Intelligent Signal Processing for Active Control
1992-06-17
FUNDING NUMSI Intelligent Signal Processing for Active Control C-NO001489-J-1633 G. AUTHOR(S) P.A. Ramamoorthy 7. P2RFORMING ORGANIZATION NAME(S) AND...unclassified .unclassified unclassified L . I mu-. W UNIVERSITY OF CINCINNATI COLLEGE OF ENGINEERING Intelligent Signal Processing For Rctiue Control...NAURI RESEARCH Conkact No: NO1489-J-1633 P.L: P.A.imoodh Intelligent Signal Processing For Active Control 1 Executive Summary The thrust of this
Smart Prosthetic Hand Technology - Phase 2
2011-05-01
identification and estimation, hand motion estimation, intelligent embedded systems and control, robotic hand and biocompatibility and signaling. The...Smart Prosthetics, Bio- Robotics , Intelligent EMG Signal Processing, Embedded Systems and Intelligent Control, Inflammatory Responses of Cells, Toxicity...estimation, intelligent embedded systems and control, robotic hand and biocompatibility and signaling. The developed identification algorithm using a new
Machine listening intelligence
NASA Astrophysics Data System (ADS)
Cella, C. E.
2017-05-01
This manifesto paper will introduce machine listening intelligence, an integrated research framework for acoustic and musical signals modelling, based on signal processing, deep learning and computational musicology.
Relationship Among Signal Fidelity, Hearing Loss, and Working Memory for Digital Noise Suppression.
Arehart, Kathryn; Souza, Pamela; Kates, James; Lunner, Thomas; Pedersen, Michael Syskind
2015-01-01
This study considered speech modified by additive babble combined with noise-suppression processing. The purpose was to determine the relative importance of the signal modifications, individual peripheral hearing loss, and individual cognitive capacity on speech intelligibility and speech quality. The participant group consisted of 31 individuals with moderate high-frequency hearing loss ranging in age from 51 to 89 years (mean = 69.6 years). Speech intelligibility and speech quality were measured using low-context sentences presented in babble at several signal-to-noise ratios. Speech stimuli were processed with a binary mask noise-suppression strategy with systematic manipulations of two parameters (error rate and attenuation values). The cumulative effects of signal modification produced by babble and signal processing were quantified using an envelope-distortion metric. Working memory capacity was assessed with a reading span test. Analysis of variance was used to determine the effects of signal processing parameters on perceptual scores. Hierarchical linear modeling was used to determine the role of degree of hearing loss and working memory capacity in individual listener response to the processed noisy speech. The model also considered improvements in envelope fidelity caused by the binary mask and the degradations to envelope caused by error and noise. The participants showed significant benefits in terms of intelligibility scores and quality ratings for noisy speech processed by the ideal binary mask noise-suppression strategy. This benefit was observed across a range of signal-to-noise ratios and persisted when up to a 30% error rate was introduced into the processing. Average intelligibility scores and average quality ratings were well predicted by an objective metric of envelope fidelity. Degree of hearing loss and working memory capacity were significant factors in explaining individual listener's intelligibility scores for binary mask processing applied to speech in babble. Degree of hearing loss and working memory capacity did not predict listeners' quality ratings. The results indicate that envelope fidelity is a primary factor in determining the combined effects of noise and binary mask processing for intelligibility and quality of speech presented in babble noise. Degree of hearing loss and working memory capacity are significant factors in explaining variability in listeners' speech intelligibility scores but not in quality ratings.
2013-09-01
Office of the Inspector General OSINT Open Source Intelligence PPD Presidential Policy Directive SIGINT Signals Intelligence SLFC State/Local Fusion...Geospatial Intelligence (GEOINT) from Geographic Information Systems (GIS), and Open Source Intelligence ( OSINT ) from Social Media. GIS is widely...and monitor make it a feasible tool to capitalize on for OSINT . A formalized EM intelligence process would help expedite the processing of such
Hernandez, Wilmar
2007-01-01
In this paper a survey on recent applications of optimal signal processing techniques to improve the performance of mechanical sensors is made. Here, a comparison between classical filters and optimal filters for automotive sensors is made, and the current state of the art of the application of robust and optimal control and signal processing techniques to the design of the intelligent (or smart) sensors that today's cars need is presented through several experimental results that show that the fusion of intelligent sensors and optimal signal processing techniques is the clear way to go. However, the switch between the traditional methods of designing automotive sensors and the new ones cannot be done overnight because there are some open research issues that have to be solved. This paper draws attention to one of the open research issues and tries to arouse researcher's interest in the fusion of intelligent sensors and optimal signal processing techniques.
Signals Intelligence - Processing - Analysis - Classification
2009-10-01
Example: Language identification from audio signals. In a certain mission, a set of languages seems important beforehand. These languages will – with a...Uebler, Ulla (2003) The Visualisation of Diverse Intelligence. In Proceedings NATO (Research and Technology Agency) conference on “Military Data
Moret-Bonillo, Vicente; Alvarez-Estévez, Diego; Fernández-Leal, Angel; Hernández-Pereira, Elena
2014-01-01
This work deals with the development of an intelligent approach for clinical decision making in the diagnosis of the Sleep Apnea/Hypopnea Syndrome, SAHS, from the analysis of respiratory signals and oxygen saturation in arterial blood, SaO2. In order to accomplish the task the proposed approach makes use of different artificial intelligence techniques and reasoning processes being able to deal with imprecise data. These reasoning processes are based on fuzzy logic and on temporal analysis of the information. The developed approach also takes into account the possibility of artifacts in the monitored signals. Detection and characterization of signal artifacts allows detection of false positives. Identification of relevant diagnostic patterns and temporal correlation of events is performed through the implementation of temporal constraints.
Moret-Bonillo, Vicente; Alvarez-Estévez, Diego; Fernández-Leal, Angel; Hernández-Pereira, Elena
2014-01-01
This work deals with the development of an intelligent approach for clinical decision making in the diagnosis of the Sleep Apnea/Hypopnea Syndrome, SAHS, from the analysis of respiratory signals and oxygen saturation in arterial blood, SaO2. In order to accomplish the task the proposed approach makes use of different artificial intelligence techniques and reasoning processes being able to deal with imprecise data. These reasoning processes are based on fuzzy logic and on temporal analysis of the information. The developed approach also takes into account the possibility of artifacts in the monitored signals. Detection and characterization of signal artifacts allows detection of false positives. Identification of relevant diagnostic patterns and temporal correlation of events is performed through the implementation of temporal constraints. PMID:25035712
Working memory, age, and hearing loss: susceptibility to hearing aid distortion.
Arehart, Kathryn H; Souza, Pamela; Baca, Rosalinda; Kates, James M
2013-01-01
Hearing aids use complex processing intended to improve speech recognition. Although many listeners benefit from such processing, it can also introduce distortion that offsets or cancels intended benefits for some individuals. The purpose of the present study was to determine the effects of cognitive ability (working memory) on individual listeners' responses to distortion caused by frequency compression applied to noisy speech. The present study analyzed a large data set of intelligibility scores for frequency-compressed speech presented in quiet and at a range of signal-to-babble ratios. The intelligibility data set was based on scores from 26 adults with hearing loss with ages ranging from 62 to 92 years. The listeners were grouped based on working memory ability. The amount of signal modification (distortion) caused by frequency compression and noise was measured using a sound quality metric. Analysis of variance and hierarchical linear modeling were used to identify meaningful differences between subject groups as a function of signal distortion caused by frequency compression and noise. Working memory was a significant factor in listeners' intelligibility of sentences presented in babble noise and processed with frequency compression based on sinusoidal modeling. At maximum signal modification (caused by both frequency compression and babble noise), the factor of working memory (when controlling for age and hearing loss) accounted for 29.3% of the variance in intelligibility scores. Combining working memory, age, and hearing loss accounted for a total of 47.5% of the variability in intelligibility scores. Furthermore, as the total amount of signal distortion increased, listeners with higher working memory performed better on the intelligibility task than listeners with lower working memory did. Working memory is a significant factor in listeners' responses to total signal distortion caused by cumulative effects of babble noise and frequency compression implemented with sinusoidal modeling. These results, together with other studies focused on wide-dynamic range compression, suggest that older listeners with hearing loss and poor working memory are more susceptible to distortions caused by at least some types of hearing aid signal-processing algorithms and by noise, and that this increased susceptibility should be considered in the hearing aid fitting process.
Characterizing Speech Intelligibility in Noise After Wide Dynamic Range Compression.
Rhebergen, Koenraad S; Maalderink, Thijs H; Dreschler, Wouter A
The effects of nonlinear signal processing on speech intelligibility in noise are difficult to evaluate. Often, the effects are examined by comparing speech intelligibility scores with and without processing measured at fixed signal to noise ratios (SNRs) or by comparing the adaptive measured speech reception thresholds corresponding to 50% intelligibility (SRT50) with and without processing. These outcome measures might not be optimal. Measuring at fixed SNRs can be affected by ceiling or floor effects, because the range of relevant SNRs is not know in advance. The SRT50 is less time consuming, has a fixed performance level (i.e., 50% correct), but the SRT50 could give a limited view, because we hypothesize that the effect of most nonlinear signal processing algorithms at the SRT50 cannot be generalized to other points of the psychometric function. In this article, we tested the value of estimating the entire psychometric function. We studied the effect of wide dynamic range compression (WDRC) on speech intelligibility in stationary, and interrupted speech-shaped noise in normal-hearing subjects, using a fast method-based local linear fitting approach and by two adaptive procedures. The measured performance differences for conditions with and without WDRC for the psychometric functions in stationary noise and interrupted speech-shaped noise show that the effects of WDRC on speech intelligibility are SNR dependent. We conclude that favorable and unfavorable effects of WDRC on speech intelligibility can be missed if the results are presented in terms of SRT50 values only.
[A novel biologic electricity signal measurement based on neuron chip].
Lei, Yinsheng; Wang, Mingshi; Sun, Tongjing; Zhu, Qiang; Qin, Ran
2006-06-01
Neuron chip is a multiprocessor with three pipeline CPU; its communication protocol and control processor are integrated in effect to carry out the function of communication, control, attemper, I/O, etc. A novel biologic electronic signal measurement network system is composed of intelligent measurement nodes with neuron chip at the core. In this study, the electronic signals such as ECG, EEG, EMG and BOS can be synthetically measured by those intelligent nodes, and some valuable diagnostic messages are found. Wavelet transform is employed in this system to analyze various biologic electronic signals due to its strong time-frequency ability of decomposing signal local character. Better effect is gained. This paper introduces the hardware structure of network and intelligent measurement node, the measurement theory and the signal figure of data acquisition and processing.
NASA Astrophysics Data System (ADS)
Miao, Changyun; Shi, Boya; Li, Hongqiang
2008-12-01
A human physiological parameters intelligent clothing is researched with FBG sensor technology. In this paper, the principles and methods of measuring human physiological parameters including body temperature and heart rate in intelligent clothing with distributed FBG are studied, the mathematical models of human physiological parameters measurement are built; the processing method of body temperature and heart rate detection signals is presented; human physiological parameters detection module is designed, the interference signals are filtered out, and the measurement accuracy is improved; the integration of the intelligent clothing is given. The intelligent clothing can implement real-time measurement, processing, storage and output of body temperature and heart rate. It has accurate measurement, portability, low cost, real-time monitoring, and other advantages. The intelligent clothing can realize the non-contact monitoring between doctors and patients, timely find the diseases such as cancer and infectious diseases, and make patients get timely treatment. It has great significance and value for ensuring the health of the elders and the children with language dysfunction.
Intelligent processing of acoustic emission signals
NASA Astrophysics Data System (ADS)
Sachse, Wolfgang; Grabec, Igor
1992-07-01
Recent developments in applying neural-like signal-processing procedures for analyzing acoustic emission signals are summarized. These procedures employ a set of learning signals to develop a memory that can subsequently be utilized to process other signals to recover information about an unknown source. A majority of the current applications to process ultrasonic waveforms are based on multilayered, feed-forward neural networks, trained with some type of back-error propagation rule.
A Binaural Grouping Model for Predicting Speech Intelligibility in Multitalker Environments
Colburn, H. Steven
2016-01-01
Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC) processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model. PMID:27698261
A Binaural Grouping Model for Predicting Speech Intelligibility in Multitalker Environments.
Mi, Jing; Colburn, H Steven
2016-10-03
Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC) processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model. © The Author(s) 2016.
NASA Astrophysics Data System (ADS)
Jia, Feng; Lei, Yaguo; Lin, Jing; Zhou, Xin; Lu, Na
2016-05-01
Aiming to promptly process the massive fault data and automatically provide accurate diagnosis results, numerous studies have been conducted on intelligent fault diagnosis of rotating machinery. Among these studies, the methods based on artificial neural networks (ANNs) are commonly used, which employ signal processing techniques for extracting features and further input the features to ANNs for classifying faults. Though these methods did work in intelligent fault diagnosis of rotating machinery, they still have two deficiencies. (1) The features are manually extracted depending on much prior knowledge about signal processing techniques and diagnostic expertise. In addition, these manual features are extracted according to a specific diagnosis issue and probably unsuitable for other issues. (2) The ANNs adopted in these methods have shallow architectures, which limits the capacity of ANNs to learn the complex non-linear relationships in fault diagnosis issues. As a breakthrough in artificial intelligence, deep learning holds the potential to overcome the aforementioned deficiencies. Through deep learning, deep neural networks (DNNs) with deep architectures, instead of shallow ones, could be established to mine the useful information from raw data and approximate complex non-linear functions. Based on DNNs, a novel intelligent method is proposed in this paper to overcome the deficiencies of the aforementioned intelligent diagnosis methods. The effectiveness of the proposed method is validated using datasets from rolling element bearings and planetary gearboxes. These datasets contain massive measured signals involving different health conditions under various operating conditions. The diagnosis results show that the proposed method is able to not only adaptively mine available fault characteristics from the measured signals, but also obtain superior diagnosis accuracy compared with the existing methods.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mohamed Abdelrahman; roger Haggard; Wagdy Mahmoud
The final goal of this project was the development of a system that is capable of controlling an industrial process effectively through the integration of information obtained through intelligent sensor fusion and intelligent control technologies. The industry of interest in this project was the metal casting industry as represented by cupola iron-melting furnaces. However, the developed technology is of generic type and hence applicable to several other industries. The system was divided into the following four major interacting components: 1. An object oriented generic architecture to integrate the developed software and hardware components @. Generic algorithms for intelligent signal analysismore » and sensor and model fusion 3. Development of supervisory structure for integration of intelligent sensor fusion data into the controller 4. Hardware implementation of intelligent signal analysis and fusion algorithms« less
Li, Junfeng; Yang, Lin; Zhang, Jianping; Yan, Yonghong; Hu, Yi; Akagi, Masato; Loizou, Philipos C
2011-05-01
A large number of single-channel noise-reduction algorithms have been proposed based largely on mathematical principles. Most of these algorithms, however, have been evaluated with English speech. Given the different perceptual cues used by native listeners of different languages including tonal languages, it is of interest to examine whether there are any language effects when the same noise-reduction algorithm is used to process noisy speech in different languages. A comparative evaluation and investigation is taken in this study of various single-channel noise-reduction algorithms applied to noisy speech taken from three languages: Chinese, Japanese, and English. Clean speech signals (Chinese words and Japanese words) were first corrupted by three types of noise at two signal-to-noise ratios and then processed by five single-channel noise-reduction algorithms. The processed signals were finally presented to normal-hearing listeners for recognition. Intelligibility evaluation showed that the majority of noise-reduction algorithms did not improve speech intelligibility. Consistent with a previous study with the English language, the Wiener filtering algorithm produced small, but statistically significant, improvements in intelligibility for car and white noise conditions. Significant differences between the performances of noise-reduction algorithms across the three languages were observed.
Comparing Binaural Pre-processing Strategies I: Instrumental Evaluation.
Baumgärtel, Regina M; Krawczyk-Becker, Martin; Marquardt, Daniel; Völker, Christoph; Hu, Hongmei; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Ernst, Stephan M A; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias
2015-12-30
In a collaborative research project, several monaural and binaural noise reduction algorithms have been comprehensively evaluated. In this article, eight selected noise reduction algorithms were assessed using instrumental measures, with a focus on the instrumental evaluation of speech intelligibility. Four distinct, reverberant scenarios were created to reflect everyday listening situations: a stationary speech-shaped noise, a multitalker babble noise, a single interfering talker, and a realistic cafeteria noise. Three instrumental measures were employed to assess predicted speech intelligibility and predicted sound quality: the intelligibility-weighted signal-to-noise ratio, the short-time objective intelligibility measure, and the perceptual evaluation of speech quality. The results show substantial improvements in predicted speech intelligibility as well as sound quality for the proposed algorithms. The evaluated coherence-based noise reduction algorithm was able to provide improvements in predicted audio signal quality. For the tested single-channel noise reduction algorithm, improvements in intelligibility-weighted signal-to-noise ratio were observed in all but the nonstationary cafeteria ambient noise scenario. Binaural minimum variance distortionless response beamforming algorithms performed particularly well in all noise scenarios. © The Author(s) 2015.
Comparing Binaural Pre-processing Strategies I
Krawczyk-Becker, Martin; Marquardt, Daniel; Völker, Christoph; Hu, Hongmei; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Ernst, Stephan M. A.; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias
2015-01-01
In a collaborative research project, several monaural and binaural noise reduction algorithms have been comprehensively evaluated. In this article, eight selected noise reduction algorithms were assessed using instrumental measures, with a focus on the instrumental evaluation of speech intelligibility. Four distinct, reverberant scenarios were created to reflect everyday listening situations: a stationary speech-shaped noise, a multitalker babble noise, a single interfering talker, and a realistic cafeteria noise. Three instrumental measures were employed to assess predicted speech intelligibility and predicted sound quality: the intelligibility-weighted signal-to-noise ratio, the short-time objective intelligibility measure, and the perceptual evaluation of speech quality. The results show substantial improvements in predicted speech intelligibility as well as sound quality for the proposed algorithms. The evaluated coherence-based noise reduction algorithm was able to provide improvements in predicted audio signal quality. For the tested single-channel noise reduction algorithm, improvements in intelligibility-weighted signal-to-noise ratio were observed in all but the nonstationary cafeteria ambient noise scenario. Binaural minimum variance distortionless response beamforming algorithms performed particularly well in all noise scenarios. PMID:26721920
Jørgensen, Søren; Dau, Torsten
2011-09-01
A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data. The model estimates the speech-to-noise envelope power ratio, SNR(env), at the output of a modulation filterbank and relates this metric to speech intelligibility using the concept of an ideal observer. Predictions were compared to data on the intelligibility of speech presented in stationary speech-shaped noise. The model was further tested in conditions with noisy speech subjected to reverberation and spectral subtraction. Good agreement between predictions and data was found in all cases. For spectral subtraction, an analysis of the model's internal representation of the stimuli revealed that the predicted decrease of intelligibility was caused by the estimated noise envelope power exceeding that of the speech. The classical concept of the speech transmission index fails in this condition. The results strongly suggest that the signal-to-noise ratio at the output of a modulation frequency selective process provides a key measure of speech intelligibility. © 2011 Acoustical Society of America
Research on intelligent machine self-perception method based on LSTM
NASA Astrophysics Data System (ADS)
Wang, Qiang; Cheng, Tao
2018-05-01
In this paper, we use the advantages of LSTM in feature extraction and processing high-dimensional and complex nonlinear data, and apply it to the autonomous perception of intelligent machines. Compared with the traditional multi-layer neural network, this model has memory, can handle time series information of any length. Since the multi-physical domain signals of processing machines have a certain timing relationship, and there is a contextual relationship between states and states, using this deep learning method to realize the self-perception of intelligent processing machines has strong versatility and adaptability. The experiment results show that the method proposed in this paper can obviously improve the sensing accuracy under various working conditions of the intelligent machine, and also shows that the algorithm can well support the intelligent processing machine to realize self-perception.
Design of the intelligent smoke alarm system based on photoelectric smoke
NASA Astrophysics Data System (ADS)
Ma, Jiangfei; Yang, Xiufang; Wang, Peipei
2017-02-01
This paper designed a kind of intelligent smoke alarm system based on photoelectric smoke detector and temperature, The system takes AT89C51 MCU as the core of hardware control and Labview as the host computer monitoring center.The sensor system acquires temperature signals and smoke signals, the MCU control A/D by Sampling and converting the output analog signals , and then the two signals will be uploaded to the host computer through the serial communication. To achieve real-time monitoring of smoke and temperature in the environment, LabVIEW monitoring platform need to hold, process, analysis and display these samping signals. The intelligent smoke alarm system is suitable for large scale shopping malls and other public places, which can greatly reduce the false alarm rate of fire, The experimental results show that the system runs well and can alarm when the setting threshold is reached,and the threshold parameters can be adjusted according to the actual conditions of the field. The system is easy to operate, simple in structure, intelligent, low cost, and with strong practical value.
Two examples of intelligent systems based on smart materials
DOE Office of Scientific and Technical Information (OSTI.GOV)
Unsworth, J.
1994-12-31
Two intelligent systems are described which are based on smart materials. The operation of the systems also rely on conventional well known technologies such as electronics, signal conditioning, signal processing, microprocessors and engineering design. However without the smart materials the development and integration into the intelligent systems would not have been possible. System 1 is a partial discharge monitor for on-line continuous checking of the condition of electrical power transformers. The ultrasonic and radio frequency detectors in this system rely on special piezoelectric composite integrated with a compact annular metal ring. Partial discharges set up ultrasonic and radio frequency signalsmore » which are received by the integrated detectors. The signals are amplified, conditioned, signal processed, the time interval between the two signals measured and the level of partial discharge activity averaged and assessed for numerous pairs and alarms triggered on remote control panels if the level is dangerous. The system has the capability of initiating automatic shutdown of the transformer once it is linked into the control computers of the electrical power authority. System 2 is called a Security Cradle and is an intelligent 3D shield designed to use the properties of electro active polymers to prevent hardware hackers from stealing valuable of sensitive information from memory devices (e.g., EPROMS) housed in computer or microprocessor installations.« less
Speech Intelligibility Predicted from Neural Entrainment of the Speech Envelope.
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.
Search for Extraterrestrial Intelligence (SETI)
NASA Technical Reports Server (NTRS)
Billingham, John
1993-01-01
Various aspects of project SETI are discussed. Some of the topics discussed include spectrum analyzers, signal processing, sky surveys, radiotelescopes, high resolution microwave survey, Deep Space Network, and signal 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.
Lee, Hon Wah; Lo, Yu-Hui; Li, Kuan-Hui; Sung, Wen-Shin; Juan, Chi-Hung
2015-01-01
Building on the theoretical framework that intellectual behavior relies on one's ability to process both task-relevant and task-irrelevant information, this study aimed to empirically investigate the association of response inhibition with intelligence in preschool children's development. In a sample of 152 typically developing children aged between 3.6 and 6.6 years, we found evidence that suggests that inhibitory control is linked to age-related differences in intelligence. Stop-signal inhibition improved at a rate similar to the age-related changes in Verbal IQ. Components of variance analyses revealed that stop-signal reaction time predicted a larger proportion of the age-related variance in children's verbal intelligence than non-age-related variance. Results are discussed with respect to possible explanations for this intriguing relationship between response inhibition and the verbal aspects of intelligence. PMID:26113838
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.
NASA Astrophysics Data System (ADS)
Lanzalaco, Felix; Pissanetzky, Sergio
2013-12-01
A recent theory of physical information based on the fundamental principles of causality and thermodynamics has proposed that a large number of observable life and intelligence signals can be described in terms of the Causal Mathematical Logic (CML), which is proposed to encode the natural principles of intelligence across any physical domain and substrate. We attempt to expound the current definition of CML, the "Action functional" as a theory in terms of its ability to possess a superior explanatory power for the current neuroscientific data we use to measure the mammalian brains "intelligence" processes at its most general biophysical level. Brain simulation projects define their success partly in terms of the emergence of "non-explicitly programmed" complex biophysical signals such as self-oscillation and spreading cortical waves. Here we propose to extend the causal theory to predict and guide the understanding of these more complex emergent "intelligence Signals". To achieve this we review whether causal logic is consistent with, can explain and predict the function of complete perceptual processes associated with intelligence. Primarily those are defined as the range of Event Related Potentials (ERP) which include their primary subcomponents; Event Related Desynchronization (ERD) and Event Related Synchronization (ERS). This approach is aiming for a universal and predictive logic for neurosimulation and AGi. The result of this investigation has produced a general "Information Engine" model from translation of the ERD and ERS. The CML algorithm run in terms of action cost predicts ERP signal contents and is consistent with the fundamental laws of thermodynamics. A working substrate independent natural information logic would be a major asset. An information theory consistent with fundamental physics can be an AGi. It can also operate within genetic information space and provides a roadmap to understand the live biophysical operation of the phenotype
NASA Astrophysics Data System (ADS)
Su, Zhongqing; Ye, Lin
2004-08-01
The practical utilization of elastic waves, e.g. Rayleigh-Lamb waves, in high-performance structural health monitoring techniques is somewhat impeded due to the complicated wave dispersion phenomena, the existence of multiple wave modes, the high susceptibility to diverse interferences, the bulky sampled data and the difficulty in signal interpretation. An intelligent signal processing and pattern recognition (ISPPR) approach using the wavelet transform and artificial neural network algorithms was developed; this was actualized in a signal processing package (SPP). The ISPPR technique comprehensively functions as signal filtration, data compression, characteristic extraction, information mapping and pattern recognition, capable of extracting essential yet concise features from acquired raw wave signals and further assisting in structural health evaluation. For validation, the SPP was applied to the prediction of crack growth in an alloy structural beam and construction of a damage parameter database for defect identification in CF/EP composite structures. It was clearly apparent that the elastic wave propagation-based damage assessment could be dramatically streamlined by introduction of the ISPPR technique.
Troubleshooting of signal power supply system for Shanghai metro line 7
NASA Astrophysics Data System (ADS)
Lu, Kaixia; Xiao, Jie
2018-03-01
With the rapid development of Urban Rail Transit Signal Technology, the demand of signal power supply system for signal equipment is higher and higher. The signal intelligent power supply panel is the main component of the urban rail traffic signal power supply system. Whether the intelligent power supply panel working or not is directly related to traffic safety. The maintenance of intelligent signal power supply panel is particularly important. Line 7 of Shanghai Metro adopts PMZG Signal Intelligent Power Supply Panel, which is produced by Beijing Jinyujiaxin Polytron Technologies Inc. Maintenance of power supply system mainly includes routine maintenance and troubleshooting. This article will make clear the routine maintenance contents of PMZG Signal Intelligent Power Supply Panel, and put forward the common fault information and troubleshooting methods of PMZG Signal Intelligent Power Supply Panel. In accordance with the steps of fault handling, the faults can be eliminated in the shortest possible time, and PMZG Signal Intelligent Power Supply Panel can be quickly restored to normal working state.
Yumba, Wycliffe Kabaywe
2017-01-01
Previous studies have demonstrated that successful listening with advanced signal processing in digital hearing aids is associated with individual cognitive capacity, particularly working memory capacity (WMC). This study aimed to examine the relationship between cognitive abilities (cognitive processing speed and WMC) and individual listeners’ responses to digital signal processing settings in adverse listening conditions. A total of 194 native Swedish speakers (83 women and 111 men), aged 33–80 years (mean = 60.75 years, SD = 8.89), with bilateral, symmetrical mild to moderate sensorineural hearing loss who had completed a lexical decision speed test (measuring cognitive processing speed) and semantic word-pair span test (SWPST, capturing WMC) participated in this study. The Hagerman test (capturing speech recognition in noise) was conducted using an experimental hearing aid with three digital signal processing settings: (1) linear amplification without noise reduction (NoP), (2) linear amplification with noise reduction (NR), and (3) non-linear amplification without NR (“fast-acting compression”). The results showed that cognitive processing speed was a better predictor of speech intelligibility in noise, regardless of the types of signal processing algorithms used. That is, there was a stronger association between cognitive processing speed and NR outcomes and fast-acting compression outcomes (in steady state noise). We observed a weaker relationship between working memory and NR, but WMC did not relate to fast-acting compression. WMC was a relatively weaker predictor of speech intelligibility in noise. These findings might have been different if the participants had been provided with training and or allowed to acclimatize to binary masking noise reduction or fast-acting compression. PMID:28861009
Processing Techniques for Intelligibility Improvement to Speech with Co-Channel Interference.
1983-09-01
processing was found to be always less than in the original unprocessed co-channel sig- nali also as the length of the comb filter increased, the...7 D- i35 702 PROCESSING TECHNIQUES FOR INTELLIGIBILITY IMPRO EMENT 1.TO SPEECH WITH CO-C..(U) SIGNAL TECHNOLOGY INC GOLETACA B A HANSON ET AL SEP...11111111122 11111.25 1111 .4 111.6 MICROCOPY RESOLUTION TEST CHART NATIONAL BUREAU Of STANDARDS- 1963-A RA R.83-225 Set ,’ember 1983 PROCESSING
Extraterrestrial intelligence: an observational approach.
Murray, B; Gulkis, S; Edelson, R E
1978-02-03
The microwave region of the electromagnetic spectrum, a plausible regime for signals from extraterrestrial intelligences, is largely unexplored. With new technology, particularly in data processing and low-noise reception, surveys can be conducted over broad regions of frequency and space with existing antennas at flux densities plausible for interstellar signals. An all-sky, broad-band survey lasting perhaps 5 years can be structured so that even negative results would establish significant boundaries on the regime in which such signals may be found. The technology and techniques developed and much of the data acquired would be applicable to radio astronomy and deep-space communications.
Is general intelligence little more than the speed of higher-order processing?
Schubert, Anna-Lena; Hagemann, Dirk; Frischkorn, Gidon T
2017-10-01
Individual differences in the speed of information processing have been hypothesized to give rise to individual differences in general intelligence. Consistent with this hypothesis, reaction times (RTs) and latencies of event-related potential have been shown to be moderately associated with intelligence. These associations have been explained either in terms of individual differences in some brain-wide property such as myelination, the speed of neural oscillations, or white-matter tract integrity, or in terms of individual differences in specific processes such as the signal-to-noise ratio in evidence accumulation, executive control, or the cholinergic system. Here we show in a sample of 122 participants, who completed a battery of RT tasks at 2 laboratory sessions while an EEG was recorded, that more intelligent individuals have a higher speed of higher-order information processing that explains about 80% of the variance in general intelligence. Our results do not support the notion that individuals with higher levels of general intelligence show advantages in some brain-wide property. Instead, they suggest that more intelligent individuals benefit from a more efficient transmission of information from frontal attention and working memory processes to temporal-parietal processes of memory storage. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)
NASA Astrophysics Data System (ADS)
Raskovic, Dejan
Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.
Hopkins, Kathryn; King, Andrew; Moore, Brian C J
2012-09-01
Hearing aids use amplitude compression to compensate for the effects of loudness recruitment. The compression speed that gives the best speech intelligibility varies among individuals. Moore [(2008). Trends Amplif. 12, 300-315] suggested that an individual's sensitivity to temporal fine structure (TFS) information may affect which compression speed gives most benefit. This hypothesis was tested using normal-hearing listeners with a simulated hearing loss. Sentences in a competing talker background were processed using multi-channel fast or slow compression followed by a simulation of threshold elevation and loudness recruitment. Signals were either tone vocoded with 1-ERB(N)-wide channels (where ERB(N) is the bandwidth of normal auditory filters) to remove the original TFS information, or not processed further. In a second experiment, signals were vocoded with either 1 - or 2-ERB(N)-wide channels, to test whether the available spectral detail affects the optimal compression speed. Intelligibility was significantly better for fast than slow compression regardless of vocoder channel bandwidth. The results suggest that the availability of original TFS or detailed spectral information does not affect the optimal compression speed. This conclusion is tentative, since while the vocoder processing removed the original TFS information, listeners may have used the altered TFS in the vocoded signals.
On the design of a postprocessor for a search for extraterrestrial intelligence /SETI/ system
NASA Technical Reports Server (NTRS)
Healy, T. J.; Seeger, C. L.; Stull, M. A.
1979-01-01
The design of an on-line postprocessor for a search for extraterrestrial intelligence (SETI) system is described. Signal processing tasks of the postprocessor include: (1) analysis of power level, phase coherence, and state of polarization of single-channel signals in a search for significant signals; (2) grouping or aggregation of adjacent channel data, time averaging of data; and (3) the detection of drifting and modulated signals. Control functions include multichannel spectrum analyzer frequency and clock control, system calibration and selfdiagnostic, control of data flow to and from short-term and long-term (archival) memories, and operation of detection subsystems, such as a visual display and a tunable receiver.
Balancing Information Analysis and Decision Value: A Model to Exploit the Decision Process
2011-12-01
technical intelli- gence e.g. signals and sensors (SIGINT and MASINT), imagery (!MINT), as well and human and open source intelligence (HUMINT and OSINT ...Clark 2006). The ability to capture large amounts of da- ta and the plenitude of modem intelligence information sources provides a rich cache of...many tech- niques for managing information collected and derived from these sources , the exploitation of intelligence assets for decision-making
Human high intelligence is involved in spectral redshift of biophotonic activities in the brain
Wang, Niting; Li, Zehua; Xiao, Fangyan; Dai, Jiapei
2016-01-01
Human beings hold higher intelligence than other animals on Earth; however, it is still unclear which brain properties might explain the underlying mechanisms. The brain is a major energy-consuming organ compared with other organs. Neural signal communications and information processing in neural circuits play an important role in the realization of various neural functions, whereas improvement in cognitive function is driven by the need for more effective communication that requires less energy. Combining the ultraweak biophoton imaging system (UBIS) with the biophoton spectral analysis device (BSAD), we found that glutamate-induced biophotonic activities and transmission in the brain, which has recently been demonstrated as a novel neural signal communication mechanism, present a spectral redshift from animals (in order of bullfrog, mouse, chicken, pig, and monkey) to humans, even up to a near-infrared wavelength (∼865 nm) in the human brain. This brain property may be a key biophysical basis for explaining high intelligence in humans because biophoton spectral redshift could be a more economical and effective measure of biophotonic signal communications and information processing in the human brain. PMID:27432962
Intelligent fiber optic sensor for solution concentration examination
NASA Astrophysics Data System (ADS)
Borecki, Michal; Kruszewski, Jerzy
2003-09-01
This paper presents the working principles of intelligent fiber-optic intensity sensor used for solution concentration examination. The sensor head is the ending of the large core polymer optical fiber. The head works on the reflection intensity basis. The reflected signal level depends on Fresnel reflection and reflection on suspended matter when the head is submersed in solution. The sensor head is mounted on a lift. For detection purposes the signal includes head submerging, submersion, emerging and emergence is measured. This way the viscosity turbidity and refraction coefficient has an effect on measured signal. The signal forthcoming from head is processed electrically in opto-electronic interface. Then it is feed to neural network. The novelty of presented sensor is implementation of neural network that works in generalization mode. The sensor resolution depends on opto-electronic signal conversion precision and neural network learning accuracy. Therefore, the number and quality of points used for learning process is very important. The example sensor application for examination of liquid soap concentration in water is presented in the paper.
Multi-time resolution analysis of speech: evidence from psychophysics
Chait, Maria; Greenberg, Steven; Arai, Takayuki; Simon, Jonathan Z.; Poeppel, David
2015-01-01
How speech signals are analyzed and represented remains a foundational challenge both for cognitive science and neuroscience. A growing body of research, employing various behavioral and neurobiological experimental techniques, now points to the perceptual relevance of both phoneme-sized (10–40 Hz modulation frequency) and syllable-sized (2–10 Hz modulation frequency) units in speech processing. However, it is not clear how information associated with such different time scales interacts in a manner relevant for speech perception. We report behavioral experiments on speech intelligibility employing a stimulus that allows us to investigate how distinct temporal modulations in speech are treated separately and whether they are combined. We created sentences in which the slow (~4 Hz; Slow) and rapid (~33 Hz; Shigh) modulations—corresponding to ~250 and ~30 ms, the average duration of syllables and certain phonetic properties, respectively—were selectively extracted. Although Slow and Shigh have low intelligibility when presented separately, dichotic presentation of Shigh with Slow results in supra-additive performance, suggesting a synergistic relationship between low- and high-modulation frequencies. A second experiment desynchronized presentation of the Slow and Shigh signals. Desynchronizing signals relative to one another had no impact on intelligibility when delays were less than ~45 ms. Longer delays resulted in a steep intelligibility decline, providing further evidence of integration or binding of information within restricted temporal windows. Our data suggest that human speech perception uses multi-time resolution processing. Signals are concurrently analyzed on at least two separate time scales, the intermediate representations of these analyses are integrated, and the resulting bound percept has significant consequences for speech intelligibility—a view compatible with recent insights from neuroscience implicating multi-timescale auditory processing. PMID:26136650
Research and design of intelligent distributed traffic signal light control system based on CAN bus
NASA Astrophysics Data System (ADS)
Chen, Yu
2007-12-01
Intelligent distributed traffic signal light control system was designed based on technologies of infrared, CAN bus, single chip microprocessor (SCM), etc. The traffic flow signal is processed with the core of SCM AT89C51. At the same time, the SCM controls the CAN bus controller SJA1000/transceiver PCA82C250 to build a CAN bus communication system to transmit data. Moreover, up PC realizes to connect and communicate with SCM through USBCAN chip PDIUSBD12. The distributed traffic signal light control system with three control styles of Vehicle flux, remote and PC is designed. This paper introduces the system composition method and parts of hardware/software design in detail.
3 CFR - Reviewing Our Global Signals Intelligence Collection and Communications Technologies
Code of Federal Regulations, 2014 CFR
2014-01-01
... 3 The President 1 2014-01-01 2014-01-01 false Reviewing Our Global Signals Intelligence Collection... August 12, 2013 Reviewing Our Global Signals Intelligence Collection and Communications Technologies Memorandum for the Director of National Intelligence The United States, like all nations, gathers...
Application of Frame Theory in Intelligent Packet-Based Communication Networks
NASA Astrophysics Data System (ADS)
Escobar-Moreira, León A.
2007-09-01
Frames are a stable and redundant representation of signals in a Hilbert space that have been used in signal processing because of their resilience to additive noise, quantization error, and their robustness to losses in packet-based networks [1,2]. Depending on the number of erasures (losses), there are some considerations to be taken into account in order to optimize the frame design. Further discussions will explain the innate characteristics of frames to include intelligence on the packet-based communication devices (routers) to increase their performance under different channel behaviors.
Black-box Brain Experiments, Causal Mathematical Logic, and the Thermodynamics of Intelligence
NASA Astrophysics Data System (ADS)
Pissanetzky, Sergio; Lanzalaco, Felix
2013-12-01
Awareness of the possible existence of a yet-unknown principle of Physics that explains cognition and intelligence does exist in several projects of emulation, simulation, and replication of the human brain currently under way. Brain simulation projects define their success partly in terms of the emergence of non-explicitly programmed biophysical signals such as self-oscillation and spreading cortical waves. We propose that a recently discovered theory of Physics known as Causal Mathematical Logic (CML) that links intelligence with causality and entropy and explains intelligent behavior from first principles, is the missing link. We further propose the theory as a roadway to understanding more complex biophysical signals, and to explain the set of intelligence principles. The new theory applies to information considered as an entity by itself. The theory proposes that any device that processes information and exhibits intelligence must satisfy certain theoretical conditions irrespective of the substrate where it is being processed. The substrate can be the human brain, a part of it, a worm's brain, a motor protein that self-locomotes in response to its environment, a computer. Here, we propose to extend the causal theory to systems in Neuroscience, because of its ability to model complex systems without heuristic approximations, and to predict emerging signals of intelligence directly from the models. The theory predicts the existence of a large number of observables (or "signals"), all of which emerge and can be directly and mathematically calculated from non-explicitly programmed detailed causal models. This approach is aiming for a universal and predictive language for Neuroscience and AGI based on causality and entropy, detailed enough to describe the finest structures and signals of the brain, yet general enough to accommodate the versatility and wholeness of intelligence. Experiments are focused on a black-box as one of the devices described above of which both the input and the output are precisely known, but not the internal implementation. The same input is separately supplied to a causal virtual machine, and the calculated output is compared with the measured output. The virtual machine, described in a previous paper, is a computer implementation of CML, fixed for all experiments and unrelated to the device in the black box. If the two outputs are equivalent, then the experiment has quantitatively succeeded and conclusions can be drawn regarding details of the internal implementation of the device. Several small black-box experiments were successfully performed and demonstrated the emergence of non-explicitly programmed cognitive function in each case
NASA Technical Reports Server (NTRS)
Mckee, James W.
1988-01-01
This final report describes the accomplishments of the General Purpose Intelligent Sensor Interface task of the Applications of Artificial Intelligence to Space Station grant for the period from October 1, 1987 through September 30, 1988. Portions of the First Biannual Report not revised will not be included but only referenced. The goal is to develop an intelligent sensor system that will simplify the design and development of expert systems using sensors of the physical phenomena as a source of data. This research will concentrate on the integration of image processing sensors and voice processing sensors with a computer designed for expert system development. The result of this research will be the design and documentation of a system in which the user will not need to be an expert in such areas as image processing algorithms, local area networks, image processor hardware selection or interfacing, television camera selection, voice recognition hardware selection, or analog signal processing. The user will be able to access data from video or voice sensors through standard LISP statements without any need to know about the sensor hardware or software.
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.
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.
The Scientific Search for Extraterrestrials
NASA Astrophysics Data System (ADS)
Shostack, S.
2001-05-01
The premise of intelligent life elsewhere in the cosmos is an old one, but has recently gained new impetus from discoveries that suggest that planets are common and biologically friendly habitats could be plentiful. Since there is some chance that a large number of sentient societies could inhabit the galaxy, a small group of scientists have undertaken the research activity known as SETI, the Search for Extraterrestrial Intelligence. SETI's methods are well founded in both astronomy and engineering: it is an attempt to find technically sophisticated civilizations in situ by looking for narrow-band radio signals or short pulses of laser light from other star systems. The rapid increase in SETI capability gives some reason to expect that a signal detection might occur early in the 21st century. If so, it would demonstrate that the natural processes that have produced intelligence on this planet have spawned functionally similar intelligence elsewhere. This would be further evidence that not only physics and chemistry are universal, but biology and the evolution of intelligence are also cosmic, rather than merely earthly phenomena.
NASA Astrophysics Data System (ADS)
Miao, Man-Xiang
2007-12-01
By using the photo-voltage characteristics of pyroelectric infrared detector to fulfill signal acquisition, the detecting signal is processed with the core of a single chip microprocessor AT89C51. AT89C51 controls the CAN bus controller SJA1000/transceiver 82C250 to structure CAN bus communication system to transmit data through serial interface MAX232 connected with PC. The intelligent lightening system of urban and rural road traffic was carried out. In this paper, its construction and part's methods of hardware and software design were introduced in detail.
Machine learning based Intelligent cognitive network using fog computing
NASA Astrophysics Data System (ADS)
Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik
2017-05-01
In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.
A novel time-domain signal processing algorithm for real time ventricular fibrillation detection
NASA Astrophysics Data System (ADS)
Monte, G. E.; Scarone, N. C.; Liscovsky, P. O.; Rotter S/N, P.
2011-12-01
This paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologies.
Ibrahim, Iman; Parsa, Vijay; Macpherson, Ewan; Cheesman, Margaret
2013-01-02
Wireless synchronization of the digital signal processing (DSP) features between two hearing aids in a bilateral hearing aid fitting is a fairly new technology. This technology is expected to preserve the differences in time and intensity between the two ears by co-ordinating the bilateral DSP features such as multichannel compression, noise reduction, and adaptive directionality. The purpose of this study was to evaluate the benefits of wireless communication as implemented in two commercially available hearing aids. More specifically, this study measured speech intelligibility and sound localization abilities of normal hearing and hearing impaired listeners using bilateral hearing aids with wireless synchronization of multichannel Wide Dynamic Range Compression (WDRC). Twenty subjects participated; 8 had normal hearing and 12 had bilaterally symmetrical sensorineural hearing loss. Each individual completed the Hearing in Noise Test (HINT) and a sound localization test with two types of stimuli. No specific benefit from wireless WDRC synchronization was observed for the HINT; however, hearing impaired listeners had better localization with the wireless synchronization. Binaural wireless technology in hearing aids may improve localization abilities although the possible effect appears to be small at the initial fitting. With adaptation, the hearing aids with synchronized signal processing may lead to an improvement in localization and speech intelligibility. Further research is required to demonstrate the effect of adaptation to the hearing aids with synchronized signal processing on different aspects of auditory performance.
Neurobiological correlates of emotional intelligence in voice and face perception networks
Karle, Kathrin N; Ethofer, Thomas; Jacob, Heike; Brück, Carolin; Erb, Michael; Lotze, Martin; Nizielski, Sophia; Schütz, Astrid; Wildgruber, Dirk; Kreifelts, Benjamin
2018-01-01
Abstract Facial expressions and voice modulations are among the most important communicational signals to convey emotional information. The ability to correctly interpret this information is highly relevant for successful social interaction and represents an integral component of emotional competencies that have been conceptualized under the term emotional intelligence. Here, we investigated the relationship of emotional intelligence as measured with the Salovey-Caruso-Emotional-Intelligence-Test (MSCEIT) with cerebral voice and face processing using functional and structural magnetic resonance imaging. MSCEIT scores were positively correlated with increased voice-sensitivity and gray matter volume of the insula accompanied by voice-sensitivity enhanced connectivity between the insula and the temporal voice area, indicating generally increased salience of voices. Conversely, in the face processing system, higher MSCEIT scores were associated with decreased face-sensitivity and gray matter volume of the fusiform face area. Taken together, these findings point to an alteration in the balance of cerebral voice and face processing systems in the form of an attenuated face-vs-voice bias as one potential factor underpinning emotional intelligence. PMID:29365199
Neurobiological correlates of emotional intelligence in voice and face perception networks.
Karle, Kathrin N; Ethofer, Thomas; Jacob, Heike; Brück, Carolin; Erb, Michael; Lotze, Martin; Nizielski, Sophia; Schütz, Astrid; Wildgruber, Dirk; Kreifelts, Benjamin
2018-02-01
Facial expressions and voice modulations are among the most important communicational signals to convey emotional information. The ability to correctly interpret this information is highly relevant for successful social interaction and represents an integral component of emotional competencies that have been conceptualized under the term emotional intelligence. Here, we investigated the relationship of emotional intelligence as measured with the Salovey-Caruso-Emotional-Intelligence-Test (MSCEIT) with cerebral voice and face processing using functional and structural magnetic resonance imaging. MSCEIT scores were positively correlated with increased voice-sensitivity and gray matter volume of the insula accompanied by voice-sensitivity enhanced connectivity between the insula and the temporal voice area, indicating generally increased salience of voices. Conversely, in the face processing system, higher MSCEIT scores were associated with decreased face-sensitivity and gray matter volume of the fusiform face area. Taken together, these findings point to an alteration in the balance of cerebral voice and face processing systems in the form of an attenuated face-vs-voice bias as one potential factor underpinning emotional intelligence.
The search for extraterrestrial intelligence: Telecommunications technology
NASA Technical Reports Server (NTRS)
Edelson, R. E.; Levy, G. S.
1980-01-01
Efforts to discover evidence of intelligent extraterrestrial life have become not only feasible, but respectable. Fledgling observational projects have begun that will use state-of-the-art hardware to develop sophisticated receiving and data processing systems. The rationale behind the Search for Extraterrestrial Intelligence, the manner in which the program is taking shape, and the implications for telecommunications are described. It is concluded that the breadth of technological development required for the detection of signals from galactic brethren has particular relevance for the future of telecommunications in Earth oriented uses.
Trewavas, Anthony
2005-09-01
Intelligent behavior is a complex adaptive phenomenon that has evolved to enable organisms to deal with variable environmental circumstances. Maximizing fitness requires skill in foraging for necessary resources (food) in competitive circumstances and is probably the activity in which intelligent behavior is most easily seen. Biologists suggest that intelligence encompasses the characteristics of detailed sensory perception, information processing, learning, memory, choice, optimisation of resource sequestration with minimal outlay, self-recognition, and foresight by predictive modeling. All these properties are concerned with a capacity for problem solving in recurrent and novel situations. Here I review the evidence that individual plant species exhibit all of these intelligent behavioral capabilities but do so through phenotypic plasticity, not movement. Furthermore it is in the competitive foraging for resources that most of these intelligent attributes have been detected. Plants should therefore be regarded as prototypical intelligent organisms, a concept that has considerable consequences for investigations of whole plant communication, computation and signal transduction.
Extended Logic Intelligent Processing System for a Sensor Fusion Processor Hardware
NASA Technical Reports Server (NTRS)
Stoica, Adrian; Thomas, Tyson; Li, Wei-Te; Daud, Taher; Fabunmi, James
2000-01-01
The paper presents the hardware implementation and initial tests from a low-power, highspeed reconfigurable sensor fusion processor. The Extended Logic Intelligent Processing System (ELIPS) is described, which combines rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor signals in compact low power VLSI. The development of the ELIPS concept is being done to demonstrate the interceptor functionality which particularly underlines the high speed and low power requirements. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Processing speeds of microseconds have been demonstrated using our test hardware.
Visemic Processing in Audiovisual Discrimination of Natural Speech: A Simultaneous fMRI-EEG Study
ERIC Educational Resources Information Center
Dubois, Cyril; Otzenberger, Helene; Gounot, Daniel; Sock, Rudolph; Metz-Lutz, Marie-Noelle
2012-01-01
In a noisy environment, visual perception of articulatory movements improves natural speech intelligibility. Parallel to phonemic processing based on auditory signal, visemic processing constitutes a counterpart based on "visemes", the distinctive visual units of speech. Aiming at investigating the neural substrates of visemic processing in a…
Disentangling syntax and intelligibility in auditory language comprehension.
Friederici, Angela D; Kotz, Sonja A; Scott, Sophie K; Obleser, Jonas
2010-03-01
Studies of the neural basis of spoken language comprehension typically focus on aspects of auditory processing by varying signal intelligibility, or on higher-level aspects of language processing such as syntax. Most studies in either of these threads of language research report brain activation including peaks in the superior temporal gyrus (STG) and/or the superior temporal sulcus (STS), but it is not clear why these areas are recruited in functionally different studies. The current fMRI study aims to disentangle the functional neuroanatomy of intelligibility and syntax in an orthogonal design. The data substantiate functional dissociations between STS and STG in the left and right hemispheres: first, manipulations of speech intelligibility yield bilateral mid-anterior STS peak activation, whereas syntactic phrase structure violations elicit strongly left-lateralized mid STG and posterior STS activation. Second, ROI analyses indicate all interactions of speech intelligibility and syntactic correctness to be located in the left frontal and temporal cortex, while the observed right-hemispheric activations reflect less specific responses to intelligibility and syntax. Our data demonstrate that the mid-to-anterior STS activation is associated with increasing speech intelligibility, while the mid-to-posterior STG/STS is more sensitive to syntactic information within the speech. 2009 Wiley-Liss, Inc.
MIXI: Mobile Intelligent X-Ray Inspection System
NASA Astrophysics Data System (ADS)
Arodzero, Anatoli; Boucher, Salime; Kutsaev, Sergey V.; Ziskin, Vitaliy
2017-07-01
A novel, low-dose Mobile Intelligent X-ray Inspection (MIXI) concept is being developed at RadiaBeam Technologies. The MIXI concept relies on a linac-based, adaptive, ramped energy source of short X-ray packets of pulses, a new type of fast X-ray detector, rapid processing of detector signals for intelligent control of the linac, and advanced radiography image processing. The key parameters for this system include: better than 3 mm line pair resolution; penetration greater than 320 mm of steel equivalent; scan speed with 100% image sampling rate of up to 15 km/h; and material discrimination over a range of thicknesses up to 200 mm of steel equivalent. Its minimal radiation dose, size and weight allow MIXI to be placed on a lightweight truck chassis.
Research on intelligent monitoring technology of machining process
NASA Astrophysics Data System (ADS)
Wang, Taiyong; Meng, Changhong; Zhao, Guoli
1995-08-01
Based upon research on sound and vibration characteristics of tool condition, we explore the multigrade monitoring system which takes single-chip microcomputers as the core hardware. By using the specially designed pickup true signal devices, we can more effectively do the intelligent multigrade monitoring and forecasting, and furthermore, we can build the tool condition models adaptively. This is the key problem in FMS, CIMS, and even the IMS.
Kyong, Jeong S.; Scott, Sophie K.; Rosen, Stuart; Howe, Timothy B.; Agnew, Zarinah K.; McGettigan, Carolyn
2014-01-01
The melodic contour of speech forms an important perceptual aspect of tonal and nontonal languages and an important limiting factor on the intelligibility of speech heard through a cochlear implant. Previous work exploring the neural correlates of speech comprehension identified a left-dominant pathway in the temporal lobes supporting the extraction of an intelligible linguistic message, whereas the right anterior temporal lobe showed an overall preference for signals clearly conveying dynamic pitch information. The current study combined modulations of overall intelligibility (through vocoding and spectral inversion) with a manipulation of pitch contour (normal vs. falling) to investigate the processing of spoken sentences in functional MRI. Our overall findings replicate and extend those of Scott et al., whereas greater sentence intelligibility was predominately associated with increased activity in the left STS, the greatest response to normal sentence melody was found right superior temporal gyrus. These data suggest a spatial distinction between brain areas associated with intelligibility and those involved in the processing of dynamic pitch information in speech. By including a set of complexity-matched unintelligible conditions created by spectral inversion, this is additionally the first study reporting a fully factorial exploration of spectrotemporal complexity and spectral inversion as they relate to the neural processing of speech intelligibility. Perhaps surprisingly, there was no evidence for an interaction between the two factors—we discuss the implications for the processing of sound and speech in the dorsolateral temporal lobes. PMID:24568205
Speech Intelligibility Advantages using an Acoustic Beamformer Display
NASA Technical Reports Server (NTRS)
Begault, Durand R.; Sunder, Kaushik; Godfroy, Martine; Otto, Peter
2015-01-01
A speech intelligibility test conforming to the Modified Rhyme Test of ANSI S3.2 "Method for Measuring the Intelligibility of Speech Over Communication Systems" was conducted using a prototype 12-channel acoustic beamformer system. The target speech material (signal) was identified against speech babble (noise), with calculated signal-noise ratios of 0, 5 and 10 dB. The signal was delivered at a fixed beam orientation of 135 deg (re 90 deg as the frontal direction of the array) and the noise at 135 deg (co-located) and 0 deg (separated). A significant improvement in intelligibility from 57% to 73% was found for spatial separation for the same signal-noise ratio (0 dB). Significant effects for improved intelligibility due to spatial separation were also found for higher signal-noise ratios (5 and 10 dB).
Bluetooth-based sensor networks for remotely monitoring the physiological signals of a patient.
Zhang, Ying; Xiao, Hannan
2009-11-01
Integrating intelligent medical microsensors into a wireless communication network makes it possible to remotely collect physiological signals of a patient, release the patient from being tethered to monitoring medical instrumentations, and facilitate the patient's early hospital discharge. This can further improve life quality by providing continuous observation without the need of disrupting the patient's normal life, thus reducing the risk of infection significantly, and decreasing the cost of the hospital and the patient. This paper discusses the implementation issues, and describes the overall system architecture of our developed Bluetooth sensor network for patient monitoring and the corresponding heart activity sensors. It also presents our approach to developing the intelligent physiological sensor nodes involving integration of Bluetooth radio technology, hardware and software organization, and our solutions for onboard signal processing.
