nonlinear constrained optimization problem by maximum likelihood estimation. We then modify and apply a quantum-inspired evolutionary algorithm, which combines the advantages of both quantum computing and evolutionary computing, to solve the optimization problem. The new algorithm does not suffer from the morass of selecting good initial values and being stuck into local optimum as usually accompanied with the conventional numerical optimization techniques. The simulation results indicate the soundness of the new method.

Resonant Tunneling Quantum Well Integrated Optical Waveguide Modulator/ Switch

DTIC Science & Technology

1994-07-01

time, which leads to the high speed operation. In this Phase I project, POC designed the RTDBQW device, including the optimization and precise definition...Effect of Free Carriers ............ 7 3.0 CHANNEL WAVEGUIDE DESIGN AND OPTIMIZATION ................... 10 3.1 Design Of Directional Coupling Mach...are essential for high speed signal routing and regeneration. POC’s design relies on the integration of an optical guided wave switch/modulator with a

Statistical Determination of the Gating Windows for Respiratory-Gated Radiotherapy Using a Visible Guiding System.

PubMed

Oh, Se An; Yea, Ji Woon; Kim, Sung Kyu

2016-01-01

Respiratory-gated radiation therapy (RGRT) is used to minimize the radiation dose to normal tissue in lung-cancer patients. Although determining the gating window in the respiratory phase of patients is important in RGRT, it is not easy. Our aim was to determine the optimal gating window when using a visible guiding system for RGRT. Between April and October 2014, the breathing signals of 23 lung-cancer patients were recorded with a real-time position management (RPM) respiratory gating system (Varian, USA). We performed statistical analysis with breathing signals to find the optimal gating window for guided breathing in RGRT. When we compared breathing signals before and after the breathing training, 19 of the 23 patients showed statistically significant differences (p < 0.05). The standard deviation of the respiration signals after breathing training was lowest for phases of 30%-70%. The results showed that the optimal gating window in RGRT is 40% (30%-70%) with respect to repeatability for breathing after respiration training with the visible guiding system. RGRT was performed with the RPM system to confirm the usefulness of the visible guiding system. The RPM system and our visible guiding system improve the respiratory regularity, which in turn should improve the accuracy and efficiency of RGRT.

Strategies to overcome photobleaching in algorithm-based adaptive optics for nonlinear in-vivo imaging.

PubMed

Caroline Müllenbroich, M; McGhee, Ewan J; Wright, Amanda J; Anderson, Kurt I; Mathieson, Keith

2014-01-01

We have developed a nonlinear adaptive optics microscope utilizing a deformable membrane mirror (DMM) and demonstrated its use in compensating for system- and sample-induced aberrations. The optimum shape of the DMM was determined with a random search algorithm optimizing on either two photon fluorescence or second harmonic signals as merit factors. We present here several strategies to overcome photobleaching issues associated with lengthy optimization routines by adapting the search algorithm and the experimental methodology. Optimizations were performed on extrinsic fluorescent dyes, fluorescent beads loaded into organotypic tissue cultures and the intrinsic second harmonic signal of these cultures. We validate the approach of using these preoptimized mirror shapes to compile a robust look-up table that can be applied for imaging over several days and through a variety of tissues. In this way, the photon exposure to the fluorescent cells under investigation is limited to imaging. Using our look-up table approach, we show signal intensity improvement factors ranging from 1.7 to 4.1 in organotypic tissue cultures and freshly excised mouse tissue. Imaging zebrafish in vivo, we demonstrate signal improvement by a factor of 2. This methodology is easily reproducible and could be applied to many photon starved experiments, for example fluorescent life time imaging, or when photobleaching is a concern.

An Optimization-Based Framework for the Transformation of Incomplete Biological Knowledge into a Probabilistic Structure and Its Application to the Utilization of Gene/Protein Signaling Pathways in Discrete Phenotype Classification.

PubMed

Esfahani, Mohammad Shahrokh; Dougherty, Edward R

2015-01-01

Phenotype classification via genomic data is hampered by small sample sizes that negatively impact classifier design. Utilization of prior biological knowledge in conjunction with training data can improve both classifier design and error estimation via the construction of the optimal Bayesian classifier. In the genomic setting, gene/protein signaling pathways provide a key source of biological knowledge. Although these pathways are neither complete, nor regulatory, with no timing associated with them, they are capable of constraining the set of possible models representing the underlying interaction between molecules. The aim of this paper is to provide a framework and the mathematical tools to transform signaling pathways to prior probabilities governing uncertainty classes of feature-label distributions used in classifier design. Structural motifs extracted from the signaling pathways are mapped to a set of constraints on a prior probability on a Multinomial distribution. Being the conjugate prior for the Multinomial distribution, we propose optimization paradigms to estimate the parameters of a Dirichlet distribution in the Bayesian setting. The performance of the proposed methods is tested on two widely studied pathways: mammalian cell cycle and a p53 pathway model.

Optimal CCD readout by digital correlated double sampling

NASA Astrophysics Data System (ADS)

Alessandri, C.; Abusleme, A.; Guzman, D.; Passalacqua, I.; Alvarez-Fontecilla, E.; Guarini, M.

2016-01-01

Digital correlated double sampling (DCDS), a readout technique for charge-coupled devices (CCD), is gaining popularity in astronomical applications. By using an oversampling ADC and a digital filter, a DCDS system can achieve a better performance than traditional analogue readout techniques at the expense of a more complex system analysis. Several attempts to analyse and optimize a DCDS system have been reported, but most of the work presented in the literature has been experimental. Some approximate analytical tools have been presented for independent parameters of the system, but the overall performance and trade-offs have not been yet modelled. Furthermore, there is disagreement among experimental results that cannot be explained by the analytical tools available. In this work, a theoretical analysis of a generic DCDS readout system is presented, including key aspects such as the signal conditioning stage, the ADC resolution, the sampling frequency and the digital filter implementation. By using a time-domain noise model, the effect of the digital filter is properly modelled as a discrete-time process, thus avoiding the imprecision of continuous-time approximations that have been used so far. As a result, an accurate, closed-form expression for the signal-to-noise ratio at the output of the readout system is reached. This expression can be easily optimized in order to meet a set of specifications for a given CCD, thus providing a systematic design methodology for an optimal readout system. Simulated results are presented to validate the theory, obtained with both time- and frequency-domain noise generation models for completeness.

Accuracy of heart rate variability estimation by photoplethysmography using an smartphone: Processing optimization and fiducial point selection.

PubMed

Ferrer-Mileo, V; Guede-Fernandez, F; Fernandez-Chimeno, M; Ramos-Castro, J; Garcia-Gonzalez, M A

2015-08-01

This work compares several fiducial points to detect the arrival of a new pulse in a photoplethysmographic signal using the built-in camera of smartphones or a photoplethysmograph. Also, an optimization process for the signal preprocessing stage has been done. Finally we characterize the error produced when we use the best cutoff frequencies and fiducial point for smartphones and photopletysmograph and compare if the error of smartphones can be reasonably be explained by variations in pulse transit time. The results have revealed that the peak of the first derivative and the minimum of the second derivative of the pulse wave have the lowest error. Moreover, for these points, high pass filtering the signal between 0.1 to 0.8 Hz and low pass around 2.7 Hz or 3.5 Hz are the best cutoff frequencies. Finally, the error in smartphones is slightly higher than in a photoplethysmograph.

Inventory of system operations data collection and use in the Virginia Department of Transportation.

DOT National Transportation Integrated Search

2006-01-01

Accurate data describing the status of the transportation network is the backbone of system operations management. Without accurate data, traffic engineers cannot optimize signal phasing and timing, effective incident management cannot be undertaken,...

Using diurnal temperature signals to infer vertical groundwater-surface water exchange

USGS Publications Warehouse

Irvine, Dylan J.; Briggs, Martin A.; Lautz, Laura K.; Gordon, Ryan P.; McKenzie, Jeffrey M.; Cartwright, Ian

2017-01-01

Heat is a powerful tracer to quantify fluid exchange between surface water and groundwater. Temperature time series can be used to estimate pore water fluid flux, and techniques can be employed to extend these estimates to produce detailed plan-view flux maps. Key advantages of heat tracing include cost-effective sensors and ease of data collection and interpretation, without the need for expensive and time-consuming laboratory analyses or induced tracers. While the collection of temperature data in saturated sediments is relatively straightforward, several factors influence the reliability of flux estimates that are based on time series analysis (diurnal signals) of recorded temperatures. Sensor resolution and deployment are particularly important in obtaining robust flux estimates in upwelling conditions. Also, processing temperature time series data involves a sequence of complex steps, including filtering temperature signals, selection of appropriate thermal parameters, and selection of the optimal analytical solution for modeling. This review provides a synthesis of heat tracing using diurnal temperature oscillations, including details on optimal sensor selection and deployment, data processing, model parameterization, and an overview of computing tools available. Recent advances in diurnal temperature methods also provide the opportunity to determine local saturated thermal diffusivity, which can improve the accuracy of fluid flux modeling and sensor spacing, which is related to streambed scour and deposition. These parameters can also be used to determine the reliability of flux estimates from the use of heat as a tracer.

A generalised optimal linear quadratic tracker with universal applications. Part 2: discrete-time systems

NASA Astrophysics Data System (ADS)

Ebrahimzadeh, Faezeh; Tsai, Jason Sheng-Hong; Chung, Min-Ching; Liao, Ying Ting; Guo, Shu-Mei; Shieh, Leang-San; Wang, Li

2017-01-01

Contrastive to Part 1, Part 2 presents a generalised optimal linear quadratic digital tracker (LQDT) with universal applications for the discrete-time (DT) systems. This includes (1) a generalised optimal LQDT design for the system with the pre-specified trajectories of the output and the control input and additionally with both the input-to-output direct-feedthrough term and known/estimated system disturbances or extra input/output signals; (2) a new optimal filter-shaped proportional plus integral state-feedback LQDT design for non-square non-minimum phase DT systems to achieve a minimum-phase-like tracking performance; (3) a new approach for computing the control zeros of the given non-square DT systems; and (4) a one-learning-epoch input-constrained iterative learning LQDT design for the repetitive DT systems.

Design and Implementation of a Video-Zoom Driven Digital Audio-Zoom System for Portable Digital Imaging Devices

NASA Astrophysics Data System (ADS)

Park, Nam In; Kim, Seon Man; Kim, Hong Kook; Kim, Ji Woon; Kim, Myeong Bo; Yun, Su Won

In this paper, we propose a video-zoom driven audio-zoom algorithm in order to provide audio zooming effects in accordance with the degree of video-zoom. The proposed algorithm is designed based on a super-directive beamformer operating with a 4-channel microphone system, in conjunction with a soft masking process that considers the phase differences between microphones. Thus, the audio-zoom processed signal is obtained by multiplying an audio gain derived from a video-zoom level by the masked signal. After all, a real-time audio-zoom system is implemented on an ARM-CORETEX-A8 having a clock speed of 600 MHz after different levels of optimization are performed such as algorithmic level, C-code, and memory optimizations. To evaluate the complexity of the proposed real-time audio-zoom system, test data whose length is 21.3 seconds long is sampled at 48 kHz. As a result, it is shown from the experiments that the processing time for the proposed audio-zoom system occupies 14.6% or less of the ARM clock cycles. It is also shown from the experimental results performed in a semi-anechoic chamber that the signal with the front direction can be amplified by approximately 10 dB compared to the other directions.

Signal-to-noise enhancement techniques for quantum cascade absorption spectrometers employing optimal filtering and other approaches

NASA Astrophysics Data System (ADS)

Disselkamp, R. S.; Kelly, J. F.; Sams, R. L.; Anderson, G. A.

Optical feedback to the laser source in tunable diode laser spectroscopy (TDLS) is known to create intensity modulation noise due to elatoning and optical feedback (i.e. multiplicative technical noise) that usually limits spectral signal-to-noise (S/N). The large technical noise often limits absorption spectroscopy to noise floors 100-fold greater than the Poisson shot noise limit due to fluctuations in the laser intensity. The high output powers generated from quantum cascade (QC) lasers, along with their high gain, makes these injection laser systems especially susceptible to technical noise. In this article we discuss a method of using optimal filtering to reduce technical noise. We have observed S/N enhancements ranging from 20% to a factor of 50. The degree to which optimal filtering enhances S/N depends on the similarity between the Fourier components of the technical noise and those of the signal, with lower S/N enhancements observed for more similar Fourier decompositions of the signal and technical noise. We also examine the linearity of optimal filtered spectra in both time and intensity. This was accomplished by creating a synthetic spectrum for the species being studied (CH4, N2O, CO2 and H2O in ambient air) utilizing line positions and linewidths with an assumed Voigt profile from a commercial database (HITRAN). Agreement better than 0.036% in wavenumber and 1.64% in intensity (up to a 260-fold intensity ratio employed) was observed. Our results suggest that rapid ex post facto digital optimal filtering can be used to enhance S/N for routine trace gas detection.

Optimization and application of cooled avalanche photodiodes for spectroscopic fluctuation measurements with ultra-fast charge exchange recombination spectroscopy

DOE PAGES

Truong, D. D.; Fonck, R. J.; McKee, G. R.

2016-09-23

The Ultra Fast Charge Exchange Recombination Spectroscopy (UF-CHERS) diagnostic is a highly specialized spectroscopic instrument with 2 spatial channels consisting of 8 spectral channels each and a resolution of ~0.25 nm deployed at DIII-D to measure turbulent ion temperature fluctuations. Charge exchange emissions are obtained between 528-530 nm with 1 μs time resolution to study plasma instabilities. A primary challenge of extracting fluctuation measurements from raw UF-CHERS signals is photon and electronic noise. In order to reduce dark current, the Avalanche Photodiode (APD) detectors are thermoelectrically cooled. State-of-the-art components are used for the signal amplifiers and conditioners to minimize electronicmore » noise. Due to the low incident photon power (≤ 1 nW), APDs with a gain of up to 300 are used to optimize the signal to noise ratio. Maximizing the APDs’ gain while minimizing the excess noise factor (ENF) is essential since the total noise of the diagnostic sets a floor for the minimum level of detectable broadband fluctuations. The APDs’ gain should be high enough that photon noise dominates electronic noise, but not excessive so that the ENF overwhelms plasma fluctuations. A new generation of cooled APDs and optimized preamplifiers exhibits significantly enhanced signal-to-noise compared to a previous generation. Experiments at DIII-D have allowed for characterization and optimization of the ENF vs. gain. Here, a gain of ~100 at 1700 V is found to be near optimal for most plasma conditions. Ion temperature and toroidal velocity fluctuations due to the Edge Harmonic Oscillation (EHO) in Quiescent H-mode (QH) plasmas are presented to demonstrate UF-CHERS’ capabilities.« less

Simulating GPS radio signal to synchronize network--a new technique for redundant timing.

PubMed

Shan, Qingxiao; Jun, Yang; Le Floch, Jean-Michel; Fan, Yaohui; Ivanov, Eugene N; Tobar, Michael E

2014-07-01

Currently, many distributed systems such as 3G mobile communications and power systems are time synchronized with a Global Positioning System (GPS) signal. If there is a GPS failure, it is difficult to realize redundant timing, and thus time-synchronized devices may fail. In this work, we develop time transfer by simulating GPS signals, which promises no extra modification to original GPS-synchronized devices. This is achieved by applying a simplified GPS simulator for synchronization purposes only. Navigation data are calculated based on a pre-assigned time at a fixed position. Pseudo-range data which describes the distance change between the space vehicle (SV) and users are calculated. Because real-time simulation requires heavy-duty computations, we use self-developed software optimized on a PC to generate data, and save the data onto memory disks while the simulator is operating. The radio signal generation is similar to the SV at an initial position, and the frequency synthesis of the simulator is locked to a pre-assigned time. A filtering group technique is used to simulate the signal transmission delay corresponding to the SV displacement. Each SV generates a digital baseband signal, where a unique identifying code is added to the signal and up-converted to generate the output radio signal at the centered frequency of 1575.42 MHz (L1 band). A prototype with a field-programmable gate array (FPGA) has been built and experiments have been conducted to prove that we can realize time transfer. The prototype has been applied to the CDMA network for a three-month long experiment. Its precision has been verified and can meet the requirements of most telecommunication systems.

Time-frequency techniques in biomedical signal analysis. a tutorial review of similarities and differences.

PubMed

Wacker, M; Witte, H

2013-01-01

This review outlines the methodological fundamentals of the most frequently used non-parametric time-frequency analysis techniques in biomedicine and their main properties, as well as providing decision aids concerning their applications. The short-term Fourier transform (STFT), the Gabor transform (GT), the S-transform (ST), the continuous Morlet wavelet transform (CMWT), and the Hilbert transform (HT) are introduced as linear transforms by using a unified concept of the time-frequency representation which is based on a standardized analytic signal. The Wigner-Ville distribution (WVD) serves as an example of the 'quadratic transforms' class. The combination of WVD and GT with the matching pursuit (MP) decomposition and that of the HT with the empirical mode decomposition (EMD) are explained; these belong to the class of signal-adaptive approaches. Similarities between linear transforms are demonstrated and differences with regard to the time-frequency resolution and interference (cross) terms are presented in detail. By means of simulated signals the effects of different time-frequency resolutions of the GT, CMWT, and WVD as well as the resolution-related properties of the interference (cross) terms are shown. The method-inherent drawbacks and their consequences for the application of the time-frequency techniques are demonstrated by instantaneous amplitude, frequency and phase measures and related time-frequency representations (spectrogram, scalogram, time-frequency distribution, phase-locking maps) of measured magnetoencephalographic (MEG) signals. The appropriate selection of a method and its parameter settings will ensure readability of the time-frequency representations and reliability of results. When the time-frequency characteristics of a signal strongly correspond with the time-frequency resolution of the analysis then a method may be considered 'optimal'. The MP-based signal-adaptive approaches are preferred as these provide an appropriate time-frequency resolution for all frequencies while simultaneously reducing interference (cross) terms.

Mathematical Sciences Division 1992 Programs

DTIC Science & Technology

1992-10-01

statistical theory that underlies modern signal analysis . There is a strong emphasis on stochastic processes and time series , particularly those which...include optimal resource planning and real- time scheduling of stochastic shop-floor processes. Scheduling systems will be developed that can adapt to...make forecasts for the length-of-service time series . Protocol analysis of these sessions will be used to idenify relevant contextual features and to

Regulation of Phagocyte Migration by Signal Regulatory Protein-Alpha Signaling.

PubMed

Alvarez-Zarate, Julian; Matlung, Hanke L; Matozaki, Takashi; Kuijpers, Taco W; Maridonneau-Parini, Isabelle; van den Berg, Timo K

2015-01-01

Signaling through the inhibitory receptor signal regulatory protein-alpha (SIRPα) controls effector functions in phagocytes. However, there are also indications that interactions between SIRPα and its ligand CD47 are involved in phagocyte transendothelial migration. We have investigated the involvement of SIRPα signaling in phagocyte migration in vitro and in vivo using mice that lack the SIRPα cytoplasmic tail. During thioglycolate-induced peritonitis in SIRPα mutant mice, both neutrophil and macrophage influx were found to occur, but to be significantly delayed. SIRPα signaling appeared to be essential for an optimal transendothelial migration and chemotaxis, and for the amoeboid type of phagocyte migration in 3-dimensional environments. These findings demonstrate, for the first time, that SIRPα signaling can directly control phagocyte migration, and this may contribute to the impaired inflammatory phenotype that has been observed in the absence of SIRPα signaling.

Tunable Signal-Off and Signal-On Electrochemical Cisplatin Sensor.

PubMed

Wu, Yao; Lai, Rebecca Y

2017-09-19

We report the first electrochemical cisplatin sensor fabricated with a thiolated and methylene blue (MB)-modified oligo-adenine (A)-guanine (G) DNA probe. Depending on the probe coverage, the sensor can behave as a signal-off or signal-on sensor. For the high-coverage sensor, formation of intrastrand Pt(II)-AG adducts rigidifies the oligo-AG probe, resulting in a concentration-dependent decrease in the MB signal. For the low-coverage sensor, the increase in probe-to-probe spacing enables binding of cisplatin via the intrastrand GNG motif (N = A), generating a bend in the probe which results in an increase in the MB current. Although both high-coverage signal-off and low-coverage signal-on sensors are capable of detecting cisplatin, the signal-on sensing mechanism is better suited for real time analysis of cisplatin. The low-coverage sensor has a lower limit of detection, wider optimal AC frequency range, and faster response time. It has high specificity for cisplatin and potentially other Pt(II) drugs and does not cross-react with satraplatin, a Pt(IV) prodrug. It is also selective enough to be employed directly in 50% saliva and 50% urine. This detection strategy may offer a new approach for sensitive and real time analysis of cisplatin in clinical samples.

Signal-to-noise ratio estimation on SEM images using cubic spline interpolation with Savitzky-Golay smoothing.

PubMed

Sim, K S; Kiani, M A; Nia, M E; Tso, C P

2014-01-01

A new technique based on cubic spline interpolation with Savitzky-Golay noise reduction filtering is designed to estimate signal-to-noise ratio of scanning electron microscopy (SEM) images. This approach is found to present better result when compared with two existing techniques: nearest neighbourhood and first-order interpolation. When applied to evaluate the quality of SEM images, noise can be eliminated efficiently with optimal choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Compact multiwire proportional counters for the detection of fission fragments

NASA Astrophysics Data System (ADS)

Jhingan, Akhil; Sugathan, P.; Golda, K. S.; Singh, R. P.; Varughese, T.; Singh, Hardev; Behera, B. R.; Mandal, S. K.

2009-12-01

Two large area multistep position sensitive (two dimensional) multiwire proportional counters have been developed for experiments involving study of fission dynamics using general purpose scattering chamber facility at IUAC. Both detectors have an active area of 20×10 cm2 and provide position signals in horizontal (X) and vertical (Y) planes, timing signal for time of flight measurements and energy signal giving the differential energy loss in the active volume. The design features are optimized for the detection of low energy heavy ions at very low gas pressures. Special care was taken in setting up the readout electronics, constant fraction discriminators for position signals in particular, to get optimum position and timing resolutions along with high count rate handling capability of low energy heavy ions. A custom made charge sensitive preamplifier, having lower gain and shorter decay time, has been developed for extracting the differential energy loss signal. The position and time resolutions of the detectors were determined to be 1.1 mm full width at half maximum (FWHM) and 1.7 ns FWHM, respectively. The detector could handle heavy ion count rates exceeding 20 kHz without any breakdown. Time of flight signal in combination with differential energy loss signal gives a clean separation of fission fragments from projectile and target like particles. The timing and position signals of the detectors are used for fission coincidence measurements and subsequent extraction of their mass, angular, and total kinetic energy distributions. This article describes systematic study of these fission counters in terms of efficiency, time resolution, count rate handling capability, position resolution, and the readout electronics. The detector has been operated with both five electrode geometry and four electrode geometry, and a comparison has been made in their performances.

Neural signal processing and closed-loop control algorithm design for an implanted neural recording and stimulation system.

PubMed

Hamilton, Lei; McConley, Marc; Angermueller, Kai; Goldberg, David; Corba, Massimiliano; Kim, Louis; Moran, James; Parks, Philip D; Sang Chin; Widge, Alik S; Dougherty, Darin D; Eskandar, Emad N

2015-08-01

A fully autonomous intracranial device is built to continually record neural activities in different parts of the brain, process these sampled signals, decode features that correlate to behaviors and neuropsychiatric states, and use these features to deliver brain stimulation in a closed-loop fashion. In this paper, we describe the sampling and stimulation aspects of such a device. We first describe the signal processing algorithms of two unsupervised spike sorting methods. Next, we describe the LFP time-frequency analysis and feature derivation from the two spike sorting methods. Spike sorting includes a novel approach to constructing a dictionary learning algorithm in a Compressed Sensing (CS) framework. We present a joint prediction scheme to determine the class of neural spikes in the dictionary learning framework; and, the second approach is a modified OSort algorithm which is implemented in a distributed system optimized for power efficiency. Furthermore, sorted spikes and time-frequency analysis of LFP signals can be used to generate derived features (including cross-frequency coupling, spike-field coupling). We then show how these derived features can be used in the design and development of novel decode and closed-loop control algorithms that are optimized to apply deep brain stimulation based on a patient's neuropsychiatric state. For the control algorithm, we define the state vector as representative of a patient's impulsivity, avoidance, inhibition, etc. Controller parameters are optimized to apply stimulation based on the state vector's current state as well as its historical values. The overall algorithm and software design for our implantable neural recording and stimulation system uses an innovative, adaptable, and reprogrammable architecture that enables advancement of the state-of-the-art in closed-loop neural control while also meeting the challenges of system power constraints and concurrent development with ongoing scientific research designed to define brain network connectivity and neural network dynamics that vary at the individual patient level and vary over time.

Binaural noise reduction via cue-preserving MMSE filter and adaptive-blocking-based noise PSD estimation

NASA Astrophysics Data System (ADS)

Azarpour, Masoumeh; Enzner, Gerald

2017-12-01

Binaural noise reduction, with applications for instance in hearing aids, has been a very significant challenge. This task relates to the optimal utilization of the available microphone signals for the estimation of the ambient noise characteristics and for the optimal filtering algorithm to separate the desired speech from the noise. The additional requirements of low computational complexity and low latency further complicate the design. A particular challenge results from the desired reconstruction of binaural speech input with spatial cue preservation. The latter essentially diminishes the utility of multiple-input/single-output filter-and-sum techniques such as beamforming. In this paper, we propose a comprehensive and effective signal processing configuration with which most of the aforementioned criteria can be met suitably. This relates especially to the requirement of efficient online adaptive processing for noise estimation and optimal filtering while preserving the binaural cues. Regarding noise estimation, we consider three different architectures: interaural (ITF), cross-relation (CR), and principal-component (PCA) target blocking. An objective comparison with two other noise PSD estimation algorithms demonstrates the superiority of the blocking-based noise estimators, especially the CR-based and ITF-based blocking architectures. Moreover, we present a new noise reduction filter based on minimum mean-square error (MMSE), which belongs to the class of common gain filters, hence being rigorous in terms of spatial cue preservation but also efficient and competitive for the acoustic noise reduction task. A formal real-time subjective listening test procedure is also developed in this paper. The proposed listening test enables a real-time assessment of the proposed computationally efficient noise reduction algorithms in a realistic acoustic environment, e.g., considering time-varying room impulse responses and the Lombard effect. The listening test outcome reveals that the signals processed by the blocking-based algorithms are significantly preferred over the noisy signal in terms of instantaneous noise attenuation. Furthermore, the listening test data analysis confirms the conclusions drawn based on the objective evaluation.

Optimization of noise in non-integrated instrumentation amplifier for the amplification of very low electrophysiological [corrected] signals. Case of electro cardio graphic signals (ECG).

PubMed

Ngounou, Guy Merlin; Kom, Martin

2014-12-01

In this paper we present an instrumentation amplifier with discrete elements and optimized noise for the amplification of very low signals. In amplifying signals of very weak amplitude, the noise can completely absorb these signals if the used amplifier does not present the optimal guarantee to minimize the noise. Based on related research and re-viewing of recent patents Journal of Medical Systems, 30:205-209, 2006, we suggest an approach of noise reduction in amplification much more thoroughly than re-viewing of recent patents and we deduce from it the general criteria necessary and essential to achieve this optimization. The comparison of these criteria with the provisions adopted in practice leads to the inadequacy of conventional amplifiers for effective noise reduction. The amplifier we propose is an instrumentation amplifier with active negative feedback and optimized noise for the amplification of signals with very low amplitude. The application of this method in the case of electro cardio graphic signals (ECG) provides simulation results fully in line with forecasts.

Warning systems in risk management.

PubMed

Paté-Cornell, M E

1986-06-01

A method is presented here that allows probabilistic evaluation and optimization of warning systems, and comparison of their performance and cost-effectiveness with those of other means of risk management. The model includes an assessment of the signals, and of human response, given the memory that people have kept of the quality of previous alerts. The trade-off between the rate of false alerts and the length of the lead time is studied to account for the long-term effects of "crying wolf" and the effectiveness of emergency actions. An explicit formulation of the system's benefits, including inputs from a signal model, a response model, and a consequence model, is given to allow optimization of the warning threshold and of the system's sensitivity.

Isotopic identification using Pulse Shape Analysis of current signals from silicon detectors: Recent results from the FAZIA collaboration

NASA Astrophysics Data System (ADS)

Pastore, G.; Gruyer, D.; Ottanelli, P.; Le Neindre, N.; Pasquali, G.; Alba, R.; Barlini, S.; Bini, M.; Bonnet, E.; Borderie, B.; Bougault, R.; Bruno, M.; Casini, G.; Chbihi, A.; Dell'Aquila, D.; Dueñas, J. A.; Fabris, D.; Francalanza, L.; Frankland, J. D.; Gramegna, F.; Henri, M.; Kordyasz, A.; Kozik, T.; Lombardo, I.; Lopez, O.; Morelli, L.; Olmi, A.; Pârlog, M.; Piantelli, S.; Poggi, G.; Santonocito, D.; Stefanini, A. A.; Valdré, S.; Verde, G.; Vient, E.; Vigilante, M.; FAZIA Collaboration

2017-07-01

The FAZIA apparatus exploits Pulse Shape Analysis (PSA) to identify nuclear fragments stopped in the first layer of a Silicon-Silicon-CsI(Tl) detector telescope. In this work, for the first time, we show that the isotopes of fragments having atomic number as high as Z∼20 can be identified. Such a remarkable result has been obtained thanks to a careful construction of the Si detectors and to the use of low noise and high performance digitizing electronics. Moreover, optimized PSA algorithms are needed. This work deals with the choice of the best algorithm for PSA of current signals. A smoothing spline algorithm is demonstrated to give optimal results without requiring too much computational resources.

Designing lymphocyte functional structure for optimal signal detection: voilà, T cells.

PubMed

Noest, A J

2000-11-21

One basic task of immune systems is to detect signals from unknown "intruders" amidst a noisy background of harmless signals. To clarify the functional importance of many observed lymphocyte properties, I ask: What properties would a cell have if one designed it according to the theory of optimal detection, with minimal regard for biological constraints? Sparse and reasonable assumptions about the statistics of available signals prove sufficient for deriving many features of the optimal functional structure, in an incremental and modular design. The use of one common formalism guarantees that all parts of the design collaborate to solve the detection task. Detection performance is computed at several stages of the design. Comparison between design variants reveals e.g. the importance of controlling the signal integration time. This predicts that an appropriate control mechanism should exist. Comparing the design to reality, I find a striking similarity with many features of T cells. For example, the formalism dictates clonal specificity, serial receptor triggering, (grades of) anergy, negative and positive selection, co-stimulation, high-zone tolerance, and clonal production of cytokines. Serious mismatches should be found if T cells were hindered by mechanistic constraints or vestiges of their (co-)evolutionary history, but I have not found clear examples. By contrast, fundamental mismatches abound when comparing the design to immune systems of e.g. invertebrates. The wide-ranging differences seem to hinge on the (in)ability to generate a large diversity of receptors. Copyright 2000 Academic Press.

Fine tuning breath-hold-based cerebrovascular reactivity analysis models.

PubMed

van Niftrik, Christiaan Hendrik Bas; Piccirelli, Marco; Bozinov, Oliver; Pangalu, Athina; Valavanis, Antonios; Regli, Luca; Fierstra, Jorn

2016-02-01

We elaborate on existing analysis methods for breath-hold (BH)-derived cerebrovascular reactivity (CVR) measurements and describe novel insights and models toward more exact CVR interpretation. Five blood-oxygen-level-dependent (BOLD) fMRI datasets of neurovascular patients with unilateral hemispheric hemodynamic impairment were used to test various BH CVR analysis methods. Temporal lag (phase), percent BOLD signal change (CVR), and explained variance (coherence) maps were calculated using three different sine models and two novel "Optimal Signal" model-free methods based on the unaffected hemisphere and the sagittal sinus fMRI signal time series, respectively. All models showed significant differences in CVR and coherence between the affected-hemodynamic impaired-and unaffected hemisphere. Voxel-wise phase determination significantly increases CVR (0.60 ± 0.18 vs. 0.82 ± 0.27; P < 0.05). Incorporating different durations of breath hold and resting period in one sine model (two-task) did increase coherence in the unaffected hemisphere, as well as eliminating negative phase commonly obtained by one-task frequency models. The novel model-free "optimal signal" methods both explained the BOLD MR data similar to the two task sine model. Our CVR analysis demonstrates an improved CVR and coherence after implementation of voxel-wise phase and frequency adjustment. The novel "optimal signal" methods provide a robust and feasible alternative to the sine models, as both are model-free and independent of compliance. Here, the sagittal sinus model may be advantageous, as it is independent of hemispheric CVR impairment.

A Survey on Optimal Signal Processing Techniques Applied to Improve the Performance of Mechanical Sensors in Automotive Applications

PubMed Central

Hernandez, Wilmar

2007-01-01

In this paper a survey on recent applications of optimal signal processing techniques to improve the performance of mechanical sensors is made. Here, a comparison between classical filters and optimal filters for automotive sensors is made, and the current state of the art of the application of robust and optimal control and signal processing techniques to the design of the intelligent (or smart) sensors that today's cars need is presented through several experimental results that show that the fusion of intelligent sensors and optimal signal processing techniques is the clear way to go. However, the switch between the traditional methods of designing automotive sensors and the new ones cannot be done overnight because there are some open research issues that have to be solved. This paper draws attention to one of the open research issues and tries to arouse researcher's interest in the fusion of intelligent sensors and optimal signal processing techniques.

Kalman Orbit Optimized Loop Tracking

NASA Technical Reports Server (NTRS)

Young, Lawrence E.; Meehan, Thomas K.

2011-01-01

Under certain conditions of low signal power and/or high noise, there is insufficient signal to noise ratio (SNR) to close tracking loops with individual signals on orbiting Global Navigation Satellite System (GNSS) receivers. In addition, the processing power available from flight computers is not great enough to implement a conventional ultra-tight coupling tracking loop. This work provides a method to track GNSS signals at very low SNR without the penalty of requiring very high processor throughput to calculate the loop parameters. The Kalman Orbit-Optimized Loop (KOOL) tracking approach constitutes a filter with a dynamic model and using the aggregate of information from all tracked GNSS signals to close the tracking loop for each signal. For applications where there is not a good dynamic model, such as very low orbits where atmospheric drag models may not be adequate to achieve the required accuracy, aiding from an IMU (inertial measurement unit) or other sensor will be added. The KOOL approach is based on research JPL has done to allow signal recovery from weak and scintillating signals observed during the use of GPS signals for limb sounding of the Earth s atmosphere. That approach uses the onboard PVT (position, velocity, time) solution to generate predictions for the range, range rate, and acceleration of the low-SNR signal. The low- SNR signal data are captured by a directed open loop. KOOL builds on the previous open loop tracking by including feedback and observable generation from the weak-signal channels so that the MSR receiver will continue to track and provide PVT, range, and Doppler data, even when all channels have low SNR.

A real-time traffic control method for the intersection with pre-signals under the phase swap sorting strategy

PubMed Central

Bie, Yiming; Wang, Yinhai

2017-01-01

To deal with the conflicts between left-turn and through traffic streams and increase the discharge capacity, this paper addresses the pre-signal which is implemented at a signalized intersection. Such an intersection with pre-signal is termed as a tandem intersection. For the tandem intersection, phase swap sorting strategy is deemed as the most effective phasing scheme in view of some exclusive merits, such as easier compliance of drivers, and shorter sorting area. However, a major limitation of the phase swap sorting strategy is not considered in previous studies: if one or more vehicle is left at the sorting area after the signal light turns to red, the capacity of the approach would be dramatically dropped. Besides, previous signal control studies deal with a fixed timing plan that is not adaptive with the fluctuation of traffic flows. Therefore, to cope with these two gaps, this paper firstly takes an in-depth analysis of the traffic flow operations at the tandem intersection. Secondly, three groups of loop detectors are placed to obtain the real-time vehicle information for adaptive signalization. The lane selection behavior in the sorting area is considered to set the green time for intersection signals. With the objective of minimizing the vehicle delay, the signal control parameters are then optimized based on a dynamic programming method. Finally, numerical experiments show that average vehicle delay and maximum queue length can be reduced under all scenarios. PMID:28531198

A real-time traffic control method for the intersection with pre-signals under the phase swap sorting strategy.

PubMed

Bie, Yiming; Liu, Zhiyuan; Wang, Yinhai

2017-01-01

To deal with the conflicts between left-turn and through traffic streams and increase the discharge capacity, this paper addresses the pre-signal which is implemented at a signalized intersection. Such an intersection with pre-signal is termed as a tandem intersection. For the tandem intersection, phase swap sorting strategy is deemed as the most effective phasing scheme in view of some exclusive merits, such as easier compliance of drivers, and shorter sorting area. However, a major limitation of the phase swap sorting strategy is not considered in previous studies: if one or more vehicle is left at the sorting area after the signal light turns to red, the capacity of the approach would be dramatically dropped. Besides, previous signal control studies deal with a fixed timing plan that is not adaptive with the fluctuation of traffic flows. Therefore, to cope with these two gaps, this paper firstly takes an in-depth analysis of the traffic flow operations at the tandem intersection. Secondly, three groups of loop detectors are placed to obtain the real-time vehicle information for adaptive signalization. The lane selection behavior in the sorting area is considered to set the green time for intersection signals. With the objective of minimizing the vehicle delay, the signal control parameters are then optimized based on a dynamic programming method. Finally, numerical experiments show that average vehicle delay and maximum queue length can be reduced under all scenarios.

Compressive Sensing of Foot Gait Signals and Its Application for the Estimation of Clinically Relevant Time Series.

