SPROC: A multiple-processor DSP IC

NASA Technical Reports Server (NTRS)

Davis, R.

1991-01-01

A large, single-chip, multiple-processor, digital signal processing (DSP) integrated circuit (IC) fabricated in HP-Cmos34 is presented. The innovative architecture is best suited for analog and real-time systems characterized by both parallel signal data flows and concurrent logic processing. The IC is supported by a powerful development system that transforms graphical signal flow graphs into production-ready systems in minutes. Automatic compiler partitioning of tasks among four on-chip processors gives the IC the signal processing power of several conventional DSP chips.

Linking automatic evaluation to mood and information processing style: consequences for experienced affect, impression formation, and stereotyping.

PubMed

Chartrand, Tanya L; van Baaren, Rick B; Bargh, John A

2006-02-01

According to the feelings-as-information account, a person's mood state signals to him or her the valence of the current environment (N. Schwarz & G. Clore, 1983). However, the ways in which the environment automatically influences mood in the first place remain to be explored. The authors propose that one mechanism by which the environment influences affect is automatic evaluation, the nonconscious evaluation of environmental stimuli as good or bad. A first experiment demonstrated that repeated brief exposure to positive or negative stimuli (which leads to automatic evaluation) induces a corresponding mood in participants. In 3 additional studies, the authors showed that automatic evaluation affects information processing style. Experiment 4 showed that participants' mood mediates the effect of valenced brief primes on information processing. ((c) 2006 APA, all rights reserved).

Linking Automatic Evaluation to Mood and Information Processing Style: Consequences for Experienced Affect, Impression Formation, and Stereotyping

PubMed Central

Chartrand, Tanya L.; van Baaren, Rick B.; Bargh, John A.

2009-01-01

According to the feelings-as-information account, a person’s mood state signals to him or her the valence of the current environment (N. Schwarz & G. Clore, 1983). However, the ways in which the environment automatically influences mood in the first place remain to be explored. The authors propose that one mechanism by which the environment influences affect is automatic evaluation, the nonconscious evaluation of environmental stimuli as good or bad. A first experiment demonstrated that repeated brief exposure to positive or negative stimuli (which leads to automatic evaluation) induces a corresponding mood in participants. In 3 additional studies, the authors showed that automatic evaluation affects information processing style. Experiment 4 showed that participants’ mood mediates the effect of valenced brief primes on information processing. PMID:16478316

Automated Signal Processing Applied to Volatile-Based Inspection of Greenhouse Crops

PubMed Central

Jansen, Roel; Hofstee, Jan Willem; Bouwmeester, Harro; van Henten, Eldert

2010-01-01

Gas chromatograph–mass spectrometers (GC-MS) have been used and shown utility for volatile-based inspection of greenhouse crops. However, a widely recognized difficulty associated with GC-MS application is the large and complex data generated by this instrument. As a consequence, experienced analysts are often required to process this data in order to determine the concentrations of the volatile organic compounds (VOCs) of interest. Manual processing is time-consuming, labour intensive and may be subject to errors due to fatigue. The objective of this study was to assess whether or not GC-MS data can also be automatically processed in order to determine the concentrations of crop health associated VOCs in a greenhouse. An experimental dataset that consisted of twelve data files was processed both manually and automatically to address this question. Manual processing was based on simple peak integration while the automatic processing relied on the algorithms implemented in the MetAlign™ software package. The results of automatic processing of the experimental dataset resulted in concentrations similar to that after manual processing. These results demonstrate that GC-MS data can be automatically processed in order to accurately determine the concentrations of crop health associated VOCs in a greenhouse. When processing GC-MS data automatically, noise reduction, alignment, baseline correction and normalisation are required. PMID:22163594

Fail-safe fire detection system

NASA Technical Reports Server (NTRS)

Bloam, E. T.

1974-01-01

Fire detection control system continually monitors its own integrity, automatically signals any malfunction, and separately signals fire in any zone being monitored. Should be of interest in fields of chemical and petroleum processing, power generation, equipment testing, and building protection.

A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm

PubMed Central

Zhu, Bohui; Ding, Yongsheng; Hao, Kuangrong

2013-01-01

This paper presents a novel maximum margin clustering method with immune evolution (IEMMC) for automatic diagnosis of electrocardiogram (ECG) arrhythmias. This diagnostic system consists of signal processing, feature extraction, and the IEMMC algorithm for clustering of ECG arrhythmias. First, raw ECG signal is processed by an adaptive ECG filter based on wavelet transforms, and waveform of the ECG signal is detected; then, features are extracted from ECG signal to cluster different types of arrhythmias by the IEMMC algorithm. Three types of performance evaluation indicators are used to assess the effect of the IEMMC method for ECG arrhythmias, such as sensitivity, specificity, and accuracy. Compared with K-means and iterSVR algorithms, the IEMMC algorithm reflects better performance not only in clustering result but also in terms of global search ability and convergence ability, which proves its effectiveness for the detection of ECG arrhythmias. PMID:23690875

Chatter detection in milling process based on VMD and energy entropy

NASA Astrophysics Data System (ADS)

Liu, Changfu; Zhu, Lida; Ni, Chenbing

2018-05-01

This paper presents a novel approach to detect the milling chatter based on Variational Mode Decomposition (VMD) and energy entropy. VMD has already been employed in feature extraction from non-stationary signals. The parameters like number of modes (K) and the quadratic penalty (α) need to be selected empirically when raw signal is decomposed by VMD. Aimed at solving the problem how to select K and α, the automatic selection method of VMD's based on kurtosis is proposed in this paper. When chatter occurs in the milling process, energy will be absorbed to chatter frequency bands. To detect the chatter frequency bands automatically, the chatter detection method based on energy entropy is presented. The vibration signal containing chatter frequency is simulated and three groups of experiments which represent three cutting conditions are conducted. To verify the effectiveness of method presented by this paper, chatter feather extraction has been successfully employed on simulation signals and experimental signals. The simulation and experimental results show that the proposed method can effectively detect the chatter.

Industrial realization of a direct Fourier transform in automated experimental data processing systems

NASA Technical Reports Server (NTRS)

Lyubashevskiy, G. S.

1973-01-01

Fourier processing of automatic signals transforms direct current voltage into a numerical form through bandpass filtration in time-pulse multiplying devices. It is shown that the ratio of the interference energy to the useful signal energy is inversely proportional to the square of the product of the depth of the width modulation and the ratio of the time constant averaging to the cross-multiplied signals.

Automatic detection of snow avalanches in continuous seismic data using hidden Markov models

NASA Astrophysics Data System (ADS)

Heck, Matthias; Hammer, Conny; van Herwijnen, Alec; Schweizer, Jürg; Fäh, Donat

2018-01-01

Snow avalanches generate seismic signals as many other mass movements. Detection of avalanches by seismic monitoring is highly relevant to assess avalanche danger. In contrast to other seismic events, signals generated by avalanches do not have a characteristic first arrival nor is it possible to detect different wave phases. In addition, the moving source character of avalanches increases the intricacy of the signals. Although it is possible to visually detect seismic signals produced by avalanches, reliable automatic detection methods for all types of avalanches do not exist yet. We therefore evaluate whether hidden Markov models (HMMs) are suitable for the automatic detection of avalanches in continuous seismic data. We analyzed data recorded during the winter season 2010 by a seismic array deployed in an avalanche starting zone above Davos, Switzerland. We re-evaluated a reference catalogue containing 385 events by grouping the events in seven probability classes. Since most of the data consist of noise, we first applied a simple amplitude threshold to reduce the amount of data. As first classification results were unsatisfying, we analyzed the temporal behavior of the seismic signals for the whole data set and found that there is a high variability in the seismic signals. We therefore applied further post-processing steps to reduce the number of false alarms by defining a minimal duration for the detected event, implementing a voting-based approach and analyzing the coherence of the detected events. We obtained the best classification results for events detected by at least five sensors and with a minimal duration of 12 s. These processing steps allowed identifying two periods of high avalanche activity, suggesting that HMMs are suitable for the automatic detection of avalanches in seismic data. However, our results also showed that more sensitive sensors and more appropriate sensor locations are needed to improve the signal-to-noise ratio of the signals and therefore the classification.

49 CFR 236.504 - Operation interconnected with automatic block-signal system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Operation interconnected with automatic block... Operation interconnected with automatic block-signal system. (a) A continuous inductive automatic train stop or train control system shall operate in connection with an automatic block signal system and shall...

Development of an automated ultrasonic testing system

NASA Astrophysics Data System (ADS)

Shuxiang, Jiao; Wong, Brian Stephen

2005-04-01

Non-Destructive Testing is necessary in areas where defects in structures emerge over time due to wear and tear and structural integrity is necessary to maintain its usability. However, manual testing results in many limitations: high training cost, long training procedure, and worse, the inconsistent test results. A prime objective of this project is to develop an automatic Non-Destructive testing system for a shaft of the wheel axle of a railway carriage. Various methods, such as the neural network, pattern recognition methods and knowledge-based system are used for the artificial intelligence problem. In this paper, a statistical pattern recognition approach, Classification Tree is applied. Before feature selection, a thorough study on the ultrasonic signals produced was carried out. Based on the analysis of the ultrasonic signals, three signal processing methods were developed to enhance the ultrasonic signals: Cross-Correlation, Zero-Phase filter and Averaging. The target of this step is to reduce the noise and make the signal character more distinguishable. Four features: 1. The Auto Regressive Model Coefficients. 2. Standard Deviation. 3. Pearson Correlation 4. Dispersion Uniformity Degree are selected. And then a Classification Tree is created and applied to recognize the peak positions and amplitudes. Searching local maximum is carried out before feature computing. This procedure reduces much computation time in the real-time testing. Based on this algorithm, a software package called SOFRA was developed to recognize the peaks, calibrate automatically and test a simulated shaft automatically. The automatic calibration procedure and the automatic shaft testing procedure are developed.

Development of wireless brain computer interface with embedded multitask scheduling and its application on real-time driver's drowsiness detection and warning.

PubMed

Lin, Chin-Teng; Chen, Yu-Chieh; Huang, Teng-Yi; Chiu, Tien-Ting; Ko, Li-Wei; Liang, Sheng-Fu; Hsieh, Hung-Yi; Hsu, Shang-Hwa; Duann, Jeng-Ren

2008-05-01

Biomedical signal monitoring systems have been rapidly advanced with electronic and information technologies in recent years. However, most of the existing physiological signal monitoring systems can only record the signals without the capability of automatic analysis. In this paper, we proposed a novel brain-computer interface (BCI) system that can acquire and analyze electroencephalogram (EEG) signals in real-time to monitor human physiological as well as cognitive states, and, in turn, provide warning signals to the users when needed. The BCI system consists of a four-channel biosignal acquisition/amplification module, a wireless transmission module, a dual-core signal processing unit, and a host system for display and storage. The embedded dual-core processing system with multitask scheduling capability was proposed to acquire and process the input EEG signals in real time. In addition, the wireless transmission module, which eliminates the inconvenience of wiring, can be switched between radio frequency (RF) and Bluetooth according to the transmission distance. Finally, the real-time EEG-based drowsiness monitoring and warning algorithms were implemented and integrated into the system to close the loop of the BCI system. The practical online testing demonstrates the feasibility of using the proposed system with the ability of real-time processing, automatic analysis, and online warning feedback in real-world operation and living environments.

Watch out for reporter gene assays with Renilla luciferase and paclitaxel.

PubMed

Theile, Dirk; Spalwisz, Adriana; Weiss, Johanna

2013-06-15

Luminescence-based reporter gene assays are widely used in biochemistry. Signals from reporter genes (e.g., firefly luminescence) are usually normalized to signals from constantly luminescing luciferases such as Renilla luciferase. This normalization step can be performed by modern luminometry devices automatically providing final results. Here we demonstrate paclitaxel to strikingly enhance Renilla luminescence, thereby potentially flawing results from reporter gene assays. In consequence, these data advocate for careful examination of raw data and militate against automatic data processing. Copyright © 2013 Elsevier Inc. All rights reserved.

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal

PubMed Central

Ramkumar, Barathram; Sabarimalai Manikandan, M.

2017-01-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal. PMID:28529758

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

PubMed

Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

2017-02-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

The application of charge-coupled device processors in automatic-control systems

NASA Technical Reports Server (NTRS)

Mcvey, E. S.; Parrish, E. A., Jr.

1977-01-01

The application of charge-coupled device (CCD) processors to automatic-control systems is suggested. CCD processors are a new form of semiconductor component with the unique ability to process sampled signals on an analog basis. Specific implementations of controllers are suggested for linear time-invariant, time-varying, and nonlinear systems. Typical processing time should be only a few microseconds. This form of technology may become competitive with microprocessors and minicomputers in addition to supplementing them.

Automatic humidification system to support the assessment of food drying processes

NASA Astrophysics Data System (ADS)

Ortiz Hernández, B. D.; Carreño Olejua, A. R.; Castellanos Olarte, J. M.

2016-07-01

This work shows the main features of an automatic humidification system to provide drying air that match environmental conditions of different climate zones. This conditioned air is then used to assess the drying process of different agro-industrial products at the Automation and Control for Agro-industrial Processes Laboratory of the Pontifical Bolivarian University of Bucaramanga, Colombia. The automatic system allows creating and improving control strategies to supply drying air under specified conditions of temperature and humidity. The development of automatic routines to control and acquire real time data was made possible by the use of robust control systems and suitable instrumentation. The signals are read and directed to a controller memory where they are scaled and transferred to a memory unit. Using the IP address is possible to access data to perform supervision tasks. One important characteristic of this automatic system is the Dynamic Data Exchange Server (DDE) to allow direct communication between the control unit and the computer used to build experimental curves.

TreSpEx—Detection of Misleading Signal in Phylogenetic Reconstructions Based on Tree Information

PubMed Central

Struck, Torsten H

2014-01-01

Phylogenies of species or genes are commonplace nowadays in many areas of comparative biological studies. However, for phylogenetic reconstructions one must refer to artificial signals such as paralogy, long-branch attraction, saturation, or conflict between different datasets. These signals might eventually mislead the reconstruction even in phylogenomic studies employing hundreds of genes. Unfortunately, there has been no program allowing the detection of such effects in combination with an implementation into automatic process pipelines. TreSpEx (Tree Space Explorer) now combines different approaches (including statistical tests), which utilize tree-based information like nodal support or patristic distances (PDs) to identify misleading signals. The program enables the parallel analysis of hundreds of trees and/or predefined gene partitions, and being command-line driven, it can be integrated into automatic process pipelines. TreSpEx is implemented in Perl and supported on Linux, Mac OS X, and MS Windows. Source code, binaries, and additional material are freely available at http://www.annelida.de/research/bioinformatics/software.html. PMID:24701118

49 CFR 236.824 - System, automatic block signal.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false System, automatic block signal. 236.824 Section..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.824 System, automatic block signal. A block signal system wherein the use of each block is...

49 CFR 236.824 - System, automatic block signal.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 4 2014-10-01 2014-10-01 false System, automatic block signal. 236.824 Section..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.824 System, automatic block signal. A block signal system wherein the use of each block is...

49 CFR 236.824 - System, automatic block signal.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 4 2013-10-01 2013-10-01 false System, automatic block signal. 236.824 Section..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.824 System, automatic block signal. A block signal system wherein the use of each block is...

Signal chain for the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

NASA Technical Reports Server (NTRS)

Bunn, James S., Jr.

1988-01-01

The AVIRIS instrument has a separate dedicated analog signal processing chain for each of its four spectrometers. The signal chains amplify low-level focal-plane line array signals (5 to 10 mV full-scale span) in the presence of larger multiplexing signals (approx 150 mV) providing the data handling system a ten-bit digital word (for each spectrometer) each 1.3 microns. This signal chain provides automatic correction for the line array dark signal nonuniformity (which can approach the full-scale signal span).

Signal chain for the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

NASA Technical Reports Server (NTRS)

Bunn, James S., Jr.

1987-01-01

The AVIRIS instrument has a separate dedicated analog signal processing chain for each of its four spectrometers. The signal chains amplify low-level focal-plane line array signals (5 to 10 mV full-scale span) in the presence of larger multiplexing signals (approx 150 mV) providing the data handling system a ten-bit digital word (for each spectrometer) each 1.3 microns. This signal chain provides automatic correction for the line array dark signal nonuniformity (which can approach the full-scale signal span).

A temporal dissociation of subliminal versus supraliminal fear perception: an event-related potential study.

PubMed

Liddell, Belinda J; Williams, Leanne M; Rathjen, Jennifer; Shevrin, Howard; Gordon, Evian

2004-04-01

Current theories of emotion suggest that threat-related stimuli are first processed via an automatically engaged neural mechanism, which occurs outside conscious awareness. This mechanism operates in conjunction with a slower and more comprehensive process that allows a detailed evaluation of the potentially harmful stimulus (LeDoux, 1998). We drew on the Halgren and Marinkovic (1995) model to examine these processes using event-related potentials (ERPs) within a backward masking paradigm. Stimuli used were faces with fear and neutral (as baseline control) expressions, presented above (supraliminal) and below (subliminal) the threshold for conscious detection. ERP data revealed a double dissociation for the supraliminal versus subliminal perception of fear. In the subliminal condition, responses to the perception of fear stimuli were enhanced relative to neutral for the N2 "excitatory" component, which is thought to represent orienting and automatic aspects of face processing. By contrast, supraliminal perception of fear was associated with relatively enhanced responses for the late P3 "inhibitory" component, implicated in the integration of emotional processes. These findings provide evidence in support of Halgren and Marinkovic's temporal model of emotion processing, and indicate that the neural mechanisms for appraising signals of threat may be initiated, not only automatically, but also without the need for conscious detection of these signals.

Towards Automatic Classification of Exoplanet-Transit-Like Signals: A Case Study on Kepler Mission Data

NASA Astrophysics Data System (ADS)

Valizadegan, Hamed; Martin, Rodney; McCauliff, Sean D.; Jenkins, Jon Michael; Catanzarite, Joseph; Oza, Nikunj C.

2015-08-01

Building new catalogues of planetary candidates, astrophysical false alarms, and non-transiting phenomena is a challenging task that currently requires a reviewing team of astrophysicists and astronomers. These scientists need to examine more than 100 diagnostic metrics and associated graphics for each candidate exoplanet-transit-like signal to classify it into one of the three classes. Considering that the NASA Explorer Program's TESS mission and ESA's PLATO mission survey even a larger area of space, the classification of their transit-like signals is more time-consuming for human agents and a bottleneck to successfully construct the new catalogues in a timely manner. This encourages building automatic classification tools that can quickly and reliably classify the new signal data from these missions. The standard tool for building automatic classification systems is the supervised machine learning that requires a large set of highly accurate labeled examples in order to build an effective classifier. This requirement cannot be easily met for classifying transit-like signals because not only are existing labeled signals very limited, but also the current labels may not be reliable (because the labeling process is a subjective task). Our experiments with using different supervised classifiers to categorize transit-like signals verifies that the labeled signals are not rich enough to provide the classifier with enough power to generalize well beyond the observed cases (e.g. to unseen or test signals). That motivated us to utilize a new category of learning techniques, so-called semi-supervised learning, that combines the label information from the costly labeled signals, and distribution information from the cheaply available unlabeled signals in order to construct more effective classifiers. Our study on the Kepler Mission data shows that semi-supervised learning can significantly improve the result of multiple base classifiers (e.g. Support Vector Machines, AdaBoost, and Decision Tree) and is a good technique for automatic classification of exoplanet-transit-like signal.

49 CFR 236.504 - Operation interconnected with automatic block-signal system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.504... or train control system shall operate in connection with an automatic block signal system and shall...

49 CFR 235.5 - Changes requiring filing of application.

Code of Federal Regulations, 2010 CFR

2010-10-01

... system, automatic train stop, train control, or cab signal system or other similar appliance or device..., automatic train stop, train control, or cab signal system; or (3) The modification of a block signal system, interlocking, traffic control system, automatic train stop, train control, or cab signal system. (b) [Reserved...

49 CFR 235.5 - Changes requiring filing of application.

Code of Federal Regulations, 2011 CFR

2011-10-01

... system, automatic train stop, train control, or cab signal system or other similar appliance or device..., automatic train stop, train control, or cab signal system; or (3) The modification of a block signal system, interlocking, traffic control system, automatic train stop, train control, or cab signal system. (b) [Reserved...

Automatic quality assessment and peak identification of auditory brainstem responses with fitted parametric peaks.

PubMed

Valderrama, Joaquin T; de la Torre, Angel; Alvarez, Isaac; Segura, Jose Carlos; Thornton, A Roger D; Sainz, Manuel; Vargas, Jose Luis

2014-05-01

The recording of the auditory brainstem response (ABR) is used worldwide for hearing screening purposes. In this process, a precise estimation of the most relevant components is essential for an accurate interpretation of these signals. This evaluation is usually carried out subjectively by an audiologist. However, the use of automatic methods for this purpose is being encouraged nowadays in order to reduce human evaluation biases and ensure uniformity among test conditions, patients, and screening personnel. This article describes a new method that performs automatic quality assessment and identification of the peaks, the fitted parametric peaks (FPP). This method is based on the use of synthesized peaks that are adjusted to the ABR response. The FPP is validated, on one hand, by an analysis of amplitudes and latencies measured manually by an audiologist and automatically by the FPP method in ABR signals recorded at different stimulation rates; and on the other hand, contrasting the performance of the FPP method with the automatic evaluation techniques based on the correlation coefficient, FSP, and cross correlation with a predefined template waveform by comparing the automatic evaluations of the quality of these methods with subjective evaluations provided by five experienced evaluators on a set of ABR signals of different quality. The results of this study suggest (a) that the FPP method can be used to provide an accurate parameterization of the peaks in terms of amplitude, latency, and width, and (b) that the FPP remains as the method that best approaches the averaged subjective quality evaluation, as well as provides the best results in terms of sensitivity and specificity in ABR signals validation. The significance of these findings and the clinical value of the FPP method are highlighted on this paper. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Intended actions and unexpected outcomes: automatic and controlled processing in a rapid motor task

PubMed Central

Cheyne, Douglas O.; Ferrari, Paul; Cheyne, James A.

2012-01-01

Human action involves a combination of controlled and automatic behavior. These processes may interact in tasks requiring rapid response selection or inhibition, where temporal constraints preclude timely intervention by conscious, controlled processes over automatized prepotent responses. Such contexts tend to produce frequent errors, but also rapidly executed correct responses, both of which may sometimes be perceived as surprising, unintended, or “automatic”. In order to identify neural processes underlying these two aspects of cognitive control, we measured neuromagnetic brain activity in 12 right-handed subjects during manual responses to rapidly presented digits, with an infrequent target digit that required switching response hand (bimanual task) or response finger (unimanual task). Automaticity of responding was evidenced by response speeding (shorter response times) prior to both failed and fast correct switches. Consistent with this automaticity interpretation of fast correct switches, we observed bilateral motor preparation, as indexed by suppression of beta band (15–30 Hz) oscillations in motor cortex, prior to processing of the switch cue in the bimanual task. In contrast, right frontal theta activity (4–8 Hz) accompanying correct switch responses began after cue onset, suggesting that it reflected controlled inhibition of the default response. Further, this activity was reduced on fast correct switch trials suggesting a more automatic mode of inhibitory control. We also observed post-movement (event-related negativity) ERN-like responses and theta band increases in medial and anterior frontal regions that were significantly larger on error trials, and may reflect a combination of error and delayed inhibitory signals. We conclude that both automatic and controlled processes are engaged in parallel during rapid motor tasks, and that the relative strength and timing of these processes may underlie both optimal task performance and subjective experiences of automaticity or control. PMID:22912612

Do the Contents of Visual Working Memory Automatically Influence Attentional Selection During Visual Search?

PubMed Central

Woodman, Geoffrey F.; Luck, Steven J.

2007-01-01

In many theories of cognition, researchers propose that working memory and perception operate interactively. For example, in previous studies researchers have suggested that sensory inputs matching the contents of working memory will have an automatic advantage in the competition for processing resources. The authors tested this hypothesis by requiring observers to perform a visual search task while concurrently maintaining object representations in visual working memory. The hypothesis that working memory activation produces a simple but uncontrollable bias signal leads to the prediction that items matching the contents of working memory will automatically capture attention. However, no evidence for automatic attentional capture was obtained; instead, the participants avoided attending to these items. Thus, the contents of working memory can be used in a flexible manner for facilitation or inhibition of processing. PMID:17469973

Do the contents of visual working memory automatically influence attentional selection during visual search?

PubMed

Woodman, Geoffrey F; Luck, Steven J

2007-04-01

In many theories of cognition, researchers propose that working memory and perception operate interactively. For example, in previous studies researchers have suggested that sensory inputs matching the contents of working memory will have an automatic advantage in the competition for processing resources. The authors tested this hypothesis by requiring observers to perform a visual search task while concurrently maintaining object representations in visual working memory. The hypothesis that working memory activation produces a simple but uncontrollable bias signal leads to the prediction that items matching the contents of working memory will automatically capture attention. However, no evidence for automatic attentional capture was obtained; instead, the participants avoided attending to these items. Thus, the contents of working memory can be used in a flexible manner for facilitation or inhibition of processing.

Linking Automatic Evaluation to Mood and Information Processing Style: Consequences for Experienced Affect, Impression Formation, and Stereotyping

ERIC Educational Resources Information Center

Chartrand, Tanya L.; van Baaren, Rick B.; Bargh, John A.

2006-01-01

According to the feelings-as-information account, a person's mood state signals to him or her the valence of the current environment (N. Schwarz & G. Clore, 1983). However, the ways in which the environment automatically influences mood in the first place remain to be explored. The authors propose that one mechanism by which the environment…

Phase editing as a signal pre-processing step for automated bearing fault detection

NASA Astrophysics Data System (ADS)

Barbini, L.; Ompusunggu, A. P.; Hillis, A. J.; du Bois, J. L.; Bartic, A.

2017-07-01

Scheduled maintenance and inspection of bearing elements in industrial machinery contributes significantly to the operating costs. Savings can be made through automatic vibration-based damage detection and prognostics, to permit condition-based maintenance. However automation of the detection process is difficult due to the complexity of vibration signals in realistic operating environments. The sensitivity of existing methods to the choice of parameters imposes a requirement for oversight from a skilled operator. This paper presents a novel approach to the removal of unwanted vibrational components from the signal: phase editing. The approach uses a computationally-efficient full-band demodulation and requires very little oversight. Its effectiveness is tested on experimental data sets from three different test-rigs, and comparisons are made with two state-of-the-art processing techniques: spectral kurtosis and cepstral pre- whitening. The results from the phase editing technique show a 10% improvement in damage detection rates compared to the state-of-the-art while simultaneously improving on the degree of automation. This outcome represents a significant contribution in the pursuit of fully automatic fault detection.

Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

NASA Astrophysics Data System (ADS)

Winda, A.; Sofyan; Sthevany; Vincent, R. S.

2017-12-01

Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

Social Media Mining for Toxicovigilance: Automatic Monitoring of Prescription Medication Abuse from Twitter.

PubMed

Sarker, Abeed; O'Connor, Karen; Ginn, Rachel; Scotch, Matthew; Smith, Karen; Malone, Dan; Gonzalez, Graciela

2016-03-01

Prescription medication overdose is the fastest growing drug-related problem in the USA. The growing nature of this problem necessitates the implementation of improved monitoring strategies for investigating the prevalence and patterns of abuse of specific medications. Our primary aims were to assess the possibility of utilizing social media as a resource for automatic monitoring of prescription medication abuse and to devise an automatic classification technique that can identify potentially abuse-indicating user posts. We collected Twitter user posts (tweets) associated with three commonly abused medications (Adderall(®), oxycodone, and quetiapine). We manually annotated 6400 tweets mentioning these three medications and a control medication (metformin) that is not the subject of abuse due to its mechanism of action. We performed quantitative and qualitative analyses of the annotated data to determine whether posts on Twitter contain signals of prescription medication abuse. Finally, we designed an automatic supervised classification technique to distinguish posts containing signals of medication abuse from those that do not and assessed the utility of Twitter in investigating patterns of abuse over time. Our analyses show that clear signals of medication abuse can be drawn from Twitter posts and the percentage of tweets containing abuse signals are significantly higher for the three case medications (Adderall(®): 23 %, quetiapine: 5.0 %, oxycodone: 12 %) than the proportion for the control medication (metformin: 0.3 %). Our automatic classification approach achieves 82 % accuracy overall (medication abuse class recall: 0.51, precision: 0.41, F measure: 0.46). To illustrate the utility of automatic classification, we show how the classification data can be used to analyze abuse patterns over time. Our study indicates that social media can be a crucial resource for obtaining abuse-related information for medications, and that automatic approaches involving supervised classification and natural language processing hold promises for essential future monitoring and intervention tasks.

A Comparison of Physiological Signal Analysis Techniques and Classifiers for Automatic Emotional Evaluation of Audiovisual Contents

PubMed Central

Colomer Granero, Adrián; Fuentes-Hurtado, Félix; Naranjo Ornedo, Valery; Guixeres Provinciale, Jaime; Ausín, Jose M.; Alcañiz Raya, Mariano

2016-01-01

This work focuses on finding the most discriminatory or representative features that allow to classify commercials according to negative, neutral and positive effectiveness based on the Ace Score index. For this purpose, an experiment involving forty-seven participants was carried out. In this experiment electroencephalography (EEG), electrocardiography (ECG), Galvanic Skin Response (GSR) and respiration data were acquired while subjects were watching a 30-min audiovisual content. This content was composed by a submarine documentary and nine commercials (one of them the ad under evaluation). After the signal pre-processing, four sets of features were extracted from the physiological signals using different state-of-the-art metrics. These features computed in time and frequency domains are the inputs to several basic and advanced classifiers. An average of 89.76% of the instances was correctly classified according to the Ace Score index. The best results were obtained by a classifier consisting of a combination between AdaBoost and Random Forest with automatic selection of features. The selected features were those extracted from GSR and HRV signals. These results are promising in the audiovisual content evaluation field by means of physiological signal processing. PMID:27471462

A Comparison of Physiological Signal Analysis Techniques and Classifiers for Automatic Emotional Evaluation of Audiovisual Contents.

PubMed

Colomer Granero, Adrián; Fuentes-Hurtado, Félix; Naranjo Ornedo, Valery; Guixeres Provinciale, Jaime; Ausín, Jose M; Alcañiz Raya, Mariano

2016-01-01

This work focuses on finding the most discriminatory or representative features that allow to classify commercials according to negative, neutral and positive effectiveness based on the Ace Score index. For this purpose, an experiment involving forty-seven participants was carried out. In this experiment electroencephalography (EEG), electrocardiography (ECG), Galvanic Skin Response (GSR) and respiration data were acquired while subjects were watching a 30-min audiovisual content. This content was composed by a submarine documentary and nine commercials (one of them the ad under evaluation). After the signal pre-processing, four sets of features were extracted from the physiological signals using different state-of-the-art metrics. These features computed in time and frequency domains are the inputs to several basic and advanced classifiers. An average of 89.76% of the instances was correctly classified according to the Ace Score index. The best results were obtained by a classifier consisting of a combination between AdaBoost and Random Forest with automatic selection of features. The selected features were those extracted from GSR and HRV signals. These results are promising in the audiovisual content evaluation field by means of physiological signal processing.

Progresses with Net-VISA on Global Infrasound Association

NASA Astrophysics Data System (ADS)

Mialle, Pierrick; Arora, Nimar

2017-04-01

Global Infrasound Association algorithms are an important area of active development at the International Data Centre (IDC). These algorithms play an important part of the automatic processing system for verification technologies. A key focus at the IDC is to enhance association and signal characterization methods by incorporating the identification of signals of interest and the optimization of the network detection threshold. The overall objective is to reduce the number of associated infrasound arrivals that are rejected from the automatic bulletins when generating the Reviewed Event Bulletins (REB), and hence reduce IDC analyst workload. Despite good accuracy by the IDC categorization, a number of signal detections due to clutter sources such as microbaroms or surf are built into events. In this work we aim to optimize the association criteria based on knowledge acquired by IDC in the last 6 years, and focus on the specificity of seismo-acoustic events. The resulting work has been incorporated into NETVISA [1], a Bayesian approach to network processing. The model that we propose is a fusion of seismic, hydroacoustic and infrasound processing built on a unified probabilistic framework. References: [1] NETVISA: Network Processing Vertically Integrated Seismic Analysis. N. S. Arora, S. Russell, and E. Sudderth. BSSA 2013

Progresses with Net-VISA on Global Infrasound Association

NASA Astrophysics Data System (ADS)

Mialle, P.; Arora, N. S.

2016-12-01

Global Infrasound Association algorithms are an important area of active development at the International Data Centre (IDC). These algorithms play an important part of the automatic processing system for verification technologies. A key focus at the IDC is to enhance association and signal characterization methods by incorporating the identification of signals of interest and the optimization of the network detection threshold. The overall objective is to reduce the number of associated infrasound arrivals that are rejected from the automatic bulletins when generating the Reviewed Event Bulletins (REB), and hence reduce IDC analyst workload. Despite good accuracy by the IDC categorization, a number of signal detections due to clutter sources such as microbaroms or surf are built into events. In this work we aim to optimize the association criteria based on knowledge acquired by IDC in the last 6 years, and focus on the specificity of seismo-acoustic events. The resulting work has been incorporated into NETVISA [1], a Bayesian approach to network processing. The model that we propose is a fusion of seismic, hydroacoustic and infrasound processing built on a unified probabilistic framework. References: [1] NETVISA: Network Processing Vertically Integrated Seismic Analysis. N. S. Arora, S. Russell, and E. Sudderth. BSSA 2013

Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

NASA Technical Reports Server (NTRS)

Jong, Jen-Yi

1997-01-01

During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

Automatic sleep stage classification based on EEG signals by using neural networks and wavelet packet coefficients.

PubMed

Ebrahimi, Farideh; Mikaeili, Mohammad; Estrada, Edson; Nazeran, Homer

2008-01-01

Currently in the world there is an alarming number of people who suffer from sleep disorders. A number of biomedical signals, such as EEG, EMG, ECG and EOG are used in sleep labs among others for diagnosis and treatment of sleep related disorders. The usual method for sleep stage classification is visual inspection by a sleep specialist. This is a very time consuming and laborious exercise. Automatic sleep stage classification can facilitate this process. The definition of sleep stages and the sleep literature show that EEG signals are similar in Stage 1 of non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep. Therefore, in this work an attempt was made to classify four sleep stages consisting of Awake, Stage 1 + REM, Stage 2 and Slow Wave Stage based on the EEG signal alone. Wavelet packet coefficients and artificial neural networks were deployed for this purpose. Seven all night recordings from Physionet database were used in the study. The results demonstrated that these four sleep stages could be automatically discriminated from each other with a specificity of 94.4 +/- 4.5%, a of sensitivity 84.2+3.9% and an accuracy of 93.0 +/- 4.0%.

Global Infrasound Association Based on Probabilistic Clutter Categorization

NASA Astrophysics Data System (ADS)

Arora, Nimar; Mialle, Pierrick

2016-04-01

The IDC advances its methods and continuously improves its automatic system for the infrasound technology. The IDC focuses on enhancing the automatic system for the identification of valid signals and the optimization of the network detection threshold by identifying ways to refine signal characterization methodology and association criteria. An objective of this study is to reduce the number of associated infrasound arrivals that are rejected from the automatic bulletins when generating the reviewed event bulletins. Indeed, a considerable number of signal detections are due to local clutter sources such as microbaroms, waterfalls, dams, gas flares, surf (ocean breaking waves) etc. These sources are either too diffuse or too local to form events. Worse still, the repetitive nature of this clutter leads to a large number of false event hypotheses due to the random matching of clutter at multiple stations. Previous studies, for example [1], have worked on categorization of clutter using long term trends on detection azimuth, frequency, and amplitude at each station. In this work we continue the same line of reasoning to build a probabilistic model of clutter that is used as part of NETVISA [2], a Bayesian approach to network processing. The resulting model is a fusion of seismic, hydroacoustic and infrasound processing built on a unified probabilistic framework. References: [1] Infrasound categorization Towards a statistics based approach. J. Vergoz, P. Gaillard, A. Le Pichon, N. Brachet, and L. Ceranna. ITW 2011 [2] NETVISA: Network Processing Vertically Integrated Seismic Analysis. N. S. Arora, S. Russell, and E. Sudderth. BSSA 2013

49 CFR 236.514 - Interconnection of cab signal system with roadway signal system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.514 Interconnection of cab signal system with roadway signal system. The automatic cab signal system shall be...

Design and Characterization of a Secure Automatic Dependent Surveillance-Broadcast Prototype

DTIC Science & Technology

2015-03-26

during the thesis process. Thank you to Mr. Dave Prentice of AFRL for providing the Aeroflex IFR 6000 baseband signals, upon which many design decisions...35 25 Example Aeroflex IFR 6000 signal. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 26...Global Positioning System HDL hardware description language I in-phase IFR Instrument Flight Rules IP Internet Protocol IP intellectual property IPSec

Feature Visibility Limits in the Non-Linear Enhancement of Turbid Images

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.; Rahman, Zia-ur; Woodell, Glenn A.

2003-01-01

The advancement of non-linear processing methods for generic automatic clarification of turbid imagery has led us from extensions of entirely passive multiscale Retinex processing to a new framework of active measurement and control of the enhancement process called the Visual Servo. In the process of testing this new non-linear computational scheme, we have identified that feature visibility limits in the post-enhancement image now simplify to a single signal-to-noise figure of merit: a feature is visible if the feature-background signal difference is greater than the RMS noise level. In other words, a signal-to-noise limit of approximately unity constitutes a lower limit on feature visibility.

49 CFR 236.506 - Release of brakes after automatic application.

Code of Federal Regulations, 2010 CFR

2010-10-01

... INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.506 Release of brakes after automatic application. The automatic train stop or train control apparatus shall prevent release of the...

49 CFR 236.506 - Release of brakes after automatic application.

Code of Federal Regulations, 2011 CFR

2011-10-01

... INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.506 Release of brakes after automatic application. The automatic train stop or train control apparatus shall prevent release of the...

Optimization and automation of quantitative NMR data extraction.

PubMed

Bernstein, Michael A; Sýkora, Stan; Peng, Chen; Barba, Agustín; Cobas, Carlos

2013-06-18

NMR is routinely used to quantitate chemical species. The necessary experimental procedures to acquire quantitative data are well-known, but relatively little attention has been applied to data processing and analysis. We describe here a robust expert system that can be used to automatically choose the best signals in a sample for overall concentration determination and determine analyte concentration using all accepted methods. The algorithm is based on the complete deconvolution of the spectrum which makes it tolerant of cases where signals are very close to one another and includes robust methods for the automatic classification of NMR resonances and molecule-to-spectrum multiplets assignments. With the functionality in place and optimized, it is then a relatively simple matter to apply the same workflow to data in a fully automatic way. The procedure is desirable for both its inherent performance and applicability to NMR data acquired for very large sample sets.

Capture versus suppression of attention by salient singletons: electrophysiological evidence for an automatic attend-to-me signal.

PubMed

Sawaki, Risa; Luck, Steven J

2010-08-01

There is considerable controversy about whether salient singletons capture attention in a bottom-up fashion, irrespective of top-down control settings. One possibility is that salient singletons always generate an attention capture signal, but this signal can be actively suppressed to avoid capture. In the present study, we investigated this issue by using event-related potential recordings, focusing on N2pc (N2-posterior-contralateral; a measure of attentional deployment) and Pd (distractor positivity; a measure of attentional suppression). Participants searched for a specific letter within one of two regions, and irrelevant color singletons were sometimes present. We found that the irrelevant singletons did not elicit N2pc but instead elicited Pd; this occurred equally within the attended and unattended regions. These findings suggest that salient singletons may automatically produce an attend-to-me signal, irrespective of top-down control settings, but this signal can be overridden by an active suppression process to prevent the actual capture of attention.

The Future of Biofeedback Training in the Field of Special Education.

ERIC Educational Resources Information Center

Walton, Wilbur T.

Biofeedback training (a process of feeding back to an organism information pertaining to its physiological functions using signals transmitted through sensory receptors) stands as one method to better educate and treat handicapped children. Recent research establishes that it is possible to influence automatic processes (such as breathing)…

49 CFR 236.502 - Automatic brake application, initiation by restrictive block conditions stopping distance in...

Code of Federal Regulations, 2011 CFR

2011-10-01

... OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.502 Automatic brake application, initiation by restrictive block conditions stopping distance in advance. An automatic train-stop or train-control system shall operate to...

Automatic mine detection based on multiple features

NASA Astrophysics Data System (ADS)

Yu, Ssu-Hsin; Gandhe, Avinash; Witten, Thomas R.; Mehra, Raman K.

2000-08-01

Recent research sponsored by the Army, Navy and DARPA has significantly advanced the sensor technologies for mine detection. Several innovative sensor systems have been developed and prototypes were built to investigate their performance in practice. Most of the research has been focused on hardware design. However, in order for the systems to be in wide use instead of in limited use by a small group of well-trained experts, an automatic process for mine detection is needed to make the final decision process on mine vs. no mine easier and more straightforward. In this paper, we describe an automatic mine detection process consisting of three stage, (1) signal enhancement, (2) pixel-level mine detection, and (3) object-level mine detection. The final output of the system is a confidence measure that quantifies the presence of a mine. The resulting system was applied to real data collected using radar and acoustic technologies.

Fuzzy Logic-Based Audio Pattern Recognition

NASA Astrophysics Data System (ADS)

Malcangi, M.

2008-11-01

Audio and audio-pattern recognition is becoming one of the most important technologies to automatically control embedded systems. Fuzzy logic may be the most important enabling methodology due to its ability to rapidly and economically model such application. An audio and audio-pattern recognition engine based on fuzzy logic has been developed for use in very low-cost and deeply embedded systems to automate human-to-machine and machine-to-machine interaction. This engine consists of simple digital signal-processing algorithms for feature extraction and normalization, and a set of pattern-recognition rules manually tuned or automatically tuned by a self-learning process.

Multichannel temperature controller for hot air solar house

NASA Technical Reports Server (NTRS)

Currie, J. R.

1979-01-01

This paper describes an electronic controller that is optimized to operate a hot air solar system. Thermal information is obtained from copper constantan thermocouples and a wall-type thermostat. The signals from the thermocouples are processed through a single amplifier using a multiplexing scheme. The multiplexing reduces the component count and automatically calibrates the thermocouple amplifier. The processed signals connect to some simple logic that selects one of the four operating modes. This simple, inexpensive, and reliable scheme is well suited to control hot air solar systems.

49 CFR 236.511 - Cab signals controlled in accordance with block conditions stopping distance in advance.

Code of Federal Regulations, 2011 CFR

2011-10-01

... INSTRUCTIONS GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards... automatic cab signal system shall be arranged so that cab signals will be continuously controlled in...

The laboratory demonstration and signal processing of the inverse synthetic aperture imaging ladar

NASA Astrophysics Data System (ADS)

Gao, Si; Zhang, ZengHui; Xu, XianWen; Yu, WenXian

2017-10-01

This paper presents a coherent inverse synthetic-aperture imaging ladar(ISAL)system to obtain high resolution images. A balanced coherent optics system in laboratory is built with binary phase coded modulation transmit waveform which is different from conventional chirp. A whole digital signal processing solution is proposed including both quality phase gradient autofocus(QPGA) algorithm and cubic phase function(CPF) algorithm. Some high-resolution well-focused ISAL images of retro-reflecting targets are shown to validate the concepts. It is shown that high resolution images can be achieved and the influences from vibrations of platform involving targets and radar can be automatically compensated by the distinctive laboratory system and digital signal process.

[Wearable Automatic External Defibrillators].

PubMed

Luo, Huajie; Luo, Zhangyuan; Jin, Xun; Zhang, Leilei; Wang, Changjin; Zhang, Wenzan; Tu, Quan

2015-11-01

Defibrillation is the most effective method of treating ventricular fibrillation(VF), this paper introduces wearable automatic external defibrillators based on embedded system which includes EGG measurements, bioelectrical impedance measurement, discharge defibrillation module, which can automatic identify VF signal, biphasic exponential waveform defibrillation discharge. After verified by animal tests, the device can realize EGG acquisition and automatic identification. After identifying the ventricular fibrillation signal, it can automatic defibrillate to abort ventricular fibrillation and to realize the cardiac electrical cardioversion.

Semi-automatic, octave-spanning optical frequency counter.

PubMed

Liu, Tze-An; Shu, Ren-Huei; Peng, Jin-Long

2008-07-07

This work presents and demonstrates a semi-automatic optical frequency counter with octave-spanning counting capability using two fiber laser combs operated at different repetition rates. Monochromators are utilized to provide an approximate frequency of the laser under measurement to determine the mode number difference between the two laser combs. The exact mode number of the beating comb line is obtained from the mode number difference and the measured beat frequencies. The entire measurement process, except the frequency stabilization of the laser combs and the optimization of the beat signal-to-noise ratio, is controlled by a computer running a semi-automatic optical frequency counter.

Automatic Processing and Interpretation of Long Records of Endogenous Micro-Seismicity: the Case of the Super-Sauze Soft-Rock Landslide.

NASA Astrophysics Data System (ADS)

Provost, F.; Malet, J. P.; Hibert, C.; Doubre, C.

2017-12-01

The Super-Sauze landslide is a clay-rich landslide located the Southern French Alps. The landslide exhibits a complex pattern of deformation: a large number of rockfalls are observed in the 100 m height main scarp while the deformation of the upper part of the accumulated material is mainly affected by material shearing along stable in-situ crests. Several fissures are locally observed. The shallowest layer of the accumulated material tends to behave in a brittle manner but may undergo fluidization and/or rapid acceleration. Previous studies have demonstrated the presence of a rich endogenous micro-seismicity associated to the deformation of the landslide. However, the lack of long-term seismic records and suitable processing chains prevented a full interpretation of the links between the external forcings, the deformation and the recorded seismic signals. Since 2013, two permanent seismic arrays are installed in the upper part of the landslide. We here present the methodology adopted to process this dataset. The processing chain consists of a set of automated methods for automatic and robust detection, classification and location of the recorded seismicity. Thousands of events are detected and further automatically classified. The classification method is based on the description of the signal through attributes (e.g. waveform, spectral content properties). These attributes are used as inputs to classify the signal using a Random Forest machine-learning algorithm in four classes: endogenous micro-quakes, rockfalls, regional earthquakes and natural/anthropogenic noises. The endogenous landslide sources (i.e. micro-quake and rockfall) are further located. The location method is adapted to the type of event. The micro-quakes are located with a 3D velocity model derived from a seismic tomography campaign and an optimization of the first arrival picking with the inter-trace correlation of the P-wave arrivals. The rockfalls are located by optimizing the inter-trace correlation of the whole signal. We analyze the temporal relationships of the endogenous seismic events with rainfall and landslide displacements. Sub-families of landslide micro-quakes are also identified and an interpretation of their source mechanism is proposed from their signal properties and spatial location.

Alsep data processing: How we processed Apollo Lunar Seismic Data

NASA Technical Reports Server (NTRS)

Latham, G. V.; Nakamura, Y.; Dorman, H. J.

1979-01-01

The Apollo lunar seismic station network gathered data continuously at a rate of 3 x 10 to the 8th power bits per day for nearly eight years until the termination in September, 1977. The data were processed and analyzed using a PDP-15 minicomputer. On the average, 1500 long-period seismic events were detected yearly. Automatic event detection and identification schemes proved unsuccessful because of occasional high noise levels and, above all, the risk of overlooking unusual natural events. The processing procedures finally settled on consist of first plotting all the data on a compressed time scale, visually picking events from the plots, transferring event data to separate sets of tapes and performing detailed analyses using the latter. Many problems remain especially for automatically processing extraterrestrial seismic signals.

Automatic classification of seismic events within a regional seismograph network

NASA Astrophysics Data System (ADS)

Tiira, Timo; Kortström, Jari; Uski, Marja

2015-04-01

A fully automatic method for seismic event classification within a sparse regional seismograph network is presented. The tool is based on a supervised pattern recognition technique, Support Vector Machine (SVM), trained here to distinguish weak local earthquakes from a bulk of human-made or spurious seismic events. The classification rules rely on differences in signal energy distribution between natural and artificial seismic sources. Seismic records are divided into four windows, P, P coda, S, and S coda. For each signal window STA is computed in 20 narrow frequency bands between 1 and 41 Hz. The 80 discrimination parameters are used as a training data for the SVM. The SVM models are calculated for 19 on-line seismic stations in Finland. The event data are compiled mainly from fully automatic event solutions that are manually classified after automatic location process. The station-specific SVM training events include 11-302 positive (earthquake) and 227-1048 negative (non-earthquake) examples. The best voting rules for combining results from different stations are determined during an independent testing period. Finally, the network processing rules are applied to an independent evaluation period comprising 4681 fully automatic event determinations, of which 98 % have been manually identified as explosions or noise and 2 % as earthquakes. The SVM method correctly identifies 94 % of the non-earthquakes and all the earthquakes. The results imply that the SVM tool can identify and filter out blasts and spurious events from fully automatic event solutions with a high level of confidence. The tool helps to reduce work-load in manual seismic analysis by leaving only ~5 % of the automatic event determinations, i.e. the probable earthquakes for more detailed seismological analysis. The approach presented is easy to adjust to requirements of a denser or wider high-frequency network, once enough training examples for building a station-specific data set are available.