Two systems analyses of SETI. [microwave Search for Extra-Terrestrial Intelligence
NASA Technical Reports Server (NTRS)
Machol, R. E.
1976-01-01
The problem of receiving and identifying a single microwave signal transmitted by extraterrestrial intelligent beings is analyzed in the cases where the signal is designed to catch our attention and the signal is designed for internal purposes of another civilization. Six variables which yield uncertainty as to the exact signal which should be searched for are described: polarization, modulation, flux level, direction, frequency (including bandwidth and drift rate), and time. It is shown that if all reasonable variations of these parameters are to be examined sequentially for 1000 seconds, the search would take over a million times longer than the age of the Universe. Ways to simplify the search are considered, including widening the frequency bin, selecting specific targets, cutting the observation time, using a Fourier transform device for data processing, and building larger antennas as well as better low-noise receivers.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Azevedo, S.G.; Fitch, J.P.
1987-10-21
Conventional software interfaces that use imperative computer commands or menu interactions are often restrictive environments when used for researching new algorithms or analyzing processed experimental data. We found this to be true with current signal-processing software (SIG). As an alternative, ''functional language'' interfaces provide features such as command nesting for a more natural interaction with the data. The Image and Signal LISP Environment (ISLE) is an example of an interpreted functional language interface based on common LISP. Advantages of ISLE include multidimensional and multiple data-type independence through dispatching functions, dynamic loading of new functions, and connections to artificial intelligence (AI)more » software. 10 refs.« less
Kates, James M; Arehart, Kathryn H
2015-10-01
This paper uses mutual information to quantify the relationship between envelope modulation fidelity and perceptual responses. Data from several previous experiments that measured speech intelligibility, speech quality, and music quality are evaluated for normal-hearing and hearing-impaired listeners. A model of the auditory periphery is used to generate envelope signals, and envelope modulation fidelity is calculated using the normalized cross-covariance of the degraded signal envelope with that of a reference signal. Two procedures are used to describe the envelope modulation: (1) modulation within each auditory frequency band and (2) spectro-temporal processing that analyzes the modulation of spectral ripple components fit to successive short-time spectra. The results indicate that low modulation rates provide the highest information for intelligibility, while high modulation rates provide the highest information for speech and music quality. The low-to-mid auditory frequencies are most important for intelligibility, while mid frequencies are most important for speech quality and high frequencies are most important for music quality. Differences between the spectral ripple components used for the spectro-temporal analysis were not significant in five of the six experimental conditions evaluated. The results indicate that different modulation-rate and auditory-frequency weights may be appropriate for indices designed to predict different types of perceptual relationships.
Kates, James M.; Arehart, Kathryn H.
2015-01-01
This paper uses mutual information to quantify the relationship between envelope modulation fidelity and perceptual responses. Data from several previous experiments that measured speech intelligibility, speech quality, and music quality are evaluated for normal-hearing and hearing-impaired listeners. A model of the auditory periphery is used to generate envelope signals, and envelope modulation fidelity is calculated using the normalized cross-covariance of the degraded signal envelope with that of a reference signal. Two procedures are used to describe the envelope modulation: (1) modulation within each auditory frequency band and (2) spectro-temporal processing that analyzes the modulation of spectral ripple components fit to successive short-time spectra. The results indicate that low modulation rates provide the highest information for intelligibility, while high modulation rates provide the highest information for speech and music quality. The low-to-mid auditory frequencies are most important for intelligibility, while mid frequencies are most important for speech quality and high frequencies are most important for music quality. Differences between the spectral ripple components used for the spectro-temporal analysis were not significant in five of the six experimental conditions evaluated. The results indicate that different modulation-rate and auditory-frequency weights may be appropriate for indices designed to predict different types of perceptual relationships. PMID:26520329
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.
Tracking signal test to monitor an intelligent time series forecasting model
NASA Astrophysics Data System (ADS)
Deng, Yan; Jaraiedi, Majid; Iskander, Wafik H.
2004-03-01
Extensive research has been conducted on the subject of Intelligent Time Series forecasting, including many variations on the use of neural networks. However, investigation of model adequacy over time, after the training processes is completed, remains to be fully explored. In this paper we demonstrate a how a smoothed error tracking signals test can be incorporated into a neuro-fuzzy model to monitor the forecasting process and as a statistical measure for keeping the forecasting model up-to-date. The proposed monitoring procedure is effective in the detection of nonrandom changes, due to model inadequacy or lack of unbiasedness in the estimation of model parameters and deviations from the existing patterns. This powerful detection device will result in improved forecast accuracy in the long run. An example data set has been used to demonstrate the application of the proposed method.
Ibrahim, Iman; Parsa, Vijay; Macpherson, Ewan; Cheesman, Margaret
2012-01-01
Wireless synchronization of the digital signal processing (DSP) features between two hearing aids in a bilateral hearing aid fitting is a fairly new technology. This technology is expected to preserve the differences in time and intensity between the two ears by co-ordinating the bilateral DSP features such as multichannel compression, noise reduction, and adaptive directionality. The purpose of this study was to evaluate the benefits of wireless communication as implemented in two commercially available hearing aids. More specifically, this study measured speech intelligibility and sound localization abilities of normal hearing and hearing impaired listeners using bilateral hearing aids with wireless synchronization of multichannel Wide Dynamic Range Compression (WDRC). Twenty subjects participated; 8 had normal hearing and 12 had bilaterally symmetrical sensorineural hearing loss. Each individual completed the Hearing in Noise Test (HINT) and a sound localization test with two types of stimuli. No specific benefit from wireless WDRC synchronization was observed for the HINT; however, hearing impaired listeners had better localization with the wireless synchronization. Binaural wireless technology in hearing aids may improve localization abilities although the possible effect appears to be small at the initial fitting. With adaptation, the hearing aids with synchronized signal processing may lead to an improvement in localization and speech intelligibility. Further research is required to demonstrate the effect of adaptation to the hearing aids with synchronized signal processing on different aspects of auditory performance. PMID:26557339
2009-09-01
SAS Statistical Analysis Software SE Systems Engineering SEP Systems Engineering Process SHP Shaft Horsepower SIGINT Signals Intelligence......management occurs (OSD 2002). The Systems Engineering Process (SEP), displayed in Figure 2, is a comprehensive , iterative and recursive problem
An Intelligent Computer-Based System for Sign Language Tutoring
ERIC Educational Resources Information Center
Ritchings, Tim; Khadragi, Ahmed; Saeb, Magdy
2012-01-01
A computer-based system for sign language tutoring has been developed using a low-cost data glove and a software application that processes the movement signals for signs in real-time and uses Pattern Matching techniques to decide if a trainee has closely replicated a teacher's recorded movements. The data glove provides 17 movement signals from…
The role of accent imitation in sensorimotor integration during processing of intelligible speech
Adank, Patti; Rueschemeyer, Shirley-Ann; Bekkering, Harold
2013-01-01
Recent theories on how listeners maintain perceptual invariance despite variation in the speech signal allocate a prominent role to imitation mechanisms. Notably, these simulation accounts propose that motor mechanisms support perception of ambiguous or noisy signals. Indeed, imitation of ambiguous signals, e.g., accented speech, has been found to aid effective speech comprehension. Here, we explored the possibility that imitation in speech benefits perception by increasing activation in speech perception and production areas. Participants rated the intelligibility of sentences spoken in an unfamiliar accent of Dutch in a functional Magnetic Resonance Imaging experiment. Next, participants in one group repeated the sentences in their own accent, while a second group vocally imitated the accent. Finally, both groups rated the intelligibility of accented sentences in a post-test. The neuroimaging results showed an interaction between type of training and pre- and post-test sessions in left Inferior Frontal Gyrus, Supplementary Motor Area, and left Superior Temporal Sulcus. Although alternative explanations such as task engagement and fatigue need to be considered as well, the results suggest that imitation may aid effective speech comprehension by supporting sensorimotor integration. PMID:24109447
D’Aquila, Laura A.; Desloge, Joseph G.; Braida, Louis D.
2017-01-01
The masking release (MR; i.e., better speech recognition in fluctuating compared with continuous noise backgrounds) that is evident for listeners with normal hearing (NH) is generally reduced or absent for listeners with sensorineural hearing impairment (HI). In this study, a real-time signal-processing technique was developed to improve MR in listeners with HI and offer insight into the mechanisms influencing the size of MR. This technique compares short-term and long-term estimates of energy, increases the level of short-term segments whose energy is below the average energy, and normalizes the overall energy of the processed signal to be equivalent to that of the original long-term estimate. This signal-processing algorithm was used to create two types of energy-equalized (EEQ) signals: EEQ1, which operated on the wideband speech plus noise signal, and EEQ4, which operated independently on each of four bands with equal logarithmic width. Consonant identification was tested in backgrounds of continuous and various types of fluctuating speech-shaped Gaussian noise including those with both regularly and irregularly spaced temporal fluctuations. Listeners with HI achieved similar scores for EEQ and the original (unprocessed) stimuli in continuous-noise backgrounds, while superior performance was obtained for the EEQ signals in fluctuating background noises that had regular temporal gaps but not for those with irregularly spaced fluctuations. Thus, in noise backgrounds with regularly spaced temporal fluctuations, the energy-normalized signals led to larger values of MR and higher intelligibility than obtained with unprocessed signals. PMID:28602128
Multi-Modal Intelligent Traffic Signal Systems (MMITSS) impacts assessment.
DOT National Transportation Integrated Search
2015-08-01
The study evaluates the potential network-wide impacts of the Multi-Modal Intelligent Transportation Signal System (MMITSS) based on a field data analysis utilizing data collected from a MMITSS prototype and a simulation analysis. The Intelligent Tra...
An Intelligent Monitoring Network for Detection of Cracks in Anvils of High-Press Apparatus.
Tian, Hao; Yan, Zhaoli; Yang, Jun
2018-04-09
Due to the endurance of alternating high pressure and temperature, the carbide anvils of the high-press apparatus, which are widely used in the synthetic diamond industry, are prone to crack. In this paper, an acoustic method is used to monitor the crack events, and the intelligent monitoring network is proposed to classify the sound samples. The pulse sound signals produced by such cracking are first extracted based on a short-time energy threshold. Then, the signals are processed with the proposed intelligent monitoring network to identify the operation condition of the anvil of the high-pressure apparatus. The monitoring network is an improved convolutional neural network that solves the problems that may occur in practice. The length of pulse sound excited by the crack growth is variable, so a spatial pyramid pooling layer is adopted to solve the variable-length input problem. An adaptive weighted algorithm for loss function is proposed in this method to handle the class imbalance problem. The good performance regarding the accuracy and balance of the proposed intelligent monitoring network is validated through the experiments finally.
All-source Information Management and Integration for Improved Collective Intelligence Production
2011-06-01
Intelligence (ELINT) • Open Source Intelligence ( OSINT ) • Technical Intelligence (TECHINT) These intelligence disciplines produce... intelligence , measurement and signature intelligence , signals intelligence , and open - source data, in the production of intelligence . All- source intelligence ...All- Source Information Integration and Management) R&D Project 3 All- Source Intelligence
Communications and Intelligent Systems Division Overview
NASA Technical Reports Server (NTRS)
Emerson, Dawn
2017-01-01
Provides expertise, and plans, conducts and directs research and engineering development in the competency fields of advanced communications and intelligent systems technologies for applications in current and future aeronautics and space systems.Advances communication systems engineering, development and analysis needed for Glenn Research Center's leadership in communications and intelligent systems technology. Focus areas include advanced high frequency devices, components, and antennas; optical communications, health monitoring and instrumentation; digital signal processing for communications and navigation, and cognitive radios; network architectures, protocols, standards and network-based applications; intelligent controls, dynamics and diagnostics; and smart micro- and nano-sensors and harsh environment electronics. Research and discipline engineering allow for the creation of innovative concepts and designs for aerospace communication systems with reduced size and weight, increased functionality and intelligence. Performs proof-of-concept studies and analyses to assess the impact of the new technologies.
Processing on weak electric signals by the autoregressive model
NASA Astrophysics Data System (ADS)
Ding, Jinli; Zhao, Jiayin; Wang, Lanzhou; Li, Qiao
2008-10-01
A model of the autoregressive model of weak electric signals in two plants was set up for the first time. The result of the AR model to forecast 10 values of the weak electric signals is well. It will construct a standard set of the AR model coefficient of the plant electric signal and the environmental factor, and can be used as the preferences for the intelligent autocontrol system based on the adaptive characteristic of plants to achieve the energy saving on agricultural productions.
An Examination of Application of Artificial Neural Network in Cognitive Radios
NASA Astrophysics Data System (ADS)
Bello Salau, H.; Onwuka, E. N.; Aibinu, A. M.
2013-12-01
Recent advancement in software radio technology has led to the development of smart device known as cognitive radio. This type of radio fuses powerful techniques taken from artificial intelligence, game theory, wideband/multiple antenna techniques, information theory and statistical signal processing to create an outstanding dynamic behavior. This cognitive radio is utilized in achieving diverse set of applications such as spectrum sensing, radio parameter adaptation and signal classification. This paper contributes by reviewing different cognitive radio implementation that uses artificial intelligence such as the hidden markov models, metaheuristic algorithm and artificial neural networks (ANNs). Furthermore, different areas of application of ANNs and their performance metrics based approach are also examined.
Review on the Traction System Sensor Technology of a Rail Transit Train.
Feng, Jianghua; Xu, Junfeng; Liao, Wu; Liu, Yong
2017-06-11
The development of high-speed intelligent rail transit has increased the number of sensors applied on trains. These play an important role in train state control and monitoring. These sensors generally work in a severe environment, so the key problem for sensor data acquisition is to ensure data accuracy and reliability. In this paper, we follow the sequence of sensor signal flow, present sensor signal sensing technology, sensor data acquisition, and processing technology, as well as sensor fault diagnosis technology based on the voltage, current, speed, and temperature sensors which are commonly used in train traction systems. Finally, intelligent sensors and future research directions of rail transit train sensors are discussed.
Review on the Traction System Sensor Technology of a Rail Transit Train
Feng, Jianghua; Xu, Junfeng; Liao, Wu; Liu, Yong
2017-01-01
The development of high-speed intelligent rail transit has increased the number of sensors applied on trains. These play an important role in train state control and monitoring. These sensors generally work in a severe environment, so the key problem for sensor data acquisition is to ensure data accuracy and reliability. In this paper, we follow the sequence of sensor signal flow, present sensor signal sensing technology, sensor data acquisition, and processing technology, as well as sensor fault diagnosis technology based on the voltage, current, speed, and temperature sensors which are commonly used in train traction systems. Finally, intelligent sensors and future research directions of rail transit train sensors are discussed. PMID:28604615
Li, Fengmei; Wei, Yaoguang; Chen, Yingyi; Li, Daoliang; Zhang, Xu
2015-12-09
Dissolved oxygen (DO) is a key factor that influences the healthy growth of fishes in aquaculture. The DO content changes with the aquatic environment and should therefore be monitored online. However, traditional measurement methods, such as iodometry and other chemical analysis methods, are not suitable for online monitoring. The Clark method is not stable enough for extended periods of monitoring. To solve these problems, this paper proposes an intelligent DO measurement method based on the fluorescence quenching mechanism. The measurement system is composed of fluorescent quenching detection, signal conditioning, intelligent processing, and power supply modules. The optical probe adopts the fluorescent quenching mechanism to detect the DO content and solves the problem, whereas traditional chemical methods are easily influenced by the environment. The optical probe contains a thermistor and dual excitation sources to isolate visible parasitic light and execute a compensation strategy. The intelligent processing module adopts the IEEE 1451.2 standard and realizes intelligent compensation. Experimental results show that the optical measurement method is stable, accurate, and suitable for online DO monitoring in aquaculture applications.
Li, Fengmei; Wei, Yaoguang; Chen, Yingyi; Li, Daoliang; Zhang, Xu
2015-01-01
Dissolved oxygen (DO) is a key factor that influences the healthy growth of fishes in aquaculture. The DO content changes with the aquatic environment and should therefore be monitored online. However, traditional measurement methods, such as iodometry and other chemical analysis methods, are not suitable for online monitoring. The Clark method is not stable enough for extended periods of monitoring. To solve these problems, this paper proposes an intelligent DO measurement method based on the fluorescence quenching mechanism. The measurement system is composed of fluorescent quenching detection, signal conditioning, intelligent processing, and power supply modules. The optical probe adopts the fluorescent quenching mechanism to detect the DO content and solves the problem, whereas traditional chemical methods are easily influenced by the environment. The optical probe contains a thermistor and dual excitation sources to isolate visible parasitic light and execute a compensation strategy. The intelligent processing module adopts the IEEE 1451.2 standard and realizes intelligent compensation. Experimental results show that the optical measurement method is stable, accurate, and suitable for online DO monitoring in aquaculture applications. PMID:26690176
[The design and applications of a non-invasive intelligent detector for cardiovascular functions].
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.
Project Cyclops: a Design Study of a System for Detecting Extraterrestrial Intelligent Life
NASA Technical Reports Server (NTRS)
1972-01-01
The requirements in hardware, manpower, time and funding to conduct a realistic effort aimed at detecting the existence of extraterrestrial intelligent life are examined. The methods used are limited to present or near term future state-of-the-art techniques. Subjects discussed include: (1) possible methods of contact, (2) communication by electromagnetic waves, (3) antenna array and system facilities, (4) antenna elements, (5) signal processing, (6) search strategy, and (7) radio and radar astronomy.
Neurotechnology for intelligence analysts
NASA Astrophysics Data System (ADS)
Kruse, Amy A.; Boyd, Karen C.; Schulman, Joshua J.
2006-05-01
Geospatial Intelligence Analysts are currently faced with an enormous volume of imagery, only a fraction of which can be processed or reviewed in a timely operational manner. Computer-based target detection efforts have failed to yield the speed, flexibility and accuracy of the human visual system. Rather than focus solely on artificial systems, we hypothesize that the human visual system is still the best target detection apparatus currently in use, and with the addition of neuroscience-based measurement capabilities it can surpass the throughput of the unaided human severalfold. Using electroencephalography (EEG), Thorpe et al1 described a fast signal in the brain associated with the early detection of targets in static imagery using a Rapid Serial Visual Presentation (RSVP) paradigm. This finding suggests that it may be possible to extract target detection signals from complex imagery in real time utilizing non-invasive neurophysiological assessment tools. To transform this phenomenon into a capability for defense applications, the Defense Advanced Research Projects Agency (DARPA) currently is sponsoring an effort titled Neurotechnology for Intelligence Analysts (NIA). The vision of the NIA program is to revolutionize the way that analysts handle intelligence imagery, increasing both the throughput of imagery to the analyst and overall accuracy of the assessments. Successful development of a neurobiologically-based image triage system will enable image analysts to train more effectively and process imagery with greater speed and precision.
Baumgärtel, Regina M; Hu, Hongmei; Krawczyk-Becker, Martin; Marquardt, Daniel; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Bomke, Katrin; Plotz, Karsten; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias
2015-12-30
Several binaural audio signal enhancement algorithms were evaluated with respect to their potential to improve speech intelligibility in noise for users of bilateral cochlear implants (CIs). 50% speech reception thresholds (SRT50) were assessed using an adaptive procedure in three distinct, realistic noise scenarios. All scenarios were highly nonstationary, complex, and included a significant amount of reverberation. Other aspects, such as the perfectly frontal target position, were idealized laboratory settings, allowing the algorithms to perform better than in corresponding real-world conditions. Eight bilaterally implanted CI users, wearing devices from three manufacturers, participated in the study. In all noise conditions, a substantial improvement in SRT50 compared to the unprocessed signal was observed for most of the algorithms tested, with the largest improvements generally provided by binaural minimum variance distortionless response (MVDR) beamforming algorithms. The largest overall improvement in speech intelligibility was achieved by an adaptive binaural MVDR in a spatially separated, single competing talker noise scenario. A no-pre-processing condition and adaptive differential microphones without a binaural link served as the two baseline conditions. SRT50 improvements provided by the binaural MVDR beamformers surpassed the performance of the adaptive differential microphones in most cases. Speech intelligibility improvements predicted by instrumental measures were shown to account for some but not all aspects of the perceptually obtained SRT50 improvements measured in bilaterally implanted CI users. © The Author(s) 2015.
NASA Technical Reports Server (NTRS)
Edelson, R. E.
1976-01-01
It is argued that a substantial portion of the capability for detecting microwave signals from extraterrestrial civilizations lies not in the application of ever larger antenna collecting areas but rather in the application of millions or billions of simultaneous frequency-channel observations combined with rapid and powerful data processing techniques. The application of these methods to existing facilities is discussed in terms of a program of modest expense and duration which will seek to discover certain classes of extraterrestrial signals of intelligent origin while defining boundaries to the search problem throughout the range of interest. This program will investigate radio-astronomical phenomena of interest and simultaneously define the background of environmental radiation in order to determine physical limitations on both the search strategies and the potential for deep-space communications. Signal parameters that must be determined are examined along with the potential of existing radio-astronomical facilities for detecting narrow-band signals. A seven-year program is described which will carry out a search for extraterrestrial intelligence over 80% of the sky and over the entire frequency range from 1 to 25 GHz with a sensitivity limit varying from 10 to the -21st power W/sq cm at the lowest frequencies to 10 to the -19th power W/sq cm at the higher frequencies.
Utianski, Rene L; Caviness, John N; Liss, Julie M
2015-01-01
High-density electroencephalography was used to evaluate cortical activity during speech comprehension via a sentence verification task. Twenty-four participants assigned true or false to sentences produced with 3 noise-vocoded channel levels (1--unintelligible, 6--decipherable, 16--intelligible), during simultaneous EEG recording. Participant data were sorted into higher- (HP) and lower-performing (LP) groups. The identification of a late-event related potential for LP listeners in the intelligible condition and in all listeners when challenged with a 6-Ch signal supports the notion that this induced potential may be related to either processing degraded speech, or degraded processing of intelligible speech. Different cortical locations are identified as neural generators responsible for this activity; HP listeners are engaging motor aspects of their language system, utilizing an acoustic-phonetic based strategy to help resolve the sentence, while LP listeners do not. This study presents evidence for neurophysiological indices associated with more or less successful speech comprehension performance across listening conditions. Copyright © 2014 Elsevier Inc. All rights reserved.
An adaptive signal-processing approach to online adaptive tutoring.
Bergeron, Bryan; Cline, Andrew
2011-01-01
Conventional intelligent or adaptive tutoring online systems rely on domain-specific models of learner behavior based on rules, deep domain knowledge, and other resource-intensive methods. We have developed and studied a domain-independent methodology of adaptive tutoring based on domain-independent signal-processing approaches that obviate the need for the construction of explicit expert and student models. A key advantage of our method over conventional approaches is a lower barrier to entry for educators who want to develop adaptive online learning materials.
TID measurement using oblique transmissions of HF pulses
NASA Astrophysics Data System (ADS)
Galkin, Ivan; Reinisch, Bodo; Huang, Xueqin; Paznukhov, Vadym; Hamel, Ryan; Kozlov, Alexander; Belehaki, Anna
2017-04-01
The Traveling Ionospheric Disturbance (TID), a wave-like signature of moving plasma density modulation in the ionosphere, is widely acknowledged for its utility in backtracking the anomalous events responsible for the TID generation, and as a major inconvenience to high-frequency (HF) operational systems because of its deleterious impact on the accuracy of navigation and geolocation. The pilot project "Net-TIDE" for the real-time detection and evaluation of TIDs began its operation in 2016 based on the remote-sensing data from synchronized, network-coordinated HF sounding between pairs of DPS4D ionosondes at five participating observatories in Europe. Measurement of all signal properties (Doppler frequency, angle of arrival, and time-of-flight from transmitter to receiver) proved to be instrumental in detecting the TID and deducing the TID parameters: amplitude, wavelength, phase velocity, and direction of propagation. Processing of the measured HF signal data required a specialized signal processing technique that is capable of consistently extracting different signals that have propagated along different ionospheric paths. The multi-path signal environment proved to be the greatest challenge for the reliable TID specification by Net-TIDE, demanding the development of an intelligent system for "signal tracking". The intelligent system is based on a neural network model of a pre-attentive vision capable of extracting continuous signal tracks from the multi-path signal ensemble. Specific examples of the Net-TIDE algorithm suite operation and its suitability for a fully automated TID warning service are discussed.
Intelligence Reform and Implications for North Korea’s Weapons of Mass Destruction Program
2005-09-01
August 2005). 36 Desmond Ball, “Signals Intelligence in North Korea,” Jane’s Intelligence Review 8, Issue 1 (January 1996 ), 1. 26...Ball, “Signals Intelligence in North Korea,” Jane’s Intelligence Review 8, Issue 1 (January 1996 ), 10. 38 Jeremy Kirk, “Intel Experts: N. Korea a...www.wmd.gov/report/index.html (accessed August 2005). Hereafter referred to as WMD Commission Report. 47 Michael Warner and J. Kenneth McDonald, “U.S
Computational intelligence for target assessment in Parkinson's disease
NASA Astrophysics Data System (ADS)
Micheli-Tzanakou, Evangelia; Hamilton, J. L.; Zheng, J.; Lehman, Richard M.
2001-11-01
Recent advances in image and signal processing have created a new challenging environment for biomedical engineers. Methods that were developed for different fields are now finding a fertile ground in biomedicine, especially in the analysis of bio-signals and in the understanding of images. More and more, these methods are used in the operating room, helping surgeons, and in the physician's office as aids for diagnostic purposes. Neural Network (NN) research on the other hand, has gone a long way in the past decade. NNs now consist of many thousands of highly interconnected processing elements that can encode, store and recall relationships between different patterns by altering the weighting coefficients of inputs in a systematic way. Although they can generate reasonable outputs from unknown input patterns, and can tolerate a great deal of noise, they are very slow when run on a serial machine. We have used advanced signal processing and innovative image processing methods that are used along with computational intelligence for diagnostic purposes and as visualization aids inside and outside the operating room. Applications to be discussed include EEGs and field potentials in Parkinson's disease along with 3D reconstruction of MR or fMR brain images in Parkinson's patients, are currently used in the operating room for Pallidotomies and Deep Brain Stimulation (DBS).
Code of Federal Regulations, 2014 CFR
2014-10-01
..., emission, or reception of signals, signs, writing, images, sounds, or intelligence of any nature, by wire... System which includes: (a) Receiving, processing, and evaluating requests for priority actions from... doubt. However, processing of Emergency NSEP service requests will not be delayed for verification...
Code of Federal Regulations, 2012 CFR
2012-10-01
..., emission, or reception of signals, signs, writing, images, sounds, or intelligence of any nature, by wire... System which includes: (a) Receiving, processing, and evaluating requests for priority actions from... doubt. However, processing of Emergency NSEP service requests will not be delayed for verification...
Kyong, Jeong S; Scott, Sophie K; Rosen, Stuart; Howe, Timothy B; Agnew, Zarinah K; McGettigan, Carolyn
2014-08-01
The melodic contour of speech forms an important perceptual aspect of tonal and nontonal languages and an important limiting factor on the intelligibility of speech heard through a cochlear implant. Previous work exploring the neural correlates of speech comprehension identified a left-dominant pathway in the temporal lobes supporting the extraction of an intelligible linguistic message, whereas the right anterior temporal lobe showed an overall preference for signals clearly conveying dynamic pitch information [Johnsrude, I. S., Penhune, V. B., & Zatorre, R. J. Functional specificity in the right human auditory cortex for perceiving pitch direction. Brain, 123, 155-163, 2000; Scott, S. K., Blank, C. C., Rosen, S., & Wise, R. J. Identification of a pathway for intelligible speech in the left temporal lobe. Brain, 123, 2400-2406, 2000]. The current study combined modulations of overall intelligibility (through vocoding and spectral inversion) with a manipulation of pitch contour (normal vs. falling) to investigate the processing of spoken sentences in functional MRI. Our overall findings replicate and extend those of Scott et al. [Scott, S. K., Blank, C. C., Rosen, S., & Wise, R. J. Identification of a pathway for intelligible speech in the left temporal lobe. Brain, 123, 2400-2406, 2000], where greater sentence intelligibility was predominately associated with increased activity in the left STS, and the greatest response to normal sentence melody was found in right superior temporal gyrus. These data suggest a spatial distinction between brain areas associated with intelligibility and those involved in the processing of dynamic pitch information in speech. By including a set of complexity-matched unintelligible conditions created by spectral inversion, this is additionally the first study reporting a fully factorial exploration of spectrotemporal complexity and spectral inversion as they relate to the neural processing of speech intelligibility. Perhaps surprisingly, there was little evidence for an interaction between the two factors-we discuss the implications for the processing of sound and speech in the dorsolateral temporal lobes.
NASA Astrophysics Data System (ADS)
Boldyreff, Anton S.; Bespalov, Dmitry A.; Adzhiev, Anatoly Kh.
2017-05-01
Methods of artificial intelligence are a good solution for weather phenomena forecasting. They allow to process a large amount of diverse data. Recirculation Neural Networks is implemented in the paper for the system of thunderstorm events prediction. Large amounts of experimental data from lightning sensors and electric field mills networks are received and analyzed. The average recognition accuracy of sensor signals is calculated. It is shown that Recirculation Neural Networks is a promising solution in the forecasting of thunderstorms and weather phenomena, characterized by the high efficiency of the recognition elements of the sensor signals, allows to compress images and highlight their characteristic features for subsequent recognition.
Context-Based Filtering for Assisted Brain-Actuated Wheelchair Driving
Vanacker, Gerolf; Millán, José del R.; Lew, Eileen; Ferrez, Pierre W.; Moles, Ferran Galán; Philips, Johan; Van Brussel, Hendrik; Nuttin, Marnix
2007-01-01
Controlling a robotic device by using human brain signals is an interesting and challenging task. The device may be complicated to control and the nonstationary nature of the brain signals provides for a rather unstable input. With the use of intelligent processing algorithms adapted to the task at hand, however, the performance can be increased. This paper introduces a shared control system that helps the subject in driving an intelligent wheelchair with a noninvasive brain interface. The subject's steering intentions are estimated from electroencephalogram (EEG) signals and passed through to the shared control system before being sent to the wheelchair motors. Experimental results show a possibility for significant improvement in the overall driving performance when using the shared control system compared to driving without it. These results have been obtained with 2 healthy subjects during their first day of training with the brain-actuated wheelchair. PMID:18354739
1979-12-01
intelligent graphics terminals in real-tim processing S (e) 5-1 to 5-9 MIel ita|ger The application of high-speed processors to propagation e.piriamnts...interface SACLANTCEN CP-25 5-2 M IM M STEIGER: Intelligent graphics terminals The less desirable features of the terminal are listed below. reiatively small...hours. Dismantling of the equipment is normally performed in less than one-half hour and often while waiting to clear customs. Transportation of the
An algorithm to improve speech recognition in noise for hearing-impaired listeners
Healy, Eric W.; Yoho, Sarah E.; Wang, Yuxuan; Wang, DeLiang
2013-01-01
Despite considerable effort, monaural (single-microphone) algorithms capable of increasing the intelligibility of speech in noise have remained elusive. Successful development of such an algorithm is especially important for hearing-impaired (HI) listeners, given their particular difficulty in noisy backgrounds. In the current study, an algorithm based on binary masking was developed to separate speech from noise. Unlike the ideal binary mask, which requires prior knowledge of the premixed signals, the masks used to segregate speech from noise in the current study were estimated by training the algorithm on speech not used during testing. Sentences were mixed with speech-shaped noise and with babble at various signal-to-noise ratios (SNRs). Testing using normal-hearing and HI listeners indicated that intelligibility increased following processing in all conditions. These increases were larger for HI listeners, for the modulated background, and for the least-favorable SNRs. They were also often substantial, allowing several HI listeners to improve intelligibility from scores near zero to values above 70%. PMID:24116438
Atmospheric effects on voice command intelligibility from acoustic hail and warning devices.
Bostron, Jason H; Brungart, Timothy A; Barnard, Andrew R; McDevitt, Timothy E
2011-04-01
Voice command sound pressure levels (SPLs) were recorded at distances up to 1500 m. Received SPLs were related to the meteorological condition during sound propagation and compared with the outdoor sound propagation standard ISO 9613-2. Intelligibility of received signals was calculated using ANSI S3.5. Intelligibility results for the present voice command indicate that meteorological condition imposes little to no effect on intelligibility when the signal-to-noise ratio (SNR) is low (<-9 dB) or high (>0 dB). In these two cases the signal is firmly unintelligible or intelligible, respectively. However, at moderate SNRs, variations in received SPL can cause a fully intelligible voice command to become unintelligible, depending on the meteorological condition along the sound propagation path. These changes in voice command intelligibility often occur on time scales as short as minutes during upward refracting conditions, typically found above ground during the day or upwind of a sound source. Reliably predicting the intelligibility of a voice command in a moderate SNR environment can be challenging due to the inherent variability imposed by sound propagation through the atmosphere.
Embedded electronics for intelligent structures
NASA Astrophysics Data System (ADS)
Warkentin, David J.; Crawley, Edward F.
The signal, power, and communications provisions for the distributed control processing, sensing, and actuation of an intelligent structure could benefit from a method of physically embedding some electronic components. The preliminary feasibility of embedding electronic components in load-bearing intelligent composite structures is addressed. A technique for embedding integrated circuits on silicon chips within graphite/epoxy composite structures is presented which addresses the problems of electrical, mechanical, and chemical isolation. The mechanical and chemical isolation of test articles manufactured by this technique are tested by subjecting them to static and cyclic mechanical loads and a temperature/humidity/bias environment. The likely failure modes under these conditions are identified, and suggestions for further improvements in the technique are discussed.
Health-Enabled Smart Sensor Fusion Technology
NASA Technical Reports Server (NTRS)
Wang, Ray
2012-01-01
A process was designed to fuse data from multiple sensors in order to make a more accurate estimation of the environment and overall health in an intelligent rocket test facility (IRTF), to provide reliable, high-confidence measurements for a variety of propulsion test articles. The object of the technology is to provide sensor fusion based on a distributed architecture. Specifically, the fusion technology is intended to succeed in providing health condition monitoring capability at the intelligent transceiver, such as RF signal strength, battery reading, computing resource monitoring, and sensor data reading. The technology also provides analytic and diagnostic intelligence at the intelligent transceiver, enhancing the IEEE 1451.x-based standard for sensor data management and distributions, as well as providing appropriate communications protocols to enable complex interactions to support timely and high-quality flow of information among the system elements.
Comparing Binaural Pre-processing Strategies III
Warzybok, Anna; Ernst, Stephan M. A.
2015-01-01
A comprehensive evaluation of eight signal pre-processing strategies, including directional microphones, coherence filters, single-channel noise reduction, binaural beamformers, and their combinations, was undertaken with normal-hearing (NH) and hearing-impaired (HI) listeners. Speech reception thresholds (SRTs) were measured in three noise scenarios (multitalker babble, cafeteria noise, and single competing talker). Predictions of three common instrumental measures were compared with the general perceptual benefit caused by the algorithms. The individual SRTs measured without pre-processing and individual benefits were objectively estimated using the binaural speech intelligibility model. Ten listeners with NH and 12 HI listeners participated. The participants varied in age and pure-tone threshold levels. Although HI listeners required a better signal-to-noise ratio to obtain 50% intelligibility than listeners with NH, no differences in SRT benefit from the different algorithms were found between the two groups. With the exception of single-channel noise reduction, all algorithms showed an improvement in SRT of between 2.1 dB (in cafeteria noise) and 4.8 dB (in single competing talker condition). Model predictions with binaural speech intelligibility model explained 83% of the measured variance of the individual SRTs in the no pre-processing condition. Regarding the benefit from the algorithms, the instrumental measures were not able to predict the perceptual data in all tested noise conditions. The comparable benefit observed for both groups suggests a possible application of noise reduction schemes for listeners with different hearing status. Although the model can predict the individual SRTs without pre-processing, further development is necessary to predict the benefits obtained from the algorithms at an individual level. PMID:26721922
Signal Processing Expert Code (SPEC)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ames, H.S.
1985-12-01
The purpose of this paper is to describe a prototype expert system called SPEC which was developed to demonstrate the utility of providing an intelligent interface for users of SIG, a general purpose signal processing code. The expert system is written in NIL, runs on a VAX 11/750 and consists of a backward chaining inference engine and an English-like parser. The inference engine uses knowledge encoded as rules about the formats of SIG commands and about how to perform frequency analyses using SIG. The system demonstrated that expert system can be used to control existing codes.
Acoustic richness modulates the neural networks supporting intelligible speech processing.
Lee, Yune-Sang; Min, Nam Eun; Wingfield, Arthur; Grossman, Murray; Peelle, Jonathan E
2016-03-01
The information contained in a sensory signal plays a critical role in determining what neural processes are engaged. Here we used interleaved silent steady-state (ISSS) functional magnetic resonance imaging (fMRI) to explore how human listeners cope with different degrees of acoustic richness during auditory sentence comprehension. Twenty-six healthy young adults underwent scanning while hearing sentences that varied in acoustic richness (high vs. low spectral detail) and syntactic complexity (subject-relative vs. object-relative center-embedded clause structures). We manipulated acoustic richness by presenting the stimuli as unprocessed full-spectrum speech, or noise-vocoded with 24 channels. Importantly, although the vocoded sentences were spectrally impoverished, all sentences were highly intelligible. These manipulations allowed us to test how intelligible speech processing was affected by orthogonal linguistic and acoustic demands. Acoustically rich speech showed stronger activation than acoustically less-detailed speech in a bilateral temporoparietal network with more pronounced activity in the right hemisphere. By contrast, listening to sentences with greater syntactic complexity resulted in increased activation of a left-lateralized network including left posterior lateral temporal cortex, left inferior frontal gyrus, and left dorsolateral prefrontal cortex. Significant interactions between acoustic richness and syntactic complexity occurred in left supramarginal gyrus, right superior temporal gyrus, and right inferior frontal gyrus, indicating that the regions recruited for syntactic challenge differed as a function of acoustic properties of the speech. Our findings suggest that the neural systems involved in speech perception are finely tuned to the type of information available, and that reducing the richness of the acoustic signal dramatically alters the brain's response to spoken language, even when intelligibility is high. Copyright © 2015 Elsevier B.V. All rights reserved.
Single Trial EEG Patterns for the Prediction of Individual Differences in Fluid Intelligence.
Qazi, Emad-Ul-Haq; Hussain, Muhammad; Aboalsamh, Hatim; Malik, Aamir Saeed; Amin, Hafeez Ullah; Bamatraf, Saeed
2016-01-01
Assessing a person's intelligence level is required in many situations, such as career counseling and clinical applications. EEG evoked potentials in oddball task and fluid intelligence score are correlated because both reflect the cognitive processing and attention. A system for prediction of an individual's fluid intelligence level using single trial Electroencephalography (EEG) signals has been proposed. For this purpose, we employed 2D and 3D contents and 34 subjects each for 2D and 3D, which were divided into low-ability (LA) and high-ability (HA) groups using Raven's Advanced Progressive Matrices (RAPM) test. Using visual oddball cognitive task, neural activity of each group was measured and analyzed over three midline electrodes (Fz, Cz, and Pz). To predict whether an individual belongs to LA or HA group, features were extracted using wavelet decomposition of EEG signals recorded in visual oddball task and support vector machine (SVM) was used as a classifier. Two different types of Haar wavelet transform based features have been extracted from the band (0.3 to 30 Hz) of EEG signals. Statistical wavelet features and wavelet coefficient features from the frequency bands 0.0-1.875 Hz (delta low) and 1.875-3.75 Hz (delta high), resulted in the 100 and 98% prediction accuracies, respectively, both for 2D and 3D contents. The analysis of these frequency bands showed clear difference between LA and HA groups. Further, discriminative values of the features have been validated using statistical significance tests and inter-class and intra-class variation analysis. Also, statistical test showed that there was no effect of 2D and 3D content on the assessment of fluid intelligence level. Comparisons with state-of-the-art techniques showed the superiority of the proposed system.
Neuromimetic Sound Representation for Percept Detection and Manipulation
NASA Astrophysics Data System (ADS)
Zotkin, Dmitry N.; Chi, Taishih; Shamma, Shihab A.; Duraiswami, Ramani
2005-12-01
The acoustic wave received at the ears is processed by the human auditory system to separate different sounds along the intensity, pitch, and timbre dimensions. Conventional Fourier-based signal processing, while endowed with fast algorithms, is unable to easily represent a signal along these attributes. In this paper, we discuss the creation of maximally separable sounds in auditory user interfaces and use a recently proposed cortical sound representation, which performs a biomimetic decomposition of an acoustic signal, to represent and manipulate sound for this purpose. We briefly overview algorithms for obtaining, manipulating, and inverting a cortical representation of a sound and describe algorithms for manipulating signal pitch and timbre separately. The algorithms are also used to create sound of an instrument between a "guitar" and a "trumpet." Excellent sound quality can be achieved if processing time is not a concern, and intelligible signals can be reconstructed in reasonable processing time (about ten seconds of computational time for a one-second signal sampled at [InlineEquation not available: see fulltext.]). Work on bringing the algorithms into the real-time processing domain is ongoing.
Intelligent detectors modelled from the cat's eye
NASA Astrophysics Data System (ADS)
Lindblad, Th.; Becanovic, V.; Lindsey, C. S.; Szekely, G.
1997-02-01
Biologically inspired image/signal processing, in particular neural networks like the Pulse-Coupled Neural Network (PCNN), are revisited. Their use with high granularity high-energy physics detectors, as well as optical sensing devices, for filtering, de-noising, segmentation, object isolation and edge detection is discussed.
Intelligent Power Swing Detection Scheme to Prevent False Relay Tripping Using S-Transform
NASA Astrophysics Data System (ADS)
Mohamad, Nor Z.; Abidin, Ahmad F.; Musirin, Ismail
2014-06-01
Distance relay design is equipped with out-of-step tripping scheme to ensure correct distance relay operation during power swing. The out-of-step condition is a consequence result from unstable power swing. It requires proper detection of power swing to initiate a tripping signal followed by separation of unstable part from the entire power system. The distinguishing process of unstable swing from stable swing poses a challenging task. This paper presents an intelligent approach to detect power swing based on S-Transform signal processing tool. The proposed scheme is based on the use of S-Transform feature of active power at the distance relay measurement point. It is demonstrated that the proposed scheme is able to detect and discriminate the unstable swing from stable swing occurring in the system. To ascertain validity of the proposed scheme, simulations were carried out with the IEEE 39 bus system and its performance has been compared with the wavelet transform-based power swing detection scheme.
Jeon, Joonryong
2017-01-01
In this paper, a data compression technology-based intelligent data acquisition (IDAQ) system was developed for structural health monitoring of civil structures, and its validity was tested using random signals (El-Centro seismic waveform). The IDAQ system was structured to include a high-performance CPU with large dynamic memory for multi-input and output in a radio frequency (RF) manner. In addition, the embedded software technology (EST) has been applied to it to implement diverse logics needed in the process of acquiring, processing and transmitting data. In order to utilize IDAQ system for the structural health monitoring of civil structures, this study developed an artificial filter bank by which structural dynamic responses (acceleration) were efficiently acquired, and also optimized it on the random El-Centro seismic waveform. All techniques developed in this study have been embedded to our system. The data compression technology-based IDAQ system was proven valid in acquiring valid signals in a compressed size. PMID:28704945
Heo, Gwanghee; Jeon, Joonryong
2017-07-12
In this paper, a data compression technology-based intelligent data acquisition (IDAQ) system was developed for structural health monitoring of civil structures, and its validity was tested using random signals (El-Centro seismic waveform). The IDAQ system was structured to include a high-performance CPU with large dynamic memory for multi-input and output in a radio frequency (RF) manner. In addition, the embedded software technology (EST) has been applied to it to implement diverse logics needed in the process of acquiring, processing and transmitting data. In order to utilize IDAQ system for the structural health monitoring of civil structures, this study developed an artificial filter bank by which structural dynamic responses (acceleration) were efficiently acquired, and also optimized it on the random El-Centro seismic waveform. All techniques developed in this study have been embedded to our system. The data compression technology-based IDAQ system was proven valid in acquiring valid signals in a compressed size.
Benzy, V K; Jasmin, E A; Koshy, Rachel Cherian; Amal, Frank; Indiradevi, K P
2018-01-01
The advancement in medical research and intelligent modeling techniques has lead to the developments in anaesthesia management. The present study is targeted to estimate the depth of anaesthesia using cognitive signal processing and intelligent modeling techniques. The neurophysiological signal that reflects cognitive state of anaesthetic drugs is the electroencephalogram signal. The information available on electroencephalogram signals during anaesthesia are drawn by extracting relative wave energy features from the anaesthetic electroencephalogram signals. Discrete wavelet transform is used to decomposes the electroencephalogram signals into four levels and then relative wave energy is computed from approximate and detail coefficients of sub-band signals. Relative wave energy is extracted to find out the degree of importance of different electroencephalogram frequency bands associated with different anaesthetic phases awake, induction, maintenance and recovery. The Kruskal-Wallis statistical test is applied on the relative wave energy features to check the discriminating capability of relative wave energy features as awake, light anaesthesia, moderate anaesthesia and deep anaesthesia. A novel depth of anaesthesia index is generated by implementing a Adaptive neuro-fuzzy inference system based fuzzy c-means clustering algorithm which uses relative wave energy features as inputs. Finally, the generated depth of anaesthesia index is compared with a commercially available depth of anaesthesia monitor Bispectral index.
Ali, Abdulbaset; Hu, Bing; Ramahi, Omar
2015-05-15
This work presents a real life experiment of implementing an artificial intelligence model for detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide sensor loaded with metamaterial elements. Crack detection using microwave sensors is typically based on human observation of change in the sensor's signal (pattern) depicted on a high-resolution screen of the test equipment. However, as demonstrated in this work, implementing artificial intelligence to classify cracked from non-cracked surfaces has appreciable impact in terms of sensing sensitivity, cost, and automation. Furthermore, applying artificial intelligence for post-processing data collected from microwave sensors is a cornerstone for handheld test equipment that can outperform rack equipment with large screens and sophisticated plotting features. The proposed method was tested on a metallic plate with different cracks and the obtained experimental results showed good crack classification accuracy rates.
Ali, Abdulbaset; Hu, Bing; Ramahi, Omar M.
2015-01-01
This work presents a real-life experiment implementing an artificial intelligence model for detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide sensor loaded with metamaterial elements. Crack detection using microwave sensors is typically based on human observation of change in the sensor's signal (pattern) depicted on a high-resolution screen of the test equipment. However, as demonstrated in this work, implementing artificial intelligence to classify cracked from non-cracked surfaces has appreciable impacts in terms of sensing sensitivity, cost, and automation. Furthermore, applying artificial intelligence for post-processing the data collected from microwave sensors is a cornerstone for handheld test equipment that can outperform rack equipment with large screens and sophisticated plotting features. The proposed method was tested on a metallic plate with different cracks, and the experimental results showed good crack classification accuracy rates. PMID:25988871
Temporal Resolution Needed for Auditory Communication: Measurement With Mosaic Speech
Nakajima, Yoshitaka; Matsuda, Mizuki; Ueda, Kazuo; Remijn, Gerard B.
2018-01-01
Temporal resolution needed for Japanese speech communication was measured. A new experimental paradigm that can reflect the spectro-temporal resolution necessary for healthy listeners to perceive speech is introduced. As a first step, we report listeners' intelligibility scores of Japanese speech with a systematically degraded temporal resolution, so-called “mosaic speech”: speech mosaicized in the coordinates of time and frequency. The results of two experiments show that mosaic speech cut into short static segments was almost perfectly intelligible with a temporal resolution of 40 ms or finer. Intelligibility dropped for a temporal resolution of 80 ms, but was still around 50%-correct level. The data are in line with previous results showing that speech signals separated into short temporal segments of <100 ms can be remarkably robust in terms of linguistic-content perception against drastic manipulations in each segment, such as partial signal omission or temporal reversal. The human perceptual system thus can extract meaning from unexpectedly rough temporal information in speech. The process resembles that of the visual system stringing together static movie frames of ~40 ms into vivid motion. PMID:29740295
Development and realization of the open fault diagnosis system based on XPE
NASA Astrophysics Data System (ADS)
Deng, Hui; Wang, TaiYong; He, HuiLong; Xu, YongGang; Zeng, JuXiang
2005-12-01
To make the complex mechanical equipment work in good service, the technology for realizing an embedded open system is introduced systematically, including open hardware configuration, customized embedded operation system and open software structure. The ETX technology is adopted in this system, integrating the CPU main-board functions, and achieving the quick, real-time signal acquisition and intelligent data analysis with applying DSP and CPLD data acquisition card. Under the open configuration, the signal bus mode such as PCI, ISA and PC/104 can be selected and the styles of the signals can be chosen too. In addition, through customizing XPE system, adopting the EWF (Enhanced Write Filter), and realizing the open system authentically, the stability of the system is enhanced. Multi-thread and multi-task programming techniques are adopted in the software programming process. Interconnecting with the remote fault diagnosis center via the net interface, cooperative diagnosis is conducted and the intelligent degree of the fault diagnosis is improved.
Stanford Hardware Development Program
NASA Technical Reports Server (NTRS)
Peterson, A.; Linscott, I.; Burr, J.
1986-01-01
Architectures for high performance, digital signal processing, particularly for high resolution, wide band spectrum analysis were developed. These developments are intended to provide instrumentation for NASA's Search for Extraterrestrial Intelligence (SETI) program. The real time signal processing is both formal and experimental. The efficient organization and optimal scheduling of signal processing algorithms were investigated. The work is complemented by efforts in processor architecture design and implementation. A high resolution, multichannel spectrometer that incorporates special purpose microcoded signal processors is being tested. A general purpose signal processor for the data from the multichannel spectrometer was designed to function as the processing element in a highly concurrent machine. The processor performance required for the spectrometer is in the range of 1000 to 10,000 million instructions per second (MIPS). Multiple node processor configurations, where each node performs at 100 MIPS, are sought. The nodes are microprogrammable and are interconnected through a network with high bandwidth for neighboring nodes, and medium bandwidth for nodes at larger distance. The implementation of both the current mutlichannel spectrometer and the signal processor as Very Large Scale Integration CMOS chip sets was commenced.
A music perception disorder (congenital amusia) influences speech comprehension.
Liu, Fang; Jiang, Cunmei; Wang, Bei; Xu, Yi; Patel, Aniruddh D
2015-01-01
This study investigated the underlying link between speech and music by examining whether and to what extent congenital amusia, a musical disorder characterized by degraded pitch processing, would impact spoken sentence comprehension for speakers of Mandarin, a tone language. Sixteen Mandarin-speaking amusics and 16 matched controls were tested on the intelligibility of news-like Mandarin sentences with natural and flat fundamental frequency (F0) contours (created via speech resynthesis) under four signal-to-noise (SNR) conditions (no noise, +5, 0, and -5dB SNR). While speech intelligibility in quiet and extremely noisy conditions (SNR=-5dB) was not significantly compromised by flattened F0, both amusic and control groups achieved better performance with natural-F0 sentences than flat-F0 sentences under moderately noisy conditions (SNR=+5 and 0dB). Relative to normal listeners, amusics demonstrated reduced speech intelligibility in both quiet and noise, regardless of whether the F0 contours of the sentences were natural or flattened. This deficit in speech intelligibility was not associated with impaired pitch perception in amusia. These findings provide evidence for impaired speech comprehension in congenital amusia, suggesting that the deficit of amusics extends beyond pitch processing and includes segmental processing. Copyright © 2014 Elsevier Ltd. All rights reserved.
Spin-Off Successes of SETI Research at Berkeley
NASA Astrophysics Data System (ADS)
Douglas, K. A.; Anderson, D. P.; Bankay, R.; Chen, H.; Cobb, J.; Korpela, E. J.; Lebofsky, M.; Parsons, A.; von Korff, J.; Werthimer, D.
2009-12-01
Our group contributes to the Search for Extra-Terrestrial Intelligence (SETI) by developing and using world-class signal processing computers to analyze data collected on the Arecibo telescope. Although no patterned signal of extra-terrestrial origin has yet been detected, and the immediate prospects for making such a detection are highly uncertain, the SETI@home project has nonetheless proven the value of pursuing such research through its impact on the fields of distributed computing, real-time signal processing, and radio astronomy. The SETI@home project has spun off the Center for Astronomy Signal Processing and Electronics Research (CASPER) and the Berkeley Open Infrastructure for Networked Computing (BOINC), both of which are responsible for catalyzing a smorgasbord of new research in scientific disciplines in countries around the world. Futhermore, the data collected and archived for the SETI@home project is proving valuable in data-mining experiments for mapping neutral galatic hydrogen and for detecting black-hole evaporation.
Wide-bandwidth high-resolution search for extraterrestrial intelligence
NASA Technical Reports Server (NTRS)
Horowitz, Paul
1992-01-01
This interim report summarizes the research accomplished during the initial 6-month period of the grant. Activities associated with antenna configurations, the channelizing downconverter, the fast Fourier transform array, the DSP (digital signal processing) array, and the backend and UNIX workstation are discussed. Publications submitted during the reporting period are listed.
Radiofrequency/Microwave Radiation Biological Effects and Safety Standards: A Review
1994-06-01
reported that a 50 year old woman had developed cataracts after intermittent exposure to a 2.45 GHz microwave oven. The incident power density levels were...include: Survelance, Communications, Command and Control, Intelligence, Signal Processing, Computer Sience and Technology, Electrom Technology, Photoracs and laiity Saences. S* I l I
Portable Intelligent Tritium in Air Monitor
DOE Office of Scientific and Technical Information (OSTI.GOV)
Purghel, L.; Calin, M.R.; Bartos, D.
2005-07-15
The tritium detection method used for this monitor is original, patented in Romania. The detection unit consists of a single ionization chamber, a special fast preamplifier and a dedicated software associated to the detection unit, for signals processing. Some results concerning the tritium in relative strong gamma-ray fields are presented.
The Effectiveness of Clear Speech as a Masker
ERIC Educational Resources Information Center
Calandruccio, Lauren; Van Engen, Kristin; Dhar, Sumitrajit; Bradlow, Ann R.
2010-01-01
Purpose: It is established that speaking clearly is an effective means of enhancing intelligibility. Because any signal-processing scheme modeled after known acoustic-phonetic features of clear speech will likely affect both target and competing speech, it is important to understand how speech recognition is affected when a competing speech signal…
A search strategy for SETI - The search for extraterrestrial intelligence
NASA Technical Reports Server (NTRS)
Billingham, J.; Wolfe, J.; Edelson, R.; Gulkis, S.; Olsen, E.; Oliver, B.; Tarter, J.; Seeger, C.
1980-01-01
A search strategy is proposed for the detection of signals of extraterrestrial intelligent origin. It constitutes an exploration of a well defined volume of search space in the microwave region of the spectrum and envisages the use of a combination of sky survey and targeted star approaches. It is predicated on the use of existing antennas equipped with sophisticated multichannel spectrum analyzers and signal processing systems operating in the digital mode. The entire sky would be surveyed between 1 and 10 GHz with resolution bin widths down to 32 Hz. More than 700 nearby solar type stars and other selected interesting directions would be searched between 1 GHz and 3 GHz with bin widths down to 1 Hz. Particular emphasis would be placed on those solar type stars that are within 20 light years of earth.