PubMed

Pant, Jeevan K; Krishnan, Sridhar

2016-07-01

A new signal reconstruction algorithm for compressive sensing based on the minimization of a pseudonorm which promotes block-sparse structure on the first-order difference of the signal is proposed. Involved optimization is carried out by using a sequential version of Fletcher-Reeves' conjugate-gradient algorithm, and the line search is based on Banach's fixed-point theorem. The algorithm is suitable for the reconstruction of foot gait signals which admit block-sparse structure on the first-order difference. An additional algorithm for the estimation of stride-interval, swing-interval, and stance-interval time series from the reconstructed foot gait signals is also proposed. This algorithm is based on finding zero crossing indices of the foot gait signal and using the resulting indices for the computation of time series. Extensive simulation results demonstrate that the proposed signal reconstruction algorithm yields improved signal-to-noise ratio and requires significantly reduced computational effort relative to several competing algorithms over a wide range of compression ratio. For a compression ratio in the range from 88% to 94%, the proposed algorithm is found to offer improved accuracy for the estimation of clinically relevant time-series parameters, namely, the mean value, variance, and spectral index of stride-interval, stance-interval, and swing-interval time series, relative to its nearest competitor algorithm. The improvement in performance for compression ratio as high as 94% indicates that the proposed algorithms would be useful for designing compressive sensing-based systems for long-term telemonitoring of human gait signals.

Improvement on Exoplanet Detection Methods and Analysis via Gaussian Process Fitting Techniques

NASA Astrophysics Data System (ADS)

Van Ross, Bryce; Teske, Johanna

2018-01-01

Planetary signals in radial velocity (RV) data are often accompanied by signals coming solely from stellar photo- or chromospheric variation. Such variation can reduce the precision of planet detection and mass measurements, and cause misidentification of planetary signals. Recently, several authors have demonstrated the utility of Gaussian Process (GP) regression for disentangling planetary signals in RV observations (Aigrain et al. 2012; Angus et al. 2017; Czekala et al. 2017; Faria et al. 2016; Gregory 2015; Haywood et al. 2014; Rajpaul et al. 2015; Foreman-Mackey et al. 2017). GP models the covariance of multivariate data to make predictions about likely underlying trends in the data, which can be applied to regions where there are no existing observations. The potency of GP has been used to infer stellar rotation periods; to model and disentangle time series spectra; and to determine physical aspects, populations, and detection of exoplanets, among other astrophysical applications. Here, we implement similar analysis techniques to times series of the Ca-2 H and K activity indicator measured simultaneously with RVs in a small sample of stars from the large Keck/HIRES RV planet search program. Our goal is to characterize the pattern(s) of non-planetary variation to be able to know what is/ is not a planetary signal. We investigated ten different GP kernels and their respective hyperparameters to determine the optimal combination (e.g., the lowest Bayesian Information Criterion value) in each stellar data set. To assess the hyperparameters’ error, we sampled their posterior distributions using Markov chain Monte Carlo (MCMC) analysis on the optimized kernels. Our results demonstrate how GP analysis of stellar activity indicators alone can contribute to exoplanet detection in RV data, and highlight the challenges in applying GP analysis to relatively small, irregularly sampled time series.

Monte Carlo modeling of time-resolved fluorescence for depth-selective interrogation of layered tissue.

PubMed

Pfefer, T Joshua; Wang, Quanzeng; Drezek, Rebekah A

2011-11-01

Computational approaches for simulation of light-tissue interactions have provided extensive insight into biophotonic procedures for diagnosis and therapy. However, few studies have addressed simulation of time-resolved fluorescence (TRF) in tissue and none have combined Monte Carlo simulations with standard TRF processing algorithms to elucidate approaches for cancer detection in layered biological tissue. In this study, we investigate how illumination-collection parameters (e.g., collection angle and source-detector separation) influence the ability to measure fluorophore lifetime and tissue layer thickness. Decay curves are simulated with a Monte Carlo TRF light propagation model. Multi-exponential iterative deconvolution is used to determine lifetimes and fractional signal contributions. The ability to detect changes in mucosal thickness is optimized by probes that selectively interrogate regions superficial to the mucosal-submucosal boundary. Optimal accuracy in simultaneous determination of lifetimes in both layers is achieved when each layer contributes 40-60% of the signal. These results indicate that depth-selective approaches to TRF have the potential to enhance disease detection in layered biological tissue and that modeling can play an important role in probe design optimization. Published by Elsevier Ireland Ltd.

Approximation of optimal filter for Ornstein-Uhlenbeck process with quantised discrete-time observation

NASA Astrophysics Data System (ADS)

Bania, Piotr; Baranowski, Jerzy

2018-02-01

Quantisation of signals is a ubiquitous property of digital processing. In many cases, it introduces significant difficulties in state estimation and in consequence control. Popular approaches either do not address properly the problem of system disturbances or lead to biased estimates. Our intention was to find a method for state estimation for stochastic systems with quantised and discrete observation, that is free of the mentioned drawbacks. We have formulated a general form of the optimal filter derived by a solution of Fokker-Planck equation. We then propose the approximation method based on Galerkin projections. We illustrate the approach for the Ornstein-Uhlenbeck process, and derive analytic formulae for the approximated optimal filter, also extending the results for the variant with control. Operation is illustrated with numerical experiments and compared with classical discrete-continuous Kalman filter. Results of comparison are substantially in favour of our approach, with over 20 times lower mean squared error. The proposed filter is especially effective for signal amplitudes comparable to the quantisation thresholds. Additionally, it was observed that for high order of approximation, state estimate is very close to the true process value. The results open the possibilities of further analysis, especially for more complex processes.

Rapid optimization method of the strong stray light elimination for extremely weak light signal detection.

PubMed

Wang, Geng; Xing, Fei; Wei, Minsong; You, Zheng

2017-10-16

The strong stray light has huge interference on the detection of weak and small optical signals, and is difficult to suppress. In this paper, a miniaturized baffle with angled vanes was proposed and a rapid optimization model of strong light elimination was built, which has better suppression of the stray lights than the conventional vanes and can optimize the positions of the vanes efficiently and accurately. Furthermore, the light energy distribution model was built based on the light projection at a specific angle, and the light propagation models of the vanes and sidewalls were built based on the Lambert scattering, both of which act as the bias of a calculation method of stray light. Moreover, the Monte-Carlo method was employed to realize the Point Source Transmittance (PST) simulation, and the simulation result indicated that it was consistent with the calculation result based on our models, and the PST could be improved by 2-3 times at the small incident angles for the baffle designed by the new method. Meanwhile, the simulation result was verified by laboratory tests, and the new model with derived analytical expressions which can reduce the simulation time significantly.

Development of a Dual Plasma Desorption/Ionization System for the Noncontact and Highly Sensitive Analysis of Surface Adhesive Compounds

PubMed Central

Aida, Mari; Iwai, Takahiro; Okamoto, Yuki; Kohno, Satoshi; Kakegawa, Ken; Miyahara, Hidekazu; Seto, Yasuo; Okino, Akitoshi

2017-01-01

We developed a dual plasma desorption/ionization system using two plasmas for the semi-invasive analysis of compounds on heat-sensitive substrates such as skin. The first plasma was used for the desorption of the surface compounds, whereas the second was used for the ionization of the desorbed compounds. Using the two plasmas, each process can be optimized individually. A successful analysis of phenyl salicylate and 2-isopropylpyridine was achieved using the developed system. Furthermore, we showed that it was possible to detect the mass signals derived from a sample even at a distance 50 times greater than the distance from the position at which the samples were detached. In addition, to increase the intensity of the mass signal, 0%–0.02% (v/v) of hydrogen gas was added to the base gas generated in the ionizing plasma. We found that by optimizing the gas flow rate through the addition of a small amount of hydrogen gas, it was possible to obtain the intensity of the mass signal that was 45–824 times greater than that obtained without the addition of hydrogen gas. PMID:29234573

Computing an optimal time window of audiovisual integration in focused attention tasks: illustrated by studies on effect of age and prior knowledge.

PubMed

Colonius, Hans; Diederich, Adele

2011-07-01

The concept of a "time window of integration" holds that information from different sensory modalities must not be perceived too far apart in time in order to be integrated into a multisensory perceptual event. Empirical estimates of window width differ widely, however, ranging from 40 to 600 ms depending on context and experimental paradigm. Searching for theoretical derivation of window width, Colonius and Diederich (Front Integr Neurosci 2010) developed a decision-theoretic framework using a decision rule that is based on the prior probability of a common source, the likelihood of temporal disparities between the unimodal signals, and the payoff for making right or wrong decisions. Here, this framework is extended to the focused attention task where subjects are asked to respond to signals from a target modality only. Evoking the framework of the time-window-of-integration (TWIN) model, an explicit expression for optimal window width is obtained. The approach is probed on two published focused attention studies. The first is a saccadic reaction time study assessing the efficiency with which multisensory integration varies as a function of aging. Although the window widths for young and older adults differ by nearly 200 ms, presumably due to their different peripheral processing speeds, neither of them deviates significantly from the optimal values. In the second study, head saccadic reactions times to a perfectly aligned audiovisual stimulus pair had been shown to depend on the prior probability of spatial alignment. Intriguingly, they reflected the magnitude of the time-window widths predicted by our decision-theoretic framework, i.e., a larger time window is associated with a higher prior probability.

A codon-optimized green fluorescent protein for live cell imaging in Zymoseptoria tritici☆

PubMed Central

Kilaru, S.; Schuster, M.; Studholme, D.; Soanes, D.; Lin, C.; Talbot, N.J.; Steinberg, G.

2015-01-01

Fluorescent proteins (FPs) are powerful tools to investigate intracellular dynamics and protein localization. Cytoplasmic expression of FPs in fungal pathogens allows greater insight into invasion strategies and the host-pathogen interaction. Detection of their fluorescent signal depends on the right combination of microscopic setup and signal brightness. Slow rates of photo-bleaching are pivotal for in vivo observation of FPs over longer periods of time. Here, we test green-fluorescent proteins, including Aequorea coerulescens GFP (AcGFP), enhanced GFP (eGFP) from Aequorea victoria and a novel Zymoseptoria tritici codon-optimized eGFP (ZtGFP), for their usage in conventional and laser-enhanced epi-fluorescence, and confocal laser-scanning microscopy. We show that eGFP, expressed cytoplasmically in Z. tritici, is significantly brighter and more photo-stable than AcGFP. The codon-optimized ZtGFP performed even better than eGFP, showing significantly slower bleaching and a 20–30% further increase in signal intensity. Heterologous expression of all GFP variants did not affect pathogenicity of Z. tritici. Our data establish ZtGFP as the GFP of choice to investigate intracellular protein dynamics in Z. tritici, but also infection stages of this wheat pathogen inside host tissue. PMID:26092799

Design of an optimal preview controller for linear discrete-time descriptor systems with state delay

NASA Astrophysics Data System (ADS)

Cao, Mengjuan; Liao, Fucheng

2015-04-01

In this paper, the linear discrete-time descriptor system with state delay is studied, and a design method for an optimal preview controller is proposed. First, by using the discrete lifting technique, the original system is transformed into a general descriptor system without state delay in form. Then, taking advantage of the first-order forward difference operator, we construct a descriptor augmented error system, including the state vectors of the lifted system, error vectors, and desired target signals. Rigorous mathematical proofs are given for the regularity, stabilisability, causal controllability, and causal observability of the descriptor augmented error system. Based on these, the optimal preview controller with preview feedforward compensation for the original system is obtained by using the standard optimal regulator theory of the descriptor system. The effectiveness of the proposed method is shown by numerical simulation.

Optimal experimental design for parameter estimation of a cell signaling model.

PubMed

Bandara, Samuel; Schlöder, Johannes P; Eils, Roland; Bock, Hans Georg; Meyer, Tobias

2009-11-01

Differential equation models that describe the dynamic changes of biochemical signaling states are important tools to understand cellular behavior. An essential task in building such representations is to infer the affinities, rate constants, and other parameters of a model from actual measurement data. However, intuitive measurement protocols often fail to generate data that restrict the range of possible parameter values. Here we utilized a numerical method to iteratively design optimal live-cell fluorescence microscopy experiments in order to reveal pharmacological and kinetic parameters of a phosphatidylinositol 3,4,5-trisphosphate (PIP(3)) second messenger signaling process that is deregulated in many tumors. The experimental approach included the activation of endogenous phosphoinositide 3-kinase (PI3K) by chemically induced recruitment of a regulatory peptide, reversible inhibition of PI3K using a kinase inhibitor, and monitoring of the PI3K-mediated production of PIP(3) lipids using the pleckstrin homology (PH) domain of Akt. We found that an intuitively planned and established experimental protocol did not yield data from which relevant parameters could be inferred. Starting from a set of poorly defined model parameters derived from the intuitively planned experiment, we calculated concentration-time profiles for both the inducing and the inhibitory compound that would minimize the predicted uncertainty of parameter estimates. Two cycles of optimization and experimentation were sufficient to narrowly confine the model parameters, with the mean variance of estimates dropping more than sixty-fold. Thus, optimal experimental design proved to be a powerful strategy to minimize the number of experiments needed to infer biological parameters from a cell signaling assay.

On the improvement of signal repeatability in laser-induced air plasmas

NASA Astrophysics Data System (ADS)

Zhang, Shuai; Sheta, Sahar; Hou, Zong-Yu; Wang, Zhe

2018-04-01

The relatively low repeatability of laser-induced breakdown spectroscopy (LIBS) severely hinders its wide commercialization. In the present work, we investigate the optimization of LIBS system for repeatability improvement for both signal generation (plasma evolution) and signal collection. Timeintegrated spectra and images were obtained under different laser energies and focal lengths to investigate the optimum configuration for stable plasmas and repeatable signals. Using our experimental setup, the optimum conditions were found to be a laser energy of 250 mJ and a focus length of 100 mm. A stable and homogeneous plasma with the largest hot core area in the optimum condition yielded the most stable LIBS signal. Time-resolved images showed that the rebounding processes through the air plasma evolution caused the relative standard deviation (RSD) to increase with laser energies of > 250 mJ. In addition, the emission collection was improved by using a concave spherical mirror. The line intensities doubled as their RSDs decreased by approximately 25%. When the signal generation and collection were optimized simultaneously, the pulse-to-pulse RSDs were reduced to approximately 3% for O(I), N(I), and H(I) lines, which are better than the RSDs reported for solid samples and showed great potential for LIBS quantitative analysis by gasifying the solid or liquid samples.

Sample-interpolation timing: an optimized technique for the digital measurement of time of flight for γ rays and neutrons at relatively low sampling rates

NASA Astrophysics Data System (ADS)

Aspinall, M. D.; Joyce, M. J.; Mackin, R. O.; Jarrah, Z.; Boston, A. J.; Nolan, P. J.; Peyton, A. J.; Hawkes, N. P.

2009-01-01

A unique, digital time pick-off method, known as sample-interpolation timing (SIT) is described. This method demonstrates the possibility of improved timing resolution for the digital measurement of time of flight compared with digital replica-analogue time pick-off methods for signals sampled at relatively low rates. Three analogue timing methods have been replicated in the digital domain (leading-edge, crossover and constant-fraction timing) for pulse data sampled at 8 GSa s-1. Events arising from the 7Li(p, n)7Be reaction have been detected with an EJ-301 organic liquid scintillator and recorded with a fast digital sampling oscilloscope. Sample-interpolation timing was developed solely for the digital domain and thus performs more efficiently on digital signals compared with analogue time pick-off methods replicated digitally, especially for fast signals that are sampled at rates that current affordable and portable devices can achieve. Sample interpolation can be applied to any analogue timing method replicated digitally and thus also has the potential to exploit the generic capabilities of analogue techniques with the benefits of operating in the digital domain. A threshold in sampling rate with respect to the signal pulse width is observed beyond which further improvements in timing resolution are not attained. This advance is relevant to many applications in which time-of-flight measurement is essential.

Psychophysical Models for Signal Detection with Time Varying Uncertainty. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Gai, E.

1975-01-01

Psychophysical models for the behavior of the human operator in detection tasks which include change in detectability, correlation between observations and deferred decisions are developed. Classical Signal Detection Theory (SDT) is discussed and its emphasis on the sensory processes is contrasted to decision strategies. The analysis of decision strategies utilizes detection tasks with time varying signal strength. The classical theory is modified to include such tasks and several optimal decision strategies are explored. Two methods of classifying strategies are suggested. The first method is similar to the analysis of ROC curves, while the second is based on the relation between the criterion level (CL) and the detectability. Experiments to verify the analysis of tasks with changes of signal strength are designed. The results show that subjects are aware of changes in detectability and tend to use strategies that involve changes in the CL's.

Design and implementation of intelligent electronic warfare decision making algorithm

NASA Astrophysics Data System (ADS)

Peng, Hsin-Hsien; Chen, Chang-Kuo; Hsueh, Chi-Shun

2017-05-01

Electromagnetic signals and the requirements of timely response have been a rapid growth in modern electronic warfare. Although jammers are limited resources, it is possible to achieve the best electronic warfare efficiency by tactical decisions. This paper proposes the intelligent electronic warfare decision support system. In this work, we develop a novel hybrid algorithm, Digital Pheromone Particle Swarm Optimization, based on Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Shuffled Frog Leaping Algorithm (SFLA). We use PSO to solve the problem and combine the concept of pheromones in ACO to accumulate more useful information in spatial solving process and speed up finding the optimal solution. The proposed algorithm finds the optimal solution in reasonable computation time by using the method of matrix conversion in SFLA. The results indicated that jammer allocation was more effective. The system based on the hybrid algorithm provides electronic warfare commanders with critical information to assist commanders in effectively managing the complex electromagnetic battlefield.

Reinforcement learning design-based adaptive tracking control with less learning parameters for nonlinear discrete-time MIMO systems.

PubMed

Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan

2015-01-01

Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. Consequently, compared with the existing results, the main contributions of this paper are: 1) only two parameters are needed to be adjusted, and thus the number of the adaptation laws is smaller than the previous results and 2) the updating parameters do not depend on the number of the subsystems for MIMO systems and the tuning rules are replaced by adjusting the norms on optimal weight vectors in both action and critic networks. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. The simulation examples are employed to illustrate the effectiveness of the proposed algorithm.

Optimal control of epidemic information dissemination over networks.

PubMed

Chen, Pin-Yu; Cheng, Shin-Ming; Chen, Kwang-Cheng

2014-12-01

Information dissemination control is of crucial importance to facilitate reliable and efficient data delivery, especially in networks consisting of time-varying links or heterogeneous links. Since the abstraction of information dissemination much resembles the spread of epidemics, epidemic models are utilized to characterize the collective dynamics of information dissemination over networks. From a systematic point of view, we aim to explore the optimal control policy for information dissemination given that the control capability is a function of its distribution time, which is a more realistic model in many applications. The main contributions of this paper are to provide an analytically tractable model for information dissemination over networks, to solve the optimal control signal distribution time for minimizing the accumulated network cost via dynamic programming, and to establish a parametric plug-in model for information dissemination control. In particular, we evaluate its performance in mobile and generalized social networks as typical examples.

Weighted finite impulse response filter for chromatic dispersion equalization in coherent optical fiber communication systems

NASA Astrophysics Data System (ADS)

Zeng, Ziyi; Yang, Aiying; Guo, Peng; Feng, Lihui

2018-01-01

Time-domain CD equalization using finite impulse response (FIR) filter is now a common approach for coherent optical fiber communication systems. The complex weights of FIR taps are calculated from a truncated impulse response of the CD transfer function, and the modulus of the complex weights is constant. In our work, we take the limited bandwidth of a single channel signal into account and propose weighted FIRs to improve the performance of CD equalization. The key in weighted FIR filters is the selection and optimization of weighted functions. In order to present the performance of different types of weighted FIR filters, a square-root raised cosine FIR (SRRC-FIR) and a Gaussian FIR (GS-FIR) are investigated. The optimization of square-root raised cosine FIR and Gaussian FIR are made in term of the bit rate error (BER) of QPSK and 16QAM coherent detection signal. The results demonstrate that the optimized parameters of the weighted filters are independent of the modulation format, symbol rate and the length of transmission fiber. With the optimized weighted FIRs, the BER of CD equalization signal is decreased significantly. Although this paper has investigated two types of weighted FIR filters, i.e. SRRC-FIR filter and GS-FIR filter, the principle of weighted FIR can also be extended to other symmetric functions super Gaussian function, hyperbolic secant function and etc.

Practical Considerations for Optimizing Position Sensitivity in Arrays of Position-sensitive TES's

NASA Technical Reports Server (NTRS)

Smith, Stephen J.; Bandler, Simon R.; Figueroa-Feliciano, Encetali; Iyomoto, Naoko; Kelley, Richard L.; Kilbourne, Caroline A.; Porder, Frederick S.; Sadleir, John E.

2007-01-01

We are developing Position-Sensitive Transitions-Edge Sensors (PoST's) for future X-ray astronomy missions such as NASA's Constellation-X. The PoST consists of one or more Transitions Edge Sensors (TES's) thermally connected to a large X-ray absorber, which through heat diffusion, gives rise to position dependence. The development of PoST's is motivated by the desire to achieve the largest the focal-plan coverage with the fewest number of readout channels. In order to develop a practical array, consisting of an inner pixellated core with an outer array of large absorber PoST's, we must be able to simultaneously read out all (-1800) channels in the array. This is achievable using time division multiplexing (TDM), but does set stringent slew rate requirements on the array. Typically, we must damp the pulses to reduce the slew rate of the input signal to the TDM. This is achieved by applying a low-pass analog filter with large inductance to the signal. This attenuates the high frequency components of the signal, essential for position discrimination in PoST's, relative to the white noise of the readout chain and degrades the position sensitivity. Using numerically simulated data, we investigate the position sensing ability of typical PoST designs under such high inductance conditions. We investigate signal-processing techniques for optimal determination of the event position and discuss the practical considerations for real-time implementation.

A Real-Time Capable Software-Defined Receiver Using GPU for Adaptive Anti-Jam GPS Sensors

PubMed Central

Seo, Jiwon; Chen, Yu-Hsuan; De Lorenzo, David S.; Lo, Sherman; Enge, Per; Akos, Dennis; Lee, Jiyun

2011-01-01

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities. PMID:22164116

A real-time capable software-defined receiver using GPU for adaptive anti-jam GPS sensors.

PubMed

Seo, Jiwon; Chen, Yu-Hsuan; De Lorenzo, David S; Lo, Sherman; Enge, Per; Akos, Dennis; Lee, Jiyun

2011-01-01

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities.

An MEG signature corresponding to an axiomatic model of reward prediction error.

PubMed

Talmi, Deborah; Fuentemilla, Lluis; Litvak, Vladimir; Duzel, Emrah; Dolan, Raymond J

2012-01-02

Optimal decision-making is guided by evaluating the outcomes of previous decisions. Prediction errors are theoretical teaching signals which integrate two features of an outcome: its inherent value and prior expectation of its occurrence. To uncover the magnetic signature of prediction errors in the human brain we acquired magnetoencephalographic (MEG) data while participants performed a gambling task. Our primary objective was to use formal criteria, based upon an axiomatic model (Caplin and Dean, 2008a), to determine the presence and timing profile of MEG signals that express prediction errors. We report analyses at the sensor level, implemented in SPM8, time locked to outcome onset. We identified, for the first time, a MEG signature of prediction error, which emerged approximately 320 ms after an outcome and expressed as an interaction between outcome valence and probability. This signal followed earlier, separate signals for outcome valence and probability, which emerged approximately 200 ms after an outcome. Strikingly, the time course of the prediction error signal, as well as the early valence signal, resembled the Feedback-Related Negativity (FRN). In simultaneously acquired EEG data we obtained a robust FRN, but the win and loss signals that comprised this difference wave did not comply with the axiomatic model. Our findings motivate an explicit examination of the critical issue of timing embodied in computational models of prediction errors as seen in human electrophysiological data. Copyright © 2011 Elsevier Inc. All rights reserved.

Improving piezo actuators for nanopositioning tasks

NASA Astrophysics Data System (ADS)

Seeliger, Martin; Gramov, Vassil; Götz, Bernt

2018-02-01

In recent years, numerous applications emerged on the market with seemingly contradicting demands. On one side, the structure size decreased while on the other side, the overall sample size and speed of operation increased. Although the principle usage of piezoelectric positioning solutions has become a standard in the field of micro- and nanopositioning, surface inspection and manipulation, piezosystem jena now enhanced the performance beyond simple control loop tuning and actuator design. In automated manufacturing machines, a given signal has to be tracked fast and precise. However, control systems naturally decrease the ability to follow this signal in real time. piezosystem jena developed a new signal feed forward system bypassing the PID control. This way, we could reduce signal tracking errors by a factor of three compared to a conventionally optimized PID control. Of course, PID-values still have to be adjusted to specific conditions, e.g. changing additional mass, to optimize the performance. This can now be done with a new automatic tuning tool designed to analyze the current setup, find the best fitting configuration, and also gather and display theoretical as well as experimental performance data. Thus, the control quality of a mechanical setup can be improved within a few minutes without the need of external calibration equipment. Furthermore, new mechanical optimization techniques that focus not only on the positioning device, but also take the whole setup into account, prevent parasitic motion down to a few nanometers.

Regulation of Phagocyte Migration by Signal Regulatory Protein-Alpha Signaling

PubMed Central

Alvarez-Zarate, Julian; Matlung, Hanke L.; Matozaki, Takashi; Kuijpers, Taco W.; Maridonneau-Parini, Isabelle; van den Berg, Timo K.

2015-01-01

Signaling through the inhibitory receptor signal regulatory protein-alpha (SIRPα) controls effector functions in phagocytes. However, there are also indications that interactions between SIRPα and its ligand CD47 are involved in phagocyte transendothelial migration. We have investigated the involvement of SIRPα signaling in phagocyte migration in vitro and in vivo using mice that lack the SIRPα cytoplasmic tail. During thioglycolate-induced peritonitis in SIRPα mutant mice, both neutrophil and macrophage influx were found to occur, but to be significantly delayed. SIRPα signaling appeared to be essential for an optimal transendothelial migration and chemotaxis, and for the amoeboid type of phagocyte migration in 3-dimensional environments. These findings demonstrate, for the first time, that SIRPα signaling can directly control phagocyte migration, and this may contribute to the impaired inflammatory phenotype that has been observed in the absence of SIRPα signaling. PMID:26057870

Optimal Averages for Nonlinear Signal Decompositions - Another Alternative for Empirical Mode Decomposition

DTIC Science & Technology

2014-10-01

nonlinear and non-stationary signals. It aims at decomposing a signal, via an iterative sifting procedure, into several intrinsic mode functions ...stationary signals. It aims at decomposing a signal, via an iterative sifting procedure into several intrinsic mode functions (IMFs), and each of the... function , optimization. 1 Introduction It is well known that nonlinear and non-stationary signal analysis is important and difficult. His- torically

Characterization of quantum interference control of injected currents in LT-GaAs for carrier-envelope phase measurements.

PubMed

Roos, Peter; Quraishi, Qudsia; Cundiff, Steven; Bhat, Ravi; Sipe, J

2003-08-25

We use two mutually coherent, harmonically related pulse trains to experimentally characterize quantum interference control (QIC) of injected currents in low-temperature-grown gallium arsenide. We observe real-time QIC interference fringes, optimize the QIC signal fidelity, uncover critical signal dependences regarding beam spatial position on the sample, measure signal dependences on the fundamental and second harmonic average optical powers, and demonstrate signal characteristics that depend on the focused beam spot sizes. Following directly from our motivation for this study, we propose an initial experiment to measure and ultimately control the carrier-envelope phase evolution of a single octave-spanning pulse train using the QIC phenomenon.

On optimal soft-decision demodulation

NASA Technical Reports Server (NTRS)

Lee, L. N.

1975-01-01

Wozencraft and Kennedy have suggested that the appropriate demodulator criterion of goodness is the cut-off rate of the discrete memoryless channel created by the modulation system; the criterion of goodness adopted in this note is the symmetric cut-off rate which differs from the former criterion only in that the signals are assumed equally likely. Massey's necessary condition for optimal demodulation of binary signals is generalized to M-ary signals. It is shown that the optimal demodulator decision regions in likelihood space are bounded by hyperplanes. An iterative method is formulated for finding these optimal decision regions from an initial good quess. For additive white Gaussian noise, the corresponding optimal decision regions in signal space are bounded by hypersurfaces with hyperplane asymptotes; these asymptotes themselves bound the decision regions of a demodulator which, in several examples, is shown to be virtually optimal. In many cases, the necessary condition for demodulator optimality is also sufficient, but a counter example to its general sufficiency is given.

Some Considerations on the Problem of Non-Steady State Traffic Flow Optimization

DOT National Transportation Integrated Search

2007-01-01

Poor traffic signal timing accounts for an estimated 10 percent of all traffic delay about 300 million vehicle-hours on major roadways alone. Americans agree that this is a problem: one U.S. Department of Transportation (DOT) survey found tha...

Optimal signal timing design for urban street networks under user equilibrium based traffic conditions : final report.

DOT National Transportation Integrated Search

2016-09-20

In the ever-growing travel demand, traffic congestion on freeways and expressways : recurs more frequently at a higher number of locations and for longer durations with : added severity. This becomes especially true in large metropolitan areas. Parti...

MIMO-OFDM signal optimization for SAR imaging radar

NASA Astrophysics Data System (ADS)

Baudais, J.-Y.; Méric, S.; Riché, V.; Pottier, É.

2016-12-01

This paper investigates the optimization of the coded orthogonal frequency division multiplexing (OFDM) transmitted signal in a synthetic aperture radar (SAR) context. We propose to design OFDM signals to achieve range ambiguity mitigation. Indeed, range ambiguities are well known to be a limitation for SAR systems which operates with pulsed transmitted signal. The ambiguous reflected signal corresponding to one pulse is then detected when the radar has already transmitted the next pulse. In this paper, we demonstrate that the range ambiguity mitigation is possible by using orthogonal transmitted wave as OFDM pulses. The coded OFDM signal is optimized through genetic optimization procedures based on radar image quality parameters. Moreover, we propose to design a multiple-input multiple-output (MIMO) configuration to enhance the noise robustness of a radar system and this configuration is mainly efficient in the case of using orthogonal waves as OFDM pulses. The results we obtain show that OFDM signals outperform conventional radar chirps for range ambiguity suppression and for robustness enhancement in 2 ×2 MIMO configuration.

Using Diurnal Temperature Signals to Infer Vertical Groundwater-Surface Water Exchange.

PubMed

Irvine, Dylan J; Briggs, Martin A; Lautz, Laura K; Gordon, Ryan P; McKenzie, Jeffrey M; Cartwright, Ian

2017-01-01

Heat is a powerful tracer to quantify fluid exchange between surface water and groundwater. Temperature time series can be used to estimate pore water fluid flux, and techniques can be employed to extend these estimates to produce detailed plan-view flux maps. Key advantages of heat tracing include cost-effective sensors and ease of data collection and interpretation, without the need for expensive and time-consuming laboratory analyses or induced tracers. While the collection of temperature data in saturated sediments is relatively straightforward, several factors influence the reliability of flux estimates that are based on time series analysis (diurnal signals) of recorded temperatures. Sensor resolution and deployment are particularly important in obtaining robust flux estimates in upwelling conditions. Also, processing temperature time series data involves a sequence of complex steps, including filtering temperature signals, selection of appropriate thermal parameters, and selection of the optimal analytical solution for modeling. This review provides a synthesis of heat tracing using diurnal temperature oscillations, including details on optimal sensor selection and deployment, data processing, model parameterization, and an overview of computing tools available. Recent advances in diurnal temperature methods also provide the opportunity to determine local saturated thermal diffusivity, which can improve the accuracy of fluid flux modeling and sensor spacing, which is related to streambed scour and deposition. These parameters can also be used to determine the reliability of flux estimates from the use of heat as a tracer. © 2016, National Ground Water Association.

Optimal weighted averaging of event related activity from acquisitions with artifacts.

PubMed

Vollero, Luca; Petrichella, Sara; Innello, Giulio

2016-08-01

In several biomedical applications that require the signal processing of biological data, the starting procedure for noise reduction is the ensemble averaging of multiple repeated acquisitions (trials). This method is based on the assumption that each trial is composed of two additive components: (i) a time-locked activity related to some sensitive/stimulation phenomenon (ERA, Event Related Activity in the following) and (ii) a sum of several other non time-locked background activities. The averaging aims at estimating the ERA activity under very low Signal to Noise and Interference Ratio (SNIR). Although averaging is a well established tool, its performance can be improved in the presence of high-power disturbances (artifacts) by a trials classification and removal stage. In this paper we propose, model and evaluate a new approach that avoids trials removal, managing trials classified as artifact-free and artifact-prone with two different weights. Based on the model, a weights tuning is possible and through modeling and simulations we show that, when optimally configured, the proposed solution outperforms classical approaches.

Waveform Optimization for Target Estimation by Cognitive Radar with Multiple Antennas.

PubMed

Yao, Yu; Zhao, Junhui; Wu, Lenan

2018-05-29

A new scheme based on Kalman filtering to optimize the waveforms of an adaptive multi-antenna radar system for target impulse response (TIR) estimation is presented. This work aims to improve the performance of TIR estimation by making use of the temporal correlation between successive received signals, and minimize the mean square error (MSE) of TIR estimation. The waveform design approach is based upon constant learning from the target feature at the receiver. Under the multiple antennas scenario, a dynamic feedback loop control system is established to real-time monitor the change in the target features extracted form received signals. The transmitter adapts its transmitted waveform to suit the time-invariant environment. Finally, the simulation results show that, as compared with the waveform design method based on the MAP criterion, the proposed waveform design algorithm is able to improve the performance of TIR estimation for extended targets with multiple iterations, and has a relatively lower level of complexity.

A junction-tree based learning algorithm to optimize network wide traffic control: A coordinated multi-agent framework

DOE PAGES

Zhu, Feng; Aziz, H. M. Abdul; Qian, Xinwu; ...

2015-01-31

Our study develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm (JTA) based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. Moreover, the algorithm is implemented and tested with a network containing 18 signalized intersections in VISSIM. Finally, our results show that the JTA based algorithm outperforms independent learning (Q-learning), real-time adaptive learning, and fixed timing plansmore » in terms of average delay, number of stops, and vehicular emissions at the network level.« less

Simplex optimization of headspace factors for headspace gas chromatography determination of residual solvents in pharmaceutical products.

PubMed

Grodowska, Katarzyna; Parczewski, Andrzej

2013-01-01

The purpose of the present work was to find optimum conditions of headspace gas chromatography (HS-GC) determination of residual solvents which usually appear in pharmaceutical products. Two groups of solvents were taken into account in the present examination. Group I consisted of isopropanol, n-propanol, isobutanol, n-butanol and 1,4-dioxane and group II included cyclohexane, n-hexane and n-heptane. The members of the groups were selected in previous investigations in which experimental design and chemometric methods were applied. Four factors were taken into consideration in optimization which describe HS conditions: sample volume, equilibration time, equilibrium temperature and NaCl concentration in a sample. The relative GC peak area served as an optimization criterion which was considered separately for each analyte. Sequential variable size simplex optimization strategy was used and the progress of optimization was traced and visualized in various ways simultaneously. The optimum HS conditions appeared different for the groups of solvents tested, which proves that influence of experimental conditions (factors) depends on analyte properties. The optimization resulted in significant signal increase (from seven to fifteen times).

Optimal sampling with prior information of the image geometry in microfluidic MRI.

PubMed

Han, S H; Cho, H; Paulsen, J L

2015-03-01

Recent advances in MRI acquisition for microscopic flows enable unprecedented sensitivity and speed in a portable NMR/MRI microfluidic analysis platform. However, the application of MRI to microfluidics usually suffers from prolonged acquisition times owing to the combination of the required high resolution and wide field of view necessary to resolve details within microfluidic channels. When prior knowledge of the image geometry is available as a binarized image, such as for microfluidic MRI, it is possible to reduce sampling requirements by incorporating this information into the reconstruction algorithm. The current approach to the design of the partial weighted random sampling schemes is to bias toward the high signal energy portions of the binarized image geometry after Fourier transformation (i.e. in its k-space representation). Although this sampling prescription is frequently effective, it can be far from optimal in certain limiting cases, such as for a 1D channel, or more generally yield inefficient sampling schemes at low degrees of sub-sampling. This work explores the tradeoff between signal acquisition and incoherent sampling on image reconstruction quality given prior knowledge of the image geometry for weighted random sampling schemes, finding that optimal distribution is not robustly determined by maximizing the acquired signal but from interpreting its marginal change with respect to the sub-sampling rate. We develop a corresponding sampling design methodology that deterministically yields a near optimal sampling distribution for image reconstructions incorporating knowledge of the image geometry. The technique robustly identifies optimal weighted random sampling schemes and provides improved reconstruction fidelity for multiple 1D and 2D images, when compared to prior techniques for sampling optimization given knowledge of the image geometry. Copyright © 2015 Elsevier Inc. All rights reserved.

Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal.

PubMed

Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D; Hubbi, Basil; Liu, Xuan

2015-11-01

Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue.

Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal

PubMed Central

Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D.; Hubbi, Basil; Liu, Xuan

2015-01-01

Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue. PMID:26600996

Time-varying higher order spectra

NASA Astrophysics Data System (ADS)

Boashash, Boualem; O'Shea, Peter

1991-12-01

A general solution for the problem of time-frequency signal representation of nonlinear FM signals is provided, based on a generalization of the Wigner-Ville distribution. The Wigner- Ville distribution (WVD) is a second order time-frequency representation. That is, it is able to give ideal energy concentration for quadratic phase signals and its ensemble average is a second order time-varying spectrum. The same holds for Cohen's class of time-frequency distributions, which are smoothed versions of the WVD. The WVD may be extended so as to achieve ideal energy concentration for higher order phase laws, and such that the expectation is a time-varying higher order spectrum. The usefulness of these generalized Wigner-Ville distributions (GWVD) is twofold. Firstly, because they achieve ideal energy concentration for polynomial phase signals, they may be used for optimal instantaneous frequency estimation. Second, they are useful for discriminating between nonstationary processes of differing higher order moments. In the same way that the WVD is generalized, we generalize Cohen's class of TFDs by defining a class of generalized time-frequency distributions (GTFDs) obtained by a two dimensional smoothing of the GWVD. Another results derived from this approach is a method based on higher order spectra which allows the separation of cross-terms and auto- terms in the WVD.

Cumulant expansions for measuring water exchange using diffusion MRI

NASA Astrophysics Data System (ADS)

Ning, Lipeng; Nilsson, Markus; Lasič, Samo; Westin, Carl-Fredrik; Rathi, Yogesh

2018-02-01

The rate of water exchange across cell membranes is a parameter of biological interest and can be measured by diffusion magnetic resonance imaging (dMRI). In this work, we investigate a stochastic model for the diffusion-and-exchange of water molecules. This model provides a general solution for the temporal evolution of dMRI signal using any type of gradient waveform, thereby generalizing the signal expressions for the Kärger model. Moreover, we also derive a general nth order cumulant expansion of the dMRI signal accounting for water exchange, which has not been explored in earlier studies. Based on this analytical expression, we compute the cumulant expansion for dMRI signals for the special case of single diffusion encoding (SDE) and double diffusion encoding (DDE) sequences. Our results provide a theoretical guideline on optimizing experimental parameters for SDE and DDE sequences, respectively. Moreover, we show that DDE signals are more sensitive to water exchange at short-time scale but provide less attenuation at long-time scale than SDE signals. Our theoretical analysis is also validated using Monte Carlo simulations on synthetic structures.

Application of Taguchi L32 orthogonal array design to optimize copper biosorption by using Spaghnum moss.

PubMed

Ozdemir, Utkan; Ozbay, Bilge; Ozbay, Ismail; Veli, Sevil

2014-09-01

In this work, Taguchi L32 experimental design was applied to optimize biosorption of Cu(2+) ions by an easily available biosorbent, Spaghnum moss. With this aim, batch biosorption tests were performed to achieve targeted experimental design with five factors (concentration, pH, biosorbent dosage, temperature and agitation time) at two different levels. Optimal experimental conditions were determined by calculated signal-to-noise ratios. "Higher is better" approach was followed to calculate signal-to-noise ratios as it was aimed to obtain high metal removal efficiencies. The impact ratios of factors were determined by the model. Within the study, Cu(2+) biosorption efficiencies were also predicted by using Taguchi method. Results of the model showed that experimental and predicted values were close to each other demonstrating the success of Taguchi approach. Furthermore, thermodynamic, isotherm and kinetic studies were performed to explain the biosorption mechanism. Calculated thermodynamic parameters were in good accordance with the results of Taguchi model. Copyright © 2014 Elsevier Inc. All rights reserved.

Piéron’s Law and Optimal Behavior in Perceptual Decision-Making

PubMed Central

van Maanen, Leendert; Grasman, Raoul P. P. P.; Forstmann, Birte U.; Wagenmakers, Eric-Jan

2012-01-01

Piéron’s Law is a psychophysical regularity in signal detection tasks that states that mean response times decrease as a power function of stimulus intensity. In this article, we extend Piéron’s Law to perceptual two-choice decision-making tasks, and demonstrate that the law holds as the discriminability between two competing choices is manipulated, even though the stimulus intensity remains constant. This result is consistent with predictions from a Bayesian ideal observer model. The model assumes that in order to respond optimally in a two-choice decision-making task, participants continually update the posterior probability of each response alternative, until the probability of one alternative crosses a criterion value. In addition to predictions for two-choice decision-making tasks, we extend the ideal observer model to predict Piéron’s Law in signal detection tasks. We conclude that Piéron’s Law is a general phenomenon that may be caused by optimality constraints. PMID:22232572

Environmental statistics and optimal regulation

NASA Astrophysics Data System (ADS)

Sivak, David; Thomson, Matt

2015-03-01

The precision with which an organism can detect its environment, and the timescale for and statistics of environmental change, will affect the suitability of different strategies for regulating protein levels in response to environmental inputs. We propose a general framework--here applied to the enzymatic regulation of metabolism in response to changing nutrient concentrations--to predict the optimal regulatory strategy given the statistics of fluctuations in the environment and measurement apparatus, and the costs associated with enzyme production. We find: (i) relative convexity of enzyme expression cost and benefit influences the fitness of thresholding or graded responses; (ii) intermediate levels of measurement uncertainty call for a sophisticated Bayesian decision rule; and (iii) in dynamic contexts, intermediate levels of uncertainty call for retaining memory of the past. Statistical properties of the environment, such as variability and correlation times, set optimal biochemical parameters, such as thresholds and decay rates in signaling pathways. Our framework provides a theoretical basis for interpreting molecular signal processing algorithms and a classification scheme that organizes known regulatory strategies and may help conceptualize heretofore unknown ones.

Joint Resource Optimization for Cognitive Sensor Networks with SWIPT-Enabled Relay.

PubMed

Lu, Weidang; Lin, Yuanrong; Peng, Hong; Nan, Tian; Liu, Xin

2017-09-13

Energy-constrained wireless networks, such as wireless sensor networks (WSNs), are usually powered by fixed energy supplies (e.g., batteries), which limits the operation time of networks. Simultaneous wireless information and power transfer (SWIPT) is a promising technique to prolong the lifetime of energy-constrained wireless networks. This paper investigates the performance of an underlay cognitive sensor network (CSN) with SWIPT-enabled relay node. In the CSN, the amplify-and-forward (AF) relay sensor node harvests energy from the ambient radio-frequency (RF) signals using power splitting-based relaying (PSR) protocol. Then, it helps forward the signal of source sensor node (SSN) to the destination sensor node (DSN) by using the harvested energy. We study the joint resource optimization including the transmit power and power splitting ratio to maximize CSN's achievable rate with the constraint that the interference caused by the CSN to the primary users (PUs) is within the permissible threshold. Simulation results show that the performance of our proposed joint resource optimization can be significantly improved.

On optimal soft-decision demodulation. [in digital communication system

NASA Technical Reports Server (NTRS)

Lee, L.-N.

1976-01-01

A necessary condition is derived for optimal J-ary coherent demodulation of M-ary (M greater than 2) signals. Optimality is defined as maximality of the symmetric cutoff rate of the resulting discrete memoryless channel. Using a counterexample, it is shown that the condition derived is generally not sufficient for optimality. This condition is employed as the basis for an iterative optimization method to find the optimal demodulator decision regions from an initial 'good guess'. In general, these regions are found to be bounded by hyperplanes in likelihood space; the corresponding regions in signal space are found to have hyperplane asymptotes for the important case of additive white Gaussian noise. Some examples are presented, showing that the regions in signal space bounded by these asymptotic hyperplanes define demodulator decision regions that are virtually optimal.

Signal optimization in urban transport: A totally asymmetric simple exclusion process with traffic lights.

PubMed

Arita, Chikashi; Foulaadvand, M Ebrahim; Santen, Ludger

2017-03-01

We consider the exclusion process on a ring with time-dependent defective bonds at which the hopping rate periodically switches between zero and one. This system models main roads in city traffics, intersecting with perpendicular streets. We explore basic properties of the system, in particular dependence of the vehicular flow on the parameters of signalization as well as the system size and the car density. We investigate various types of the spatial distribution of the vehicular density, and show existence of a shock profile. We also measure waiting time behind traffic lights, and examine its relationship with the traffic flow.

Signal optimization in urban transport: A totally asymmetric simple exclusion process with traffic lights

NASA Astrophysics Data System (ADS)

Arita, Chikashi; Foulaadvand, M. Ebrahim; Santen, Ludger

2017-03-01

We consider the exclusion process on a ring with time-dependent defective bonds at which the hopping rate periodically switches between zero and one. This system models main roads in city traffics, intersecting with perpendicular streets. We explore basic properties of the system, in particular dependence of the vehicular flow on the parameters of signalization as well as the system size and the car density. We investigate various types of the spatial distribution of the vehicular density, and show existence of a shock profile. We also measure waiting time behind traffic lights, and examine its relationship with the traffic flow.

Pacific Northwest GridWise™ Testbed Demonstration Projects; Part I. Olympic Peninsula Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hammerstrom, Donald J.; Ambrosio, Ron; Carlon, Teresa A.

2008-01-09

This report describes the implementation and results of a field demonstration wherein residential electric water heaters and thermostats, commercial building space conditioning, municipal water pump loads, and several distributed generators were coordinated to manage constrained feeder electrical distribution through the two-way communication of load status and electric price signals. The field demonstration took place in Washington and Oregon and was paid for by the U.S. Department of Energy and several northwest utilities. Price is found to be an effective control signal for managing transmission or distribution congestion. Real-time signals at 5-minute intervals are shown to shift controlled load in time.more » The behaviors of customers and their responses under fixed, time-of-use, and real-time price contracts are compared. Peak loads are effectively reduced on the experimental feeder. A novel application of portfolio theory is applied to the selection of an optimal mix of customer contract types.« less

Simulation of an enzyme-based glucose sensor

NASA Astrophysics Data System (ADS)

Sha, Xianzheng; Jablecki, Michael; Gough, David A.

2001-09-01

An important biosensor application is the continuous monitoring blood or tissue fluid glucose concentration in people with diabetes. Our research focuses on the development of a glucose sensor based on potentiostatic oxygen electrodes and immobilized glucose oxidase for long- term application as an implant in tissues. As the sensor signal depends on many design variables, a trial-and-error approach to sensor optimization can be time-consuming. Here, the properties of an implantable glucose sensor are optimized by a systematic computational simulation approach.

Waveform Design and Diversity for Advanced Space-Time Adaptive Processing and Multiple Input Multiple Output Systems

DTIC Science & Technology

2012-08-01

It suggests that a smart use of some a-priori information about the operating environment, when processing the received signal and designing the...random variable with the same variance of the backscattering target amplitude αT , and D ( αT , α G T ) is the Kullback − Leibler divergence, see [65...MI . Proof. See Appendix 3.6.6. Thus, we can use the optimization procedure of Algorithm 4 to optimize the Mutual Information between the target

An Advanced simulation Code for Modeling Inductive Output Tubes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thuc Bui; R. Lawrence Ives

2012-04-27

During the Phase I program, CCR completed several major building blocks for a 3D large signal, inductive output tube (IOT) code using modern computer language and programming techniques. These included a 3D, Helmholtz, time-harmonic, field solver with a fully functional graphical user interface (GUI), automeshing and adaptivity. Other building blocks included the improved electrostatic Poisson solver with temporal boundary conditions to provide temporal fields for the time-stepping particle pusher as well as the self electric field caused by time-varying space charge. The magnetostatic field solver was also updated to solve for the self magnetic field caused by time changing currentmore » density in the output cavity gap. The goal function to optimize an IOT cavity was also formulated, and the optimization methodologies were investigated.« less

Modeling and optimization of Look-Locker spin labeling for measuring perfusion and transit time changes in activation studies taking into account arterial blood volume.

PubMed

Francis, S T; Bowtell, R; Gowland, P A

2008-02-01

This work describes a new compartmental model with step-wise temporal analysis for a Look-Locker (LL)-flow-sensitive alternating inversion-recovery (FAIR) sequence, which combines the FAIR arterial spin labeling (ASL) scheme with a LL echo planar imaging (EPI) measurement, using a multireadout EPI sequence for simultaneous perfusion and T*(2) measurements. The new model highlights the importance of accounting for the transit time of blood through the arteriolar compartment, delta, in the quantification of perfusion. The signal expected is calculated in a step-wise manner to avoid discontinuities between different compartments. The optimal LL-FAIR pulse sequence timings for the measurement of perfusion with high signal-to-noise ratio (SNR), and high temporal resolution at 1.5, 3, and 7T are presented. LL-FAIR is shown to provide better SNR per unit time compared to standard FAIR. The sequence has been used experimentally for simultaneous monitoring of perfusion, transit time, and T*(2) changes in response to a visual stimulus in four subjects. It was found that perfusion increased by 83 +/- 4% on brain activation from a resting state value of 94 +/- 13 ml/100 g/min, while T*(2) increased by 3.5 +/- 0.5%. (c) 2008 Wiley-Liss, Inc.

TOFPET2: a high-performance ASIC for time and amplitude measurements of SiPM signals in time-of-flight applications

NASA Astrophysics Data System (ADS)

Di Francesco, A.; Bugalho, R.; Oliveira, L.; Pacher, L.; Rivetti, A.; Rolo, M.; Silva, J. C.; Silva, R.; Varela, J.

2016-03-01

We present a readout and digitization ASIC featuring low-noise and low-power for time-of flight (TOF) applications using SiPMs. The circuit is designed in standard CMOS 110 nm technology, has 64 independent channels and is optimized for time-of-flight measurement in Positron Emission Tomography (TOF-PET). The input amplifier is a low impedance current conveyor based on a regulated common-gate topology. Each channel has quad-buffered analogue interpolation TDCs (time binning 20 ps) and charge integration ADCs with linear response at full scale (1500 pC). The signal amplitude can also be derived from the measurement of time-over-threshold (ToT). Simulation results show that for a single photo-electron signal with charge 200 (550) fC generated by a SiPM with 320 pF capacitance the circuit has 24 (30) dB SNR, 75(39) ps r.m.s. resolution, and 4(8) mW power consumption. The event rate is 600 kHz per channel, with up to 2 MHz dark counts rejection.

Effect of injection rate on contrast-enhanced MR angiography image quality: Modulation transfer function analysis.

PubMed

Clark, Toshimasa J; Wilson, Gregory J; Maki, Jeffrey H

2017-07-01

Contrast-enhanced (CE)-MRA optimization involves interactions of sequence duration, bolus timing, contrast recirculation, and both R 1 relaxivity and R2*-related reduction of signal. Prior data suggest superior image quality with slower gadolinium injection rates than typically used. A computer-based model of CE-MRA was developed, with contrast injection, physiologic, and image acquisition parameters varied over a wide gamut. Gadolinium concentration was derived using Verhoeven's model with recirculation, R 1 and R2* calculated at each time point, and modulation transfer curves used to determine injection rates, resulting in optimal resolution and image contrast for renal and carotid artery CE-MRA. Validation was via a vessel stenosis phantom and example patients who underwent carotid CE-MRA with low effective injection rates. Optimal resolution for renal and carotid CE-MRA is achieved with injection rates between 0.5 to 0.9 mL/s and 0.2 to 0.3 mL/s, respectively, dependent on contrast volume. Optimal image contrast requires slightly faster injection rates. Expected signal-to-noise ratio varies with both contrast volume and cardiac output. Simulated vessel phantom and clinical carotid CE-MRA exams at an effective contrast injection rate of 0.4 to 0.5 mL/s demonstrate increased resolution. Optimal image resolution is achieved at intuitively low, effective injection rates (0.2-0.9 mL/s, dependent on imaging parameters and contrast injection volume). Magn Reson Med 78:357-369, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Removal of Noise from a Voice Signal by Synthesis

DTIC Science & Technology

1973-05-01

for 102.4 millisecond windows is about five times as great as the cost of computing for 25.6 millisecond windows. Hammett in his work on an adaptive...spectrum analysis vocoder, has examined the selection of data window widths in detail [18]. The solution Hammett used to optimize the trade off between...result is: n s(t) E Ri(t - i . T) i-1 In this equation n is the number of impulse responses under consideration, s(t) is the resulting synthetic signal

Ellipticity angle of electromagnetic signals and its use for non-energetic detection optimal by the Neumann-Pearson criterion

NASA Astrophysics Data System (ADS)

Gromov, V. A.; Sharygin, G. S.; Mironov, M. V.

2012-08-01

An interval method of radar signal detection and selection based on non-energetic polarization parameter - the ellipticity angle - is suggested. The examined method is optimal by the Neumann-Pearson criterion. The probability of correct detection for a preset probability of false alarm is calculated for different signal/noise ratios. Recommendations for optimization of the given method are provided.

An optimized compression algorithm for real-time ECG data transmission in wireless network of medical information systems.

PubMed

Cho, Gyoun-Yon; Lee, Seo-Joon; Lee, Tae-Ro

2015-01-01

Recent medical information systems are striving towards real-time monitoring models to care patients anytime and anywhere through ECG signals. However, there are several limitations such as data distortion and limited bandwidth in wireless communications. In order to overcome such limitations, this research focuses on compression. Few researches have been made to develop a specialized compression algorithm for ECG data transmission in real-time monitoring wireless network. Not only that, recent researches' algorithm is not appropriate for ECG signals. Therefore this paper presents a more developed algorithm EDLZW for efficient ECG data transmission. Results actually showed that the EDLZW compression ratio was 8.66, which was a performance that was 4 times better than any other recent compression method widely used today.

  Ultrasonic monitoring of fish thawing process optimal time of thawing and effect of freezing/thawing.

PubMed

El Kadi, Youssef Ait; Moudden, Ali; Faiz, Bouazza; Maze, Gerard; Decultot, Dominique

2013-01-01

Fish quality is traditionally controlled by chemical and microbiological analysis. The non-destructive control presents an enormous professional interest thanks to the technical contribution and precision of the analysis to which it leads. This paper presents the results obtained from a characterisation of fish thaw-ing process by the ultrasonic technique, with monitoring thermal processing from frozen to defrosted states. The study was carried out on fish type red drum and salmon cut into fillets of 15 mm thickness. After being frozen at -20°C, the sample is enclosed in a plexiglas vessel with parallel walls at the ambient temperature 30°C and excited in perpendicular incidence at 0.5 MHz by an ultrasonic pulser-receiver Sofranel 5052PR. the technique of measurement consists to study the signals reflected by fish during its thawing, the specific techniques of signal processing are implemented to deduce informations characterizing the state of fish and its thawing process by examining the evolution of the position echoes reflected by the sample and the viscoelastic parameters of fish during its thawing. The obtained results show a relationship between the thermal state of fish and its acoustic properties, which allowed to deduce the optimal time of the first thawing in order to restrict the growth of microbial flora. For salmon, the results show a decrease of 36% of the time of the second thawing and an increase of 10.88% of the phase velocity, with a decrease of 65.5% of the peak-to-peak voltage of the signal reflected, thus a decrease of the acoustic impedance. This study shows an optimal time and an evolution rate of thawing specific to each type offish and a correlation between the acoustic behavior of fish and its thermal state which approves that this technique of ultrasonic monitoring can substitute the control using the destructive chemical analysis in order to monitor the thawing process and to know whether a fish has suffered an accidental thawing.

Noninvasive extraction of fetal electrocardiogram based on Support Vector Machine

NASA Astrophysics Data System (ADS)

Fu, Yumei; Xiang, Shihan; Chen, Tianyi; Zhou, Ping; Huang, Weiyan

2015-10-01

The fetal electrocardiogram (FECG) signal has important clinical value for diagnosing the fetal heart diseases and choosing suitable therapeutics schemes to doctors. So, the noninvasive extraction of FECG from electrocardiogram (ECG) signals becomes a hot research point. A new method, the Support Vector Machine (SVM) is utilized for the extraction of FECG with limited size of data. Firstly, the theory of the SVM and the principle of the extraction based on the SVM are studied. Secondly, the transformation of maternal electrocardiogram (MECG) component in abdominal composite signal is verified to be nonlinear and fitted with the SVM. Then, the SVM is trained, and the training results are compared with the real data to ensure the effect of the training. Meanwhile, the parameters of the SVM are optimized to achieve the best performance so that the learning machine can be utilized to fit the unknown samples. Finally, the FECG is extracted by removing the optimal estimation of MECG component from the abdominal composite signal. In order to evaluate the performance of FECG extraction based on the SVM, the Signal-to-Noise Ratio (SNR) and the visual test are used. The experimental results show that the FECG with good quality can be extracted, its SNR ratio is significantly increased as high as 9.2349 dB and the time cost is significantly decreased as short as 0.802 seconds. Compared with the traditional method, the noninvasive extraction method based on the SVM has a simple realization, the shorter treatment time and the better extraction quality under the same conditions.

Optimal and adaptive methods of processing hydroacoustic signals (review)

NASA Astrophysics Data System (ADS)

Malyshkin, G. S.; Sidel'nikov, G. B.

2014-09-01

Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

A model of optimal voluntary muscular control.

PubMed

FitzHugh, R

1977-07-19

In the absence of detailed knowledge of how the CNS controls a muscle through its motor fibers, a reasonable hypothesis is that of optimal control. This hypothesis is studied using a simplified mathematical model of a single muscle, based on A.V. Hill's equations, with series elastic element omitted, and with the motor signal represented by a single input variable. Two cost functions were used. The first was total energy expended by the muscle (work plus heat). If the load is a constant force, with no inertia, Hill's optimal velocity of shortening results. If the load includes a mass, analysis by optimal control theory shows that the motor signal to the muscle consists of three phases: (1) maximal stimulation to accelerate the mass to the optimal velocity as quickly as possible, (2) an intermediate level of stimulation to hold the velocity at its optimal value, once reached, and (3) zero stimulation, to permit the mass to slow down, as quickly as possible, to zero velocity at the specified distance shortened. If the latter distance is too small, or the mass too large, the optimal velocity is not reached, and phase (2) is absent. For lengthening, there is no optimal velocity; there are only two phases, zero stimulation followed by maximal stimulation. The second cost function was total time. The optimal control for shortening consists of only phases (1) and (3) above, and is identical to the minimal energy control whenever phase (2) is absent from the latter. Generalization of this model to include viscous loads and a series elastic element are discussed.

Intraoperative near infrared fluorescence guided identification of the ureters using low dose methylene blue: a first in human experience.

PubMed

Verbeek, Floris P R; van der Vorst, Joost R; Schaafsma, Boudewijn E; Swijnenburg, Rutger-Jan; Gaarenstroom, Katja N; Elzevier, Henk W; van de Velde, Cornelis J H; Frangioni, John V; Vahrmeijer, Alexander L

2013-08-01

Near infrared fluorescence imaging is a promising technique that offers real-time visual information during surgery. In this study we report the first clinical results to our knowledge of ureteral imaging using near infrared fluorescence after a simple peripheral infusion of methylene blue. Furthermore, we assessed the optimal timing and dose of methylene blue. A total of 12 patients who underwent lower abdominal surgery were included in this prospective feasibility study. Near infrared fluorescence imaging was performed using the Mini-FLARE™ imaging system. To determine optimal timing and dose, methylene blue was injected intravenously at doses of 0.25, 0.5 or 1 mg/kg after exposure of the ureters. Imaging was performed for up to 60 minutes after injection. In all patients both ureters could be clearly visualized within 10 minutes after infusion of methylene blue. The signal lasted at least up to 60 minutes after injection. The mean signal-to-background ratio of the ureter was 2.27 ± 1.22 (4), 2.61 ± 1.88 (4) and 3.58 ± 3.36 (4) for the 0.25, 0.5 and 1 mg/kg groups, respectively. A mixed model analysis was used to compare signal-to-background ratios among dose groups and times, and to assess the relationship between dose and time. A significant difference among time points (p <0.001) was found. However, no difference was observed among dose groups (p = 0.811). This study demonstrates the first successful use of near infrared fluorescence using low dose methylene blue for the identification of the ureters during lower abdominal surgery. Copyright © 2013 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

RMP: Reduced-set matching pursuit approach for efficient compressed sensing signal reconstruction.

PubMed

Abdel-Sayed, Michael M; Khattab, Ahmed; Abu-Elyazeed, Mohamed F

2016-11-01

Compressed sensing enables the acquisition of sparse signals at a rate that is much lower than the Nyquist rate. Compressed sensing initially adopted [Formula: see text] minimization for signal reconstruction which is computationally expensive. Several greedy recovery algorithms have been recently proposed for signal reconstruction at a lower computational complexity compared to the optimal [Formula: see text] minimization, while maintaining a good reconstruction accuracy. In this paper, the Reduced-set Matching Pursuit (RMP) greedy recovery algorithm is proposed for compressed sensing. Unlike existing approaches which either select too many or too few values per iteration, RMP aims at selecting the most sufficient number of correlation values per iteration, which improves both the reconstruction time and error. Furthermore, RMP prunes the estimated signal, and hence, excludes the incorrectly selected values. The RMP algorithm achieves a higher reconstruction accuracy at a significantly low computational complexity compared to existing greedy recovery algorithms. It is even superior to [Formula: see text] minimization in terms of the normalized time-error product, a new metric introduced to measure the trade-off between the reconstruction time and error. RMP superior performance is illustrated with both noiseless and noisy samples.

Adaptive optimization of reference intensity for optical coherence imaging using galvanometric mirror tilting method

NASA Astrophysics Data System (ADS)

Kim, Ji-hyun; Han, Jae-Ho; Jeong, Jichai

2015-09-01

Integration time and reference intensity are important factors for achieving high signal-to-noise ratio (SNR) and sensitivity in optical coherence tomography (OCT). In this context, we present an adaptive optimization method of reference intensity for OCT setup. The reference intensity is automatically controlled by tilting a beam position using a Galvanometric scanning mirror system. Before sample scanning, the OCT system acquires two dimensional intensity map with normalized intensity and variables in color spaces using false-color mapping. Then, the system increases or decreases reference intensity following the map data for optimization with a given algorithm. In our experiments, the proposed method successfully corrected the reference intensity with maintaining spectral shape, enabled to change integration time without manual calibration of the reference intensity, and prevented image degradation due to over-saturation and insufficient reference intensity. Also, SNR and sensitivity could be improved by increasing integration time with automatic adjustment of the reference intensity. We believe that our findings can significantly aid in the optimization of SNR and sensitivity for optical coherence tomography systems.

The DCU: the detector control unit for SPICA-SAFARI

NASA Astrophysics Data System (ADS)

Clénet, Antoine; Ravera, Laurent; Bertrand, Bernard; den Hartog, Roland H.; Jackson, Brian D.; van Leeuven, Bert-Joost; van Loon, Dennis; Parot, Yann; Pointecouteau, Etienne; Sournac, Anthony

2014-08-01

IRAP is developing the warm electronic, so called Detector Control Unit" (DCU), in charge of the readout of the SPICA-SAFARI's TES type detectors. The architecture of the electronics used to readout the 3 500 sensors of the 3 focal plane arrays is based on the frequency domain multiplexing technique (FDM). In each of the 24 detection channels the data of up to 160 pixels are multiplexed in frequency domain between 1 and 3:3 MHz. The DCU provides the AC signals to voltage-bias the detectors; it demodulates the detectors data which are readout in the cold by a SQUID; and it computes a feedback signal for the SQUID to linearize the detection chain in order to optimize its dynamic range. The feedback is computed with a specific technique, so called baseband feedback (BBFB) which ensures that the loop is stable even with long propagation and processing delays (i.e. several µs) and with fast signals (i.e. frequency carriers at 3:3 MHz). This digital signal processing is complex and has to be done at the same time for the 3 500 pixels. It thus requires an optimisation of the power consumption. We took the advantage of the relatively reduced science signal bandwidth (i.e. 20 - 40 Hz) to decouple the signal sampling frequency (10 MHz) and the data processing rate. Thanks to this method we managed to reduce the total number of operations per second and thus the power consumption of the digital processing circuit by a factor of 10. Moreover we used time multiplexing techniques to share the resources of the circuit (e.g. a single BBFB module processes 32 pixels). The current version of the firmware is under validation in a Xilinx Virtex 5 FPGA, the final version will be developed in a space qualified digital ASIC. Beyond the firmware architecture the optimization of the instrument concerns the characterization routines and the definition of the optimal parameters. Indeed the operation of the detection and readout chains requires to properly define more than 17 500 parameters (about 5 parameters per pixel). Thus it is mandatory to work out an automatic procedure to set up these optimal values. We defined a fast algorithm which characterizes the phase correction to be applied by the BBFB firmware and the pixel resonance frequencies. We also defined a technique to define the AC-carrier initial phases in such a way that the amplitude of their sum is minimized (for a better use of the DAC dynamic range).

Phase-sensitive dual-inversion recovery for accelerated carotid vessel wall imaging.

PubMed

Bonanno, Gabriele; Brotman, David; Stuber, Matthias

2015-03-01

Dual-inversion recovery (DIR) is widely used for magnetic resonance vessel wall imaging. However, optimal contrast may be difficult to obtain and is subject to RR variability. Furthermore, DIR imaging is time-inefficient and multislice acquisitions may lead to prolonged scanning times. Therefore, an extension of phase-sensitive (PS) DIR is proposed for carotid vessel wall imaging. The statistical distribution of the phase signal after DIR is probed to segment carotid lumens and suppress their residual blood signal. The proposed PS-DIR technique was characterized over a broad range of inversion times. Multislice imaging was then implemented by interleaving the acquisition of 3 slices after DIR. Quantitative evaluation was then performed in healthy adult subjects and compared with conventional DIR imaging. Single-slice PS-DIR provided effective blood-signal suppression over a wide range of inversion times, enhancing wall-lumen contrast and vessel wall conspicuity for carotid arteries. Multislice PS-DIR imaging with effective blood-signal suppression is enabled. A variant of the PS-DIR method has successfully been implemented and tested for carotid vessel wall imaging. This technique removes timing constraints related to inversion recovery, enhances wall-lumen contrast, and enables a 3-fold increase in volumetric coverage at no extra cost in scanning time.

Parameter optimization for reproducible cardiac 1 H-MR spectroscopy at 3 Tesla.

PubMed

de Heer, Paul; Bizino, Maurice B; Lamb, Hildo J; Webb, Andrew G

2016-11-01

To optimize data acquisition parameters in cardiac proton MR spectroscopy, and to evaluate the intra- and intersession variability in myocardial triglyceride content. Data acquisition parameters at 3 Tesla (T) were optimized and reproducibility measured using, in total, 49 healthy subjects. The signal-to-noise-ratio (SNR) and the variance in metabolite amplitude between averages were measured for: (i) global versus local power optimization; (ii) static magnetic field (B 0 ) shimming performed during free-breathing or within breathholds; (iii) post R-wave peak measurement times between 50 and 900 ms; (iv) without respiratory compensation, with breathholds and with navigator triggering; and (v) frequency selective excitation, Chemical Shift Selective (CHESS) and Multiply Optimized Insensitive Suppression Train (MOIST) water suppression techniques. Using the optimized parameters intra- and intersession myocardial triglyceride content reproducibility was measured. Two cardiac proton spectra were acquired with the same parameters and compared (intrasession reproducibility) after which the subject was removed from the scanner and placed back in the scanner and a third spectrum was acquired which was compared with the first measurement (intersession reproducibility). Local power optimization increased SNR on average by 22% compared with global power optimization (P = 0.0002). The average linewidth was not significantly different for pencil beam B 0 shimming using free-breathing or breathholds (19.1 Hz versus 17.5 Hz; P = 0.15). The highest signal stability occurred at a cardiac trigger delay around 240 ms. The mean amplitude variation was significantly lower for breathholds versus free-breathing (P = 0.03) and for navigator triggering versus free-breathing (P = 0.03) as well as for navigator triggering versus breathhold (P = 0.02). The mean residual water signal using CHESS (1.1%, P = 0.01) or MOIST (0.7%, P = 0.01) water suppression was significantly lower than using frequency selective excitation water suppression (7.0%). Using the optimized parameters an intrasession limits of agreement of the myocardial triglyceride content of -0.11% to +0.04%, and an intersession of -0.15% to +0.9%, were achieved. The coefficient of variation was 5% for the intrasession reproducibility and 6.5% for the intersession reproducibility. Using approaches designed to optimize SNR and minimize the variation in inter-average signal intensities and frequencies/phases, a protocol was developed to perform cardiac MR spectroscopy on a clinical 3T system with high reproducibility. J. Magn. Reson. Imaging 2016;44:1151-1158. © 2016 International Society for Magnetic Resonance in Medicine.

DOA-informed source extraction in the presence of competing talkers and background noise

NASA Astrophysics Data System (ADS)

Taseska, Maja; Habets, Emanuël A. P.

2017-12-01

A desired speech signal in hands-free communication systems is often degraded by noise and interfering speech. Even though the number and locations of the interferers are often unknown in practice, it is justified to assume in certain applications that the direction-of-arrival (DOA) of the desired source is approximately known. Using the known DOA, fixed spatial filters such as the delay-and-sum beamformer can be steered to extract the desired source. However, it is well-known that fixed data-independent spatial filters do not provide sufficient reduction of directional interferers. Instead, the DOA information can be used to estimate the statistics of the desired and the undesired signals and to compute optimal data-dependent spatial filters. One way the DOA is exploited for optimal spatial filtering in the literature, is by designing DOA-based narrowband detectors to determine whether a desired or an undesired signal is dominant at each time-frequency (TF) bin. Subsequently, the statistics of the desired and the undesired signals can be estimated during the TF bins where the respective signal is dominant. In a similar manner, a Gaussian signal model-based detector which does not incorporate DOA information has been used in scenarios where the undesired signal consists of stationary background noise. However, when the undesired signal is non-stationary, resulting for example from interfering speakers, such a Gaussian signal model-based detector is unable to robustly distinguish desired from undesired speech. To this end, we propose a DOA model-based detector to determine the dominant source at each TF bin and estimate the desired and undesired signal statistics. We demonstrate that data-dependent spatial filters that use the statistics estimated by the proposed framework achieve very good undesired signal reduction, even when using only three microphones.

Matching Pursuit with Asymmetric Functions for Signal Decomposition and Parameterization

PubMed Central

Spustek, Tomasz; Jedrzejczak, Wiesław Wiktor; Blinowska, Katarzyna Joanna

2015-01-01

The method of adaptive approximations by Matching Pursuit makes it possible to decompose signals into basic components (called atoms). The approach relies on fitting, in an iterative way, functions from a large predefined set (called dictionary) to an analyzed signal. Usually, symmetric functions coming from the Gabor family (sine modulated Gaussian) are used. However Gabor functions may not be optimal in describing waveforms present in physiological and medical signals. Many biomedical signals contain asymmetric components, usually with a steep rise and slower decay. For the decomposition of this kind of signal we introduce a dictionary of functions of various degrees of asymmetry – from symmetric Gabor atoms to highly asymmetric waveforms. The application of this enriched dictionary to Otoacoustic Emissions and Steady-State Visually Evoked Potentials demonstrated the advantages of the proposed method. The approach provides more sparse representation, allows for correct determination of the latencies of the components and removes the "energy leakage" effect generated by symmetric waveforms that do not sufficiently match the structures of the analyzed signal. Additionally, we introduced a time-frequency-amplitude distribution that is more adequate for representation of asymmetric atoms than the conventional time-frequency-energy distribution. PMID:26115480

Asymptotic Cramer-Rao bounds for Morlet wavelet filter bank transforms of FM signals

NASA Astrophysics Data System (ADS)

Scheper, Richard

2002-03-01

Wavelet filter banks are potentially useful tools for analyzing and extracting information from frequency modulated (FM) signals in noise. Chief among the advantages of such filter banks is the tendency of wavelet transforms to concentrate signal energy while simultaneously dispersing noise energy over the time-frequency plane, thus raising the effective signal to noise ratio of filtered signals. Over the past decade, much effort has gone into devising new algorithms to extract the relevant information from transformed signals while identifying and discarding the transformed noise. Therefore, estimates of the ultimate performance bounds on such algorithms would serve as valuable benchmarks in the process of choosing optimal algorithms for given signal classes. Discussed here is the specific case of FM signals analyzed by Morlet wavelet filter banks. By making use of the stationary phase approximation of the Morlet transform, and assuming that the measured signals are well resolved digitally, the asymptotic form of the Fisher Information Matrix is derived. From this, Cramer-Rao bounds are analytically derived for simple cases.

Tangeretin inhibits extracellular-signal-regulated kinase (ERK) phosphorylation.

PubMed

Van Slambrouck, Séverine; Parmar, Virinder S; Sharma, Sunil K; De Bondt, Bart; Foré, Fleur; Coopman, Peter; Vanhoecke, Barbara W; Boterberg, Tom; Depypere, Herman T; Leclercq, Guy; Bracke, Marc E

2005-03-14

Tangeretin is a methoxyflavone from citrus fruits, which inhibits growth of human mammary cancer cells and cytolysis by natural killer cells. Attempting to unravel the flavonoid's action mechanism, we found that it inhibited extracellular-signal-regulated kinases 1/2 (ERK1/2) phosphorylation in a dose- and time-dependent way. In human T47D mammary cancer cells this inhibition was optimally observed after priming with estradiol. The spectrum of the intracellular signalling kinase inhibition was narrow and comparison of structural congeners showed that inhibition of ERK phosphorylation was not unique for tangeretin. Our data add tangeretin to the list of small kinase inhibitors with a restricted intracellular inhibition profile.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jang, Junhwan; Hwang, Sungui; Park, Kyihwan, E-mail: khpark@gist.ac.kr

To utilize a time-of-flight-based laser scanner as a distance measurement sensor, the measurable distance and accuracy are the most important performance parameters to consider. For these purposes, the optical system and electronic signal processing of the laser scanner should be optimally designed in order to reduce a distance error caused by the optical crosstalk and wide dynamic range input. Optical system design for removing optical crosstalk problem is proposed in this work. Intensity control is also considered to solve the problem of a phase-shift variation in the signal processing circuit caused by object reflectivity. The experimental results for optical systemmore » and signal processing design are performed using 3D measurements.« less

Multichannel Baseband Processor for Wideband CDMA

NASA Astrophysics Data System (ADS)

Jalloul, Louay M. A.; Lin, Jim

2005-12-01

The system architecture of the cellular base station modem engine (CBME) is described. The CBME is a single-chip multichannel transceiver capable of processing and demodulating signals from multiple users simultaneously. It is optimized to process different classes of code-division multiple-access (CDMA) signals. The paper will show that through key functional system partitioning, tightly coupled small digital signal processing cores, and time-sliced reuse architecture, CBME is able to achieve a high degree of algorithmic flexibility while maintaining efficiency. The paper will also highlight the implementation and verification aspects of the CBME chip design. In this paper, wideband CDMA is used as an example to demonstrate the architecture concept.

