WorldWideScience

Sample records for neural reference space

  1. Iodine frequency references for space

    International Nuclear Information System (INIS)

    Schuldt, Thilo; Braxmaier, Claus; Döringshoff, Klaus; Peters, Achim; Oswald, Markus; Johann, Ulrich

    2017-01-01

    Optical frequency references are a key element for the realization of future space missions. They are needed for missions related to tests of fundamental physics, gravitational wave detection, Earth observation and navigation and ranging. In missions such as GRACE follow-on or LISA the optical frequency reference is used as light source for high-sensitivity inter-satellite distance metrology. While cavity-based systems are current baseline e.g. for LISA, frequency stabilization on a hyperfine transition in molecular iodine near 532 nm is a promising alternative. Due to its absolute frequency, iodine standards crucially simplify the initial spacecraft acquisition procedures. Current setups fulfill the GRACE-FO and LISA frequency stability requirements and are realized near Engineering Model level. We present the current status of our developments on Elegant Breadboard (EBB) and Engineering Model (EM) level taking into account specific design criteria for space compatibility such as compactness (size iodine spectroscopy EM: 38 × 18 × 10 cm 3 ) and robustness. Both setups achieved similar frequency stabilities of ∼ 1 · 10 −14 at an integration time of 1 s and below 5 · 10 −15 at integration times between 10 s and 1000 s. Furthermore, we present an even more compact design currently developed for a sounding rocket mission with launch in 2017. (paper)

  2. Space-Time Reference Systems

    CERN Document Server

    Soffel, Michael

    2013-01-01

    The high accuracy of modern astronomical spatial-temporal reference systems has made them considerably complex. This book offers a comprehensive overview of such systems. It begins with a discussion of ‘The Problem of Time’, including recent developments in the art of clock making (e.g., optical clocks) and various time scales. The authors address  the definitions and realization of spatial coordinates by reference to remote celestial objects such as quasars. After an extensive treatment of classical equinox-based coordinates, new paradigms for setting up a celestial reference system are introduced that no longer refer to the translational and rotational motion of the Earth. The role of relativity in the definition and realization of such systems is clarified. The topics presented in this book are complemented by exercises (with solutions). The authors offer a series of files, written in Maple, a standard computer algebra system, to help readers get a feel for the various models and orders of magnitude. ...

  3. Teaching methodology for modeling reference evapotranspiration with artificial neural networks

    OpenAIRE

    Martí, Pau; Pulido Calvo, Inmaculada; Gutiérrez Estrada, Juan Carlos

    2015-01-01

    [EN] Artificial neural networks are a robust alternative to conventional models for estimating different targets in irrigation engineering, among others, reference evapotranspiration, a key variable for estimating crop water requirements. This paper presents a didactic methodology for introducing students in the application of artificial neural networks for reference evapotranspiration estimation using MatLab c . Apart from learning a specific application of this software wi...

  4. Neural network-based model reference adaptive control system.

    Science.gov (United States)

    Patino, H D; Liu, D

    2000-01-01

    In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.

  5. A Reference Architecture for Space Information Management

    Science.gov (United States)

    Mattmann, Chris A.; Crichton, Daniel J.; Hughes, J. Steven; Ramirez, Paul M.; Berrios, Daniel C.

    2006-01-01

    We describe a reference architecture for space information management systems that elegantly overcomes the rigid design of common information systems in many domains. The reference architecture consists of a set of flexible, reusable, independent models and software components that function in unison, but remain separately managed entities. The main guiding principle of the reference architecture is to separate the various models of information (e.g., data, metadata, etc.) from implemented system code, allowing each to evolve independently. System modularity, systems interoperability, and dynamic evolution of information system components are the primary benefits of the design of the architecture. The architecture requires the use of information models that are substantially more advanced than those used by the vast majority of information systems. These models are more expressive and can be more easily modularized, distributed and maintained than simpler models e.g., configuration files and data dictionaries. Our current work focuses on formalizing the architecture within a CCSDS Green Book and evaluating the architecture within the context of the C3I initiative.

  6. Neural redundancy applied to the parity space for signal validation

    International Nuclear Information System (INIS)

    Mol, Antonio Carlos de Abreu; Pereira, Claudio Marcio Nascimento Abreu; Martinez, Aquilino Senra

    2005-01-01

    The objective of signal validation is to provide more reliable information from the plant sensor data The method presented in this work introduces the concept of neural redundancy and applies it to the space parity method [1] to overcome an inherent deficiency of this method - the determination of the best estimative of the redundant measures when they are inconsistent. The concept of neural redundancy consists on the calculation of a redundancy through neural networks based on the time series of the own state variable. Therefore, neural networks, dynamically trained with the time series, will estimate the current value of the own measure, which will be used as referee of the redundant measures in the parity space. For this purpose the neural network should have the capacity to supply the neural redundancy in real time and with maximum error corresponding to the group deviation. The historical series should be enough to allow the estimate of the next value, during transients and at the same time, it should be optimized to facilitate the retraining of the neural network to each acquisition. In order to have the capacity to reproduce the tendency of the time series even under accident condition, the dynamic training of the neural network privileges the recent points of the time series. The tests accomplished with simulated data of a nuclear plant, demonstrated that this method applied on the parity space method improves the signal validation process. (author)

  7. Neural redundancy applied to the parity space for signal validation

    Energy Technology Data Exchange (ETDEWEB)

    Mol, Antonio Carlos de Abreu; Pereira, Claudio Marcio Nascimento Abreu [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil)]. E-mail: cmnap@ien.gov.br; Martinez, Aquilino Senra [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia]. E-mail: aquilino@lmp.br

    2005-07-01

    The objective of signal validation is to provide more reliable information from the plant sensor data The method presented in this work introduces the concept of neural redundancy and applies it to the space parity method [1] to overcome an inherent deficiency of this method - the determination of the best estimative of the redundant measures when they are inconsistent. The concept of neural redundancy consists on the calculation of a redundancy through neural networks based on the time series of the own state variable. Therefore, neural networks, dynamically trained with the time series, will estimate the current value of the own measure, which will be used as referee of the redundant measures in the parity space. For this purpose the neural network should have the capacity to supply the neural redundancy in real time and with maximum error corresponding to the group deviation. The historical series should be enough to allow the estimate of the next value, during transients and at the same time, it should be optimized to facilitate the retraining of the neural network to each acquisition. In order to have the capacity to reproduce the tendency of the time series even under accident condition, the dynamic training of the neural network privileges the recent points of the time series. The tests accomplished with simulated data of a nuclear plant, demonstrated that this method applied on the parity space method improves the signal validation process. (author)

  8. Reference nuclear data for space technology

    International Nuclear Information System (INIS)

    Burrows, T.W.; Holden, N.E.; Pearlstein, S.

    1977-01-01

    Specialized bibliographic searches, data compilations, and data evaluations help the basic and applied research scientist in his work. The National Nuclear Data Center (NNDC) collates and analyzes nuclear physics information, and is concerned with the timely production and revision of reference nuclear data. A frequently revised reference data base in computerized form has the advantage of large quantities of data available without publication delays. The information normally handled by coordinated efforts of NNDC consists of neutron, charged-particle, nuclear structure, radioactive decay, and photonuclear data. 2 figures

  9. Discrete Optimization in Chemical Space Reference Manual

    Science.gov (United States)

    2012-10-01

    includes instructions on setting up constrained optimizations of substitutional frameworks and the full application programming interface ( API ) necessary...space size • bool space size computed • ulong bits • bool bits computed • string Nam 4.26.1 Detailed Description This class provides the API that...1, 0) 1102 (O, 0, 1.4, -3, 120, -2, 180) 1103 (C, 1, 1.5, 0, 120, -3, -30(150)) 1104 (H, 2, 1.1, 1, 109.47, 0,180) 1105 (H, 2, 1.1, 1, 109.47, 3, 120

  10. Efficient Neural Network Modeling for Flight and Space Dynamics Simulation

    Directory of Open Access Journals (Sweden)

    Ayman Hamdy Kassem

    2011-01-01

    Full Text Available This paper represents an efficient technique for neural network modeling of flight and space dynamics simulation. The technique will free the neural network designer from guessing the size and structure for the required neural network model and will help to minimize the number of neurons. For linear flight/space dynamics systems, the technique can find the network weights and biases directly by solving a system of linear equations without the need for training. Nonlinear flight dynamic systems can be easily modeled by training its linearized models keeping the same network structure. The training is fast, as it uses the linear system knowledge to speed up the training process. The technique is tested on different flight/space dynamic models and showed promising results.

  11. Space Science Reference Guide, 2nd Edition

    Science.gov (United States)

    Dotson, Renee (Editor)

    2003-01-01

    This Edition contains the following reports: GRACE: Gravity Recovery and Climate Experiment; Impact Craters in the Solar System; 1997 Apparition of Comet Hale-Bopp Historical Comet Observations; Baby Stars in Orion Solve Solar System Mystery; The Center of the Galaxy; The First Rock in the Solar System; Fun Times with Cosmic Rays; The Gamma-Ray Burst Next Door; The Genesis Mission: An Overview; The Genesis Solar Wind Sample Return Mission; How to Build a Supermassive Black Hole; Journey to the Center of a Neutron Star; Kepler's Laws of Planetary Motion; The Kuiper Belt and Oort Cloud ; Mapping the Baby Universe; More Hidden Black Hole Dangers; A Polarized Universe; Presolar Grains of Star Dust: Astronomy Studied with Microscopes; Ring Around the Black Hole; Searching Antarctic Ice for Meteorites; The Sun; Astrobiology: The Search for Life in the Universe; Europa and Titan: Oceans in the Outer Solar System?; Rules for Identifying Ancient Life; Inspire ; Remote Sensing; What is the Electromagnetic Spectrum? What is Infrared? How was the Infrared Discovered?; Brief History of Gyroscopes ; Genesis Discovery Mission: Science Canister Processing at JSC; Genesis Solar-Wind Sample Return Mission: The Materials ; ICESat: Ice, Cloud, and Land Elevation Satellite ICESat: Ice, Cloud, and Land; Elevation Satellite ICESat: Ice, Cloud, and Land Elevation Satellite ICESat: Ice, Cloud, and Land Elevation Satellite ICESat: Ice, Cloud, and Land Elevation Satellite Measuring Temperature Reading; The Optical Telescope ; Space Instruments General Considerations; Damage by Impact: The Case at Meteor Crater, Arizona; Mercury Unveiled; New Data, New Ideas, and Lively Debate about Mercury; Origin of the Earth and Moon; Space Weather: The Invisible Foe; Uranus, Neptune, and the Mountains of the Moon; Dirty Ice on Mars; For a Cup of Water on Mars; Life on Mars?; The Martian Interior; Meteorites from Mars, Rocks from Canada; Organic Compounds in Martian Meteorites May be Terrestrial

  12. Neural network based satellite tracking for deep space applications

    Science.gov (United States)

    Amoozegar, F.; Ruggier, C.

    2003-01-01

    The objective of this paper is to provide a survey of neural network trends as applied to the tracking of spacecrafts in deep space at Ka-band under various weather conditions and examine the trade-off between tracing accuracy and communication link performance.

  13. The neural correlates of reference to the past

    Directory of Open Access Journals (Sweden)

    Laura S. Bos

    2014-04-01

    Analysis (see Figure 1 showed greater BOLD signal change for both types of past over non-past time-reference bilaterally frontal—the SMA and frontal superior medial gyrus. We ascribe this to increased difficulty in selecting past time-reference inflection, hence, discourse linking. We found significantly increased LIFG activation for simple past over simple present, but not for periphrastic past over future (see Figure 1C. LIFG might be taxed for past tense inflection, but not past time-reference specifically. Although periphrastic past and future differ in time-reference, both verb clusters have a present tense auxiliary. Our results align with a fundamental difference between past and non-past time-reference, and are in accordance with past time-reference processing difficulties of aphasic individuals.

  14. A First Look at the Upcoming SISO Space Reference FOM

    Science.gov (United States)

    Mueller, Bjorn; Crues, Edwin Z.; Dexter, Dan; Garro, Alfredo; Skuratovskiy, Anton; Vankov, Alexander

    2016-01-01

    Spaceflight is difficult, dangerous and expensive; human spaceflight even more so. In order to mitigate some of the danger and expense, professionals in the space domain have relied, and continue to rely, on computer simulation. Simulation is used at every level including concept, design, analysis, construction, testing, training and ultimately flight. As space systems have grown more complex, new simulation technologies have been developed, adopted and applied. Distributed simulation is one those technologies. Distributed simulation provides a base technology for segmenting these complex space systems into smaller, and usually simpler, component systems or subsystems. This segmentation also supports the separation of responsibilities between participating organizations. This segmentation is particularly useful for complex space systems like the International Space Station (ISS), which is composed of many elements from many nations along with visiting vehicles from many nations. This is likely to be the case for future human space exploration activities. Over the years, a number of distributed simulations have been built within the space domain. While many use the High Level Architecture (HLA) to provide the infrastructure for interoperability, HLA without a Federation Object Model (FOM) is insufficient by itself to insure interoperability. As a result, the Simulation Interoperability Standards Organization (SISO) is developing a Space Reference FOM. The Space Reference FOM Product Development Group is composed of members from several countries. They contribute experiences from projects within NASA, ESA and other organizations and represent government, academia and industry. The initial version of the Space Reference FOM is focusing on time and space and will provide the following: (i) a flexible positioning system using reference frames for arbitrary bodies in space, (ii) a naming conventions for well-known reference frames, (iii) definitions of common time scales

  15. A reference model for space data system interconnection services

    Science.gov (United States)

    Pietras, John; Theis, Gerhard

    1993-01-01

    The widespread adoption of standard packet-based data communication protocols and services for spaceflight missions provides the foundation for other standard space data handling services. These space data handling services can be defined as increasingly sophisticated processing of data or information received from lower-level services, using a layering approach made famous in the International Organization for Standardization (ISO) Open System Interconnection Reference Model (OSI-RM). The Space Data System Interconnection Reference Model (SDSI-RM) incorporates the conventions of the OSIRM to provide a framework within which a complete set of space data handling services can be defined. The use of the SDSI-RM is illustrated through its application to data handling services and protocols that have been defined by, or are under consideration by, the Consultative Committee for Space Data Systems (CCSDS).

  16. Perception of space by multiple intrinsic frames of reference.

    Directory of Open Access Journals (Sweden)

    Yanlong Sun

    Full Text Available It has been documented that when memorizing a physical space, the person's mental representation of that space is biased with distortion and segmentation. Two experiments reported here suggest that distortion and segmentation arise due to a hierarchical organization of the spatial representation. The spatial relations associated with salient landmarks are more strongly encoded and easier to recall than those associated with non-salient landmarks. In the presence of multiple salient landmarks, multiple intrinsic frames of reference are formed and spatial relations are anchored to each individual frame of reference. Multiple such representations may co-exist and interactively determine a person's spatial performance.

  17. Practical Application of Neural Networks in State Space Control

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon

    the networks, although some modifications are needed for the method to apply to the multilayer perceptron network. In connection with the multilayer perceptron networks it is also pointed out how instantaneous, sample-by-sample linearized state space models can be extracted from a trained network, thus opening......In the present thesis we address some problems in discrete-time state space control of nonlinear dynamical systems and attempt to solve them using generic nonlinear models based on artificial neural networks. The main aim of the work is to examine how well such control algorithms perform when...... theoretic notions followed by a detailed description of the topology, neuron functions and learning rules of the two types of neural networks treated in the thesis, the multilayer perceptron and the neurofuzzy networks. In both cases, a Least Squares second-order gradient method is used to train...

  18. Face-infringement space: the frame of reference of the ventral intraparietal area.

    Science.gov (United States)

    McCollum, Gin; Klam, François; Graf, Werner

    2012-07-01

    Experimental studies have shown that responses of ventral intraparietal area (VIP) neurons specialize in head movements and the environment near the head. VIP neurons respond to visual, auditory, and tactile stimuli, smooth pursuit eye movements, and passive and active movements of the head. This study demonstrates mathematical structure on a higher organizational level created within VIP by the integration of a complete set of variables covering face-infringement. Rather than positing dynamics in an a priori defined coordinate system such as those of physical space, we assemble neuronal receptive fields to find out what space of variables VIP neurons together cover. Section 1 presents a view of neurons as multidimensional mathematical objects. Each VIP neuron occupies or is responsive to a region in a sensorimotor phase space, thus unifying variables relevant to the disparate sensory modalities and movements. Convergence on one neuron joins variables functionally, as space and time are joined in relativistic physics to form a unified spacetime. The space of position and motion together forms a neuronal phase space, bridging neurophysiology and the physics of face-infringement. After a brief review of the experimental literature, the neuronal phase space natural to VIP is sequentially characterized, based on experimental data. Responses of neurons indicate variables that may serve as axes of neural reference frames, and neuronal responses have been so used in this study. The space of sensory and movement variables covered by VIP receptive fields joins visual and auditory space to body-bound sensory modalities: somatosensation and the inertial senses. This joining of allocentric and egocentric modalities is in keeping with the known relationship of the parietal lobe to the sense of self in space and to hemineglect, in both humans and monkeys. Following this inductive step, variables are formalized in terms of the mathematics of graph theory to deduce which

  19. The Reference Ability Neural Network Study: Life-time stability of reference-ability neural networks derived from task maps of young adults.

    Science.gov (United States)

    Habeck, C; Gazes, Y; Razlighi, Q; Steffener, J; Brickman, A; Barulli, D; Salthouse, T; Stern, Y

    2016-01-15

    Analyses of large test batteries administered to individuals ranging from young to old have consistently yielded a set of latent variables representing reference abilities (RAs) that capture the majority of the variance in age-related cognitive change: Episodic Memory, Fluid Reasoning, Perceptual Processing Speed, and Vocabulary. In a previous paper (Stern et al., 2014), we introduced the Reference Ability Neural Network Study, which administers 12 cognitive neuroimaging tasks (3 for each RA) to healthy adults age 20-80 in order to derive unique neural networks underlying these 4 RAs and investigate how these networks may be affected by aging. We used a multivariate approach, linear indicator regression, to derive a unique covariance pattern or Reference Ability Neural Network (RANN) for each of the 4 RAs. The RANNs were derived from the neural task data of 64 younger adults of age 30 and below. We then prospectively applied the RANNs to fMRI data from the remaining sample of 227 adults of age 31 and above in order to classify each subject-task map into one of the 4 possible reference domains. Overall classification accuracy across subjects in the sample age 31 and above was 0.80±0.18. Classification accuracy by RA domain was also good, but variable; memory: 0.72±0.32; reasoning: 0.75±0.35; speed: 0.79±0.31; vocabulary: 0.94±0.16. Classification accuracy was not associated with cross-sectional age, suggesting that these networks, and their specificity to the respective reference domain, might remain intact throughout the age range. Higher mean brain volume was correlated with increased overall classification accuracy; better overall performance on the tasks in the scanner was also associated with classification accuracy. For the RANN network scores, we observed for each RANN that a higher score was associated with a higher corresponding classification accuracy for that reference ability. Despite the absence of behavioral performance information in the

  20. Space-time reference with an optical link

    International Nuclear Information System (INIS)

    Berceau, P; Hollberg, L; Taylor, M; Kahn, J

    2016-01-01

    We describe a concept for realizing a high performance space-time reference using a stable atomic clock in a precisely defined orbit and synchronizing the orbiting clock to high-accuracy atomic clocks on the ground. The synchronization would be accomplished using a two-way lasercom link between ground and space. The basic approach is to take advantage of the highest-performance cold-atom atomic clocks at national standards laboratories on the ground and to transfer that performance to an orbiting clock that has good stability and that serves as a ‘frequency-flywheel’ over time-scales of a few hours. The two-way lasercom link would also provide precise range information and thus precise orbit determination. With a well-defined orbit and a synchronized clock, the satellite could serve as a high-accuracy space-time reference, providing precise time worldwide, a valuable reference frame for geodesy, and independent high-accuracy measurements of GNSS clocks. Under reasonable assumptions, a practical system would be able to deliver picosecond timing worldwide and millimeter orbit determination, and could serve as an enabling subsystem for other proposed space-gravity missions, which are briefly reviewed. (paper)

  1. Time and Space Partitioning the EagleEye Reference Misson

    Science.gov (United States)

    Bos, Victor; Mendham, Peter; Kauppinen, Panu; Holsti, Niklas; Crespo, Alfons; Masmano, Miguel; de la Puente, Juan A.; Zamorano, Juan

    2013-08-01

    We discuss experiences gained by porting a Software Validation Facility (SVF) and a satellite Central Software (CSW) to a platform with support for Time and Space Partitioning (TSP). The SVF and CSW are part of the EagleEye Reference mission of the European Space Agency (ESA). As a reference mission, EagleEye is a perfect candidate to evaluate practical aspects of developing satellite CSW for and on TSP platforms. The specific TSP platform we used consists of a simulated LEON3 CPU controlled by the XtratuM separation micro-kernel. On top of this, we run five separate partitions. Each partition runs its own real-time operating system or Ada run-time kernel, which in turn are running the application software of the CSW. We describe issues related to partitioning; inter-partition communication; scheduling; I/O; and fault-detection, isolation, and recovery (FDIR).

  2. Tracking down abstract linguistic meaning: neural correlates of spatial frame of reference ambiguities in language.

    Directory of Open Access Journals (Sweden)

    Gabriele Janzen

    Full Text Available This functional magnetic resonance imaging (fMRI study investigates a crucial parameter in spatial description, namely variants in the frame of reference chosen. Two frames of reference are available in European languages for the description of small-scale assemblages, namely the intrinsic (or object-oriented frame and the relative (or egocentric frame. We showed participants a sentence such as "the ball is in front of the man", ambiguous between the two frames, and then a picture of a scene with a ball and a man--participants had to respond by indicating whether the picture did or did not match the sentence. There were two blocks, in which we induced each frame of reference by feedback. Thus for the crucial test items, participants saw exactly the same sentence and the same picture but now from one perspective, now the other. Using this method, we were able to precisely pinpoint the pattern of neural activation associated with each linguistic interpretation of the ambiguity, while holding the perceptual stimuli constant. Increased brain activity in bilateral parahippocampal gyrus was associated with the intrinsic frame of reference whereas increased activity in the right superior frontal gyrus and in the parietal lobe was observed for the relative frame of reference. The study is among the few to show a distinctive pattern of neural activation for an abstract yet specific semantic parameter in language. It shows with special clarity the nature of the neural substrate supporting each frame of spatial reference.

  3. Parameter estimation in space systems using recurrent neural networks

    Science.gov (United States)

    Parlos, Alexander G.; Atiya, Amir F.; Sunkel, John W.

    1991-01-01

    The identification of time-varying parameters encountered in space systems is addressed, using artificial neural systems. A hybrid feedforward/feedback neural network, namely a recurrent multilayer perception, is used as the model structure in the nonlinear system identification. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard back-propagation-learning algorithm is modified and it is used for both the off-line and on-line supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying parameters of nonlinear dynamic systems is investigated by estimating the mass properties of a representative large spacecraft. The changes in the spacecraft inertia are predicted using a trained neural network, during two configurations corresponding to the early and late stages of the spacecraft on-orbit assembly sequence. The proposed on-line mass properties estimation capability offers encouraging results, though, further research is warranted for training and testing the predictive capabilities of these networks beyond nominal spacecraft operations.

  4. A future large-aperture UVOIR space observatory: reference designs

    Science.gov (United States)

    Rioux, Norman; Thronson, Harley; Feinberg, Lee; Stahl, H. Philip; Redding, Dave; Jones, Andrew; Sturm, James; Collins, Christine; Liu, Alice

    2015-09-01

    Our joint NASA GSFC/JPL/MSFC/STScI study team has used community-provided science goals to derive mission needs, requirements, and candidate mission architectures for a future large-aperture, non-cryogenic UVOIR space observatory. We describe the feasibility assessment of system thermal and dynamic stability for supporting coronagraphy. The observatory is in a Sun-Earth L2 orbit providing a stable thermal environment and excellent field of regard. Reference designs include a 36-segment 9.2 m aperture telescope that stows within a five meter diameter launch vehicle fairing. Performance needs developed under the study are traceable to a variety of reference designs including options for a monolithic primary mirror.

  5. Neural correlates of the processing of self-referent emotional information in bulimia nervosa.

    Science.gov (United States)

    Pringle, A; Ashworth, F; Harmer, C J; Norbury, R; Cooper, M J

    2011-10-01

    There is increasing interest in understanding the roles of distorted beliefs about the self, ostensibly unrelated to eating, weight and shape, in eating disorders (EDs), but little is known about their neural correlates. We therefore used functional magnetic resonance imaging to investigate the neural correlates of self-referent emotional processing in EDs. During the scan, unmedicated patients with bulimia nervosa (n=11) and healthy controls (n=16) responded to personality words previously found to be related to negative self beliefs in EDs and depression. Rating of the negative personality descriptors resulted in reduced activation in patients compared to controls in parietal, occipital and limbic areas including the amygdala. There was no evidence that reduced activity in patients was secondary to increased cognitive control. Different patterns of neural activation between patients and controls may be the result of either habituation to personally relevant negative self beliefs or of emotional blunting in patients. Copyright © 2011 Elsevier Ltd. All rights reserved.

  6. Classical field theory in the space of reference frames. [Space-time manifold, action principle

    Energy Technology Data Exchange (ETDEWEB)

    Toller, M [Dipartimento di Matematica e Fisica, Libera Universita, Trento (Italy)

    1978-03-11

    The formalism of classical field theory is generalized by replacing the space-time manifold M by the ten-dimensional manifold S of all the local reference frames. The geometry of the manifold S is determined by ten vector fields corresponding to ten operationally defined infinitesimal transformations of the reference frames. The action principle is written in terms of a differential 4-form in the space S (the Lagrangian form). Densities and currents are represented by differential 3-forms in S. The field equations and the connection between symmetries and conservation laws (Noether's theorem) are derived from the action principle. Einstein's theory of gravitation and Maxwell's theory of electromagnetism are reformulated in this language. The general formalism can also be used to formulate theories in which charge, energy and momentum cannot be localized in space-time and even theories in which a space-time manifold cannot be defined exactly in any useful way.

  7. An ultra-stable optical frequency reference for space

    Science.gov (United States)

    Schuldt, T.; Döringshoff, K.; Kovalchuk, E.; Pahl, J.; Gohlke, M.; Weise, D.; Johann, U.; Peters, A.; Braxmaier, C.

    2017-11-01

    We realized ultra-stable optical frequency references on elegant breadboard (EBB) and engineering model (EM) level utilizing Doppler-free spectroscopy of molecular iodine near 532nm. A frequency stability of about 1•10-14 at an integration time of 1 s and below 5•10-15 at integration times between 10 s and 100 s was achieved. These values are comparable to the currently best laboratory setups. Both setups use a baseplate made of glass material where the optical components are joint using a specific assembly-integration technology. Compared to the EBB setup, the EM setup is further developed with respect to compactness and mechanical and thermal stability. The EM setup uses a baseplate made of fused silica with dimensions of 380 x 180 x 40 mm3 and a specifically designed 100 x 100 x 30 mm3 rectangular iodine cell in nine-pass configuration with a specific robust cold finger design. The EM setup was subjected to thermal cycling and vibrational testing. Applications of such an optical frequency reference in space can be found in fundamental physics, geoscience, Earth observation, and navigation & ranging. One example is the proposed mSTAR (mini SpaceTime Asymmetry Research) mission, dedicated to perform a Kennedy-Thorndike experiment on a satellite in a sunsynchronous low-Earth orbit. By comparing an iodine standard to a cavity-based frequency reference and integration over 2 year mission lifetime, the Kennedy-Thorndike coefficient will be determined with up to two orders of magnitude higher accuracy than the current best ground experiment. In a current study, the compatibility of the payload with the SaudiSat-4 host vehicle is investigated.

  8. Spaced Learning Enhances Subsequent Recognition Memory by Reducing Neural Repetition Suppression

    Science.gov (United States)

    Xue, Gui; Mei, Leilei; Chen, Chuansheng; Lu, Zhong-Lin; Poldrack, Russell; Dong, Qi

    2011-01-01

    Spaced learning usually leads to better recognition memory as compared with massed learning, yet the underlying neural mechanisms remain elusive. One open question is whether the spacing effect is achieved by reducing neural repetition suppression. In this fMRI study, participants were scanned while intentionally memorizing 120 novel faces, half…

  9. Deep learning quick reference useful hacks for training and optimizing deep neural networks with TensorFlow and Keras

    CERN Document Server

    Bernico, Michael

    2018-01-01

    This book is a practical guide to applying deep neural networks including MLPs, CNNs, LSTMs, and more in Keras and TensorFlow. Packed with useful hacks to solve real-world challenges along with the supported math and theory around each topic, this book will be a quick reference for training and optimize your deep neural networks.

  10. Experiments in Neural-Network Control of a Free-Flying Space Robot

    National Research Council Canada - National Science Library

    Wilson, Edward

    1995-01-01

    Four important generic issues are identified and addressed in some depth in this thesis as part of the development of an adaptive neural network based control system for an experimental free flying space robot prototype...

  11. Visual Experience Shapes the Neural Networks Remapping Touch into External Space.

    Science.gov (United States)

    Crollen, Virginie; Lazzouni, Latifa; Rezk, Mohamed; Bellemare, Antoine; Lepore, Franco; Collignon, Olivier

    2017-10-18

    Localizing touch relies on the activation of skin-based and externally defined spatial frames of reference. Psychophysical studies have demonstrated that early visual deprivation prevents the automatic remapping of touch into external space. We used fMRI to characterize how visual experience impacts the brain circuits dedicated to the spatial processing of touch. Sighted and congenitally blind humans performed a tactile temporal order judgment (TOJ) task, either with the hands uncrossed or crossed over the body midline. Behavioral data confirmed that crossing the hands has a detrimental effect on TOJ judgments in sighted but not in early blind people. Crucially, the crossed hand posture elicited enhanced activity, when compared with the uncrossed posture, in a frontoparietal network in the sighted group only. Psychophysiological interaction analysis revealed, however, that the congenitally blind showed enhanced functional connectivity between parietal and frontal regions in the crossed versus uncrossed hand postures. Our results demonstrate that visual experience scaffolds the neural implementation of the location of touch in space. SIGNIFICANCE STATEMENT In daily life, we seamlessly localize touch in external space for action planning toward a stimulus making contact with the body. For efficient sensorimotor integration, the brain has therefore to compute the current position of our limbs in the external world. In the present study, we demonstrate that early visual deprivation alters the brain activity in a dorsal parietofrontal network typically supporting touch localization in the sighted. Our results therefore conclusively demonstrate the intrinsic role that developmental vision plays in scaffolding the neural implementation of touch perception. Copyright © 2017 the authors 0270-6474/17/3710097-07$15.00/0.

  12. Similarity estimation for reference image retrieval in mammograms using convolutional neural network

    Science.gov (United States)

    Muramatsu, Chisako; Higuchi, Shunichi; Morita, Takako; Oiwa, Mikinao; Fujita, Hiroshi

    2018-02-01

    Periodic breast cancer screening with mammography is considered effective in decreasing breast cancer mortality. For screening programs to be successful, an intelligent image analytic system may support radiologists' efficient image interpretation. In our previous studies, we have investigated image retrieval schemes for diagnostic references of breast lesions on mammograms and ultrasound images. Using a machine learning method, reliable similarity measures that agree with radiologists' similarity were determined and relevant images could be retrieved. However, our previous method includes a feature extraction step, in which hand crafted features were determined based on manual outlines of the masses. Obtaining the manual outlines of masses is not practical in clinical practice and such data would be operator-dependent. In this study, we investigated a similarity estimation scheme using a convolutional neural network (CNN) to skip such procedure and to determine data-driven similarity scores. By using CNN as feature extractor, in which extracted features were employed in determination of similarity measures with a conventional 3-layered neural network, the determined similarity measures were correlated well with the subjective ratings and the precision of retrieving diagnostically relevant images was comparable with that of the conventional method using handcrafted features. By using CNN for determination of similarity measure directly, the result was also comparable. By optimizing the network parameters, results may be further improved. The proposed method has a potential usefulness in determination of similarity measure without precise lesion outlines for retrieval of similar mass images on mammograms.

  13. Demonstration of Self-Training Autonomous Neural Networks in Space Vehicle Docking Simulations

    Science.gov (United States)

    Patrick, M. Clinton; Thaler, Stephen L.; Stevenson-Chavis, Katherine

    2006-01-01

    Neural Networks have been under examination for decades in many areas of research, with varying degrees of success and acceptance. Key goals of computer learning, rapid problem solution, and automatic adaptation have been elusive at best. This paper summarizes efforts at NASA's Marshall Space Flight Center harnessing such technology to autonomous space vehicle docking for the purpose of evaluating applicability to future missions.

  14. The Role of Architectural and Learning Constraints in Neural Network Models: A Case Study on Visual Space Coding.

    Science.gov (United States)

    Testolin, Alberto; De Filippo De Grazia, Michele; Zorzi, Marco

    2017-01-01

    The recent "deep learning revolution" in artificial neural networks had strong impact and widespread deployment for engineering applications, but the use of deep learning for neurocomputational modeling has been so far limited. In this article we argue that unsupervised deep learning represents an important step forward for improving neurocomputational models of perception and cognition, because it emphasizes the role of generative learning as opposed to discriminative (supervised) learning. As a case study, we present a series of simulations investigating the emergence of neural coding of visual space for sensorimotor transformations. We compare different network architectures commonly used as building blocks for unsupervised deep learning by systematically testing the type of receptive fields and gain modulation developed by the hidden neurons. In particular, we compare Restricted Boltzmann Machines (RBMs), which are stochastic, generative networks with bidirectional connections trained using contrastive divergence, with autoencoders, which are deterministic networks trained using error backpropagation. For both learning architectures we also explore the role of sparse coding, which has been identified as a fundamental principle of neural computation. The unsupervised models are then compared with supervised, feed-forward networks that learn an explicit mapping between different spatial reference frames. Our simulations show that both architectural and learning constraints strongly influenced the emergent coding of visual space in terms of distribution of tuning functions at the level of single neurons. Unsupervised models, and particularly RBMs, were found to more closely adhere to neurophysiological data from single-cell recordings in the primate parietal cortex. These results provide new insights into how basic properties of artificial neural networks might be relevant for modeling neural information processing in biological systems.

  15. New Search Space Reduction Algorithm for Vertical Reference Trajectory Optimization

    Directory of Open Access Journals (Sweden)

    Alejandro MURRIETA-MENDOZA

    2016-06-01

    Full Text Available Burning the fuel required to sustain a given flight releases pollution such as carbon dioxide and nitrogen oxides, and the amount of fuel consumed is also a significant expense for airlines. It is desirable to reduce fuel consumption to reduce both pollution and flight costs. To increase fuel savings in a given flight, one option is to compute the most economical vertical reference trajectory (or flight plan. A deterministic algorithm was developed using a numerical aircraft performance model to determine the most economical vertical flight profile considering take-off weight, flight distance, step climb and weather conditions. This algorithm is based on linear interpolations of the performance model using the Lagrange interpolation method. The algorithm downloads the latest available forecast from Environment Canada according to the departure date and flight coordinates, and calculates the optimal trajectory taking into account the effects of wind and temperature. Techniques to avoid unnecessary calculations are implemented to reduce the computation time. The costs of the reference trajectories proposed by the algorithm are compared with the costs of the reference trajectories proposed by a commercial flight management system using the fuel consumption estimated by the FlightSim® simulator made by Presagis®.

  16. An alternative reference space for H&E color normalization.

    Directory of Open Access Journals (Sweden)

    Mark D Zarella

    Full Text Available Digital imaging of H&E stained slides has enabled the application of image processing to support pathology workflows. Potential applications include computer-aided diagnostics, advanced quantification tools, and innovative visualization platforms. However, the intrinsic variability of biological tissue and the vast differences in tissue preparation protocols often lead to significant image variability that can hamper the effectiveness of these computational tools. We developed an alternative representation for H&E images that operates within a space that is more amenable to many of these image processing tools. The algorithm to derive this representation operates by exploiting the correlation between color and the spatial properties of the biological structures present in most H&E images. In this way, images are transformed into a structure-centric space in which images are segregated into tissue structure channels. We demonstrate that this framework can be extended to achieve color normalization, effectively reducing inter-slide variability.

  17. Learning characteristics of a space-time neural network as a tether skiprope observer

    Science.gov (United States)

    Lea, Robert N.; Villarreal, James A.; Jani, Yashvant; Copeland, Charles

    1993-01-01

    The Software Technology Laboratory at the Johnson Space Center is testing a Space Time Neural Network (STNN) for observing tether oscillations present during retrieval of a tethered satellite. Proper identification of tether oscillations, known as 'skiprope' motion, is vital to safe retrieval of the tethered satellite. Our studies indicate that STNN has certain learning characteristics that must be understood properly to utilize this type of neural network for the tethered satellite problem. We present our findings on the learning characteristics including a learning rate versus momentum performance table.

  18. Experiments in Neural-Network Control of a Free-Flying Space Robot

    Science.gov (United States)

    Wilson, Edward

    1995-01-01

    Four important generic issues are identified and addressed in some depth in this thesis as part of the development of an adaptive neural network based control system for an experimental free flying space robot prototype. The first issue concerns the importance of true system level design of the control system. A new hybrid strategy is developed here, in depth, for the beneficial integration of neural networks into the total control system. A second important issue in neural network control concerns incorporating a priori knowledge into the neural network. In many applications, it is possible to get a reasonably accurate controller using conventional means. If this prior information is used purposefully to provide a starting point for the optimizing capabilities of the neural network, it can provide much faster initial learning. In a step towards addressing this issue, a new generic Fully Connected Architecture (FCA) is developed for use with backpropagation. A third issue is that neural networks are commonly trained using a gradient based optimization method such as backpropagation; but many real world systems have Discrete Valued Functions (DVFs) that do not permit gradient based optimization. One example is the on-off thrusters that are common on spacecraft. A new technique is developed here that now extends backpropagation learning for use with DVFs. The fourth issue is that the speed of adaptation is often a limiting factor in the implementation of a neural network control system. This issue has been strongly resolved in the research by drawing on the above new contributions.

  19. Neural Correlates of Realistic and Unrealistic Auditory Space Perception

    Directory of Open Access Journals (Sweden)

    Akiko Callan

    2011-10-01

    Full Text Available Binaural recordings can simulate externalized auditory space perception over headphones. However, if the orientation of the recorder's head and the orientation of the listener's head are incongruent, the simulated auditory space is not realistic. For example, if a person lying flat on a bed listens to an environmental sound that was recorded by microphones inserted in ears of a person who was in an upright position, the sound simulates an auditory space rotated 90 degrees to the real-world horizontal axis. Our question is whether brain activation patterns are different between the unrealistic auditory space (ie, the orientation of the listener's head and the orientation of the recorder's head are incongruent and the realistic auditory space (ie, the orientations are congruent. River sounds that were binaurally recorded either in a supine position or in an upright body position were served as auditory stimuli. During fMRI experiments, participants listen to the stimuli and pressed one of two buttons indicating the direction of the water flow (horizontal/vertical. Behavioral results indicated that participants could not differentiate between the congruent and the incongruent conditions. However, neuroimaging results showed that the congruent condition activated the planum temporale significantly more than the incongruent condition.

  20. Reference Concepts for a Space-Based Hydrogen-Oxygen Combustion, Turboalternator, Burst Power System

    National Research Council Canada - National Science Library

    Edenburn, Michael

    1990-01-01

    This report describes reference concepts for a hydrogen-oxygen combustion, turboalternator power system that supplies power during battle engagement to a space-based, ballistic missile defense platform...