The sequentially discounting autoregressive (SDAR) method for on-line automatic seismic event detecting on long term observation

NASA Astrophysics Data System (ADS)

Wang, L.; Toshioka, T.; Nakajima, T.; Narita, A.; Xue, Z.

2017-12-01

In recent years, more and more Carbon Capture and Storage (CCS) studies focus on seismicity monitoring. For the safety management of geological CO2 storage at Tomakomai, Hokkaido, Japan, an Advanced Traffic Light System (ATLS) combined different seismic messages (magnitudes, phases, distributions et al.) is proposed for injection controlling. The primary task for ATLS is the seismic events detection in a long-term sustained time series record. Considering the time-varying characteristics of Signal to Noise Ratio (SNR) of a long-term record and the uneven energy distributions of seismic event waveforms will increase the difficulty in automatic seismic detecting, in this work, an improved probability autoregressive (AR) method for automatic seismic event detecting is applied. This algorithm, called sequentially discounting AR learning (SDAR), can identify the effective seismic event in the time series through the Change Point detection (CPD) of the seismic record. In this method, an anomaly signal (seismic event) can be designed as a change point on the time series (seismic record). The statistical model of the signal in the neighborhood of event point will change, because of the seismic event occurrence. This means the SDAR aims to find the statistical irregularities of the record thought CPD. There are 3 advantages of SDAR. 1. Anti-noise ability. The SDAR does not use waveform messages (such as amplitude, energy, polarization) for signal detecting. Therefore, it is an appropriate technique for low SNR data. 2. Real-time estimation. When new data appears in the record, the probability distribution models can be automatic updated by SDAR for on-line processing. 3. Discounting property. the SDAR introduces a discounting parameter to decrease the influence of present statistic value on future data. It makes SDAR as a robust algorithm for non-stationary signal processing. Within these 3 advantages, the SDAR method can handle the non-stationary time-varying long-term series and achieve real-time monitoring. Finally, we employ the SDAR on a synthetic model and Tomakomai Ocean Bottom Cable (OBC) baseline data to prove the feasibility and advantage of our method.

An adaptive spatio-temporal Gaussian filter for processing cardiac optical mapping data.

PubMed

Pollnow, S; Pilia, N; Schwaderlapp, G; Loewe, A; Dössel, O; Lenis, G

2018-06-04

Optical mapping is widely used as a tool to investigate cardiac electrophysiology in ex vivo preparations. Digital filtering of fluorescence-optical data is an important requirement for robust subsequent data analysis and still a challenge when processing data acquired from thin mammalian myocardium. Therefore, we propose and investigate the use of an adaptive spatio-temporal Gaussian filter for processing optical mapping signals from these kinds of tissue usually having low signal-to-noise ratio (SNR). We demonstrate how filtering parameters can be chosen automatically without additional user input. For systematic comparison of this filter with standard filtering methods from the literature, we generated synthetic signals representing optical recordings from atrial myocardium of a rat heart with varying SNR. Furthermore, all filter methods were applied to experimental data from an ex vivo setup. Our developed filter outperformed the other filter methods regarding local activation time detection at SNRs smaller than 3 dB which are typical noise ratios expected in these signals. At higher SNRs, the proposed filter performed slightly worse than the methods from literature. In conclusion, the proposed adaptive spatio-temporal Gaussian filter is an appropriate tool for investigating fluorescence-optical data with low SNR. The spatio-temporal filter parameters were automatically adapted in contrast to the other investigated filters. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

Automatic detection of slight parameter changes associated to complex biomedical signals using multiresolution q-entropy1.

PubMed

Torres, M E; Añino, M M; Schlotthauer, G

2003-12-01

It is well known that, from a dynamical point of view, sudden variations in physiological parameters which govern certain diseases can cause qualitative changes in the dynamics of the corresponding physiological process. The purpose of this paper is to introduce a technique that allows the automated temporal localization of slight changes in a parameter of the law that governs the nonlinear dynamics of a given signal. This tool takes, from the multiresolution entropies, the ability to show these changes as statistical variations at each scale. These variations are held in the corresponding principal component. Appropriately combining these techniques with a statistical changes detector, a complexity change detection algorithm is obtained. The relevance of the approach, together with its robustness in the presence of moderate noise, is discussed in numerical simulations and the automatic detector is applied to real and simulated biological signals.

Automatic welding detection by an intelligent tool pipe inspection

NASA Astrophysics Data System (ADS)

Arizmendi, C. J.; Garcia, W. L.; Quintero, M. A.

2015-07-01

This work provide a model based on machine learning techniques in welds recognition, based on signals obtained through in-line inspection tool called “smart pig” in Oil and Gas pipelines. The model uses a signal noise reduction phase by means of pre-processing algorithms and attribute-selection techniques. The noise reduction techniques were selected after a literature review and testing with survey data. Subsequently, the model was trained using recognition and classification algorithms, specifically artificial neural networks and support vector machines. Finally, the trained model was validated with different data sets and the performance was measured with cross validation and ROC analysis. The results show that is possible to identify welding automatically with an efficiency between 90 and 98 percent.

[Development of automatic urine monitoring system].

PubMed

Wei, Liang; Li, Yongqin; Chen, Bihua

2014-03-01

An automatic urine monitoring system is presented to replace manual operation. The system is composed of the flow sensor, MSP430f149 single chip microcomputer, human-computer interaction module, LCD module, clock module and memory module. The signal of urine volume is captured when the urine flows through the flow sensor and then displayed on the LCD after data processing. The experiment results suggest that the design of the monitor provides a high stability, accurate measurement and good real-time, and meets the demand of the clinical application.

Changes in default mode network as automaticity develops in a categorization task.

PubMed

Shamloo, Farzin; Helie, Sebastien

2016-10-15

The default mode network (DMN) is a set of brain regions in which blood oxygen level dependent signal is suppressed during attentional focus on the external environment. Because automatic task processing requires less attention, development of automaticity in a rule-based categorization task may result in less deactivation and altered functional connectivity of the DMN when compared to the initial learning stage. We tested this hypothesis by re-analyzing functional magnetic resonance imaging data of participants trained in rule-based categorization for over 10,000 trials (Helie et al., 2010) [12,13]. The results show that some DMN regions are deactivated in initial training but not after automaticity has developed. There is also a significant decrease in DMN deactivation after extensive practice. Seed-based functional connectivity analyses with the precuneus, medial prefrontal cortex (two important DMN regions) and Brodmann area 6 (an important region in automatic categorization) were also performed. The results show increased functional connectivity with both DMN and non-DMN regions after the development of automaticity, and a decrease in functional connectivity between the medial prefrontal cortex and ventromedial orbitofrontal cortex. Together, these results further support the hypothesis of a strategy shift in automatic categorization and bridge the cognitive and neuroscientific conceptions of automaticity in showing that the reduced need for cognitive resources in automatic processing is accompanied by a disinhibition of the DMN and stronger functional connectivity between DMN and task-related brain regions. Copyright © 2016 Elsevier B.V. All rights reserved.

49 CFR 236.739 - Device, acknowledging.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.739... locomotive equipped with an automatic train stop or train control device, an automatic brake application can be forestalled, or by means of which, on a locomotive equipped with an automatic cab signal device...

Automatic protein structure solution from weak X-ray data

NASA Astrophysics Data System (ADS)

Skubák, Pavol; Pannu, Navraj S.

2013-11-01

Determining new protein structures from X-ray diffraction data at low resolution or with a weak anomalous signal is a difficult and often an impossible task. Here we propose a multivariate algorithm that simultaneously combines the structure determination steps. In tests on over 140 real data sets from the protein data bank, we show that this combined approach can automatically build models where current algorithms fail, including an anisotropically diffracting 3.88 Å RNA polymerase II data set. The method seamlessly automates the process, is ideal for non-specialists and provides a mathematical framework for successfully combining various sources of information in image processing.

Modis, SeaWIFS, and Pathfinder funded activities

NASA Technical Reports Server (NTRS)

Evans, Robert H.

1995-01-01

MODIS (Moderate Resolution Imaging Spectrometer), SeaWIFS (Sea-viewing Wide Field Sensor), Pathfinder, and DSP (Digital Signal Processor) objectives are summarized. An overview of current progress is given for the automatic processing database, client/server status, matchup database, and DSP support.

SIG: a general-purpose signal processing program

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

Lager, D.; Azevedo, S.

1986-02-01

SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. It also accommodates other representations for data such as transfer function polynomials. Signal processing operations include digital filtering, auto/cross spectral density, transfer function/impulse response, convolution, Fourier transform, and inverse Fourier transform. Graphical operations provide display of signals and spectra, including plotting, cursor zoom, families of curves, and multiple viewport plots. SIG provides two user interfaces with a menu mode for occasional users and a command mode for more experienced users. Capability exits for multiple commands per line, commandmore » files with arguments, commenting lines, defining commands, automatic execution for each item in a repeat sequence, etc. SIG is presently available for VAX(VMS), VAX (BERKELEY 4.2 UNIX), SUN (BERKELEY 4.2 UNIX), DEC-20 (TOPS-20), LSI-11/23 (TSX), and DEC PRO 350 (TSX). 4 refs., 2 figs.« less

Automatic topics segmentation for TV news video

NASA Astrophysics Data System (ADS)

Hmayda, Mounira; Ejbali, Ridha; Zaied, Mourad

2017-03-01

Automatic identification of television programs in the TV stream is an important task for operating archives. This article proposes a new spatio-temporal approach to identify the programs in TV stream into two main steps: First, a reference catalogue for video features visual jingles built. We operate the features that characterize the instances of the same program type to identify the different types of programs in the flow of television. The role of video features is to represent the visual invariants for each visual jingle using appropriate automatic descriptors for each television program. On the other hand, programs in television streams are identified by examining the similarity of the video signal for visual grammars in the catalogue. The main idea of the identification process is to compare the visual similarity of the video signal features in the flow of television to the catalogue. After presenting the proposed approach, the paper overviews encouraging experimental results on several streams extracted from different channels and compounds of several programs.

A method for the automatic reconstruction of fetal cardiac signals from magnetocardiographic recordings

NASA Astrophysics Data System (ADS)

Mantini, D.; Alleva, G.; Comani, S.

2005-10-01

Fetal magnetocardiography (fMCG) allows monitoring the fetal heart function through algorithms able to retrieve the fetal cardiac signal, but no standardized automatic model has become available so far. In this paper, we describe an automatic method that restores the fetal cardiac trace from fMCG recordings by means of a weighted summation of fetal components separated with independent component analysis (ICA) and identified through dedicated algorithms that analyse the frequency content and temporal structure of each source signal. Multichannel fMCG datasets of 66 healthy and 4 arrhythmic fetuses were used to validate the automatic method with respect to a classical procedure requiring the manual classification of fetal components by an expert investigator. ICA was run with input clusters of different dimensions to simulate various MCG systems. Detection rates, true negative and false positive component categorization, QRS amplitude, standard deviation and signal-to-noise ratio of reconstructed fetal signals, and real and per cent QRS differences between paired fetal traces retrieved automatically and manually were calculated to quantify the performances of the automatic method. Its robustness and reliability, particularly evident with the use of large input clusters, might increase the diagnostic role of fMCG during the prenatal period.

Speech Intelligibility Predicted from Neural Entrainment of the Speech Envelope.

PubMed

Vanthornhout, Jonas; Decruy, Lien; Wouters, Jan; Simon, Jonathan Z; Francart, Tom

2018-04-01

Speech intelligibility is currently measured by scoring how well a person can identify a speech signal. The results of such behavioral measures reflect neural processing of the speech signal, but are also influenced by language processing, motivation, and memory. Very often, electrophysiological measures of hearing give insight in the neural processing of sound. However, in most methods, non-speech stimuli are used, making it hard to relate the results to behavioral measures of speech intelligibility. The use of natural running speech as a stimulus in electrophysiological measures of hearing is a paradigm shift which allows to bridge the gap between behavioral and electrophysiological measures. Here, by decoding the speech envelope from the electroencephalogram, and correlating it with the stimulus envelope, we demonstrate an electrophysiological measure of neural processing of running speech. We show that behaviorally measured speech intelligibility is strongly correlated with our electrophysiological measure. Our results pave the way towards an objective and automatic way of assessing neural processing of speech presented through auditory prostheses, reducing confounds such as attention and cognitive capabilities. We anticipate that our electrophysiological measure will allow better differential diagnosis of the auditory system, and will allow the development of closed-loop auditory prostheses that automatically adapt to individual users.

[Sociophysiology: basic processes of empathy].

PubMed

Haker, Helene; Schimansky, Jenny; Rössler, Wulf

2010-01-01

The aim of this review is to describe sociophysiological and social cognitive processes that underlie the complex phenomenon of human empathy. Automatic reflexive processes such as physiological contagion and action mirroring are mediated by the mirror neuron system. They are a basis for further processing of social signals and a physiological link between two individuals. This link comprises simultaneous activation of shared motor representations. Shared representations lead implicitly via individual associations in the limbic and vegetative system to a shared affective state. These processes are called sociophysiology. Further controlled- reflective, self-referential processing of those social signals leads to explicit, conscious representations of others' minds. Those higher-order processes are called social cognition. The interaction of physiological and cognitive social processes lets arise the phenomenon of human empathy.

EEG feature selection method based on decision tree.

PubMed

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

Structural analysis of vibroacoustical processes

NASA Technical Reports Server (NTRS)

Gromov, A. P.; Myasnikov, L. L.; Myasnikova, Y. N.; Finagin, B. A.

1973-01-01

The method of automatic identification of acoustical signals, by means of the segmentation was used to investigate noises and vibrations in machines and mechanisms, for cybernetic diagnostics. The structural analysis consists of presentation of a noise or vibroacoustical signal as a sequence of segments, determined by the time quantization, in which each segment is characterized by specific spectral characteristics. The structural spectrum is plotted as a histogram of the segments, also as a relation of the probability density of appearance of a segment to the segment type. It is assumed that the conditions of ergodic processes are maintained.

49 CFR 236.567 - Restrictions imposed when device fails and/or is cut out en route.

Code of Federal Regulations, 2011 CFR

2011-10-01

... GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions... restricted speed or if an automatic block signal system is in operation according to signal indication but...

49 CFR 236.512 - Cab signal indication when locomotive enters block where restrictive conditions obtain.

Code of Federal Regulations, 2011 CFR

2011-10-01

... TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.512 Cab signal indication when locomotive enters block where restrictive conditions obtain. The automatic cab signal system shall be arranged so that when a locomotive enters or is...

National Radar Conference, Los Angeles, CA, March 12, 13, 1986, Proceedings

NASA Astrophysics Data System (ADS)

The topics discussed include radar systems, radar subsystems, and radar signal processing. Papers are presented on millimeter wave radar for proximity fuzing of smart munitions, a solid state low pulse power ground surveillance radar, and the Radarsat prototype synthetic-aperture radar signal processor. Consideration is also given to automatic track quality assessment in ADT radar systems instrumentation of RCS measurements of modulation spectra of aircraft blades.

49 CFR 236.401 - Automatic block signal system and interlocking standards applicable to traffic control systems.

Code of Federal Regulations, 2011 CFR

2011-10-01

... TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Traffic Control Systems Standards § 236.401 Automatic... 49 Transportation 4 2011-10-01 2011-10-01 false Automatic block signal system and interlocking standards applicable to traffic control systems. 236.401 Section 236.401 Transportation Other Regulations...

[Research on automatic external defibrillator based on DSP].

PubMed

Jing, Jun; Ding, Jingyan; Zhang, Wei; Hong, Wenxue

2012-10-01

Electrical defibrillation is the most effective way to treat the ventricular tachycardia (VT) and ventricular fibrillation (VF). An automatic external defibrillator based on DSP is introduced in this paper. The whole design consists of the signal collection module, the microprocessor controlingl module, the display module, the defibrillation module and the automatic recognition algorithm for VF and non VF, etc. This automatic external defibrillator has achieved goals such as ECG signal real-time acquisition, ECG wave synchronous display, data delivering to U disk and automatic defibrillate when shockable rhythm appears, etc.

Holoentropy enabled-decision tree for automatic classification of diabetic retinopathy using retinal fundus images.

PubMed

Mane, Vijay Mahadeo; Jadhav, D V

2017-05-24

Diabetic retinopathy (DR) is the most common diabetic eye disease. Doctors are using various test methods to detect DR. But, the availability of test methods and requirements of domain experts pose a new challenge in the automatic detection of DR. In order to fulfill this objective, a variety of algorithms has been developed in the literature. In this paper, we propose a system consisting of a novel sparking process and a holoentropy-based decision tree for automatic classification of DR images to further improve the effectiveness. The sparking process algorithm is developed for automatic segmentation of blood vessels through the estimation of optimal threshold. The holoentropy enabled decision tree is newly developed for automatic classification of retinal images into normal or abnormal using hybrid features which preserve the disease-level patterns even more than the signal level of the feature. The effectiveness of the proposed system is analyzed using standard fundus image databases DIARETDB0 and DIARETDB1 for sensitivity, specificity and accuracy. The proposed system yields sensitivity, specificity and accuracy values of 96.72%, 97.01% and 96.45%, respectively. The experimental result reveals that the proposed technique outperforms the existing algorithms.

Adaptive Self-Tuning Networks

NASA Astrophysics Data System (ADS)

Knox, H. A.; Draelos, T.; Young, C. J.; Lawry, B.; Chael, E. P.; Faust, A.; Peterson, M. G.

2015-12-01

The quality of automatic detections from seismic sensor networks depends on a large number of data processing parameters that interact in complex ways. The largely manual process of identifying effective parameters is painstaking and does not guarantee that the resulting controls are the optimal configuration settings. Yet, achieving superior automatic detection of seismic events is closely related to these parameters. We present an automated sensor tuning (AST) system that learns near-optimal parameter settings for each event type using neuro-dynamic programming (reinforcement learning) trained with historic data. AST learns to test the raw signal against all event-settings and automatically self-tunes to an emerging event in real-time. The overall goal is to reduce the number of missed legitimate event detections and the number of false event detections. Reducing false alarms early in the seismic pipeline processing will have a significant impact on this goal. Applicable both for existing sensor performance boosting and new sensor deployment, this system provides an important new method to automatically tune complex remote sensing systems. Systems tuned in this way will achieve better performance than is currently possible by manual tuning, and with much less time and effort devoted to the tuning process. With ground truth on detections in seismic waveforms from a network of stations, we show that AST increases the probability of detection while decreasing false alarms.

Automatic classification of sleep stages based on the time-frequency image of EEG signals.

PubMed

Bajaj, Varun; Pachori, Ram Bilas

2013-12-01

In this paper, a new method for automatic sleep stage classification based on time-frequency image (TFI) of electroencephalogram (EEG) signals is proposed. Automatic classification of sleep stages is an important part for diagnosis and treatment of sleep disorders. The smoothed pseudo Wigner-Ville distribution (SPWVD) based time-frequency representation (TFR) of EEG signal has been used to obtain the time-frequency image (TFI). The segmentation of TFI has been performed based on the frequency-bands of the rhythms of EEG signals. The features derived from the histogram of segmented TFI have been used as an input feature set to multiclass least squares support vector machines (MC-LS-SVM) together with the radial basis function (RBF), Mexican hat wavelet, and Morlet wavelet kernel functions for automatic classification of sleep stages from EEG signals. The experimental results are presented to show the effectiveness of the proposed method for classification of sleep stages from EEG signals. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

49 CFR 236.566 - Locomotive of each train operating in train stop, train control or cab signal territory; equipped.

Code of Federal Regulations, 2010 CFR

2010-10-01

... OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and... controlled, of each train operating in automatic train stop, train control, or cab signal territory shall be..., train control or cab signal territory; equipped. 236.566 Section 236.566 Transportation Other...

49 CFR 236.566 - Locomotive of each train operating in train stop, train control or cab signal territory; equipped.

Code of Federal Regulations, 2011 CFR

2011-10-01

... OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and... controlled, of each train operating in automatic train stop, train control, or cab signal territory shall be..., train control or cab signal territory; equipped. 236.566 Section 236.566 Transportation Other...

Control Method for Video Guidance Sensor System

NASA Technical Reports Server (NTRS)

Howard, Richard T. (Inventor); Book, Michael L. (Inventor); Bryan, Thomas C. (Inventor)

2005-01-01

A method is provided for controlling operations in a video guidance sensor system wherein images of laser output signals transmitted by the system and returned from a target are captured and processed by the system to produce data used in tracking of the target. Six modes of operation are provided as follows: (i) a reset mode; (ii) a diagnostic mode; (iii) a standby mode; (iv) an acquisition mode; (v) a tracking mode; and (vi) a spot mode wherein captured images of returned laser signals are processed to produce data for all spots found in the image. The method provides for automatic transition to the standby mode from the reset mode after integrity checks are performed and from the diagnostic mode to the reset mode after diagnostic operations are commands is permitted only when the system is in the carried out. Further, acceptance of reset and diagnostic standby mode. The method also provides for automatic transition from the acquisition mode to the tracking mode when an acceptable target is found.

Control method for video guidance sensor system

NASA Technical Reports Server (NTRS)

Howard, Richard T. (Inventor); Book, Michael L. (Inventor); Bryan, Thomas C. (Inventor)

2005-01-01

A method is provided for controlling operations in a video guidance sensor system wherein images of laser output signals transmitted by the system and returned from a target are captured and processed by the system to produce data used in tracking of the target. Six modes of operation are provided as follows: (i) a reset mode; (ii) a diagnostic mode; (iii) a standby mode; (iv) an acquisition mode; (v) a tracking mode; and (vi) a spot mode wherein captured images of returned laser signals are processed to produce data for all spots found in the image. The method provides for automatic transition to the standby mode from the reset mode after integrity checks are performed and from the diagnostic mode to the reset mode after diagnostic operations are carried out. Further, acceptance of reset and diagnostic commands is permitted only when the system is in the standby mode. The method also provides for automatic transition from the acquisition mode to the tracking mode when an acceptable target is found.

The Doubting System 1: Evidence for automatic substitution sensitivity.

PubMed

Johnson, Eric D; Tubau, Elisabet; De Neys, Wim

2016-02-01

A long prevailing view of human reasoning suggests severe limits on our ability to adhere to simple logical or mathematical prescriptions. A key position assumes these failures arise from insufficient monitoring of rapidly produced intuitions. These faulty intuitions are thought to arise from a proposed substitution process, by which reasoners unknowingly interpret more difficult questions as easier ones. Recent work, however, suggests that reasoners are not blind to this substitution process, but in fact detect that their erroneous responses are not warranted. Using the popular bat-and-ball problem, we investigated whether this substitution sensitivity arises out of an automatic System 1 process or whether it depends on the operation of an executive resource demanding System 2 process. Results showed that accuracy on the bat-and-ball problem clearly declined under cognitive load. However, both reduced response confidence and increased response latencies indicated that biased reasoners remained sensitive to their faulty responses under load. Results suggest that a crucial substitution monitoring process is not only successfully engaged, but that it automatically operates as an autonomous System 1 process. By signaling its doubt along with a biased intuition, it appears System 1 is "smarter" than traditionally assumed.

Signal processing techniques for damage detection with piezoelectric wafer active sensors and embedded ultrasonic structural radar

NASA Astrophysics Data System (ADS)

Yu, Lingyu; Bao, Jingjing; Giurgiutiu, Victor

2004-07-01

Embedded ultrasonic structural radar (EUSR) algorithm is developed for using piezoelectric wafer active sensor (PWAS) array to detect defects within a large area of a thin-plate specimen. Signal processing techniques are used to extract the time of flight of the wave packages, and thereby to determine the location of the defects with the EUSR algorithm. In our research, the transient tone-burst wave propagation signals are generated and collected by the embedded PWAS. Then, with signal processing, the frequency contents of the signals and the time of flight of individual frequencies are determined. This paper starts with an introduction of embedded ultrasonic structural radar algorithm. Then we will describe the signal processing methods used to extract the time of flight of the wave packages. The signal processing methods being used include the wavelet denoising, the cross correlation, and Hilbert transform. Though hardware device can provide averaging function to eliminate the noise coming from the signal collection process, wavelet denoising is included to ensure better signal quality for the application in real severe environment. For better recognition of time of flight, cross correlation method is used. Hilbert transform is applied to the signals after cross correlation in order to extract the envelope of the signals. Signal processing and EUSR are both implemented by developing a graphical user-friendly interface program in LabView. We conclude with a description of our vision for applying EUSR signal analysis to structural health monitoring and embedded nondestructive evaluation. To this end, we envisage an automatic damage detection application utilizing embedded PWAS, EUSR, and advanced signal processing.

49 CFR 236.534 - Entrance to equipped territory; requirements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Roadway § 236.534... not exceed restricted speed, the automatic train stop, train control, or cab signal device shall be...

49 CFR 236.513 - Audible indicator.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.513 Audible indicator. (a) The automatic cab signal... control system shall have a distinctive sound and be clearly audible throughout the cab under all...

49 CFR 236.513 - Audible indicator.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.513 Audible indicator. (a) The automatic cab signal... control system shall have a distinctive sound and be clearly audible throughout the cab under all...

49 CFR 236.534 - Entrance to equipped territory; requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Roadway § 236.534... not exceed restricted speed, the automatic train stop, train control, or cab signal device shall be...

49 CFR 236.587 - Departure test.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Inspection and Tests; Locomotive § 236.587 Departure test. (a) The automatic train stop, train control, or cab signal apparatus on each locomotive, except a locomotive or a...

Achieving Accurate Automatic Sleep Staging on Manually Pre-processed EEG Data Through Synchronization Feature Extraction and Graph Metrics.

PubMed

Chriskos, Panteleimon; Frantzidis, Christos A; Gkivogkli, Polyxeni T; Bamidis, Panagiotis D; Kourtidou-Papadeli, Chrysoula

2018-01-01

Sleep staging, the process of assigning labels to epochs of sleep, depending on the stage of sleep they belong, is an arduous, time consuming and error prone process as the initial recordings are quite often polluted by noise from different sources. To properly analyze such data and extract clinical knowledge, noise components must be removed or alleviated. In this paper a pre-processing and subsequent sleep staging pipeline for the sleep analysis of electroencephalographic signals is described. Two novel methods of functional connectivity estimation (Synchronization Likelihood/SL and Relative Wavelet Entropy/RWE) are comparatively investigated for automatic sleep staging through manually pre-processed electroencephalographic recordings. A multi-step process that renders signals suitable for further analysis is initially described. Then, two methods that rely on extracting synchronization features from electroencephalographic recordings to achieve computerized sleep staging are proposed, based on bivariate features which provide a functional overview of the brain network, contrary to most proposed methods that rely on extracting univariate time and frequency features. Annotation of sleep epochs is achieved through the presented feature extraction methods by training classifiers, which are in turn able to accurately classify new epochs. Analysis of data from sleep experiments on a randomized, controlled bed-rest study, which was organized by the European Space Agency and was conducted in the "ENVIHAB" facility of the Institute of Aerospace Medicine at the German Aerospace Center (DLR) in Cologne, Germany attains high accuracy rates, over 90% based on ground truth that resulted from manual sleep staging by two experienced sleep experts. Therefore, it can be concluded that the above feature extraction methods are suitable for semi-automatic sleep staging.

Detection and characterization of lightning-based sources using continuous wavelet transform: application to audio-magnetotellurics

NASA Astrophysics Data System (ADS)

Larnier, H.; Sailhac, P.; Chambodut, A.

2018-01-01

Atmospheric electromagnetic waves created by global lightning activity contain information about electrical processes of the inner and the outer Earth. Large signal-to-noise ratio events are particularly interesting because they convey information about electromagnetic properties along their path. We introduce a new methodology to automatically detect and characterize lightning-based waves using a time-frequency decomposition obtained through the application of continuous wavelet transform. We focus specifically on three types of sources, namely, atmospherics, slow tails and whistlers, that cover the frequency range 10 Hz to 10 kHz. Each wave has distinguishable characteristics in the time-frequency domain due to source shape and dispersion processes. Our methodology allows automatic detection of each type of event in the time-frequency decomposition thanks to their specific signature. Horizontal polarization attributes are also recovered in the time-frequency domain. This procedure is first applied to synthetic extremely low frequency time-series with different signal-to-noise ratios to test for robustness. We then apply it on real data: three stations of audio-magnetotelluric data acquired in Guadeloupe, oversea French territories. Most of analysed atmospherics and slow tails display linear polarization, whereas analysed whistlers are elliptically polarized. The diversity of lightning activity is finally analysed in an audio-magnetotelluric data processing framework, as used in subsurface prospecting, through estimation of the impedance response functions. We show that audio-magnetotelluric processing results depend mainly on the frequency content of electromagnetic waves observed in processed time-series, with an emphasis on the difference between morning and afternoon acquisition. Our new methodology based on the time-frequency signature of lightning-induced electromagnetic waves allows automatic detection and characterization of events in audio-magnetotelluric time-series, providing the means to assess quality of response functions obtained through processing.

Achieving Accurate Automatic Sleep Staging on Manually Pre-processed EEG Data Through Synchronization Feature Extraction and Graph Metrics

PubMed Central

Chriskos, Panteleimon; Frantzidis, Christos A.; Gkivogkli, Polyxeni T.; Bamidis, Panagiotis D.; Kourtidou-Papadeli, Chrysoula

2018-01-01

Sleep staging, the process of assigning labels to epochs of sleep, depending on the stage of sleep they belong, is an arduous, time consuming and error prone process as the initial recordings are quite often polluted by noise from different sources. To properly analyze such data and extract clinical knowledge, noise components must be removed or alleviated. In this paper a pre-processing and subsequent sleep staging pipeline for the sleep analysis of electroencephalographic signals is described. Two novel methods of functional connectivity estimation (Synchronization Likelihood/SL and Relative Wavelet Entropy/RWE) are comparatively investigated for automatic sleep staging through manually pre-processed electroencephalographic recordings. A multi-step process that renders signals suitable for further analysis is initially described. Then, two methods that rely on extracting synchronization features from electroencephalographic recordings to achieve computerized sleep staging are proposed, based on bivariate features which provide a functional overview of the brain network, contrary to most proposed methods that rely on extracting univariate time and frequency features. Annotation of sleep epochs is achieved through the presented feature extraction methods by training classifiers, which are in turn able to accurately classify new epochs. Analysis of data from sleep experiments on a randomized, controlled bed-rest study, which was organized by the European Space Agency and was conducted in the “ENVIHAB” facility of the Institute of Aerospace Medicine at the German Aerospace Center (DLR) in Cologne, Germany attains high accuracy rates, over 90% based on ground truth that resulted from manual sleep staging by two experienced sleep experts. Therefore, it can be concluded that the above feature extraction methods are suitable for semi-automatic sleep staging. PMID:29628883

Floating-point scaling technique for sources separation automatic gain control

NASA Astrophysics Data System (ADS)

Fermas, A.; Belouchrani, A.; Ait-Mohamed, O.

2012-07-01

Based on the floating-point representation and taking advantage of scaling factor indetermination in blind source separation (BSS) processing, we propose a scaling technique applied to the separation matrix, to avoid the saturation or the weakness in the recovered source signals. This technique performs an automatic gain control in an on-line BSS environment. We demonstrate the effectiveness of this technique by using the implementation of a division-free BSS algorithm with two inputs, two outputs. The proposed technique is computationally cheaper and efficient for a hardware implementation compared to the Euclidean normalisation.

49 CFR 236.401 - Automatic block signal system and interlocking standards applicable to traffic control systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Automatic block signal system and interlocking standards applicable to traffic control systems. 236.401 Section 236.401 Transportation Other Regulations... block signal system and interlocking standards applicable to traffic control systems. The standards...

49 CFR 236.563 - Delay time.

Code of Federal Regulations, 2011 CFR

2011-10-01

... OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives § 236.563 Delay time. Delay time of automatic train stop or train control system shall not exceed 8 seconds and the spacing of signals to meet the...

49 CFR 236.586 - Daily or after trip test.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Inspection and Tests; Locomotive § 236.586 Daily or after trip test..., each locomotive equipped with an automatic cab signal or train stop or train control device operating...

49 CFR 236.588 - Periodic test.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Inspection and Tests; Locomotive § 236.588 Periodic test. Except as provided in § 236.586, periodic test of the automatic train stop, train control, or cab signal apparatus...

49 CFR 236.509 - Two or more locomotives coupled.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.509 Two or more locomotives coupled. The automatic train stop, train control or cab signal apparatus shall be arranged so that when two or...

49 CFR 236.557 - Receiver; location with respect to rail.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives § 236.557 Receiver... automatic cab signal, train stop, or train control device of locomotive equipped with onboard test equipment...

49 CFR 236.586 - Daily or after trip test.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Inspection and Tests; Locomotive § 236.586 Daily or after trip test..., each locomotive equipped with an automatic cab signal or train stop or train control device operating...

49 CFR 236.509 - Two or more locomotives coupled.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.509 Two or more locomotives coupled. The automatic train stop, train control or cab signal apparatus shall be arranged so that when two or...

Satellite single-axis attitude determination based on Automatic Dependent Surveillance - Broadcast signals

NASA Astrophysics Data System (ADS)

Zhou, Kaixing; Sun, Xiucong; Huang, Hai; Wang, Xinsheng; Ren, Guangwei

2017-10-01

The space-based Automatic Dependent Surveillance - Broadcast (ADS-B) is a new technology for air traffic management. The satellite equipped with spaceborne ADS-B system receives the broadcast signals from aircraft and transfers the message to ground stations, so as to extend the coverage area of terrestrial-based ADS-B. In this work, a novel satellite single-axis attitude determination solution based on the ADS-B receiving system is proposed. This solution utilizes the signal-to-noise ratio (SNR) measurement of the broadcast signals from aircraft to determine the boresight orientation of the ADS-B receiving antenna fixed on the satellite. The basic principle of this solution is described. The feasibility study of this new attitude determination solution is implemented, including the link budget and the access analysis. On this basis, the nonlinear least squares estimation based on the Levenberg-Marquardt method is applied to estimate the single-axis orientation. A full digital simulation has been carried out to verify the effectiveness and performance of this solution. Finally, the corresponding results are processed and presented minutely.

Call recognition and individual identification of fish vocalizations based on automatic speech recognition: An example with the Lusitanian toadfish.

PubMed

Vieira, Manuel; Fonseca, Paulo J; Amorim, M Clara P; Teixeira, Carlos J C

2015-12-01

The study of acoustic communication in animals often requires not only the recognition of species specific acoustic signals but also the identification of individual subjects, all in a complex acoustic background. Moreover, when very long recordings are to be analyzed, automatic recognition and identification processes are invaluable tools to extract the relevant biological information. A pattern recognition methodology based on hidden Markov models is presented inspired by successful results obtained in the most widely known and complex acoustical communication signal: human speech. This methodology was applied here for the first time to the detection and recognition of fish acoustic signals, specifically in a stream of round-the-clock recordings of Lusitanian toadfish (Halobatrachus didactylus) in their natural estuarine habitat. The results show that this methodology is able not only to detect the mating sounds (boatwhistles) but also to identify individual male toadfish, reaching an identification rate of ca. 95%. Moreover this method also proved to be a powerful tool to assess signal durations in large data sets. However, the system failed in recognizing other sound types.

Steam generator on-line efficiency monitor

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

Johnson, R.K.; Kaya, A.; Keyes, M.A. IV

1987-08-04

This patent describes a system for automatically and continuously determining the efficiency of a combustion process in a fossil-fuel fired vapor generator for utilization by an automatic load control system that controls the distribution of a system load among a plurality of vapor generators, comprising: a first function generator, connected to an oxygen transducer for sensing the level of excess air in the flue gas, for generating a first signal indicative of the total air supplied for combustion in percent by weight; a second function generator, connected to a combustibles transducer for sensing the level of combustibles in the fluemore » gas, for generating a second signal indicative of the percent combustibles present in the flue gas; means for correcting the first signal, connected to the first and second function generators, when the oxygen transducer is of a type that operates at a temperature level sufficient to cause the unburned combustibles to react with the oxygen present in the flue gas; an ambient air temperature transducer for generating a third signal indicative of the temperature of the ambient air supplied to the vapor generator for combustion.« less

Signal processing for non-destructive testing of railway tracks

NASA Astrophysics Data System (ADS)

Heckel, Thomas; Casperson, Ralf; Rühe, Sven; Mook, Gerhard

2018-04-01

Increased speed, heavier loads, altered material and modern drive systems result in an increasing number of rail flaws. The appearance of these flaws also changes continually due to the rapid change in damage mechanisms of modern rolling stock. Hence, interpretation has become difficult when evaluating non-destructive rail testing results. Due to the changed interplay between detection methods and flaws, the recorded signals may result in unclassified types of rail flaws. Methods for automatic rail inspection (according to defect detection and classification) undergo continual development. Signal processing is a key technology to master the challenge of classification and maintain resolution and detection quality, independent of operation speed. The basic ideas of signal processing, based on the Glassy-Rail-Diagram for classification purposes, are presented herein. Examples for the detection of damages caused by rolling contact fatigue also are given, and synergetic effects of combined evaluation of diverse inspection methods are shown.

Multichannel Detection in High-Performance Liquid Chromatography.

ERIC Educational Resources Information Center

Miller, James C.; And Others

1982-01-01

A linear photodiode array is used as the photodetector element in a new ultraviolet-visible detection system for high-performance liquid chromatography (HPLC). Using a computer network, the system processes eight different chromatographic signals simultaneously in real-time and acquires spectra manually/automatically. Applications in fast HPLC…

Automatic and Controlled Response Inhibition: Associative Learning in the Go/No-Go and Stop-Signal Paradigms

ERIC Educational Resources Information Center

Verbruggen, Frederick; Logan, Gordon D.

2008-01-01

In 5 experiments, the authors examined the development of automatic response inhibition in the go/no-go paradigm and a modified version of the stop-signal paradigm. They hypothesized that automatic response inhibition may develop over practice when stimuli are consistently associated with stopping. All 5 experiments consisted of a training phase…

Automatic Modulation Classification Based on Deep Learning for Unmanned Aerial Vehicles.

PubMed

Zhang, Duona; Ding, Wenrui; Zhang, Baochang; Xie, Chunyu; Li, Hongguang; Liu, Chunhui; Han, Jungong

2018-03-20

Deep learning has recently attracted much attention due to its excellent performance in processing audio, image, and video data. However, few studies are devoted to the field of automatic modulation classification (AMC). It is one of the most well-known research topics in communication signal recognition and remains challenging for traditional methods due to complex disturbance from other sources. This paper proposes a heterogeneous deep model fusion (HDMF) method to solve the problem in a unified framework. The contributions include the following: (1) a convolutional neural network (CNN) and long short-term memory (LSTM) are combined by two different ways without prior knowledge involved; (2) a large database, including eleven types of single-carrier modulation signals with various noises as well as a fading channel, is collected with various signal-to-noise ratios (SNRs) based on a real geographical environment; and (3) experimental results demonstrate that HDMF is very capable of coping with the AMC problem, and achieves much better performance when compared with the independent network.

Automatic Modulation Classification Based on Deep Learning for Unmanned Aerial Vehicles

PubMed Central

Ding, Wenrui; Zhang, Baochang; Xie, Chunyu; Li, Hongguang; Liu, Chunhui; Han, Jungong

2018-01-01

Deep learning has recently attracted much attention due to its excellent performance in processing audio, image, and video data. However, few studies are devoted to the field of automatic modulation classification (AMC). It is one of the most well-known research topics in communication signal recognition and remains challenging for traditional methods due to complex disturbance from other sources. This paper proposes a heterogeneous deep model fusion (HDMF) method to solve the problem in a unified framework. The contributions include the following: (1) a convolutional neural network (CNN) and long short-term memory (LSTM) are combined by two different ways without prior knowledge involved; (2) a large database, including eleven types of single-carrier modulation signals with various noises as well as a fading channel, is collected with various signal-to-noise ratios (SNRs) based on a real geographical environment; and (3) experimental results demonstrate that HDMF is very capable of coping with the AMC problem, and achieves much better performance when compared with the independent network. PMID:29558434

Improved nutrient removal using in situ continuous on-line sensors with short response time.

PubMed

Ingildsen, P; Wendelboe, H

2003-01-01

Nutrient sensors that can be located directly in the activated sludge processes are gaining in number at wastewater treatment plants. The in situ location of the sensors means that they can be located close to the processes that they aim to control and hence are perfectly suited for automatic process control. Compared to the location of automatic analysers in the effluent from the sedimentation reactors the in situ location means a large reduction in the response time. The settlers typically work as a first-order delay on the signal with a retention time in the range of 4-12 hours depending on the size of the settlers. Automatic process control of the nitrogen and phosphorus removal processes means that considerable improvements in the performance of aeration, internal recirculation, carbon dosage and phosphate precipitation dosage can be reached by using a simple control structure as well as simple PID controllers. The performance improvements can be seen in decreased energy and chemicals consumption and less variation in effluent concentrations of ammonium, total nitrogen and phosphate. Simple control schemes are demonstrated for the pre-denitrification and the post precipitation system by means of full-scale plant experiments and model simulations.

Automatic identification of bullet signatures based on consecutive matching striae (CMS) criteria.

PubMed

Chu, Wei; Thompson, Robert M; Song, John; Vorburger, Theodore V

2013-09-10

The consecutive matching striae (CMS) numeric criteria for firearm and toolmark identifications have been widely accepted by forensic examiners, although there have been questions concerning its observer subjectivity and limited statistical support. In this paper, based on signal processing and extraction, a model for the automatic and objective counting of CMS is proposed. The position and shape information of the striae on the bullet land is represented by a feature profile, which is used for determining the CMS number automatically. Rapid counting of CMS number provides a basis for ballistics correlations with large databases and further statistical and probability analysis. Experimental results in this report using bullets fired from ten consecutively manufactured barrels support this developed model. Published by Elsevier Ireland Ltd.

Automatic Identification of Artifact-Related Independent Components for Artifact Removal in EEG Recordings.

PubMed

Zou, Yuan; Nathan, Viswam; Jafari, Roozbeh

2016-01-01

Electroencephalography (EEG) is the recording of electrical activity produced by the firing of neurons within the brain. These activities can be decoded by signal processing techniques. However, EEG recordings are always contaminated with artifacts which hinder the decoding process. Therefore, identifying and removing artifacts is an important step. Researchers often clean EEG recordings with assistance from independent component analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event-related potential (ERP)-related independent components. However, existing ICA-based artifact identification strategies mostly restrict themselves to a subset of artifacts, e.g., identifying eye movement artifacts only, and have not been shown to reliably identify artifacts caused by nonbiological origins like high-impedance electrodes. In this paper, we propose an automatic algorithm for the identification of general artifacts. The proposed algorithm consists of two parts: 1) an event-related feature-based clustering algorithm used to identify artifacts which have physiological origins; and 2) the electrode-scalp impedance information employed for identifying nonbiological artifacts. The results on EEG data collected from ten subjects show that our algorithm can effectively detect, separate, and remove both physiological and nonbiological artifacts. Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display ERPs in the raw EEG. The performance results also show that our proposed method can effectively identify artifacts and subsequently enhance the classification accuracies compared to four commonly used automatic artifact removal methods.

Automatic Identification of Artifact-related Independent Components for Artifact Removal in EEG Recordings

PubMed Central

Zou, Yuan; Nathan, Viswam; Jafari, Roozbeh

2017-01-01

Electroencephalography (EEG) is the recording of electrical activity produced by the firing of neurons within the brain. These activities can be decoded by signal processing techniques. However, EEG recordings are always contaminated with artifacts which hinder the decoding process. Therefore, identifying and removing artifacts is an important step. Researchers often clean EEG recordings with assistance from Independent Component Analysis (ICA), since it can decompose EEG recordings into a number of artifact-related and event related potential (ERP)-related independent components (ICs). However, existing ICA-based artifact identification strategies mostly restrict themselves to a subset of artifacts, e.g. identifying eye movement artifacts only, and have not been shown to reliably identify artifacts caused by non-biological origins like high-impedance electrodes. In this paper, we propose an automatic algorithm for the identification of general artifacts. The proposed algorithm consists of two parts: 1) an event-related feature based clustering algorithm used to identify artifacts which have physiological origins and 2) the electrode-scalp impedance information employed for identifying non-biological artifacts. The results on EEG data collected from 10 subjects show that our algorithm can effectively detect, separate, and remove both physiological and non-biological artifacts. Qualitative evaluation of the reconstructed EEG signals demonstrates that our proposed method can effectively enhance the signal quality, especially the quality of ERPs, even for those that barely display ERPs in the raw EEG. The performance results also show that our proposed method can effectively identify artifacts and subsequently enhance the classification accuracies compared to four commonly used automatic artifact removal methods. PMID:25415992

Design Automation for Streaming Systems

DTIC Science & Technology

2005-12-16

which are FIFO buffered channels. We develop a process network model for streaming sys - tems (TDFPN) and a hardware description language with built in...and may include an automatic address generator. A complete synthesis sys - tem would provide separate segment operator implementations for every...Acoustics, Speech, and Signal Processing (ICASSP ’89), pages 988– 991, 1989. [Luk et al., 1997] Wayne Luk, Nabeel Shirazi, and Peter Y. K. Cheung

Efficacious insect and disease control with laser-guided air-assisted sprayer

USDA-ARS?s Scientific Manuscript database

Efficacy of a newly developed air-assisted variable-rate sprayer was investigated for the control of arthropod pests and plant diseases in six commercial fields. The sprayer was integrated with a high-speed laser scanning sensor, a custom-designed signal processing program, an automatic flow control...

Classroom Social Signal Analysis

ERIC Educational Resources Information Center

Raca, Mirko; Dillenbourg, Pierre

2014-01-01

We present our efforts towards building an observational system for measuring classroom activity. The goal is to explore visual cues which can be acquired with a system of video cameras and automatically processed to enrich the teacher's perception of the audience. The paper will give a brief overview of our methodology, explored features, and…

Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks

NASA Technical Reports Server (NTRS)

Smith, Aaron; Evans, Michael; Downey, Joseph

2017-01-01

National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.

Mathematical approach to recover EEG brain signals with artifacts by means of Gram-Schmidt transform

NASA Astrophysics Data System (ADS)

Runnova, A. E.; Zhuravlev, M. O.; Koronovskiy, A. A.; Hramov, A. E.

2017-04-01

A novel method for removing oculomotor artifacts on electroencephalographical signals is proposed and based on the orthogonal Gram-Schmidt transform using electrooculography data. The method has shown high efficiency removal of artifacts caused by spontaneous movements of the eyeballs (about 95-97% correct remote oculomotor artifacts). This method may be recommended for multi-channel electroencephalography data processing in an automatic on-line in a variety of psycho-physiological experiments.

Automatic characteristic frequency association and all-sideband demodulation for the detection of a bearing fault

NASA Astrophysics Data System (ADS)

Firla, Marcin; Li, Zhong-Yang; Martin, Nadine; Pachaud, Christian; Barszcz, Tomasz

2016-12-01

This paper proposes advanced signal-processing techniques to improve condition monitoring of operating machines. The proposed methods use the results of a blind spectrum interpretation that includes harmonic and sideband series detection. The first contribution of this study is an algorithm for automatic association of harmonic and sideband series to characteristic fault frequencies according to a kinematic configuration. The approach proposed has the advantage of taking into account a possible slip of the rolling-element bearings. In the second part, we propose a full-band demodulation process from all sidebands that are relevant to the spectral estimation. To do so, a multi-rate filtering process in an iterative schema provides satisfying precision and stability over the targeted demodulation band, even for unsymmetrical and extremely narrow bands. After synchronous averaging, the filtered signal is demodulated for calculation of the amplitude and frequency modulation functions, and then any features that indicate faults. Finally, the proposed algorithms are validated on vibration signals measured on a test rig that was designed as part of the European Innovation Project 'KAStrion'. This rig simulates a wind turbine drive train at a smaller scale. The data show the robustness of the method for localizing and extracting a fault on the main bearing. The evolution of the proposed features is a good indicator of the fault severity.