Information theory, animal communication, and the search for extraterrestrial intelligence
NASA Astrophysics Data System (ADS)
Doyle, Laurance R.; McCowan, Brenda; Johnston, Simon; Hanser, Sean F.
2011-02-01
We present ongoing research in the application of information theory to animal communication systems with the goal of developing additional detectors and estimators for possible extraterrestrial intelligent signals. Regardless of the species, for intelligence (i.e., complex knowledge) to be transmitted certain rules of information theory must still be obeyed. We demonstrate some preliminary results of applying information theory to socially complex marine mammal species (bottlenose dolphins and humpback whales) as well as arboreal squirrel monkeys, because they almost exclusively rely on vocal signals for their communications, producing signals which can be readily characterized by signal analysis. Metrics such as Zipf's Law and higher-order information-entropic structure are emerging as indicators of the communicative complexity characteristic of an "intelligent message" content within these animals' signals, perhaps not surprising given these species' social complexity. In addition to human languages, for comparison we also apply these metrics to pulsar signals—perhaps (arguably) the most "organized" of stellar systems—as an example of astrophysical systems that would have to be distinguished from an extraterrestrial intelligence message by such information theoretic filters. We also look at a message transmitted from Earth (Arecibo Observatory) that contains a lot of meaning but little information in the mathematical sense we define it here. We conclude that the study of non-human communication systems on our own planet can make a valuable contribution to the detection of extraterrestrial intelligence by providing quantitative general measures of communicative complexity. Studying the complex communication systems of other intelligent species on our own planet may also be one of the best ways to deprovincialize our thinking about extraterrestrial communication systems in general.
NASA Astrophysics Data System (ADS)
Yang, Wen-Xian
2006-05-01
Available machine fault diagnostic methods show unsatisfactory performances on both on-line and intelligent analyses because their operations involve intensive calculations and are labour intensive. Aiming at improving this situation, this paper describes the development of an intelligent approach by using the Genetic Programming (abbreviated as GP) method. Attributed to the simple calculation of the mathematical model being constructed, different kinds of machine faults may be diagnosed correctly and quickly. Moreover, human input is significantly reduced in the process of fault diagnosis. The effectiveness of the proposed strategy is validated by an illustrative example, in which three kinds of valve states inherent in a six-cylinders/four-stroke cycle diesel engine, i.e. normal condition, valve-tappet clearance and gas leakage faults, are identified. In the example, 22 mathematical functions have been specially designed and 8 easily obtained signal features are used to construct the diagnostic model. Different from existing GPs, the diagnostic tree used in the algorithm is constructed in an intelligent way by applying a power-weight coefficient to each feature. The power-weight coefficients vary adaptively between 0 and 1 during the evolutionary process. Moreover, different evolutionary strategies are employed, respectively for selecting the diagnostic features and functions, so that the mathematical functions are sufficiently utilized and in the meantime, the repeated use of signal features may be fully avoided. The experimental results are illustrated diagrammatically in the following sections.
Comparing Binaural Pre-processing Strategies II
Hu, Hongmei; Krawczyk-Becker, Martin; Marquardt, Daniel; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Bomke, Katrin; Plotz, Karsten; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias
2015-01-01
Several binaural audio signal enhancement algorithms were evaluated with respect to their potential to improve speech intelligibility in noise for users of bilateral cochlear implants (CIs). 50% speech reception thresholds (SRT50) were assessed using an adaptive procedure in three distinct, realistic noise scenarios. All scenarios were highly nonstationary, complex, and included a significant amount of reverberation. Other aspects, such as the perfectly frontal target position, were idealized laboratory settings, allowing the algorithms to perform better than in corresponding real-world conditions. Eight bilaterally implanted CI users, wearing devices from three manufacturers, participated in the study. In all noise conditions, a substantial improvement in SRT50 compared to the unprocessed signal was observed for most of the algorithms tested, with the largest improvements generally provided by binaural minimum variance distortionless response (MVDR) beamforming algorithms. The largest overall improvement in speech intelligibility was achieved by an adaptive binaural MVDR in a spatially separated, single competing talker noise scenario. A no-pre-processing condition and adaptive differential microphones without a binaural link served as the two baseline conditions. SRT50 improvements provided by the binaural MVDR beamformers surpassed the performance of the adaptive differential microphones in most cases. Speech intelligibility improvements predicted by instrumental measures were shown to account for some but not all aspects of the perceptually obtained SRT50 improvements measured in bilaterally implanted CI users. PMID:26721921
DOT National Transportation Integrated Search
2015-03-01
The Connected Vehicle Mobility Policy team (herein, policy team) developed this report to document policy considerations for the Multi-Modal Intelligent Traffic Signal System, or MMITSS. MMITSS comprises a bundle of dynamic mobility application...
Selected examples of intelligent (micro) sensor systems: state-of-the-art and tendencies
NASA Astrophysics Data System (ADS)
Hauptmann, Peter R.
2006-03-01
The capability of intelligent sensors to have more intelligence built into them continues to drive their application in areas including automotive, aerospace and defense, industrial, intelligent house and wear, medical and homeland security. In principle it is difficult to overestimate the importance of intelligent (micro) sensors or sensor systems within advanced societies but one characteristic feature is the global market for sensors, which is now about 20 billion annually. Therefore sensors or sensor systems play a dominant role in many fields from the macro sensor in manufacturing industry down to the miniaturized sensor for medical applications. The diversity of sensors precludes a complete description of the state-of-the-art; selected examples will illustrate the current situation. MEMS (microelectromechanical systems) devices are of special interest in the context of micro sensor systems. In past the main requirements of a sensor were in terms of metrological performance. The electrical (or optical) signal produced by the sensor needed to match the measure relatively accurately. Such basic functionality is no longer sufficient. Data processing near the sensor, the extraction of more information than just the direct sensor information by signal analysis, system aspects and multi-sensor information are the new demands. A shifting can be observed away from aiming to design perfect single-function transducers and towards the utilization of system-based sensors as system components. In the ideal case such systems contain sensors, actuators and electronics. They can be realized in monolithic, hybrid or discrete form—which kind is used depends on the application. In this article the state-of-the-art of intelligent sensors or sensor systems is reviewed using selected examples. Future trends are deduced.
Do potential SETI signals need to be decontaminated?
NASA Astrophysics Data System (ADS)
Carrigan, Richard A., Jr.
2006-01-01
Biological contamination from space samples is a remote but accepted possibility. Signals received by searches for extraterrestrial intelligence (SETI) could also contain harmful information in the spirit of a computer virus, the so-called "SETI Hacker" hypothesis. Over the last four decades extraterrestrial intelligence searches have given little consideration to this possibility. Some argue that information in an extraterrestrial signal could not attack a terrestrial computer because the computer logic and code is idiosyncratic and constitutes an impenetrable firewall. Suggestions are given on how to probe these arguments. Measures for decontaminating extraterrestrial intelligence signals (ETI) are discussed. Modifications to the current SETI detection protocol may be appropriate. Beyond that, the potential character of ETI message content requires much broader discussion.
Phytometric intelligence sensors
NASA Technical Reports Server (NTRS)
Seelig, Hans-Dieter (Inventor); Stoner, II, Richard J. (Inventor); Hoehn, Alexander (Inventor); Adams, III, William Walter (Inventor)
2010-01-01
Methods and apparatus for determining when plants require watering, and methods of attending to the watering of plants including signaling the grower that the plants are in need of hydration are provided. The novel methods include real-time measurement of plant metabolics and phytometric physiology changes of intrinsic physical or behavioral traits within the plant such as determining physiological flux measurement of enzyme flux due to environmental changes such as the wind and drought stress, soil and plant mineral deficiencies, or the interaction with a bio-control for organic disease control including, cell movement, signal transduction, internal chemical processes and external environmental processes including when plants require watering, and methods of attending to the watering of plants including signaling the grower that the plants are in need of hydration.
NASA Technical Reports Server (NTRS)
Chan, Jeffrey W.; Simpson, Carol A.
1990-01-01
Active Noise Reduction (ANR) is a new technology which can reduce the level of aircraft cockpit noise that reaches the pilot's ear while simultaneously improving the signal to noise ratio for voice communications and other information bearing sound signals in the cockpit. A miniature, ear-cup mounted ANR system was tested to determine whether speech intelligibility is better for helicopter pilots using ANR compared to a control condition of ANR turned off. Two signal to noise ratios (S/N), representative of actual cockpit conditions, were used for the ratio of the speech to cockpit noise sound pressure levels. Speech intelligibility was significantly better with ANR compared to no ANR for both S/N conditions. Variability of speech intelligibility among pilots was also significantly less with ANR. When the stock helmet was used with ANR turned off, the average PB Word speech intelligibility score was below the Normally Acceptable level. In comparison, it was above that level with ANR on in both S/N levels.
Smiljanić, Rajka; Bradlow, Ann R.
2011-01-01
This study investigated how native language background interacts with speaking style adaptations in determining levels of speech intelligibility. The aim was to explore whether native and high proficiency non-native listeners benefit similarly from native and non-native clear speech adjustments. The sentence-in-noise perception results revealed that fluent non-native listeners gained a large clear speech benefit from native clear speech modifications. Furthermore, proficient non-native talkers in this study implemented conversational-to-clear speaking style modifications in their second language (L2) that resulted in significant intelligibility gain for both native and non-native listeners. The results of the accentedness ratings obtained for native and non-native conversational and clear speech sentences showed that while intelligibility was improved, the presence of foreign accent remained constant in both speaking styles. This suggests that objective intelligibility and subjective accentedness are two independent dimensions of non-native speech. Overall, these results provide strong evidence that greater experience in L2 processing leads to improved intelligibility in both production and perception domains. These results also demonstrated that speaking style adaptations along with less signal distortion can contribute significantly towards successful native and non-native interactions. PMID:22225056
NASA Astrophysics Data System (ADS)
Zhang, Meijun; Tang, Jian; Zhang, Xiaoming; Zhang, Jiaojiao
2016-03-01
The high accurate classification ability of an intelligent diagnosis method often needs a large amount of training samples with high-dimensional eigenvectors, however the characteristics of the signal need to be extracted accurately. Although the existing EMD(empirical mode decomposition) and EEMD(ensemble empirical mode decomposition) are suitable for processing non-stationary and non-linear signals, but when a short signal, such as a hydraulic impact signal, is concerned, their decomposition accuracy become very poor. An improve EEMD is proposed specifically for short hydraulic impact signals. The improvements of this new EEMD are mainly reflected in four aspects, including self-adaptive de-noising based on EEMD, signal extension based on SVM(support vector machine), extreme center fitting based on cubic spline interpolation, and pseudo component exclusion based on cross-correlation analysis. After the energy eigenvector is extracted from the result of the improved EEMD, the fault pattern recognition based on SVM with small amount of low-dimensional training samples is studied. At last, the diagnosis ability of improved EEMD+SVM method is compared with the EEMD+SVM and EMD+SVM methods, and its diagnosis accuracy is distinctly higher than the other two methods no matter the dimension of the eigenvectors are low or high. The improved EEMD is very propitious for the decomposition of short signal, such as hydraulic impact signal, and its combination with SVM has high ability for the diagnosis of hydraulic impact faults.
Rönnberg, Niklas; Rudner, Mary; Lunner, Thomas; Stenfelt, Stefan
2014-01-01
Listening in noise is often perceived to be effortful. This is partly because cognitive resources are engaged in separating the target signal from background noise, leaving fewer resources for storage and processing of the content of the message in working memory. The Auditory Inference Span Test (AIST) is designed to assess listening effort by measuring the ability to maintain and process heard information. The aim of this study was to use AIST to investigate the effect of background noise types and signal-to-noise ratio (SNR) on listening effort, as a function of working memory capacity (WMC) and updating ability (UA). The AIST was administered in three types of background noise: steady-state speech-shaped noise, amplitude modulated speech-shaped noise, and unintelligible speech. Three SNRs targeting 90% speech intelligibility or better were used in each of the three noise types, giving nine different conditions. The reading span test assessed WMC, while UA was assessed with the letter memory test. Twenty young adults with normal hearing participated in the study. Results showed that AIST performance was not influenced by noise type at the same intelligibility level, but became worse with worse SNR when background noise was speech-like. Performance on AIST also decreased with increasing memory load level. Correlations between AIST performance and the cognitive measurements suggested that WMC is of more importance for listening when SNRs are worse, while UA is of more importance for listening in easier SNRs. The results indicated that in young adults with normal hearing, the effort involved in listening in noise at high intelligibility levels is independent of the noise type. However, when noise is speech-like and intelligibility decreases, listening effort increases, probably due to extra demands on cognitive resources added by the informational masking created by the speech fragments and vocal sounds in the background noise. PMID:25566159
Rönnberg, Niklas; Rudner, Mary; Lunner, Thomas; Stenfelt, Stefan
2014-01-01
Listening in noise is often perceived to be effortful. This is partly because cognitive resources are engaged in separating the target signal from background noise, leaving fewer resources for storage and processing of the content of the message in working memory. The Auditory Inference Span Test (AIST) is designed to assess listening effort by measuring the ability to maintain and process heard information. The aim of this study was to use AIST to investigate the effect of background noise types and signal-to-noise ratio (SNR) on listening effort, as a function of working memory capacity (WMC) and updating ability (UA). The AIST was administered in three types of background noise: steady-state speech-shaped noise, amplitude modulated speech-shaped noise, and unintelligible speech. Three SNRs targeting 90% speech intelligibility or better were used in each of the three noise types, giving nine different conditions. The reading span test assessed WMC, while UA was assessed with the letter memory test. Twenty young adults with normal hearing participated in the study. Results showed that AIST performance was not influenced by noise type at the same intelligibility level, but became worse with worse SNR when background noise was speech-like. Performance on AIST also decreased with increasing memory load level. Correlations between AIST performance and the cognitive measurements suggested that WMC is of more importance for listening when SNRs are worse, while UA is of more importance for listening in easier SNRs. The results indicated that in young adults with normal hearing, the effort involved in listening in noise at high intelligibility levels is independent of the noise type. However, when noise is speech-like and intelligibility decreases, listening effort increases, probably due to extra demands on cognitive resources added by the informational masking created by the speech fragments and vocal sounds in the background noise.
NASA Astrophysics Data System (ADS)
Zepf, Joachim; Rufa, Gerhard
1994-04-01
This paper focuses on the transient performance analysis of the congestion and flow control mechanisms in CCITT Signaling System No. 7 (SS7). Special attention is directed to the impacts of the introduction of intelligent services and new applications, e.g., Freephone, credit card services, user-to-user signaling, etc. In particular, we show that signaling traffic characteristics like signaling scenarios or signaling message length as well as end-to-end signaling capabilities have a significant influence on the congestion and flow control and, therefore, on the real-time signaling performance. One important result of our performance studies is that if, e.g., intelligent services are introduced, the SS7 congestion and flow control does not work correctly. To solve this problem, some reinvestigations into these mechanisms would be necessary. Therefore, some approaches, e.g., modification of the Signaling Connection Control Part (SCCP) congestion control, usage of the SCCP relay function, or a redesign of the MTP flow control procedures are discussed in order to guarantee the efficacy of the congestion and flow control mechanisms also in the future.
2017-12-05
George Franz, David Pendall, and Jeffrey Steffan, “Host Nation Information Requirements – Achieving Unity of Understanding in Counterinsurgency... Information Dominance Center Fuels Comprehensive Operations,” SIGNAL, April 2010...1 Spell-outs of terms in parentheses: Diplomatic, Information , Military, Economic, Financial, Intelligence and Law Enforcement (DIMEFIL
Creative reflections-the strategic use of reflections in multitrack music production
NASA Astrophysics Data System (ADS)
Case, Alexander
2005-09-01
There is a long tradition of deliberately capturing and even synthesizing early reflections to enhance the music intended for loudspeaker playback. The desire to improve or at least alter the quality, audibility, intelligibility, stereo width, and/or uniqueness of the audio signal guides the recording engineer's use of the recording space, influences their microphone selection and placement, and inspires countless signal-processing approaches. This paper reviews contemporary multitrack production techniques that specifically take advantage of reflected sound energy for musical benefit.
Park, Hyojin; Ince, Robin A A; Schyns, Philippe G; Thut, Gregor; Gross, Joachim
2015-06-15
Humans show a remarkable ability to understand continuous speech even under adverse listening conditions. This ability critically relies on dynamically updated predictions of incoming sensory information, but exactly how top-down predictions improve speech processing is still unclear. Brain oscillations are a likely mechanism for these top-down predictions [1, 2]. Quasi-rhythmic components in speech are known to entrain low-frequency oscillations in auditory areas [3, 4], and this entrainment increases with intelligibility [5]. We hypothesize that top-down signals from frontal brain areas causally modulate the phase of brain oscillations in auditory cortex. We use magnetoencephalography (MEG) to monitor brain oscillations in 22 participants during continuous speech perception. We characterize prominent spectral components of speech-brain coupling in auditory cortex and use causal connectivity analysis (transfer entropy) to identify the top-down signals driving this coupling more strongly during intelligible speech than during unintelligible speech. We report three main findings. First, frontal and motor cortices significantly modulate the phase of speech-coupled low-frequency oscillations in auditory cortex, and this effect depends on intelligibility of speech. Second, top-down signals are significantly stronger for left auditory cortex than for right auditory cortex. Third, speech-auditory cortex coupling is enhanced as a function of stronger top-down signals. Together, our results suggest that low-frequency brain oscillations play a role in implementing predictive top-down control during continuous speech perception and that top-down control is largely directed at left auditory cortex. This suggests a close relationship between (left-lateralized) speech production areas and the implementation of top-down control in continuous speech perception. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Park, Hyojin; Ince, Robin A.A.; Schyns, Philippe G.; Thut, Gregor; Gross, Joachim
2015-01-01
Summary Humans show a remarkable ability to understand continuous speech even under adverse listening conditions. This ability critically relies on dynamically updated predictions of incoming sensory information, but exactly how top-down predictions improve speech processing is still unclear. Brain oscillations are a likely mechanism for these top-down predictions [1, 2]. Quasi-rhythmic components in speech are known to entrain low-frequency oscillations in auditory areas [3, 4], and this entrainment increases with intelligibility [5]. We hypothesize that top-down signals from frontal brain areas causally modulate the phase of brain oscillations in auditory cortex. We use magnetoencephalography (MEG) to monitor brain oscillations in 22 participants during continuous speech perception. We characterize prominent spectral components of speech-brain coupling in auditory cortex and use causal connectivity analysis (transfer entropy) to identify the top-down signals driving this coupling more strongly during intelligible speech than during unintelligible speech. We report three main findings. First, frontal and motor cortices significantly modulate the phase of speech-coupled low-frequency oscillations in auditory cortex, and this effect depends on intelligibility of speech. Second, top-down signals are significantly stronger for left auditory cortex than for right auditory cortex. Third, speech-auditory cortex coupling is enhanced as a function of stronger top-down signals. Together, our results suggest that low-frequency brain oscillations play a role in implementing predictive top-down control during continuous speech perception and that top-down control is largely directed at left auditory cortex. This suggests a close relationship between (left-lateralized) speech production areas and the implementation of top-down control in continuous speech perception. PMID:26028433
SETI - The search for extraterrestrial intelligence - Plans and rationale
NASA Technical Reports Server (NTRS)
Wolfe, J. H.; Billingham, J.; Edelson, R. E.; Crow, R. B.; Gulkis, S.; Olsen, E. T.; Oliver, B. M.; Peterson, A. M.
1981-01-01
The methodology and instrumentation of a 10 yr search for extraterrestrial intelligence (SETI) program by NASA, comprising 5 yr for instrumentation development and 5 yr for observations, is described. A full sky survey in two polarizations between 1.2 and 10 GHz with resolution binwidths down to 32 Hz, and a two polarization can between 1.2-3 GHz with resolution binwidths down to 1 Hz of 700 nearby solar type stars within 20 light years of earth will extend the sensitivity of previous surveys by 300 times and cover 20,000 times more frequency space. EM signals are perceived as the only means for detecting life outside the solar system, and the SETI effort is driven by the empirical experience that once a physical process has been observed to occur, its occurrence elsewhere is assured. Further discussion is given of the history of searches for life in the Universe, the SETI search strategy, instrumentation, and signal identification.
NASA Technical Reports Server (NTRS)
Albus, James S.
1996-01-01
The Real-time Control System (RCS) developed at NIST and elsewhere over the past two decades defines a reference model architecture for design and analysis of complex intelligent control systems. The RCS architecture consists of a hierarchically layered set of functional processing modules connected by a network of communication pathways. The primary distinguishing feature of the layers is the bandwidth of the control loops. The characteristic bandwidth of each level is determined by the spatial and temporal integration window of filters, the temporal frequency of signals and events, the spatial frequency of patterns, and the planning horizon and granularity of the planners that operate at each level. At each level, tasks are decomposed into sequential subtasks, to be performed by cooperating sets of subordinate agents. At each level, signals from sensors are filtered and correlated with spatial and temporal features that are relevant to the control function being implemented at that level.
Bernstein, Joshua G.W.; Mehraei, Golbarg; Shamma, Shihab; Gallun, Frederick J.; Theodoroff, Sarah M.; Leek, Marjorie R.
2014-01-01
Background A model that can accurately predict speech intelligibility for a given hearing-impaired (HI) listener would be an important tool for hearing-aid fitting or hearing-aid algorithm development. Existing speech-intelligibility models do not incorporate variability in suprathreshold deficits that are not well predicted by classical audiometric measures. One possible approach to the incorporation of such deficits is to base intelligibility predictions on sensitivity to simultaneously spectrally and temporally modulated signals. Purpose The likelihood of success of this approach was evaluated by comparing estimates of spectrotemporal modulation (STM) sensitivity to speech intelligibility and to psychoacoustic estimates of frequency selectivity and temporal fine-structure (TFS) sensitivity across a group of HI listeners. Research Design The minimum modulation depth required to detect STM applied to an 86 dB SPL four-octave noise carrier was measured for combinations of temporal modulation rate (4, 12, or 32 Hz) and spectral modulation density (0.5, 1, 2, or 4 cycles/octave). STM sensitivity estimates for individual HI listeners were compared to estimates of frequency selectivity (measured using the notched-noise method at 500, 1000measured using the notched-noise method at 500, 2000, and 4000 Hz), TFS processing ability (2 Hz frequency-modulation detection thresholds for 500, 10002 Hz frequency-modulation detection thresholds for 500, 2000, and 4000 Hz carriers) and sentence intelligibility in noise (at a 0 dB signal-to-noise ratio) that were measured for the same listeners in a separate study. Study Sample Eight normal-hearing (NH) listeners and 12 listeners with a diagnosis of bilateral sensorineural hearing loss participated. Data Collection and Analysis STM sensitivity was compared between NH and HI listener groups using a repeated-measures analysis of variance. A stepwise regression analysis compared STM sensitivity for individual HI listeners to audiometric thresholds, age, and measures of frequency selectivity and TFS processing ability. A second stepwise regression analysis compared speech intelligibility to STM sensitivity and the audiogram-based Speech Intelligibility Index. Results STM detection thresholds were elevated for the HI listeners, but only for low rates and high densities. STM sensitivity for individual HI listeners was well predicted by a combination of estimates of frequency selectivity at 4000 Hz and TFS sensitivity at 500 Hz but was unrelated to audiometric thresholds. STM sensitivity accounted for an additional 40% of the variance in speech intelligibility beyond the 40% accounted for by the audibility-based Speech Intelligibility Index. Conclusions Impaired STM sensitivity likely results from a combination of a reduced ability to resolve spectral peaks and a reduced ability to use TFS information to follow spectral-peak movements. Combining STM sensitivity estimates with audiometric threshold measures for individual HI listeners provided a more accurate prediction of speech intelligibility than audiometric measures alone. These results suggest a significant likelihood of success for an STM-based model of speech intelligibility for HI listeners. PMID:23636210
2001-10-25
wavelet decomposition of signals and classification using neural network. Inputs to the system are the heart sound signals acquired by a stethoscope in a...Proceedings. pp. 415–418, 1990. [3] G. Ergun, “An intelligent diagnostic system for interpretation of arterpartum fetal heart rate tracings based on ANNs and...AN INTELLIGENT PATTERN RECOGNITION SYSTEM BASED ON NEURAL NETWORK AND WAVELET DECOMPOSITION FOR INTERPRETATION OF HEART SOUNDS I. TURKOGLU1, A
Moving Object Detection Using Scanning Camera on a High-Precision Intelligent Holder.
Chen, Shuoyang; Xu, Tingfa; Li, Daqun; Zhang, Jizhou; Jiang, Shenwang
2016-10-21
During the process of moving object detection in an intelligent visual surveillance system, a scenario with complex background is sure to appear. The traditional methods, such as "frame difference" and "optical flow", may not able to deal with the problem very well. In such scenarios, we use a modified algorithm to do the background modeling work. In this paper, we use edge detection to get an edge difference image just to enhance the ability of resistance illumination variation. Then we use a "multi-block temporal-analyzing LBP (Local Binary Pattern)" algorithm to do the segmentation. In the end, a connected component is used to locate the object. We also produce a hardware platform, the core of which consists of the DSP (Digital Signal Processor) and FPGA (Field Programmable Gate Array) platforms and the high-precision intelligent holder.
An intelligent remote control system for ECEI on EAST
NASA Astrophysics Data System (ADS)
Chen, Dongxu; Zhu, Yilun; Zhao, Zhenling; Qu, Chengming; Liao, Wang; Xie, Jinlin; Liu, Wandong
2017-08-01
An intelligent remote control system based on a power distribution unit (PDU) and Arduino has been designed for the electron cyclotron emission imaging (ECEI) system on Experimental Advanced Superconducting Tokamak (EAST). This intelligent system has three major functions: ECEI system reboot, measurement region adjustment and signal amplitude optimization. The observation region of ECEI can be modified for different physics proposals by remotely tuning the optical and electronics systems. Via the remote adjustment of the attenuation level, the ECEI intermediate frequency signal amplitude can be efficiently optimized. The remote control system provides a feasible and reliable solution for the improvement of signal quality and the efficiency of the ECEI diagnostic system, which is also valuable for other diagnostic systems.
Searching for extraterrestrial intelligence - The ultimate exploration
NASA Technical Reports Server (NTRS)
Black, D.; Tarter, J.; Cuzzi, J. N.; Conners, M.; Clark, T. A.
1977-01-01
A survey highlighting the central issues of the SETI program (Search for Extraterrestrial Intelligence), including its rationale, scope, search problems, and goals is presented. Electromagnetic radiation is suggested as the most likely means via which knowledge of extraterrestrial intelligence will be obtained, and the variables governing these signals are discussed, including: signal frequency and polarization, state, possible coordinates, and signal duration. The modern history of SETI and NASA's involvement is briefly reviewed, and the search strategies used by the Jet Propulsion Laboratory and the Ames Research Center are discussed and compared. Some of the potential scientific and cultural impacts of the SETI program are mentioned, noting advancements in technological, biological, and chemical research.
ERIC Educational Resources Information Center
Hommel, Bernhard; Colzato, Lorenza S.; Scorolli, Claudia; Borghi, Anna M.; van den Wildenberg, Wery P. M.
2011-01-01
Previous findings suggest that religion has a specific impact on attentional processes. Here we show that religion also affects action control. Experiment 1 compared Dutch Calvinists and Dutch atheists, matched for age, sex, intelligence, education, and cultural and socio-economic background, and Experiment 2 compared Italian Catholics with…
NASA Astrophysics Data System (ADS)
Herzing, Denise L.
2014-02-01
Intelligence has historically been studied by comparing nonhuman cognitive and language abilities with human abilities. Primate-like species, which show human-like anatomy and share evolutionary lineage, have been the most studied. However, when comparing animals of non-primate origins our abilities to profile the potential for intelligence remains inadequate. Historically our measures for nonhuman intelligence have included a variety of tools: (1) physical measurements - brain to body ratio, brain structure/convolution/neural density, presence of artifacts and physical tools, (2) observational and sensory measurements - sensory signals, complexity of signals, cross-modal abilities, social complexity, (3) data mining - information theory, signal/noise, pattern recognition, (4) experimentation - memory, cognition, language comprehension/use, theory of mind, (5) direct interfaces - one way and two way interfaces with primates, dolphins, birds and (6) accidental interactions - human/animal symbiosis, cross-species enculturation. Because humans tend to focus on "human-like" attributes and measures and scientists are often unwilling to consider other "types" of intelligence that may not be human equated, our abilities to profile "types" of intelligence that differ on a variety of scales is weak. Just as biologists stretch their definitions of life to look at extremophiles in unusual conditions, so must we stretch our descriptions of types of minds and begin profiling, rather than equating, other life forms we may encounter.
Computational problems and signal processing in SETI
NASA Technical Reports Server (NTRS)
Deans, Stanley R.; Cullers, D. K.; Stauduhar, Richard
1991-01-01
The Search for Extraterrestrial Intelligence (SETI), currently being planned at NASA, will require that an enormous amount of data (on the order of 10 exp 11 distinct signal paths for a typical observation) be analyzed in real time by special-purpose hardware. Even though the SETI system design is not based on maximum entropy and Bayesian methods (partly due to the real-time processing constraint), it is expected that enough data will be saved to be able to apply these and other methods off line where computational complexity is not an overriding issue. Interesting computational problems that relate directly to the system design for processing such an enormous amount of data have emerged. Some of these problems are discussed, along with the current status on their solution.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zepf, J.; Rufa, G.
1994-04-01
This paper focuses on the transient performance analysis of the congestion and flow control mechanisms in CCITT Signaling System No. 7 (SS7). Special attention is directed to the impacts of the introduction of intelligent services and new applications, e.g., Freephone, credit card services, user-to-user signaling, etc. In particular, we show that signaling traffic characteristics like signaling scenarios or signaling message length as well as end-to-end signaling capabilities have a significant influence on the congestion and flow control and, therefore, on the real-time signaling performance. One important result of our performance studies is that if, e.g., intelligent services are introduced, themore » SS7 congestion and flow control does not work correctly. To solve this problem, some reinvestigations into these mechanisms would be necessary. Therefore, some approaches, e.g., modification of the Signaling Connection Control Part (SCCP) congestion control, usage of the SCCP relay function, or a redesign of the MTP flow control procedures are discussed in order to guarantee the efficacy of the congestion and flow control mechanisms also in the future. 16 refs.« less
Intelligence, Information Technology, and Information Warfare.
ERIC Educational Resources Information Center
Davies, Philip H. J.
2002-01-01
Addresses the use of information technology for intelligence and information warfare in the context of national security and reviews the status of clandestine collection. Discusses hacking, human agent collection, signal interception, covert action, counterintelligence and security, and communications between intelligence producers and consumers…
Implementation of Integrated System Fault Management Capability
NASA Technical Reports Server (NTRS)
Figueroa, Fernando; Schmalzel, John; Morris, Jon; Smith, Harvey; Turowski, Mark
2008-01-01
Fault Management to support rocket engine test mission with highly reliable and accurate measurements; while improving availability and lifecycle costs. CORE ELEMENTS: Architecture, taxonomy, and ontology (ATO) for DIaK management. Intelligent Sensor Processes; Intelligent Element Processes; Intelligent Controllers; Intelligent Subsystem Processes; Intelligent System Processes; Intelligent Component Processes.
"Fast" Is Not "Real-Time": Designing Effective Real-Time AI Systems
NASA Astrophysics Data System (ADS)
O'Reilly, Cindy A.; Cromarty, Andrew S.
1985-04-01
Realistic practical problem domains (such as robotics, process control, and certain kinds of signal processing) stand to benefit greatly from the application of artificial intelligence techniques. These problem domains are of special interest because they are typified by complex dynamic environments in which the ability to select and initiate a proper response to environmental events in real time is a strict prerequisite to effective environmental interaction. Artificial intelligence systems developed to date have been sheltered from this real-time requirement, however, largely by virtue of their use of simplified problem domains or problem representations. The plethora of colloquial and (in general) mutually inconsistent interpretations of the term "real-time" employed by workers in each of these domains further exacerbates the difficul-ties in effectively applying state-of-the-art problem solving tech-niques to time-critical problems. Indeed, the intellectual waters are by now sufficiently muddied that the pursuit of a rigorous treatment of intelligent real-time performance mandates the redevelopment of proper problem perspective on what "real-time" means, starting from first principles. We present a simple but nonetheless formal definition of real-time performance. We then undertake an analysis of both conventional techniques and AI technology with respect to their ability to meet substantive real-time performance criteria. This analysis provides a basis for specification of problem-independent design requirements for systems that would claim real-time performance. Finally, we discuss the application of these design principles to a pragmatic problem in real-time signal understanding.
The recognition of extraterrestrial artificial signals
NASA Technical Reports Server (NTRS)
Seeger, C. L.
1980-01-01
Considerations in the design of receivers for the detection and recognition of artificial microwave signals of extraterrestrial origin are discussed. Following a review of the objectives of SETI and the probable reception and detection characteristics of extraterrestrial signals, means for the improvement of the sensitivity, signal-to-noise ratios and on-line data processing capabilities of SETI receivers are indicated. The characteristics of the signals likely to be present at the output of an ultra-low-noise microwave receiver are then examined, including the system background noise, terrestrial radiations, astrophysical radiations, accidental artificial radiations of terrestrial origin, and intentional radiations produced by humans and by extraterrestrial intelligence. The classes of extraterrestrial signals likely to be detected, beacons and leakage signals, are considered, and options in the specification of gating and thresholding for a high-spectral resolution, high-time-resolution signal discriminator are indicated. Possible tests for the nonhuman origin of a received signal are also pointed out.
Biomedical signal and image processing.
Cerutti, Sergio; Baselli, Giuseppe; Bianchi, Anna; Caiani, Enrico; Contini, Davide; Cubeddu, Rinaldo; Dercole, Fabio; Rienzo, Luca; Liberati, Diego; Mainardi, Luca; Ravazzani, Paolo; Rinaldi, Sergio; Signorini, Maria; Torricelli, Alessandro
2011-01-01
Generally, physiological modeling and biomedical signal processing constitute two important paradigms of biomedical engineering (BME): their fundamental concepts are taught starting from undergraduate studies and are more completely dealt with in the last years of graduate curricula, as well as in Ph.D. courses. Traditionally, these two cultural aspects were separated, with the first one more oriented to physiological issues and how to model them and the second one more dedicated to the development of processing tools or algorithms to enhance useful information from clinical data. A practical consequence was that those who did models did not do signal processing and vice versa. However, in recent years,the need for closer integration between signal processing and modeling of the relevant biological systems emerged very clearly [1], [2]. This is not only true for training purposes(i.e., to properly prepare the new professional members of BME) but also for the development of newly conceived research projects in which the integration between biomedical signal and image processing (BSIP) and modeling plays a crucial role. Just to give simple examples, topics such as brain–computer machine or interfaces,neuroengineering, nonlinear dynamical analysis of the cardiovascular (CV) system,integration of sensory-motor characteristics aimed at the building of advanced prostheses and rehabilitation tools, and wearable devices for vital sign monitoring and others do require an intelligent fusion of modeling and signal processing competences that are certainly peculiar of our discipline of BME.
Fuller, Christina D.; Galvin, John J.; Maat, Bert; Free, Rolien H.; Başkent, Deniz
2014-01-01
Cochlear implants (CIs) are auditory prostheses that restore hearing via electrical stimulation of the auditory nerve. Compared to normal acoustic hearing, sounds transmitted through the CI are spectro-temporally degraded, causing difficulties in challenging listening tasks such as speech intelligibility in noise and perception of music. In normal hearing (NH), musicians have been shown to better perform than non-musicians in auditory processing and perception, especially for challenging listening tasks. This “musician effect” was attributed to better processing of pitch cues, as well as better overall auditory cognitive functioning in musicians. Does the musician effect persist when pitch cues are degraded, as it would be in signals transmitted through a CI? To answer this question, NH musicians and non-musicians were tested while listening to unprocessed signals or to signals processed by an acoustic CI simulation. The task increasingly depended on pitch perception: (1) speech intelligibility (words and sentences) in quiet or in noise, (2) vocal emotion identification, and (3) melodic contour identification (MCI). For speech perception, there was no musician effect with the unprocessed stimuli, and a small musician effect only for word identification in one noise condition, in the CI simulation. For emotion identification, there was a small musician effect for both. For MCI, there was a large musician effect for both. Overall, the effect was stronger as the importance of pitch in the listening task increased. This suggests that the musician effect may be more rooted in pitch perception, rather than in a global advantage in cognitive processing (in which musicians would have performed better in all tasks). The results further suggest that musical training before (and possibly after) implantation might offer some advantage in pitch processing that could partially benefit speech perception, and more strongly emotion and music perception. PMID:25071428
Forewarning of Debris flows using Intelligent Geophones
NASA Astrophysics Data System (ADS)
PK, I.; Ramesh, M. V.
2017-12-01
Landslides are one of the major catastrophic disasters that cause significant damage to human life and civil structures. Heavy rainfall on landslide prone areas can lead to most dangerous debris flow, where the materials such as mud, sand, soil, rock, water and air will move with greater velocity down the mountain. This sudden slope instability can lead to loss of human life and infrastructure. According to our knowledge, till now no one could identify the minutest factors that lead to initiation of the landslide. In this work, we aim to study the landslide phenomena deeply, using the landslide laboratory set up in our university. This unique mechanical simulator for landslide initiation is equipped with the capability to generate rainfall, seepage, etc., in the laboratory setup. Using this setup, we aim to study several landslide initiation scenarios generated by varying different parameters. The complete setup will be equipped with heterogeneous sensors such as rain gauge, moisture sensor, pore pressure sensor, strain gauges, tiltmeter, inclinometer, extensometer, and geophones. Our work will focus on the signals received from the intelligent geophone system for identifying the underground vibrations during a debris flow. Using the large amount of signals derived from the laboratory set up, we have performed detailed signal processing and data analysis to determine the fore warning signals captured by these heterogeneous sensors. Detailed study of these heterogeneous signals has provided the insights to forewarning the community based on the signals generated during the laboratory tests. In this work we will describe the details of the design, development, methodology, results, inferences and the suggestion for the next step to detect and forewarn the students. The response of intelligent geophone sensors at the time of failure, failure style and subsequent debris flow for heterogeneous soil layers were studied, thus helping in the development of fore warning systems for debris flows.
The interaction of acoustic and linguistic grouping cues in auditory object formation
NASA Astrophysics Data System (ADS)
Shapley, Kathy; Carrell, Thomas
2005-09-01
One of the earliest explanations for good speech intelligibility in poor listening situations was context [Miller et al., J. Exp. Psychol. 41 (1951)]. Context presumably allows listeners to group and predict speech appropriately and is known as a top-down listening strategy. Amplitude comodulation is another mechanism that has been shown to improve sentence intelligibility. Amplitude comodulation provides acoustic grouping information without changing the linguistic content of the desired signal [Carrell and Opie, Percept. Psychophys. 52 (1992); Hu and Wang, Proceedings of ICASSP-02 (2002)] and is considered a bottom-up process. The present experiment investigated how amplitude comodulation and semantic information combined to improve speech intelligibility. Sentences with high- and low-predictability word sequences [Boothroyd and Nittrouer, J. Acoust. Soc. Am. 84 (1988)] were constructed in two different formats: time-varying sinusoidal sentences (TVS) and reduced-channel sentences (RC). The stimuli were chosen because they minimally represent the traditionally defined speech cues and therefore emphasized the importance of the high-level context effects and low-level acoustic grouping cues. Results indicated that semantic information did not influence intelligibility levels of TVS and RC sentences. In addition amplitude modulation aided listeners' intelligibility scores in the TVS condition but hindered listeners' intelligibility scores in the RC condition.
A comparative intelligibility study of single-microphone noise reduction algorithms.
Hu, Yi; Loizou, Philipos C
2007-09-01
The evaluation of intelligibility of noise reduction algorithms is reported. IEEE sentences and consonants were corrupted by four types of noise including babble, car, street and train at two signal-to-noise ratio levels (0 and 5 dB), and then processed by eight speech enhancement methods encompassing four classes of algorithms: spectral subtractive, sub-space, statistical model based and Wiener-type algorithms. The enhanced speech was presented to normal-hearing listeners for identification. With the exception of a single noise condition, no algorithm produced significant improvements in speech intelligibility. Information transmission analysis of the consonant confusion matrices indicated that no algorithm improved significantly the place feature score, significantly, which is critically important for speech recognition. The algorithms which were found in previous studies to perform the best in terms of overall quality, were not the same algorithms that performed the best in terms of speech intelligibility. The subspace algorithm, for instance, was previously found to perform the worst in terms of overall quality, but performed well in the present study in terms of preserving speech intelligibility. Overall, the analysis of consonant confusion matrices suggests that in order for noise reduction algorithms to improve speech intelligibility, they need to improve the place and manner feature scores.
Liu, Hui; Li, Yingzi; Zhang, Yingxu; Chen, Yifu; Song, Zihang; Wang, Zhenyu; Zhang, Suoxin; Qian, Jianqiang
2018-01-01
Proportional-integral-derivative (PID) parameters play a vital role in the imaging process of an atomic force microscope (AFM). Traditional parameter tuning methods require a lot of manpower and it is difficult to set PID parameters in unattended working environments. In this manuscript, an intelligent tuning method of PID parameters based on iterative learning control is proposed to self-adjust PID parameters of the AFM according to the sample topography. This method gets enough information about the output signals of PID controller and tracking error, which will be used to calculate the proper PID parameters, by repeated line scanning until convergence before normal scanning to learn the topography. Subsequently, the appropriate PID parameters are obtained by fitting method and then applied to the normal scanning process. The feasibility of the method is demonstrated by the convergence analysis. Simulations and experimental results indicate that the proposed method can intelligently tune PID parameters of the AFM for imaging different topographies and thus achieve good tracking performance. Copyright © 2017 Elsevier Ltd. All rights reserved.
Research on wheelchair robot control system based on EOG
NASA Astrophysics Data System (ADS)
Xu, Wang; Chen, Naijian; Han, Xiangdong; Sun, Jianbo
2018-04-01
The paper describes an intelligent wheelchair control system based on EOG. It can help disabled people improve their living ability. The system can acquire EOG signal from the user, detect the number of blink and the direction of glancing, and then send commands to the wheelchair robot via RS-232 to achieve the control of wheelchair robot. Wheelchair robot control system based on EOG is composed of processing EOG signal and human-computer interactive technology, which achieves a purpose of using conscious eye movement to control wheelchair robot.
Moving Object Detection Using Scanning Camera on a High-Precision Intelligent Holder
Chen, Shuoyang; Xu, Tingfa; Li, Daqun; Zhang, Jizhou; Jiang, Shenwang
2016-01-01
During the process of moving object detection in an intelligent visual surveillance system, a scenario with complex background is sure to appear. The traditional methods, such as “frame difference” and “optical flow”, may not able to deal with the problem very well. In such scenarios, we use a modified algorithm to do the background modeling work. In this paper, we use edge detection to get an edge difference image just to enhance the ability of resistance illumination variation. Then we use a “multi-block temporal-analyzing LBP (Local Binary Pattern)” algorithm to do the segmentation. In the end, a connected component is used to locate the object. We also produce a hardware platform, the core of which consists of the DSP (Digital Signal Processor) and FPGA (Field Programmable Gate Array) platforms and the high-precision intelligent holder. PMID:27775671
Ohlenforst, Barbara; Souza, Pamela E; MacDonald, Ewen N
2016-01-01
Previous work has shown that individuals with lower working memory demonstrate reduced intelligibility for speech processed with fast-acting compression amplification. This relationship has been noted in fluctuating noise, but the extent of noise modulation that must be present to elicit such an effect is unknown. This study expanded on previous study by exploring the effect of background noise modulations in relation to compression speed and working memory ability, using a range of signal to noise ratios. Twenty-six older participants between ages 61 and 90 years were grouped by high or low working memory according to their performance on a reading span test. Speech intelligibility was measured for low-context sentences presented in background noise, where the noise varied in the extent of amplitude modulation. Simulated fast- or slow-acting compression amplification combined with individual frequency-gain shaping was applied to compensate for the individual's hearing loss. Better speech intelligibility scores were observed for participants with high working memory when fast compression was applied than when slow compression was applied. The low working memory group behaved in the opposite way and performed better under slow compression compared with fast compression. There was also a significant effect of the extent of amplitude modulation in the background noise, such that the magnitude of the score difference (fast versus slow compression) depended on the number of talkers in the background noise. The presented signal to noise ratios were not a significant factor on the measured intelligibility performance. In agreement with earlier research, high working memory allowed better speech intelligibility when fast compression was applied in modulated background noise. In the present experiment, that effect was present regardless of the extent of background noise modulation.
The foundations of plant intelligence.
Trewavas, Anthony
2017-06-06
Intelligence is defined for wild plants and its role in fitness identified. Intelligent behaviour exhibited by single cells and systems similarity between the interactome and connectome indicates neural systems are not necessary for intelligent capabilities. Plants sense and respond to many environmental signals that are assessed to competitively optimize acquisition of patchily distributed resources. Situations of choice engender motivational states in goal-directed plant behaviour; consequent intelligent decisions enable efficient gain of energy over expenditure. Comparison of swarm intelligence and plant behaviour indicates the origins of plant intelligence lie in complex communication and is exemplified by cambial control of branch function. Error correction in behaviours indicates both awareness and intention as does the ability to count to five. Volatile organic compounds are used as signals in numerous plant interactions. Being complex in composition and often species and individual specific, they may represent the plant language and account for self and alien recognition between individual plants. Game theory has been used to understand competitive and cooperative interactions between plants and microbes. Some unexpected cooperative behaviour between individuals and potential aliens has emerged. Behaviour profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses.
The foundations of plant intelligence
2017-01-01
Intelligence is defined for wild plants and its role in fitness identified. Intelligent behaviour exhibited by single cells and systems similarity between the interactome and connectome indicates neural systems are not necessary for intelligent capabilities. Plants sense and respond to many environmental signals that are assessed to competitively optimize acquisition of patchily distributed resources. Situations of choice engender motivational states in goal-directed plant behaviour; consequent intelligent decisions enable efficient gain of energy over expenditure. Comparison of swarm intelligence and plant behaviour indicates the origins of plant intelligence lie in complex communication and is exemplified by cambial control of branch function. Error correction in behaviours indicates both awareness and intention as does the ability to count to five. Volatile organic compounds are used as signals in numerous plant interactions. Being complex in composition and often species and individual specific, they may represent the plant language and account for self and alien recognition between individual plants. Game theory has been used to understand competitive and cooperative interactions between plants and microbes. Some unexpected cooperative behaviour between individuals and potential aliens has emerged. Behaviour profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses. PMID:28479977
van den Tillaart-Haverkate, Maj; de Ronde-Brons, Inge; Dreschler, Wouter A; Houben, Rolph
2017-01-01
Single-microphone noise reduction leads to subjective benefit, but not to objective improvements in speech intelligibility. We investigated whether response times (RTs) provide an objective measure of the benefit of noise reduction and whether the effect of noise reduction is reflected in rated listening effort. Twelve normal-hearing participants listened to digit triplets that were either unprocessed or processed with one of two noise-reduction algorithms: an ideal binary mask (IBM) and a more realistic minimum mean square error estimator (MMSE). For each of these three processing conditions, we measured (a) speech intelligibility, (b) RTs on two different tasks (identification of the last digit and arithmetic summation of the first and last digit), and (c) subjective listening effort ratings. All measurements were performed at four signal-to-noise ratios (SNRs): -5, 0, +5, and +∞ dB. Speech intelligibility was high (>97% correct) for all conditions. A significant decrease in response time, relative to the unprocessed condition, was found for both IBM and MMSE for the arithmetic but not the identification task. Listening effort ratings were significantly lower for IBM than for MMSE and unprocessed speech in noise. We conclude that RT for an arithmetic task can provide an objective measure of the benefit of noise reduction. For young normal-hearing listeners, both ideal and realistic noise reduction can reduce RTs at SNRs where speech intelligibility is close to 100%. Ideal noise reduction can also reduce perceived listening effort.
Signal processing and control challenges for smart vehicles
NASA Astrophysics Data System (ADS)
Zhang, Hui; Braun, Simon G.
2017-03-01
Smart phones have changed not only the mobile phone market but also our society during the past few years. Could the next potential intelligent device may be the vehicle? Judging by the visibility, in all media, of the numerous attempts to develop autonomous vehicles, this is certainly one of the logical outcomes. Smart vehicles would be equipped with an advanced operating system such that the vehicles could communicate with others, optimize the operation to reduce fuel consumption and emissions, enhance safety, or even become self-driving. These combined new features of vehicles require instrumentation and hardware developments, fast signal processing/fusion, decision making and online optimization. Meanwhile, the inevitable increasing system complexity would certainly challenges the control unit design.
SPEECH PERCEPTION AS A TALKER-CONTINGENT PROCESS
Nygaard, Lynne C.; Sommers, Mitchell S.; Pisoni, David B.
2011-01-01
To determine how familiarity with a talker’s voice affects perception of spoken words, we trained two groups of subjects to recognize a set of voices over a 9-day period. One group then identified novel words produced by the same set of talkers at four signal-to-noise ratios. Control subjects identified the same words produced by a different set of talkers. The results showed that the ability to identify a talker’s voice improved intelligibility of novel words produced by that talker. The results suggest that speech perception may involve talker-contingent processes whereby perceptual learning of aspects of the vocal source facilitates the subsequent phonetic analysis of the acoustic signal. PMID:21526138
Speaker Localisation Using Time Difference of Arrival
2008-04-01
School of Electrical and Electronic Engineering of the University of Adelaide. His area of expertise and interest is in Signal Processing including audio ...support of Theatre intelligence capabilities. His recent research interests include: information visualisation , text and data mining, and speech and...by: steering microphone arrays to improve the quality of audio pickup for recording, communication and transcription; enhancing the separation – and
1993-12-01
72 D. MINES AND THE MILITARY-TECHNOLOGICAL REVOLUTION ...................................... 74 E. CUSTOMIZING THE TDD PROLIFERATION MARKET M...Data Storage & Peripherals - Systems Managmnt Technologies 4. Passive Sensors - Sensors and Signal Processing 5. Photonics - Electronic and...a reproducible procedure to allow customization of the model, provides the "guts" of the method. 18 Third, because they are not optimized for
Analysis of a crossed Bragg-cell acousto optical spectrometer for SETI
NASA Technical Reports Server (NTRS)
Gulkis, S.
1986-01-01
The search for radio signals from extraterrestrial intelligent (SETI) beings requires the use of large instantaneous bandwidth (500 MHz) and high resolution (20 Hz) spectrometers. Digital systems with a high degree of modularity can be used to provide this capability, and this method has been widely discussed. Another technique for meeting the SETI requirement is to use a crossed Bragg-cell spectrometer as described by Psaltis and Casasent (1979). This technique makes use of the Folded Spectrum concept, introduced by Thomas (1966). The Folded Spectrum is a two-dimensional Fourier Transform of a raster scanned one-dimensional signal. It is directly related to the long one-dimensional spectrum of the original signal and is ideally suited for optical signal processing.
Analysis of a crossed Bragg-cell acousto optical spectrometer for SETI
NASA Astrophysics Data System (ADS)
Gulkis, S.
1986-10-01
The search for radio signals from extraterrestrial intelligent (SETI) beings requires the use of large instantaneous bandwidth (500 MHz) and high resolution (20 Hz) spectrometers. Digital systems with a high degree of modularity can be used to provide this capability, and this method has been widely discussed. Another technique for meeting the SETI requirement is to use a crossed Bragg-cell spectrometer as described by Psaltis and Casasent (1979). This technique makes use of the Folded Spectrum concept, introduced by Thomas (1966). The Folded Spectrum is a two-dimensional Fourier Transform of a raster scanned one-dimensional signal. It is directly related to the long one-dimensional spectrum of the original signal and is ideally suited for optical signal processing.
An iconic approach to communicating musical concepts in interstellar messages
NASA Astrophysics Data System (ADS)
Vakoch, Douglas A.
2010-12-01
Some characteristics of terrestrial music may be meaningful to extraterrestrial civilizations by virtue of the connection between acoustics and mathematics—both of which might be known by technologically advanced extraterrestrial intelligence. For example, a fundamental characteristic of terrestrial polyphonic music is found the number of tones used various scales, insofar as the number of tones represents a compromise between competing musical demands; the number of tones in a scale, however, also reflects some of the perceptual characteristics of the species developing that music. Thus, in the process of communicating something about the structure of terrestrial music through interstellar messages, additional information about human perceptual and cognitive processes can also be conveyed. This paper also discusses methods for sending signals that bear information through the form of the very frequencies in which the signals are transmitted. If the challenges of creating intelligible messages are greater than often thought, the advantage of reduced conventionality of encoding the message by using an iconic format of this sort may be of significant value. Such an approach would allow the incremental introduction of musical concepts, somewhat akin to the step-by-step tutorials in mathematics and logic that form the basis of Freudenthal's Lincos.
Intelligent hearing aids: the next revolution.
Tao Zhang; Mustiere, Fred; Micheyl, Christophe
2016-08-01
The first revolution in hearing aids came from nonlinear amplification, which allows better compensation for both soft and loud sounds. The second revolution stemmed from the introduction of digital signal processing, which allows better programmability and more sophisticated algorithms. The third revolution in hearing aids is wireless, which allows seamless connectivity between a pair of hearing aids and with more and more external devices. Each revolution has fundamentally transformed hearing aids and pushed the entire industry forward significantly. Machine learning has received significant attention in recent years and has been applied in many other industries, e.g., robotics, speech recognition, genetics, and crowdsourcing. We argue that the next revolution in hearing aids is machine intelligence. In fact, this revolution is already quietly happening. We will review the development in at least three major areas: applications of machine learning in speech enhancement; applications of machine learning in individualization and customization of signal processing algorithms; applications of machine learning in improving the efficiency and effectiveness of clinical tests. With the advent of the internet of things, the above developments will accelerate. This revolution will bring patient satisfactions to a new level that has never been seen before.
An algorithm that improves speech intelligibility in noise for normal-hearing listeners.
Kim, Gibak; Lu, Yang; Hu, Yi; Loizou, Philipos C
2009-09-01
Traditional noise-suppression algorithms have been shown to improve speech quality, but not speech intelligibility. Motivated by prior intelligibility studies of speech synthesized using the ideal binary mask, an algorithm is proposed that decomposes the input signal into time-frequency (T-F) units and makes binary decisions, based on a Bayesian classifier, as to whether each T-F unit is dominated by the target or the masker. Speech corrupted at low signal-to-noise ratio (SNR) levels (-5 and 0 dB) using different types of maskers is synthesized by this algorithm and presented to normal-hearing listeners for identification. Results indicated substantial improvements in intelligibility (over 60% points in -5 dB babble) over that attained by human listeners with unprocessed stimuli. The findings from this study suggest that algorithms that can estimate reliably the SNR in each T-F unit can improve speech intelligibility.