  1. Xenotransplantation of human neural progenitor cells to the subretinal space of nonimmunosuppressed pigs

    DEFF Research Database (Denmark)

    Warfvinge, Karin; Schwartz, Philip H; Kiilgaard, Jens Folke

    2011-01-01

    To investigate the feasibility of transplanting human neural progenitor cells (hNPCs) to the retina of nonimmunosuppressed pigs, cultured hNPCs were injected into the subretinal space of 5 adult pigs after laser burns were applied to promote donor cell integration. Postoperatively, the retinal ve...

  2. Xenotransplantation of human neural progenitor cells to the subretinal space of nonimmunosuppressed pigs

    DEFF Research Database (Denmark)

    Warfvinge, Karin; Schwartz, Philip H; Kiilgaard, Jens Folke

    2011-01-01

    To investigate the feasibility of transplanting human neural progenitor cells (hNPCs) to the retina of nonimmunosuppressed pigs, cultured hNPCs were injected into the subretinal space of 5 adult pigs after laser burns were applied to promote donor cell integration. Postoperatively, the retinal ve...... that modulation of host immunity is likely necessary for prolonged xenograft survival in this model....

  3. Feed-Forward Neural Networks and Minimal Search Space Learning

    Czech Academy of Sciences Publication Activity Database

    Neruda, Roman

    2005-01-01

    Roč. 4, č. 12 (2005), s. 1867-1872 ISSN 1109-2750 R&D Projects: GA ČR GA201/05/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : search space * feed-forward networks * genetic algorithm s Subject RIV: BA - General Mathematics

  4. A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements.

    Directory of Open Access Journals (Sweden)

    Daniel Durstewitz

    2017-06-01

    Full Text Available The computational and cognitive properties of neural systems are often thought to be implemented in terms of their (stochastic network dynamics. Hence, recovering the system dynamics from experimentally observed neuronal time series, like multiple single-unit recordings or neuroimaging data, is an important step toward understanding its computations. Ideally, one would not only seek a (lower-dimensional state space representation of the dynamics, but would wish to have access to its statistical properties and their generative equations for in-depth analysis. Recurrent neural networks (RNNs are a computationally powerful and dynamically universal formal framework which has been extensively studied from both the computational and the dynamical systems perspective. Here we develop a semi-analytical maximum-likelihood estimation scheme for piecewise-linear RNNs (PLRNNs within the statistical framework of state space models, which accounts for noise in both the underlying latent dynamics and the observation process. The Expectation-Maximization algorithm is used to infer the latent state distribution, through a global Laplace approximation, and the PLRNN parameters iteratively. After validating the procedure on toy examples, and using inference through particle filters for comparison, the approach is applied to multiple single-unit recordings from the rodent anterior cingulate cortex (ACC obtained during performance of a classical working memory task, delayed alternation. Models estimated from kernel-smoothed spike time data were able to capture the essential computational dynamics underlying task performance, including stimulus-selective delay activity. The estimated models were rarely multi-stable, however, but rather were tuned to exhibit slow dynamics in the vicinity of a bifurcation point. In summary, the present work advances a semi-analytical (thus reasonably fast maximum-likelihood estimation framework for PLRNNs that may enable to recover

  5. Sample selection via angular distance in the space of the arguments of an artificial neural network

    Science.gov (United States)

    Fernández Jaramillo, J. M.; Mayerle, R.

    2018-05-01

    In the construction of an artificial neural network (ANN) a proper data splitting of the available samples plays a major role in the training process. This selection of subsets for training, testing and validation affects the generalization ability of the neural network. Also the number of samples has an impact in the time required for the design of the ANN and the training. This paper introduces an efficient and simple method for reducing the set of samples used for training a neural network. The method reduces the required time to calculate the network coefficients, while keeping the diversity and avoiding overtraining the ANN due the presence of similar samples. The proposed method is based on the calculation of the angle between two vectors, each one representing one input of the neural network. When the angle formed among samples is smaller than a defined threshold only one input is accepted for the training. The accepted inputs are scattered throughout the sample space. Tidal records are used to demonstrate the proposed method. The results of a cross-validation show that with few inputs the quality of the outputs is not accurate and depends on the selection of the first sample, but as the number of inputs increases the accuracy is improved and differences among the scenarios with a different starting sample have and important reduction. A comparison with the K-means clustering algorithm shows that for this application the proposed method with a smaller number of samples is producing a more accurate network.

  6. Modal-space reference-model-tracking fuzzy control of earthquake excited structures

    Science.gov (United States)

    Park, Kwan-Soon; Ok, Seung-Yong

    2015-01-01

    This paper describes an adaptive modal-space reference-model-tracking fuzzy control technique for the vibration control of earthquake-excited structures. In the proposed approach, the fuzzy logic is introduced to update optimal control force so that the controlled structural response can track the desired response of a reference model. For easy and practical implementation, the reference model is constructed by assigning the target damping ratios to the first few dominant modes in modal space. The numerical simulation results demonstrate that the proposed approach successfully achieves not only the adaptive fault-tolerant control system against partial actuator failures but also the robust performance against the variations of the uncertain system properties by redistributing the feedback control forces to the available actuators.

  7. Single dose antidepressant administration modulates the neural processing of self-referent personality trait words

    DEFF Research Database (Denmark)

    Miskowiak, Kamilla; Papadatou-Pastou, Marietta; Cowen, Philip J

    2007-01-01

    categorisation and recognition of self-referent personality trait words were assessed using event-related functional Magnetic Resonance Imaging (fMRI). Reboxetine had no effect on neuronal response during self-referent categorisation of positive or negative personality trait words. However, in a subsequent...

  8. Artificial neural networks contribution to the operational security of embedded systems. Artificial neural networks contribution to fault tolerance of on-board functions in space environment

    International Nuclear Information System (INIS)

    Vintenat, Lionel

    1999-01-01

    A good quality often attributed to artificial neural networks is fault tolerance. In general presentation works, this property is almost always introduced as 'natural', i.e. being obtained without any specific precaution during learning. Besides, space environment is known to be aggressive towards on-board hardware, inducing various abnormal operations. Particularly, digital components suffer from upset phenomenon, i.e. misplaced switches of memory flip-flops. These two observations lead to the question: would neural chips constitute an interesting and robust solution to implement some board functions of spacecrafts? First, the various aspects of the problem are detailed: artificial neural networks and their fault tolerance, neural chips, space environment and resulting failures. Further to this presentation, a particular technique to carry out neural chips is selected because of its simplicity, and especially because it requires few memory flip-flops: random pulse streams. An original method for star recognition inside a field-of-view is then proposed for the board function 'attitude computation'. This method relies on a winner-takes-all competition network, and on a Kohonen self-organized map. An hardware implementation of those two neural models is then proposed using random pulse streams. Thanks to this realization, on one hand difficulties related to that particular implementation technique can be highlighted, and on the other hand a first evaluation of its practical fault tolerance can be carried out. (author) [fr

  9. A neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine

    Science.gov (United States)

    Guo, T. H.; Musgrave, J.

    1992-11-01

    In order to properly utilize the available fuel and oxidizer of a liquid propellant rocket engine, the mixture ratio is closed loop controlled during main stage (65 percent - 109 percent power) operation. However, because of the lack of flight-capable instrumentation for measuring mixture ratio, the value of mixture ratio in the control loop is estimated using available sensor measurements such as the combustion chamber pressure and the volumetric flow, and the temperature and pressure at the exit duct on the low pressure fuel pump. This estimation scheme has two limitations. First, the estimation formula is based on an empirical curve fitting which is accurate only within a narrow operating range. Second, the mixture ratio estimate relies on a few sensor measurements and loss of any of these measurements will make the estimate invalid. In this paper, we propose a neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine. The estimator is an extension of a previously developed neural network based sensor failure detection and recovery algorithm (sensor validation). This neural network uses an auto associative structure which utilizes the redundant information of dissimilar sensors to detect inconsistent measurements. Two approaches have been identified for synthesizing mixture ratio from measurement data using a neural network. The first approach uses an auto associative neural network for sensor validation which is modified to include the mixture ratio as an additional output. The second uses a new network for the mixture ratio estimation in addition to the sensor validation network. Although mixture ratio is not directly measured in flight, it is generally available in simulation and in test bed firing data from facility measurements of fuel and oxidizer volumetric flows. The pros and cons of these two approaches will be discussed in terms of robustness to sensor failures and accuracy of the estimate during typical transients using

  10. Neural evidence for Reference-dependence in real-market-transactions.

    Science.gov (United States)

    Weber, Bernd; Aholt, Andreas; Neuhaus, Carolin; Trautner, Peter; Elger, Christian E; Teichert, Thorsten

    2007-03-01

    Human decision making has become one of the major research-foci in economics, marketing and in neuroscience. This study integrates perspectives from these disciplines by examining neurophysiological correlates to Reference-dependence of utility evaluations in real market contexts both before and after choice. First, by comparing buying and selling decisions, we observe an activation of the amygdala only in the latter. We interpret this as loss aversion with respect to prior possessions. This finding contributes to the settling of an ongoing fundamental dispute in economic theory by indicating the absence of loss aversion for money in routine transactions. Second, ex post satisfaction statements are accompanied by an activation of the reward processing orbitofrontal cortex, if the evaluation context is framed by a high external reference price instead of a lower internal reference price. This indicates a nonrational Reference-dependence--despite the neoclassical view of a rational Homo Economicus--of satisfaction measures and challenges a central marketing variable.

  11. An artificial neural network system to identify alleles in reference electropherograms.

    Science.gov (United States)

    Taylor, Duncan; Harrison, Ash; Powers, David

    2017-09-01

    Electropherograms are produced in great numbers in forensic DNA laboratories as part of everyday criminal casework. Before the results of these electropherograms can be used they must be scrutinised by analysts to determine what the identified data tells them about the underlying DNA sequences and what is purely an artefact of the DNA profiling process. This process of interpreting the electropherograms can be time consuming and is prone to subjective differences between analysts. Recently it was demonstrated that artificial neural networks could be used to classify information within an electropherogram as allelic (i.e. representative of a DNA fragment present in the DNA extract) or as one of several different categories of artefactual fluorescence that arise as a result of generating an electropherogram. We extend that work here to demonstrate a series of algorithms and artificial neural networks that can be used to identify peaks on an electropherogram and classify them. We demonstrate the functioning of the system on several profiles and compare the results to a leading commercial DNA profile reading system. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Artificial neural network for the determination of Hubble Space Telescope aberration from stellar images

    Science.gov (United States)

    Barrett, Todd K.; Sandler, David G.

    1993-01-01

    An artificial-neural-network method, first developed for the measurement and control of atmospheric phase distortion, using stellar images, was used to estimate the optical aberration of the Hubble Space Telescope. A total of 26 estimates of distortion was obtained from 23 stellar images acquired at several secondary-mirror axial positions. The results were expressed as coefficients of eight orthogonal Zernike polynomials: focus through third-order spherical. For all modes other than spherical the measured aberration was small. The average spherical aberration of the estimates was -0.299 micron rms, which is in good agreement with predictions obtained when iterative phase-retrieval algorithms were used.

  13. Real-space mapping of topological invariants using artificial neural networks

    Science.gov (United States)

    Carvalho, D.; García-Martínez, N. A.; Lado, J. L.; Fernández-Rossier, J.

    2018-03-01

    Topological invariants allow one to characterize Hamiltonians, predicting the existence of topologically protected in-gap modes. Those invariants can be computed by tracing the evolution of the occupied wave functions under twisted boundary conditions. However, those procedures do not allow one to calculate a topological invariant by evaluating the system locally, and thus require information about the wave functions in the whole system. Here we show that artificial neural networks can be trained to identify the topological order by evaluating a local projection of the density matrix. We demonstrate this for two different models, a one-dimensional topological superconductor and a two-dimensional quantum anomalous Hall state, both with spatially modulated parameters. Our neural network correctly identifies the different topological domains in real space, predicting the location of in-gap states. By combining a neural network with a calculation of the electronic states that uses the kernel polynomial method, we show that the local evaluation of the invariant can be carried out by evaluating a local quantity, in particular for systems without translational symmetry consisting of tens of thousands of atoms. Our results show that supervised learning is an efficient methodology to characterize the local topology of a system.

  14. An Engineering Design Reference Mission for a Future Large-Aperture UVOIR Space Observatory

    Science.gov (United States)

    Thronson, Harley A.; Bolcar, Matthew R.; Clampin, Mark; Crooke, Julie A.; Redding, David; Rioux, Norman; Stahl, H. Philip

    2016-01-01

    From the 2010 NRC Decadal Survey and the NASA Thirty-Year Roadmap, Enduring Quests, Daring Visions, to the recent AURA report, From Cosmic Birth to Living Earths, multiple community assessments have recommended development of a large-aperture UVOIR space observatory capable of achieving a broad range of compelling scientific goals. Of these priority science goals, the most technically challenging is the search for spectroscopic biomarkers in the atmospheres of exoplanets in the solar neighborhood. Here we present an engineering design reference mission (EDRM) for the Advanced Technology Large-Aperture Space Telescope (ATLAST), which was conceived from the start as capable of breakthrough science paired with an emphasis on cost control and cost effectiveness. An EDRM allows the engineering design trade space to be explored in depth to determine what are the most demanding requirements and where there are opportunities for margin against requirements. Our joint NASA GSFC/JPL/MSFC/STScI study team has used community-provided science goals to derive mission needs, requirements, and candidate mission architectures for a future large-aperture, non-cryogenic UVOIR space observatory. The ATLAST observatory is designed to operate at a Sun-Earth L2 orbit, which provides a stable thermal environment and excellent field of regard. Our reference designs have emphasized a serviceable 36-segment 9.2 m aperture telescope that stows within a five-meter diameter launch vehicle fairing. As part of our cost-management effort, this particular reference mission builds upon the engineering design for JWST. Moreover, it is scalable to a variety of launch vehicle fairings. Performance needs developed under the study are traceable to a variety of additional reference designs, including options for a monolithic primary mirror.

  15. Analytically continued Fock space multi-reference coupled-cluster theory: Application to the shape resonance

    International Nuclear Information System (INIS)

    Pal, Sourav; Sajeev, Y.; Vaval, Nayana

    2006-01-01

    The Fock space multi-reference coupled-cluster (FSMRCC) method is used for the study of the shape resonance energy and width in an electron-atom/molecule collision. The procedure is based upon combining a complex absorbing potential (CAP) with FSMRCC theory. Accurate resonance parameters are obtained by solving a small non-Hermitian eigen-value problem. We study the shape resonances in e - -C 2 H 4 and e - -Mg

  16. A Ka-Band Celestial Reference Frame with Applications to Deep Space Navigation

    Science.gov (United States)

    Jacobs, Christopher S.; Clark, J. Eric; Garcia-Miro, Cristina; Horiuchi, Shinji; Sotuela, Ioana

    2011-01-01

    The Ka-band radio spectrum is now being used for a wide variety of applications. This paper highlights the use of Ka-band as a frequency for precise deep space navigation based on a set of reference beacons provided by extragalactic quasars which emit broadband noise at Ka-band. This quasar-based celestial reference frame is constructed using X/Ka-band (8.4/32 GHz) from fifty-five 24-hour sessions with the Deep Space Network antennas in California, Australia, and Spain. We report on observations which have detected 464 sources covering the full 24 hours of Right Ascension and declinations down to -45 deg. Comparison of this X/Ka-band frame to the international standard S/X-band (2.3/8.4 GHz) ICRF2 shows wRMS agreement of approximately 200 micro-arcsec in alpha cos(delta) and approximately 300 micro-arcsec in delta. There is evidence for systematic errors at the 100 micro-arcsec level. Known errors include limited SNR, lack of instrumental phase calibration, tropospheric refraction mis-modeling, and limited southern geometry. The motivation for extending the celestial reference frame to frequencies above 8 GHz is to access more compact source morphology for improved frame stability and to support spacecraft navigation for Ka-band based NASA missions.

  17. Prediction of Thermal Environment in a Large Space Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Hyun-Jung Yoon

    2018-02-01

    Full Text Available Since the thermal environment of large space buildings such as stadiums can vary depending on the location of the stands, it is important to divide them into different zones and evaluate their thermal environment separately. The thermal environment can be evaluated using physical values measured with the sensors, but the occupant density of the stadium stands is high, which limits the locations available to install the sensors. As a method to resolve the limitations of installing the sensors, we propose a method to predict the thermal environment of each zone in a large space. We set six key thermal factors affecting the thermal environment in a large space to be predicted factors (indoor air temperature, mean radiant temperature, and clothing and the fixed factors (air velocity, metabolic rate, and relative humidity. Using artificial neural network (ANN models and the outdoor air temperature and the surface temperature of the interior walls around the stands as input data, we developed a method to predict the three thermal factors. Learning and verification datasets were established using STAR CCM+ (2016.10, Siemens PLM software, Plano, TX, USA. An analysis of each model’s prediction results showed that the prediction accuracy increased with the number of learning data points. The thermal environment evaluation process developed in this study can be used to control heating, ventilation, and air conditioning (HVAC facilities in each zone in a large space building with sufficient learning by ANN models at the building testing or the evaluation stage.

  18. Hybrid state‐space time integration in a rotating frame of reference

    DEFF Research Database (Denmark)

    Krenk, Steen; Nielsen, Martin Bjerre

    2011-01-01

    displacements and the global velocities are represented by the same shape functions. This leads to a simple generalization of the corresponding equations of motion in a stationary frame in which all inertial effects are represented via the classic global mass matrix. The formulation introduces two gyroscopic......A time integration algorithm is developed for the equations of motion of a flexible body in a rotating frame of reference. The equations are formulated in a hybrid state‐space, formed by the local displacement components and the global velocity components. In the spatial discretization the local...... terms, while the centrifugal forces are represented implicitly via the hybrid state‐space format. An angular momentum and energy conserving algorithm is developed, in which the angular velocity of the frame is represented by its mean value. A consistent algorithmic damping scheme is identified...

  19. Evapotranspiration Modeling by Linear, Nonlinear Regression and Artificial Neural Network in Greenhouse (Case study Reference Crop, Cucumber and Tomato

    Directory of Open Access Journals (Sweden)

    vahid Rezaverdinejad

    2017-01-01

    important models to estimate ETc in greenhouse. The inputs of these models are net radiation, temperature, day after planting and air vapour pressure deficit (or relative humidity. Materials and Methods: In this study, daily ETc of reference crop, greenhouse tomato and cucumber crops were measured using lysimeter method in Urmia region. Several linear, nonlinear regressions and artificial neural networks were considered for ETc modelling in greenhouse. For this purpose, the effective meteorological parameters on ETc process includes: air temperature (T, air humidity (RH, air pressure (P, air vapour pressure deficit (VPD, day after planting (N and greenhouse net radiation (SR were considered and measured. According to the goodness of fit, different models of artificial neural networks and regression were compared and evaluated. Furthermore, based on partial derivatives of regression models, sensitivity analysis was conducted. The accuracy and performance of the employed models was judged by ten statistical indices namely root mean square error (RMSE, normalized root mean square error (NRMSE and coefficient of determination (R2. Results and Discussion: Based on the results, the most accurate regression model to reference ETc prediction was obtained three variables exponential function of VPD, RH and SR with RMSE=0.378 mm day-1. The RMSE of optimal artificial neural network to reference ET prediction for train and test data sets were obtained 0.089 and 0.365 mm day-1, respectively. The performance of logarithmic and exponential functions to prediction of cucumber ETc were proper, with high dependent variables especially, and the most accurate regression model to cucumber ET prediction was obtained for exponential function of five variables: VPD, N, T, RH and SR with RMSE=0.353 mm day-1. In addition, for tomato ET prediction, the most accurate regression model was obtained for exponential function of four variables: VPD, N, RH and SR with RMSE= 0.329 mm day-1. The best

  20. An ultra-stable iodine-based frequency reference for space applications

    Science.gov (United States)

    Schuldt, Thilo; Braxmaier, Claus; Doeringshoff, Klaus; Keetman, Anja; Reggentin, Matthias; Kovalchuk, Evgeny; Peters, Achim

    2012-07-01

    Future space missions require for ultra-stable optical frequency references. Examples are the gravitational wave detector LISA/eLISA (Laser Interferometer Space Antenna), the SpaceTime Asymmetry Research (STAR) program, the aperture-synthesis telescope Darwin and the GRACE (Gravity Recovery and Climate Experiment) follow on mission exploring Earth's gravity. As high long-term frequency stability is required, lasers stabilized to atomic or molecular transitions are preferred, also offering an absolute frequency reference. Frequency stabilities in the 10 ^{-15} domains at longer integration times (up to several hours) are demonstrated in laboratory experiments using setups based on Doppler-free spectroscopy. Such setups with a frequency stability comparable to the hydrogen maser in the microwave domain, have the potential to be developed space compatible on a relatively short time scale. Here, we present the development of ultra-stable optical frequency references based on modulation-transfer spectroscopy of molecular iodine. Noise levels of 2\\cdot10 ^{-14} at an integration time of 1 s and below 3\\cdot10 ^{-15} at integration times between 100 s and 1000 s are demonstrated with a laboratory setup using an 80 cm long iodine cell in single-pass configuration in combination with a frequency-doubled Nd:YAG laser and standard optical components and optomechanic mounts. The frequency stability at longer integration times is (amongst other things) limited by the dimensional stability of the optical setup, i.e. by th pointing stability of the two counter-propagating beams overlapped in the iodine cell. With the goal of a future space compatible setup, a compact frequency standard on EBB (elegant breadboard) level was realized. The spectroscopy unit utilizes a baseplate made of Clearceram-HS, a glass ceramics with an ultra-low coefficient of thermal expansion of 2\\cdot10 ^{-8} K ^{-1}. The optical components are joint to the baseplate using adhesive bonding technology

  1. The association between reconstructed phase space and Artificial Neural Networks for vectorcardiographic recognition of myocardial infarction.

    Science.gov (United States)

    Costa, Cecília M; Silva, Ittalo S; de Sousa, Rafael D; Hortegal, Renato A; Regis, Carlos Danilo M

    Myocardial infarction is one of the leading causes of death worldwide. As it is life threatening, it requires an immediate and precise treatment. Due to this, a growing number of research and innovations in the field of biomedical signal processing is in high demand. This paper proposes the association of Reconstructed Phase Space and Artificial Neural Networks for Vectorcardiography Myocardial Infarction Recognition. The algorithm promotes better results for the box size 10 × 10 and the combination of four parameters: box counting (Vx), box counting (Vz), self-similarity method (Vx) and self-similarity method (Vy) with sensitivity = 92%, specificity = 96% and accuracy = 94%. The topographic diagnosis presented different performances for different types of infarctions with better results for anterior wall infarctions and less accurate results for inferior infarctions. Copyright © 2018 Elsevier Inc. All rights reserved.

  2. A Reference Database for Circular Dichroism Spectroscopy Covering Fold and Secondary Structure Space

    International Nuclear Information System (INIS)

    Lees, J.; Miles, A.; Wien, F.; Wallace, B.

    2006-01-01

    Circular Dichroism (CD) spectroscopy is a long-established technique for studying protein secondary structures in solution. Empirical analyses of CD data rely on the availability of reference datasets comprised of far-UV CD spectra of proteins whose crystal structures have been determined. This article reports on the creation of a new reference dataset which effectively covers both secondary structure and fold space, and uses the higher information content available in synchrotron radiation circular dichroism (SRCD) spectra to more accurately predict secondary structure than has been possible with existing reference datasets. It also examines the effects of wavelength range, structural redundancy and different means of categorizing secondary structures on the accuracy of the analyses. In addition, it describes a novel use of hierarchical cluster analyses to identify protein relatedness based on spectral properties alone. The databases are shown to be applicable in both conventional CD and SRCD spectroscopic analyses of proteins. Hence, by combining new bioinformatics and biophysical methods, a database has been produced that should have wide applicability as a tool for structural molecular biology

  3. Demonstration of free-space reference frame independent quantum key distribution

    International Nuclear Information System (INIS)

    Wabnig, J; Bitauld, D; Li, H W; Niskanen, A O; Laing, A; O'Brien, J L

    2013-01-01

    Quantum key distribution (QKD) is moving from research laboratories towards applications. As computing becomes more mobile, cashless as well as cardless payment solutions are introduced. A possible route to increase the security of wireless communications is to incorporate QKD in a mobile device. Handheld devices present a particular challenge as the orientation and the phase of a qubit will depend on device motion. This problem is addressed by the reference frame independent (RFI) QKD scheme. The scheme tolerates an unknown phase between logical states that vary slowly compared to the rate of particle repetition. Here we experimentally demonstrate the feasibility of RFI QKD over a free-space link in a prepare and measure scheme using polarization encoding. We extend the security analysis of the RFI QKD scheme to be able to deal with uncalibrated devices and a finite number of measurements. Together these advances are an important step towards mass production of handheld QKD devices. (paper)

  4. Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

    Science.gov (United States)

    Ferreria, Paulo Victor R.; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy M.; Bilen, Sven G.; Reinhart, Richard C.; Mortensen, Dale J.

    2017-01-01

    Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

  5. Gravity in the Brain as a Reference for Space and Time Perception.

    Science.gov (United States)

    Lacquaniti, Francesco; Bosco, Gianfranco; Gravano, Silvio; Indovina, Iole; La Scaleia, Barbara; Maffei, Vincenzo; Zago, Myrka

    2015-01-01

    Moving and interacting with the environment require a reference for orientation and a scale for calibration in space and time. There is a wide variety of environmental clues and calibrated frames at different locales, but the reference of gravity is ubiquitous on Earth. The pull of gravity on static objects provides a plummet which, together with the horizontal plane, defines a three-dimensional Cartesian frame for visual images. On the other hand, the gravitational acceleration of falling objects can provide a time-stamp on events, because the motion duration of an object accelerated by gravity over a given path is fixed. Indeed, since ancient times, man has been using plumb bobs for spatial surveying, and water clocks or pendulum clocks for time keeping. Here we review behavioral evidence in favor of the hypothesis that the brain is endowed with mechanisms that exploit the presence of gravity to estimate the spatial orientation and the passage of time. Several visual and non-visual (vestibular, haptic, visceral) cues are merged to estimate the orientation of the visual vertical. However, the relative weight of each cue is not fixed, but depends on the specific task. Next, we show that an internal model of the effects of gravity is combined with multisensory signals to time the interception of falling objects, to time the passage through spatial landmarks during virtual navigation, to assess the duration of a gravitational motion, and to judge the naturalness of periodic motion under gravity.

  6. Implementation of a model reference adaptive control system using neural network to control a fast breeder reactor evaporator

    International Nuclear Information System (INIS)

    Ugolini, D.; Yoshikawa, S.; Endou, A.

    1994-01-01

    Artificial intelligence is foreseen as the base for new control systems aimed to replace traditional controllers and to assist and eventually advise plant operators. This paper discusses the development of an indirect model reference adaptive control (MRAC) system, using the artificial neural network (ANN) technique, and its implementation to control the outlet steam temperature of a sodium to water evaporator. The ANN technique is applied in the identification and in the control process of the indirect MRAC system. The emphasis is placed on demonstrating the efficacy of the indirect MRAC system in controlling the outlet steam temperature of the evaporator, and on showing the important function covered by the ANN technique. An important characteristic of this control system is that it relays only on some selected input variables and output variables of the evaporator model. These are the variables that can be actually measured or calculated in a real environment. The results obtained applying the indirect MRAC system to control the evaporator model are quite remarkable. The outlet temperature of the steam is almost perfectly kept close to its desired set point, when the evaporator is forced to depart from steady state conditions, either due to the variation of some input variables or due to the alteration of some of its internal parameters. The results also show the importance of the role played by the ANN technique in the overall control action. The connecting weights of the ANN nodes self adjust to follow the modifications which may occur in the characteristic of the evaporator model during a transient. The efficiency and the accuracy of the control action highly depends on the on-line identification process of the ANN, which is responsible for upgrading the connecting weights of the ANN nodes. (J.P.N.)

  7. Illusions in the spatial sense of the eye: geometrical-optical illusions and the neural representation of space.

    Science.gov (United States)

    Westheimer, Gerald

    2008-09-01

    Differences between the geometrical properties of simple configurations and their visual percept are called geometrical-optical illusions. They can be differentiated from illusions in the brightness or color domains, from ambiguous figures and impossible objects, from trompe l'oeil and perspective drawing with perfectly valid views, and from illusory contours. They were discovered independently by several scientists in a short time span in the 1850's. The clear distinction between object and visual space that they imply allows the question to be raised whether the transformation between the two spaces can be productively investigated in terms of differential geometry and metrical properties. Perceptual insight and psychophysical research prepares the ground for investigation of the neural representation of space but, because visual attributes are processed separately in parallel, one looks in vain for a neural map that is isomorphic with object space or even with individual forms it contains. Geometrical-optical illusions help reveal parsing rules for sensory signals by showing how conflicts are resolved when there is mismatch in the output of the processing modules for various primitives as a perceptual pattern's unitary structure is assembled. They point to a hierarchical ordering of spatial primitives: cardinal directions and explicit contours predominate over oblique orientation and implicit contours (Poggendorff illusion); rectilinearity yields to continuity (Hering illusion), point position and line length to contour orientation (Ponzo). Hence the geometrical-optical illusions show promise as analytical tools in unraveling neural processing in vision.

  8. Experimental validation of the buildings energy performance (PEC assessment methods with reference to occupied spaces heating

    Directory of Open Access Journals (Sweden)

    Cristian PETCU

    2010-01-01

    Full Text Available This paper is part of the series of pre-standardization research aimed to analyze the existing methods of calculating the Buildings Energy Performance (PEC in view of their correction of completing. The entire research activity aims to experimentally validate the PEC Calculation Algorithm as well as the comparative application, on the support of several case studies focused on representative buildings of the stock of buildings in Romania, of the PEC calculation methodology for buildings equipped with occupied spaces heating systems. The targets of the report are the experimental testing of the calculation models so far known (NP 048-2000, Mc 001-2006, SR EN 13790:2009, on the support provided by the CE INCERC Bucharest experimental building, together with the complex calculation algorithms specific to the dynamic modeling, for the evaluation of the occupied spaces heat demand in the cold season, specific to the traditional buildings and to modern buildings equipped with solar radiation passive systems, of the ventilated solar space type. The schedule of the measurements performed in the 2008-2009 cold season is presented as well as the primary processing of the measured data and the experimental validation of the heat demand monthly calculation methods, on the support of CE INCERC Bucharest. The calculation error per heating season (153 days of measurements between the measured heat demand and the calculated one was of 0.61%, an exceptional value confirming the phenomenological nature of the INCERC method, NP 048-2006. The mathematical model specific to the hourly thermal balance is recurrent – decisional with alternating paces. The experimental validation of the theoretical model is based on the measurements performed on the CE INCERC Bucharest building, within a time lag of 57 days (06.01-04.03.2009. The measurements performed on the CE INCERC Bucharest building confirm the accuracy of the hourly calculation model by comparison to the values

  9. Gravity field recovery in the framework of a Geodesy and Time Reference in Space (GETRIS)

    Science.gov (United States)

    Hauk, Markus; Schlicht, Anja; Pail, Roland; Murböck, Michael

    2017-04-01

    The study ;Geodesy and Time Reference in Space; (GETRIS), funded by European Space Agency (ESA), evaluates the potential and opportunities coming along with a global space-borne infrastructure for data transfer, clock synchronization and ranging. Gravity field recovery could be one of the first beneficiary applications of such an infrastructure. This paper analyzes and evaluates the two-way high-low satellite-to-satellite-tracking as a novel method and as a long-term perspective for the determination of the Earth's gravitational field, using it as a synergy of one-way high-low combined with low-low satellite-to-satellite-tracking, in order to generate adequate de-aliasing products. First planned as a constellation of geostationary satellites, it turned out, that an integration of European Union Global Navigation Satellite System (Galileo) satellites (equipped with inter-Galileo links) into a Geostationary Earth Orbit (GEO) constellation would extend the capability of such a mission constellation remarkably. We report about simulations of different Galileo and Low Earth Orbiter (LEO) satellite constellations, computed using time variable geophysical background models, to determine temporal changes in the Earth's gravitational field. Our work aims at an error analysis of this new satellite/instrument scenario by investigating the impact of different error sources. Compared to a low-low satellite-to-satellite-tracking mission, results show reduced temporal aliasing errors due to a more isotropic error behavior caused by an improved observation geometry, predominantly in near-radial direction within the inter-satellite-links, as well as the potential of an improved gravity recovery with higher spatial and temporal resolution. The major error contributors of temporal gravity retrieval are aliasing errors due to undersampling of high frequency signals (mainly atmosphere, ocean and ocean tides). In this context, we investigate adequate methods to reduce these errors. We

  10. Neural correlates of the spacing effect in explicit verbal semantic encoding support the deficient-processing theory.

    Science.gov (United States)

    Callan, Daniel E; Schweighofer, Nicolas

    2010-04-01

    Spaced presentations of to-be-learned items during encoding leads to superior long-term retention over massed presentations. Despite over a century of research, the psychological and neural basis of this spacing effect however is still under investigation. To test the hypotheses that the spacing effect results either from reduction in encoding-related verbal maintenance rehearsal in massed relative to spaced presentations (deficient processing hypothesis) or from greater encoding-related elaborative rehearsal of relational information in spaced relative to massed presentations (encoding variability hypothesis), we designed a vocabulary learning experiment in which subjects encoded paired-associates, each composed of a known word paired with a novel word, in both spaced and massed conditions during functional magnetic resonance imaging. As expected, recall performance in delayed cued-recall tests was significantly better for spaced over massed conditions. Analysis of brain activity during encoding revealed that the left frontal operculum, known to be involved in encoding via verbal maintenance rehearsal, was associated with greater performance-related increased activity in the spaced relative to massed condition. Consistent with the deficient processing hypothesis, a significant decrease in activity with subsequent episodes of presentation was found in the frontal operculum for the massed but not the spaced condition. Our results suggest that the spacing effect is mediated by activity in the frontal operculum, presumably by encoding-related increased verbal maintenance rehearsal, which facilitates binding of phonological and word level verbal information for transfer into long-term memory. Copyright 2009 Wiley-Liss, Inc.

  11. A reference radiation facility for dosimetry at flight altitude and in space

    CERN Document Server

    Ferrari, A; Silari, Marco

    2001-01-01

    A reference facility for the intercomparison of active and passive detectors in high-energy neutron fields is available at CERN since 1993. A positive charged hadron beam (a mixture of protons and pions) with momentum of 120 GeV/c hits a copper target, 50 cm thick and 7 cm in diameter. The secondary particles produced in the interaction are filtered by a shielding of either 80 cm of concrete or 40 cm of iron. Behind the iron shielding, the resulting neutron spectrum has a maximum at about 1 MeV, with an additional high-energy component. Behind the concrete shielding, the neutron spectrum has a pronounced maximum at about 70 MeV and resembles the high-energy component of the radiation field created by cosmic rays at commercial flight altitudes. The facility is used for a variety of investigations with active and passive neutron dosimeters. Its use for measurements related to the space programme is discussed. (21 refs).

  12. Origins Space Telescope: Science Case and Design Reference Mission for Concept 1

    Science.gov (United States)

    Meixner, Margaret; Cooray, Asantha; Pope, Alexandra; Armus, Lee; Vieira, Joaquin Daniel; Milam, Stefanie N.; Melnick, Gary; Leisawitz, David; Staguhn, Johannes G.; Bergin, Edwin; Origins Space Telescope Science and Technology Definition Team

    2018-01-01

    The Origins Space Telescope (OST) is the mission concept for the Far-Infrared Surveyor, one of the four science and technology definition studies of NASA Headquarters for the 2020 Astronomy and Astrophysics Decadal survey. The science case for OST covers four themes: Tracing the Signature of Life and the Ingredients of Habitable Worlds; Charting the Rise of Metals, Dust and the First Galaxies, Unraveling the Co-evolution of Black Holes and Galaxies and Understanding Our Solar System in the Context of Planetary System Formation. Using a set of proposed observing programs from the community, we estimate a design reference mission for OST mission concept 1. The mission will complete significant programs in these four themes and have time for other programs from the community. Origins will enable flagship-quality general observing programs led by the astronomical community in the 2030s. We welcome you to contact the Science and Technology Definition Team (STDT) with your science needs and ideas by emailing us at ost_info@lists.ipac.caltech.edu.

  13. Artificial neural network application for space station power system fault diagnosis

    Science.gov (United States)

    Momoh, James A.; Oliver, Walter E.; Dias, Lakshman G.

    1995-01-01

    This study presents a methodology for fault diagnosis using a Two-Stage Artificial Neural Network Clustering Algorithm. Previously, SPICE models of a 5-bus DC power distribution system with assumed constant output power during contingencies from the DDCU were used to evaluate the ANN's fault diagnosis capabilities. This on-going study uses EMTP models of the components (distribution lines, SPDU, TPDU, loads) and power sources (DDCU) of Space Station Alpha's electrical Power Distribution System as a basis for the ANN fault diagnostic tool. The results from the two studies are contrasted. In the event of a major fault, ground controllers need the ability to identify the type of fault, isolate the fault to the orbital replaceable unit level and provide the necessary information for the power management expert system to optimally determine a degraded-mode load schedule. To accomplish these goals, the electrical power distribution system's architecture can be subdivided into three major classes: DC-DC converter to loads, DC Switching Unit (DCSU) to Main bus Switching Unit (MBSU), and Power Sources to DCSU. Each class which has its own electrical characteristics and operations, requires a unique fault analysis philosophy. This study identifies these philosophies as Riddles 1, 2 and 3 respectively. The results of the on-going study addresses Riddle-1. It is concluded in this study that the combination of the EMTP models of the DDCU, distribution cables and electrical loads yields a more accurate model of the behavior and in addition yielded more accurate fault diagnosis using ANN versus the results obtained with the SPICE models.

  14. Examining egocentric and allocentric frames of reference in virtual space systems

    NARCIS (Netherlands)

    Friedman, A.