The use of transmission line modelling to test the effectiveness of I-kaz as autonomous selection of intrinsic mode function

NASA Astrophysics Data System (ADS)

Yusop, Hanafi M.; Ghazali, M. F.; Yusof, M. F. M.; PiRemli, M. A.; Karollah, B.; Rusman

2017-10-01

Pressure transient signal occurred due to sudden changes in fluid propagation filled in pipelines system, which is caused by rapid pressure and flow fluctuation in a system, such as closing and opening valve rapidly. The application of Hilbert-Huang Transform (HHT) as the method to analyse the pressure transient signal utilised in this research. However, this method has the difficulty in selecting the suitable IMF for the further post-processing, which is Hilbert Transform (HT). This paper proposed the implementation of Integrated Kurtosis-based Algorithm for z-filter Technique (I-kaz) to kurtosis ratio (I-kaz-Kurtosis) for that allows automatic selection of intrinsic mode function (IMF) that’s should be used. This work demonstrated the synthetic pressure transient signal generates using transmission line modelling (TLM) in order to test the effectiveness of I-kaz as the autonomous selection of intrinsic mode function (IMF). A straight fluid network was designed using TLM fixing with higher resistance at some point act as a leak and connecting to the pipe feature (junction, pipefitting or blockage). The analysis results using I-kaz-kurtosis ratio revealed that the method can be utilised as an automatic selection of intrinsic mode function (IMF) although the noise level ratio of the signal is lower. I-kaz-kurtosis ratio is recommended and advised to be implemented as automatic selection of intrinsic mode function (IMF) through HHT analysis.

The unbalanced signal measuring of automotive brake drum

NASA Astrophysics Data System (ADS)

Wang, Xiao-Dong; Ye, Sheng-Hua; Zhang, Bang-Cheng

2005-04-01

For the purpose of the research and development of automatic balancing system by mass removing, the dissertation deals with the measuring method of the unbalance signal, the design the automatic balance equipment and the software. This paper emphases the testing system of the balancer of automotive brake drum. The paper designs the band-pass filter product with favorable automatic follow of electronic product, and with favorable automatic follow capability, filtration effect and stability. The system of automatic balancing system by mass removing based on virtual instrument is designed in this paper. A lab system has been constructed. The results of contrast experiments indicate the notable effect of 1-plane automatic balance and the high precision of dynamic balance, and demonstrate the application value of the system.

Automatic Coregistration and orthorectification (ACRO) and subsequent mosaicing of NASA high-resolution imagery over the Mars MC11 quadrangle, using HRSC as a baseline

NASA Astrophysics Data System (ADS)

Sidiropoulos, Panagiotis; Muller, Jan-Peter; Watson, Gillian; Michael, Gregory; Walter, Sebastian

2018-02-01

This work presents the coregistered, orthorectified and mosaiced high-resolution products of the MC11 quadrangle of Mars, which have been processed using novel, fully automatic, techniques. We discuss the development of a pipeline that achieves fully automatic and parameter independent geometric alignment of high-resolution planetary images, starting from raw input images in NASA PDS format and following all required steps to produce a coregistered geotiff image, a corresponding footprint and useful metadata. Additionally, we describe the development of a radiometric calibration technique that post-processes coregistered images to make them radiometrically consistent. Finally, we present a batch-mode application of the developed techniques over the MC11 quadrangle to validate their potential, as well as to generate end products, which are released to the planetary science community, thus assisting in the analysis of Mars static and dynamic features. This case study is a step towards the full automation of signal processing tasks that are essential to increase the usability of planetary data, but currently, require the extensive use of human resources.

Image processing in biodosimetry: A proposal of a generic free software platform.

PubMed

Dumpelmann, Matthias; Cadena da Matta, Mariel; Pereira de Lemos Pinto, Marcela Maria; de Salazar E Fernandes, Thiago; Borges da Silva, Edvane; Amaral, Ademir

2015-08-01

The scoring of chromosome aberrations is the most reliable biological method for evaluating individual exposure to ionizing radiation. However, microscopic analyses of chromosome human metaphases, generally employed to identify aberrations mainly dicentrics (chromosome with two centromeres), is a laborious task. This method is time consuming and its application in biological dosimetry would be almost impossible in case of a large scale radiation incidents. In this project, a generic software was enhanced for automatic chromosome image processing from a framework originally developed for the Framework V project Simbio, of the European Union for applications in the area of source localization from electroencephalographic signals. The platforms capability is demonstrated by a study comparing automatic segmentation strategies of chromosomes from microscopic images.

Error measuring system of rotary Inductosyn

NASA Astrophysics Data System (ADS)

Liu, Chengjun; Zou, Jibin; Fu, Xinghe

2008-10-01

The inductosyn is a kind of high-precision angle-position sensor. It has important applications in servo table, precision machine tool and other products. The precision of inductosyn is calibrated by its error. It's an important problem about the error measurement in the process of production and application of the inductosyn. At present, it mainly depends on the method of artificial measurement to obtain the error of inductosyn. Therefore, the disadvantages can't be ignored such as the high labour intensity of the operator, the occurrent error which is easy occurred and the poor repeatability, and so on. In order to solve these problems, a new automatic measurement method is put forward in this paper which based on a high precision optical dividing head. Error signal can be obtained by processing the output signal of inductosyn and optical dividing head precisely. When inductosyn rotating continuously, its zero position error can be measured dynamically, and zero error curves can be output automatically. The measuring and calculating errors caused by man-made factor can be overcome by this method, and it makes measuring process more quickly, exactly and reliably. Experiment proves that the accuracy of error measuring system is 1.1 arc-second (peak - peak value).

Acousto-optic RF signal acquisition system

NASA Astrophysics Data System (ADS)

Bloxham, Laurence H.

1990-09-01

This paper describes the architecture and performance of a prototype Acousto-Optic RF Signal Acquisition System designed to intercept, automatically identify, and track communication signals in the VHF band. The system covers 28.0 to 92.0 MHz with five manually selectable, dual conversion; 12.8 MHZ bandwidth front ends. An acousto-optic spectrum analyzer (AOSA) implemented using a tellurium dioxide (Te02) Bragg cell is used to channelize the 12.8 MHz pass band into 512 25 KHz channels. Polarization switching is used to suppress optical noise. Excellent isolation and dynamic range are achieved by using a linear array of 512 custom 40/50 micron fiber optic cables to collect the light at the focal plane of the AOSA and route the light to individual photodetectors. The photodetectors are operated in the photovoltaic mode to compress the greater than 60 dB input optical dynamic range into an easily processed electrical signal. The 512 signals are multiplexed and processed as a line in a video image by a customized digital image processing system. The image processor simultaneously analyzes the channelized signal data and produces a classical waterfall display.

30 CFR 27.23 - Automatic warning device.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Automatic warning device. 27.23 Section 27.23... Automatic warning device. (a) An automatic warning device shall be suitably constructed for incorporation in... automatic warning device shall include an alarm signal (audible or colored light), which shall be made to...

30 CFR 27.23 - Automatic warning device.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Automatic warning device. 27.23 Section 27.23... Automatic warning device. (a) An automatic warning device shall be suitably constructed for incorporation in... automatic warning device shall include an alarm signal (audible or colored light), which shall be made to...

30 CFR 27.23 - Automatic warning device.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Automatic warning device. 27.23 Section 27.23... Automatic warning device. (a) An automatic warning device shall be suitably constructed for incorporation in... automatic warning device shall include an alarm signal (audible or colored light), which shall be made to...

30 CFR 27.23 - Automatic warning device.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Automatic warning device. 27.23 Section 27.23... Automatic warning device. (a) An automatic warning device shall be suitably constructed for incorporation in... automatic warning device shall include an alarm signal (audible or colored light), which shall be made to...

From data towards knowledge: revealing the architecture of signaling systems by unifying knowledge mining and data mining of systematic perturbation data.

PubMed

Lu, Songjian; Jin, Bo; Cowart, L Ashley; Lu, Xinghua

2013-01-01

Genetic and pharmacological perturbation experiments, such as deleting a gene and monitoring gene expression responses, are powerful tools for studying cellular signal transduction pathways. However, it remains a challenge to automatically derive knowledge of a cellular signaling system at a conceptual level from systematic perturbation-response data. In this study, we explored a framework that unifies knowledge mining and data mining towards the goal. The framework consists of the following automated processes: 1) applying an ontology-driven knowledge mining approach to identify functional modules among the genes responding to a perturbation in order to reveal potential signals affected by the perturbation; 2) applying a graph-based data mining approach to search for perturbations that affect a common signal; and 3) revealing the architecture of a signaling system by organizing signaling units into a hierarchy based on their relationships. Applying this framework to a compendium of yeast perturbation-response data, we have successfully recovered many well-known signal transduction pathways; in addition, our analysis has led to many new hypotheses regarding the yeast signal transduction system; finally, our analysis automatically organized perturbed genes as a graph reflecting the architecture of the yeast signaling system. Importantly, this framework transformed molecular findings from a gene level to a conceptual level, which can be readily translated into computable knowledge in the form of rules regarding the yeast signaling system, such as "if genes involved in the MAPK signaling are perturbed, genes involved in pheromone responses will be differentially expressed."

Study of the time and effort signal in cutting operations

NASA Astrophysics Data System (ADS)

Grosset, E.; Maillard, A.; Bouhelier, C.; Gasnier, J.

1990-02-01

Perception and treatment of an effort signal by computer methods is discussed. An automatic control system used to measure the wear of machine tools and carry out quality control throughout the cutting process is described. The testing system is used to evaluate the performance of tools which have been vacuum plated. The system is used as part of the BRITE study, the goal of which is to develop an expert system for measuring the wear of tools used during drilling and perforation operations.

Proteomic Prediction of Breast Cancer Risk: A Cohort Study

DTIC Science & Technology

2007-03-01

Total 1728 1189 68.81 (c) Data processing. Data analysis was performed using in-house software (Du P , Angeletti RH. Automatic deconvolution of...isotope-resolved mass spectra using variable selection and quantized peptide mass distribution. Anal Chem., 78:3385-92, 2006; P Du, R Sudha, MB...control. Reportable Outcomes So far our publications have been on the development of algorithms for signal processing: 1. Du P , Angeletti RH

Design and Realization of Controllable Ultrasonic Fault Detector Automatic Verification System

NASA Astrophysics Data System (ADS)

Sun, Jing-Feng; Liu, Hui-Ying; Guo, Hui-Juan; Shu, Rong; Wei, Kai-Li

The ultrasonic flaw detection equipment with remote control interface is researched and the automatic verification system is developed. According to use extensible markup language, the building of agreement instruction set and data analysis method database in the system software realizes the controllable designing and solves the diversification of unreleased device interfaces and agreements. By using the signal generator and a fixed attenuator cascading together, a dynamic error compensation method is proposed, completes what the fixed attenuator does in traditional verification and improves the accuracy of verification results. The automatic verification system operating results confirms that the feasibility of the system hardware and software architecture design and the correctness of the analysis method, while changes the status of traditional verification process cumbersome operations, and reduces labor intensity test personnel.

Automatic and controlled processing in the corticocerebellar system.

PubMed

Ramnani, Narender

2014-01-01

During learning, performance changes often involve a transition from controlled processing in which performance is flexible and responsive to ongoing error feedback, but effortful and slow, to a state in which processing becomes swift and automatic. In this state, performance is unencumbered by the requirement to process feedback, but its insensitivity to feedback reduces its flexibility. Many properties of automatic processing are similar to those that one would expect of forward models, and many have suggested that these may be instantiated in cerebellar circuitry. Since hierarchically organized frontal lobe areas can both send and receive commands, I discuss the possibility that they can act both as controllers and controlled objects and that their behaviors can be independently modeled by forward models in cerebellar circuits. Since areas of the prefrontal cortex contribute to this hierarchically organized system and send outputs to the cerebellar cortex, I suggest that the cerebellum is likely to contribute to the automation of cognitive skills, and to the formation of habitual behavior which is resistant to error feedback. An important prerequisite to these ideas is that cerebellar circuitry should have access to higher order error feedback that signals the success or failure of cognitive processing. I have discussed the pathways through which such feedback could arrive via the inferior olive and the dopamine system. Cerebellar outputs inhibit both the inferior olive and the dopamine system. It is possible that learned representations in the cerebellum use this as a mechanism to suppress the processing of feedback in other parts of the nervous system. Thus, cerebellar processes that control automatic performance may be completed without triggering the engagement of controlled processes by prefrontal mechanisms. © 2014 Elsevier B.V. All rights reserved.

Long-Term Aftereffects of Response Inhibition: Memory Retrieval, Task Goals, and Cognitive Control

ERIC Educational Resources Information Center

Verbruggen, Frederick; Logan, Gordon D.

2008-01-01

Cognitive control theories attribute control to executive processes that adjust and control behavior online. Theories of automaticity attribute control to memory retrieval. In the present study, online adjustments and memory retrieval were examined, and their roles in controlling performance in the stop-signal paradigm were elucidated. There was…

Sleepers' Lag: Study on Motion and Attention

ERIC Educational Resources Information Center

Raca, Mirko; Tormey, Roland; Dillenbourg, Pierre

2016-01-01

Body language is an essential source of information in everyday communication. Low signal-to-noise ratio prevents us from using it in the automatic processing of student behaviour, an obstacle that we are slowly overcoming with advanced statistical methods. Instead of profiling individual behaviour of students in the classroom, the idea is to…

Methods for Processing and Interpretation of AIS Signals Corrupted by Noise and Packet Collisions

NASA Astrophysics Data System (ADS)

Poļevskis, J.; Krastiņš, M.; Korāts, G.; Skorodumovs, A.; Trokšs, J.

2012-01-01

The authors deal with the operation of Automatic Identification System (AIS) used in the marine traffic monitoring to broadcast messages containing information about the vessel: id, payload, size, speed, destination etc., meant primarily for avoidance of ship collisions. To extend the radius of AIS operation, it is envisaged to dispose its receivers on satellites. However, in space, due to a large coverage area, interfering factors are especially pronounced - such as packet collision, Doppler's shift and noise impact on AIS message receiving, pre-processing and decoding. To assess the quality of an AIS receiver's operation, a test was carried out in which, varying automatically frequency, amplitude, noise, and other parameters, the data on the ability of the receiver's ability to decode AIS signals are collected. In the work, both hardware- and software-based AIS decoders were tested. As a result, quite satisfactory statistics has been gathered - both on the common and the differing features of such decoders when operating in space. To obtain reliable data on the software-defined radio AIS receivers, further research is envisaged.

Automatic target recognition apparatus and method

DOEpatents

Baumgart, Chris W.; Ciarcia, Christopher A.

2000-01-01

An automatic target recognition apparatus (10) is provided, having a video camera/digitizer (12) for producing a digitized image signal (20) representing an image containing therein objects which objects are to be recognized if they meet predefined criteria. The digitized image signal (20) is processed within a video analysis subroutine (22) residing in a computer (14) in a plurality of parallel analysis chains such that the objects are presumed to be lighter in shading than the background in the image in three of the chains and further such that the objects are presumed to be darker than the background in the other three chains. In two of the chains the objects are defined by surface texture analysis using texture filter operations. In another two of the chains the objects are defined by background subtraction operations. In yet another two of the chains the objects are defined by edge enhancement processes. In each of the analysis chains a calculation operation independently determines an error factor relating to the probability that the objects are of the type which should be recognized, and a probability calculation operation combines the results of the analysis chains.

49 CFR 236.564 - Acknowledging time.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives § 236.564 Acknowledging time. Acknowledging time of intermittent automatic train-stop device shall be not more than 30 seconds. ...

A boost of confidence: The role of the ventromedial prefrontal cortex in memory, decision-making, and schemas.

PubMed

Hebscher, Melissa; Gilboa, Asaf

2016-09-01

The ventromedial prefrontal cortex (vmPFC) has been implicated in a wide array of functions across multiple domains. In this review, we focus on the vmPFC's involvement in mediating strategic aspects of memory retrieval, memory-related schema functions, and decision-making. We suggest that vmPFC generates a confidence signal that informs decisions and memory-guided behaviour. Confidence is central to these seemingly diverse functions: (1) Strategic retrieval: lesions to the vmPFC impair an early, automatic, and intuitive monitoring process ("feeling of rightness"; FOR) often associated with confabulation (spontaneous reporting of erroneous memories). Critically, confabulators typically demonstrate high levels of confidence in their false memories, suggesting that faulty monitoring following vmPFC damage may lead to indiscriminate confidence signals. (2) Memory schemas: the vmPFC is critically involved in instantiating and maintaining contextually relevant schemas, broadly defined as higher level knowledge structures that encapsulate lower level representational elements. The correspondence between memory retrieval cues and these activated schemas leads to FOR monitoring. Stronger, more elaborate schemas produce stronger FOR and influence confidence in the veracity of memory candidates. (3) Finally, we review evidence on the vmPFC's role in decision-making, extending this role to decision-making during memory retrieval. During non-mnemonic and mnemonic decision-making the vmPFC automatically encodes confidence. Confidence signal in the vmPFC is revealed as a non-linear relationship between a first-order monitoring assessment and second-order action or choice. Attempting to integrate the multiple functions of the vmPFC, we propose a posterior-anterior organizational principle for this region. More posterior vmPFC regions are involved in earlier, automatic, subjective, and contextually sensitive functions, while more anterior regions are involved in controlled actions based on these earlier functions. Confidence signals reflect the non-linear relationship between first-order, posterior-mediated and second-order, anterior-mediated processes and are represented along the entire axis. Copyright © 2016 Elsevier Ltd. All rights reserved.

SIG. Signal Processing, Analysis, & Display

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

Hernandez, J.; Lager, D.; Azevedo, S.

1992-01-22

SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Two user interfaces are provided in SIG; a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time and frequency-domain signals includingmore » operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments, commenting lines, defining commands, and automatic execution for each item in a `repeat` sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.« less

SIG. Signal Processing, Analysis, & Display

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

Hernandez, J.; Lager, D.; Azevedo, S.

1992-01-22

SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time-and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Two user interfaces are provided in SIG - a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time and frequency-domain signals includingmore » operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments, commenting lines, defining commands, and automatic execution for each item in a repeat sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.« less

Workshop on Algorithms for Time-Series Analysis

NASA Astrophysics Data System (ADS)

Protopapas, Pavlos

2012-04-01

abstract-type="normal">SummaryThis Workshop covered the four major subjects listed below in two 90-minute sessions. Each talk or tutorial allowed questions, and concluded with a discussion. Classification: Automatic classification using machine-learning methods is becoming a standard in surveys that generate large datasets. Ashish Mahabal (Caltech) reviewed various methods, and presented examples of several applications. Time-Series Modelling: Suzanne Aigrain (Oxford University) discussed autoregressive models and multivariate approaches such as Gaussian Processes. Meta-classification/mixture of expert models: Karim Pichara (Pontificia Universidad Católica, Chile) described the substantial promise which machine-learning classification methods are now showing in automatic classification, and discussed how the various methods can be combined together. Event Detection: Pavlos Protopapas (Harvard) addressed methods of fast identification of events with low signal-to-noise ratios, enlarging on the characterization and statistical issues of low signal-to-noise ratios and rare events.

Ultrasonic guided wave interpretation for structural health inspections

NASA Astrophysics Data System (ADS)

Bingham, Jill Paisley

Structural Health Management (SHM) combines the use of onboard sensors with artificial intelligence algorithms to automatically identify and monitor structural health issues. A fully integrated approach to SHM systems demands an understanding of the sensor output relative to the structure, along with sophisticated prognostic systems that automatically draw conclusions about structural integrity issues. Ultrasonic guided wave methods allow us to examine the interaction of multimode signals within key structural components. Since they propagate relatively long distances within plate- and shell-like structures, guided waves allow inspection of greater areas with fewer sensors, making this technique attractive for a variety of applications. This dissertation describes the experimental development of automatic guided wave interpretation for three real world applications. Using the guided wave theories for idealized plates we have systematically developed techniques for identifying the mass loading of underwater limpet mines on US Navy ship hulls, characterizing type and bonding of protective coatings on large diameter pipelines, and detecting the thinning effects of corrosion on aluminum aircraft structural stringers. In each of these circumstances the signals received are too complex for interpretation without knowledge of the guided wave physics. We employ a signal processing technique called the Dynamic Wavelet Fingerprint Technique (DFWT) in order to render the guided wave mode information in two-dimensional binary images. The use of wavelets allows us to keep track of both time and scale features from the original signals. With simple image processing we have developed automatic extraction algorithms for features that correspond to the arrival times of the guided wave modes of interest for each of the applications. Due to the dispersive nature of the guided wave modes, the mode arrival times give details of the structure in the propagation path. For further understanding of how the guided wave modes propagate through the real structures, we have developed parallel processing, 3D elastic wave simulations using the finite integration technique (EFIT). This full field, numeric simulation technique easily examines models too complex for analytical solutions. We have developed the algorithm to handle built up 3D structures as well as layers with different material properties and surface detail. The simulations produce informative visualizations of the guided wave modes in the structures as well as the output from sensors placed in the simulation space to mimic the placement from experiment. Using the previously developed mode extraction algorithms we were then able to compare our 3D EFIT data to their experimental counterparts with consistency.

Sparsity guided empirical wavelet transform for fault diagnosis of rolling element bearings

NASA Astrophysics Data System (ADS)

Wang, Dong; Zhao, Yang; Yi, Cai; Tsui, Kwok-Leung; Lin, Jianhui

2018-02-01

Rolling element bearings are widely used in various industrial machines, such as electric motors, generators, pumps, gearboxes, railway axles, turbines, and helicopter transmissions. Fault diagnosis of rolling element bearings is beneficial to preventing any unexpected accident and reducing economic loss. In the past years, many bearing fault detection methods have been developed. Recently, a new adaptive signal processing method called empirical wavelet transform attracts much attention from readers and engineers and its applications to bearing fault diagnosis have been reported. The main problem of empirical wavelet transform is that Fourier segments required in empirical wavelet transform are strongly dependent on the local maxima of the amplitudes of the Fourier spectrum of a signal, which connotes that Fourier segments are not always reliable and effective if the Fourier spectrum of the signal is complicated and overwhelmed by heavy noises and other strong vibration components. In this paper, sparsity guided empirical wavelet transform is proposed to automatically establish Fourier segments required in empirical wavelet transform for fault diagnosis of rolling element bearings. Industrial bearing fault signals caused by single and multiple railway axle bearing defects are used to verify the effectiveness of the proposed sparsity guided empirical wavelet transform. Results show that the proposed method can automatically discover Fourier segments required in empirical wavelet transform and reveal single and multiple railway axle bearing defects. Besides, some comparisons with three popular signal processing methods including ensemble empirical mode decomposition, the fast kurtogram and the fast spectral correlation are conducted to highlight the superiority of the proposed method.

Automatic identification of alpine mass movements based on seismic and infrasound signals

NASA Astrophysics Data System (ADS)

Schimmel, Andreas; Hübl, Johannes

2017-04-01

The automatic detection and identification of alpine mass movements like debris flows, debris floods or landslides gets increasing importance for mitigation measures in the densely populated and intensively used alpine regions. Since this mass movement processes emits characteristically seismic and acoustic waves in the low frequency range this events can be detected and identified based on this signals. So already several approaches for detection and warning systems based on seismic or infrasound signals has been developed. But a combination of both methods, which can increase detection probability and reduce false alarms is currently used very rarely and can serve as a promising method for developing an automatic detection and identification system. So this work presents an approach for a detection and identification system based on a combination of seismic and infrasound sensors, which can detect sediment related mass movements from a remote location unaffected by the process. The system is based on one infrasound sensor and one geophone which are placed co-located and a microcontroller where a specially designed detection algorithm is executed which can detect mass movements in real time directly at the sensor site. Further this work tries to get out more information from the seismic and infrasound spectrum produced by different sediment related mass movements to identify the process type and estimate the magnitude of the event. The system is currently installed and tested on five test sites in Austria, two in Italy and one in Switzerland as well as one in Germany. This high number of test sites is used to get a large database of very different events which will be the basis for a new identification method for alpine mass movements. These tests shows promising results and so this system provides an easy to install and inexpensive approach for a detection and warning system.

49 CFR 236.507 - Brake application; full service.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.507 Brake application; full service. The automatic train stop or train control apparatus shall, when operated, cause a full service...

49 CFR 236.507 - Brake application; full service.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.507 Brake application; full service. The automatic train stop or train control apparatus shall, when operated, cause a full service...

Detecting REM sleep from the finger: an automatic REM sleep algorithm based on peripheral arterial tone (PAT) and actigraphy.

PubMed

Herscovici, Sarah; Pe'er, Avivit; Papyan, Surik; Lavie, Peretz

2007-02-01

Scoring of REM sleep based on polysomnographic recordings is a laborious and time-consuming process. The growing number of ambulatory devices designed for cost-effective home-based diagnostic sleep recordings necessitates the development of a reliable automatic REM sleep detection algorithm that is not based on the traditional electroencephalographic, electrooccolographic and electromyographic recordings trio. This paper presents an automatic REM detection algorithm based on the peripheral arterial tone (PAT) signal and actigraphy which are recorded with an ambulatory wrist-worn device (Watch-PAT100). The PAT signal is a measure of the pulsatile volume changes at the finger tip reflecting sympathetic tone variations. The algorithm was developed using a training set of 30 patients recorded simultaneously with polysomnography and Watch-PAT100. Sleep records were divided into 5 min intervals and two time series were constructed from the PAT amplitudes and PAT-derived inter-pulse periods in each interval. A prediction function based on 16 features extracted from the above time series that determines the likelihood of detecting a REM epoch was developed. The coefficients of the prediction function were determined using a genetic algorithm (GA) optimizing process tuned to maximize a price function depending on the sensitivity, specificity and agreement of the algorithm in comparison with the gold standard of polysomnographic manual scoring. Based on a separate validation set of 30 patients overall sensitivity, specificity and agreement of the automatic algorithm to identify standard 30 s epochs of REM sleep were 78%, 92%, 89%, respectively. Deploying this REM detection algorithm in a wrist worn device could be very useful for unattended ambulatory sleep monitoring. The innovative method of optimization using a genetic algorithm has been proven to yield robust results in the validation set.

Signal Processing, Analysis, & Display

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

Lager, Darrell; Azevado, Stephen

1986-06-01

SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Two user interfaces are provided in SIG - a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time- and frequency-domain signalsmore » including operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments,commenting lines, defining commands, and automatic execution for each item in a repeat sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.« less

SIG. Signal Processing, Analysis, & Display

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

Hernandez, J.; Lager, D.; Azevedo, S.

1992-01-22

SIG is a general-purpose signal processing, analysis, and display program. Its main purpose is to perform manipulations on time- and frequency-domain signals. However, it has been designed to ultimately accommodate other representations for data such as multiplexed signals and complex matrices. Two user interfaces are provided in SIG - a menu mode for the unfamiliar user and a command mode for more experienced users. In both modes errors are detected as early as possible and are indicated by friendly, meaningful messages. An on-line HELP package is also included. A variety of operations can be performed on time- and frequency-domain signalsmore » including operations on the samples of a signal, operations on the entire signal, and operations on two or more signals. Signal processing operations that can be performed are digital filtering (median, Bessel, Butterworth, and Chebychev), ensemble average, resample, auto and cross spectral density, transfer function and impulse response, trend removal, convolution, Fourier transform and inverse window functions (Hamming, Kaiser-Bessel), simulation (ramp, sine, pulsetrain, random), and read/write signals. User definable signal processing algorithms are also featured. SIG has many options including multiple commands per line, command files with arguments,commenting lines, defining commands, and automatic execution for each item in a repeat sequence. Graphical operations on signals and spectra include: x-y plots of time signals; real, imaginary, magnitude, and phase plots of spectra; scaling of spectra for continuous or discrete domain; cursor zoom; families of curves; and multiple viewports.« less

Mobile Healthcare for Automatic Driving Sleep-Onset Detection Using Wavelet-Based EEG and Respiration Signals

PubMed Central

Lee, Boon-Giin; Lee, Boon-Leng; Chung, Wan-Young

2014-01-01

Driving drowsiness is a major cause of traffic accidents worldwide and has drawn the attention of researchers in recent decades. This paper presents an application for in-vehicle non-intrusive mobile-device-based automatic detection of driver sleep-onset in real time. The proposed application classifies the driving mental fatigue condition by analyzing the electroencephalogram (EEG) and respiration signals of a driver in the time and frequency domains. Our concept is heavily reliant on mobile technology, particularly remote physiological monitoring using Bluetooth. Respiratory events are gathered, and eight-channel EEG readings are captured from the frontal, central, and parietal (Fpz-Cz, Pz-Oz) regions. EEGs are preprocessed with a Butterworth bandpass filter, and features are subsequently extracted from the filtered EEG signals by employing the wavelet-packet-transform (WPT) method to categorize the signals into four frequency bands: α, β, θ, and δ. A mutual information (MI) technique selects the most descriptive features for further classification. The reduction in the number of prominent features improves the sleep-onset classification speed in the support vector machine (SVM) and results in a high sleep-onset recognition rate. Test results reveal that the combined use of the EEG and respiration signals results in 98.6% recognition accuracy. Our proposed application explores the possibility of processing long-term multi-channel signals. PMID:25264954

Data mining spacecraft telemetry: towards generic solutions to automatic health monitoring and status characterisation

NASA Astrophysics Data System (ADS)

Royer, P.; De Ridder, J.; Vandenbussche, B.; Regibo, S.; Huygen, R.; De Meester, W.; Evans, D. J.; Martinez, J.; Korte-Stapff, M.

2016-07-01

We present the first results of a study aimed at finding new and efficient ways to automatically process spacecraft telemetry for automatic health monitoring. The goal is to reduce the load on the flight control team while extending the "checkability" to the entire telemetry database, and provide efficient, robust and more accurate detection of anomalies in near real time. We present a set of effective methods to (a) detect outliers in the telemetry or in its statistical properties, (b) uncover and visualise special properties of the telemetry and (c) detect new behavior. Our results are structured around two main families of solutions. For parameters visiting a restricted set of signal values, i.e. all status parameters and about one third of all the others, we focus on a transition analysis, exploiting properties of Poincare plots. For parameters with an arbitrarily high number of possible signal values, we describe the statistical properties of the signal via its Kernel Density Estimate. We demonstrate that this allows for a generic and dynamic approach of the soft-limit definition. Thanks to a much more accurate description of the signal and of its time evolution, we are more sensitive and more responsive to outliers than the traditional checks against hard limits. Our methods were validated on two years of Venus Express telemetry. They are generic for assisting in health monitoring of any complex system with large amounts of diagnostic sensor data. Not only spacecraft systems but also present-day astronomical observatories can benefit from them.

49 CFR 236.825 - System, automatic train control.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false System, automatic train control. 236.825 Section..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.825 System, automatic train control. A system so arranged that its operation will automatically...

49 CFR 236.825 - System, automatic train control.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false System, automatic train control. 236.825 Section..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.825 System, automatic train control. A system so arranged that its operation will automatically...

49 CFR 236.552 - Insulation resistance; requirement.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic... control system, or automatic train stop system shall be not less than one megohm, and that of an... system, automatic train control system, or automatic train stop system, and 20,000 ohms for an...

49 CFR 236.562 - Minimum rail current required.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives § 236.562 Minimum... continuous inductive automatic train stop or train control device to normal condition or to obtain a proceed...

49 CFR 236.562 - Minimum rail current required.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives § 236.562 Minimum... continuous inductive automatic train stop or train control device to normal condition or to obtain a proceed...

Automatic Methods in Image Processing and Their Relevance to Map-Making.

DTIC Science & Technology

1981-02-11

23b) and ECfg ) = DC1 1 reIc (5-24) Is an example, let the image function f be white noise so that Cf( ) = s, ,), the Dirac impulse . Then (5-24...based on image and correlator models which describe the behavior of correlation processors under condi- tions of low image contrast or signal-to- noise ...71 Sensor Noise ......................... 74 Self Noise .7.................. 6 Ma chine Noise ................ 81 Fixed Point Processing

Automated seismic detection of landslides at regional scales: a Random Forest based detection algorithm

NASA Astrophysics Data System (ADS)

Hibert, C.; Michéa, D.; Provost, F.; Malet, J. P.; Geertsema, M.

2017-12-01

Detection of landslide occurrences and measurement of their dynamics properties during run-out is a high research priority but a logistical and technical challenge. Seismology has started to help in several important ways. Taking advantage of the densification of global, regional and local networks of broadband seismic stations, recent advances now permit the seismic detection and location of landslides in near-real-time. This seismic detection could potentially greatly increase the spatio-temporal resolution at which we study landslides triggering, which is critical to better understand the influence of external forcings such as rainfalls and earthquakes. However, detecting automatically seismic signals generated by landslides still represents a challenge, especially for events with small mass. The low signal-to-noise ratio classically observed for landslide-generated seismic signals and the difficulty to discriminate these signals from those generated by regional earthquakes or anthropogenic and natural noises are some of the obstacles that have to be circumvented. We present a new method for automatically constructing instrumental landslide catalogues from continuous seismic data. We developed a robust and versatile solution, which can be implemented in any context where a seismic detection of landslides or other mass movements is relevant. The method is based on a spectral detection of the seismic signals and the identification of the sources with a Random Forest machine learning algorithm. The spectral detection allows detecting signals with low signal-to-noise ratio, while the Random Forest algorithm achieve a high rate of positive identification of the seismic signals generated by landslides and other seismic sources. The processing chain is implemented to work in a High Performance Computers centre which permits to explore years of continuous seismic data rapidly. We present here the preliminary results of the application of this processing chain for years of continuous seismic record by the Alaskan permanent seismic network and Hi-Climb trans-Himalayan seismic network. The processing chain we developed also opens the possibility for a near-real time seismic detection of landslides, in association with remote-sensing automated detection from Sentinel 2 images for example.

Automatic video summarization driven by a spatio-temporal attention model

NASA Astrophysics Data System (ADS)

Barland, R.; Saadane, A.

2008-02-01

According to the literature, automatic video summarization techniques can be classified in two parts, following the output nature: "video skims", which are generated using portions of the original video and "key-frame sets", which correspond to the images, selected from the original video, having a significant semantic content. The difference between these two categories is reduced when we consider automatic procedures. Most of the published approaches are based on the image signal and use either pixel characterization or histogram techniques or image decomposition by blocks. However, few of them integrate properties of the Human Visual System (HVS). In this paper, we propose to extract keyframes for video summarization by studying the variations of salient information between two consecutive frames. For each frame, a saliency map is produced simulating the human visual attention by a bottom-up (signal-dependent) approach. This approach includes three parallel channels for processing three early visual features: intensity, color and temporal contrasts. For each channel, the variations of the salient information between two consecutive frames are computed. These outputs are then combined to produce the global saliency variation which determines the key-frames. Psychophysical experiments have been defined and conducted to analyze the relevance of the proposed key-frame extraction algorithm.

fMRat: an extension of SPM for a fully automatic analysis of rodent brain functional magnetic resonance series.

PubMed

Chavarrías, Cristina; García-Vázquez, Verónica; Alemán-Gómez, Yasser; Montesinos, Paula; Pascau, Javier; Desco, Manuel

2016-05-01

The purpose of this study was to develop a multi-platform automatic software tool for full processing of fMRI rodent studies. Existing tools require the usage of several different plug-ins, a significant user interaction and/or programming skills. Based on a user-friendly interface, the tool provides statistical parametric brain maps (t and Z) and percentage of signal change for user-provided regions of interest. The tool is coded in MATLAB (MathWorks(®)) and implemented as a plug-in for SPM (Statistical Parametric Mapping, the Wellcome Trust Centre for Neuroimaging). The automatic pipeline loads default parameters that are appropriate for preclinical studies and processes multiple subjects in batch mode (from images in either Nifti or raw Bruker format). In advanced mode, all processing steps can be selected or deselected and executed independently. Processing parameters and workflow were optimized for rat studies and assessed using 460 male-rat fMRI series on which we tested five smoothing kernel sizes and three different hemodynamic models. A smoothing kernel of FWHM = 1.2 mm (four times the voxel size) yielded the highest t values at the somatosensorial primary cortex, and a boxcar response function provided the lowest residual variance after fitting. fMRat offers the features of a thorough SPM-based analysis combined with the functionality of several SPM extensions in a single automatic pipeline with a user-friendly interface. The code and sample images can be downloaded from https://github.com/HGGM-LIM/fmrat .

Automatic Carbon Dioxide-Methane Gas Sensor Based on the Solubility of Gases in Water

PubMed Central

Cadena-Pereda, Raúl O.; Rivera-Muñoz, Eric M.; Herrera-Ruiz, Gilberto; Gomez-Melendez, Domingo J.; Anaya-Rivera, Ely K.

2012-01-01

Biogas methane content is a relevant variable in anaerobic digestion processing where knowledge of process kinetics or an early indicator of digester failure is needed. The contribution of this work is the development of a novel, simple and low cost automatic carbon dioxide-methane gas sensor based on the solubility of gases in water as the precursor of a sensor for biogas quality monitoring. The device described in this work was used for determining the composition of binary mixtures, such as carbon dioxide-methane, in the range of 0–100%. The design and implementation of a digital signal processor and control system into a low-cost Field Programmable Gate Array (FPGA) platform has permitted the successful application of data acquisition, data distribution and digital data processing, making the construction of a standalone carbon dioxide-methane gas sensor possible. PMID:23112626

Automatic carbon dioxide-methane gas sensor based on the solubility of gases in water.

PubMed

Cadena-Pereda, Raúl O; Rivera-Muñoz, Eric M; Herrera-Ruiz, Gilberto; Gomez-Melendez, Domingo J; Anaya-Rivera, Ely K

2012-01-01

Biogas methane content is a relevant variable in anaerobic digestion processing where knowledge of process kinetics or an early indicator of digester failure is needed. The contribution of this work is the development of a novel, simple and low cost automatic carbon dioxide-methane gas sensor based on the solubility of gases in water as the precursor of a sensor for biogas quality monitoring. The device described in this work was used for determining the composition of binary mixtures, such as carbon dioxide-methane, in the range of 0-100%. The design and implementation of a digital signal processor and control system into a low-cost Field Programmable Gate Array (FPGA) platform has permitted the successful application of data acquisition, data distribution and digital data processing, making the construction of a standalone carbon dioxide-methane gas sensor possible.

Automatic characterization of sleep need dissipation dynamics using a single EEG signal.

PubMed

Garcia-Molina, Gary; Bellesi, Michele; Riedner, Brady; Pastoor, Sander; Pfundtner, Stefan; Tononi, Giulio

2015-01-01

In the two-process model of sleep regulation, slow-wave activity (SWA, i.e. the EEG power in the 0.5-4 Hz frequency band) is considered a direct indicator of sleep need. SWA builds up during non-rapid eye movement (NREM) sleep, declines before the onset of rapid-eye-movement (REM) sleep, remains low during REM and the level of increase in successive NREM episodes gets progressively lower. Sleep need dissipates with a speed that is proportional to SWA and can be characterized in terms of the initial sleep need, and the decay rate. The goal in this paper is to automatically characterize sleep need from a single EEG signal acquired at a frontal location. To achieve this, a highly specific and reasonably sensitive NREM detection algorithm is proposed that leverages the concept of a single-class Kernel-based classifier. Using automatic NREM detection, we propose a method to estimate the decay rate and the initial sleep need. This method was tested on experimental data from 8 subjects who recorded EEG during three nights at home. We found that on average the estimates of the decay rate and the initial sleep need have higher values when automatic NREM detection was used as compared to manual NREM annotation. However, the average variability of these estimates across multiple nights of the same subject was lower when the automatic NREM detection classifier was used. While this method slightly over estimates the sleep need parameters, the reduced variability across subjects makes it more effective for within subject statistical comparisons of a given sleep intervention.

Automatic differential analysis of NMR experiments in complex samples.

PubMed

Margueritte, Laure; Markov, Petar; Chiron, Lionel; Starck, Jean-Philippe; Vonthron-Sénécheau, Catherine; Bourjot, Mélanie; Delsuc, Marc-André

2018-06-01

Liquid state nuclear magnetic resonance (NMR) is a powerful tool for the analysis of complex mixtures of unknown molecules. This capacity has been used in many analytical approaches: metabolomics, identification of active compounds in natural extracts, and characterization of species, and such studies require the acquisition of many diverse NMR measurements on series of samples. Although acquisition can easily be performed automatically, the number of NMR experiments involved in these studies increases very rapidly, and this data avalanche requires to resort to automatic processing and analysis. We present here a program that allows the autonomous, unsupervised processing of a large corpus of 1D, 2D, and diffusion-ordered spectroscopy experiments from a series of samples acquired in different conditions. The program provides all the signal processing steps, as well as peak-picking and bucketing of 1D and 2D spectra, the program and its components are fully available. In an experiment mimicking the search of a bioactive species in a natural extract, we use it for the automatic detection of small amounts of artemisinin added to a series of plant extracts and for the generation of the spectral fingerprint of this molecule. This program called Plasmodesma is a novel tool that should be useful to decipher complex mixtures, particularly in the discovery of biologically active natural products from plants extracts but can also in drug discovery or metabolomics studies. Copyright © 2017 John Wiley & Sons, Ltd.

AUTOMATIC COUNTER

DOEpatents

Robinson, H.P.

1960-06-01

An automatic counter of alpha particle tracks recorded by a sensitive emulsion of a photographic plate is described. The counter includes a source of mcdulated dark-field illumination for developing light flashes from the recorded particle tracks as the photographic plate is automatically scanned in narrow strips. Photoelectric means convert the light flashes to proportional current pulses for application to an electronic counting circuit. Photoelectric means are further provided for developing a phase reference signal from the photographic plate in such a manner that signals arising from particle tracks not parallel to the edge of the plate are out of phase with the reference signal. The counting circuit includes provision for rejecting the out-of-phase signals resulting from unoriented tracks as well as signals resulting from spurious marks on the plate such as scratches, dust or grain clumpings, etc. The output of the circuit is hence indicative only of the tracks that would be counted by a human operator.

Fiber optic crossbar switch for automatically patching optical signals

NASA Technical Reports Server (NTRS)

Bell, C. H. (Inventor)

1983-01-01

A system for automatically optically switching fiber optic data signals between a plurality of input optical fibers and selective ones of a plurality of output fibers is described. The system includes optical detectors which are connected to each of the input fibers for converting the optic data signals appearing at the respective input fibers to an RF signal. A plurality of RF to optical signal converters are arranged in rows and columns. The output of each of the optical detectors are each applied to a respective row of optical signal converted for being converters back to an optical signal when the particular optical signal converter is selectively activated by a dc voltage.

49 CFR 236.826 - System, automatic train stop.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false System, automatic train stop. 236.826 Section 236..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.826 System, automatic train stop. A system so arranged that its operation will automatically...

49 CFR 236.826 - System, automatic train stop.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false System, automatic train stop. 236.826 Section 236..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.826 System, automatic train stop. A system so arranged that its operation will automatically...

49 CFR 236.528 - Restrictive condition resulting from open hand-operated switch; requirement.

Code of Federal Regulations, 2010 CFR

2010-10-01

... INSTRUCTIONS GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and... with circuit controller is used, the resultant restrictive condition of an automatic train stop or...

49 CFR 236.528 - Restrictive condition resulting from open hand-operated switch; requirement.

Code of Federal Regulations, 2011 CFR

2011-10-01

... INSTRUCTIONS GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and... with circuit controller is used, the resultant restrictive condition of an automatic train stop or...

49 CFR 236.554 - Rate of pressure reduction; equalizing reservoir or brake pipe.

Code of Federal Regulations, 2011 CFR

2011-10-01

... GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions... pressure or brake-pipe pressure reduction during an automatic brake application shall be at a rate not less...

49 CFR 236.554 - Rate of pressure reduction; equalizing reservoir or brake pipe.

Code of Federal Regulations, 2010 CFR

2010-10-01

... GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions... pressure or brake-pipe pressure reduction during an automatic brake application shall be at a rate not less...

Methodology Investigation Automatic Magnetic Recording Borescope.

DTIC Science & Technology

1986-01-01

or other brushless signal coupling devices to the extent possible and feasible to reduce or eliminate the need for slip ring and brush type signal...the inspection head, is used to magnetically couple the necessary energy across the rotary interface. Because there is (1) an appreciable air gap in...were written. (2) As required by the contract, the signal conditioners in the MB employ automatic gain control to compensate for the changes in

Automatic and Controlled Response Inhibition: Associative Learning in the Go/No-Go and Stop-Signal Paradigms

PubMed Central

Verbruggen, Frederick; Logan, Gordon D.

2008-01-01

In five experiments, the authors examined the development of automatic response inhibition in the go/no-go paradigm and a modified version of the stop-signal paradigm. They hypothesized that automatic response inhibition may develop over practice when stimuli are consistently associated with stopping. All five experiments consisted of a training phase and a test phase in which the stimulus mapping was reversed for a subset of the stimuli. Consistent with the automatic-inhibition hypothesis, the authors found that responding in the test phase was slowed when the stimulus had been consistently associated with stopping in the training phase. In addition, they found that response inhibition benefited from consistent stimulus-stop associations. These findings suggest that response inhibition may rely on the retrieval of stimulus-stop associations after practice with consistent stimulus-stop mappings. Stimulus-stop mapping is typically consistent in the go/no-go paradigm, so automatic inhibition is likely to occur. However, stimulus-stop mapping is typically inconsistent in the stop-signal paradigm, so automatic inhibition is unlikely to occur. Thus, the results suggest that the two paradigms are not equivalent because they allow different kinds of response inhibition. PMID:18999358

Should I Stop or Should I Go? The Role of Associations and Expectancies

PubMed Central

2015-01-01

Following exposure to consistent stimulus–stop mappings, response inhibition can become automatized with practice. What is learned is less clear, even though this has important theoretical and practical implications. A recent analysis indicates that stimuli can become associated with a stop signal or with a stop goal. Furthermore, expectancy may play an important role. Previous studies that have used stop or no-go signals to manipulate stimulus–stop learning cannot distinguish between stimulus-signal and stimulus-goal associations, and expectancy has not been measured properly. In the present study, participants performed a task that combined features of the go/no-go task and the stop-signal task in which the stop-signal rule changed at the beginning of each block. The go and stop signals were superimposed over 40 task-irrelevant images. Our results show that participants can learn direct associations between images and the stop goal without mediation via the stop signal. Exposure to the image-stop associations influenced task performance during training, and expectancies measured following task completion or measured within the task. But, despite this, we found an effect of stimulus–stop learning on test performance only when the task increased the task-relevance of the images. This could indicate that the influence of stimulus–stop learning on go performance is strongly influenced by attention to both task-relevant and task-irrelevant stimulus features. More generally, our findings suggest a strong interplay between automatic and controlled processes. PMID:26322688

Automatic measurement of images on astrometric plates

NASA Astrophysics Data System (ADS)

Ortiz Gil, A.; Lopez Garcia, A.; Martinez Gonzalez, J. M.; Yershov, V.

1994-04-01

We present some results on the process of automatic detection and measurement of objects in overlapped fields of astrometric plates. The main steps of our algorithm are the following: determination of the Scale and Tilt between charge coupled devices (CCD) and microscope coordinate systems and estimation of signal-to-noise ratio in each field;--image identification and improvement of its position and size;--image final centering;--image selection and storage. Several parameters allow the use of variable criteria for image identification, characterization and selection. Problems related with faint images and crowded fields will be approached by special techniques (morphological filters, histogram properties and fitting models).

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

Uchida, Y., E-mail: h1312101@mailg.nc-toyama.ac.jp; Takada, E.; Fujisaki, A.

Neutron and γ-ray (n-γ) discrimination with a digital signal processing system has been used to measure the neutron emission profile in magnetic confinement fusion devices. However, a sampling rate must be set low to extend the measurement time because the memory storage is limited. Time jitter decreases a discrimination quality due to a low sampling rate. As described in this paper, a new charge comparison method was developed. Furthermore, automatic n-γ discrimination method was examined using a probabilistic approach. Analysis results were investigated using the figure of merit. Results show that the discrimination quality was improved. Automatic discrimination was appliedmore » using the EM algorithm and k-means algorithm.« less

pySPACE—a signal processing and classification environment in Python

PubMed Central

Krell, Mario M.; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Teiwes, Johannes; Metzen, Jan H.; Kirchner, Elsa A.; Kirchner, Frank

2013-01-01

In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. With the presented software pySPACE (http://pyspace.github.io/pyspace), signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG). The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms, and evaluation schemes. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. In the presented work, the structural hierarchies are described. It is illustrated how users and developers can interface the software and execute offline and online modes. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. It further allows to define own algorithms, or to integrate and use already existing libraries. PMID:24399965

pySPACE-a signal processing and classification environment in Python.

PubMed

Krell, Mario M; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Teiwes, Johannes; Metzen, Jan H; Kirchner, Elsa A; Kirchner, Frank

2013-01-01

In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. With the presented software pySPACE (http://pyspace.github.io/pyspace), signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG). The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms, and evaluation schemes. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. In the presented work, the structural hierarchies are described. It is illustrated how users and developers can interface the software and execute offline and online modes. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. It further allows to define own algorithms, or to integrate and use already existing libraries.

SERS as a tool for in vitro toxicology.