St. Laurent, Georges; Savva, Yiannis A.; Kapranov, Philipp
2012-01-01
Perhaps no other topic in contemporary genomics has inspired such diverse viewpoints as the 95+% of the genome, previously known as “junk DNA,” that does not code for proteins. Here, we present a theory in which dark matter RNA plays a role in the generation of a landscape of spatial micro-domains coupled to the information signaling matrix of the nuclear landscape. Within and between these micro-domains, dark matter RNAs additionally function to tether RNA interacting proteins and complexes of many different types, and by doing so, allow for a higher performance of the various processes requiring them at ultra-fast rates. This improves signal to noise characteristics of RNA processing, trafficking, and epigenetic signaling, where competition and differential RNA binding among proteins drives the computational decisions inherent in regulatory events. PMID:22539933
Schlagenhauf, Florian; Rapp, Michael A.; Huys, Quentin J. M.; Beck, Anne; Wüstenberg, Torsten; Deserno, Lorenz; Buchholz, Hans-Georg; Kalbitzer, Jan; Buchert, Ralph; Kienast, Thorsten; Cumming, Paul; Plotkin, Michail; Kumakura, Yoshitaka; Grace, Anthony A.; Dolan, Raymond J.; Heinz, Andreas
2013-01-01
Fluid intelligence represents the capacity for flexible problem solving and rapid behavioral adaptation. Rewards drive flexible behavioral adaptation, in part via a teaching signal expressed as reward prediction errors in the ventral striatum, which has been associated with phasic dopamine release in animal studies. We examined a sample of 28 healthy male adults using multimodal imaging and biological parametric mapping with 1) functional magnetic resonance imaging during a reversal learning task and 2) in a subsample of 17 subjects also with positron emission tomography using 6-[18F]fluoro-L-DOPA to assess dopamine synthesis capacity. Fluid intelligence was measured using a battery of nine standard neuropsychological tests. Ventral striatal BOLD correlates of reward prediction errors were positively correlated with fluid intelligence and, in the right ventral striatum, also inversely correlated with dopamine synthesis capacity (FDOPA Kinapp). When exploring aspects of fluid intelligence, we observed that prediction error signaling correlates with complex attention and reasoning. These findings indicate that individual differences in the capacity for flexible problem solving may be driven by ventral striatal activation during reward-related learning, which in turn proved to be inversely associated with ventral striatal dopamine synthesis capacity. PMID:22344813
Hey, Matthias; Hocke, Thomas; Mauger, Stefan; Müller-Deile, Joachim
2016-11-01
Individual speech intelligibility was measured in quiet and noise for cochlear Implant recipients upgrading from the Freedom to the CP900 series sound processor. The postlingually deafened participants (n = 23) used either Nucleus CI24RE or CI512 cochlear implant, and currently wore a Freedom sound processor. A significant group mean improvement in speech intelligibility was found in quiet (Freiburg monosyllabic words at 50 dB SPL ) and in noise (adaptive Oldenburger sentences in noise) for the two CP900 series SmartSound programs compared to the Freedom program. Further analysis was carried out on individual's speech intelligibility outcomes in quiet and in noise. Results showed a significant improvement or decrement for some recipients when upgrading to the new programs. To further increase speech intelligibility outcomes when upgrading, an enhanced upgrade procedure is proposed that includes additional testing with different signal-processing schemes. Implications of this research are that future automated scene analysis and switching technologies could provide additional performance improvements by introducing individualized scene-dependent settings.
Wu, Yu-Hsiang; Stangl, Elizabeth; Pang, Carol; Zhang, Xuyang
2014-02-01
Little is known regarding the acoustic features of a stimulus used by listeners to determine the acceptable noise level (ANL). Features suggested by previous research include speech intelligibility (noise is unacceptable when it degrades speech intelligibility to a certain degree; the intelligibility hypothesis) and loudness (noise is unacceptable when the speech-to-noise loudness ratio is poorer than a certain level; the loudness hypothesis). The purpose of the study was to investigate if speech intelligibility or loudness is the criterion feature that determines ANL. To achieve this, test conditions were chosen so that the intelligibility and loudness hypotheses would predict different results. In Experiment 1, the effect of audiovisual (AV) and binaural listening on ANL was investigated; in Experiment 2, the effect of interaural correlation (ρ) on ANL was examined. A single-blinded, repeated-measures design was used. Thirty-two and twenty-five younger adults with normal hearing participated in Experiments 1 and 2, respectively. In Experiment 1, both ANL and speech recognition performance were measured using the AV version of the Connected Speech Test (CST) in three conditions: AV-binaural, auditory only (AO)-binaural, and AO-monaural. Lipreading skill was assessed using the Utley lipreading test. In Experiment 2, ANL and speech recognition performance were measured using the Hearing in Noise Test (HINT) in three binaural conditions, wherein the interaural correlation of noise was varied: ρ = 1 (N(o)S(o) [a listening condition wherein both speech and noise signals are identical across two ears]), -1 (NπS(o) [a listening condition wherein speech signals are identical across two ears whereas the noise signals of two ears are 180 degrees out of phase]), and 0 (N(u)S(o) [a listening condition wherein speech signals are identical across two ears whereas noise signals are uncorrelated across ears]). The results were compared to the predictions made based on the intelligibility and loudness hypotheses. The results of the AV and AO conditions appeared to support the intelligibility hypothesis due to the significant correlation between visual benefit in ANL (AV re: AO ANL) and (1) visual benefit in CST performance (AV re: AO CST) and (2) lipreading skill. The results of the N(o)S(o), NπS(o), and N(u)S(o) conditions negated the intelligibility hypothesis because binaural processing benefit (NπS(o) re: N(o)S(o), and N(u)S(o) re: N(o)S(o)) in ANL was not correlated to that in HINT performance. Instead, the results somewhat supported the loudness hypothesis because the pattern of ANL results across the three conditions (N(o)S(o) ≈ NπS(o) ≈ N(u)S(o) ANL) was more consistent with what was predicted by the loudness hypothesis (N(o)S(o) ≈ NπS(o) < N(u)S(o) ANL) than by the intelligibility hypothesis (NπS(o) < N(u)S(o) < N(o)S(o) ANL). The results of the binaural and monaural conditions supported neither hypothesis because (1) binaural benefit (binaural re: monaural) in ANL was not correlated to that in speech recognition performance, and (2) the pattern of ANL results across conditions (binaural < monaural ANL) was not consistent with the prediction made based on previous binaural loudness summation research (binaural ≥ monaural ANL). The study suggests that listeners may use multiple acoustic features to make ANL judgments. The binaural/monaural results showing that neither hypothesis was supported further indicate that factors other than speech intelligibility and loudness, such as psychological factors, may affect ANL. The weightings of different acoustic features in ANL judgments may vary widely across individuals and listening conditions. American Academy of Audiology.
NASA Astrophysics Data System (ADS)
Tingay, S. J.; Tremblay, C. D.; Croft, S.
2018-03-01
Following the results of the first systematic modern low-frequency search for extraterrestrial intelligence using the Murchison Widefield Array (MWA), which was directed toward a Galactic Center field, we report a second survey toward a Galactic Anticenter field. Using the MWA in the frequency range 99–122 MHz over a three-hour period, a 625 deg2 field centered on Orion KL (in the general direction of the Galactic Anticenter) was observed with a frequency resolution of 10 kHz. Within this field, 22 exoplanets are known. At the positions of these exoplanets, we searched for narrowband signals consistent with radio transmissions from intelligent civilizations. No such signals were found with a 5σ detection threshold. Our sample is significantly different to the 45 exoplanets previously studied with the MWA toward the Galactic Center, since the Galactic Center sample is dominated by exoplanets detected using microlensing, and hence at much larger distances than the exoplanets toward the Anticenter, found via radial velocity and transit detection methods. Our average effective sensitivity to extraterrestrial transmitter power is therefore much improved for the Anticenter sample. Added to this, our data processing techniques have improved, reducing our observational errors, leading to our best detection limit being reduced by approximately a factor of four compared to our previously published results.
A bibliography on the search for extraterrestrial intelligence
NASA Technical Reports Server (NTRS)
Mallove, E. F.; Connors, M. M.; Forward, R. L.; Paprotny, Z.
1978-01-01
This report presents a uniform compilation of works dealing with the search for extraterrestrial intelligence. Entries are by first author, with cross-reference by topic index and by periodical index. This bibliography updates earlier bibliographies on this general topic while concentrating on research related to listening for signals from extraterrestrial intelligence.
Horowitz, P; Matthews, B S; Forster, J; Linscott, I; Teague, C C; Chen, K; Backus, P
1986-01-01
Multichannel spectroscopy with millihertz resolution constitutes an attractive strategy for a microwave search for extraterrestrial intelligence (SETI), assuming the transmission of a narrow-band radiofrequency beacon. Such resolution matches the properties of the interstellar medium, and the necessary receiver Doppler corrections provide a high degree of interference rejection. We have constructed a frequency-agile swept receiver with an 8,388,608-channel spectrum analyzer, on-line signal recognition, and multithreshold archiving. A search of 250 Sun-like stars at 1.4 and 2.8 GHz has been carried out with the Arecibo 305-m antenna, and a meridian transit search of the northern sky is in progress at the Harvard-Smithsonian 26-m antenna. Successive spectra of 400 kHz at 0.05 Hz resolution are searched for features characteristic of an intentional narrowband beacon transmission. These spectra are centered on guessable ("magic") frequencies (such as the 21-cm hydrogen hyperfine line), referenced successively to the local standard of rest, the galactic barycenter, and the cosmic blackbody rest frame.
Call sign intelligibility improvement using a spatial auditory display
NASA Technical Reports Server (NTRS)
Begault, Durand R.
1993-01-01
A spatial auditory display was used to convolve speech stimuli, consisting of 130 different call signs used in the communications protocol of NASA's John F. Kennedy Space Center, to different virtual auditory positions. An adaptive staircase method was used to determine intelligibility levels of the signal against diotic speech babble, with spatial positions at 30 deg azimuth increments. Non-individualized, minimum-phase approximations of head-related transfer functions were used. The results showed a maximal intelligibility improvement of about 6 dB when the signal was spatialized to 60 deg or 90 deg azimuth positions.
Network-Capable Application Process and Wireless Intelligent Sensors for ISHM
NASA Technical Reports Server (NTRS)
Figueroa, Fernando; Morris, Jon; Turowski, Mark; Wang, Ray
2011-01-01
Intelligent sensor technology and systems are increasingly becoming attractive means to serve as frameworks for intelligent rocket test facilities with embedded intelligent sensor elements, distributed data acquisition elements, and onboard data acquisition elements. Networked intelligent processors enable users and systems integrators to automatically configure their measurement automation systems for analog sensors. NASA and leading sensor vendors are working together to apply the IEEE 1451 standard for adding plug-and-play capabilities for wireless analog transducers through the use of a Transducer Electronic Data Sheet (TEDS) in order to simplify sensor setup, use, and maintenance, to automatically obtain calibration data, and to eliminate manual data entry and error. A TEDS contains the critical information needed by an instrument or measurement system to identify, characterize, interface, and properly use the signal from an analog sensor. A TEDS is deployed for a sensor in one of two ways. First, the TEDS can reside in embedded, nonvolatile memory (typically flash memory) within the intelligent processor. Second, a virtual TEDS can exist as a separate file, downloadable from the Internet. This concept of virtual TEDS extends the benefits of the standardized TEDS to legacy sensors and applications where the embedded memory is not available. An HTML-based user interface provides a visual tool to interface with those distributed sensors that a TEDS is associated with, to automate the sensor management process. Implementing and deploying the IEEE 1451.1-based Network-Capable Application Process (NCAP) can achieve support for intelligent process in Integrated Systems Health Management (ISHM) for the purpose of monitoring, detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, mitigation to maintain operability, and integrated awareness of system health by the operator. It can also support local data collection and storage. This invention enables wide-area sensing and employs numerous globally distributed sensing devices that observe the physical world through the existing sensor network. This innovation enables distributed storage, distributed processing, distributed intelligence, and the availability of DiaK (Data, Information, and Knowledge) to any element as needed. It also enables the simultaneous execution of multiple processes, and represents models that contribute to the determination of the condition and health of each element in the system. The NCAP (intelligent process) can configure data-collection and filtering processes in reaction to sensed data, allowing it to decide when and how to adapt collection and processing with regard to sophisticated analysis of data derived from multiple sensors. The user will be able to view the sensing device network as a single unit that supports a high-level query language. Each query would be able to operate over data collected from across the global sensor network just as a search query encompasses millions of Web pages. The sensor web can preserve ubiquitous information access between the querier and the queried data. Pervasive monitoring of the physical world raises significant data and privacy concerns. This innovation enables different authorities to control portions of the sensing infrastructure, and sensor service authors may wish to compose services across authority boundaries.
Improved chemical identification from sensor arrays using intelligent algorithms
NASA Astrophysics Data System (ADS)
Roppel, Thaddeus A.; Wilson, Denise M.
2001-02-01
Intelligent signal processing algorithms are shown to improve identification rates significantly in chemical sensor arrays. This paper focuses on the use of independently derived sensor status information to modify the processing of sensor array data by using a fast, easily-implemented "best-match" approach to filling in missing sensor data. Most fault conditions of interest (e.g., stuck high, stuck low, sudden jumps, excess noise, etc.) can be detected relatively simply by adjunct data processing, or by on-board circuitry. The objective then is to devise, implement, and test methods for using this information to improve the identification rates in the presence of faulted sensors. In one typical example studied, utilizing separately derived, a-priori knowledge about the health of the sensors in the array improved the chemical identification rate by an artificial neural network from below 10 percent correct to over 99 percent correct. While this study focuses experimentally on chemical sensor arrays, the results are readily extensible to other types of sensor platforms.
Intelligent Sensors for Atomization Processing of Molten Metals and Alloys
1988-06-01
20ff. 12. Hirleman, Dan E. Particle Sizing by Optical , Nonimaging Techniques. Liquid Particle Size Measurement Techniques, ASTM, 1984, pp. 35ff. 13...sensors are based on electric, electromagnetic or optical principles, the latter being most developed in fields obviously related to atomization. Optical ...beams to observe various interference, diffraction, and heterodyning effects, and to observe, with high signal-to-noise ratio, even weak optical
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matteson, A.; Morris, R.; Tate, R.
1993-12-31
The acoustic signal produced by the gas metal arc welding (GMAW) arc contains information about the behavior of the arc column, the molten pool and droplet transfer. It is possible to detect some defect producing conditions from the acoustic signal from the GMAW arc. An intelligent sensor, called the Weld Acoustic Monitor (WAM) has been developed to take advantage of this acoustic information in order to provide real-time quality assessment information for process control. The WAM makes use of an Artificial Neural Network (ANN) to classify the characteristic arc acoustic signals of acceptable and unacceptable welds. The ANN used inmore » the Weld Acoustic Monitor developed its own set of rules for this classification problem by learning a data base of known GMAW acoustic signals.« less
On Intelligent Design and Planning Method of Process Route Based on Gun Breech Machining Process
NASA Astrophysics Data System (ADS)
Hongzhi, Zhao; Jian, Zhang
2018-03-01
The paper states an approach of intelligent design and planning of process route based on gun breech machining process, against several problems, such as complex machining process of gun breech, tedious route design and long period of its traditional unmanageable process route. Based on gun breech machining process, intelligent design and planning system of process route are developed by virtue of DEST and VC++. The system includes two functional modules--process route intelligent design and its planning. The process route intelligent design module, through the analysis of gun breech machining process, summarizes breech process knowledge so as to complete the design of knowledge base and inference engine. And then gun breech process route intelligently output. On the basis of intelligent route design module, the final process route is made, edited and managed in the process route planning module.
ERIC Educational Resources Information Center
Escultura, E. E.
2012-01-01
This paper explores the physics of intelligence and provides an overview of what happens in the brain when a person is engaged in mental activity that we classify under thought or intelligence. It traces the formation of a concept starting with reception of visible or detectable signals from the real world by and external to the sense organs,…
NASA Technical Reports Server (NTRS)
Aanstoos, J. V.; Snyder, W. E.
1981-01-01
Anticipated major advances in integrated circuit technology in the near future are described as well as their impact on satellite onboard signal processing systems. Dramatic improvements in chip density, speed, power consumption, and system reliability are expected from very large scale integration. Improvements are expected from very large scale integration enable more intelligence to be placed on remote sensing platforms in space, meeting the goals of NASA's information adaptive system concept, a major component of the NASA End-to-End Data System program. A forecast of VLSI technological advances is presented, including a description of the Defense Department's very high speed integrated circuit program, a seven-year research and development effort.
SEARCHING FOR EXTRATERRESTRIAL INTELLIGENCE SIGNALS IN ASTRONOMICAL SPECTRA, INCLUDING EXISTING DATA
DOE Office of Scientific and Technical Information (OSTI.GOV)
Borra, Ermanno F., E-mail: borra@phy.ulaval.ca
The main purpose of this article is to make astronomers aware that Searches for Extraterrestrial Intelligence (SETIs) can be carried out by analyzing standard astronomical spectra, including those they have already taken. Simplicity is the outstanding advantage of a search in spectra. The spectra can be analyzed by simple eye inspection or a few lines of code that uses Fourier transform software. Theory, confirmed by published experiments, shows that periodic signals in spectra can be easily generated by sending light pulses separated by constant time intervals. While part of this article, like all articles on SETIs, is highly speculative themore » basic physics is sound. In particular, technology now available on Earth could be used to send signals having the required energy to be detected at a target located 1000 lt-yr away. Extraterrestrial Intelligence (ETI) could use these signals to make us aware of their existence. For an ETI, the technique would also have the advantage that the signals could be detected both in spectra and searches for intensity pulses like those currently carried out on Earth.« less
Separation of Intercepted Multi-Radar Signals Based on Parameterized Time-Frequency Analysis
NASA Astrophysics Data System (ADS)
Lu, W. L.; Xie, J. W.; Wang, H. M.; Sheng, C.
2016-09-01
Modern radars use complex waveforms to obtain high detection performance and low probabilities of interception and identification. Signals intercepted from multiple radars overlap considerably in both the time and frequency domains and are difficult to separate with primary time parameters. Time-frequency analysis (TFA), as a key signal-processing tool, can provide better insight into the signal than conventional methods. In particular, among the various types of TFA, parameterized time-frequency analysis (PTFA) has shown great potential to investigate the time-frequency features of such non-stationary signals. In this paper, we propose a procedure for PTFA to separate overlapped radar signals; it includes five steps: initiation, parameterized time-frequency analysis, demodulating the signal of interest, adaptive filtering and recovering the signal. The effectiveness of the method was verified with simulated data and an intercepted radar signal received in a microwave laboratory. The results show that the proposed method has good performance and has potential in electronic reconnaissance applications, such as electronic intelligence, electronic warfare support measures, and radar warning.
Thunderstorm Hypothesis Reasoner
NASA Technical Reports Server (NTRS)
Mulvehill, Alice M.
1994-01-01
THOR is a knowledge-based system which incorporates techniques from signal processing, pattern recognition, and artificial intelligence (AI) in order to determine the boundary of small thunderstorms which develop and dissipate over the area encompassed by KSC and the Cape Canaveral Air Force Station. THOR interprets electric field mill data (derived from a network of electric field mills) by using heuristics and algorithms about thunderstorms that have been obtained from several domain specialists. THOR generates two forms of output: contour plots which visually describe the electric field activity over the network and a verbal interpretation of the activity. THOR uses signal processing and pattern recognition to detect signatures associated with noise or thunderstorm behavior in a near real time fashion from over 31 electrical field mills. THOR's AI component generates hypotheses identifying areas which are under a threat from storm activity, such as lightning. THOR runs on a VAX/VMS at the Kennedy Space Center. Its software is a coupling of C and FORTRAN programs, several signal processing packages, and an expert system development shell.
At what wavelengths should we search for signals from extraterrestrial intelligence?
Townes, C. H.
1983-01-01
It has often been concluded that searches for extraterrestrial intelligence (SETI) should concentrate on attempts to receive signals in the microwave region, the argument being given that communication can occur there at minimum broadcasted power. Such a conclusion is shown to result only under a restricted set of assumptions. If generalized types of detection are considered—in particular, photon detection rather than linear detection alone—and if advantage is taken of the directivity of telescopes at short wavelengths, then somewhat less power is required for communication at infrared wavelengths than in the microwave region. Furthermore, a variety of parameters other than power alone may be chosen for optimization by an extraterrestrial civilization. Hence, while partially satisfying arguments may be given about optimal wavelengths for a search for signals from extraterrestrial intelligence, considerable uncertainty must remain. PMID:16593279
At what wavelengths should we search for signals from extraterrestrial intelligence?
Townes, C H
1983-02-01
It has often been concluded that searches for extraterrestrial intelligence (SETI) should concentrate on attempts to receive signals in the microwave region, the argument being given that communication can occur there at minimum broadcasted power. Such a conclusion is shown to result only under a restricted set of assumptions. If generalized types of detection are considered-in particular, photon detection rather than linear detection alone-and if advantage is taken of the directivity of telescopes at short wavelengths, then somewhat less power is required for communication at infrared wavelengths than in the microwave region. Furthermore, a variety of parameters other than power alone may be chosen for optimization by an extraterrestrial civilization. Hence, while partially satisfying arguments may be given about optimal wavelengths for a search for signals from extraterrestrial intelligence, considerable uncertainty must remain.
NASA Technical Reports Server (NTRS)
Shewhart, Mark
1991-01-01
Statistical Process Control (SPC) charts are one of several tools used in quality control. Other tools include flow charts, histograms, cause and effect diagrams, check sheets, Pareto diagrams, graphs, and scatter diagrams. A control chart is simply a graph which indicates process variation over time. The purpose of drawing a control chart is to detect any changes in the process signalled by abnormal points or patterns on the graph. The Artificial Intelligence Support Center (AISC) of the Acquisition Logistics Division has developed a hybrid machine learning expert system prototype which automates the process of constructing and interpreting control charts.
Empirical modeling for intelligent, real-time manufacture control
NASA Technical Reports Server (NTRS)
Xu, Xiaoshu
1994-01-01
Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, nonlinear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS's to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System and the Welding Penetration Monitoring System, are discussed in the body of this paper.
Pavel, M; Sperling, G; Riedl, T; Vanderbeek, A
1987-12-01
To determine the limits of human observers' ability to identify visually presented American Sign Language (ASL), the contrast s and the amount of additive noise n in dynamic ASL images were varied independently. Contrast was tested over a 4:1 range; the rms signal-to-noise ratios (s/n) investigated were s/n = 1/4, 1/2, 1, and infinity (which is used to designate the original, uncontaminated images). Fourteen deaf subjects were tested with an intelligibility test composed of 85 isolated ASL signs, each 2-3 sec in length. For these ASL signs (64 x 96 pixels, 30 frames/sec), subjects' performance asymptotes between s/n = 0.5 and 1.0; further increases in s/n do not improve intelligibility. Intelligibility was found to depend only on s/n and not on contrast. A formulation in terms of logistic functions was proposed to derive intelligibility of ASL signs from s/n, sign familiarity, and sign difficulty. Familiarity (ignorance) is represented by additive signal-correlated noise; it represents the likelihood of a subject's knowing a particular ASL sign, and it adds to s/n. Difficulty is represented by a multiplicative difficulty coefficient; it represents the perceptual vulnerability of an ASL sign to noise and it adds to log(s/n).
Intelligent Optimization of Modulation Indexes in Unified Tracking and Communication System
NASA Astrophysics Data System (ADS)
Yang, Wei-wei; Cong, Bo; Huang, Qiong; Zhu, Li-wei
2016-02-01
In the unified tracking and communication system, the ranging signal and the telemetry, communication signals are used in the same channel. In the link budget, it is necessary to allocate the power reasonably, so as to ensure the performance of system and reduce the cost. In this paper, the nonlinear optimization problem is studied using intelligent optimization method. Simulation analysis results show that the proposed method is effective.
NASA Technical Reports Server (NTRS)
Gat, N.; Subramanian, S.; Barhen, J.; Toomarian, N.
1996-01-01
This paper reviews the activities at OKSI related to imaging spectroscopy presenting current and future applications of the technology. The authors discuss the development of several systems including hardware, signal processing, data classification algorithms and benchmarking techniques to determine algorithm performance. Signal processing for each application is tailored by incorporating the phenomenology appropriate to the process, into the algorithms. Pixel signatures are classified using techniques such as principal component analyses, generalized eigenvalue analysis and novel very fast neural network methods. The major hyperspectral imaging systems developed at OKSI include the Intelligent Missile Seeker (IMS) demonstration project for real-time target/decoy discrimination, and the Thermal InfraRed Imaging Spectrometer (TIRIS) for detection and tracking of toxic plumes and gases. In addition, systems for applications in medical photodiagnosis, manufacturing technology, and for crop monitoring are also under development.
NASA Astrophysics Data System (ADS)
Liu, Yang; Song, Fazhi; Yang, Xiaofeng; Dong, Yue; Tan, Jiubin
2018-06-01
Due to their structural simplicity, linear motors are increasingly receiving attention for use in high velocity and high precision applications. The force ripple, as a space-periodic disturbance, however, would deteriorate the achievable dynamic performance. Conventional force ripple measurement approaches are time-consuming and have high requirements on the experimental conditions. In this paper, a novel learning identification algorithm is proposed for force ripple intelligent measurement and compensation. Existing identification schemes always use all the error signals to update the parameters in the force ripple. However, the error induced by noise is non-effective for force ripple identification, and even deteriorates the identification process. In this paper only the most pertinent information in the error signal is utilized for force ripple identification. Firstly, the effective error signals caused by the reference trajectory and the force ripple are extracted by projecting the overall error signals onto a subspace spanned by the physical model of the linear motor as well as the sinusoidal model of the force ripple. The time delay in the linear motor is compensated in the basis functions. Then, a data-driven approach is proposed to design the learning gain. It balances the trade-off between convergence speed and robustness against noise. Simulation and experimental results validate the proposed method and confirm its effectiveness and superiority.
NASA Astrophysics Data System (ADS)
Lapshenkov, E. M.; Volkov, V. Y.; Kulagin, V. P.
2018-05-01
The article is devoted to the problem of pattern creation of the NMR sensor signal for subsequent recognition by the artificial neural network in the intelligent device "the electronic tongue". The specific problem of removing redundant data from the spin-spin relaxation signal pattern that is used as a source of information in analyzing the composition of oil and petroleum products is considered. The method is proposed that makes it possible to remove redundant data of the relaxation decay pattern but without introducing additional distortion. This method is based on combining some relaxation decay curve intervals that increment below the noise level such that the increment of the combined intervals is above the noise level. In this case, the relaxation decay curve samples that are located inside the combined intervals are removed from the pattern. This method was tested on the heavy-oil NMR signal patterns that were created by using the Carr-Purcell-Meibum-Gill (CPMG) sequence for recording the relaxation process. Parameters of CPMG sequence are: 100 μs - time interval between 180° pulses, 0.4s - duration of measurement. As a result, it was revealed that the proposed method allowed one to reduce the number of samples 15 times (from 4000 to 270), and the maximum detected root mean square error (RMS error) equals 0.00239 (equivalent to signal-to-noise ratio 418).
Brain entropy and human intelligence: A resting-state fMRI study
Calderone, Daniel; Morales, Leah J.
2018-01-01
Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns. PMID:29432427
Brain entropy and human intelligence: A resting-state fMRI study.
Saxe, Glenn N; Calderone, Daniel; Morales, Leah J
2018-01-01
Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns.
Ceci n'est pas une micromachine.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yarberry, Victor R.; Diegert, Carl F.
2010-03-01
The image created in reflected light DIC can often be interpreted as a true three-dimensional representation of the surface geometry, provided a clear distinction can be realized between raised and lowered regions in the specimen. It may be helpful if our definition of saliency embraces work on the human visual system (HVS) as well as the more abstract work on saliency, as it is certain that understanding by humans will always stand between recording of a useful signal from all manner of sensors and so-called actionable intelligence. A DARPA/DSO program lays down this requirement in a current program (Kruse 2010):more » The vision for the Neurotechnology for Intelligence Analysts (NIA) Program is to revolutionize the way that analysts handle intelligence imagery, increasing both the throughput of imagery to the analyst and overall accuracy of the assessments. Current computer-based target detection capabilities cannot process vast volumes of imagery with the speed, flexibility, and precision of the human visual system.« less
Intelligent Membranes: Dream or Reality?
Gugliuzza, Annarosa
2013-07-15
Intelligent materials are claimed to overcome current drawbacks associated with the attainment of high standards of life, health, security and defense. Membrane-based sensors represent a category of smart systems capable of providing a large number of benefits to different markets of textiles, biomedicine, environment, chemistry, agriculture, architecture, transport and energy. Intelligent membranes can be characterized by superior sensitivity, broader dynamic range and highly sophisticated mechanisms of autorecovery. These prerogatives are regarded as the result of multi-compartment arrays, where complementary functions can be accommodated and well-integrated. Based on the mechanism of "sense to act", stimuli-responsive membranes adapt themselves to surrounding environments, producing desired effects such as smart regulation of transport, wetting, transcription, hydrodynamics, separation, and chemical or energy conversion. Hopefully, the design of new smart devices easier to manufacture and assemble can be realized through the integration of sensing membranes with wireless networks, looking at the ambitious challenge to establish long-distance communications. Thus, the transfer of signals to collecting systems could allow continuous and real-time monitoring of data, events and/or processes.
Design of intelligent composites with life-cycle health management capabilities
NASA Astrophysics Data System (ADS)
Rosania, Colleen L.; Larrosa, Cecilia C.; Chang, Fu-Kuo
2015-03-01
Use of carbon fiber reinforced polymers (CFRPs) presents challenges because of their complex manufacturing processes and different damage mechanics in relation to legacy metal materials. New monitoring methods for manufacturing, quality verification, damage estimation, and prognosis are needed to use CFRPs safely and efficiently. This work evaluates the development of intelligent composite materials using integrated piezoelectric sensors to monitor the material during cure and throughout service life. These sensors are used to propagate ultrasonic waves through the structure for health monitoring. During manufacturing, data is collected at different stages during the cure cycle, detecting the changing material properties during cure and verifying quality and degree of cure. The same sensors can then be used with previously developed techniques to perform damage detection, such as impact detection and matrix crack density estimation. Real-time damage estimation can be combined with prognostic models to predict future propagation of damage in the material. In this work experimental results will be presented from composite coupons with embedded piezoelectric sensors. Cure monitoring and damage detection results derived from analysis of the ultrasonic sensor signal will be shown. Sensitive signal parameters to the different stimuli in both the time and frequency domains will be explored for this analysis. From these results, use of the same sensor networks from manufacturing throughout the life of the composite material will demonstrate the full life-cycle monitoring capability of these intelligent materials.
SETI - A preliminary search for narrowband signals at microwave frequencies
NASA Technical Reports Server (NTRS)
Cuzzi, J. N.; Clark, T. A.; Tarter, J. C.; Black, D. C.
1977-01-01
In the search for intelligent signals of extraterrestrial origin, certain forms of signals merit immediate and special attention. Extremely narrowband signals of spectral width similar to our own television transmissions are most favored energetically and least likely to be confused with natural celestial emission. A search of selected stars has been initiated using observational and data processing techniques optimized for the detection of such signals. These techniques allow simultaneous observation of 10 to the 5th to 10 to the 6th channels within the observed spectral range. About two hundred nearby (within 80 LY) solar type stars have been observed at frequencies near the main microwave transitions of the hydroxyl radical. In addition, several molecular (hydroxyl) masers and other non-thermal sources have been observed in this way in order to uncover any possible fine spectral structure of natural origin and to investigate the potential of such an instrument for radioastronomy.
Lai, Ying-Hui; Chen, Fei; Wang, Syu-Siang; Lu, Xugang; Tsao, Yu; Lee, Chin-Hui
2017-07-01
In a cochlear implant (CI) speech processor, noise reduction (NR) is a critical component for enabling CI users to attain improved speech perception under noisy conditions. Identifying an effective NR approach has long been a key topic in CI research. Recently, a deep denoising autoencoder (DDAE) based NR approach was proposed and shown to be effective in restoring clean speech from noisy observations. It was also shown that DDAE could provide better performance than several existing NR methods in standardized objective evaluations. Following this success with normal speech, this paper further investigated the performance of DDAE-based NR to improve the intelligibility of envelope-based vocoded speech, which simulates speech signal processing in existing CI devices. We compared the performance of speech intelligibility between DDAE-based NR and conventional single-microphone NR approaches using the noise vocoder simulation. The results of both objective evaluations and listening test showed that, under the conditions of nonstationary noise distortion, DDAE-based NR yielded higher intelligibility scores than conventional NR approaches. This study confirmed that DDAE-based NR could potentially be integrated into a CI processor to provide more benefits to CI users under noisy conditions.
2012-04-10
builders . Human Intelligence (HUMINT) and Signals Intelligence (SIGINT) could then also be prioritized and employed accordingly for optimal 8...responsibility for digital and multimedia forensics, and DIA responsibility for forensic intelligence activities and programs.31 The Army is also currently...aligning functional oversight of Forensics, Biometrics, Law Enforcement, Detainee Operations, and Physical Security 11 under one overarching
Keller, M David; Ziriax, John M; Barns, William; Sheffield, Benjamin; Brungart, Douglas; Thomas, Tony; Jaeger, Bobby; Yankaskas, Kurt
2017-06-01
Noise, hearing loss, and electronic signal distortion, which are common problems in military environments, can impair speech intelligibility and thereby jeopardize mission success. The current study investigated the impact that impaired communication has on operational performance in a command and control environment by parametrically degrading speech intelligibility in a simulated shipborne Combat Information Center. Experienced U.S. Navy personnel served as the study participants and were required to monitor information from multiple sources and respond appropriately to communications initiated by investigators playing the roles of other personnel involved in a realistic Naval scenario. In each block of the scenario, an adaptive intelligibility modification system employing automatic gain control was used to adjust the signal-to-noise ratio to achieve one of four speech intelligibility levels on a Modified Rhyme Test: No Loss, 80%, 60%, or 40%. Objective and subjective measures of operational performance suggested that performance systematically degraded with decreasing speech intelligibility, with the largest drop occurring between 80% and 60%. These results confirm the importance of noise reduction, good communication design, and effective hearing conservation programs to maximize the operational effectiveness of military personnel. Published by Elsevier B.V.
NASA Technical Reports Server (NTRS)
Townes, C. H.
1979-01-01
Searches for extraterrestrial intelligence concentrate on attempts to receive signals in the microwave region, the argument being given that communication occurs there at minimum broadcasted power. Such a conclusion is shown to result only under a restricted set of assumptions. If generalized types of detection are considered, in particular photon detection rather than linear detection alone, and if advantage is taken of the directivity of telescopes at short wavelengths, then somewhat less power is required for communication at infrared wavelengths than in the microwave region. Furthermore, a variety of parameters other than power alone can be chosen for optimization by an extraterrestrial civilization.
The Brain as a Distributed Intelligent Processing System: An EEG Study
da Rocha, Armando Freitas; Rocha, Fábio Theoto; Massad, Eduardo
2011-01-01
Background Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. Methodology and Principal Findings In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Whechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. Conclusion The present results support these claims and the neural efficiency hypothesis. PMID:21423657
Lai, Daniel T H; Begg, Rezaul K; Palaniswami, Marimuthu
2009-09-01
Our mobility is an important daily requirement so much so that any disruption to it severely degrades our perceived quality of life. Studies in gait and human movement sciences, therefore, play a significant role in maintaining the well-being of our mobility. Current gait analysis involves numerous interdependent gait parameters that are difficult to adequately interpret due to the large volume of recorded data and lengthy assessment times in gait laboratories. A proposed solution to these problems is computational intelligence (CI), which is an emerging paradigm in biomedical engineering most notably in pathology detection and prosthesis design. The integration of CI technology in gait systems facilitates studies in disorders caused by lower limb defects, cerebral disorders, and aging effects by learning data relationships through a combination of signal processing and machine learning techniques. Learning paradigms, such as supervised learning, unsupervised learning, and fuzzy and evolutionary algorithms, provide advanced modeling capabilities for biomechanical systems that in the past have relied heavily on statistical analysis. CI offers the ability to investigate nonlinear data relationships, enhance data interpretation, design more efficient diagnostic methods, and extrapolate model functionality. These are envisioned to result in more cost-effective, efficient, and easy-to-use systems, which would address global shortages in medical personnel and rising medical costs. This paper surveys current signal processing and CI methodologies followed by gait applications ranging from normal gait studies and disorder detection to artificial gait simulation. We review recent systems focusing on the existing challenges and issues involved in making them successful. We also examine new research in sensor technologies for gait that could be combined with these intelligent systems to develop more effective healthcare solutions.
Embodiment of Learning in Electro-Optical Signal Processors
NASA Astrophysics Data System (ADS)
Hermans, Michiel; Antonik, Piotr; Haelterman, Marc; Massar, Serge
2016-09-01
Delay-coupled electro-optical systems have received much attention for their dynamical properties and their potential use in signal processing. In particular, it has recently been demonstrated, using the artificial intelligence algorithm known as reservoir computing, that photonic implementations of such systems solve complex tasks such as speech recognition. Here, we show how the backpropagation algorithm can be physically implemented on the same electro-optical delay-coupled architecture used for computation with only minor changes to the original design. We find that, compared to when the backpropagation algorithm is not used, the error rate of the resulting computing device, evaluated on three benchmark tasks, decreases considerably. This demonstrates that electro-optical analog computers can embody a large part of their own training process, allowing them to be applied to new, more difficult tasks.
NASA Astrophysics Data System (ADS)
Hatlinski, Grzegorz J.; Kornacki, Witold; Kukwa, Andrzej; Dobrowiecka, Bozena; Pikiel, Marek
2004-07-01
This paper proposes non-invasive solution to the problem of sleep apnea diagnosis especially in small children when sudden death syndrome is suspected. Plethysmographic wave analysis and digital signal processing algorithms are applied in order to find the effect invoked by respiratory movements of sleeping patients so as to diagnose the sleep apnea syndrome. The practical results of finding solution to problems mentioned above will be the possibility of algorithms implementation in a portable intelligent measurement system with a non-invasive monitoring of respiratory action. It works without any disturbances of sleep and respiratory movements especially in small children what could make possible in the future when continuous monitoring were applied to prevent sudden death syndrome occurrence.
Embodiment of Learning in Electro-Optical Signal Processors.
Hermans, Michiel; Antonik, Piotr; Haelterman, Marc; Massar, Serge
2016-09-16
Delay-coupled electro-optical systems have received much attention for their dynamical properties and their potential use in signal processing. In particular, it has recently been demonstrated, using the artificial intelligence algorithm known as reservoir computing, that photonic implementations of such systems solve complex tasks such as speech recognition. Here, we show how the backpropagation algorithm can be physically implemented on the same electro-optical delay-coupled architecture used for computation with only minor changes to the original design. We find that, compared to when the backpropagation algorithm is not used, the error rate of the resulting computing device, evaluated on three benchmark tasks, decreases considerably. This demonstrates that electro-optical analog computers can embody a large part of their own training process, allowing them to be applied to new, more difficult tasks.
A scalable SIMD digital signal processor for high-quality multifunctional printer systems
NASA Astrophysics Data System (ADS)
Kang, Hyeong-Ju; Choi, Yongwoo; Kim, Kimo; Park, In-Cheol; Kim, Jung-Wook; Lee, Eul-Hwan; Gahang, Goo-Soo
2005-01-01
This paper describes a high-performance scalable SIMD digital signal processor (DSP) developed for multifunctional printer systems. The DSP supports a variable number of datapaths to cover a wide range of performance and maintain a RISC-like pipeline structure. Many special instructions suitable for image processing algorithms are included in the DSP. Quad/dual instructions are introduced for 8-bit or 16-bit data, and bit-field extraction/insertion instructions are supported to process various data types. Conditional instructions are supported to deal with complex relative conditions efficiently. In addition, an intelligent DMA block is integrated to align data in the course of data reading. Experimental results show that the proposed DSP outperforms a high-end printer-system DSP by at least two times.
A bio-inspired memory model for structural health monitoring
NASA Astrophysics Data System (ADS)
Zheng, Wei; Zhu, Yong
2009-04-01
Long-term structural health monitoring (SHM) systems need intelligent management of the monitoring data. By analogy with the way the human brain processes memories, we present a bio-inspired memory model (BIMM) that does not require prior knowledge of the structure parameters. The model contains three time-domain areas: a sensory memory area, a short-term memory area and a long-term memory area. First, the initial parameters of the structural state are specified to establish safety criteria. Then the large amount of monitoring data that falls within the safety limits is filtered while the data outside the safety limits are captured instantly in the sensory memory area. Second, disturbance signals are distinguished from danger signals in the short-term memory area. Finally, the stable data of the structural balance state are preserved in the long-term memory area. A strategy for priority scheduling via fuzzy c-means for the proposed model is then introduced. An experiment on bridge tower deformation demonstrates that the proposed model can be applied for real-time acquisition, limited-space storage and intelligent mining of the monitoring data in a long-term SHM system.
Zekveld, Adriana A; Rudner, Mary; Kramer, Sophia E; Lyzenga, Johannes; Rönnberg, Jerker
2014-01-01
We investigated changes in speech recognition and cognitive processing load due to the masking release attributable to decreasing similarity between target and masker speech. This was achieved by using masker voices with either the same (female) gender as the target speech or different gender (male) and/or by spatially separating the target and masker speech using HRTFs. We assessed the relation between the signal-to-noise ratio required for 50% sentence intelligibility, the pupil response and cognitive abilities. We hypothesized that the pupil response, a measure of cognitive processing load, would be larger for co-located maskers and for same-gender compared to different-gender maskers. We further expected that better cognitive abilities would be associated with better speech perception and larger pupil responses as the allocation of larger capacity may result in more intense mental processing. In line with previous studies, the performance benefit from different-gender compared to same-gender maskers was larger for co-located masker signals. The performance benefit of spatially-separated maskers was larger for same-gender maskers. The pupil response was larger for same-gender than for different-gender maskers, but was not reduced by spatial separation. We observed associations between better perception performance and better working memory, better information updating, and better executive abilities when applying no corrections for multiple comparisons. The pupil response was not associated with cognitive abilities. Thus, although both gender and location differences between target and masker facilitate speech perception, only gender differences lower cognitive processing load. Presenting a more dissimilar masker may facilitate target-masker separation at a later (cognitive) processing stage than increasing the spatial separation between the target and masker. The pupil response provides information about speech perception that complements intelligibility data.
Zekveld, Adriana A.; Rudner, Mary; Kramer, Sophia E.; Lyzenga, Johannes; Rönnberg, Jerker
2014-01-01
We investigated changes in speech recognition and cognitive processing load due to the masking release attributable to decreasing similarity between target and masker speech. This was achieved by using masker voices with either the same (female) gender as the target speech or different gender (male) and/or by spatially separating the target and masker speech using HRTFs. We assessed the relation between the signal-to-noise ratio required for 50% sentence intelligibility, the pupil response and cognitive abilities. We hypothesized that the pupil response, a measure of cognitive processing load, would be larger for co-located maskers and for same-gender compared to different-gender maskers. We further expected that better cognitive abilities would be associated with better speech perception and larger pupil responses as the allocation of larger capacity may result in more intense mental processing. In line with previous studies, the performance benefit from different-gender compared to same-gender maskers was larger for co-located masker signals. The performance benefit of spatially-separated maskers was larger for same-gender maskers. The pupil response was larger for same-gender than for different-gender maskers, but was not reduced by spatial separation. We observed associations between better perception performance and better working memory, better information updating, and better executive abilities when applying no corrections for multiple comparisons. The pupil response was not associated with cognitive abilities. Thus, although both gender and location differences between target and masker facilitate speech perception, only gender differences lower cognitive processing load. Presenting a more dissimilar masker may facilitate target-masker separation at a later (cognitive) processing stage than increasing the spatial separation between the target and masker. The pupil response provides information about speech perception that complements intelligibility data. PMID:24808818
Utilizing semantic Wiki technology for intelligence analysis at the tactical edge
NASA Astrophysics Data System (ADS)
Little, Eric
2014-05-01
Challenges exist for intelligence analysts to efficiently and accurately process large amounts of data collected from a myriad of available data sources. These challenges are even more evident for analysts who must operate within small military units at the tactical edge. In such environments, decisions must be made quickly without guaranteed access to the kinds of large-scale data sources available to analysts working at intelligence agencies. Improved technologies must be provided to analysts at the tactical edge to make informed, reliable decisions, since this is often a critical collection point for important intelligence data. To aid tactical edge users, new types of intelligent, automated technology interfaces are required to allow them to rapidly explore information associated with the intersection of hard and soft data fusion, such as multi-INT signals, semantic models, social network data, and natural language processing of text. Abilities to fuse these types of data is paramount to providing decision superiority. For these types of applications, we have developed BLADE. BLADE allows users to dynamically add, delete and link data via a semantic wiki, allowing for improved interaction between different users. Analysts can see information updates in near-real-time due to a common underlying set of semantic models operating within a triple store that allows for updates on related data points from independent users tracking different items (persons, events, locations, organizations, etc.). The wiki can capture pictures, videos and related information. New information added directly to pages is automatically updated in the triple store and its provenance and pedigree is tracked over time, making that data more trustworthy and easily integrated with other users' pages.
Asynchronous sampling of speech with some vocoder experimental results
NASA Technical Reports Server (NTRS)
Babcock, M. L.
1972-01-01
The method of asynchronously sampling speech is based upon the derivatives of the acoustical speech signal. The following results are apparent from experiments to date: (1) It is possible to represent speech by a string of pulses of uniform amplitude, where the only information contained in the string is the spacing of the pulses in time; (2) the string of pulses may be produced in a simple analog manner; (3) the first derivative of the original speech waveform is the most important for the encoding process; (4) the resulting pulse train can be utilized to control an acoustical signal production system to regenerate the intelligence of the original speech.
A wideband, high-resolution spectrum analyzer
NASA Technical Reports Server (NTRS)
Quirk, M. P.; Wilck, H. C.; Garyantes, M. F.; Grimm, M. J.
1988-01-01
A two-million-channel, 40 MHz bandwidth, digital spectrum analyzer under development at the Jet Propulsion Laboratory is described. The analyzer system will serve as a prototype processor for the sky survey portion of NASA's Search for Extraterrestrial Intelligence program and for other applications in the Deep Space Network. The analyzer digitizes an analog input, performs a 2 (sup 21) point Discrete Fourier Transform, accumulates the output power, normalizes the output to remove frequency-dependent gain, and automates simple signal detection algorithms. Due to its built-in frequency-domain processing functions and configuration flexibility, the analyzer is a very powerful tool for real-time signal analysis.
NASA Astrophysics Data System (ADS)
Hramov, Alexander E.; Frolov, Nikita S.; Musatov, Vyachaslav Yu.
2018-02-01
In present work we studied features of the human brain states classification, corresponding to the real movements of hands and legs. For this purpose we used supervised learning algorithm based on feed-forward artificial neural networks (ANNs) with error back-propagation along with the support vector machine (SVM) method. We compared the quality of operator movements classification by means of EEG signals obtained experimentally in the absence of preliminary processing and after filtration in different ranges up to 25 Hz. It was shown that low-frequency filtering of multichannel EEG data significantly improved accuracy of operator movements classification.
A wide-band high-resolution spectrum analyzer.
Quirk, M P; Garyantes, M F; Wilck, H C; Grimm, M J
1988-12-01
This paper describes a two-million-channel 40-MHz-bandwidth, digital spectrum analyzer under development at the Jet Propulsion Laboratory. The analyzer system will serve as a prototype processor for the sky survey portion of NASA's Search for Extraterrestrial Intelligence program and for other applications in the Deep Space Network. The analyzer digitizes an analog input, performs a 2(21)-point, Discrete Fourier Transform, accumulates the output power, normalizes the output to remove frequency-dependent gain, and automates simple signal detection algorithms. Due to its built-in frequency-domain processing functions and configuration flexibility, the analyzer is a very powerful tool for real-time signal analysis and detection.
Goehring, Tobias; Bolner, Federico; Monaghan, Jessica J M; van Dijk, Bas; Zarowski, Andrzej; Bleeck, Stefan
2017-02-01
Speech understanding in noisy environments is still one of the major challenges for cochlear implant (CI) users in everyday life. We evaluated a speech enhancement algorithm based on neural networks (NNSE) for improving speech intelligibility in noise for CI users. The algorithm decomposes the noisy speech signal into time-frequency units, extracts a set of auditory-inspired features and feeds them to the neural network to produce an estimation of which frequency channels contain more perceptually important information (higher signal-to-noise ratio, SNR). This estimate is used to attenuate noise-dominated and retain speech-dominated CI channels for electrical stimulation, as in traditional n-of-m CI coding strategies. The proposed algorithm was evaluated by measuring the speech-in-noise performance of 14 CI users using three types of background noise. Two NNSE algorithms were compared: a speaker-dependent algorithm, that was trained on the target speaker used for testing, and a speaker-independent algorithm, that was trained on different speakers. Significant improvements in the intelligibility of speech in stationary and fluctuating noises were found relative to the unprocessed condition for the speaker-dependent algorithm in all noise types and for the speaker-independent algorithm in 2 out of 3 noise types. The NNSE algorithms used noise-specific neural networks that generalized to novel segments of the same noise type and worked over a range of SNRs. The proposed algorithm has the potential to improve the intelligibility of speech in noise for CI users while meeting the requirements of low computational complexity and processing delay for application in CI devices. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Kolata, Stefan; Light, Kenneth; Wass, Christopher D.; Colas-Zelin, Danielle; Roy, Debasri; Matzel, Louis D.
2010-01-01
Background Genetically heterogeneous mice express a trait that is qualitatively and psychometrically analogous to general intelligence in humans, and as in humans, this trait co-varies with the processing efficacy of working memory (including its dependence on selective attention). Dopamine signaling in the prefrontal cortex (PFC) has been established to play a critical role in animals' performance in both working memory and selective attention tasks. Owing to this role of the PFC in the regulation of working memory, here we compared PFC gene expression profiles of 60 genetically diverse CD-1 mice that exhibited a wide range of general learning abilities (i.e., aggregate performance across five diverse learning tasks). Methodology/Principal Findings Animals' general cognitive abilities were first determined based on their aggregate performance across a battery of five diverse learning tasks. With a procedure designed to minimize false positive identifications, analysis of gene expression microarrays (comprised of ≈25,000 genes) identified a small number (<20) of genes that were differentially expressed across animals that exhibited fast and slow aggregate learning abilities. Of these genes, one functional cluster was identified, and this cluster (Darpp-32, Drd1a, and Rgs9) is an established modulator of dopamine signaling. Subsequent quantitative PCR found that expression of these dopaminegic genes plus one vascular gene (Nudt6) were significantly correlated with individual animal's general cognitive performance. Conclusions/Significance These results indicate that D1-mediated dopamine signaling in the PFC, possibly through its modulation of working memory, is predictive of general cognitive abilities. Furthermore, these results provide the first direct evidence of specific molecular pathways that might potentially regulate general intelligence. PMID:21103339
The SERENDIP 2 SETI project: Current status
NASA Technical Reports Server (NTRS)
Bowyer, C. S.; Werthimer, D.; Donnelly, C.; Herrick, W.; Lampton, M.
1991-01-01
Over the past 30 years, interest in extraterrestrial intelligence has progressed from philosophical discussion to rigorous scientific endeavors attempting to make contact. Since it is impossible to assess the probability of success and the amount of telescope time needed for detection, Search for Extraterrestrial Intelligence (SETI) Projects are plagued with the problem of attaining the large amounts of time needed on the world's precious few large radio telescopes. To circumvent this problem, the Search for Extraterrestrial Radio Emissions from Nearby Developed Intelligent Populations (SERENDIP) instrument operates autonomously in a piggyback mode utilizing whatever observing plan is chosen by the primary observer. In this way, large quantities of high-quality data can be collected in a cost-effective and unobtrusive manner. During normal operations, SERENDIP logs statistically significant events for further offline analysis. Due to the large number of terrestrial and near-space transmitters on earth, a major element of the SERENDIP project involves identifying and rejecting spurious signals from these sources. Another major element of the SERENDIP Project (as well as most other SETI efforts) is detecting extraterrestrial intelligence (ETI) signals. Events selected as candidate ETI signals are studied further in a targeted search program which utilizes between 24 to 48 hours of dedicated telescope time each year.
NASA Astrophysics Data System (ADS)
Oral, I.; Dogan, O.
2007-04-01
The aim of this study is to find out the effect of the course materials based on Multiple Intelligence Theory upon the intelligence groups' learning process. In conclusion, the results proved that the materials prepared according to Multiple Intelligence Theory have a considerable effect on the students' learning process. This effect was particularly seen on the student groups of the musical-rhythmic, verbal-linguistic, interpersonal-social and naturalist intelligence.
Data-Driven Process Discovery: A Discrete Time Algebra for Relational Signal Analysis
1996-12-01
would also like to thank Dr. Mark Oxley for his assistance in developing this abstract algebra and the mathematical notation found herein. Lastly, I... Mathematical Result.. 4-13 4.4. Demostration of Coefficient Signature Additon ........................ 4-14 4.5. Multivariate Relational Discovery...spaces with the recognition of cues in a specific space" [21]. Up to now, most of the Artificial Intelligence (Al) ’discovery’ work has emphasized one
Time Critical Targeting: Predictive Vs Reactionary Methods An Analysis For The Future
2002-06-01
critical targets. To conduct the analysis, a four-step process is used. First, research is conducted to determine which future aircraft, spacecraft , and...the most promising aircraft, spacecraft , and weapons are determined , they are categorized for use in either the reactive or preemptive method. For...no significant delays, 292; Alan Vick et al., 17. 33 Ibid. 12 sensors are Electro-optical (EO) sensors, thermal imagers , and signal intelligence
NASA Astrophysics Data System (ADS)
Noah, Paul V.; Noah, Meg A.; Schroeder, John W.; Chernick, Julian A.
1990-09-01
The U.S. Army has a requirement to develop systems for the detection and identification of ground targets in a clutter environment. Autonomous Homing Munitions (AHM) using infrared, visible, millimeter wave and other sensors are being investigated for this application. Advanced signal processing and computational approaches using pattern recognition and artificial intelligence techniques combined with multisensor data fusion have the potential to meet the Army's requirements for next generation ARM.
[Experience in the use of equipment for ECG system analysis in municipal polyclinics].
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.
An intelligent system with EMG-based joint angle estimation for telemanipulation.
Suryanarayanan, S; Reddy, N P; Gupta, V
1996-01-01
Bio-control of telemanipulators is being researched as an alternate control strategy. This study investigates the use of surface EMG from the biceps to predict joint angle during flexion of the arm that can be used to control an anthropomorphic telemanipulator. An intelligent system based on neural networks and fuzzy logic has been developed to use the processed surface EMG signal and predict the joint angle. The system has been tested on various angles of flexion-extension of the arm and at several speeds of flexion-extension. Preliminary results show the RMS error between the predicted angle and the actual angle to be less than 3% during training and less than 15% during testing. The technique of direct bio-control using EMG has the potential as an interface for telemanipulation applications.
Perceptual learning for speech in noise after application of binary time-frequency masks
Ahmadi, Mahnaz; Gross, Vauna L.; Sinex, Donal G.
2013-01-01
Ideal time-frequency (TF) masks can reject noise and improve the recognition of speech-noise mixtures. An ideal TF mask is constructed with prior knowledge of the target speech signal. The intelligibility of a processed speech-noise mixture depends upon the threshold criterion used to define the TF mask. The study reported here assessed the effect of training on the recognition of speech in noise after processing by ideal TF masks that did not restore perfect speech intelligibility. Two groups of listeners with normal hearing listened to speech-noise mixtures processed by TF masks calculated with different threshold criteria. For each group, a threshold criterion that initially produced word recognition scores between 0.56–0.69 was chosen for training. Listeners practiced with one set of TF-masked sentences until their word recognition performance approached asymptote. Perceptual learning was quantified by comparing word-recognition scores in the first and last training sessions. Word recognition scores improved with practice for all listeners with the greatest improvement observed for the same materials used in training. PMID:23464038
Evaluation of the importance of time-frequency contributions to speech intelligibility in noise
Yu, Chengzhu; Wójcicki, Kamil K.; Loizou, Philipos C.; Hansen, John H. L.; Johnson, Michael T.