Least-mean-square spatial filter for IR sensors.

PubMed

Takken, E H; Friedman, D; Milton, A F; Nitzberg, R

1979-12-15

A new least-mean-square filter is defined for signal-detection problems. The technique is proposed for scanning IR surveillance systems operating in poorly characterized but primarily low-frequency clutter interference. Near-optimal detection of point-source targets is predicted both for continuous-time and sampled-data systems.

Photovoltaic Inverter Controllers Seeking AC Optimal Power Flow Solutions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall'Anese, Emiliano; Dhople, Sairaj V.; Giannakis, Georgios B.

This paper considers future distribution networks featuring inverter-interfaced photovoltaic (PV) systems, and addresses the synthesis of feedback controllers that seek real- and reactive-power inverter setpoints corresponding to AC optimal power flow (OPF) solutions. The objective is to bridge the temporal gap between long-term system optimization and real-time inverter control, and enable seamless PV-owner participation without compromising system efficiency and stability. The design of the controllers is grounded on a dual ..epsilon..-subgradient method, while semidefinite programming relaxations are advocated to bypass the non-convexity of AC OPF formulations. Global convergence of inverter output powers is analytically established for diminishing stepsize rules formore » cases where: i) computational limits dictate asynchronous updates of the controller signals, and ii) inverter reference inputs may be updated at a faster rate than the power-output settling time.« less

Autocorrelation-based time synchronous averaging for condition monitoring of planetary gearboxes in wind turbines

NASA Astrophysics Data System (ADS)

Ha, Jong M.; Youn, Byeng D.; Oh, Hyunseok; Han, Bongtae; Jung, Yoongho; Park, Jungho

2016-03-01

We propose autocorrelation-based time synchronous averaging (ATSA) to cope with the challenges associated with the current practice of time synchronous averaging (TSA) for planet gears in planetary gearboxes of wind turbine (WT). An autocorrelation function that represents physical interactions between the ring, sun, and planet gears in the gearbox is utilized to define the optimal shape and range of the window function for TSA using actual kinetic responses. The proposed ATSA offers two distinctive features: (1) data-efficient TSA processing and (2) prevention of signal distortion during the TSA process. It is thus expected that an order analysis with the ATSA signals significantly improves the efficiency and accuracy in fault diagnostics of planet gears in planetary gearboxes. Two case studies are presented to demonstrate the effectiveness of the proposed method: an analytical signal from a simulation and a signal measured from a 2 kW WT testbed. It can be concluded from the results that the proposed method outperforms conventional TSA methods in condition monitoring of the planetary gearbox when the amount of available stationary data is limited.

Impact of physiological noise correction on detecting blood oxygenation level-dependent contrast in the breast

NASA Astrophysics Data System (ADS)

Wallace, Tess E.; Manavaki, Roido; Graves, Martin J.; Patterson, Andrew J.; Gilbert, Fiona J.

2017-01-01

Physiological fluctuations are expected to be a dominant source of noise in blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) experiments to assess tumour oxygenation and angiogenesis. This work investigates the impact of various physiological noise regressors: retrospective image correction (RETROICOR), heart rate (HR) and respiratory volume per unit time (RVT), on signal variance and the detection of BOLD contrast in the breast in response to a modulated respiratory stimulus. BOLD MRI was performed at 3 T in ten volunteers at rest and during cycles of oxygen and carbogen gas breathing. RETROICOR was optimized using F-tests to determine which cardiac and respiratory phase terms accounted for a significant amount of signal variance. A nested regression analysis was performed to assess the effect of RETROICOR, HR and RVT on the model fit residuals, temporal signal-to-noise ratio, and BOLD activation parameters. The optimized RETROICOR model accounted for the largest amount of signal variance ( Δ R\\text{adj}2   =  3.3  ±  2.1%) and improved the detection of BOLD activation (P  =  0.002). Inclusion of HR and RVT regressors explained additional signal variance, but had a negative impact on activation parameter estimation (P  <  0.001). Fluctuations in HR and RVT appeared to be correlated with the stimulus and may contribute to apparent BOLD signal reactivity.

Improvement of the fringe analysis algorithm for wavelength scanning interferometry based on filter parameter optimization.

PubMed

Zhang, Tao; Gao, Feng; Muhamedsalih, Hussam; Lou, Shan; Martin, Haydn; Jiang, Xiangqian

2018-03-20

The phase slope method which estimates height through fringe pattern frequency and the algorithm which estimates height through the fringe phase are the fringe analysis algorithms widely used in interferometry. Generally they both extract the phase information by filtering the signal in frequency domain after Fourier transform. Among the numerous papers in the literature about these algorithms, it is found that the design of the filter, which plays an important role, has never been discussed in detail. This paper focuses on the filter design in these algorithms for wavelength scanning interferometry (WSI), trying to optimize the parameters to acquire the optimal results. The spectral characteristics of the interference signal are analyzed first. The effective signal is found to be narrow-band (near single frequency), and the central frequency is calculated theoretically. Therefore, the position of the filter pass-band is determined. The width of the filter window is optimized with the simulation to balance the elimination of the noise and the ringing of the filter. Experimental validation of the approach is provided, and the results agree very well with the simulation. The experiment shows that accuracy can be improved by optimizing the filter design, especially when the signal quality, i.e., the signal noise ratio (SNR), is low. The proposed method also shows the potential of improving the immunity to the environmental noise by adapting the signal to acquire the optimal results through designing an adaptive filter once the signal SNR can be estimated accurately.

Brain-computer interface signal processing at the Wadsworth Center: mu and sensorimotor beta rhythms.

PubMed

McFarland, Dennis J; Krusienski, Dean J; Wolpaw, Jonathan R

2006-01-01

The Wadsworth brain-computer interface (BCI), based on mu and beta sensorimotor rhythms, uses one- and two-dimensional cursor movement tasks and relies on user training. This is a real-time closed-loop system. Signal processing consists of channel selection, spatial filtering, and spectral analysis. Feature translation uses a regression approach and normalization. Adaptation occurs at several points in this process on the basis of different criteria and methods. It can use either feedforward (e.g., estimating the signal mean for normalization) or feedback control (e.g., estimating feature weights for the prediction equation). We view this process as the interaction between a dynamic user and a dynamic system that coadapt over time. Understanding the dynamics of this interaction and optimizing its performance represent a major challenge for BCI research.

Engineering New Aptamer Geometries for Electrochemical Aptamer-Based Sensors

PubMed Central

White, Ryan J.; Plaxco, Kevin W.

2010-01-01

Electrochemical aptamer-based sensors (E-AB sensors) represent a promising new approach to the detection of small molecules. E-AB sensors comprise an aptamer that is attached at one end to an electrode surface. The distal end of the aptamer probed is modified with an electroactive redox marker for signal transduction. Herein we report on the optimization of a cocaine-detecting E-AB sensor via optimization of the geometry of the aptamer. We explore two new aptamer architectures, one in which we concatenate three cocaine aptamers into a poly-aptamer and a second in which we divide the cocaine aptamer into pieces connected via an unstructured, 60-thymine linker. Both of these structures are designed such that the reporting redox tag will be located farther from the electrode in the unfolded, target-free conformation. Consistent with this, we find that signal gains of these two constructs are two to three times higher than that of the original E-AB architecture. Likewise all three architectures are selective enough to deploy directly in complex sample matrices, such as undiluted whole blood, with all three sensors successfully detecting the presence of cocaine. The findings in this ongoing study should be of value in future efforts to optimize the signaling of electrochemical aptamer-based sensors. PMID:20436792

An Improved Response Surface Methodology Algorithm with an Application to Traffic Signal Optimization for Urban Networks

DOT National Transportation Integrated Search

1995-01-01

Prepared ca. 1995. This paper illustrates the use of the simulation-optimization technique of response surface methodology (RSM) in traffic signal optimization of urban networks. It also quantifies the gains of using the common random number (CRN) va...

Optimization of flow-sensitive alternating inversion recovery (FAIR) for perfusion functional MRI of rodent brain.

PubMed

Nasrallah, Fatima A; Lee, Eugene L Q; Chuang, Kai-Hsiang

2012-11-01

Arterial spin labeling (ASL) MRI provides a noninvasive method to image perfusion, and has been applied to map neural activation in the brain. Although pulsed labeling methods have been widely used in humans, continuous ASL with a dedicated neck labeling coil is still the preferred method in rodent brain functional MRI (fMRI) to maximize the sensitivity and allow multislice acquisition. However, the additional hardware is not readily available and hence its application is limited. In this study, flow-sensitive alternating inversion recovery (FAIR) pulsed ASL was optimized for fMRI of rat brain. A practical challenge of FAIR is the suboptimal global inversion by the transmit coil of limited dimensions, which results in low effective labeling. By using a large volume transmit coil and proper positioning to optimize the body coverage, the perfusion signal was increased by 38.3% compared with positioning the brain at the isocenter. An additional 53.3% gain in signal was achieved using optimized repetition and inversion times compared with a long TR. Under electrical stimulation to the forepaws, a perfusion activation signal change of 63.7 ± 6.3% can be reliably detected in the primary somatosensory cortices using single slice or multislice echo planar imaging at 9.4 T. This demonstrates the potential of using pulsed ASL for multislice perfusion fMRI in functional and pharmacological applications in rat brain. Copyright © 2012 John Wiley & Sons, Ltd.

A real-time spike sorting method based on the embedded GPU.

PubMed

Zelan Yang; Kedi Xu; Xiang Tian; Shaomin Zhang; Xiaoxiang Zheng

2017-07-01

Microelectrode arrays with hundreds of channels have been widely used to acquire neuron population signals in neuroscience studies. Online spike sorting is becoming one of the most important challenges for high-throughput neural signal acquisition systems. Graphic processing unit (GPU) with high parallel computing capability might provide an alternative solution for increasing real-time computational demands on spike sorting. This study reported a method of real-time spike sorting through computing unified device architecture (CUDA) which was implemented on an embedded GPU (NVIDIA JETSON Tegra K1, TK1). The sorting approach is based on the principal component analysis (PCA) and K-means. By analyzing the parallelism of each process, the method was further optimized in the thread memory model of GPU. Our results showed that the GPU-based classifier on TK1 is 37.92 times faster than the MATLAB-based classifier on PC while their accuracies were the same with each other. The high-performance computing features of embedded GPU demonstrated in our studies suggested that the embedded GPU provide a promising platform for the real-time neural signal processing.

Optimisation of wavelength modulated Raman spectroscopy: towards high throughput cell screening.

PubMed

Praveen, Bavishna B; Mazilu, Michael; Marchington, Robert F; Herrington, C Simon; Riches, Andrew; Dholakia, Kishan

2013-01-01

In the field of biomedicine, Raman spectroscopy is a powerful technique to discriminate between normal and cancerous cells. However the strong background signal from the sample and the instrumentation affects the efficiency of this discrimination technique. Wavelength Modulated Raman spectroscopy (WMRS) may suppress the background from the Raman spectra. In this study we demonstrate a systematic approach for optimizing the various parameters of WMRS to achieve a reduction in the acquisition time for potential applications such as higher throughput cell screening. The Signal to Noise Ratio (SNR) of the Raman bands depends on the modulation amplitude, time constant and total acquisition time. It was observed that the sampling rate does not influence the signal to noise ratio of the Raman bands if three or more wavelengths are sampled. With these optimised WMRS parameters, we increased the throughput in the binary classification of normal human urothelial cells and bladder cancer cells by reducing the total acquisition time to 6 s which is significantly lower in comparison to previous acquisition times required for the discrimination between similar cell types.

Optimized 31P MRS in the human brain at 7 T with a dedicated RF coil setup

PubMed Central

van de Bank, Bart L.; Orzada, Stephan; Smits, Frits; Lagemaat, Miriam W.; Rodgers, Christopher T.; Bitz, Andreas K.

2015-01-01

The design and construction of a dedicated RF coil setup for human brain imaging (1H) and spectroscopy (31P) at ultra‐high magnetic field strength (7 T) is presented. The setup is optimized for signal handling at the resonance frequencies for 1H (297.2 MHz) and 31P (120.3 MHz). It consists of an eight‐channel 1H transmit–receive head coil with multi‐transmit capabilities, and an insertable, actively detunable 31P birdcage (transmit–receive and transmit only), which can be combined with a seven‐channel receive‐only 31P array. The setup enables anatomical imaging and 31P studies without removal of the coil or the patient. By separating transmit and receive channels and by optimized addition of array signals with whitened singular value decomposition we can obtain a sevenfold increase in SNR of 31P signals in the occipital lobe of the human brain compared with the birdcage alone. These signals can be further enhanced by 30 ± 9% using the nuclear Overhauser effect by B 1‐shimmed low‐power irradiation of water protons. Together, these features enable acquisition of 31P MRSI at high spatial resolutions (3.0 cm3 voxel) in the occipital lobe of the human brain in clinically acceptable scan times (~15 min). © 2015 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd. PMID:26492089

[Optimal scan parameters for a method of k-space trajectory (radial scan method) in evaluation of carotid plaque characteristics].

PubMed

Nakamura, Manami; Makabe, Takeshi; Tezuka, Hideomi; Miura, Takahiro; Umemura, Takuma; Sugimori, Hiroyuki; Sakata, Motomichi

2013-04-01

The purpose of this study was to optimize scan parameters for evaluation of carotid plaque characteristics by k-space trajectory (radial scan method), using a custom-made carotid plaque phantom. The phantom was composed of simulated sternocleidomastoid muscle and four types of carotid plaque. The effect of chemical shift artifact was compared using T1 weighted images (T1WI) of the phantom obtained with and without fat suppression, and using two types of k-space trajectory (the radial scan method and the Cartesian method). The ratio of signal intensity of simulated sternocleidomastoid muscle to the signal intensity of hematoma, blood (including heparin), lard, and mayonnaise was compared among various repetition times (TR) using T1WI and T2 weighted imaging (T2WI). In terms of chemical shift artifacts, image quality was improved using fat suppression for both the radial scan and Cartesian methods. In terms of signal ratio, the highest values were obtained for the radial scan method with TR of 500 ms for T1WI, and TR of 3000 ms for T2WI. For evaluation of carotid plaque characteristics using the radial scan method, chemical shift artifacts were reduced with fat suppression. Signal ratio was improved by optimizing the TR settings for T1WI and T2WI. These results suggest the potential for using magnetic resonance imaging for detailed evaluation of carotid plaque.

Prospects of in vivo singlet oxygen luminescence monitoring: Kinetics at different locations on living mice.

PubMed

Pfitzner, Michael; Schlothauer, Jan C; Bastien, Estelle; Hackbarth, Steffen; Bezdetnaya, Lina; Lassalle, Henri-Pierre; Röder, Beate

2016-06-01

Singlet oxygen observation is considered a valuable tool to assess and optimize PDT treatment. In complex systems, such as tumors in vivo, only the direct, time-resolved singlet oxygen luminescence detection can give reliable information about generation and interaction of singlet oxygen. Up to now, evaluation of kinetics was not possible due to insufficient signal-to-noise ratio. Here we present high signal-to-noise ratio singlet oxygen luminescence kinetics obtained in mouse tumor model under PDT relevant conditions. A highly optimized system based on a custom made laser diode excitation source and a high aperture multi-furcated fiber, utilizing a photomultiplier tube with a multi photon counting device was used. Luminescence kinetics with unsurpassed signal-to-noise ratio were gained from tumor bearing nude mice in vivo upon topic application, subcutaneous injection as well as intravenous injection of different photosensitizers (chlorin e6 and dendrimer formulations of chlorin e6). Singlet oxygen kinetics in appropriate model systems are discussed to facilitate the interpretation of complex kinetics obtained from in vivo tumor tissue. This is the first study addressing the complexity of singlet oxygen luminescence kinetics in tumor tissue. At present, further investigations are needed to fully explain the processes involved. Nevertheless, the high signal-to-noise ratio proves the applicability of direct time-resolved singlet oxygen luminescence detection as a prospective tool for monitoring photodynamic therapy. Copyright © 2016 Elsevier B.V. All rights reserved.

LMD Based Features for the Automatic Seizure Detection of EEG Signals Using SVM.

PubMed

Zhang, Tao; Chen, Wanzhong

2017-08-01

Achieving the goal of detecting seizure activity automatically using electroencephalogram (EEG) signals is of great importance and significance for the treatment of epileptic seizures. To realize this aim, a newly-developed time-frequency analytical algorithm, namely local mean decomposition (LMD), is employed in the presented study. LMD is able to decompose an arbitrary signal into a series of product functions (PFs). Primarily, the raw EEG signal is decomposed into several PFs, and then the temporal statistical and non-linear features of the first five PFs are calculated. The features of each PF are fed into five classifiers, including back propagation neural network (BPNN), K-nearest neighbor (KNN), linear discriminant analysis (LDA), un-optimized support vector machine (SVM) and SVM optimized by genetic algorithm (GA-SVM), for five classification cases, respectively. Confluent features of all PFs and raw EEG are further passed into the high-performance GA-SVM for the same classification tasks. Experimental results on the international public Bonn epilepsy EEG dataset show that the average classification accuracy of the presented approach are equal to or higher than 98.10% in all the five cases, and this indicates the effectiveness of the proposed approach for automated seizure detection.

Comparative Analysis of Neural Network Training Methods in Real-time Radiotherapy.

PubMed

Nouri, S; Hosseini Pooya, S M; Soltani Nabipour, J

2017-03-01

The motions of body and tumor in some regions such as chest during radiotherapy treatments are one of the major concerns protecting normal tissues against high doses. By using real-time radiotherapy technique, it is possible to increase the accuracy of delivered dose to the tumor region by means of tracing markers on the body of patients. This study evaluates the accuracy of some artificial intelligence methods including neural network and those of combination with genetic algorithm as well as particle swarm optimization (PSO) estimating tumor positions in real-time radiotherapy. One hundred recorded signals of three external markers were used as input data. The signals from 3 markers thorough 10 breathing cycles of a patient treated via a cyber-knife for a lung tumor were used as data input. Then, neural network method and its combination with genetic or PSO algorithms were applied determining the tumor locations using MATLAB© software program. The accuracies were obtained 0.8%, 12% and 14% in neural network, genetic and particle swarm optimization algorithms, respectively. The internal target volume (ITV) should be determined based on the applied neural network algorithm on training steps.

Photonic generation of background-free millimeter-wave ultra-wideband pulses based on a single dual-drive Mach-Zehnder modulator.

PubMed

Li, Wei; Wang, Wen Ting; Sun, Wen Hui; Wang, Li Xian; Zhu, Ning Hua

2014-03-01

We propose a novel photonic approach for generating a background-free millimeter-wave (MMW) ultra-wideband (UWB) signal based on a conventional dual-drive Mach-Zehnder modulator (DMZM). One arm of the DMZM is driven by a local oscillator (LO) signal. The LO power is optimized to realize optical carrier suppressed modulation. The other arm is fed by a rectangular signal. The MMW UWB pulses are generated by truncating the continuous wave LO signal into a pulsed one in a photodetector (PD). The generated MMW UWB signal is background-free by eliminating the baseband frequency components because the optical power launched to the PD keeps constant all the time. The proposed method is theoretically analyzed and experimentally verified. The generated MMW UWB signal centered at a frequency of 26 GHz meets the Federal Communications Commission spectral mask very well.

Considerations on the Optimal and Efficient Processing of Information-Bearing Signals

ERIC Educational Resources Information Center

Harms, Herbert Andrew

2013-01-01

Noise is a fundamental hurdle that impedes the processing of information-bearing signals, specifically the extraction of salient information. Processing that is both optimal and efficient is desired; optimality ensures the extracted information has the highest fidelity allowed by the noise, while efficiency ensures limited resource usage. Optimal…

Multi-input multioutput orthogonal frequency division multiplexing radar waveform design for improving the detection performance of space-time adaptive processing

NASA Astrophysics Data System (ADS)

Wang, Hongyan

2017-04-01

This paper addresses the waveform optimization problem for improving the detection performance of multi-input multioutput (MIMO) orthogonal frequency division multiplexing (OFDM) radar-based space-time adaptive processing (STAP) in the complex environment. By maximizing the output signal-to-interference-and-noise-ratio (SINR) criterion, the waveform optimization problem for improving the detection performance of STAP, which is subjected to the constant modulus constraint, is derived. To tackle the resultant nonlinear and complicated optimization issue, a diagonal loading-based method is proposed to reformulate the issue as a semidefinite programming one; thereby, this problem can be solved very efficiently. In what follows, the optimized waveform can be obtained to maximize the output SINR of MIMO-OFDM such that the detection performance of STAP can be improved. The simulation results show that the proposed method can improve the output SINR detection performance considerably as compared with that of uncorrelated waveforms and the existing MIMO-based STAP method.

Breath detection by transcutaneous electromyography of the diaphragm and the Graseby capsule in preterm infants.

PubMed

de Waal, Cornelia G; Kraaijenga, Juliette V; Hutten, Gerard J; de Jongh, Frans H; van Kaam, Anton H

2017-12-01

To compare triggering, breath detection and delay time of the Graseby capsule (GC) and transcutaneous electromyography of the diaphragm (dEMG) in spontaneous breathing preterm infants. In this observational study, a 30 minutes respiration measurement was conducted by respiratory inductance plethysmography (RIP), the GC, and dEMG in stable preterm infants. Triggering was investigated with an in vitro set-up using the Infant Flow ® SiPAP TM system. The possibility to optimize breath detection was tested by developing new algorithms with the abdominal RIP band (RIP AB ) as gold standard. In a subset of breaths, the delay time was calculated between the inspiratory onset in the RIP AB signal and in the GC and dEMG signal. Fifteen preterm infants with a mean gestational age of 28 ± 2 weeks and a mean birth weight of 1086 ± 317 g were included. In total, 14 773 breaths were analyzed. Based on the GC and dEMG signal, the Infant Flow ® SiPAP™ system, respectively, triggered 67.8% and 62.6% of the breaths. Breath detection was improved to 99.9% for the GC and 113.4% for dEMG in new algorithms. In 1492 stable breaths, the median delay time of inspiratory onset detection was +154 ms (IQR +118 to +164) in the GC and -50 ms (IQR -90 to -22) in the dEMG signal. Breath detection using the GC can be improved by optimizing the algorithm. Transcutaneous dEMG provides similar breath detection but with the advantage of detecting the onset of inspiration earlier than the GC. © 2017 Wiley Periodicals, Inc.

Optimal control of information epidemics modeled as Maki Thompson rumors

NASA Astrophysics Data System (ADS)

Kandhway, Kundan; Kuri, Joy

2014-12-01

We model the spread of information in a homogeneously mixed population using the Maki Thompson rumor model. We formulate an optimal control problem, from the perspective of single campaigner, to maximize the spread of information when the campaign budget is fixed. Control signals, such as advertising in the mass media, attempt to convert ignorants and stiflers into spreaders. We show the existence of a solution to the optimal control problem when the campaigning incurs non-linear costs under the isoperimetric budget constraint. The solution employs Pontryagin's Minimum Principle and a modified version of forward backward sweep technique for numerical computation to accommodate the isoperimetric budget constraint. The techniques developed in this paper are general and can be applied to similar optimal control problems in other areas. We have allowed the spreading rate of the information epidemic to vary over the campaign duration to model practical situations when the interest level of the population in the subject of the campaign changes with time. The shape of the optimal control signal is studied for different model parameters and spreading rate profiles. We have also studied the variation of the optimal campaigning costs with respect to various model parameters. Results indicate that, for some model parameters, significant improvements can be achieved by the optimal strategy compared to the static control strategy. The static strategy respects the same budget constraint as the optimal strategy and has a constant value throughout the campaign horizon. This work finds application in election and social awareness campaigns, product advertising, movie promotion and crowdfunding campaigns.

[Application of recombinase polymerase amplification in the detection of Pseudomonas aeruginosa].

PubMed

Jin, X J; Gong, Y L; Yang, L; Mo, B H; Peng, Y Z; He, P; Zhao, J N; Li, X L

2018-04-20

Objective: To establish an optimized method of recombinase polymerase amplification (RPA) to rapidly detect Pseudomonas aeruginosa in clinic. Methods: (1) The DNA templates of one standard Pseudomonas aeruginosa strain was extracted and detected by polymerase chain reaction (PCR), real-time fluorescence quantitative PCR and RPA. Time of sample loading, time of amplification, and time of detection of the three methods were recorded. (2) One standard Pseudomonas aeruginosa strain was diluted in 7 concentrations of 1×10(7,) 1×10(6,) 1×10(5,) 1×10(4,) 1×10(3,) 1×10(2,) and 1×10(1) colony forming unit (CFU)/mL after recovery and cultivation. The DNA templates of Pseudomonas aeruginosa and negative control strain Pseudomonas putida were extracted and detected by PCR, real-time fluorescence quantitative PCR, and RPA separately. The sensitivity of the three methods in detecting Pseudomonas aeruginosa was analyzed. (3) The DNA templates of one standard Pseudomonas aeruginosa strain and four negative control strains ( Staphylococcus aureus, Acinetobacter baumanii, Candida albicans, and Pseudomonas putida ) were extracted separately, and then they were detected by PCR, real-time fluorescence quantitative PCR, and RPA. The specificity of the three methods in detecting Pseudomonas aeruginosa was analyzed. (4) The DNA templates of 28 clinical strains of Pseudomonas aeruginosa preserved in glycerin, 1 clinical strain of which was taken by cotton swab, and negative control strain Pseudomonas putida were extracted separately, and then they were detected by RPA. Positive amplification signals of the clinical strains were observed, and the detection rate was calculated. All experiments were repeated for 3 times. Sensitivity results were analyzed by GraphPad Prism 5.01 statistical software. Results: (1) The loading time of RPA, PCR, and real-time fluorescence quantitative PCR for detecting Pseudomonas aeruginosa were all 20 minutes. In PCR, time of amplification was 98 minutes, time of gel detection was 20 minutes, and the total time was 138 minutes. In real-time fluorescence quantitative PCR, amplification and detection could be completed simultaneously, which took 90 minutes, and the total time was 110 minutes. In RPA, amplification and detection could also be completed simultaneously, which took 15 minutes, and the total time was 35 minutes. (2) Pseudomonas putida did not show positive amplification signals or gel positive results in any of the three detection methods. The detection limit of Pseudomonas aeruginosa in real-time fluorescence quantitative PCR and PCR was 1×10(1) CFU/mL, and that of Pseudomonas aeruginosa in RPA was 1×10(2) CFU/mL. In RPA and real-time fluorescence quantitative PCR, the higher the concentration of Pseudomonas aeruginosa, the shorter threshold time and smaller the number of cycles, namely shorter time for detecting the positive amplified signal. In real-time fluorescence quantitative PCR, all positive amplification signal could be detected when the concentration of Pseudomonas aeruginosa was 1×10(1)-1×10(7) CFU/mL. In RPA, the detection rate of positive amplification signal was 0 when the concentration of Pseudomonas aeruginosa was 1×10(1) CFU/mL, while the detection rate of positive amplification signal was 67% when the concentration of Pseudomonas aeruginosa was 1×10(2) CFU/mL, and the detection rate of positive amplification signal was 100% when the concentration of Pseudomonas aeruginosa was 1×10(3)-1×10(7) CFU/mL. (3) In RPA, PCR, and real-time fluorescence quantitative PCR, Pseudomonas aeruginosa showed positive amplification signals and gel positive results, but there were no positive amplification signals or gel positive results in four negative control strains of Acinetobacter baumannii, Staphylococcus aureus, Candida albicans, and Pseudomonas putida . (4) In RPA, 28 clinical strains of Pseudomonas aeruginosa preserved in glycerin and 1 clinical strain of Pseudomonas aeruginosa taken by cotton swab showed positive amplification signals, while Pseudomonas putida did not show positive amplification signal. The detection rate of positive amplification signal of 29 clinical strains of Pseudomonas aeruginosa in RPA was 100%. Conclusions: The established optimized RPA technology for fast detection of Pseudomonas aeruginosa requires shorter time, with high sensitivity and specificity. It was of great value in fast detection of Pseudomonas aeruginosa infection in clinic.

Exploiting EMI Signals During Active Transmission

DTIC Science & Technology

2010-08-12

Surveys) fixed wing airborne EM system. (Center) AeroTEM (AeroQuest Surveys) helicopter-based airborne time-domain EM system, (Right) VTEM ( GeoTech Ltd...Center) AeroTEM (AeroQuest Surveys) helicopter-based airborne time-domain EM system, (Right) VTEM ( GeoTech Ltd.) helicopter-borne AEM system. All three...systems such as the UTEM (Lamontange Geophysics) and the SPECTREM AEM systems. Geotech Ltd. uses a complicated waveform which has been optimized to

Time-Varying Delay Estimation Applied to the Surface Electromyography Signals Using the Parametric Approach

NASA Astrophysics Data System (ADS)

Luu, Gia Thien; Boualem, Abdelbassit; Duy, Tran Trung; Ravier, Philippe; Butteli, Olivier

Muscle Fiber Conduction Velocity (MFCV) can be calculated from the time delay between the surface electromyographic (sEMG) signals recorded by electrodes aligned with the fiber direction. In order to take into account the non-stationarity during the dynamic contraction (the most daily life situation) of the data, the developed methods have to consider that the MFCV changes over time, which induces time-varying delays and the data is non-stationary (change of Power Spectral Density (PSD)). In this paper, the problem of TVD estimation is considered using a parametric method. First, the polynomial model of TVD has been proposed. Then, the TVD model parameters are estimated by using a maximum likelihood estimation (MLE) strategy solved by a deterministic optimization technique (Newton) and stochastic optimization technique, called simulated annealing (SA). The performance of the two techniques is also compared. We also derive two appropriate Cramer-Rao Lower Bounds (CRLB) for the estimated TVD model parameters and for the TVD waveforms. Monte-Carlo simulation results show that the estimation of both the model parameters and the TVD function is unbiased and that the variance obtained is close to the derived CRBs. A comparison with non-parametric approaches of the TVD estimation is also presented and shows the superiority of the method proposed.

Optimization of image quality and acquisition time for lab-based X-ray microtomography using an iterative reconstruction algorithm

NASA Astrophysics Data System (ADS)

Lin, Qingyang; Andrew, Matthew; Thompson, William; Blunt, Martin J.; Bijeljic, Branko

2018-05-01

Non-invasive laboratory-based X-ray microtomography has been widely applied in many industrial and research disciplines. However, the main barrier to the use of laboratory systems compared to a synchrotron beamline is its much longer image acquisition time (hours per scan compared to seconds to minutes at a synchrotron), which results in limited application for dynamic in situ processes. Therefore, the majority of existing laboratory X-ray microtomography is limited to static imaging; relatively fast imaging (tens of minutes per scan) can only be achieved by sacrificing imaging quality, e.g. reducing exposure time or number of projections. To alleviate this barrier, we introduce an optimized implementation of a well-known iterative reconstruction algorithm that allows users to reconstruct tomographic images with reasonable image quality, but requires lower X-ray signal counts and fewer projections than conventional methods. Quantitative analysis and comparison between the iterative and the conventional filtered back-projection reconstruction algorithm was performed using a sandstone rock sample with and without liquid phases in the pore space. Overall, by implementing the iterative reconstruction algorithm, the required image acquisition time for samples such as this, with sparse object structure, can be reduced by a factor of up to 4 without measurable loss of sharpness or signal to noise ratio.

Optimization of three FISH procedures for in situ detection of anaerobic ammonium oxidizing bacteria in biological wastewater treatment.

PubMed

Pavlekovic, Marko; Schmid, Markus C; Schmider-Poignee, Nadja; Spring, Stefan; Pilhofer, Martin; Gaul, Tobias; Fiandaca, Mark; Löffler, Frank E; Jetten, Mike; Schleifer, K-H; Lee, Natuschka M

2009-08-01

Fluorescence in situ hybridization (FISH) using fluorochrome-labeled DNA oligonucleotide probes has been successfully applied for in situ detection of anaerobic ammonium oxidizing (anammox) bacteria. However, application of the standard FISH protocols to visualize anammox bacteria in biofilms from a laboratory-scale wastewater reactor produced only weak signals. Increased signal intensity was achieved either by modifying the standard FISH protocol, using peptide nucleic acid probes (PNA FISH), or applying horse radish peroxidase- (HRP-) labeled probes and subsequent catalyzed reporter deposition (CARD-FISH). A comparative analysis using anammox biofilm samples and suspended anammox biomass from different laboratory wastewater bioreactors revealed that the modified standard FISH protocol and the PNA FISH probes produced equally strong fluorescence signals on suspended biomass, but only weak signals were obtained with the biofilm samples. The probe signal intensities in the biofilm samples could be enhanced by enzymatic pre-treatment of fixed cells, and by increasing the hybridization time of the PNA FISH protocol. CARD-FISH always produced up to four-fold stronger fluorescent signals but unspecific fluorescence signals, likely caused by endogenous peroxidases as reported in several previous studies, compromised the results. Interference of the development of fluorescence intensity with endogenous peroxidases was also observed in cells of aerobic ammonium oxidizers like Nitrosomonas europea, and sulfate-reducers like Desulfobacter postgatei. Interestingly, no interference was observed with other peroxidase-positive microorganisms, suggesting that CARD-FISH is not only compromised by the mere presence of peroxidases. Pre-treatment of cells to inactivate peroxidase with HCl or autoclavation/pasteurization failed to inactive peroxidases, but H(2)O(2) significantly reduced endogenous peroxidase activity. However, for optimal inactivation, different H(2)O(2) concentrations and incubation time may be needed, depending on nature of sample and should therefore always be individually determined for each study.

Optimizing the Laser-Pulse Configuration for Coherent Raman Spectroscopy

NASA Astrophysics Data System (ADS)

Pestov, Dmitry; Murawski, Robert K.; Ariunbold, Gombojav O.; Wang, Xi; Zhi, Miaochan; Sokolov, Alexei V.; Sautenkov, Vladimir A.; Rostovtsev, Yuri V.; Dogariu, Arthur; Huang, Yu; Scully, Marlan O.

2007-04-01

We introduce a hybrid technique that combines the robustness of frequency-resolved coherent anti-Stokes Raman scattering (CARS) with the advantages of time-resolved CARS spectroscopy. Instantaneous coherent broadband excitation of several characteristic molecular vibrations and the subsequent probing of these vibrations by an optimally shaped time-delayed narrowband laser pulse help to suppress the nonresonant background and to retrieve the species-specific signal. We used this technique for coherent Raman spectroscopy of sodium dipicolinate powder, which is similar to calcium dipicolinate (a marker molecule for bacterial endospores, such as Bacillus subtilis and Bacillus anthracis), and we demonstrated a rapid and highly specific detection scheme that works even in the presence of multiple scattering.

Optimizing the laser-pulse configuration for coherent Raman spectroscopy.

PubMed

Pestov, Dmitry; Murawski, Robert K; Ariunbold, Gombojav O; Wang, Xi; Zhi, Miaochan; Sokolov, Alexei V; Sautenkov, Vladimir A; Rostovtsev, Yuri V; Dogariu, Arthur; Huang, Yu; Scully, Marlan O

2007-04-13

We introduce a hybrid technique that combines the robustness of frequency-resolved coherent anti-Stokes Raman scattering (CARS) with the advantages of time-resolved CARS spectroscopy. Instantaneous coherent broadband excitation of several characteristic molecular vibrations and the subsequent probing of these vibrations by an optimally shaped time-delayed narrowband laser pulse help to suppress the nonresonant background and to retrieve the species-specific signal. We used this technique for coherent Raman spectroscopy of sodium dipicolinate powder, which is similar to calcium dipicolinate (a marker molecule for bacterial endospores, such as Bacillus subtilis and Bacillus anthracis), and we demonstrated a rapid and highly specific detection scheme that works even in the presence of multiple scattering.

Functional Near Infrared Spectroscopy: Watching the Brain in Flight

NASA Technical Reports Server (NTRS)

Harrivel, Angela; Hearn, Tristan

2012-01-01

Functional Near Infrared Spectroscopy (fNIRS) is an emerging neurological sensing technique applicable to optimizing human performance in transportation operations, such as commercial aviation. Cognitive state can be determined via pattern classification of functional activations measured with fNIRS. Operational application calls for further development of algorithms and filters for dynamic artifact removal. The concept of using the frequency domain phase shift signal to tune a Kalman filter is introduced to improve the quality of fNIRS signals in realtime. Hemoglobin concentration and phase shift traces were simulated for four different types of motion artifact to demonstrate the filter. Unwanted signal was reduced by at least 43%, and the contrast of the filtered oxygenated hemoglobin signal was increased by more than 100% overall. This filtering method is a good candidate for qualifying fNIRS signals in real time without auxiliary sensors

In-line mixing states monitoring of suspensions using ultrasonic reflection technique.