    2005-01-01

    The aim of this paper is to examine the egocentric and allocentric frames of reference, through evidence from both gesture and linguistic communication. The action of frames of reference, helps the user refer to the agent as a base for movement or to the object as a guiding point. We will show that

  15. The Lyman alpha reference sample. II. Hubble space telescope imaging results, integrated properties, and trends

    Energy Technology Data Exchange (ETDEWEB)

    Hayes, Matthew; Östlin, Göran; Duval, Florent; Sandberg, Andreas; Guaita, Lucia; Melinder, Jens; Rivera-Thorsen, Thøger [Department of Astronomy, Oskar Klein Centre, Stockholm University, AlbaNova University Centre, SE-106 91 Stockholm (Sweden); Adamo, Angela [Max Planck Institute for Astronomy, Königstuhl 17, D-69117 Heidelberg (Germany); Schaerer, Daniel [Université de Toulouse, UPS-OMP, IRAP, F-31000 Toulouse (France); Verhamme, Anne; Orlitová, Ivana [Geneva Observatory, University of Geneva, 51 Chemin des Maillettes, CH-1290 Versoix (Switzerland); Mas-Hesse, J. Miguel; Otí-Floranes, Héctor [Centro de Astrobiología (CSIC-INTA), Departamento de Astrofísica, P.O. Box 78, E-28691 Villanueva de la Cañada (Spain); Cannon, John M.; Pardy, Stephen [Department of Physics and Astronomy, Macalester College, 1600 Grand Avenue, Saint Paul, MN 55105 (United States); Atek, Hakim [Laboratoire dAstrophysique, École Polytechnique Fédérale de Lausanne (EPFL), Observatoire, CH-1290 Sauverny (Switzerland); Kunth, Daniel [Institut d' Astrophysique de Paris, UMR 7095, CNRS and UPMC, 98 bis Bd Arago, F-75014 Paris (France); Laursen, Peter [Dark Cosmology Centre, Niels Bohr Institute, University of Copenhagen, Juliane Maries Vej 30, DK-2100 Copenhagen (Denmark); Herenz, E. Christian, E-mail: matthew@astro.su.se [Leibniz-Institut für Astrophysik (AIP), An der Sternwarte 16, D-14482 Potsdam (Germany)

    2014-02-10

    We report new results regarding the Lyα output of galaxies, derived from the Lyman Alpha Reference Sample, and focused on Hubble Space Telescope imaging. For 14 galaxies we present intensity images in Lyα, Hα, and UV, and maps of Hα/Hβ, Lyα equivalent width (EW), and Lyα/Hα. We present Lyα and UV radial light profiles and show they are well-fitted by Sérsic profiles, but Lyα profiles show indices systematically lower than those of the UV (n ≈ 1-2 instead of ≳ 4). This reveals a general lack of the central concentration in Lyα that is ubiquitous in the UV. Photometric growth curves increase more slowly for Lyα than the far ultraviolet, showing that small apertures may underestimate the EW. For most galaxies, however, flux and EW curves flatten by radii ≈10 kpc, suggesting that if placed at high-z only a few of our galaxies would suffer from large flux losses. We compute global properties of the sample in large apertures, and show total Lyα luminosities to be independent of all other quantities. Normalized Lyα throughput, however, shows significant correlations: escape is found to be higher in galaxies of lower star formation rate, dust content, mass, and nebular quantities that suggest harder ionizing continuum and lower metallicity. Six galaxies would be selected as high-z Lyα emitters, based upon their luminosity and EW. We discuss the results in the context of high-z Lyα and UV samples. A few galaxies have EWs above 50 Å, and one shows f{sub esc}{sup Lyα} of 80%; such objects have not previously been reported at low-z.

  16. The Lyman alpha reference sample. II. Hubble space telescope imaging results, integrated properties, and trends

    International Nuclear Information System (INIS)

    Hayes, Matthew; Östlin, Göran; Duval, Florent; Sandberg, Andreas; Guaita, Lucia; Melinder, Jens; Rivera-Thorsen, Thøger; Adamo, Angela; Schaerer, Daniel; Verhamme, Anne; Orlitová, Ivana; Mas-Hesse, J. Miguel; Otí-Floranes, Héctor; Cannon, John M.; Pardy, Stephen; Atek, Hakim; Kunth, Daniel; Laursen, Peter; Herenz, E. Christian

    2014-01-01

    We report new results regarding the Lyα output of galaxies, derived from the Lyman Alpha Reference Sample, and focused on Hubble Space Telescope imaging. For 14 galaxies we present intensity images in Lyα, Hα, and UV, and maps of Hα/Hβ, Lyα equivalent width (EW), and Lyα/Hα. We present Lyα and UV radial light profiles and show they are well-fitted by Sérsic profiles, but Lyα profiles show indices systematically lower than those of the UV (n ≈ 1-2 instead of ≳ 4). This reveals a general lack of the central concentration in Lyα that is ubiquitous in the UV. Photometric growth curves increase more slowly for Lyα than the far ultraviolet, showing that small apertures may underestimate the EW. For most galaxies, however, flux and EW curves flatten by radii ≈10 kpc, suggesting that if placed at high-z only a few of our galaxies would suffer from large flux losses. We compute global properties of the sample in large apertures, and show total Lyα luminosities to be independent of all other quantities. Normalized Lyα throughput, however, shows significant correlations: escape is found to be higher in galaxies of lower star formation rate, dust content, mass, and nebular quantities that suggest harder ionizing continuum and lower metallicity. Six galaxies would be selected as high-z Lyα emitters, based upon their luminosity and EW. We discuss the results in the context of high-z Lyα and UV samples. A few galaxies have EWs above 50 Å, and one shows f esc Lyα of 80%; such objects have not previously been reported at low-z.

  17. A neural model for temporal order judgments and their active recalibration: a common mechanism for space and time?

    Directory of Open Access Journals (Sweden)

    Mingbo eCai

    2012-11-01

    Full Text Available When observers experience a constant delay between their motor actions and sensory feedback, their perception of the temporal order between actions and sensations adapt (Stetson et al., 2006a. We present here a novel neural model that can explain temporal order judgments (TOJs and their recalibration. Our model employs three ubiquitous features of neural systems: 1 information pooling, 2 opponent processing, and 3 synaptic scaling. Specifically, the model proposes that different populations of neurons encode different delays between motor-sensory events, the outputs of these populations feed into rivaling neural populations (encoding before and after, and the activity difference between these populations determines the perceptual judgment. As a consequence of synaptic scaling of input weights, motor acts which are consistently followed by delayed sensory feedback will cause the network to recalibrate its point of subjective simultaneity. The structure of our model raises the possibility that recalibration of TOJs is a temporal analogue to the motion aftereffect. In other words, identical neural mechanisms may be used to make perceptual determinations about both space and time. Our model captures behavioral recalibration results for different numbers of adapting trials and different adapting delays. In line with predictions of the model, we additionally demonstrate that temporal recalibration can last through time, in analogy to storage of the motion aftereffect.

  18. Identifying the relevant dependencies of the neural network response on characteristics of the input space

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    This talk presents an approach to identify those characteristics of the neural network inputs that are most relevant for the response and therefore provides essential information to determine the systematic uncertainties.

  19. A method of camera calibration in the measurement process with reference mark for approaching observation space target

    Science.gov (United States)

    Zhang, Hua; Zeng, Luan

    2017-11-01

    Binocular stereoscopic vision can be used for space-based space targets near observation. In order to solve the problem that the traditional binocular vision system cannot work normally after interference, an online calibration method of binocular stereo measuring camera with self-reference is proposed. The method uses an auxiliary optical imaging device to insert the image of the standard reference object into the edge of the main optical path and image with the target on the same focal plane, which is equivalent to a standard reference in the binocular imaging optical system; When the position of the system and the imaging device parameters are disturbed, the image of the standard reference will change accordingly in the imaging plane, and the position of the standard reference object does not change. The camera's external parameters can be re-calibrated by the visual relationship of the standard reference object. The experimental results show that the maximum mean square error of the same object can be reduced from the original 72.88mm to 1.65mm when the right camera is deflected by 0.4 degrees and the left camera is high and low with 0.2° rotation. This method can realize the online calibration of binocular stereoscopic vision measurement system, which can effectively improve the anti - jamming ability of the system.

  20. Life Sciences Space Station planning document: A reference payload for the Life Sciences Research Facility

    Science.gov (United States)

    1986-01-01

    The Space Station, projected for construction in the early 1990s, will be an orbiting, low-gravity, permanently manned facility providing unprecedented opportunities for scientific research. Facilities for Life Sciences research will include a pressurized research laboratory, attached payloads, and platforms which will allow investigators to perform experiments in the crucial areas of Space Medicine, Space Biology, Exobiology, Biospherics and Controlled Ecological Life Support System (CELSS). These studies are designed to determine the consequences of long-term exposure to space conditions, with particular emphasis on assuring the permanent presence of humans in space. The applied and basic research to be performed, using humans, animals, and plants, will increase our understanding of the effects of the space environment on basic life processes. Facilities being planned for remote observations from platforms and attached payloads of biologically important elements and compounds in space and on other planets (Exobiology) will permit exploration of the relationship between the evolution of life and the universe. Space-based, global scale observations of terrestrial biology (Biospherics) will provide data critical for understanding and ultimately managing changes in the Earth's ecosystem. The life sciences community is encouraged to participate in the research potential the Space Station facilities will make possible. This document provides the range and scope of typical life sciences experiments which could be performed within a pressurized laboratory module on Space Station.

  1. Real-time estimation of free spaces in regulated on-street parking spaces using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Magaña Suarez, M.

    2016-07-01

    In this paper we will develop a methodology for estimating the percentage of free parking spaces available in the area of the city where a user is interested through a real-time query in a mobile app. The smartphone screen will provide a colour-coded map of the requested area that indicates the saturation state of the parking spaces. (Author)

  2. Identification of Abnormal System Noise Temperature Patterns in Deep Space Network Antennas Using Neural Network Trained Fuzzy Logic

    Science.gov (United States)

    Lu, Thomas; Pham, Timothy; Liao, Jason

    2011-01-01

    This paper presents the development of a fuzzy logic function trained by an artificial neural network to classify the system noise temperature (SNT) of antennas in the NASA Deep Space Network (DSN). The SNT data were classified into normal, marginal, and abnormal classes. The irregular SNT pattern was further correlated with link margin and weather data. A reasonably good correlation is detected among high SNT, low link margin and the effect of bad weather; however we also saw some unexpected non-correlations which merit further study in the future.

  3. Reference Management Methodologies for Large Structural Models at Kennedy Space Center

    Science.gov (United States)

    Jones, Corey; Bingham, Ryan; Schmidt, Rick

    2011-01-01

    There have been many challenges associated with modeling some of NASA KSC's largest structures. Given the size of the welded structures here at KSC, it was critically important to properly organize model struc.ture and carefully manage references. Additionally, because of the amount of hardware to be installed on these structures, it was very important to have a means to coordinate between different design teams and organizations, check for interferences, produce consistent drawings, and allow for simple release processes. Facing these challenges, the modeling team developed a unique reference management methodology and model fidelity methodology. This presentation will describe the techniques and methodologies that were developed for these projects. The attendees will learn about KSC's reference management and model fidelity methodologies for large structures. The attendees will understand the goals of these methodologies. The attendees will appreciate the advantages of developing a reference management methodology.

  4. Model Reference Adaptive Control of the Air Flow Rate of Centrifugal Compressor Using State Space Method

    International Nuclear Information System (INIS)

    Han, Jaeyoung; Jung, Mooncheong; Yu, Sangseok; Yi, Sun

    2016-01-01

    In this study, a model reference adaptive controller is developed to regulate the outlet air flow rate of centrifugal compressor for automotive supercharger. The centrifugal compressor is developed using the analytical based method to predict the transient behavior of operating and the designed model is validated with experimental data to confirm the system accuracy. The model reference adaptive control structure consists of a compressor model and a MRAC(model reference adaptive control) mechanism. The feedback control do not robust with variation of system parameter but the applied adaptive control is robust even if the system parameter is changed. As a result, the MRAC was regulated to reference air flow rate. Also MRAC was found to be more robust control compared with the feedback control even if the system parameter is changed.

  5. Model Reference Adaptive Control of the Air Flow Rate of Centrifugal Compressor Using State Space Method

    Energy Technology Data Exchange (ETDEWEB)

    Han, Jaeyoung; Jung, Mooncheong; Yu, Sangseok [Chungnam Nat’l Univ., Daejeon (Korea, Republic of); Yi, Sun [North Carolina A and T State Univ., Raleigh (United States)

    2016-08-15

    In this study, a model reference adaptive controller is developed to regulate the outlet air flow rate of centrifugal compressor for automotive supercharger. The centrifugal compressor is developed using the analytical based method to predict the transient behavior of operating and the designed model is validated with experimental data to confirm the system accuracy. The model reference adaptive control structure consists of a compressor model and a MRAC(model reference adaptive control) mechanism. The feedback control do not robust with variation of system parameter but the applied adaptive control is robust even if the system parameter is changed. As a result, the MRAC was regulated to reference air flow rate. Also MRAC was found to be more robust control compared with the feedback control even if the system parameter is changed.

  6. Knowledge-based approach for functional MRI analysis by SOM neural network using prior labels from Talairach stereotaxic space

    Science.gov (United States)

    Erberich, Stephan G.; Willmes, Klaus; Thron, Armin; Oberschelp, Walter; Huang, H. K.

    2002-04-01

    Among the methods proposed for the analysis of functional MR we have previously introduced a model-independent analysis based on the self-organizing map (SOM) neural network technique. The SOM neural network can be trained to identify the temporal patterns in voxel time-series of individual functional MRI (fMRI) experiments. The separated classes consist of activation, deactivation and baseline patterns corresponding to the task-paradigm. While the classification capability of the SOM is not only based on the distinctness of the patterns themselves but also on their frequency of occurrence in the training set, a weighting or selection of voxels of interest should be considered prior to the training of the neural network to improve pattern learning. Weighting of interesting voxels by means of autocorrelation or F-test significance levels has been used successfully, but still a large number of baseline voxels is included in the training. The purpose of this approach is to avoid the inclusion of these voxels by using three different levels of segmentation and mapping from Talairach space: (1) voxel partitions at the lobe level, (2) voxel partitions at the gyrus level and (3) voxel partitions at the cell level (Brodmann areas). The results of the SOM classification based on these mapping levels in comparison to training with all brain voxels are presented in this paper.

  7. Habituation to novel visual vestibular environments with special reference to space flight

    Science.gov (United States)

    Young, L. R.; Kenyon, R. V.; Oman, C. M.

    1981-01-01

    The etiology of space motion sickness and the underlying physiological mechanisms associated with spatial orientation in a space environment were investigated. Human psychophysical experiments were used as the basis for the research concerning the interaction of visual and vestibular cues in the development of motion sickness. Particular emphasis is placed on the conflict theory in terms of explaining these interactions. Research on the plasticity of the vestibulo-ocular reflex is discussed.

  8. Docking Offset Between the Space Shuttle and the International Space Station and Resulting Impacts to the Transfer of Attitude Reference and Control

    Science.gov (United States)

    Helms, W. Jason; Pohlkamp, Kara M.

    2011-01-01

    The Space Shuttle does not dock at an exact 90 degrees to the International Space Station (ISS) x-body axis. This offset from 90 degrees, along with error sources within their respective attitude knowledge, causes the two vehicles to never completely agree on their attitude, even though they operate as a single, mated stack while docked. The docking offset can be measured in flight when both vehicles have good attitude reference and is a critical component in calculations to transfer attitude reference from one vehicle to another. This paper will describe how the docking offset and attitude reference errors between both vehicles are measured and how this information would be used to recover Shuttle attitude reference from ISS in the event of multiple failures. During STS-117, ISS on-board Guidance, Navigation and Control (GNC) computers began having problems and after several continuous restarts, the systems failed. The failure took the ability for ISS to maintain attitude knowledge. This paper will also demonstrate how with knowledge of the docking offset, the contingency procedure to recover Shuttle attitude reference from ISS was reversed in order to provide ISS an attitude reference from Shuttle. Finally, this paper will show how knowledge of the docking offset can be used to speed up attitude control handovers from Shuttle to ISS momentum management. By taking into account the docking offset, Shuttle can be commanded to hold a more precise attitude which better agrees with the ISS commanded attitude such that start up transients with the ISS momentum management controllers are reduced. By reducing start-up transients, attitude control can be transferred from Shuttle to ISS without the use of ISS thrusters saving precious on-board propellant, crew time and minimizing loads placed upon the mated stack.

  9. Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank

    OpenAIRE

    Zhao, Liang; Liao, Siyu; Wang, Yanzhi; Li, Zhe; Tang, Jian; Pan, Victor; Yuan, Bo

    2017-01-01

    Recently low displacement rank (LDR) matrices, or so-called structured matrices, have been proposed to compress large-scale neural networks. Empirical results have shown that neural networks with weight matrices of LDR matrices, referred as LDR neural networks, can achieve significant reduction in space and computational complexity while retaining high accuracy. We formally study LDR matrices in deep learning. First, we prove the universal approximation property of LDR neural networks with a ...

  10. Assessment of the possible contribution of space ties on-board GNSS satellites to the terrestrial reference frame

    Science.gov (United States)

    Bruni, Sara; Rebischung, Paul; Zerbini, Susanna; Altamimi, Zuheir; Errico, Maddalena; Santi, Efisio

    2018-04-01

    The realization of the international terrestrial reference frame (ITRF) is currently based on the data provided by four space geodetic techniques. The accuracy of the different technique-dependent materializations of the frame physical parameters (origin and scale) varies according to the nature of the relevant observables and to the impact of technique-specific errors. A reliable computation of the ITRF requires combining the different inputs, so that the strengths of each technique can compensate for the weaknesses of the others. This combination, however, can only be performed providing some additional information which allows tying together the independent technique networks. At present, the links used for that purpose are topometric surveys (local/terrestrial ties) available at ITRF sites hosting instruments of different techniques. In principle, a possible alternative could be offered by spacecrafts accommodating the positioning payloads of multiple geodetic techniques realizing their co-location in orbit (space ties). In this paper, the GNSS-SLR space ties on-board GPS and GLONASS satellites are thoroughly examined in the framework of global reference frame computations. The investigation focuses on the quality of the realized physical frame parameters. According to the achieved results, the space ties on-board GNSS satellites cannot, at present, substitute terrestrial ties in the computation of the ITRF. The study is completed by a series of synthetic simulations investigating the impact that substantial improvements in the volume and quality of SLR observations to GNSS satellites would have on the precision of the GNSS frame parameters.

  11. Prediction of Optimal Design and Deflection of Space Structures Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Reza Kamyab Moghadas

    2012-01-01

    Full Text Available The main aim of the present work is to determine the optimal design and maximum deflection of double layer grids spending low computational cost using neural networks. The design variables of the optimization problem are cross-sectional area of the elements as well as the length of the span and height of the structures. In this paper, a number of double layer grids with various random values of length and height are selected and optimized by simultaneous perturbation stochastic approximation algorithm. Then, radial basis function (RBF and generalized regression (GR neural networks are trained to predict the optimal design and maximum deflection of the structures. The numerical results demonstrate the efficiency of the proposed methodology.

  12. Neural stem cell heterogeneity through time and space in the ventricular-subventricular zone.

    Science.gov (United States)

    Rushing, Gabrielle; Ihrie, Rebecca A

    2016-08-01

    The origin and classification of neural stem cells (NSCs) has been a subject of intense investigation for the past two decades. Efforts to categorize NSCs based on their location, function and expression have established that these cells are a heterogeneous pool in both the embryonic and adult brain. The discovery and additional characterization of adult NSCs has introduced the possibility of using these cells as a source for neuronal and glial replacement following injury or disease. To understand how one could manipulate NSC developmental programs for therapeutic use, additional work is needed to elucidate how NSCs are programmed and how signals during development are interpreted to determine cell fate. This review describes the identification, classification and characterization of NSCs within the large neurogenic niche of the ventricular-subventricular zone (V-SVZ). A literature search was conducted using Pubmed including the keywords "ventricular-subventricular zone," "neural stem cell," "heterogeneity," "identity" and/or "single cell" to find relevant manuscripts to include within the review. A special focus was placed on more recent findings using single-cell level analyses on neural stem cells within their niche(s). This review discusses over 20 research articles detailing findings on V-SVZ NSC heterogeneity, over 25 articles describing fate determinants of NSCs, and focuses on 8 recent publications using distinct single-cell analyses of neural stem cells including flow cytometry and RNA-seq. Additionally, over 60 manuscripts highlighting the markers expressed on cells within the NSC lineage are included in a chart divided by cell type. Investigation of NSC heterogeneity and fate decisions is ongoing. Thus far, much research has been conducted in mice however, findings in human and other mammalian species are also discussed here. Implications of NSC heterogeneity established in the embryo for the properties of NSCs in the adult brain are explored, including

  13. Out of body, out of space: Impaired reference frame processing in eating disorders.

    Science.gov (United States)

    Serino, Silvia; Dakanalis, Antonios; Gaudio, Santino; Carrà, Giuseppe; Cipresso, Pietro; Clerici, Massimo; Riva, Giuseppe

    2015-12-15

    A distorted body representation is a core symptom in eating disorders (EDs), though its mechanism is unclear. Allocentric lock theory, emphasising the role of reference frame processing in body image, suggests that ED patients may be (b)locked to an (allocentric) representation of their own body stored in long-term memory (e.g., my body is fat) that is not updated (modified) by the (real-time egocentric) perception-driven experience of the physical body. Employing a well-validated virtual reality-based procedure, relative to healthy controls, ED patients showed deficits in the ability to refer to and update a long-term stored (allocentric) representation with (egocentric) perceptual-driven inputs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  14. Neural Response After a Single ECT Session During Retrieval of Emotional Self-Referent Words in Depression

    DEFF Research Database (Denmark)

    Miskowiak, Kamilla W; Macoveanu, Julian; Jørgensen, Martin B

    2018-01-01

    of their electroconvulsive therapy course in a double-blind, between-groups design. The following day, patients were given a self-referential emotional word categorization test and a free recall test. This was followed by an incidental word recognition task during whole-brain functional magnetic resonance imaging at 3T...... response may reflect early facilitation of memory for positive self-referent information, which could contribute to improvements in depressive symptoms including feelings of self-worth with repeated treatments....

  15. The role of space communication in promoting national development with specific reference to experiments conducted in India

    Science.gov (United States)

    Chitnis, E. V.

    The paper describes the role of space communication in promoting national development with special reference to experiments conducted in India, namely SITE (1975-1976), STEP (1977-1979) and APPLE (1981 onwards). The impact of these experiments in economic, cultural and educational terms are discussed, pointing out social implications involved in using advance space communication technology for instruction and information in the areas of education, national integration and development. The paper covers special requirements which arise when a communication system covers backward and remote rural areas in a developing country. The impact on the population measured by conducting social surveys has been discussed - especially the gains of predominently illiterate new media - participants have been highlighted. Possibilities of improving skills of teachers, the quality of the primary and higher education have been covered. The preparation required both on ground as well as space to derive benefits of space technology are considered. A profile of INSAT which marks the culmination of the experimental phase and the beginning of operational domestic satellite system is sketched.

  16. Artificial Neural Network Test Support Development for the Space Shuttle PRCS Thrusters

    Science.gov (United States)

    Lehr, Mark E.

    2005-01-01

    A significant anomaly, Fuel Valve Pilot Seal Extrusion, is affecting the Shuttle Primary Reaction Control System (PRCS) Thrusters, and has caused 79 to fail. To help address this problem, a Shuttle PRCS Thruster Process Evaluation Team (TPET) was formed. The White Sands Test Facility (WSTF) and Boeing members of the TPET have identified many discrete valve current trace characteristics that are predictive of the problem. However, these are difficult and time consuming to identify and trend by manual analysis. Based on this exhaustive analysis over months, 22 thrusters previously delivered by the Depot were identified as high risk for flight failures. Although these had only recently been installed, they had to be removed from Shuttles OV103 and OV104 for reprocessing, by directive of the Shuttle Project Office. The resulting impact of the thruster removal, replacement, and valve replacement was significant (months of work and hundreds of thousands of dollars). Much of this could have been saved had the proposed Neural Network (NN) tool described in this paper been in place. In addition to the significant benefits to the Shuttle indicated above, the development and implementation of this type of testing will be the genesis for potential Quality improvements across many areas of WSTF test data analysis and will be shared with other NASA centers. Future tests can be designed to incorporate engineering experience via Artificial Neural Nets (ANN) into depot level acceptance of hardware. Additionally, results were shared with a NASA Engineering and Safety Center (NESC) Super Problem Response Team (SPRT). There was extensive interest voiced among many different personnel from several centers. There are potential spin-offs of this effort that can be directly applied to other data acquisition systems as well as vehicle health management for current and future flight vehicles.

  17. Sustainable Spaces with Psychological Values: Historical Architecture as Reference Book for Biomimetic Models with Biophilic Qualities

    Directory of Open Access Journals (Sweden)

    Nely Ramzy

    2015-07-01

    Full Text Available Biomimicry is a growing area of interest in architecture due to the potentials it offers for innovative architectural solutions and for more sustainable, regenerative built environment. Yet, a growing body of research identified various deficiencies to the employment of this approach in architecture. Of particular note are that: first, some biomimetic technologies are not inherently more sustainable or Nature-friendly than conventional equivalents; second, they lack any spatial expression of Nature and are visually ill-integrated into it. In a trial to redeem these deficiencies, this paper suggests a frame-work for more sustainable strategy that combines this approach with the relative approach of "Biophilia", with reference to examples from historical architecture. Using pioneering strategies and applications from different historical styles, the paper shows that the combination of these two approaches may lead to enhanced outcomes in terms of sustainability as well as human psychology and well-being. In doing so, architects may go beyond simply mimicking Nature to synthesizing architecture in tune with it and bringing in bio-inspired solutions that is more responsive to human needs and well-being.

  18. A Rapid Identification Method for Calamine Using Near-Infrared Spectroscopy Based on Multi-Reference Correlation Coefficient Method and Back Propagation Artificial Neural Network.

    Science.gov (United States)

    Sun, Yangbo; Chen, Long; Huang, Bisheng; Chen, Keli

    2017-07-01

    As a mineral, the traditional Chinese medicine calamine has a similar shape to many other minerals. Investigations of commercially available calamine samples have shown that there are many fake and inferior calamine goods sold on the market. The conventional identification method for calamine is complicated, therefore as a result of the large scale of calamine samples, a rapid identification method is needed. To establish a qualitative model using near-infrared (NIR) spectroscopy for rapid identification of various calamine samples, large quantities of calamine samples including crude products, counterfeits and processed products were collected and correctly identified using the physicochemical and powder X-ray diffraction method. The NIR spectroscopy method was used to analyze these samples by combining the multi-reference correlation coefficient (MRCC) method and the error back propagation artificial neural network algorithm (BP-ANN), so as to realize the qualitative identification of calamine samples. The accuracy rate of the model based on NIR and MRCC methods was 85%; in addition, the model, which took comprehensive multiple factors into consideration, can be used to identify crude calamine products, its counterfeits and processed products. Furthermore, by in-putting the correlation coefficients of multiple references as the spectral feature data of samples into BP-ANN, a BP-ANN model of qualitative identification was established, of which the accuracy rate was increased to 95%. The MRCC method can be used as a NIR-based method in the process of BP-ANN modeling.

  19. Astrocytic mechanisms explaining neural-activity-induced shrinkage of extraneuronal space

    DEFF Research Database (Denmark)

    Østby, Ivar; Øyehaug, Leiv; Einevoll, Gaute T

    2009-01-01

    Neuronal stimulation causes approximately 30% shrinkage of the extracellular space (ECS) between neurons and surrounding astrocytes in grey and white matter under experimental conditions. Despite its possible implications for a proper understanding of basic aspects of potassium clearance and astr......Neuronal stimulation causes approximately 30% shrinkage of the extracellular space (ECS) between neurons and surrounding astrocytes in grey and white matter under experimental conditions. Despite its possible implications for a proper understanding of basic aspects of potassium clearance...... concentrations observed in connection with neuronal stimulation, the actions of the Na(+)/K(+)/Cl(-) (NKCC1) and the Na(+)/HCO(3) (-) (NBC) cotransporters appear to be critical determinants for achieving observed quantitative levels of ECS shrinkage. Considering the current state of knowledge, the model...

  20. Estimação da evapotranspiração de referência no estado do Rio de Janeiro usando redes neurais artificiais Reference evapotranspiration estimate in Rio de Janeiro state using artificial neural networks

    Directory of Open Access Journals (Sweden)

    Sidney S. Zanetti

    2008-04-01

    Full Text Available Propor uma rede neural artificial (RNA para estimar a evapotranspiração de referência (ETo em função das coordenadas de posição geográfica e da temperatura do ar no Estado do Rio de Janeiro, motivou a realização do presente estudo. Os dados utilizados no treinamento da rede foram obtidos de 17 séries históricas de elementos climáticos localizadas nesse Estado. A ETo diária calculada pelo método de Penman-Monteith (FAO-56 foi utilizada como referência para treinar as redes. As RNAs, do tipo perceptron de múltiplas camadas, foram treinadas para estimar a ETo em função da latitude, longitude, altitude, temperatura média do ar, amplitude térmica diária e dia do ano. Após o treinamento com várias configurações de rede, selecionou-se a que apresentou o melhor desempenho, a qual é composta de apenas uma camada intermediária (com vinte neurônios e função de ativação do tipo sigmóide logística e uma camada de saída (com um neurônio e função de ativação linear. Pelos resultados obtidos conclui-se que, levando-se em consideração apenas as coordenadas de posição geográfica e a temperatura do ar, pode-se estimar a ETo (valores diários em 17 localidades do Estado do Rio de Janeiro usando uma RNA.This work was performed with the aim of proposing an artificial neural network (ANN to estimate the reference evapotranspiration (ETo as a function of geographic position coordinates and air temperature in the State of Rio de Janeiro. Data used for the network training were collected from 17 historical time series of climatic elements located in the State of Rio de Janeiro. The daily ETo calculated by Penman-Monteith (FAO-56 method was used as a reference for network training. ANNs of multilayer perceptron type were trained to estimate ETo as a function of latitude, longitude, altitude, mean air temperature, thermal daily amplitude and day of the year. After training with different network configurations, the one showing

  1. Aural localization of silent objects by active human biosonar: neural representations of virtual echo-acoustic space.

    Science.gov (United States)

    Wallmeier, Ludwig; Kish, Daniel; Wiegrebe, Lutz; Flanagin, Virginia L

    2015-03-01

    Some blind humans have developed the remarkable ability to detect and localize objects through the auditory analysis of self-generated tongue clicks. These echolocation experts show a corresponding increase in 'visual' cortex activity when listening to echo-acoustic sounds. Echolocation in real-life settings involves multiple reflections as well as active sound production, neither of which has been systematically addressed. We developed a virtualization technique that allows participants to actively perform such biosonar tasks in virtual echo-acoustic space during magnetic resonance imaging (MRI). Tongue clicks, emitted in the MRI scanner, are picked up by a microphone, convolved in real time with the binaural impulse responses of a virtual space, and presented via headphones as virtual echoes. In this manner, we investigated the brain activity during active echo-acoustic localization tasks. Our data show that, in blind echolocation experts, activations in the calcarine cortex are dramatically enhanced when a single reflector is introduced into otherwise anechoic virtual space. A pattern-classification analysis revealed that, in the blind, calcarine cortex activation patterns could discriminate left-side from right-side reflectors. This was found in both blind experts, but the effect was significant for only one of them. In sighted controls, 'visual' cortex activations were insignificant, but activation patterns in the planum temporale were sufficient to discriminate left-side from right-side reflectors. Our data suggest that blind and echolocation-trained, sighted subjects may recruit different neural substrates for the same active-echolocation task. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  2. PHOTOMETRIC OBSERVATIONS OF SELECTED, OPTICALLY BRIGHT QUASARS FOR SPACE INTERFEROMETRY MISSION AND OTHER FUTURE CELESTIAL REFERENCE FRAMES

    International Nuclear Information System (INIS)

    Ojha, Roopesh; Zacharias, Norbert; Hennessy, Gregory S.; Gaume, Ralph A.; Johnston, Kenneth J.

    2009-01-01

    Photometric observations of 235 extragalactic objects that are potential targets for the Space Interferometry Mission (SIM) are presented. Mean B, V, R, I magnitudes at the 5% level are obtained at 1-4 epochs between 2005 and 2007 using the 1 m telescopes at Cerro Tololo Inter-American Observatory and the Naval Observatory Flagstaff Station. Of the 134 sources that have V magnitudes in the Veron and Veron-Cetty catalog, a difference of over 1.0 mag is found for the observed-catalog magnitudes for about 36% of the common sources, and 10 sources show over 3 mag difference. Our first set of observations presented here form the basis of a long-term photometric variability study of the selected reference frame sources to assist in mission target selection and to support QSO multicolor photometric variability studies in general.

  3. Neural Response After a Single ECT Session During Retrieval of Emotional Self-Referent Words in Depression: A Randomized, Sham-Controlled fMRI Study

    Science.gov (United States)

    Miskowiak, Kamilla W; Macoveanu, Julian; Jørgensen, Martin B; Støttrup, Mette M; Ott, Caroline V; Jensen, Hans M; Jørgensen, Anders; Harmer, J; Paulson, Olaf B; Kessing, Lars V; Siebner, Hartwig R

    2018-01-01

    Abstract Background Negative neurocognitive bias is a core feature of depression that is reversed by antidepressant drug treatment. However, it is unclear whether modulation of neurocognitive bias is a common mechanism of distinct biological treatments. This randomized controlled functional magnetic resonance imaging study explored the effects of a single electroconvulsive therapy session on self-referent emotional processing. Methods Twenty-nine patients with treatment-resistant major depressive disorder were randomized to one active or sham electroconvulsive therapy session at the beginning of their electroconvulsive therapy course in a double-blind, between-groups design. The following day, patients were given a self-referential emotional word categorization test and a free recall test. This was followed by an incidental word recognition task during whole-brain functional magnetic resonance imaging at 3T. Mood was assessed at baseline, on the functional magnetic resonance imaging day, and after 6 electroconvulsive therapy sessions. Data were complete and analyzed for 25 patients (electroconvulsive therapy: n = 14, sham: n = 11). The functional magnetic resonance imaging data were analyzed using the FMRIB Software Library randomize algorithm, and the Threshold-Free Cluster Enhancement method was used to identify significant clusters (corrected at P words. However, electroconvulsive therapy reduced the retrieval-specific neural response for positive words in the left frontopolar cortex. This effect occurred in the absence of differences between groups in behavioral performance or mood symptoms. Conclusions The observed effect of electroconvulsive therapy on prefrontal response may reflect early facilitation of memory for positive self-referent information, which could contribute to improvements in depressive symptoms including feelings of self-worth with repeated treatments. PMID:29718333

  4. Independent Aftereffects of Fat and Muscle: Implications for neural encoding, body space representation, and body image disturbance

    Science.gov (United States)

    Sturman, Daniel; Stephen, Ian D.; Mond, Jonathan; Stevenson, Richard J; Brooks, Kevin R.

    2017-01-01

    Although research addressing body size misperception has focused on socio-cognitive processes, such as internalization of the “ideal” images of bodies in the media, the perceptual basis of this phenomenon remains largely unknown. Further, most studies focus on body size per se even though this depends on both fat and muscle mass – variables that have very different relationships with health. We tested visual adaptation as a mechanism for inducing body fat and muscle mass misperception, and assessed whether these two dimensions of body space are processed independently. Observers manipulated the apparent fat and muscle mass of bodies to make them appear “normal” before and after inspecting images from one of four adaptation conditions (increased fat/decreased fat/increased muscle/decreased muscle). Exposure resulted in a shift in the point of subjective normality in the direction of the adapting images along the relevant (fat or muscle) axis, suggesting that the neural mechanisms involved in body fat and muscle perception are independent. This supports the viability of adaptation as a model of real-world body size misperception, and extends its applicability to clinical manifestations of body image disturbance that entail not only preoccupation with thinness (e.g., anorexia nervosa) but also with muscularity (e.g., muscle dysmorphia). PMID:28071712

  5. Astrocytic mechanisms explaining neural-activity-induced shrinkage of extraneuronal space.

    Directory of Open Access Journals (Sweden)

    Ivar Østby

    2009-01-01

    Full Text Available Neuronal stimulation causes approximately 30% shrinkage of the extracellular space (ECS between neurons and surrounding astrocytes in grey and white matter under experimental conditions. Despite its possible implications for a proper understanding of basic aspects of potassium clearance and astrocyte function, the phenomenon remains unexplained. Here we present a dynamic model that accounts for current experimental data related to the shrinkage phenomenon in wild-type as well as in gene knockout individuals. We find that neuronal release of potassium and uptake of sodium during stimulation, astrocyte uptake of potassium, sodium, and chloride in passive channels, action of the Na/K/ATPase pump, and osmotically driven transport of water through the astrocyte membrane together seem sufficient for generating ECS shrinkage as such. However, when taking into account ECS and astrocyte ion concentrations observed in connection with neuronal stimulation, the actions of the Na(+/K(+/Cl(- (NKCC1 and the Na(+/HCO(3 (- (NBC cotransporters appear to be critical determinants for achieving observed quantitative levels of ECS shrinkage. Considering the current state of knowledge, the model framework appears sufficiently detailed and constrained to guide future key experiments and pave the way for more comprehensive astroglia-neuron interaction models for normal as well as pathophysiological situations.

  6. Space weather modeling using artificial neural network. (Slovak Title: Modelovanie kozmického počasia umelou neurónovou sietou)

    Science.gov (United States)

    Valach, F.; Revallo, M.; Hejda, P.; Bochníček, J.

    2010-12-01

    Our modern society with its advanced technology is becoming increasingly vulnerable to the Earth's system disorders originating in explosive processes on the Sun. Coronal mass ejections (CMEs) blasted into interplanetary space as gigantic clouds of ionized gas can hit Earth within a few hours or days and cause, among other effects, geomagnetic storms - perhaps the best known manifestation of solar wind interaction with Earth's magnetosphere. Solar energetic particles (SEP), accelerated to near relativistic energy during large solar storms, arrive at the Earth's orbit even in few minutes and pose serious risk to astronauts traveling through the interplanetary space. These and many other threats are the reason why experts pay increasing attention to space weather and its predictability. For research on space weather, it is typically necessary to examine a large number of parameters which are interrelated in a complex non-linear way. One way to cope with such a task is to use an artificial neural network for space weather modeling, a tool originally developed for artificial intelligence. In our contribution, we focus on practical aspects of the neural networks application to modeling and forecasting selected space weather parameters.

  7. The CERN-EU high-energy reference field (CERF) facility for dosimetry at commercial flight altitudes and in space.

    Science.gov (United States)

    Mitaroff, A; Cern, M Silari

    2002-01-01

    A reference facility for the calibration and intercomparison of active and passive detectors in broad neutron fields has been available at CERN since 1992. A positively charged hadron beam (a mixture of protons and pions) with momentum of 120 GeV/c hits a copper target, 50 cm thick and 7 cm in diameter. The secondary particles produced in the interaction traverse a shield, at 90 degrees with respect to the direction of the incoming beam. made of either 80 to 160 cm of concrete or 40 cm of iron. Behind the iron shield, the resulting neutron spectrum has a maximum at about 1 MeV, with an additional high-energy component. Behind the 80 cm concrete shield, the neutron spectrum has a second pronounced maximum at about 70 MeV and resembles the high-energy component of the radiation field created by cosmic rays at commercial flight altitudes. This paper describes the facility, reports on the latest neutron spectral measurements, gives an overview of the most important experiments performed by the various collaborating institutions over recent years and briefly addresses the possible application of the facility to measurements related to the space programme.

  8. Network Events on Multiple Space and Time Scales in Cultured Neural Networks and in a Stochastic Rate Model.

    Directory of Open Access Journals (Sweden)

    Guido Gigante

    2015-11-01

    Full Text Available Cortical networks, in-vitro as well as in-vivo, can spontaneously generate a variety of collective dynamical events such as network spikes, UP and DOWN states, global oscillations, and avalanches. Though each of them has been variously recognized in previous works as expression of the excitability of the cortical tissue and the associated nonlinear dynamics, a unified picture of the determinant factors (dynamical and architectural is desirable and not yet available. Progress has also been partially hindered by the use of a variety of statistical measures to define the network events of interest. We propose here a common probabilistic definition of network events that, applied to the firing activity of cultured neural networks, highlights the co-occurrence of network spikes, power-law distributed avalanches, and exponentially distributed 'quasi-orbits', which offer a third type of collective behavior. A rate model, including synaptic excitation and inhibition with no imposed topology, synaptic short-term depression, and finite-size noise, accounts for all these different, coexisting phenomena. We find that their emergence is largely regulated by the proximity to an oscillatory instability of the dynamics, where the non-linear excitable behavior leads to a self-amplification of activity fluctuations over a wide range of scales in space and time. In this sense, the cultured network dynamics is compatible with an excitation-inhibition balance corresponding to a slightly sub-critical regime. Finally, we propose and test a method to infer the characteristic time of the fatigue process, from the observed time course of the network's firing rate. Unlike the model, possessing a single fatigue mechanism, the cultured network appears to show multiple time scales, signalling the possible coexistence of different fatigue mechanisms.