2014-01-01
Recent studies on binary masking techniques make the assumption that each time-frequency (T-F) unit contributes an equal amount to the overall intelligibility of speech. The present study demonstrated that the importance of each T-F unit to speech intelligibility varies in accordance with speech content. Specifically, T-F units are categorized into two classes, speech-present T-F units and speech-absent T-F units. Results indicate that the importance of each speech-present T-F unit to speech intelligibility is highly related to the loudness of its target component, while the importance of each speech-absent T-F unit varies according to the loudness of its masker component. Two types of mask errors are also considered, which include miss and false alarm errors. Consistent with previous work, false alarm errors are shown to be more harmful to speech intelligibility than miss errors when the mixture signal-to-noise ratio (SNR) is below 0 dB. However, the relative importance between the two types of error is conditioned on the SNR level of the input speech signal. Based on these observations, a mask-based objective measure, the loudness weighted hit-false, is proposed for predicting speech intelligibility. The proposed objective measure shows significantly higher correlation with intelligibility compared to two existing mask-based objective measures. PMID:24815280
Visualizing Host-Nation Sentiment at the Tactical Edge
2014-06-01
HUMINT) and open source intelligence ( OSINT ) become prioritized above more traditional intelligence based on signals (SIGINT) and electronic sources...reliance on HUMINT and OSINT . Soldiers as peacekeepers must manage multiple information assets and resources, often relying on local and international
Speech communications in noise
NASA Technical Reports Server (NTRS)
1984-01-01
The physical characteristics of speech, the methods of speech masking measurement, and the effects of noise on speech communication are investigated. Topics include the speech signal and intelligibility, the effects of noise on intelligibility, the articulation index, and various devices for evaluating speech systems.
Hu, Yi; Loizou, Philipos C
2010-01-01
Pre-processing based noise-reduction algorithms used for cochlear implants (CIs) can sometimes introduce distortions which are carried through the vocoder stages of CI processing. While the background noise may be notably suppressed, the harmonic structure and/or spectral envelope of the signal may be distorted. The present study investigates the potential of preserving the signal's harmonic structure in voiced segments (e.g., vowels) as a means of alleviating the negative effects of pre-processing. The hypothesis tested is that preserving the harmonic structure of the signal is crucial for subsequent vocoder processing. The implications of preserving either the main harmonic components occurring at multiples of F0 or the main harmonics along with adjacent partials are investigated. This is done by first pre-processing noisy speech with a conventional noise-reduction algorithm, regenerating the harmonics, and vocoder processing the stimuli with eight channels of stimulation in steady speech-shaped noise. Results indicated that preserving the main low-frequency harmonics (spanning 1 or 3 kHz) alone was not beneficial. Preserving, however, the harmonic structure of the stimulus, i.e., the main harmonics along with the adjacent partials, was found to be critically important and provided substantial improvements (41 percentage points) in intelligibility.
Overview of the NASA SETI Program
NASA Technical Reports Server (NTRS)
Oliver, B. M.
1986-01-01
The NASA Search of Extraterrestrial Intelligence (SETI) program plan is to scan the microwave window from 1 to 10 GHz with existing radio telescopes and sophisticated signal processing equipment looking for narrow band features that might represent artificial signals. A microwave spectrometer was built and is being field tested. A pattern recognition computer to search for drifting continuous wave signals and pulse trains in the output spectra is being designed. Equipment to characterize the radio frequency interference environment was also built. The plan is to complete the hardware and software by FY-88. Then, with increased funding, this equipment will be replicated in Very Large Scale Integration form. Observations, both a complete sky survey and a search fo nearby solar type stars, will begin in about 1990. The hypothesis that very powerful signals exist or that signals are being beamed at us will be tested. To detect the kinds of signals radiated at distances of 100 light years will require a collecting area kilometers in diameter.
Eyes and ears: Using eye tracking and pupillometry to understand challenges to speech recognition.
Van Engen, Kristin J; McLaughlin, Drew J
2018-05-04
Although human speech recognition is often experienced as relatively effortless, a number of common challenges can render the task more difficult. Such challenges may originate in talkers (e.g., unfamiliar accents, varying speech styles), the environment (e.g. noise), or in listeners themselves (e.g., hearing loss, aging, different native language backgrounds). Each of these challenges can reduce the intelligibility of spoken language, but even when intelligibility remains high, they can place greater processing demands on listeners. Noisy conditions, for example, can lead to poorer recall for speech, even when it has been correctly understood. Speech intelligibility measures, memory tasks, and subjective reports of listener difficulty all provide critical information about the effects of such challenges on speech recognition. Eye tracking and pupillometry complement these methods by providing objective physiological measures of online cognitive processing during listening. Eye tracking records the moment-to-moment direction of listeners' visual attention, which is closely time-locked to unfolding speech signals, and pupillometry measures the moment-to-moment size of listeners' pupils, which dilate in response to increased cognitive load. In this paper, we review the uses of these two methods for studying challenges to speech recognition. Copyright © 2018. Published by Elsevier B.V.
Borghini, Giulia; Hazan, Valerie
2018-01-01
Current evidence demonstrates that even though some non-native listeners can achieve native-like performance for speech perception tasks in quiet, the presence of a background noise is much more detrimental to speech intelligibility for non-native compared to native listeners. Even when performance is equated across groups, it is likely that greater listening effort is required for non-native listeners. Importantly, the added listening effort might result in increased fatigue and a reduced ability to successfully perform multiple tasks simultaneously. Task-evoked pupil responses have been demonstrated to be a reliable measure of cognitive effort and can be useful in clarifying those aspects. In this study we compared the pupil response for 23 native English speakers and 27 Italian speakers of English as a second language. Speech intelligibility was tested for sentences presented in quiet and in background noise at two performance levels that were matched across groups. Signal-to-noise levels corresponding to these sentence intelligibility levels were pre-determined using an adaptive intelligibility task. Pupil response was significantly greater in non-native compared to native participants across both intelligibility levels. Therefore, for a given intelligibility level, a greater listening effort is required when listening in a second language in order to understand speech in noise. Results also confirmed that pupil response is sensitive to speech intelligibility during language comprehension, in line with previous research. However, contrary to our predictions, pupil response was not differentially modulated by intelligibility levels for native and non-native listeners. The present study corroborates that pupillometry can be deemed as a valid measure to be used in speech perception investigation, because it is sensitive to differences both across participants, such as listener type, and across conditions, such as variations in the level of speech intelligibility. Importantly, pupillometry offers us the possibility to uncover differences in listening effort even when those do not emerge in the performance level of individuals. PMID:29593489
Schwaibold, M; Schöller, B; Penzel, T; Bolz, A
2001-05-01
We describe a novel approach to the problem of automated sleep stage recognition. The ARTISANA algorithm mimics the behaviour of a human expert visually scoring sleep stages (Rechtschaffen and Kales classification). It comprises a number of interacting components that imitate the stepwise approach of the human expert, and artificial intelligence components. On the basis of parameters extracted at 1-s intervals from the signal curves, artificial neural networks recognize the incidence of typical patterns, e.g. delta activity or K complexes. This is followed by a rule interpretation stage that identifies the sleep stage with the aid of a neuro-fuzzy system while taking account of the context. Validation studies based on the records of 8 patients with obstructive sleep apnoea have confirmed the potential of this approach. Further features of the system include the transparency of the decision-taking process, and the flexibility of the option for expanding the system to cover new patterns and criteria.
An Experimental Determination of the Intelligibility of Two Different Speech Synthesizers in Noise.
1987-12-01
to control the signal to noise ratios and to maintain an overall SPL of 80 dBC. The calibration of the speech signal was not easy due to its non ...ft" 432 AN EXPERIMENTAL DETERMINATION OF THE INTELLIGIBILITY OF 1.11 TiHO DIFFERENT SPE (U) PENNSYLVANIA STATE UNIV UNIVERSITY PARK APPLIED RESEARCH ...0 0 * Applied Research Laboratory The Pennsylvania State University CD4 A’ - 4,. ,__ TOO AN EcPERi.taTrAL DETEMINATION OF TlE IIjZINTELLIGIBILITY OF
Analysis of a crossed Bragg cell acousto-optical spectrometer for SETI
NASA Technical Reports Server (NTRS)
Gulkis, S.
1989-01-01
The search for radio signals from extraterrestrial intelligent beings (SETI) requires the use of large instantaneous bandwidth (500 MHz) and high resolution (20 Hz) spectrometers. Digital systems with a high degree of modularity can be used to provide this capability, and this method has been widely discussed. Another technique for meeting the SETI requirement is to use a crossed Bragg cell spectrometer as described by Psaltis and Casasent. This technique makes use of the Folded Spectrum concept, introduced by Thomas. The Folded Spectrum is a 2-D Fourier Transform of a raster scanned 1-D signal. It is directly related to the long 1-D spectrum of the original signal and is ideally suited for optical signal processing. The folded spectrum technique has received little attention to date, primarily because early systems made use of photographic film which are unsuitable for the real time data analysis and voluminous data requirements of SETI. An analysis of the crossed Bragg cell spectrometer is presented as a method to achieve the spectral processing requirements for SETI. Systematic noise contributions unique to the Bragg cell system will be discussed.
Analysis of a crossed Bragg cell acousto-optical spectrometer for SETI.
Gulkis, S
1989-01-01
The search for radio signals from extraterrestrial intelligent beings (SETI) requires the use of large instantaneous bandwidth (500 MHz) and high resolution (20 Hz) spectrometers. Digital systems with a high degree of modularity can be used to provide this capability, and this method has been widely discussed. Another technique for meeting the SETI requirement is to use a crossed Bragg cell spectrometer as described by Psaltis and Casasent. This technique makes use of the Folded Spectrum concept, introduced by Thomas. The Folded Spectrum is a 2-D Fourier Transform of a raster scanned 1-D signal. It is directly related to the long 1-D spectrum of the original signal and is ideally suited for optical signal processing. The folded spectrum technique has received little attention to date, primarily because early systems made use of photographic film which are unsuitable for the real time data analysis and voluminous data requirements of SETI. An analysis of the crossed Bragg cell spectrometer is presented as a method to achieve the spectral processing requirements for SETI. Systematic noise contributions unique to the Bragg cell system will be discussed.
Analysis of a crossed Bragg cell acousto-optical spectrometer for SETI
NASA Astrophysics Data System (ADS)
Gulkis, Samuel
The search for radio signals from extraterrestrial intelligent beings (SETI) requires the use of large instantaneous bandwidth (500 MHz) and high resolution (20 Hz) spectrometers. Digital systems with a high degree of modularity can be used to provide this capability, and this method has been widely discussed. Another technique for meeting the SETI requirement is to use a crossed Bragg cell spectrometer as described by Psaltis and Casasent. This technique makes use of the Folded Spectrum concept, introduced by Thomas. The Folded Spectrum is a 2-D Fourier Transform of a raster scanned 1-D signal. It is directly related to the long 1-D spectrum of the original signal and is ideally suited for optical signal processing. The folded spectrum technique has received little attention to date, primarily because early systems made use of photographic film which are unsuitable for the real time data analysis and voluminous data requirements of SETI. An analysis of the crossed Bragg cell spectrometer is presented as a method to achieve the spectral processing requirements for SETI. Systematic noise contributions unique to the Bragg cell system will be discussed.
STI: An objective measure for the performance of voice communication systems
NASA Astrophysics Data System (ADS)
Houtgast, T.; Steeneken, H. J. M.
1981-06-01
A measuring device was developed for determining the quality of speech communication systems. It comprises two parts, a signal source which replaces the talker, producing an artificial speech-like signal, and an analysis part which replaces the listener, by which the signal at the receiving end of the system under test is evaluated. Each single measurement results in an index (ranging from 0-100%) which indicates the effect of that communication system on speech intelligibility. The index is called STI (Speech Transmission Index). A careful design of the characteristics of the test signal and of the type of signal analysis makes the present approach widely applicable. It was verified experimentally that a given STI implies a given effect on speech intelligibility, irrespective of the nature of the actual disturbance (noise interference, band-pass limiting, peak clipping, etc.).
Design of an Intelligent Front-End Signal Conditioning Circuit for IR Sensors
NASA Astrophysics Data System (ADS)
de Arcas, G.; Ruiz, M.; Lopez, J. M.; Gutierrez, R.; Villamayor, V.; Gomez, L.; Montojo, Mª. T.
2008-02-01
This paper presents the design of an intelligent front-end signal conditioning system for IR sensors. The system has been developed as an interface between a PbSe IR sensor matrix and a TMS320C67x digital signal processor. The system architecture ensures its scalability so it can be used for sensors with different matrix sizes. It includes an integrator based signal conditioning circuit, a data acquisition converter block, and a FPGA based advanced control block that permits including high level image preprocessing routines such as faulty pixel detection and sensor calibration in the signal conditioning front-end. During the design phase virtual instrumentation technologies proved to be a very valuable tool for prototyping when choosing the best A/D converter type for the application. Development time was significantly reduced due to the use of this technology.
Intelligence moderates reinforcement learning: a mini-review of the neural evidence
2014-01-01
Our understanding of the neural basis of reinforcement learning and intelligence, two key factors contributing to human strivings, has progressed significantly recently. However, the overlap of these two lines of research, namely, how intelligence affects neural responses during reinforcement learning, remains uninvestigated. A mini-review of three existing studies suggests that higher IQ (especially fluid IQ) may enhance the neural signal of positive prediction error in dorsolateral prefrontal cortex, dorsal anterior cingulate cortex, and striatum, several brain substrates of reinforcement learning or intelligence. PMID:25185818
Intelligence moderates reinforcement learning: a mini-review of the neural evidence.
Chen, Chong
2015-06-01
Our understanding of the neural basis of reinforcement learning and intelligence, two key factors contributing to human strivings, has progressed significantly recently. However, the overlap of these two lines of research, namely, how intelligence affects neural responses during reinforcement learning, remains uninvestigated. A mini-review of three existing studies suggests that higher IQ (especially fluid IQ) may enhance the neural signal of positive prediction error in dorsolateral prefrontal cortex, dorsal anterior cingulate cortex, and striatum, several brain substrates of reinforcement learning or intelligence. Copyright © 2015 the American Physiological Society.
DOT National Transportation Integrated Search
2000-12-01
In this document, a group of authors looks back on the ten years of the national intelligent transportation systems program and examines which ITS technology applications have been successful, which have not been successful, and what are the underlyi...
Park, Hyojin; Kayser, Christoph; Thut, Gregor; Gross, Joachim
2016-01-01
During continuous speech, lip movements provide visual temporal signals that facilitate speech processing. Here, using MEG we directly investigated how these visual signals interact with rhythmic brain activity in participants listening to and seeing the speaker. First, we investigated coherence between oscillatory brain activity and speaker’s lip movements and demonstrated significant entrainment in visual cortex. We then used partial coherence to remove contributions of the coherent auditory speech signal from the lip-brain coherence. Comparing this synchronization between different attention conditions revealed that attending visual speech enhances the coherence between activity in visual cortex and the speaker’s lips. Further, we identified a significant partial coherence between left motor cortex and lip movements and this partial coherence directly predicted comprehension accuracy. Our results emphasize the importance of visually entrained and attention-modulated rhythmic brain activity for the enhancement of audiovisual speech processing. DOI: http://dx.doi.org/10.7554/eLife.14521.001 PMID:27146891
NASA Astrophysics Data System (ADS)
El Mountassir, M.; Yaacoubi, S.; Dahmene, F.
2015-07-01
Intelligent feature extraction and advanced signal processing techniques are necessary for a better interpretation of ultrasonic guided waves signals either in structural health monitoring (SHM) or in nondestructive testing (NDT). Such signals are characterized by at least multi-modal and dispersive components. In addition, in SHM, these signals are closely vulnerable to environmental and operational conditions (EOCs), and can be severely affected. In this paper we investigate the use of Artificial Neural Network (ANN) to overcome these effects and to provide a reliable damage detection method with a minimal of false indications. An experimental case of study (full scale pipe) is presented. Damages sizes have been increased and their shapes modified in different steps. Various parameters such as the number of inputs and the number of hidden neurons were studied to find the optimal configuration of the neural network.
Five Strategies for Detecting Intelligence
NASA Astrophysics Data System (ADS)
Tough, Allen
If highly intelligent life has evolved elsewhere in our galaxy, how might scientists detect it? This paper compares eleven search strategies on three dimensions. Which strategies are most likely to detect extraterrestrial intelligence or technology? Which strategies, if successful, will likely contribute a wealth of knowledge? What is the current status of actual projects? In order to detect evidence of extraterrestrial intelligence or technology many light-years from Earth, astronomers can search for (1) radio signals, using various approaches, (2) laser or other optical signals, (3) other incoming signals, or (4) signs of an astroengineering project or Dyson sphere. Scientists could also (5) broadcast a radio message asking distant civilizations to respond. Additional strategies arise because any civilizations in our galaxy are probably much older than us and will therefore have technology far beyond ours. A technologically sophisticated civilization could likely send a small but super-smart probe to explore our solar system. An alien probe in our solar system, beyond the Moon, might be detected (6) by ongoing astronomy and space exploration, or (7) by a dedicated search for evidence of a probe or its byproducts. If a super-smart probe has reached Earth, it might be detected (8) by routine military and intelligence monitoring, (9) by an invitation to ETI on the World Wide Web, (10) by achieving peace or some other threshold that the probe requires before contact, or (11) by developing rigorous new research designs to study anomalous phenomena.
Köbler, S; Rosenhall, U
2002-10-01
Speech intelligibility and horizontal localization of 19 subjects with mild-to-moderate hearing loss were studied in order to evaluate the advantages and disadvantages of bilateral and unilateral hearing aid (HA) fittings. Eight loudspeakers were arranged in a circular array covering the horizontal plane around the subjects. Speech signals of a sentence test were delivered by one, randomly chosen, loudspeaker. At the same time, the other seven loudspeakers emitted noise with the same long-term average spectrum as the speech signals. The subjects were asked to repeat the speech signal and to point out the corresponding loudspeaker. Speech intelligibility was significantly improved by HAs, bilateral amplification being superior to unilateral. Horizontal localization could not be improved by HA amplification. However, bilateral HAs preserved the subjects' horizontal localization, whereas unilateral amplification decreased their horizontal localization abilities. Front-back confusions were common in the horizontal localization test. The results indicate that bilateral HA amplification has advantages compared with unilateral amplification.
State of the art in perceptual design of hearing aids
NASA Astrophysics Data System (ADS)
Edwards, Brent W.; van Tasell, Dianne J.
2002-05-01
Hearing aid capabilities have increased dramatically over the past six years, in large part due to the development of small, low-power digital signal processing chips suitable for hearing aid applications. As hearing aid signal processing capabilities increase, there will be new opportunities to apply perceptually based knowledge to technological development. Most hearing loss compensation techniques in today's hearing aids are based on simple estimates of audibility and loudness. As our understanding of the psychoacoustical and physiological characteristics of sensorineural hearing loss improves, the result should be improved design of hearing aids and fitting methods. The state of the art in hearing aids will be reviewed, including form factors, user requirements, and technology that improves speech intelligibility, sound quality, and functionality. General areas of auditory perception that remain unaddressed by current hearing aid technology will be discussed.
The trillion planet survey: an optical search for directed intelligence in M31
NASA Astrophysics Data System (ADS)
Stewart, Andrew; Lubin, Philip
2017-09-01
In realm of optical SETI, searches for pulsed laser signals have historically been preferred over those for continuous wave beacons. There are many valid reasons for this, namely the near elimination of false positives and simple experimental components. However, due to significant improvements in laser technologies and light-detection systems since the mid-20th century, as well as new data from the recent Kepler mission, continuous wave searches should no longer be ignored. In this paper we propose a search for continuous wave laser beacons from an intelligent civilization in the Andromeda galaxy. Using only a 0.8 meter telescope, a standard photometric system, and an image processing pipeline, we expect to be able to detect any CW laser signal directed at us from an extraterrestrial civilization in M31, as long as the civilization is operating at a wavelength we can "see" and has left the beacon on long enough for us to detect it here on Earth. The search target is M31 due to its high stellar density relative to our own Milky Way galaxy. Andromeda is home to at least one trillion stars, and thus at least one trillion planets. As a result, in surveying M31, we are surveying one trillion planets, and consequently one trillion possible locations of intelligent life. This is an unprecedented number of targets relative to other past SETI searches. We call this the TPS or Trillion Planet Survey.
Proactive Problem Avoidance and Quality of Service (QOS) Guarantees for Large Heterogeneous Networks
2002-03-01
host, and can be used to monitor and provide problem response data to multiple network elements. A blowup of the components of an RA is shown in...developed based on stati signal processing and learning. T ts to stical here are two salient features on the intelligent gents developed: (1) an...For multiple routers, the physical connections between interfaces along with the respective health of terface are represented. in In addition to
Ultranarrowband searches for extraterrestrial intelligence with dedicated signal-processing hardware
NASA Technical Reports Server (NTRS)
Horowitz, P.; Matthews, B. S.; Forster, J.; Linscott, I.; Teague, C. C.; Chen, K.; Backus, P.
1986-01-01
An evaluation is made of the prospects for SETI applications of multichannel spectroscopy, assuming narrowband RF beacon transmission, with a mHz resolution that matches interstellar medium properties. Receiver Doppler corrections must furnish substantial interference rejection. Results are presented from an Arecibo antenna search of 250 sunlike stars at 1.4 and 2.8 GHz. A meridian transit search of the northern sky is also in progress with the Harvard-Smithsonian 26-m antenna.
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.
Tool path strategy and cutting process monitoring in intelligent machining
NASA Astrophysics Data System (ADS)
Chen, Ming; Wang, Chengdong; An, Qinglong; Ming, Weiwei
2018-06-01
Intelligent machining is a current focus in advanced manufacturing technology, and is characterized by high accuracy and efficiency. A central technology of intelligent machining—the cutting process online monitoring and optimization—is urgently needed for mass production. In this research, the cutting process online monitoring and optimization in jet engine impeller machining, cranio-maxillofacial surgery, and hydraulic servo valve deburring are introduced as examples of intelligent machining. Results show that intelligent tool path optimization and cutting process online monitoring are efficient techniques for improving the efficiency, quality, and reliability of machining.
Active vision in satellite scene analysis
NASA Technical Reports Server (NTRS)
Naillon, Martine
1994-01-01
In earth observation or planetary exploration it is necessary to have more and, more autonomous systems, able to adapt to unpredictable situations. This imposes the use, in artificial systems, of new concepts in cognition, based on the fact that perception should not be separated from recognition and decision making levels. This means that low level signal processing (perception level) should interact with symbolic and high level processing (decision level). This paper is going to describe the new concept of active vision, implemented in Distributed Artificial Intelligence by Dassault Aviation following a 'structuralist' principle. An application to spatial image interpretation is given, oriented toward flexible robotics.
Rivera, José; Carrillo, Mariano; Chacón, Mario; Herrera, Gilberto; Bojorquez, Gilberto
2007-01-01
The development of smart sensors involves the design of reconfigurable systems capable of working with different input sensors. Reconfigurable systems ideally should spend the least possible amount of time in their calibration. An autocalibration algorithm for intelligent sensors should be able to fix major problems such as offset, variation of gain and lack of linearity, as accurately as possible. This paper describes a new autocalibration methodology for nonlinear intelligent sensors based on artificial neural networks, ANN. The methodology involves analysis of several network topologies and training algorithms. The proposed method was compared against the piecewise and polynomial linearization methods. Method comparison was achieved using different number of calibration points, and several nonlinear levels of the input signal. This paper also shows that the proposed method turned out to have a better overall accuracy than the other two methods. Besides, experimentation results and analysis of the complete study, the paper describes the implementation of the ANN in a microcontroller unit, MCU. In order to illustrate the method capability to build autocalibration and reconfigurable systems, a temperature measurement system was designed and tested. The proposed method is an improvement over the classic autocalibration methodologies, because it impacts on the design process of intelligent sensors, autocalibration methodologies and their associated factors, like time and cost.
Harlander, Niklas; Rosenkranz, Tobias; Hohmann, Volker
2012-08-01
Single channel noise reduction has been well investigated and seems to have reached its limits in terms of speech intelligibility improvement, however, the quality of such schemes can still be advanced. This study tests to what extent novel model-based processing schemes might improve performance in particular for non-stationary noise conditions. Two prototype model-based algorithms, a speech-model-based, and a auditory-model-based algorithm were compared to a state-of-the-art non-parametric minimum statistics algorithm. A speech intelligibility test, preference rating, and listening effort scaling were performed. Additionally, three objective quality measures for the signal, background, and overall distortions were applied. For a better comparison of all algorithms, particular attention was given to the usage of the similar Wiener-based gain rule. The perceptual investigation was performed with fourteen hearing-impaired subjects. The results revealed that the non-parametric algorithm and the auditory model-based algorithm did not affect speech intelligibility, whereas the speech-model-based algorithm slightly decreased intelligibility. In terms of subjective quality, both model-based algorithms perform better than the unprocessed condition and the reference in particular for highly non-stationary noise environments. Data support the hypothesis that model-based algorithms are promising for improving performance in non-stationary noise conditions.
An Artificial Intelligence Approach for Gears Diagnostics in AUVs
Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano
2016-01-01
In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved. PMID:27077868
An Artificial Intelligence Approach for Gears Diagnostics in AUVs.
Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano
2016-04-12
In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.
Jena, Manas Kumar; Samantaray, Subhransu Ranjan
2016-01-01
This paper presents a data-mining-based intelligent differential relaying scheme for transmission lines, including flexible ac transmission system device, such as unified power flow controller (UPFC) and wind farms. Initially, the current and voltage signals are processed through extended Kalman filter phasor measurement unit for phasor estimation, and 21 potential features are computed at both ends of the line. Once the features are extracted at both ends, the corresponding differential features are derived. These differential features are fed to a data-mining model known as decision tree (DT) to provide the final relaying decision. The proposed technique has been extensively tested for single-circuit transmission line, including UPFC and wind farms with in-feed, double-circuit line with UPFC on one line and wind farm as one of the substations with wide variations in operating parameters. The test results obtained from simulation as well as in real-time digital simulator testing indicate that the DT-based intelligent differential relaying scheme is highly reliable and accurate with a response time of 2.25 cycles from the fault inception.
Posturing Tactical ISR Beyond The Umbilical Cord
2017-02-03
intelligence sensors, it carries a lethal payload of ordinance for strike and or close air support missions. In fact, world media have discussed the MQ-9’s...awareness all their visual and signal intelligence sensors provide is a force multiplier that enhances mission success significantly. For example, when...on C-17 Photo Source http://www.aircav.com/dodphoto/dod98/mh60-002rs.jpg 407MRH multirole armed ISR ( intelligence , surveillance, reconnaissance
Onboard Processor for Compressing HSI Data
NASA Technical Reports Server (NTRS)
Cook, Sid; Harsanyi, Joe; Day, John H. (Technical Monitor)
2002-01-01
With EO-1 Hyperion and MightySat in orbit NASA and the DoD are showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor greater than 100, while retaining the necessary spectral fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our initial spectral compression experiments leverage commercial-off-the-shelf (COTS) spectral exploitation algorithms for segmentation, material identification and spectral compression that ASIT has developed. ASIT will also support the modification and integration of this COTS software into the OBP. Other commercially available COTS software for spatial compression will also be employed as part of the overall compression processing sequence. Over the next year elements of a high-performance reconfigurable OBP will be developed to implement proven preprocessing steps that distill the HSI data stream in both spectral and spatial dimensions. The system will intelligently reduce the volume of data that must be stored, transmitted to the ground, and processed while minimizing the loss of information.
The dynamic lift of developmental process.
Smith, Linda B; Breazeal, Cynthia
2007-01-01
What are the essential properties of human intelligence, currently unparalleled in its power relative to other biological forms and relative to artificial forms of intelligence? We suggest that answering this question depends critically on understanding developmental process. This paper considers three principles potentially essential to building human-like intelligence: the heterogeneity of the component processes, the embedding of development in a social world, and developmental processes that change the cognitive system as a function of the history of soft-assemblies of these heterogeneous processes in specific tasks. The paper uses examples from human development and from developmental robotics to show how these processes also may underlie biological intelligence and enable us to generate more advanced forms of artificial intelligence.
Sun, Weifang; Yao, Bin; Zeng, Nianyin; Chen, Binqiang; He, Yuchao; Cao, Xincheng; He, Wangpeng
2017-07-12
As a typical example of large and complex mechanical systems, rotating machinery is prone to diversified sorts of mechanical faults. Among these faults, one of the prominent causes of malfunction is generated in gear transmission chains. Although they can be collected via vibration signals, the fault signatures are always submerged in overwhelming interfering contents. Therefore, identifying the critical fault's characteristic signal is far from an easy task. In order to improve the recognition accuracy of a fault's characteristic signal, a novel intelligent fault diagnosis method is presented. In this method, a dual-tree complex wavelet transform (DTCWT) is employed to acquire the multiscale signal's features. In addition, a convolutional neural network (CNN) approach is utilized to automatically recognise a fault feature from the multiscale signal features. The experiment results of the recognition for gear faults show the feasibility and effectiveness of the proposed method, especially in the gear's weak fault features.
A review of intelligent systems for heart sound signal analysis.
Nabih-Ali, Mohammed; El-Dahshan, El-Sayed A; Yahia, Ashraf S
2017-10-01
Intelligent computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of physicians and reduce the time required for accurate diagnosis. CAD systems could provide physicians with a suggestion about the diagnostic of heart diseases. The objective of this paper is to review the recent published preprocessing, feature extraction and classification techniques and their state of the art of phonocardiogram (PCG) signal analysis. Published literature reviewed in this paper shows the potential of machine learning techniques as a design tool in PCG CAD systems and reveals that the CAD systems for PCG signal analysis are still an open problem. Related studies are compared to their datasets, feature extraction techniques and the classifiers they used. Current achievements and limitations in developing CAD systems for PCG signal analysis using machine learning techniques are presented and discussed. In the light of this review, a number of future research directions for PCG signal analysis are provided.
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
Artificial Intelligence Estimation of Carotid-Femoral Pulse Wave Velocity using Carotid Waveform.
Tavallali, Peyman; Razavi, Marianne; Pahlevan, Niema M
2018-01-17
In this article, we offer an artificial intelligence method to estimate the carotid-femoral Pulse Wave Velocity (PWV) non-invasively from one uncalibrated carotid waveform measured by tonometry and few routine clinical variables. Since the signal processing inputs to this machine learning algorithm are sensor agnostic, the presented method can accompany any medical instrument that provides a calibrated or uncalibrated carotid pressure waveform. Our results show that, for an unseen hold back test set population in the age range of 20 to 69, our model can estimate PWV with a Root-Mean-Square Error (RMSE) of 1.12 m/sec compared to the reference method. The results convey the fact that this model is a reliable surrogate of PWV. Our study also showed that estimated PWV was significantly associated with an increased risk of CVDs.
Signal Processing Methods for Removing the Effects of Whole Body Vibration upon Speech
NASA Technical Reports Server (NTRS)
Bitner, Rachel M.; Begault, Durand R.
2014-01-01
Humans may be exposed to whole-body vibration in environments where clear speech communications are crucial, particularly during the launch phases of space flight and in high-performance aircraft. Prior research has shown that high levels of vibration cause a decrease in speech intelligibility. However, the effects of whole-body vibration upon speech are not well understood, and no attempt has been made to restore speech distorted by whole-body vibration. In this paper, a model for speech under whole-body vibration is proposed and a method to remove its effect is described. The method described reduces the perceptual effects of vibration, yields higher ASR accuracy scores, and may significantly improve intelligibility. Possible applications include incorporation within communication systems to improve radio-communication systems in environments such a spaceflight, aviation, or off-road vehicle operations.
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
NASA Technical Reports Server (NTRS)
Olsen, E.; Backus, C.; Gulkis, S.; Levin, S.
1993-01-01
The NASA High Resolution Microwave Survey (HRMS) Sky Survey component will survey the entire celestial sphere over the microwave frequency band to search for signals of intelligent origin which originate from beyond our solar system.
Ren, Xuezhu; Schweizer, Karl; Wang, Tengfei; Chu, Pei; Gong, Qin
2017-10-01
The aim of the current study is to provide new insights into the relationship between executive functions and intelligence measures in considering the item-position effect observed in intelligence items. Raven's Advanced Progressive Matrices (APM) and Horn's LPS reasoning test were used to assess fluid intelligence which served as criterion in investigating the relationship between intelligence and executive functions. A battery of six experimental tasks measured the updating, shifting, and inhibition processes of executive functions. Data were collected from 205 university students. Fluid intelligence showed substantial correlations with the updating and inhibition processes and no correlation with the shifting process without considering the item-position effect. Next, the fixed-link model was applied to APM and LPS data separately to decompose them into an ability component and an item-position component. The results of relating the components to executive functions showed that the updating and shifting processes mainly contributed to the item-position component whereas the inhibition process was mainly associated with the ability component of each fluid intelligence test. These findings suggest that improvements in the efficiency of updating and shifting processes are likely to occur during the course of completing intelligence measures and inhibition is important for intelligence in general. Copyright © 2017 Elsevier B.V. All rights reserved.
The Search for Extraterrestrial Intelligence.
ERIC Educational Resources Information Center
Jones, Barrie W.
2003-01-01
Traces the efforts of Searching for Extraterrestrial Technological Intelligence (SETI) since 1960 when a radio-telescope was used to see if any messages were being sent from the vicinity of two nearby stars. Describes attempts to detect microwave/optical signals and technological modification of the cosmic environment. (Author/KHR)
Intelligent Gearbox Diagnosis Methods Based on SVM, Wavelet Lifting and RBR
Gao, Lixin; Ren, Zhiqiang; Tang, Wenliang; Wang, Huaqing; Chen, Peng
2010-01-01
Given the problems in intelligent gearbox diagnosis methods, it is difficult to obtain the desired information and a large enough sample size to study; therefore, we propose the application of various methods for gearbox fault diagnosis, including wavelet lifting, a support vector machine (SVM) and rule-based reasoning (RBR). In a complex field environment, it is less likely for machines to have the same fault; moreover, the fault features can also vary. Therefore, a SVM could be used for the initial diagnosis. First, gearbox vibration signals were processed with wavelet packet decomposition, and the signal energy coefficients of each frequency band were extracted and used as input feature vectors in SVM for normal and faulty pattern recognition. Second, precision analysis using wavelet lifting could successfully filter out the noisy signals while maintaining the impulse characteristics of the fault; thus effectively extracting the fault frequency of the machine. Lastly, the knowledge base was built based on the field rules summarized by experts to identify the detailed fault type. Results have shown that SVM is a powerful tool to accomplish gearbox fault pattern recognition when the sample size is small, whereas the wavelet lifting scheme can effectively extract fault features, and rule-based reasoning can be used to identify the detailed fault type. Therefore, a method that combines SVM, wavelet lifting and rule-based reasoning ensures effective gearbox fault diagnosis. PMID:22399894
Intelligent gearbox diagnosis methods based on SVM, wavelet lifting and RBR.
Gao, Lixin; Ren, Zhiqiang; Tang, Wenliang; Wang, Huaqing; Chen, Peng
2010-01-01
Given the problems in intelligent gearbox diagnosis methods, it is difficult to obtain the desired information and a large enough sample size to study; therefore, we propose the application of various methods for gearbox fault diagnosis, including wavelet lifting, a support vector machine (SVM) and rule-based reasoning (RBR). In a complex field environment, it is less likely for machines to have the same fault; moreover, the fault features can also vary. Therefore, a SVM could be used for the initial diagnosis. First, gearbox vibration signals were processed with wavelet packet decomposition, and the signal energy coefficients of each frequency band were extracted and used as input feature vectors in SVM for normal and faulty pattern recognition. Second, precision analysis using wavelet lifting could successfully filter out the noisy signals while maintaining the impulse characteristics of the fault; thus effectively extracting the fault frequency of the machine. Lastly, the knowledge base was built based on the field rules summarized by experts to identify the detailed fault type. Results have shown that SVM is a powerful tool to accomplish gearbox fault pattern recognition when the sample size is small, whereas the wavelet lifting scheme can effectively extract fault features, and rule-based reasoning can be used to identify the detailed fault type. Therefore, a method that combines SVM, wavelet lifting and rule-based reasoning ensures effective gearbox fault diagnosis.
Hill, W D; Davies, G; van de Lagemaat, L N; Christoforou, A; Marioni, R E; Fernandes, C P D; Liewald, D C; Croning, M D R; Payton, A; Craig, L C A; Whalley, L J; Horan, M; Ollier, W; Hansell, N K; Wright, M J; Martin, N G; Montgomery, G W; Steen, V M; Le Hellard, S; Espeseth, T; Lundervold, A J; Reinvang, I; Starr, J M; Pendleton, N; Grant, S G N; Bates, T C; Deary, I J
2014-01-01
Differences in general cognitive ability (intelligence) account for approximately half of the variation in any large battery of cognitive tests and are predictive of important life events including health. Genome-wide analyses of common single-nucleotide polymorphisms indicate that they jointly tag between a quarter and a half of the variance in intelligence. However, no single polymorphism has been reliably associated with variation in intelligence. It remains possible that these many small effects might be aggregated in networks of functionally linked genes. Here, we tested a network of 1461 genes in the postsynaptic density and associated complexes for an enriched association with intelligence. These were ascertained in 3511 individuals (the Cognitive Ageing Genetics in England and Scotland (CAGES) consortium) phenotyped for general cognitive ability, fluid cognitive ability, crystallised cognitive ability, memory and speed of processing. By analysing the results of a genome wide association study (GWAS) using Gene Set Enrichment Analysis, a significant enrichment was found for fluid cognitive ability for the proteins found in the complexes of N-methyl-D-aspartate receptor complex; P=0.002. Replication was sought in two additional cohorts (N=670 and 2062). A meta-analytic P-value of 0.003 was found when these were combined with the CAGES consortium. The results suggest that genetic variation in the macromolecular machines formed by membrane-associated guanylate kinase (MAGUK) scaffold proteins and their interaction partners contributes to variation in intelligence. PMID:24399044
Intelligence moderates neural responses to monetary reward and punishment.
Hawes, Daniel R; DeYoung, Colin G; Gray, Jeremy R; Rustichini, Aldo
2014-05-01
The relations between intelligence (IQ) and neural responses to monetary gains and losses were investigated in a simple decision task. In 94 healthy adults, typical responses of striatal blood oxygen level-dependent (BOLD) signal after monetary reward and punishment were weaker for subjects with higher IQ. IQ-moderated differential responses to gains and losses were also found for regions in the medial prefrontal cortex, posterior cingulate cortex, and left inferior frontal cortex. These regions have previously been identified with the subjective utility of monetary outcomes. Analysis of subjects' behavior revealed a correlation between IQ and the extent to which choices were related to experienced decision outcomes in preceding trials. Specifically, higher IQ predicted behavior to be more strongly correlated with an extended period of previously experienced decision outcomes, whereas lower IQ predicted behavior to be correlated exclusively to the most recent decision outcomes. We link these behavioral and imaging findings to a theoretical model capable of describing a role for intelligence during the evaluation of rewards generated by unknown probabilistic processes. Our results demonstrate neural differences in how people of different intelligence respond to experienced monetary rewards and punishments. Our theoretical discussion offers a functional description for how these individual differences may be linked to choice behavior. Together, our results and model support the hypothesis that observed correlations between intelligence and preferences may be rooted in the way decision outcomes are experienced ex post, rather than deriving exclusively from how choices are evaluated ex ante.
Conception d'un capteur intelligent pour la détection des vapeurs de styrène dans l'industrie
NASA Astrophysics Data System (ADS)
Agbossou, Kodjo; Agbebavi, T. James; Koffi, Demagna; Elhiri, Mohammed
1994-10-01
The techniques of measurement of toxic gases are nowadays based on the semiconductor type sensors. The modelling and the electronic processing of their signals can be used to improve the accuracy and the efficiency of the measurement. In this paper, an intelligent system using a semiconductor sensor has been designed for the detection of the styrene vapors. A set of the environmental parameters sensors such as the temperature, the pressure and the humidity, is added to the basic sensor and allows a precise detection of the styrene vapors in air. A microcontroller and a communication interface, that are included in the control system and in the data processing system, provide the local intelligence. The linearization routines of the differents sensors are in the memory of the microcontroller. The system made of the sensors, of the amplification circuits, of the microcontroller and of the communication network between the smart sensor and the computer is analysed. A laboratory test of the device is presented and the accuracies and efficiencies of the differents sensors are given. Les techniques fiables de quantification des gaz polluants sont aujourd'hui basées sur l'utilisation des détecteurs à récepteurs chimiques et sur des capteurs à semiconducteurs. La modélisation et le traitement numérique des signaux résultants sont importants pour une mesure efficace et précise dans un milieu donné. Dans cet article, un capteur intelligent, utilisant un détecteur de gaz type semiconducteur a été réalisé pour la détection des vapeurs de styrène. Un ensemble de détecteurs des paramètres environnementaux, tels que la température, la pression et l'humidité, ajoutés au capteur de styrène, permettent de mesurer avec un bon contrôle les vapeurs de styrène dans l'air. Le système de contrôle et de gestion local des données est constitué d'un microcontrôleur et d'une interface de communication. Le microcontrôleur contient dans sa mémoire toutes les fonctions de linéarisation des différents capteurs. Cet ensemble de capteurs, de circuits conditionneurs, de microcontrôleur et d'interface de communication est appelé " capteur intelligent ". Le réseau de communication entre le capteur intelligent et le micro-ordinateur est analysé en terme de traitement de signal. Un exemple d'application au laboratoire est présenté, les sensibilités et les précisions des différents capteurs sont données.
Auditory-Phonetic Projection and Lexical Structure in the Recognition of Sine-Wave Words
ERIC Educational Resources Information Center
Remez, Robert E.; Dubowski, Kathryn R.; Broder, Robin S.; Davids, Morgana L.; Grossman, Yael S.; Moskalenko, Marina; Pardo, Jennifer S.; Hasbun, Sara Maria
2011-01-01
Speech remains intelligible despite the elimination of canonical acoustic correlates of phonemes from the spectrum. A portion of this perceptual flexibility can be attributed to modulation sensitivity in the auditory-to-phonetic projection, although signal-independent properties of lexical neighborhoods also affect intelligibility in utterances…
Howard, Mary F; Poeppel, David
2010-11-01
Speech stimuli give rise to neural activity in the listener that can be observed as waveforms using magnetoencephalography. Although waveforms vary greatly from trial to trial due to activity unrelated to the stimulus, it has been demonstrated that spoken sentences can be discriminated based on theta-band (3-7 Hz) phase patterns in single-trial response waveforms. Furthermore, manipulations of the speech signal envelope and fine structure that reduced intelligibility were found to produce correlated reductions in discrimination performance, suggesting a relationship between theta-band phase patterns and speech comprehension. This study investigates the nature of this relationship, hypothesizing that theta-band phase patterns primarily reflect cortical processing of low-frequency (<40 Hz) modulations present in the acoustic signal and required for intelligibility, rather than processing exclusively related to comprehension (e.g., lexical, syntactic, semantic). Using stimuli that are quite similar to normal spoken sentences in terms of low-frequency modulation characteristics but are unintelligible (i.e., their time-inverted counterparts), we find that discrimination performance based on theta-band phase patterns is equal for both types of stimuli. Consistent with earlier findings, we also observe that whereas theta-band phase patterns differ across stimuli, power patterns do not. We use a simulation model of the single-trial response to spoken sentence stimuli to demonstrate that phase-locked responses to low-frequency modulations of the acoustic signal can account not only for the phase but also for the power results. The simulation offers insight into the interpretation of the empirical results with respect to phase-resetting and power-enhancement models of the evoked response.
Advanced technologies in the ASI MLRO towards a new generation laser ranging system
NASA Technical Reports Server (NTRS)
Varghese, Thomas; Bianco, Giuseppe
1994-01-01
Matera Laser Ranging Observatory (MLRO) is a high performance, highly automated optical and astronomical observatory currently under design and development by AlliedSignal for the Italian Space Agency (ASI). It is projected to become operational at the Centro Geodesia Spaziale in Matera, Italy, in 1997. MLRO, based on a 1.5-meter astronomical quality telescope, will perform ranging to spacecraft in earthbound orbits, lunar reflectors, and specially equipped deep space missions. The primary emphasis during design is to incorporate state-of-the-art technologies to produce an intelligent, automated, high accuracy ranging system that will mimic the characteristic features of a fifth generation laser ranging system. The telescope has multiple ports and foci to support future experiments in the areas of laser communications, lidar, astrometry, etc. The key features providing state-of-the-art ranging performance include: a diode-pumped picosecond (50 ps) laser, high speed (3-5 GHz) optoelectronic detection and signal processing, and a high accuracy (6 ps) high resolution (less than 2 ps) time measurement capability. The above combination of technologies is expected to yield millimeter laser ranging precision and accuracy on targets up to 300,000 km, surpassing the best operational instrument performance to date by a factor of five or more. Distributed processing and control using a state-of-the-art computing environment provides the framework for efficient operation, system optimization, and diagnostics. A computationally intelligent environment permits optimal planning, scheduling, tracking, and data processing. It also supports remote access, monitor, and control for joint experiments with other observatories.
Finke, Mareike; Sandmann, Pascale; Bönitz, Hanna; Kral, Andrej; Büchner, Andreas
2016-01-01
Single-sided deaf subjects with a cochlear implant (CI) provide the unique opportunity to compare central auditory processing of the electrical input (CI ear) and the acoustic input (normal-hearing, NH, ear) within the same individual. In these individuals, sensory processing differs between their two ears, while cognitive abilities are the same irrespectively of the sensory input. To better understand perceptual-cognitive factors modulating speech intelligibility with a CI, this electroencephalography study examined the central-auditory processing of words, the cognitive abilities, and the speech intelligibility in 10 postlingually single-sided deaf CI users. We found lower hit rates and prolonged response times for word classification during an oddball task for the CI ear when compared with the NH ear. Also, event-related potentials reflecting sensory (N1) and higher-order processing (N2/N4) were prolonged for word classification (targets versus nontargets) with the CI ear compared with the NH ear. Our results suggest that speech processing via the CI ear and the NH ear differs both at sensory (N1) and cognitive (N2/N4) processing stages, thereby affecting the behavioral performance for speech discrimination. These results provide objective evidence for cognition to be a key factor for speech perception under adverse listening conditions, such as the degraded speech signal provided from the CI. © 2016 S. Karger AG, Basel.
The application of intelligent process control to space based systems
NASA Technical Reports Server (NTRS)
Wakefield, G. Steve
1990-01-01
The application of Artificial Intelligence to electronic and process control can help attain the autonomy and safety requirements of manned space systems. An overview of documented applications within various industries is presented. The development process is discussed along with associated issues for implementing an intelligence process control system.
An Ensemble of Neural Networks for Stock Trading Decision Making
NASA Astrophysics Data System (ADS)
Chang, Pei-Chann; Liu, Chen-Hao; Fan, Chin-Yuan; Lin, Jun-Lin; Lai, Chih-Ming
Stock turning signals detection are very interesting subject arising in numerous financial and economic planning problems. In this paper, Ensemble Neural Network system with Intelligent Piecewise Linear Representation for stock turning points detection is presented. The Intelligent piecewise linear representation method is able to generate numerous stocks turning signals from the historic data base, then Ensemble Neural Network system will be applied to train the pattern and retrieve similar stock price patterns from historic data for training. These turning signals represent short-term and long-term trading signals for selling or buying stocks from the market which are applied to forecast the future turning points from the set of test data. Experimental results demonstrate that the hybrid system can make a significant and constant amount of profit when compared with other approaches using stock data available in the market.
Computer Vision for Artificially Intelligent Robotic Systems
NASA Astrophysics Data System (ADS)
Ma, Chialo; Ma, Yung-Lung
1987-04-01
In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Model, we use a narrow beam transducer and it's input voltage is 50V p-p. A RobOt equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.
Open ended intelligence: the individuation of intelligent agents
NASA Astrophysics Data System (ADS)
Weinbaum Weaver, David; Veitas, Viktoras
2017-03-01
Artificial general intelligence is a field of research aiming to distil the principles of intelligence that operate independently of a specific problem domain and utilise these principles in order to synthesise systems capable of performing any intellectual task a human being is capable of and beyond. While "narrow" artificial intelligence which focuses on solving specific problems such as speech recognition, text comprehension, visual pattern recognition and robotic motion has shown impressive breakthroughs lately, understanding general intelligence remains elusive. We propose a paradigm shift from intelligence perceived as a competence of individual agents defined in relation to an a priori given problem domain or a goal, to intelligence perceived as a formative process of self-organisation. We call this process open-ended intelligence. Starting with a brief introduction of the current conceptual approach, we expose a number of serious limitations that are traced back to the ontological roots of the concept of intelligence. Open-ended intelligence is then developed as an abstraction of the process of human cognitive development, so its application can be extended to general agents and systems. We introduce and discuss three facets of the idea: the philosophical concept of individuation, sense-making and the individuation of general cognitive agents. We further show how open-ended intelligence can be framed in terms of a distributed, self-organising network of interacting elements and how such process is scalable. The framework highlights an important relation between coordination and intelligence and a new understanding of values.
Impact of VLSI/VHSIC on satellite on-board signal processing
NASA Astrophysics Data System (ADS)
Aanstoos, J. V.; Ruedger, W. H.; Snyder, W. E.; Kelly, W. L.
Forecasted improvements in IC fabrication techniques, such as the use of X-ray lithography, are expected to yield submicron circuit feature sizes within the decade of the 1980s. As dimensions decrease, reliability, cost, speed, power consumption and density improvements will be realized which have a significant impact on the capabilities of onboard spacecraft signal processing functions. This will in turn result in increases of the intelligence that may be deployed on spaceborne remote sensing platforms. Among programs oriented toward such goals are the silicon-based Very High Speed Integrated Circuit (VHSIC) researches sponsored by the U.S. Department of Defense, and efforts toward the development of GaAs devices which will compete with silicon VLSI technology for future applications. GaAs has an electron mobility which is five to six times that of silicon, and promises commensurate computation speed increases under low field conditions.
On adaptive robustness approach to Anti-Jam signal processing
NASA Astrophysics Data System (ADS)
Poberezhskiy, Y. S.; Poberezhskiy, G. Y.
An effective approach to exploiting statistical differences between desired and jamming signals named adaptive robustness is proposed and analyzed in this paper. It combines conventional Bayesian, adaptive, and robust approaches that are complementary to each other. This combining strengthens the advantages and mitigates the drawbacks of the conventional approaches. Adaptive robustness is equally applicable to both jammers and their victim systems. The capabilities required for realization of adaptive robustness in jammers and victim systems are determined. The employment of a specific nonlinear robust algorithm for anti-jam (AJ) processing is described and analyzed. Its effectiveness in practical situations has been proven analytically and confirmed by simulation. Since adaptive robustness can be used by both sides in electronic warfare, it is more advantageous for the fastest and most intelligent side. Many results obtained and discussed in this paper are also applicable to commercial applications such as communications in unregulated or poorly regulated frequency ranges and systems with cognitive capabilities.
The Search for Extra-Terrestrial Intelligence
NASA Astrophysics Data System (ADS)
Tarter, J.
1998-12-01
Aliens abound on the movie screens, but in reality we are still trying to find out if we share our universe with other sentient creatures. Intelligence is very difficult to define, and impossible to directly detect over interstellar distances. Therefore, SETI, the search for extraterrestrial intelligence, is actually an attempt to detect evidence of another distant technology. If we find such evidence, we will infer the existence of intelligent technologists. For the past 36 years, the SETI community has had a very pragmatic definition of intelligence - the ability to build radio telescopes! Radio signals are not the only possible way to detect a technology across the vast distances that separate the stars, but given our own current technological state, it remains the best way.
Noise suppression methods for robust speech processing
NASA Astrophysics Data System (ADS)
Boll, S. F.; Ravindra, H.; Randall, G.; Armantrout, R.; Power, R.
1980-05-01
Robust speech processing in practical operating environments requires effective environmental and processor noise suppression. This report describes the technical findings and accomplishments during this reporting period for the research program funded to develop real time, compressed speech analysis synthesis algorithms whose performance in invariant under signal contamination. Fulfillment of this requirement is necessary to insure reliable secure compressed speech transmission within realistic military command and control environments. Overall contributions resulting from this research program include the understanding of how environmental noise degrades narrow band, coded speech, development of appropriate real time noise suppression algorithms, and development of speech parameter identification methods that consider signal contamination as a fundamental element in the estimation process. This report describes the current research and results in the areas of noise suppression using the dual input adaptive noise cancellation using the short time Fourier transform algorithms, articulation rate change techniques, and a description of an experiment which demonstrated that the spectral subtraction noise suppression algorithm can improve the intelligibility of 2400 bps, LPC 10 coded, helicopter speech by 10.6 point.
The outlook for cosmic company.
Shostak, S
2001-12-01
The last 100 million years or so has seen a continued increase in encephalization for several terrestrial species. Intelligence has survival value. Developments in astrobiology suggest that what was once considered enormously improbable, namely life, is now suspected of being ubiquitous. It may be that the evolution of intelligence is unlikely, but in a finite, breathtakingly large universe (10(22) stars) small probability likely does not matter. Even if nature is indifferent to producing intelligence, SETI might still succeed. Biological intelligence may be rare, but it has the potential for creating engineered synthetic intelligence, capable of rapid and directed self-evolution. The galaxy could be rife with such long-lived, communicating devices, even if intelligent protoplasm is both rare and fleeting. SETI is looking for narrow-band, microwave signals that are not produced naturally. Ultimately, SETI is more exploration than experimentation.
Intelligent deflection routing in buffer-less networks.
Haeri, Soroush; Trajković, Ljiljana
2015-02-01
Deflection routing is employed to ameliorate packet loss caused by contention in buffer-less architectures such as optical burst-switched networks. The main goal of deflection routing is to successfully deflect a packet based only on a limited knowledge that network nodes possess about their environment. In this paper, we present a framework that introduces intelligence to deflection routing (iDef). iDef decouples the design of the signaling infrastructure from the underlying learning algorithm. It consists of a signaling and a decision-making module. Signaling module implements a feedback management protocol while the decision-making module implements a reinforcement learning algorithm. We also propose several learning-based deflection routing protocols, implement them in iDef using the ns-3 network simulator, and compare their performance.
Study on Unified Chaotic System-Based Wind Turbine Blade Fault Diagnostic System
NASA Astrophysics Data System (ADS)
Kuo, Ying-Che; Hsieh, Chin-Tsung; Yau, Her-Terng; Li, Yu-Chung
At present, vibration signals are processed and analyzed mostly in the frequency domain. The spectrum clearly shows the signal structure and the specific characteristic frequency band is analyzed, but the number of calculations required is huge, resulting in delays. Therefore, this study uses the characteristics of a nonlinear system to load the complete vibration signal to the unified chaotic system, applying the dynamic error to analyze the wind turbine vibration signal, and adopting extenics theory for artificial intelligent fault diagnosis of the analysis signal. Hence, a fault diagnostor has been developed for wind turbine rotating blades. This study simulates three wind turbine blade states, namely stress rupture, screw loosening and blade loss, and validates the methods. The experimental results prove that the unified chaotic system used in this paper has a significant effect on vibration signal analysis. Thus, the operating conditions of wind turbines can be quickly known from this fault diagnostic system, and the maintenance schedule can be arranged before the faults worsen, making the management and implementation of wind turbines smoother, so as to reduce many unnecessary costs.