PubMed

Zhan, Xiaobin; Yang, Yili; Liang, Jian; Zou, Dajun; Zhang, Jiaqi; Feng, Luyi; Shi, Tielin; Li, Xiwen

2016-02-01

Based on the measurement of echo signal changes caused by different concentration distributions in the mixing process, a simple ultrasonic reflection technique is proposed for in-line monitoring of the mixing states of suspensions in an agitated tank in this study. The relation between the echo signals and the concentration of suspensions is studied, and the mixing process of suspensions is tracked by in-line measurement of ultrasonic echo signals using two ultrasonic sensors. Through the analysis of echo signals over time, the mixing states of suspensions are obtained, and the homogeneity of suspensions is quantified. With the proposed technique, the effects of impeller diameter and agitation speed on the mixing process are studied, and the optimal agitation speed and the minimum mixing time to achieve the maximum homogeneity are acquired under different operating conditions and design parameters. The proposed technique is stable and feasible and shows great potential for in-line monitoring of mixing states of suspensions. Copyright © 2015 Elsevier B.V. All rights reserved.

A Perspective on Studying G-Protein–Coupled Receptor Signaling with Resonance Energy Transfer Biosensors in Living Organisms

PubMed Central

van Unen, Jakobus; Woolard, Jeanette; Rinken, Ago; Hoffmann, Carsten; Hill, Stephen J.; Goedhart, Joachim; Bruchas, Michael R.; Bouvier, Michel

2015-01-01

The last frontier for a complete understanding of G-protein–coupled receptor (GPCR) biology is to be able to assess GPCR activity, interactions, and signaling in vivo, in real time within biologically intact systems. This includes the ability to detect GPCR activity, trafficking, dimerization, protein-protein interactions, second messenger production, and downstream signaling events with high spatial resolution and fast kinetic readouts. Resonance energy transfer (RET)–based biosensors allow for all of these possibilities in vitro and in cell-based assays, but moving RET into intact animals has proven difficult. Here, we provide perspectives on the optimization of biosensor design, of signal detection in living organisms, and the multidisciplinary development of in vitro and cell-based assays that more appropriately reflect the physiologic situation. In short, further development of RET-based probes, optical microscopy techniques, and mouse genome editing hold great potential over the next decade to bring real-time in vivo GPCR imaging to the forefront of pharmacology. PMID:25972446

Multi-images deconvolution improves signal-to-noise ratio on gated stimulated emission depletion microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Castello, Marco; DIBRIS, University of Genoa, Via Opera Pia 13, Genoa 16145; Diaspro, Alberto

2014-12-08

Time-gated detection, namely, only collecting the fluorescence photons after a time-delay from the excitation events, reduces complexity, cost, and illumination intensity of a stimulated emission depletion (STED) microscope. In the gated continuous-wave- (CW-) STED implementation, the spatial resolution improves with increased time-delay, but the signal-to-noise ratio (SNR) reduces. Thus, in sub-optimal conditions, such as a low photon-budget regime, the SNR reduction can cancel-out the expected gain in resolution. Here, we propose a method which does not discard photons, but instead collects all the photons in different time-gates and recombines them through a multi-image deconvolution. Our results, obtained on simulated andmore » experimental data, show that the SNR of the restored image improves relative to the gated image, thereby improving the effective resolution.« less

A computer controlled signal preprocessor for laser fringe anemometer applications

NASA Technical Reports Server (NTRS)

Oberle, Lawrence G.

1987-01-01

The operation of most commercially available laser fringe anemometer (LFA) counter-processors assumes that adjustments are made to the signal processing independent of the computer used for reducing the data acquired. Not only does the researcher desire a record of these parameters attached to the data acquired, but changes in flow conditions generally require that these settings be changed to improve data quality. Because of this limitation, on-line modification of the data acquisition parameters can be difficult and time consuming. A computer-controlled signal preprocessor has been developed which makes possible this optimization of the photomultiplier signal as a normal part of the data acquisition process. It allows computer control of the filter selection, signal gain, and photo-multiplier voltage. The raw signal from the photomultiplier tube is input to the preprocessor which, under the control of a digital computer, filters the signal and amplifies it to an acceptable level. The counter-processor used at Lewis Research Center generates the particle interarrival times, as well as the time-of-flight of the particle through the probe volume. The signal preprocessor allows computer control of the acquisition of these data.Through the preprocessor, the computer also can control the hand shaking signals for the interface between itself and the counter-processor. Finally, the signal preprocessor splits the pedestal from the signal before filtering, and monitors the photo-multiplier dc current, sends a signal proportional to this current to the computer through an analog to digital converter, and provides an alarm if the current exceeds a predefined maximum. Complete drawings and explanations are provided in the text as well as a sample interface program for use with the data acquisition software.

Locating arbitrarily time-dependent sound sources in three dimensional space in real time.

PubMed

Wu, Sean F; Zhu, Na

2010-08-01

This paper presents a method for locating arbitrarily time-dependent acoustic sources in a free field in real time by using only four microphones. This method is capable of handling a wide variety of acoustic signals, including broadband, narrowband, impulsive, and continuous sound over the entire audible frequency range, produced by multiple sources in three dimensional (3D) space. Locations of acoustic sources are indicated by the Cartesian coordinates. The underlying principle of this method is a hybrid approach that consists of modeling of acoustic radiation from a point source in a free field, triangulation, and de-noising to enhance the signal to noise ratio (SNR). Numerical simulations are conducted to study the impacts of SNR, microphone spacing, source distance and frequency on spatial resolution and accuracy of source localizations. Based on these results, a simple device that consists of four microphones mounted on three mutually orthogonal axes at an optimal distance, a four-channel signal conditioner, and a camera is fabricated. Experiments are conducted in different environments to assess its effectiveness in locating sources that produce arbitrarily time-dependent acoustic signals, regardless whether a sound source is stationary or moves in space, even toward behind measurement microphones. Practical limitations on this method are discussed.

Feasibility of deep-inspiration breath-hold PET/CT with short-time acquisition: detectability for pulmonary lesions compared with respiratory-gated PET/CT.

PubMed

Yamashita, Shozo; Yokoyama, Kunihiko; Onoguchi, Masahisa; Yamamoto, Haruki; Hiko, Shigeaki; Horita, Akihiro; Nakajima, Kenichi

2014-01-01

Deep-inspiration breath-hold (DIBH) PET/CT with short-time acquisition and respiratory-gated (RG) PET/CT are performed for pulmonary lesions to reduce the respiratory motion artifacts, and to obtain more accurate standardized uptake value (SUV). DIBH PET/CT demonstrates significant advantages in terms of rapid examination, good quality of CT images and low radiation exposure. On the other hand, the image quality of DIBH PET is generally inferior to that of RG PET because of short-time acquisition resulting in poor signal-to-noise ratio. In this study, RG PET has been regarded as a gold standard, and its detectability between DIBH and RG PET studies was compared using each of the most optimal reconstruction parameters. In the phantom study, the most optimal reconstruction parameters for DIBH and RG PET were determined. In the clinical study, 19 cases were examined using each of the most optimal reconstruction parameters. In the phantom study, the most optimal reconstruction parameters for DIBH and RG PET were different. Reconstruction parameters of DIBH PET could be obtained by reducing the number of subsets for those of RG PET in the state of fixing the number of iterations. In the clinical study, high correlation in the maximum SUV was observed between DIBH and RG PET studies. The clinical result was consistent with that of the phantom study surrounded by air since most of the lesions were located in the low pulmonary radioactivity. DIBH PET/CT may be the most practical method which can be the first choice to reduce respiratory motion artifacts if the detectability of DIBH PET is equivalent with that of RG PET. Although DIBH PET may have limitations in suboptimal signal-to-noise ratio, most of the lesions surrounded by low background radioactivity could provide nearly equivalent image quality between DIBH and RG PET studies when each of the most optimal reconstruction parameters was used.

Optimization of lens layout for THz signal free-space delivery

NASA Astrophysics Data System (ADS)

Yu, Jimmy; Zhou, Wen

2018-03-01

We investigate how to extend the air-space distance for Terahertz (THz) signal by using optimized lens layout. After a delivery over 129.6 cm air-space we realize the BER of 10 Gb/s QPSK signal at 450 GHz smaller than 1 ×10-4 with this optimized lens layout. If only two lenses are employed, the BER is higher than forward error correction (FEC) threshold at the input power of 15 dBm into the photodiode.

Concrete thawing studied by single-point ramped imaging.

PubMed

Prado, P J; Balcom, B J; Beyea, S D; Armstrong, R L; Bremner, T W

1997-12-01

A series of two-dimensional images of proton distribution in a hardened concrete sample has been obtained during the thawing process (from -50 degrees C up to 11 degrees C). The SPRITE sequence is optimal for this study given the characteristic short relaxation times of water in this porous media (T2* < 200 micros and T1 < 3.6 ms). The relaxation parameters of the sample were determined in order to optimize the time efficiency of the sequence, permitting a 4-scan 64 x 64 acquisition in under 3 min. The image acquisition is fast on the time scale of the temperature evolution of the specimen. The frozen water distribution is quantified through a position based study of the image contrast. A multiple point acquisition method is presented and the signal sensitivity improvement is discussed.

A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection

NASA Astrophysics Data System (ADS)

Bechet, P.; Mitran, R.; Munteanu, M.

2013-08-01

Non-contact methods for the assessment of vital signs are of great interest for specialists due to the benefits obtained in both medical and special applications, such as those for surveillance, monitoring, and search and rescue. This paper investigates the possibility of implementing a digital processing algorithm based on the MUSIC (Multiple Signal Classification) parametric spectral estimation in order to reduce the observation time needed to accurately measure the heart rate. It demonstrates that, by proper dimensioning the signal subspace, the MUSIC algorithm can be optimized in order to accurately assess the heart rate during an 8-28 s time interval. The validation of the processing algorithm performance was achieved by minimizing the mean error of the heart rate after performing simultaneous comparative measurements on several subjects. In order to calculate the error the reference value of heart rate was measured using a classic measurement system through direct contact.

Flexible Conductive Composite Integrated with Personal Earphone for Wireless, Real-Time Monitoring of Electrophysiological Signs.

PubMed

Lee, Joong Hoon; Hwang, Ji-Young; Zhu, Jia; Hwang, Ha Ryeon; Lee, Seung Min; Cheng, Huanyu; Lee, Sang-Hoon; Hwang, Suk-Won

2018-06-14

We introduce optimized elastomeric conductive electrodes using a mixture of silver nanowires (AgNWs) with carbon nanotubes/polydimethylsiloxane (CNTs/PDMS), to build a portable earphone type of wearable system that is designed to enable recording electrophysiological activities as well as listening to music at the same time. A custom-built, plastic frame integrated with soft, deformable fabric-based memory foam of earmuffs facilitates essential electronic components, such as conductive elastomers, metal strips, signal transducers and a speaker. Such platform incorporates with accessory cables to attain wireless, real-time monitoring of electrical potentials whose information can be displayed on a cell phone during outdoor activities and music appreciation. Careful evaluations on experimental results reveal that the performance of fabricated dry electrodes are comparable to that of commercial wet electrodes, and position-dependent signal behaviors provide a route toward accomplishing maximized signal quality. This research offers a facile approach for a wearable healthcare monitor via integration of soft electronic constituents with personal belongings.

The Researches on Damage Detection Method for Truss Structures

NASA Astrophysics Data System (ADS)

Wang, Meng Hong; Cao, Xiao Nan

2018-06-01

This paper presents an effective method to detect damage in truss structures. Numerical simulation and experimental analysis were carried out on a damaged truss structure under instantaneous excitation. The ideal excitation point and appropriate hammering method were determined to extract time domain signals under two working conditions. The frequency response function and principal component analysis were used for data processing, and the angle between the frequency response function vectors was selected as a damage index to ascertain the location of a damaged bar in the truss structure. In the numerical simulation, the time domain signal of all nodes was extracted to determine the location of the damaged bar. In the experimental analysis, the time domain signal of a portion of the nodes was extracted on the basis of an optimal sensor placement method based on the node strain energy coefficient. The results of the numerical simulation and experimental analysis showed that the damage detection method based on the frequency response function and principal component analysis could locate the damaged bar accurately.

Contrast research of CDMA and GSM network optimization

NASA Astrophysics Data System (ADS)

Wu, Yanwen; Liu, Zehong; Zhou, Guangyue

2004-03-01

With the development of mobile telecommunication network, users of CDMA advanced their request of network service quality. While the operators also change their network management object from signal coverage to performance improvement. In that case, reasonably layout & optimization of mobile telecommunication network, reasonably configuration of network resource, improvement of the service quality, and increase the enterprise's core competition ability, all those have been concerned by the operator companies. This paper firstly looked into the flow of CDMA network optimization. Then it dissertated to some keystones in the CDMA network optimization, like PN code assignment, calculation of soft handover, etc. As GSM is also the similar cellular mobile telecommunication system like CDMA, so this paper also made a contrast research of CDMA and GSM network optimization in details, including the similarity and the different. In conclusion, network optimization is a long time job; it will run through the whole process of network construct. By the adjustment of network hardware (like BTS equipments, RF systems, etc.) and network software (like parameter optimized, configuration optimized, capacity optimized, etc.), network optimization work can improve the performance and service quality of the network.

Liver imaging at 3.0 T: diffusion-induced black-blood echo-planar imaging with large anatomic volumetric coverage as an alternative for specific absorption rate-intensive echo-train spin-echo sequences: feasibility study.

PubMed

van den Bos, Indra C; Hussain, Shahid M; Krestin, Gabriel P; Wielopolski, Piotr A

2008-07-01

Institutional Review Board approval and signed informed consent were obtained by all participants for an ongoing sequence optimization project at 3.0 T. The purpose of this study was to evaluate breath-hold diffusion-induced black-blood echo-planar imaging (BBEPI) as a potential alternative for specific absorption rate (SAR)-intensive spin-echo sequences, in particular, the fast spin-echo (FSE) sequences, at 3.0 T. Fourteen healthy volunteers (seven men, seven women; mean age +/- standard deviation, 32.7 years +/- 6.8) were imaged for this purpose. Liver coverage (20 cm, z-axis) was always performed in one 25-second breath hold. Imaging parameters were varied interactively with regard to echo time, diffusion b value, and voxel size. Images were evaluated and compared with fat-suppressed T2-weighted FSE images for image quality, liver delineation, geometric distortions, fat suppression, suppression of the blood signal, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR). An optimized short- (25 msec) and long-echo (80 msec) BBEPI provided full anatomic, single breath-hold liver coverage (100 and 50 sections, respectively), with resulting voxel sizes of 3.3 x 2.7 x 2.0 mm and 3.3 x 2.7 x 4.0 mm, respectively. Repetition time was 6300 msec, matrix size was 160 x 192, and an acceleration factor of 2.00 was used. b Values of more than 20 sec/mm(2) showed better suppression of the blood signal but b values of 10 sec/mm(2) provided improved volume coverage and signal consistency. Compared with fat-suppressed T2-weighted FSE, the optimized BBEPI sequence provided (a) comparable image quality and liver delineation, (b) acceptable geometric distortions, (c) improved suppression of fat and blood signals, and (d) high CNR and SNR. BBEPI is feasible for fast, low-SAR, thin-section morphologic imaging of the entire liver in a single breath hold at 3.0 T. (c) RSNA, 2008.

Bypassing the Limits of Ll Regularization: Convex Sparse Signal Processing Using Non-Convex Regularization

NASA Astrophysics Data System (ADS)

Parekh, Ankit

Sparsity has become the basis of some important signal processing methods over the last ten years. Many signal processing problems (e.g., denoising, deconvolution, non-linear component analysis) can be expressed as inverse problems. Sparsity is invoked through the formulation of an inverse problem with suitably designed regularization terms. The regularization terms alone encode sparsity into the problem formulation. Often, the ℓ1 norm is used to induce sparsity, so much so that ℓ1 regularization is considered to be `modern least-squares'. The use of ℓ1 norm, as a sparsity-inducing regularizer, leads to a convex optimization problem, which has several benefits: the absence of extraneous local minima, well developed theory of globally convergent algorithms, even for large-scale problems. Convex regularization via the ℓ1 norm, however, tends to under-estimate the non-zero values of sparse signals. In order to estimate the non-zero values more accurately, non-convex regularization is often favored over convex regularization. However, non-convex regularization generally leads to non-convex optimization, which suffers from numerous issues: convergence may be guaranteed to only a stationary point, problem specific parameters may be difficult to set, and the solution is sensitive to the initialization of the algorithm. The first part of this thesis is aimed toward combining the benefits of non-convex regularization and convex optimization to estimate sparse signals more effectively. To this end, we propose to use parameterized non-convex regularizers with designated non-convexity and provide a range for the non-convex parameter so as to ensure that the objective function is strictly convex. By ensuring convexity of the objective function (sum of data-fidelity and non-convex regularizer), we can make use of a wide variety of convex optimization algorithms to obtain the unique global minimum reliably. The second part of this thesis proposes a non-linear signal decomposition technique for an important biomedical signal processing problem: the detection of sleep spindles and K-complexes in human sleep electroencephalography (EEG). We propose a non-linear model for the EEG consisting of three components: (1) a transient (sparse piecewise constant) component, (2) a low-frequency component, and (3) an oscillatory component. The oscillatory component admits a sparse time-frequency representation. Using a convex objective function, we propose a fast non-linear optimization algorithm to estimate the three components in the proposed signal model. The low-frequency and oscillatory components are then used to estimate the K-complexes and sleep spindles respectively. The proposed detection method is shown to outperform several state-of-the-art automated sleep spindles detection methods.

An algorithm for control system design via parameter optimization. M.S. Thesis

NASA Technical Reports Server (NTRS)

Sinha, P. K.

1972-01-01

An algorithm for design via parameter optimization has been developed for linear-time-invariant control systems based on the model reference adaptive control concept. A cost functional is defined to evaluate the system response relative to nominal, which involves in general the error between the system and nominal response, its derivatives and the control signals. A program for the practical implementation of this algorithm has been developed, with the computational scheme for the evaluation of the performance index based on Lyapunov's theorem for stability of linear invariant systems.

FIBER OPTICS. ACOUSTOOPTICS: Compression of random pulses in fiber waveguides

NASA Astrophysics Data System (ADS)

Aleshkevich, Viktor A.; Kozhoridze, G. D.

1990-07-01

An investigation is made of the compression of randomly modulated signal + noise pulses during their propagation in a fiber waveguide. An allowance is made for a cubic nonlinearity and quadratic dispersion. The relationships governing the kinetics of transformation of the time envelope, and those which determine the duration and intensity of a random pulse are derived. The expressions for the optimal length of a fiber waveguide and for the maximum degree of compression are compared with the available data for regular pulses and the recommendations on selection of the optimal parameters are given.

Optimization of contrast-to-tissue ratio by adaptation of transmitted ternary signal in ultrasound pulse inversion imaging.

PubMed

Ménigot, Sébastien; Girault, Jean-Marc

2013-01-01

Ultrasound contrast imaging has provided more accurate medical diagnoses thanks to the development of innovating modalities like the pulse inversion imaging. However, this latter modality that improves the contrast-to-tissue ratio (CTR) is not optimal, since the frequency is manually chosen jointly with the probe. However, an optimal choice of this command is possible, but it requires precise information about the transducer and the medium which can be experimentally difficult to obtain, even inaccessible. It turns out that the optimization can become more complex by taking into account the kind of generators, since the generators of electrical signals in a conventional ultrasound scanner can be unipolar, bipolar, or tripolar. Our aim was to seek the ternary command which maximized the CTR. By combining a genetic algorithm and a closed loop, the system automatically proposed the optimal ternary command. In simulation, the gain compared with the usual ternary signal could reach about 3.9 dB. Another interesting finding was that, in contrast to what is generally accepted, the optimal command was not a fixed-frequency signal but had harmonic components.

Adaptive sparsest narrow-band decomposition method and its applications to rolling element bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Cheng, Junsheng; Peng, Yanfeng; Yang, Yu; Wu, Zhantao

2017-02-01

Enlightened by ASTFA method, adaptive sparsest narrow-band decomposition (ASNBD) method is proposed in this paper. In ASNBD method, an optimized filter must be established at first. The parameters of the filter are determined by solving a nonlinear optimization problem. A regulated differential operator is used as the objective function so that each component is constrained to be a local narrow-band signal. Afterwards, the signal is filtered by the optimized filter to generate an intrinsic narrow-band component (INBC). ASNBD is proposed aiming at solving the problems existed in ASTFA. Gauss-Newton type method, which is applied to solve the optimization problem in ASTFA, is irreplaceable and very sensitive to initial values. However, more appropriate optimization method such as genetic algorithm (GA) can be utilized to solve the optimization problem in ASNBD. Meanwhile, compared with ASTFA, the decomposition results generated by ASNBD have better physical meaning by constraining the components to be local narrow-band signals. Comparisons are made between ASNBD, ASTFA and EMD by analyzing simulation and experimental signals. The results indicate that ASNBD method is superior to the other two methods in generating more accurate components from noise signal, restraining the boundary effect, possessing better orthogonality and diagnosing rolling element bearing fault.

Detection and Quantification of Viable and Nonviable Trypanosoma cruzi Parasites by a Propidium Monoazide Real-Time Polymerase Chain Reaction Assay

PubMed Central

Cancino-Faure, Beatriz; Fisa, Roser; Alcover, M. Magdalena; Jimenez-Marco, Teresa; Riera, Cristina

2016-01-01

Molecular techniques based on real-time polymerase chain reaction (qPCR) allow the detection and quantification of DNA but are unable to distinguish between signals from dead or live cells. Because of the lack of simple techniques to differentiate between viable and nonviable cells, the aim of this study was to optimize and evaluate a straightforward test based on propidium monoazide (PMA) dye action combined with a qPCR assay (PMA-qPCR) for the selective quantification of viable/nonviable epimastigotes of Trypanosoma cruzi. PMA has the ability to penetrate the plasma membrane of dead cells and covalently cross-link to the DNA during exposure to bright visible light, thereby inhibiting PCR amplification. Different concentrations of PMA (50–200 μM) and epimastigotes of the Maracay strain of T. cruzi (1 × 105–10 parasites/mL) were assayed; viable and nonviable parasites were tested and quantified by qPCR with a TaqMan probe specific for T. cruzi. In the PMA-qPCR assay optimized at 100 μM PMA, a significant qPCR signal reduction was observed in the nonviable versus viable epimastigotes treated with PMA, with a mean signal reduction of 2.5 logarithm units and a percentage of signal reduction > 98%, in all concentrations of parasites assayed. This signal reduction was also observed when PMA-qPCR was applied to a mixture of live/dead parasites, which allowed the detection of live cells, except when the concentration of live parasites was low (10 parasites/mL). The PMA-qPCR developed allows differentiation between viable and nonviable epimastigotes of T. cruzi and could thus be a potential method of parasite viability assessment and quantification. PMID:27139452

Model Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Primary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib

PubMed Central

Sobotta, Svantje; Raue, Andreas; Huang, Xiaoyun; Vanlier, Joep; Jünger, Anja; Bohl, Sebastian; Albrecht, Ute; Hahnel, Maximilian J.; Wolf, Stephanie; Mueller, Nikola S.; D'Alessandro, Lorenza A.; Mueller-Bohl, Stephanie; Boehm, Martin E.; Lucarelli, Philippe; Bonefas, Sandra; Damm, Georg; Seehofer, Daniel; Lehmann, Wolf D.; Rose-John, Stefan; van der Hoeven, Frank; Gretz, Norbert; Theis, Fabian J.; Ehlting, Christian; Bode, Johannes G.; Timmer, Jens; Schilling, Marcel; Klingmüller, Ursula

2017-01-01

IL-6 is a central mediator of the immediate induction of hepatic acute phase proteins (APP) in the liver during infection and after injury, but increased IL-6 activity has been associated with multiple pathological conditions. In hepatocytes, IL-6 activates JAK1-STAT3 signaling that induces the negative feedback regulator SOCS3 and expression of APPs. While different inhibitors of IL-6-induced JAK1-STAT3-signaling have been developed, understanding their precise impact on signaling dynamics requires a systems biology approach. Here we present a mathematical model of IL-6-induced JAK1-STAT3 signaling that quantitatively links physiological IL-6 concentrations to the dynamics of IL-6-induced signal transduction and expression of target genes in hepatocytes. The mathematical model consists of coupled ordinary differential equations (ODE) and the model parameters were estimated by a maximum likelihood approach, whereas identifiability of the dynamic model parameters was ensured by the Profile Likelihood. Using model simulations coupled with experimental validation we could optimize the long-term impact of the JAK-inhibitor Ruxolitinib, a therapeutic compound that is quickly metabolized. Model-predicted doses and timing of treatments helps to improve the reduction of inflammatory APP gene expression in primary mouse hepatocytes close to levels observed during regenerative conditions. The concept of improved efficacy of the inhibitor through multiple treatments at optimized time intervals was confirmed in primary human hepatocytes. Thus, combining quantitative data generation with mathematical modeling suggests that repetitive treatment with Ruxolitinib is required to effectively target excessive inflammatory responses without exceeding doses recommended by the clinical guidelines. PMID:29062282

Model Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Primary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib.

PubMed

Sobotta, Svantje; Raue, Andreas; Huang, Xiaoyun; Vanlier, Joep; Jünger, Anja; Bohl, Sebastian; Albrecht, Ute; Hahnel, Maximilian J; Wolf, Stephanie; Mueller, Nikola S; D'Alessandro, Lorenza A; Mueller-Bohl, Stephanie; Boehm, Martin E; Lucarelli, Philippe; Bonefas, Sandra; Damm, Georg; Seehofer, Daniel; Lehmann, Wolf D; Rose-John, Stefan; van der Hoeven, Frank; Gretz, Norbert; Theis, Fabian J; Ehlting, Christian; Bode, Johannes G; Timmer, Jens; Schilling, Marcel; Klingmüller, Ursula

2017-01-01

IL-6 is a central mediator of the immediate induction of hepatic acute phase proteins (APP) in the liver during infection and after injury, but increased IL-6 activity has been associated with multiple pathological conditions. In hepatocytes, IL-6 activates JAK1-STAT3 signaling that induces the negative feedback regulator SOCS3 and expression of APPs. While different inhibitors of IL-6-induced JAK1-STAT3-signaling have been developed, understanding their precise impact on signaling dynamics requires a systems biology approach. Here we present a mathematical model of IL-6-induced JAK1-STAT3 signaling that quantitatively links physiological IL-6 concentrations to the dynamics of IL-6-induced signal transduction and expression of target genes in hepatocytes. The mathematical model consists of coupled ordinary differential equations (ODE) and the model parameters were estimated by a maximum likelihood approach, whereas identifiability of the dynamic model parameters was ensured by the Profile Likelihood. Using model simulations coupled with experimental validation we could optimize the long-term impact of the JAK-inhibitor Ruxolitinib, a therapeutic compound that is quickly metabolized. Model-predicted doses and timing of treatments helps to improve the reduction of inflammatory APP gene expression in primary mouse hepatocytes close to levels observed during regenerative conditions. The concept of improved efficacy of the inhibitor through multiple treatments at optimized time intervals was confirmed in primary human hepatocytes. Thus, combining quantitative data generation with mathematical modeling suggests that repetitive treatment with Ruxolitinib is required to effectively target excessive inflammatory responses without exceeding doses recommended by the clinical guidelines.

Coherent phase control of internal conversion in pyrazine

NASA Astrophysics Data System (ADS)

Gordon, Robert J.; Hu, Zhan; Seideman, Tamar; Singha, Sima; Sukharev, Maxim; Zhao, Youbo

2015-04-01

Shaped ultrafast laser pulses were used to study and control the ionization dynamics of electronically excited pyrazine in a pump and probe experiment. For pump pulses created without feedback from the product signal, the ion growth curve (the parent ion signal as a function of pump/probe delay) was described quantitatively by the classical rate equations for internal conversion of the S2 and S1 states. Very different, non-classical behavior was observed when a genetic algorithm (GA) employing phase-only modulation was used to minimize the ion signal at some pre-determined target time, T. Two qualitatively different control mechanisms were identified for early (T < 1.5 ps) and late (T > 1.5 ps) target times. In the former case, the ion signal was largely suppressed for t < T, while for t ≫ T, the ion signal produced by the GA-optimized pulse and a transform limited (TL) pulse coalesced. In contrast, for T > 1.5 ps, the ion growth curve followed the classical rate equations for t < T, while for t ≫ T, the quantum yield for the GA-optimized pulse was much smaller than for a TL pulse. We interpret the first type of behavior as an indication that the wave packet produced by the pump laser is localized in a region of the S2 potential energy surface where the vertical ionization energy exceeds the probe photon energy, whereas the second type of behavior may be described by a reduced absorption cross section for S0 → S2 followed by incoherent decay of the excited molecules. Amplitude modulation observed in the spectrum of the shaped pulse may have contributed to the control mechanism, although this possibility is mitigated by the very small focal volume of the probe laser.

An orbital angular momentum radio communication system optimized by intensity controlled masks effectively: Theoretical design and experimental verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Xinlu; Applied Optics Beijing Area Major Laboratory, Department of Physics, Beijing Normal University, Beijing 100875; Huang, Shanguo, E-mail: shghuang@bupt.edu.cn

A system of generating and receiving orbital angular momentum (OAM) radio beams, which are collectively formed by two circular array antennas (CAAs) and effectively optimized by two intensity controlled masks, is proposed and experimentally investigated. The scheme is effective in blocking of the unwanted OAM modes and enhancing the power of received radio signals, which results in the capacity gain of system and extended transmission distance of the OAM radio beams. The operation principle of the intensity controlled masks, which can be regarded as both collimator and filter, is feasible and simple to realize. Numerical simulations of intensity and phasemore » distributions at each key cross-sectional plane of the radio beams demonstrate the collimated results. The experimental results match well with the theoretical analysis and the receive distance of the OAM radio beam at radio frequency (RF) 20 GHz is extended up to 200 times of the wavelength of the RF signals, the measured distance is 5 times of the original measured distance. The presented proof-of-concept experiment demonstrates the feasibility of the system.« less

Optimal variable flip angle schemes for dynamic acquisition of exchanging hyperpolarized substrates

NASA Astrophysics Data System (ADS)

Xing, Yan; Reed, Galen D.; Pauly, John M.; Kerr, Adam B.; Larson, Peder E. Z.

2013-09-01

In metabolic MRI with hyperpolarized contrast agents, the signal levels vary over time due to T1 decay, T2 decay following RF excitations, and metabolic conversion. Efficient usage of the nonrenewable hyperpolarized magnetization requires specialized RF pulse schemes. In this work, we introduce two novel variable flip angle schemes for dynamic hyperpolarized MRI in which the flip angle is varied between excitations and between metabolites. These were optimized to distribute the magnetization relatively evenly throughout the acquisition by accounting for T1 decay, prior RF excitations, and metabolic conversion. Simulation results are presented to confirm the flip angle designs and evaluate the variability of signal dynamics across typical ranges of T1 and metabolic conversion. They were implemented using multiband spectral-spatial RF pulses to independently modulate the flip angle at various chemical shift frequencies. With these schemes we observed increased SNR of [1-13C]lactate generated from [1-13C]pyruvate, particularly at later time points. This will allow for improved characterization of tissue perfusion and metabolic profiles in dynamic hyperpolarized MRI.

Chip Design Process Optimization Based on Design Quality Assessment

NASA Astrophysics Data System (ADS)

Häusler, Stefan; Blaschke, Jana; Sebeke, Christian; Rosenstiel, Wolfgang; Hahn, Axel

2010-06-01

Nowadays, the managing of product development projects is increasingly challenging. Especially the IC design of ASICs with both analog and digital components (mixed-signal design) is becoming more and more complex, while the time-to-market window narrows at the same time. Still, high quality standards must be fulfilled. Projects and their status are becoming less transparent due to this complexity. This makes the planning and execution of projects rather difficult. Therefore, there is a need for efficient project control. A main challenge is the objective evaluation of the current development status. Are all requirements successfully verified? Are all intermediate goals achieved? Companies often develop special solutions that are not reusable in other projects. This makes the quality measurement process itself less efficient and produces too much overhead. The method proposed in this paper is a contribution to solve these issues. It is applied at a German design house for analog mixed-signal IC design. This paper presents the results of a case study and introduces an optimized project scheduling on the basis of quality assessment results.

Evolutionary Algorithm Based Feature Optimization for Multi-Channel EEG Classification.

PubMed

Wang, Yubo; Veluvolu, Kalyana C

2017-01-01

The most BCI systems that rely on EEG signals employ Fourier based methods for time-frequency decomposition for feature extraction. The band-limited multiple Fourier linear combiner is well-suited for such band-limited signals due to its real-time applicability. Despite the improved performance of these techniques in two channel settings, its application in multiple-channel EEG is not straightforward and challenging. As more channels are available, a spatial filter will be required to eliminate the noise and preserve the required useful information. Moreover, multiple-channel EEG also adds the high dimensionality to the frequency feature space. Feature selection will be required to stabilize the performance of the classifier. In this paper, we develop a new method based on Evolutionary Algorithm (EA) to solve these two problems simultaneously. The real-valued EA encodes both the spatial filter estimates and the feature selection into its solution and optimizes it with respect to the classification error. Three Fourier based designs are tested in this paper. Our results show that the combination of Fourier based method with covariance matrix adaptation evolution strategy (CMA-ES) has the best overall performance.

AC signal characterization for optimization of a CMOS single-electron pump

NASA Astrophysics Data System (ADS)

Murray, Roy; Perron, Justin K.; Stewart, M. D., Jr.; Zimmerman, Neil M.

2018-02-01

Pumping single electrons at a set rate is being widely pursued as an electrical current standard. Semiconductor charge pumps have been pursued in a variety of modes, including single gate ratchet, a variety of 2-gate ratchet pumps, and 2-gate turnstiles. Whether pumping with one or two AC signals, lower error rates can result from better knowledge of the properties of the AC signal at the device. In this work, we operated a CMOS single-electron pump with a 2-gate ratchet style measurement and used the results to characterize and optimize our two AC signals. Fitting this data at various frequencies revealed both a difference in signal path length and attenuation between our two AC lines. Using this data, we corrected for the difference in signal path length and attenuation by applying an offset in both the phase and the amplitude at the signal generator. Operating the device as a turnstile while using the optimized parameters determined from the 2-gate ratchet measurement led to much flatter, more robust charge pumping plateaus. This method was useful in tuning our device up for optimal charge pumping, and may prove useful to the semiconductor quantum dot community to determine signal attenuation and path differences at the device.

A novel approach for automatic visualization and activation detection of evoked potentials induced by epidural spinal cord stimulation in individuals with spinal cord injury.

PubMed

Mesbah, Samineh; Angeli, Claudia A; Keynton, Robert S; El-Baz, Ayman; Harkema, Susan J

2017-01-01

Voluntary movements and the standing of spinal cord injured patients have been facilitated using lumbosacral spinal cord epidural stimulation (scES). Identifying the appropriate stimulation parameters (intensity, frequency and anode/cathode assignment) is an arduous task and requires extensive mapping of the spinal cord using evoked potentials. Effective visualization and detection of muscle evoked potentials induced by scES from the recorded electromyography (EMG) signals is critical to identify the optimal configurations and the effects of specific scES parameters on muscle activation. The purpose of this work was to develop a novel approach to automatically detect the occurrence of evoked potentials, quantify the attributes of the signal and visualize the effects across a high number of scES parameters. This new method is designed to automate the current process for performing this task, which has been accomplished manually by data analysts through observation of raw EMG signals, a process that is laborious and time-consuming as well as prone to human errors. The proposed method provides a fast and accurate five-step algorithms framework for activation detection and visualization of the results including: conversion of the EMG signal into its 2-D representation by overlaying the located signal building blocks; de-noising the 2-D image by applying the Generalized Gaussian Markov Random Field technique; detection of the occurrence of evoked potentials using a statistically optimal decision method through the comparison of the probability density functions of each segment to the background noise utilizing log-likelihood ratio; feature extraction of detected motor units such as peak-to-peak amplitude, latency, integrated EMG and Min-max time intervals; and finally visualization of the outputs as Colormap images. In comparing the automatic method vs. manual detection on 700 EMG signals from five individuals, the new approach decreased the processing time from several hours to less than 15 seconds for each set of data, and demonstrated an average accuracy of 98.28% based on the combined false positive and false negative error rates. The sensitivity of this method to the signal-to-noise ratio (SNR) was tested using simulated EMG signals and compared to two existing methods, where the novel technique showed much lower sensitivity to the SNR.

A novel approach for automatic visualization and activation detection of evoked potentials induced by epidural spinal cord stimulation in individuals with spinal cord injury

PubMed Central

Mesbah, Samineh; Angeli, Claudia A.; Keynton, Robert S.; Harkema, Susan J.

2017-01-01

Voluntary movements and the standing of spinal cord injured patients have been facilitated using lumbosacral spinal cord epidural stimulation (scES). Identifying the appropriate stimulation parameters (intensity, frequency and anode/cathode assignment) is an arduous task and requires extensive mapping of the spinal cord using evoked potentials. Effective visualization and detection of muscle evoked potentials induced by scES from the recorded electromyography (EMG) signals is critical to identify the optimal configurations and the effects of specific scES parameters on muscle activation. The purpose of this work was to develop a novel approach to automatically detect the occurrence of evoked potentials, quantify the attributes of the signal and visualize the effects across a high number of scES parameters. This new method is designed to automate the current process for performing this task, which has been accomplished manually by data analysts through observation of raw EMG signals, a process that is laborious and time-consuming as well as prone to human errors. The proposed method provides a fast and accurate five-step algorithms framework for activation detection and visualization of the results including: conversion of the EMG signal into its 2-D representation by overlaying the located signal building blocks; de-noising the 2-D image by applying the Generalized Gaussian Markov Random Field technique; detection of the occurrence of evoked potentials using a statistically optimal decision method through the comparison of the probability density functions of each segment to the background noise utilizing log-likelihood ratio; feature extraction of detected motor units such as peak-to-peak amplitude, latency, integrated EMG and Min-max time intervals; and finally visualization of the outputs as Colormap images. In comparing the automatic method vs. manual detection on 700 EMG signals from five individuals, the new approach decreased the processing time from several hours to less than 15 seconds for each set of data, and demonstrated an average accuracy of 98.28% based on the combined false positive and false negative error rates. The sensitivity of this method to the signal-to-noise ratio (SNR) was tested using simulated EMG signals and compared to two existing methods, where the novel technique showed much lower sensitivity to the SNR. PMID:29020054

An optimal general type-2 fuzzy controller for Urban Traffic Network.