  9. Can space ties on board GNSS satellites replace terrestrial ties in the implementation of Terrestrial Reference Frames?

    Science.gov (United States)

    Bruni, Sara; Zerbini, Susanna; Altamimi, Zuheir; Rebischung, Paul; Errico, Maddalena; Santi, Efisio

    2016-04-01

    The realization of Terrestrial Reference Frames (TRFs) must be periodically updated in order to account for newly acquired observations and for upgrades in data analysis procedures and/or combination techniques. Any innovative computation strategy should ameliorate the definition of the frame physical parameters, upon which a number of scientific applications critically rely. On the basis of the requirements of scientific cutting edge studies, the geodetic community has estimated that the present day challenge in the determination of TRFs is to provide a frame that is accurate and long-term stable at the level of 1 mm and 0.1 mm/y respectively. This work aims at characterizing the frame realized by a combination of Satellite Laser Ranging (SLR) and Global Navigation Satellite Systems (GNSS) observations via their co-location on board GNSS spacecrafts. In particular, it is established how such a frame compares to the traditional ITRF computation and what is the impact on the realization of the frame origin and scale. Four years of data from a global network encompassing about one hundred GNSS stations and all SLR sites have been analyzed. In order to ensure the highest possible consistency, the raw data of both techniques are treated with the same analysis Software (Bernese GNSS Software 5.2) following IERS2010 Conventions. Both weekly and long term solutions are carried out exploiting either the Bernese or the Combination and Analysis of Terrestrial Reference Frames (CATREF) Software packages. We present the results of a combination study involving GNSS data and SLR observations to the two LAGEOS and to the GNSS satellites equipped with retroreflector arrays. The latter type of measurements is currently not included in the computation of the official ITRF solutions. The assessment of the benefit that they could provide to the definition of the origin and scale of the ITRF is however worth investigating, as such data provide the potential for linking the GNSS and

  10. Selected Legal Challenges Relating to the Military use of Outer Space, with Specific Reference to Article IV of the Outer Space Treaty

    Directory of Open Access Journals (Sweden)

    Anél Ferreira-Snyman

    2015-12-01

    Full Text Available Since the end of the Second World War the potential use of outer space for military purposes persisted to be intrinsically linked to the development of space technology and space flight. The launch of the first artificial satellite, Sputnik 1, by the USSR in 1957 made Western states realise that a surprise attack from space was a real possibility, resulting in the so-called "space-race" between the USA and the USSR. During the Cold War space activities were intrinsically linked to the political objectives, priorities and national security concerns of the USA and the Soviet Union. After the Cold War the political relevance and benefits of space continued to be recognised by states. In view of the recent emergence of new major space powers such as China, the focus has again shifted to the military use of outer space and the potential that a state with advanced space technology may use it for military purposes in order to dominate other states. Article IV of the Outer Space Treaty prohibits the installation of nuclear weapons and weapons of mass destruction in outer space and determines that the moon and other celestial bodies shall be used for peaceful purposes only. Due to the dual-use character of many space assets, the distinction between military and non-military uses of outer space is becoming increasingly blurred. This article discusses a number of legal challenges presented by article IV of the Outer Space Treaty, relating specifically to the term peaceful, the distinction between the terms militarisation and weaponisation and the nature of a space weapon. It is concluded that article IV is in many respects outdated and that it cannot address the current legal issues relating to the military use of outer space. The legal vacuum in this area may have grave consequences not only for maintaining peace and security in outer space, but also on earth. Consequently, an international dialogue on the military uses of outer space should be

  11. Space-time adaptive decision feedback neural receivers with data selection for high-data-rate users in DS-CDMA systems.

    Science.gov (United States)

    de Lamare, Rodrigo C; Sampaio-Neto, Raimundo

    2008-11-01

    A space-time adaptive decision feedback (DF) receiver using recurrent neural networks (RNNs) is proposed for joint equalization and interference suppression in direct-sequence code-division multiple-access (DS-CDMA) systems equipped with antenna arrays. The proposed receiver structure employs dynamically driven RNNs in the feedforward section for equalization and multiaccess interference (MAI) suppression and a finite impulse response (FIR) linear filter in the feedback section for performing interference cancellation. A data selective gradient algorithm, based upon the set-membership (SM) design framework, is proposed for the estimation of the coefficients of RNN structures and is applied to the estimation of the parameters of the proposed neural receiver structure. Simulation results show that the proposed techniques achieve significant performance gains over existing schemes.

  12. Neural Networks

    International Nuclear Information System (INIS)

    Smith, Patrick I.

    2003-01-01

    information [2]. Each one of these cells acts as a simple processor. When individual cells interact with one another, the complex abilities of the brain are made possible. In neural networks, the input or data are processed by a propagation function that adds up the values of all the incoming data. The ending value is then compared with a threshold or specific value. The resulting value must exceed the activation function value in order to become output. The activation function is a mathematical function that a neuron uses to produce an output referring to its input value. [8] Figure 1 depicts this process. Neural networks usually have three components an input, a hidden, and an output. These layers create the end result of the neural network. A real world example is a child associating the word dog with a picture. The child says dog and simultaneously looks a picture of a dog. The input is the spoken word ''dog'', the hidden is the brain processing, and the output will be the category of the word dog based on the picture. This illustration describes how a neural network functions

  13. Social scaling of extrapersonal space: target objects are judged as closer when the reference frame is a human agent with available movement potentialities.

    Science.gov (United States)

    Fini, C; Brass, M; Committeri, G

    2015-01-01

    Space perception depends on our motion potentialities and our intended actions are affected by space perception. Research on peripersonal space (the space in reaching distance) shows that we perceive an object as being closer when we (Witt, Proffitt, & Epstein, 2005; Witt & Proffitt, 2008) or another actor (Costantini, Ambrosini, Sinigaglia, & Gallese, 2011; Bloesch, Davoli, Roth, Brockmole, & Abrams, 2012) can interact with it. Similarly, an object only triggers specific movements when it is placed in our peripersonal space (Costantini, Ambrosini, Tieri, Sinigaglia, & Committeri, 2010) or in the other's peripersonal space (Costantini, Committeri, & Sinigaglia, 2011; Cardellicchio, Sinigaglia, & Costantini, 2013). Moreover, also the extrapersonal space (the space outside reaching distance) seems to be perceived in relation to our movement capabilities: the more effort it takes to cover a distance, the greater we perceive the distance to be (Proffitt, Stefanucci, Banton, & Epstein, 2003; Sugovic & Witt, 2013). However, not much is known about the influence of the other's movement potentialities on our extrapersonal space perception. Three experiments were carried out investigating the categorization of distance in extrapersonal space using human or non-human allocentric reference frames (RF). Subjects were asked to judge the distance ("Near" or "Far") of a target object (a beach umbrella) placed at progressively increasing or decreasing distances until a change from near to far or vice versa was reported. In the first experiment we found a significant "Near space extension" when the allocentric RF was a human virtual agent instead of a static, inanimate object. In the second experiment we tested whether the "Near space extension" depended on the anatomical structure of the RF or its movement potentialities by adding a wooden dummy. The "Near space extension" was only observed for the human agent but not for the dummy. Finally, to rule out the possibility that the

  14. A Novel Robust H∞ Filter Based on Krein Space Theory in the SINS/CNS Attitude Reference System

    Directory of Open Access Journals (Sweden)

    Fei Yu

    2016-03-01

    Full Text Available Owing to their numerous merits, such as compact, autonomous and independence, the strapdown inertial navigation system (SINS and celestial navigation system (CNS can be used in marine applications. What is more, due to the complementary navigation information obtained from two different kinds of sensors, the accuracy of the SINS/CNS integrated navigation system can be enhanced availably. Thus, the SINS/CNS system is widely used in the marine navigation field. However, the CNS is easily interfered with by the surroundings, which will lead to the output being discontinuous. Thus, the uncertainty problem caused by the lost measurement will reduce the system accuracy. In this paper, a robust H∞ filter based on the Krein space theory is proposed. The Krein space theory is introduced firstly, and then, the linear state and observation models of the SINS/CNS integrated navigation system are established reasonably. By taking the uncertainty problem into account, in this paper, a new robust H∞ filter is proposed to improve the robustness of the integrated system. At last, this new robust filter based on the Krein space theory is estimated by numerical simulations and actual experiments. Additionally, the simulation and experiment results and analysis show that the attitude errors can be reduced by utilizing the proposed robust filter effectively when the measurements are missing discontinuous. Compared to the traditional Kalman filter (KF method, the accuracy of the SINS/CNS integrated system is improved, verifying the robustness and the availability of the proposed robust H∞ filter.

  15. CT findings of the infraorbital space. Special reference to odontogenic infection caused by periapical lesions of the maxillary canine

    International Nuclear Information System (INIS)

    Ikarugi, Yuko; Tanaka, Ray; Hayashi, Takafumi

    2008-01-01

    The purpose of this study was to estimate the clinical significance of the infraorbital space demonstrated on CT for the diagnosis of odontogenic infection caused by periapical lesions of the maxillary canine tooth. We evaluated the radiological appearance of the labial cortical bone and the surrounding soft tissue adjacent to the root apex of the maxillary canine in 12 patients with infraorbital space infection demonstrated on CT. The patients consisted of 6 males and 6 females, and age ranged from 33 to 84 years with a mean age of 58.7 years. On CT, disruption of the labial cortical bone around the root apex of the maxillary canine accompanied with pathological soft tissue density adjacent to the disrupted cortical bone was observed in all of the cases. Swelling of the facial muscles (levator labii superioris muscle, levator anguli oris muscle) was shown in 6 (50%) of 12 cases. Deviation of the levator labii superioris muscle was demonstrated in 9 cases (75%), whereas that of the levator anguli oris muscle was observed only in 2 cases (17%). The anatomical appearance of the infraorbital space which is clearly demonstrated on CT might be useful in diagnosing the spread of odontogenic infection caused by periapical lesions of the maxillary canine. (author)

  16. NASA/NBS (National Aeronautics and Space Administration/National Bureau of Standards) standard reference model for telerobot control system architecture (NASREM)

    Science.gov (United States)

    Albus, James S.; Mccain, Harry G.; Lumia, Ronald

    1989-01-01

    The document describes the NASA Standard Reference Model (NASREM) Architecture for the Space Station Telerobot Control System. It defines the functional requirements and high level specifications of the control system for the NASA space Station document for the functional specification, and a guideline for the development of the control system architecture, of the 10C Flight Telerobot Servicer. The NASREM telerobot control system architecture defines a set of standard modules and interfaces which facilitates software design, development, validation, and test, and make possible the integration of telerobotics software from a wide variety of sources. Standard interfaces also provide the software hooks necessary to incrementally upgrade future Flight Telerobot Systems as new capabilities develop in computer science, robotics, and autonomous system control.

  17. Co-location of space geodetic techniques carried out at the Geodetic Observatory Wettzell using a closure in time and a multi-technique reference target

    Science.gov (United States)

    Kodet, J.; Schreiber, K. U.; Eckl, J.; Plötz, C.; Mähler, S.; Schüler, T.; Klügel, T.; Riepl, S.

    2018-01-01

    The quality of the links between the different space geodetic techniques (VLBI, SLR, GNSS and DORIS) is still one of the major limiting factors for the realization of a unique global terrestrial reference frame that is accurate enough to allow the monitoring of the Earth system, i.e., of processes like sea level change, postglacial rebound and silent earthquakes. According to the specifications of the global geodetic observing system of the International Association of Geodesy, such a reference frame should be accurate to 1 mm over decades, with rates of change stable at the level of 0.1 mm/year. The deficiencies arise from inaccurate or incomplete local ties at many fundamental sites as well as from systematic instrumental biases in the individual space geodetic techniques. Frequently repeated surveys, the continuous monitoring of antenna heights and the geometrical mount stability (Lösler et al. in J Geod 90:467-486, 2016. https://doi.org/10.1007/s00190-016-0887-8) have not provided evidence for insufficient antenna stability. Therefore, we have investigated variations in the respective system delays caused by electronic circuits, which is not adequately captured by the calibration process, either because of subtle differences in the circuitry between geodetic measurement and calibration, high temporal variability or because of lacking resolving bandwidth. The measured system delay variations in the electric chain of both VLBI- and SLR systems reach the order of 100 ps, which is equivalent to 3 cm of path length. Most of this variability is usually removed by the calibrations but by far not all. This paper focuses on the development of new technologies and procedures for co-located geodetic instrumentation in order to identify and remove systematic measurement biases within and between the individual measurement techniques. A closed-loop optical time and frequency distribution system and a common inter-technique reference target provide the possibility to remove

  18. The CERN-EU high-energy reference field (CERF) facility for dosimetry at commercial flight altitudes and in space

    CERN Document Server

    Mitaroff, Angela

    2002-01-01

    A reference facility for the calibration and intercomparison of active and passive detectors in broad neutron fields has been available at CERN since 1992. A positively charged hadron beam (a mixture of protons and pions) with momentum of 120 GeV/c hits a copper target, 50 cm thick and 7 cut in diameter. The secondary particles produced in the interaction traverse a shield, at 90 degrees with respect to the direction of the incoming beam, made of either 80 to 160 cm of concrete or 40 cm of iron. Behind the iron shield, the resulting neutron spectrum has a maximum at about 1 MeV, with an additional high-energy component. Behind the 80 cm concrete shield, the neutron spectrum has a second pronounced maximum at about 70 MeV and resembles the high-energy component of the radiation field created by cosmic rays at commercial flight altitudes. This paper describes the facility, reports on the latest neutron spectral measurements, gives an overview of the most important experiments performed by the various collaborat...

  19. Protecting Neural Structures and Cognitive Function During Prolonged Space Flight by Targeting the Brain Derived Neurotrophic Factor Molecular Network

    Science.gov (United States)

    Schmidt, M. A.; Goodwin, T. J.

    2014-01-01

    Brain derived neurotrophic factor (BDNF) is the main activity-dependent neurotrophin in the human nervous system. BDNF is implicated in production of new neurons from dentate gyrus stem cells (hippocampal neurogenesis), synapse formation, sprouting of new axons, growth of new axons, sprouting of new dendrites, and neuron survival. Alterations in the amount or activity of BDNF can produce significant detrimental changes to cortical function and synaptic transmission in the human brain. This can result in glial and neuronal dysfunction, which may contribute to a range of clinical conditions, spanning a number of learning, behavioral, and neurological disorders. There is an extensive body of work surrounding the BDNF molecular network, including BDNF gene polymorphisms, methylated BDNF gene promoters, multiple gene transcripts, varied BDNF functional proteins, and different BDNF receptors (whose activation differentially drive the neuron to neurogenesis or apoptosis). BDNF is also closely linked to mitochondrial biogenesis through PGC-1alpha, which can influence brain and muscle metabolic efficiency. BDNF AS A HUMAN SPACE FLIGHT COUNTERMEASURE TARGET Earth-based studies reveal that BDNF is negatively impacted by many of the conditions encountered in the space environment, including oxidative stress, radiation, psychological stressors, sleep deprivation, and many others. A growing body of work suggests that the BDNF network is responsive to a range of diet, nutrition, exercise, drug, and other types of influences. This section explores the BDNF network in the context of 1) protecting the brain and nervous system in the space environment, 2) optimizing neurobehavioral performance in space, and 3) reducing the residual effects of space flight on the nervous system on return to Earth

  20. Sequential neural models with stochastic layers

    DEFF Research Database (Denmark)

    Fraccaro, Marco; Sønderby, Søren Kaae; Paquet, Ulrich

    2016-01-01

    How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural...... generative model. The clear separation of deterministic and stochastic layers allows a structured variational inference network to track the factorization of the model's posterior distribution. By retaining both the nonlinear recursive structure of a recurrent neural network and averaging over...

  1. Mixed quantum/classical theory of rotationally and vibrationally inelastic scattering in space-fixed and body-fixed reference frames.

    Science.gov (United States)

    Semenov, Alexander; Babikov, Dmitri

    2013-11-07

    We formulated the mixed quantum/classical theory for rotationally and vibrationally inelastic scattering process in the diatomic molecule + atom system. Two versions of theory are presented, first in the space-fixed and second in the body-fixed reference frame. First version is easy to derive and the resultant equations of motion are transparent, but the state-to-state transition matrix is complex-valued and dense. Such calculations may be computationally demanding for heavier molecules and/or higher temperatures, when the number of accessible channels becomes large. In contrast, the second version of theory requires some tedious derivations and the final equations of motion are rather complicated (not particularly intuitive). However, the state-to-state transitions are driven by real-valued sparse matrixes of much smaller size. Thus, this formulation is the method of choice from the computational point of view, while the space-fixed formulation can serve as a test of the body-fixed equations of motion, and the code. Rigorous numerical tests were carried out for a model system to ensure that all equations, matrixes, and computer codes in both formulations are correct.

  2. Mixed quantum/classical theory of rotationally and vibrationally inelastic scattering in space-fixed and body-fixed reference frames

    International Nuclear Information System (INIS)

    Semenov, Alexander; Babikov, Dmitri

    2013-01-01

    We formulated the mixed quantum/classical theory for rotationally and vibrationally inelastic scattering process in the diatomic molecule + atom system. Two versions of theory are presented, first in the space-fixed and second in the body-fixed reference frame. First version is easy to derive and the resultant equations of motion are transparent, but the state-to-state transition matrix is complex-valued and dense. Such calculations may be computationally demanding for heavier molecules and/or higher temperatures, when the number of accessible channels becomes large. In contrast, the second version of theory requires some tedious derivations and the final equations of motion are rather complicated (not particularly intuitive). However, the state-to-state transitions are driven by real-valued sparse matrixes of much smaller size. Thus, this formulation is the method of choice from the computational point of view, while the space-fixed formulation can serve as a test of the body-fixed equations of motion, and the code. Rigorous numerical tests were carried out for a model system to ensure that all equations, matrixes, and computer codes in both formulations are correct

  3. A new velocity field for Africa from combined GPS and DORIS space geodetic Solutions: Contribution to the definition of the African reference frame (AFREF)

    Science.gov (United States)

    Saria, E.; Calais, E.; Altamimi, Z.; Willis, P.; Farah, H.

    2013-04-01

    We analyzed 16 years of GPS and 17 years of Doppler orbitography and radiopositioning integrated by satellite (DORIS) data at continuously operating geodetic sites in Africa and surroundings to describe the present-day kinematics of the Nubian and Somalian plates and constrain relative motions across the East African Rift. The resulting velocity field describes horizontal and vertical motion at 133 GPS sites and 9 DORIS sites. Horizontal velocities at sites located on stable Nubia fit a single plate model with a weighted root mean square residual of 0.6 mm/yr (maximum residual 1 mm/yr), an upper bound for plate-wide motions and for regional-scale deformation in the seismically active southern Africa and Cameroon volcanic line. We confirm significant southward motion ( ˜ 1.5 mm/yr) in Morocco with respect to Nubia, consistent with earlier findings. We propose an updated angular velocity for the divergence between Nubia and Somalia, which provides the kinematic boundary conditions to rifting in East Africa. We update a plate motion model for the East African Rift and revise the counterclockwise rotation of the Victoria plate and clockwise rotation of the Rovuma plate with respect to Nubia. Vertical velocities range from - 2 to +2 mm/yr, close to their uncertainties, with no clear geographic pattern. This study provides the first continent-wide position/velocity solution for Africa, expressed in International Terrestrial Reference Frame (ITRF2008), a contribution to the upcoming African Reference Frame (AFREF). Except for a few regions, the African continent remains largely under-sampled by continuous space geodetic data. Efforts are needed to augment the geodetic infrastructure and openly share existing data sets so that the objectives of AFREF can be fully reached.

  4. Analysis of neural mechanisms underlying verbal fluency in cytoarchitectonically defined stereotaxic space--the roles of Brodmann areas 44 and 45.

    Science.gov (United States)

    Amunts, Katrin; Weiss, Peter H; Mohlberg, Hartmut; Pieperhoff, Peter; Eickhoff, Simon; Gurd, Jennifer M; Marshall, John C; Shah, Nadim J; Fink, Gereon R; Zilles, Karl

    2004-05-01

    We investigated neural activations underlying a verbal fluency task and cytoarchitectonic probabilistic maps of Broca's speech region (Brodmann's areas 44 and 45). To do so, we reanalyzed data from a previous functional magnetic resonance imaging (fMRI) [Brain 125 (2002) 1024] and from a cytoarchitectonic study [J. Comp. Neurol. 412 (1999) 319] and developed a method to combine both data sets. In the fMRI experiment, verbal fluency was investigated in 11 healthy volunteers, who covertly produced words from predefined categories. A factorial design was used with factors verbal class (semantic vs. overlearned fluency) and switching between categories (no vs. yes). fMRI data analysis employed SPM99 (Statistical Parametric Mapping). Cytoarchitectonic maps of areas 44 and 45 were derived from histologic sections of 10 postmortem brains. Both the in vivo fMRI and postmortem MR data were warped to a common reference brain using a new elastic warping tool. Cytoarchitectonic probability maps with stereotaxic information about intersubject variability were calculated for both areas and superimposed on the functional data, which showed the involvement of left hemisphere areas with verbal fluency relative to the baseline. Semantic relative to overlearned fluency showed greater involvement of left area 45 than of 44. Thus, although both areas participate in verbal fluency, they do so differentially. Left area 45 is more involved in semantic aspects of language processing, while area 44 is probably involved in high-level aspects of programming speech production per se. The combination of functional data analysis with a new elastic warping tool and cytoarchitectonic maps opens new perspectives for analyzing the cortical networks involved in language.

  5. Avoided crossings, conical intersections, and low-lying excited states with a single reference method: the restricted active space spin-flip configuration interaction approach.

    Science.gov (United States)

    Casanova, David

    2012-08-28

    The restricted active space spin-flip CI (RASCI-SF) performance is tested in the electronic structure computation of the ground and the lowest electronically excited states in the presence of near-degeneracies. The feasibility of the method is demonstrated by analyzing the avoided crossing between the ionic and neutral singlet states of LiF along the molecular dissociation. The two potential energy surfaces (PESs) are explored by means of the energies of computed adiabatic and approximated diabatic states, dipole moments, and natural orbital electronic occupancies of both states. The RASCI-SF methodology is also used to study the ground and first excited singlet surface crossing involved in the double bond isomerization of ethylene, as a model case. The two-dimensional PESs of the ground (S(0)) and excited (S(1)) states are calculated for the complete configuration space of torsion and pyramidalization molecular distortions. The parameters that define the state energetics in the vicinity of the S(0)/S(1) conical intersection region are compared to complete active space self-consistent field (CASSCF) results. These examples show that it is possible to describe strongly correlated electronic states using a single reference methodology without the need to expand the wavefunction to high levels of collective excitations. Finally, RASCI is also examined in the electronic structure characterization of the ground and 2(1)A(g)(-), 1(1)B(u)(+), 1(1)B(u)(-), and 1(3)B(u)(-) states of all-trans polyenes with two to seven double bonds and beyond. Transition energies are compared to configuration interaction singles, time-dependent density functional theory (TDDFT), CASSCF, and its second-order perturbation correction calculations, and to experimental data. The capability of RASCI-SF to describe the nature and properties of each electronic state is discussed in detail. This example is also used to expose the properties of different truncations of the RASCI wavefunction and to

  6. Stimulus reference frame and neural coding precision

    Czech Academy of Sciences Publication Activity Database

    Košťál, Lubomír

    2016-01-01

    Roč. 71, Apr 2016 (2016), s. 22-27 ISSN 0022-2496 R&D Projects: GA ČR(CZ) GA15-08066S Institutional support: RVO:67985823 Keywords : Fisher information * coding accuracy * measurement scale * Jeffreys prior Subject RIV: FH - Neurology Impact factor: 1.377, year: 2016

  7. Neural networks

    International Nuclear Information System (INIS)

    Denby, Bruce; Lindsey, Clark; Lyons, Louis

    1992-01-01

    The 1980s saw a tremendous renewal of interest in 'neural' information processing systems, or 'artificial neural networks', among computer scientists and computational biologists studying cognition. Since then, the growth of interest in neural networks in high energy physics, fueled by the need for new information processing technologies for the next generation of high energy proton colliders, can only be described as explosive

  8. From sensation to perception: Using multivariate classification of visual illusions to identify neural correlates of conscious awareness in space and time.

    Science.gov (United States)

    Hogendoorn, Hinze

    2015-01-01

    An important goal of cognitive neuroscience is understanding the neural underpinnings of conscious awareness. Although the low-level processing of sensory input is well understood in most modalities, it remains a challenge to understand how the brain translates such input into conscious awareness. Here, I argue that the application of multivariate pattern classification techniques to neuroimaging data acquired while observers experience perceptual illusions provides a unique way to dissociate sensory mechanisms from mechanisms underlying conscious awareness. Using this approach, it is possible to directly compare patterns of neural activity that correspond to the contents of awareness, independent from changes in sensory input, and to track these neural representations over time at high temporal resolution. I highlight five recent studies using this approach, and provide practical considerations and limitations for future implementations.

  9. The contribution of 3D quantitative meniscal and cartilage measures to variation in normal radiographic joint space width—Data from the Osteoarthritis Initiative healthy reference cohort

    International Nuclear Information System (INIS)

    Roth, Melanie; Wirth, Wolfgang; Emmanuel, Katja; Culvenor, Adam G.; Eckstein, Felix

    2017-01-01

    Objective: To explore to what extent three-dimensional measures of the meniscus and femorotibial cartilage explain the variation in medial and lateral femorotibial radiographic joint space width (JSW), in healthy men and women. Methods: The right knees of 87 Osteoarthritis Initiative healthy reference participants (no symptoms, radiographic signs or risk factors of osteoarthritis; 37 men, 50 women; age 55.0 ± 7.6; BMI 24.4 ± 3.1) were assessed. Quantitative measures of subregional femorotibial cartilage thickness and meniscal position and morphology were computed from segmented magnetic resonance images. Minimal and medial/lateral fixed-location JSW were determined from fixed-flexion radiographs. Correlation and regression analyses were used to explore the contribution of demographic, cartilage and meniscal parameters to JSW in healthy subjects. Results: The correlation with (medial) minimal JSW was somewhat stronger for cartilage thickness (0.54 ≤ r ≤ 0.67) than for meniscal (−0.31 ≤ r ≤ 0.50) or demographic measures (−0.15 ≤ r ≤ 0.48), in particular in men. In women, in contrast, the strength of the correlations of cartilage thickness and meniscal measures with minimal JSW were in the same range. Fixed-location JSW measures showed stronger correlations with cartilage thickness (r ≥ 0.68 medially; r ≥ 0.59 laterally) than with meniscal measures (r ≤ |0.32| medially; r ≤ |0.32| laterally). Stepwise regression models revealed that meniscal measures added significant independent information to the total variance explained in minimal JSW (adjusted multiple r 2 = 58%) but not in medial or lateral fixed-location JSW (r 2 = 60/51%, respectively). Conclusions: In healthy subjects, minimal JSW was observed to reflect a combination of cartilage and meniscal measures, particularly in women. Fixed-location JSW, in contrast, was found to be dominated by variance in cartilage thickness in both men and women, with somewhat higher correlations between

  10. The contribution of 3D quantitative meniscal and cartilage measures to variation in normal radiographic joint space width—Data from the Osteoarthritis Initiative healthy reference cohort

    Energy Technology Data Exchange (ETDEWEB)

    Roth, Melanie, E-mail: melanie.roth@pmu.ac.at [Institute of Anatomy, Paracelsus Medical University Salzburg & Nuremberg, Strubergasse 21, 5020, Salzburg (Austria); Wirth, Wolfgang, E-mail: wolfgang.wirth@pmu.ac.at [Institute of Anatomy, Paracelsus Medical University Salzburg & Nuremberg, Strubergasse 21, 5020, Salzburg (Austria); Chondrometrics GmbH, Ulrichshöglerstrasse 23, 83404, Ainring (Germany); Emmanuel, Katja, E-mail: katja.emmanuel@icloud.com [Institute of Anatomy, Paracelsus Medical University Salzburg & Nuremberg, Strubergasse 21, 5020, Salzburg (Austria); Department of Orthopedics and Traumatology, Paracelsus Medical University, Müllner Hauptstraße 48, 5020, Salzburg (Austria); Culvenor, Adam G., E-mail: adam.culvenor@pmu.ac.at [Institute of Anatomy, Paracelsus Medical University Salzburg & Nuremberg, Strubergasse 21, 5020, Salzburg (Austria); School of Allied Health, La Trobe University, Plenty Road, Bundoora, 3086, Victoria (Australia); Eckstein, Felix, E-mail: felix.eckstein@pmu.ac.at [Institute of Anatomy, Paracelsus Medical University Salzburg & Nuremberg, Strubergasse 21, 5020, Salzburg (Austria); Chondrometrics GmbH, Ulrichshöglerstrasse 23, 83404, Ainring (Germany)

    2017-02-15

    Objective: To explore to what extent three-dimensional measures of the meniscus and femorotibial cartilage explain the variation in medial and lateral femorotibial radiographic joint space width (JSW), in healthy men and women. Methods: The right knees of 87 Osteoarthritis Initiative healthy reference participants (no symptoms, radiographic signs or risk factors of osteoarthritis; 37 men, 50 women; age 55.0 ± 7.6; BMI 24.4 ± 3.1) were assessed. Quantitative measures of subregional femorotibial cartilage thickness and meniscal position and morphology were computed from segmented magnetic resonance images. Minimal and medial/lateral fixed-location JSW were determined from fixed-flexion radiographs. Correlation and regression analyses were used to explore the contribution of demographic, cartilage and meniscal parameters to JSW in healthy subjects. Results: The correlation with (medial) minimal JSW was somewhat stronger for cartilage thickness (0.54 ≤ r ≤ 0.67) than for meniscal (−0.31 ≤ r ≤ 0.50) or demographic measures (−0.15 ≤ r ≤ 0.48), in particular in men. In women, in contrast, the strength of the correlations of cartilage thickness and meniscal measures with minimal JSW were in the same range. Fixed-location JSW measures showed stronger correlations with cartilage thickness (r ≥ 0.68 medially; r ≥ 0.59 laterally) than with meniscal measures (r ≤ |0.32| medially; r ≤ |0.32| laterally). Stepwise regression models revealed that meniscal measures added significant independent information to the total variance explained in minimal JSW (adjusted multiple r{sup 2} = 58%) but not in medial or lateral fixed-location JSW (r{sup 2} = 60/51%, respectively). Conclusions: In healthy subjects, minimal JSW was observed to reflect a combination of cartilage and meniscal measures, particularly in women. Fixed-location JSW, in contrast, was found to be dominated by variance in cartilage thickness in both men and women, with somewhat higher correlations

  11. On the origin of reproducible sequential activity in neural circuits

    Science.gov (United States)

    Afraimovich, V. S.; Zhigulin, V. P.; Rabinovich, M. I.

    2004-12-01

    Robustness and reproducibility of sequential spatio-temporal responses is an essential feature of many neural circuits in sensory and motor systems of animals. The most common mathematical images of dynamical regimes in neural systems are fixed points, limit cycles, chaotic attractors, and continuous attractors (attractive manifolds of neutrally stable fixed points). These are not suitable for the description of reproducible transient sequential neural dynamics. In this paper we present the concept of a stable heteroclinic sequence (SHS), which is not an attractor. SHS opens the way for understanding and modeling of transient sequential activity in neural circuits. We show that this new mathematical object can be used to describe robust and reproducible sequential neural dynamics. Using the framework of a generalized high-dimensional Lotka-Volterra model, that describes the dynamics of firing rates in an inhibitory network, we present analytical results on the existence of the SHS in the phase space of the network. With the help of numerical simulations we confirm its robustness in presence of noise in spite of the transient nature of the corresponding trajectories. Finally, by referring to several recent neurobiological experiments, we discuss possible applications of this new concept to several problems in neuroscience.

  12. From sensation to perception: : Using multivariate classification of visual illusions to identify neural correlates of conscious awareness in space and time

    NARCIS (Netherlands)

    Hogendoorn, Hinze

    2015-01-01

    An important goal of cognitive neuroscience is understanding the neural underpinnings of conscious awareness. Although the low-level processing of sensory input is well understood in most modalities, it remains a challenge to understand how the brain translates such input into conscious awareness.

  13. Growth references

    NARCIS (Netherlands)

    Buuren, S. van

    2007-01-01

    A growth reference describes the variation of an anthropometric measurement within a group of individuals. A reference is a tool for grouping and analyzing data and provides a common basis for comparing populations.1 A well known type of reference is the age-conditional growth diagram. The

  14. Complex-Valued Neural Networks

    CERN Document Server

    Hirose, Akira

    2012-01-01

    This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. In the second edition the recent trends in CVNNs research are included, resulting in e.g. almost a doubled number of references. The parametron invented in 1954 is also referred to with discussion on analogy and disparity. Also various additional arguments on the advantages of the complex-valued neural networks enhancing the difference to real-valued neural networks are given in various sections. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplina...

  15. Deep Space Gateway Facilitates Exploration of Planetary Crusts: A Human/Robotic Exploration Design Reference Campaign to the Lunar Orientale Basin

    Science.gov (United States)

    Head, J. W.; Pieters, C. M.; Scott, D. R.

    2018-02-01

    We outline an Orientale Basin Human/Robotic Architecture that can be facilitated by a Deep Space Gateway International Science Operations Center (DSG-ISOC) (like McMurdo/Antarctica) to address fundamental scientific problems about the Moon and Mars.

  16. A modular architecture for transparent computation in recurrent neural networks.

    Science.gov (United States)

    Carmantini, Giovanni S; Beim Graben, Peter; Desroches, Mathieu; Rodrigues, Serafim

    2017-01-01

    Computation is classically studied in terms of automata, formal languages and algorithms; yet, the relation between neural dynamics and symbolic representations and operations is still unclear in traditional eliminative connectionism. Therefore, we suggest a unique perspective on this central issue, to which we would like to refer as transparent connectionism, by proposing accounts of how symbolic computation can be implemented in neural substrates. In this study we first introduce a new model of dynamics on a symbolic space, the versatile shift, showing that it supports the real-time simulation of a range of automata. We then show that the Gödelization of versatile shifts defines nonlinear dynamical automata, dynamical systems evolving on a vectorial space. Finally, we present a mapping between nonlinear dynamical automata and recurrent artificial neural networks. The mapping defines an architecture characterized by its granular modularity, where data, symbolic operations and their control are not only distinguishable in activation space, but also spatially localizable in the network itself, while maintaining a distributed encoding of symbolic representations. The resulting networks simulate automata in real-time and are programmed directly, in the absence of network training. To discuss the unique characteristics of the architecture and their consequences, we present two examples: (i) the design of a Central Pattern Generator from a finite-state locomotive controller, and (ii) the creation of a network simulating a system of interactive automata that supports the parsing of garden-path sentences as investigated in psycholinguistics experiments. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Innervation of Extrahepatic Biliary Tract, With Special Reference to the Direct Bidirectional Neural Connections of the Gall Bladder, Sphincter of Oddi and Duodenum in Suncus murinus, in Whole-Mount Immunohistochemical Study.

    Science.gov (United States)

    Yi, S-Q; Ren, K; Kinoshita, M; Takano, N; Itoh, M; Ozaki, N

    2016-06-01

    Sphincter of Oddi dysfunction is one of the most important symptoms in post-cholecystectomy syndrome. Using either electrical or mechanical stimulation and retrogradely transported neuronal dyes, it has been demonstrated that there are direct neural pathways connecting gall bladder and the sphincter of Oddi in the Australian opossum and the golden hamster. In the present study, we employed whole-mount immunohistochemistry staining to observe and verify that there are two different plexuses of the extrahepatic biliary tract in Suncus murinus. One, named Pathway One, showed a fine, irregular but dense network plexus that ran adhesively and resided on/in the extrahepatic biliary tract wall, and the plexus extended into the intrahepatic area. On the other hand, named Pathway Two, exhibiting simple, thicker and straight neural bundles, ran parallel to the surface of the extrahepatic biliary tract and passed between the gall bladder and duodenum, but did not give off any branches to the liver. Pathway Two was considered to involve direct bidirectional neural connections between the duodenum and the biliary tract system. For the first time, morphologically, we demonstrated direct neural connections between gall bladder and duodenum in S. murinus. Malfunction of the sphincter of Oddi may be caused by injury of the direct neural pathways between gall bladder and duodenum by cholecystectomy. From the viewpoint of preserving the function of the major duodenal papilla and common bile duct, we emphasize the importance of avoiding kocherization of the common bile duct so as to preserve the direct neural connections between gall bladder and sphincter of Oddi. © 2015 Blackwell Verlag GmbH.

  18. [Reference citation].

    Science.gov (United States)

    Brkić, Silvija

    2013-01-01

    Scientific and professional papers represent the information basis for scientific research and professional work. References important for the paper should be cited within the text, and listed at the end of the paper. This paper deals with different styles of reference citation. Special emphasis was placed on the Vancouver Style for reference citation in biomedical journals established by the International Committee of Medical Journal Editors. It includes original samples for citing various types of articles, both printed and electronic, as well as recommendations related to reference citation in accordance with the methodology and ethics of scientific research and guidelines for preparing manuscripts for publication.

  19. Assessing the suitability of American National Aeronautics and Space Administration (NASA) agro-climatology archive to predict daily meteorological variables and reference evapotranspiration in Sicily, Italy

    Science.gov (United States)

    For decades, the importance of evapotranspiration processes has been recognized in many disciplines, including hydrologic and drainage studies, irrigation systems design and management. A wide number of equations have been proposed to estimate crop reference evapotranspiration, ET0, based on the var...

  20. Reference Assessment

    Science.gov (United States)

    Bivens-Tatum, Wayne

    2006-01-01

    This article presents interesting articles that explore several different areas of reference assessment, including practical case studies and theoretical articles that address a range of issues such as librarian behavior, patron satisfaction, virtual reference, or evaluation design. They include: (1) "Evaluating the Quality of a Chat Service"…

  1. Evolvable synthetic neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2009-01-01

    An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

  2. Grounding word learning in space.

    Directory of Open Access Journals (Sweden)

    Larissa K Samuelson

    Full Text Available Humans and objects, and thus social interactions about objects, exist within space. Words direct listeners' attention to specific regions of space. Thus, a strong correspondence exists between where one looks, one's bodily orientation, and what one sees. This leads to further correspondence with what one remembers. Here, we present data suggesting that children use associations between space and objects and space and words to link words and objects--space binds labels to their referents. We tested this claim in four experiments, showing that the spatial consistency of where objects are presented affects children's word learning. Next, we demonstrate that a process model that grounds word learning in the known neural dynamics of spatial attention, spatial memory, and associative learning can capture the suite of results reported here. This model also predicts that space is special, a prediction supported in a fifth experiment that shows children do not use color as a cue to bind words and objects. In a final experiment, we ask whether spatial consistency affects word learning in naturalistic word learning contexts. Children of parents who spontaneously keep objects in a consistent spatial location during naming interactions learn words more effectively. Together, the model and data show that space is a powerful tool that can effectively ground word learning in social contexts.

  3. Space space space

    CERN Document Server

    Trembach, Vera

    2014-01-01

    Space is an introduction to the mysteries of the Universe. Included are Task Cards for independent learning, Journal Word Cards for creative writing, and Hands-On Activities for reinforcing skills in Math and Language Arts. Space is a perfect introduction to further research of the Solar System.