PubMed

Fisher, Kate M; McLeish, Jennifer A; Jamieson, Lauren E; Jiang, Jing; Hopgood, James R; McLaughlin, Stephen; Donaldson, Ken; Campbell, Colin J

2016-06-23

Measuring markers of stress such as pH and redox potential are important when studying toxicology in in vitro models because they are markers of oxidative stress, apoptosis and viability. While surface enhanced Raman spectroscopy is ideally suited to the measurement of redox potential and pH in live cells, the time-intensive nature and perceived difficulty in signal analysis and interpretation can be a barrier to its broad uptake by the biological community. In this paper we detail the development of signal processing and analysis algorithms that allow SERS spectra to be automatically processed so that the output of the processing is a pH or redox potential value. By automating signal processing we were able to carry out a comparative evaluation of the toxicology of silver and zinc oxide nanoparticles and correlate our findings with qPCR analysis. The combination of these two analytical techniques sheds light on the differences in toxicology between these two materials from the perspective of oxidative stress.

MATtrack: A MATLAB-Based Quantitative Image Analysis Platform for Investigating Real-Time Photo-Converted Fluorescent Signals in Live Cells.

PubMed

Courtney, Jane; Woods, Elena; Scholz, Dimitri; Hall, William W; Gautier, Virginie W

2015-01-01

We introduce here MATtrack, an open source MATLAB-based computational platform developed to process multi-Tiff files produced by a photo-conversion time lapse protocol for live cell fluorescent microscopy. MATtrack automatically performs a series of steps required for image processing, including extraction and import of numerical values from Multi-Tiff files, red/green image classification using gating parameters, noise filtering, background extraction, contrast stretching and temporal smoothing. MATtrack also integrates a series of algorithms for quantitative image analysis enabling the construction of mean and standard deviation images, clustering and classification of subcellular regions and injection point approximation. In addition, MATtrack features a simple user interface, which enables monitoring of Fluorescent Signal Intensity in multiple Regions of Interest, over time. The latter encapsulates a region growing method to automatically delineate the contours of Regions of Interest selected by the user, and performs background and regional Average Fluorescence Tracking, and automatic plotting. Finally, MATtrack computes convenient visualization and exploration tools including a migration map, which provides an overview of the protein intracellular trajectories and accumulation areas. In conclusion, MATtrack is an open source MATLAB-based software package tailored to facilitate the analysis and visualization of large data files derived from real-time live cell fluorescent microscopy using photoconvertible proteins. It is flexible, user friendly, compatible with Windows, Mac, and Linux, and a wide range of data acquisition software. MATtrack is freely available for download at eleceng.dit.ie/courtney/MATtrack.zip.

MATtrack: A MATLAB-Based Quantitative Image Analysis Platform for Investigating Real-Time Photo-Converted Fluorescent Signals in Live Cells

PubMed Central

Courtney, Jane; Woods, Elena; Scholz, Dimitri; Hall, William W.; Gautier, Virginie W.

2015-01-01

We introduce here MATtrack, an open source MATLAB-based computational platform developed to process multi-Tiff files produced by a photo-conversion time lapse protocol for live cell fluorescent microscopy. MATtrack automatically performs a series of steps required for image processing, including extraction and import of numerical values from Multi-Tiff files, red/green image classification using gating parameters, noise filtering, background extraction, contrast stretching and temporal smoothing. MATtrack also integrates a series of algorithms for quantitative image analysis enabling the construction of mean and standard deviation images, clustering and classification of subcellular regions and injection point approximation. In addition, MATtrack features a simple user interface, which enables monitoring of Fluorescent Signal Intensity in multiple Regions of Interest, over time. The latter encapsulates a region growing method to automatically delineate the contours of Regions of Interest selected by the user, and performs background and regional Average Fluorescence Tracking, and automatic plotting. Finally, MATtrack computes convenient visualization and exploration tools including a migration map, which provides an overview of the protein intracellular trajectories and accumulation areas. In conclusion, MATtrack is an open source MATLAB-based software package tailored to facilitate the analysis and visualization of large data files derived from real-time live cell fluorescent microscopy using photoconvertible proteins. It is flexible, user friendly, compatible with Windows, Mac, and Linux, and a wide range of data acquisition software. MATtrack is freely available for download at eleceng.dit.ie/courtney/MATtrack.zip. PMID:26485569

Automatic weld torch guidance control system

NASA Technical Reports Server (NTRS)

Smaith, H. E.; Wall, W. A.; Burns, M. R., Jr.

1982-01-01

A highly reliable, fully digital, closed circuit television optical, type automatic weld seam tracking control system was developed. This automatic tracking equipment is used to reduce weld tooling costs and increase overall automatic welding reliability. The system utilizes a charge injection device digital camera which as 60,512 inidividual pixels as the light sensing elements. Through conventional scanning means, each pixel in the focal plane is sequentially scanned, the light level signal digitized, and an 8-bit word transmitted to scratch pad memory. From memory, the microprocessor performs an analysis of the digital signal and computes the tracking error. Lastly, the corrective signal is transmitted to a cross seam actuator digital drive motor controller to complete the closed loop, feedback, tracking system. This weld seam tracking control system is capable of a tracking accuracy of + or - 0.2 mm, or better. As configured, the system is applicable to square butt, V-groove, and lap joint weldments.

Digital Baseband Architecture For Transponder

NASA Technical Reports Server (NTRS)

Nguyen, Tien M.; Yeh, Hen-Geul

1995-01-01

Proposed advanced transponder for long-distance radio communication system with turnaround ranging contains carrier-signal-tracking loop including baseband digital "front end." For reduced cost, transponder includes analog intermediate-frequency (IF) section and analog automatic gain control (AGC) loop at first of two IF mixers. However, second IF mixer redesigned to ease digitization of baseband functions. To conserve power and provide for simpler and smaller transponder hardware, baseband digital signal-processing circuits designed to implement undersampling scheme. Furthermore, sampling scheme and sampling frequency chosen so redesign involves minimum modification of command-detector unit (CDU).

High-speed event detector for embedded nanopore bio-systems.

PubMed

Huang, Yiyun; Magierowski, Sebastian; Ghafar-Zadeh, Ebrahim; Wang, Chengjie

2015-08-01

Biological measurements of microscopic phenomena often deal with discrete-event signals. The ability to automatically carry out such measurements at high-speed in a miniature embedded system is desirable but compromised by high-frequency noise along with practical constraints on filter quality and sampler resolution. This paper presents a real-time event-detection method in the context of nanopore sensing that helps to mitigate these drawbacks and allows accurate signal processing in an embedded system. Simulations show at least a 10× improvement over existing on-line detection methods.

Automatic transponder. [measurement of the internal delay time of a transponder

NASA Technical Reports Server (NTRS)

Anderson, R. E.; Brisken, A. F.; Lewis, J. R. (Inventor)

1977-01-01

A method and apparatus for the automatic, remote measurement of the internal delay time of a transponder at the time of operation is provided. A small portion of the transmitted signal of the transponder is converted to the receive signal frequency of the transponder and supplied to the input of the transponder. The elapsed time between the receive signal locally generated and the receive signal causing the transmission of the transmitted signal is measured, said time being representative of or equal to the internal delay time of the transponder at the time of operation.

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information.

PubMed

Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Yan, Bin; Li, Jianxin

2015-01-01

Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition.

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information

PubMed Central

Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Li, Jianxin

2015-01-01

Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition. PMID:26380294

Research on the Additional Secondary Phase Factor for Automatic Identification System Signals Transmitted over a Rough Sea Surface

PubMed Central

Zhang, Shufang; Sun, Xiaowen

2018-01-01

This paper investigates the Additional Secondary Phase Factor (ASF) characteristics of Automatic Identification System (AIS) signals spreading over a rough sea surface. According to the change of the ASFs for AIS signals in different signal form, the influences of the different propagation conditions on the ASFs are analyzed. The expression, numerical calculation, and simulation analysis of the ASFs of AIS signal are performed in the rough sea surface. The results contribute to the high-accuracy propagation delay measurement of AIS signals spreading over the rough sea surface as, well as providing a reference for reliable communication link design in marine engineering for Very High Frequency (VHF) signals. PMID:29462995

A PC-based computer package for automatic detection and location of earthquakes: Application to a seismic network in eastern sicity (Italy)

NASA Astrophysics Data System (ADS)

Patanè, Domenico; Ferrari, Ferruccio; Giampiccolo, Elisabetta; Gresta, Stefano

Few automated data acquisition and processing systems operate on mainframes, some run on UNIX-based workstations and others on personal computers, equipped with either DOS/WINDOWS or UNIX-derived operating systems. Several large and complex software packages for automatic and interactive analysis of seismic data have been developed in recent years (mainly for UNIX-based systems). Some of these programs use a variety of artificial intelligence techniques. The first operational version of a new software package, named PC-Seism, for analyzing seismic data from a local network is presented in Patanè et al. (1999). This package, composed of three separate modules, provides an example of a new generation of visual object-oriented programs for interactive and automatic seismic data-processing running on a personal computer. In this work, we mainly discuss the automatic procedures implemented in the ASDP (Automatic Seismic Data-Processing) module and real time application to data acquired by a seismic network running in eastern Sicily. This software uses a multi-algorithm approach and a new procedure MSA (multi-station-analysis) for signal detection, phase grouping and event identification and location. It is designed for an efficient and accurate processing of local earthquake records provided by single-site and array stations. Results from ASDP processing of two different data sets recorded at Mt. Etna volcano by a regional network are analyzed to evaluate its performance. By comparing the ASDP pickings with those revised manually, the detection and subsequently the location capabilities of this software are assessed. The first data set is composed of 330 local earthquakes recorded in the Mt. Etna erea during 1997 by the telemetry analog seismic network. The second data set comprises about 970 automatic locations of more than 2600 local events recorded at Mt. Etna during the last eruption (July 2001) at the present network. For the former data set, a comparison of the automatic results with the manual picks indicates that the ASDP module can accurately pick 80% of the P-waves and 65% of S-waves. The on-line application on the latter data set shows that automatic locations are affected by larger errors, due to the preliminary setting of the configuration parameters in the program. However, both automatic ASDP and manual hypocenter locations are comparable within the estimated error bounds. New improvements of the PC-Seism software for on-line analysis are also discussed.

Automatic multimodal detection for long-term seizure documentation in epilepsy.

PubMed

Fürbass, F; Kampusch, S; Kaniusas, E; Koren, J; Pirker, S; Hopfengärtner, R; Stefan, H; Kluge, T; Baumgartner, C

2017-08-01

This study investigated sensitivity and false detection rate of a multimodal automatic seizure detection algorithm and the applicability to reduced electrode montages for long-term seizure documentation in epilepsy patients. An automatic seizure detection algorithm based on EEG, EMG, and ECG signals was developed. EEG/ECG recordings of 92 patients from two epilepsy monitoring units including 494 seizures were used to assess detection performance. EMG data were extracted by bandpass filtering of EEG signals. Sensitivity and false detection rate were evaluated for each signal modality and for reduced electrode montages. All focal seizures evolving to bilateral tonic-clonic (BTCS, n=50) and 89% of focal seizures (FS, n=139) were detected. Average sensitivity in temporal lobe epilepsy (TLE) patients was 94% and 74% in extratemporal lobe epilepsy (XTLE) patients. Overall detection sensitivity was 86%. Average false detection rate was 12.8 false detections in 24h (FD/24h) for TLE and 22 FD/24h in XTLE patients. Utilization of 8 frontal and temporal electrodes reduced average sensitivity from 86% to 81%. Our automatic multimodal seizure detection algorithm shows high sensitivity with full and reduced electrode montages. Evaluation of different signal modalities and electrode montages paces the way for semi-automatic seizure documentation systems. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Scene Analysis: Non-Linear Spatial Filtering for Automatic Target Detection.

DTIC Science & Technology

1982-12-01

In this thesis, a method for two-dimensional pattern recognition was developed and tested. The method included a global search scheme for candidate...test global switch TYPEO Creating negative video file only.W 11=0 12=256 13=512 14=768 GO 70 2 1 TYPE" Creating negative and horizontally flipped video...purpose was to develop a base of image processing software for the AFIT Digital Signal Processing Laboratory NOVA- ECLIPSE minicomputer system, for

Probabilistic Reasoning Over Seismic Time Series: Volcano Monitoring by Hidden Markov Models at Mt. Etna

NASA Astrophysics Data System (ADS)

Cassisi, Carmelo; Prestifilippo, Michele; Cannata, Andrea; Montalto, Placido; Patanè, Domenico; Privitera, Eugenio

2016-07-01

From January 2011 to December 2015, Mt. Etna was mainly characterized by a cyclic eruptive behavior with more than 40 lava fountains from New South-East Crater. Using the RMS (Root Mean Square) of the seismic signal recorded by stations close to the summit area, an automatic recognition of the different states of volcanic activity (QUIET, PRE-FOUNTAIN, FOUNTAIN, POST-FOUNTAIN) has been applied for monitoring purposes. Since values of the RMS time series calculated on the seismic signal are generated from a stochastic process, we can try to model the system generating its sampled values, assumed to be a Markov process, using Hidden Markov Models (HMMs). HMMs analysis seeks to recover the sequence of hidden states from the observations. In our framework, observations are characters generated by the Symbolic Aggregate approXimation (SAX) technique, which maps RMS time series values with symbols of a pre-defined alphabet. The main advantages of the proposed framework, based on HMMs and SAX, with respect to other automatic systems applied on seismic signals at Mt. Etna, are the use of multiple stations and static thresholds to well characterize the volcano states. Its application on a wide seismic dataset of Etna volcano shows the possibility to guess the volcano states. The experimental results show that, in most of the cases, we detected lava fountains in advance.

Measurement fidelity of heart rate variability signal processing: The devil is in the details

PubMed Central

Jarrin, Denise C.; McGrath, Jennifer J.; Giovanniello, Sabrina; Poirier, Paul; Lambert, Marie

2017-01-01

Heart rate variability (HRV) is a particularly valuable quantitative marker of the flexibility and balance of the autonomic nervous system. Significant advances in software programs to automatically derive HRV have led to its extensive use in psychophysiological research. However, there is a lack of systematic comparisons across software programs used to derive HRV indices. Further, researchers report meager details on important signal processing decisions making synthesis across studies challenging. The aim of the present study was to evaluate the measurement fidelity of time- and frequency-domain HRV indices derived from three predominant signal processing software programs commonly used in clinical and research settings. Triplicate ECG recordings were derived from 20 participants using identical data acquisition hardware. Among the time-domain indices, there was strong to excellent correspondence (ICCavg =0.93) for SDNN, SDANN, SDNNi, rMSSD, and pNN50. The frequency-domain indices yielded excellent correspondence (ICCavg =0.91) for LF, HF, and LF/HF ratio, except for VLF which exhibited poor correspondence (ICCavg =0.19). Stringent user-decisions and technical specifications for nuanced HRV processing details are essential to ensure measurement fidelity across signal processing software programs. PMID:22820268

49 CFR 236.560 - Contact element, mechanical trip type; location with respect to rail.

Code of Federal Regulations, 2011 CFR

2011-10-01

... INSTRUCTIONS GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and.... Contact element of automatic train stop device of the mechanical trip type shall be maintained at a height...

49 CFR 236.508 - Interference with application of brakes by means of brake valve.

Code of Federal Regulations, 2011 CFR

2011-10-01

... GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.508 Interference with application of brakes by means of brake valve. The automatic train stop, train control, or...

49 CFR 236.508 - Interference with application of brakes by means of brake valve.

Code of Federal Regulations, 2010 CFR

2010-10-01

... GOVERNING THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.508 Interference with application of brakes by means of brake valve. The automatic train stop, train control, or...

Improved Techniques for Automatic Chord Recognition from Music Audio Signals

ERIC Educational Resources Information Center

Cho, Taemin

2014-01-01

This thesis is concerned with the development of techniques that facilitate the effective implementation of capable automatic chord transcription from music audio signals. Since chord transcriptions can capture many important aspects of music, they are useful for a wide variety of music applications and also useful for people who learn and perform…

49 CFR 236.311 - Signal control circuits, selection through track relays or devices functioning as track relays...

Code of Federal Regulations, 2010 CFR

2010-10-01

... automatic interlocking. (a) The control circuits for aspects with indications more favorable than “proceed... 49 Transportation 4 2010-10-01 2010-10-01 false Signal control circuits, selection through track... automatic interlocking. 236.311 Section 236.311 Transportation Other Regulations Relating to Transportation...

Automatic sweep circuit

DOEpatents

Keefe, Donald J.

1980-01-01

An automatically sweeping circuit for searching for an evoked response in an output signal in time with respect to a trigger input. Digital counters are used to activate a detector at precise intervals, and monitoring is repeated for statistical accuracy. If the response is not found then a different time window is examined until the signal is found.

Automatic segmentation of triaxial accelerometry signals for falls risk estimation.

PubMed

Redmond, Stephen J; Scalzi, Maria Elena; Narayanan, Michael R; Lord, Stephen R; Cerutti, Sergio; Lovell, Nigel H

2010-01-01

Falls-related injuries in the elderly population represent one of the most significant contributors to rising health care expense in developed countries. In recent years, falls detection technologies have become more common. However, very few have adopted a preferable falls prevention strategy through unsupervised monitoring in the free-living environment. The basis of the monitoring described herein was a self-administered directed-routine (DR) comprising three separate tests measured by way of a waist-mounted triaxial accelerometer. Using features extracted from the manually segmented signals, a reasonable estimate of falls risk can be achieved. We describe here a series of algorithms for automatically segmenting these recordings, enabling the use of the DR assessment in the unsupervised and home environments. The accelerometry signals, from 68 subjects performing the DR, were manually annotated by an observer. Using the proposed signal segmentation routines, an good agreement was observed between the manually annotated markers and the automatically estimated values. However, a decrease in the correlation with falls risk to 0.73 was observed using the automatic segmentation, compared to 0.81 when using markers manually placed by an observer.

Multi-ball and one-ball geolocation

NASA Astrophysics Data System (ADS)

Nelson, D. J.; Townsend, J. L.

2017-05-01

We present analysis methods that may be used to geolocate emitters using one or more moving receivers. While some of the methods we present may apply to a broader class of signals, our primary interest is locating and tracking ships from short pulsed transmissions, such as the maritime Automatic Identification System (AIS.) The AIS signal is difficult to process and track since the pulse duration is only 25 milliseconds, and the pulses may only be transmitted every six to ten seconds. In this article, we address several problems including accurate TDOA and FDOA estimation methods that do not require searching a two dimensional surface such as the cross-ambiguity surface. As an example, we apply these methods to identify and process AIS pulses from a single emitter, making it possible to geolocate the AIS signal using a single moving receiver.

Unsupervised pattern recognition methods in ciders profiling based on GCE voltammetric signals.

PubMed

Jakubowska, Małgorzata; Sordoń, Wanda; Ciepiela, Filip

2016-07-15

This work presents a complete methodology of distinguishing between different brands of cider and ageing degrees, based on voltammetric signals, utilizing dedicated data preprocessing procedures and unsupervised multivariate analysis. It was demonstrated that voltammograms recorded on glassy carbon electrode in Britton-Robinson buffer at pH 2 are reproducible for each brand. By application of clustering algorithms and principal component analysis visible homogenous clusters were obtained. Advanced signal processing strategy which included automatic baseline correction, interval scaling and continuous wavelet transform with dedicated mother wavelet, was a key step in the correct recognition of the objects. The results show that voltammetry combined with optimized univariate and multivariate data processing is a sufficient tool to distinguish between ciders from various brands and to evaluate their freshness. Copyright © 2016 Elsevier Ltd. All rights reserved.

Designing and Implementing a Retrospective Earthquake Detection Framework at the U.S. Geological Survey National Earthquake Information Center

NASA Astrophysics Data System (ADS)

Patton, J.; Yeck, W.; Benz, H.

2017-12-01

The U.S. Geological Survey National Earthquake Information Center (USGS NEIC) is implementing and integrating new signal detection methods such as subspace correlation, continuous beamforming, multi-band picking and automatic phase identification into near-real-time monitoring operations. Leveraging the additional information from these techniques help the NEIC utilize a large and varied network on local to global scales. The NEIC is developing an ordered, rapid, robust, and decentralized framework for distributing seismic detection data as well as a set of formalized formatting standards. These frameworks and standards enable the NEIC to implement a seismic event detection framework that supports basic tasks, including automatic arrival time picking, social media based event detections, and automatic association of different seismic detection data into seismic earthquake events. In addition, this framework enables retrospective detection processing such as automated S-wave arrival time picking given a detected event, discrimination and classification of detected events by type, back-azimuth and slowness calculations, and ensuring aftershock and induced sequence detection completeness. These processes and infrastructure improve the NEIC's capabilities, accuracy, and speed of response. In addition, this same infrastructure provides an improved and convenient structure to support access to automatic detection data for both research and algorithmic development.

Infrared-enhanced TV for fire detection

NASA Technical Reports Server (NTRS)

Hall, J. R.

1978-01-01

Closed-circuit television is superior to conventional smoke or heat sensors for detecting fires in large open spaces. Single TV camera scans entire area, whereas many conventional sensors and maze of interconnecting wiring might be required to get same coverage. Camera is monitored by person who would trip alarm if fire were detected, or electronic circuitry could process camera signal for fully-automatic alarm system.

A Triadic Neurocognitive Approach to Addiction for Clinical Interventions

PubMed Central

Noël, Xavier; Brevers, Damien; Bechara, Antoine

2013-01-01

According to the triadic neurocognitive model of addiction to drugs (e.g., cocaine) and non-drugs (e.g., gambling), weakened “willpower” associated with these behaviors is the product of an abnormal functioning in one or more of three key neural and cognitive systems: (1) an amygdala-striatum dependent system mediating automatic, habitual, and salient behaviors; (2) a prefrontal cortex dependent system important for self-regulation and forecasting the future consequences of a behavior; and (3) an insula dependent system for the reception of interoceptive signals and their translation into feeling states (such as urge and craving), which in turn plays a strong influential role in decision-making and impulse control processes related to uncertainty, risk, and reward. The described three-systems account for poor decision-making (i.e., prioritizing short-term consequences of a decisional option) and stimulus-driven actions, thus leading to a more elevated risk for relapse. Finally, this article elaborates on the need for “personalized” clinical model-based interventions targeting interactions between implicit processes, interoceptive signaling, and supervisory function aimed at helping individuals become less governed by immediate situations and automatic pre-potent responses, and more influenced by systems involved in the pursuit of future valued goals. PMID:24409155

[Construction of automatic elucidation platform for mechanism of traditional Chinese medicine].

PubMed

Zhang, Bai-xia; Luo, Si-jun; Yan, Jing; Gu, Hao; Luo, Ji; Zhang, Yan-ling; Tao, Ou; Wang, Yun

2015-10-01

Aim at the two problems in the field of traditional Chinese medicine (TCM) mechanism elucidation, one is the lack of detailed biological processes information, next is the low efficient in constructing network models, we constructed an auxiliary elucidation system for the TCM mechanism and realize the automatic establishment of biological network model. This study used the Entity Grammar Systems (EGS) as the theoretical framework, integrated the data of formulae, herbs, chemical components, targets of component, biological reactions, signaling pathways and disease related proteins, established the formal models, wrote the reasoning engine, constructed the auxiliary elucidation system for the TCM mechanism elucidation. The platform provides an automatic modeling method for biological network model of TCM mechanism. It would be benefit to perform the in-depth research on TCM theory of natures and combination and provides the scientific references for R&D of TCM.

An automatic rat brain extraction method based on a deformable surface model.

PubMed

Li, Jiehua; Liu, Xiaofeng; Zhuo, Jiachen; Gullapalli, Rao P; Zara, Jason M

2013-08-15

The extraction of the brain from the skull in medical images is a necessary first step before image registration or segmentation. While pre-clinical MR imaging studies on small animals, such as rats, are increasing, fully automatic imaging processing techniques specific to small animal studies remain lacking. In this paper, we present an automatic rat brain extraction method, the Rat Brain Deformable model method (RBD), which adapts the popular human brain extraction tool (BET) through the incorporation of information on the brain geometry and MR image characteristics of the rat brain. The robustness of the method was demonstrated on T2-weighted MR images of 64 rats and compared with other brain extraction methods (BET, PCNN, PCNN-3D). The results demonstrate that RBD reliably extracts the rat brain with high accuracy (>92% volume overlap) and is robust against signal inhomogeneity in the images. Copyright © 2013 Elsevier B.V. All rights reserved.

Assessment of Severe Apnoea through Voice Analysis, Automatic Speech, and Speaker Recognition Techniques

NASA Astrophysics Data System (ADS)

Fernández Pozo, Rubén; Blanco Murillo, Jose Luis; Hernández Gómez, Luis; López Gonzalo, Eduardo; Alcázar Ramírez, José; Toledano, Doroteo T.

2009-12-01

This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.

Early Detection of Severe Apnoea through Voice Analysis and Automatic Speaker Recognition Techniques

NASA Astrophysics Data System (ADS)

Fernández, Ruben; Blanco, Jose Luis; Díaz, David; Hernández, Luis A.; López, Eduardo; Alcázar, José

This study is part of an on-going collaborative effort between the medical and the signal processing communities to promote research on applying voice analysis and Automatic Speaker Recognition techniques (ASR) for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based diagnosis could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we present and discuss the possibilities of using generative Gaussian Mixture Models (GMMs), generally used in ASR systems, to model distinctive apnoea voice characteristics (i.e. abnormal nasalization). Finally, we present experimental findings regarding the discriminative power of speaker recognition techniques applied to severe apnoea detection. We have achieved an 81.25 % correct classification rate, which is very promising and underpins the interest in this line of inquiry.

Automatic detection of sleep macrostructure based on a sensorized T-shirt.

PubMed

Bianchi, Anna M; Mendez, Martin O

2010-01-01

In the present work we apply a fully automatic procedure to the analysis of signal coming from a sensorized T-shit, worn during the night, for sleep evaluation. The goodness and reliability of the signals recorded trough the T-shirt was previously tested, while the employed algorithms for feature extraction and sleep classification were previously developed on standard ECG recordings and the obtained classification was compared to the standard clinical practice based on polysomnography (PSG). In the present work we combined T-shirt recordings and automatic classification and could obtain reliable sleep profiles, i.e. the sleep classification in WAKE, REM (rapid eye movement) and NREM stages, based on heart rate variability (HRV), respiration and movement signals.

Temporally flexible feedback signal to foveal cortex for peripheral object recognition

PubMed Central

Fan, Xiaoxu; Wang, Lan; Shao, Hanyu; Kersten, Daniel; He, Sheng

2016-01-01

Recent studies have shown that information from peripherally presented images is present in the human foveal retinotopic cortex, presumably because of feedback signals. We investigated this potential feedback signal by presenting noise in fovea at different object–noise stimulus onset asynchronies (SOAs), whereas subjects performed a discrimination task on peripheral objects. Results revealed a selective impairment of performance when foveal noise was presented at 250-ms SOA, but only for tasks that required comparing objects’ spatial details, suggesting a task- and stimulus-dependent foveal processing mechanism. Critically, the temporal window of foveal processing was shifted when mental rotation was required for the peripheral objects, indicating that the foveal retinotopic processing is not automatically engaged at a fixed time following peripheral stimulation; rather, it occurs at a stage when detailed information is required. Moreover, fMRI measurements using multivoxel pattern analysis showed that both image and object category-relevant information of peripheral objects was represented in the foveal cortex. Taken together, our results support the hypothesis of a temporally flexible feedback signal to the foveal retinotopic cortex when discriminating objects in the visual periphery. PMID:27671651

Robot Command Interface Using an Audio-Visual Speech Recognition System

NASA Astrophysics Data System (ADS)

Ceballos, Alexánder; Gómez, Juan; Prieto, Flavio; Redarce, Tanneguy

In recent years audio-visual speech recognition has emerged as an active field of research thanks to advances in pattern recognition, signal processing and machine vision. Its ultimate goal is to allow human-computer communication using voice, taking into account the visual information contained in the audio-visual speech signal. This document presents a command's automatic recognition system using audio-visual information. The system is expected to control the laparoscopic robot da Vinci. The audio signal is treated using the Mel Frequency Cepstral Coefficients parametrization method. Besides, features based on the points that define the mouth's outer contour according to the MPEG-4 standard are used in order to extract the visual speech information.

An all digital low data rate communication system

NASA Technical Reports Server (NTRS)

Chen, C.-H.; Fan, M.

1973-01-01

The advent of digital hardwares has made it feasible to implement many communication system components digitally. With the exception of frequency down conversion, the proposed low data rate communication system uses digital hardware completely. Although the system is designed primarily for deep space communications with large frequency uncertainty and low signal-to-noise ratio, it is also suitable for other low data rate applications with time-shared operation among a number of channels. Emphasis is placed on the fast Fourier transform receiver and the automatic frequency control via digital filtering. The speed available from the digital system allows sophisticated signal processing to reduce frequency uncertainty and to increase the signal-to-noise ratio.

Artificial intelligence applied to process signal analysis

NASA Technical Reports Server (NTRS)

Corsberg, Dan

1988-01-01

Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge base approach to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored.

Automatic detection of echolocation clicks based on a Gabor model of their waveform.

PubMed

Madhusudhana, Shyam; Gavrilov, Alexander; Erbe, Christine

2015-06-01

Prior research has shown that echolocation clicks of several species of terrestrial and marine fauna can be modelled as Gabor-like functions. Here, a system is proposed for the automatic detection of a variety of such signals. By means of mathematical formulation, it is shown that the output of the Teager-Kaiser Energy Operator (TKEO) applied to Gabor-like signals can be approximated by a Gaussian function. Based on the inferences, a detection algorithm involving the post-processing of the TKEO outputs is presented. The ratio of the outputs of two moving-average filters, a Gaussian and a rectangular filter, is shown to be an effective detection parameter. Detector performance is assessed using synthetic and real (taken from MobySound database) recordings. The detection method is shown to work readily with a variety of echolocation clicks and in various recording scenarios. The system exhibits low computational complexity and operates several times faster than real-time. Performance comparisons are made to other publicly available detectors including pamguard.

Optical modulator system

NASA Technical Reports Server (NTRS)

Brand, J.

1972-01-01

The fabrication, test, and delivery of an optical modulator system which will operate with a mode-locked Nd:YAG laser indicating at either 1.06 or 0.53 micrometers is discussed. The delivered hardware operates at data rates up to 400 Mbps and includes a 0.53 micrometer electrooptic modulator, a 1.06 micrometer electrooptic modulator with power supply and signal processing electronics with power supply. The modulators contain solid state drivers which accept digital signals with MECL logic levels, temperature controllers to maintain a stable thermal environment for the modulator crystals, and automatic electronic compensation to maximize the extinction ratio. The modulators use two lithium tantalate crystals cascaded in a double pass configuration. The signal processing electronics include encoding electronics which are capable of digitizing analog signals between the limit of + or - 0.75 volts at a maximum rate of 80 megasamples per second with 5 bit resolution. The digital samples are serialized and made available as a 400 Mbps serial NRZ data source for the modulators. A pseudorandom (PN) generator is also included in the signal processing electronics. This data source generates PN sequences with lengths between 31 bits and 32,767 bits in a serial NRZ format at rates up to 400 Mbps.

Extraction of small boat harmonic signatures from passive sonar.

PubMed

Ogden, George L; Zurk, Lisa M; Jones, Mark E; Peterson, Mary E

2011-06-01

This paper investigates the extraction of acoustic signatures from small boats using a passive sonar system. Noise radiated from a small boats consists of broadband noise and harmonically related tones that correspond to engine and propeller specifications. A signal processing method to automatically extract the harmonic structure of noise radiated from small boats is developed. The Harmonic Extraction and Analysis Tool (HEAT) estimates the instantaneous fundamental frequency of the harmonic tones, refines the fundamental frequency estimate using a Kalman filter, and automatically extracts the amplitudes of the harmonic tonals to generate a harmonic signature for the boat. Results are presented that show the HEAT algorithms ability to extract these signatures. © 2011 Acoustical Society of America

Fast automatic segmentation of anatomical structures in x-ray computed tomography images to improve fluorescence molecular tomography reconstruction.

PubMed

Freyer, Marcus; Ale, Angelique; Schulz, Ralf B; Zientkowska, Marta; Ntziachristos, Vasilis; Englmeier, Karl-Hans

2010-01-01

The recent development of hybrid imaging scanners that integrate fluorescence molecular tomography (FMT) and x-ray computed tomography (XCT) allows the utilization of x-ray information as image priors for improving optical tomography reconstruction. To fully capitalize on this capacity, we consider a framework for the automatic and fast detection of different anatomic structures in murine XCT images. To accurately differentiate between different structures such as bone, lung, and heart, a combination of image processing steps including thresholding, seed growing, and signal detection are found to offer optimal segmentation performance. The algorithm and its utilization in an inverse FMT scheme that uses priors is demonstrated on mouse images.

Detection and enforcement of failure-to-yield in an emergency vehicle preemption system

NASA Technical Reports Server (NTRS)

Bachelder, Aaron (Inventor); Wickline, Richard (Inventor)

2007-01-01

An intersection controlled by an intersection controller receives trigger signals from on-coming emergency vehicles responding to an emergency call. The intersection controller initiates surveillance of the intersection via cameras installed at the intersection in response to a received trigger signal. The surveillance may begin immediately upon receipt of the trigger signal from an emergency vehicle, or may wait until the intersection controller determines that the signaling emergency vehicle is in the field of view of the cameras at the intersection. Portions of the captured images are tagged by the intersection controller based on tag signals transmitted by the vehicle or based on detected traffic patterns that indicate a potential traffic violation. The captured images are downloaded to a processing facility that analyzes the images and automatically issues citations for captured traffic violations.

Robust automated classification of first-motion polarities for focal mechanism determination with machine learning

NASA Astrophysics Data System (ADS)

Ross, Z. E.; Meier, M. A.; Hauksson, E.

2017-12-01

Accurate first-motion polarities are essential for determining earthquake focal mechanisms, but are difficult to measure automatically because of picking errors and signal to noise issues. Here we develop an algorithm for reliable automated classification of first-motion polarities using machine learning algorithms. A classifier is designed to identify whether the first-motion polarity is up, down, or undefined by examining the waveform data directly. We first improve the accuracy of automatic P-wave onset picks by maximizing a weighted signal/noise ratio for a suite of candidate picks around the automatic pick. We then use the waveform amplitudes before and after the optimized pick as features for the classification. We demonstrate the method's potential by training and testing the classifier on tens of thousands of hand-made first-motion picks by the Southern California Seismic Network. The classifier assigned the same polarity as chosen by an analyst in more than 94% of the records. We show that the method is generalizable to a variety of learning algorithms, including neural networks and random forest classifiers. The method is suitable for automated processing of large seismic waveform datasets, and can potentially be used in real-time applications, e.g. for improving the source characterizations of earthquake early warning algorithms.

Apparatus and method for processing Korotkov sounds. [for blood pressure measurement

NASA Technical Reports Server (NTRS)

Golden, D. P., Jr.; Hoffler, G. W.; Wolthuis, R. A. (Inventor)

1974-01-01

A Korotkov sound processor, used in a noninvasive automatic blood measuring system where the brachial artery is occluded by an inflatable cuff, is disclosed. The Korotkoff sound associated with the systolic event is determined when the ratio of the absolute value of a voltage signal, representing Korotkov sounds in the range of 18 to 26 Hz to a maximum absolute peak value of the unfiltered signals, first equals or exceeds a value of 0.45. Korotkov sound associated with the diastolic event is determined when a ratio of the voltage signal of the Korotkov sounds in the range of 40 to 60 Hz to the absolute peak value of such signals within a single measurement cycle first falls below a value of 0.17. The processor signals the occurrence of the systolic and diastolic events and these signals can be used to control a recorder to record pressure values for these events.

TV audio and video on the same channel

NASA Technical Reports Server (NTRS)

Hopkins, J. B.

1979-01-01

Transmitting technique adds audio to video signal during vertical blanking interval. SIVI (signal in the vertical interval) is used by TV networks and stations to transmit cuing and automatic-switching tone signals to augment automatic and manual operations. It can also be used to transmit one-way instructional information, such as bulletin alerts, program changes, and commercial-cutaway aural cues from the networks to affiliates. Additonally, it can be used as extra sound channel for second-language transmission to biligual stations.

A method for studying the hunting oscillations of an airplane with a simple type of automatic control

NASA Technical Reports Server (NTRS)

Jones, R. T.

1976-01-01

A method is presented for predicting the amplitude and frequency, under certain simplifying conditions, of the hunting oscillations of an automatically controlled aircraft with lag in the control system or in the response of the aircraft to the controls. If the steering device is actuated by a simple right-left type of signal, the series of alternating fixed amplitude signals occuring during the hunting may ordinarily be represented by a square wave. Formulas are given expressing the response to such a variation of signal in terms of the response to a unit signal.

49 CFR 236.552 - Insulation resistance; requirement.

Code of Federal Regulations, 2010 CFR

2010-10-01

... ADMINISTRATION, DEPARTMENT OF TRANSPORTATION RULES, STANDARDS, AND INSTRUCTIONS GOVERNING THE INSTALLATION... resistance between wiring and ground of continuous inductive automatic cab signal system, automatic train...

A Novel Signal Modeling Approach for Classification of Seizure and Seizure-Free EEG Signals.

PubMed

Gupta, Anubha; Singh, Pushpendra; Karlekar, Mandar

2018-05-01

This paper presents a signal modeling-based new methodology of automatic seizure detection in EEG signals. The proposed method consists of three stages. First, a multirate filterbank structure is proposed that is constructed using the basis vectors of discrete cosine transform. The proposed filterbank decomposes EEG signals into its respective brain rhythms: delta, theta, alpha, beta, and gamma. Second, these brain rhythms are statistically modeled with the class of self-similar Gaussian random processes, namely, fractional Brownian motion and fractional Gaussian noises. The statistics of these processes are modeled using a single parameter called the Hurst exponent. In the last stage, the value of Hurst exponent and autoregressive moving average parameters are used as features to design a binary support vector machine classifier to classify pre-ictal, inter-ictal (epileptic with seizure free interval), and ictal (seizure) EEG segments. The performance of the classifier is assessed via extensive analysis on two widely used data set and is observed to provide good accuracy on both the data set. Thus, this paper proposes a novel signal model for EEG data that best captures the attributes of these signals and hence, allows to boost the classification accuracy of seizure and seizure-free epochs.

Phase coherence adaptive processor for automatic signal detection and identification

NASA Astrophysics Data System (ADS)

Wagstaff, Ronald A.

2006-05-01

A continuously adapting acoustic signal processor with an automatic detection/decision aid is presented. Its purpose is to preserve the signals of tactical interest, and filter out other signals and noise. It utilizes single sensor or beamformed spectral data and transforms the signal and noise phase angles into "aligned phase angles" (APA). The APA increase the phase temporal coherence of signals and leave the noise incoherent. Coherence thresholds are set, which are representative of the type of source "threat vehicle" and the geographic area or volume in which it is operating. These thresholds separate signals, based on the "quality" of their APA coherence. An example is presented in which signals from a submerged source in the ocean are preserved, while clutter signals from ships and noise are entirely eliminated. Furthermore, the "signals of interest" were identified by the processor's automatic detection aid. Similar performance is expected for air and ground vehicles. The processor's equations are formulated in such a manner that they can be tuned to eliminate noise and exploit signal, based on the "quality" of their APA temporal coherence. The mathematical formulation for this processor is presented, including the method by which the processor continuously self-adapts. Results show nearly complete elimination of noise, with only the selected category of signals remaining, and accompanying enhancements in spectral and spatial resolution. In most cases, the concept of signal-to-noise ratio looses significance, and "adaptive automated /decision aid" is more relevant.

Laser Calibration of an Impact Disdrometer

NASA Technical Reports Server (NTRS)

Lane, John E.; Kasparis, Takis; Metzger, Philip T.; Jones, W. Linwood

2014-01-01

A practical approach to developing an operational low-cost disdrometer hinges on implementing an effective in situ adaptive calibration strategy. This calibration strategy lowers the cost of the device and provides a method to guarantee continued automatic calibration. In previous work, a collocated tipping bucket rain gauge was utilized to provide a calibration signal to the disdrometer's digital signal processing software. Rainfall rate is proportional to the 11/3 moment of the drop size distribution (a 7/2 moment can also be assumed, depending on the choice of terminal velocity relationship). In the previous case, the disdrometer calibration was characterized and weighted to the 11/3 moment of the drop size distribution (DSD). Optical extinction by rainfall is proportional to the 2nd moment of the DSD. Using visible laser light as a means to focus and generate an auxiliary calibration signal, the adaptive calibration processing is significantly improved.

Automatic Parametrization of Somatosensory Evoked Potentials With Chirp Modeling.

PubMed

Vayrynen, Eero; Noponen, Kai; Vipin, Ashwati; Thow, X Y; Al-Nashash, Hasan; Kortelainen, Jukka; All, Angelo

2016-09-01

In this paper, an approach using polynomial phase chirp signals to model somatosensory evoked potentials (SEPs) is proposed. SEP waveforms are assumed as impulses undergoing group velocity dispersion while propagating along a multipath neural connection. Mathematical analysis of pulse dispersion resulting in chirp signals is performed. An automatic parameterization of SEPs is proposed using chirp models. A Particle Swarm Optimization algorithm is used to optimize the model parameters. Features describing the latencies and amplitudes of SEPs are automatically derived. A rat model is then used to evaluate the automatic parameterization of SEPs in two experimental cases, i.e., anesthesia level and spinal cord injury (SCI). Experimental results show that chirp-based model parameters and the derived SEP features are significant in describing both anesthesia level and SCI changes. The proposed automatic optimization based approach for extracting chirp parameters offers potential for detailed SEP analysis in future studies. The method implementation in Matlab technical computing language is provided online.

A real time dynamic data acquisition and processing system for velocity, density, and total temperature fluctuation measurements

NASA Technical Reports Server (NTRS)

Clukey, Steven J.

1991-01-01

The real time Dynamic Data Acquisition and Processing System (DDAPS) is described which provides the capability for the simultaneous measurement of velocity, density, and total temperature fluctuations. The system of hardware and software is described in context of the wind tunnel environment. The DDAPS replaces both a recording mechanism and a separate data processing system. DDAPS receives input from hot wire anemometers. Amplifiers and filters condition the signals with computer controlled modules. The analog signals are simultaneously digitized and digitally recorded on disk. Automatic acquisition collects necessary calibration and environment data. Hot wire sensitivities are generated and applied to the hot wire data to compute fluctuations. The presentation of the raw and processed data is accomplished on demand. The interface to DDAPS is described along with the internal mechanisms of DDAPS. A summary of operations relevant to the use of the DDAPS is also provided.

Automatic and Direct Identification of Blink Components from Scalp EEG

PubMed Central

Kong, Wanzeng; Zhou, Zhanpeng; Hu, Sanqing; Zhang, Jianhai; Babiloni, Fabio; Dai, Guojun

2013-01-01

Eye blink is an important and inevitable artifact during scalp electroencephalogram (EEG) recording. The main problem in EEG signal processing is how to identify eye blink components automatically with independent component analysis (ICA). Taking into account the fact that the eye blink as an external source has a higher sum of correlation with frontal EEG channels than all other sources due to both its location and significant amplitude, in this paper, we proposed a method based on correlation index and the feature of power distribution to automatically detect eye blink components. Furthermore, we prove mathematically that the correlation between independent components and scalp EEG channels can be translating directly from the mixing matrix of ICA. This helps to simplify calculations and understand the implications of the correlation. The proposed method doesn't need to select a template or thresholds in advance, and it works without simultaneously recording an electrooculography (EOG) reference. The experimental results demonstrate that the proposed method can automatically recognize eye blink components with a high accuracy on entire datasets from 15 subjects. PMID:23959240

Design of an intelligent instrument for large direct-current measurement

NASA Astrophysics Data System (ADS)

Zhang, Rong; Zhang, Gang; Zhang, Zhipeng

2000-05-01

The principle and structure of an intelligent large direct current measurement is presented in this paper. It is of reflective type and detects signal by employing the high direct current sensor. The single-chip microcomputer of this system provides a powerful function of control and processing and greatly improves the extent of intelligence. The value can be displayed and printed automatically or manually.

Development of an Advanced, Automatic, Ultrasonic NDE Imaging System via Adaptive Learning Network Signal Processing Techniques

DTIC Science & Technology

1981-03-13

UNCLASSIFIED SECURITY CLAS,:FtfC ’i OF TH*!’ AGC W~ct P- A* 7~9r1) 0. ABSTRACT (continued) onuing in concert with a sophisticated detector has...and New York, 1969. Whalen, M.F., L.J. O’Brien, and A.N. Mucciardi, "Application of Adaptive Learning Netowrks for the Characterization of Two

49 CFR 236.202 - Signal governing movements over hand-operated switch.

Code of Federal Regulations, 2011 CFR

2011-10-01

... THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Block Signal Systems Standards § 236.202 Signal governing movements over hand...

Optical Fiber On-Line Detection System for Non-Touch Monitoring Roller Shape

NASA Astrophysics Data System (ADS)

Guo, Y.; Wang, Y. T.

2006-10-01

Basing on the principle of reflective displacement fiber-optic sensor, a high accuracy non-touch on-line optical fiber measurement system for roller shape is presented. The principle and composition of the detection system and the operation process are expatiated also. By using a novel probe of three optical fibers in equal transverse space, the effects of fluctuations in the light source, reflective changing of target surface and the intensity losses in the fiber lines are automatically compensated. Meantime, an optical fiber sensor model of correcting static error based on BP artificial neural network (ANN) is set up. Also by using interpolation method and value filtering to process the signals, effectively reduce the influence of random noise and the vibration of the roller bearing. So enhance the accuracy and resolution remarkably. Experiment proves that the accuracy of the system reach to the demand of practical production process, it provides a new method for the high speed, accurate and automatic on line detection of the mill roller shape.

Brain correlates of automatic visual change detection.

PubMed

Cléry, H; Andersson, F; Fonlupt, P; Gomot, M

2013-07-15

A number of studies support the presence of visual automatic detection of change, but little is known about the brain generators involved in such processing and about the modulation of brain activity according to the salience of the stimulus. The study presented here was designed to locate the brain activity elicited by unattended visual deviant and novel stimuli using fMRI. Seventeen adult participants were presented with a passive visual oddball sequence while performing a concurrent visual task. Variations in BOLD signal were observed in the modality-specific sensory cortex, but also in non-specific areas involved in preattentional processing of changing events. A degree-of-deviance effect was observed, since novel stimuli elicited more activity in the sensory occipital regions and at the medial frontal site than small changes. These findings could be compared to those obtained in the auditory modality and might suggest a "general" change detection process operating in several sensory modalities. Copyright © 2013 Elsevier Inc. All rights reserved.

Quantum dots-based double imaging combined with organic dye imaging to establish an automatic computerized method for cancer Ki67 measurement.

PubMed

Wang, Lin-Wei; Qu, Ai-Ping; Liu, Wen-Lou; Chen, Jia-Mei; Yuan, Jing-Ping; Wu, Han; Li, Yan; Liu, Juan

2016-02-03

As a widely used proliferative marker, Ki67 has important impacts on cancer prognosis, especially for breast cancer (BC). However, variations in analytical practice make it difficult for pathologists to manually measure Ki67 index. This study is to establish quantum dots (QDs)-based double imaging of nuclear Ki67 as red signal by QDs-655, cytoplasmic cytokeratin (CK) as yellow signal by QDs-585, and organic dye imaging of cell nucleus as blue signal by 4',6-diamidino-2-phenylindole (DAPI), and to develop a computer-aided automatic method for Ki67 index measurement. The newly developed automatic computerized Ki67 measurement could efficiently recognize and count Ki67-positive cancer cell nuclei with red signals and cancer cell nuclei with blue signals within cancer cell cytoplasmic with yellow signals. Comparisons of computerized Ki67 index, visual Ki67 index, and marked Ki67 index for 30 patients of 90 images with Ki67 ≤ 10% (low grade), 10% < Ki67 < 50% (moderate grade), and Ki67 ≥ 50% (high grade) showed computerized Ki67 counting is better than visual Ki67 counting, especially for Ki67 low and moderate grades. Based on QDs-based double imaging and organic dye imaging on BC tissues, this study successfully developed an automatic computerized Ki67 counting method to measure Ki67 index.

49 CFR 236.204 - Track signaled for movements in both directions, requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Block Signal Systems Standards § 236.204 Track signaled for movements in both...

49 CFR 236.204 - Track signaled for movements in both directions, requirements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Block Signal Systems Standards § 236.204 Track signaled for movements in both...

Emotion brain alterations in anorexia nervosa: a candidate biological marker and implications for treatment.