PubMed

Khooban, Mohammad Hassan; Vafamand, Navid; Liaghat, Alireza; Dragicevic, Tomislav

2017-01-01

Urban traffic network model is illustrated by state-charts and object-diagram. However, they have limitations to show the behavioral perspective of the Traffic Information flow. Consequently, a state space model is used to calculate the half-value waiting time of vehicles. In this study, a combination of the general type-2 fuzzy logic sets and the Modified Backtracking Search Algorithm (MBSA) techniques are used in order to control the traffic signal scheduling and phase succession so as to guarantee a smooth flow of traffic with the least wait times and average queue length. The parameters of input and output membership functions are optimized simultaneously by the novel heuristic algorithm MBSA. A comparison is made between the achieved results with those of optimal and conventional type-1 fuzzy logic controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Error field optimization in DIII-D using extremum seeking control

NASA Astrophysics Data System (ADS)

Lanctot, M. J.; Olofsson, K. E. J.; Capella, M.; Humphreys, D. A.; Eidietis, N.; Hanson, J. M.; Paz-Soldan, C.; Strait, E. J.; Walker, M. L.

2016-07-01

DIII-D experiments have demonstrated a new real-time approach to tokamak error field control based on maximizing the toroidal angular momentum. This approach uses extremum seeking control theory to optimize the error field in real time without inducing instabilities. Slowly-rotating n  =  1 fields (the dither), generated by external coils, are used to perturb the angular momentum, monitored in real-time using a charge-exchange spectroscopy diagnostic. Simple signal processing of the rotation measurements extracts information about the rotation gradient with respect to the control coil currents. This information is used to converge the control coil currents to a point that maximizes the toroidal angular momentum. The technique is well-suited for multi-coil, multi-harmonic error field optimizations in disruption sensitive devices as it does not require triggering locked tearing modes or plasma current disruptions. Control simulations highlight the importance of the initial search direction on the rate of the convergence, and identify future algorithm upgrades that may allow more rapid convergence that projects to convergence times in ITER on the order of tens of seconds.

Test apparatus to monitor time-domain signals from semiconductor-detector pixel arrays

NASA Astrophysics Data System (ADS)

Haston, Kyle; Barber, H. Bradford; Furenlid, Lars R.; Salçin, Esen; Bora, Vaibhav

2011-10-01

Pixellated semiconductor detectors, such as CdZnTe, CdTe, or TlBr, are used for gamma-ray imaging in medicine and astronomy. Data analysis for these detectors typically estimates the position (x, y, z) and energy (E) of each interacting gamma ray from a set of detector signals {Si} corresponding to completed charge transport on the hit pixel and any of its neighbors that take part in charge sharing, plus the cathode. However, it is clear from an analysis of signal induction, that there are transient signal on all pixel electrodes during the charge transport and, when there is charge trapping, small negative residual signals on all electrodes. If we wish to optimally obtain the event parameters, we should take all these signals into account. We wish to estimate x,y,z and E from the set of all electrode signals, {Si(t)}, including time dependence, using maximum-likelihood techniques[1]. To do this, we need to determine the probability of the electrode signals, given the event parameters {x, y, z, E}, i.e. Pr( {Si(t)} | {x, y, z, E} ). Thus we need to map the detector response of all pixels, {Si(t)}, for a large number of events with known x,y,z and E.In this paper we demonstrate the existence of the transient signals and residual signals and determine their magnitudes. They are typically 50-100 times smaller than the hit-pixel signals. We then describe development of an apparatus to measure the response of a 16-pixel semiconductor detector and show some preliminary results. We also discuss techniques for measuring the event parameters for individual gamma-ray interactions, a requirement for determining Pr( {Si(t)} | {x, y, z, E}).

Novel multireceiver communication systems configurations based on optimal estimation theory

NASA Technical Reports Server (NTRS)

Kumar, Rajendra

1992-01-01

A novel multireceiver configuration for carrier arraying and/or signal arraying is presented. The proposed configuration is obtained by formulating the carrier and/or signal arraying problem as an optimal estimation problem, and it consists of two stages. The first stage optimally estimates various phase processes received at different receivers with coupled phase-locked loops wherein the individual loops acquire and track their respective receivers' phase processes but are aided by each other in an optimal manner via LF error signals. The proposed configuration results in the minimization of the the effective radio loss at the combiner output, and thus maximization of energy per bit to noise power spectral density ratio is achieved. A novel adaptive algorithm for the estimator of the signal model parameters when these are not known a priori is also presented.

Optimal visual-haptic integration with articulated tools.

PubMed

Takahashi, Chie; Watt, Simon J

2017-05-01

When we feel and see an object, the nervous system integrates visual and haptic information optimally, exploiting the redundancy in multiple signals to estimate properties more precisely than is possible from either signal alone. We examined whether optimal integration is similarly achieved when using articulated tools. Such tools (tongs, pliers, etc) are a defining characteristic of human hand function, but complicate the classical sensory 'correspondence problem' underlying multisensory integration. Optimal integration requires establishing the relationship between signals acquired by different sensors (hand and eye) and, therefore, in fundamentally unrelated units. The system must also determine when signals refer to the same property of the world-seeing and feeling the same thing-and only integrate those that do. This could be achieved by comparing the pattern of current visual and haptic input to known statistics of their normal relationship. Articulated tools disrupt this relationship, however, by altering the geometrical relationship between object properties and hand posture (the haptic signal). We examined whether different tool configurations are taken into account in visual-haptic integration. We indexed integration by measuring the precision of size estimates, and compared our results to optimal predictions from a maximum-likelihood integrator. Integration was near optimal, independent of tool configuration/hand posture, provided that visual and haptic signals referred to the same object in the world. Thus, sensory correspondence was determined correctly (trial-by-trial), taking tool configuration into account. This reveals highly flexible multisensory integration underlying tool use, consistent with the brain constructing internal models of tools' properties.

RFID Technology for Continuous Monitoring of Physiological Signals in Small Animals.

PubMed

Volk, Tobias; Gorbey, Stefan; Bhattacharyya, Mayukh; Gruenwald, Waldemar; Lemmer, Björn; Reindl, Leonhard M; Stieglitz, Thomas; Jansen, Dirk

2015-02-01

Telemetry systems enable researchers to continuously monitor physiological signals in unrestrained, freely moving small rodents. Drawbacks of common systems are limited operation time, the need to house the animals separately, and the necessity of a stable communication link. Furthermore, the costs of the typically proprietary telemetry systems reduce the acceptance. The aim of this paper is to introduce a low-cost telemetry system based on common radio frequency identification technology optimized for battery-independent operational time, good reusability, and flexibility. The presented implant is equipped with sensors to measure electrocardiogram, arterial blood pressure, and body temperature. The biological signals are transmitted as digital data streams. The device is able of monitoring several freely moving animals housed in groups with a single reader station. The modular concept of the system significantly reduces the costs to monitor multiple physiological functions and refining procedures in preclinical research.

Using hyperentanglement to enhance resolution, signal-to-noise ratio, and measurement time

NASA Astrophysics Data System (ADS)

Smith, James F.

2017-03-01

A hyperentanglement-based atmospheric imaging/detection system involving only a signal and an ancilla photon will be considered for optical and infrared frequencies. Only the signal photon will propagate in the atmosphere and its loss will be classical. The ancilla photon will remain within the sensor experiencing low loss. Closed form expressions for the wave function, normalization, density operator, reduced density operator, symmetrized logarithmic derivative, quantum Fisher information, quantum Cramer-Rao lower bound, coincidence probabilities, probability of detection, probability of false alarm, probability of error after M measurements, signal-to-noise ratio, quantum Chernoff bound, time-on-target expressions related to probability of error, and resolution will be provided. The effect of noise in every mode will be included as well as loss. The system will provide the basic design for an imaging/detection system functioning at optical or infrared frequencies that offers better than classical angular and range resolution. Optimization for enhanced resolution will be included. The signal-to-noise ratio will be increased by a factor equal to the number of modes employed during the hyperentanglement process. Likewise, the measurement time can be reduced by the same factor. The hyperentanglement generator will typically make use of entanglement in polarization, energy-time, orbital angular momentum and so on. Mathematical results will be provided describing the system's performance as a function of loss mechanisms and noise.

MAC Protocol for Ad Hoc Networks Using a Genetic Algorithm

PubMed Central

Elizarraras, Omar; Panduro, Marco; Méndez, Aldo L.

2014-01-01

The problem of obtaining the transmission rate in an ad hoc network consists in adjusting the power of each node to ensure the signal to interference ratio (SIR) and the energy required to transmit from one node to another is obtained at the same time. Therefore, an optimal transmission rate for each node in a medium access control (MAC) protocol based on CSMA-CDMA (carrier sense multiple access-code division multiple access) for ad hoc networks can be obtained using evolutionary optimization. This work proposes a genetic algorithm for the transmission rate election considering a perfect power control, and our proposition achieves improvement of 10% compared with the scheme that handles the handshaking phase to adjust the transmission rate. Furthermore, this paper proposes a genetic algorithm that solves the problem of power combining, interference, data rate, and energy ensuring the signal to interference ratio in an ad hoc network. The result of the proposed genetic algorithm has a better performance (15%) compared to the CSMA-CDMA protocol without optimizing. Therefore, we show by simulation the effectiveness of the proposed protocol in terms of the throughput. PMID:25140339

Computational photoacoustic imaging with sparsity-based optimization of the initial pressure distribution

NASA Astrophysics Data System (ADS)

Shang, Ruibo; Archibald, Richard; Gelb, Anne; Luke, Geoffrey P.

2018-02-01

In photoacoustic (PA) imaging, the optical absorption can be acquired from the initial pressure distribution (IPD). An accurate reconstruction of the IPD will be very helpful for the reconstruction of the optical absorption. However, the image quality of PA imaging in scattering media is deteriorated by the acoustic diffraction, imaging artifacts, and weak PA signals. In this paper, we propose a sparsity-based optimization approach that improves the reconstruction of the IPD in PA imaging. A linear imaging forward model was set up based on time-and-delay method with the assumption that the point spread function (PSF) is spatial invariant. Then, an optimization equation was proposed with a regularization term to denote the sparsity of the IPD in a certain domain to solve this inverse problem. As a proof of principle, the approach was applied to reconstructing point objects and blood vessel phantoms. The resolution and signal-to-noise ratio (SNR) were compared between conventional back-projection and our proposed approach. Overall these results show that computational imaging can leverage the sparsity of PA images to improve the estimation of the IPD.

Representation of DNA sequences in genetic codon context with applications in exon and intron prediction.

PubMed

Yin, Changchuan

2015-04-01

To apply digital signal processing (DSP) methods to analyze DNA sequences, the sequences first must be specially mapped into numerical sequences. Thus, effective numerical mappings of DNA sequences play key roles in the effectiveness of DSP-based methods such as exon prediction. Despite numerous mappings of symbolic DNA sequences to numerical series, the existing mapping methods do not include the genetic coding features of DNA sequences. We present a novel numerical representation of DNA sequences using genetic codon context (GCC) in which the numerical values are optimized by simulation annealing to maximize the 3-periodicity signal to noise ratio (SNR). The optimized GCC representation is then applied in exon and intron prediction by Short-Time Fourier Transform (STFT) approach. The results show the GCC method enhances the SNR values of exon sequences and thus increases the accuracy of predicting protein coding regions in genomes compared with the commonly used 4D binary representation. In addition, this study offers a novel way to reveal specific features of DNA sequences by optimizing numerical mappings of symbolic DNA sequences.

Adaptive sampling of AEM transients

NASA Astrophysics Data System (ADS)

Di Massa, Domenico; Florio, Giovanni; Viezzoli, Andrea

2016-02-01

This paper focuses on the sampling of the electromagnetic transient as acquired by airborne time-domain electromagnetic (TDEM) systems. Typically, the sampling of the electromagnetic transient is done using a fixed number of gates whose width grows logarithmically (log-gating). The log-gating has two main benefits: improving the signal to noise (S/N) ratio at late times, when the electromagnetic signal has amplitudes equal or lower than the natural background noise, and ensuring a good resolution at the early times. However, as a result of fixed time gates, the conventional log-gating does not consider any geological variations in the surveyed area, nor the possibly varying characteristics of the measured signal. We show, using synthetic models, how a different, flexible sampling scheme can increase the resolution of resistivity models. We propose a new sampling method, which adapts the gating on the base of the slope variations in the electromagnetic (EM) transient. The use of such an alternative sampling scheme aims to get more accurate inverse models by extracting the geoelectrical information from the measured data in an optimal way.

Trellis coding with Continuous Phase Modulation (CPM) for satellite-based land-mobile communications

NASA Technical Reports Server (NTRS)

1989-01-01

This volume of the final report summarizes the results of our studies on the satellite-based mobile communications project. It includes: a detailed analysis, design, and simulations of trellis coded, full/partial response CPM signals with/without interleaving over various Rician fading channels; analysis and simulation of computational cutoff rates for coherent, noncoherent, and differential detection of CPM signals; optimization of the complete transmission system; analysis and simulation of power spectrum of the CPM signals; design and development of a class of Doppler frequency shift estimators; design and development of a symbol timing recovery circuit; and breadboard implementation of the transmission system. Studies prove the suitability of the CPM system for mobile communications.

An adaptive DPCM algorithm for predicting contours in NTSC composite video signals

NASA Astrophysics Data System (ADS)

Cox, N. R.

An adaptive DPCM algorithm is proposed for encoding digitized National Television Systems Committee (NTSC) color video signals. This algorithm essentially predicts picture contours in the composite signal without resorting to component separation. The contour parameters (slope thresholds) are optimized using four 'typical' television frames that have been sampled at three times the color subcarrier frequency. Three variations of the basic predictor are simulated and compared quantitatively with three non-adaptive predictors of similar complexity. By incorporating a dual-word-length coder and buffer memory, high quality color pictures can be encoded at 4.0 bits/pel or 42.95 Mbit/s. The effect of channel error propagation is also investigated.

An improved experimental scheme for simultaneous measurement of high-resolution zero electron kinetic energy (ZEKE) photoelectron and threshold photoion (MATI) spectra

NASA Astrophysics Data System (ADS)

Michels, François; Mazzoni, Federico; Becucci, Maurizio; Müller-Dethlefs, Klaus

2017-10-01

An improved detection scheme is presented for threshold ionization spectroscopy with simultaneous recording of the Zero Electron Kinetic Energy (ZEKE) and Mass Analysed Threshold Ionisation (MATI) signals. The objective is to obtain accurate dissociation energies for larger molecular clusters by simultaneously detecting the fragment and parent ion MATI signals with identical transmission. The scheme preserves an optimal ZEKE spectral resolution together with excellent separation of the spontaneous ion and MATI signals in the time-of-flight mass spectrum. The resulting improvement in sensitivity will allow for the determination of dissociation energies in clusters with substantial mass difference between parent and daughter ions.

A novel green analytical procedure for monitoring of azoxystrobin in water samples by a flow injection chemiluminescence method with off-line ultrasonic treatment.

PubMed

Yang, Xin-an; Zhang, Wang-bing

2013-01-01

A simple and green flow injection chemiluminescence (FI-CL) method for determination of the fungicide azoxystrobin was described for the first time. CL signal was generated when azoxystrobin was injected into a mixed stream of luminol and KMnO4 . The CL signal of azoxystrobin could be greatly improved when an off-line ultrasonic treatment was adopted. Meanwhile, the signal intensity increases with the analyte concentration proportionally. Several variables, such as the ultrasonic parameters, flow rate of reagents, concentrations of sodium hydroxide solution and CL reagents (potassium permanganate, luminol) were investigated, and the optimal CL conditions were obtained. Under optimal conditions, the linear range of 1-100 ng/mL for azoxystrobin was obtained and the detection limit (3σ) was determined as 0.13 ng/mL. The relative standard deviation was 1.5% for 10 consecutive measurements of 20 ng/mL azoxystrobin. The method has been applied to the determination of azoxystrobin residues in water samples. Copyright © 2012 John Wiley & Sons, Ltd.

Utilizing T-cell Activation Signals 1, 2, and 3 for Tumor-infiltrating Lymphocytes (TIL) Expansion: The Advantage Over the Sole Use of Interleukin-2 in Cutaneous and Uveal Melanoma.

PubMed

Tavera, René J; Forget, Marie-Andrée; Kim, Young Uk; Sakellariou-Thompson, Donastas; Creasy, Caitlin A; Bhatta, Ankit; Fulbright, Orenthial J; Ramachandran, Renjith; Thorsen, Shawne T; Flores, Esteban; Wahl, Arely; Gonzalez, Audrey M; Toth, Christopher; Wardell, Seth; Mansaray, Rahmatu; Radvanyi, Laszlo G; Gombos, Dan S; Patel, Sapna P; Hwu, Patrick; Amaria, Rodabe N; Bernatchez, Chantale; Haymaker, Cara

2018-05-11

In this study, we address one of the major critiques for tumor-infiltrating lymphocyte (TIL) therapy-the time needed for proper expansion of a suitable product. We postulated that T-cell receptor activation in the first phase of expansion combined with an agonistic stimulation of CD137/4-1BB and interleukin-2 would favor preferential expansion of CD8 TIL. Indeed, this novel 3-signal approach for optimal T-cell activation resulted in faster and more consistent expansion of CD8CD3 TIL. This new method allowed for successful expansion of TIL from cutaneous and uveal melanoma tumors in 100% of the cultures in <3 weeks. Finally, providing the 3 signals attributed to optimal T-cell activation led to expansion of TIL capable of recognizing their tumor counterpart in cutaneous and uveal melanoma. This new methodology for the initial phase of TIL expansion brings a new opportunity for translation of TIL therapy in challenging malignancies such as uveal melanoma.

East Europe Report: Political, Sociological and Military Affairs, No. 2229

DTIC Science & Technology

1983-11-10

possible in the RDC III, using all develop- ment partners, to fully meet the internationally standardized very hard re- quirements regarding mechanical...complicated fashion . The difference between these time marks is proportional to the useful signal voltage and hence to the dose. This time difference is...decontamination) it is possible at least in the end phase to carry out this training optimally only while using technologies and radioactive materi- als

A high precision position sensor design and its signal processing algorithm for a maglev train.

PubMed

Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen

2012-01-01

High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.

A High Precision Position Sensor Design and Its Signal Processing Algorithm for a Maglev Train

PubMed Central

Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen

2012-01-01

High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run. PMID:22778582

Optimizing Complexity Measures for fMRI Data: Algorithm, Artifact, and Sensitivity

PubMed Central

Rubin, Denis; Fekete, Tomer; Mujica-Parodi, Lilianne R.

2013-01-01

Introduction Complexity in the brain has been well-documented at both neuronal and hemodynamic scales, with increasing evidence supporting its use in sensitively differentiating between mental states and disorders. However, application of complexity measures to fMRI time-series, which are short, sparse, and have low signal/noise, requires careful modality-specific optimization. Methods Here we use both simulated and real data to address two fundamental issues: choice of algorithm and degree/type of signal processing. Methods were evaluated with regard to resilience to acquisition artifacts common to fMRI as well as detection sensitivity. Detection sensitivity was quantified in terms of grey-white matter contrast and overlap with activation. We additionally investigated the variation of complexity with activation and emotional content, optimal task length, and the degree to which results scaled with scanner using the same paradigm with two 3T magnets made by different manufacturers. Methods for evaluating complexity were: power spectrum, structure function, wavelet decomposition, second derivative, rescaled range, Higuchi’s estimate of fractal dimension, aggregated variance, and detrended fluctuation analysis. To permit direct comparison across methods, all results were normalized to Hurst exponents. Results Power-spectrum, Higuchi’s fractal dimension, and generalized Hurst exponent based estimates were most successful by all criteria; the poorest-performing measures were wavelet, detrended fluctuation analysis, aggregated variance, and rescaled range. Conclusions Functional MRI data have artifacts that interact with complexity calculations in nontrivially distinct ways compared to other physiological data (such as EKG, EEG) for which these measures are typically used. Our results clearly demonstrate that decisions regarding choice of algorithm, signal processing, time-series length, and scanner have a significant impact on the reliability and sensitivity of complexity estimates. PMID:23700424

Accelerated dynamic cardiac MRI exploiting sparse-Kalman-smoother self-calibration and reconstruction (k  -  t SPARKS)

NASA Astrophysics Data System (ADS)

Park, Suhyung; Park, Jaeseok

2015-05-01

Accelerated dynamic MRI, which exploits spatiotemporal redundancies in k  -  t space and coil dimension, has been widely used to reduce the number of signal encoding and thus increase imaging efficiency with minimal loss of image quality. Nonetheless, particularly in cardiac MRI it still suffers from artifacts and amplified noise in the presence of time-drifting coil sensitivity due to relative motion between coil and subject (e.g. free breathing). Furthermore, a substantial number of additional calibrating signals is to be acquired to warrant accurate calibration of coil sensitivity. In this work, we propose a novel, accelerated dynamic cardiac MRI with sparse-Kalman-smoother self-calibration and reconstruction (k  -  t SPARKS), which is robust to time-varying coil sensitivity even with a small number of calibrating signals. The proposed k  -  t SPARKS incorporates Kalman-smoother self-calibration in k  -  t space and sparse signal recovery in x  -   f space into a single optimization problem, leading to iterative, joint estimation of time-varying convolution kernels and missing signals in k  -  t space. In the Kalman-smoother calibration, motion-induced uncertainties over the entire time frames were included in modeling state transition while a coil-dependent noise statistic in describing measurement process. The sparse signal recovery iteratively alternates with the self-calibration to tackle the ill-conditioning problem potentially resulting from insufficient calibrating signals. Simulations and experiments were performed using both the proposed and conventional methods for comparison, revealing that the proposed k  -  t SPARKS yields higher signal-to-error ratio and superior temporal fidelity in both breath-hold and free-breathing cardiac applications over all reduction factors.

Accelerated dynamic cardiac MRI exploiting sparse-Kalman-smoother self-calibration and reconstruction (k  -  t SPARKS).

PubMed

Park, Suhyung; Park, Jaeseok

2015-05-07

Accelerated dynamic MRI, which exploits spatiotemporal redundancies in k  -  t space and coil dimension, has been widely used to reduce the number of signal encoding and thus increase imaging efficiency with minimal loss of image quality. Nonetheless, particularly in cardiac MRI it still suffers from artifacts and amplified noise in the presence of time-drifting coil sensitivity due to relative motion between coil and subject (e.g. free breathing). Furthermore, a substantial number of additional calibrating signals is to be acquired to warrant accurate calibration of coil sensitivity. In this work, we propose a novel, accelerated dynamic cardiac MRI with sparse-Kalman-smoother self-calibration and reconstruction (k  -  t SPARKS), which is robust to time-varying coil sensitivity even with a small number of calibrating signals. The proposed k  -  t SPARKS incorporates Kalman-smoother self-calibration in k  -  t space and sparse signal recovery in x  -   f space into a single optimization problem, leading to iterative, joint estimation of time-varying convolution kernels and missing signals in k  -  t space. In the Kalman-smoother calibration, motion-induced uncertainties over the entire time frames were included in modeling state transition while a coil-dependent noise statistic in describing measurement process. The sparse signal recovery iteratively alternates with the self-calibration to tackle the ill-conditioning problem potentially resulting from insufficient calibrating signals. Simulations and experiments were performed using both the proposed and conventional methods for comparison, revealing that the proposed k  -  t SPARKS yields higher signal-to-error ratio and superior temporal fidelity in both breath-hold and free-breathing cardiac applications over all reduction factors.

Optimizing communication satellites payload configuration with exact approaches

NASA Astrophysics Data System (ADS)

Stathakis, Apostolos; Danoy, Grégoire; Bouvry, Pascal; Talbi, El-Ghazali; Morelli, Gianluigi

2015-12-01

The satellite communications market is competitive and rapidly evolving. The payload, which is in charge of applying frequency conversion and amplification to the signals received from Earth before their retransmission, is made of various components. These include reconfigurable switches that permit the re-routing of signals based on market demand or because of some hardware failure. In order to meet modern requirements, the size and the complexity of current communication payloads are increasing significantly. Consequently, the optimal payload configuration, which was previously done manually by the engineers with the use of computerized schematics, is now becoming a difficult and time consuming task. Efficient optimization techniques are therefore required to find the optimal set(s) of switch positions to optimize some operational objective(s). In order to tackle this challenging problem for the satellite industry, this work proposes two Integer Linear Programming (ILP) models. The first one is single-objective and focuses on the minimization of the length of the longest channel path, while the second one is bi-objective and additionally aims at minimizing the number of switch changes in the payload switch matrix. Experiments are conducted on a large set of instances of realistic payload sizes using the CPLEX® solver and two well-known exact multi-objective algorithms. Numerical results demonstrate the efficiency and limitations of the ILP approach on this real-world problem.

Dynamic optimization of open-loop input signals for ramp-up current profiles in tokamak plasmas

NASA Astrophysics Data System (ADS)

Ren, Zhigang; Xu, Chao; Lin, Qun; Loxton, Ryan; Teo, Kok Lay

2016-03-01

Establishing a good current spatial profile in tokamak fusion reactors is crucial to effective steady-state operation. The evolution of the current spatial profile is related to the evolution of the poloidal magnetic flux, which can be modeled in the normalized cylindrical coordinates using a parabolic partial differential equation (PDE) called the magnetic diffusion equation. In this paper, we consider the dynamic optimization problem of attaining the best possible current spatial profile during the ramp-up phase of the tokamak. We first use the Galerkin method to obtain a finite-dimensional ordinary differential equation (ODE) model based on the original magnetic diffusion PDE. Then, we combine the control parameterization method with a novel time-scaling transformation to obtain an approximate optimal parameter selection problem, which can be solved using gradient-based optimization techniques such as sequential quadratic programming (SQP). This control parameterization approach involves approximating the tokamak input signals by piecewise-linear functions whose slopes and break-points are decision variables to be optimized. We show that the gradient of the objective function with respect to the decision variables can be computed by solving an auxiliary dynamic system governing the state sensitivity matrix. Finally, we conclude the paper with simulation results for an example problem based on experimental data from the DIII-D tokamak in San Diego, California.

Enhanced Gravitational Wave Science with LISA and gLISA.

NASA Astrophysics Data System (ADS)

Tinto, Massimo

2017-05-01

The geosynchronous Laser Interferometer Space Antenna (gLISA) is a space-based gravitational wave (GW) mission that, for the past five years, has been under joint study at the Jet Propulsion Laboratory, Stanford University, the National Institute for Space Research (I.N.P.E., Brazil), and Space Systems Loral. With an arm length of 73,000 km, gLISA will display optimal sensitivity over a frequency region that is exactly in between those accessible by LISA and LIGO. Such a GW frequency band is characterized by the presence of a very large ensemble of coalescing black-hole binaries (BHBs) similar to those first observed by LIGO and with masses that are 10 to 100 times the mass of the Sun. gLISA will detect thousands of such signals with good signal-to-noise ratio (SNR) and enhance the LIGO science by measuring with high precision the parameters characterizing such signals (source direction, chirp parameter, time to coalescence, etc.) well before they will enter the LIGO band. This valuable information will improve LIGO’s ability to detect these signals and facilitate its study of the merger and ring-down phases not observable by space-based detectors. If flown at the same time as the LISA mission, the two arrays will deliver a joint sensitivity that accounts for the best performance of both missions in their respective parts of the milliHertz band. This simultaneous operation will result in an optimally combined sensitivity curve that is “white” from about 3 × 10-3 Hz to 1 Hz, making the two antennas capable of detecting, with high signal-to-noise ratios (SNRs), BHBs with masses in the range (10 - 107)M ⊙. Their ability of jointly tracking, with enhanced SNR, signals similar to that observed by the Advanced Laser Interferometer Gravitational Wave Observatory (aLIGO) on September 14, 2015 (the GW150914 event) will result in a larger number of observable small-mass binary black-holes and an improved precision of the parameters characterizing these sources. Together, LISA, gLISA and aLIGO will cover, with good sensitivity, the (10-4 - 103) Hz frequency band.

Adaptive linearization of phase space. A hydrological case study

NASA Astrophysics Data System (ADS)

Angarita, Hector; Domínguez, Efraín

2013-04-01

Here is presented a method and its implementation to extract transition operators from hydrological signals with significant algorithmic complexity, i.e. signals with an identifiable deterministic component and a non-periodic and irregular part, being the latter a source of uncertainty for the observer. The method assumes that in a system such as a hydrological system, from the perspective of information theory, signals cannot be known to an arbitrary level of precision due to limited observation or coding capabilities. According to the Shannon-Hartley theorem, at a given sampling frequency -fs' there is a theoretical peak capacity C to observe data from a random signal (i.e. the discharge) transmitted through a noisy channel with a signal to noise ratio -SNR. This imposes a limit on the observer capability to completely reconstruct an observed signal if the sampling frequency -fs' is lower than a given threshold -fs', for which a system signal can be completely recovered for any given SNR. Since most hydrological monitoring systems have low monitoring frequency, the observations may contain less information than required to describe the process dynamics and as a result observed signals exhibit some level of uncertainty if compared with the "true" signal. In the proposed approach, a simple local phase-space model, with locally linearized deterministic and stochastic differential equations, is applied to extract system's state transition operators and to probabilistically characterize the signal uncertainty. In order to determine optimality of the local operators, three main elements are considered: i: System state dimensionality, ii. Sampling frequency and, iii. Parameterization window length. Two examples are shown and discussed to illustrate the method. First, the evaluation of the feasibility of real-time forecasting models for levels and fow rates, from hourly to 14-day lead times. The results of this application demonstrate the operational feasibility for simple predictive models for most of the evaluated cases. The second application is the definition of a stage-discharge decoding method based on the dynamics of the water level observed signal. The results indicate that the method leads to a reduction of hysteresis in the decoded flow, which however is not satisfactory as a quadratic bias emerged in the decoded values and needs explanation. Both examples allow to conclude about the optimal sampling frequency of studied variables.

Signal-domain optimization metrics for MPRAGE RF pulse design in parallel transmission at 7 tesla.

PubMed

Gras, V; Vignaud, A; Mauconduit, F; Luong, M; Amadon, A; Le Bihan, D; Boulant, N

2016-11-01

Standard radiofrequency pulse design strategies focus on minimizing the deviation of the flip angle from a target value, which is sufficient but not necessary for signal homogeneity. An alternative approach, based directly on the signal, here is proposed for the MPRAGE sequence, and is developed in the parallel transmission framework with the use of the k T -points parametrization. The flip angle-homogenizing and the proposed methods were investigated numerically under explicit power and specific absorption rate constraints and tested experimentally in vivo on a 7 T parallel transmission system enabling real time local specific absorption rate monitoring. Radiofrequency pulse performance was assessed by a careful analysis of the signal and contrast between white and gray matter. Despite a slight reduction of the flip angle uniformity, an improved signal and contrast homogeneity with a significant reduction of the specific absorption rate was achieved with the proposed metric in comparison with standard pulse designs. The proposed joint optimization of the inversion and excitation pulses enables significant reduction of the specific absorption rate in the MPRAGE sequence while preserving image quality. The work reported thus unveils a possible direction to increase the potential of ultra-high field MRI and parallel transmission. Magn Reson Med 76:1431-1442, 2016. © 2015 International Society for Magnetic Resonance in Medicine. © 2015 International Society for Magnetic Resonance in Medicine.

Improvement in the amine glass platform by bubbling method for a DNA microarray

PubMed Central

Jee, Seung Hyun; Kim, Jong Won; Lee, Ji Hyeong; Yoon, Young Soo

2015-01-01

A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool. PMID:26468293

Improvement in the amine glass platform by bubbling method for a DNA microarray.

PubMed

Jee, Seung Hyun; Kim, Jong Won; Lee, Ji Hyeong; Yoon, Young Soo

2015-01-01

A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool.

Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market

DOE Office of Scientific and Technical Information (OSTI.GOV)

Powell, Kody M.; Kim, Jong Suk; Cole, Wesley J.

2016-10-01

District energy systems can produce low-cost utilities for large energy networks, but can also be a resource for the electric grid by their ability to ramp production or to store thermal energy by responding to real-time market signals. In this work, dynamic optimization exploits the flexibility of thermal energy storage by determining optimal times to store and extract excess energy. This concept is applied to a polygeneration distributed energy system with combined heat and power, district heating, district cooling, and chilled water thermal energy storage. The system is a university campus responsible for meeting the energy needs of tens ofmore » thousands of people. The objective for the dynamic optimization problem is to minimize cost over a 24-h period while meeting multiple loads in real time. The paper presents a novel algorithm to solve this dynamic optimization problem with energy storage by decomposing the problem into multiple static mixed-integer nonlinear programming (MINLP) problems. Another innovative feature of this work is the study of a large, complex energy network which includes the interrelations of a wide variety of energy technologies. Results indicate that a cost savings of 16.5% is realized when the system can participate in the wholesale electricity market.« less

A multi-purpose readout electronics for CdTe and CZT detectors for x-ray imaging applications

NASA Astrophysics Data System (ADS)

Yue, X. B.; Deng, Z.; Xing, Y. X.; Liu, Y. N.

2017-09-01

A multi-purpose readout electronics based on the DPLMS digital filter has been developed for CdTe and CZT detectors for X-ray imaging applications. Different filter coefficients can be synthesized optimized either for high energy resolution at relatively low counting rate or for high rate photon-counting with reduced energy resolution. The effects of signal width constraints, sampling rate and length were numerical studied by Mento Carlo simulation with simple CRRC shaper input signals. The signal width constraint had minor effect and the ENC was only increased by 6.5% when the signal width was shortened down to 2 τc. The sampling rate and length depended on the characteristic time constants of both input and output signals. For simple CR-RC input signals, the minimum number of the filter coefficients was 12 with 10% increase in ENC when the output time constant was close to the input shaping time. A prototype readout electronics was developed for demonstration, using a previously designed analog front ASIC and a commercial ADC card. Two different DPLMS filters were successfully synthesized and applied for high resolution and high counting rate applications respectively. The readout electronics was also tested with a linear array CdTe detector. The energy resolutions of Am-241 59.5 keV peak were measured to be 6.41% in FWHM for the high resolution filter and to be 13.58% in FWHM for the high counting rate filter with 160 ns signal width constraint.

Inseparability of Go and Stop in Inhibitory Control: Go Stimulus Discriminability Affects Stopping Behavior.

PubMed

Ma, Ning; Yu, Angela J

2016-01-01

Inhibitory control, the ability to stop or modify preplanned actions under changing task conditions, is an important component of cognitive functions. Two lines of models of inhibitory control have previously been proposed for human response in the classical stop-signal task, in which subjects must inhibit a default go response upon presentation of an infrequent stop signal: (1) the race model, which posits two independent go and stop processes that race to determine the behavioral outcome, go or stop; and (2) an optimal decision-making model, which posits that observers decides whether and when to go based on continually (Bayesian) updated information about both the go and stop stimuli. In this work, we probe the relationship between go and stop processing by explicitly manipulating the discrimination difficulty of the go stimulus. While the race model assumes the go and stop processes are independent, and therefore go stimulus discriminability should not affect the stop stimulus processing, we simulate the optimal model to show that it predicts harder go discrimination should result in longer go reaction time (RT), lower stop error rate, as well as faster stop-signal RT. We then present novel behavioral data that validate these model predictions. The results thus favor a fundamentally inseparable account of go and stop processing, in a manner consistent with the optimal model, and contradicting the independence assumption of the race model. More broadly, our findings contribute to the growing evidence that the computations underlying inhibitory control are systematically modulated by cognitive influences in a Bayes-optimal manner, thus opening new avenues for interpreting neural responses underlying inhibitory control.

Optimization of parameters affecting signal intensity in an LTQ-orbitrap in negative ion mode: A design of experiments approach.

PubMed

Lemonakis, Nikolaos; Skaltsounis, Alexios-Leandros; Tsarbopoulos, Anthony; Gikas, Evagelos

2016-01-15

A multistage optimization of all the parameters affecting detection/response in an LTQ-orbitrap analyzer was performed, using a design of experiments methodology. The signal intensity, a critical issue for mass analysis, was investigated and the optimization process was completed in three successive steps, taking into account the three main regions of an orbitrap, the ion generation, the ion transmission and the ion detection regions. Oleuropein and hydroxytyrosol were selected as the model compounds. Overall, applying this methodology the sensitivity was increased more than 24%, the resolution more than 6.5%, whereas the elapsed scan time was reduced nearly to its half. A high-resolution LTQ Orbitrap Discovery mass spectrometer was used for the determination of the analytes of interest. Thus, oleuropein and hydroxytyrosol were infused via the instruments syringe pump and they were analyzed employing electrospray ionization (ESI) in the negative high-resolution full-scan ion mode. The parameters of the three main regions of the LTQ-orbitrap were independently optimized in terms of maximum sensitivity. In this context, factorial design, response surface model and Plackett-Burman experiments were performed and analysis of variance was carried out to evaluate the validity of the statistical model and to determine the most significant parameters for signal intensity. The optimum MS conditions for each analyte were summarized and the method optimum condition was achieved by maximizing the desirability function. Our observation showed good agreement between the predicted optimum response and the responses collected at the predicted optimum conditions. Copyright © 2015 Elsevier B.V. All rights reserved.