  4. Recent references

    International Nuclear Information System (INIS)

    Ramavataram, S.

    1991-01-01

    In support of a continuing program of systematic evaluation of nuclear structure data, the National Nuclear Data Center maintains a complete computer file of references to the nuclear physics literature. Each reference is tagged by a keyword string, which indicates the kinds of data contained in the article. This master file of Nuclear Structure References (NSR) contains complete keyword indexes to literature published since 1969, with partial indexing of older references. Any reader who finds errors in the keyword descriptions is urged to report them to the National Nuclear Data Center so that the master NSR file can be corrected. In 1966, the first collection of Recent References was published as a separate issue of Nuclear Data Sheets. Every four months since 1970, a similar indexed bibliography to new nuclear experiments has been prepared from additions to the NSR file and published. Beginning in 1978, Recent References was cumulated annually, with the third issue completely superseding the two issues previously published during a given year. Due to publication policy changes, cumulation of Recent Reference was discontinued in 1986. The volume and issue number of all the cumulative issues published to date are given. NNDC will continue to respond to individual requests for special bibliographies on nuclear physics topics, in addition to those easily obtained from Recent References. If the required information is available from the keyword string, a reference list can be prepared automatically from the computer files. This service can be provided on request, in exchange for the timely communication of new nuclear physics results (e.g., preprints). A current copy of the NSR file may also be obtained in a standard format on magnetic tape from NNDC. Requests for special searches of the NSR file may also be directed to the National Nuclear Data Center

  5. Learning from neural control.

    Science.gov (United States)

    Wang, Cong; Hill, David J

    2006-01-01

    One of the amazing successes of biological systems is their ability to "learn by doing" and so adapt to their environment. In this paper, first, a deterministic learning mechanism is presented, by which an appropriately designed adaptive neural controller is capable of learning closed-loop system dynamics during tracking control to a periodic reference orbit. Among various neural network (NN) architectures, the localized radial basis function (RBF) network is employed. A property of persistence of excitation (PE) for RBF networks is established, and a partial PE condition of closed-loop signals, i.e., the PE condition of a regression subvector constructed out of the RBFs along a periodic state trajectory, is proven to be satisfied. Accurate NN approximation for closed-loop system dynamics is achieved in a local region along the periodic state trajectory, and a learning ability is implemented during a closed-loop feedback control process. Second, based on the deterministic learning mechanism, a neural learning control scheme is proposed which can effectively recall and reuse the learned knowledge to achieve closed-loop stability and improved control performance. The significance of this paper is that the presented deterministic learning mechanism and the neural learning control scheme provide elementary components toward the development of a biologically-plausible learning and control methodology. Simulation studies are included to demonstrate the effectiveness of the approach.

  6. Sobolev spaces

    CERN Document Server

    Adams, Robert A

    2003-01-01

    Sobolev Spaces presents an introduction to the theory of Sobolev Spaces and other related spaces of function, also to the imbedding characteristics of these spaces. This theory is widely used in pure and Applied Mathematics and in the Physical Sciences.This second edition of Adam''s ''classic'' reference text contains many additions and much modernizing and refining of material. The basic premise of the book remains unchanged: Sobolev Spaces is intended to provide a solid foundation in these spaces for graduate students and researchers alike.* Self-contained and accessible for readers in other disciplines.* Written at elementary level making it accessible to graduate students.

  7. NEURAL METHODS FOR THE FINANCIAL PREDICTION

    OpenAIRE

    Jerzy Balicki; Piotr Dryja; Waldemar Korłub; Piotr Przybyłek; Maciej Tyszka; Marcin Zadroga; Marcin Zakidalski

    2016-01-01

    Artificial neural networks can be used to predict share investment on the stock market, assess the reliability of credit client or predicting banking crises. Moreover, this paper discusses the principles of cooperation neural network algorithms with evolutionary method, and support vector machines. In addition, a reference is made to other methods of artificial intelligence, which are used in finance prediction.

  8. NEURAL METHODS FOR THE FINANCIAL PREDICTION

    Directory of Open Access Journals (Sweden)

    Jerzy Balicki

    2016-06-01

    Full Text Available Artificial neural networks can be used to predict share investment on the stock market, assess the reliability of credit client or predicting banking crises. Moreover, this paper discusses the principles of cooperation neural network algorithms with evolutionary method, and support vector machines. In addition, a reference is made to other methods of artificial intelligence, which are used in finance prediction.

  9. Adaptive optimization and control using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.

    1993-10-22

    Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.

  10. Neural components of altruistic punishment

    Directory of Open Access Journals (Sweden)

    Emily eDu

    2015-02-01

    Full Text Available Altruistic punishment, which occurs when an individual incurs a cost to punish in response to unfairness or a norm violation, may play a role in perpetuating cooperation. The neural correlates underlying costly punishment have only recently begun to be explored. Here we review the current state of research on the neural basis of altruism from the perspectives of costly punishment, emphasizing the importance of characterizing elementary neural processes underlying a decision to punish. In particular, we emphasize three cognitive processes that contribute to the decision to altruistically punish in most scenarios: inequity aversion, cost-benefit calculation, and social reference frame to distinguish self from others. Overall, we argue for the importance of understanding the neural correlates of altruistic punishment with respect to the core computations necessary to achieve a decision to punish.

  11. Setting reference targets

    International Nuclear Information System (INIS)

    Ruland, R.E.

    1997-04-01

    Reference Targets are used to represent virtual quantities like the magnetic axis of a magnet or the definition of a coordinate system. To explain the function of reference targets in the sequence of the alignment process, this paper will first briefly discuss the geometry of the trajectory design space and of the surveying space, then continue with an overview of a typical alignment process. This is followed by a discussion on magnet fiducialization. While the magnetic measurement methods to determine the magnetic centerline are only listed (they will be discussed in detail in a subsequent talk), emphasis is given to the optical/mechanical methods and to the task of transferring the centerline position to reference targets

  12. References: BSCW

    Data.gov (United States)

    National Aeronautics and Space Administration — Benchmark Supercritical Wing was also tested on the OTT with oscillations in Pitch. Only one row of pressure transducers were acquired during these tests. The time...

  13. Analysis of neural data

    CERN Document Server

    Kass, Robert E; Brown, Emery N

    2014-01-01

    Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.

  14. A graph-Laplacian-based feature extraction algorithm for neural spike sorting.

    Science.gov (United States)

    Ghanbari, Yasser; Spence, Larry; Papamichalis, Panos

    2009-01-01

    Analysis of extracellular neural spike recordings is highly dependent upon the accuracy of neural waveform classification, commonly referred to as spike sorting. Feature extraction is an important stage of this process because it can limit the quality of clustering which is performed in the feature space. This paper proposes a new feature extraction method (which we call Graph Laplacian Features, GLF) based on minimizing the graph Laplacian and maximizing the weighted variance. The algorithm is compared with Principal Components Analysis (PCA, the most commonly-used feature extraction method) using simulated neural data. The results show that the proposed algorithm produces more compact and well-separated clusters compared to PCA. As an added benefit, tentative cluster centers are output which can be used to initialize a subsequent clustering stage.

  15. The pharmaco-kinetics of angiographic contrast media with special reference to the extravascular spaces. Fundamental studies on dogs for the characterization of angiographic media. Pt. 1

    International Nuclear Information System (INIS)

    Lagemann, K.

    1975-01-01

    The pharmaco-kinetics of angiographic contrast media in the extra-vascular space, which are largely unknown, were investigated experimentally in dogs. As part of a basic study, using radio-active contrast media, it was possible to determine the concentration and rate of elimination in practically all organs and tissues. Measurements were carried out first after prolonged infusion of contrast under conditions of balanced flow, and secondly six hours after the end of the infusion. It was therefore possible to determine the inflow and loss of contrast medium in various organs, or organs systems. The most commonly used angiographic contrast media in Germany were investigated. Their kinetic behaviour is largely identical, their pattern of distribution and elimination depended principally on the organ or tissue. (orig.) [de

  16. "EWS Matrix" and "EWG Matrix": "De-sign for All" tools referred to the development of a enabling communication system for public spaces.

    Science.gov (United States)

    Di Bucchianico, Giuseppe; Camplone, Stefania; Picciani, Stefano; Vallese, Valeria

    2012-01-01

    The widespread sense of spatial disorientation that can be experienced in many public places (buildings and open spaces),generally depends on a design approach that doesn't take into account both the "communication skills" of the different parts of the spatial organization, both the variability of people and their ways of interacting with environments, orienteering themselves. Nevertheless, "not find the way" often has some obvious practical costs (loss of time, failure to achieve a target) and some more intangible, but no less important, emotional costs. That's why the design of signage systems must take into account both the specificities of places and the extreme variability of its users. The paper presents the results of a study on this specific issue. In particular, the study focuses on the description of some tools useful for the analysis and design of a signage system that is truly "for All".

  17. How do reference montage and electrodes setup affect the measured scalp EEG potentials?

    Science.gov (United States)

    Hu, Shiang; Lai, Yongxiu; Valdes-Sosa, Pedro A.; Bringas-Vega, Maria L.; Yao, Dezhong

    2018-04-01

    Objective. Human scalp electroencephalogram (EEG) is widely applied in cognitive neuroscience and clinical studies due to its non-invasiveness and ultra-high time resolution. However, the representativeness of the measured EEG potentials for the underneath neural activities is still a problem under debate. This study aims to investigate systematically how both reference montage and electrodes setup affect the accuracy of EEG potentials. Approach. First, the standard EEG potentials are generated by the forward calculation with a single dipole in the neural source space, for eleven channel numbers (10, 16, 21, 32, 64, 85, 96, 128, 129, 257, 335). Here, the reference is the ideal infinity implicitly determined by forward theory. Then, the standard EEG potentials are transformed to recordings with different references including five mono-polar references (Left earlobe, Fz, Pz, Oz, Cz), and three re-references (linked mastoids (LM), average reference (AR) and reference electrode standardization technique (REST)). Finally, the relative errors between the standard EEG potentials and the transformed ones are evaluated in terms of channel number, scalp regions, electrodes layout, dipole source position and orientation, as well as sensor noise and head model. Main results. Mono-polar reference recordings are usually of large distortions; thus, a re-reference after online mono-polar recording should be adopted in general to mitigate this effect. Among the three re-references, REST is generally superior to AR for all factors compared, and LM performs worst. REST is insensitive to head model perturbation. AR is subject to electrodes coverage and dipole orientation but no close relation with channel number. Significance. These results indicate that REST would be the first choice of re-reference and AR may be an alternative option for high level sensor noise case. Our findings may provide the helpful suggestions on how to obtain the EEG potentials as accurately as possible for

  18. A steady state solution for ditch drainage problem with special reference to seepage face and unsaturated zone flow contribution: Derivation of a new drainage spacing eqaution

    Science.gov (United States)

    Yousfi, Ammar; Mechergui, Mohammed

    2016-04-01

    al. (2001). In this work, a novel solution based on theoretical approach will be adapted to incorporate both the seepage face and the unsaturated zone flow contribution for solving ditch drained aquifers problems. This problem will be tackled on the basis of the approximate 2D solution given by Castro-Orgaz et al. (2012). This given solution yields the generalized water table profile function with a suitable boundary condition to be determined and provides a modified DF theory which permits as an outcome the analytical determination of the seepage face. To assess the ability of the developed equation for water-table estimations, the obtained results were compared with numerical solutions to the 2-D problem under different conditions. It is shown that results are in fair agreement and thus the resulting model can be used for designing ditch drainage systems. With respect to drainage design, the spacings calculated with the newly derived equation are compared with those computed from the DF theory. It is shown that the effect of the unsaturated zone flow contribution is limited to sandy soils and The calculated maximum increase in drain spacing is about 30%. Keywords: subsurface ditch drainage; unsaturated zone; seepage face; water-table, ditch spacing equation

  19. Neural Networks

    Directory of Open Access Journals (Sweden)

    Schwindling Jerome

    2010-04-01

    Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

  20. Enterprise Reference Library

    Science.gov (United States)

    Bickham, Grandin; Saile, Lynn; Havelka, Jacque; Fitts, Mary

    2011-01-01

    Introduction: Johnson Space Center (JSC) offers two extensive libraries that contain journals, research literature and electronic resources. Searching capabilities are available to those individuals residing onsite or through a librarian s search. Many individuals have rich collections of references, but no mechanisms to share reference libraries across researchers, projects, or directorates exist. Likewise, information regarding which references are provided to which individuals is not available, resulting in duplicate requests, redundant labor costs and associated copying fees. In addition, this tends to limit collaboration between colleagues and promotes the establishment of individual, unshared silos of information The Integrated Medical Model (IMM) team has utilized a centralized reference management tool during the development, test, and operational phases of this project. The Enterprise Reference Library project expands the capabilities developed for IMM to address the above issues and enhance collaboration across JSC. Method: After significant market analysis for a multi-user reference management tool, no available commercial tool was found to meet this need, so a software program was built around a commercial tool, Reference Manager 12 by The Thomson Corporation. A use case approach guided the requirements development phase. The premise of the design is that individuals use their own reference management software and export to SharePoint when their library is incorporated into the Enterprise Reference Library. This results in a searchable user-specific library application. An accompanying share folder will warehouse the electronic full-text articles, which allows the global user community to access full -text articles. Discussion: An enterprise reference library solution can provide a multidisciplinary collection of full text articles. This approach improves efficiency in obtaining and storing reference material while greatly reducing labor, purchasing and

  1. The ESA Mice in Space (MIS) habitat: effects of cage confinement on neuromusculoskeletal structure and function and stress/behavior using wild-type C57Bl/6JRj mice in a modular science reference model (MSRM) test on ground

    Science.gov (United States)

    Blottner, Dieter; Vico, Laurence; Jamon, D. Berckmansp L. Vicop Y. Liup R. Canceddap M.

    Background: Environmental conditions likely affect physiology and behaviour of mice used for Life Sciences Research on Earth and in Space. Thus, mice habitats with sufficient statistical numbers should be developed for adequate life support and care and that should meet all nesces-sary ethical and scientific requirements needed to successfully perform animal experimentation in Space. Aim of study: We here analysed the effects of cage confinement on the weightbear-ing musculoskeletal system, behaviour and stress of wild-type mice (C57BL/6JRj, 30 g b.wt., total n = 24) housed for 25 days in a prototypical ground-based MSRM (modular science ref-erence module) in the frame of breadboard activities for a fully automated life support habitat called "Mice in Space" (MIS) at the Leuven University, Belgium. Results: Compared with control housing (individually ventilated cages, IVC-mice) the MIS mice revealed no significant changes in soleus muscle size and myofiber distribution (type I vs. II) and quality of bone (3-D microarchitecture and mineralisation of calvaria, spine and femur) determined by confocal and micro-computed tomography. Corticosterone metabolism measured non-invasively (faeces) monitored elevated adrenocortical activity at only start of the MIS cage confinement (day 1). Behavioural tests (i.e., grip strength, rotarod, L/D box, elevated plus-maze, open field, ag-gressiveness) performed subsequently revealed only minor changes in motor performance (MIS vs. controls). Conclusions: The MIS habitat will not, on its own, produce major effects that could confound interpretation of data induced by microgravity exposure on orbit as planned for future biosatellite programmes. Sponsors: ESA-ESTEC, Noordwijk, NL

  2. Neural neworks in a management information systems

    Directory of Open Access Journals (Sweden)

    Jana Weinlichová

    2009-01-01

    Full Text Available For having retrospection for all over the data which are used, analyzed, evaluated and for a future incident predictions are used Management Information Systems and Business Intelligence. In case of not to be able to apply standard methods of data processing there can be with benefit applied an Artificial Intelligence. In this article will be referred to proofed abilities of Neural Networks. The Neural Networks is supported by many software products related to provide effective solution of manager issues. Those products are given as primary support for manager issues solving. We were tried to find reciprocally between products using Neural Networks and between Management Information Systems for finding a real possibility of applying Neural Networks as a direct part of Management Information Systems (MIS. In the article are presented possibilities to apply Neural Networks on different types of tasks in MIS.

  3. Fuzzy logic and neural networks basic concepts & application

    CERN Document Server

    Alavala, Chennakesava R

    2008-01-01

    About the Book: The primary purpose of this book is to provide the student with a comprehensive knowledge of basic concepts of fuzzy logic and neural networks. The hybridization of fuzzy logic and neural networks is also included. No previous knowledge of fuzzy logic and neural networks is required. Fuzzy logic and neural networks have been discussed in detail through illustrative examples, methods and generic applications. Extensive and carefully selected references is an invaluable resource for further study of fuzzy logic and neural networks. Each chapter is followed by a question bank

  4. Neural neworks in a management information systems

    OpenAIRE

    Jana Weinlichová; Michael Štencl

    2009-01-01

    For having retrospection for all over the data which are used, analyzed, evaluated and for a future incident predictions are used Management Information Systems and Business Intelligence. In case of not to be able to apply standard methods of data processing there can be with benefit applied an Artificial Intelligence. In this article will be referred to proofed abilities of Neural Networks. The Neural Networks is supported by many software products related to provide effective solution of ma...

  5. Scheduling with artificial neural networks

    OpenAIRE

    Gürgün, Burçkaan

    1993-01-01

    Ankara : Department of Industrial Engineering and The Institute of Engineering and Sciences of Bilkent Univ., 1993. Thesis (Master's) -- Bilkent University, 1993. Includes bibliographical references leaves 59-65. Artificial Neural Networks (ANNs) attempt to emulate the massively parallel and distributed processing of the human brain. They are being examined for a variety of problems that have been very difficult to solve. The objective of this thesis is to review the curren...

  6. Diabetic retinopathy screening using deep neural network.

    Science.gov (United States)

    Ramachandran, Nishanthan; Hong, Sheng Chiong; Sime, Mary J; Wilson, Graham A

    2017-09-07

    There is a burgeoning interest in the use of deep neural network in diabetic retinal screening. To determine whether a deep neural network could satisfactorily detect diabetic retinopathy that requires referral to an ophthalmologist from a local diabetic retinal screening programme and an international database. Retrospective audit. Diabetic retinal photos from Otago database photographed during October 2016 (485 photos), and 1200 photos from Messidor international database. Receiver operating characteristic curve to illustrate the ability of a deep neural network to identify referable diabetic retinopathy (moderate or worse diabetic retinopathy or exudates within one disc diameter of the fovea). Area under the receiver operating characteristic curve, sensitivity and specificity. For detecting referable diabetic retinopathy, the deep neural network had an area under receiver operating characteristic curve of 0.901 (95% confidence interval 0.807-0.995), with 84.6% sensitivity and 79.7% specificity for Otago and 0.980 (95% confidence interval 0.973-0.986), with 96.0% sensitivity and 90.0% specificity for Messidor. This study has shown that a deep neural network can detect referable diabetic retinopathy with sensitivities and specificities close to or better than 80% from both an international and a domestic (New Zealand) database. We believe that deep neural networks can be integrated into community screening once they can successfully detect both diabetic retinopathy and diabetic macular oedema. © 2017 Royal Australian and New Zealand College of Ophthalmologists.

  7. PI controller based model reference adaptive control for nonlinear

    African Journals Online (AJOL)

    user

    Keywords: Model Reference Adaptive Controller (MRAC), Artificial Neural ... attention, and many new approaches have been applied to practical process .... effectiveness of proposed method, it is compared with the simulation results of the ...

  8. Analysis of neural networks

    CERN Document Server

    Heiden, Uwe

    1980-01-01

    The purpose of this work is a unified and general treatment of activity in neural networks from a mathematical pOint of view. Possible applications of the theory presented are indica­ ted throughout the text. However, they are not explored in de­ tail for two reasons : first, the universal character of n- ral activity in nearly all animals requires some type of a general approach~ secondly, the mathematical perspicuity would suffer if too many experimental details and empirical peculiarities were interspersed among the mathematical investigation. A guide to many applications is supplied by the references concerning a variety of specific issues. Of course the theory does not aim at covering all individual problems. Moreover there are other approaches to neural network theory (see e.g. Poggio-Torre, 1978) based on the different lev­ els at which the nervous system may be viewed. The theory is a deterministic one reflecting the average be­ havior of neurons or neuron pools. In this respect the essay is writt...

  9. Optics in neural computation

    Science.gov (United States)

    Levene, Michael John

    In all attempts to emulate the considerable powers of the brain, one is struck by both its immense size, parallelism, and complexity. While the fields of neural networks, artificial intelligence, and neuromorphic engineering have all attempted oversimplifications on the considerable complexity, all three can benefit from the inherent scalability and parallelism of optics. This thesis looks at specific aspects of three modes in which optics, and particularly volume holography, can play a part in neural computation. First, holography serves as the basis of highly-parallel correlators, which are the foundation of optical neural networks. The huge input capability of optical neural networks make them most useful for image processing and image recognition and tracking. These tasks benefit from the shift invariance of optical correlators. In this thesis, I analyze the capacity of correlators, and then present several techniques for controlling the amount of shift invariance. Of particular interest is the Fresnel correlator, in which the hologram is displaced from the Fourier plane. In this case, the amount of shift invariance is limited not just by the thickness of the hologram, but by the distance of the hologram from the Fourier plane. Second, volume holography can provide the huge storage capacity and high speed, parallel read-out necessary to support large artificial intelligence systems. However, previous methods for storing data in volume holograms have relied on awkward beam-steering or on as-yet non- existent cheap, wide-bandwidth, tunable laser sources. This thesis presents a new technique, shift multiplexing, which is capable of very high densities, but which has the advantage of a very simple implementation. In shift multiplexing, the reference wave consists of a focused spot a few millimeters in front of the hologram. Multiplexing is achieved by simply translating the hologram a few tens of microns or less. This thesis describes the theory for how shift

  10. A fuzzy neural network for sensor signal estimation

    International Nuclear Information System (INIS)

    Na, Man Gyun

    2000-01-01

    In this work, a fuzzy neural network is used to estimate the relevant sensor signal using other sensor signals. Noise components in input signals into the fuzzy neural network are removed through the wavelet denoising technique. Principal component analysis (PCA) is used to reduce the dimension of an input space without losing a significant amount of information. A lower dimensional input space will also usually reduce the time necessary to train a fuzzy-neural network. Also, the principal component analysis makes easy the selection of the input signals into the fuzzy neural network. The fuzzy neural network parameters are optimized by two learning methods. A genetic algorithm is used to optimize the antecedent parameters of the fuzzy neural network and a least-squares algorithm is used to solve the consequent parameters. The proposed algorithm was verified through the application to the pressurizer water level and the hot-leg flowrate measurements in pressurized water reactors

  11. Neural Network Approach to Locating Cryptography in Object Code

    Energy Technology Data Exchange (ETDEWEB)

    Jason L. Wright; Milos Manic

    2009-09-01

    Finding and identifying cryptography is a growing concern in the malware analysis community. In this paper, artificial neural networks are used to classify functional blocks from a disassembled program as being either cryptography related or not. The resulting system, referred to as NNLC (Neural Net for Locating Cryptography) is presented and results of applying this system to various libraries are described.

  12. The challenges of neural mind-reading paradigms

    OpenAIRE

    Vilarroya, Oscar

    2013-01-01

    Neural mind-reading studies, based on multivariate pattern analysis (MVPA) methods, are providing exciting new studies. Some of the results obtained with these paradigms have raised high expectations, such as the possibility of creating brain reading devices. However, such hopes are based on the assumptions that: (a) the BOLD signal is a marker of neural activity; (b) the BOLD pattern identified by a MVPA is a neurally sound pattern; (c) the MVPA's feature space is a good mapping of the neura...

  13. Germinal Center Optimization Applied to Neural Inverse Optimal Control for an All-Terrain Tracked Robot

    Directory of Open Access Journals (Sweden)

    Carlos Villaseñor

    2017-12-01

    Full Text Available Nowadays, there are several meta-heuristics algorithms which offer solutions for multi-variate optimization problems. These algorithms use a population of candidate solutions which explore the search space, where the leadership plays a big role in the exploration-exploitation equilibrium. In this work, we propose to use a Germinal Center Optimization algorithm (GCO which implements temporal leadership through modeling a non-uniform competitive-based distribution for particle selection. GCO is used to find an optimal set of parameters for a neural inverse optimal control applied to all-terrain tracked robot. In the Neural Inverse Optimal Control (NIOC scheme, a neural identifier, based on Recurrent High Orden Neural Network (RHONN trained with an extended kalman filter algorithm, is used to obtain a model of the system, then, a control law is design using such model with the inverse optimal control approach. The RHONN identifier is developed without knowledge of the plant model or its parameters, on the other hand, the inverse optimal control is designed for tracking velocity references. Applicability of the proposed scheme is illustrated using simulations results as well as real-time experimental results with an all-terrain tracked robot.

  14. The neural representation of typical and atypical experiences of negative images: comparing fear, disgust and morbid fascination

    Science.gov (United States)

    Lindquist, Kristen A.; Adebayo, Morenikeji; Barrett, Lisa Feldman

    2016-01-01

    Negative stimuli do not only evoke fear or disgust, but can also evoke a state of ‘morbid fascination’ which is an urge to approach and explore a negative stimulus. In the present neuroimaging study, we applied an innovative method to investigate the neural systems involved in typical and atypical conceptualizations of negative images. Participants received false feedback labeling their mental experience as fear, disgust or morbid fascination. This manipulation was successful; participants judged the false feedback correct for 70% of the trials on average. The neuroimaging results demonstrated differential activity within regions in the ‘neural reference space for discrete emotion’ depending on the type of feedback. We found robust differences in the ventrolateral prefrontal cortex, the dorsomedial prefrontal cortex and the lateral orbitofrontal cortex comparing morbid fascination to control feedback. More subtle differences in the dorsomedial prefrontal cortex and the lateral orbitofrontal cortex were also found between morbid fascination feedback and the other emotion feedback conditions. This study is the first to forward evidence about the neural representation of the experimentally unexplored state of morbid fascination. In line with a constructionist framework, our findings suggest that neural resources associated with the process of conceptualization contribute to the neural representation of this state. PMID:26180088

  15. Antenna analysis using neural networks

    Science.gov (United States)

    Smith, William T.

    1992-01-01

    shaping. The interesting thing about D-C synthesis is that the side lobes have the same amplitude. Five-element arrays were used. Again, 41 pattern samples were used for the input. Nine actual D-C patterns ranging from -10 dB to -30 dB side lobe levels were used to train the network. A comparison between simulated and actual D-C techniques for a pattern with -22 dB side lobe level is shown. The goal for this research was to evaluate the performance of neural network computing with antennas. Future applications will employ the backpropagation training algorithm to drastically reduce the computational complexity involved in performing EM compensation for surface errors in large space reflector antennas.

  16. Additive Feed Forward Control with Neural Networks

    DEFF Research Database (Denmark)

    Sørensen, O.

    1999-01-01

    This paper demonstrates a method to control a non-linear, multivariable, noisy process using trained neural networks. The basis for the method is a trained neural network controller acting as the inverse process model. A training method for obtaining such an inverse process model is applied....... A suitable 'shaped' (low-pass filtered) reference is used to overcome problems with excessive control action when using a controller acting as the inverse process model. The control concept is Additive Feed Forward Control, where the trained neural network controller, acting as the inverse process model......, is placed in a supplementary pure feed-forward path to an existing feedback controller. This concept benefits from the fact, that an existing, traditional designed, feedback controller can be retained without any modifications, and after training the connection of the neural network feed-forward controller...

  17. The Lyman alpha reference sample

    DEFF Research Database (Denmark)

    Hayes, M.; Östlin, G.; Schaerer, D.

    2013-01-01

    We report on new imaging observations of the Lyman alpha emission line (Lyα), performed with the Hubble Space Telescope, that comprise the backbone of the Lyman alpha Reference Sample. We present images of 14 starburst galaxies at redshifts 0.028

  18. NL(q) Theory: A Neural Control Framework with Global Asymptotic Stability Criteria.

    Science.gov (United States)

    Vandewalle, Joos; De Moor, Bart L.R.; Suykens, Johan A.K.

    1997-06-01

    In this paper a framework for model-based neural control design is presented, consisting of nonlinear state space models and controllers, parametrized by multilayer feedforward neural networks. The models and closed-loop systems are transformed into so-called NL(q) system form. NL(q) systems represent a large class of nonlinear dynamical systems consisting of q layers with alternating linear and static nonlinear operators that satisfy a sector condition. For such NL(q)s sufficient conditions for global asymptotic stability, input/output stability (dissipativity with finite L(2)-gain) and robust stability and performance are presented. The stability criteria are expressed as linear matrix inequalities. In the analysis problem it is shown how stability of a given controller can be checked. In the synthesis problem two methods for neural control design are discussed. In the first method Narendra's dynamic backpropagation for tracking on a set of specific reference inputs is modified with an NL(q) stability constraint in order to ensure, e.g., closed-loop stability. In a second method control design is done without tracking on specific reference inputs, but based on the input/output stability criteria itself, within a standard plant framework as this is done, for example, in H( infinity ) control theory and &mgr; theory. Copyright 1997 Elsevier Science Ltd.

  19. Morphological neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

    1996-12-31

    The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

  20. Neural Tube Defects

    Science.gov (United States)

    Neural tube defects are birth defects of the brain, spine, or spinal cord. They happen in the ... that she is pregnant. The two most common neural tube defects are spina bifida and anencephaly. In ...

  1. fMRI Evidence for Strategic Decision-Making during Resolution of Pronoun Reference

    Science.gov (United States)

    McMillan, Corey T.; Clark, Robin; Gunawardena, Delani; Ryant, Neville; Grossman, Murray

    2012-01-01

    Pronouns are extraordinarily common in daily language yet little is known about the neural mechanisms that support decisions about pronoun reference. We propose a large-scale neural network for resolving pronoun reference that consists of two components. First, a core language network in peri-Sylvian cortex supports syntactic and semantic…

  2. Non-invasive neural stimulation

    Science.gov (United States)

    Tyler, William J.; Sanguinetti, Joseph L.; Fini, Maria; Hool, Nicholas

    2017-05-01

    Neurotechnologies for non-invasively interfacing with neural circuits have been evolving from those capable of sensing neural activity to those capable of restoring and enhancing human brain function. Generally referred to as non-invasive neural stimulation (NINS) methods, these neuromodulation approaches rely on electrical, magnetic, photonic, and acoustic or ultrasonic energy to influence nervous system activity, brain function, and behavior. Evidence that has been surmounting for decades shows that advanced neural engineering of NINS technologies will indeed transform the way humans treat diseases, interact with information, communicate, and learn. The physics underlying the ability of various NINS methods to modulate nervous system activity can be quite different from one another depending on the energy modality used as we briefly discuss. For members of commercial and defense industry sectors that have not traditionally engaged in neuroscience research and development, the science, engineering and technology required to advance NINS methods beyond the state-of-the-art presents tremendous opportunities. Within the past few years alone there have been large increases in global investments made by federal agencies, foundations, private investors and multinational corporations to develop advanced applications of NINS technologies. Driven by these efforts NINS methods and devices have recently been introduced to mass markets via the consumer electronics industry. Further, NINS continues to be explored in a growing number of defense applications focused on enhancing human dimensions. The present paper provides a brief introduction to the field of non-invasive neural stimulation by highlighting some of the more common methods in use or under current development today.

  3. Neural Networks in Mobile Robot Motion

    Directory of Open Access Journals (Sweden)

    Danica Janglová

    2004-03-01

    Full Text Available This paper deals with a path planning and intelligent control of an autonomous robot which should move safely in partially structured environment. This environment may involve any number of obstacles of arbitrary shape and size; some of them are allowed to move. We describe our approach to solving the motion-planning problem in mobile robot control using neural networks-based technique. Our method of the construction of a collision-free path for moving robot among obstacles is based on two neural networks. The first neural network is used to determine the “free” space using ultrasound range finder data. The second neural network “finds” a safe direction for the next robot section of the path in the workspace while avoiding the nearest obstacles. Simulation examples of generated path with proposed techniques will be presented.

  4. Hopfield neural network in HEP track reconstruction

    International Nuclear Information System (INIS)

    Muresan, R.; Pentia, M.

    1997-01-01

    In experimental particle physics, pattern recognition problems, specifically for neural network methods, occur frequently in track finding or feature extraction. Track finding is a combinatorial optimization problem. Given a set of points in Euclidean space, one tries the reconstruction of particle trajectories, subject to smoothness constraints.The basic ingredients in a neural network are the N binary neurons and the synaptic strengths connecting them. In our case the neurons are the segments connecting all possible point pairs.The dynamics of the neural network is given by a local updating rule wich evaluates for each neuron the sign of the 'upstream activity'. An updating rule in the form of sigmoid function is given. The synaptic strengths are defined in terms of angle between the segments and the lengths of the segments implied in the track reconstruction. An algorithm based on Hopfield neural network has been developed and tested on the track coordinates measured by silicon microstrip tracking system

  5. Control of autonomous robot using neural networks

    Science.gov (United States)

    Barton, Adam; Volna, Eva

    2017-07-01

    The aim of the article is to design a method of control of an autonomous robot using artificial neural networks. The introductory part describes control issues from the perspective of autonomous robot navigation and the current mobile robots controlled by neural networks. The core of the article is the design of the controlling neural network, and generation and filtration of the training set using ART1 (Adaptive Resonance Theory). The outcome of the practical part is an assembled Lego Mindstorms EV3 robot solving the problem of avoiding obstacles in space. To verify models of an autonomous robot behavior, a set of experiments was created as well as evaluation criteria. The speed of each motor was adjusted by the controlling neural network with respect to the situation in which the robot was found.

  6. Neural network based multiscale image restoration approach

    Science.gov (United States)

    de Castro, Ana Paula A.; da Silva, José D. S.

    2007-02-01

    This paper describes a neural network based multiscale image restoration approach. Multilayer perceptrons are trained with artificial images of degraded gray level circles, in an attempt to make the neural network learn inherent space relations of the degraded pixels. The present approach simulates the degradation by a low pass Gaussian filter blurring operation and the addition of noise to the pixels at pre-established rates. The training process considers the degraded image as input and the non-degraded image as output for the supervised learning process. The neural network thus performs an inverse operation by recovering a quasi non-degraded image in terms of least squared. The main difference of the approach to existing ones relies on the fact that the space relations are taken from different scales, thus providing relational space data to the neural network. The approach is an attempt to come up with a simple method that leads to an optimum solution to the problem. Considering different window sizes around a pixel simulates the multiscale operation. In the generalization phase the neural network is exposed to indoor, outdoor, and satellite degraded images following the same steps use for the artificial circle image.

  7. Neural tissue-spheres

    DEFF Research Database (Denmark)

    Andersen, Rikke K; Johansen, Mathias; Blaabjerg, Morten

    2007-01-01

    By combining new and established protocols we have developed a procedure for isolation and propagation of neural precursor cells from the forebrain subventricular zone (SVZ) of newborn rats. Small tissue blocks of the SVZ were dissected and propagated en bloc as free-floating neural tissue...... content, thus allowing experimental studies of neural precursor cells and their niche...

  8. Transit space

    DEFF Research Database (Denmark)

    Raahauge, Kirsten Marie

    2008-01-01

    This article deals with representations of one specific city, Århus, Denmark, especially its central district. The analysis is based on anthropological fieldwork conducted in Skåde Bakker and Fedet, two well-off neighborhoods. The overall purpose of the project is to study perceptions of space...... and the interaction of cultural, social, and spatial organizations, as seen from the point of view of people living in Skåde Bakker and Fedet. The focus is on the city dwellers’ representations of the central district of Århus with specific reference to the concept of transit space. When applied to various Århusian...

  9. Modeling Broadband Microwave Structures by Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    V. Otevrel

    2004-06-01

    Full Text Available The paper describes the exploitation of feed-forward neural networksand recurrent neural networks for replacing full-wave numerical modelsof microwave structures in complex microwave design tools. Building aneural model, attention is turned to the modeling accuracy and to theefficiency of building a model. Dealing with the accuracy, we describea method of increasing it by successive completing a training set.Neural models are mutually compared in order to highlight theiradvantages and disadvantages. As a reference model for comparisons,approximations based on standard cubic splines are used. Neural modelsare used to replace both the time-domain numeric models and thefrequency-domain ones.

  10. Artificial Neural Networks For Hadron Hadron Cross-sections

    International Nuclear Information System (INIS)

    ELMashad, M.; ELBakry, M.Y.; Tantawy, M.; Habashy, D.M.

    2011-01-01

    In recent years artificial neural networks (ANN ) have emerged as a mature and viable framework with many applications in various areas. Artificial neural networks theory is sometimes used to refer to a branch of computational science that uses neural networks as models to either simulate or analyze complex phenomena and/or study the principles of operation of neural networks analytically. In this work a model of hadron- hadron collision using the ANN technique is present, the hadron- hadron based ANN model calculates the cross sections of hadron- hadron collision. The results amply demonstrate the feasibility of such new technique in extracting the collision features and prove its effectiveness

  11. Parking Space Verification

    DEFF Research Database (Denmark)

    Høg Peter Jensen, Troels; Thomsen Schmidt, Helge; Dyremose Bodin, Niels

    2018-01-01

    system, based on a Convolutional Neural Network, that is capable of determining if a parking space is occupied or not. A benchmark database consisting of images captured from different parking areas, under different weather and illumination conditions, has been used to train and test the system...

  12. Space Rescue

    Science.gov (United States)

    Muratore, John F.

    2007-01-01

    Space Rescue has been a topic of speculation for a wide community of people for decades. Astronauts, aerospace engineers, diplomats, medical and rescue professionals, inventors and science fiction writers have all speculated on this problem. Martin Caidin's 1964 novel Marooned dealt with the problems of rescuing a crew stranded in low earth orbit. Legend at the Johnson Space Center says that Caidin's portrayal of a Russian attempt to save the American crew played a pivotal role in convincing the Russians to join the real joint Apollo-Soyuz mission. Space Rescue has been a staple in science fiction television and movies portrayed in programs such as Star Trek, Stargate-SG1 and Space 1999 and movies such as Mission To Mars and Red Planet. As dramatic and as difficult as rescue appears in fictional accounts, in the real world it has even greater drama and greater difficulty. Space rescue is still in its infancy as a discipline and the purpose of this chapter is to describe the issues associated with space rescue and the work done so far in this field. For the purposes of this chapter, the term space rescue will refer to any system which allows for rescue or escape of personnel from situations which endanger human life in a spaceflight operation. This will span the period from crew ingress prior to flight through crew egress postlanding. For the purposes of this chapter, the term primary system will refer to the spacecraft system that a crew is either attempting to escape from or from which an attempt is being made to rescue the crew.

  13. Epidural anaesthesia with levobupivacaine and ropivacaine : effects of age on the pharmacokinetics, neural blockade and haemodynamics

    NARCIS (Netherlands)

    Simon, Mischa J.G.

    2006-01-01

    Epidural neural blockade results from processes after the administration of a local anaesthetic in the epidural space until the uptake in neural tissue. The pharmacokinetics, neural blockade and haemodynamics after epidural anaesthesia may be influenced by several factors, with age as the most

  14. Neural electrical activity and neural network growth.

    Science.gov (United States)

    Gafarov, F M

    2018-05-01

    The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

  15. Real-Time Inverse Optimal Neural Control for Image Based Visual Servoing with Nonholonomic Mobile Robots

    Directory of Open Access Journals (Sweden)

    Carlos López-Franco

    2015-01-01

    Full Text Available We present an inverse optimal neural controller for a nonholonomic mobile robot with parameter uncertainties and unknown external disturbances. The neural controller is based on a discrete-time recurrent high order neural network (RHONN trained with an extended Kalman filter. The reference velocities for the neural controller are obtained with a visual sensor. The effectiveness of the proposed approach is tested by simulations and real-time experiments.