Kreifelts, Benjamin; Ethofer, Thomas; Huberle, Elisabeth; Grodd, Wolfgang; Wildgruber, Dirk
2010-07-01
Multimodal integration of nonverbal social signals is essential for successful social interaction. Previous studies have implicated the posterior superior temporal sulcus (pSTS) in the perception of social signals such as nonverbal emotional signals as well as in social cognitive functions like mentalizing/theory of mind. In the present study, we evaluated the relationships between trait emotional intelligence (EI) and fMRI activation patterns in individual subjects during the multimodal perception of nonverbal emotional signals from voice and face. Trait EI was linked to hemodynamic responses in the right pSTS, an area which also exhibits a distinct sensitivity to human voices and faces. Within all other regions known to subserve the perceptual audiovisual integration of human social signals (i.e., amygdala, fusiform gyrus, thalamus), no such linked responses were observed. This functional difference in the network for the audiovisual perception of human social signals indicates a specific contribution of the pSTS as a possible interface between the perception of social information and social cognition. (c) 2009 Wiley-Liss, Inc.
Color regeneration from reflective color sensor using an artificial intelligent technique.
Saracoglu, Ömer Galip; Altural, Hayriye
2010-01-01
A low-cost optical sensor based on reflective color sensing is presented. Artificial neural network models are used to improve the color regeneration from the sensor signals. Analog voltages of the sensor are successfully converted to RGB colors. The artificial intelligent models presented in this work enable color regeneration from analog outputs of the color sensor. Besides, inverse modeling supported by an intelligent technique enables the sensor probe for use of a colorimetric sensor that relates color changes to analog voltages.
Advanced Communication Processing Techniques
NASA Astrophysics Data System (ADS)
Scholtz, Robert A.
This document contains the proceedings of the workshop Advanced Communication Processing Techniques, held May 14 to 17, 1989, near Ruidoso, New Mexico. Sponsored by the Army Research Office (under Contract DAAL03-89-G-0016) and organized by the Communication Sciences Institute of the University of Southern California, the workshop had as its objective to determine those applications of intelligent/adaptive communication signal processing that have been realized and to define areas of future research. We at the Communication Sciences Institute believe that there are two emerging areas which deserve considerably more study in the near future: (1) Modulation characterization, i.e., the automation of modulation format recognition so that a receiver can reliably demodulate a signal without using a priori information concerning the signal's structure, and (2) the incorporation of adaptive coding into communication links and networks. (Encoders and decoders which can operate with a wide variety of codes exist, but the way to utilize and control them in links and networks is an issue). To support these two new interest areas, one must have both a knowledge of (3) the kinds of channels and environments in which the systems must operate, and of (4) the latest adaptive equalization techniques which might be employed in these efforts.
Gao, Zhao; Yang, Qi; Ma, Xiaole; Becker, Benjamin; Li, Keshuang; Zhou, Feng; Kendrick, Keith M.
2017-01-01
Language may have evolved as a signal of mental fitness. However, it remains unclear what language form and topic men use to covertly signal mate quality. In this study 69 men created compliments to impress unfamiliar women they chose to either date or work with and provided hand scans to compute 2D4D ratio as a proxy for prenatal testosterone exposure and masculinity indicator. Compliments were coded in terms of form (literal vs. metaphorical) and topic (women's appearance vs. non-appearance), with metaphorical ones being subsequently rated by 114 women for psycholinguistic features, indices of intelligence and willingness to have a romantic relationship with the author. Results showed that in a dating context, men produced more metaphorical form compliments targeting appearance compared to the working context and they were associated with men's art creativity and negatively with 2D4D ratio (i.e., positively with masculinity). Women preferred establishing a romantic relationship with a higher proportion of the men producing metaphorical compliments in a dating than a working context. Furthermore, in the dating but not the working context, women perceived men producing such compliments as being more intelligent, and importantly this correlated with the men's actual verbal intelligence. Overall, findings suggest that men may use metaphorical language compliments targeting women's appearance in a dating context to signal covertly their mate quality. PMID:29312054
Gao, Zhao; Yang, Qi; Ma, Xiaole; Becker, Benjamin; Li, Keshuang; Zhou, Feng; Kendrick, Keith M
2017-01-01
Language may have evolved as a signal of mental fitness. However, it remains unclear what language form and topic men use to covertly signal mate quality. In this study 69 men created compliments to impress unfamiliar women they chose to either date or work with and provided hand scans to compute 2D4D ratio as a proxy for prenatal testosterone exposure and masculinity indicator. Compliments were coded in terms of form (literal vs. metaphorical) and topic (women's appearance vs. non-appearance), with metaphorical ones being subsequently rated by 114 women for psycholinguistic features, indices of intelligence and willingness to have a romantic relationship with the author. Results showed that in a dating context, men produced more metaphorical form compliments targeting appearance compared to the working context and they were associated with men's art creativity and negatively with 2D4D ratio (i.e., positively with masculinity). Women preferred establishing a romantic relationship with a higher proportion of the men producing metaphorical compliments in a dating than a working context. Furthermore, in the dating but not the working context, women perceived men producing such compliments as being more intelligent, and importantly this correlated with the men's actual verbal intelligence. Overall, findings suggest that men may use metaphorical language compliments targeting women's appearance in a dating context to signal covertly their mate quality.
Health monitoring and rehabilitation of a concrete structure using intelligent materials
NASA Astrophysics Data System (ADS)
Song, G.; Mo, Y. L.; Otero, K.; Gu, H.
2006-04-01
This paper presents the concept of an intelligent reinforced concrete structure (IRCS) and its application in structural health monitoring and rehabilitation. The IRCS has multiple functions which include self-rehabilitation, self-vibration damping, and self-structural health monitoring. These functions are enabled by two types of intelligent (smart) materials: shape memory alloys (SMAs) and piezoceramics. In this research, Nitinol type SMA and PZT (lead zirconate titanate) type piezoceramics are used. The proposed concrete structure is reinforced by martensite Nitinol cables using the method of post-tensioning. The martensite SMA significantly increases the concrete's damping property and its ability to handle large impact. In the presence of cracks due to explosions or earthquakes, by electrically heating the SMA cables, the SMA cables contract and close up the cracks. In this research, PZT patches are embedded in the concrete structure to detect possible cracks inside the concrete structure. The wavelet packet analysis method is then applied as a signal-processing tool to analyze the sensor signals. A damage index is defined to describe the damage severity for health monitoring purposes. In addition, by monitoring the electric resistance change of the SMA cables, the crack width can be estimated. To demonstrate this concept, a concrete beam specimen with reinforced SMA cables and with embedded PZT patches is fabricated. Experiments demonstrate that the IRC has the ability of self-sensing and self-rehabilitation. Three-point bending tests were conducted. During the loading process, a crack opens up to 0.47 inches. Upon removal of the load and heating the SMA cables, the crack closes up. The damage index formed by wavelet packet analysis of the PZT sensor data predicts and confirms the onset and severity of the crack during the loading. Also during the loading, the electrical resistance value of the SMA cable changes by up to 27% and this phenomenon is used to monitor the crack width.
Signal Detection Framework Using Semantic Text Mining Techniques
ERIC Educational Resources Information Center
Sudarsan, Sithu D.
2009-01-01
Signal detection is a challenging task for regulatory and intelligence agencies. Subject matter experts in those agencies analyze documents, generally containing narrative text in a time bound manner for signals by identification, evaluation and confirmation, leading to follow-up action e.g., recalling a defective product or public advisory for…
2010-12-01
Methodology RMAT Risk Management Assessment Tool SIDA Security Identification Display Area SIGINT Signals Intelligence SO18 Aviation Security...aircraft operate (§ 1542.203); • Provide detection and physical security measures for the “Security Identification Display Area” ( SIDA ), i.e., the area
The Listener: No Longer the Silent Partner in Reduced Intelligibility
ERIC Educational Resources Information Center
Zielinski, Beth W.
2008-01-01
In this study I investigate the impact of different characteristics of the L2 speech signal on the intelligibility of L2 speakers of English to native listeners. Three native listeners were observed and questioned as they orthographically transcribed utterances taken from connected conversational speech produced by three L2 speakers from different…
Design and implementation of an intelligent belt system using accelerometer.
Liu, Botong; Wang, Duo; Li, Sha; Nie, Xuhui; Xu, Shan; Jiao, Bingli; Duan, Xiaohui; Huang, Anpeng
2015-01-01
Activity monitor systems are increasing used recently. They are important for athletes and casual users to manage physical activity during daily exercises. In this paper, we use a triaxial accelerometer to design and implement an intelligent belt system, which can detect the user's step and flapping motion. In our system, a wearable intelligent belt is worn on the user's waist to collect activity acceleration signals. We present a step detection algorithm to detect real-time human step, which has high accuracy and low complexity. In our system, an Android App is developed to manage the intelligent belt. We also propose a protocol, which can guarantee data transmission between smartphones and wearable belt effectively and efficiently. In addition, when users flap the belt in emergency, the smartphone will receive alarm signal sending by the belt, and then notifies the emergency contact person, which can be really helpful for users in danger. Our experiment results show our system can detect physical activities with high accuracy (overall accuracy of our algorithm is above 95%) and has an effective alarm subsystem, which is significant for the practical use.
Lai, Ying-Hui; Tsao, Yu; Lu, Xugang; Chen, Fei; Su, Yu-Ting; Chen, Kuang-Chao; Chen, Yu-Hsuan; Chen, Li-Ching; Po-Hung Li, Lieber; Lee, Chin-Hui
2018-01-20
We investigate the clinical effectiveness of a novel deep learning-based noise reduction (NR) approach under noisy conditions with challenging noise types at low signal to noise ratio (SNR) levels for Mandarin-speaking cochlear implant (CI) recipients. The deep learning-based NR approach used in this study consists of two modules: noise classifier (NC) and deep denoising autoencoder (DDAE), thus termed (NC + DDAE). In a series of comprehensive experiments, we conduct qualitative and quantitative analyses on the NC module and the overall NC + DDAE approach. Moreover, we evaluate the speech recognition performance of the NC + DDAE NR and classical single-microphone NR approaches for Mandarin-speaking CI recipients under different noisy conditions. The testing set contains Mandarin sentences corrupted by two types of maskers, two-talker babble noise, and a construction jackhammer noise, at 0 and 5 dB SNR levels. Two conventional NR techniques and the proposed deep learning-based approach are used to process the noisy utterances. We qualitatively compare the NR approaches by the amplitude envelope and spectrogram plots of the processed utterances. Quantitative objective measures include (1) normalized covariance measure to test the intelligibility of the utterances processed by each of the NR approaches; and (2) speech recognition tests conducted by nine Mandarin-speaking CI recipients. These nine CI recipients use their own clinical speech processors during testing. The experimental results of objective evaluation and listening test indicate that under challenging listening conditions, the proposed NC + DDAE NR approach yields higher intelligibility scores than the two compared classical NR techniques, under both matched and mismatched training-testing conditions. When compared to the two well-known conventional NR techniques under challenging listening condition, the proposed NC + DDAE NR approach has superior noise suppression capabilities and gives less distortion for the key speech envelope information, thus, improving speech recognition more effectively for Mandarin CI recipients. The results suggest that the proposed deep learning-based NR approach can potentially be integrated into existing CI signal processors to overcome the degradation of speech perception caused by noise.
A Visual Cortical Network for Deriving Phonological Information from Intelligible Lip Movements.
Hauswald, Anne; Lithari, Chrysa; Collignon, Olivier; Leonardelli, Elisa; Weisz, Nathan
2018-05-07
Successful lip-reading requires a mapping from visual to phonological information [1]. Recently, visual and motor cortices have been implicated in tracking lip movements (e.g., [2]). It remains unclear, however, whether visuo-phonological mapping occurs already at the level of the visual cortex-that is, whether this structure tracks the acoustic signal in a functionally relevant manner. To elucidate this, we investigated how the cortex tracks (i.e., entrains to) absent acoustic speech signals carried by silent lip movements. Crucially, we contrasted the entrainment to unheard forward (intelligible) and backward (unintelligible) acoustic speech. We observed that the visual cortex exhibited stronger entrainment to the unheard forward acoustic speech envelope compared to the unheard backward acoustic speech envelope. Supporting the notion of a visuo-phonological mapping process, this forward-backward difference of occipital entrainment was not present for actually observed lip movements. Importantly, the respective occipital region received more top-down input, especially from left premotor, primary motor, and somatosensory regions and, to a lesser extent, also from posterior temporal cortex. Strikingly, across participants, the extent of top-down modulation of the visual cortex stemming from these regions partially correlated with the strength of entrainment to absent acoustic forward speech envelope, but not to present forward lip movements. Our findings demonstrate that a distributed cortical network, including key dorsal stream auditory regions [3-5], influences how the visual cortex shows sensitivity to the intelligibility of speech while tracking silent lip movements. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.
Venezia, Jonathan H.; Hickok, Gregory; Richards, Virginia M.
2016-01-01
Speech intelligibility depends on the integrity of spectrotemporal patterns in the signal. The current study is concerned with the speech modulation power spectrum (MPS), which is a two-dimensional representation of energy at different combinations of temporal and spectral (i.e., spectrotemporal) modulation rates. A psychophysical procedure was developed to identify the regions of the MPS that contribute to successful reception of auditory sentences. The procedure, based on the two-dimensional image classification technique known as “bubbles” (Gosselin and Schyns (2001). Vision Res. 41, 2261–2271), involves filtering (i.e., degrading) the speech signal by removing parts of the MPS at random, and relating filter patterns to observer performance (keywords identified) over a number of trials. The result is a classification image (CImg) or “perceptual map” that emphasizes regions of the MPS essential for speech intelligibility. This procedure was tested using normal-rate and 2×-time-compressed sentences. The results indicated: (a) CImgs could be reliably estimated in individual listeners in relatively few trials, (b) CImgs tracked changes in spectrotemporal modulation energy induced by time compression, though not completely, indicating that “perceptual maps” deviated from physical stimulus energy, and (c) the bubbles method captured variance in intelligibility not reflected in a common modulation-based intelligibility metric (spectrotemporal modulation index or STMI). PMID:27586738
Measures for assessing architectural speech security (privacy) of closed offices and meeting rooms.
Gover, Bradford N; Bradley, John S
2004-12-01
Objective measures were investigated as predictors of the speech security of closed offices and rooms. A new signal-to-noise type measure is shown to be a superior indicator for security than existing measures such as the Articulation Index, the Speech Intelligibility Index, the ratio of the loudness of speech to that of noise, and the A-weighted level difference of speech and noise. This new measure is a weighted sum of clipped one-third-octave-band signal-to-noise ratios; various weightings and clipping levels are explored. Listening tests had 19 subjects rate the audibility and intelligibility of 500 English sentences, filtered to simulate transmission through various wall constructions, and presented along with background noise. The results of the tests indicate that the new measure is highly correlated with sentence intelligibility scores and also with three security thresholds: the threshold of intelligibility (below which speech is unintelligible), the threshold of cadence (below which the cadence of speech is inaudible), and the threshold of audibility (below which speech is inaudible). The ratio of the loudness of speech to that of noise, and simple A-weighted level differences are both shown to be well correlated with these latter two thresholds (cadence and audibility), but not well correlated with intelligibility.
Expanding the Targeting Process into the Space Domain
2008-06-01
planning and operations. The process is a continuous method by which information is converted into intelligence and made available to users...Targeting personnel and organizations consume intelligence produced by various agencies and organizations. Actionable and predictive intelligence applies to... intelligence and operations communities (Figure 1). 1 United States Department of Defense Joint
Expert system constant false alarm rate processor
NASA Astrophysics Data System (ADS)
Baldygo, William J., Jr.; Wicks, Michael C.
1993-10-01
The requirements for high detection probability and low false alarm probability in modern wide area surveillance radars are rarely met due to spatial variations in clutter characteristics. Many filtering and CFAR detection algorithms have been developed to effectively deal with these variations; however, any single algorithm is likely to exhibit excessive false alarms and intolerably low detection probabilities in a dynamically changing environment. A great deal of research has led to advances in the state of the art in Artificial Intelligence (AI) and numerous areas have been identified for application to radar signal processing. The approach suggested here, discussed in a patent application submitted by the authors, is to intelligently select the filtering and CFAR detection algorithms being executed at any given time, based upon the observed characteristics of the interference environment. This approach requires sensing the environment, employing the most suitable algorithms, and applying an appropriate multiple algorithm fusion scheme or consensus algorithm to produce a global detection decision.
NASA Astrophysics Data System (ADS)
Antony, Joby; Mathuria, D. S.; Chaudhary, Anup; Datta, T. S.; Maity, T.
2017-02-01
Cryogenic network for linear accelerator operations demand a large number of Cryogenic sensors, associated instruments and other control-instrumentation to measure, monitor and control different cryogenic parameters remotely. Here we describe an alternate approach of six types of newly designed integrated intelligent cryogenic instruments called device-servers which has the complete circuitry for various sensor-front-end analog instrumentation and the common digital back-end http-server built together, to make crateless PLC-free model of controls and data acquisition. These identified instruments each sensor-specific viz. LHe server, LN2 Server, Control output server, Pressure server, Vacuum server and Temperature server are completely deployed over LAN for the cryogenic operations of IUAC linac (Inter University Accelerator Centre linear Accelerator), New Delhi. This indigenous design gives certain salient features like global connectivity, low cost due to crateless model, easy signal processing due to integrated design, less cabling and device-interconnectivity etc.
Intelligent imaging systems for automotive applications
NASA Astrophysics Data System (ADS)
Thompson, Chris; Huang, Yingping; Fu, Shan
2004-03-01
In common with many other application areas, visual signals are becoming an increasingly important information source for many automotive applications. For several years CCD cameras have been used as research tools for a range of automotive applications. Infrared cameras, RADAR and LIDAR are other types of imaging sensors that have also been widely investigated for use in cars. This paper will describe work in this field performed in C2VIP over the last decade - starting with Night Vision Systems and looking at various other Advanced Driver Assistance Systems. Emerging from this experience, we make the following observations which are crucial for "intelligent" imaging systems: 1. Careful arrangement of sensor array. 2. Dynamic-Self-Calibration. 3. Networking and processing. 4. Fusion with other imaging sensors, both at the image level and the feature level, provides much more flexibility and reliability in complex situations. We will discuss how these problems can be addressed and what are the outstanding issues.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, Qishi; Zhu, Mengxia; Rao, Nageswara S
We propose an intelligent decision support system based on sensor and computer networks that incorporates various component techniques for sensor deployment, data routing, distributed computing, and information fusion. The integrated system is deployed in a distributed environment composed of both wireless sensor networks for data collection and wired computer networks for data processing in support of homeland security defense. We present the system framework and formulate the analytical problems and develop approximate or exact solutions for the subtasks: (i) sensor deployment strategy based on a two-dimensional genetic algorithm to achieve maximum coverage with cost constraints; (ii) data routing scheme tomore » achieve maximum signal strength with minimum path loss, high energy efficiency, and effective fault tolerance; (iii) network mapping method to assign computing modules to network nodes for high-performance distributed data processing; and (iv) binary decision fusion rule that derive threshold bounds to improve system hit rate and false alarm rate. These component solutions are implemented and evaluated through either experiments or simulations in various application scenarios. The extensive results demonstrate that these component solutions imbue the integrated system with the desirable and useful quality of intelligence in decision making.« less
Evaluation of Algorithms for Compressing Hyperspectral Data
NASA Technical Reports Server (NTRS)
Cook, Sid; Harsanyi, Joseph; Faber, Vance
2003-01-01
With EO-1 Hyperion in orbit NASA is showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI spectral compression and Mapping Science (MSI) for JPEG 2000 spatial compression expertise, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor > 100, while retaining the necessary spectral and spatial fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our compression algorithms leverage commercial-off-the-shelf (COTS) spectral and spatial exploitation algorithms. We are currently in the process of evaluating these compression algorithms using statistical analysis and NASA scientists. We are also developing special purpose processors for executing these algorithms onboard a spacecraft.
Advanced telemetry systems for payloads. Technology needs, objectives and issues
NASA Technical Reports Server (NTRS)
1990-01-01
The current trends in advanced payload telemetry are the new developments in advanced modulation/coding, the applications of intelligent techniques, data distribution processing, and advanced signal processing methodologies. Concerted efforts will be required to design ultra-reliable man-rated software to cope with these applications. The intelligence embedded and distributed throughout various segments of the telemetry system will need to be overridden by an operator in case of life-threatening situations, making it a real-time integration issue. Suitable MIL standards on physical interfaces and protocols will be adopted to suit the payload telemetry system. New technologies and techniques will be developed for fast retrieval of mass data. Currently, these technology issues are being addressed to provide more efficient, reliable, and reconfigurable systems. There is a need, however, to change the operation culture. The current role of NASA as a leader in developing all the new innovative hardware should be altered to save both time and money. We should use all the available hardware/software developed by the industry and use the existing standards rather than inventing our own.
Hands-free human-machine interaction with voice
NASA Astrophysics Data System (ADS)
Juang, B. H.
2004-05-01
Voice is natural communication interface between a human and a machine. The machine, when placed in today's communication networks, may be configured to provide automation to save substantial operating cost, as demonstrated in AT&T's VRCP (Voice Recognition Call Processing), or to facilitate intelligent services, such as virtual personal assistants, to enhance individual productivity. These intelligent services often need to be accessible anytime, anywhere (e.g., in cars when the user is in a hands-busy-eyes-busy situation or during meetings where constantly talking to a microphone is either undersirable or impossible), and thus call for advanced signal processing and automatic speech recognition techniques which support what we call ``hands-free'' human-machine communication. These techniques entail a broad spectrum of technical ideas, ranging from use of directional microphones and acoustic echo cancellatiion to robust speech recognition. In this talk, we highlight a number of key techniques that were developed for hands-free human-machine communication in the mid-1990s after Bell Labs became a unit of Lucent Technologies. A video clip will be played to demonstrate the accomplishement.
NASA Astrophysics Data System (ADS)
Herzing, Denise L.
2010-12-01
In the past SETI has focused on the reception and deciphering of radio signals from potential remote civilizations. It is conceivable that real-time contact and interaction with a social intelligence may occur in the future. A serious look at the development of relationship, and deciphering of communication signals within and between a non-terrestrial, non-primate sentient species is relevant. Since 1985 a resident community of free-ranging Atlantic spotted dolphins has been observed regularly in the Bahamas. Life history, relationships, regular interspecific interactions with bottlenose dolphins, and multi-modal underwater communication signals have been documented. Dolphins display social communication signals modified for water, their body types, and sensory systems. Like anthropologists, human researchers engage in benign observation in the water and interact with these dolphins to develop rapport and trust. Many individual dolphins have been known for over 20 years. Learning the culturally appropriate etiquette has been important in the relationship with this alien society. To engage humans in interaction the dolphins often initiate spontaneous displays, mimicry, imitation, and synchrony. These elements may be emergent/universal features of one intelligent species contacting another for the intention of initiating interaction. This should be a consideration for real-time contact and interaction for future SETI work.
Brydges, Christopher R; Ozolnieks, Krista L; Roberts, Gareth
2017-09-01
Attention deficit/hyperactivity disorder (ADHD) is a psychological condition characterized by inattention and hyperactivity. Cognitive deficits are commonly observed in ADHD patients, including impaired working memory, processing speed, and fluid intelligence, the three of which are theorized to be closely associated with one another. In this study, we aimed to determine if decreased fluid intelligence was associated with ADHD, and was mediated by deficits in working memory and processing speed. This study tested 142 young adults from the general population on a range of working memory, processing speed, and fluid intelligence tasks, and an ADHD self-report symptoms questionnaire. Results showed that total and hyperactive ADHD symptoms correlated significantly and negatively with fluid intelligence, but this association was fully mediated by working memory. However, inattentive symptoms were not associated with fluid intelligence. Additionally, processing speed was not associated with ADHD symptoms at all, and was not uniquely predictive of fluid intelligence. The results provide implications for working memory training programs for ADHD patients, and highlight potential differences between the neuropsychological profiles of ADHD subtypes. © 2015 The British Psychological Society.
A Research Program on Artificial Intelligence in Process Engineering.
ERIC Educational Resources Information Center
Stephanopoulos, George
1986-01-01
Discusses the use of artificial intelligence systems in process engineering. Describes a new program at the Massachusetts Institute of Technology which attempts to advance process engineering through technological advances in the areas of artificial intelligence and computers. Identifies the program's hardware facilities, software support,…
Preusse, Franziska; Elke, van der Meer; Deshpande, Gopikrishna; Krueger, Frank; Wartenburger, Isabell
2011-01-01
Fluid intelligence is the ability to think flexibly and to understand abstract relations. People with high fluid intelligence (hi-fluIQ) perform better in analogical reasoning tasks than people with average fluid intelligence (ave-fluIQ). Although previous neuroimaging studies reported involvement of parietal and frontal brain regions in geometric analogical reasoning (which is a prototypical task for fluid intelligence), however, neuroimaging findings on geometric analogical reasoning in hi-fluIQ are sparse. Furthermore, evidence on the relation between brain activation and intelligence while solving cognitive tasks is contradictory. The present study was designed to elucidate the cerebral correlates of geometric analogical reasoning in a sample of hi-fluIQ and ave-fluIQ high school students. We employed a geometric analogical reasoning task with graded levels of task difficulty and confirmed the involvement of the parieto-frontal network in solving this task. In addition to characterizing the brain regions involved in geometric analogical reasoning in hi-fluIQ and ave-fluIQ, we found that blood oxygenation level dependency (BOLD) signal changes were greater for hi-fluIQ than for ave-fluIQ in parietal brain regions. However, ave-fluIQ showed greater BOLD signal changes in the anterior cingulate cortex and medial frontal gyrus than hi-fluIQ. Thus, we showed that a similar network of brain regions is involved in geometric analogical reasoning in both groups. Interestingly, the relation between brain activation and intelligence is not mono-directional, but rather, it is specific for each brain region. The negative brain activation–intelligence relationship in frontal brain regions in hi-fluIQ goes along with a better behavioral performance and reflects a lower demand for executive monitoring compared to ave-fluIQ individuals. In conclusion, our data indicate that flexibly modulating the extent of regional cerebral activity is characteristic for fluid intelligence. PMID:21415916
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.
Sutojo, Sarinah; van de Par, Steven; Schoenmaker, Esther
2018-06-01
In situations with competing talkers or in the presence of masking noise, speech intelligibility can be improved by spatially separating the target speaker from the interferers. This advantage is generally referred to as spatial release from masking (SRM) and different mechanisms have been suggested to explain it. One proposed mechanism to benefit from spatial cues is the binaural masking release, which is purely stimulus driven. According to this mechanism, the spatial benefit results from differences in the binaural cues of target and masker, which need to appear simultaneously in time and frequency to improve the signal detection. In an alternative proposed mechanism, the differences in the interaural cues improve the segregation of auditory streams, a process, which involves top-down processing rather than being purely stimulus driven. Other than the cues that produce binaural masking release, the interaural cue differences between target and interferer required to improve stream segregation do not have to appear simultaneously in time and frequency. This study is concerned with the contribution of binaural masking release to SRM for three masker types that differ with respect to the amount of energetic masking they exert. Speech intelligibility was measured, employing a stimulus manipulation that inhibits binaural masking release, and analyzed with a metric to account for the number of better-ear glimpses. Results indicate that the contribution of the stimulus-driven binaural masking release plays a minor role while binaural stream segregation and the availability of glimpses in the better ear had a stronger influence on improving the speech intelligibility. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
iSANLA: intelligent sensor and actuator network for life science applications.
Schloesser, Mario; Schnitzer, Andreas; Ying, Hong; Silex, Carmen; Schiek, Michael
2008-01-01
In the fields of neurological rehabilitation and neurophysiological research there is a strong need for miniaturized, multi channel, battery driven, wireless networking DAQ systems enabling real-time digital signal processing and feedback experiments. For the scientific investigation on the passive auditory based 3D-orientation of Barn Owls and the scientific research on vegetative locomotor coordination of Parkinson's disease patients during rehabilitation we developed our 'intelligent Sensor and Actuator Network for Life science Application' (iSANLA) system. Implemented on the ultra low power microcontroller MSP430 sample rates up to 96 kHz have been realised for single channel DAQ. The system includes lossless local data storage up to 4 GB. With its outer dimensions of 20mm per rim and less than 15 g of weight including the Lithium-Ion battery our modular designed sensor node is thoroughly capable of up to eight channel recordings with 8 kHz sample rate each and provides sufficient computational power for digital signal processing ready to start our first mobile experiments. For wireless mobility a compact communication protocol based on the IEEE 802.15.4 wireless standard with net data rates up to 141 kbit/s has been implemented. To merge the lossless acquired data of the distributed iNODEs a time synchronization protocol has been developed preserving causality. Hence the necessary time synchronous start of the data acquisition inside a network of multiple sensors with a precision better than the highest sample rate has been realized.
Doelling, Keith; Arnal, Luc; Ghitza, Oded; Poeppel, David
2013-01-01
A growing body of research suggests that intrinsic neuronal slow (< 10 Hz) oscillations in auditory cortex appear to track incoming speech and other spectro-temporally complex auditory signals. Within this framework, several recent studies have identified critical-band temporal envelopes as the specific acoustic feature being reflected by the phase of these oscillations. However, how this alignment between speech acoustics and neural oscillations might underpin intelligibility is unclear. Here we test the hypothesis that the ‘sharpness’ of temporal fluctuations in the critical band envelope acts as a temporal cue to speech syllabic rate, driving delta-theta rhythms to track the stimulus and facilitate intelligibility. We interpret our findings as evidence that sharp events in the stimulus cause cortical rhythms to re-align and parse the stimulus into syllable-sized chunks for further decoding. Using magnetoencephalographic recordings, we show that by removing temporal fluctuations that occur at the syllabic rate, envelope-tracking activity is reduced. By artificially reinstating these temporal fluctuations, envelope-tracking activity is regained. These changes in tracking correlate with intelligibility of the stimulus. Together, the results suggest that the sharpness of fluctuations in the stimulus, as reflected in the cochlear output, drive oscillatory activity to track and entrain to the stimulus, at its syllabic rate. This process likely facilitates parsing of the stimulus into meaningful chunks appropriate for subsequent decoding, enhancing perception and intelligibility. PMID:23791839
Backup Warning Signals: Driver Perception and Response
DOT National Transportation Integrated Search
1996-08-01
This report describes the findings of three experiments that concern driver reaction to acoustic signals that might be used for backup warning devices. Intelligent warning devices are under development that will use vehicle-based sensors to warn back...
Adaptive Urban Signal Control and Integration (AUSCI) : evaluation final report
DOT National Transportation Integrated Search
2000-10-01
This report presents an evaluation of the Adaptive Urban Signal Control and Integration (AUSCI) Intelligent Transportation System (ITS) Field Operational Test in Minneapolis, Minnesota. The project involved a 56-intersection portion of Minneapolis, e...
NASA Technical Reports Server (NTRS)
Edelson, R. E.
1977-01-01
Some aspects of signal extraction in a microwave search for evidence of extraterrestrial intelligence are examined. Parametric relations are summarized which are applicable to a microwave search of constrained duration that employs FFT spectrum-analyzer receivers, with sensitivity enhancement by spectrum accumulation and detection by a threshold criterion. Three types of natural and man-made false alarms are identified, the probability of false alarm in a single data channel is computed, and the implications of false alarms for a constant-beamwidth sky survey are considered. It is shown that the key to an efficient search is the prompt and unambiguous elimination of false alarms. An experimental protocol is suggested which eliminates spurious signals primarily through procedural techniques involving antenna repointing, delayed repeated observations, and storage of particular historical parameters for suspect signals.
ERIC Educational Resources Information Center
Mitchell, Gordon R.
2006-01-01
The 2003 Iraq prewar intelligence failure was not simply a case of the U.S. intelligence community providing flawed data to policy-makers. It also involved subversion of the competitive intelligence analysis process, where unofficial intelligence boutiques "stovepiped" misleading intelligence assessments directly to policy-makers and…
NASA Astrophysics Data System (ADS)
The present conference on global telecommunications discusses topics in the fields of Integrated Services Digital Network (ISDN) technology field trial planning and results to date, motion video coding, ISDN networking, future network communications security, flexible and intelligent voice/data networks, Asian and Pacific lightwave and radio systems, subscriber radio systems, the performance of distributed systems, signal processing theory, satellite communications modulation and coding, and terminals for the handicapped. Also discussed are knowledge-based technologies for communications systems, future satellite transmissions, high quality image services, novel digital signal processors, broadband network access interface, traffic engineering for ISDN design and planning, telecommunications software, coherent optical communications, multimedia terminal systems, advanced speed coding, portable and mobile radio communications, multi-Gbit/second lightwave transmission systems, enhanced capability digital terminals, communications network reliability, advanced antimultipath fading techniques, undersea lightwave transmission, image coding, modulation and synchronization, adaptive signal processing, integrated optical devices, VLSI technologies for ISDN, field performance of packet switching, CSMA protocols, optical transport system architectures for broadband ISDN, mobile satellite communications, indoor wireless communication, echo cancellation in communications, and distributed network algorithms.
Multi-talker background and semantic priming effect
Dekerle, Marie; Boulenger, Véronique; Hoen, Michel; Meunier, Fanny
2014-01-01
The reported studies have aimed to investigate whether informational masking in a multi-talker background relies on semantic interference between the background and target using an adapted semantic priming paradigm. In 3 experiments, participants were required to perform a lexical decision task on a target item embedded in backgrounds composed of 1–4 voices. These voices were Semantically Consistent (SC) voices (i.e., pronouncing words sharing semantic features with the target) or Semantically Inconsistent (SI) voices (i.e., pronouncing words semantically unrelated to each other and to the target). In the first experiment, backgrounds consisted of 1 or 2 SC voices. One and 2 SI voices were added in Experiments 2 and 3, respectively. The results showed a semantic priming effect only in the conditions where the number of SC voices was greater than the number of SI voices, suggesting that semantic priming depended on prime intelligibility and strategic processes. However, even if backgrounds were composed of 3 or 4 voices, reducing intelligibility, participants were able to recognize words from these backgrounds, although no semantic priming effect on the targets was observed. Overall this finding suggests that informational masking can occur at a semantic level if intelligibility is sufficient. Based on the Effortfulness Hypothesis, we also suggest that when there is an increased difficulty in extracting target signals (caused by a relatively high number of voices in the background), more cognitive resources were allocated to formal processes (i.e., acoustic and phonological), leading to a decrease in available resources for deeper semantic processing of background words, therefore preventing semantic priming from occurring. PMID:25400572
Interference and deception detection technology of satellite navigation based on deep learning
NASA Astrophysics Data System (ADS)
Chen, Weiyi; Deng, Pingke; Qu, Yi; Zhang, Xiaoguang; Li, Yaping
2017-10-01
Satellite navigation system plays an important role in people's daily life and war. The strategic position of satellite navigation system is prominent, so it is very important to ensure that the satellite navigation system is not disturbed or destroyed. It is a critical means to detect the jamming signal to avoid the accident in a navigation system. At present, the detection technology of jamming signal in satellite navigation system is not intelligent , mainly relying on artificial decision and experience. For this issue, the paper proposes a method based on deep learning to monitor the interference source in a satellite navigation. By training the interference signal data, and extracting the features of the interference signal, the detection sys tem model is constructed. The simulation results show that, the detection accuracy of our detection system can reach nearly 70%. The method in our paper provides a new idea for the research on intelligent detection of interference and deception signal in a satellite navigation system.
On the importance of early reflections for speech in rooms.
Bradley, J S; Sato, H; Picard, M
2003-06-01
This paper presents the results of new studies based on speech intelligibility tests in simulated sound fields and analyses of impulse response measurements in rooms used for speech communication. The speech intelligibility test results confirm the importance of early reflections for achieving good conditions for speech in rooms. The addition of early reflections increased the effective signal-to-noise ratio and related speech intelligibility scores for both impaired and nonimpaired listeners. The new results also show that for common conditions where the direct sound is reduced, it is only possible to understand speech because of the presence of early reflections. Analyses of measured impulse responses in rooms intended for speech show that early reflections can increase the effective signal-to-noise ratio by up to 9 dB. A room acoustics computer model is used to demonstrate that the relative importance of early reflections can be influenced by the room acoustics design.
NASA Astrophysics Data System (ADS)
Okano, Teruo; Kikuchi, Akihiko
1996-04-01
Considerable research attention has been focused recently on materials which change their structure and properties in response to external stimuli. These materials, termed `intelligent materials', sense a stimulus as a signal (sensor function), judge the magnitude of this signal (processor function), and then alter their function in direct response (effector function). Introduction of stimuli-responsive polymers as switching sequences into both artificial materials and bioactive molecules would permit external, stimuli-induced modulation of their structures and `on-off' switching of their respective functions at molecular levels. Intelligent materials embodying these concepts would contribute to the establishment of basic principles for fabricating novel systems which modulate their structural changes and functional changes in response to external stimuli. These materials are attractive not only as new, sophisticated biomaterials but also for utilization in protein biotechnology, medical diagnosis and advanced site-specific drug delivery system.
A novel method for intelligent fault diagnosis of rolling bearings using ensemble deep auto-encoders
NASA Astrophysics Data System (ADS)
Shao, Haidong; Jiang, Hongkai; Lin, Ying; Li, Xingqiu
2018-03-01
Automatic and accurate identification of rolling bearings fault categories, especially for the fault severities and fault orientations, is still a major challenge in rotating machinery fault diagnosis. In this paper, a novel method called ensemble deep auto-encoders (EDAEs) is proposed for intelligent fault diagnosis of rolling bearings. Firstly, different activation functions are employed as the hidden functions to design a series of auto-encoders (AEs) with different characteristics. Secondly, EDAEs are constructed with various auto-encoders for unsupervised feature learning from the measured vibration signals. Finally, a combination strategy is designed to ensure accurate and stable diagnosis results. The proposed method is applied to analyze the experimental bearing vibration signals. The results confirm that the proposed method can get rid of the dependence on manual feature extraction and overcome the limitations of individual deep learning models, which is more effective than the existing intelligent diagnosis methods.
Soft optics in intelligent optical networks
NASA Astrophysics Data System (ADS)
Shue, Chikong; Cao, Yang
2001-10-01
In addition to the recent advances in Hard-optics that pushes the optical transmission speed, distance, wave density and optical switching capacity, Soft-optics provides the necessary intelligence and control software that reduces operational costs, increase efficiency, and enhances revenue generating services by automating optimal optical circuit placement and restoration, and enabling value-added new services like Optical VPN. This paper describes the advances in 1) Overall Hard-optics and Soft-optics 2) Layered hierarchy of Soft-optics 3) Component of Soft-optics, including hard-optics drivers, Management Soft-optics, Routing Soft-optics and System Soft-optics 4) Key component of Routing and System Soft-optics, namely optical routing and signaling (including UNI/NNI and GMPLS signaling). In summary, the soft-optics on a new generation of OXC's enables Intelligent Optical Networks to provide just-in-time service delivery and fast restoration, and real-time capacity management that eliminates stranded bandwidth. It reduces operational costs and provides new revenue opportunities.
A synthetic genetic edge detection program.
Tabor, Jeffrey J; Salis, Howard M; Simpson, Zachary Booth; Chevalier, Aaron A; Levskaya, Anselm; Marcotte, Edward M; Voigt, Christopher A; Ellington, Andrew D
2009-06-26
Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E. coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.
A Synthetic Genetic Edge Detection Program
Tabor, Jeffrey J.; Salis, Howard; Simpson, Zachary B.; Chevalier, Aaron A.; Levskaya, Anselm; Marcotte, Edward M.; Voigt, Christopher A.; Ellington, Andrew D.
2009-01-01
Summary Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E.coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks. PMID:19563759
Five Years of SETI with the Allen Telescope Array: Lessons Learned
NASA Astrophysics Data System (ADS)
Harp, Gerald
2016-01-01
We discuss recent observations at the Allen Telescope Array (ATA) supporting a wide ranging Search for Extraterrestrial Intelligence (SETI). The ATA supports observations over the frequency range 1-10 GHz with three simultaneous phased array beams used in an anticoincidence detector for false positive rejection. Here we summarize observational results over the years 2011-2015 covering multiple campaigns of exoplanet stars, the galactic plane, infrared excess targets, etc. Approximately 2 x 108 signals were identified and classified over more than 5000 hours of observation. From these results we consider various approaches to the rapid identification of human generated interference in the process of the search for a signal with origins outside the radius of the Moon's orbit. We conclude that the multi-beam technique is superb tool for answering the very difficult question of the direction of origin of signals. Data-based simulations of future instruments with more than 3 beams are compared.
Hu, Yi
2010-05-01
Recent research results show that combined electric and acoustic stimulation (EAS) significantly improves speech recognition in noise, and it is generally established that access to the improved F0 representation of target speech, along with the glimpse cues, provide the EAS benefits. Under noisy listening conditions, noise signals degrade these important cues by introducing undesired temporal-frequency components and corrupting harmonics structure. In this study, the potential of combining noise reduction and harmonics regeneration techniques was investigated to further improve speech intelligibility in noise by providing improved beneficial cues for EAS. Three hypotheses were tested: (1) noise reduction methods can improve speech intelligibility in noise for EAS; (2) harmonics regeneration after noise reduction can further improve speech intelligibility in noise for EAS; and (3) harmonics sideband constraints in frequency domain (or equivalently, amplitude modulation in temporal domain), even deterministic ones, can provide additional benefits. Test results demonstrate that combining noise reduction and harmonics regeneration can significantly improve speech recognition in noise for EAS, and it is also beneficial to preserve the harmonics sidebands under adverse listening conditions. This finding warrants further work into the development of algorithms that regenerate harmonics and the related sidebands for EAS processing under noisy conditions.
Simulation research on the process of large scale ship plane segmentation intelligent workshop
NASA Astrophysics Data System (ADS)
Xu, Peng; Liao, Liangchuang; Zhou, Chao; Xue, Rui; Fu, Wei
2017-04-01
Large scale ship plane segmentation intelligent workshop is a new thing, and there is no research work in related fields at home and abroad. The mode of production should be transformed by the existing industry 2.0 or part of industry 3.0, also transformed from "human brain analysis and judgment + machine manufacturing" to "machine analysis and judgment + machine manufacturing". In this transforming process, there are a great deal of tasks need to be determined on the aspects of management and technology, such as workshop structure evolution, development of intelligent equipment and changes in business model. Along with them is the reformation of the whole workshop. Process simulation in this project would verify general layout and process flow of large scale ship plane section intelligent workshop, also would analyze intelligent workshop working efficiency, which is significant to the next step of the transformation of plane segmentation intelligent workshop.
The "Wow! signal" of the terrestrial genetic code
NASA Astrophysics Data System (ADS)
shCherbak, Vladimir I.; Makukov, Maxim A.
2013-05-01
It has been repeatedly proposed to expand the scope for SETI, and one of the suggested alternatives to radio is the biological media. Genomic DNA is already used on Earth to store non-biological information. Though smaller in capacity, but stronger in noise immunity is the genetic code. The code is a flexible mapping between codons and amino acids, and this flexibility allows modifying the code artificially. But once fixed, the code might stay unchanged over cosmological timescales; in fact, it is the most durable construct known. Therefore it represents an exceptionally reliable storage for an intelligent signature, if that conforms to biological and thermodynamic requirements. As the actual scenario for the origin of terrestrial life is far from being settled, the proposal that it might have been seeded intentionally cannot be ruled out. A statistically strong intelligent-like "signal" in the genetic code is then a testable consequence of such scenario. Here we show that the terrestrial code displays a thorough precision-type orderliness matching the criteria to be considered an informational signal. Simple arrangements of the code reveal an ensemble of arithmetical and ideographical patterns of the same symbolic language. Accurate and systematic, these underlying patterns appear as a product of precision logic and nontrivial computing rather than of stochastic processes (the null hypothesis that they are due to chance coupled with presumable evolutionary pathways is rejected with P-value < 10-13). The patterns are profound to the extent that the code mapping itself is uniquely deduced from their algebraic representation. The signal displays readily recognizable hallmarks of artificiality, among which are the symbol of zero, the privileged decimal syntax and semantical symmetries. Besides, extraction of the signal involves logically straightforward but abstract operations, making the patterns essentially irreducible to any natural origin. Plausible ways of embedding the signal into the code and possible interpretation of its content are discussed. Overall, while the code is nearly optimized biologically, its limited capacity is used extremely efficiently to pass non-biological information.
Cyber Vigilance: The Human Factor
2016-10-21
88ABW-2014-5661; American Intelligence Journal 14. Cyber-defenders face lengthy, repetitive work assignments with few critical signals and little...research is inadvisable. To understand this unique domain, we asked participants to perform a simulated cybersecurity task, searching for attack...detection. To avoid this, IDS detection algorithms are purposely liberal, broadly flagging any activity that resembles a known American Intelligence
Intelligent Control of Flexible-Joint Robotic Manipulators
NASA Technical Reports Server (NTRS)
Colbaugh, R.; Gallegos, G.
1997-01-01
This paper considers the trajectory tracking problem for uncertain rigid-link. flexible.joint manipulators, and presents a new intelligent controller as a solution to this problem. The proposed control strategy is simple and computationally efficient, requires little information concerning either the manipulator or actuator/transmission models and ensures uniform boundedness of all signals and arbitrarily accurate task-space trajectory tracking.
An Evaluation of Articulatory Working Space Area in Vowel Production of Adults with Down Syndrome
ERIC Educational Resources Information Center
Bunton, Kate; Leddy, Mark
2011-01-01
Many adolescents and adults with Down syndrome have reduced speech intelligibility. Reasons for this reduction may relate to differences in anatomy and physiology, both of which are important for creating an intelligible speech signal. The purpose of this study was to document acoustic vowel space and articulatory working space for two adult…
Intelligent open-architecture controller using knowledge server
NASA Astrophysics Data System (ADS)
Nacsa, Janos; Kovacs, George L.; Haidegger, Geza
2001-12-01
In an ideal scenario of intelligent machine tools [22] the human mechanist was almost replaced by the controller. During the last decade many efforts have been made to get closer to this ideal scenario, but the way of information processing within the CNC did not change too much. The paper summarizes the requirements of an intelligent CNC evaluating the different research efforts done in this field using different artificial intelligence (AI) methods. The need for open CNC architecture was emerging at many places around the world. The second part of the paper introduces and shortly compares these efforts. In the third part a low cost concept for intelligent and open systems named Knowledge Server for Controllers (KSC) is introduced. It allows more devices to solve their intelligent processing needs using the same server that is capable to process intelligent data. In the final part the KSC concept is used in an open CNC environment to build up some elements of an intelligent CNC. The preliminary results of the implementation are also introduced.
State of the art in the detection of intelligent extraterrestrial signals.
NASA Technical Reports Server (NTRS)
Oliver, B. M.
1972-01-01
Recent progress in ideas of how signals that might represent electromagnetic radiations of intelligent civilizations elsewhere in the galaxy is summarized. Project Cyclops, carried out at Ames Research Center under the auspices of NASA and the American Society for Engineering Education, determined that microwaves are superior to lasers for interstellar signalling. It is felt that the band lying between the resonances of the two dissociation products of water, the hydrogen line at 1420 MHz, and the first hydroxyl line at 1662 MHz, is the most suitable. Phased antenna arrays of perhaps 1000 to 10,000 dishes of 100 m diam would be required. It is considered that a list of likely stars should be compiled, and these should be searched one at a time. Procedures for combing the spectrum are outlined.
Relationship Between Speech Intelligibility and Speech Comprehension in Babble Noise.
Fontan, Lionel; Tardieu, Julien; Gaillard, Pascal; Woisard, Virginie; Ruiz, Robert
2015-06-01
The authors investigated the relationship between the intelligibility and comprehension of speech presented in babble noise. Forty participants listened to French imperative sentences (commands for moving objects) in a multitalker babble background for which intensity was experimentally controlled. Participants were instructed to transcribe what they heard and obey the commands in an interactive environment set up for this purpose. The former test provided intelligibility scores and the latter provided comprehension scores. Collected data revealed a globally weak correlation between intelligibility and comprehension scores (r = .35, p < .001). The discrepancy tended to grow as noise level increased. An analysis of standard deviations showed that variability in comprehension scores increased linearly with noise level, whereas higher variability in intelligibility scores was found for moderate noise level conditions. These results support the hypothesis that intelligibility scores are poor predictors of listeners' comprehension in real communication situations. Intelligibility and comprehension scores appear to provide different insights, the first measure being centered on speech signal transfer and the second on communicative performance. Both theoretical and practical implications for the use of speech intelligibility tests as indicators of speakers' performances are discussed.
An Anticipatory Model of Cavitation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Allgood, G.O.; Dress, W.B., Jr.; Hylton, J.O.
1999-04-05
The Anticipatory System (AS) formalism developed by Robert Rosen provides some insight into the problem of embedding intelligent behavior in machines. AS emulates the anticipatory behavior of biological systems. AS bases its behavior on its expectations about the near future and those expectations are modified as the system gains experience. The expectation is based on an internal model that is drawn from an appeal to physical reality. To be adaptive, the model must be able to update itself. To be practical, the model must run faster than real-time. The need for a physical model and the requirement that the modelmore » execute at extreme speeds, has held back the application of AS to practical problems. Two recent advances make it possible to consider the use of AS for practical intelligent sensors. First, advances in transducer technology make it possible to obtain previously unavailable data from which a model can be derived. For example, acoustic emissions (AE) can be fed into a Bayesian system identifier that enables the separation of a weak characterizing signal, such as the signature of pump cavitation precursors, from a strong masking signal, such as a pump vibration feature. The second advance is the development of extremely fast, but inexpensive, digital signal processing hardware on which it is possible to run an adaptive Bayesian-derived model faster than real-time. This paper reports the investigation of an AS using a model of cavitation based on hydrodynamic principles and Bayesian analysis of data from high-performance AE sensors.« less
Automatic Speech Recognition from Neural Signals: A Focused Review.
Herff, Christian; Schultz, Tanja
2016-01-01
Speech interfaces have become widely accepted and are nowadays integrated in various real-life applications and devices. They have become a part of our daily life. However, speech interfaces presume the ability to produce intelligible speech, which might be impossible due to either loud environments, bothering bystanders or incapabilities to produce speech (i.e., patients suffering from locked-in syndrome). For these reasons it would be highly desirable to not speak but to simply envision oneself to say words or sentences. Interfaces based on imagined speech would enable fast and natural communication without the need for audible speech and would give a voice to otherwise mute people. This focused review analyzes the potential of different brain imaging techniques to recognize speech from neural signals by applying Automatic Speech Recognition technology. We argue that modalities based on metabolic processes, such as functional Near Infrared Spectroscopy and functional Magnetic Resonance Imaging, are less suited for Automatic Speech Recognition from neural signals due to low temporal resolution but are very useful for the investigation of the underlying neural mechanisms involved in speech processes. In contrast, electrophysiologic activity is fast enough to capture speech processes and is therefor better suited for ASR. Our experimental results indicate the potential of these signals for speech recognition from neural data with a focus on invasively measured brain activity (electrocorticography). As a first example of Automatic Speech Recognition techniques used from neural signals, we discuss the Brain-to-text system.
Rhythm Perception and Its Role in Perception and Learning of Dysrhythmic Speech.
Borrie, Stephanie A; Lansford, Kaitlin L; Barrett, Tyson S
2017-03-01
The perception of rhythm cues plays an important role in recognizing spoken language, especially in adverse listening conditions. Indeed, this has been shown to hold true even when the rhythm cues themselves are dysrhythmic. This study investigates whether expertise in rhythm perception provides a processing advantage for perception (initial intelligibility) and learning (intelligibility improvement) of naturally dysrhythmic speech, dysarthria. Fifty young adults with typical hearing participated in 3 key tests, including a rhythm perception test, a receptive vocabulary test, and a speech perception and learning test, with standard pretest, familiarization, and posttest phases. Initial intelligibility scores were calculated as the proportion of correct pretest words, while intelligibility improvement scores were calculated by subtracting this proportion from the proportion of correct posttest words. Rhythm perception scores predicted intelligibility improvement scores but not initial intelligibility. On the other hand, receptive vocabulary scores predicted initial intelligibility scores but not intelligibility improvement. Expertise in rhythm perception appears to provide an advantage for processing dysrhythmic speech, but a familiarization experience is required for the advantage to be realized. Findings are discussed in relation to the role of rhythm in speech processing and shed light on processing models that consider the consequence of rhythm abnormalities in dysarthria.
Large Efficient Intelligent Heating Relay Station System
NASA Astrophysics Data System (ADS)
Wu, C. Z.; Wei, X. G.; Wu, M. Q.
2017-12-01
The design of large efficient intelligent heating relay station system aims at the improvement of the existing heating system in our country, such as low heating efficiency, waste of energy and serious pollution, and the control still depends on the artificial problem. In this design, we first improve the existing plate heat exchanger. Secondly, the ATM89C51 is used to control the whole system and realize the intelligent control. The detection part is using the PT100 temperature sensor, pressure sensor, turbine flowmeter, heating temperature, detection of user end liquid flow, hydraulic, and real-time feedback, feedback signal to the microcontroller through the heating for users to adjust, realize the whole system more efficient, intelligent and energy-saving.
Intelligent acoustic data fusion technique for information security analysis
NASA Astrophysics Data System (ADS)
Jiang, Ying; Tang, Yize; Lu, Wenda; Wang, Zhongfeng; Wang, Zepeng; Zhang, Luming
2017-08-01
Tone is an essential component of word formation in all tonal languages, and it plays an important role in the transmission of information in speech communication. Therefore, tones characteristics study can be applied into security analysis of acoustic signal by the means of language identification, etc. In speech processing, fundamental frequency (F0) is often viewed as representing tones by researchers of speech synthesis. However, regular F0 values may lead to low naturalness in synthesized speech. Moreover, F0 and tone are not equivalent linguistically; F0 is just a representation of a tone. Therefore, the Electroglottography (EGG) signal is collected for deeper tones characteristics study. In this paper, focusing on the Northern Kam language, which has nine tonal contours and five level tone types, we first collected EGG and speech signals from six natural male speakers of the Northern Kam language, and then achieved the clustering distributions of the tone curves. After summarizing the main characteristics of tones of Northern Kam, we analyzed the relationship between EGG and speech signal parameters, and laid the foundation for further security analysis of acoustic signal.
DYNACLIPS (DYNAmic CLIPS): A dynamic knowledge exchange tool for intelligent agents
NASA Technical Reports Server (NTRS)
Cengeloglu, Yilmaz; Khajenoori, Soheil; Linton, Darrell
1994-01-01
In a dynamic environment, intelligent agents must be responsive to unanticipated conditions. When such conditions occur, an intelligent agent may have to stop a previously planned and scheduled course of actions and replan, reschedule, start new activities and initiate a new problem solving process to successfully respond to the new conditions. Problems occur when an intelligent agent does not have enough knowledge to properly respond to the new situation. DYNACLIPS is an implementation of a framework for dynamic knowledge exchange among intelligent agents. Each intelligent agent is a CLIPS shell and runs a separate process under SunOS operating system. Intelligent agents can exchange facts, rules, and CLIPS commands at run time. Knowledge exchange among intelligent agents at run times does not effect execution of either sender and receiver intelligent agent. Intelligent agents can keep the knowledge temporarily or permanently. In other words, knowledge exchange among intelligent agents would allow for a form of learning to be accomplished.