Start/End Delays of Voiced and Unvoiced Speech Signals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Herrnstein, A

Recent experiments using low power EM-radar like sensors (e.g, GEMs) have demonstrated a new method for measuring vocal fold activity and the onset times of voiced speech, as vocal fold contact begins to take place. Similarly the end time of a voiced speech segment can be measured. Secondly it appears that in most normal uses of American English speech, unvoiced-speech segments directly precede or directly follow voiced-speech segments. For many applications, it is useful to know typical duration times of these unvoiced speech segments. A corpus, assembled earlier of spoken ''Timit'' words, phrases, and sentences and recorded using simultaneously measuredmore » acoustic and EM-sensor glottal signals, from 16 male speakers, was used for this study. By inspecting the onset (or end) of unvoiced speech, using the acoustic signal, and the onset (or end) of voiced speech using the EM sensor signal, the average duration times for unvoiced segments preceding onset of vocalization were found to be 300ms, and for following segments, 500ms. An unvoiced speech period is then defined in time, first by using the onset of the EM-sensed glottal signal, as the onset-time marker for the voiced speech segment and end marker for the unvoiced segment. Then, by subtracting 300ms from the onset time mark of voicing, the unvoiced speech segment start time is found. Similarly, the times for a following unvoiced speech segment can be found. While data of this nature have proven to be useful for work in our laboratory, a great deal of additional work remains to validate such data for use with general populations of users. These procedures have been useful for applying optimal processing algorithms over time segments of unvoiced, voiced, and non-speech acoustic signals. For example, these data appear to be of use in speaker validation, in vocoding, and in denoising algorithms.« less

Machine learning based Intelligent cognitive network using fog computing

NASA Astrophysics Data System (ADS)

Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

2017-05-01

In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

When good news leads to bad choices.

PubMed

McDevitt, Margaret A; Dunn, Roger M; Spetch, Marcia L; Ludvig, Elliot A

2016-01-01

Pigeons and other animals sometimes deviate from optimal choice behavior when given informative signals for delayed outcomes. For example, when pigeons are given a choice between an alternative that always leads to food after a delay and an alternative that leads to food only half of the time after a delay, preference changes dramatically depending on whether the stimuli during the delays are correlated with (signal) the outcomes or not. With signaled outcomes, pigeons show a much greater preference for the suboptimal alternative than with unsignaled outcomes. Key variables and research findings related to this phenomenon are reviewed, including the effects of durations of the choice and delay periods, probability of reinforcement, and gaps in the signal. We interpret the available evidence as reflecting a preference induced by signals for good news in a context of uncertainty. Other explanations are briefly summarized and compared. © 2016 Society for the Experimental Analysis of Behavior.

Stochastic resonance algorithm applied to quantitative analysis for weak chromatographic signals of alkyl halides and alkyl benzenes in water samples.

PubMed

Xiang, Suyun; Wang, Wei; Xia, Jia; Xiang, Bingren; Ouyang, Pingkai

2009-09-01

The stochastic resonance algorithm is applied to the trace analysis of alkyl halides and alkyl benzenes in water samples. Compared to encountering a single signal when applying the algorithm, the optimization of system parameters for a multicomponent is more complex. In this article, the resolution of adjacent chromatographic peaks is first involved in the optimization of parameters. With the optimized parameters, the algorithm gave an ideal output with good resolution as well as enhanced signal-to-noise ratio. Applying the enhanced signals, the method extended the limit of detection and exhibited good linearity, which ensures accurate determination of the multicomponent.

An optimal filter for short photoplethysmogram signals

PubMed Central

Liang, Yongbo; Elgendi, Mohamed; Chen, Zhencheng; Ward, Rabab

2018-01-01

A photoplethysmogram (PPG) contains a wealth of cardiovascular system information, and with the development of wearable technology, it has become the basic technique for evaluating cardiovascular health and detecting diseases. However, due to the varying environments in which wearable devices are used and, consequently, their varying susceptibility to noise interference, effective processing of PPG signals is challenging. Thus, the aim of this study was to determine the optimal filter and filter order to be used for PPG signal processing to make the systolic and diastolic waves more salient in the filtered PPG signal using the skewness quality index. Nine types of filters with 10 different orders were used to filter 219 (2.1s) short PPG signals. The signals were divided into three categories by PPG experts according to their noise levels: excellent, acceptable, or unfit. Results show that the Chebyshev II filter can improve the PPG signal quality more effectively than other types of filters and that the optimal order for the Chebyshev II filter is the 4th order. PMID:29714722

Neural integration underlying a time-compensated sun compass in the migratory monarch butterfly

PubMed Central

Shlizerman, Eli; Phillips-Portillo, James; Reppert, Steven M.

2016-01-01

Migrating Eastern North American monarch butterflies use a time-compensated sun compass to adjust their flight to the southwest direction. While the antennal genetic circadian clock and the azimuth of the sun are instrumental for proper function of the compass, it is unclear how these signals are represented on a neuronal level and how they are integrated to produce flight control. To address these questions, we constructed a receptive field model of the compound eye that encodes the solar azimuth. We then derived a neural circuit model, which integrates azimuthal and circadian signals to correct flight direction. The model demonstrates an integration mechanism, which produces robust trajectories reaching the southwest regardless of the time of day and includes a configuration for remigration. Comparison of model simulations with flight trajectories of butterflies in a flight simulator shows analogous behaviors and affirms the prediction that midday is the optimal time for migratory flight. PMID:27149852

In vivo time-gated fluorescence imaging with biodegradable luminescent porous silicon nanoparticles.

PubMed

Gu, Luo; Hall, David J; Qin, Zhengtao; Anglin, Emily; Joo, Jinmyoung; Mooney, David J; Howell, Stephen B; Sailor, Michael J

2013-01-01

Fluorescence imaging is one of the most versatile and widely used visualization methods in biomedical research. However, tissue autofluorescence is a major obstacle confounding interpretation of in vivo fluorescence images. The unusually long emission lifetime (5-13 μs) of photoluminescent porous silicon nanoparticles can allow the time-gated imaging of tissues in vivo, completely eliminating shorter-lived (<10 ns) emission signals from organic chromophores or tissue autofluorescence. Here using a conventional animal imaging system not optimized for such long-lived excited states, we demonstrate improvement of signal to background contrast ratio by >50-fold in vitro and by >20-fold in vivo when imaging porous silicon nanoparticles. Time-gated imaging of porous silicon nanoparticles accumulated in a human ovarian cancer xenograft following intravenous injection is demonstrated in a live mouse. The potential for multiplexing of images in the time domain by using separate porous silicon nanoparticles engineered with different excited state lifetimes is discussed.

Evaluation of different time domain peak models using extreme learning machine-based peak detection for EEG signal.

PubMed

Adam, Asrul; Ibrahim, Zuwairie; Mokhtar, Norrima; Shapiai, Mohd Ibrahim; Cumming, Paul; Mubin, Marizan

2016-01-01

Various peak models have been introduced to detect and analyze peaks in the time domain analysis of electroencephalogram (EEG) signals. In general, peak model in the time domain analysis consists of a set of signal parameters, such as amplitude, width, and slope. Models including those proposed by Dumpala, Acir, Liu, and Dingle are routinely used to detect peaks in EEG signals acquired in clinical studies of epilepsy or eye blink. The optimal peak model is the most reliable peak detection performance in a particular application. A fair measure of performance of different models requires a common and unbiased platform. In this study, we evaluate the performance of the four different peak models using the extreme learning machine (ELM)-based peak detection algorithm. We found that the Dingle model gave the best performance, with 72 % accuracy in the analysis of real EEG data. Statistical analysis conferred that the Dingle model afforded significantly better mean testing accuracy than did the Acir and Liu models, which were in the range 37-52 %. Meanwhile, the Dingle model has no significant difference compared to Dumpala model.

Optimized Time-Gated Fluorescence Spectroscopy for the Classification and Recycling of Fluorescently Labeled Plastics.

PubMed

Fomin, Petr; Zhelondz, Dmitry; Kargel, Christian

2017-05-01

For the production of high-quality parts from recycled plastics, a very high purity of the plastic waste to be recycled is mandatory. The incorporation of fluorescent tracers ("markers") into plastics during the manufacturing process helps overcome typical problems of non-tracer based optical classification methods. Despite the unique emission spectra of fluorescent markers, the classification becomes difficult when the host plastics exhibit (strong) autofluorescence that spectrally overlaps the marker fluorescence. Increasing the marker concentration is not an option from an economic perspective and might also adversely affect the properties of the plastics. A measurement approach that suppresses the autofluorescence in the acquired signal is time-gated fluorescence spectroscopy (TGFS). Unfortunately, TGFS is associated with a lower signal-to-noise (S/N) ratio, which results in larger classification errors. In order to optimize the S/N ratio we investigate and validate the best TGFS parameters-derived from a model for the fluorescence signal-for plastics labeled with four specifically designed fluorescent markers. In this study we also demonstrate the implementation of TGFS on a measurement and classification prototype system and determine its performance. Mean values for a sensitivity of [Formula: see text] = 99.93% and precision [Formula: see text] = 99.80% were achieved, proving that a highly reliable classification of plastics can be achieved in practice.

Spatial and Functional Selectivity of Peripheral Nerve Signal Recording With the Transversal Intrafascicular Multichannel Electrode (TIME).

PubMed

Badia, Jordi; Raspopovic, Stanisa; Carpaneto, Jacopo; Micera, Silvestro; Navarro, Xavier

2016-01-01

The selection of suitable peripheral nerve electrodes for biomedical applications implies a trade-off between invasiveness and selectivity. The optimal design should provide the highest selectivity for targeting a large number of nerve fascicles with the least invasiveness and potential damage to the nerve. The transverse intrafascicular multichannel electrode (TIME), transversally inserted in the peripheral nerve, has been shown to be useful for the selective activation of subsets of axons, both at inter- and intra-fascicular levels, in the small sciatic nerve of the rat. In this study we assessed the capabilities of TIME for the selective recording of neural activity, considering the topographical selectivity and the distinction of neural signals corresponding to different sensory types. Topographical recording selectivity was proved by the differential recording of CNAPs from different subsets of nerve fibers, such as those innervating toes 2 and 4 of the hindpaw of the rat. Neural signals elicited by sensory stimuli applied to the rat paw were successfully recorded. Signal processing allowed distinguishing three different types of sensory stimuli such as tactile, proprioceptive and nociceptive ones with high performance. These findings further support the suitability of TIMEs for neuroprosthetic applications, by exploiting the transversal topographical structure of the peripheral nerves.

Reducing the number of reconstructions needed for estimating channelized observer performance

NASA Astrophysics Data System (ADS)

Pineda, Angel R.; Miedema, Hope; Brenner, Melissa; Altaf, Sana

2018-03-01

A challenge for task-based optimization is the time required for each reconstructed image in applications where reconstructions are time consuming. Our goal is to reduce the number of reconstructions needed to estimate the area under the receiver operating characteristic curve (AUC) of the infinitely-trained optimal channelized linear observer. We explore the use of classifiers which either do not invert the channel covariance matrix or do feature selection. We also study the assumption that multiple low contrast signals in the same image of a non-linear reconstruction do not significantly change the estimate of the AUC. We compared the AUC of several classifiers (Hotelling, logistic regression, logistic regression using Firth bias reduction and the least absolute shrinkage and selection operator (LASSO)) with a small number of observations both for normal simulated data and images from a total variation reconstruction in magnetic resonance imaging (MRI). We used 10 Laguerre-Gauss channels and the Mann-Whitney estimator for AUC. For this data, our results show that at small sample sizes feature selection using the LASSO technique can decrease bias of the AUC estimation with increased variance and that for large sample sizes the difference between these classifiers is small. We also compared the use of multiple signals in a single reconstructed image to reduce the number of reconstructions in a total variation reconstruction for accelerated imaging in MRI. We found that AUC estimation using multiple low contrast signals in the same image resulted in similar AUC estimates as doing a single reconstruction per signal leading to a 13x reduction in the number of reconstructions needed.

Boolean network identification from perturbation time series data combining dynamics abstraction and logic programming.

PubMed

Ostrowski, M; Paulevé, L; Schaub, T; Siegel, A; Guziolowski, C

2016-11-01

Boolean networks (and more general logic models) are useful frameworks to study signal transduction across multiple pathways. Logic models can be learned from a prior knowledge network structure and multiplex phosphoproteomics data. However, most efficient and scalable training methods focus on the comparison of two time-points and assume that the system has reached an early steady state. In this paper, we generalize such a learning procedure to take into account the time series traces of phosphoproteomics data in order to discriminate Boolean networks according to their transient dynamics. To that end, we identify a necessary condition that must be satisfied by the dynamics of a Boolean network to be consistent with a discretized time series trace. Based on this condition, we use Answer Set Programming to compute an over-approximation of the set of Boolean networks which fit best with experimental data and provide the corresponding encodings. Combined with model-checking approaches, we end up with a global learning algorithm. Our approach is able to learn logic models with a true positive rate higher than 78% in two case studies of mammalian signaling networks; for a larger case study, our method provides optimal answers after 7min of computation. We quantified the gain in our method predictions precision compared to learning approaches based on static data. Finally, as an application, our method proposes erroneous time-points in the time series data with respect to the optimal learned logic models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Optimization and evaluation of asymmetric flow field-flow fractionation of silver nanoparticles.

PubMed

Loeschner, Katrin; Navratilova, Jana; Legros, Samuel; Wagner, Stephan; Grombe, Ringo; Snell, James; von der Kammer, Frank; Larsen, Erik H

2013-01-11

Asymmetric flow field-flow fractionation (AF(4)) in combination with on-line optical detection and mass spectrometry is one of the most promising methods for separation and quantification of nanoparticles (NPs) in complex matrices including food. However, to obtain meaningful results regarding especially the NP size distribution a number of parameters influencing the separation need to be optimized. This paper describes the development of a separation method for polyvinylpyrrolidone-stabilized silver nanoparticles (AgNPs) in aqueous suspension. Carrier liquid composition, membrane material, cross flow rate and spacer height were shown to have a significant influence on the recoveries and retention times of the nanoparticles. Focus time and focus flow rate were optimized with regard to minimum elution of AgNPs in the void volume. The developed method was successfully tested for injected masses of AgNPs from 0.2 to 5.0 μg. The on-line combination of AF(4) with detection methods including ICP-MS, light absorbance and light scattering was helpful because each detector provided different types of information about the eluting NP fraction. Differences in the time-resolved appearance of the signals obtained by the three detection methods were explained based on the physical origin of the signal. Two different approaches for conversion of retention times of AgNPs to their corresponding sizes and size distributions were tested and compared, namely size calibration with polystyrene nanoparticles (PSNPs) and calculations of size based on AF(4) theory. Fraction collection followed by transmission electron microscopy was performed to confirm the obtained size distributions and to obtain further information regarding the AgNP shape. Characteristics of the absorbance spectra were used to confirm the presence of non-spherical AgNP. Copyright © 2012 Elsevier B.V. All rights reserved.

Wide-area Power System Damping Control Coordination Based on Particle Swarm Optimization with Time Delay Considered

NASA Astrophysics Data System (ADS)

Zhang, J. Y.; Jiang, Y.

2017-10-01

To ensure satisfactory dynamic performance of controllers in time-delayed power systems, a WAMS-based control strategy is investigated in the presence of output feedback delay. An integrated approach based on Pade approximation and particle swarm optimization (PSO) is employed for parameter configuration of PSS. The coordination configuration scheme of power system controllers is achieved by a series of stability constraints at the aim of maximizing the minimum damping ratio of inter-area mode of power system. The validity of this derived PSS is verified on a prototype power system. The findings demonstrate that the proposed approach for control design could damp the inter-area oscillation and enhance the small-signal stability.

Target-based optimization of advanced gravitational-wave detector network operations

NASA Astrophysics Data System (ADS)

Szölgyén, Á.; Dálya, G.; Gondán, L.; Raffai, P.

2017-04-01

We introduce two novel time-dependent figures of merit for both online and offline optimizations of advanced gravitational-wave (GW) detector network operations with respect to (i) detecting continuous signals from known source locations and (ii) detecting GWs of neutron star binary coalescences from known local galaxies, which thereby have the highest potential for electromagnetic counterpart detection. For each of these scientific goals, we characterize an N-detector network, and all its (N  -  1)-detector subnetworks, to identify subnetworks and individual detectors (key contributors) that contribute the most to achieving the scientific goal. Our results show that aLIGO-Hanford is expected to be the key contributor in 2017 to the goal of detecting GWs from the Crab pulsar within the network of LIGO and Virgo detectors. For the same time period and for the same network, both LIGO detectors are key contributors to the goal of detecting GWs from the Vela pulsar, as well as to detecting signals from 10 high interest pulsars. Key contributors to detecting continuous GWs from the Galactic Center can only be identified for finite time intervals within each sidereal day with either the 3-detector network of the LIGO and Virgo detectors in 2017, or the 4-detector network of the LIGO, Virgo, and KAGRA detectors in 2019-2020. Characterization of the LIGO-Virgo detectors with respect to goal (ii) identified the two LIGO detectors as key contributors. Additionally, for all analyses, we identify time periods within a day when lock losses or scheduled service operations could result with the least amount of signal-to-noise or transient detection probability loss for a detector network.

General solution of undersampling frequency conversion and its optimization for parallel photodisplacement imaging.

PubMed

Nakata, Toshihiko; Ninomiya, Takanori

2006-10-10

A general solution of undersampling frequency conversion and its optimization for parallel photodisplacement imaging is presented. Phase-modulated heterodyne interference light generated by a linear region of periodic displacement is captured by a charge-coupled device image sensor, in which the interference light is sampled at a sampling rate lower than the Nyquist frequency. The frequencies of the components of the light, such as the sideband and carrier (which include photodisplacement and topography information, respectively), are downconverted and sampled simultaneously based on the integration and sampling effects of the sensor. A general solution of frequency and amplitude in this downconversion is derived by Fourier analysis of the sampling procedure. The optimal frequency condition for the heterodyne beat signal, modulation signal, and sensor gate pulse is derived such that undesirable components are eliminated and each information component is converted into an orthogonal function, allowing each to be discretely reproduced from the Fourier coefficients. The optimal frequency parameters that maximize the sideband-to-carrier amplitude ratio are determined, theoretically demonstrating its high selectivity over 80 dB. Preliminary experiments demonstrate that this technique is capable of simultaneous imaging of reflectivity, topography, and photodisplacement for the detection of subsurface lattice defects at a speed corresponding to an acquisition time of only 0.26 s per 256 x 256 pixel area.

Robust time-shifted spoke pulse design in the presence of large B0 variations with simultaneous reduction of through-plane dephasing, B1+ effects, and the specific absorption rate using parallel transmission.

PubMed

Guérin, Bastien; Stockmann, Jason P; Baboli, Mehran; Torrado-Carvajal, Angel; Stenger, Andrew V; Wald, Lawrence L

2016-08-01

To design parallel transmission spokes pulses with time-shifted profiles for joint mitigation of intensity variations due to B1+ effects, signal loss due to through-plane dephasing, and the specific absorption rate (SAR) at 7T. We derived a slice-averaged small tip angle (SA-STA) approximation of the magnetization signal at echo time that depends on the B1+ transmit profiles, the through-slice B0 gradient and the amplitude and time-shifts of the spoke waveforms. We minimize a magnitude least-squares objective based on this signal equation using a fast interior-point approach with analytical expressions of the Jacobian and Hessian. Our algorithm runs in less than three minutes for the design of two-spoke pulses subject to hundreds of local SAR constraints. On a B0/B1+ head phantom, joint optimization of the channel-dependent time-shifts and spoke amplitudes allowed signal recovery in high-B0 regions at no increase of SAR. Although the method creates uniform magnetization profiles (ie, uniform intensity), the flip angle varies across the image, which makes it ill-suited to T1-weighted applications. The SA-STA approach presented in this study is best suited to T2*-weighted applications with long echo times that require signal recovery around high B0 regions. Magn Reson Med 76:540-554, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

An Incentive-based Online Optimization Framework for Distribution Grids

DOE PAGES

Zhou, Xinyang; Dall'Anese, Emiliano; Chen, Lijun; ...

2017-10-09

This article formulates a time-varying social-welfare maximization problem for distribution grids with distributed energy resources (DERs) and develops online distributed algorithms to identify (and track) its solutions. In the considered setting, network operator and DER-owners pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. The proposed algorithm affords an online implementation to enable tracking of the solutions in the presence of time-varying operational conditions and changing optimization objectives. It involves a strategy where the network operator collects voltage measurements throughout the feeder to build incentive signals for the DER-owners in real time; DERs thenmore » adjust the generated/consumed powers in order to avoid the violation of the voltage constraints while maximizing given objectives. Stability of the proposed schemes is analytically established and numerically corroborated.« less

An Incentive-based Online Optimization Framework for Distribution Grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Xinyang; Dall'Anese, Emiliano; Chen, Lijun

This article formulates a time-varying social-welfare maximization problem for distribution grids with distributed energy resources (DERs) and develops online distributed algorithms to identify (and track) its solutions. In the considered setting, network operator and DER-owners pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. The proposed algorithm affords an online implementation to enable tracking of the solutions in the presence of time-varying operational conditions and changing optimization objectives. It involves a strategy where the network operator collects voltage measurements throughout the feeder to build incentive signals for the DER-owners in real time; DERs thenmore » adjust the generated/consumed powers in order to avoid the violation of the voltage constraints while maximizing given objectives. Stability of the proposed schemes is analytically established and numerically corroborated.« less

A temperature control method for shortening thermal cycling time to achieve rapid polymerase chain reaction (PCR) in a disposable polymer microfluidic device

NASA Astrophysics Data System (ADS)

Bu, Minqiang; Perch-Nielsen, Ivan R.; Sørensen, Karen S.; Skov, Julia; Sun, Yi; Duong Bang, Dang; Pedersen, Michael E.; Hansen, Mikkel F.; Wolff, Anders

2013-07-01

We present a temperature control method capable of effectively shortening the thermal cycling time of polymerase chain reaction (PCR) in a disposable polymer microfluidic device with an external heater and a temperature sensor. The method employs optimized temperature overshooting and undershooting steps to achieve a rapid ramping between the temperature steps for DNA denaturation, annealing and extension. The temperature dynamics within the microfluidic PCR chamber was characterized and the overshooting and undershooting parameters were optimized using the temperature-dependent fluorescence signal from Rhodamine B. The method was validated with the PCR amplification of mecA gene (162 bp) from methicillin-resistant Staphylococcus aureus bacterium (MRSA), where the time for 30 cycles was reduced from 50 min (without over- and undershooting) to 20 min.

Monaural Sound Localization Based on Reflective Structure and Homomorphic Deconvolution

PubMed Central

Park, Yeonseok; Choi, Anthony

2017-01-01

The asymmetric structure around the receiver provides a particular time delay for the specific incoming propagation. This paper designs a monaural sound localization system based on the reflective structure around the microphone. The reflective plates are placed to present the direction-wise time delay, which is naturally processed by convolutional operation with a sound source. The received signal is separated for estimating the dominant time delay by using homomorphic deconvolution, which utilizes the real cepstrum and inverse cepstrum sequentially to derive the propagation response’s autocorrelation. Once the localization system accurately estimates the information, the time delay model computes the corresponding reflection for localization. Because of the structure limitation, two stages of the localization process perform the estimation procedure as range and angle. The software toolchain from propagation physics and algorithm simulation realizes the optimal 3D-printed structure. The acoustic experiments in the anechoic chamber denote that 79.0% of the study range data from the isotropic signal is properly detected by the response value, and 87.5% of the specific direction data from the study range signal is properly estimated by the response time. The product of both rates shows the overall hit rate to be 69.1%. PMID:28946625

Extracting a shape function for a signal with intra-wave frequency modulation.

PubMed

Hou, Thomas Y; Shi, Zuoqiang

2016-04-13

In this paper, we develop an effective and robust adaptive time-frequency analysis method for signals with intra-wave frequency modulation. To handle this kind of signals effectively, we generalize our data-driven time-frequency analysis by using a shape function to describe the intra-wave frequency modulation. The idea of using a shape function in time-frequency analysis was first proposed by Wu (Wu 2013 Appl. Comput. Harmon. Anal. 35, 181-199. (doi:10.1016/j.acha.2012.08.008)). A shape function could be any smooth 2π-periodic function. Based on this model, we propose to solve an optimization problem to extract the shape function. By exploring the fact that the shape function is a periodic function with respect to its phase function, we can identify certain low-rank structure of the signal. This low-rank structure enables us to extract the shape function from the signal. Once the shape function is obtained, the instantaneous frequency with intra-wave modulation can be recovered from the shape function. We demonstrate the robustness and efficiency of our method by applying it to several synthetic and real signals. One important observation is that this approach is very stable to noise perturbation. By using the shape function approach, we can capture the intra-wave frequency modulation very well even for noise-polluted signals. In comparison, existing methods such as empirical mode decomposition/ensemble empirical mode decomposition seem to have difficulty in capturing the intra-wave modulation when the signal is polluted by noise. © 2016 The Author(s).

Is there more to communications technology than just information transfer

NASA Astrophysics Data System (ADS)

Kaltschmidt, H.

1980-02-01

In the present paper, communications is discussed in terms of information transfer among people, among automata, and among people and automata. Communications is treated as a cybernetics problem involving information sources and sinks. The principal signals and components of a communications system are examined, along with frequency- and time-multiplexing, optimal detection, correlators, etc.

Reference tissue quantification of DCE-MRI data without a contrast agent calibration

NASA Astrophysics Data System (ADS)

Walker-Samuel, Simon; Leach, Martin O.; Collins, David J.

2007-02-01

The quantification of dynamic contrast-enhanced (DCE) MRI data conventionally requires a conversion from signal intensity to contrast agent concentration by measuring a change in the tissue longitudinal relaxation rate, R1. In this paper, it is shown that the use of a spoiled gradient-echo acquisition sequence (optimized so that signal intensity scales linearly with contrast agent concentration) in conjunction with a reference tissue-derived vascular input function (VIF), avoids the need for the conversion to Gd-DTPA concentration. This study evaluates how to optimize such sequences and which dynamic time-series parameters are most suitable for this type of analysis. It is shown that signal difference and relative enhancement provide useful alternatives when full contrast agent quantification cannot be achieved, but that pharmacokinetic parameters derived from both contain sources of error (such as those caused by differences between reference tissue and region of interest proton density and native T1 values). It is shown in a rectal cancer study that these sources of uncertainty are smaller when using signal difference, compared with relative enhancement (15 ± 4% compared with 33 ± 4%). Both of these uncertainties are of the order of those associated with the conversion to Gd-DTPA concentration, according to literature estimates.

Optimization of VLf/ELF Wave Generation using Beam Painting

NASA Astrophysics Data System (ADS)

Robinson, A.; Moore, R. C.

2017-12-01

A novel optimized beam painting algorithm (OBP) is used to generate high amplitude very low frequency (VLF) and extremely low frequency (ELF) waves in the D-region of the ionosphere above the High-frequency Active Auroral Research Program (HAARP) observatory. The OBP method creates a phased array of sources in the ionosphere by varying the azimuth and zenith angles of the high frequency (HF) transmitter to capitalize on the constructive interference of propagating VLF/ELF waves. OBP generates higher amplitude VLF/ELF signals than any other previously proposed method. From April through June during 2014, OBP was performed at HAARP over 1200 times. We compare the BP generated signals against vertical amplitude modulated transmissions at 50 % duty cycle (V), oblique amplitude modulated transmissions at 15 degrees zenith and 81 degrees azimuth at 50 % duty cycle (O), and geometric (circle-sweep) modulation at 15 degrees off-zenith angle at 1562.5 Hz, 3125 Hz, and 5000 Hz. We present an analysis of the directional dependence of each signal, its polarization, and its dependence on the properties of the different source region elements. We find that BP increases the received signal amplitudes of VLF and ELF waves when compared to V, O, and GM methods over a statistically significant number of trials.

Further steps toward direct magnetic resonance (MR) imaging detection of neural action currents: optimization of MR sensitivity to transient and weak currents in a conductor.

PubMed

Pell, Gaby S; Abbott, David F; Fleming, Steven W; Prichard, James W; Jackson, Graeme D

2006-05-01

The characteristics of an MRI technique that could be used for direct detection of neuronal activity are investigated. It was shown that magnitude imaging using echo planar imaging can detect transient local currents. The sensitivity of this method was thoroughly investigated. A partial k-space EPI acquisition with homodyne reconstruction was found to increase the signal change. A unique sensitivity to the position of the current pulse within the imaging sequence was demonstrated with the greatest signal change occurring when the current pulse coincides with the acquisition of the center lines of k-space. The signal change was shown to be highly sensitive to the spatial position of the current conductor relative to the voxel. Furthermore, with the use of optimization of spatial and temporal placement of the current pulse, the level of signal change obtained at this lower limit of current detectability was considerably magnified. It was possible to detect a current of 1.7 microA applied for 20 ms with an imaging time of 1.8 min. The level of sensitivity observed in our study brings us closer to that theoretically required for the detection of action currents in nerves. Copyright (c) 2006 Wiley-Liss, Inc.

Mechanistic and quantitative insight into cell surface targeted molecular imaging agent design.

PubMed

Zhang, Liang; Bhatnagar, Sumit; Deschenes, Emily; Thurber, Greg M

2016-05-05

Molecular imaging agent design involves simultaneously optimizing multiple probe properties. While several desired characteristics are straightforward, including high affinity and low non-specific background signal, in practice there are quantitative trade-offs between these properties. These include plasma clearance, where fast clearance lowers background signal but can reduce target uptake, and binding, where high affinity compounds sometimes suffer from lower stability or increased non-specific interactions. Further complicating probe development, many of the optimal parameters vary depending on both target tissue and imaging agent properties, making empirical approaches or previous experience difficult to translate. Here, we focus on low molecular weight compounds targeting extracellular receptors, which have some of the highest contrast values for imaging agents. We use a mechanistic approach to provide a quantitative framework for weighing trade-offs between molecules. Our results show that specific target uptake is well-described by quantitative simulations for a variety of targeting agents, whereas non-specific background signal is more difficult to predict. Two in vitro experimental methods for estimating background signal in vivo are compared - non-specific cellular uptake and plasma protein binding. Together, these data provide a quantitative method to guide probe design and focus animal work for more cost-effective and time-efficient development of molecular imaging agents.

Effect of reflected and refracted signals on coherent underwater acoustic communication: results from the Kauai experiment (KauaiEx 2003).

PubMed

Rouseff, Daniel; Badiey, Mohsen; Song, Aijun

2009-11-01

The performance of a communications equalizer is quantified in terms of the number of acoustic paths that are treated as usable signal. The analysis uses acoustical and oceanographic data collected off the Hawaiian Island of Kauai. Communication signals were measured on an eight-element vertical array at two different ranges, 1 and 2 km, and processed using an equalizer based on passive time-reversal signal processing. By estimating the Rayleigh parameter, it is shown that all paths reflected by the sea surface at both ranges undergo incoherent scattering. It is demonstrated that some of these incoherently scattered paths are still useful for coherent communications. At range of 1 km, optimal communications performance is achieved when six acoustic paths are retained and all paths with more than one reflection off the sea surface are rejected. Consistent with a model that ignores loss from near-surface bubbles, the performance improves by approximately 1.8 dB when increasing the number of retained paths from four to six. The four-path results though are more stable and require less frequent channel estimation. At range of 2 km, ray refraction is observed and communications performance is optimal when some paths with two sea-surface reflections are retained.

Separate encoding of model-based and model-free valuations in the human brain.

PubMed

Beierholm, Ulrik R; Anen, Cedric; Quartz, Steven; Bossaerts, Peter

2011-10-01

Behavioral studies have long shown that humans solve problems in two ways, one intuitive and fast (System 1, model-free), and the other reflective and slow (System 2, model-based). The neurobiological basis of dual process problem solving remains unknown due to challenges of separating activation in concurrent systems. We present a novel neuroeconomic task that predicts distinct subjective valuation and updating signals corresponding to these two systems. We found two concurrent value signals in human prefrontal cortex: a System 1 model-free reinforcement signal and a System 2 model-based Bayesian signal. We also found a System 1 updating signal in striatal areas and a System 2 updating signal in lateral prefrontal cortex. Further, signals in prefrontal cortex preceded choices that are optimal according to either updating principle, while signals in anterior cingulate cortex and globus pallidus preceded deviations from optimal choice for reinforcement learning. These deviations tended to occur when uncertainty regarding optimal values was highest, suggesting that disagreement between dual systems is mediated by uncertainty rather than conflict, confirming recent theoretical proposals. Copyright © 2011 Elsevier Inc. All rights reserved.

340 nm pulsed UV LED system for europium-based time-resolved fluorescence detection of immunoassays.

PubMed

Rodenko, Olga; Fodgaard, Henrik; Tidemand-Lichtenberg, Peter; Petersen, Paul Michael; Pedersen, Christian

2016-09-19

We report on the design, development and investigation of an optical system based on UV light emitting diode (LED) excitation at 340 nm for time-resolved fluorescence detection of immunoassays. The system was tested to measure cardiac marker Troponin I with a concentration of 200 ng/L in immunoassay. The signal-to-noise ratio was comparable to state-of-the-art Xenon flash lamp based unit with equal excitation energy and without overdriving the LED. We performed a comparative study of the flash lamp and the LED based system and discussed temporal, spatial, and spectral features of the LED excitation for time-resolved fluorimetry. Optimization of the suggested key parameters of the LED promises significant increase of the signal-to-noise ratio and hence of the sensitivity of immunoassay systems.

Fault diagnosis for analog circuits utilizing time-frequency features and improved VVRKFA

NASA Astrophysics Data System (ADS)

He, Wei; He, Yigang; Luo, Qiwu; Zhang, Chaolong

2018-04-01

This paper proposes a novel scheme for analog circuit fault diagnosis utilizing features extracted from the time-frequency representations of signals and an improved vector-valued regularized kernel function approximation (VVRKFA). First, the cross-wavelet transform is employed to yield the energy-phase distribution of the fault signals over the time and frequency domain. Since the distribution is high-dimensional, a supervised dimensionality reduction technique—the bilateral 2D linear discriminant analysis—is applied to build a concise feature set from the distributions. Finally, VVRKFA is utilized to locate the fault. In order to improve the classification performance, the quantum-behaved particle swarm optimization technique is employed to gradually tune the learning parameter of the VVRKFA classifier. The experimental results for the analog circuit faults classification have demonstrated that the proposed diagnosis scheme has an advantage over other approaches.

Robust extrema features for time-series data analysis.

PubMed

Vemulapalli, Pramod K; Monga, Vishal; Brennan, Sean N

2013-06-01

The extraction of robust features for comparing and analyzing time series is a fundamentally important problem. Research efforts in this area encompass dimensionality reduction using popular signal analysis tools such as the discrete Fourier and wavelet transforms, various distance metrics, and the extraction of interest points from time series. Recently, extrema features for analysis of time-series data have assumed increasing significance because of their natural robustness under a variety of practical distortions, their economy of representation, and their computational benefits. Invariably, the process of encoding extrema features is preceded by filtering of the time series with an intuitively motivated filter (e.g., for smoothing), and subsequent thresholding to identify robust extrema. We define the properties of robustness, uniqueness, and cardinality as a means to identify the design choices available in each step of the feature generation process. Unlike existing methods, which utilize filters "inspired" from either domain knowledge or intuition, we explicitly optimize the filter based on training time series to optimize robustness of the extracted extrema features. We demonstrate further that the underlying filter optimization problem reduces to an eigenvalue problem and has a tractable solution. An encoding technique that enhances control over cardinality and uniqueness is also presented. Experimental results obtained for the problem of time series subsequence matching establish the merits of the proposed algorithm.

Cassini First Diametric Radio Occultation of Saturn's Rings

NASA Astrophysics Data System (ADS)

Marouf, E.; French, R.; Rappaport, N.; Kliore, A.; Flasar, M.; Nagy, A.; Ambrosini, R.; McGhee, C.; Schinder, P.; Anabtawi, A.; Barbinis, E.; Goltz, G.; Thomson, F.; Wong, K.

2005-05-01

We present preliminary results expected from the first planned Cassini radio occultation observation of Saturn's rings, to be conducted on May 3rd, 2005. The path of Cassini as seen from Earth (the occultation track) has been designed to cross the rings from the west to the east ansa almost diametrically, allowing for occultation of all major ring features at two widely separated longitudes (about 180 deg apart). The duration of the geometric occultation is about 1.5 hours on each side. During the occultation, Cassini transmits through the rings three coherent monochromatic radio signals of wavelength 0.94, 3.6, and 13 cm (Ka-, X-, and S-band respectively), a capability unique to Cassini. The perturbed signals received at the Earth are recorded at the NASA DSN complexes at Goldstone and Canberra. Both direct and forward-scattered components of the signal may be identified in spectrograms of the received signals. The time history of the extinction of the direct signal is expected to yield high-spatial-resolution optical depth and phase shift profiles of ring structure. The timing of the occultation was optimized to allow probing the rings when the ring-opening-angle B (the angle between the line-of-sight and the ring plane) is relatively large (B = 23 deg), hence maximizing chances of measuring for the first time the structure of the relatively optically thick Ring B. In a similar experiment by Voyager in 1980, excessive signal attenuation along the long path within the nearly closed rings (B = 5.9 deg) limited the utility of the observations in relatively thick ring regions, in particular the main Ring B. For the Cassini optimized occultation geometry, a large B, slow radial velocity along the occultation track, and much improved phase stability of the reference ultrastable oscillator (USO) on board Cassini combine to promise achievable radial resolution approaching 100 m over a good fraction of the rings. Measurement of the amplitude and phase of the diffracted signal enables reconstruction of the observations to remove diffraction effects. Reliable high resolution profiling of ring structure at multiple ring longitudes is at the heart of investigating ring kinematics and dynamics, a major scientific objective of this experiment. In addition, observations of the scattered signal combined with measurements of the differential extinction of the three radio signals are expected to yield complementary information about ring physical properties, including particle size distribution and thickness, another major scientific objective.