  16. Design of efficient and safe neural stimulators a multidisciplinary approach

    CERN Document Server

    van Dongen, Marijn

    2016-01-01

    This book discusses the design of neural stimulator systems which are used for the treatment of a wide variety of brain disorders such as Parkinson’s, depression and tinnitus. Whereas many existing books treating neural stimulation focus on one particular design aspect, such as the electrical design of the stimulator, this book uses a multidisciplinary approach: by combining the fields of neuroscience, electrophysiology and electrical engineering a thorough understanding of the complete neural stimulation chain is created (from the stimulation IC down to the neural cell). This multidisciplinary approach enables readers to gain new insights into stimulator design, while context is provided by presenting innovative design examples. Provides a single-source, multidisciplinary reference to the field of neural stimulation, bridging an important knowledge gap among the fields of bioelectricity, neuroscience, neuroengineering and microelectronics;Uses a top-down approach to understanding the neural activation proc...

  17. Neural Architecture for Feature Binding in Visual Working Memory.

    Science.gov (United States)

    Schneegans, Sebastian; Bays, Paul M

    2017-04-05

    Binding refers to the operation that groups different features together into objects. We propose a neural architecture for feature binding in visual working memory that employs populations of neurons with conjunction responses. We tested this model using cued recall tasks, in which subjects had to memorize object arrays composed of simple visual features (color, orientation, and location). After a brief delay, one feature of one item was given as a cue, and the observer had to report, on a continuous scale, one or two other features of the cued item. Binding failure in this task is associated with swap errors, in which observers report an item other than the one indicated by the cue. We observed that the probability of swapping two items strongly correlated with the items' similarity in the cue feature dimension, and found a strong correlation between swap errors occurring in spatial and nonspatial report. The neural model explains both swap errors and response variability as results of decoding noisy neural activity, and can account for the behavioral results in quantitative detail. We then used the model to compare alternative mechanisms for binding nonspatial features. We found the behavioral results fully consistent with a model in which nonspatial features are bound exclusively via their shared location, with no indication of direct binding between color and orientation. These results provide evidence for a special role of location in feature binding, and the model explains how this special role could be realized in the neural system. SIGNIFICANCE STATEMENT The problem of feature binding is of central importance in understanding the mechanisms of working memory. How do we remember not only that we saw a red and a round object, but that these features belong together to a single object rather than to different objects in our environment? Here we present evidence for a neural mechanism for feature binding in working memory, based on encoding of visual

  18. Chaotic diagonal recurrent neural network

    International Nuclear Information System (INIS)

    Wang Xing-Yuan; Zhang Yi

    2012-01-01

    We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks. (interdisciplinary physics and related areas of science and technology)

  19. The Laplacian spectrum of neural networks

    Science.gov (United States)

    de Lange, Siemon C.; de Reus, Marcel A.; van den Heuvel, Martijn P.

    2014-01-01

    The brain is a complex network of neural interactions, both at the microscopic and macroscopic level. Graph theory is well suited to examine the global network architecture of these neural networks. Many popular graph metrics, however, encode average properties of individual network elements. Complementing these “conventional” graph metrics, the eigenvalue spectrum of the normalized Laplacian describes a network's structure directly at a systems level, without referring to individual nodes or connections. In this paper, the Laplacian spectra of the macroscopic anatomical neuronal networks of the macaque and cat, and the microscopic network of the Caenorhabditis elegans were examined. Consistent with conventional graph metrics, analysis of the Laplacian spectra revealed an integrative community structure in neural brain networks. Extending previous findings of overlap of network attributes across species, similarity of the Laplacian spectra across the cat, macaque and C. elegans neural networks suggests a certain level of consistency in the overall architecture of the anatomical neural networks of these species. Our results further suggest a specific network class for neural networks, distinct from conceptual small-world and scale-free models as well as several empirical networks. PMID:24454286

  20. Adaptive competitive learning neural networks

    Directory of Open Access Journals (Sweden)

    Ahmed R. Abas

    2013-11-01

    Full Text Available In this paper, the adaptive competitive learning (ACL neural network algorithm is proposed. This neural network not only groups similar input feature vectors together but also determines the appropriate number of groups of these vectors. This algorithm uses a new proposed criterion referred to as the ACL criterion. This criterion evaluates different clustering structures produced by the ACL neural network for an input data set. Then, it selects the best clustering structure and the corresponding network architecture for this data set. The selected structure is composed of the minimum number of clusters that are compact and balanced in their sizes. The selected network architecture is efficient, in terms of its complexity, as it contains the minimum number of neurons. Synaptic weight vectors of these neurons represent well-separated, compact and balanced clusters in the input data set. The performance of the ACL algorithm is evaluated and compared with the performance of a recently proposed algorithm in the literature in clustering an input data set and determining its number of clusters. Results show that the ACL algorithm is more accurate and robust in both determining the number of clusters and allocating input feature vectors into these clusters than the other algorithm especially with data sets that are sparsely distributed.

  1. Evolvable Neural Software System

    Science.gov (United States)

    Curtis, Steven A.

    2009-01-01

    The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

  2. Standard Reference Tables -

    Data.gov (United States)

    Department of Transportation — The Standard Reference Tables (SRT) provide consistent reference data for the various applications that support Flight Standards Service (AFS) business processes and...

  3. A neural flow estimator

    DEFF Research Database (Denmark)

    Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik

    1995-01-01

    This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system...... is implemented using switched-current technique and is capable of estimating flow in the μl/s range. The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V...

  4. Neural Systems Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — As part of the Electrical and Computer Engineering Department and The Institute for System Research, the Neural Systems Laboratory studies the functionality of the...

  5. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    are examined. The models are separated into three groups representing input/output descriptions as well as state space descriptions: - Models, where all in- and outputs are measurable (static networks). - Models, where some inputs are non-measurable (recurrent networks). - Models, where some in- and some...... outputs are non-measurable (recurrent networks with incomplete state information). The three groups are ordered in increasing complexity, and for each group it is shown how to solve the problems concerning training and application of the specific model type. Of particular interest are the model types...... Kalmann filter) representing state space description. The potentials of neural networks for control of non-linear processes are also examined, focusing on three different groups of control concepts, all considered as generalizations of known linear control concepts to handle also non-linear processes...

  6. Neural Networks: Implementations and Applications

    OpenAIRE

    Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

    1996-01-01

    Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

  7. Critical Branching Neural Networks

    Science.gov (United States)

    Kello, Christopher T.

    2013-01-01

    It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…

  8. Consciousness and neural plasticity

    DEFF Research Database (Denmark)

    changes or to abandon the strong identity thesis altogether. Were one to pursue a theory according to which consciousness is not an epiphenomenon to brain processes, consciousness may in fact affect its own neural basis. The neural correlate of consciousness is often seen as a stable structure, that is...

  9. Recurrent Neural Network for Computing Outer Inverse.

    Science.gov (United States)

    Živković, Ivan S; Stanimirović, Predrag S; Wei, Yimin

    2016-05-01

    Two linear recurrent neural networks for generating outer inverses with prescribed range and null space are defined. Each of the proposed recurrent neural networks is based on the matrix-valued differential equation, a generalization of dynamic equations proposed earlier for the nonsingular matrix inversion, the Moore-Penrose inversion, as well as the Drazin inversion, under the condition of zero initial state. The application of the first approach is conditioned by the properties of the spectrum of a certain matrix; the second approach eliminates this drawback, though at the cost of increasing the number of matrix operations. The cases corresponding to the most common generalized inverses are defined. The conditions that ensure stability of the proposed neural network are presented. Illustrative examples present the results of numerical simulations.

  10. Third Conference on Artificial Intelligence for Space Applications, part 2

    Science.gov (United States)

    Denton, Judith S. (Compiler); Freeman, Michael S. (Compiler); Vereen, Mary (Compiler)

    1988-01-01

    Topics relative to the application of artificial intelligence to space operations are discussed. New technologies for space station automation, design data capture, computer vision, neural nets, automatic programming, and real time applications are discussed.

  11. 2002 reference document; Document de reference 2002

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2002-07-01

    This 2002 reference document of the group Areva, provides information on the society. Organized in seven chapters, it presents the persons responsible for the reference document and for auditing the financial statements, information pertaining to the transaction, general information on the company and share capital, information on company operation, changes and future prospects, assets, financial position, financial performance, information on company management and executive board and supervisory board, recent developments and future prospects. (A.L.B.)

  12. Representations of locally symmetric spaces

    International Nuclear Information System (INIS)

    Rahman, M.S.

    1995-09-01

    Locally symmetric spaces in reference to globally and Hermitian symmetric Riemannian spaces are studied. Some relations between locally and globally symmetric spaces are exhibited. A lucid account of results on relevant spaces, motivated by fundamental problems, are formulated as theorems and propositions. (author). 10 refs

  13. Prototype-Incorporated Emotional Neural Network.

    Science.gov (United States)

    Oyedotun, Oyebade K; Khashman, Adnan

    2017-08-15

    Artificial neural networks (ANNs) aim to simulate the biological neural activities. Interestingly, many ''engineering'' prospects in ANN have relied on motivations from cognition and psychology studies. So far, two important learning theories that have been subject of active research are the prototype and adaptive learning theories. The learning rules employed for ANNs can be related to adaptive learning theory, where several examples of the different classes in a task are supplied to the network for adjusting internal parameters. Conversely, the prototype-learning theory uses prototypes (representative examples); usually, one prototype per class of the different classes contained in the task. These prototypes are supplied for systematic matching with new examples so that class association can be achieved. In this paper, we propose and implement a novel neural network algorithm based on modifying the emotional neural network (EmNN) model to unify the prototype- and adaptive-learning theories. We refer to our new model as ``prototype-incorporated EmNN''. Furthermore, we apply the proposed model to two real-life challenging tasks, namely, static hand-gesture recognition and face recognition, and compare the result to those obtained using the popular back-propagation neural network (BPNN), emotional BPNN (EmNN), deep networks, an exemplar classification model, and k-nearest neighbor.

  14. Communication spaces.

    Science.gov (United States)

    Coiera, Enrico

    2014-01-01

    Annotations to physical workspaces such as signs and notes are ubiquitous. When densely annotated, work areas become communication spaces. This study aims to characterize the types and purpose of such annotations. A qualitative observational study was undertaken in two wards and the radiology department of a 440-bed metropolitan teaching hospital. Images were purposefully sampled; 39 were analyzed after excluding inferior images. Annotation functions included signaling identity, location, capability, status, availability, and operation. They encoded data, rules or procedural descriptions. Most aggregated into groups that either created a workflow by referencing each other, supported a common workflow without reference to each other, or were heterogeneous, referring to many workflows. Higher-level assemblies of such groupings were also observed. Annotations make visible the gap between work done and the capability of a space to support work. Annotations are repairs of an environment, improving fitness for purpose, fixing inadequacy in design, or meeting emergent needs. Annotations thus record the missing information needed to undertake tasks, typically added post-implemented. Measuring annotation levels post-implementation could help assess the fit of technology to task. Physical and digital spaces could meet broader user needs by formally supporting user customization, 'programming through annotation'. Augmented reality systems could also directly support annotation, addressing existing information gaps, and enhancing work with context sensitive annotation. Communication spaces offer a model of how work unfolds. Annotations make visible local adaptation that makes technology fit for purpose post-implementation and suggest an important role for annotatable information systems and digital augmentation of the physical environment.

  15. Systematic design of active spaces for multi-reference calculations of singlet-triplet gaps of organic diradicals, with benchmarks against doubly electron-attached coupled-cluster data

    Science.gov (United States)

    Stoneburner, Samuel J.; Shen, Jun; Ajala, Adeayo O.; Piecuch, Piotr; Truhlar, Donald G.; Gagliardi, Laura

    2017-10-01

    Singlet-triplet gaps in diradical organic π-systems are of interest in many applications. In this study, we calculate them in a series of molecules, including cyclobutadiene and its derivatives and cyclopentadienyl cation, by using correlated participating orbitals within the complete active space (CAS) and restricted active space (RAS) self-consistent field frameworks, followed by second-order perturbation theory (CASPT2 and RASPT2). These calculations are evaluated by comparison with the results of doubly electron-attached (DEA) equation-of-motion (EOM) coupled-cluster (CC) calculations with up to 4-particle-2-hole (4p-2h) excitations. We find active spaces that can accurately reproduce the DEA-EOMCC(4p-2h) data while being small enough to be applicable to larger organic diradicals.

  16. VBE reference framework

    NARCIS (Netherlands)

    Afsarmanesh, H.; Camarinha-Matos, L.M.; Ermilova, E.; Camarinha-Matos, L.M.; Afsarmanesh, H.; Ollus, M.

    2008-01-01

    Defining a comprehensive and generic "reference framework" for Virtual organizations Breeding Environments (VBEs), addressing all their features and characteristics, is challenging. While the definition and modeling of VBEs has become more formalized during the last five years, "reference models"

  17. CMS Statistics Reference Booklet

    Data.gov (United States)

    U.S. Department of Health & Human Services — The annual CMS Statistics reference booklet provides a quick reference for summary information about health expenditures and the Medicare and Medicaid health...

  18. Genetics Home Reference: spondylocostal dysostosis

    Science.gov (United States)

    ... when a structure called the neural tube, a layer of cells that ultimately develops into the brain and spinal cord, fails to close completely during the first few weeks of embryonic development. Examples of neural tube defects that occur ...

  19. A comparative study of two neural networks for document retrieval

    International Nuclear Information System (INIS)

    Hui, S.C.; Goh, A.

    1997-01-01

    In recent years there has been specific interest in adopting advanced computer techniques in the field of document retrieval. This interest is generated by the fact that classical methods such as the Boolean search, the vector space model or even probabilistic retrieval cannot handle the increasing demands of end-users in satisfying their needs. The most recent attempt is the application of the neural network paradigm as a means of providing end-users with a more powerful retrieval mechanism. Neural networks are not only good pattern matchers but also highly versatile and adaptable. In this paper, we demonstrate how to apply two neural networks, namely Adaptive Resonance Theory and Fuzzy Kohonen Neural Network, for document retrieval. In addition, a comparison of these two neural networks based on performance is also given

  20. Changing quantum reference frames

    OpenAIRE

    Palmer, Matthew C.; Girelli, Florian; Bartlett, Stephen D.

    2013-01-01

    We consider the process of changing reference frames in the case where the reference frames are quantum systems. We find that, as part of this process, decoherence is necessarily induced on any quantum system described relative to these frames. We explore this process with examples involving reference frames for phase and orientation. Quantifying the effect of changing quantum reference frames serves as a first step in developing a relativity principle for theories in which all objects includ...

  1. Dynamics of neural cryptography.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-05-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

  2. Dynamics of neural cryptography

    International Nuclear Information System (INIS)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-01-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible

  3. Dynamics of neural cryptography

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-05-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

  4. File access prediction using neural networks.

    Science.gov (United States)

    Patra, Prashanta Kumar; Sahu, Muktikanta; Mohapatra, Subasish; Samantray, Ronak Kumar

    2010-06-01

    One of the most vexing issues in design of a high-speed computer is the wide gap of access times between the memory and the disk. To solve this problem, static file access predictors have been used. In this paper, we propose dynamic file access predictors using neural networks to significantly improve upon the accuracy, success-per-reference, and effective-success-rate-per-reference by using neural-network-based file access predictor with proper tuning. In particular, we verified that the incorrect prediction has been reduced from 53.11% to 43.63% for the proposed neural network prediction method with a standard configuration than the recent popularity (RP) method. With manual tuning for each trace, we are able to improve upon the misprediction rate and effective-success-rate-per-reference using a standard configuration. Simulations on distributed file system (DFS) traces reveal that exact fit radial basis function (RBF) gives better prediction in high end system whereas multilayer perceptron (MLP) trained with Levenberg-Marquardt (LM) backpropagation outperforms in system having good computational capability. Probabilistic and competitive predictors are the most suitable for work stations having limited resources to deal with and the former predictor is more efficient than the latter for servers having maximum system calls. Finally, we conclude that MLP with LM backpropagation algorithm has better success rate of file prediction than those of simple perceptron, last successor, stable successor, and best k out of m predictors.

  5. ANT Advanced Neural Tool

    Energy Technology Data Exchange (ETDEWEB)

    Labrador, I.; Carrasco, R.; Martinez, L.

    1996-07-01

    This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs.

  6. ANT Advanced Neural Tool

    International Nuclear Information System (INIS)

    Labrador, I.; Carrasco, R.; Martinez, L.

    1996-01-01

    This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs

  7. The past and space

    DEFF Research Database (Denmark)

    Lund, Christian

    2013-01-01

    of legitimate forms of land control, complex combinations of claims emerge. The ubiquity of ‘the past’ in African politics and the increasing competition over space suggest that the naturalness with which some refer to the past and others conceive of space should be under constant scrutiny. Based on work...... that competing social elite groups instrumentalize. Each group sees its interests best served by a particular reading of the past and a particular conception of space....

  8. System and method for determining stability of a neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2011-01-01

    Disclosed are methods, systems, and computer-readable media for determining stability of a neural system. The method includes tracking a function world line of an N element neural system within at least one behavioral space, determining whether the tracking function world line is approaching a psychological stability surface, and implementing a quantitative solution that corrects instability if the tracked function world line is approaching the psychological stability surface.

  9. IAEA biological reference materials

    International Nuclear Information System (INIS)

    Parr, R.M.; Schelenz, R.; Ballestra, S.

    1988-01-01

    The Analytical Quality Control Services programme of the IAEA encompasses a wide variety of intercomparisons and reference materials. This paper reviews only those aspects of the subject having to do with biological reference materials. The 1988 programme foresees 13 new intercomparison exercises, one for major, minor and trace elements, five for radionuclides, and seven for stable isotopes. Twenty-two natural matrix biological reference materials are available: twelve for major, minor and trace elements, six for radionuclides, and four for chlorinated hydrocarbons. Seven new intercomparisons and reference materials are in preparation or under active consideration. Guidelines on the correct use of reference materials are being prepared for publication in 1989 in consultation with other major international producers and users of biological reference materials. The IAEA database on available reference materials is being updated and expanded in scope, and a new publication is planned for 1989. (orig.)

  10. Polarized DIS Structure Functions from Neural Networks

    International Nuclear Information System (INIS)

    Del Debbio, L.; Guffanti, A.; Piccione, A.

    2007-01-01

    We present a parametrization of polarized Deep-Inelastic-Scattering (DIS) structure functions based on Neural Networks. The parametrization provides a bias-free determination of the probability measure in the space of structure functions, which retains information on experimental errors and correlations. As an example we discuss the application of this method to the study of the structure function g 1 p (x,Q 2 )

  11. Development of beta reference radiations

    International Nuclear Information System (INIS)

    Wan Zhaoyong; Cai Shanyu; Li Yanbo; Yin Wei; Feng Jiamin; Sun Yuhua; Li Yongqiang

    1997-09-01

    A system of beta reference radiation has been developed, that is composed of 740 MBq 147 Pm beta source, 74 MBq and 740 MBq 90 Sr + 90 Y β sources, compensation filters, a source handling tool, a source jig, spacing bars, a shutter, a control unit and a beta dose meter calibration stand. For 740 MBq 147 Pm and 74 MBq 90 Sr + 90 Y beta reference radiations with compensation filters and 740 MBq 90 Sr + 90 Y beta reference radiation without compensation filter, at 20 cm, 30 cm and 30 cm distance separately; the residual energy of maximum is 0.14 MeV, 1.98 MeV and 2.18 MeV separately; the absorbed dose to tissue D (0.07) is 1.547 mGy/h (1996-05-20), 5.037 mGy/h (1996-05-10) and 93.57 mGy/h (1996-05-15) separately; the total uncertainty is 3.0%, 1.7% and 1.7% separately. For the first and the second beta reference radiation, the dose rate variability in the area of 18 cm diameter in the plane perpendicular to the beta-ray beam axis is within +-6% and +-3% separately. (3 refs., 2 tabs., 8 figs.)

  12. Hidden neural networks

    DEFF Research Database (Denmark)

    Krogh, Anders Stærmose; Riis, Søren Kamaric

    1999-01-01

    A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...

  13. Neural networks for aircraft control

    Science.gov (United States)

    Linse, Dennis

    1990-01-01

    Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.

  14. Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control

    Science.gov (United States)

    Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.

    1997-01-01

    One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.

  15. Active Neural Localization

    OpenAIRE

    Chaplot, Devendra Singh; Parisotto, Emilio; Salakhutdinov, Ruslan

    2018-01-01

    Localization is the problem of estimating the location of an autonomous agent from an observation and a map of the environment. Traditional methods of localization, which filter the belief based on the observations, are sub-optimal in the number of steps required, as they do not decide the actions taken by the agent. We propose "Active Neural Localizer", a fully differentiable neural network that learns to localize accurately and efficiently. The proposed model incorporates ideas of tradition...

  16. Neural cryptography with feedback.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido

    2004-04-01

    Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.

  17. Imaging Posture Veils Neural Signals

    Directory of Open Access Journals (Sweden)

    Robert T Thibault

    2016-10-01

    Full Text Available Whereas modern brain imaging often demands holding body positions incongruent with everyday life, posture governs both neural activity and cognitive performance. Humans commonly perform while upright; yet, many neuroimaging methodologies require participants to remain motionless and adhere to non-ecological comportments within a confined space. This inconsistency between ecological postures and imaging constraints undermines the transferability and generalizability of many a neuroimaging assay.Here we highlight the influence of posture on brain function and behavior. Specifically, we challenge the tacit assumption that brain processes and cognitive performance are comparable across a spectrum of positions. We provide an integrative synthesis regarding the increasingly prominent influence of imaging postures on autonomic function, mental capacity, sensory thresholds, and neural activity. Arguing that neuroimagers and cognitive scientists could benefit from considering the influence posture wields on both general functioning and brain activity, we examine existing imaging technologies and the potential of portable and versatile imaging devices (e.g., functional near infrared spectroscopy. Finally, we discuss ways that accounting for posture may help unveil the complex brain processes of everyday cognition.

  18. Artificial Neural Networks and the Mass Appraisal of Real Estate

    Directory of Open Access Journals (Sweden)

    Gang Zhou

    2018-03-01

    Full Text Available With the rapid development of computer, artificial intelligence and big data technology, artificial neural networks have become one of the most powerful machine learning algorithms. In the practice, most of the applications of artificial neural networks use back propagation neural network and its variation. Besides the back propagation neural network, various neural networks have been developing in order to improve the performance of standard models. Though neural networks are well known method in the research of real estate, there is enormous space for future research in order to enhance their function. Some scholars combine genetic algorithm, geospatial information, support vector machine model, particle swarm optimization with artificial neural networks to appraise the real estate, which is helpful for the existing appraisal technology. The mass appraisal of real estate in this paper includes the real estate valuation in the transaction and the tax base valuation in the real estate holding. In this study we focus on the theoretical development of artificial neural networks and mass appraisal of real estate, artificial neural networks model evolution and algorithm improvement, artificial neural networks practice and application, and review the existing literature about artificial neural networks and mass appraisal of real estate. Finally, we provide some suggestions for the mass appraisal of China's real estate.

  19. Accelerated optimizations of an electromagnetic acoustic transducer with artificial neural networks as metamodels

    Directory of Open Access Journals (Sweden)

    S. Wang

    2017-08-01

    Full Text Available Electromagnetic acoustic transducers (EMATs are noncontact transducers generating ultrasonic waves directly in the conductive sample. Despite the advantages, their transduction efficiencies are relatively low, so it is imperative to build accurate multiphysics models of EMATs and optimize the structural parameters accordingly, using a suitable optimization algorithm. The optimizing process often involves a large number of runs of the computationally expensive numerical models, so metamodels as substitutes for the real numerical models are helpful for the optimizations. In this work the focus is on the artificial neural networks as the metamodels of an omnidirectional EMAT, including the multilayer feedforward networks trained with the basic and improved back propagation algorithms and the radial basis function networks with exact and nonexact interpolations. The developed neural-network programs are tested on an example problem. Then the model of an omnidirectional EMAT generating Lamb waves in a linearized steel plate is introduced, and various approaches to calculate the amplitudes of the displacement component waveforms are discussed. The neural-network metamodels are then built for the EMAT model and compared to the displacement component amplitude (or ratio of amplitudes surface data on a discrete grid of the design variables as the reference, applying a multifrequency model with FFT (fast Fourier transform/IFFT (inverse FFT processing. Finally the two-objective optimization problem is formulated with one objective function minimizing the ratio of the amplitude of the S0-mode Lamb wave to that of the A0 mode, and the other objective function minimizing as the negative amplitude of the A0 mode. Pareto fronts in the criterion space are solved with the neural-network models and the total time consumption is greatly decreased. From the study it could be observed that the radial basis function network with exact interpolation has the best

  20. Reference design for LAMPF II

    International Nuclear Information System (INIS)

    Thiessen, H.A.

    1983-01-01

    A reference design for the 32-GeV LAMPF II proton accelerator is proposed. This design consists of a 30-Hz rapid-cycling synchrotron with a dc stretcher. A superiodicity 5 design with dispersion-free straight sections is suggested for both machines. Beam-dynamics calculations are partially complete and rf requirements are given. Apertures are calculated for 2 x 10 13 protons per pulse (100 μA average current). No significant problems are observed at any time in the cycle in a longitudinal beam-dynamics simulation including space charge

  1. Computationally efficient model predictive control algorithms a neural network approach

    CERN Document Server

    Ławryńczuk, Maciej

    2014-01-01

    This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: ·         A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. ·         Implementation details of the MPC algorithms for feedforward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. ·         The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). ·         The MPC algorithms with neural approximation with no on-line linearization. ·         The MPC algorithms with guaranteed stability and robustness. ·         Cooperation between the MPC algorithms and set-point optimization. Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require d...

  2. Speed Sensorless Control of PMSM using Model Reference Adaptive System and RBFN

    OpenAIRE

    Wei Gao; Zhirong Guo

    2013-01-01

    In the speed sensorless vector control system, the amended method of estimating the rotor speed about model reference adaptive system (MRAS) based on radial basis function neural network (RBFN) for PMSM sensorless vector control system was presented. Based on the PI regulator, the radial basis function neural network which is more prominent learning efficiency and performance is combined with MRAS. The reference model and the adjust model are the PMSM itself and the PMSM current, respectively...

  3. Are All Spatial Reference Frames Egocentric? Reinterpreting Evidence for Allocentric, Object-Centered, or World-Centered Reference Frames

    OpenAIRE

    Filimon, Flavia

    2015-01-01

    The use and neural representation of egocentric spatial reference frames is well-documented. In contrast, whether the brain represents spatial relationships between objects in allocentric, object-centered, or world-centered coordinates is debated. Here, I review behavioral, neuropsychological, neurophysiological (neuronal recording), and neuroimaging evidence for and against allocentric, object-centered, or world-centered spatial reference frames. Based on theoretical considerations, simulati...

  4. Indoor air: Reference bibliography

    International Nuclear Information System (INIS)

    Campbell, D.; Staves, D.; McDonald, S.

    1989-07-01

    The U. S. Environmental Protection Agency initially established the indoor air Reference Bibliography in 1987 as an appendix to the Indoor Air Quality Implementation Plan. The document was submitted to Congress as required under Title IV--Radon Gas and Indoor Air Quality Research of the Superfund Amendments and Reauthorization Act of 1986. The Reference Bibliography is an extensive bibliography of reference materials on indoor air pollution. The Bibliography contains over 4500 citations and continues to increase as new articles appear

  5. Reconfigurable Flight Control Design using a Robust Servo LQR and Radial Basis Function Neural Networks

    Science.gov (United States)

    Burken, John J.

    2005-01-01

    This viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.

  6. Neural network feedforward control of a closed-circuit wind tunnel

    Science.gov (United States)

    Sutcliffe, Peter

    Accurate control of wind-tunnel test conditions can be dramatically enhanced using feedforward control architectures which allow operating conditions to be maintained at a desired setpoint through the use of mathematical models as the primary source of prediction. However, as the desired accuracy of the feedforward prediction increases, the model complexity also increases, so that an ever increasing computational load is incurred. This drawback can be avoided by employing a neural network that is trained offline using the output of a high fidelity wind-tunnel mathematical model, so that the neural network can rapidly reproduce the predictions of the model with a greatly reduced computational overhead. A novel neural network database generation method, developed through the use of fractional factorial arrays, was employed such that a neural network can accurately predict wind-tunnel parameters across a wide range of operating conditions whilst trained upon a highly efficient database. The subsequent network was incorporated into a Neural Network Model Predictive Control (NNMPC) framework to allow an optimised output schedule capable of providing accurate control of the wind-tunnel operating parameters. Facilitation of an optimised path through the solution space is achieved through the use of a chaos optimisation algorithm such that a more globally optimum solution is likely to be found with less computational expense than the gradient descent method. The parameters associated with the NNMPC such as the control horizon are determined through the use of a Taguchi methodology enabling the minimum number of experiments to be carried out to determine the optimal combination. The resultant NNMPC scheme was employed upon the Hessert Low Speed Wind Tunnel at the University of Notre Dame to control the test-section temperature such that it follows a pre-determined reference trajectory during changes in the test-section velocity. Experimental testing revealed that the

  7. Android quick APIs reference

    CERN Document Server

    Cinar, Onur

    2015-01-01

    The Android Quick APIs Reference is a condensed code and APIs reference for the new Google Android 5.0 SDK. It presents the essential Android APIs in a well-organized format that can be used as a handy reference. You won't find any technical jargon, bloated samples, drawn out history lessons, or witty stories in this book. What you will find is a software development kit and APIs reference that is concise, to the point and highly accessible. The book is packed with useful information and is a must-have for any mobile or Android app developer or programmer. In the Android Quick APIs Refe

  8. Neutron spectrometry with artificial neural networks

    International Nuclear Information System (INIS)

    Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E.; Rodriguez, J.M.; Mercado S, G.A.; Iniguez de la Torre Bayo, M.P.; Barquero, R.; Arteaga A, T.

    2005-01-01

    An artificial neural network has been designed to obtain the neutron spectra from the Bonner spheres spectrometer's count rates. The neural network was trained using 129 neutron spectra. These include isotopic neutron sources; reference and operational spectra from accelerators and nuclear reactors, spectra from mathematical functions as well as few energy groups and monoenergetic spectra. The spectra were transformed from lethargy to energy distribution and were re-bin ned to 31 energy groups using the MCNP 4C code. Re-binned spectra and UTA4 response matrix were used to calculate the expected count rates in Bonner spheres spectrometer. These count rates were used as input and the respective spectrum was used as output during neural network training. After training the network was tested with the Bonner spheres count rates produced by a set of neutron spectra. This set contains data used during network training as well as data not used. Training and testing was carried out in the Mat lab program. To verify the network unfolding performance the original and unfolded spectra were compared using the χ 2 -test and the total fluence ratios. The use of Artificial Neural Networks to unfold neutron spectra in neutron spectrometry is an alternative procedure that overcomes the drawbacks associated in this ill-conditioned problem. (Author)

  9. Neutron spectrometry using artificial neural networks

    International Nuclear Information System (INIS)

    Vega-Carrillo, Hector Rene; Martin Hernandez-Davila, Victor; Manzanares-Acuna, Eduardo; Mercado Sanchez, Gema A.; Pilar Iniguez de la Torre, Maria; Barquero, Raquel; Palacios, Francisco; Mendez Villafane, Roberto; Arteaga Arteaga, Tarcicio; Manuel Ortiz Rodriguez, Jose

    2006-01-01

    An artificial neural network has been designed to obtain neutron spectra from Bonner spheres spectrometer count rates. The neural network was trained using 129 neutron spectra. These include spectra from isotopic neutron sources; reference and operational spectra from accelerators and nuclear reactors, spectra based on mathematical functions as well as few energy groups and monoenergetic spectra. The spectra were transformed from lethargy to energy distribution and were re-binned to 31 energy groups using the MCNP 4C code. The re-binned spectra and the UTA4 response matrix were used to calculate the expected count rates in Bonner spheres spectrometer. These count rates were used as input and their respective spectra were used as output during the neural network training. After training, the network was tested with the Bonner spheres count rates produced by folding a set of neutron spectra with the response matrix. This set contains data used during network training as well as data not used. Training and testing was carried out using the Matlab ( R) program. To verify the network unfolding performance, the original and unfolded spectra were compared using the root mean square error. The use of artificial neural networks to unfold neutron spectra in neutron spectrometry is an alternative procedure that overcomes the drawbacks associated with this ill-conditioned problem

  10. Marketing Reference Services.

    Science.gov (United States)

    Norman, O. Gene

    1995-01-01

    Relates the marketing concept to library reference services. Highlights include a review of the literature and an overview of marketing, including research, the marketing mix, strategic plan, marketing plan, and marketing audit. Marketing principles are applied to reference services through the marketing mix elements of product, price, place, and…

  11. Reference class forecasting

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent

    optimisme og misinformation. RCF bygger på teorier, som vandt Daniel Kahneman Nobelprisen i økonomi i 2002. RCF estimerer budgettet for et givet projekt på grundlag af de faktiske udfald for budgetterne i en reference-klasse af projekter. RCF udføres i tre trin: 1. Identifikation af en relevant reference...

  12. Advanced neural network-based computational schemes for robust fault diagnosis

    CERN Document Server

    Mrugalski, Marcin

    2014-01-01

    The present book is devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemes. It presents neural networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems. A part of the book focuses on fundamental issues such as architectures of dynamic neural networks, methods for designing of neural networks and fault diagnosis schemes as well as the importance of robustness. The book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. The book is also devoted to advanced schemes of description of neural model uncertainty. In particular, the methods of computation of neural networks uncertainty with robust parameter estimation are presented. Moreover, a novel approach for system identification with the state-space GMDH neural network is delivered. All the concepts described in this book are illustrated by both simple academic illustrative examples and practica...

  13. 14 CFR 135.207 - VFR: Helicopter surface reference requirements.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false VFR: Helicopter surface reference... VFR/IFR Operating Limitations and Weather Requirements § 135.207 VFR: Helicopter surface reference requirements. No person may operate a helicopter under VFR unless that person has visual surface reference or...

  14. Quantum mechanics with respect to different reference frames

    International Nuclear Information System (INIS)

    Mangiarotti, L.; Sardanashvily, G.

    2007-01-01

    Geometric (Schroedinger) quantization of nonrelativistic mechanics with respect to different reference frames is considered. In classical nonrelativistic mechanics, a reference frame is represented by a connection on a configuration space fibered over a time axis R. Under quantization, it yields a connection on the quantum algebra of Schroedinger operators. The operators of energy with respect to different reference frames are examined

  15. Parallel consensual neural networks.

    Science.gov (United States)

    Benediktsson, J A; Sveinsson, J R; Ersoy, O K; Swain, P H

    1997-01-01

    A new type of a neural-network architecture, the parallel consensual neural network (PCNN), is introduced and applied in classification/data fusion of multisource remote sensing and geographic data. The PCNN architecture is based on statistical consensus theory and involves using stage neural networks with transformed input data. The input data are transformed several times and the different transformed data are used as if they were independent inputs. The independent inputs are first classified using the stage neural networks. The output responses from the stage networks are then weighted and combined to make a consensual decision. In this paper, optimization methods are used in order to weight the outputs from the stage networks. Two approaches are proposed to compute the data transforms for the PCNN, one for binary data and another for analog data. The analog approach uses wavelet packets. The experimental results obtained with the proposed approach show that the PCNN outperforms both a conjugate-gradient backpropagation neural network and conventional statistical methods in terms of overall classification accuracy of test data.

  16. Predictive Control of Hydronic Floor Heating Systems using Neural Networks and Genetic Algorithms

    DEFF Research Database (Denmark)

    Vinther, Kasper; Green, Torben; Østergaard, Søren

    2017-01-01

    This paper presents the use a neural network and a micro genetic algorithm to optimize future set-points in existing hydronic floor heating systems for improved energy efficiency. The neural network can be trained to predict the impact of changes in set-points on future room temperatures. Additio...... space is not guaranteed. Evaluation of the performance of multiple neural networks is performed, using different levels of information, and optimization results are presented on a detailed house simulation model....

  17. Image Encryption and Chaotic Cellular Neural Network

    Science.gov (United States)

    Peng, Jun; Zhang, Du

    Machine learning has been playing an increasingly important role in information security and assurance. One of the areas of new applications is to design cryptographic systems by using chaotic neural network due to the fact that chaotic systems have several appealing features for information security applications. In this chapter, we describe a novel image encryption algorithm that is based on a chaotic cellular neural network. We start by giving an introduction to the concept of image encryption and its main technologies, and an overview of the chaotic cellular neural network. We then discuss the proposed image encryption algorithm in details, which is followed by a number of security analyses (key space analysis, sensitivity analysis, information entropy analysis and statistical analysis). The comparison with the most recently reported chaos-based image encryption algorithms indicates that the algorithm proposed in this chapter has a better security performance. Finally, we conclude the chapter with possible future work and application prospects of the chaotic cellular neural network in other information assurance and security areas.

  18. A neural network approach to the study of dynamics and structure of molecular systems

    International Nuclear Information System (INIS)

    Getino, C.; Sumpter, B.G.; Noid, D.W.

    1994-01-01

    Neural networks are used to study intramolecular energy flow in molecular systems (tetratomics to macromolecules), developing new techniques for efficient analysis of data obtained from molecular-dynamics and quantum mechanics calculations. Neural networks can map phase space points to intramolecular vibrational energies along a classical trajectory (example of complicated coordinate transformation), producing reasonably accurate values for any region of the multidimensional phase space of a tetratomic molecule. Neural network energy flow predictions are found to significantly enhance the molecular-dynamics method to longer time-scales and extensive averaging of trajectories for macromolecular systems. Pattern recognition abilities of neural networks can be used to discern phase space features. Neural networks can also expand model calculations by interpolation of costly quantum mechanical ab initio data, used to develop semiempirical potential energy functions

  19. Women's social space and the reference for breastfeeding practice El espacio social de mujeres y su referencia para el cuidado en la práctica de la lactancia O espaço social das mulheres e a referência para o cuidado na prática da amamentação

    Directory of Open Access Journals (Sweden)

    Ana Márcia Spanó Nakano

    2007-04-01

    Full Text Available This study aimed to identify agents or institutions taken as reference by women when breastfeeding. A qualitative study was carried out on 20 primiparous who were assisted, for reasons not related to breastfeeding, in the five health services selected by this study. Data were collected by semi-structured interviews carried out in the participants' households and were analyzed by content analysis in the thematic mode. We identified that health professionals play a standardize role of breastfeeding based on scientific knowledge. In the daily breastfeeding routine, the family is the first reference for women, transmitting beliefs, habits and behaviors. We believe in the valorization of the family context by the health professional, in which actions and interactions in the breastfeeding issue are developed in order to constitute the foundations for a new care model in breastfeeding. This model should, therefore, consider the practice diversity, adapting actions to the multiple roles of being mother/fortress/wife/worker in the social context.Este estudio tuvo como objetivo identificar los agentes o instituciones consideradas como referencia por las madres lactantes en la práctica de amamatación. Investigación cualitativa con 20 puérperas quienes buscaron por razones ajenas a la lactancia una de las 5 unidades básicas de salud seleccionadas en este estudio. Los datos fueron recolectados a través de entrevistas semi-estructuradas realizadas en su domicilio; su análisis se apoyó en el análisis de contenido, modalidad temática. Fue identificado que el profesional de salud asume un rol normativo en este proceso, apoyándose en conocimientos científicos. Dentro del proceso de amamantar, la familia ocupa el primer lugar de referencia para las mujeres, transmitiendo creencias, hábitos y conductas. Se cree que la valorización del contexto familiar por el profesional de salud, al desarrollar acciones e interacciones durante la lactancia, se

  20. Neural and Fuzzy Adaptive Control of Induction Motor Drives

    International Nuclear Information System (INIS)

    Bensalem, Y.; Sbita, L.; Abdelkrim, M. N.