PubMed

Hatch, Ainslie; Madden, Sloane; Kohn, Michael R; Clarke, Simon; Touyz, Stephen; Gordon, Evian; Williams, Leanne M

2010-07-01

Identification of the biological markers of anorexia nervosa (AN) is crucial for the development of new treatments. We aimed to determine whether AN is associated with disturbances in the nonconscious neural processing of innate signals of emotion and whether these disturbances persist after weight gain. In a retest design, 28 adolescent females with AN were tested at first ad not mission to hospital and again after they had gained weight. Matched healthy control participants were tested at the same times. We assessed emotion-elicited event-related potentials (ERPs) during overt and covert presentation of emotion expressions, scores on an emotion-identification behavioural task, and symptom measures. We performed between and within group analyses. Individuals with AN had a marked alteration in ERPs relative to healthy controls. Irrespective of the form of stimulus, early and late ERP componotnents were significantly reduced in AN patients at baseline (when underweight) and on retest (after weight gain), especially in the temporo-occipital regions, suggesting a persistent disruption of the early automatic appraisal of salient emotional signals. This study could have been improved with a longer standardized retest interval. There is likely a core, generic disturbance in AN in the early "automatic" neural processing of emotion irrespective of weight or nutritional status. New innovative emotion-based psychologic or pharmacologic treatments targeting these nonconscious processes may prove beneficial.

49 CFR 236.502 - Automatic brake application, initiation by restrictive block conditions stopping distance in...

Code of Federal Regulations, 2010 CFR

2010-10-01

... restrictive block conditions stopping distance in advance. 236.502 Section 236.502 Transportation Other... Cab Signal Systems Standards § 236.502 Automatic brake application, initiation by restrictive block... initiate an automatic brake application at least stopping distance from the entrance to a block, wherein...

Web-based health services and clinical decision support.

PubMed

Jegelevicius, Darius; Marozas, Vaidotas; Lukosevicius, Arunas; Patasius, Martynas

2004-01-01

The purpose of this study was the development of a Web-based e-health service for comprehensive assistance and clinical decision support. The service structure consists of a Web server, a PHP-based Web interface linked to a clinical SQL database, Java applets for interactive manipulation and visualization of signals and a Matlab server linked with signal and data processing algorithms implemented by Matlab programs. The service ensures diagnostic signal- and image analysis-sbased clinical decision support. By using the discussed methodology, a pilot service for pathology specialists for automatic calculation of the proliferation index has been developed. Physicians use a simple Web interface for uploading the pictures under investigation to the server; subsequently a Java applet interface is used for outlining the region of interest and, after processing on the server, the requested proliferation index value is calculated. There is also an "expert corner", where experts can submit their index estimates and comments on particular images, which is especially important for system developers. These expert evaluations are used for optimization and verification of automatic analysis algorithms. Decision support trials have been conducted for ECG and ophthalmology ultrasonic investigations of intraocular tumor differentiation. Data mining algorithms have been applied and decision support trees constructed. These services are under implementation by a Web-based system too. The study has shown that the Web-based structure ensures more effective, flexible and accessible services compared with standalone programs and is very convenient for biomedical engineers and physicians, especially in the development phase.

Automatic bad channel detection in intracranial electroencephalographic recordings using ensemble machine learning.

PubMed

Tuyisenge, Viateur; Trebaul, Lena; Bhattacharjee, Manik; Chanteloup-Forêt, Blandine; Saubat-Guigui, Carole; Mîndruţă, Ioana; Rheims, Sylvain; Maillard, Louis; Kahane, Philippe; Taussig, Delphine; David, Olivier

2018-03-01

Intracranial electroencephalographic (iEEG) recordings contain "bad channels", which show non-neuronal signals. Here, we developed a new method that automatically detects iEEG bad channels using machine learning of seven signal features. The features quantified signals' variance, spatial-temporal correlation and nonlinear properties. Because the number of bad channels is usually much lower than the number of good channels, we implemented an ensemble bagging classifier known to be optimal in terms of stability and predictive accuracy for datasets with imbalanced class distributions. This method was applied on stereo-electroencephalographic (SEEG) signals recording during low frequency stimulations performed in 206 patients from 5 clinical centers. We found that the classification accuracy was extremely good: It increased with the number of subjects used to train the classifier and reached a plateau at 99.77% for 110 subjects. The classification performance was thus not impacted by the multicentric nature of data. The proposed method to automatically detect bad channels demonstrated convincing results and can be envisaged to be used on larger datasets for automatic quality control of iEEG data. This is the first method proposed to classify bad channels in iEEG and should allow to improve the data selection when reviewing iEEG signals. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Onboard Autonomous Corrections for Accurate IRF Pointing.

NASA Astrophysics Data System (ADS)

Jorgensen, J. L.; Betto, M.; Denver, T.

2002-05-01

Over the past decade, the Noise Equivalent Angle (NEA) of onboard attitude reference instruments, has decreased from tens-of-arcseconds to the sub-arcsecond level. This improved performance is partly due to improved sensor-technology with enhanced signal to noise ratios, partly due to improved processing electronics which allows for more sophisticated and faster signal processing. However, the main reason for the increased precision, is the application of onboard autonomy, which apart from simple outlier rejection also allows for removal of "false positive" answers, and other "unexpected" noise sources, that otherwise would degrade the quality of the measurements (e.g. discrimination between signals caused by starlight and ionizing radiation). The utilization of autonomous signal processing has also provided the means for another onboard processing step, namely the autonomous recovery from lost in space, where the attitude instrument without a priori knowledge derive the absolute attitude, i.e. in IRF coordinates, within fractions of a second. Combined with precise orbital state or position data, the absolute attitude information opens for multiple ways to improve the mission performance, either by reducing operations costs, by increasing pointing accuracy, by reducing mission expendables, or by providing backup decision information in case of anomalies. The Advanced Stellar Compass's (ASC) is a miniature, high accuracy, attitude instrument which features fully autonomous operations. The autonomy encompass all direct steps from automatic health checkout at power-on, over fully automatic SEU and SEL handling and proton induced sparkle removal, to recovery from "lost in space", and optical disturbance detection and handling. But apart from these more obvious autonomy functions, the ASC also features functions to handle and remove the aforementioned residuals. These functions encompass diverse operators such as a full orbital state vector model with automatic cloud filtered GPS updates, a world time clock, astrometric correction tables, and a attitude output transform system, that allow the ASC to deliver the spacecraft attitude relative to the Inertial Reference Frame (IRF) in realtime. This paper describes the operations of the onboard autonomy of the ASC, which in realtime removes the residuals from the attitude measurements, whereby a timely IRF attitude at arcsecond level, is delivered to the AOCS (or sent to ground). A discussion about achievable robustness and accuracy is given, and compared to inflight results from the operations of the two Advanced Stellar Compass's (ASC), which are flying in LEO onboard the German geo-potential research satellite CHAMP. The ASC's onboard CHAMP are dual head versions, i.e. each processing unit is attached to two star camera heads. The dual head configuration is primarily employed to achieve a carefree AOCS control with respect to the Sun, Moon and Earth, and to increase the attitude accuracy, but it also enables onboard estimation and removal of thermal generated biases.

Study on automatic ECT data evaluation by using neural network

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

Komatsu, H.; Matsumoto, Y.; Badics, Z.

1994-12-31

At the in--service inspection of the steam generator (SG) tubings in Pressurized Water Reactor (PWR) plant, eddy current testing (ECT) has been widely used at each outage. At present, ECT data evaluation is mainly performed by ECT data analyst, therefore it has the following problems. Only ECT signal configuration on the impedance trajectory is used in the evaluation. It is an enormous time consuming process. The evaluation result is influenced by the ability and experience of the analyst. Especially, it is difficult to identify the true defect signal hidden in background signals such as lift--off noise and deposit signals. Inmore » this work, the authors performed the study on the possibility of the application of neural network to ECT data evaluation. It was demonstrated that the neural network proved to be effective to identify the nature of defect, by selecting several optimum input parameters to categorize the raw ECT signals.« less

Filter design for cancellation of baseline-fluctuation in needle EMG recordings.

PubMed

Rodríguez-Carreño, I; Malanda-Trigueros, A; Gila-Useros, L; Navallas-Irujo, J; Rodríguez-Falces, J

2006-01-01

Appropriate cancellation of the baseline fluctuation (BLF) is an important issue when recording EMG signals as it may degrade signal quality and distort qualitative and quantitative analysis. We present a novel filter-design approach for automatic cancellation of the BLF based on several signal processing techniques used sequentially. The methodology is to estimate the spectral content of the BLF, and then to use this estimation to design a high-pass FIR filter that cancel the BLF present in the signal. Two merit figures are devised for measuring the degree of BLF present in an EMG record. These figures are used to compare our method with the conventional approach, which naively considers the baseline course to be of constant (without any fluctuation) potential shift. Applications of the technique on real and simulated EMG signals show the superior performance of our approach in terms of both visual inspection and the merit figures.

Automated aural classification used for inter-species discrimination of cetaceans.

PubMed

Binder, Carolyn M; Hines, Paul C

2014-04-01

Passive acoustic methods are in widespread use to detect and classify cetacean species; however, passive acoustic systems often suffer from large false detection rates resulting from numerous transient sources. To reduce the acoustic analyst workload, automatic recognition methods may be implemented in a two-stage process. First, a general automatic detector is implemented that produces many detections to ensure cetacean presence is noted. Then an automatic classifier is used to significantly reduce the number of false detections and classify the cetacean species. This process requires development of a robust classifier capable of performing inter-species classification. Because human analysts can aurally discriminate species, an automated aural classifier that uses perceptual signal features was tested on a cetacean data set. The classifier successfully discriminated between four species of cetaceans-bowhead, humpback, North Atlantic right, and sperm whales-with 85% accuracy. It also performed well (100% accuracy) for discriminating sperm whale clicks from right whale gunshots. An accuracy of 92% and area under the receiver operating characteristic curve of 0.97 were obtained for the relatively challenging bowhead and humpback recognition case. These results demonstrated that the perceptual features employed by the aural classifier provided powerful discrimination cues for inter-species classification of cetaceans.

Automatic performance budget: towards a risk reduction

NASA Astrophysics Data System (ADS)

Laporte, Philippe; Blake, Simon; Schmoll, Jürgen; Rulten, Cameron; Savoie, Denis

2014-08-01

In this paper, we discuss the performance matrix of the SST-GATE telescope developed to allow us to partition and allocate the important characteristics to the various subsystems as well as to describe the process in order to verify that the current design will deliver the required performance. Due to the integrated nature of the telescope, a large number of parameters have to be controlled and effective calculation tools must be developed such as an automatic performance budget. Its main advantages consist in alleviating the work of the system engineer when changes occur in the design, in avoiding errors during any re-allocation process and recalculate automatically the scientific performance of the instrument. We explain in this paper the method to convert the ensquared energy (EE) and the signal-to-noise ratio (SNR) required by the science cases into the "as designed" instrument. To ensure successful design, integration and verification of the next generation instruments, it is of the utmost importance to have methods to control and manage the instrument's critical performance characteristics at its very early design steps to limit technical and cost risks in the project development. Such a performance budget is a tool towards this goal.

Development of an Automatic Echo-counting Program for HROFFT Spectrograms

NASA Astrophysics Data System (ADS)

Noguchi, Kazuya; Yamamoto, Masa-Yuki

2008-06-01

Radio meteor observations by Ham-band beacon or FM radio broadcasts using “Ham-band Radio meteor Observation Fast Fourier Transform” (HROFFT) an automatic operating software have been performed widely in recent days. Previously, counting of meteor echoes on the spectrograms of radio meteor observation was performed manually by observers. In the present paper, we introduce an automatic meteor echo counting software application. Although output images of the HROFFT contain both the features of meteor echoes and those of various types of noises, a newly developed image processing technique has been applied, resulting in software that enables a useful auto-counting tool. There exists a slight error in the processing on spectrograms when the observation site is affected by many disturbing noises. Nevertheless, comparison between software and manual counting revealed an agreement of almost 90%. Therefore, we can easily obtain a dataset of detection time, duration time, signal strength, and Doppler shift of each meteor echo from the HROFFT spectrograms. Using this software, statistical analyses of meteor activities is based on the results obtained at many Ham-band Radio meteor Observation (HRO) sites throughout the world, resulting in a very useful “standard” for monitoring meteor stream activities in real time.

Prostate segmentation in MRI using fused T2-weighted and elastography images

NASA Astrophysics Data System (ADS)

Nir, Guy; Sahebjavaher, Ramin S.; Baghani, Ali; Sinkus, Ralph; Salcudean, Septimiu E.

2014-03-01

Segmentation of the prostate in medical imaging is a challenging and important task for surgical planning and delivery of prostate cancer treatment. Automatic prostate segmentation can improve speed, reproducibility and consistency of the process. In this work, we propose a method for automatic segmentation of the prostate in magnetic resonance elastography (MRE) images. The method utilizes the complementary property of the elastogram and the corresponding T2-weighted image, which are obtained from the phase and magnitude components of the imaging signal, respectively. It follows a variational approach to propagate an active contour model based on the combination of region statistics in the elastogram and the edge map of the T2-weighted image. The method is fast and does not require prior shape information. The proposed algorithm is tested on 35 clinical image pairs from five MRE data sets, and is evaluated in comparison with manual contouring. The mean absolute distance between the automatic and manual contours is 1.8mm, with a maximum distance of 5.6mm. The relative area error is 7.6%, and the duration of the segmentation process is 2s per slice.

Automatic generation of pictorial transcripts of video programs

NASA Astrophysics Data System (ADS)

Shahraray, Behzad; Gibbon, David C.

1995-03-01

An automatic authoring system for the generation of pictorial transcripts of video programs which are accompanied by closed caption information is presented. A number of key frames, each of which represents the visual information in a segment of the video (i.e., a scene), are selected automatically by performing a content-based sampling of the video program. The textual information is recovered from the closed caption signal and is initially segmented based on its implied temporal relationship with the video segments. The text segmentation boundaries are then adjusted, based on lexical analysis and/or caption control information, to account for synchronization errors due to possible delays in the detection of scene boundaries or the transmission of the caption information. The closed caption text is further refined through linguistic processing for conversion to lower- case with correct capitalization. The key frames and the related text generate a compact multimedia presentation of the contents of the video program which lends itself to efficient storage and transmission. This compact representation can be viewed on a computer screen, or used to generate the input to a commercial text processing package to generate a printed version of the program.

The Influence of Facial Signals on the Automatic Imitation of Hand Actions

PubMed Central

Butler, Emily E.; Ward, Robert; Ramsey, Richard

2016-01-01

Imitation and facial signals are fundamental social cues that guide interactions with others, but little is known regarding the relationship between these behaviors. It is clear that during expression detection, we imitate observed expressions by engaging similar facial muscles. It is proposed that a cognitive system, which matches observed and performed actions, controls imitation and contributes to emotion understanding. However, there is little known regarding the consequences of recognizing affective states for other forms of imitation, which are not inherently tied to the observed emotion. The current study investigated the hypothesis that facial cue valence would modulate automatic imitation of hand actions. To test this hypothesis, we paired different types of facial cue with an automatic imitation task. Experiments 1 and 2 demonstrated that a smile prompted greater automatic imitation than angry and neutral expressions. Additionally, a meta-analysis of this and previous studies suggests that both happy and angry expressions increase imitation compared to neutral expressions. By contrast, Experiments 3 and 4 demonstrated that invariant facial cues, which signal trait-levels of agreeableness, had no impact on imitation. Despite readily identifying trait-based facial signals, levels of agreeableness did not differentially modulate automatic imitation. Further, a Bayesian analysis showed that the null effect was between 2 and 5 times more likely than the experimental effect. Therefore, we show that imitation systems are more sensitive to prosocial facial signals that indicate “in the moment” states than enduring traits. These data support the view that a smile primes multiple forms of imitation including the copying actions that are not inherently affective. The influence of expression detection on wider forms of imitation may contribute to facilitating interactions between individuals, such as building rapport and affiliation. PMID:27833573

The Influence of Facial Signals on the Automatic Imitation of Hand Actions.

PubMed

Butler, Emily E; Ward, Robert; Ramsey, Richard

2016-01-01

Imitation and facial signals are fundamental social cues that guide interactions with others, but little is known regarding the relationship between these behaviors. It is clear that during expression detection, we imitate observed expressions by engaging similar facial muscles. It is proposed that a cognitive system, which matches observed and performed actions, controls imitation and contributes to emotion understanding. However, there is little known regarding the consequences of recognizing affective states for other forms of imitation, which are not inherently tied to the observed emotion. The current study investigated the hypothesis that facial cue valence would modulate automatic imitation of hand actions. To test this hypothesis, we paired different types of facial cue with an automatic imitation task. Experiments 1 and 2 demonstrated that a smile prompted greater automatic imitation than angry and neutral expressions. Additionally, a meta-analysis of this and previous studies suggests that both happy and angry expressions increase imitation compared to neutral expressions. By contrast, Experiments 3 and 4 demonstrated that invariant facial cues, which signal trait-levels of agreeableness, had no impact on imitation. Despite readily identifying trait-based facial signals, levels of agreeableness did not differentially modulate automatic imitation. Further, a Bayesian analysis showed that the null effect was between 2 and 5 times more likely than the experimental effect. Therefore, we show that imitation systems are more sensitive to prosocial facial signals that indicate "in the moment" states than enduring traits. These data support the view that a smile primes multiple forms of imitation including the copying actions that are not inherently affective. The influence of expression detection on wider forms of imitation may contribute to facilitating interactions between individuals, such as building rapport and affiliation.

Vestibular signals in primate cortex for self-motion perception.

PubMed

Gu, Yong

2018-04-21

The vestibular peripheral organs in our inner ears detect transient motion of the head in everyday life. This information is sent to the central nervous system for automatic processes such as vestibulo-ocular reflexes, balance and postural control, and higher cognitive functions including perception of self-motion and spatial orientation. Recent neurophysiological studies have discovered a prominent vestibular network in the primate cerebral cortex. Many of the areas involved are multisensory: their neurons are modulated by both vestibular signals and visual optic flow, potentially facilitating more robust heading estimation through cue integration. Combining psychophysics, computation, physiological recording and causal manipulation techniques, recent work has addressed both the encoding and decoding of vestibular signals for self-motion perception. Copyright © 2018. Published by Elsevier Ltd.

Analysis on electronic control unit of continuously variable transmission

NASA Astrophysics Data System (ADS)

Cao, Shuanggui

Continuously variable transmission system can ensure that the engine work along the line of best fuel economy, improve fuel economy, save fuel and reduce harmful gas emissions. At the same time, continuously variable transmission allows the vehicle speed is more smooth and improves the ride comfort. Although the CVT technology has made great development, but there are many shortcomings in the CVT. The CVT system of ordinary vehicles now is still low efficiency, poor starting performance, low transmission power, and is not ideal controlling, high cost and other issues. Therefore, many scholars began to study some new type of continuously variable transmission. The transmission system with electronic systems control can achieve automatic control of power transmission, give full play to the characteristics of the engine to achieve optimal control of powertrain, so the vehicle is always traveling around the best condition. Electronic control unit is composed of the core processor, input and output circuit module and other auxiliary circuit module. Input module collects and process many signals sent by sensor and , such as throttle angle, brake signals, engine speed signal, speed signal of input and output shaft of transmission, manual shift signals, mode selection signals, gear position signal and the speed ratio signal, so as to provide its corresponding processing for the controller core.

Method and apparatus for telemetry adaptive bandwidth compression

NASA Technical Reports Server (NTRS)

Graham, Olin L.

1987-01-01

Methods and apparatus are provided for automatic and/or manual adaptive bandwidth compression of telemetry. An adaptive sampler samples a video signal from a scanning sensor and generates a sequence of sampled fields. Each field and range rate information from the sensor are hence sequentially transmitted to and stored in a multiple and adaptive field storage means. The field storage means then, in response to an automatic or manual control signal, transfers the stored sampled field signals to a video monitor in a form for sequential or simultaneous display of a desired number of stored signal fields. The sampling ratio of the adaptive sample, the relative proportion of available communication bandwidth allocated respectively to transmitted data and video information, and the number of fields simultaneously displayed are manually or automatically selectively adjustable in functional relationship to each other and detected range rate. In one embodiment, when relatively little or no scene motion is detected, the control signal maximizes sampling ratio and causes simultaneous display of all stored fields, thus maximizing resolution and bandwidth available for data transmission. When increased scene motion is detected, the control signal is adjusted accordingly to cause display of fewer fields. If greater resolution is desired, the control signal is adjusted to increase the sampling ratio.

On the recognition of emotional vocal expressions: motivations for a holistic approach.

PubMed

Esposito, Anna; Esposito, Antonietta M

2012-10-01

Human beings seem to be able to recognize emotions from speech very well and information communication technology aims to implement machines and agents that can do the same. However, to be able to automatically recognize affective states from speech signals, it is necessary to solve two main technological problems. The former concerns the identification of effective and efficient processing algorithms capable of capturing emotional acoustic features from speech sentences. The latter focuses on finding computational models able to classify, with an approximation as good as human listeners, a given set of emotional states. This paper will survey these topics and provide some insights for a holistic approach to the automatic analysis, recognition and synthesis of affective states.

A study on fast digital discrimination of neutron and gamma-ray for improvement neutron emission profile measurementa)

PubMed Central

Uchida, Y.; Takada, E.; Fujisaki, A.; Isobe, M.; Shinohara, K.; Tomita, H.; Kawarabayashi, J.; Iguchi, T.

2014-01-01

Neutron and γ-ray (n-γ) discrimination with a digital signal processing system has been used to measure the neutron emission profile in magnetic confinement fusion devices. However, a sampling rate must be set low to extend the measurement time because the memory storage is limited. Time jitter decreases a discrimination quality due to a low sampling rate. As described in this paper, a new charge comparison method was developed. Furthermore, automatic n-γ discrimination method was examined using a probabilistic approach. Analysis results were investigated using the figure of merit. Results show that the discrimination quality was improved. Automatic discrimination was applied using the EM algorithm and k-means algorithm. PMID:25430297

30 CFR 75.1103-5 - Automatic fire warning devices; actions and response.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Automatic fire warning devices; actions and... Protection § 75.1103-5 Automatic fire warning devices; actions and response. (a) When the carbon monoxide... fire sensor and warning device systems shall provide an effective warning signal at the following...

30 CFR 75.1103-5 - Automatic fire warning devices; actions and response.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Automatic fire warning devices; actions and... Protection § 75.1103-5 Automatic fire warning devices; actions and response. (a) When the carbon monoxide... fire sensor and warning device systems shall provide an effective warning signal at the following...

Automatic control of positioning along the joint during EBW in conditions of action of magnetic fields

NASA Astrophysics Data System (ADS)

Druzhinina, A. A.; Laptenok, V. D.; Murygin, A. V.; Laptenok, P. V.

2016-11-01

Positioning along the joint during the electron beam welding is a difficult scientific and technical problem to achieve the high quality of welds. The final solution of this problem is not found. This is caused by weak interference protection of sensors of the joint position directly in the welding process. Frequently during the electron beam welding magnetic fields deflect the electron beam from the optical axis of the electron beam gun. The collimated X-ray sensor is used to monitor the beam deflection caused by the action of magnetic fields. Signal of X-ray sensor is processed by the method of synchronous detection. Analysis of spectral characteristics of the X-ray sensor showed that the displacement of the joint from the optical axis of the gun affects on the output signal of sensor. The authors propose dual-circuit system for automatic positioning of the electron beam on the joint during the electron beam welding in conditions of action of magnetic interference. This system includes a contour of joint tracking and contour of compensation of magnetic fields. The proposed system is stable. Calculation of dynamic error of system showed that error of positioning does not exceed permissible deviation of the electron beam from the joint plane.

Perceiving pain in others: validation of a dual processing model.

PubMed

McCrystal, Kalie N; Craig, Kenneth D; Versloot, Judith; Fashler, Samantha R; Jones, Daniel N

2011-05-01

Accurate perception of another person's painful distress would appear to be accomplished through sensitivity to both automatic (unintentional, reflexive) and controlled (intentional, purposive) behavioural expression. We examined whether observers would construe diverse behavioural cues as falling within these domains, consistent with cognitive neuroscience findings describing activation of both automatic and controlled neuroregulatory processes. Using online survey methodology, 308 research participants rated behavioural cues as "goal directed vs. non-goal directed," "conscious vs. unconscious," "uncontrolled vs. controlled," "fast vs. slow," "intentional (deliberate) vs. unintentional," "stimulus driven (obligatory) vs. self driven," and "requiring contemplation vs. not requiring contemplation." The behavioural cues were the 39 items provided by the PROMIS pain behaviour bank, constructed to be representative of the diverse possibilities for pain expression. Inter-item correlations among rating scales provided evidence of sufficient internal consistency justifying a single score on an automatic/controlled dimension (excluding the inconsistent fast vs. slow scale). An initial exploratory factor analysis on 151 participant data sets yielded factors consistent with "controlled" and "automatic" actions, as well as behaviours characterized as "ambiguous." A confirmatory factor analysis using the remaining 151 data sets replicated EFA findings, supporting theoretical predictions that observers would distinguish immediate, reflexive, and spontaneous reactions (primarily facial expression and paralinguistic features of speech) from purposeful and controlled expression (verbal behaviour, instrumental behaviour requiring ongoing, integrated responses). There are implicit dispositions to organize cues signaling pain in others into the well-defined categories predicted by dual process theory. Copyright © 2011 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

A Real-Time Rejection Circuit to Automatically Reject Multiple Interfering Hopping Signals While Passing a Lower Level Desired Signal.

DTIC Science & Technology

contain the low level desired frequency components that are passed through an inverse transform device for producing a frequency domain signal of the desired signal uncorrupted by unwanted signals. Patent applications. (RRH)

Signal-Noise Identification of Magnetotelluric Signals Using Fractal-Entropy and Clustering Algorithm for Targeted De-Noising

NASA Astrophysics Data System (ADS)

Li, Jin; Zhang, Xian; Gong, Jinzhe; Tang, Jingtian; Ren, Zhengyong; Li, Guang; Deng, Yanli; Cai, Jin

A new technique is proposed for signal-noise identification and targeted de-noising of Magnetotelluric (MT) signals. This method is based on fractal-entropy and clustering algorithm, which automatically identifies signal sections corrupted by common interference (square, triangle and pulse waves), enabling targeted de-noising and preventing the loss of useful information in filtering. To implement the technique, four characteristic parameters — fractal box dimension (FBD), higuchi fractal dimension (HFD), fuzzy entropy (FuEn) and approximate entropy (ApEn) — are extracted from MT time-series. The fuzzy c-means (FCM) clustering technique is used to analyze the characteristic parameters and automatically distinguish signals with strong interference from the rest. The wavelet threshold (WT) de-noising method is used only to suppress the identified strong interference in selected signal sections. The technique is validated through signal samples with known interference, before being applied to a set of field measured MT/Audio Magnetotelluric (AMT) data. Compared with the conventional de-noising strategy that blindly applies the filter to the overall dataset, the proposed method can automatically identify and purposefully suppress the intermittent interference in the MT/AMT signal. The resulted apparent resistivity-phase curve is more continuous and smooth, and the slow-change trend in the low-frequency range is more precisely reserved. Moreover, the characteristic of the target-filtered MT/AMT signal is close to the essential characteristic of the natural field, and the result more accurately reflects the inherent electrical structure information of the measured site.

White balance tester with color sensor for industrial applications

NASA Astrophysics Data System (ADS)

Chen, Jiasheng; Zhu, XiaoSong

1996-12-01

The white balance tester is an instrument that adjusts the white balance for color TVs, monitors, and PC displays. We have designed a new white balance tester for use directly at the production line. It picks up the R (Red), G (Green), and B (Blue) signals for the screen using color sensors, compares the signals with the data previously stored in the internal memory, displays their differences with LED bars in the compare mode or displays x y Y, u v Y, JND (just noticeable difference) as well as correlated color temperature in the numerical mode. A built-in TV signal generator sets the luminance of the adjusting screen to the brightness of the reference white screen automatically. A 16-bit single chip microcomputer processes the measured values and controls the output levels of the TV signal generator.

Compensated gain control circuit for buck regulator command charge circuit

DOEpatents

Barrett, David M.

1996-01-01

A buck regulator command charge circuit includes a compensated-gain control signal for compensating for changes in the component values in order to achieve optimal voltage regulation. The compensated-gain control circuit includes an automatic-gain control circuit for generating a variable-gain control signal. The automatic-gain control circuit is formed of a precision rectifier circuit, a filter network, an error amplifier, and an integrator circuit.

Compensated gain control circuit for buck regulator command charge circuit

DOEpatents

Barrett, D.M.

1996-11-05

A buck regulator command charge circuit includes a compensated-gain control signal for compensating for changes in the component values in order to achieve optimal voltage regulation. The compensated-gain control circuit includes an automatic-gain control circuit for generating a variable-gain control signal. The automatic-gain control circuit is formed of a precision rectifier circuit, a filter network, an error amplifier, and an integrator circuit. 5 figs.

Automatic detection of Parkinson's disease in running speech spoken in three different languages.

PubMed

Orozco-Arroyave, J R; Hönig, F; Arias-Londoño, J D; Vargas-Bonilla, J F; Daqrouq, K; Skodda, S; Rusz, J; Nöth, E

2016-01-01

The aim of this study is the analysis of continuous speech signals of people with Parkinson's disease (PD) considering recordings in different languages (Spanish, German, and Czech). A method for the characterization of the speech signals, based on the automatic segmentation of utterances into voiced and unvoiced frames, is addressed here. The energy content of the unvoiced sounds is modeled using 12 Mel-frequency cepstral coefficients and 25 bands scaled according to the Bark scale. Four speech tasks comprising isolated words, rapid repetition of the syllables /pa/-/ta/-/ka/, sentences, and read texts are evaluated. The method proves to be more accurate than classical approaches in the automatic classification of speech of people with PD and healthy controls. The accuracies range from 85% to 99% depending on the language and the speech task. Cross-language experiments are also performed confirming the robustness and generalization capability of the method, with accuracies ranging from 60% to 99%. This work comprises a step forward for the development of computer aided tools for the automatic assessment of dysarthric speech signals in multiple languages.

Robust automatic P-phase picking: an on-line implementation in the analysis of broadband seismogram recordings

NASA Astrophysics Data System (ADS)

Sleeman, Reinoud; van Eck, Torild

1999-06-01

The onset of a seismic signal is determined through joint AR modeling of the noise and the seismic signal, and the application of the Akaike Information Criterion (AIC) using the onset time as parameter. This so-called AR-AIC phase picker has been tested successfully and implemented on the Z-component of the broadband station HGN to provide automatic P-phase picks for a rapid warning system. The AR-AIC picker is shown to provide accurate and robust automatic picks on a large experimental database. Out of 1109 P-phase onsets with signal-to-noise ratio (SNR) above 1 from local, regional and teleseismic earthquakes, our implementation detects 71% and gives a mean difference with manual picks of 0.1 s. An optimal version of the well-established picker of Baer and Kradolfer [Baer, M., Kradolfer, U., An automatic phase picker for local and teleseismic events, Bull. Seism. Soc. Am. 77 (1987) 1437-1445] detects less than 41% and gives a mean difference with manual picks of 0.3 s using the same dataset.

Automated Electroglottographic Inflection Events Detection. A Pilot Study.

PubMed

Codino, Juliana; Torres, María Eugenia; Rubin, Adam; Jackson-Menaldi, Cristina

2016-11-01

Vocal-fold vibration can be analyzed in a noninvasive way by registering impedance changes within the glottis, through electroglottography. The morphology of the electroglottographic (EGG) signal is related to different vibratory patterns. In the literature, a characteristic knee in the descending portion of the signal has been reported. Some EGG signals do not exhibit this particular knee and have other types of events (inflection events) throughout the ascending and/or descending portion of the vibratory cycle. The goal of this work is to propose an automatic method to identify and classify these events. A computational algorithm was developed based on the mathematical properties of the EGG signal, which detects and reports events throughout the contact phase. Retrospective analysis of EGG signals obtained during routine voice evaluation of adult individuals with a variety of voice disorders was performed using the algorithm as well as human raters. Two judges, both experts in clinical voice analysis, and three general speech pathologists performed manual and visual evaluation of the sample set. The results obtained by the automatic method were compared with those of the human raters. Statistical analysis revealed a significant level of agreement. This automatic tool could allow professionals in the clinical setting to obtain an automatic quantitative and qualitative report of such events present in a voice sample, without having to manually analyze the whole EGG signal. In addition, it might provide the speech pathologist with more information that would complement the standard voice evaluation. It could also be a valuable tool in voice research. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

49 CFR 236.515 - Visibility of cab signals.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Visibility of cab signals. 236.515 Section 236.515..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.515 Visibility of cab signals. The cab signals...

49 CFR 236.515 - Visibility of cab signals.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false Visibility of cab signals. 236.515 Section 236.515..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.515 Visibility of cab signals. The cab signals...

49 CFR 236.515 - Visibility of cab signals.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 4 2014-10-01 2014-10-01 false Visibility of cab signals. 236.515 Section 236.515..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.515 Visibility of cab signals. The cab signals...

49 CFR 236.515 - Visibility of cab signals.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 4 2012-10-01 2012-10-01 false Visibility of cab signals. 236.515 Section 236.515..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.515 Visibility of cab signals. The cab signals...

49 CFR 236.515 - Visibility of cab signals.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 4 2013-10-01 2013-10-01 false Visibility of cab signals. 236.515 Section 236.515..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Standards § 236.515 Visibility of cab signals. The cab signals...

A novelty detection diagnostic methodology for gearboxes operating under fluctuating operating conditions using probabilistic techniques

NASA Astrophysics Data System (ADS)

Schmidt, S.; Heyns, P. S.; de Villiers, J. P.

2018-02-01

In this paper, a fault diagnostic methodology is developed which is able to detect, locate and trend gear faults under fluctuating operating conditions when only vibration data from a single transducer, measured on a healthy gearbox are available. A two-phase feature extraction and modelling process is proposed to infer the operating condition and based on the operating condition, to detect changes in the machine condition. Information from optimised machine and operating condition hidden Markov models are statistically combined to generate a discrepancy signal which is post-processed to infer the condition of the gearbox. The discrepancy signal is processed and combined with statistical methods for automatic fault detection and localisation and to perform fault trending over time. The proposed methodology is validated on experimental data and a tacholess order tracking methodology is used to enhance the cost-effectiveness of the diagnostic methodology.

Automatic sleep staging using empirical mode decomposition, discrete wavelet transform, time-domain, and nonlinear dynamics features of heart rate variability signals.

PubMed

Ebrahimi, Farideh; Setarehdan, Seyed-Kamaledin; Ayala-Moyeda, Jose; Nazeran, Homer

2013-10-01

The conventional method for sleep staging is to analyze polysomnograms (PSGs) recorded in a sleep lab. The electroencephalogram (EEG) is one of the most important signals in PSGs but recording and analysis of this signal presents a number of technical challenges, especially at home. Instead, electrocardiograms (ECGs) are much easier to record and may offer an attractive alternative for home sleep monitoring. The heart rate variability (HRV) signal proves suitable for automatic sleep staging. Thirty PSGs from the Sleep Heart Health Study (SHHS) database were used. Three feature sets were extracted from 5- and 0.5-min HRV segments: time-domain features, nonlinear-dynamics features and time-frequency features. The latter was achieved by using empirical mode decomposition (EMD) and discrete wavelet transform (DWT) methods. Normalized energies in important frequency bands of HRV signals were computed using time-frequency methods. ANOVA and t-test were used for statistical evaluations. Automatic sleep staging was based on HRV signal features. The ANOVA followed by a post hoc Bonferroni was used for individual feature assessment. Most features were beneficial for sleep staging. A t-test was used to compare the means of extracted features in 5- and 0.5-min HRV segments. The results showed that the extracted features means were statistically similar for a small number of features. A separability measure showed that time-frequency features, especially EMD features, had larger separation than others. There was not a sizable difference in separability of linear features between 5- and 0.5-min HRV segments but separability of nonlinear features, especially EMD features, decreased in 0.5-min HRV segments. HRV signal features were classified by linear discriminant (LD) and quadratic discriminant (QD) methods. Classification results based on features from 5-min segments surpassed those obtained from 0.5-min segments. The best result was obtained from features using 5-min HRV segments classified by the LD classifier. A combination of linear/nonlinear features from HRV signals is effective in automatic sleep staging. Moreover, time-frequency features are more informative than others. In addition, a separability measure and classification results showed that HRV signal features, especially nonlinear features, extracted from 5-min segments are more discriminative than those from 0.5-min segments in automatic sleep staging. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Automatic calibration system for analog instruments based on DSP and CCD sensor

NASA Astrophysics Data System (ADS)

Lan, Jinhui; Wei, Xiangqin; Bai, Zhenlong

2008-12-01

Currently, the calibration work of analog measurement instruments is mainly completed by manual and there are many problems waiting for being solved. In this paper, an automatic calibration system (ACS) based on Digital Signal Processor (DSP) and Charge Coupled Device (CCD) sensor is developed and a real-time calibration algorithm is presented. In the ACS, TI DM643 DSP processes the data received by CCD sensor and the outcome is displayed on Liquid Crystal Display (LCD) screen. For the algorithm, pointer region is firstly extracted for improving calibration speed. And then a math model of the pointer is built to thin the pointer and determine the instrument's reading. Through numbers of experiments, the time of once reading is no more than 20 milliseconds while it needs several seconds if it is done manually. At the same time, the error of the instrument's reading satisfies the request of the instruments. It is proven that the automatic calibration system can effectively accomplish the calibration work of the analog measurement instruments.

Kinase Pathway Database: An Integrated Protein-Kinase and NLP-Based Protein-Interaction Resource

PubMed Central

Koike, Asako; Kobayashi, Yoshiyuki; Takagi, Toshihisa

2003-01-01

Protein kinases play a crucial role in the regulation of cellular functions. Various kinds of information about these molecules are important for understanding signaling pathways and organism characteristics. We have developed the Kinase Pathway Database, an integrated database involving major completely sequenced eukaryotes. It contains the classification of protein kinases and their functional conservation, ortholog tables among species, protein–protein, protein–gene, and protein–compound interaction data, domain information, and structural information. It also provides an automatic pathway graphic image interface. The protein, gene, and compound interactions are automatically extracted from abstracts for all genes and proteins by natural-language processing (NLP).The method of automatic extraction uses phrase patterns and the GENA protein, gene, and compound name dictionary, which was developed by our group. With this database, pathways are easily compared among species using data with more than 47,000 protein interactions and protein kinase ortholog tables. The database is available for querying and browsing at http://kinasedb.ontology.ims.u-tokyo.ac.jp/. PMID:12799355

Automatic pattern identification of rock moisture based on the Staff-RF model

NASA Astrophysics Data System (ADS)

Zheng, Wei; Tao, Kai; Jiang, Wei

2018-04-01

Studies on the moisture and damage state of rocks generally focus on the qualitative description and mechanical information of rocks. This method is not applicable to the real-time safety monitoring of rock mass. In this study, a musical staff computing model is used to quantify the acoustic emission signals of rocks with different moisture patterns. Then, the random forest (RF) method is adopted to form the staff-RF model for the real-time pattern identification of rock moisture. The entire process requires only the computing information of the AE signal and does not require the mechanical conditions of rocks.

Self-Calibrating and Remote Programmable Signal Conditioning Amplifier System and Method

NASA Technical Reports Server (NTRS)

Medelius, Pedro J. (Inventor); Hallberg, Carl G. (Inventor); Simpson, Howard J., III (Inventor); Thayer, Stephen W. (Inventor)

1998-01-01

A self-calibrating, remote programmable signal conditioning amplifier system employs information read from a memory attached to a measurement transducer for automatic calibration. The signal conditioning amplifier is self-calibrated on a continuous basis through use of a dual input path arrangement, with each path containing a multiplexer and a programmable amplifier. A digital signal processor controls operation of the system such that a transducer signal is applied to one of the input paths, while one or more calibration signals are applied to the second input path. Once the second path is calibrated, the digital signal processor switches the transducer signal to the second path. and then calibrates the first path. This process is continually repeated so that each path is calibrated on an essentially continuous basis. Dual output paths are also employed which are calibrated in the same manner. The digital signal processor also allows the implementation of a variety of digital filters which are either programmed into the system or downloaded by an operator, and performs up to eighth order linearization.

Real power regulation for the utility power grid via responsive loads

DOEpatents

McIntyre, Timothy J [Knoxville, TN; Kirby, Brendan J [Knoxville, TN; Kisner, Roger A

2009-05-19

A system for dynamically managing an electrical power system that determines measures of performance and control criteria for the electric power system, collects at least one automatic generation control (AGC) input parameter to at least one AGC module and at least one automatic load control (ALC) input parameter to at least one ALC module, calculates AGC control signals and loads as resources (LAR) control signals in response to said measures of performance and control criteria, propagates AGC control signals to power generating units in response to control logic in AGC modules, and propagates LAR control signals to at least one LAR in response to control logic in ALC modules.

eCTG: an automatic procedure to extract digital cardiotocographic signals from digital images.

PubMed

Sbrollini, Agnese; Agostinelli, Angela; Marcantoni, Ilaria; Morettini, Micaela; Burattini, Luca; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura

2018-03-01

Cardiotocography (CTG), consisting in the simultaneous recording of fetal heart rate (FHR) and maternal uterine contractions (UC), is a popular clinical test to assess fetal health status. Typically, CTG machines provide paper reports that are visually interpreted by clinicians. Consequently, visual CTG interpretation depends on clinician's experience and has a poor reproducibility. The lack of databases containing digital CTG signals has limited number and importance of retrospective studies finalized to set up procedures for automatic CTG analysis that could contrast visual CTG interpretation subjectivity. In order to help overcoming this problem, this study proposes an electronic procedure, termed eCTG, to extract digital CTG signals from digital CTG images, possibly obtainable by scanning paper CTG reports. eCTG was specifically designed to extract digital CTG signals from digital CTG images. It includes four main steps: pre-processing, Otsu's global thresholding, signal extraction and signal calibration. Its validation was performed by means of the "CTU-UHB Intrapartum Cardiotocography Database" by Physionet, that contains digital signals of 552 CTG recordings. Using MATLAB, each signal was plotted and saved as a digital image that was then submitted to eCTG. Digital CTG signals extracted by eCTG were eventually compared to corresponding signals directly available in the database. Comparison occurred in terms of signal similarity (evaluated by the correlation coefficient ρ, and the mean signal error MSE) and clinical features (including FHR baseline and variability; number, amplitude and duration of tachycardia, bradycardia, acceleration and deceleration episodes; number of early, variable, late and prolonged decelerations; and UC number, amplitude, duration and period). The value of ρ between eCTG and reference signals was 0.85 (P < 10 -560 ) for FHR and 0.97 (P < 10 -560 ) for UC. On average, MSE value was 0.00 for both FHR and UC. No CTG feature was found significantly different when measured in eCTG vs. reference signals. eCTG procedure is a promising useful tool to accurately extract digital FHR and UC signals from digital CTG images. Copyright © 2018 Elsevier B.V. All rights reserved.

Reward history but not search history explains value-driven attentional capture.

PubMed

Marchner, Janina R; Preuschhof, Claudia

2018-04-19

In past years, an extensive amount of research has focused on how past experiences guide future attention. Humans automatically attend to stimuli previously associated with reward and stimuli that have been experienced during visual search, even when it is disadvantageous in present situations. Recently, the relationship between "reward history" and "search history" has been discussed critically. We review results from research on value-driven attentional capture (VDAC) with a focus on these two experience-based attentional selection processes and their distinction. To clarify inconsistencies, we examined VDAC within a design that allows a direct comparison with other mechanisms of attentional selection. Eighty-four healthy adults were trained to incidentally associate colors with reward (10 cents, 2 cents) or with no reward. In a subsequent visual search task, distraction by reward-associated and unrewarded stimuli was contrasted. In the training phase, reward signals facilitated performance. When these value-signaling stimuli appeared as distractors in the test phase, they continuously shaped attentional selection, despite their task irrelevance. Our findings clearly cannot be attributed to a history of target search. We conclude that once an association is established, value signals guide attention automatically in new situations, which can be beneficial or not, depending on the congruency with current goals.

7. OBLIQUE VIEW, HOME SIGNAL, WESTBOUND ON CATENARY BRIDGE 518 ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

7. OBLIQUE VIEW, HOME SIGNAL, WESTBOUND ON CATENARY BRIDGE 518 - New York, New Haven & Hartford Railroad, Automatic Signalization System, Long Island Sound shoreline between Stamford & New Haven, Stamford, Fairfield County, CT

49 CFR 236.804 - Signal, block.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Signal, block. 236.804 Section 236.804 Transportation Other Regulations Relating to Transportation (Continued) FEDERAL RAILROAD ADMINISTRATION... Signal, block. A roadway signal operated either automatically or manually at the entrance to a block. ...

New technique for real-time distortion-invariant multiobject recognition and classification

NASA Astrophysics Data System (ADS)

Hong, Rutong; Li, Xiaoshun; Hong, En; Wang, Zuyi; Wei, Hongan

2001-04-01

A real-time hybrid distortion-invariant OPR system was established to make 3D multiobject distortion-invariant automatic pattern recognition. Wavelet transform technique was used to make digital preprocessing of the input scene, to depress the noisy background and enhance the recognized object. A three-layer backpropagation artificial neural network was used in correlation signal post-processing to perform multiobject distortion-invariant recognition and classification. The C-80 and NOA real-time processing ability and the multithread programming technology were used to perform high speed parallel multitask processing and speed up the post processing rate to ROIs. The reference filter library was constructed for the distortion version of 3D object model images based on the distortion parameter tolerance measuring as rotation, azimuth and scale. The real-time optical correlation recognition testing of this OPR system demonstrates that using the preprocessing, post- processing, the nonlinear algorithm os optimum filtering, RFL construction technique and the multithread programming technology, a high possibility of recognition and recognition rate ere obtained for the real-time multiobject distortion-invariant OPR system. The recognition reliability and rate was improved greatly. These techniques are very useful to automatic target recognition.

An Application of Reassigned Time-Frequency Representations for Seismic Noise/Signal Decomposition

NASA Astrophysics Data System (ADS)

Mousavi, S. M.; Langston, C. A.

2016-12-01

Seismic data recorded by surface arrays are often strongly contaminated by unwanted noise. This background noise makes the detection of small magnitude events difficult. An automatic method for seismic noise/signal decomposition is presented based upon an enhanced time-frequency representation. Synchrosqueezing is a time-frequency reassignment method aimed at sharpening a time-frequency picture. Noise can be distinguished from the signal and suppressed more easily in this reassigned domain. The threshold level is estimated using a general cross validation approach that does not rely on any prior knowledge about the noise level. Efficiency of thresholding has been improved by adding a pre-processing step based on higher order statistics and a post-processing step based on adaptive hard-thresholding. In doing so, both accuracy and speed of the denoising have been improved compared to our previous algorithms (Mousavi and Langston, 2016a, 2016b; Mousavi et al., 2016). The proposed algorithm can either kill the noise (either white or colored) and keep the signal or kill the signal and keep the noise. Hence, It can be used in either normal denoising applications or in ambient noise studies. Application of the proposed method on synthetic and real seismic data shows the effectiveness of the method for denoising/designaling of local microseismic, and ocean bottom seismic data. References: Mousavi, S.M., C. A. Langston., and S. P. Horton (2016), Automatic Microseismic Denoising and Onset Detection Using the Synchrosqueezed-Continuous Wavelet Transform. Geophysics. 81, V341-V355, doi: 10.1190/GEO2015-0598.1. Mousavi, S.M., and C. A. Langston (2016a), Hybrid Seismic Denoising Using Higher-Order Statistics and Improved Wavelet Block Thresholding. Bull. Seismol. Soc. Am., 106, doi: 10.1785/0120150345. Mousavi, S.M., and C.A. Langston (2016b), Adaptive noise estimation and suppression for improving microseismic event detection, Journal of Applied Geophysics., doi: http://dx.doi.org/10.1016/j.jappgeo.2016.06.008.

49 CFR 236.804 - Signal, block.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false Signal, block. 236.804 Section 236.804..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.804 Signal, block. A roadway signal operated either automatically or manually at the entrance to a block. ...

49 CFR 236.205 - Signal control circuits; requirements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false Signal control circuits; requirements. 236.205..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Block Signal Systems Standards § 236.205 Signal control circuits; requirements. The circuits shall be so...

49 CFR 236.205 - Signal control circuits; requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Signal control circuits; requirements. 236.205..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Block Signal Systems Standards § 236.205 Signal control circuits; requirements. The circuits shall be so...

49 CFR 236.804 - Signal, block.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 4 2014-10-01 2014-10-01 false Signal, block. 236.804 Section 236.804..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.804 Signal, block. A roadway signal operated either automatically or manually at the entrance to a block. ...

49 CFR 236.804 - Signal, block.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 4 2013-10-01 2013-10-01 false Signal, block. 236.804 Section 236.804..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.804 Signal, block. A roadway signal operated either automatically or manually at the entrance to a block. ...

49 CFR 236.804 - Signal, block.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 4 2012-10-01 2012-10-01 false Signal, block. 236.804 Section 236.804..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.804 Signal, block. A roadway signal operated either automatically or manually at the entrance to a block. ...