Developing traffic signal control systems using the national ITS architecture
DOT National Transportation Integrated Search
1998-02-01
This is one of a series of documents providing support for deploying Intelligent Transportation Systems (ITS). This document focuses on traffic signal control, a component of ITS. It aims to provide practical help for the traffic engineering communit...
Developing Traffic Signal Control Systems using the National ITS Architecture
DOT National Transportation Integrated Search
1998-02-01
This is one of a series of documents providing support for deploying Intelligent Transportation Systems (ITS). This document focuses on traffic signal control, a component of ITS. It aims to provide practical help for the traffic engineering communit...
2007-02-28
Program •Services executed Defense HUMINT Activities •DIA ran attaché system •Over time , deferred the Secretary’s Authorities •Post-1995 (Perry and White...ornl.gov orbucma@doe.ic.gov 26 February, 2007 TT L SENSO RS COMMS time trust Intelligence …the power of change… hameleon ORNL Cognitive Radio Program...and internal states in real- time to meet user requirements and goals • Learns: uses statistical signal processing and machine learning to reflect
NASA Technical Reports Server (NTRS)
Wolf, Jared J.
1977-01-01
The following research was discussed: (1) speech signal processing; (2) automatic speech recognition; (3) continuous speech understanding; (4) speaker recognition; (5) speech compression; (6) subjective and objective evaluation of speech communication system; (7) measurement of the intelligibility and quality of speech when degraded by noise or other masking stimuli; (8) speech synthesis; (9) instructional aids for second-language learning and for training of the deaf; and (10) investigation of speech correlates of psychological stress. Experimental psychology, control systems, and human factors engineering, which are often relevant to the proper design and operation of speech systems are described.
NASA Technical Reports Server (NTRS)
Billingham, J.; Brocker, D. H.
1991-01-01
In 1959, it was proposed that a sensible way to conduct interstellar communication would be to use radio at or near the frequency of hydrogen. In 1960, the first Search for Extraterrestrial Intelligence (SETI) was conducted using a radiotelescope at Green Bank in West Virginia. Since 1970, NASA has systematically developed a definitive program to conduct a sophisticated search for evidence of extraterrestrial intelligent life. The basic hypothesis is that life may be widespread in the univers, and that in many instances extraterrestrial life may have evolved into technological civilizations. The underlying scientific arguments are based on the continuously improving knowledge of astronomy and astrophysics, especially star system formation, and of planetary science, chemical evolution, and biological evolution. If only one in a million sun-like stars in our galaxy harbors species with cognitive intelligence, then there are 100,000 civilizations in the Milky Way alone. The fields of radioastronomy digital electronic engineering, spectrum analysis, and signal detection have advanced rapidly in the last twenty years and now allow for sophisticated systems to be built in order to attempt the detection of extraterrestrial intelligence signals. In concert with the scientific and engineering communities, NASA has developed, over the last several years, a Microwave Observing Project whose goal is to design, build, and operate SETI systems during the decade of the nineties in pursuit of the goal signal detection. The Microwave Observing Project is now approved and underway. There are two major components in the project: the Target Search Element and the Sky Survey Element.
Two speed factors of visual recognition independently correlated with fluid intelligence.
Tachibana, Ryosuke; Namba, Yuri; Noguchi, Yasuki
2014-01-01
Growing evidence indicates a moderate but significant relationship between processing speed in visuo-cognitive tasks and general intelligence. On the other hand, findings from neuroscience proposed that the primate visual system consists of two major pathways, the ventral pathway for objects recognition and the dorsal pathway for spatial processing and attentive analysis. Previous studies seeking for visuo-cognitive factors of human intelligence indicated a significant correlation between fluid intelligence and the inspection time (IT), an index for a speed of object recognition performed in the ventral pathway. We thus presently examined a possibility that neural processing speed in the dorsal pathway also represented a factor of intelligence. Specifically, we used the mental rotation (MR) task, a popular psychometric measure for mental speed of spatial processing in the dorsal pathway. We found that the speed of MR was significantly correlated with intelligence scores, while it had no correlation with one's IT (recognition speed of visual objects). Our results support the new possibility that intelligence could be explained by two types of mental speed, one related to object recognition (IT) and another for manipulation of mental images (MR).
Maritime Domain Awareness: C4I for the 1000 Ship Navy
2009-12-04
unit action, provide unit sensed contacts, coordinate unit operations, process unit information, release image , and release contact report, Figure 33...Intelligence Tasking Request Intelligence Summary Release Unit Person Incident Release Unit Vessel Incident Process Intelligence Tasking Release Image ...xi LIST OF FIGURES Figure 1. Functional Problem Sequence Process Flow. ....................................................4 Figure 2. United
Speech-Message Extraction from Interference Introduced by External Distributed Sources
NASA Astrophysics Data System (ADS)
Kanakov, V. A.; Mironov, N. A.
2017-08-01
The problem of this study involves the extraction of a speech signal originating from a certain spatial point and calculation of the intelligibility of the extracted voice message. It is solved by the method of decreasing the influence of interference from the speech-message sources on the extracted signal. This method is based on introducing the time delays, which depend on the spatial coordinates, to the recording channels. Audio records of the voices of eight different people were used as test objects during the studies. It is proved that an increase in the number of microphones improves intelligibility of the speech message which is extracted from interference.
NASA Astrophysics Data System (ADS)
Lukić, M.; Ćojbašić, Ž.; Rabasović, M. D.; Markushev, D. D.; Todorović, D. M.
2017-11-01
In this paper, the possibilities of computational intelligence applications for trace gas monitoring are discussed. For this, pulsed infrared photoacoustics is used to investigate SF6-Ar mixtures in a multiphoton regime, assisted by artificial neural networks. Feedforward multilayer perceptron networks are applied in order to recognize both the spatial characteristics of the laser beam and the values of laser fluence Φ from the given photoacoustic signal and prevent changes. Neural networks are trained in an offline batch training regime to simultaneously estimate four parameters from theoretical or experimental photoacoustic signals: the laser beam spatial profile R(r), vibrational-to-translational relaxation time τ _{V-T} , distance from the laser beam to the absorption molecules in the photoacoustic cell r* and laser fluence Φ . The results presented in this paper show that neural networks can estimate an unknown laser beam spatial profile and the parameters of photoacoustic signals in real time and with high precision. Real-time operation, high accuracy and the possibility of application for higher intensities of radiation for a wide range of laser fluencies are factors that classify the computational intelligence approach as efficient and powerful for the in situ measurement of atmospheric pollutants.
Tran, Phuong K; Letowski, Tomasz R; McBride, Maranda E
2013-06-01
Speech signals can be converted into electrical audio signals using either conventional air conduction (AC) microphone or a contact bone conduction (BC) microphone. The goal of this study was to investigate the effects of the location of a BC microphone on the intensity and frequency spectrum of the recorded speech. Twelve locations, 11 on the talker's head and 1 on the collar bone, were investigated. The speech sounds were three vowels (/u/, /a/, /i/) and two consonants (/m/, /∫/). The sounds were produced by 12 talkers. Each sound was recorded simultaneously with two BC microphones and an AC microphone. Analyzed spectral data showed that the BC recordings made at the forehead of the talker were the most similar to the AC recordings, whereas the collar bone recordings were most different. Comparison of the spectral data with speech intelligibility data collected in another study revealed a strong negative relationship between BC speech intelligibility and the degree of deviation of the BC speech spectrum from the AC spectrum. In addition, the head locations that resulted in the highest speech intelligibility were associated with the lowest output signals among all tested locations. Implications of these findings for BC communication are discussed.
Speed of Information Processing and Individual Differences in Intelligence.
1986-06-01
years of age. As criteria, the students were given the Vocabulary and Block Design subtests of the Wechsler Adult Intelligence Scale --Revised (WAIS-R... Wechsler Adult Intelligence Scale (WAIS) and inspection time (Nettelbeck & Lally, 1976), most subsequent investigations found a less spectacular, but...Design sdbtests of the Wechsler Adult Intelligence Scale , Revised (WAIS-R) and the Cognitive Laterality Battery (Gordon, 1983). Visual Processing Tasks
Envelope and intensity based prediction of psychoacoustic masking and speech intelligibility.
Biberger, Thomas; Ewert, Stephan D
2016-08-01
Human auditory perception and speech intelligibility have been successfully described based on the two concepts of spectral masking and amplitude modulation (AM) masking. The power-spectrum model (PSM) [Patterson and Moore (1986). Frequency Selectivity in Hearing, pp. 123-177] accounts for effects of spectral masking and critical bandwidth, while the envelope power-spectrum model (EPSM) [Ewert and Dau (2000). J. Acoust. Soc. Am. 108, 1181-1196] has been successfully applied to AM masking and discrimination. Both models extract the long-term (envelope) power to calculate signal-to-noise ratios (SNR). Recently, the EPSM has been applied to speech intelligibility (SI) considering the short-term envelope SNR on various time scales (multi-resolution speech-based envelope power-spectrum model; mr-sEPSM) to account for SI in fluctuating noise [Jørgensen, Ewert, and Dau (2013). J. Acoust. Soc. Am. 134, 436-446]. Here, a generalized auditory model is suggested combining the classical PSM and the mr-sEPSM to jointly account for psychoacoustics and speech intelligibility. The model was extended to consider the local AM depth in conditions with slowly varying signal levels, and the relative role of long-term and short-term SNR was assessed. The suggested generalized power-spectrum model is shown to account for a large variety of psychoacoustic data and to predict speech intelligibility in various types of background noise.
Bentsen, Thomas; May, Tobias; Kressner, Abigail A; Dau, Torsten
2018-01-01
Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements. A selection of components may be responsible for the success with these state-of-the-art approaches: the system architecture, a time frame concatenation technique and the learning objective. The aim of this study was to explore the roles and the relative contributions of these components by measuring speech intelligibility in normal-hearing listeners. A substantial improvement of 25.4 percentage points in speech intelligibility scores was found going from a subband-based architecture, in which a Gaussian Mixture Model-based classifier predicts the distributions of speech and noise for each frequency channel, to a state-of-the-art deep neural network-based architecture. Another improvement of 13.9 percentage points was obtained by changing the learning objective from the ideal binary mask, in which individual time-frequency units are labeled as either speech- or noise-dominated, to the ideal ratio mask, where the units are assigned a continuous value between zero and one. Therefore, both components play significant roles and by combining them, speech intelligibility improvements were obtained in a six-talker condition at a low signal-to-noise ratio.
Intelligence, Cognition, and Language of Green Plants.
Trewavas, Anthony
2016-01-01
A summary definition of some 70 descriptions of intelligence provides a definition for all other organisms including plants that stresses fitness. Barbara McClintock, a plant biologist, posed the notion of the 'thoughtful cell' in her Nobel prize address. The systems structure necessary for a thoughtful cell is revealed by comparison of the interactome and connectome. The plant root cap, a group of some 200 cells that act holistically in responding to numerous signals, likely possesses a similar systems structure agreeing with Darwin's description of acting like the brain of a lower organism. Intelligent behavior requires assessment of different choices and taking the beneficial one. Decisions are constantly required to optimize the plant phenotype to a dynamic environment and the cambium is the assessing tissue diverting more or removing resources from different shoot and root branches through manipulation of vascular elements. Environmental awareness likely indicates consciousness. Spontaneity in plant behavior, ability to count to five and error correction indicate intention. Volatile organic compounds are used as signals in plant interactions and being complex in composition may be the equivalent of language accounting for self and alien recognition by individual plants. Game theory describes competitive interactions. Interactive and intelligent outcomes emerge from application of various games between plants themselves and interactions with microbes. Behavior profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses.
Thirty years of artificial intelligence in medicine (AIME) conferences: A review of research themes.
Peek, Niels; Combi, Carlo; Marin, Roque; Bellazzi, Riccardo
2015-09-01
Over the past 30 years, the international conference on Artificial Intelligence in MEdicine (AIME) has been organized at different venues across Europe every 2 years, establishing a forum for scientific exchange and creating an active research community. The Artificial Intelligence in Medicine journal has published theme issues with extended versions of selected AIME papers since 1998. To review the history of AIME conferences, investigate its impact on the wider research field, and identify challenges for its future. We analyzed a total of 122 session titles to create a taxonomy of research themes and topics. We classified all 734 AIME conference papers published between 1985 and 2013 with this taxonomy. We also analyzed the citations to these conference papers and to 55 special issue papers. We identified 30 research topics across 12 themes. AIME was dominated by knowledge engineering research in its first decade, while machine learning and data mining prevailed thereafter. Together these two themes have contributed about 51% of all papers. There have been eight AIME papers that were cited at least 10 times per year since their publication. There has been a major shift from knowledge-based to data-driven methods while the interest for other research themes such as uncertainty management, image and signal processing, and natural language processing has been stable since the early 1990s. AIME papers relating to guidelines and protocols are among the most highly cited. Copyright © 2015 Elsevier B.V. All rights reserved.
Code of Federal Regulations, 2010 CFR
2010-07-01
... Defense Other Regulations Relating to National Defense CENTRAL INTELLIGENCE AGENCY PROCEDURES GOVERNING ACCEPTANCE OF SERVICE OF PROCESS § 1904.2 Definitions. (a) Agency or CIA means the Central Intelligence Agency and include all staff elements of the Director of Central Intelligence. (b) Process means a...
Code of Federal Regulations, 2014 CFR
2014-07-01
... Defense Other Regulations Relating to National Defense CENTRAL INTELLIGENCE AGENCY PROCEDURES GOVERNING ACCEPTANCE OF SERVICE OF PROCESS § 1904.2 Definitions. (a) Agency or CIA means the Central Intelligence Agency and include all staff elements of the Director of Central Intelligence. (b) Process means a...
Code of Federal Regulations, 2013 CFR
2013-07-01
... Defense Other Regulations Relating to National Defense CENTRAL INTELLIGENCE AGENCY PROCEDURES GOVERNING ACCEPTANCE OF SERVICE OF PROCESS § 1904.2 Definitions. (a) Agency or CIA means the Central Intelligence Agency and include all staff elements of the Director of Central Intelligence. (b) Process means a...
Code of Federal Regulations, 2012 CFR
2012-07-01
... Defense Other Regulations Relating to National Defense CENTRAL INTELLIGENCE AGENCY PROCEDURES GOVERNING ACCEPTANCE OF SERVICE OF PROCESS § 1904.2 Definitions. (a) Agency or CIA means the Central Intelligence Agency and include all staff elements of the Director of Central Intelligence. (b) Process means a...
Code of Federal Regulations, 2011 CFR
2011-07-01
... Defense Other Regulations Relating to National Defense CENTRAL INTELLIGENCE AGENCY PROCEDURES GOVERNING ACCEPTANCE OF SERVICE OF PROCESS § 1904.2 Definitions. (a) Agency or CIA means the Central Intelligence Agency and include all staff elements of the Director of Central Intelligence. (b) Process means a...
A watershed model of individual differences in fluid intelligence.
Kievit, Rogier A; Davis, Simon W; Griffiths, John; Correia, Marta M; Cam-Can; Henson, Richard N
2016-10-01
Fluid intelligence is a crucial cognitive ability that predicts key life outcomes across the lifespan. Strong empirical links exist between fluid intelligence and processing speed on the one hand, and white matter integrity and processing speed on the other. We propose a watershed model that integrates these three explanatory levels in a principled manner in a single statistical model, with processing speed and white matter figuring as intermediate endophenotypes. We fit this model in a large (N=555) adult lifespan cohort from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) using multiple measures of processing speed, white matter health and fluid intelligence. The model fit the data well, outperforming competing models and providing evidence for a many-to-one mapping between white matter integrity, processing speed and fluid intelligence. The model can be naturally extended to integrate other cognitive domains, endophenotypes and genotypes. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Real Time Conference 2014 Overview
NASA Astrophysics Data System (ADS)
Nomachi, Masaharu
2015-06-01
This article presents an overview of the 19th Real Time Conference held last May 26-30, 2014, at the Nara Prefectural New Public Hall, Nara, Japan, organized by the Research Center for Nuclear Physics of the Osaka University. The program included many invited talks and oral sessions offering an extensive overview on the following topics: real-time system architectures, intelligent signal processing, fast data transfer links and networks, trigger systems, data acquisition, processing-farms, control, monitoring and test systems, emerging real-time technologies, new standards, real-time safety and security, and some feedback on experiences. In parallel to the oral and poster presentations, industrial exhibits by companies, workshops and short courses also ran through the week.
Open-Source Intelligence in the Czech Military: Knowledge System and Process Design
2002-06-01
in Open-Source Intelligence OSINT, as one of the intelligence disciplines, bears some of the general problems of intelligence " business " OSINT...ADAPTING KNOWLEDGE MANAGEMENT THEORY TO THE CZECH MILITARY INTELLIGENCE Knowledge work is the core business of the military intelligence . As...NAVAL POSTGRADUATE SCHOOL Monterey, California THESIS Approved for public release; distribution is unlimited OPEN-SOURCE INTELLIGENCE IN THE
Hommel, Bernhard; Colzato, Lorenza S; Scorolli, Claudia; Borghi, Anna M; van den Wildenberg, Wery P M
2011-08-01
Previous findings suggest that religion has a specific impact on attentional processes. Here we show that religion also affects action control. Experiment 1 compared Dutch Calvinists and Dutch atheists, matched for age, sex, intelligence, education, and cultural and socio-economic background, and Experiment 2 compared Italian Catholics with matched Italian seculars. As expected, Calvinists showed a smaller and Catholics a larger Simon effect than nonbelievers, while performance of the groups was comparable in the Stop-Signal task. This pattern suggests that religions emphasizing individualism or collectivism affects action control in specific ways, presumably by inducing chronic biases towards a more "exclusive" or "inclusive" style of decision-making. Interestingly, there was no evidence that religious practice affects inhibitory skills. Copyright © 2011 Elsevier B.V. All rights reserved.
The use of Matlab for colour fuzzy representation of multichannel EEG short time spectra.
Bigan, C; Strungaru, R
1998-01-01
During the last years, a lot of EEG research efforts was directed to intelligent methods for automatic analysis of data from multichannel EEG recordings. However, all the applications reported were focused on specific single tasks like detection of one specific "event" in the EEG signal: spikes, sleep spindles, epileptic seizures, K complexes, alpha or other rhythms or even artefacts. The aim of this paper is to present a complex system being able to perform a representation of the dynamic changes in frequency components of each EEG channel. This representation uses colours as a powerful means to show the only one frequency range chosen from the shortest epoch of signal able to be processed with the conventional "Short Time Fast Fourier Transform" (S.T.F.F.T.) method.
Hybrid soft computing systems for electromyographic signals analysis: a review.
Xie, Hong-Bo; Guo, Tianruo; Bai, Siwei; Dokos, Socrates
2014-02-03
Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis.
Hybrid soft computing systems for electromyographic signals analysis: a review
2014-01-01
Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis. PMID:24490979
Closing Intelligence Gaps: Synchronizing the Collection Management Process
information flow. The US military divides the world into six distinct geographic areas with corresponding commanders managing risk and weighing...analyzed information , creating a mismatch between supply and demand. The result is a burden on all facets of the intelligence process. However, if the target...system, or problem requiring analysis is not collected, intelligence fails. Executing collection management under the traditional tasking process
NASA Astrophysics Data System (ADS)
Phipps, Marja; Lewis, Gina
2012-06-01
Over the last decade, intelligence capabilities within the Department of Defense/Intelligence Community (DoD/IC) have evolved from ad hoc, single source, just-in-time, analog processing; to multi source, digitally integrated, real-time analytics; to multi-INT, predictive Processing, Exploitation and Dissemination (PED). Full Motion Video (FMV) technology and motion imagery tradecraft advancements have greatly contributed to Intelligence, Surveillance and Reconnaissance (ISR) capabilities during this timeframe. Imagery analysts have exploited events, missions and high value targets, generating and disseminating critical intelligence reports within seconds of occurrence across operationally significant PED cells. Now, we go beyond FMV, enabling All-Source Analysts to effectively deliver ISR information in a multi-INT sensor rich environment. In this paper, we explore the operational benefits and technical challenges of an Activity Based Intelligence (ABI) approach to FMV PED. Existing and emerging ABI features within FMV PED frameworks are discussed, to include refined motion imagery tools, additional intelligence sources, activity relevant content management techniques and automated analytics.
Photonic band gap materials: towards an all-optical transistor
NASA Astrophysics Data System (ADS)
Florescu, Marian
2002-05-01
The transmission of information as optical signals encoded on light waves traveling through optical fibers and optical networks is increasingly moving to shorter and shorter distance scales. In the near future, optical networking is poised to supersede conventional transmission over electric wires and electronic networks for computer-to-computer communications, chip-to-chip communications, and even on-chip communications. The ever-increasing demand for faster and more reliable devices to process the optical signals offers new opportunities in developing all-optical signal processing systems (systems in which one optical signal controls another, thereby adding "intelligence" to the optical networks). All-optical switches, two-state and many-state all-optical memories, all-optical limiters, all-optical discriminators and all-optical transistors are only a few of the many devices proposed during the last two decades. The "all-optical" label is commonly used to distinguish the devices that do not involve dissipative electronic transport and require essentially no electrical communication of information. The all-optical transistor action was first observed in the context of optical bistability [1] and consists in a strong differential gain regime, in which, for small variations in the input intensity, the output intensity has a very strong variation. This analog operation is for all-optical input what transistor action is for electrical inputs.
Intelligent Vision On The SM9O Mini-Computer Basis And Applications
NASA Astrophysics Data System (ADS)
Hawryszkiw, J.
1985-02-01
Distinction has to be made between image processing and vision Image processing finds its roots in the strong tradition of linear signal processing and promotes geometrical transform techniques, such as fi I tering , compression, and restoration. Its purpose is to transform an image for a human observer to easily extract from that image information significant for him. For example edges after a gradient operator, or a specific direction after a directional filtering operation. Image processing consists in fact in a set of local or global space-time transforms. The interpretation of the final image is done by the human observer. The purpose of vision is to extract the semantic content of the image. The machine can then understand that content, and run a process of decision, which turns into an action. Thus, intel I i gent vision depends on - Image processing - Pattern recognition - Artificial intel I igence
Absence of both auditory evoked potentials and auditory percepts dependent on timing cues.
Starr, A; McPherson, D; Patterson, J; Don, M; Luxford, W; Shannon, R; Sininger, Y; Tonakawa, L; Waring, M
1991-06-01
An 11-yr-old girl had an absence of sensory components of auditory evoked potentials (brainstem, middle and long-latency) to click and tone burst stimuli that she could clearly hear. Psychoacoustic tests revealed a marked impairment of those auditory perceptions dependent on temporal cues, that is, lateralization of binaural clicks, change of binaural masked threshold with changes in signal phase, binaural beats, detection of paired monaural clicks, monaural detection of a silent gap in a sound, and monaural threshold elevation for short duration tones. In contrast, auditory functions reflecting intensity or frequency discriminations (difference limens) were only minimally impaired. Pure tone audiometry showed a moderate (50 dB) bilateral hearing loss with a disproportionate severe loss of word intelligibility. Those auditory evoked potentials that were preserved included (1) cochlear microphonics reflecting hair cell activity; (2) cortical sustained potentials reflecting processing of slowly changing signals; and (3) long-latency cognitive components (P300, processing negativity) reflecting endogenous auditory cognitive processes. Both the evoked potential and perceptual deficits are attributed to changes in temporal encoding of acoustic signals perhaps occurring at the synapse between hair cell and eighth nerve dendrites. The results from this patient are discussed in relation to previously published cases with absent auditory evoked potentials and preserved hearing.
Distributed neural system for emotional intelligence revealed by lesion mapping.
Barbey, Aron K; Colom, Roberto; Grafman, Jordan
2014-03-01
Cognitive neuroscience has made considerable progress in understanding the neural architecture of human intelligence, identifying a broadly distributed network of frontal and parietal regions that support goal-directed, intelligent behavior. However, the contributions of this network to social and emotional aspects of intellectual function remain to be well characterized. Here we investigated the neural basis of emotional intelligence in 152 patients with focal brain injuries using voxel-based lesion-symptom mapping. Latent variable modeling was applied to obtain measures of emotional intelligence, general intelligence and personality from the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT), the Wechsler Adult Intelligence Scale and the Neuroticism-Extroversion-Openness Inventory, respectively. Regression analyses revealed that latent scores for measures of general intelligence and personality reliably predicted latent scores for emotional intelligence. Lesion mapping results further indicated that these convergent processes depend on a shared network of frontal, temporal and parietal brain regions. The results support an integrative framework for understanding the architecture of executive, social and emotional processes and make specific recommendations for the interpretation and application of the MSCEIT to the study of emotional intelligence in health and disease.
Distributed neural system for emotional intelligence revealed by lesion mapping
Colom, Roberto; Grafman, Jordan
2014-01-01
Cognitive neuroscience has made considerable progress in understanding the neural architecture of human intelligence, identifying a broadly distributed network of frontal and parietal regions that support goal-directed, intelligent behavior. However, the contributions of this network to social and emotional aspects of intellectual function remain to be well characterized. Here we investigated the neural basis of emotional intelligence in 152 patients with focal brain injuries using voxel-based lesion-symptom mapping. Latent variable modeling was applied to obtain measures of emotional intelligence, general intelligence and personality from the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT), the Wechsler Adult Intelligence Scale and the Neuroticism-Extroversion-Openness Inventory, respectively. Regression analyses revealed that latent scores for measures of general intelligence and personality reliably predicted latent scores for emotional intelligence. Lesion mapping results further indicated that these convergent processes depend on a shared network of frontal, temporal and parietal brain regions. The results support an integrative framework for understanding the architecture of executive, social and emotional processes and make specific recommendations for the interpretation and application of the MSCEIT to the study of emotional intelligence in health and disease. PMID:23171618
ERIC Educational Resources Information Center
Bergeron, Pierrette; Hiller, Christine A.
2002-01-01
Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…
The Breakthrough Listen Search for Intelligent Life: Data Calibration using Pulsars
NASA Astrophysics Data System (ADS)
Brinkman-Traverse, Casey Lynn; Gajjar, Vishal; BSRC
2018-01-01
The ability to distinguish ET signals requires a deep understanding of the radio telescopes with which we search; therefore, before we observe stars of interest, the Breathrough Listen scientists at Berkeley SETI Research Center first observe a Pulsar with well-documented flux and polarization properties. The process of calibrating the flux and polarization is a lengthy process by hand, so we produced a pipeline code that will automatically calibrate the pulsar in under an hour. Using PSRCHIVE the code coherently dedisperses the pulsed radio signals, and then calibrates the flux using observation files with a noise diode turning on and off. The code was developed using PSR B1937+ 21 and is primarily used on PSR B0329+54. This will expedite the process of assessing the quality of data collected from the Green Bank Telescope in West Virginia and will allow us to more efficiently find life beyond Planet Earth. Additionally, the stability of the B0329+54 calibration data will allow us to analyze data taken on FRB's with confidence of its cosmic origin.
Real-Time Digital Signal Processing Based on FPGAs for Electronic Skin Implementation †
Ibrahim, Ali; Gastaldo, Paolo; Chible, Hussein; Valle, Maurizio
2017-01-01
Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g., robots), biomedical instrumentation, and replacement prosthetic devices. An essential task of the electronic skin system is to locally process the tactile data and send structured information either to mimic human skin or to respond to the application demands. The electronic skin must be fabricated together with an embedded electronic system which has the role of acquiring the tactile data, processing, and extracting structured information. On the other hand, processing tactile data requires efficient methods to extract meaningful information from raw sensor data. Machine learning represents an effective method for data analysis in many domains: it has recently demonstrated its effectiveness in processing tactile sensor data. In this framework, this paper presents the implementation of digital signal processing based on FPGAs for tactile data processing. It provides the implementation of a tensorial kernel function for a machine learning approach. Implementation results are assessed by highlighting the FPGA resource utilization and power consumption. Results demonstrate the feasibility of the proposed implementation when real-time classification of input touch modalities are targeted. PMID:28287448
Real-Time Digital Signal Processing Based on FPGAs for Electronic Skin Implementation.
Ibrahim, Ali; Gastaldo, Paolo; Chible, Hussein; Valle, Maurizio
2017-03-10
Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g., robots), biomedical instrumentation, and replacement prosthetic devices. An essential task of the electronic skin system is to locally process the tactile data and send structured information either to mimic human skin or to respond to the application demands. The electronic skin must be fabricated together with an embedded electronic system which has the role of acquiring the tactile data, processing, and extracting structured information. On the other hand, processing tactile data requires efficient methods to extract meaningful information from raw sensor data. Machine learning represents an effective method for data analysis in many domains: it has recently demonstrated its effectiveness in processing tactile sensor data. In this framework, this paper presents the implementation of digital signal processing based on FPGAs for tactile data processing. It provides the implementation of a tensorial kernel function for a machine learning approach. Implementation results are assessed by highlighting the FPGA resource utilization and power consumption. Results demonstrate the feasibility of the proposed implementation when real-time classification of input touch modalities are targeted.
Measuring up to speech intelligibility.
Miller, Nick
2013-01-01
Improvement or maintenance of speech intelligibility is a central aim in a whole range of conditions in speech-language therapy, both developmental and acquired. Best clinical practice and pursuance of the evidence base for interventions would suggest measurement of intelligibility forms a vital role in clinical decision-making and monitoring. However, what should be measured to gauge intelligibility and how this is achieved and relates to clinical planning continues to be a topic of debate. This review considers the strengths and weaknesses of selected clinical approaches to intelligibility assessment, stressing the importance of explanatory, diagnostic testing as both a more sensitive and a clinically informative method. The worth of this, and any approach, is predicated, though, on awareness and control of key design, elicitation, transcription and listening/listener variables to maximize validity and reliability of assessments. These are discussed. A distinction is drawn between signal-dependent and -independent factors in intelligibility evaluation. Discussion broaches how these different perspectives might be reconciled to deliver comprehensive insights into intelligibility levels and their clinical/educational significance. The paper ends with a call for wider implementation of best practice around intelligibility assessment. © 2013 Royal College of Speech and Language Therapists.
Design of programmable intelligent cell phone jammer
NASA Astrophysics Data System (ADS)
Elangovan, Divya; Ravi, Aswin
2011-12-01
The usage of cell phones has increased enormously; at present silence and security is the need of the hour in many places. This can be done by using cell phone jammer, which blocks all the signals. This paper describes the design of an enhanced technique for jamming the cell phone signals. Our main objective is to concentrate on a specific band of frequency, which makes communication possible, by jamming this frequency we block out the specific signal that are responsible for making the call. This method enables the jammer to be more precise and effective, so precise that it can focus on specific area and allowing the programmer to define the area. The major advancement will be that emergency services can be availed which is very crucial in case of any calamity, they are intelligent devices as they act only after they receive signals and also it has a lesser power consumption than existing models. This technique has infinite potentials and sure can this be modified to match all our imaginations.
Sun, Weifang; Yao, Bin; Zeng, Nianyin; He, Yuchao; Cao, Xincheng; He, Wangpeng
2017-01-01
As a typical example of large and complex mechanical systems, rotating machinery is prone to diversified sorts of mechanical faults. Among these faults, one of the prominent causes of malfunction is generated in gear transmission chains. Although they can be collected via vibration signals, the fault signatures are always submerged in overwhelming interfering contents. Therefore, identifying the critical fault’s characteristic signal is far from an easy task. In order to improve the recognition accuracy of a fault’s characteristic signal, a novel intelligent fault diagnosis method is presented. In this method, a dual-tree complex wavelet transform (DTCWT) is employed to acquire the multiscale signal’s features. In addition, a convolutional neural network (CNN) approach is utilized to automatically recognise a fault feature from the multiscale signal features. The experiment results of the recognition for gear faults show the feasibility and effectiveness of the proposed method, especially in the gear’s weak fault features. PMID:28773148
A high-sensitivity search for extraterrestrial intelligence at lambda 18 cm
NASA Technical Reports Server (NTRS)
Tarter, J.; Cuzzi, J.; Black, D.; Clark, T.
1980-01-01
A targeted high-sensitivity search for narrow-band signals near a wavelength of 18 cm has been conducted using the 91-m radiotelescope of the National Radio Astronomy Observatory. The search included 201 nearby solar-type stars and achieved a frequency resolution of 5.5 Hz over a 1.4-MHz bandwidth. This high spectral resolution was obtained through a non-real-time reduction procedure using a Mark I VLBI recording terminal in conjunction with the CDC 7600 computational facility at the NASA-Ames Research Center. This is the first high-resolution search for narrow-band signals in this wavelength regime. To date it is the most sensitive search per unit observing time of any search strategy which does not postulate a unique magic frequency. Data show no evidence for narrow-band signals due to extraterrestrial intelligence at a 12-standard-deviation upper limit on signal strength of 1.1 x 10 to the -23rd W/sq m.
Two Speed Factors of Visual Recognition Independently Correlated with Fluid Intelligence
Tachibana, Ryosuke; Namba, Yuri; Noguchi, Yasuki
2014-01-01
Growing evidence indicates a moderate but significant relationship between processing speed in visuo-cognitive tasks and general intelligence. On the other hand, findings from neuroscience proposed that the primate visual system consists of two major pathways, the ventral pathway for objects recognition and the dorsal pathway for spatial processing and attentive analysis. Previous studies seeking for visuo-cognitive factors of human intelligence indicated a significant correlation between fluid intelligence and the inspection time (IT), an index for a speed of object recognition performed in the ventral pathway. We thus presently examined a possibility that neural processing speed in the dorsal pathway also represented a factor of intelligence. Specifically, we used the mental rotation (MR) task, a popular psychometric measure for mental speed of spatial processing in the dorsal pathway. We found that the speed of MR was significantly correlated with intelligence scores, while it had no correlation with one’s IT (recognition speed of visual objects). Our results support the new possibility that intelligence could be explained by two types of mental speed, one related to object recognition (IT) and another for manipulation of mental images (MR). PMID:24825574
A situation-response model for intelligent pilot aiding
NASA Technical Reports Server (NTRS)
Schudy, Robert; Corker, Kevin
1987-01-01
An intelligent pilot aiding system needs models of the pilot information processing to provide the computational basis for successful cooperation between the pilot and the aiding system. By combining artificial intelligence concepts with the human information processing model of Rasmussen, an abstraction hierarchy of states of knowledge, processing functions, and shortcuts are developed, which is useful for characterizing the information processing both of the pilot and of the aiding system. This approach is used in the conceptual design of a real time intelligent aiding system for flight crews of transport aircraft. One promising result was the tentative identification of a particular class of information processing shortcuts, from situation characterizations to appropriate responses, as the most important reliable pathway for dealing with complex time critical situations.
NASA Astrophysics Data System (ADS)
Zhang, Zhifen; Chen, Huabin; Xu, Yanling; Zhong, Jiyong; Lv, Na; Chen, Shanben
2015-08-01
Multisensory data fusion-based online welding quality monitoring has gained increasing attention in intelligent welding process. This paper mainly focuses on the automatic detection of typical welding defect for Al alloy in gas tungsten arc welding (GTAW) by means of analzing arc spectrum, sound and voltage signal. Based on the developed algorithms in time and frequency domain, 41 feature parameters were successively extracted from these signals to characterize the welding process and seam quality. Then, the proposed feature selection approach, i.e., hybrid fisher-based filter and wrapper was successfully utilized to evaluate the sensitivity of each feature and reduce the feature dimensions. Finally, the optimal feature subset with 19 features was selected to obtain the highest accuracy, i.e., 94.72% using established classification model. This study provides a guideline for feature extraction, selection and dynamic modeling based on heterogeneous multisensory data to achieve a reliable online defect detection system in arc welding.
Cui, De-Mi; Yan, Weizhong; Wang, Xiao-Quan; Lu, Lie-Min
2017-10-25
Low strain pile integrity testing (LSPIT), due to its simplicity and low cost, is one of the most popular NDE methods used in pile foundation construction. While performing LSPIT in the field is generally quite simple and quick, determining the integrity of the test piles by analyzing and interpreting the test signals (reflectograms) is still a manual process performed by experienced experts only. For foundation construction sites where the number of piles to be tested is large, it may take days before the expert can complete interpreting all of the piles and delivering the integrity assessment report. Techniques that can automate test signal interpretation, thus shortening the LSPIT's turnaround time, are of great business value and are in great need. Motivated by this need, in this paper, we develop a computer-aided reflectogram interpretation (CARI) methodology that can interpret a large number of LSPIT signals quickly and consistently. The methodology, built on advanced signal processing and machine learning technologies, can be used to assist the experts in performing both qualitative and quantitative interpretation of LSPIT signals. Specifically, the methodology can ease experts' interpretation burden by screening all test piles quickly and identifying a small number of suspected piles for experts to perform manual, in-depth interpretation. We demonstrate the methodology's effectiveness using the LSPIT signals collected from a number of real-world pile construction sites. The proposed methodology can potentially enhance LSPIT and make it even more efficient and effective in quality control of deep foundation construction.
All-digital radar architecture
NASA Astrophysics Data System (ADS)
Molchanov, Pavlo A.
2014-10-01
All digital radar architecture requires exclude mechanical scan system. The phase antenna array is necessarily large because the array elements must be co-located with very precise dimensions and will need high accuracy phase processing system for aggregate and distribute T/R modules data to/from antenna elements. Even phase array cannot provide wide field of view. New nature inspired all digital radar architecture proposed. The fly's eye consists of multiple angularly spaced sensors giving the fly simultaneously thee wide-area visual coverage it needs to detect and avoid the threats around him. Fly eye radar antenna array consist multiple directional antennas loose distributed along perimeter of ground vehicle or aircraft and coupled with receiving/transmitting front end modules connected by digital interface to central processor. Non-steering antenna array allows creating all-digital radar with extreme flexible architecture. Fly eye radar architecture provides wide possibility of digital modulation and different waveform generation. Simultaneous correlation and integration of thousands signals per second from each point of surveillance area allows not only detecting of low level signals ((low profile targets), but help to recognize and classify signals (targets) by using diversity signals, polarization modulation and intelligent processing. Proposed all digital radar architecture with distributed directional antenna array can provide a 3D space vector to the jammer by verification direction of arrival for signals sources and as result jam/spoof protection not only for radar systems, but for communication systems and any navigation constellation system, for both encrypted or unencrypted signals, for not limited number or close positioned jammers.
NASA Astrophysics Data System (ADS)
Elliott, John R.; Baxter, Stephen
2012-09-01
D.I.S.C: Decipherment Impact of a Signal's Content. The authors present a numerical method to characterise the significance of the receipt of a complex and potentially decipherable signal from extraterrestrial intelligence (ETI). The purpose of the scale is to facilitate the public communication of work on any such claimed signal, as such work proceeds, and to assist in its discussion and interpretation. Building on a "position" paper rationale, this paper looks at the DISC quotient proposed and develops the algorithmic steps and comprising measures that form this post detection strategy for information dissemination, based on prior work on message detection, decipherment. As argued, we require a robust and incremental strategy, to disseminate timely, accurate and meaningful information, to the scientific community and the general public, in the event we receive an "alien" signal that displays decipherable information. This post-detection strategy is to serve as a stepwise algorithm for a logical approach to information extraction and a vehicle for sequential information dissemination, to manage societal impact. The "DISC Quotient", which is based on signal analysis processing stages, includes factors based on the signal's data quantity, structure, affinity to known human languages, and likely decipherment times. Comparisons with human and other phenomena are included as a guide to assessing likely societal impact. It is submitted that the development, refinement and implementation of DISC as an integral strategy, during the complex processes involved in post detection and decipherment, is essential if we wish to minimize disruption and optimize dissemination.
32 CFR 1702.3 - Procedures governing acceptance of service of process.
Code of Federal Regulations, 2010 CFR
2010-07-01
... THE DIRECTOR OF NATIONAL INTELLIGENCE PROCEDURES GOVERNING THE ACCEPTANCE OF SERVICE OF PROCESS § 1702... Intelligence, Office of General Counsel, Washington, DC 20511, and the envelope must be conspicuously marked... capacity. Except for the DNI, the Principal Deputy Director of National Intelligence, and the Director of...
32 CFR 1702.3 - Procedures governing acceptance of service of process.
Code of Federal Regulations, 2012 CFR
2012-07-01
... THE DIRECTOR OF NATIONAL INTELLIGENCE PROCEDURES GOVERNING THE ACCEPTANCE OF SERVICE OF PROCESS § 1702... Intelligence, Office of General Counsel, Washington, DC 20511, and the envelope must be conspicuously marked... capacity. Except for the DNI, the Principal Deputy Director of National Intelligence, and the Director of...
32 CFR 1702.3 - Procedures governing acceptance of service of process.
Code of Federal Regulations, 2011 CFR
2011-07-01
... THE DIRECTOR OF NATIONAL INTELLIGENCE PROCEDURES GOVERNING THE ACCEPTANCE OF SERVICE OF PROCESS § 1702... Intelligence, Office of General Counsel, Washington, DC 20511, and the envelope must be conspicuously marked... capacity. Except for the DNI, the Principal Deputy Director of National Intelligence, and the Director of...
32 CFR 1702.3 - Procedures governing acceptance of service of process.
Code of Federal Regulations, 2014 CFR
2014-07-01
... THE DIRECTOR OF NATIONAL INTELLIGENCE PROCEDURES GOVERNING THE ACCEPTANCE OF SERVICE OF PROCESS § 1702... Intelligence, Office of General Counsel, Washington, DC 20511, and the envelope must be conspicuously marked... capacity. Except for the DNI, the Principal Deputy Director of National Intelligence, and the Director of...
32 CFR 1702.3 - Procedures governing acceptance of service of process.
Code of Federal Regulations, 2013 CFR
2013-07-01
... THE DIRECTOR OF NATIONAL INTELLIGENCE PROCEDURES GOVERNING THE ACCEPTANCE OF SERVICE OF PROCESS § 1702... Intelligence, Office of General Counsel, Washington, DC 20511, and the envelope must be conspicuously marked... capacity. Except for the DNI, the Principal Deputy Director of National Intelligence, and the Director of...
Partial Bibliography of Work on Expert Systems,
1982-12-01
Bibliography: AAAI American Association for Artificial Intelligence ACM Association for Computing Machinery AFIPS American Federation of Information...Processing Societies ECAI European Conference on Artificial Intelligence IEEE Institute for Electrical and Electronic Engineers IFIPS International...Federation of Information Processing Societies IJCAI International Joint Conferences on Artificial Intelligence SIGPLAN ACM Special Interest Group on
Aircraft Assessment and Acceptance Testing.
1980-05-01
telaque le pilote automatique, et lautomnanette, lee syst.-mes de stabilit6 artificielle etc.. A5 - La v~rification des dispositifs de odcuritd B - Essais...signals should be monitored on an oscilloscope, and modulation meter to assist in diagnosis or reasons for poor intelligibility . 7 Qualitative...conditioning in origin, so tests of the effect on com- munications intelligibility should be made in the flight regime that is operationally most
Artificial intelligence and signal processing for infrastructure assessment
NASA Astrophysics Data System (ADS)
Assaleh, Khaled; Shanableh, Tamer; Yehia, Sherif
2015-04-01
The Ground Penetrating Radar (GPR) is being recognized as an effective nondestructive evaluation technique to improve the inspection process. However, data interpretation and complexity of the results impose some limitations on the practicality of using this technique. This is mainly due to the need of a trained experienced person to interpret images obtained by the GPR system. In this paper, an algorithm to classify and assess the condition of infrastructures utilizing image processing and pattern recognition techniques is discussed. Features extracted form a dataset of images of defected and healthy slabs are used to train a computer vision based system while another dataset is used to evaluate the proposed algorithm. Initial results show that the proposed algorithm is able to detect the existence of defects with about 77% success rate.
Time and space integrating acousto-optic folded spectrum processing for SETI
NASA Technical Reports Server (NTRS)
Wagner, K.; Psaltis, D.
1986-01-01
Time and space integrating folded spectrum techniques utilizing acousto-optic devices (AOD) as 1-D input transducers are investigated for a potential application as wideband, high resolution, large processing gain spectrum analyzers in the search for extra-terrestrial intelligence (SETI) program. The space integrating Fourier transform performed by a lens channels the coarse spectral components diffracted from an AOD onto an array of time integrating narrowband fine resolution spectrum analyzers. The pulsing action of a laser diode samples the interferometrically detected output, aliasing the fine resolution components to baseband, as required for the subsequent charge coupled devices (CCD) processing. The raster scan mechanism incorporated into the readout of the CCD detector array is used to unfold the 2-D transform, reproducing the desired high resolution Fourier transform of the input signal.
Intelligent Processing Equipment Within the Environmental Protection Agency
NASA Technical Reports Server (NTRS)
Greathouse, Daniel G.; Nalesnik, Richard P.
1992-01-01
Protection of the environment and environmental remediation requires the cooperation, at all levels, of government and industry. Intelligent processing equipment, in addition to other artificial intelligence based tools, was used by the Environmental Protection Agency to provide personnel safety and improve the efficiency of those responsible for protection and remediation of the environment. These exploratory efforts demonstrate the feasibility and utility of expanding development and widespread use of these tools. A survey of current intelligent processing equipment applications in the Agency is presented and is followed by a brief discussion of possible uses in the future.
Strong Genetic Overlap Between Executive Functions and Intelligence
Engelhardt, Laura E.; Mann, Frank D.; Briley, Daniel A.; Church, Jessica A.; Harden, K. Paige; Tucker-Drob, Elliot M.
2016-01-01
Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision-making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic influences on EFs are very high, even in middle childhood, but the extent to which these genetic influences overlap with those on intelligence is unclear. We examined genetic and environmental overlap between EFs and intelligence in a racially and socioeconomically diverse sample of 811 twins ages 7-15 years (M = 10.91, SD = 1.74) from the Texas Twin Project. A general EF factor representing variance common to inhibition, switching, working memory, and updating domains accounted for substantial proportions of variance in intelligence, primarily via a genetic pathway. General EF continued to have a strong, genetically-mediated association with intelligence even after controlling for processing speed. Residual variation in general intelligence was influenced only by shared and nonshared environmental factors, and there remained no genetic variance in general intelligence that was unique of EF. Genetic variance independent of EF did remain, however, in a more specific perceptual reasoning ability. These results provide evidence that genetic influences on general intelligence are highly overlapping with those on EF. PMID:27359131
Colom, Roberto; Burgaleta, Miguel; Román, Francisco J; Karama, Sherif; Alvarez-Linera, Juan; Abad, Francisco J; Martínez, Kenia; Quiroga, Ma Ángeles; Haier, Richard J
2013-05-15
Evidence from neuroimaging studies suggests that intelligence differences may be supported by a parieto-frontal network. Research shows that this network is also relevant for cognitive functions such as working memory and attention. However, previous studies have not explicitly analyzed the commonality of brain areas between a broad array of intelligence factors and cognitive functions tested in the same sample. Here fluid, crystallized, and spatial intelligence, along with working memory, executive updating, attention, and processing speed were each measured by three diverse tests or tasks. These twenty-one measures were completed by a group of one hundred and four healthy young adults. Three cortical measures (cortical gray matter volume, cortical surface area, and cortical thickness) were regressed against psychological latent scores obtained from a confirmatory factor analysis for removing test and task specific variance. For cortical gray matter volume and cortical surface area, the main overlapping clusters were observed in the middle frontal gyrus and involved fluid intelligence and working memory. Crystallized intelligence showed an overlapping cluster with fluid intelligence and working memory in the middle frontal gyrus. The inferior frontal gyrus showed overlap for crystallized intelligence, spatial intelligence, attention, and processing speed. The fusiform gyrus in temporal cortex showed overlap for spatial intelligence and attention. Parietal and occipital areas did not show any overlap across intelligence and cognitive factors. Taken together, these findings underscore that structural features of gray matter in the frontal lobes support those aspects of intelligence related to basic cognitive processes. Copyright © 2013 Elsevier Inc. All rights reserved.
NASA SETI microwave observing project: Sky Survey element
NASA Technical Reports Server (NTRS)
Klein, M. J.
1991-01-01
The SETI Sky Survey Observing Program is one of two complimentary strategies that NASA plans to use in its microwave Search for Extraterrestrial Intelligence (SETI). The primary objective of the sky survey is to search the entire sky over the frequency range of 1.0 to 10.0 GHz for evidence of narrow band signals of extraterrestrial intelligent origin. Frequency resolutions of 30 Hz or narrower will be used across the entire band. Spectrum analyzers with upwards of ten million channels are required to keep the survey time approximately 6 years. Data rates in excess of 10 megabits per second will be generated in the data taking process. Sophisticated data processing techniques will be required to determine the ever changing receiver baselines, and to detect and archive potential SETI signals. Existing radio telescopes, including several of NASA's Deep Space Network (DSN) 34 meter antennas located at Goldstone, CA and Tidbinbilla, Australia will be used for the observations. The JPL has the primary responsibility to develop and carry out the sky survey. In order to lay the foundation for the full scale SETI Sky Survey, a prototype system is being developed at the JPL. The system will be installed at the new 34-m high efficiency antenna at the Deep Space Station (DSS) 13 research and development station, Goldstone, CA, where it will be used to initiate the observational phase of the NASA SETI Sky Survey. It is anticipated that the early observations will be useful to test signal detection algorithms, scan strategies, and radio frequency interference rejection schemes. The SETI specific elements of the prototype system are: (1) the Wide Band Spectrum Analyzer (WBSA); a 2-million channel fast Fourier transformation (FFT) spectrum analyzer which covers an instantaneous bandpass of 40 MHz; (2) the signal detection processor; and (3) the SETI Sky Survey Manager, a network-based C-language environment that provides observatory control, performs data acquisition and analysis algorithms. A high level description of the prototype hardware and software systems will be given and the current status of the system development will be reported.
Multichannel spatial auditory display for speech communications
NASA Technical Reports Server (NTRS)
Begault, D. R.; Erbe, T.; Wenzel, E. M. (Principal Investigator)
1994-01-01
A spatial auditory display for multiple speech communications was developed at NASA/Ames Research Center. Input is spatialized by the use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four-letter call signs used by launch personnel at NASA against diotic speech babble. Spatial positions at 30 degrees azimuth increments were evaluated. The results from eight subjects showed a maximum intelligibility improvement of about 6-7 dB when the signal was spatialized to 60 or 90 degrees azimuth positions.
Multi-channel spatial auditory display for speech communications
NASA Astrophysics Data System (ADS)
Begault, Durand; Erbe, Tom
1993-10-01
A spatial auditory display for multiple speech communications was developed at NASA-Ames Research Center. Input is spatialized by use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four letter call signs used by launch personnel at NASA, against diotic speech babble. Spatial positions at 30 deg azimuth increments were evaluated. The results from eight subjects showed a maximal intelligibility improvement of about 6 to 7 dB when the signal was spatialized to 60 deg or 90 deg azimuth positions.
Multichannel spatial auditory display for speech communications.
Begault, D R; Erbe, T
1994-10-01
A spatial auditory display for multiple speech communications was developed at NASA/Ames Research Center. Input is spatialized by the use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four-letter call signs used by launch personnel at NASA against diotic speech babble. Spatial positions at 30 degrees azimuth increments were evaluated. The results from eight subjects showed a maximum intelligibility improvement of about 6-7 dB when the signal was spatialized to 60 or 90 degrees azimuth positions.
Multichannel Spatial Auditory Display for Speed Communications
NASA Technical Reports Server (NTRS)
Begault, Durand R.; Erbe, Tom
1994-01-01
A spatial auditory display for multiple speech communications was developed at NASA/Ames Research Center. Input is spatialized by the use of simplifiedhead-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four-letter call signs used by launch personnel at NASA against diotic speech babble. Spatial positions at 30 degree azimuth increments were evaluated. The results from eight subjects showed a maximum intelligibility improvement of about 6-7 dB when the signal was spatialized to 60 or 90 degree azimuth positions.
Multi-channel spatial auditory display for speech communications
NASA Technical Reports Server (NTRS)
Begault, Durand; Erbe, Tom
1993-01-01
A spatial auditory display for multiple speech communications was developed at NASA-Ames Research Center. Input is spatialized by use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four letter call signs used by launch personnel at NASA, against diotic speech babble. Spatial positions at 30 deg azimuth increments were evaluated. The results from eight subjects showed a maximal intelligibility improvement of about 6 to 7 dB when the signal was spatialized to 60 deg or 90 deg azimuth positions.
Audiovisual Asynchrony Detection in Human Speech
ERIC Educational Resources Information Center
Maier, Joost X.; Di Luca, Massimiliano; Noppeney, Uta
2011-01-01
Combining information from the visual and auditory senses can greatly enhance intelligibility of natural speech. Integration of audiovisual speech signals is robust even when temporal offsets are present between the component signals. In the present study, we characterized the temporal integration window for speech and nonspeech stimuli with…
Detecting the signature of intelligent life
NASA Astrophysics Data System (ADS)
Elliott, John R.
2010-12-01
The detection of a communication from another planet would be one of the greatest events in human history, so we need to be ready for such an eventuality. How to solve messages from other worlds and to contemplate all possibilities is an extremely complex challenge; however, we have to begin somewhere. So, the problem goal is therefore to separate intelligent from non-intelligent content without dialogue, and learn something about the structure of the content in the passing. These structural phenomena range over a multi-layered hierarchical system that can not only indicate the core syntactic devices but also the cognition [intellectual power] of the author. In identifying whether a signal has been detected from an ET source and that it fulfils the criteria for being a bona fide signature from another planet, SETI has well established methods in place. However, for CETI and deciphering whether this signal has an intelligent author, work is still in its initial stages. To commence developing a system that tackles this ultimate phase of contact, strategies have been developed to enable classification and partial decipherment of such a signal, given declared assumptions and initial constraints based on cosmological anthropic principles. A set of assumptions based on the Sparseness principle that postulates that certain complex systems like mathematics and language must have underlying structural truths to enable their systems to work effectively and efficiently; any other variation lessens this significantly: a premise supported for language by comparing over 50 terrestrial languages. This paper looks back at what has been achieved to-date and what is planned for the future.
Energy-efficient neural information processing in individual neurons and neuronal networks.
Yu, Lianchun; Yu, Yuguo
2017-11-01
Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Biologically inspired binaural hearing aid algorithms: Design principles and effectiveness
NASA Astrophysics Data System (ADS)
Feng, Albert
2002-05-01
Despite rapid advances in the sophistication of hearing aid technology and microelectronics, listening in noise remains problematic for people with hearing impairment. To solve this problem two algorithms were designed for use in binaural hearing aid systems. The signal processing strategies are based on principles in auditory physiology and psychophysics: (a) the location/extraction (L/E) binaural computational scheme determines the directions of source locations and cancels noise by applying a simple subtraction method over every frequency band; and (b) the frequency-domain minimum-variance (FMV) scheme extracts a target sound from a known direction amidst multiple interfering sound sources. Both algorithms were evaluated using standard metrics such as signal-to-noise-ratio gain and articulation index. Results were compared with those from conventional adaptive beam-forming algorithms. In free-field tests with multiple interfering sound sources our algorithms performed better than conventional algorithms. Preliminary intelligibility and speech reception results in multitalker environments showed gains for every listener with normal or impaired hearing when the signals were processed in real time with the FMV binaural hearing aid algorithm. [Work supported by NIH-NIDCD Grant No. R21DC04840 and the Beckman Institute.
Johannesen, Peter T.; Pérez-González, Patricia; Kalluri, Sridhar; Blanco, José L.