    2008-01-01

    This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller

  1. Uranium reference materials

    International Nuclear Information System (INIS)

    Donivan, S.; Chessmore, R.

    1987-07-01

    The Technical Measurements Center has prepared uranium mill tailings reference materials for use by remedial action contractors and cognizant federal and state agencies. Four materials were prepared with varying concentrations of radionuclides, using three tailings materials and a river-bottom soil diluent. All materials were ground, dried, and blended thoroughly to ensure homogeneity. The analyses on which the recommended values for nuclides in the reference materials are based were performed, using independent methods, by the UNC Geotech (UNC) Chemistry Laboratory, Grand Junction, Colorado, and by C.W. Sill (Sill), Idaho National Engineering Laboratory, Idaho Falls, Idaho. Several statistical tests were performed on the analytical data to characterize the reference materials. Results of these tests reveal that the four reference materials are homogeneous and that no large systematic bias exists between the analytical methods used by Sill and those used by TMC. The average values for radionuclides of the two data sets, representing an unbiased estimate, were used as the recommended values for concentrations of nuclides in the reference materials. The recommended concentrations of radionuclides in the four reference materials are provided. Use of these reference materials will aid in providing uniform standardization among measurements made by remedial action contractors. 11 refs., 9 tabs

  2. Neural Architectures for Control

    Science.gov (United States)

    Peterson, James K.

    1991-01-01

    The cerebellar model articulated controller (CMAC) neural architectures are shown to be viable for the purposes of real-time learning and control. Software tools for the exploration of CMAC performance are developed for three hardware platforms, the MacIntosh, the IBM PC, and the SUN workstation. All algorithm development was done using the C programming language. These software tools were then used to implement an adaptive critic neuro-control design that learns in real-time how to back up a trailer truck. The truck backer-upper experiment is a standard performance measure in the neural network literature, but previously the training of the controllers was done off-line. With the CMAC neural architectures, it was possible to train the neuro-controllers on-line in real-time on a MS-DOS PC 386. CMAC neural architectures are also used in conjunction with a hierarchical planning approach to find collision-free paths over 2-D analog valued obstacle fields. The method constructs a coarse resolution version of the original problem and then finds the corresponding coarse optimal path using multipass dynamic programming. CMAC artificial neural architectures are used to estimate the analog transition costs that dynamic programming requires. The CMAC architectures are trained in real-time for each obstacle field presented. The coarse optimal path is then used as a baseline for the construction of a fine scale optimal path through the original obstacle array. These results are a very good indication of the potential power of the neural architectures in control design. In order to reach as wide an audience as possible, we have run a seminar on neuro-control that has met once per week since 20 May 1991. This seminar has thoroughly discussed the CMAC architecture, relevant portions of classical control, back propagation through time, and adaptive critic designs.

  3. Neural Adaptation Effects in Conceptual Processing

    Directory of Open Access Journals (Sweden)

    Barbara F. M. Marino

    2015-07-01

    Full Text Available We investigated the conceptual processing of nouns referring to objects characterized by a highly typical color and orientation. We used a go/no-go task in which we asked participants to categorize each noun as referring or not to natural entities (e.g., animals after a selective adaptation of color-edge neurons in the posterior LV4 region of the visual cortex was induced by means of a McCollough effect procedure. This manipulation affected categorization: the green-vertical adaptation led to slower responses than the green-horizontal adaptation, regardless of the specific color and orientation of the to-be-categorized noun. This result suggests that the conceptual processing of natural entities may entail the activation of modality-specific neural channels with weights proportional to the reliability of the signals produced by these channels during actual perception. This finding is discussed with reference to the debate about the grounded cognition view.

  4. STL pocket reference

    CERN Document Server

    Lischner, Ray

    2003-01-01

    The STL Pocket Reference describes the functions, classes, and templates in that part of the C++ standard library often referred to as the Standard Template Library (STL). The STL encompasses containers, iterators, algorithms, and function objects, which collectively represent one of the most important and widely used subsets of standard library functionality. The C++ standard library, even the subset known as the STL, is vast. It's next to impossible to work with the STL without some sort of reference at your side to remind you of template parameters, function invocations, return types--ind

  5. Handbook of reference electrodes

    CERN Document Server

    Inzelt, György; Scholz, Fritz

    2013-01-01

    Reference Electrodes are a crucial part of any electrochemical system, yet an up-to-date and comprehensive handbook is long overdue. Here, an experienced team of electrochemists provides an in-depth source of information and data for the proper choice and construction of reference electrodes. This includes all kinds of applications such as aqueous and non-aqueous solutions, ionic liquids, glass melts, solid electrolyte systems, and membrane electrodes. Advanced technologies such as miniaturized, conducting-polymer-based, screen-printed or disposable reference electrodes are also covered. Essen

  6. Regular Expression Pocket Reference

    CERN Document Server

    Stubblebine, Tony

    2007-01-01

    This handy little book offers programmers a complete overview of the syntax and semantics of regular expressions that are at the heart of every text-processing application. Ideal as a quick reference, Regular Expression Pocket Reference covers the regular expression APIs for Perl 5.8, Ruby (including some upcoming 1.9 features), Java, PHP, .NET and C#, Python, vi, JavaScript, and the PCRE regular expression libraries. This concise and easy-to-use reference puts a very powerful tool for manipulating text and data right at your fingertips. Composed of a mixture of symbols and text, regular exp

  7. Neptunium: a bibliographic reference

    International Nuclear Information System (INIS)

    Mosley, R.E.

    1979-06-01

    A comprehensive bibliograhy of the literature on the element neptunium published prior to January 1976 is presented. A short abstract is given for each listed reference, with a few exceptions. The references are divided into sections categorized as General, Man-Made Sources (Reactors), Man-Made Sources (Fuel Reprocessing), Chemistry (Solubility), Chemistry (Compounds), Chemistry (Isotopes), Analyses (Instrumental), Analyses (Chemical), Chemical (Animal), Biological (Effects), Biological (Animal-Metabolism-Retention), Biological (Air Movement), Biological (Human Inhalation), Measurement, and Dosimetry. The bibliography contains author and keyword indexes and was compiled to serve as a quick reference source for neptunium-related work. 184 citations

  8. CSS Pocket Reference

    CERN Document Server

    Meyer, Eric

    2011-01-01

    When you're working with CSS and need a quick answer, CSS Pocket Reference delivers. This handy, concise book provides all of the essential information you need to implement CSS on the fly. Ideal for intermediate to advanced web designers and developers, the 4th edition is revised and updated for CSS3, the latest version of the Cascading Style Sheet specification. Along with a complete alphabetical reference to CSS3 selectors and properties, you'll also find a short introduction to the key concepts of CSS. Based on Cascading Style Sheets: The Definitive Guide, this reference is an easy-to-us

  9. Biomedical Engineering Desk Reference

    CERN Document Server

    Ratner, Buddy D; Schoen, Frederick J; Lemons, Jack E; Dyro, Joseph; Martinsen, Orjan G; Kyle, Richard; Preim, Bernhard; Bartz, Dirk; Grimnes, Sverre; Vallero, Daniel; Semmlow, John; Murray, W Bosseau; Perez, Reinaldo; Bankman, Isaac; Dunn, Stanley; Ikada, Yoshito; Moghe, Prabhas V; Constantinides, Alkis

    2009-01-01

    A one-stop Desk Reference, for Biomedical Engineers involved in the ever expanding and very fast moving area; this is a book that will not gather dust on the shelf. It brings together the essential professional reference content from leading international contributors in the biomedical engineering field. Material covers a broad range of topics including: Biomechanics and Biomaterials; Tissue Engineering; and Biosignal Processing* A hard-working desk reference providing all the essential material needed by biomedical and clinical engineers on a day-to-day basis * Fundamentals, key techniques,

  10. LINQ Pocket Reference

    CERN Document Server

    Albahari, Joseph

    2008-01-01

    Ready to take advantage of LINQ with C# 3.0? This guide has the detail you need to grasp Microsoft's new querying technology, and concise explanations to help you learn it quickly. And once you begin to apply LINQ, the book serves as an on-the-job reference when you need immediate reminders. All the examples in the LINQ Pocket Reference are preloaded into LINQPad, the highly praised utility that lets you work with LINQ interactively. Created by the authors and free to download, LINQPad will not only help you learn LINQ, it will have you thinking in LINQ. This reference explains: LINQ's ke

  11. R quick syntax reference

    CERN Document Server

    Tollefson, Margot

    2014-01-01

    The R Quick Syntax Reference is a handy reference book detailing the intricacies of the R language. Not only is R a free, open-source tool, R is powerful, flexible, and has state of the art statistical techniques available. With the many details which must be correct when using any language, however, the R Quick Syntax Reference makes using R easier.Starting with the basic structure of R, the book takes you on a journey through the terminology used in R and the syntax required to make R work. You will find looking up the correct form for an expression quick and easy. With a copy of the R Quick

  12. Phylogenetic convolutional neural networks in metagenomics.

    Science.gov (United States)

    Fioravanti, Diego; Giarratano, Ylenia; Maggio, Valerio; Agostinelli, Claudio; Chierici, Marco; Jurman, Giuseppe; Furlanello, Cesare

    2018-03-08

    Convolutional Neural Networks can be effectively used only when data are endowed with an intrinsic concept of neighbourhood in the input space, as is the case of pixels in images. We introduce here Ph-CNN, a novel deep learning architecture for the classification of metagenomics data based on the Convolutional Neural Networks, with the patristic distance defined on the phylogenetic tree being used as the proximity measure. The patristic distance between variables is used together with a sparsified version of MultiDimensional Scaling to embed the phylogenetic tree in a Euclidean space. Ph-CNN is tested with a domain adaptation approach on synthetic data and on a metagenomics collection of gut microbiota of 38 healthy subjects and 222 Inflammatory Bowel Disease patients, divided in 6 subclasses. Classification performance is promising when compared to classical algorithms like Support Vector Machines and Random Forest and a baseline fully connected neural network, e.g. the Multi-Layer Perceptron. Ph-CNN represents a novel deep learning approach for the classification of metagenomics data. Operatively, the algorithm has been implemented as a custom Keras layer taking care of passing to the following convolutional layer not only the data but also the ranked list of neighbourhood of each sample, thus mimicking the case of image data, transparently to the user.

  13. Sacred or Neural?

    DEFF Research Database (Denmark)

    Runehov, Anne Leona Cesarine

    Are religious spiritual experiences merely the product of the human nervous system? Anne L.C. Runehov investigates the potential of contemporary neuroscience to explain religious experiences. Following the footsteps of Michael Persinger, Andrew Newberg and Eugene d'Aquili she defines...... the terminological bounderies of "religious experiences" and explores the relevant criteria for the proper evaluation of scientific research, with a particular focus on the validity of reductionist models. Runehov's theis is that the perspectives looked at do not necessarily exclude each other but can be merged....... The question "sacred or neural?" becomes a statement "sacred and neural". The synergies thus produced provide manifold opportunities for interdisciplinary dialogue and research....

  14. Deconvolution using a neural network

    Energy Technology Data Exchange (ETDEWEB)

    Lehman, S.K.

    1990-11-15

    Viewing one dimensional deconvolution as a matrix inversion problem, we compare a neural network backpropagation matrix inverse with LMS, and pseudo-inverse. This is a largely an exercise in understanding how our neural network code works. 1 ref.

  15. Introduction to Artificial Neural Networks

    DEFF Research Database (Denmark)

    Larsen, Jan

    1999-01-01

    The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks.......The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks....

  16. First observations of tropospheric δD data observed by ground- and space-based remote sensing and surface in-situ measurement techniques at MUSICA's principle reference station (Izaña Observatory, Spain)

    Science.gov (United States)

    González, Yenny; Schneider, Matthias; Christner, Emanuel; Rodríguez, Omaira E.; Sepúlveda, Eliezer; Dyroff, Christoph; Wiegele, Andreas

    2013-04-01

    The main goal of the project MUSICA (Multiplatform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) is the generation of a quasi global tropospheric water vapor isototopologue dataset of a good and well-documented quality. Therefore, new ground- and space-based remote sensing observations (NDACC-FTIR and IASI/METOP) are combined with in-situ measurements. This work presents the first comparison between in-situ and remote sensing observations made at the Izaña Atmospheric Research Centre (Tenerife, Canary Islands, Spain). The in-situ measurements are made by a Picarro L2120-i water vapor isotopologue analyzer. At Izaña the in-situ data are affected by local small-scale mixing processes: during daylight, the thermally buoyant upslope flow prompts the mixing between the Marine Boundary Layer (MBL) and the low Free Troposphere (FT). However, the remote sensors detect δD values averaged over altitudes that are more representative for the free troposphere. This difference has to be considered for the comparison. In general, a good agreement between the MUSICA remote sensing and the in situ H2O-versus-δD plots is found, which demonstrates that the MUSICA δD remote sensing products add scientifically valuable information to the H2O data.

  17. The application of artificial neural networks to TLD dose algorithm

    International Nuclear Information System (INIS)

    Moscovitch, M.

    1997-01-01

    We review the application of feed forward neural networks to multi element thermoluminescence dosimetry (TLD) dose algorithm development. A Neural Network is an information processing method inspired by the biological nervous system. A dose algorithm based on a neural network is a fundamentally different approach from conventional algorithms, as it has the capability to learn from its own experience. The neural network algorithm is shown the expected dose values (output) associated with a given response of a multi-element dosimeter (input) many times.The algorithm, being trained that way, eventually is able to produce its own unique solution to similar (but not exactly the same) dose calculation problems. For personnel dosimetry, the output consists of the desired dose components: deep dose, shallow dose, and eye dose. The input consists of the TL data obtained from the readout of a multi-element dosimeter. For this application, a neural network architecture was developed based on the concept of functional links network (FLN). The FLN concept allowed an increase in the dimensionality of the input space and construction of a neural network without any hidden layers. This simplifies the problem and results in a relatively simple and reliable dose calculation algorithm. Overall, the neural network dose algorithm approach has been shown to significantly improve the precision and accuracy of dose calculations. (authors)

  18. Optimal primitive reference frames

    International Nuclear Information System (INIS)

    Jennings, David

    2011-01-01

    We consider the smallest possible directional reference frames allowed and determine the best one can ever do in preserving quantum information in various scenarios. We find that for the preservation of a single spin state, two orthogonal spins are optimal primitive reference frames; and in a product state, they do approximately 22% as well as an infinite-sized classical frame. By adding a small amount of entanglement to the reference frame, this can be raised to 2(2/3) 5 =26%. Under the different criterion of entanglement preservation, a very similar optimal reference frame is found; however, this time it is for spins aligned at an optimal angle of 87 deg. In this case 24% of the negativity is preserved. The classical limit is considered numerically, and indicates under the criterion of entanglement preservation, that 90 deg. is selected out nonmonotonically, with a peak optimal angle of 96.5 deg. for L=3 spins.

  19. Reference Climatological Stations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Reference Climatological Stations (RCS) network represents the first effort by NOAA to create and maintain a nationwide network of stations located only in areas...

  20. Toxicity Reference Database

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Toxicity Reference Database (ToxRefDB) contains approximately 30 years and $2 billion worth of animal studies. ToxRefDB allows scientists and the interested...

  1. Python essential reference

    CERN Document Server

    Beazley, David M

    2009-01-01

    Python Essential Reference is the definitive reference guide to the Python programming language — the one authoritative handbook that reliably untangles and explains both the core Python language and the most essential parts of the Python library. Designed for the professional programmer, the book is concise, to the point, and highly accessible. It also includes detailed information on the Python library and many advanced subjects that is not available in either the official Python documentation or any other single reference source. Thoroughly updated to reflect the significant new programming language features and library modules that have been introduced in Python 2.6 and Python 3, the fourth edition of Python Essential Reference is the definitive guide for programmers who need to modernize existing Python code or who are planning an eventual migration to Python 3. Programmers starting a new Python project will find detailed coverage of contemporary Python programming idioms.

  2. Collaborative networks: Reference modeling

    NARCIS (Netherlands)

    Camarinha-Matos, L.M.; Afsarmanesh, H.

    2008-01-01

    Collaborative Networks: Reference Modeling works to establish a theoretical foundation for Collaborative Networks. Particular emphasis is put on modeling multiple facets of collaborative networks and establishing a comprehensive modeling framework that captures and structures diverse perspectives of

  3. Ozone Standard Reference Photometer

    Data.gov (United States)

    Federal Laboratory Consortium — The Standard Reference Photometer (SRP) Program began in the early 1980s as collaboration between NIST and the U.S. Environmental Protection Agency (EPA) to design,...

  4. The Challenges of Neural Mind-reading Paradigms

    Directory of Open Access Journals (Sweden)

    Oscar eVilarroya

    2013-06-01

    Full Text Available Neural mind-reading studies, based on multivariate pattern analysis (MVPA methods, are providing exciting new studies. Some of the results obtained with these paradigms have raised high expectations, such as the possibility of creating brain reading devices. However, such hopes are based on the assumptions that: a the BOLD signal is a marker of neural activity; b the BOLD pattern identified by a MVPA is a neurally sound pattern; c the MVPA’s feature space is a good mapping of the neural representation of a stimulus, and d the pattern identified by a MVPA corresponds to a representation. I examine here the challenges that still have to be met before fully accepting such assumptions.

  5. The challenges of neural mind-reading paradigms.

    Science.gov (United States)

    Vilarroya, Oscar

    2013-01-01

    Neural mind-reading studies, based on multivariate pattern analysis (MVPA) methods, are providing exciting new studies. Some of the results obtained with these paradigms have raised high expectations, such as the possibility of creating brain reading devices. However, such hopes are based on the assumptions that: (a) the BOLD signal is a marker of neural activity; (b) the BOLD pattern identified by a MVPA is a neurally sound pattern; (c) the MVPA's feature space is a good mapping of the neural representation of a stimulus, and (d) the pattern identified by a MVPA corresponds to a representation. I examine here the challenges that still have to be met before fully accepting such assumptions.

  6. Comparability of reference values

    International Nuclear Information System (INIS)

    Rossbach, M.; Stoeppler, M.

    1993-01-01

    Harmonization of certified values in Reference Materials (RMs) can be carried out by applying nuclear analytical techniques to RMs of various matrix types and concentration levels. Although RMs generally should not be used as primary standards the cross evaluation of concentrations in RMs leads to better compatibility of reference values and thus to a greater agreement between analytical results from different laboratories using these RMs for instrument calibration and quality assurance. (orig.)

  7. Electronics engineer's reference book

    CERN Document Server

    Turner, L W

    1976-01-01

    Electronics Engineer's Reference Book, 4th Edition is a reference book for electronic engineers that reviews the knowledge and techniques in electronics engineering and covers topics ranging from basics to materials and components, devices, circuits, measurements, and applications. This edition is comprised of 27 chapters; the first of which presents general information on electronics engineering, including terminology, mathematical equations, mathematical signs and symbols, and Greek alphabet and symbols. Attention then turns to the history of electronics; electromagnetic and nuclear radiatio

  8. 2002 reference document

    International Nuclear Information System (INIS)

    2002-01-01

    This 2002 reference document of the group Areva, provides information on the society. Organized in seven chapters, it presents the persons responsible for the reference document and for auditing the financial statements, information pertaining to the transaction, general information on the company and share capital, information on company operation, changes and future prospects, assets, financial position, financial performance, information on company management and executive board and supervisory board, recent developments and future prospects. (A.L.B.)

  9. Development of a neural net paradigm that predicts simulator sickness

    Energy Technology Data Exchange (ETDEWEB)

    Allgood, G.O.

    1993-03-01

    A disease exists that affects pilots and aircrew members who use Navy Operational Flight Training Systems. This malady, commonly referred to as simulator sickness and whose symptomatology closely aligns with that of motion sickness, can compromise the use of these systems because of a reduced utilization factor, negative transfer of training, and reduction in combat readiness. A report is submitted that develops an artificial neural network (ANN) and behavioral model that predicts the onset and level of simulator sickness in the pilots and aircrews who sue these systems. It is proposed that the paradigm could be implemented in real time as a biofeedback monitor to reduce the risk to users of these systems. The model captures the neurophysiological impact of use (human-machine interaction) by developing a structure that maps the associative and nonassociative behavioral patterns (learned expectations) and vestibular (otolith and semicircular canals of the inner ear) and tactile interaction, derived from system acceleration profiles, onto an abstract space that predicts simulator sickness for a given training flight.

  10. Are all spatial reference frames egocentric? Reinterpreting evidence for allocentric, object-centered, or world-centered reference frames

    Directory of Open Access Journals (Sweden)

    Flavia eFilimon

    2015-12-01

    Full Text Available The use and neural representation of egocentric spatial reference frames is well documented. In contrast, whether the brain represents spatial relationships between objects in allocentric, object-centered, or world-centered coordinates is debated. Here, I review behavioral, neuropsychological, neurophysiological (neuronal recording, and neuroimaging evidence for and against allocentric, object-centered, or world-centered spatial reference frames. Based on theoretical considerations, simulations, and empirical findings from spatial navigation, spatial judgments, and goal-directed movements, I suggest that all spatial representations may in fact be dependent on egocentric reference frames.

  11. Artificial Neural Networks for SCADA Data based Load Reconstruction (poster)

    NARCIS (Netherlands)

    Hofemann, C.; Van Bussel, G.J.W.; Veldkamp, H.

    2011-01-01

    If at least one reference wind turbine is available, which provides sufficient information about the wind turbine loads, the loads acting on the neighbouring wind turbines can be predicted via an artificial neural network (ANN). This research explores the possibilities to apply such a network not

  12. Neural Network Ensembles

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Salamon, Peter

    1990-01-01

    We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....

  13. Neural correlates of consciousness

    African Journals Online (AJOL)

    neural cells.1 Under this approach, consciousness is believed to be a product of the ... possible only when the 40 Hz electrical hum is sustained among the brain circuits, ... expect the brain stem ascending reticular activating system. (ARAS) and the ... related synchrony of cortical neurons.11 Indeed, stimulation of brainstem ...

  14. Neural Networks and Micromechanics

    Science.gov (United States)

    Kussul, Ernst; Baidyk, Tatiana; Wunsch, Donald C.

    The title of the book, "Neural Networks and Micromechanics," seems artificial. However, the scientific and technological developments in recent decades demonstrate a very close connection between the two different areas of neural networks and micromechanics. The purpose of this book is to demonstrate this connection. Some artificial intelligence (AI) methods, including neural networks, could be used to improve automation system performance in manufacturing processes. However, the implementation of these AI methods within industry is rather slow because of the high cost of conducting experiments using conventional manufacturing and AI systems. To lower the cost, we have developed special micromechanical equipment that is similar to conventional mechanical equipment but of much smaller size and therefore of lower cost. This equipment could be used to evaluate different AI methods in an easy and inexpensive way. The proved methods could be transferred to industry through appropriate scaling. In this book, we describe the prototypes of low cost microequipment for manufacturing processes and the implementation of some AI methods to increase precision, such as computer vision systems based on neural networks for microdevice assembly and genetic algorithms for microequipment characterization and the increase of microequipment precision.

  15. Introduction to neural networks

    International Nuclear Information System (INIS)

    Pavlopoulos, P.

    1996-01-01

    This lecture is a presentation of today's research in neural computation. Neural computation is inspired by knowledge from neuro-science. It draws its methods in large degree from statistical physics and its potential applications lie mainly in computer science and engineering. Neural networks models are algorithms for cognitive tasks, such as learning and optimization, which are based on concepts derived from research into the nature of the brain. The lecture first gives an historical presentation of neural networks development and interest in performing complex tasks. Then, an exhaustive overview of data management and networks computation methods is given: the supervised learning and the associative memory problem, the capacity of networks, the Perceptron networks, the functional link networks, the Madaline (Multiple Adalines) networks, the back-propagation networks, the reduced coulomb energy (RCE) networks, the unsupervised learning and the competitive learning and vector quantization. An example of application in high energy physics is given with the trigger systems and track recognition system (track parametrization, event selection and particle identification) developed for the CPLEAR experiment detectors from the LEAR at CERN. (J.S.). 56 refs., 20 figs., 1 tab., 1 appendix

  16. Neural systems for control

    National Research Council Canada - National Science Library

    Omidvar, Omid; Elliott, David L

    1997-01-01

    ... is reprinted with permission from A. Barto, "Reinforcement Learning," Handbook of Brain Theory and Neural Networks, M.A. Arbib, ed.. The MIT Press, Cambridge, MA, pp. 804-809, 1995. Chapter 4, Figures 4-5 and 7-9 and Tables 2-5, are reprinted with permission, from S. Cho, "Map Formation in Proprioceptive Cortex," International Jour...

  17. Neural underpinnings of music

    DEFF Research Database (Denmark)

    Vuust, Peter; Gebauer, Line K; Witek, Maria A G

    2014-01-01

    . According to this theory, perception and learning is manifested through the brain’s Bayesian minimization of the error between the input to the brain and the brain’s prior expectations. Fourth, empirical studies of neural and behavioral effects of syncopation, polyrhythm and groove will be reported, and we...

  18. Determining the confidence levels of sensor outputs using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Broten, G S; Wood, H C [Saskatchewan Univ., Saskatoon, SK (Canada). Dept. of Electrical Engineering

    1996-12-31

    This paper describes an approach for determining the confidence level of a sensor output using multi-sensor arrays, sensor fusion and artificial neural networks. The authors have shown in previous work that sensor fusion and artificial neural networks can be used to learn the relationships between the outputs of an array of simulated partially selective sensors and the individual analyte concentrations in a mixture of analyses. Other researchers have shown that an array of partially selective sensors can be used to determine the individual gas concentrations in a gaseous mixture. The research reported in this paper shows that it is possible to extract confidence level information from an array of partially selective sensors using artificial neural networks. The confidence level of a sensor output is defined as a numeric value, ranging from 0% to 100%, that indicates the confidence associated with a output of a given sensor. A three layer back-propagation neural network was trained on a subset of the sensor confidence level space, and was tested for its ability to generalize, where the confidence level space is defined as all possible deviations from the correct sensor output. A learning rate of 0.1 was used and no momentum terms were used in the neural network. This research has shown that an artificial neural network can accurately estimate the confidence level of individual sensors in an array of partially selective sensors. This research has also shown that the neural network`s ability to determine the confidence level is influenced by the complexity of the sensor`s response and that the neural network is able to estimate the confidence levels even if more than one sensor is in error. The fundamentals behind this research could be applied to other configurations besides arrays of partially selective sensors, such as an array of sensors separated spatially. An example of such a configuration could be an array of temperature sensors in a tank that is not in

  19. On the neural mechanisms subserving consciousness and attention

    Directory of Open Access Journals (Sweden)

    Catherine eTallon-Baudry

    2012-01-01

    Full Text Available Consciousness, as described in the experimental literature, is a multi-faceted phenomenon, that impinges on other well-studied concepts such as attention and control. Do consciousness and attention refer to different aspects of the same core phenomenon, or do they correspond to distinct functions? One possibility to address this question is to examine the neural mechanisms underlying consciousness and attention. If consciousness and attention pertain to the same concept, they should rely on shared neural mechanisms. Conversely, if their underlying mechanisms are distinct, then consciousness and attention should be considered as distinct entities. This paper therefore reviews neurophysiological facts arguing in favor or against a tight relationship between consciousness and attention. Three neural mechanisms that have been associated with both attention and consciousness are examined (neural amplification, involvement of the fronto-parietal network, and oscillatory synchrony, to conclude that the commonalities between attention and consciousness at the neural level may have been overestimated. Last but not least, experiments in which both attention and consciousness were probed at the neural level point toward a dissociation between the two concepts. It therefore appears from this review that consciousness and attention rely on distinct neural properties, although they can interact at the behavioral level. It is proposed that a "cumulative influence model", in which attention and consciousness correspond to distinct neural mechanisms feeding a single decisional process leading to behavior, fits best with available neural and behavioral data. In this view, consciousness should not be considered as a top-level executive function but should rather be defined by its experiential properties.

  20. High-Dimensional Function Approximation With Neural Networks for Large Volumes of Data.

    Science.gov (United States)

    Andras, Peter

    2018-02-01

    Approximation of high-dimensional functions is a challenge for neural networks due to the curse of dimensionality. Often the data for which the approximated function is defined resides on a low-dimensional manifold and in principle the approximation of the function over this manifold should improve the approximation performance. It has been show that projecting the data manifold into a lower dimensional space, followed by the neural network approximation of the function over this space, provides a more precise approximation of the function than the approximation of the function with neural networks in the original data space. However, if the data volume is very large, the projection into the low-dimensional space has to be based on a limited sample of the data. Here, we investigate the nature of the approximation error of neural networks trained over the projection space. We show that such neural networks should have better approximation performance than neural networks trained on high-dimensional data even if the projection is based on a relatively sparse sample of the data manifold. We also find that it is preferable to use a uniformly distributed sparse sample of the data for the purpose of the generation of the low-dimensional projection. We illustrate these results considering the practical neural network approximation of a set of functions defined on high-dimensional data including real world data as well.

  1. Visual properties and memorising scenes: Effects of image-space sparseness and uniformity.

    Science.gov (United States)

    Lukavský, Jiří; Děchtěrenko, Filip

    2017-10-01

    Previous studies have demonstrated that humans have a remarkable capacity to memorise a large number of scenes. The research on memorability has shown that memory performance can be predicted by the content of an image. We explored how remembering an image is affected by the image properties within the context of the reference set, including the extent to which it is different from its neighbours (image-space sparseness) and if it belongs to the same category as its neighbours (uniformity). We used a reference set of 2,048 scenes (64 categories), evaluated pairwise scene similarity using deep features from a pretrained convolutional neural network (CNN), and calculated the image-space sparseness and uniformity for each image. We ran three memory experiments, varying the memory workload with experiment length and colour/greyscale presentation. We measured the sensitivity and criterion value changes as a function of image-space sparseness and uniformity. Across all three experiments, we found separate effects of 1) sparseness on memory sensitivity, and 2) uniformity on the recognition criterion. People better remembered (and correctly rejected) images that were more separated from others. People tended to make more false alarms and fewer miss errors in images from categorically uniform portions of the image-space. We propose that both image-space properties affect human decisions when recognising images. Additionally, we found that colour presentation did not yield better memory performance over grayscale images.

  2. A Formal Method for Verification and Validation of Neural Network High Assurance Systems, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Our proposed innovation is to develop neural network (NN) rule extraction technology to a level where it can be incorporated into a software tool, we are calling...

  3. Reference Japanese man

    International Nuclear Information System (INIS)

    Tanaka, Giichiro

    1985-01-01

    To make real and accurate dose assessment method so far, it is necessitated to provide ''Reference Japanese Man'' based on anotomical, physiological and biochemical data of Japanese people instead of the Reference Man presented in ICRP Publications 23 and 30. This review describes present status of researched for the purpose of establishing of Reference Japanese Man. The Reference Japanese Man is defined as a male or female adult who lives in Japan with a Japanese life-style and food custom. His stature and body weight, and the other data was decided as mean values of male or female people of Japan. As for food custom, Japanese people take significantly smaller amount of meat and milk products than Western people, while larger intake amount of cereals and marine products such as fish or seaweeds. Weight of organs is a principal factor for internal dose assessment and mean values for living Japanese adult has been investigated and the value employable for dose assessment for organs and tissues are shown. To employ these values of Reference Japanese Man, it should be taken into account of age. Metabolic parameters should also be considered. Iodine metabolism in Japanese is quite different from that of Western people. The above-mentioned data are now tentatively employing in modification of table of MIRD method and others. (Takagi, S.)

  4. Implementing Signature Neural Networks with Spiking Neurons.

    Science.gov (United States)

    Carrillo-Medina, José Luis; Latorre, Roberto

    2016-01-01

    Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm-i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data-to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence

  5. Large-scale multielectrode recording and stimulation of neural activity

    International Nuclear Information System (INIS)

    Sher, A.; Chichilnisky, E.J.; Dabrowski, W.; Grillo, A.A.; Grivich, M.; Gunning, D.; Hottowy, P.; Kachiguine, S.; Litke, A.M.; Mathieson, K.; Petrusca, D.

    2007-01-01

    Large circuits of neurons are employed by the brain to encode and process information. How this encoding and processing is carried out is one of the central questions in neuroscience. Since individual neurons communicate with each other through electrical signals (action potentials), the recording of neural activity with arrays of extracellular electrodes is uniquely suited for the investigation of this question. Such recordings provide the combination of the best spatial (individual neurons) and temporal (individual action-potentials) resolutions compared to other large-scale imaging methods. Electrical stimulation of neural activity in turn has two very important applications: it enhances our understanding of neural circuits by allowing active interactions with them, and it is a basis for a large variety of neural prosthetic devices. Until recently, the state-of-the-art in neural activity recording systems consisted of several dozen electrodes with inter-electrode spacing ranging from tens to hundreds of microns. Using silicon microstrip detector expertise acquired in the field of high-energy physics, we created a unique neural activity readout and stimulation framework that consists of high-density electrode arrays, multi-channel custom-designed integrated circuits, a data acquisition system, and data-processing software. Using this framework we developed a number of neural readout and stimulation systems: (1) a 512-electrode system for recording the simultaneous activity of as many as hundreds of neurons, (2) a 61-electrode system for electrical stimulation and readout of neural activity in retinas and brain-tissue slices, and (3) a system with telemetry capabilities for recording neural activity in the intact brain of awake, naturally behaving animals. We will report on these systems, their various applications to the field of neurobiology, and novel scientific results obtained with some of them. We will also outline future directions

  6. An industrial robot singular trajectories planning based on graphs and neural networks

    Science.gov (United States)

    Łęgowski, Adrian; Niezabitowski, Michał

    2016-06-01

    Singular trajectories are rarely used because of issues during realization. A method of planning trajectories for given set of points in task space with use of graphs and neural networks is presented. In every desired point the inverse kinematics problem is solved in order to derive all possible solutions. A graph of solutions is made. The shortest path is determined to define required nodes in joint space. Neural networks are used to define the path between these nodes.

  7. Bioprinting for Neural Tissue Engineering.

    Science.gov (United States)

    Knowlton, Stephanie; Anand, Shivesh; Shah, Twisha; Tasoglu, Savas

    2018-01-01

    Bioprinting is a method by which a cell-encapsulating bioink is patterned to create complex tissue architectures. Given the potential impact of this technology on neural research, we review the current state-of-the-art approaches for bioprinting neural tissues. While 2D neural cultures are ubiquitous for studying neural cells, 3D cultures can more accurately replicate the microenvironment of neural tissues. By bioprinting neuronal constructs, one can precisely control the microenvironment by specifically formulating the bioink for neural tissues, and by spatially patterning cell types and scaffold properties in three dimensions. We review a range of bioprinted neural tissue models and discuss how they can be used to observe how neurons behave, understand disease processes, develop new therapies and, ultimately, design replacement tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Reference costs of electricity

    International Nuclear Information System (INIS)

    Terraz, N.

    1997-01-01

    The calculation of electric power production reference costs is used in France, even in the present case of over-capacity, for comparing the relative interest of the various means of power generation (nuclear plants, coal plants, hydroelectricity, gas combined cycles, etc.) and as an aid for future investment decisions. Reference costs show a sharp decrease between 1993 and 1997 due to advancements in nuclear plant operating ability and fossil fuel price decrease. Actuarial rates, plant service life, fuel costs and exchange rates are important parameters. The various costs from the research stage to the waste processing stages are discussed and the reference costs of the various power generation systems are presented and compared together with their competitiveness; the future of wind energy and cogeneration and the prospective of the renewal of nuclear plants at the 2010 horizon are also addressed

  9. A reactive, scalable, and transferable model for molecular energies from a neural network approach based on local information

    Science.gov (United States)

    Unke, Oliver T.; Meuwly, Markus

    2018-06-01

    Despite the ever-increasing computer power, accurate ab initio calculations for large systems (thousands to millions of atoms) remain infeasible. Instead, approximate empirical energy functions are used. Most current approaches are either transferable between different chemical systems, but not particularly accurate, or they are fine-tuned to a specific application. In this work, a data-driven method to construct a potential energy surface based on neural networks is presented. Since the total energy is decomposed into local atomic contributions, the evaluation is easily parallelizable and scales linearly with system size. With prediction errors below 0.5 kcal mol-1 for both unknown molecules and configurations, the method is accurate across chemical and configurational space, which is demonstrated by applying it to datasets from nonreactive and reactive molecular dynamics simulations and a diverse database of equilibrium structures. The possibility to use small molecules as reference data to predict larger structures is also explored. Since the descriptor only uses local information, high-level ab initio methods, which are computationally too expensive for large molecules, become feasible for generating the necessary reference data used to train the neural network.

  10. Tuning Recurrent Neural Networks for Recognizing Handwritten Arabic Words

    KAUST Repository

    Qaralleh, Esam; Abandah, Gheith; Jamour, Fuad Tarek

    2013-01-01

    and sizes of the hidden layers. Large sizes are slow and small sizes are generally not accurate. Tuning the neural network size is a hard task because the design space is often large and training is often a long process. We use design of experiments

  11. Successful neural network projects at the Idaho National Engineering Laboratory

    International Nuclear Information System (INIS)

    Cordes, G.A.

    1991-01-01

    This paper presents recent and current projects at the Idaho National Engineering Laboratory (INEL) that research and apply neural network technology. The projects are summarized in the paper and their direct application to space reactor power and propulsion systems activities is discussed. 9 refs., 10 figs., 3 tabs

  12. Electrical engineer's reference book

    CERN Document Server

    Jones, G R

    2013-01-01

    A long established reference book: radical revision for the fifteenth edition includes complete rearrangement to take in chapters on new topics and regroup the subjects covered for easy access to information.The Electrical Engineer's Reference Book, first published in 1945, maintains its original aims: to reflect the state of the art in electrical science and technology and cater for the needs of practising engineers. Most chapters have been revised and many augmented so as to deal properly with both fundamental developments and new technology and applications that have come to the fore since

  13. Python pocket reference

    CERN Document Server

    Lutz, Mark

    2010-01-01

    This is the book to reach for when you're coding on the fly and need an answer now. It's an easy-to-use reference to the core language, with descriptions of commonly used modules and toolkits, and a guide to recent changes, new features, and upgraded built-ins -- all updated to cover Python 3.X as well as version 2.6. You'll also quickly find exactly what you need with the handy index. Written by Mark Lutz -- widely recognized as the world's leading Python trainer -- Python Pocket Reference, Fourth Edition, is the perfect companion to O'Reilly's classic Python tutorials, also written by Mark

  14. The Reference Return Ratio

    DEFF Research Database (Denmark)

    Nicolaisen, Jeppe; Faber Frandsen, Tove

    2008-01-01

    The paper introduces a new journal impact measure called The Reference Return Ratio (3R). Unlike the traditional Journal Impact Factor (JIF), which is based on calculations of publications and citations, the new measure is based on calculations of bibliographic investments (references) and returns...... (citations). A comparative study of the two measures shows a strong relationship between the 3R and the JIF. Yet, the 3R appears to correct for citation habits, citation dynamics, and composition of document types - problems that typically are raised against the JIF. In addition, contrary to traditional...