49 CFR 236.205 - Signal control circuits; requirements.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 4 2014-10-01 2014-10-01 false Signal control circuits; requirements. 236.205..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Block Signal Systems Standards § 236.205 Signal control circuits; requirements. The circuits shall be so...

49 CFR 236.205 - Signal control circuits; requirements.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 4 2012-10-01 2012-10-01 false Signal control circuits; requirements. 236.205..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Block Signal Systems Standards § 236.205 Signal control circuits; requirements. The circuits shall be so...

49 CFR 236.205 - Signal control circuits; requirements.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 4 2013-10-01 2013-10-01 false Signal control circuits; requirements. 236.205..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Block Signal Systems Standards § 236.205 Signal control circuits; requirements. The circuits shall be so...

On comprehensive recovery of an aftershock sequence with cross correlation

NASA Astrophysics Data System (ADS)

Kitov, I.; Bobrov, D.; Coyne, J.; Turyomurugyendo, G.

2012-04-01

We have introduced cross correlation between seismic waveforms as a technique for signal detection and automatic event building at the International Data Centre (IDC) of the Comprehensive Nuclear-Test-Ban Treaty Organization. The intuition behind signal detection is simple - small and mid-sized seismic events close in space should produce similar signals at the same seismic stations. Equivalently, these signals have to be characterized by a high cross correlation coefficient. For array stations with many individual sensors distributed over a large area, signals from events at distances beyond, say, 50 km, are subject to destructive interference when cross correlated due to changing time delays between various channels. Thus, any cross correlation coefficient above some predefined threshold can be considered as a signature of a valid signal. With a dense grid of master events (spacing between adjacent masters between 20 km and 50 km corresponds to the statistically estimated correlation distance) with high quality (signal-to-noise ratio above 10) template waveforms at primary array stations of the International Monitoring System one can detect signals from and then build natural and manmade seismic events close to the master ones. The use of cross correlation allows detecting smaller signals (sometimes below noise level) than provided by the current IDC detecting techniques. As a result it is possible to automatically build from 50% to 100% more valid seismic events than included in the Reviewed Event Bulletin (REB). We have developed a tentative pipeline for automatic processing at the IDC. It includes three major stages. Firstly, we calculate cross correlation coefficient for a given master and continuous waveforms at the same stations and carry out signal detection as based on the statistical behavior of signal-to-noise ratio of the cross correlation coefficient. Secondly, a thorough screening is performed for all obtained signals using f-k analysis and F-statistics as applied to the cross-correlation traces at individual channels of all included array stations. Thirdly, local (i.e. confined to the correlation distance around the master event) association of origin times of all qualified signals is fulfilled. These origin times are calculated from the arrival times of these signals, which are reduced to the origin times by the travel times from the master event. An aftershock sequence of a mid-size earthquake is an ideal case to test cross correlation techniques for autiomatic event building. All events should be close to the mainshock and occur within several days. Here we analyse the aftershock sequence of an earthquake in the North Atlantic Ocean with mb(IDC)=4.79. The REB includes 38 events at distances less than 150 km from the mainshock. Our ultimate goal is to excersice the complete iterative procedure to find all possible aftershocks. We start with the mainshock and recover ten aftershocks with the largest number of stations to produce an initial set of master events with the highest quality templates. Then we find all aftershocks in the REB and many additional events, which were not originally found by the IDC. Using all events found after the first iteration as master events we find new events, which are also used in the next iteration. The iterative process stops when no new events can be found. In that sense the final set of aftershocks obtained with cross correlation is a comprehensive one.

Knowing who's boss: implicit perceptions of status from the nonverbal expression of pride.

PubMed

Shariff, Azim F; Tracy, Jessica L

2009-10-01

Evolutionary theory suggests that the universal recognition of nonverbal expressions of emotions functions to enhance fitness. Specifically, emotion expressions may send survival-relevant messages to other social group members, who have the capacity to automatically interpret these signals. In the present research, we used 3 different implicit association methodologies to test whether the nonverbal expression of pride sends a functional, automatically perceived signal about a social group member's increased social status. Results suggest that the pride expression strongly signals high status, and this association cannot be accounted for by positive valence or artifacts of the expression such as expanded size due to outstretched arms. These findings suggest that the pride expression may function to uniquely communicate the high status of those who show it. Discussion focuses on the implications of these findings for social functions of emotion expressions and the automatic communication of status.

Automatic Speech Acquisition and Recognition for Spacesuit Audio Systems

NASA Technical Reports Server (NTRS)

Ye, Sherry

2015-01-01

NASA has a widely recognized but unmet need for novel human-machine interface technologies that can facilitate communication during astronaut extravehicular activities (EVAs), when loud noises and strong reverberations inside spacesuits make communication challenging. WeVoice, Inc., has developed a multichannel signal-processing method for speech acquisition in noisy and reverberant environments that enables automatic speech recognition (ASR) technology inside spacesuits. The technology reduces noise by exploiting differences between the statistical nature of signals (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, ASR accuracy can be improved to the level at which crewmembers will find the speech interface useful. System components and features include beam forming/multichannel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, and ASR decoding. Arithmetic complexity models were developed and will help designers of real-time ASR systems select proper tasks when confronted with constraints in computational resources. In Phase I of the project, WeVoice validated the technology. The company further refined the technology in Phase II and developed a prototype for testing and use by suited astronauts.

Computer controlled synchronous shifting of an automatic transmission

DOEpatents

Davis, Roy I.; Patil, Prabhakar B.

1989-01-01

A multiple forward speed automatic transmission produces its lowest forward speed ratio when a hydraulic clutch and hydraulic brake are disengaged and a one-way clutch connects a ring gear to the transmission casing. Second forward speed ratio results when the hydraulic clutch is engaged to connect the ring gear to the planetary carrier of a second gear set. Reverse drive and regenerative operation result when an hydraulic brake fixes the planetary and the direction of power flow is reversed. Various sensors produce signals representing the torque at the output of the transmission or drive wheels, the speed of the power source, and the hydraulic pressure applied to a clutch and brake. A control algorithm produces input data representing a commanded upshift, a commanded downshift, a commanded transmission output torque, and commanded power source speed. A microprocessor processes the inputs and produces a response to them in accordance with the execution of a control algorithm. Output or response signals cause selective engagement and disengagement of the clutch and brake at a rate that satisfies the requirements for a short gear ratio change and smooth torque transfer between the friction elements.

Efficient Sparse Signal Transmission over a Lossy Link Using Compressive Sensing

PubMed Central

Wu, Liantao; Yu, Kai; Cao, Dongyu; Hu, Yuhen; Wang, Zhi

2015-01-01

Reliable data transmission over lossy communication link is expensive due to overheads for error protection. For signals that have inherent sparse structures, compressive sensing (CS) is applied to facilitate efficient sparse signal transmissions over lossy communication links without data compression or error protection. The natural packet loss in the lossy link is modeled as a random sampling process of the transmitted data, and the original signal will be reconstructed from the lossy transmission results using the CS-based reconstruction method at the receiving end. The impacts of packet lengths on transmission efficiency under different channel conditions have been discussed, and interleaving is incorporated to mitigate the impact of burst data loss. Extensive simulations and experiments have been conducted and compared to the traditional automatic repeat request (ARQ) interpolation technique, and very favorable results have been observed in terms of both accuracy of the reconstructed signals and the transmission energy consumption. Furthermore, the packet length effect provides useful insights for using compressed sensing for efficient sparse signal transmission via lossy links. PMID:26287195

Motor signatures of emotional reactivity in frontotemporal dementia.

PubMed

Marshall, Charles R; Hardy, Chris J D; Russell, Lucy L; Clark, Camilla N; Bond, Rebecca L; Dick, Katrina M; Brotherhood, Emilie V; Mummery, Cath J; Schott, Jonathan M; Rohrer, Jonathan D; Kilner, James M; Warren, Jason D

2018-01-18

Automatic motor mimicry is essential to the normal processing of perceived emotion, and disrupted automatic imitation might underpin socio-emotional deficits in neurodegenerative diseases, particularly the frontotemporal dementias. However, the pathophysiology of emotional reactivity in these diseases has not been elucidated. We studied facial electromyographic responses during emotion identification on viewing videos of dynamic facial expressions in 37 patients representing canonical frontotemporal dementia syndromes versus 21 healthy older individuals. Neuroanatomical associations of emotional expression identification accuracy and facial muscle reactivity were assessed using voxel-based morphometry. Controls showed characteristic profiles of automatic imitation, and this response predicted correct emotion identification. Automatic imitation was reduced in the behavioural and right temporal variant groups, while the normal coupling between imitation and correct identification was lost in the right temporal and semantic variant groups. Grey matter correlates of emotion identification and imitation were delineated within a distributed network including primary visual and motor, prefrontal, insular, anterior temporal and temporo-occipital junctional areas, with common involvement of supplementary motor cortex across syndromes. Impaired emotional mimesis may be a core mechanism of disordered emotional signal understanding and reactivity in frontotemporal dementia, with implications for the development of novel physiological biomarkers of socio-emotional dysfunction in these diseases.

Activity classification using realistic data from wearable sensors.

PubMed

Pärkkä, Juha; Ermes, Miikka; Korpipää, Panu; Mäntyjärvi, Jani; Peltola, Johannes; Korhonen, Ilkka

2006-01-01

Automatic classification of everyday activities can be used for promotion of health-enhancing physical activities and a healthier lifestyle. In this paper, methods used for classification of everyday activities like walking, running, and cycling are described. The aim of the study was to find out how to recognize activities, which sensors are useful and what kind of signal processing and classification is required. A large and realistic data library of sensor data was collected. Sixteen test persons took part in the data collection, resulting in approximately 31 h of annotated, 35-channel data recorded in an everyday environment. The test persons carried a set of wearable sensors while performing several activities during the 2-h measurement session. Classification results of three classifiers are shown: custom decision tree, automatically generated decision tree, and artificial neural network. The classification accuracies using leave-one-subject-out cross validation range from 58 to 97% for custom decision tree classifier, from 56 to 97% for automatically generated decision tree, and from 22 to 96% for artificial neural network. Total classification accuracy is 82 % for custom decision tree classifier, 86% for automatically generated decision tree, and 82% for artificial neural network.

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.

Manufacturing Methods and Technology Program Automatic In-Process Microcircuit Evaluation.

DTIC Science & Technology

1980-10-01

methods of controlling the AIME system are with the computer and associated inter- face (CPU control), and with controls located on the front panels...Sync and Blanking signals When the AIME system is being operated by the front panel controls , the computer does not influence the system operation. SU...the color video monitor display. The operator controls these parameters by 1) depressing the appropriate key on the keyboard, 2) observing on the

Sensory Information Processing and Symbolic Computation

DTIC Science & Technology

1973-12-31

plague all image deblurring methods when working with high signal to noise ratios, is that of a ringing or ghost image phenomenon which surrounds high...Figure 11 The Impulse Response of an All-Pass Random Phase Filter 24 Figure 12 (a) Unsmoothed Log Spectra of the Sentence "The pipe began to...of automatic deblurring of images, linear predictive coding of speech and the refinement and application of mathematical models of human vision and

Review of Current Aided/Automatic Target Acquisition Technology for Military Target Acquisition Tasks

DTIC Science & Technology

2011-07-01

radar [e.g., synthetic aperture radar (SAR)]. EO/IR includes multi- and hyperspectral imaging. Signal processing of data from nonimaging sensors, such...enhanced recognition ability. Other nonimage -based techniques, such as category theory,45 hierarchical systems,46 and gradient index flow,47 are possible...the battle- field. There is a plethora of imaging and nonimaging sensors on the battlefield that are being networked together for trans- mission of

[Experience in the use of equipment for ECG system analysis in municipal polyclinics].

PubMed

Bondarenko, A A

2006-01-01

Two electrocardiographs, an analog-digital electrocardiograph with preliminary analog filtering of signal and a smart cardiograph implemented as a PC-compatible device without preliminary analog filtering, are considered. Advantages and disadvantages of ECG systems based on artificial intelligence are discussed. ECG interpretation modes provided by the two electrocardiographs are considered. The reliability of automatic ECG interpretation is assessed. Problems of rational use of automated ECG processing systems are discussed.

Automatic processing of semantic relations in fMRI: neural activation during semantic priming of taxonomic and thematic categories.

PubMed

Sachs, Olga; Weis, Susanne; Zellagui, Nadia; Huber, Walter; Zvyagintsev, Mikhail; Mathiak, Klaus; Kircher, Tilo

2008-07-07

Most current models of knowledge organization are based on hierarchical or taxonomic categories (animals, tools). Another important organizational pattern is thematic categorization, i.e. categories held together by external relations, a unifying scene or event (car and garage). The goal of this study was to compare the neural correlates of these categories under automatic processing conditions that minimize strategic influences. We used fMRI to examine neural correlates of semantic priming for category members with a short stimulus onset asynchrony (SOA) of 200 ms as subjects performed a lexical decision task. Four experimental conditions were compared: thematically related words (car-garage); taxonomically related (car-bus); unrelated (car-spoon); non-word trials (car-derf). We found faster reaction times for related than for unrelated prime-target pairs for both thematic and taxonomic categories. However, the size of the thematic priming effect was greater than that of the taxonomic. The imaging data showed signal changes for the taxonomic priming effects in the right precuneus, postcentral gyrus, middle frontal and superior frontal gyri and thematic priming effects in the right middle frontal gyrus and anterior cingulate. The contrast of neural priming effects showed larger signal changes in the right precuneus associated with the taxonomic but not with thematic priming response. We suggest that the greater involvement of precuneus in the processing of taxonomic relations indicates their reduced salience in the knowledge structure compared to more prominent thematic relations.

49 CFR 236.201 - Track-circuit control of signals.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Block Signal Systems Standards § 236.201 Track-circuit control of signals. The control circuits for home... 49 Transportation 4 2011-10-01 2011-10-01 false Track-circuit control of signals. 236.201 Section...

49 CFR 236.201 - Track-circuit control of signals.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Block Signal Systems Standards § 236.201 Track-circuit control of signals. The control circuits for home... 49 Transportation 4 2010-10-01 2010-10-01 false Track-circuit control of signals. 236.201 Section...

49 CFR 236.202 - Signal governing movements over hand-operated switch.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Signal governing movements over hand-operated..., AND APPLIANCES Automatic Block Signal Systems Standards § 236.202 Signal governing movements over hand-operated switch. Signal governing movements over hand-operated switch in the facing direction shall display...

49 CFR 236.14 - Spring switch signal protection; requirements.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 4 2012-10-01 2012-10-01 false Spring switch signal protection; requirements. 236... Rules and Instructions: All Systems General § 236.14 Spring switch signal protection; requirements. (a... track signaled for movements in only one direction through a spring switch in automatic block signal...

49 CFR 236.14 - Spring switch signal protection; requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Spring switch signal protection; requirements. 236... Rules and Instructions: All Systems General § 236.14 Spring switch signal protection; requirements. (a... track signaled for movements in only one direction through a spring switch in automatic block signal...

49 CFR 236.14 - Spring switch signal protection; requirements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false Spring switch signal protection; requirements. 236... Rules and Instructions: All Systems General § 236.14 Spring switch signal protection; requirements. (a... track signaled for movements in only one direction through a spring switch in automatic block signal...

49 CFR 236.14 - Spring switch signal protection; requirements.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 4 2013-10-01 2013-10-01 false Spring switch signal protection; requirements. 236... Rules and Instructions: All Systems General § 236.14 Spring switch signal protection; requirements. (a... track signaled for movements in only one direction through a spring switch in automatic block signal...

49 CFR 236.14 - Spring switch signal protection; requirements.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 4 2014-10-01 2014-10-01 false Spring switch signal protection; requirements. 236... Rules and Instructions: All Systems General § 236.14 Spring switch signal protection; requirements. (a... track signaled for movements in only one direction through a spring switch in automatic block signal...

Security Enhancement of Wireless Sensor Networks Using Signal Intervals

PubMed Central

Moon, Jaegeun; Jung, Im Y.; Yoo, Jaesoo

2017-01-01

Various wireless technologies, such as RF, Bluetooth, and Zigbee, have been applied to sensor communications. However, the applications of Bluetooth-based wireless sensor networks (WSN) have a security issue. In one pairing process during Bluetooth communication, which is known as simple secure pairing (SSP), the devices are required to specify I/O capability or user interference to prevent man-in-the-middle (MITM) attacks. This study proposes an enhanced SSP in which a nonce to be transferred is converted to a corresponding signal interval. The quantization level, which is used to interpret physical signal intervals, is renewed at every connection by the transferred nonce and applied to the next nonce exchange so that the same signal intervals can represent different numbers. Even if attackers eavesdrop on the signals, they cannot understand what is being transferred because they cannot determine the quantization level. Furthermore, the proposed model does not require exchanging passkeys as data, and the devices are secure in the case of using a fixed PIN. Subsequently, the new quantization level is calculated automatically whenever the same devices attempt to connect with each other. Therefore, the pairing process can be protected from MITM attacks and be convenient for users. PMID:28368341

Security Enhancement of Wireless Sensor Networks Using Signal Intervals.

PubMed

Moon, Jaegeun; Jung, Im Y; Yoo, Jaesoo

2017-04-02

Various wireless technologies, such as RF, Bluetooth, and Zigbee, have been applied to sensor communications. However, the applications of Bluetooth-based wireless sensor networks (WSN) have a security issue. In one pairing process during Bluetooth communication, which is known as simple secure pairing (SSP), the devices are required to specify I/O capability or user interference to prevent man-in-the-middle (MITM) attacks. This study proposes an enhanced SSP in which a nonce to be transferred is converted to a corresponding signal interval. The quantization level, which is used to interpret physical signal intervals, is renewed at every connection by the transferred nonce and applied to the next nonce exchange so that the same signal intervals can represent different numbers. Even if attackers eavesdrop on the signals, they cannot understand what is being transferred because they cannot determine the quantization level. Furthermore, the proposed model does not require exchanging passkeys as data, and the devices are secure in the case of using a fixed PIN. Subsequently, the new quantization level is calculated automatically whenever the same devices attempt to connect with each other. Therefore, the pairing process can be protected from MITM attacks and be convenient for users.

Automated processing of label-free Raman microscope images of macrophage cells with standardized regression for high-throughput analysis.

PubMed

Milewski, Robert J; Kumagai, Yutaro; Fujita, Katsumasa; Standley, Daron M; Smith, Nicholas I

2010-11-19

Macrophages represent the front lines of our immune system; they recognize and engulf pathogens or foreign particles thus initiating the immune response. Imaging macrophages presents unique challenges, as most optical techniques require labeling or staining of the cellular compartments in order to resolve organelles, and such stains or labels have the potential to perturb the cell, particularly in cases where incomplete information exists regarding the precise cellular reaction under observation. Label-free imaging techniques such as Raman microscopy are thus valuable tools for studying the transformations that occur in immune cells upon activation, both on the molecular and organelle levels. Due to extremely low signal levels, however, Raman microscopy requires sophisticated image processing techniques for noise reduction and signal extraction. To date, efficient, automated algorithms for resolving sub-cellular features in noisy, multi-dimensional image sets have not been explored extensively. We show that hybrid z-score normalization and standard regression (Z-LSR) can highlight the spectral differences within the cell and provide image contrast dependent on spectral content. In contrast to typical Raman imaging processing methods using multivariate analysis, such as single value decomposition (SVD), our implementation of the Z-LSR method can operate nearly in real-time. In spite of its computational simplicity, Z-LSR can automatically remove background and bias in the signal, improve the resolution of spatially distributed spectral differences and enable sub-cellular features to be resolved in Raman microscopy images of mouse macrophage cells. Significantly, the Z-LSR processed images automatically exhibited subcellular architectures whereas SVD, in general, requires human assistance in selecting the components of interest. The computational efficiency of Z-LSR enables automated resolution of sub-cellular features in large Raman microscopy data sets without compromise in image quality or information loss in associated spectra. These results motivate further use of label free microscopy techniques in real-time imaging of live immune cells.

Space Weather Effects on Mid-Latitude Railways: a Statistical Study of Anomalies observed in the Operation of Signaling and Train Control Equipment on the East-Siberian Railway

NASA Astrophysics Data System (ADS)

Kasinskii, V. V.; Ptitsyna, N. G.; Lyahov, N. N.; Dorman, L. I.; Villoresi, G.; Iucci, N.

The end result of a long chain of space weather events beginning on the Sun is the induction of currents in ground-based long conductors as power lines pipelines and railways Intense geomagnetically induced currents GIC can hamper rail traffic by disturbing signaling and train control systems In few cases induced voltages were believed to have affected signaling equipment in Sweden Jansen et al 2000 and in the North of Russia Belov et al 2005 GIC threats have been a concern for technological systems at high-latitude locations due to disturbances driven by electrojet intensifications However other geomagnetic storm processes such as SSC and ring current enhancement can also cause GIC concerns for the technological systems Objective of this report is to continue our research Ptitsyna et al 2005 on possible influence of geomagnetic storms on mid-latitude railways and to perform a statistical research in addition to case studies This will help in providing a basis for railway companies to evaluate the risk of disruption to signaling and train control equipment and devise engineering solutions In the present report we analyzed anomalies in operation of automatic signaling and train control equipment occurred in 2004-2005 on the East-Siberian Railway located at mid-latitudes latitudes 51N-56N longitudes 96E-114E The anomalies consist mainly in unstable functioning and false operations in traffic automatic control systems rail chain switches locomotive control devices etc often resulting in false engagement of railway

Sparse representation of electrodermal activity with knowledge-driven dictionaries.

PubMed

Chaspari, Theodora; Tsiartas, Andreas; Stein, Leah I; Cermak, Sharon A; Narayanan, Shrikanth S

2015-03-01

Biometric sensors and portable devices are being increasingly embedded into our everyday life, creating the need for robust physiological models that efficiently represent, analyze, and interpret the acquired signals. We propose a knowledge-driven method to represent electrodermal activity (EDA), a psychophysiological signal linked to stress, affect, and cognitive processing. We build EDA-specific dictionaries that accurately model both the slow varying tonic part and the signal fluctuations, called skin conductance responses (SCR), and use greedy sparse representation techniques to decompose the signal into a small number of atoms from the dictionary. Quantitative evaluation of our method considers signal reconstruction, compression rate, and information retrieval measures, that capture the ability of the model to incorporate the main signal characteristics, such as SCR occurrences. Compared to previous studies fitting a predetermined structure to the signal, results indicate that our approach provides benefits across all aforementioned criteria. This paper demonstrates the ability of appropriate dictionaries along with sparse decomposition methods to reliably represent EDA signals and provides a foundation for automatic measurement of SCR characteristics and the extraction of meaningful EDA features.

Automation of data collection for PWAS-based structural health monitoring

NASA Astrophysics Data System (ADS)

Liu, Weiping; Giurgiutiu, Victor

2005-05-01

Crack detection with piezoelectric wafer active sensors (PWAS) is emerging as an effective and powerful technique in structural health monitoring (SHM). Because of the piezoelectric properties of the PWAS, they act as both transmitters and receivers of guided Lamb waves for such applications. With arrays of PWAS attached to the structure, excitation signals are sent to one of the PWAS and wave signals from the structure are received at all the PWAS. The signals are analyzed to detect the position of cracks. One important issue associated with the PWAS-assisted SHM is the connectivity between the PWAS arrays and the measurement instruments. An automatic signal collection unit is necessary to send the excitation signals to PWAS and acquire the response signal from another PWAS. Such a program-controlled switching unit can quickly and precisely execute the data collection in a way which is more efficient and reliable than the manual switching operations. In this paper, we present an innovative design of a LabVIEW controlled automatic signal collection unit (ASCU) for PWAS-assisted SHM. The hardware circuit construction and the control LabVIEW program are discussed. As a conduit between the phase array of PWAS and the signal instruments (signal generators, oscilloscopes etc.), the ASCU provides a convenient way to switch excitation and echo signals automatically to the selected PWAS transducers with the help of GUI in the LabVIEW control program. The control program is easy to implement and can be integrated into an upper level program that executes the whole task of signal acquisition and analysis. Because of the concise design of the hardware, the ASCU concept of the auto signal switch has been extended to other application cases such as the electromechanical (E/M) impedance measurement for SHM.

Automatic channel trimming for control systems: A concept

NASA Technical Reports Server (NTRS)

Vandervoort, R. J.; Sykes, H. A.

1977-01-01

Set of bias signals added to channel inputs automatically normalize differences between channels. Algorithm and second feedback loop compute trim biases. Concept could be applied to regulators and multichannel servosystems for remote manipulators in undersea mining.

Automatic Clustering of Rolling Element Bearings Defects with Artificial Neural Network

NASA Astrophysics Data System (ADS)

Antonini, M.; Faglia, R.; Pedersoli, M.; Tiboni, M.

2006-06-01

The paper presents the optimization of a methodology for automatic clustering based on Artificial Neural Networks to detect the presence of defects in rolling bearings. The research activity was developed in co-operation with an Italian company which is expert in the production of water pumps for automotive use (Industrie Saleri Italo). The final goal of the work is to develop a system for the automatic control of the pumps, at the end of the production line. In this viewpoint, we are gradually considering the main elements of the water pump, which can cause malfunctioning. The first elements we have considered are the rolling bearing, a very critic component for the system. The experimental activity is based on the vibration measuring of rolling bearings opportunely damaged; vibration signals are in the second phase elaborated; the third and last phase is an automatic clustering. Different signal elaboration techniques are compared to optimize the methodology.

Wavelet-based automatic determination of the P- and S-wave arrivals

NASA Astrophysics Data System (ADS)

Bogiatzis, P.; Ishii, M.

2013-12-01

The detection of P- and S-wave arrivals is important for a variety of seismological applications including earthquake detection and characterization, and seismic tomography problems such as imaging of hydrocarbon reservoirs. For many years, dedicated human-analysts manually selected the arrival times of P and S waves. However, with the rapid expansion of seismic instrumentation, automatic techniques that can process a large number of seismic traces are becoming essential in tomographic applications, and for earthquake early-warning systems. In this work, we present a pair of algorithms for efficient picking of P and S onset times. The algorithms are based on the continuous wavelet transform of the seismic waveform that allows examination of a signal in both time and frequency domains. Unlike Fourier transform, the basis functions are localized in time and frequency, therefore, wavelet decomposition is suitable for analysis of non-stationary signals. For detecting the P-wave arrival, the wavelet coefficients are calculated using the vertical component of the seismogram, and the onset time of the wave is identified. In the case of the S-wave arrival, we take advantage of the polarization of the shear waves, and cross-examine the wavelet coefficients from the two horizontal components. In addition to the onset times, the automatic picking program provides estimates of uncertainty, which are important for subsequent applications. The algorithms are tested with synthetic data that are generated to include sudden changes in amplitude, frequency, and phase. The performance of the wavelet approach is further evaluated using real data by comparing the automatic picks with manual picks. Our results suggest that the proposed algorithms provide robust measurements that are comparable to manual picks for both P- and S-wave arrivals.

2dx_automator: implementation of a semiautomatic high-throughput high-resolution cryo-electron crystallography pipeline.

PubMed

Scherer, Sebastian; Kowal, Julia; Chami, Mohamed; Dandey, Venkata; Arheit, Marcel; Ringler, Philippe; Stahlberg, Henning

2014-05-01

The introduction of direct electron detectors (DED) to cryo-electron microscopy has tremendously increased the signal-to-noise ratio (SNR) and quality of the recorded images. We discuss the optimal use of DEDs for cryo-electron crystallography, introduce a new automatic image processing pipeline, and demonstrate the vast improvement in the resolution achieved by the use of both together, especially for highly tilted samples. The new processing pipeline (now included in the software package 2dx) exploits the high SNR and frame readout frequency of DEDs to automatically correct for beam-induced sample movement, and reliably processes individual crystal images without human interaction as data are being acquired. A new graphical user interface (GUI) condenses all information required for quality assessment in one window, allowing the imaging conditions to be verified and adjusted during the data collection session. With this new pipeline an automatically generated unit cell projection map of each recorded 2D crystal is available less than 5 min after the image was recorded. The entire processing procedure yielded a three-dimensional reconstruction of the 2D-crystallized ion-channel membrane protein MloK1 with a much-improved resolution of 5Å in-plane and 7Å in the z-direction, within 2 days of data acquisition and simultaneous processing. The results obtained are superior to those delivered by conventional photographic film-based methodology of the same sample, and demonstrate the importance of drift-correction. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Research on on-line monitoring technology for steel ball's forming process based on load signal analysis method

NASA Astrophysics Data System (ADS)

Li, Ying-jun; Ai, Chang-sheng; Men, Xiu-hua; Zhang, Cheng-liang; Zhang, Qi

2013-04-01

This paper presents a novel on-line monitoring technology to obtain forming quality in steel ball's forming process based on load signal analysis method, in order to reveal the bottom die's load characteristic in initial cold heading forging process of steel balls. A mechanical model of the cold header producing process is established and analyzed by using finite element method. The maximum cold heading force is calculated. The results prove that the monitoring on the cold heading process with upsetting force is reasonable and feasible. The forming defects are inflected on the three feature points of the bottom die signals, which are the initial point, infection point, and peak point. A novel PVDF piezoelectric force sensor which is simple on construction and convenient on installation is designed. The sensitivity of the PVDF force sensor is calculated. The characteristics of PVDF force sensor are analyzed by FEM. The PVDF piezoelectric force sensor is fabricated to acquire the actual load signals in the cold heading process, and calibrated by a special device. The measuring system of on-line monitoring is built. The characteristics of the actual signals recognized by learning and identification algorithm are in consistence with simulation results. Identification of actual signals shows that the timing difference values of all feature points for qualified products are not exceed ±6 ms, and amplitude difference values are less than ±3%. The calibration and application experiments show that PVDF force sensor has good static and dynamic performances, and is competent at dynamic measuring on upsetting force. It greatly improves automatic level and machining precision. Equipment capacity factor with damages identification method depends on grade of steel has been improved to 90%.

Real time microcontroller implementation of an adaptive myoelectric filter.

PubMed

Bagwell, P J; Chappell, P H

1995-03-01

This paper describes a real time digital adaptive filter for processing myoelectric signals. The filter time constant is automatically selected by the adaptation algorithm, giving a significant improvement over linear filters for estimating the muscle force and controlling a prosthetic device. Interference from mains sources often produces problems for myoelectric processing, and so 50 Hz and all harmonic frequencies are reduced by an averaging filter and differential process. This makes practical electrode placement and contact less critical and time consuming. An economic real time implementation is essential for a prosthetic controller, and this is achieved using an Intel 80C196KC microcontroller.

Elements of person knowledge: Episodic recollection helps us to identify people but not to recognize their faces.

PubMed

MacKenzie, Graham; Donaldson, David I

2016-12-01

Faces automatically draw attention, allowing rapid assessments of personality and likely behaviour. How we respond to people is, however, highly dependent on whether we know who they are. According to face processing models person knowledge comes from an extended neural system that includes structures linked to episodic memory. Here we use scalp recorded brain signals to demonstrate the specific role of episodic memory processes during face processing. In two experiments we recorded Event-Related Potentials (ERPs) while participants made identify, familiar or unknown responses to famous faces. ERPs revealed neural signals previously associated with episodic recollection for identify but not familiar faces. These findings provide novel evidence suggesting that recollection is central to face processing, providing one source of person knowledge that can be used to moderate the initial impressions gleaned from the core neural system that supports face recognition. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Software system for data management and distributed processing of multichannel biomedical signals.

PubMed

Franaszczuk, P J; Jouny, C C

2004-01-01

The presented software is designed for efficient utilization of cluster of PC computers for signal analysis of multichannel physiological data. The system consists of three main components: 1) a library of input and output procedures, 2) a database storing additional information about location in a storage system, 3) a user interface for selecting data for analysis, choosing programs for analysis, and distributing computing and output data on cluster nodes. The system allows for processing multichannel time series data in multiple binary formats. The description of data format, channels and time of recording are included in separate text files. Definition and selection of multiple channel montages is possible. Epochs for analysis can be selected both manually and automatically. Implementation of a new signal processing procedures is possible with a minimal programming overhead for the input/output processing and user interface. The number of nodes in cluster used for computations and amount of storage can be changed with no major modification to software. Current implementations include the time-frequency analysis of multiday, multichannel recordings of intracranial EEG of epileptic patients as well as evoked response analyses of repeated cognitive tasks.

Implementation and evaluation of a new workflow for registration and segmentation of pulmonary MRI data for regional lung perfusion assessment.

PubMed

Böttger, T; Grunewald, K; Schöbinger, M; Fink, C; Risse, F; Kauczor, H U; Meinzer, H P; Wolf, Ivo

2007-03-07

Recently it has been shown that regional lung perfusion can be assessed using time-resolved contrast-enhanced magnetic resonance (MR) imaging. Quantification of the perfusion images has been attempted, based on definition of small regions of interest (ROIs). Use of complete lung segmentations instead of ROIs could possibly increase quantification accuracy. Due to the low signal-to-noise ratio, automatic segmentation algorithms cannot be applied. On the other hand, manual segmentation of the lung tissue is very time consuming and can become inaccurate, as the borders of the lung to adjacent tissues are not always clearly visible. We propose a new workflow for semi-automatic segmentation of the lung from additionally acquired morphological HASTE MR images. First the lung is delineated semi-automatically in the HASTE image. Next the HASTE image is automatically registered with the perfusion images. Finally, the transformation resulting from the registration is used to align the lung segmentation from the morphological dataset with the perfusion images. We evaluated rigid, affine and locally elastic transformations, suitable optimizers and different implementations of mutual information (MI) metrics to determine the best possible registration algorithm. We located the shortcomings of the registration procedure and under which conditions automatic registration will succeed or fail. Segmentation results were evaluated using overlap and distance measures. Integration of the new workflow reduces the time needed for post-processing of the data, simplifies the perfusion quantification and reduces interobserver variability in the segmentation process. In addition, the matched morphological data set can be used to identify morphologic changes as the source for the perfusion abnormalities.

A rule-based automatic sleep staging method.

PubMed

Liang, Sheng-Fu; Kuo, Chin-En; Hu, Yu-Han; Cheng, Yu-Shian

2012-03-30

In this paper, a rule-based automatic sleep staging method was proposed. Twelve features including temporal and spectrum analyses of the EEG, EOG, and EMG signals were utilized. Normalization was applied to each feature to eliminating individual differences. A hierarchical decision tree with fourteen rules was constructed for sleep stage classification. Finally, a smoothing process considering the temporal contextual information was applied for the continuity. The overall agreement and kappa coefficient of the proposed method applied to the all night polysomnography (PSG) of seventeen healthy subjects compared with the manual scorings by R&K rules can reach 86.68% and 0.79, respectively. This method can integrate with portable PSG system for sleep evaluation at-home in the near future. Copyright © 2012 Elsevier B.V. All rights reserved.

Design and testing of a 750MHz CW-EPR digital console for small animal imaging.

PubMed

Sato-Akaba, Hideo; Emoto, Miho C; Hirata, Hiroshi; Fujii, Hirotada G

2017-11-01

This paper describes the development of a digital console for three-dimensional (3D) continuous wave electron paramagnetic resonance (CW-EPR) imaging of a small animal to improve the signal-to-noise ratio and lower the cost of the EPR imaging system. A RF generation board, an RF acquisition board and a digital signal processing (DSP) & control board were built for the digital EPR detection. Direct sampling of the reflected RF signal from a resonator (approximately 750MHz), which contains the EPR signal, was carried out using a band-pass subsampling method. A direct automatic control system to reduce the reflection from the resonator was proposed and implemented in the digital EPR detection scheme. All DSP tasks were carried out in field programmable gate array ICs. In vivo 3D imaging of nitroxyl radicals in a mouse's head was successfully performed. Copyright © 2017 Elsevier Inc. All rights reserved.

Method to improve the blade tip-timing accuracy of fiber bundle sensor under varying tip clearance

NASA Astrophysics Data System (ADS)

Duan, Fajie; Zhang, Jilong; Jiang, Jiajia; Guo, Haotian; Ye, Dechao

2016-01-01

Blade vibration measurement based on the blade tip-timing method has become an industry-standard procedure. Fiber bundle sensors are widely used for tip-timing measurement. However, the variation of clearance between the sensor and the blade will bring a tip-timing error to fiber bundle sensors due to the change in signal amplitude. This article presents methods based on software and hardware to reduce the error caused by the tip clearance change. The software method utilizes both the rising and falling edges of the tip-timing signal to determine the blade arrival time, and a calibration process suitable for asymmetric tip-timing signals is presented. The hardware method uses an automatic gain control circuit to stabilize the signal amplitude. Experiments are conducted and the results prove that both methods can effectively reduce the impact of tip clearance variation on the blade tip-timing and improve the accuracy of measurements.

Bayesian least squares deconvolution

NASA Astrophysics Data System (ADS)

Asensio Ramos, A.; Petit, P.

2015-11-01

Aims: We develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods: We consider LSD under the Bayesian framework and we introduce a flexible Gaussian process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results: We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.

Design and testing of a 750 MHz CW-EPR digital console for small animal imaging

NASA Astrophysics Data System (ADS)

Sato-Akaba, Hideo; Emoto, Miho C.; Hirata, Hiroshi; Fujii, Hirotada G.

2017-11-01

This paper describes the development of a digital console for three-dimensional (3D) continuous wave electron paramagnetic resonance (CW-EPR) imaging of a small animal to improve the signal-to-noise ratio and lower the cost of the EPR imaging system. A RF generation board, an RF acquisition board and a digital signal processing (DSP) & control board were built for the digital EPR detection. Direct sampling of the reflected RF signal from a resonator (approximately 750 MHz), which contains the EPR signal, was carried out using a band-pass subsampling method. A direct automatic control system to reduce the reflection from the resonator was proposed and implemented in the digital EPR detection scheme. All DSP tasks were carried out in field programmable gate array ICs. In vivo 3D imaging of nitroxyl radicals in a mouse's head was successfully performed.

Adaptive variational mode decomposition method for signal processing based on mode characteristic

NASA Astrophysics Data System (ADS)

Lian, Jijian; Liu, Zhuo; Wang, Haijun; Dong, Xiaofeng

2018-07-01

Variational mode decomposition is a completely non-recursive decomposition model, where all the modes are extracted concurrently. However, the model requires a preset mode number, which limits the adaptability of the method since a large deviation in the number of mode set will cause the discard or mixing of the mode. Hence, a method called Adaptive Variational Mode Decomposition (AVMD) was proposed to automatically determine the mode number based on the characteristic of intrinsic mode function. The method was used to analyze the simulation signals and the measured signals in the hydropower plant. Comparisons have also been conducted to evaluate the performance by using VMD, EMD and EWT. It is indicated that the proposed method has strong adaptability and is robust to noise. It can determine the mode number appropriately without modulation even when the signal frequencies are relatively close.

[Integration of the functional signal of intraoperative EMG of the facial nerve in to navigation model for surgery of the petrous bone].

PubMed

Strauss, G; Strauss, M; Lüders, C; Stopp, S; Shi, J; Dietz, A; Lüth, T

2008-10-01

PROBLEM DEFINITION: The goal of this work is the integration of the information of the intraoperative EMG monitoring of the facial nerve into the radiological data of the petrous bone. The following hypotheses are to be examined: (I) the N. VII can be determined intraoperatively with a high reliability by the stimulation-probe. A computer program is able to discriminate true-positive EMG signals from false-positive artifacts. (II) The course of the facial nerve can be registered in a three-dimensional area by EMG signals at a nerve model in the lab test. The individual items of the nerve can be combined into a route model. The route model can be integrated into the data of digital volume tomography (DVT). (I) Intraoperative EMG signals of the facial nerve were classified at 128 measurements by an automatic software. The results were correlated with the actual intraoperative situation. (II) The nerve phantom was designed and a DVT data set was provided. Phantom was registered with a navigation system (Karl Storz NPU, Tuttlingen, Germany). The stimulation probe of the EMG-system was tracked by the navigation system. The navigation system was extended by a processing unit (MiMed, Technische Universität München, Germany). Thus the classified EMG parameters of the facial route can be received, processed and be generated to a model of the facial nerve route. The operability was examined at 120 (10 x 12) measuring points. The evaluation of the examined algorithm for classification EMG-signals of the facial nerve resulted as correct in all measuring events. In all 10 attempts it succeeded to visualize the nerve route as three-dimensional model. The different sizes of the individual measuring points reflect the appropriate values of Istim and UEMG correctly. This work proves the feasibility of an automatic classification of an intraoperative EMG signal of the facial nerve by a processing unit. Furthermore the work shows the feasibility of tracking of the position of the stimulation probe and its integration into amodel of the route of the facial nerve (e. g. DVT). The rediability, with which the position of the nerve can be seized by the stimulation probe, is also included into the resulting route model.

Hidden Markov models in automatic speech recognition

NASA Astrophysics Data System (ADS)

Wrzoskowicz, Adam

1993-11-01

This article describes a method for constructing an automatic speech recognition system based on hidden Markov models (HMMs). The author discusses the basic concepts of HMM theory and the application of these models to the analysis and recognition of speech signals. The author provides algorithms which make it possible to train the ASR system and recognize signals on the basis of distinct stochastic models of selected speech sound classes. The author describes the specific components of the system and the procedures used to model and recognize speech. The author discusses problems associated with the choice of optimal signal detection and parameterization characteristics and their effect on the performance of the system. The author presents different options for the choice of speech signal segments and their consequences for the ASR process. The author gives special attention to the use of lexical, syntactic, and semantic information for the purpose of improving the quality and efficiency of the system. The author also describes an ASR system developed by the Speech Acoustics Laboratory of the IBPT PAS. The author discusses the results of experiments on the effect of noise on the performance of the ASR system and describes methods of constructing HMM's designed to operate in a noisy environment. The author also describes a language for human-robot communications which was defined as a complex multilevel network from an HMM model of speech sounds geared towards Polish inflections. The author also added mandatory lexical and syntactic rules to the system for its communications vocabulary.

Sub-surface defects detection of by using active thermography and advanced image edge detection

NASA Astrophysics Data System (ADS)

Tse, Peter W.; Wang, Gaochao

2017-05-01

Active or pulsed thermography is a popular non-destructive testing (NDT) tool for inspecting the integrity and anomaly of industrial equipment. One of the recent research trends in using active thermography is to automate the process in detecting hidden defects. As of today, human effort has still been using to adjust the temperature intensity of the thermo camera in order to visually observe the difference in cooling rates caused by a normal target as compared to that by a sub-surface crack exists inside the target. To avoid the tedious human-visual inspection and minimize human induced error, this paper reports the design of an automatic method that is capable of detecting subsurface defects. The method used the technique of active thermography, edge detection in machine vision and smart algorithm. An infrared thermo-camera was used to capture a series of temporal pictures after slightly heating up the inspected target by flash lamps. Then the Canny edge detector was employed to automatically extract the defect related images from the captured pictures. The captured temporal pictures were preprocessed by a packet of Canny edge detector and then a smart algorithm was used to reconstruct the whole sequences of image signals. During the processes, noise and irrelevant backgrounds exist in the pictures were removed. Consequently, the contrast of the edges of defective areas had been highlighted. The designed automatic method was verified by real pipe specimens that contains sub-surface cracks. After applying such smart method, the edges of cracks can be revealed visually without the need of using manual adjustment on the setting of thermo-camera. With the help of this automatic method, the tedious process in manually adjusting the colour contract and the pixel intensity in order to reveal defects can be avoided.

Sources of Infrasound events listed in IDC Reviewed Event Bulletin

NASA Astrophysics Data System (ADS)

Bittner, Paulina; Polich, Paul; Gore, Jane; Ali, Sherif; Medinskaya, Tatiana; Mialle, Pierrick

2017-04-01

Until 2003 two waveform technologies, i.e. seismic and hydroacoustic were used to detect and locate events included in the International Data Centre (IDC) Reviewed Event Bulletin (REB). The first atmospheric event was published in the REB in 2003, however automatic processing required significant improvements to reduce the number of false events. In the beginning of 2010 the infrasound technology was reintroduced to the IDC operations and has contributed to both automatic and reviewed IDC bulletins. The primary contribution of infrasound technology is to detect atmospheric events. These events may also be observed at seismic stations, which will significantly improve event location. Examples sources of REB events, which were detected by the International Monitoring System (IMS) infrasound network were fireballs (e.g. Bangkok fireball, 2015), volcanic eruptions (e.g. Calbuco, Chile 2015) and large surface explosions (e.g. Tjanjin, China 2015). Query blasts (e.g. Zheleznogorsk) and large earthquakes (e.g. Italy 2016) belong to events primarily recorded at seismic stations of the IMS network but often detected at the infrasound stations. In case of earthquakes analysis of infrasound signals may help to estimate the area affected by ground vibration. Infrasound associations to query blast events may help to obtain better source location. The role of IDC analysts is to verify and improve location of events detected by the automatic system and to add events which were missed in the automatic process. Open source materials may help to identify nature of some events. Well recorded examples may be added to the Reference Infrasound Event Database to help in analysis process. This presentation will provide examples of events generated by different sources which were included in the IDC bulletins.

Load-Dependent Interference of Deep Brain Stimulation of the Subthalamic Nucleus with Switching from Automatic to Controlled Processing During Random Number Generation in Parkinson's Disease.

PubMed

Williams, Isobel Anne; Wilkinson, Leonora; Limousin, Patricia; Jahanshahi, Marjan

2015-01-01

Deep brain stimulation of the subthalamic nucleus (STN DBS) ameliorates the motor symptoms of Parkinson's disease (PD). However, some aspects of executive control are impaired with STN DBS. We tested the prediction that (i) STN DBS interferes with switching from automatic to controlled processing during fast-paced random number generation (RNG) (ii) STN DBS-induced cognitive control changes are load-dependent. Fifteen PD patients with bilateral STN DBS performed paced-RNG, under three levels of cognitive load synchronised with a pacing stimulus presented at 1, 0.5 and 0.33 Hz (faster rates require greater cognitive control), with DBS on or off. Measures of output randomness were calculated. Countscore 1 (CS1) indicates habitual counting in steps of one (CS1). Countscore 2 (CS2) indicates a more controlled strategy of counting in twos. The fastest rate was associated with an increased CS1 score with STN DBS on compared to off. At the slowest rate, patients had higher CS2 scores with DBS off than on, such that the differences between CS1 and CS2 scores disappeared. We provide evidence for a load-dependent effect of STN DBS on paced RNG in PD. Patients could switch to more controlled RNG strategies during conditions of low cognitive load at slower rates only when the STN stimulators were off, but when STN stimulation was on, they engaged in more automatic habitual counting under increased cognitive load. These findings are consistent with the proposal that the STN implements a switch signal from the medial frontal cortex which enables a shift from automatic to controlled processing.

Load-Dependent Interference of Deep Brain Stimulation of the Subthalamic Nucleus with Switching from Automatic to Controlled Processing During Random Number Generation in Parkinson’s Disease

PubMed Central

Williams, Isobel Anne; Wilkinson, Leonora; Limousin, Patricia; Jahanshahi, Marjan

2015-01-01

Background: Deep brain stimulation of the subthalamic nucleus (STN DBS) ameliorates the motor symptoms of Parkinson’s disease (PD). However, some aspects of executive control are impaired with STN DBS. Objective: We tested the prediction that (i) STN DBS interferes with switching from automatic to controlled processing during fast-paced random number generation (RNG) (ii) STN DBS-induced cognitive control changes are load-dependent. Methods: Fifteen PD patients with bilateral STN DBS performed paced-RNG, under three levels of cognitive load synchronised with a pacing stimulus presented at 1, 0.5 and 0.33 Hz (faster rates require greater cognitive control), with DBS on or off. Measures of output randomness were calculated. Countscore 1 (CS1) indicates habitual counting in steps of one (CS1). Countscore 2 (CS2) indicates a more controlled strategy of counting in twos. Results: The fastest rate was associated with an increased CS1 score with STN DBS on compared to off. At the slowest rate, patients had higher CS2 scores with DBS off than on, such that the differences between CS1 and CS2 scores disappeared. Conclusions: We provide evidence for a load-dependent effect of STN DBS on paced RNG in PD. Patients could switch to more controlled RNG strategies during conditions of low cognitive load at slower rates only when the STN stimulators were off, but when STN stimulation was on, they engaged in more automatic habitual counting under increased cognitive load. These findings are consistent with the proposal that the STN implements a switch signal from the medial frontal cortex which enables a shift from automatic to controlled processing. PMID:25720447

An 1.4 ppm/°C bandgap voltage reference with automatic curvature-compensation technique

NASA Astrophysics Data System (ADS)

Zhou, Zekun; Yu, Hongming; Shi, Yue; Zhang, Bo

2017-12-01

A high-precision Bandgap voltage reference (BGR) with a novel curvature-compensation scheme is proposed in this paper. The temperature coefficient (TC) can be automatically optimized with a built-in adaptive curvature-compensation technique, which is realized in a digitization control way. Firstly, an exponential curvature compensation method is adopted to reduce the TC in a certain degree, especially in low temperature range. Then, the temperature drift of BGR in higher temperature range can be further minimized by dynamic zero-temperature-coefficient point tracking with temperature changes. With the help of proposed adaptive signal processing, the output voltage of BGR can approximately maintain zero TC in a wider temperature range. Experiment results of the BGR proposed in this paper, which is implemented in 0.35-μm BCD process, illustrate that the TC of 1.4ppm/°C is realized under the power supply voltage of 3.6V and the power supply rejection of the proposed circuit is -67dB.