Electrode channel selection based on backtracking search optimization in motor imagery brain-computer interfaces.

PubMed

Dai, Shengfa; Wei, Qingguo

2017-01-01

Common spatial pattern algorithm is widely used to estimate spatial filters in motor imagery based brain-computer interfaces. However, use of a large number of channels will make common spatial pattern tend to over-fitting and the classification of electroencephalographic signals time-consuming. To overcome these problems, it is necessary to choose an optimal subset of the whole channels to save computational time and improve the classification accuracy. In this paper, a novel method named backtracking search optimization algorithm is proposed to automatically select the optimal channel set for common spatial pattern. Each individual in the population is a N-dimensional vector, with each component representing one channel. A population of binary codes generate randomly in the beginning, and then channels are selected according to the evolution of these codes. The number and positions of 1's in the code denote the number and positions of chosen channels. The objective function of backtracking search optimization algorithm is defined as the combination of classification error rate and relative number of channels. Experimental results suggest that higher classification accuracy can be achieved with much fewer channels compared to standard common spatial pattern with whole channels.

Optimal Fault-Tolerant Control for Discrete-Time Nonlinear Strict-Feedback Systems Based on Adaptive Critic Design.

PubMed

Wang, Zhanshan; Liu, Lei; Wu, Yanming; Zhang, Huaguang

2018-06-01

This paper investigates the problem of optimal fault-tolerant control (FTC) for a class of unknown nonlinear discrete-time systems with actuator fault in the framework of adaptive critic design (ACD). A pivotal highlight is the adaptive auxiliary signal of the actuator fault, which is designed to offset the effect of the fault. The considered systems are in strict-feedback forms and involve unknown nonlinear functions, which will result in the causal problem. To solve this problem, the original nonlinear systems are transformed into a novel system by employing the diffeomorphism theory. Besides, the action neural networks (ANNs) are utilized to approximate a predefined unknown function in the backstepping design procedure. Combined the strategic utility function and the ACD technique, a reinforcement learning algorithm is proposed to set up an optimal FTC, in which the critic neural networks (CNNs) provide an approximate structure of the cost function. In this case, it not only guarantees the stability of the systems, but also achieves the optimal control performance as well. In the end, two simulation examples are used to show the effectiveness of the proposed optimal FTC strategy.

Digital Signal Processing Methods for Ultrasonic Echoes.

PubMed

Sinding, Kyle; Drapaca, Corina; Tittmann, Bernhard

2016-04-28

Digital signal processing has become an important component of data analysis needed in industrial applications. In particular, for ultrasonic thickness measurements the signal to noise ratio plays a major role in the accurate calculation of the arrival time. For this application a band pass filter is not sufficient since the noise level cannot be significantly decreased such that a reliable thickness measurement can be performed. This paper demonstrates the abilities of two regularization methods - total variation and Tikhonov - to filter acoustic and ultrasonic signals. Both of these methods are compared to a frequency based filtering for digitally produced signals as well as signals produced by ultrasonic transducers. This paper demonstrates the ability of the total variation and Tikhonov filters to accurately recover signals from noisy acoustic signals faster than a band pass filter. Furthermore, the total variation filter has been shown to reduce the noise of a signal significantly for signals with clear ultrasonic echoes. Signal to noise ratios have been increased over 400% by using a simple parameter optimization. While frequency based filtering is efficient for specific applications, this paper shows that the reduction of noise in ultrasonic systems can be much more efficient with regularization methods.

Mathematical models for the diffusion magnetic resonance signal abnormality in patients with prion diseases.

PubMed

Figini, Matteo; Alexander, Daniel C; Redaelli, Veronica; Fasano, Fabrizio; Grisoli, Marina; Baselli, Giuseppe; Gambetti, Pierluigi; Tagliavini, Fabrizio; Bizzi, Alberto

2015-01-01

In clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of sporadic Creutzfeldt-Jakob Disease (sCJD). MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abnormality are unknown. The aim of this prospective study is to combine an advanced DWI protocol with new mathematical models of the microstructural changes occurring in prion disease patients to investigate the cause of MR signal alterations. This underpins the later development of more sensitive and specific image-based biomarkers. DWI data with a wide a range of echo times and diffusion weightings were acquired in 15 patients with suspected diagnosis of prion disease and in 4 healthy age-matched subjects. Clinical diagnosis of sCJD was made in nine patients, genetic CJD in one, rapidly progressive encephalopathy in three, and Gerstmann-Sträussler-Scheinker syndrome in two. Data were analysed with two bi-compartment models that represent different hypotheses about the histopathological alterations responsible for the DWI signal hyperintensity. A ROI-based analysis was performed in 13 grey matter areas located in affected and apparently unaffected regions from patients and healthy subjects. We provide for the first time non-invasive estimate of the restricted compartment radius, designed to reflect vacuole size, which is a key discriminator of sCJD subtypes. The estimated vacuole size in DWI hyperintense cortex was in the range between 3 and 10 µm that is compatible with neuropathology measurements. In DWI hyperintense grey matter of sCJD patients the two bi-compartment models outperform the classic mono-exponential ADC model. Both new models show that T2 relaxation times significantly increase, fast and slow diffusivities reduce, and the fraction of the compartment with slow/restricted diffusion increases compared to unaffected grey matter of patients and healthy subjects. Analysis of the raw DWI signal allows us to suggest the following acquisition parameters for optimized detection of CJD lesions: b = 3000 s/mm(2) and TE = 103 ms. In conclusion, these results provide the first in vivo estimate of mean vacuole size, new insight on the mechanisms of DWI signal changes in prionopathies and open the way to designing an optimized acquisition protocol to improve early clinical diagnosis and subtyping of sCJD.

A new adaptive algorithm for automated feature extraction in exponentially damped signals for health monitoring of smart structures

NASA Astrophysics Data System (ADS)

Qarib, Hossein; Adeli, Hojjat

2015-12-01

In this paper authors introduce a new adaptive signal processing technique for feature extraction and parameter estimation in noisy exponentially damped signals. The iterative 3-stage method is based on the adroit integration of the strengths of parametric and nonparametric methods such as multiple signal categorization, matrix pencil, and empirical mode decomposition algorithms. The first stage is a new adaptive filtration or noise removal scheme. The second stage is a hybrid parametric-nonparametric signal parameter estimation technique based on an output-only system identification technique. The third stage is optimization of estimated parameters using a combination of the primal-dual path-following interior point algorithm and genetic algorithm. The methodology is evaluated using a synthetic signal and a signal obtained experimentally from transverse vibrations of a steel cantilever beam. The method is successful in estimating the frequencies accurately. Further, it estimates the damping exponents. The proposed adaptive filtration method does not include any frequency domain manipulation. Consequently, the time domain signal is not affected as a result of frequency domain and inverse transformations.

Energy-signal quality trade-offs in a WiMAX mobile station with a booster amplifier

NASA Astrophysics Data System (ADS)

Suherman; Mubarakah, N.; Wiranata, O.; Kasim, S. T.

2018-02-01

Worldwide Interoperability for Microwave Access (WiMAX) is a broadband wireless access technology that is able to provide high bit rate mobile internet services. Battery endurance remains a problem in current mobile communication. On the other hand, signal quality determines the successful run of the mobile applications. Energy consumption optimization cannot sacrifice the signal level required by the application to run smoothly. On the contrary, the application should consider battery life time. This paper examines the tradeoffs between energy and signal quality in WiMAX subscriber station by adjusting signal level using a booster amplifier. Simulation evaluations show that an increment of 0.00000104% energy consumption on using amplifier adaptively produces 16.411% signal to noise ratio (SNR) increment and 10.7% bit error rate (BER) decrement. By keeping the amplifier turned on, energy consumption increases up to 0.00000136%, causing the SNR rises to 17.2638% and BER drops to 11.13%. The evaluated application is video streaming, other application may behave differently.

Architecture and settings optimization procedure of a TES frequency domain multiplexed readout firmware

NASA Astrophysics Data System (ADS)

Clenet, A.; Ravera, L.; Bertrand, B.; den Hartog, R.; Jackson, B.; van Leeuwen, B.-J.; van Loon, D.; Parot, Y.; Pointecouteau, E.; Sournac, A.

2014-11-01

IRAP is developing the readout electronics of the SPICA-SAFARI's TES bolometer arrays. Based on the frequency domain multiplexing technique the readout electronics provides the AC-signals to voltage-bias the detectors; it demodulates the data; and it computes a feedback to linearize the detection chain. The feedback is computed with a specific technique, so called baseband feedback (BBFB) which ensures that the loop is stable even with long propagation and processing delays (i.e. several μ s) and with fast signals (i.e. frequency carriers of the order of 5 MHz). To optimize the power consumption we took advantage of the reduced science signal bandwidth to decouple the signal sampling frequency and the data processing rate. This technique allowed a reduction of the power consumption of the circuit by a factor of 10. Beyond the firmware architecture the optimization of the instrument concerns the characterization routines and the definition of the optimal parameters. Indeed, to operate an array TES one has to properly define about 21000 parameters. We defined a set of procedures to automatically characterize these parameters and find out the optimal settings.

Near-Infrared Fluorescence Imaging of Liver Metastases in Rats using Indocyanine Green

PubMed Central

van der Vorst, Joost R.; Hutteman, Merlijn; Mieog, Sven D.; de Rooij, Karien E.; Kaijzel, Eric L.; Löwik, Clemens W.G.M.; Putter, Hein; Kuppen, Peter J.K.; Frangioni, John V.; van de Velde, Cornelis J.H.; Vahrmeijer, Alexander L.

2011-01-01

Background Near-infrared (NIR) fluorescence imaging using indocyanine green (ICG) is a promising technique to obtain real-time assessment of the extent and number of colorectal liver metastases during surgery. The current study aims to optimize dosage and timing of ICG administration. Materials and methods Liver tumors were induced in 18 male WAG/Rij rats by subcapsular inoculation of CC531 rat colorectal cancer cells into three distinct liver lobes. Rats were divided in 2 groups: imaging after 24 and 48 hours or 72 and 96 hours after intravenous ICG administration. In each time group, rats were allocated to three dose groups: 0.04, 0.08, or 0.16 mg ICG. Intraoperative imaging and ex vivo measurements were performed using Mini-FLARE™ and confirmed by fluorescence microscopy. Fluorescence intensity was quantified using the Mini-FLARE software and the difference between tumor signal and liver signal (tumor-to-liver ratio; TLR) was calculated. Results In all 18 rats, all colorectal liver metastases (N = 34), some as small as 1.2 mm, were identified using ICG and the Mini-FLARE™ imaging system. Average tumor-to-liver ratio (TLR) over all groups was 3.0 ± 1.2. TLR was significantly higher in the 72 h time group compared to other time points. ICG dose did not significantly influence TLR, but a trend was found favoring the 0.08 mg dose group. Fluorescence microscopy demonstrated a clear fluorescent rim around the tumor. Conclusions This study demonstrates that colorectal cancer liver metastases can be clearly identified during surgery using ICG and the Mini-FLARE™ imaging system, with optimal timing of 72 h post-injection and an optimal dose of 0.08 mg (0.25 mg/kg) ICG. NIR fluorescence imaging has the potential to improve intraoperative detection of micrometastases and thus the completeness of resection. PMID:21396660

Capacity of noncoherent MFSK channels

NASA Technical Reports Server (NTRS)

Bar-David, I.; Butman, S. A.; Klass, M. J.; Levitt, B. K.; Lyon, R. F.

1974-01-01

Performance limits theoretically achievable over noncoherent channels perturbed by additive Gaussian noise in hard decision, optimal, and soft decision receivers are computed as functions of the number of orthogonal signals and the predetection signal-to-noise ratio. Equations are derived for orthogonal signal capacity, the ultimate MFSK capacity, and the convolutional coding and decoding limit. It is shown that performance improves as the signal-to-noise ratio increases, provided the bandwidth can be increased, that the optimum number of signals is not infinite (except for the optimal receiver), and that the optimum number decreases as the signal-to-noise ratio decreases, but is never less than 7 for even the hard decision receiver.

Numerical study of ultra-low field nuclear magnetic resonance relaxometry utilizing a single axis magnetometer for signal detection.

PubMed

Vogel, Michael W; Vegh, Viktor; Reutens, David C

2013-05-01

This paper investigates optimal placement of a localized single-axis magnetometer for ultralow field (ULF) relaxometry in view of various sample shapes and sizes. The authors used finite element method for the numerical analysis to determine the sample magnetic field environment and evaluate the optimal location of the single-axis magnetometer. Given the different samples, the authors analysed the magnetic field distribution around the sample and determined the optimal orientation and possible positions of the sensor to maximize signal strength, that is, the power of the free induction decay. The authors demonstrate that a glass vial with flat bottom and 10 ml volume is the best structure to achieve the highest signal out of samples studied. This paper demonstrates the importance of taking into account the combined effects of sensor configuration and sample parameters for signal generation prior to designing and constructing ULF systems with a single-axis magnetometer. Through numerical simulations the authors were able to optimize structural parameters, such as sample shape and size, sensor orientation and location, to maximize the measured signal in ultralow field relaxometry.

A Novel Estimator for the Rate of Information Transfer by Continuous Signals

PubMed Central

Takalo, Jouni; Ignatova, Irina; Weckström, Matti; Vähäsöyrinki, Mikko

2011-01-01

The information transfer rate provides an objective and rigorous way to quantify how much information is being transmitted through a communications channel whose input and output consist of time-varying signals. However, current estimators of information content in continuous signals are typically based on assumptions about the system's linearity and signal statistics, or they require prohibitive amounts of data. Here we present a novel information rate estimator without these limitations that is also optimized for computational efficiency. We validate the method with a simulated Gaussian information channel and demonstrate its performance with two example applications. Information transfer between the input and output signals of a nonlinear system is analyzed using a sensory receptor neuron as the model system. Then, a climate data set is analyzed to demonstrate that the method can be applied to a system based on two outputs generated by interrelated random processes. These analyses also demonstrate that the new method offers consistent performance in situations where classical methods fail. In addition to these examples, the method is applicable to a wide range of continuous time series commonly observed in the natural sciences, economics and engineering. PMID:21494562

Phase retrieval via incremental truncated amplitude flow algorithm

NASA Astrophysics Data System (ADS)

Zhang, Quanbing; Wang, Zhifa; Wang, Linjie; Cheng, Shichao

2017-10-01

This paper considers the phase retrieval problem of recovering the unknown signal from the given quadratic measurements. A phase retrieval algorithm based on Incremental Truncated Amplitude Flow (ITAF) which combines the ITWF algorithm and the TAF algorithm is proposed. The proposed ITAF algorithm enhances the initialization by performing both of the truncation methods used in ITWF and TAF respectively, and improves the performance in the gradient stage by applying the incremental method proposed in ITWF to the loop stage of TAF. Moreover, the original sampling vector and measurements are preprocessed before initialization according to the variance of the sensing matrix. Simulation experiments verified the feasibility and validity of the proposed ITAF algorithm. The experimental results show that it can obtain higher success rate and faster convergence speed compared with other algorithms. Especially, for the noiseless random Gaussian signals, ITAF can recover any real-valued signal accurately from the magnitude measurements whose number is about 2.5 times of the signal length, which is close to the theoretic limit (about 2 times of the signal length). And it usually converges to the optimal solution within 20 iterations which is much less than the state-of-the-art algorithms.

Design of a completely model free adaptive control in the presence of parametric, non-parametric uncertainties and random control signal delay.

PubMed

Tutsoy, Onder; Barkana, Duygun Erol; Tugal, Harun

2018-05-01

In this paper, an adaptive controller is developed for discrete time linear systems that takes into account parametric uncertainty, internal-external non-parametric random uncertainties, and time varying control signal delay. Additionally, the proposed adaptive control is designed in such a way that it is utterly model free. Even though these properties are studied separately in the literature, they are not taken into account all together in adaptive control literature. The Q-function is used to estimate long-term performance of the proposed adaptive controller. Control policy is generated based on the long-term predicted value, and this policy searches an optimal stabilizing control signal for uncertain and unstable systems. The derived control law does not require an initial stabilizing control assumption as in the ones in the recent literature. Learning error, control signal convergence, minimized Q-function, and instantaneous reward are analyzed to demonstrate the stability and effectiveness of the proposed adaptive controller in a simulation environment. Finally, key insights on parameters convergence of the learning and control signals are provided. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal signal constellation design for ultra-high-speed optical transport in the presence of nonlinear phase noise.

PubMed

Liu, Tao; Djordjevic, Ivan B

2014-12-29

In this paper, we first describe an optimal signal constellation design algorithm suitable for the coherent optical channels dominated by the linear phase noise. Then, we modify this algorithm to be suitable for the nonlinear phase noise dominated channels. In optimization procedure, the proposed algorithm uses the cumulative log-likelihood function instead of the Euclidian distance. Further, an LDPC coded modulation scheme is proposed to be used in combination with signal constellations obtained by proposed algorithm. Monte Carlo simulations indicate that the LDPC-coded modulation schemes employing the new constellation sets, obtained by our new signal constellation design algorithm, outperform corresponding QAM constellations significantly in terms of transmission distance and have better nonlinearity tolerance.

A preliminary study on multi-wavelength PPG based pulse transit time detection for cuffless blood pressure measurement.

PubMed

Jing Liu; Yuan-Ting Zhang; Xiao-Rong Ding; Wen-Xuan Dai; Ni Zhao

2016-08-01

Pulse transit time (PTT) has been widely studied as an index of blood pressure (BP) changes. In recent years, some prototypes of PTT-based wearable BP measurement devices have been developed, which can relieve users from the discomfort caused by the inflating cuff used in auscultatory and oscillometric BP measurement techniques. However, in the common practice for PTT detection, multi-site sensor implementation on human body is required, making it difficult for the integration of wearable devices. Since multi-wavelength (MW) photoplethysmogram (PPG) signals carry blood pulsation information of different blood vessels embedded in different skin depths, the time difference between different wavelength PPG signals collected at the same body site can be treated as a special PTT on a short length of blood vessels beneath the skin. In this work, the time difference between MW PPG, denoted as PTT_MW, was explored to track BP changes as a substitute of infrared (IR) PTT_EP. (PTT_EP is the time interval between electrocardiogram (ECG) and IR PPG.) Ten healthy adult subjects participated in the experiment, and their continuous BP, ECG and fingertip MW PPG signals generated from blue, green, yellow and IR light were recorded after 2-minute static handgrip exercise at 33% maximal voluntary contraction. The results showed that the correlation between Systolic BP (SBP) and IR-Blue PTT_MW (|r|= 0.52) was comparable to the correlation between SBP and IR PTT_EP (|r|= 0.59). Moreover, we optimized the wavelength combination of PTT_MWs for each subject and found the average value of optimal correlation between SBP and PTT_MW reached 0.76, which was significantly (p<;0.01) higher than the correlation between IR PTT_EP and SBP. This study reveals that the time difference between MW PPG can be potentially used as PTT for cuffless BP measurement with its unique advantage in simple sensor implementation at only one body site.

Noise-Optimized Silicon Radiometers

PubMed Central

Eppeldauer, George P.

2000-01-01

This paper describes a new, experimentally verified, noise analysis and the design considerations of the dynamic characteristics of silicon radiometers. Transimpedance gain, loop gain, and voltage gain were optimized versus frequency for photodiode current meters measuring ac and dc optical radiation. Silicon radiometers with improved dynamic characteristics were built and tested. The frequency-dependent photocurrent gains were measured. The noise floor was optimized in an ac measurement mode using photodiodes of different shunt resistance and operational amplifiers with low 1/f voltage and current noise. In the dark (without any signal), the noise floor of the optimized silicon radiometers was dominated by the Johnson noise of the source resistance. The Johnson noise was decreased and equalized to the amplified 1/f input noise at a 9 Hz chopping frequency and 30 s integration time constant, resulting in an equivalent root-mean-square (rms) photocurrent noise of 8 × 10−17 A. The lowest noise floor of 5 × 10−17 A, equal to a noise equivalent power (NEP) of 1.4 × 10−16 W at the 730 nm peak responsivity, was obtained at a 100 s integration time constant. The radiometers, optimized for ac measurements, were tested in a dc measurement mode as well. Performances in ac and dc measurement modes were compared. In the ac mode, a ten times shorter (40 s) overall measurement time was needed than in the dc mode (400 s) to obtain the same 10−16 A noise floor. PMID:27551606

Optimal use of electrophysiological indicators of muscular effort and fatigue

NASA Technical Reports Server (NTRS)

Updike, O. L.

1981-01-01

Electromyograms (EMG) from working muscles convey information on effort and fatigue. Their application, e.g., to assess the demands of vehicle control tasks, is complicated by the cooperative action of sets of muscles, by both intrinsic and imposed filtering, and by numerous other sources of variation. Fourier analyses of these noise like signals offer one approach to interpretation; downward spectral shifts accompany fatigue. Techniques are being sought (in both time and frequency domains) for further condensing the wideband EMG signals, while retaining essential information, into a concise 'state vector' usable in comparing control system designs.

Electrochemical concentration measurements for multianalyte mixtures in simulated electrorefiner salt

NASA Astrophysics Data System (ADS)

Rappleye, Devin Spencer

The development of electroanalytical techniques in multianalyte molten salt mixtures, such as those found in used nuclear fuel electrorefiners, would enable in situ, real-time concentration measurements. Such measurements are beneficial for process monitoring, optimization and control, as well as for international safeguards and nuclear material accountancy. Electroanalytical work in molten salts has been limited to single-analyte mixtures with a few exceptions. This work builds upon the knowledge of molten salt electrochemistry by performing electrochemical measurements on molten eutectic LiCl-KCl salt mixture containing two analytes, developing techniques for quantitatively analyzing the measured signals even with an additional signal from another analyte, correlating signals to concentration and identifying improvements in experimental and analytical methodologies. (Abstract shortened by ProQuest.).

Sub-Audible Speech Recognition Based upon Electromyographic Signals

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C. (Inventor); Agabon, Shane T. (Inventor); Lee, Diana D. (Inventor)

2012-01-01

Method and system for processing and identifying a sub-audible signal formed by a source of sub-audible sounds. Sequences of samples of sub-audible sound patterns ("SASPs") for known words/phrases in a selected database are received for overlapping time intervals, and Signal Processing Transforms ("SPTs") are formed for each sample, as part of a matrix of entry values. The matrix is decomposed into contiguous, non-overlapping two-dimensional cells of entries, and neural net analysis is applied to estimate reference sets of weight coefficients that provide sums with optimal matches to reference sets of values. The reference sets of weight coefficients are used to determine a correspondence between a new (unknown) word/phrase and a word/phrase in the database.

Real time standoff gas detection and environmental monitoring with LWIR hyperspectral imager

NASA Astrophysics Data System (ADS)

Prel, Florent; Moreau, Louis; Lavoie, Hugo; Bouffard, François; Thériault, Jean-Marc; Vallieres, Christian; Roy, Claude; Dubé, Denis

2012-10-01

MR-i is a dual band Hyperspectral Imaging Spectro-radiometer. This field instrument generates spectral datacubes in the MWIR and LWIR. MR-i is modular and can be configured in different ways. One of its configurations is optimized for the standoff measurements of gases in differential mode. In this mode, the instrument is equipped with a dual-input telescope to perform optical background subtraction. The resulting signal is the differential between the spectral radiance entering each input port. With that method, the signal from the background is automatically removed from the signal of the target of interest. The spectral range of this configuration extends in the VLWIR (cut-off near 14 μm) to take full advantage of the LW atmospheric window.

Data collection system for a wide range of gas-discharge proportional neutron counters

NASA Astrophysics Data System (ADS)

Oskomov, V.; Sedov, A.; Saduyev, N.; Kalikulov, O.; Kenzhina, I.; Tautaev, E.; Mukhamejanov, Y.; Dyachkov, V.; Utey, Sh

2017-12-01

This article describes the development and creation of a universal system of data collection to measure the intensity of pulsed signals. As a result of careful analysis of time conditions and operating conditions of software and hardware complex circuit solutions were selected that meet the required specifications: frequency response is optimized in order to obtain the maximum ratio signal/noise; methods and modes of operation of the microcontroller were worked out to implement the objectives of continuous measurement of signal amplitude at the output of amplifier and send the data to a computer; function of control of high voltage source was implemented. The preliminary program has been developed for microcontroller in its simplest form, which works on a particular algorithm.

SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

PubMed

Pastore, Vito Paolo; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

2018-01-01

We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with Microsoft Visual Studio based on .NET framework 4.5 development environment. Accepted input data formats are HDF5, level 5 MAT and text files, containing recorded or generated time series spike signals data. SPICODYN processes such electrophysiological signals focusing on: spiking and bursting dynamics and functional-effective connectivity analysis. In particular, for inferring network connectivity, a new implementation of the transfer entropy method is presented dealing with multiple time delays (temporal extension) and with multiple binary patterns (high order extension). SPICODYN is specifically tailored to process data coming from different Multi-Electrode Arrays setups, guarantying, in those specific cases, automated processing. The optimized implementation of the Delayed Transfer Entropy and the High-Order Transfer Entropy algorithms, allows performing accurate and rapid analysis on multiple spike trains from thousands of electrodes.

A Direction of Arrival Estimation Algorithm Based on Orthogonal Matching Pursuit

NASA Astrophysics Data System (ADS)

Tang, Junyao; Cao, Fei; Liu, Lipeng

2018-02-01

The results show that the modified DSM is able to predict local buckling capacity of hot-rolled RHS and SHS accurately. In order to solve the problem of the weak ability of anti-radiation missile against active decoy in modern electronic warfare, a direction of arrival estimation algorithm based on orthogonal matching pursuit is proposed in this paper. The algorithm adopts the compression sensing technology. This paper uses array antennas to receive signals, gets the sparse representation of signals, and then designs the corresponding perception matrix. The signal is reconstructed by orthogonal matching pursuit algorithm to estimate the optimal solution. At the same time, the error of the whole measurement system is analyzed and simulated, and the validity of this algorithm is verified. The algorithm greatly reduces the measurement time, the quantity of equipment and the total amount of the calculation, and accurately estimates the angle and strength of the incoming signal. This technology can effectively improve the angle resolution of the missile, which is of reference significance to the research of anti-active decoy.

A Perspective on Studying G-Protein-Coupled Receptor Signaling with Resonance Energy Transfer Biosensors in Living Organisms.

PubMed

van Unen, Jakobus; Woolard, Jeanette; Rinken, Ago; Hoffmann, Carsten; Hill, Stephen J; Goedhart, Joachim; Bruchas, Michael R; Bouvier, Michel; Adjobo-Hermans, Merel J W

2015-09-01

The last frontier for a complete understanding of G-protein-coupled receptor (GPCR) biology is to be able to assess GPCR activity, interactions, and signaling in vivo, in real time within biologically intact systems. This includes the ability to detect GPCR activity, trafficking, dimerization, protein-protein interactions, second messenger production, and downstream signaling events with high spatial resolution and fast kinetic readouts. Resonance energy transfer (RET)-based biosensors allow for all of these possibilities in vitro and in cell-based assays, but moving RET into intact animals has proven difficult. Here, we provide perspectives on the optimization of biosensor design, of signal detection in living organisms, and the multidisciplinary development of in vitro and cell-based assays that more appropriately reflect the physiologic situation. In short, further development of RET-based probes, optical microscopy techniques, and mouse genome editing hold great potential over the next decade to bring real-time in vivo GPCR imaging to the forefront of pharmacology. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

Track Detection in Railway Sidings Based on MEMS Gyroscope Sensors

PubMed Central

Broquetas, Antoni; Comerón, Adolf; Gelonch, Antoni; Fuertes, Josep M.; Castro, J. Antonio; Felip, Damià; López, Miguel A.; Pulido, José A.

2012-01-01

The paper presents a two-step technique for real-time track detection in single-track railway sidings using low-cost MEMS gyroscopes. The objective is to reliably know the path the train has taken in a switch, diverted or main road, immediately after the train head leaves the switch. The signal delivered by the gyroscope is first processed by an adaptive low-pass filter that rejects noise and converts the temporal turn rate data in degree/second units into spatial turn rate data in degree/meter. The conversion is based on the travelled distance taken from odometer data. The filter is implemented to achieve a speed-dependent cut-off frequency to maximize the signal-to-noise ratio. Although direct comparison of the filtered turn rate signal with a predetermined threshold is possible, the paper shows that better detection performance can be achieved by processing the turn rate signal with a filter matched to the rail switch curvature parameters. Implementation aspects of the track detector have been optimized for real-time operation. The detector has been tested with both simulated data and real data acquired in railway campaigns. PMID:23443376

STFT or CWT for the detection of Doppler ultrasound embolic signals.

PubMed

Gonçalves, Ivo B; Leiria, Ana; Moura, M M M

2013-09-01

Aiming reliable detection and localization of cerebral blood flow and emboli, embolic signals were added to simulated middle cerebral artery Doppler signals and analysed. Short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were used in the evaluation. The following parameters were used in this study: the powers of the embolic signals added were 5, 6, 6.5, 7, 7.5, 8 and 9 dB; the mother wavelets for CWT analysis were Morlet, Mexican hat, Meyer, Gaussian (order 4) and Daubechies (orders 4 and 8); and the thresholds for detection (equated in terms of false positive, false negative and sensitivity) were 2 and 3.5 dB for the CWT and STFT, respectively. The results indicate that although the STFT allows accurately detecting emboli, better time localization can be achieved with the CWT. Among the CWT, the current best overall results were obtained with Mexican Hat mother wavelet, with optimal results for sensitivity (100% detection rate) for nearly all emboli power values studied. Copyright © 2013 John Wiley & Sons, Ltd.

Radar antenna pointing for optimized signal to noise ratio.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doerry, Armin Walter; Marquette, Brandeis

2013-01-01

The Signal-to-Noise Ratio (SNR) of a radar echo signal will vary across a range swath, due to spherical wavefront spreading, atmospheric attenuation, and antenna beam illumination. The antenna beam illumination will depend on antenna pointing. Calculations of geometry are complicated by the curved earth, and atmospheric refraction. This report investigates optimizing antenna pointing to maximize the minimum SNR across the range swath.

Geometric subspace methods and time-delay embedding for EEG artifact removal and classification.

PubMed

Anderson, Charles W; Knight, James N; O'Connor, Tim; Kirby, Michael J; Sokolov, Artem

2006-06-01

Generalized singular-value decomposition is used to separate multichannel electroencephalogram (EEG) into components found by optimizing a signal-to-noise quotient. These components are used to filter out artifacts. Short-time principal components analysis of time-delay embedded EEG is used to represent windowed EEG data to classify EEG according to which mental task is being performed. Examples are presented of the filtering of various artifacts and results are shown of classification of EEG from five mental tasks using committees of decision trees.

Brain-computer interface analysis of a dynamic visuo-motor task.

PubMed

Logar, Vito; Belič, Aleš

2011-01-01

The area of brain-computer interfaces (BCIs) represents one of the more interesting fields in neurophysiological research, since it investigates the development of the machines that perform different transformations of the brain's "thoughts" to certain pre-defined actions. Experimental studies have reported some successful implementations of BCIs; however, much of the field still remains unexplored. According to some recent reports the phase coding of informational content is an important mechanism in the brain's function and cognition, and has the potential to explain various mechanisms of the brain's data transfer, but it has yet to be scrutinized in the context of brain-computer interface. Therefore, if the mechanism of phase coding is plausible, one should be able to extract the phase-coded content, carried by brain signals, using appropriate signal-processing methods. In our previous studies we have shown that by using a phase-demodulation-based signal-processing approach it is possible to decode some relevant information on the current motor action in the brain from electroencephalographic (EEG) data. In this paper the authors would like to present a continuation of their previous work on the brain-information-decoding analysis of visuo-motor (VM) tasks. The present study shows that EEG data measured during more complex, dynamic visuo-motor (dVM) tasks carries enough information about the currently performed motor action to be successfully extracted by using the appropriate signal-processing and identification methods. The aim of this paper is therefore to present a mathematical model, which by means of the EEG measurements as its inputs predicts the course of the wrist movements as applied by each subject during the task in simulated or real time (BCI analysis). However, several modifications to the existing methodology are needed to achieve optimal decoding results and a real-time, data-processing ability. The information extracted from the EEG could, therefore, be further used for the development of a closed-loop, non-invasive, brain-computer interface. For the case of this study two types of measurements were performed, i.e., the electroencephalographic (EEG) signals and the wrist movements were measured simultaneously, during the subject's performance of a dynamic visuo-motor task. Wrist-movement predictions were computed by using the EEG data-processing methodology of double brain-rhythm filtering, double phase demodulation and double principal component analyses (PCA), each with a separate set of parameters. For the movement-prediction model a fuzzy inference system was used. The results have shown that the EEG signals measured during the dVM tasks carry enough information about the subjects' wrist movements for them to be successfully decoded using the presented methodology. Reasonably high values of the correlation coefficients suggest that the validation of the proposed approach is satisfactory. Moreover, since the causality of the rhythm filtering and the PCA transformation has been achieved, we have shown that these methods can also be used in a real-time, brain-computer interface. The study revealed that using non-causal, optimized methods yields better prediction results in comparison with the causal, non-optimized methodology; however, taking into account that the causality of these methods allows real-time processing, the minor decrease in prediction quality is acceptable. The study suggests that the methodology that was proposed in our previous studies is also valid for identifying the EEG-coded content during dVM tasks, albeit with various modifications, which allow better prediction results and real-time data processing. The results have shown that wrist movements can be predicted in simulated or real time; however, the results of the non-causal, optimized methodology (simulated) are slightly better. Nevertheless, the study has revealed that these methods should be suitable for use in the development of a non-invasive, brain-computer interface. Copyright © 2010 Elsevier B.V. All rights reserved.

Using spatiotemporal source separation to identify prominent features in multichannel data without sinusoidal filters.

PubMed

Cohen, Michael X

2017-09-27

The number of simultaneously recorded electrodes in neuroscience is steadily increasing, providing new opportunities for understanding brain function, but also new challenges for appropriately dealing with the increase in dimensionality. Multivariate source separation analysis methods have been particularly effective at improving signal-to-noise ratio while reducing the dimensionality of the data and are widely used for cleaning, classifying and source-localizing multichannel neural time series data. Most source separation methods produce a spatial component (that is, a weighted combination of channels to produce one time series); here, this is extended to apply source separation to a time series, with the idea of obtaining a weighted combination of successive time points, such that the weights are optimized to satisfy some criteria. This is achieved via a two-stage source separation procedure, in which an optimal spatial filter is first constructed and then its optimal temporal basis function is computed. This second stage is achieved with a time-delay-embedding matrix, in which additional rows of a matrix are created from time-delayed versions of existing rows. The optimal spatial and temporal weights can be obtained by solving a generalized eigendecomposition of covariance matrices. The method is demonstrated in simulated data and in an empirical electroencephalogram study on theta-band activity during response conflict. Spatiotemporal source separation has several advantages, including defining empirical filters without the need to apply sinusoidal narrowband filters. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Optimization of a direct analysis in real time/time-of-flight mass spectrometry method for rapid serum metabolomic fingerprinting.

PubMed

Zhou, Manshui; McDonald, John F; Fernández, Facundo M

2010-01-01

Metabolomic fingerprinting of bodily fluids can reveal the underlying causes of metabolic disorders associated with many diseases, and has thus been recognized as a potential tool for disease diagnosis and prognosis following therapy. Here we report a rapid approach in which direct analysis in real time (DART) coupled with time-of-flight (TOF) mass spectrometry (MS) and hybrid quadrupole TOF (Q-TOF) MS is used as a means for metabolomic fingerprinting of human serum. In this approach, serum samples are first treated to precipitate proteins, and the volatility of the remaining metabolites increased by derivatization, followed by DART MS analysis. Maximum DART MS performance was obtained by optimizing instrumental parameters such as ionizing gas temperature and flow rate for the analysis of identical aliquots of a healthy human serum samples. These variables were observed to have a significant effect on the overall mass range of the metabolites detected as well as the signal-to-noise ratios in DART mass spectra. Each DART run requires only 1.2 min, during which more than 1500 different spectral features are observed in a time-dependent fashion. A repeatability of 4.1% to 4.5% was obtained for the total ion signal using a manual sampling arm. With the appealing features of high-throughput, lack of memory effects, and simplicity, DART MS has shown potential to become an invaluable tool for metabolomic fingerprinting. 2010 American Society for Mass Spectrometry. Published by Elsevier Inc. All rights reserved.

Non-linear dynamic compensation system

NASA Technical Reports Server (NTRS)

Lin, Yu-Hwan (Inventor); Lurie, Boris J. (Inventor)

1992-01-01

A non-linear dynamic compensation subsystem is added in the feedback loop of a high precision optical mirror positioning control system to smoothly alter the control system response bandwidth from a relatively wide response bandwidth optimized for speed of control system response to a bandwidth sufficiently narrow to reduce position errors resulting from the quantization noise inherent in the inductosyn used to measure mirror position. The non-linear dynamic compensation system includes a limiter for limiting the error signal within preselected limits, a compensator for modifying the limiter output to achieve the reduced bandwidth response, and an adder for combining the modified error signal with the difference between the limited and unlimited error signals. The adder output is applied to control system motor so that the system response is optimized for accuracy when the error signal is within the preselected limits, optimized for speed of response when the error signal is substantially beyond the preselected limits and smoothly varied therebetween as the error signal approaches the preselected limits.