2016-01-01
The aim of this study was to assess the relative importance of cochlear mechanical dysfunction, temporal processing deficits, and age on the ability of hearing-impaired listeners to understand speech in noisy backgrounds. Sixty-eight listeners took part in the study. They were provided with linear, frequency-specific amplification to compensate for their audiometric losses, and intelligibility was assessed for speech-shaped noise (SSN) and a time-reversed two-talker masker (R2TM). Behavioral estimates of cochlear gain loss and residual compression were available from a previous study and were used as indicators of cochlear mechanical dysfunction. Temporal processing abilities were assessed using frequency modulation detection thresholds. Age, audiometric thresholds, and the difference between audiometric threshold and cochlear gain loss were also included in the analyses. Stepwise multiple linear regression models were used to assess the relative importance of the various factors for intelligibility. Results showed that (a) cochlear gain loss was unrelated to intelligibility, (b) residual cochlear compression was related to intelligibility in SSN but not in a R2TM, (c) temporal processing was strongly related to intelligibility in a R2TM and much less so in SSN, and (d) age per se impaired intelligibility. In summary, all factors affected intelligibility, but their relative importance varied across maskers. PMID:27604779
Intelligent Weld Manufacturing: Role of Integrated Computational Welding Engineering
David, Stan A.; Chen, Jian; Feng, Zhili; ...
2017-12-02
A master welder uses his sensory perceptions to evaluate the process and connect them with his/her knowledge base to take the necessary corrective measures with his/her acquired skills to make a good weld. All these actions must take place in real time. Success depends on intuition and skills, and the procedure is labor-intensive and frequently unreliable. The solution is intelligent weld manufacturing. The ultimate goal of intelligent weld manufacturing would involve sensing and control of heat source position, weld temperature, weld penetration, defect formation and ultimately control of microstructure and properties. This involves a solution to a problem (welding) withmore » many highly coupled and nonlinear variables. The trend is to use an emerging tool known as intelligent control. This approach enables the user to choose a desirable end factor such as properties, defect control, or productivity to derive the selection of process parameters such as current, voltage, or speed to provide for appropriate control of the process. Important elements of intelligent manufacturing are sensing and control theory and design, process modeling, and artificial intelligence. Significant progress has been made in all these areas. Integrated computational welding engineering (ICWE) is an emerging field that will aid in the realization of intelligent weld manufacturing. The paper will discuss the progress in process modeling, microstructure, properties, and process control and automation and the importance of ICWE. Also, control and automation strategies for friction stir welding will be discussed.« less
Intelligent Weld Manufacturing: Role of Integrated Computational Welding Engineering
DOE Office of Scientific and Technical Information (OSTI.GOV)
David, Stan A.; Chen, Jian; Feng, Zhili
A master welder uses his sensory perceptions to evaluate the process and connect them with his/her knowledge base to take the necessary corrective measures with his/her acquired skills to make a good weld. All these actions must take place in real time. Success depends on intuition and skills, and the procedure is labor-intensive and frequently unreliable. The solution is intelligent weld manufacturing. The ultimate goal of intelligent weld manufacturing would involve sensing and control of heat source position, weld temperature, weld penetration, defect formation and ultimately control of microstructure and properties. This involves a solution to a problem (welding) withmore » many highly coupled and nonlinear variables. The trend is to use an emerging tool known as intelligent control. This approach enables the user to choose a desirable end factor such as properties, defect control, or productivity to derive the selection of process parameters such as current, voltage, or speed to provide for appropriate control of the process. Important elements of intelligent manufacturing are sensing and control theory and design, process modeling, and artificial intelligence. Significant progress has been made in all these areas. Integrated computational welding engineering (ICWE) is an emerging field that will aid in the realization of intelligent weld manufacturing. The paper will discuss the progress in process modeling, microstructure, properties, and process control and automation and the importance of ICWE. Also, control and automation strategies for friction stir welding will be discussed.« less
NASA Astrophysics Data System (ADS)
Radchenko, Andro
River bridge scour is an erosion process in which flowing water removes sediment materials (such as sand, rocks) from a bridge foundation, river beds and banks. As a result, the level of the river bed near a bridge pier is lowering such that the bridge foundation stability can be compromised, and the bridge can collapse. The scour is a dynamic process, which can accelerate rapidly during a flood event. Thus, regular monitoring of the scour progress is necessary to be performed at most river bridges. Present techniques are usually expensive, require large man/hour efforts, and often lack the real-time monitoring capabilities. In this dissertation a new method--'Smart Rocks Network for bridge scour monitoring' is introduced. The method is based on distributed wireless sensors embedded in ground underwater nearby the bridge pillars. The sensor nodes are unconstrained in movement, are equipped with years-lasting batteries and intelligent custom designed electronics, which minimizes power consumption during operation and communication. The electronic part consists of a microcontroller, communication interfaces, orientation and environment sensors (such as are accelerometer, magnetometer, temperature and pressure sensors), supporting power supplies and circuitries. Embedded in the soil nearby a bridge pillar the Smart Rocks can move/drift together with the sediments, and act as the free agent probes transmitting the unique signature signals to the base-station monitors. Individual movement of a Smart Rock can be remotely detected processing the orientation sensors reading. This can give an indication of the on-going scour progress, and set a flag for the on-site inspection. The map of the deployed Smart Rocks Network can be obtained utilizing the custom developed in-network communication protocol with signals intensity (RSSI) analysis. Particle Swarm Optimization (PSO) is applied for map reconstruction. Analysis of the map can provide detailed insight into the scour progress and topology. Smart Rocks Network wireless communication is based on the magnetoinductive (MI) link, at low (125 KHz) frequency, allowing for signal to penetrate through the water, rocks, and the bridge structure. The dissertation describes the Smart Rocks Network implementation, its electronic design and the electromagnetic/computational intelligence techniques used for the network mapping.
Bacterial intelligence: imitation games, time-sharing, and long-range quantum coherence.
Majumdar, Sarangam; Pal, Sukla
2017-09-01
Bacteria are far more intelligent than we can think of. They adopt different survival strategies to make their life comfortable. Researches on bacterial communication to date suggest that bacteria can communicate with each other using chemical signaling molecules as well as using ion channel mediated electrical signaling. Though in past few decades the scopes of chemical signaling have been investigated extensively, those of electrical signaling have received less attention. In this article, we present a novel perspective on time-sharing behavior, which maintains the biofilm growth under reduced nutrient supply between two distant biofilms through electrical signaling based on the experimental evidence reported by Liu et al., in 2017. In addition, following the recent work by Humphries et al. Cell 168(1):200-209, in 2017, we highlight the consequences of long range electrical signaling within biofilm communities through spatially propagating waves of potassium. Furthermore, we address the possibility of two-way cellular communication between artificial and natural cells through chemical signaling being inspired by recent experimental observation (Lentini et al. 2017) where the efficiency of artificial cells in imitating the natural cells is estimated through cellular Turing test. These three spectacular observations lead us to envisage and devise new classical and quantum views of these complex biochemical networks that have never been realized previously.
A survey of body sensor networks.
Lai, Xiaochen; Liu, Quanli; Wei, Xin; Wang, Wei; Zhou, Guoqiao; Han, Guangyi
2013-04-24
The technology of sensor, pervasive computing, and intelligent information processing is widely used in Body Sensor Networks (BSNs), which are a branch of wireless sensor networks (WSNs). BSNs are playing an increasingly important role in the fields of medical treatment, social welfare and sports, and are changing the way humans use computers. Existing surveys have placed emphasis on the concept and architecture of BSNs, signal acquisition, context-aware sensing, and system technology, while this paper will focus on sensor, data fusion, and network communication. And we will introduce the research status of BSNs, the analysis of hotspots, and future development trends, the discussion of major challenges and technical problems facing currently. The typical research projects and practical application of BSNs are introduced as well. BSNs are progressing along the direction of multi-technology integration and intelligence. Although there are still many problems, the future of BSNs is fundamentally promising, profoundly changing the human-machine relationships and improving the quality of people's lives.
Yang, Yongqi; Guan, Lin; Gao, Guanghui
2018-04-25
Traditional optoelectronic devices without stretchable performance could be limited for substrates with irregular shape. Therefore, it is urgent to explore a new generation of flexible, stretchable, and low-cost intelligent vehicles as visual display and storage devices, such as hydrogels. In the investigation, a novel photochromic hydrogel was developed by introducing the negatively charged ammonium molybdate as a photochromic unit into polyacrylamide via ionic and covalent cross-linking. The hydrogel exhibited excellent properties of low cost, easy preparation, stretchable deformation, fatigue resistance, high transparency, and second-order response to external signals. Moreover, the photochromic and fading process of hydrogels could be precisely controlled and repeated under the irradiation of UV light and exposure of oxygen at different time and temperature. The photochromic hydrogel could be considered applied for artificial intelligence system, wearable healthcare device, and flexible memory device. Therefore, the strategy for designing a soft photochromic material would open a new direction to manufacture flexible and stretchable devices.
Artificial intelligence techniques used in respiratory sound analysis--a systematic review.
Palaniappan, Rajkumar; Sundaraj, Kenneth; Sundaraj, Sebastian
2014-02-01
Artificial intelligence (AI) has recently been established as an alternative method to many conventional methods. The implementation of AI techniques for respiratory sound analysis can assist medical professionals in the diagnosis of lung pathologies. This article highlights the importance of AI techniques in the implementation of computer-based respiratory sound analysis. Articles on computer-based respiratory sound analysis using AI techniques were identified by searches conducted on various electronic resources, such as the IEEE, Springer, Elsevier, PubMed, and ACM digital library databases. Brief descriptions of the types of respiratory sounds and their respective characteristics are provided. We then analyzed each of the previous studies to determine the specific respiratory sounds/pathology analyzed, the number of subjects, the signal processing method used, the AI techniques used, and the performance of the AI technique used in the analysis of respiratory sounds. A detailed description of each of these studies is provided. In conclusion, this article provides recommendations for further advancements in respiratory sound analysis.
Design and implementation of intelligent electronic warfare decision making algorithm
NASA Astrophysics Data System (ADS)
Peng, Hsin-Hsien; Chen, Chang-Kuo; Hsueh, Chi-Shun
2017-05-01
Electromagnetic signals and the requirements of timely response have been a rapid growth in modern electronic warfare. Although jammers are limited resources, it is possible to achieve the best electronic warfare efficiency by tactical decisions. This paper proposes the intelligent electronic warfare decision support system. In this work, we develop a novel hybrid algorithm, Digital Pheromone Particle Swarm Optimization, based on Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Shuffled Frog Leaping Algorithm (SFLA). We use PSO to solve the problem and combine the concept of pheromones in ACO to accumulate more useful information in spatial solving process and speed up finding the optimal solution. The proposed algorithm finds the optimal solution in reasonable computation time by using the method of matrix conversion in SFLA. The results indicated that jammer allocation was more effective. The system based on the hybrid algorithm provides electronic warfare commanders with critical information to assist commanders in effectively managing the complex electromagnetic battlefield.
Sensors control gas metal arc welding
DOE Office of Scientific and Technical Information (OSTI.GOV)
Siewert, T.A.; Madigan, R.B.; Quinn, T.P.
1997-04-01
The response time of a trained welder from the time a weld problem is identified to the time action is taken is about one second--especially after a long, uneventful period of welding. This is acceptable for manual welding because it is close to the time it takes for the weld pool to solidify. If human response time were any slower, manual welding would not be possible. However, human response time is too slow to respond to some weld events, such as melting of the contact tube in gas metal arc welding (GMAW), and only automated intelligent control systems can reactmore » fast enough to correct or avoid these problems. Control systems incorporate welding knowledge that enables intelligent decisions to be made about weld quality and, ultimately, to keep welding parameters in the range where only high-quality welds are produced. This article discusses the correlation of electrical signals with contact-tube wear, changes in shielding gas, changes in arc length, and other weld process data.« less
Flexible hemispheric microarrays of highly pressure-sensitive sensors based on breath figure method.
Wang, Zhihui; Zhang, Ling; Liu, Jin; Jiang, Hao; Li, Chunzhong
2018-05-30
Recently, flexible pressure sensors featuring high sensitivity, broad sensing range and real-time detection have aroused great attention owing to their crucial role in the development of artificial intelligent devices and healthcare systems. Herein, highly sensitive pressure sensors based on hemisphere-microarray flexible substrates are fabricated via inversely templating honeycomb structures deriving from a facile and static breath figure process. The interlocked and subtle microstructures greatly improve the sensing characteristics and compressibility of the as-prepared pressure sensor, endowing it a sensitivity as high as 196 kPa-1 and a wide pressure sensing range (0-100 kPa), as well as other superior performance, including a lower detection limit of 0.5 Pa, fast response time (<26 ms) and high reversibility (>10 000 cycles). Based on the outstanding sensing performance, the potential capability of our pressure sensor in capturing physiological information and recognizing speech signals has been demonstrated, indicating promising application in wearable and intelligent electronics.
A Survey of Body Sensor Networks
Lai, Xiaochen; Liu, Quanli; Wei, Xin; Wang, Wei; Zhou, Guoqiao; Han, Guangyi
2013-01-01
The technology of sensor, pervasive computing, and intelligent information processing is widely used in Body Sensor Networks (BSNs), which are a branch of wireless sensor networks (WSNs). BSNs are playing an increasingly important role in the fields of medical treatment, social welfare and sports, and are changing the way humans use computers. Existing surveys have placed emphasis on the concept and architecture of BSNs, signal acquisition, context-aware sensing, and system technology, while this paper will focus on sensor, data fusion, and network communication. And we will introduce the research status of BSNs, the analysis of hotspots, and future development trends, the discussion of major challenges and technical problems facing currently. The typical research projects and practical application of BSNs are introduced as well. BSNs are progressing along the direction of multi-technology integration and intelligence. Although there are still many problems, the future of BSNs is fundamentally promising, profoundly changing the human-machine relationships and improving the quality of people's lives. PMID:23615581
Intelligence, Cognition, and Language of Green Plants
Trewavas, Anthony
2016-01-01
A summary definition of some 70 descriptions of intelligence provides a definition for all other organisms including plants that stresses fitness. Barbara McClintock, a plant biologist, posed the notion of the ‘thoughtful cell’ in her Nobel prize address. The systems structure necessary for a thoughtful cell is revealed by comparison of the interactome and connectome. The plant root cap, a group of some 200 cells that act holistically in responding to numerous signals, likely possesses a similar systems structure agreeing with Darwin’s description of acting like the brain of a lower organism. Intelligent behavior requires assessment of different choices and taking the beneficial one. Decisions are constantly required to optimize the plant phenotype to a dynamic environment and the cambium is the assessing tissue diverting more or removing resources from different shoot and root branches through manipulation of vascular elements. Environmental awareness likely indicates consciousness. Spontaneity in plant behavior, ability to count to five and error correction indicate intention. Volatile organic compounds are used as signals in plant interactions and being complex in composition may be the equivalent of language accounting for self and alien recognition by individual plants. Game theory describes competitive interactions. Interactive and intelligent outcomes emerge from application of various games between plants themselves and interactions with microbes. Behavior profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses. PMID:27199823
Road Nail: Experimental Solar Powered Intelligent Road Marking System
NASA Astrophysics Data System (ADS)
Samardžija, Dragan; Teslić, Nikola; Todorović, Branislav M.; Kovač, Erne; Isailović, Đorđe; Miladinović, Bojan
2012-03-01
Driving in low visibility conditions (night time, fog or heavy precipitation) is particularly challenging task with an increased probability of traffic accidents and possible injuries. Road Nail is a solar powered intelligent road marking system of wirelessly networked signaling devices that improve driver safety in low visibility conditions along hazardous roadways. Nails or signaling devices are autonomous nodes with capability to accumulate energy, exchange wireless messages, detect approaching vehicles and emit signalization light. We have built an experimental test-bed that consists of 20 nodes and a cellular gateway. Implementation details of the above system, including extensive measurements and performance evaluations in realistic field deployments are presented. A novel distributed network topology discovery scheme is proposed which integrates both sensor and wireless communication aspects, where nodes act autonomously. Finally, integration of the Road Nail system with the cellular network and the Internet is described.
Wi-Fi location fingerprinting using an intelligent checkpoint sequence
NASA Astrophysics Data System (ADS)
Retscher, Günther; Hofer, Hannes
2017-09-01
For Wi-Fi positioning location fingerprinting is very common but has the disadvantage that it is very labour consuming for the establishment of a database (DB) with received signal strength (RSS) scans measured on a large number of known reference points (RPs). To overcome this drawback a novel approach is developed which uses a logical sequence of intelligent checkpoints (iCPs) instead of RPs distributed in a regular grid. The iCPs are the selected RPs which have to be passed along the way for navigation from a start point A to the destination B. They are twofold intelligent because of the fact that they depend on their meaningful selection and because of their logical sequence in their correct order. Thus, always the following iCP is known due to a vector graph allocation in the DB and only a small limited number of iCPs needs to be tested when matching the current RSS scans. This reduces the required processing time significantly. It is proven that the iCP approach achieves a higher success rate than conventional approaches. In average correct matching results of 90.0% were achieved using a joint DB including RSS scans of all employed smartphones. An even higher success rate is achieved if the same mobile device is used in both the training and positioning phase.
ERIC Educational Resources Information Center
Cho, Seokhee; Lin, Chia-Yi
2011-01-01
Predictive relationships among perceived family processes, intrinsic and extrinsic motivation, incremental beliefs about intelligence, confidence in intelligence, and creative problem-solving practices in mathematics and science were examined. Participants were 733 scientifically talented Korean students in fourth through twelfth grades as well as…
ERIC Educational Resources Information Center
Malakar, Partha; Basu, Jayanti
2017-01-01
The aim of the study was to determine whether the general intelligence, cognitive processes, school achievement, and intelligence-achievement relationship of adolescents with subclinical levels of obsessive-compulsive symptoms differed from those of their normal counterparts. From an initial large pool of 14-year-old Bengali students in eighth…
ERIC Educational Resources Information Center
Saklofske, Donald H.; Zhu, Jianjun; Coalson, Diane L.; Raiford, Susan E.; Weiss, Lawrence G.
2010-01-01
The Cognitive Proficiency Index (CPI) developed for the most recent Wechsler intelligence scales comprises the working memory and processing speed subtests. It reflects the proficiency and efficiency of cognitive processing and provides another lens for analyzing children's abilities assessed by the Wechsler Intelligence Scale for Children--Fourth…
Colom, Roberto; Stein, Jason L.; Rajagopalan, Priya; Martínez, Kenia; Hermel, David; Wang, Yalin; Álvarez-Linera, Juan; Burgaleta, Miguel; Quiroga, MªÁngeles; Shih, Pei Chun; Thompson, Paul M.
2014-01-01
Here we apply a method for automated segmentation of the hippocampus in 3D high-resolution structural brain MRI scans. One hundred and four healthy young adults completed twenty one tasks measuring abstract, verbal, and spatial intelligence, along with working memory, executive control, attention, and processing speed. After permutation tests corrected for multiple comparisons across vertices (p < .05) significant relationships were found for spatial intelligence, spatial working memory, and spatial executive control. Interactions with sex revealed significant relationships with the general factor of intelligence (g), along with abstract and spatial intelligence. These correlations were mainly positive for males but negative for females, which might support the efficiency hypothesis in women. Verbal intelligence, attention, and processing speed were not related to hippocampal structural differences. PMID:25632167
Compensatory neurofuzzy model for discrete data classification in biomedical
NASA Astrophysics Data System (ADS)
Ceylan, Rahime
2015-03-01
Biomedical data is separated to two main sections: signals and discrete data. So, studies in this area are about biomedical signal classification or biomedical discrete data classification. There are artificial intelligence models which are relevant to classification of ECG, EMG or EEG signals. In same way, in literature, many models exist for classification of discrete data taken as value of samples which can be results of blood analysis or biopsy in medical process. Each algorithm could not achieve high accuracy rate on classification of signal and discrete data. In this study, compensatory neurofuzzy network model is presented for classification of discrete data in biomedical pattern recognition area. The compensatory neurofuzzy network has a hybrid and binary classifier. In this system, the parameters of fuzzy systems are updated by backpropagation algorithm. The realized classifier model is conducted to two benchmark datasets (Wisconsin Breast Cancer dataset and Pima Indian Diabetes dataset). Experimental studies show that compensatory neurofuzzy network model achieved 96.11% accuracy rate in classification of breast cancer dataset and 69.08% accuracy rate was obtained in experiments made on diabetes dataset with only 10 iterations.
Signals and circuits in the purkinje neuron.
Abrams, Zéev R; Zhang, Xiang
2011-01-01
Purkinje neurons (PN) in the cerebellum have over 100,000 inputs organized in an orthogonal geometry, and a single output channel. As the sole output of the cerebellar cortex layer, their complex firing pattern has been associated with motor control and learning. As such they have been extensively modeled and measured using tools ranging from electrophysiology and neuroanatomy, to dynamic systems and artificial intelligence methods. However, there is an alternative approach to analyze and describe the neuronal output of these cells using concepts from electrical engineering, particularly signal processing and digital/analog circuits. By viewing the PN as an unknown circuit to be reverse-engineered, we can use the tools that provide the foundations of today's integrated circuits and communication systems to analyze the Purkinje system at the circuit level. We use Fourier transforms to analyze and isolate the inherent frequency modes in the PN and define three unique frequency ranges associated with the cells' output. Comparing the PN to a signal generator that can be externally modulated adds an entire level of complexity to the functional role of these neurons both in terms of data analysis and information processing, relying on Fourier analysis methods in place of statistical ones. We also re-describe some of the recent literature in the field, using the nomenclature of signal processing. Furthermore, by comparing the experimental data of the past decade with basic electronic circuitry, we can resolve the outstanding controversy in the field, by recognizing that the PN can act as a multivibrator circuit.
Willinger, Ulrike; Hergovich, Andreas; Schmoeger, Michaela; Deckert, Matthias; Stoettner, Susanne; Bunda, Iris; Witting, Andrea; Seidler, Melanie; Moser, Reinhilde; Kacena, Stefanie; Jaeckle, David; Loader, Benjamin; Mueller, Christian; Auff, Eduard
2017-05-01
Humour processing is a complex information-processing task that is dependent on cognitive and emotional aspects which presumably influence frame-shifting and conceptual blending, mental operations that underlie humour processing. The aim of the current study was to find distinctive groups of subjects with respect to black humour processing, intellectual capacities, mood disturbance and aggressiveness. A total of 156 adults rated black humour cartoons and conducted measurements of verbal and nonverbal intelligence, mood disturbance and aggressiveness. Cluster analysis yields three groups comprising following properties: (1) moderate black humour preference and moderate comprehension; average nonverbal and verbal intelligence; low mood disturbance and moderate aggressiveness; (2) low black humour preference and moderate comprehension; average nonverbal and verbal intelligence, high mood disturbance and high aggressiveness; and (3) high black humour preference and high comprehension; high nonverbal and verbal intelligence; no mood disturbance and low aggressiveness. Age and gender do not differ significantly, differences in education level can be found. Black humour preference and comprehension are positively associated with higher verbal and nonverbal intelligence as well as higher levels of education. Emotional instability and higher aggressiveness apparently lead to decreased levels of pleasure when dealing with black humour. These results support the hypothesis that humour processing involves cognitive as well as affective components and suggest that these variables influence the execution of frame-shifting and conceptual blending in the course of humour processing.
A mobile care system with alert mechanism.
Lee, Ren-Guey; Chen, Kuei-Chien; Hsiao, Chun-Chieh; Tseng, Chwan-Lu
2007-09-01
Hypertension and arrhythmia are chronic diseases, which can be effectively prevented and controlled only if the physiological parameters of the patient are constantly monitored, along with the full support of the health education and professional medical care. In this paper, a role-based intelligent mobile care system with alert mechanism in chronic care environment is proposed and implemented. The roles in our system include patients, physicians, nurses, and healthcare providers. Each of the roles represents a person that uses a mobile device such as a mobile phone to communicate with the server setup in the care center such that he or she can go around without restrictions. For commercial mobile phones with Bluetooth communication capability attached to chronic patients, we have developed physiological signal recognition algorithms that were implemented and built-in in the mobile phone without affecting its original communication functions. It is thus possible to integrate several front-end mobile care devices with Bluetooth communication capability to extract patients' various physiological parameters [such as blood pressure, pulse, saturation of haemoglobin (SpO2), and electrocardiogram (ECG)], to monitor multiple physiological signals without space limit, and to upload important or abnormal physiological information to healthcare center for storage and analysis or transmit the information to physicians and healthcare providers for further processing. Thus, the physiological signal extraction devices only have to deal with signal extraction and wireless transmission. Since they do not have to do signal processing, their form factor can be further reduced to reach the goal of microminiaturization and power saving. An alert management mechanism has been included in back-end healthcare center to initiate various strategies for automatic emergency alerts after receiving emergency messages or after automatically recognizing emergency messages. Within the time intervals in system setting, according to the medical history of a specific patient, our prototype system can inform various healthcare providers in sequence to provide healthcare service with their reply to ensure the accuracy of alert information and the completeness of early warning notification to further improve the healthcare quality. In the end, with the testing results and performance evaluation of our implemented system prototype, we conclude that it is possible to set up a complete intelligent healt care chain with mobile monitoring and healthcare service via the assistance of our system.
Design and implementation of green intelligent lights based on the ZigBee
NASA Astrophysics Data System (ADS)
Gan, Yong; Jia, Chunli; Zou, Dongyao; Yang, Jiajia; Guo, Qianqian
2013-03-01
By analysis of the low degree of intelligence of the traditional lighting control methods, the paper uses the singlechip microcomputer for the control core, and uses a pyroelectric infrared technology to detect the existence of the human body, light sensors to sense the light intensity; the interface uses infrared sensor module, photosensitive sensor module, relay module to transmit the signal, which based on ZigBee wireless network. The main function of the design is to realize that the lighting can intelligently adjust the brightness according to the indoor light intensity when people in door, and it can turn off the light when people left. The circuit and program design of this system is flexible, and the system achieves the effect of intelligent energy saving control.
DOT National Transportation Integrated Search
2002-10-01
The success of automation for intelligent transportation systems is ultimately contingent upon the Interface between the users (humans) and the system (ITS). The issues of variable message signs (VMS) and traffic signal device (TSD) design were studi...
A lunar base for SETI (Search for Extraterrestrial Intelligence)
NASA Technical Reports Server (NTRS)
Oliver, Bernard M.
1988-01-01
The possibilities of using lanar based radio antennas in search of intelligent extraterrestrial communications is explored. The proposed NASA search will have two search modes: (1) An all sky survey covering the frequency range from 1 to 10 GHz; and (2) A high sensitivity targeted search listening for signals from the approx. 800 solar type stars within 80 light years of the Sun, and covering 1 to 3 GHz.
Marine Corps Intelligence for War as It Really Is
1991-06-01
had a strong psychological effect on the Lebanese civilians. (Wade, 1959, p. 15) By 31 July, Chehab was elected President of Lebanon and the U.S. Army...Dominican Republic to exploit what signal intelligence (SIGINT) was possible. There was a great need for exten~sive Civil Affairs and Psychological ...problem. * The Marine Corps needed a Civil Affairs and Psychological Operations capability to deal with the political-economic-sociological aspects of
Exploring the Analytical Processes of Intelligence Analysts
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chin, George; Kuchar, Olga A.; Wolf, Katherine E.
We present an observational case study in which we investigate and analyze the analytical processes of intelligence analysts. Participating analysts in the study carry out two scenarios where they organize and triage information, conduct intelligence analysis, report results, and collaborate with one another. Through a combination of artifact analyses, group interviews, and participant observations, we explore the space and boundaries in which intelligence analysts work and operate. We also assess the implications of our findings on the use and application of relevant information technologies.
Improving patient access and streamlining processes through enterprise intelligence systems.
Dunn, Ronald L
2014-01-01
This article demonstrates how enterprise intelligence systems can be used to improve operational efficiency in hospitals. Enterprise intelligence systems mine raw data from disparate systems and transform the data into actionable information, which when used appropriately, support streamlined processes, optimize resources, and positively affect staff efficiency and the quality of patient care. Case studies on the implementation of McKesson Performance Visibility and Capacity Planner enterprise intelligence solutions at the Southlake Regional Health Centre and Lions Gate and Richmond Hospitals are provided.
The Medawar Lecture 2001 Knowledge for vision: vision for knowledge
Gregory, Richard L
2005-01-01
An evolutionary development of perception is suggested—from passive reception to active perception to explicit conception—earlier stages being largely retained and incorporated in later species. A key is innate and then individually learned knowledge, giving meaning to sensory signals. Inappropriate or misapplied knowledge produces rich cognitive phenomena of illusions, revealing normally hidden processes of vision, tentatively classified here in a ‘peeriodic table’. Phenomena of physiology are distinguished from phenomena of general rules and specific object knowledge. It is concluded that vision uses implicit knowledge, and provides knowledge for intelligent behaviour and for explicit conceptual understanding including science. PMID:16147519
Inference Engine in an Intelligent Ship Course-Keeping System
2017-01-01
The article presents an original design of an expert system, whose function is to automatically stabilize ship's course. The focus is put on the inference engine, a mechanism that consists of two functional components. One is responsible for the construction of state space regions, implemented on the basis of properly processed signals recorded by sensors from the input and output of an object. The other component is responsible for generating a control decision based on the knowledge obtained in the first module. The computing experiments described herein prove the effective and correct operation of the proposed system. PMID:29317859
FUNCTIONAL BIOMATERIALS: Design of Novel Biomaterials
NASA Astrophysics Data System (ADS)
Sakiyama-Elbert, Se; Hubbell, Ja
2001-08-01
The field of biomaterials has recently been focused on the design of intelligent materials. Toward this goal, materials have been developed that can provide specific bioactive signals to control the biological environment around them during the process of materials integration and wound healing. In addition, materials have been developed that can respond to changes in their environment, such as a change in pH or cell-associated enzymatic activity. In designing such novel biomaterials, researchers have sought not merely to create bio-inert materials, but rather materials that can respond to the cellular environment around them to improve device integration and tissue regeneration.
Artificial Intelligence--Applications in Education.
ERIC Educational Resources Information Center
Poirot, James L.; Norris, Cathleen A.
1987-01-01
This first in a projected series of five articles discusses artificial intelligence and its impact on education. Highlights include the history of artificial intelligence and the impact of microcomputers; learning processes; human factors and interfaces; computer assisted instruction and intelligent tutoring systems; logic programing; and expert…
NASA Astrophysics Data System (ADS)
Siddiqui, Aleem; Reinke, Charles; Shin, Heedeuk; Jarecki, Robert L.; Starbuck, Andrew L.; Rakich, Peter
2017-05-01
The performance of electronic systems for radio-frequency (RF) spectrum analysis is critical for agile radar and communications systems, ISR (intelligence, surveillance, and reconnaissance) operations in challenging electromagnetic (EM) environments, and EM-environment situational awareness. While considerable progress has been made in size, weight, and power (SWaP) and performance metrics in conventional RF technology platforms, fundamental limits make continued improvements increasingly difficult. Alternatively, we propose employing cascaded transduction processes in a chip-scale nano-optomechanical system (NOMS) to achieve a spectral sensor with exceptional signal-linearity, high dynamic range, narrow spectral resolution and ultra-fast sweep times. By leveraging the optimal capabilities of photons and phonons, the system we pursue in this work has performance metrics scalable well beyond the fundamental limitations inherent to all electronic systems. In our device architecture, information processing is performed on wide-bandwidth RF-modulated optical signals by photon-mediated phononic transduction of the modulation to the acoustical-domain for narrow-band filtering, and then back to the optical-domain by phonon-mediated phase modulation (the reverse process). Here, we rely on photonics to efficiently distribute signals for parallel processing, and on phononics for effective and flexible RF-frequency manipulation. This technology is used to create RF-filters that are insensitive to the optical wavelength, with wide center frequency bandwidth selectivity (1-100GHz), ultra-narrow filter bandwidth (1-100MHz), and high dynamic range (70dB), which we will present. Additionally, using this filter as a building block, we will discuss current results and progress toward demonstrating a multichannel-filter with a bandwidth of < 10MHz per channel, while minimizing cumulative optical/acoustic/optical transduced insertion-loss to ideally < 10dB. These proposed metric represent significant improvements over RF-platforms.
Real-time diagnostics for a reusable rocket engine
NASA Technical Reports Server (NTRS)
Guo, T. H.; Merrill, W.; Duyar, A.
1992-01-01
A hierarchical, decentralized diagnostic system is proposed for the Real-Time Diagnostic System component of the Intelligent Control System (ICS) for reusable rocket engines. The proposed diagnostic system has three layers of information processing: condition monitoring, fault mode detection, and expert system diagnostics. The condition monitoring layer is the first level of signal processing. Here, important features of the sensor data are extracted. These processed data are then used by the higher level fault mode detection layer to do preliminary diagnosis on potential faults at the component level. Because of the closely coupled nature of the rocket engine propulsion system components, it is expected that a given engine condition may trigger more than one fault mode detector. Expert knowledge is needed to resolve the conflicting reports from the various failure mode detectors. This is the function of the diagnostic expert layer. Here, the heuristic nature of this decision process makes it desirable to use an expert system approach. Implementation of the real-time diagnostic system described above requires a wide spectrum of information processing capability. Generally, in the condition monitoring layer, fast data processing is often needed for feature extraction and signal conditioning. This is usually followed by some detection logic to determine the selected faults on the component level. Three different techniques are used to attack different fault detection problems in the NASA LeRC ICS testbed simulation. The first technique employed is the neural network application for real-time sensor validation which includes failure detection, isolation, and accommodation. The second approach demonstrated is the model-based fault diagnosis system using on-line parameter identification. Besides these model based diagnostic schemes, there are still many failure modes which need to be diagnosed by the heuristic expert knowledge. The heuristic expert knowledge is implemented using a real-time expert system tool called G2 by Gensym Corp. Finally, the distributed diagnostic system requires another level of intelligence to oversee the fault mode reports generated by component fault detectors. The decision making at this level can best be done using a rule-based expert system. This level of expert knowledge is also implemented using G2.
Capturing and Modeling Domain Knowledge Using Natural Language Processing Techniques
2005-06-01
Intelligence Artificielle , France, May 2001, p. 109- 118 [Barrière, 2001] -----. “Investigating the Causal Relation in Informative Texts”. Terminology, 7:2...out of the flood of information, military have to create new ways of processing sensor and intelligence information, and of providing the results to...have to create new ways of processing sensor and intelligence information, and of providing the results to commanders who must take timely operational
Intelligent systems/software engineering methodology - A process to manage cost and risk
NASA Technical Reports Server (NTRS)
Friedlander, Carl; Lehrer, Nancy
1991-01-01
A systems development methodology is discussed that has been successfully applied to the construction of a number of intelligent systems. This methodology is a refinement of both evolutionary and spiral development methodologies. It is appropriate for development of intelligent systems. The application of advanced engineering methodology to the development of software products and intelligent systems is an important step toward supporting the transition of AI technology into aerospace applications. A description of the methodology and the process model from which it derives is given. Associated documents and tools are described which are used to manage the development process and record and report the emerging design.
Basic research on machinery fault diagnostics: Past, present, and future trends
NASA Astrophysics Data System (ADS)
Chen, Xuefeng; Wang, Shibin; Qiao, Baijie; Chen, Qiang
2018-06-01
Machinery fault diagnosis has progressed over the past decades with the evolution of machineries in terms of complexity and scale. High-value machineries require condition monitoring and fault diagnosis to guarantee their designed functions and performance throughout their lifetime. Research on machinery Fault diagnostics has grown rapidly in recent years. This paper attempts to summarize and review the recent R&D trends in the basic research field of machinery fault diagnosis in terms of four main aspects: Fault mechanism, sensor technique and signal acquisition, signal processing, and intelligent diagnostics. The review discusses the special contributions of Chinese scholars to machinery fault diagnostics. On the basis of the review of basic theory of machinery fault diagnosis and its practical applications in engineering, the paper concludes with a brief discussion on the future trends and challenges in machinery fault diagnosis.
An Intrinsically Digital Amplification Scheme for Hearing Aids
NASA Astrophysics Data System (ADS)
Blamey, Peter J.; Macfarlane, David S.; Steele, Brenton R.
2005-12-01
Results for linear and wide-dynamic range compression were compared with a new 64-channel digital amplification strategy in three separate studies. The new strategy addresses the requirements of the hearing aid user with efficient computations on an open-platform digital signal processor (DSP). The new amplification strategy is not modeled on prior analog strategies like compression and linear amplification, but uses statistical analysis of the signal to optimize the output dynamic range in each frequency band independently. Using the open-platform DSP processor also provided the opportunity for blind trial comparisons of the different processing schemes in BTE and ITE devices of a high commercial standard. The speech perception scores and questionnaire results show that it is possible to provide improved audibility for sound in many narrow frequency bands while simultaneously improving comfort, speech intelligibility in noise, and sound quality.
Strong genetic overlap between executive functions and intelligence.
Engelhardt, Laura E; Mann, Frank D; Briley, Daniel A; Church, Jessica A; Harden, K Paige; Tucker-Drob, Elliot M
2016-09-01
Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic influences on EFs are very high, even in middle childhood, but the extent to which these genetic influences overlap with those on intelligence is unclear. We examined genetic and environmental overlap between EFs and intelligence in a racially and socioeconomically diverse sample of 811 twins ages 7 to 15 years (M = 10.91, SD = 1.74) from the Texas Twin Project. A general EF factor representing variance common to inhibition, switching, working memory, and updating domains accounted for substantial proportions of variance in intelligence, primarily via a genetic pathway. General EF continued to have a strong, genetically mediated association with intelligence even after controlling for processing speed. Residual variation in general intelligence was influenced only by shared and nonshared environmental factors, and there remained no genetic variance in general intelligence that was unique of EF. Genetic variance independent of EF did remain, however, in a more specific perceptual reasoning ability. These results provide evidence that genetic influences on general intelligence are highly overlapping with those on EF. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
ERIC Educational Resources Information Center
Conway, Andrew R. A.; Cowan, Nelsin; Bunting, Michael F.; Therriault, David J.; Minkoff, Scott R. B.
2002-01-01
Studied the interrelationships among general fluid intelligence, short-term memory capacity, working memory capacity, and processing speed in 120 young adults and used structural equation modeling to determine the best predictor of general fluid intelligence. Results suggest that working memory capacity, but not short-term memory capacity or…
ERIC Educational Resources Information Center
McNicholas, Patrick J.; Floyd, Randy G.
2017-01-01
The Reynolds Intellectual Assessment Scales, Second Edition (RIAS-2; Reynolds & Kamphaus, 2015) is an intelligence test for those aged 3 to 94 years. It contains eight subtests designed to assess general intelligence, verbal and nonverbal intelligence, memory, and processing speed. The two subtests targeting processing speed are new to the…
Energy-efficient digital and wireless IC design for wireless smart sensing
NASA Astrophysics Data System (ADS)
Zhou, Jun; Huang, Xiongchuan; Wang, Chao; Tae-Hyoung Kim, Tony; Lian, Yong
2017-10-01
Wireless smart sensing is now widely used in various applications such as health monitoring and structural monitoring. In conventional wireless sensor nodes, significant power is consumed in wirelessly transmitting the raw data. Smart sensing adds local intelligence to the sensor node and reduces the amount of wireless data transmission via on-node digital signal processing. While the total power consumption is reduced compared to conventional wireless sensing, the power consumption of the digital processing becomes as dominant as wireless data transmission. This paper reviews the state-of-the-art energy-efficient digital and wireless IC design techniques for reducing the power consumption of the wireless smart sensor node to prolong battery life and enable self-powered applications.
NASA Astrophysics Data System (ADS)
Evans, Garrett Nolan
In this work, I present two projects that both contribute to the aim of discovering how intelligence manifests in the brain. The first project is a method for analyzing recorded neural signals, which takes the form of a convolution-based metric on neural membrane potential recordings. Relying only on integral and algebraic operations, the metric compares the timing and number of spikes within recordings as well as the recordings' subthreshold features: summarizing differences in these with a single "distance" between the recordings. Like van Rossum's (2001) metric for spike trains, the metric is based on a convolution operation that it performs on the input data. The kernel used for the convolution is carefully chosen such that it produces a desirable frequency space response and, unlike van Rossum's kernel, causes the metric to be first order both in differences between nearby spike times and in differences between same-time membrane potential values: an important trait. The second project is a combinatorial syntax method for connectionist semantic network encoding. Combinatorial syntax has been a point on which those who support a symbol-processing view of intelligent processing and those who favor a connectionist view have had difficulty seeing eye-to-eye. Symbol-processing theorists have persuasively argued that combinatorial syntax is necessary for certain intelligent mental operations, such as reasoning by analogy. Connectionists have focused on the versatility and adaptability offered by self-organizing networks of simple processing units. With this project, I show that there is a way to reconcile the two perspectives and to ascribe a combinatorial syntax to a connectionist network. The critical principle is to interpret nodes, or units, in the connectionist network as bound integrations of the interpretations for nodes that they share links with. Nodes need not correspond exactly to neurons and may correspond instead to distributed sets, or assemblies, of neurons.
Combined analysis of cortical (EEG) and nerve stump signals improves robotic hand control.
Tombini, Mario; Rigosa, Jacopo; Zappasodi, Filippo; Porcaro, Camillo; Citi, Luca; Carpaneto, Jacopo; Rossini, Paolo Maria; Micera, Silvestro
2012-01-01
Interfacing an amputee's upper-extremity stump nerves to control a robotic hand requires training of the individual and algorithms to process interactions between cortical and peripheral signals. To evaluate for the first time whether EEG-driven analysis of peripheral neural signals as an amputee practices could improve the classification of motor commands. Four thin-film longitudinal intrafascicular electrodes (tf-LIFEs-4) were implanted in the median and ulnar nerves of the stump in the distal upper arm for 4 weeks. Artificial intelligence classifiers were implemented to analyze LIFE signals recorded while the participant tried to perform 3 different hand and finger movements as pictures representing these tasks were randomly presented on a screen. In the final week, the participant was trained to perform the same movements with a robotic hand prosthesis through modulation of tf-LIFE-4 signals. To improve the classification performance, an event-related desynchronization/synchronization (ERD/ERS) procedure was applied to EEG data to identify the exact timing of each motor command. Real-time control of neural (motor) output was achieved by the participant. By focusing electroneurographic (ENG) signal analysis in an EEG-driven time window, movement classification performance improved. After training, the participant regained normal modulation of background rhythms for movement preparation (α/β band desynchronization) in the sensorimotor area contralateral to the missing limb. Moreover, coherence analysis found a restored α band synchronization of Rolandic area with frontal and parietal ipsilateral regions, similar to that observed in the opposite hemisphere for movement of the intact hand. Of note, phantom limb pain (PLP) resolved for several months. Combining information from both cortical (EEG) and stump nerve (ENG) signals improved the classification performance compared with tf-LIFE signals processing alone; training led to cortical reorganization and mitigation of PLP.
International law implications of the detection of extraterrestrial intelligent signals
NASA Astrophysics Data System (ADS)
Kopal, Vladimir
This paper first considers whether the present law of outer space, as it has been enshrined in five United Nations treaties and other legal documents concerning outer space, provides a satisfactory basis for SETI/CETI activities. In the author's opinion, these activities may serve "the common interest of all mankind in the progress of the exploration and use of outer space for peaceful purposes," as recognized in the 1967 Outer Space Treaty. The use of the radio frequency spectrum for SETI/CETI purposes should be in conformity with the legal principles governing this valuable natural resource, as expressed in the International Telecommunication Convention and related documents, and with allocations of the relevant segments of the spectrum by the competent bodies of the International Telecommunication Union. In the second part the author examines the impact that the detection of extraterrestrial intelligent signals may have on the present body of space law. A possible role for the United Nations in this respect is also explored and a timely interest of the world body in discussing questions relating to this subject is recommended. Consideration of these questions could become a tool helping to concentrate the attention of the world community on problems of common concern and thus to strengthen international cooperation. However, the author believes that a law-making process that would aim at elaborating a special regulation of activities in this field would be premature at this stage. It should be initiated only when the boundary between possibilities and realities is crossed. Finally, the paper outlines some likely transformation in our space law thinking that would be the consequence of the detection of extraterrestrial intelligent signals. Elaboration of the principles and norms to govern relations between the international community of our own planet and other intelligent communities in the universe would add a new dimension to the present body of outer space law. At the same time this new approach might exercise a beneficial influence on relations between nations and peoples of the planet Earth. Considerations of legal implications of new phenomena in the world for our life are usually made from two points of view that reflect two basic levels of our thinking. First, we try to establish what exists and then decide what could or should be done. This two-fold approach, known in legal terminology as de lege lata and de lege ferenda, can also be used in the consideration of our present problem, though it seems to be still a rather extraordinary subject.
The windows of SETI--frequency and time in the search for extraterrestrial intelligence.
Oliver, B M
1987-01-01
On Earth intelligent life evolved as a natural consequence of the events set in motion when the planet formed over 4 billion years ago. Since chemical evolution and solar-system formation appear to be occurring throughout the universe, we theorize that our universe may be rich with planets populated by intelligent beings who, like us, can search for evidence of other technological civilizations. Terrestrial civilization now has this capability. But if we do not begin the search soon, we'll lose the opportunity to do it from Earth as interfering signals of Earthly origin rapidly close the microwave window.
The design of electric vehicle intelligent charger
NASA Astrophysics Data System (ADS)
Xu, Yangyang; Wang, Ying
2018-05-01
As the situation of the lack of energy and environment pollution deteriorates rapidly, electric vehicle, a new type of traffic tool, is being researched worldwide. As the core components of electric vehicle, the battery and charger's performance play an important roles in the quality of electric vehicle. So the design of the Electric Vehicle Intelligent Charger based on language-C is designed in this paper. The hardware system is used to produce the input signals of Electric Vehicle Intelligent Charger. The software system adopts the language-C software as development environment. The design can accomplish the test of the parametric such as voltage-current and temperature.
Lin, Chin-Teng; Chang, Kuan-Cheng; Lin, Chun-Ling; Chiang, Chia-Cheng; Lu, Shao-Wei; Chang, Shih-Sheng; Lin, Bor-Shyh; Liang, Hsin-Yueh; Chen, Ray-Jade; Lee, Yuan-Teh; Ko, Li-Wei
2010-05-01
This study presents a novel wireless, ambulatory, real-time, and autoalarm intelligent telecardiology system to improve healthcare for cardiovascular disease, which is one of the most prevalent and costly health problems in the world. This system consists of a lightweight and power-saving wireless ECG device equipped with a built-in automatic warning expert system. This device is connected to a mobile and ubiquitous real-time display platform. The acquired ECG signals are instantaneously transmitted to mobile devices, such as netbooks or mobile phones through Bluetooth, and then, processed by the expert system. An alert signal is sent to the remote database server, which can be accessed by an Internet browser, once an abnormal ECG is detected. The current version of the expert system can identify five types of abnormal cardiac rhythms in real-time, including sinus tachycardia, sinus bradycardia, wide QRS complex, atrial fibrillation (AF), and cardiac asystole, which is very important for both the subjects who are being monitored and the healthcare personnel tracking cardiac-rhythm disorders. The proposed system also activates an emergency medical alarm system when problems occur. Clinical testing reveals that the proposed system is approximately 94% accurate, with high sensitivity, specificity, and positive prediction rates for ten normal subjects and 20 AF patients. We believe that in the future a business-card-like ECG device, accompanied with a mobile phone, can make universal cardiac protection service possible.
Aircraft noise and speech intelligibility in an outdoor living space.
Alvarsson, Jesper J; Nordström, Henrik; Lundén, Peter; Nilsson, Mats E
2014-06-01
Studies of effects on speech intelligibility from aircraft noise in outdoor places are currently lacking. To explore these effects, first-order ambisonic recordings of aircraft noise were reproduced outdoors in a pergola. The average background level was 47 dB LA eq. Lists of phonetically balanced words (LAS max,word = 54 dB) were reproduced simultaneously with aircraft passage noise (LAS max,noise = 72-84 dB). Twenty individually tested listeners wrote down each presented word while seated in the pergola. The main results were (i) aircraft noise negatively affects speech intelligibility at sound pressure levels that exceed those of the speech sound (signal-to-noise ratio, S/N < 0), and (ii) the simple A-weighted S/N ratio was nearly as good an indicator of speech intelligibility as were two more advanced models, the Speech Intelligibility Index and Glasberg and Moore's [J. Audio Eng. Soc. 53, 906-918 (2005)] partial loudness model. This suggests that any of these indicators is applicable for predicting effects of aircraft noise on speech intelligibility outdoors.
NASA Astrophysics Data System (ADS)
Ryan, Timothy James
The effects of multiple arrivals on the intelligibility of speech produced by live-sound reinforcement systems are examined. The intent is to determine if correlations exist between the manipulation of sound system optimization parameters and the subjective attribute speech intelligibility. Given the number, and wide range, of variables involved, this exploratory research project attempts to narrow the focus of further studies. Investigated variables are delay time between signals arriving from multiple elements of a loudspeaker array, array type and geometry and the two-way interactions of speech-to-noise ratio and array geometry with delay time. Intelligibility scores were obtained through subjective evaluation of binaural recordings, reproduced via headphone, using the Modified Rhyme Test. These word-score results are compared with objective measurements of Speech Transmission Index (STI). Results indicate that both variables, delay time and array geometry, have significant effects on intelligibility. Additionally, it is seen that all three of the possible two-way interactions have significant effects. Results further reveal that the STI measurement method overestimates the decrease in intelligibility due to short delay times between multiple arrivals.
Intelligent methods for the process parameter determination of plastic injection molding
NASA Astrophysics Data System (ADS)
Gao, Huang; Zhang, Yun; Zhou, Xundao; Li, Dequn
2018-03-01
Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories: Case-based reasoning methods, expert system- based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.
2016-01-01
People with hearing impairment are thought to rely heavily on context to compensate for reduced audibility. Here, we explore the resulting cost of this compensatory behavior, in terms of effort and the efficiency of ongoing predictive language processing. The listening task featured predictable or unpredictable sentences, and participants included people with cochlear implants as well as people with normal hearing who heard full-spectrum/unprocessed or vocoded speech. The crucial metric was the growth of the pupillary response and the reduction of this response for predictable versus unpredictable sentences, which would suggest reduced cognitive load resulting from predictive processing. Semantic context led to rapid reduction of listening effort for people with normal hearing; the reductions were observed well before the offset of the stimuli. Effort reduction was slightly delayed for people with cochlear implants and considerably more delayed for normal-hearing listeners exposed to spectrally degraded noise-vocoded signals; this pattern of results was maintained even when intelligibility was perfect. Results suggest that speed of sentence processing can still be disrupted, and exertion of effort can be elevated, even when intelligibility remains high. We discuss implications for experimental and clinical assessment of speech recognition, in which good performance can arise because of cognitive processes that occur after a stimulus, during a period of silence. Because silent gaps are not common in continuous flowing speech, the cognitive/linguistic restorative processes observed after sentences in such studies might not be available to listeners in everyday conversations, meaning that speech recognition in conventional tests might overestimate sentence-processing capability. PMID:27698260
Pathways of Learning: Teaching Students and Parents about Multiple Intelligences.
ERIC Educational Resources Information Center
Lazear, David
This book is concerned with reinventing the learning process from a multiple intelligences perspective and urges explicitly teaching students about multiple intelligences to further their metacognitive understanding. The multiple-intelligence-based curriculum is intended to interface with the regular academic curriculum. An introductory chapter…
Emotional Intelligence Tests: Potential Impacts on the Hiring Process for Accounting Students
ERIC Educational Resources Information Center
Nicholls, Shane; Wegener, Matt; Bay, Darlene; Cook, Gail Lynn
2012-01-01
Emotional intelligence is increasingly recognized as being important for professional career success. Skills related to emotional intelligence (e.g. organizational commitment, public speaking, teamwork, and leadership) are considered essential. Human resource professionals have begun including tests of emotional intelligence (EI) in job applicant…
On the use of multi-agent systems for the monitoring of industrial systems
NASA Astrophysics Data System (ADS)
Rezki, Nafissa; Kazar, Okba; Mouss, Leila Hayet; Kahloul, Laid; Rezki, Djamil
2016-03-01
The objective of the current paper is to present an intelligent system for complex process monitoring, based on artificial intelligence technologies. This system aims to realize with success all the complex process monitoring tasks that are: detection, diagnosis, identification and reconfiguration. For this purpose, the development of a multi-agent system that combines multiple intelligences such as: multivariate control charts, neural networks, Bayesian networks and expert systems has became a necessity. The proposed system is evaluated in the monitoring of the complex process Tennessee Eastman process.
Interdisciplinary Study on Artificial Intelligence.
1983-07-01
systems, uiophysics of information processing, cognitive science, and traditional artificial intelligence. The objective behi d this objective was to...information processing, cognitive science, and traditional * artificial intelligence. The objective behind this objective was to provide a vehicle for reviewing...Another departure from ’classical’ neurodynamics must be sought in the strong coupling between the micro and macroscopic scales. No other physical mechanism
Radio SETI Observations of the Anomalous Star KIC 8462852
NASA Astrophysics Data System (ADS)
Harp, G. R.; Richards, Jon; Shostak, Seth; Tarter, J. C.; Vakoch, Douglas A.; Munson, Chris
2016-07-01
We report on a search for the presence of signals from extraterrestrial intelligence in the direction of the star system KIC 8462852. Observations were made at radio frequencies between 1 and 10 GHz using the Allen Telescope Array. No narrowband radio signals were found at a level of 180-300 Jy in a 1 Hz channel, or medium band signals above 10 Jy in a 100 kHz channel.
Clewett, David V; Lee, Tae-Ho; Greening, Steven; Ponzio, Allison; Margalit, Eshed; Mather, Mara
2016-01-01
Leading a mentally stimulating life may build up a reserve of neural and mental resources that preserve cognitive abilities in late life. Recent autopsy evidence links neuronal density in the locus coeruleus (LC), the brain's main source of norepinephrine, to slower cognitive decline before death, inspiring the idea that the noradrenergic system is a key component of reserve (Robertson, I. H. 2013. A noradrenergic theory of cognitive reserve: implications for Alzheimer's disease. Neurobiol. Aging. 34, 298-308). Here, we tested this hypothesis using neuromelanin-sensitive magnetic resonance imaging to visualize and measure LC signal intensity in healthy younger and older adults. Established proxies of reserve, including education, occupational attainment, and verbal intelligence, were linearly correlated with LC signal intensity in both age groups. Results indicated that LC signal intensity was significantly higher in older than younger adults and significantly lower in women than in men. Consistent with the LC-reserve hypothesis, both verbal intelligence and a composite reserve score were positively associated with LC signal intensity in older adults. LC signal intensity was also more strongly associated with attentional shifting ability in older adults with lower cognitive reserve. Together these findings link in vivo estimates of LC neuromelanin signal intensity to cognitive reserve in normal aging. Copyright © 2016 Elsevier Inc. All rights reserved.
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.
Infant Perception of Atypical Speech Signals
ERIC Educational Resources Information Center
Vouloumanos, Athena; Gelfand, Hanna M.
2013-01-01
The ability to decode atypical and degraded speech signals as intelligible is a hallmark of speech perception. Human adults can perceive sounds as speech even when they are generated by a variety of nonhuman sources including computers and parrots. We examined how infants perceive the speech-like vocalizations of a parrot. Further, we examined how…