[An automatic system for anatomophysiological correlation in three planes simultaneously during functional neurosurgery].

PubMed

Teijeiro, E J; Macías, R J; Morales, J M; Guerra, E; López, G; Alvarez, L M; Fernández, F; Maragoto, C; Seijo, F; Alvarez, E

The Neurosurgical Deep Recording System (NDRS) using a personal computer takes the place of complex electronic equipment for recording and processing deep cerebral electrical activity, as a guide in stereotaxic functional neurosurgery. It also permits increased possibilities of presenting information in direct graphic form with automatic management and sufficient flexibility to implement different analyses. This paper describes the possibilities of automatic simultaneous graphic representation in three almost orthogonal planes, available with the new 5.1 version of NDRS so as to facilitate the analysis of anatomophysiological correlation in the localization of deep structures of the brain during minimal access surgery. This new version can automatically show the spatial behaviour of signals registered throughout the path of the electrode inside the brain, superimposed simultaneously on sagittal, coronal and axial sections of an anatomical atlas of the brain, after adjusting the scale automatically according to the dimensions of the brain of each individual patient. This may also be shown in a tridimensional representation of the different planes themselves intercepting. The NDRS system has been successfully used in Spain and Cuba in over 300 functional neurosurgery operations. The new version further facilitates analysis of spatial anatomophysiological correlation for the localization of brain structures. This system has contributed to increase the precision and safety in selecting surgical targets in the control of Parkinson s disease and other disorders of movement.

49 CFR 236.526 - Roadway element not functioning properly.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Roadway § 236.526 Roadway..., train control or cab signal system is not functioning as intended, the signal associated with such...

49 CFR 236.526 - Roadway element not functioning properly.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Roadway § 236.526 Roadway..., train control or cab signal system is not functioning as intended, the signal associated with such...

76 FR 78732 - Petition for Waiver of Compliance

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-19

... or modification of a signal system. FRA has assigned the petition Docket Number FRA-2011-0092. CSX seeks approval of the proposed modification of the bridge tender controlled signals to automatic signals..., Jacksonville Division. The modification consists of the conversion of bridge tender controlled signals to...

A method for studying the hunting oscillations of an airplane with a simple type of automatic control

NASA Technical Reports Server (NTRS)

Jones, Robert T

1944-01-01

A method is presented for predicting the amplitude and frequency, under certain simplifying conditions, of the hunting oscillations of an automatically controlled aircraft with lag in the control system or in the response of the aircraft to the controls. If the steering device is actuated by a simple right-left type of signal, the series of alternating fixed-amplified signals occurring during the hunting may ordinarily be represented by a "square wave." Formulas are given expressing the response to such a variations of signal in terms of the response to a unit signal. A more complex type of hunting, which may involve cyclic repetition of signals of varying duration, has not been treated and requires further analysis. Several examples of application of the method are included and the results discussed.

Design considerations for a LORAN-C timing receiver in a hostile signal to noise environment

NASA Technical Reports Server (NTRS)

Porter, J. W.; Bowell, J. R.; Price, G. E.

1981-01-01

The environment in which a LORAN-C Timing Receiver may function effectively depends to a large extent on the techniques utilized to insure that interfering signals within the pass band of the unit are neutralized. The baseline performance manually operated timing receivers is discussed and the basic design considerations and necessary parameters for an automatic unit utilizing today's technology are established. Actual performance data is presented comparing the results obtained from a present generation timing receiver against a new generation microprocessor controlled automatic acquisition receiver. The achievements possible in a wide range of signal to noise situations are demonstrated.

49 CFR 233.1 - Scope.

Code of Federal Regulations, 2011 CFR

2011-10-01

... TRANSPORTATION SIGNAL SYSTEMS REPORTING REQUIREMENTS § 233.1 Scope. This part prescribed reporting requirements with respect to methods of train operation, block signal systems, interlockings, traffic control systems, automatic train stop, train control, and cab signal systems, or other similar appliances, methods...

49 CFR 233.1 - Scope.

Code of Federal Regulations, 2010 CFR

2010-10-01

... TRANSPORTATION SIGNAL SYSTEMS REPORTING REQUIREMENTS § 233.1 Scope. This part prescribed reporting requirements with respect to methods of train operation, block signal systems, interlockings, traffic control systems, automatic train stop, train control, and cab signal systems, or other similar appliances, methods...

[The design and applications of a non-invasive intelligent detector for cardiovascular functions].

PubMed

Li, Feng; Xing, Wu; Chen, Ming-zhi; Shang, Huai

2006-05-01

An apparatus based on a high sensitive sensor which detects cardiovascular functions is introduced in this paper. Some intelligent detecting technologies, such as syntactic pattern recognition and a medical expert system are used in this detector. Its embedded single-chip microcomputer processes and analyzes pulse signals for gaining automatically the parameters about heart, blood vessel and blood etc., so as to get the health evaluation, correct medical diagnosis and prediction of cardiovascular diseases.

Intelligent technologies in process of highly-precise products manufacturing

NASA Astrophysics Data System (ADS)

Vakhidova, K. L.; Khakimov, Z. L.; Isaeva, M. R.; Shukhin, V. V.; Labazanov, M. A.; Ignatiev, S. A.

2017-10-01

One of the main control methods of the surface layer of bearing parts is the eddy current testing method. Surface layer defects of bearing parts, like burns, cracks and some others, are reflected in the results of the rolling surfaces scan. The previously developed method for detecting defects from the image of the raceway was quite effective, but the processing algorithm is complicated and lasts for about 12 ... 16 s. The real non-stationary signals from an eddy current transducer (ECT) consist of short-time high-frequency and long-time low-frequency components, therefore a transformation is used for their analysis, which provides different windows for different frequencies. The wavelet transform meets these conditions. Based on aforesaid, a methodology for automatically detecting and recognizing local defects in bearing parts surface layer has been developed on the basis of wavelet analysis using integral estimates. Some of the defects are recognized by the amplitude component, otherwise an automatic transition to recognition by the phase component of information signals (IS) is carried out. The use of intelligent technologies in the manufacture of bearing parts will, firstly, significantly improve the quality of bearings, and secondly, significantly improve production efficiency by reducing (eliminating) rejections in the manufacture of products, increasing the period of normal operation of the technological equipment (inter-adjustment period), the implementation of the system of Flexible facilities maintenance, as well as reducing production costs.

Automatic calibration and signal switching system for the particle beam fusion research data acquisition facility

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

Boyer, W.B.

1979-09-01

This report describes both the hardware and software components of an automatic calibration and signal system (Autocal) for the data acquisition system for the Sandia particle beam fusion research accelerators Hydra, Proto I, and Proto II. The Autocal hardware consists of off-the-shelf commercial equipment. The various hardware components, special modifications and overall system configuration are described. Special software has been developed to support the Autocal hardware. Software operation and maintenance are described.

Modeling and Performance Optimization of Large-Scale Data-Communication Networks.

DTIC Science & Technology

1981-06-01

IT-17, no. 1, pp. 71-76, 1971. 12. Y. Ho, M. Kastner, and E. Wong, "Teams, market signalling, and information theory," IEEE Trans. Automat. Contr...modifies the flow assignment to satisfy end-to-end delay constraints. 3.2.1 Rationale for Min-Hop Strategr The Min-Hop algorithm proposed in this...Prentice-Hall, 1980. Ho, Y., M. Kostner and E. Wong, "Teams, market signalling, and information theory," IEEE Trans. Automat. Contr., vol. AC-23, pp

Electrical capacitance clearanceometer

NASA Technical Reports Server (NTRS)

Hester, Norbert J. (Inventor); Hornbeck, Charles E. (Inventor); Young, Joseph C. (Inventor)

1992-01-01

A hot gas turbine engine capacitive probe clearanceometer is employed to measure the clearance gap or distance between blade tips on a rotor wheel and its confining casing under operating conditions. A braze sealed tip of the probe carries a capacitor electrode which is electrically connected to an electrical inductor within the probe which is inserted into a turbine casing to position its electrode at the inner surface of the casing. Electrical power is supplied through a voltage controlled variable frequency oscillator having a tuned circuit in which the probe is a component. The oscillator signal is modulated by a change in electrical capacitance between the probe electrode and a passing blade tip surface while an automatic feedback correction circuit corrects oscillator signal drift. A change in distance between a blade tip and the probe electrode is a change in capacitance therebetween which frequency modulates the oscillator signal. The modulated oscillator signal which is then processed through a phase detector and related circuitry to provide an electrical signal is proportional to the clearance gap.

Weather satellite picture receiving stations, APT digital scan converter

NASA Technical Reports Server (NTRS)

Vermillion, C. H.; Kamowski, J. C.

1975-01-01

The automatic picture transmission digital scan converter is used at ground stations to convert signals received from scanning radiometers to data compatible with ground equipment designed to receive signals from vidicons aboard operational meteorological satellites. Information necessary to understand the circuit theory, functional operation, general construction and calibration of the converter is provided. Brief and detailed descriptions of each of the individual circuits are included, accompanied by a schematic diagram contained at the end of each circuit description. Listings of integral parts and testing equipment required as well as an overall wiring diagram are included. This unit will enable the user to readily accept and process weather photographs from the operational meteorological satellites.

Research progress of free space coherent optical communication

NASA Astrophysics Data System (ADS)

Tan, Zhenkun; Ke, Xizheng

2018-02-01

This paper mainly introduces the research progress of free space coherent optical communication in Xi'an University of Technology. In recent years, the research on the outer modulation technology of the laser, free-space-to-fiber coupling technique, the design of transmitting and receiving optical antenna, adaptive optical technology with or without wave-front sensor, automatic polarization control technology, frequency stabilization technology, heterodyne detection technology and high speed signal processing technology. Based on the above related research, the digital signal modulation, transmission, detection and data recovery are realized by the heterodyne detection technology in the free space optical communication system, and finally the function of smooth viewing high-definition video is realized.

Intelligent Unmanned Monitoring of Remediated Sites

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

Emile Fiesler, Ph.D.

During this Phase I project, IOS demonstrated the feasibility of combining digital signal processing and neural network analysis to analyze spectral signals from pure samples of several typical contaminants. We fabricated and tested a prototype system by automatically analyzing Raman spectral data taken in the Vadose zone at the 321 M site in the M area of DOE's Savannah River Site in South Carolina. This test demonstration proved the ability of IOS's technology to detect the target contaminants, tetrachloroethylene (PCE) and trichloroethylene (TCE), in isolation, and to detect the spectra of these contaminants in real-world noisy samples taken from amore » mixture of materials obtained from this typical remediation target site.« less

Mobile/android application for QRS detection using zero cross method

NASA Astrophysics Data System (ADS)

Rizqyawan, M. I.; Simbolon, A. I.; Suhendra, M. A.; Amri, M. F.; Kusumandari, D. E.

2018-03-01

In automatic ECG signal processing, one of the main topics of research is QRS complex detection. Detecting correct QRS complex or R peak is important since it is used to measure several other ECG metrics. One of the robust methods for QRS detection is Zero Cross method. This method uses an addition of high-frequency signal and zero crossing count to detect QRS complex which has a low-frequency oscillation. This paper presents an application of QRS detection using Zero Cross algorithm in the Android-based system. The performance of the algorithm in the mobile environment is measured. The result shows that this method is suitable for real-time QRS detection in a mobile application.

A cloud masking algorithm for EARLINET lidar systems

NASA Astrophysics Data System (ADS)

Binietoglou, Ioannis; Baars, Holger; D'Amico, Giuseppe; Nicolae, Doina

2015-04-01

Cloud masking is an important first step in any aerosol lidar processing chain as most data processing algorithms can only be applied on cloud free observations. Up to now, the selection of a cloud-free time interval for data processing is typically performed manually, and this is one of the outstanding problems for automatic processing of lidar data in networks such as EARLINET. In this contribution we present initial developments of a cloud masking algorithm that permits the selection of the appropriate time intervals for lidar data processing based on uncalibrated lidar signals. The algorithm is based on a signal normalization procedure using the range of observed values of lidar returns, designed to work with different lidar systems with minimal user input. This normalization procedure can be applied to measurement periods of only few hours, even if no suitable cloud-free interval exists, and thus can be used even when only a short period of lidar measurements is available. Clouds are detected based on a combination of criteria including the magnitude of the normalized lidar signal and time-space edge detection performed using the Sobel operator. In this way the algorithm avoids misclassification of strong aerosol layers as clouds. Cloud detection is performed using the highest available time and vertical resolution of the lidar signals, allowing the effective detection of low-level clouds (e.g. cumulus humilis). Special attention is given to suppress false cloud detection due to signal noise that can affect the algorithm's performance, especially during day-time. In this contribution we present the details of algorithm, the effect of lidar characteristics (space-time resolution, available wavelengths, signal-to-noise ratio) to detection performance, and highlight the current strengths and limitations of the algorithm using lidar scenes from different lidar systems in different locations across Europe.

Fast Quantitative Susceptibility Mapping with L1-Regularization and Automatic Parameter Selection

PubMed Central

Bilgic, Berkin; Fan, Audrey P.; Polimeni, Jonathan R.; Cauley, Stephen F.; Bianciardi, Marta; Adalsteinsson, Elfar; Wald, Lawrence L.; Setsompop, Kawin

2014-01-01

Purpose To enable fast reconstruction of quantitative susceptibility maps with Total Variation penalty and automatic regularization parameter selection. Methods ℓ1-regularized susceptibility mapping is accelerated by variable-splitting, which allows closed-form evaluation of each iteration of the algorithm by soft thresholding and FFTs. This fast algorithm also renders automatic regularization parameter estimation practical. A weighting mask derived from the magnitude signal can be incorporated to allow edge-aware regularization. Results Compared to the nonlinear Conjugate Gradient (CG) solver, the proposed method offers 20× speed-up in reconstruction time. A complete pipeline including Laplacian phase unwrapping, background phase removal with SHARP filtering and ℓ1-regularized dipole inversion at 0.6 mm isotropic resolution is completed in 1.2 minutes using Matlab on a standard workstation compared to 22 minutes using the Conjugate Gradient solver. This fast reconstruction allows estimation of regularization parameters with the L-curve method in 13 minutes, which would have taken 4 hours with the CG algorithm. Proposed method also permits magnitude-weighted regularization, which prevents smoothing across edges identified on the magnitude signal. This more complicated optimization problem is solved 5× faster than the nonlinear CG approach. Utility of the proposed method is also demonstrated in functional BOLD susceptibility mapping, where processing of the massive time-series dataset would otherwise be prohibitive with the CG solver. Conclusion Online reconstruction of regularized susceptibility maps may become feasible with the proposed dipole inversion. PMID:24259479

Binding of motion and colour is early and automatic.

PubMed

Blaser, Erik; Papathomas, Thomas; Vidnyánszky, Zoltán

2005-04-01

At what stages of the human visual hierarchy different features are bound together, and whether this binding requires attention, is still highly debated. We used a colour-contingent motion after-effect (CCMAE) to study the binding of colour and motion signals. The logic of our approach was as follows: if CCMAEs can be evoked by targeted adaptation of early motion processing stages, without allowing for feedback from higher motion integration stages, then this would support our hypothesis that colour and motion are bound automatically on the basis of spatiotemporally local information. Our results show for the first time that CCMAE's can be evoked by adaptation to a locally paired opposite-motion dot display, a stimulus that, importantly, is known to trigger direction-specific responses in the primary visual cortex yet results in strong inhibition of the directional responses in area MT of macaques as well as in area MT+ in humans and, indeed, is perceived only as motionless flicker. The magnitude of the CCMAE in the locally paired condition was not significantly different from control conditions where the different directions were spatiotemporally separated (i.e. not locally paired) and therefore perceived as two moving fields. These findings provide evidence that adaptation at an early, local motion stage, and only adaptation at this stage, underlies this CCMAE, which in turn implies that spatiotemporally coincident colour and motion signals are bound automatically, most probably as early as cortical area V1, even when the association between colour and motion is perceptually inaccessible.

Automatic quadrature control and measuring system

NASA Technical Reports Server (NTRS)

Hamlet, J. F.

1973-01-01

Quadrature is separated from amplified signal by use of phase detector, with phase shifter providing appropriate reference. Output of phase detector is further amplified and filtered by dc amplifier. Output of dc amplifier provides signal to neutralize quadrature component of transducer signal.

Automatic Identification of Motion Artifacts in EHG Recording for Robust Analysis of Uterine Contractions

PubMed Central

Ye-Lin, Yiyao; Alberola-Rubio, José; Perales, Alfredo

2014-01-01

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique. PMID:24523828

Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions.

PubMed

Ye-Lin, Yiyao; Garcia-Casado, Javier; Prats-Boluda, Gema; Alberola-Rubio, José; Perales, Alfredo

2014-01-01

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique.

Experimental facility for the study of acoustic emission registered in the primary circuit components of WWER power units

NASA Astrophysics Data System (ADS)

Petrosyan, V. G.; Hovakimyan, T. H.; Yeghoyan, E. A.; Hovhannisyan, H. T.; Mayilyan, D. G.; Petrosyan, A. P.

2017-01-01

This paper is dedicated to the creation of a facility for the experimental study of a phenomenon of background acoustic emission (AE), which is detected in the main circulation loop (MCL) of WWER power units. The analysis of the operating principle and the design of a primary feed-and-blow down system (FB) deaerator of NPP as the most likely source of continuous acoustic emission is carried out. The experimental facility for the systematic study of a phenomenon of continuous AE is developed. A physical model of a thermal deaerator is designed and constructed. A thermal monitoring system is introduced. An automatic system providing acoustic signal registration in a low frequency (0.03-30 kHz) and high frequency (30-300 kHz) bands and study of its spectral characteristics is designed. Special software for recording and processing of digitized electrical sensor signals is developed. A separate and independent principle of study of the most probable processes responsible for the generation of acoustic emission signals in the deaerator is applied. Trial series of experiments and prechecks of acoustic signals in different modes of the deaerator model are conducted. Compliance of basic technological parameters with operating range of the real deaerator was provided. It is shown that the acoustic signal time-intensity curve has several typical regions. The pilot research showed an impact of various processes that come about during the operation of the deaerator physical model on the intensity of the AE signal. The experimental results suggest that the main sources of generation of the AE signals are the processes of steam condensation, turbulent flow of gas-vapor medium, and water boiling.

Reward processing in the value-driven attention network: reward signals tracking cue identity and location.

PubMed

Anderson, Brian A

2017-03-01

Through associative reward learning, arbitrary cues acquire the ability to automatically capture visual attention. Previous studies have examined the neural correlates of value-driven attentional orienting, revealing elevated activity within a network of brain regions encompassing the visual corticostriatal loop [caudate tail, lateral occipital complex (LOC) and early visual cortex] and intraparietal sulcus (IPS). Such attentional priority signals raise a broader question concerning how visual signals are combined with reward signals during learning to create a representation that is sensitive to the confluence of the two. This study examines reward signals during the cued reward training phase commonly used to generate value-driven attentional biases. High, compared with low, reward feedback preferentially activated the value-driven attention network, in addition to regions typically implicated in reward processing. Further examination of these reward signals within the visual system revealed information about the identity of the preceding cue in the caudate tail and LOC, and information about the location of the preceding cue in IPS, while early visual cortex represented both location and identity. The results reveal teaching signals within the value-driven attention network during associative reward learning, and further suggest functional specialization within different regions of this network during the acquisition of an integrated representation of stimulus value. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

77 FR 31429 - Notice of Application for Approval of Discontinuance or Modification of a Railroad Signal System

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-25

... of Application for Approval of Discontinuance or Modification of a Railroad Signal System In... discontinuance or modification of a signal system. FRA assigned the petition Docket Number FRA-2012-0046... discontinuance of an automatic block signal (ABS) system and a traffic control signal (TCS) system on the...

49 CFR 236.830 - Time, acknowledging.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.830 Time, acknowledging. As applied to an intermittent automatic train stop system, a predetermined time within which an automatic brake application may be forestalled by means of the acknowledging device. ...

Audio signal processor

NASA Technical Reports Server (NTRS)

Hymer, R. L.

1970-01-01

System provides automatic volume control for an audio amplifier or a voice communication system without introducing noise surges during pauses in the input, and without losing the initial signal when the input resumes.

A Robust Distributed Multipoint Fiber Optic Gas Sensor System Based on AGC Amplifier Structure.

PubMed

Zhu, Cunguang; Wang, Rende; Tao, Xuechen; Wang, Guangwei; Wang, Pengpeng

2016-07-28

A harsh environment-oriented distributed multipoint fiber optic gas sensor system realized by automatic gain control (AGC) technology is proposed. To improve the photoelectric signal reliability, the electronic variable gain can be modified in real time by an AGC closed-loop feedback structure to compensate for optical transmission loss which is caused by the fiber bend loss or other reasons. The deviation of the system based on AGC structure is below 4.02% when photoelectric signal decays due to fiber bending loss for bending radius of 5 mm, which is 20 times lower than the ordinary differential system. In addition, the AGC circuit with the same electric parameters can keep the baseline intensity of signals in different channels of the distributed multipoint sensor system at the same level. This avoids repetitive calibrations and streamlines the installation process.

Automatic Phase Calibration for RF Cavities using Beam-Loading Signals

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

Edelen, J. P.; Chase, B. E.

Precise calibration of the cavity phase signals is necessary for the operation of any particle accelerator. For many systems this requires human in the loop adjustments based on measurements of the beam parameters downstream. Some recent work has developed a scheme for the calibration of the cavity phase using beam measurements and beam-loading however this scheme is still a multi-step process that requires heavy automation or human in the loop. In this paper we analyze a new scheme that uses only RF signals reacting to beam-loading to calculate the phase of the beam relative to the cavity. This technique couldmore » be used in slow control loops to provide real-time adjustment of the cavity phase calibration without human intervention thereby increasing the stability and reliability of the accelerator.« less

Cognition and balance control: does processing of explicit contextual cues of impending perturbations modulate automatic postural responses?

PubMed

Coelho, Daniel Boari; Teixeira, Luis Augusto

2017-08-01

Processing of predictive contextual cues of an impending perturbation is thought to induce adaptive postural responses. Cueing in previous research has been provided through repeated perturbations with a constant foreperiod. This experimental strategy confounds explicit predictive cueing with adaptation and non-specific properties of temporal cueing. Two experiments were performed to assess those factors separately. To perturb upright balance, the base of support was suddenly displaced backwards in three amplitudes: 5, 10 and 15 cm. In Experiment 1, we tested the effect of cueing the amplitude of the impending postural perturbation by means of visual signals, and the effect of adaptation to repeated exposures by comparing block versus random sequences of perturbation. In Experiment 2, we evaluated separately the effects of cueing the characteristics of an impending balance perturbation and cueing the timing of perturbation onset. Results from Experiment 1 showed that the block sequence of perturbations led to increased stability of automatic postural responses, and modulation of magnitude and onset latency of muscular responses. Results from Experiment 2 showed that only the condition cueing timing of platform translation onset led to increased balance stability and modulation of onset latency of muscular responses. Conversely, cueing platform displacement amplitude failed to induce any effects on automatic postural responses in both experiments. Our findings support the interpretation of improved postural responses via optimized sensorimotor processes, at the same time that cast doubt on the notion that cognitive processing of explicit contextual cues advancing the magnitude of an impending perturbation can preset adaptive postural responses.

Pipe leak diagnostic using high frequency piezoelectric pressure sensor and automatic selection of intrinsic mode function

NASA Astrophysics Data System (ADS)

Yusop, Hanafi M.; Ghazali, M. F.; Yusof, M. F. M.; Remli, M. A. Pi; Kamarulzaman, M. H.

2017-10-01

In a recent study, the analysis of pressure transient signals could be seen as an accurate and low-cost method for leak and feature detection in water distribution systems. Transient phenomena occurs due to sudden changes in the fluid’s propagation in pipelines system caused by rapid pressure and flow fluctuation due to events such as closing and opening valves rapidly or through pump failure. In this paper, the feasibility of the Hilbert-Huang transform (HHT) method/technique in analysing the pressure transient signals in presented and discussed. HHT is a way to decompose a signal into intrinsic mode functions (IMF). However, the advantage of HHT is its difficulty in selecting the suitable IMF for the next data postprocessing method which is Hilbert Transform (HT). This paper reveals that utilizing the application of an integrated kurtosis-based algorithm for a z-filter technique (I-Kaz) to kurtosis ratio (I-Kaz-Kurtosis) allows/contributes to/leads to automatic selection of the IMF that should be used. This technique is demonstrated on a 57.90-meter medium high-density polyethylene (MDPE) pipe installed with a single artificial leak. The analysis results using the I-Kaz-kurtosis ratio revealed/confirmed that the method can be used as an automatic selection of the IMF although the noise level ratio of the signal is low. Therefore, the I-Kaz-kurtosis ratio method is recommended as a means to implement an automatic selection technique of the IMF for HHT analysis.

49 CFR 235.1 - Scope.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SIGNAL SYSTEM OR RELIEF FROM THE REQUIREMENTS OF PART 236 § 235.1 Scope. This part prescribes application for approval to discontinue or materially modify block signal systems, interlockings, traffic control systems, automatic train stop, train control, or cab signal systems, or other similar appliances, devices...

49 CFR 236.576 - Roadway element.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Inspection and Tests; Roadway § 236.576 Roadway element. Roadway...

49 CFR 236.576 - Roadway element.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Inspection and Tests; Roadway § 236.576 Roadway element. Roadway...

Research on Vehicle Temperature Regulation System Based on Air Convection Principle

NASA Astrophysics Data System (ADS)

Zhuge, Muzi; Li, Xiang; Liang, Caifeng

2018-03-01

The long time parking outdoors in the summer will lead to too high temperature in the car, and the harmful gas produced by the vehicle engine will stay in the confined space for a long time during the parking process, which will do great harm to the human body. If the air conditioning system is turned on before driving, the cooling rate is slow and the battery loss is large. To solve the above problems, we designed a temperature adjusting system based on the principle of air convection. We can choose the automatic mode or manual mode to achieve control of a convection window. In the automatic mode, the system will automatically detect the environmental temperature, through the sensor to complete the detection, and the signal is transmitted to the microcontroller to control the window open or close, in manual mode, the remote control of the window can be realized by Bluetooth. Therefore, the system has important practical significance to effectively regulate temperature, prolong battery life, and improve the safety and comfort of traffic vehicles.

Real-time inspection by submarine images

NASA Astrophysics Data System (ADS)

Tascini, Guido; Zingaretti, Primo; Conte, Giuseppe

1996-10-01

A real-time application of computer vision concerning tracking and inspection of a submarine pipeline is described. The objective is to develop automatic procedures for supporting human operators in the real-time analysis of images acquired by means of cameras mounted on underwater remotely operated vehicles (ROV) Implementation of such procedures gives rise to a human-machine system for underwater pipeline inspection that can automatically detect and signal the presence of the pipe, of its structural or accessory elements, and of dangerous or alien objects in its neighborhood. The possibility of modifying the image acquisition rate in the simulations performed on video- recorded images is used to prove that the system performs all necessary processing with an acceptable robustness working in real-time up to a speed of about 2.5 kn, widely greater than that the actual ROVs and the security features allow.

Finite element analysis of cylinder shell resonator and design of intelligent density meter

NASA Astrophysics Data System (ADS)

W, Sui X.; M, Fan Y.; X, Zhang G.; R, Qiu Z.

2005-01-01

On the basis of the mathematical model and finite element analysis of the cylinder shell resonator, a novel resonant liquid density meter is designed. The meter consists of a cylinder shell resonator fixed on both ends, a measurement circuit with automatic gain control and automatic phase control, and a signal processing system with microcomputer unit C8051F021. The density meter is insensitive to the liquid pressure, and it can intelligently compensate for the temperature. The experiment results show the meter characteristic coefficients of K0, K1, and K2 at 25 centigrade are -129.5668 kg m-3, -0.2535 × 106 kg m-3 s-1 and 0.6239 × 1010 kg m-3 s-2, respectively. The accuracy of the sensor is ±0.1% in range of 700-900 kg m-3

PREFACE: 12th European Workshop on Advanced Control and Diagnosis (ACD 2015)

NASA Astrophysics Data System (ADS)

Straka, Ondřej; Punčochář, Ivo; Duník, Jindřich

2015-11-01

The 12th European Workshop on Advanced Control and Diagnosis (ACD 2015) took place at the Research Centre NTIS - New Technologies for the Information Society, Faculty of Applied Sciences, University of West Bohemia, Pilsen, Czech Republic, on November 19 - 20, 2015. The annual European Workshop on Advanced Control and Diagnosis has been organized since 2003 by Control Engineering departments of several European universities in Germany, France, the UK, Poland, Italy, Hungary, and Denmark to bring together senior and junior academics and engineers from diverse fields of automatic control, fault detection, and signal processing. The workshop provides an opportunity for researchers and developers to present their recent theoretical developments, practical applications, or even open problems. It also offers a great opportunity for industrial partners to express their needs and priorities and to review the current activities in the fields. A total of 74 papers have been submitted for ACD 2015. Based on the peer reviews 48 papers were accepted for the oral presentation and 10 papers for the poster presentation. The accepted papers covered areas of control theory and applications, identification, estimation, signal processing, and fault detection. In addition, four excellent plenary lectures were delivered by Prof. Fredrik Gustafsson (Automotive Sensor Mining for Tire Pressure Monitoring), Prof. Vladimír Havlena (Advanced Process Control for Energy Efficiency), Prof. Silvio Simani (Advanced Issues on Wind Turbine Modelling and Control), and Prof. Robert Babuška (Learning Control in Robotics). The ACD 2015 was for the first time in the workshop history co-sponsored by the International Federation of Automatic Control (IFAC). On behalf of the ACD 2015 organising committee, we would like to thank all those who prepared and submitted papers, participated in the peer review process, supported, and attended the workshop.

DALMATIAN: An Algorithm for Automatic Cell Detection and Counting in 3D.

PubMed

Shuvaev, Sergey A; Lazutkin, Alexander A; Kedrov, Alexander V; Anokhin, Konstantin V; Enikolopov, Grigori N; Koulakov, Alexei A

2017-01-01

Current 3D imaging methods, including optical projection tomography, light-sheet microscopy, block-face imaging, and serial two photon tomography enable visualization of large samples of biological tissue. Large volumes of data obtained at high resolution require development of automatic image processing techniques, such as algorithms for automatic cell detection or, more generally, point-like object detection. Current approaches to automated cell detection suffer from difficulties originating from detection of particular cell types, cell populations of different brightness, non-uniformly stained, and overlapping cells. In this study, we present a set of algorithms for robust automatic cell detection in 3D. Our algorithms are suitable for, but not limited to, whole brain regions and individual brain sections. We used watershed procedure to split regional maxima representing overlapping cells. We developed a bootstrap Gaussian fit procedure to evaluate the statistical significance of detected cells. We compared cell detection quality of our algorithm and other software using 42 samples, representing 6 staining and imaging techniques. The results provided by our algorithm matched manual expert quantification with signal-to-noise dependent confidence, including samples with cells of different brightness, non-uniformly stained, and overlapping cells for whole brain regions and individual tissue sections. Our algorithm provided the best cell detection quality among tested free and commercial software.

Method for automatically evaluating a transition from a batch manufacturing technique to a lean manufacturing technique

DOEpatents

Ivezic, Nenad; Potok, Thomas E.

2003-09-30

A method for automatically evaluating a manufacturing technique comprises the steps of: receiving from a user manufacturing process step parameters characterizing a manufacturing process; accepting from the user a selection for an analysis of a particular lean manufacturing technique; automatically compiling process step data for each process step in the manufacturing process; automatically calculating process metrics from a summation of the compiled process step data for each process step; and, presenting the automatically calculated process metrics to the user. A method for evaluating a transition from a batch manufacturing technique to a lean manufacturing technique can comprise the steps of: collecting manufacturing process step characterization parameters; selecting a lean manufacturing technique for analysis; communicating the selected lean manufacturing technique and the manufacturing process step characterization parameters to an automatic manufacturing technique evaluation engine having a mathematical model for generating manufacturing technique evaluation data; and, using the lean manufacturing technique evaluation data to determine whether to transition from an existing manufacturing technique to the selected lean manufacturing technique.

A system for multichannel recording and automatic reading of information. [for onboard cosmic ray counter

NASA Technical Reports Server (NTRS)

Bogomolov, E. A.; Yevstafev, Y. Y.; Karakadko, V. K.; Lubyanaya, N. D.; Romanov, V. A.; Totubalina, M. G.; Yamshchikov, M. A.

1975-01-01

A system for the recording and processing of telescope data is considered for measurements of EW asymmetry. The information is recorded by 45 channels on a continuously moving 35-mm film. The dead time of the recorder is about 0.1 sec. A sorting electronic circuit is used to reduce the errors when the statistical time distribution of the pulses is recorded. The recorded information is read out by means of photoresistors. The phototransmitter signals are fed either to the mechanical recorder unit for preliminary processing, or to a logical circuit which controls the operation of the punching device. The punched tape is processed by an electronic computer.

Real-time monitoring and massive inversion of source parameters of very long period seismic signals: An application to Stromboli Volcano, Italy

USGS Publications Warehouse

Auger, E.; D'Auria, L.; Martini, M.; Chouet, B.; Dawson, P.

2006-01-01

We present a comprehensive processing tool for the real-time analysis of the source mechanism of very long period (VLP) seismic data based on waveform inversions performed in the frequency domain for a point source. A search for the source providing the best-fitting solution is conducted over a three-dimensional grid of assumed source locations, in which the Green's functions associated with each point source are calculated by finite differences using the reciprocal relation between source and receiver. Tests performed on 62 nodes of a Linux cluster indicate that the waveform inversion and search for the best-fitting signal over 100,000 point sources require roughly 30 s of processing time for a 2-min-long record. The procedure is applied to post-processing of a data archive and to continuous automatic inversion of real-time data at Stromboli, providing insights into different modes of degassing at this volcano. Copyright 2006 by the American Geophysical Union.

Adaptive Self Tuning

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

Peterson, Matthew; Draelos, Timothy; Knox, Hunter

2017-05-02

The AST software includes numeric methods to 1) adjust STA/LTA signal detector trigger level (TL) values and 2) filter detections for a network of sensors. AST adapts TL values to the current state of the environment by leveraging cooperation within a neighborhood of sensors. The key metric that guides the dynamic tuning is consistency of each sensor with its nearest neighbors: TL values are automatically adjusted on a per station basis to be more or less sensitive to produce consistent agreement of detections in its neighborhood. The AST algorithm adapts in near real-time to changing conditions in an attempt tomore » automatically self-tune a signal detector to identify (detect) only signals from events of interest.« less

49 CFR 236.747 - Forestall.

Code of Federal Regulations, 2011 CFR

2011-10-01

... OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.747 Forestall. As applied to an automatic train stop or train control device, to prevent an automatic brake application by operation of an acknowledging device or by manual control of the speed of the train. ...

49 CFR 236.747 - Forestall.

Code of Federal Regulations, 2010 CFR

2010-10-01

... OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.747 Forestall. As applied to an automatic train stop or train control device, to prevent an automatic brake application by operation of an acknowledging device or by manual control of the speed of the train. ...

47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

Code of Federal Regulations, 2010 CFR

2010-10-01

... identified through the use of an automatic transmitter identification system as specified below. (a.... (3) The ATIS signal as a minimum shall consist of the following: (i) The FCC assigned earth station... (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON...

47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

Code of Federal Regulations, 2013 CFR

2013-10-01

... identified through the use of an automatic transmitter identification system as specified below. (a.... (3) The ATIS signal as a minimum shall consist of the following: (i) The FCC assigned earth station... (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON...

47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

Code of Federal Regulations, 2012 CFR

2012-10-01

... identified through the use of an automatic transmitter identification system as specified below. (a.... (3) The ATIS signal as a minimum shall consist of the following: (i) The FCC assigned earth station... (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON...

47 CFR 25.281 - Automatic Transmitter Identification System (ATIS).

Code of Federal Regulations, 2011 CFR

2011-10-01

... identified through the use of an automatic transmitter identification system as specified below. (a.... (3) The ATIS signal as a minimum shall consist of the following: (i) The FCC assigned earth station... (ATIS). 25.281 Section 25.281 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON...

Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

PubMed

Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

2013-11-01

The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

78 FR 46679 - Notice of Application for Approval of Discontinuance or Modification of a Railroad Signal System

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-01

... of Application for Approval of Discontinuance or Modification of a Railroad Signal System In... of a signal system. FRA assigned the petition Docket Number FRA-2013-0073. Applicant: Norfolk..., Georgia 30309. NS seeks approval of the proposed discontinuance of automatic signals within traffic...

77 FR 74736 - Notice of Application for Approval of Discontinuance or Modification of a Railroad Signal System

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-17

... of Application for Approval of Discontinuance or Modification of a Railroad Signal System In... discontinuance or modification of a signal system. FRA assigned the petition docket number FRA-2012-0087... Street NE., Atlanta, Georgia 30309. NS seeks approval of the proposed discontinuance of automatic signals...

78 FR 59754 - Notice of Application for Approval of Discontinuance or Modification of a Railroad Signal System

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-27

... of Application for Approval of Discontinuance or Modification of a Railroad Signal System In... of a signal system. FRA assigned the petition Docket Number FRA-2013-0095. Applicant: Grenada Railway... seeks approval of the proposed discontinuance and removal of the automatic block signal (ABS) system...

77 FR 9296 - Notice of Application for Approval of Discontinuance or Modification of a Railroad Signal System

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-16

... of Application for Approval of Discontinuance or Modification of a Railroad Signal System In... or modification of a signal system. FRA assigned the petition Docket Number FRA-2012-0012. UP seeks approval of the proposed discontinuance of the automatic block signal (ABS) system between Control Point...

On the influence of high-pass filtering on ICA-based artifact reduction in EEG-ERP.

PubMed

Winkler, Irene; Debener, Stefan; Müller, Klaus-Robert; Tangermann, Michael

2015-01-01

Standard artifact removal methods for electroencephalographic (EEG) signals are either based on Independent Component Analysis (ICA) or they regress out ocular activity measured at electrooculogram (EOG) channels. Successful ICA-based artifact reduction relies on suitable pre-processing. Here we systematically evaluate the effects of high-pass filtering at different frequencies. Offline analyses were based on event-related potential data from 21 participants performing a standard auditory oddball task and an automatic artifactual component classifier method (MARA). As a pre-processing step for ICA, high-pass filtering between 1-2 Hz consistently produced good results in terms of signal-to-noise ratio (SNR), single-trial classification accuracy and the percentage of `near-dipolar' ICA components. Relative to no artifact reduction, ICA-based artifact removal significantly improved SNR and classification accuracy. This was not the case for a regression-based approach to remove EOG artifacts.

The impact of compression of speech signal, background noise and acoustic disturbances on the effectiveness of speaker identification

NASA Astrophysics Data System (ADS)

Kamiński, K.; Dobrowolski, A. P.

2017-04-01

The paper presents the architecture and the results of optimization of selected elements of the Automatic Speaker Recognition (ASR) system that uses Gaussian Mixture Models (GMM) in the classification process. Optimization was performed on the process of selection of individual characteristics using the genetic algorithm and the parameters of Gaussian distributions used to describe individual voices. The system that was developed was tested in order to evaluate the impact of different compression methods used, among others, in landline, mobile, and VoIP telephony systems, on effectiveness of the speaker identification. Also, the results were presented of effectiveness of speaker identification at specific levels of noise with the speech signal and occurrence of other disturbances that could appear during phone calls, which made it possible to specify the spectrum of applications of the presented ASR system.

Improved EEG Event Classification Using Differential Energy.

PubMed

Harati, A; Golmohammadi, M; Lopez, S; Obeid, I; Picone, J

2015-12-01

Feature extraction for automatic classification of EEG signals typically relies on time frequency representations of the signal. Techniques such as cepstral-based filter banks or wavelets are popular analysis techniques in many signal processing applications including EEG classification. In this paper, we present a comparison of a variety of approaches to estimating and postprocessing features. To further aid in discrimination of periodic signals from aperiodic signals, we add a differential energy term. We evaluate our approaches on the TUH EEG Corpus, which is the largest publicly available EEG corpus and an exceedingly challenging task due to the clinical nature of the data. We demonstrate that a variant of a standard filter bank-based approach, coupled with first and second derivatives, provides a substantial reduction in the overall error rate. The combination of differential energy and derivatives produces a 24 % absolute reduction in the error rate and improves our ability to discriminate between signal events and background noise. This relatively simple approach proves to be comparable to other popular feature extraction approaches such as wavelets, but is much more computationally efficient.

Assessing ECG signal quality indices to discriminate ECGs with artefacts from pathologically different arrhythmic ECGs.

PubMed

Daluwatte, C; Johannesen, L; Galeotti, L; Vicente, J; Strauss, D G; Scully, C G

2016-08-01

False and non-actionable alarms in critical care can be reduced by developing algorithms which assess the trueness of an arrhythmia alarm from a bedside monitor. Computational approaches that automatically identify artefacts in ECG signals are an important branch of physiological signal processing which tries to address this issue. Signal quality indices (SQIs) derived considering differences between artefacts which occur in ECG signals and normal QRS morphology have the potential to discriminate pathologically different arrhythmic ECG segments as artefacts. Using ECG signals from the PhysioNet/Computing in Cardiology Challenge 2015 training set, we studied previously reported ECG SQIs in the scientific literature to differentiate ECG segments with artefacts from arrhythmic ECG segments. We found that the ability of SQIs to discriminate between ECG artefacts and arrhythmic ECG varies based on arrhythmia type since the pathology of each arrhythmic ECG waveform is different. Therefore, to reduce the risk of SQIs classifying arrhythmic events as noise it is important to validate and test SQIs with databases that include arrhythmias. Arrhythmia specific SQIs may also minimize the risk of misclassifying arrhythmic events as noise.

49 CFR 236.556 - Adjustment of relay.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives § 236.556 Adjustment of relay...

49 CFR 236.527 - Roadway element insulation resistance.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Roadway § 236.527 Roadway...

49 CFR 236.527 - Roadway element insulation resistance.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Roadway § 236.527 Roadway...

49 CFR 236.556 - Adjustment of relay.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives § 236.556 Adjustment of relay...

MM&T Program to Establish Production Techniques for the Automatic Detection and Qualification of Trace Elements Present in the Production of Microwave Semiconductors.

DTIC Science & Technology

1981-03-01

lots. A single store of partially processed devices may serve as a source for several different product lines. Because the manufacture of microwave...matrix, or react chem- ically with some of the semiconductor materials. In some cases these element impurities may migrate to an interface inducing... different viscosity, the background intensity varied independently of the signal, a significant error could be introduced. A more effec- tive method

Automotive Control Systems: For Engine, Driveline, and Vehicle

NASA Astrophysics Data System (ADS)

Kiencke, Uwe; Nielsen, Lars

Advances in automotive control systems continue to enhance safety and comfort and to reduce fuel consumption and emissions. Reflecting the trend to optimization through integrative approaches for engine, driveline, and vehicle control, this valuable book enables control engineers to understand engine and vehicle models necessary for controller design, and also introduces mechanical engineers to vehicle-specific signal processing and automatic control. The emphasis on measurement, comparisons between performance and modeling, and realistic examples derive from the authors' unique industrial experience

Automatic Seismic Signal Processing Research.

DTIC Science & Technology

1981-09-01

be used. We then rave mD(k) AT(k) + b (11) S2 aT S SD(k) - a(k) a so Equation (9) becomes ( Gnanadesikan , 1977, p. 83; Young and Calvert, 1974, Equation... Gnanadesikan (1977, p. 196), "The main function of statistical data analysis is to extricate and explicate the informational content of a body of...R. C. Goff (1980), "Evaluation of the MARS Seismic Event Detector," Systems, Science and Software Report SSS-R-81-4656, August. Gnanadesikan , R

AAAIC '88 - Aerospace Applications of Artificial Intelligence; Proceedings of the Fourth Annual Conference, Dayton, OH, Oct. 25-27, 1988. Volumes 1 2

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

Johnson, J.R.; Netrologic, Inc., San Diego, CA)

1988-01-01

Topics presented include integrating neural networks and expert systems, neural networks and signal processing, machine learning, cognition and avionics applications, artificial intelligence and man-machine interface issues, real time expert systems, artificial intelligence, and engineering applications. Also considered are advanced problem solving techniques, combinational optimization for scheduling and resource control, data fusion/sensor fusion, back propagation with momentum, shared weights and recurrency, automatic target recognition, cybernetics, optical neural networks.

An automatic classifier of emotions built from entropy of noise.

PubMed

Ferreira, Jacqueline; Brás, Susana; Silva, Carlos F; Soares, Sandra C

2017-04-01

The electrocardiogram (ECG) signal has been widely used to study the physiological substrates of emotion. However, searching for better filtering techniques in order to obtain a signal with better quality and with the maximum relevant information remains an important issue for researchers in this field. Signal processing is largely performed for ECG analysis and interpretation, but this process can be susceptible to error in the delineation phase. In addition, it can lead to the loss of important information that is usually considered as noise and, consequently, discarded from the analysis. The goal of this study was to evaluate if the ECG noise allows for the classification of emotions, while using its entropy as an input in a decision tree classifier. We collected the ECG signal from 25 healthy participants while they were presented with videos eliciting negative (fear and disgust) and neutral emotions. The results indicated that the neutral condition showed a perfect identification (100%), whereas the classification of negative emotions indicated good identification performances (60% of sensitivity and 80% of specificity). These results suggest that the entropy of noise contains relevant information that can be useful to improve the analysis of the physiological correlates of emotion. © 2016 Society for Psychophysiological Research.

Automatic oscillator frequency control system

NASA Technical Reports Server (NTRS)

Smith, S. F. (Inventor)

1985-01-01

A frequency control system makes an initial correction of the frequency of its own timing circuit after comparison against a frequency of known accuracy and then sequentially checks and corrects the frequencies of several voltage controlled local oscillator circuits. The timing circuit initiates the machine cycles of a central processing unit which applies a frequency index to an input register in a modulo-sum frequency divider stage and enables a multiplexer to clock an accumulator register in the divider stage with a cyclical signal derived from the oscillator circuit being checked. Upon expiration of the interval, the processing unit compares the remainder held as the contents of the accumulator against a stored zero error constant and applies an appropriate correction word to a correction stage to shift the frequency of the oscillator being checked. A signal from the accumulator register may be used to drive a phase plane ROM and, with periodic shifts in the applied frequency index, to provide frequency shift keying of the resultant output signal. Interposition of a phase adder between the accumulator register and phase plane ROM permits phase shift keying of the output signal by periodic variation in the value of a phase index applied to one input of the phase adder.

HCPCF-based in-line fiber Fabry-Perot refractometer and high sensitivity signal processing method

NASA Astrophysics Data System (ADS)

Liu, Xiaohui; Jiang, Mingshun; Sui, Qingmei; Geng, Xiangyi; Song, Furong

2017-12-01

An in-line fiber Fabry-Perot interferometer (FPI) based on the hollow-core photonic crystal fiber (HCPCF) for refractive index (RI) measurement is proposed in this paper. The FPI is formed by splicing both ends of a short section of the HCPCF to single mode fibers (SMFs) and cleaving the SMF pigtail to a proper length. The RI response of the sensor is analyzed theoretically and demonstrated experimentally. The results show that the FPI sensor has linear response to external RI and good repeatability. The sensitivity calculated from the maximum fringe contrast is -136 dB/RIU. A new spectrum differential integration (SDI) method for signal processing is also presented in this study. In this method, the RI is obtained from the integrated intensity of the absolute difference between the interference spectrum and its smoothed spectrum. The results show that the sensitivity obtained from the integrated intensity is about -1.34×105 dB/RIU. Compared with the maximum fringe contrast method, the new SDI method can provide the higher sensitivity, better linearity, improved reliability, and accuracy, and it's also convenient for automatic and fast signal processing in real-time monitoring of RI.

New Modular Ultrasonic Signal Processing Building Blocks for Real-Time Data Acquisition and Post Processing

NASA Astrophysics Data System (ADS)

Weber, Walter H.; Mair, H. Douglas; Jansen, Dion

2003-03-01

A suite of basic signal processors has been developed. These basic building blocks can be cascaded together to form more complex processors without the need for programming. The data structures between each of the processors are handled automatically. This allows a processor built for one purpose to be applied to any type of data such as images, waveform arrays and single values. The processors are part of Winspect Data Acquisition software. The new processors are fast enough to work on A-scan signals live while scanning. Their primary use is to extract features, reduce noise or to calculate material properties. The cascaded processors work equally well on live A-scan displays, live gated data or as a post-processing engine on saved data. Researchers are able to call their own MATLAB or C-code from anywhere within the processor structure. A built-in formula node processor that uses a simple algebraic editor may make external user programs unnecessary. This paper also discusses the problems associated with ad hoc software development and how graphical programming languages can tie up researchers writing software rather than designing experiments.

Adaptive sleep-wake discrimination for wearable devices.

PubMed

Karlen, Walter; Floreano, Dario

2011-04-01

Sleep/wake classification systems that rely on physiological signals suffer from intersubject differences that make accurate classification with a single, subject-independent model difficult. To overcome the limitations of intersubject variability, we suggest a novel online adaptation technique that updates the sleep/wake classifier in real time. The objective of the present study was to evaluate the performance of a newly developed adaptive classification algorithm that was embedded on a wearable sleep/wake classification system called SleePic. The algorithm processed ECG and respiratory effort signals for the classification task and applied behavioral measurements (obtained from accelerometer and press-button data) for the automatic adaptation task. When trained as a subject-independent classifier algorithm, the SleePic device was only able to correctly classify 74.94 ± 6.76% of the human-rated sleep/wake data. By using the suggested automatic adaptation method, the mean classification accuracy could be significantly improved to 92.98 ± 3.19%. A subject-independent classifier based on activity data only showed a comparable accuracy of 90.44 ± 3.57%. We demonstrated that subject-independent models used for online sleep-wake classification can successfully be adapted to previously unseen subjects without the intervention of human experts or off-line calibration.

An algorithm developed in Matlab for the automatic selection of cut-off frequencies, in the correction of strong motion data

NASA Astrophysics Data System (ADS)

Sakkas, Georgios; Sakellariou, Nikolaos

2018-05-01

Strong motion recordings are the key in many earthquake engineering applications and are also fundamental for seismic design. The present study focuses on the automated correction of accelerograms, analog and digital. The main feature of the proposed algorithm is the automatic selection for the cut-off frequencies based on a minimum spectral value in a predefined frequency bandwidth, instead of the typical signal-to-noise approach. The algorithm follows the basic steps of the correction procedure (instrument correction, baseline correction and appropriate filtering). Besides the corrected time histories, Peak Ground Acceleration, Peak Ground Velocity, Peak Ground Displacement values and the corrected Fourier Spectra are also calculated as well as the response spectra. The algorithm is written in Matlab environment, is fast enough and can be used for batch processing or in real-time applications. In addition, the possibility to also perform a signal-to-noise ratio is added as well as to perform causal or acausal filtering. The algorithm has been tested in six significant earthquakes (Kozani-Grevena 1995, Aigio 1995, Athens 1999, Lefkada 2003 and Kefalonia 2014) of the Greek territory with analog and digital accelerograms.

Computer controllable synchronous shifting of an automatic transmission

DOEpatents

Davis, R.I.; Patil, P.B.

1989-08-08

A multiple forward speed automatic transmission produces its lowest forward speed ratio when a hydraulic clutch and hydraulic brake are disengaged and a one-way clutch connects a ring gear to the transmission casing. Second forward speed ratio results when the hydraulic clutch is engaged to connect the ring gear to the planetary carrier of a second gear set. Reverse drive and regenerative operation result when an hydraulic brake fixes the planetary and the direction of power flow is reversed. Various sensors produce signals representing the torque at the output of the transmission or drive wheels, the speed of the power source, and the hydraulic pressure applied to a clutch and brake. A control algorithm produces input data representing a commanded upshift, a commanded downshift, a commanded transmission output torque, and commanded power source speed. A microprocessor processes the inputs and produces a response to them in accordance with the execution of a control algorithm. Output or response signals cause selective engagement and disengagement of the clutch and brake at a rate that satisfies the requirements for a short gear ratio change and smooth torque transfer between the friction elements. 6 figs.

Second sound tracking system

NASA Astrophysics Data System (ADS)

Yang, Jihee; Ihas, Gary G.; Ekdahl, Dan

2017-10-01

It is common that a physical system resonates at a particular frequency, whose frequency depends on physical parameters which may change in time. Often, one would like to automatically track this signal as the frequency changes, measuring, for example, its amplitude. In scientific research, one would also like to utilize the standard methods, such as lock-in amplifiers, to improve the signal to noise ratio. We present a complete He ii second sound system that uses positive feedback to generate a sinusoidal signal of constant amplitude via automatic gain control. This signal is used to produce temperature/entropy waves (second sound) in superfluid helium-4 (He ii). A lock-in amplifier limits the oscillation to a desirable frequency and demodulates the received sound signal. Using this tracking system, a second sound signal probed turbulent decay in He ii. We present results showing that the tracking system is more reliable than those of a conventional fixed frequency method; there is less correlation with temperature (frequency) fluctuation when the tracking system is used.

75 FR 6252 - Notice of Application for Approval of Discontinuance or Modification of a Railroad Signal System...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-08

... Discontinuance or Modification of a Railroad Signal System or Relief From the Requirements of Title 49 Code of... approval for the discontinuance or modification of the signal system or relief from the requirements of 49... the conversion of dispatcher controlled holdout signals, 96L and 96R, to automatic signals, 8221 and...

49 CFR 236.555 - Repaired or rewound receiver coil.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives § 236.555 Repaired...

49 CFR 236.558-236.559 - [Reserved

Code of Federal Regulations, 2010 CFR

2010-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives §§ 236.558-236.559 [Reserved] ...

49 CFR 236.529 - Roadway element inductor; height and distance from rail.

Code of Federal Regulations, 2011 CFR

2011-10-01

... THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions...

49 CFR 236.529 - Roadway element inductor; height and distance from rail.

Code of Federal Regulations, 2010 CFR

2010-10-01

... THE INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions...

49 CFR 236.558-236.559 - [Reserved

Code of Federal Regulations, 2011 CFR

2011-10-01

..., MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives §§ 236.558-236.559 [Reserved] ...

49 CFR 236.555 - Repaired or rewound receiver coil.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives § 236.555 Repaired...

A system for automatic analysis of blood pressure data for digital computer entry

NASA Technical Reports Server (NTRS)

Miller, R. L.

1972-01-01

Operation of automatic blood pressure data system is described. Analog blood pressure signal is analyzed by three separate circuits, systolic, diastolic, and cycle defect. Digital computer output is displayed on teletype paper tape punch and video screen. Illustration of system is included.

Automatic data processing and analysis system for monitoring region around a planned nuclear power plant

NASA Astrophysics Data System (ADS)

Kortström, Jari; Tiira, Timo; Kaisko, Outi

2016-03-01

The Institute of Seismology of University of Helsinki is building a new local seismic network, called OBF network, around planned nuclear power plant in Northern Ostrobothnia, Finland. The network will consist of nine new stations and one existing station. The network should be dense enough to provide azimuthal coverage better than 180° and automatic detection capability down to ML -0.1 within a radius of 25 km from the site.The network construction work began in 2012 and the first four stations started operation at the end of May 2013. We applied an automatic seismic signal detection and event location system to a network of 13 stations consisting of the four new stations and the nearest stations of Finnish and Swedish national seismic networks. Between the end of May and December 2013 the network detected 214 events inside the predefined area of 50 km radius surrounding the planned nuclear power plant site. Of those detections, 120 were identified as spurious events. A total of 74 events were associated with known quarries and mining areas. The average location error, calculated as a difference between the announced location from environment authorities and companies and the automatic location, was 2.9 km. During the same time period eight earthquakes between magnitude range 0.1-1.0 occurred within the area. Of these seven could be automatically detected. The results from the phase 1 stations of the OBF network indicates that the planned network can achieve its goals.

49 CFR 236.532 - Strap iron inductor; use restricted.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Roadway § 236.532 Strap iron...

49 CFR 236.532 - Strap iron inductor; use restricted.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Roadway § 236.532 Strap iron...

49 CFR 236.577 - Test, acknowledgement, and cut-in circuits.

Code of Federal Regulations, 2011 CFR

2011-10-01

... INSTALLATION, INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Inspection and Tests; Roadway § 236.577 Test...

Automated enforcement of traffic signals : a literature review

DOT National Transportation Integrated Search

2001-08-13

This document presents the results of an extensive review of available documents regarding automated enforcement of traffic signal compliance. The literature regarding the operation and impacts of systems that automatically enforce driver compliance ...

Automatic Adaptation to Fast Input Changes in a Time-Invariant Neural Circuit

PubMed Central

Bharioke, Arjun; Chklovskii, Dmitri B.

2015-01-01

Neurons must faithfully encode signals that can vary over many orders of magnitude despite having only limited dynamic ranges. For a correlated signal, this dynamic range constraint can be relieved by subtracting away components of the signal that can be predicted from the past, a strategy known as predictive coding, that relies on learning the input statistics. However, the statistics of input natural signals can also vary over very short time scales e.g., following saccades across a visual scene. To maintain a reduced transmission cost to signals with rapidly varying statistics, neuronal circuits implementing predictive coding must also rapidly adapt their properties. Experimentally, in different sensory modalities, sensory neurons have shown such adaptations within 100 ms of an input change. Here, we show first that linear neurons connected in a feedback inhibitory circuit can implement predictive coding. We then show that adding a rectification nonlinearity to such a feedback inhibitory circuit allows it to automatically adapt and approximate the performance of an optimal linear predictive coding network, over a wide range of inputs, while keeping its underlying temporal and synaptic properties unchanged. We demonstrate that the resulting changes to the linearized temporal filters of this nonlinear network match the fast adaptations observed experimentally in different sensory modalities, in different vertebrate species. Therefore, the nonlinear feedback inhibitory network can provide automatic adaptation to fast varying signals, maintaining the dynamic range necessary for accurate neuronal transmission of natural inputs. PMID:26247884

Automatic verification of SSD and generation of respiratory signal with lasers in radiotherapy: a preliminary study.

PubMed

Prabhakar, Ramachandran

2012-01-01

Source to surface distance (SSD) plays a very important role in external beam radiotherapy treatment verification. In this study, a simple technique has been developed to verify the SSD automatically with lasers. The study also suggests a methodology for determining the respiratory signal with lasers. Two lasers, red and green are mounted on the collimator head of a Clinac 2300 C/D linac along with a camera to determine the SSD. A software (SSDLas) was developed to estimate the SSD automatically from the images captured by a 12-megapixel camera. To determine the SSD to a patient surface, the external body contour of the central axis transverse computed tomography (CT) cut is imported into the software. Another important aspect in radiotherapy is the generation of respiratory signal. The changes in the lasers separation as the patient breathes are converted to produce a respiratory signal. Multiple frames of laser images were acquired from the camera mounted on the collimator head and each frame was analyzed with SSDLas to generate the respiratory signal. The SSD as observed with the ODI on the machine and SSD measured by the SSDlas software was found to be within the tolerance limit. The methodology described for generating the respiratory signals will be useful for the treatment of mobile tumors such as lung, liver, breast, pancreas etc. The technique described for determining the SSD and the generation of respiratory signals using lasers is cost effective and simple to implement. Copyright © 2011 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Active Learning for Automatic Audio Processing of Unwritten Languages (ALAPUL)

DTIC Science & Technology

2016-07-01

AFRL-RH-WP-TR-2016-0074 ACTIVE LEARNING FOR AUTOMATIC AUDIO PROCESSING OF UNWRITTEN LANGUAGES (ALAPUL) Dimitra Vergyri Andreas Kathol Wen Wang...June 2015-July 2016 4. TITLE AND SUBTITLE Active Learning for Automatic Audio Processing of Unwritten Languages (ALAPUL) 5a. CONTRACT NUMBER...5430, 27 October 2016 1. SUMMARY The goal of the project was to investigate development of an automatic spoken language processing (ASLP) system

Using Dual-Task Methodology to Dissociate Automatic from Nonautomatic Processes Involved in Artificial Grammar Learning

ERIC Educational Resources Information Center

Hendricks, Michelle A.; Conway, Christopher M.; Kellogg, Ronald T.

2013-01-01

Previous studies have suggested that both automatic and intentional processes contribute to the learning of grammar and fragment knowledge in artificial grammar learning (AGL) tasks. To explore the relative contribution of automatic and intentional processes to knowledge gained in AGL, we utilized dual-task methodology to dissociate automatic and…

Time-Domain Receiver Function Deconvolution using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Moreira, L. P.

2017-12-01

Receiver Functions (RF) are well know method for crust modelling using passive seismological signals. Many different techniques were developed to calculate the RF traces, applying the deconvolution calculation to radial and vertical seismogram components. A popular method used a spectral division of both components, which requires human intervention to apply the Water Level procedure to avoid instabilities from division by small numbers. One of most used method is an iterative procedure to estimate the RF peaks and applying the convolution with vertical component seismogram, comparing the result with the radial component. This method is suitable for automatic processing, however several RF traces are invalid due to peak estimation failure.In this work it is proposed a deconvolution algorithm using Genetic Algorithm (GA) to estimate the RF peaks. This method is entirely processed in the time domain, avoiding the time-to-frequency calculations (and vice-versa), and totally suitable for automatic processing. Estimated peaks can be used to generate RF traces in a seismogram format for visualization. The RF trace quality is similar for high magnitude events, although there are less failures for RF calculation of smaller events, increasing the overall performance for high number of events per station.

Real-time automatic inspection under adverse conditions

NASA Astrophysics Data System (ADS)

Carvalho, Fernando D.; Correia, Fernando C.; Freitas, Jose C. A.; Rodrigues, Fernando C.

1991-03-01

This paper presents the results of a R&D Program supported by a grant from the Ministry of Defense, devoted to the development of an inteffigent camera for surveillance in the open air. The effects of shadows, clouds and winds were problems to be solved without generating false alarm events. The system is based on a video CCD camera which generates a video CCIR signal. The signal is then processed in modular hardware which detects the changes in the scene and processes the image, in order to enhance the intruder image and path. Windows may be defined over the image in order to increase the information obtained about the intruder and a first approach to the classification of the type of intruder may be achieved. The paper describes the hardware used in the system, as well as the software, used for the installation of the camera and the software developed for the microprocessor which is responsible for the generation of the alarm signals. The paper also presents some results of surveillance tasks in the open air executed by the system with real time performance.

Enhanced performance for differential detection in coherent Brillouin optical time-domain analysis sensors

NASA Astrophysics Data System (ADS)

Shao, Liyang; Zhang, Yunpeng; Li, Zonglei; Zhang, Zhiyong; Zou, Xihua; Luo, Bin; Pan, Wei; Yan, Lianshan

2016-11-01

Logarithmic detectors (LogDs) have been used in coherent Brillouin optical time-domain analysis (BOTDA) sensors to reduce the effect of phase fluctuation, demodulation complexities, and measurement time. However, because of the inherent properties of LogDs, a DC component at the level of hundreds of millivolts that prohibits high-gain signal amplification (SA) could be generated, resulting in unacceptable data acquisition (DAQ) inaccuracies and decoding errors in the process of prototype integration. By generating a reference light at a level similar to the probe light, differential detection can be applied to remove the DC component automatically using a differential amplifier before the DAQ process. Therefore, high-gain SA can be employed to reduce quantization errors. The signal-to-noise ratio of the weak Brillouin gain signal is improved from ˜11.5 to ˜21.8 dB. A BOTDA prototype is implemented based on the proposed scheme. The experimental results show that the measurement accuracy of the Brillouin frequency shift (BFS) is improved from ±1.9 to ±0.8 MHz at the end of a 40-km sensing fiber.

Monitoring the Earth's Atmosphere with the Global IMS Infrasound Network

NASA Astrophysics Data System (ADS)

Brachet, Nicolas; Brown, David; Mialle, Pierrick; Le Bras, Ronan; Coyne, John; Given, Jeffrey

2010-05-01

The Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) is tasked with monitoring compliance with the Comprehensive Nuclear-Test-Ban Treaty (CTBT) which bans nuclear weapon explosions underground, in the oceans, and in the atmosphere. The verification regime includes a globally distributed network of seismic, hydroacoustic, infrasound and radionuclide stations which collect and transmit data to the International Data Centre (IDC) in Vienna, Austria shortly after the data are recorded at each station. The infrasound network defined in the Protocol of the CTBT comprises 60 infrasound array stations. Each array is built according to the same technical specifications, it is typically composed of 4 to 9 sensors, with 1 to 3 km aperture geometry. At the end of 2000 only one infrasound station was transmitting data to the IDC. Since then, 41 additional stations have been installed and 70% of the infrasound network is currently certified and contributing data to the IDC. This constitutes the first global infrasound network ever built with such a large and uniform distribution of stations. Infrasound data at the IDC are processed at the station level using the Progressive Multi-Channel Correlation (PMCC) method for the detection and measurement of infrasound signals. The algorithm calculates the signal correlation between sensors at an infrasound array. If the signal is sufficiently correlated and consistent over an extended period of time and frequency range a detection is created. Groups of detections are then categorized according to their propagation and waveform features, and a phase name is assigned for infrasound, seismic or noise detections. The categorization complements the PMCC algorithm to avoid overwhelming the IDC automatic association algorithm with false alarm infrasound events. Currently, 80 to 90% of the detections are identified as noise by the system. Although the noise detections are not used to build events in the context of CTBT monitoring, they represent valuable data for other civil applications like monitoring of natural hazards (volcanic activity, storm tracking) and climate change. Non-noise detections are used in network processing at the IDC along with seismic and hydroacoustic technologies. The arrival phases detected on the three waveform technologies may be combined and used for locating events in an automatically generated bulletin of events. This automatic event bulletin is routinely reviewed by analysts during the interactive review process. However, the fusion of infrasound data with the other waveform technologies has only recently (in early 2010) become part of the IDC operational system, after a software development and testing period that began in 2004. The build-up of the IMS infrasound network, the recent developments of the IDC infrasound software, and the progress accomplished during the last decade in the domain of real-time atmospheric modelling have allowed better understanding of infrasound signals and identification of a growing data set of ground-truth sources. These infragenic sources originate from natural or man-made sources. Some of the detected signals are emitted by local or regional phenomena recorded by a single IMS infrasound station: man-made cultural activity, wind farms, aircraft, artillery exercises, ocean surf, thunderstorms, rumbling volcanoes, iceberg calving, aurora, avalanches. Other signals may be recorded by several IMS infrasound stations at larger distances: ocean swell, sonic booms, and mountain associated waves. Only a small fraction of events meet the event definition criteria considering the Treaty verification mission of the Organization. Candidate event types for the IDC Reviewed Event Bulletin include atmospheric or surface explosions, meteor explosions, rocket launches, signals from large earthquakes and explosive volcanic eruptions.

Adaptive method of recognition of signals for one and two-frequency signal system in the telephony on the background of speech

NASA Astrophysics Data System (ADS)

Kuznetsov, Michael V.

2006-05-01

For reliable teamwork of various systems of automatic telecommunication including transferring systems of optical communication networks it is necessary authentic recognition of signals for one- or two-frequency service signal system. The analysis of time parameters of an accepted signal allows increasing reliability of detection and recognition of the service signal system on a background of speech.

75 FR 34200 - Notice of Application for Approval of Discontinuance or Modification of a Railroad Signal System

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-16

... of Application for Approval of Discontinuance or Modification of a Railroad Signal System Pursuant to... of the signal, as detailed below. Docket Number: FRA-2010-0084. Applicant: Pan Am Railways, Mr... CPF-428, all associated appliances, and the installation of an automatic block signal at mile 428.27...

Measuring circuit

DOEpatents

Sun, Shan C.; Chaprnka, Anthony G.

1977-01-11

An automatic gain control circuit functions to adjust the magnitude of an input signal supplied to a measuring circuit to a level within the dynamic range of the measuring circuit while a log-ratio circuit adjusts the magnitude of the output signal from the measuring circuit to the level of the input signal and optimizes the signal-to-noise ratio performance of the measuring circuit.

Automatic Detection of Landslides at Stromboli Volcano

NASA Astrophysics Data System (ADS)

Giudicepietro, F.; Esposito, A. M.; D'Auria, L.; Peluso, R.; Martini, M.

2011-12-01

In this work we present an automatic system for the landslide detection at Stromboli volcano that has proved to be effective both during the 2007 effusive eruption and in the recent (2 August 2011) volcanic activity. The study of the landslides at Stromboli is important because they could be considered short-term precursors of effusive eruptions, as seen during the 2007 eruption, and in addition they allow to improve the monitoring of the gravitational instabilities of the Sciara del Fuoco flank. The proposed system uses a two-class MLP (Multi Layer Perceptron) neural network in order to discriminate the landslides from other seismic signals usually recorded at Stromboli, such as explosion-quakes and volcanic tremor. To train and test the network we used a dataset of 537 signals, including 267 landslides and 270 other events (130 explosion-quakes and 140 tremor signals). The net performance is of 98.7%, if averaged over different net configurations, and of 99.5% for the best net performance. Based on the neural network response, the automatic system calculates a Landslide Percentage Index (LPI) defined on the number of signals identified as landslides by the net on a given temporal interval in order to recognize anomalies in the landslide rate. This system was sensitive to the signals produced by the flow of lava front during a recent mild effusive episode on the "La Sciara del Fuoco" slope.

Implementation of a computer-assisted monitoring system for the detection of adverse drug reactions in gastroenterology.

PubMed

Dormann, H; Criegee-Rieck, M; Neubert, A; Egger, T; Levy, M; Hahn, E G; Brune, K

2004-02-01

To investigate the effectiveness of a computer monitoring system that detects adverse drug reactions (ADRs) by laboratory signals in gastroenterology. A prospective, 6-month, pharmaco-epidemiological survey was carried out on a gastroenterological ward at the University Hospital Erlangen-Nuremberg. Two methods were used to identify ADRs. (i) All charts were reviewed daily by physicians and clinical pharmacists. (ii) A computer monitoring system generated a daily list of automatic laboratory signals and alerts of ADRs, including patient data and dates of events. One hundred and nine ADRs were detected in 474 admissions (377 patients). The computer monitoring system generated 4454 automatic laboratory signals from 39 819 laboratory parameters tested, and issued 2328 alerts, 914 (39%) of which were associated with ADRs; 574 (25%) were associated with ADR-positive admissions. Of all the alerts generated, signals of hepatotoxicity (1255), followed by coagulation disorders (407) and haematological toxicity (207), were prevalent. Correspondingly, the prevailing ADRs were concerned with the metabolic and hepato-gastrointestinal system (61). The sensitivity was 91%: 69 of 76 ADR-positive patients were indicated by an alert. The specificity of alerts was increased from 23% to 76% after implementation of an automatic laboratory signal trend monitoring algorithm. This study shows that a computer monitoring system is a useful tool for the systematic and automated detection of ADRs in gastroenterological patients.

Automatic QRS complex detection using two-level convolutional neural network.

PubMed

Xiang, Yande; Lin, Zhitao; Meng, Jianyi

2018-01-29

The QRS complex is the most noticeable feature in the electrocardiogram (ECG) signal, therefore, its detection is critical for ECG signal analysis. The existing detection methods largely depend on hand-crafted manual features and parameters, which may introduce significant computational complexity, especially in the transform domains. In addition, fixed features and parameters are not suitable for detecting various kinds of QRS complexes under different circumstances. In this study, based on 1-D convolutional neural network (CNN), an accurate method for QRS complex detection is proposed. The CNN consists of object-level and part-level CNNs for extracting different grained ECG morphological features automatically. All the extracted morphological features are used by multi-layer perceptron (MLP) for QRS complex detection. Additionally, a simple ECG signal preprocessing technique which only contains difference operation in temporal domain is adopted. Based on the MIT-BIH arrhythmia (MIT-BIH-AR) database, the proposed detection method achieves overall sensitivity Sen = 99.77%, positive predictivity rate PPR = 99.91%, and detection error rate DER = 0.32%. In addition, the performance variation is performed according to different signal-to-noise ratio (SNR) values. An automatic QRS detection method using two-level 1-D CNN and simple signal preprocessing technique is proposed for QRS complex detection. Compared with the state-of-the-art QRS complex detection approaches, experimental results show that the proposed method acquires comparable accuracy.

New low-level a-c amplifier provides adjustable noise cancellation and automatic temperature compensation

NASA Technical Reports Server (NTRS)

Smith, J. R., Jr.

1964-01-01

Circuit utilizing a transistorized differential amplifier is developed for biomedical use. This low voltage operating circuit provides adjustable cancellation at the input for unbalanced noise signals, and automatic temperature compensation is accomplished by a single active element across the input-output ends.

Controlled versus automatic processes: which is dominant to safety? The moderating effect of inhibitory control.

PubMed

Xu, Yaoshan; Li, Yongjuan; Ding, Weidong; Lu, Fan

2014-01-01

This study explores the precursors of employees' safety behaviors based on a dual-process model, which suggests that human behaviors are determined by both controlled and automatic cognitive processes. Employees' responses to a self-reported survey on safety attitudes capture their controlled cognitive process, while the automatic association concerning safety measured by an Implicit Association Test (IAT) reflects employees' automatic cognitive processes about safety. In addition, this study investigates the moderating effects of inhibition on the relationship between self-reported safety attitude and safety behavior, and that between automatic associations towards safety and safety behavior. The results suggest significant main effects of self-reported safety attitude and automatic association on safety behaviors. Further, the interaction between self-reported safety attitude and inhibition and that between automatic association and inhibition each predict unique variances in safety behavior. Specifically, the safety behaviors of employees with lower level of inhibitory control are influenced more by automatic association, whereas those of employees with higher level of inhibitory control are guided more by self-reported safety attitudes. These results suggest that safety behavior is the joint outcome of both controlled and automatic cognitive processes, and the relative importance of these cognitive processes depends on employees' individual differences in inhibitory control. The implications of these findings for theoretical and practical issues are discussed at the end.

Controlled versus Automatic Processes: Which Is Dominant to Safety? The Moderating Effect of Inhibitory Control

PubMed Central

Xu, Yaoshan; Li, Yongjuan; Ding, Weidong; Lu, Fan

2014-01-01

This study explores the precursors of employees' safety behaviors based on a dual-process model, which suggests that human behaviors are determined by both controlled and automatic cognitive processes. Employees' responses to a self-reported survey on safety attitudes capture their controlled cognitive process, while the automatic association concerning safety measured by an Implicit Association Test (IAT) reflects employees' automatic cognitive processes about safety. In addition, this study investigates the moderating effects of inhibition on the relationship between self-reported safety attitude and safety behavior, and that between automatic associations towards safety and safety behavior. The results suggest significant main effects of self-reported safety attitude and automatic association on safety behaviors. Further, the interaction between self-reported safety attitude and inhibition and that between automatic association and inhibition each predict unique variances in safety behavior. Specifically, the safety behaviors of employees with lower level of inhibitory control are influenced more by automatic association, whereas those of employees with higher level of inhibitory control are guided more by self-reported safety attitudes. These results suggest that safety behavior is the joint outcome of both controlled and automatic cognitive processes, and the relative importance of these cognitive processes depends on employees' individual differences in inhibitory control. The implications of these findings for theoretical and practical issues are discussed at the end. PMID:24520338

A hardware-software system for the automation of verification and calibration of oil metering units secondary equipment

NASA Astrophysics Data System (ADS)

Boyarnikov, A. V.; Boyarnikova, L. V.; Kozhushko, A. A.; Sekachev, A. F.

2017-08-01

In the article the process of verification (calibration) of oil metering units secondary equipment is considered. The purpose of the work is to increase the reliability and reduce the complexity of this process by developing a software and hardware system that provides automated verification and calibration. The hardware part of this complex carries out the commutation of the measuring channels of the verified controller and the reference channels of the calibrator in accordance with the introduced algorithm. The developed software allows controlling the commutation of channels, setting values on the calibrator, reading the measured data from the controller, calculating errors and compiling protocols. This system can be used for checking the controllers of the secondary equipment of the oil metering units in the automatic verification mode (with the open communication protocol) or in the semi-automatic verification mode (without it). The peculiar feature of the approach used is the development of a universal signal switch operating under software control, which can be configured for various verification methods (calibration), which allows to cover the entire range of controllers of metering units secondary equipment. The use of automatic verification with the help of a hardware and software system allows to shorten the verification time by 5-10 times and to increase the reliability of measurements, excluding the influence of the human factor.

Method and apparatus for automatic control of a humanoid robot

NASA Technical Reports Server (NTRS)

Abdallah, Muhammad E (Inventor); Platt, Robert (Inventor); Wampler, II, Charles W. (Inventor); Sanders, Adam M (Inventor); Reiland, Matthew J (Inventor)

2013-01-01

A robotic system includes a humanoid robot having a plurality of joints adapted for force control with respect to an object acted upon by the robot, a graphical user interface (GUI) for receiving an input signal from a user, and a controller. The GUI provides the user with intuitive programming access to the controller. The controller controls the joints using an impedance-based control framework, which provides object level, end-effector level, and/or joint space-level control of the robot in response to the input signal. A method for controlling the robotic system includes receiving the input signal via the GUI, e.g., a desired force, and then processing the input signal using a host machine to control the joints via an impedance-based control framework. The framework provides object level, end-effector level, and/or joint space-level control of the robot, and allows for functional-based GUI to simplify implementation of a myriad of operating modes.

Design of Weft Detection System in The Stenter Machine

NASA Astrophysics Data System (ADS)

Gu, Minming; Xu, Xianju; Dai, Wenzhan

2017-12-01

In order to build an effective automatic weft-straightening system, it is important for the sensing device to detect most the possible fabric styles, designs, colours and structures, an optical sensing system that detects the angular orientation of weft threads in a moving web of a textile has been built. It contains an adjustable light source, two lens systems and photodiode sensor array. The sensor array includes 13 radial pattern of photosensitive areas that each generate an electrical signal proportional to the total intensity of the light incident on the area. The moving shadow of a weft thread passing over the area will modulate the output signal. A signal processed circuit was built to do the I/V conversion, amplifying, hardware filtering. An embed micro control system then deals with the information of these signals, calculates the angle of the weft drew. Finally, the experiments were done, the results showed that the weft detection system can deal with the fabric weft skew up to 30° and has achieved good results in the application.

Instrument-independent analysis of music by means of the continuous wavelet transform

NASA Astrophysics Data System (ADS)

Olmo, Gabriella; Dovis, Fabio; Benotto, Paolo; Calosso, Claudio; Passaro, Pierluigi

1999-10-01

This paper deals with the problem of automatic recognition of music. Segments of digitized music are processed by means of a Continuous Wavelet Transform, properly chosen so as to match the spectral characteristics of the signal. In order to achieve a good time-scale representation of the signal components a novel wavelet has been designed suited to the musical signal features. particular care has been devoted towards an efficient implementation, which operates in the frequency domain, and includes proper segmentation and aliasing reduction techniques to make the analysis of long signals feasible. The method achieves very good performance in terms of both time and frequency selectivity, and can yield the estimate and the localization in time of both the fundamental frequency and the main harmonics of each tone. The analysis is used as a preprocessing step for a recognition algorithm, which we show to be almost independent on the instrument reproducing the sounds. Simulations are provided to demonstrate the effectiveness of the proposed method.

An all digital low data rate communication system

NASA Technical Reports Server (NTRS)

Chen, C.; Fan, M.

1973-01-01

The advent of digital hardwares has made it feasible to implement many communication system components digitally. With the exception of frequency down conversion, the proposed low data rate communication system uses digital hardwares completely. Although the system is designed primarily for deep space communications with large frequency uncertainty and low signal-to-noise ratio, it is also suitable for other low data rate applications with time-shared operation among a number of channels. Emphasis is placed on the fast Fourier transform receiver and the automatic frequency control via digital filtering. The speed available from the digital system allows sophisticated signal processing to reduce frequency uncertainty and to increase the signal-to-noise ratio. The practical limitations of the system such as the finite register length are examined. It is concluded that the proposed all-digital system is not only technically feasible but also has potential cost reduction over the existing receiving systems.

The role of metacognition in human social interactions

PubMed Central

Frith, Chris D.

2012-01-01

Metacognition concerns the processes by which we monitor and control our own cognitive processes. It can also be applied to others, in which case it is known as mentalizing. Both kinds of metacognition have implicit and explicit forms, where implicit means automatic and without awareness. Implicit metacognition enables us to adopt a we-mode, through which we automatically take account of the knowledge and intentions of others. Adoption of this mode enhances joint action. Explicit metacognition enables us to reflect on and justify our behaviour to others. However, access to the underlying processes is very limited for both self and others and our reports on our own and others' intentions can be very inaccurate. On the other hand, recent experiments have shown that, through discussions of our perceptual experiences with others, we can detect sensory signals more accurately, even in the absence of objective feedback. Through our willingness to discuss with others the reasons for our actions and perceptions, we overcome our lack of direct access to the underlying cognitive processes. This creates the potential for us to build more accurate accounts of the world and of ourselves. I suggest, therefore, that explicit metacognition is a uniquely human ability that has evolved through its enhancement of collaborative decision-making. PMID:22734064

Truck circuits diagnosis for railway lines equipped with an automatic block signalling system

NASA Astrophysics Data System (ADS)

Spunei, E.; Piroi, I.; Muscai, C.; Răduca, E.; Piroi, F.

2018-01-01

This work presents a diagnosis method for detecting track circuits failures on a railway traffic line equipped with an Automatic Block Signalling installation. The diagnosis method uses the installation’s electrical schemas, based on which a series of diagnosis charts have been created. Further, the diagnosis charts were used to develop a software package, CDCBla, which substantially contributes to reducing the diagnosis time and human error during failure remedies. The proposed method can also be used as a training package for the maintenance staff. Since the diagnosis method here does not need signal or measurement inputs, using it does not necessitate additional IT knowledge and can be deployed on a mobile computing device (tablet, smart phone).

Automatic processing influences free recall: converging evidence from the process dissociation procedure and remember-know judgments.

PubMed

McCabe, David P; Roediger, Henry L; Karpicke, Jeffrey D

2011-04-01

Dual-process theories of retrieval suggest that controlled and automatic processing contribute to memory performance. Free recall tests are often considered pure measures of recollection, assessing only the controlled process. We report two experiments demonstrating that automatic processes also influence free recall. Experiment 1 used inclusion and exclusion tasks to estimate recollection and automaticity in free recall, adopting a new variant of the process dissociation procedure. Dividing attention during study selectively reduced the recollection estimate but did not affect the automatic component. In Experiment 2, we replicated the results of Experiment 1, and subjects additionally reported remember-know-guess judgments during recall in the inclusion condition. In the latter task, dividing attention during study reduced remember judgments for studied items, but know responses were unaffected. Results from both methods indicated that free recall is partly driven by automatic processes. Thus, we conclude that retrieval in free recall tests is not driven solely by conscious recollection (or remembering) but also by automatic influences of the same sort believed to drive priming on implicit memory tests. Sometimes items come to mind without volition in free recall.

A quantitative image cytometry technique for time series or population analyses of signaling networks.

PubMed

Ozaki, Yu-ichi; Uda, Shinsuke; Saito, Takeshi H; Chung, Jaehoon; Kubota, Hiroyuki; Kuroda, Shinya

2010-04-01

Modeling of cellular functions on the basis of experimental observation is increasingly common in the field of cellular signaling. However, such modeling requires a large amount of quantitative data of signaling events with high spatio-temporal resolution. A novel technique which allows us to obtain such data is needed for systems biology of cellular signaling. We developed a fully automatable assay technique, termed quantitative image cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision image-processing algorithm for cell identification. With the aid of an automated sample preparation system, this device can quantify protein expression, phosphorylation and localization with subcellular resolution at one-minute intervals. The signaling activities quantified by the assay system showed good correlation with, as well as comparable reproducibility to, western blot analysis. Taking advantage of the high spatio-temporal resolution, we investigated the signaling dynamics of the ERK pathway in PC12 cells. The QIC technique appears as a highly quantitative and versatile technique, which can be a convenient replacement for the most conventional techniques including western blot, flow cytometry and live cell imaging. Thus, the QIC technique can be a powerful tool for investigating the systems biology of cellular signaling.

A Modified Empirical Wavelet Transform for Acoustic Emission Signal Decomposition in Structural Health Monitoring.

PubMed

Dong, Shaopeng; Yuan, Mei; Wang, Qiusheng; Liang, Zhiling

2018-05-21

The acoustic emission (AE) method is useful for structural health monitoring (SHM) of composite structures due to its high sensitivity and real-time capability. The main challenge, however, is how to classify the AE data into different failure mechanisms because the detected signals are affected by various factors. Empirical wavelet transform (EWT) is a solution for analyzing the multi-component signals and has been used to process the AE data. In order to solve the spectrum separation problem of the AE signals, this paper proposes a novel modified separation method based on local window maxima (LWM) algorithm. It searches the local maxima of the Fourier spectrum in a proper window, and automatically determines the boundaries of spectrum segmentations, which helps to eliminate the impact of noise interference or frequency dispersion in the detected signal and obtain the meaningful empirical modes that are more related to the damage characteristics. Additionally, both simulation signal and AE signal from the composite structures are used to verify the effectiveness of the proposed method. Finally, the experimental results indicate that the proposed method performs better than the original EWT method in identifying different damage mechanisms of composite structures.

A Modified Empirical Wavelet Transform for Acoustic Emission Signal Decomposition in Structural Health Monitoring

PubMed Central

Dong, Shaopeng; Yuan, Mei; Wang, Qiusheng; Liang, Zhiling

2018-01-01

The acoustic emission (AE) method is useful for structural health monitoring (SHM) of composite structures due to its high sensitivity and real-time capability. The main challenge, however, is how to classify the AE data into different failure mechanisms because the detected signals are affected by various factors. Empirical wavelet transform (EWT) is a solution for analyzing the multi-component signals and has been used to process the AE data. In order to solve the spectrum separation problem of the AE signals, this paper proposes a novel modified separation method based on local window maxima (LWM) algorithm. It searches the local maxima of the Fourier spectrum in a proper window, and automatically determines the boundaries of spectrum segmentations, which helps to eliminate the impact of noise interference or frequency dispersion in the detected signal and obtain the meaningful empirical modes that are more related to the damage characteristics. Additionally, both simulation signal and AE signal from the composite structures are used to verify the effectiveness of the proposed method. Finally, the experimental results indicate that the proposed method performs better than the original EWT method in identifying different damage mechanisms of composite structures. PMID:29883411

Automatic Classification of Extensive Aftershock Sequences Using Empirical Matched Field Processing

NASA Astrophysics Data System (ADS)

Gibbons, Steven J.; Harris, David B.; Kværna, Tormod; Dodge, Douglas A.

2013-04-01

The aftershock sequences that follow large earthquakes create considerable problems for data centers attempting to produce comprehensive event bulletins in near real-time. The greatly increased number of events which require processing can overwhelm analyst resources and reduce the capacity for analyzing events of monitoring interest. This exacerbates a potentially reduced detection capability at key stations, due the noise generated by the sequence, and a deterioration in the quality of the fully automatic preliminary event bulletins caused by the difficulty in associating the vast numbers of closely spaced arrivals over the network. Considerable success has been enjoyed by waveform correlation methods for the automatic identification of groups of events belonging to the same geographical source region, facilitating the more time-efficient analysis of event ensembles as opposed to individual events. There are, however, formidable challenges associated with the automation of correlation procedures. The signal generated by a very large earthquake seldom correlates well enough with the signals generated by far smaller aftershocks for a correlation detector to produce statistically significant triggers at the correct times. Correlation between events within clusters of aftershocks is significantly better, although the issues of when and how to initiate new pattern detectors are still being investigated. Empirical Matched Field Processing (EMFP) is a highly promising method for detecting event waveforms suitable as templates for correlation detectors. EMFP is a quasi-frequency-domain technique that calibrates the spatial structure of a wavefront crossing a seismic array in a collection of narrow frequency bands. The amplitude and phase weights that result are applied in a frequency-domain beamforming operation that compensates for scattering and refraction effects not properly modeled by plane-wave beams. It has been demonstrated to outperform waveform correlation as a classifier of ripple-fired mining blasts since the narrowband procedure is insensitive to differences in the source-time functions. For sequences in which the spectral content and time-histories of the signals from the main shock and aftershocks vary greatly, the spatial structure calibrated by EMFP is an invariant that permits reliable detection of events in the specific source region. Examples from the 2005 Kashmir and 2011 Van earthquakes demonstrate how EMFP templates from the main events detect arrivals from the aftershock sequences with high sensitivity and exceptionally low false alarm rates. Classical waveform correlation detectors are demonstrated to fail for these examples. Even arrivals with SNR below unity can produce significant EMFP triggers as the spatial pattern of the incoming wavefront is identified, leading to robust detections at a greater number of stations and potentially more reliable automatic bulletins. False EMFP triggers are readily screened by scanning a space of phase shifts relative to the imposed template. EMFP has the potential to produce a rapid and robust overview of the evolving aftershock sequence such that correlation and subspace detectors can be applied semi-autonomously, with well-chosen parameter specifications, to identify and classify clusters of very closely spaced aftershocks.

Four-Channel Biosignal Analysis and Feature Extraction for Automatic Emotion Recognition

NASA Astrophysics Data System (ADS)

Kim, Jonghwa; André, Elisabeth

This paper investigates the potential of physiological signals as a reliable channel for automatic recognition of user's emotial state. For the emotion recognition, little attention has been paid so far to physiological signals compared to audio-visual emotion channels such as facial expression or speech. All essential stages of automatic recognition system using biosignals are discussed, from recording physiological dataset up to feature-based multiclass classification. Four-channel biosensors are used to measure electromyogram, electrocardiogram, skin conductivity and respiration changes. A wide range of physiological features from various analysis domains, including time/frequency, entropy, geometric analysis, subband spectra, multiscale entropy, etc., is proposed in order to search the best emotion-relevant features and to correlate them with emotional states. The best features extracted are specified in detail and their effectiveness is proven by emotion recognition results.

Automatic Tuning Matching Cycler (ATMC) in situ NMR spectroscopy as a novel approach for real-time investigations of Li- and Na-ion batteries

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

Pecher, Oliver; Bayley, Paul M.; Liu, Hao

We have developed and explored the use of a new Automatic Tuning Matching Cycler (ATMC) in situ NMR probe system to track the formation of intermediate phases and investigate electrolyte decomposition during electrochemical cycling of Li- and Na-ion batteries (LIBs and NIBs). The new approach addresses many of the issues arising during in situ NMR, e.g., significantly different shifts of the multi-component samples, changing sample conditions (such as the magnetic susceptibility and conductivity) during cycling, signal broadening due to paramagnetism as well as interferences between the NMR and external cycler circuit that might impair the experiments. We provide practical insightmore » into how to conduct ATMC in situ NMR experiments and discuss applications of the methodology to LiFePO4 (LFP) and Na3V2(PO4)2F3 cathodes as well as Na metal anodes. Automatic frequency sweep 7Li in situ NMR reveals significant changes of the strongly paramagnetic broadened LFP line shape in agreement with the structural changes due to delithiation. Additionally, 31P in situ NMR shows a full separation of the electrolyte and cathode NMR signals and is a key feature for a deeper understanding of the processes occurring during charge/discharge on the local atomic scale of NMR. 31P in situ NMR with “on-the-fly” re-calibrated, varying carrier frequencies on Na3V2(PO4)2F3 as a cathode in a NIB enabled the detection of different P signals within a huge frequency range of 4000 ppm. The experiments show a significant shift and changes in the number as well as intensities of 31P signals during desodiation/sodiation of the cathode. The in situ experiments reveal changes of local P environments that in part have not been seen in ex situ NMR investigations. Furthermore, we applied ATMC 23Na in situ NMR on symmetrical Na–Na cells during galvanostatic plating. An automatic adjustment of the NMR carrier frequency during the in situ experiment ensured on-resonance conditions for the Na metal and electrolyte peak, respectively. Thus, interleaved measurements with different optimal NMR set-ups for the metal and electrolyte, respectively, became possible. This allowed the formation of different Na metal species as well as a quantification of electrolyte consumption during the electrochemical experiment to be monitored. The new approach is likely to benefit a further understanding of Na-ion battery chemistries.« less

Automatic Tuning Matching Cycler (ATMC) in situ NMR spectroscopy as a novel approach for real-time investigations of Li- and Na-ion batteries

NASA Astrophysics Data System (ADS)

Pecher, Oliver; Bayley, Paul M.; Liu, Hao; Liu, Zigeng; Trease, Nicole M.; Grey, Clare P.

2016-04-01

We have developed and explored the use of a new Automatic Tuning Matching Cycler (ATMC) in situ NMR probe system to track the formation of intermediate phases and investigate electrolyte decomposition during electrochemical cycling of Li- and Na-ion batteries (LIBs and NIBs). The new approach addresses many of the issues arising during in situ NMR, e.g., significantly different shifts of the multi-component samples, changing sample conditions (such as the magnetic susceptibility and conductivity) during cycling, signal broadening due to paramagnetism as well as interferences between the NMR and external cycler circuit that might impair the experiments. We provide practical insight into how to conduct ATMC in situ NMR experiments and discuss applications of the methodology to LiFePO4 (LFP) and Na3V2(PO4)2F3 cathodes as well as Na metal anodes. Automatic frequency sweep 7Li in situ NMR reveals significant changes of the strongly paramagnetic broadened LFP line shape in agreement with the structural changes due to delithiation. Additionally, 31P in situ NMR shows a full separation of the electrolyte and cathode NMR signals and is a key feature for a deeper understanding of the processes occurring during charge/discharge on the local atomic scale of NMR. 31P in situ NMR with "on-the-fly" re-calibrated, varying carrier frequencies on Na3V2(PO4)2F3 as a cathode in a NIB enabled the detection of different P signals within a huge frequency range of 4000 ppm. The experiments show a significant shift and changes in the number as well as intensities of 31P signals during desodiation/sodiation of the cathode. The in situ experiments reveal changes of local P environments that in part have not been seen in ex situ NMR investigations. Furthermore, we applied ATMC 23Na in situ NMR on symmetrical Na-Na cells during galvanostatic plating. An automatic adjustment of the NMR carrier frequency during the in situ experiment ensured on-resonance conditions for the Na metal and electrolyte peak, respectively. Thus, interleaved measurements with different optimal NMR set-ups for the metal and electrolyte, respectively, became possible. This allowed the formation of different Na metal species as well as a quantification of electrolyte consumption during the electrochemical experiment to be monitored. The new approach is likely to benefit a further understanding of Na-ion battery chemistries.

Sensor, signal, and image informatics - state of the art and current topics.

PubMed

Lehmann, T M; Aach, T; Witte, H

2006-01-01

The number of articles published annually in the fields of biomedical signal and image acquisition and processing is increasing. Based on selected examples, this survey aims at comprehensively demonstrating the recent trends and developments. Four articles are selected for biomedical data acquisition covering topics such as dose saving in CT, C-arm X-ray imaging systems for volume imaging, and the replacement of dose-intensive CT-based diagnostic with harmonic ultrasound imaging. Regarding biomedical signal analysis (BSA), the four selected articles discuss the equivalence of different time-frequency approaches for signal analysis, an application to Cochlea implants, where time-frequency analysis is applied for controlling the replacement system, recent trends for fusion of different modalities, and the role of BSA as part of a brain machine interfaces. To cover the broad spectrum of publications in the field of biomedical image processing, six papers are focused. Important topics are content-based image retrieval in medical applications, automatic classification of tongue photographs from traditional Chinese medicine, brain perfusion analysis in single photon emission computed tomography (SPECT), model-based visualization of vascular trees, and virtual surgery, where enhanced visualization and haptic feedback techniques are combined with a sphere-filled model of the organ. The selected papers emphasize the five fields forming the chain of biomedical data processing: (1) data acquisition, (2) data reconstruction and pre-processing, (3) data handling, (4) data analysis, and (5) data visualization. Fields 1 and 2 form the sensor informatics, while fields 2 to 5 form signal or image informatics with respect to the nature of the data considered. Biomedical data acquisition and pre-processing, as well as data handling, analysis and visualization aims at providing reliable tools for decision support that improve the quality of health care. Comprehensive evaluation of the processing methods and their reliable integration in routine applications are future challenges in the field of sensor, signal and image informatics.

An independent software system for the analysis of dynamic MR images.

PubMed

Torheim, G; Lombardi, M; Rinck, P A

1997-01-01

A computer system for the manual, semi-automatic, and automatic analysis of dynamic MR images was to be developed on UNIX and personal computer platforms. The system was to offer an integrated and standardized way of performing both image processing and analysis that was independent of the MR unit used. The system consists of modules that are easily adaptable to special needs. Data from MR units or other diagnostic imaging equipment in techniques such as CT, ultrasonography, or nuclear medicine can be processed through the ACR-NEMA/DICOM standard file formats. A full set of functions is available, among them cine-loop visual analysis, and generation of time-intensity curves. Parameters such as cross-correlation coefficients, area under the curve, peak/maximum intensity, wash-in and wash-out slopes, time to peak, and relative signal intensity/contrast enhancement can be calculated. Other parameters can be extracted by fitting functions like the gamma-variate function. Region-of-interest data and parametric values can easily be exported. The system has been successfully tested in animal and patient examinations.