  15. Perl Pocket Reference

    CERN Document Server

    Vromans, Johan

    2011-01-01

    If you have a Perl programming question, you'll find the answer quickly in this handy, easy-to-use quick reference. The Perl Pocket Reference condenses and organizes stacks of documentation down to the most essential facts, so you can find what you need in a heartbeat. Updated for Perl 5.14, the 5th edition provides a summary of Perl syntax rules and a complete list of operators, built-in functions, and other features. It's the perfect companion to O'Reilly's authoritative and in-depth Perl programming books, including Learning Perl, Programming Perl, and the Perl Cookbook..

  16. HTML & XHTML Pocket Reference

    CERN Document Server

    Robbins, Jennifer

    2010-01-01

    After years of using spacer GIFs, layers of nested tables, and other improvised solutions for building your web sites, getting used to the more stringent standards-compliant design can be intimidating. HTML and XHTML Pocket Reference is the perfect little book when you need answers immediately. Jennifer Niederst-Robbins, author Web Design in a Nutshell, has revised and updated the fourth edition of this pocket guide by taking the top 20% of vital reference information from her Nutshell book, augmenting it judiciously, cross-referencing everything, and organizing it according to the most com

  17. CSS Pocket Reference

    CERN Document Server

    Meyer, Eric A

    2007-01-01

    They say that good things come in small packages, and it's certainly true for this edition of CSS Pocket Reference. Completely revised and updated to reflect the latest Cascading Style Sheet specifications in CSS 2.1, this indispensable little book covers the most essential information that web designers and developers need to implement CSS effectively across all browsers. Inside, you'll find: A short introduction to the key concepts of CSS A complete alphabetical reference to all CSS 2.1 selectors and properties A chart displaying detailed information about CSS support for every style ele

  18. JDBC Pocket Reference

    CERN Document Server

    Bales, Donald

    2003-01-01

    JDBC--the Java Database Connectivity specification--is a complex set of application programming interfaces (APIs) that developers need to understand if they want their Java applications to work with databases. JDBC is so complex that even the most experienced developers need to refresh their memories from time to time on specific methods and details. But, practically speaking, who wants to stop and thumb through a weighty tutorial volume each time a question arises? The answer is the JDBC Pocket Reference, a data-packed quick reference that is both a time-saver and a lifesaver. The JDBC P

  19. Reference values for electrooculography

    International Nuclear Information System (INIS)

    Barrientos Castanno, Alberto; Herrera Mora, Maritza; Garcia Baez, Obel

    2012-01-01

    Obtain electrooculographic reference values based on the patterns set by the Standardization Committee of the International Society for Clinical Electrophysiology of Vision (ISCEV). the lowest amplitude values of the potential ranged between 388 and 882 μv in the dark phase. The light peak was obtained between 9 and 10 minutes, and during this phase the potential reached an amplitude ranging between 808 and 1 963 μv. This amplitude variability may be related to the fact that the test was conducted without pupillary mydriasis. The reference value obtained for Arden index was 1,55 to 2,87

  20. NASCAP programmer's reference manual

    Science.gov (United States)

    Mandell, M. J.; Stannard, P. R.; Katz, I.

    1993-05-01

    The NASA Charging Analyzer Program (NASCAP) is a computer program designed to model the electrostatic charging of complicated three-dimensional objects, both in a test tank and at geosynchronous altitudes. This document is a programmer's reference manual and user's guide. It is designed as a reference to experienced users of the code, as well as an introduction to its use for beginners. All of the many capabilities of NASCAP are covered in detail, together with examples of their use. These include the definition of objects, plasma environments, potential calculations, particle emission and detection simulations, and charging analysis.

  1. Self-Reference Acts as a Golden Thread in Binding.

    Science.gov (United States)

    Sui, Jie

    2016-07-01

    In a recent article in this journal, Glyn Humphreys and I proposed a model of how self-reference enhances binding in perception and cognition [1]. We showed that self-reference changes particular functional processes; notably, self-reference increases binding between the features of stimuli and between different stages of processing. Lane and colleagues [2] provide an interesting comment on our article that suggests our theory of self-reference is compatible with Dennett's philosophical perspective on the narrative nature of the self. Although the nature of the self has attracted the attention of both philosophers and scientists, the two disciplines have generated different perspectives on the functions of the self, largely due to their different methodologies. For example, Dennett argues that the self is constituted through human narration on experience [3]. By contrast, work from psychologists and cognitive neuroscientists focuses on the functional and neural mechanisms of self-reference. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Physical meaning of the optical reference geometry

    International Nuclear Information System (INIS)

    Abramowicz, M.A.

    1990-09-01

    I show that contrary to a popular misconception the optical reference geometry, introduced a few years ago as a formally possible metric of a 3-space corresponding to a static spacetime, is quite satisfactory also from the physical point of view. The optical reference geometry has a clear physical meaning, as it may be constructed experimentally by measuring light round travel time between static observers. Distances and directions in the optical reference geometry are more strongly connected to experiment than distances and directions in the widely used directly projected metric (discussed e.g. in Landau and Lifshitz textbook. In addition, the optical reference geometry is more natural and convenient than the directly projected one in application to dynamics. In the optical geometry dynamical behaviour of matter is described by concepts and formulae identical to those well known in Newtonian dynamics on a given two dimensional (curved) surface. (author). 22 refs

  3. Book Catalogs; Selected References.

    Science.gov (United States)

    Brandhorst, Wesley T.

    The 116 citations on book catalogs are divided into the following two main sections: (1) Selected References, in alphabetic sequence by personal or institutional author and (2) Anonymous Entries, in alphabetic sequence by title. One hundred and seven of the citations cover the years 1960 through March 1969. There are five scattered citations in…

  4. ROOT Reference Documentation

    CERN Document Server

    Fuakye, Eric Gyabeng

    2017-01-01

    A ROOT Reference Documentation has been implemented to generate all the lists of libraries needed for each ROOT class. Doxygen has no option to generate or add the lists of libraries for each ROOT class. Therefore shell scripting and a basic C++ program was employed to import the lists of libraries needed by each ROOT class.

  5. Hospitality Services Reference Book.

    Science.gov (United States)

    Texas Tech Univ., Lubbock. Home Economics Curriculum Center.

    This reference book provides information needed by employees in hospitality services occupations. It includes 29 chapters that cover the following topics: the hospitality services industry; professional ethics; organization and management structures; safety practices and emergency procedures; technology; property maintenance and repair; purchasing…

  6. Quantum frames of reference

    International Nuclear Information System (INIS)

    Kaufherr, T.

    1981-01-01

    The idea that only relative variables have physical meaning came to be known as Mach's principle. Carrying over this idea to quantum theory, has led to the consideration of finite mass, macroscopic reference frames, relative to which all physical quantities are measured. During the process of measurement, a finite mass observer receives a kickback, and this reaction of the measuring device is not negligible in quantum theory because of the quantization of the action. Hence, the observer himself has to be included in the system that is being considered. Using this as the starting point, a number of thought experiments involving finite mass observers is discussed which have quantum uncertainties in their time or in their position. These thought experiments serve to elucidate in a qualitative way some of the difficulties involved, as well as pointing out a direction to take in seeking solutions to them. When the discussion is extended to include more than one observer, the question of the covariance of the theory immediately arises. Because none of the frames of reference should be preferred, the theory should be covariant. This demand expresses an equivalence principle which here is extended to include reference frames which are in quantum uncertainties relative to each other. Formulating the problem in terms of canonical variables, the ensueing free Hamiltonian contains vector and scalar potentials which represent the kick that the reference frame receives during measurement. These are essentially gravitational type potentials, resulting, as it were, from the extension of the equivalence principle into the quantum domain

  7. Pollen reference collection digitization

    NARCIS (Netherlands)

    Ercan, F.E.Z.; Donders, T.H.; Bijl, P.K.; Wagner, F.

    2016-01-01

    The extensive Utrecht University pollen reference collection holds thousands of pollen samples of many species and genera from all over the world and has been a basis for the widely-used North West European Pollen Flora. These samples are fixed on glass slides for microscopy use, but the aging

  8. Virtual Reference Services.

    Science.gov (United States)

    Brewer, Sally

    2003-01-01

    As the need to access information increases, school librarians must create virtual libraries. Linked to reliable reference resources, the virtual library extends the physical collection and library hours and lets students learn to use Web-based resources in a protected learning environment. The growing number of virtual schools increases the need…

  9. Reference-Dependent Sympathy

    Science.gov (United States)

    Small, Deborah A.

    2010-01-01

    Natural disasters and other traumatic events often draw a greater charitable response than do ongoing misfortunes, even those that may cause even more widespread misery, such as famine or malaria. Why is the response disproportionate to need? The notion of reference dependence critical to Prospect Theory (Kahneman & Tversky, 1979) maintains that…

  10. Genetics Home Reference

    Science.gov (United States)

    ... Page Search Home Health Conditions Genes Chromosomes & mtDNA Resources Help Me Understand Genetics Share: Email Facebook Twitter Genetics Home Reference provides consumer-friendly information about the effects of genetic variation on human health. Health Conditions More than 1,200 health ...

  11. Python library reference

    NARCIS (Netherlands)

    G. van Rossum (Guido)

    1995-01-01

    textabstractPython is an extensible, interpreted, object-oriented programming language. It supports a wide range of applications, from simple text processing scripts to interactive WWW browsers. While the Python Reference Manual describes the exact syntax and semantics of the language, it does not

  12. Synchronization criteria for generalized reaction-diffusion neural networks via periodically intermittent control.

    Science.gov (United States)

    Gan, Qintao; Lv, Tianshi; Fu, Zhenhua

    2016-04-01

    In this paper, the synchronization problem for a class of generalized neural networks with time-varying delays and reaction-diffusion terms is investigated concerning Neumann boundary conditions in terms of p-norm. The proposed generalized neural networks model includes reaction-diffusion local field neural networks and reaction-diffusion static neural networks as its special cases. By establishing a new inequality, some simple and useful conditions are obtained analytically to guarantee the global exponential synchronization of the addressed neural networks under the periodically intermittent control. According to the theoretical results, the influences of diffusion coefficients, diffusion space, and control rate on synchronization are analyzed. Finally, the feasibility and effectiveness of the proposed methods are shown by simulation examples, and by choosing different diffusion coefficients, diffusion spaces, and control rates, different controlled synchronization states can be obtained.

  13. Optimization of multilayer neural network parameters for speaker recognition

    Science.gov (United States)

    Tovarek, Jaromir; Partila, Pavol; Rozhon, Jan; Voznak, Miroslav; Skapa, Jan; Uhrin, Dominik; Chmelikova, Zdenka

    2016-05-01

    This article discusses the impact of multilayer neural network parameters for speaker identification. The main task of speaker identification is to find a specific person in the known set of speakers. It means that the voice of an unknown speaker (wanted person) belongs to a group of reference speakers from the voice database. One of the requests was to develop the text-independent system, which means to classify wanted person regardless of content and language. Multilayer neural network has been used for speaker identification in this research. Artificial neural network (ANN) needs to set parameters like activation function of neurons, steepness of activation functions, learning rate, the maximum number of iterations and a number of neurons in the hidden and output layers. ANN accuracy and validation time are directly influenced by the parameter settings. Different roles require different settings. Identification accuracy and ANN validation time were evaluated with the same input data but different parameter settings. The goal was to find parameters for the neural network with the highest precision and shortest validation time. Input data of neural networks are a Mel-frequency cepstral coefficients (MFCC). These parameters describe the properties of the vocal tract. Audio samples were recorded for all speakers in a laboratory environment. Training, testing and validation data set were split into 70, 15 and 15 %. The result of the research described in this article is different parameter setting for the multilayer neural network for four speakers.

  14. Neutron spectrum unfolding using neural networks

    International Nuclear Information System (INIS)

    Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E.

    2004-01-01

    An artificial neural network has been designed to obtain the neutron spectra from the Bonner spheres spectrometer's count rates. The neural network was trained using a large set of neutron spectra compiled by the International Atomic Energy Agency. These include spectra from iso- topic neutron sources, reference and operational neutron spectra obtained from accelerators and nuclear reactors. The spectra were transformed from lethargy to energy distribution and were re-binned to 31 energy groups using the MCNP 4C code. Re-binned spectra and UTA4 matrix were used to calculate the expected count rates in Bonner spheres spectrometer. These count rates were used as input and correspondent spectrum was used as output during neural network training. The network has 7 input nodes, 56 neurons as hidden layer and 31 neurons in the output layer. After training the network was tested with the Bonner spheres count rates produced by twelve neutron spectra. The network allows unfolding the neutron spectrum from count rates measured with Bonner spheres. Good results are obtained when testing count rates belong to neutron spectra used during training, acceptable results are obtained for count rates obtained from actual neutron fields; however the network fails when count rates belong to monoenergetic neutron sources. (Author)

  15. Cosmic-ray discrimination capabilities of DELTA E-E silicon nuclear telescopes using neural networks

    CERN Document Server

    Ambriola, M; Cafagna, F; Castellano, M; Ciacio, F; Circella, M; De Marzo, C N; Montaruli, T

    2000-01-01

    An isotope classifier of cosmic-ray events collected by space detectors has been implemented using a multi-layer perceptron neural architecture. In order to handle a great number of different isotopes a modular architecture of the 'mixture of experts' type is proposed. The performance of this classifier has been tested on simulated data and has been compared with a 'classical' classifying procedure. The quantitative comparison with traditional techniques shows that the neural approach has classification performances comparable - within 1% - with that of the classical one, with efficiency of the order of 98%. A possible hardware implementation of such a kind of neural architecture in future space missions is considered.

  16. Nonlinear analysis and synthesis of video images using deep dynamic bottleneck neural networks for face recognition.

    Science.gov (United States)

    Moghadam, Saeed Montazeri; Seyyedsalehi, Seyyed Ali

    2018-05-31

    Nonlinear components extracted from deep structures of bottleneck neural networks exhibit a great ability to express input space in a low-dimensional manifold. Sharing and combining the components boost the capability of the neural networks to synthesize and interpolate new and imaginary data. This synthesis is possibly a simple model of imaginations in human brain where the components are expressed in a nonlinear low dimensional manifold. The current paper introduces a novel Dynamic Deep Bottleneck Neural Network to analyze and extract three main features of videos regarding the expression of emotions on the face. These main features are identity, emotion and expression intensity that are laid in three different sub-manifolds of one nonlinear general manifold. The proposed model enjoying the advantages of recurrent networks was used to analyze the sequence and dynamics of information in videos. It is noteworthy to mention that this model also has also the potential to synthesize new videos showing variations of one specific emotion on the face of unknown subjects. Experiments on discrimination and recognition ability of extracted components showed that the proposed model has an average of 97.77% accuracy in recognition of six prominent emotions (Fear, Surprise, Sadness, Anger, Disgust, and Happiness), and 78.17% accuracy in the recognition of intensity. The produced videos revealed variations from neutral to the apex of an emotion on the face of the unfamiliar test subject which is on average 0.8 similar to reference videos in the scale of the SSIM method. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. Deep Neural Yodelling

    OpenAIRE

    Pfäffli, Daniel (Autor/in)

    2018-01-01

    Yodel music differs from most other genres by exercising the transition from chest voice to falsetto with an audible glottal stop which is recognised even by laymen. Yodel often consists of a yodeller with a choir accompaniment. In Switzerland, it is differentiated between the natural yodel and yodel songs. Today's approaches to music generation with machine learning algorithms are based on neural networks, which are best described by stacked layers of neurons which are connected with neurons...

  18. Neural networks for triggering

    International Nuclear Information System (INIS)

    Denby, B.; Campbell, M.; Bedeschi, F.; Chriss, N.; Bowers, C.; Nesti, F.

    1990-01-01

    Two types of neural network beauty trigger architectures, based on identification of electrons in jets and recognition of secondary vertices, have been simulated in the environment of the Fermilab CDF experiment. The efficiencies for B's and rejection of background obtained are encouraging. If hardware tests are successful, the electron identification architecture will be tested in the 1991 run of CDF. 10 refs., 5 figs., 1 tab

  19. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  20. Rotation Invariance Neural Network

    OpenAIRE

    Li, Shiyuan

    2017-01-01

    Rotation invariance and translation invariance have great values in image recognition tasks. In this paper, we bring a new architecture in convolutional neural network (CNN) named cyclic convolutional layer to achieve rotation invariance in 2-D symbol recognition. We can also get the position and orientation of the 2-D symbol by the network to achieve detection purpose for multiple non-overlap target. Last but not least, this architecture can achieve one-shot learning in some cases using thos...

  1. Neural Mechanisms of Foraging

    OpenAIRE

    Kolling, Nils; Behrens, Timothy EJ; Mars, Rogier B; Rushworth, Matthew FS

    2012-01-01

    Behavioural economic studies, involving limited numbers of choices, have provided key insights into neural decision-making mechanisms. By contrast, animals’ foraging choices arise in the context of sequences of encounters with prey/food. On each encounter the animal chooses to engage or whether the environment is sufficiently rich that searching elsewhere is merited. The cost of foraging is also critical. We demonstrate humans can alternate between two modes of choice, comparative decision-ma...

  2. Maps into projective spaces

    Indian Academy of Sciences (India)

    Usha N Bhosle. Acknowledgements. This work was initiated during the author's visit to the Isaac Newton Institute, Cambridge,. UK as a visiting fellow to participate in the programme Moduli Spaces (MOS) during. June 2011. She would like to thank the Institute for hospitality and excellent working environment. References.

  3. I-space

    DEFF Research Database (Denmark)

    Helms, Niels Henrik; Tellerup, Susanne; Bryderup, Karin Jensen

    This paper presents I-Space. The purpose of this project is to improve the wellbeing and life quality of mentally impaired citizens through the development of new technologies, which could enhance learning and motivation. The project is used as reference to a discussion on structures within design...

  4. Space and composition

    DEFF Research Database (Denmark)

    Kjølner, Torunn

    2005-01-01

    The article takes concept art and Deleuze and Guattari's understanding of concept as  references for thinking theatre as an art form defined as a composition of elements in time and space. It offers a discussion of three different kinds of spatial approaches to theatre making and  a discussion...

  5. Optical neural network system for pose determination of spinning satellites

    Science.gov (United States)

    Lee, Andrew; Casasent, David

    1990-01-01

    An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

  6. Third Conference on Artificial Intelligence for Space Applications, part 1

    Science.gov (United States)

    Denton, Judith S. (Compiler); Freeman, Michael S. (Compiler); Vereen, Mary (Compiler)

    1987-01-01

    The application of artificial intelligence to spacecraft and aerospace systems is discussed. Expert systems, robotics, space station automation, fault diagnostics, parallel processing, knowledge representation, scheduling, man-machine interfaces and neural nets are among the topics discussed.

  7. Improved Local Weather Forecasts Using Artificial Neural Networks

    DEFF Research Database (Denmark)

    Wollsen, Morten Gill; Jørgensen, Bo Nørregaard

    2015-01-01

    Solar irradiance and temperature forecasts are used in many different control systems. Such as intelligent climate control systems in commercial greenhouses, where the solar irradiance affects the use of supplemental lighting. This paper proposes a novel method to predict the forthcoming weather...... using an artificial neural network. The neural network used is a NARX network, which is known to model non-linear systems well. The predictions are compared to both a design reference year as well as commercial weather forecasts based upon numerical modelling. The results presented in this paper show...

  8. Identifying Broadband Rotational Spectra with Neural Networks

    Science.gov (United States)

    Zaleski, Daniel P.; Prozument, Kirill

    2017-06-01

    A typical broadband rotational spectrum may contain several thousand observable transitions, spanning many species. Identifying the individual spectra, particularly when the dynamic range reaches 1,000:1 or even 10,000:1, can be challenging. One approach is to apply automated fitting routines. In this approach, combinations of 3 transitions can be created to form a "triple", which allows fitting of the A, B, and C rotational constants in a Watson-type Hamiltonian. On a standard desktop computer, with a target molecule of interest, a typical AUTOFIT routine takes 2-12 hours depending on the spectral density. A new approach is to utilize machine learning to train a computer to recognize the patterns (frequency spacing and relative intensities) inherit in rotational spectra and to identify the individual spectra in a raw broadband rotational spectrum. Here, recurrent neural networks have been trained to identify different types of rotational spectra and classify them accordingly. Furthermore, early results in applying convolutional neural networks for spectral object recognition in broadband rotational spectra appear promising. Perez et al. "Broadband Fourier transform rotational spectroscopy for structure determination: The water heptamer." Chem. Phys. Lett., 2013, 571, 1-15. Seifert et al. "AUTOFIT, an Automated Fitting Tool for Broadband Rotational Spectra, and Applications to 1-Hexanal." J. Mol. Spectrosc., 2015, 312, 13-21. Bishop. "Neural networks for pattern recognition." Oxford university press, 1995.

  9. Artificial neural network applications in ionospheric studies

    Directory of Open Access Journals (Sweden)

    L. R. Cander

    1998-06-01

    Full Text Available The ionosphere of Earth exhibits considerable spatial changes and has large temporal variability of various timescales related to the mechanisms of creation, decay and transport of space ionospheric plasma. Many techniques for modelling electron density profiles through entire ionosphere have been developed in order to solve the "age-old problem" of ionospheric physics which has not yet been fully solved. A new way to address this problem is by applying artificial intelligence methodologies to current large amounts of solar-terrestrial and ionospheric data. It is the aim of this paper to show by the most recent examples that modern development of numerical models for ionospheric monthly median long-term prediction and daily hourly short-term forecasting may proceed successfully applying the artificial neural networks. The performance of these techniques is illustrated with different artificial neural networks developed to model and predict the temporal and spatial variations of ionospheric critical frequency, f0F2 and Total Electron Content (TEC. Comparisons between results obtained by the proposed approaches and measured f0F2 and TEC data provide prospects for future applications of the artificial neural networks in ionospheric studies.

  10. Genetic optimization of neural network architecture

    International Nuclear Information System (INIS)

    Harp, S.A.; Samad, T.

    1994-03-01

    Neural networks are now a popular technology for a broad variety of application domains, including the electric utility industry. Yet, as the technology continues to gain increasing acceptance, it is also increasingly apparent that the power that neural networks provide is not an unconditional blessing. Considerable care must be exercised during application development if the full benefit of the technology is to be realized. At present, no fully general theory or methodology for neural network design is available, and application development is a trial-and-error process that is time-consuming and expertise-intensive. Each application demands appropriate selections of the network input space, the network structure, and values of learning algorithm parameters-design choices that are closely coupled in ways that largely remain a mystery. This EPRI-funded exploratory research project was initiated to take the key next step in this research program: the validation of the approach on a realistic problem. We focused on the problem of modeling the thermal performance of the TVA Sequoyah nuclear power plant (units 1 and 2)

  11. Neural Based Orthogonal Data Fitting The EXIN Neural Networks

    CERN Document Server

    Cirrincione, Giansalvo

    2008-01-01

    Written by three leaders in the field of neural based algorithms, Neural Based Orthogonal Data Fitting proposes several neural networks, all endowed with a complete theory which not only explains their behavior, but also compares them with the existing neural and traditional algorithms. The algorithms are studied from different points of view, including: as a differential geometry problem, as a dynamic problem, as a stochastic problem, and as a numerical problem. All algorithms have also been analyzed on real time problems (large dimensional data matrices) and have shown accurate solutions. Wh

  12. ``Frames of Reference'' revisited

    Science.gov (United States)

    Steyn-Ross, Alistair; Ivey, Donald G.

    1992-12-01

    The PSSC teaching film, ``Frames of Reference,'' was made in 1960, and was one of the first audio-visual attempts at showing how your physical ``point of view,'' or frame of reference, necessarily alters both your perceptions and your observations of motion. The gentle humor and original demonstrations made a lasting impact on many audiences, and with its recent re-release as part of the AAPT Cinema Classics videodisc it is timely that we should review both the message and the methods of the film. An annotated script and photographs from the film are presented, followed by extension material on rotating frames which teachers may find appropriate for use in their classrooms: constructions, demonstrations, an example, and theory.

  13. Program reference schedule baseline

    International Nuclear Information System (INIS)

    1986-07-01

    This Program Reference Schedule Baseline (PRSB) provides the baseline Program-level milestones and associated schedules for the Civilian Radioactive Waste Management Program. It integrates all Program-level schedule-related activities. This schedule baseline will be used by the Director, Office of Civilian Radioactive Waste Management (OCRWM), and his staff to monitor compliance with Program objectives. Chapter 1 includes brief discussions concerning the relationship of the PRSB to the Program Reference Cost Baseline (PRCB), the Mission Plan, the Project Decision Schedule, the Total System Life Cycle Cost report, the Program Management Information System report, the Program Milestone Review, annual budget preparation, and system element plans. Chapter 2 includes the identification of all Level 0, or Program-level, milestones, while Chapter 3 presents and discusses the critical path schedules that correspond to those Level 0 milestones

  14. OSH technical reference manual

    Energy Technology Data Exchange (ETDEWEB)

    1993-11-01

    In an evaluation of the Department of Energy (DOE) Occupational Safety and Health programs for government-owned contractor-operated (GOCO) activities, the Department of Labor`s Occupational Safety and Health Administration (OSHA) recommended a technical information exchange program. The intent was to share written safety and health programs, plans, training manuals, and materials within the entire DOE community. The OSH Technical Reference (OTR) helps support the secretary`s response to the OSHA finding by providing a one-stop resource and referral for technical information that relates to safe operations and practice. It also serves as a technical information exchange tool to reference DOE-wide materials pertinent to specific safety topics and, with some modification, as a training aid. The OTR bridges the gap between general safety documents and very specific requirements documents. It is tailored to the DOE community and incorporates DOE field experience.

  15. Electrical engineer's reference book

    CERN Document Server

    Laughton, M A

    1985-01-01

    Electrical Engineer's Reference Book, Fourteenth Edition focuses on electrical engineering. The book first discusses units, mathematics, and physical quantities, including the international unit system, physical properties, and electricity. The text also looks at network and control systems analysis. The book examines materials used in electrical engineering. Topics include conducting materials, superconductors, silicon, insulating materials, electrical steels, and soft irons and relay steels. The text underscores electrical metrology and instrumentation, steam-generating plants, turbines

  16. Reference Sources in Chemistry

    OpenAIRE

    Sthapit, Dilip Man

    1995-01-01

    Information plays an important role in the development of every field. Therefore a brief knowledge regarding information sources is necessary to function in any field. There are many information sources about scientific and technical subjects. In this context there are many reference sources in Chemistry too. Chemistry is one important part of the science which deals with the study of the composition of substances and the chemical changes that they undergo. The purpose of this report is...

  17. Radioactive certified reference materials

    International Nuclear Information System (INIS)

    Watanabe, Kazuo

    2010-01-01

    Outline of radioactive certified reference materials (CRM) for the analysis of nuclear materials and radioactive nuclides were described. The nuclear fuel CRMs are supplied by the three institutes: NBL in the US, CETAMA in France and IRMM in Belgium. For the RI CRMs, the Japan Radioisotope Association is engaged in activities concerning supply. The natural-matrix CRMs for the analysis of trace levels of radio-nuclides are prepared and supplied by NIST in the US and the IAEA. (author)

  18. Reference Japanese man

    International Nuclear Information System (INIS)

    Tanaka, G.-I.; Kawamura, H.; Nakahara, Y.

    1979-01-01

    The weight of organs from autopsy cases of normal Japanese adults, children, and infants is presented for the purpose of approaching a Reference Japanese Man. The skeletal content and the daily intake of alkaline earth elements are given. A lower rate of transfer (K 2 ) to the thyroid gland of ingested radioiodine, as well as a remarkably shorter biological half-life than the data adopted by ICRP, is also proved as a result of this study. (author)

  19. Genetics Home Reference: spina bifida

    Science.gov (United States)

    ... a condition in which the neural tube, a layer of cells that ultimately develops into the brain and spinal cord, fails to close completely during the first few weeks of embryonic development. As a result, when the spine forms, ...

  20. Genetics Home Reference: Meckel syndrome

    Science.gov (United States)

    ... when a structure called the neural tube, a layer of cells that ultimately develops into the brain and spinal cord, fails to close completely during the first few weeks of embryonic development. Meckel syndrome can also cause problems with ...

  1. Reference handbook: Level detectors

    International Nuclear Information System (INIS)

    1990-01-01

    The purpose of this handbook is to provide Rocky Flats personnel with the information necessary to understand level measurement and detection. Upon completion of this handbook you should be able to do the following: List three reasons for measuring level. Describe the basic operating principles of the sight glass. Demonstrate proper techniques for reading a sight glass. Describe the basic operating principles of a float level detector. Describe the basic operating principles of a bubbler level indicating system. Explain the differences between a wet and dry reference leg indicating system, and describe how each functions. This handbook is designed for use by experienced Rocky Flats operators to reinforce and improve their current knowledge level, and by entry-level operators to ensure that they possess a minimum level of fundamental knowledge. Level Detectors is applicable to many job classifications and can be used as a reference for classroom work or for self-study. Although this reference handbook is by no means all-encompassing, you will gain enough information about this subject area to assist you in contributing to the safe operation of Rocky Flats Plant

  2. Electroacoustical reference data

    CERN Document Server

    Eargle, John M

    2002-01-01

    The need for a general collection of electroacoustical reference and design data in graphical form has been felt by acousticians and engineers for some time. This type of data can otherwise only be found in a collection of handbooks. Therefore, it is the author's intention that this book serve as a single source for many electroacoustical reference and system design requirements. In form, the volume closely resembles Frank Massa's Acoustic Design Charts, a handy book dating from 1942 that has long been out of print. The basic format of Massa's book has been followed here: For each entry, graphical data are presented on the right page, while text, examples, and refer­ ences appear on the left page. In this manner, the user can solve a given problem without thumbing from one page to the next. All graphs and charts have been scaled for ease in data entry and reading. The book is divided into the following sections: A. General Acoustical Relationships. This section covers the behavior of sound transmis­ sion in...

  3. Neural Networks for Modeling and Control of Particle Accelerators

    Science.gov (United States)

    Edelen, A. L.; Biedron, S. G.; Chase, B. E.; Edstrom, D.; Milton, S. V.; Stabile, P.

    2016-04-01

    Particle accelerators are host to myriad nonlinear and complex physical phenomena. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. The purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

  4. Trimaran Resistance Artificial Neural Network

    Science.gov (United States)

    2011-01-01

    11th International Conference on Fast Sea Transportation FAST 2011, Honolulu, Hawaii, USA, September 2011 Trimaran Resistance Artificial Neural Network Richard...Trimaran Resistance Artificial Neural Network 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e... Artificial Neural Network and is restricted to the center and side-hull configurations tested. The value in the parametric model is that it is able to

  5. Face recognition: a convolutional neural-network approach.

    Science.gov (United States)

    Lawrence, S; Giles, C L; Tsoi, A C; Back, A D

    1997-01-01

    We present a hybrid neural-network for human face recognition which compares favourably with other methods. The system combines local image sampling, a self-organizing map (SOM) neural network, and a convolutional neural network. The SOM provides a quantization of the image samples into a topological space where inputs that are nearby in the original space are also nearby in the output space, thereby providing dimensionality reduction and invariance to minor changes in the image sample, and the convolutional neural network provides partial invariance to translation, rotation, scale, and deformation. The convolutional network extracts successively larger features in a hierarchical set of layers. We present results using the Karhunen-Loeve transform in place of the SOM, and a multilayer perceptron (MLP) in place of the convolutional network for comparison. We use a database of 400 images of 40 individuals which contains quite a high degree of variability in expression, pose, and facial details. We analyze the computational complexity and discuss how new classes could be added to the trained recognizer.

  6. Yearbook on space policy 2015 access to space and the evolution of space activities

    CERN Document Server

    Baranes, Blandina; Hulsroj, Peter; Lahcen, Arne

    2017-01-01

    The Yearbook on Space Policy, edited by the European Space Policy Institute (ESPI), is the reference publication analysing space policy developments. Each year it presents issues and trends in space policy and the space sector as a whole. Its scope is global and its perspective is European. The Yearbook also links space policy with other policy areas. It highlights specific events and issues, and provides useful insights, data and information on space activities. The first part of the Yearbook sets out a comprehensive overview of the economic, political, technological and institutional trends that have affected space activities. The second part of the Yearbook offers a more analytical perspective on the yearly ESPI theme and consists of external contributions written by professionals with diverse backgrounds and areas of expertise. The third part of the Yearbook carries forward the character of the Yearbook as an archive of space activities. The Yearbook is designed for government decision-makers and agencies...

  7. Rock images classification by using deep convolution neural network

    Science.gov (United States)

    Cheng, Guojian; Guo, Wenhui

    2017-08-01

    Granularity analysis is one of the most essential issues in authenticate under microscope. To improve the efficiency and accuracy of traditional manual work, an convolutional neural network based method is proposed for granularity analysis from thin section image, which chooses and extracts features from image samples while build classifier to recognize granularity of input image samples. 4800 samples from Ordos basin are used for experiments under colour spaces of HSV, YCbCr and RGB respectively. On the test dataset, the correct rate in RGB colour space is 98.5%, and it is believable in HSV and YCbCr colour space. The results show that the convolution neural network can classify the rock images with high reliability.

  8. Deep learning classification in asteroseismology using an improved neural network

    DEFF Research Database (Denmark)

    Hon, Marc; Stello, Dennis; Yu, Jie

    2018-01-01

    Deep learning in the form of 1D convolutional neural networks have previously been shown to be capable of efficiently classifying the evolutionary state of oscillating red giants into red giant branch stars and helium-core burning stars by recognizing visual features in their asteroseismic...... frequency spectra. We elaborate further on the deep learning method by developing an improved convolutional neural network classifier. To make our method useful for current and future space missions such as K2, TESS, and PLATO, we train classifiers that are able to classify the evolutionary states of lower...

  9. Neighborhood spaces

    OpenAIRE

    D. C. Kent; Won Keun Min

    2002-01-01

    Neighborhood spaces, pretopological spaces, and closure spaces are topological space generalizations which can be characterized by means of their associated interior (or closure) operators. The category NBD of neighborhood spaces and continuous maps contains PRTOP as a bicoreflective subcategory and CLS as a bireflective subcategory, whereas TOP is bireflectively embedded in PRTOP and bicoreflectively embedded in CLS. Initial and final structures are described in these categories, and it is s...

  10. Optical Reference Stars for Space Surveillance: Future Plans: Latest Developments

    Science.gov (United States)

    2010-01-01

    Micron All Sky Survey ( 2MASS ) has imaged the entire sky in near-infrared J(1.25m), H(1.65 m), and Ks(2.16 m) bandpasses from Mt Hopkins, Arizona...and Cerro Tololo, Chile. The 10-sigma detection levels reached 15.8, 15.1, and 14.3 mag at the J, H, and Ks bands, respectively. The 2MASS data...no proper motions for the stars. Information on 2MASS can be found at http://www.ipac.caltech.edu/ 2mass . UCAC The basis of the USNO CCD

  11. Saha equation in Rindler space

    Indian Academy of Sciences (India)

    Sanchari De

    2017-05-31

    May 31, 2017 ... scenario, the flat local geometry is called the Rindler space. For an illustration, let us consider two reference ... the local acceleration of the frame. To investigate Saha equation in a uniformly acceler- ... the best of our knowledge, the study of Saha equa- tion in Rindler space has not been reported earlier.

  12. Lorentz Transformation from Symmetry of Reference Principle

    International Nuclear Information System (INIS)

    Petre, M.; Dima, M.; Dima, A.; Petre, C.; Precup, I.

    2010-01-01

    The Lorentz Transformation is traditionally derived requiring the Principle of Relativity and light-speed universality. While the latter can be relaxed, the Principle of Relativity is seen as core to the transformation. The present letter relaxes both statements to the weaker, Symmetry of Reference Principle. Thus the resulting Lorentz transformation and its consequences (time dilatation, length contraction) are, in turn, effects of how we manage space and time.

  13. Instrumentation reference book

    CERN Document Server

    Boyes, Walt

    2002-01-01

    Instrumentation is not a clearly defined subject, having a 'fuzzy' boundary with a number of other disciplines. Often categorized as either 'techniques' or 'applications' this book addresses the various applications that may be needed with reference to the practical techniques that are available for the instrumentation or measurement of a specific physical quantity or quality. This makes it of direct interest to anyone working in the process, control and instrumentation fields where these measurements are essential.* Comprehensive and authoritative collection of technical information* Writte

  14. XSLT 10 Pocket Reference

    CERN Document Server

    Lenz, Evan

    2008-01-01

    XSLT is an essential tool for converting XML into other kinds of documents: HTML, PDF file, and many others. It's a critical technology for XML-based platforms such as Microsoft .NET, Sun Microsystems' Sun One, as well as for most web browsers and authoring tools. As useful as XSLT is, however, most people have a difficult time getting used to its peculiar characteristics. The ability to use advanced techniques depends on a clear and exact understanding of how XSLT templates work and interact. The XSLT 1.0 Pocket Reference from O'Reilly wants to make sure you achieve that level of understan

  15. Electronics engineer's reference book

    CERN Document Server

    Mazda, F F

    1989-01-01

    Electronics Engineer's Reference Book, Sixth Edition is a five-part book that begins with a synopsis of mathematical and electrical techniques used in the analysis of electronic systems. Part II covers physical phenomena, such as electricity, light, and radiation, often met with in electronic systems. Part III contains chapters on basic electronic components and materials, the building blocks of any electronic design. Part IV highlights electronic circuit design and instrumentation. The last part shows the application areas of electronics such as radar and computers.

  16. International Geomagnetic Reference Field

    DEFF Research Database (Denmark)

    Finlay, Chris; Maus, S.; Beggan, C. D.

    2010-01-01

    The eleventh generation of the International Geomagnetic Reference Field (IGRF) was adopted in December 2009 by the International Association of Geomagnetism and Aeronomy Working Group V‐MOD. It updates the previous IGRF generation with a definitive main field model for epoch 2005.0, a main field...... model for epoch 2010.0, and a linear predictive secular variation model for 2010.0–2015.0. In this note the equations defining the IGRF model are provided along with the spherical harmonic coefficients for the eleventh generation. Maps of the magnetic declination, inclination and total intensity...

  17. Mechanical engineer's reference book

    CERN Document Server

    Parrish, A

    1973-01-01

    Mechanical Engineer's Reference Book: 11th Edition presents a comprehensive examination of the use of Systéme International d' Unités (SI) metrication. It discusses the effectiveness of such a system when used in the field of engineering. It addresses the basic concepts involved in thermodynamics and heat transfer. Some of the topics covered in the book are the metallurgy of iron and steel; screw threads and fasteners; hole basis and shaft basis fits; an introduction to geometrical tolerancing; mechanical working of steel; high strength alloy steels; advantages of making components as castings

  18. VBScript pocket reference

    CERN Document Server

    Lomax, Paul; Petrusha, Ron

    2008-01-01

    Microsoft's Visual Basic Scripting Edition (VBScript), a subset of Visual Basic for Applications, is a powerful language for Internet application development, where it can serve as a scripting language for server-side, client-side, and system scripting. Whether you're developing code for Active Server Pages, client-side scripts for Internet Explorer, code for Outlook forms, or scripts for Windows Script Host, VBScript Pocket Reference will be your constant companion. Don't let the pocket-friendly format fool you. Based on the bestsellingVBScript in a Nutshell, this small book details every V

  19. Xcode 5 developer reference

    CERN Document Server

    Wentk, Richard

    2014-01-01

    Design, code, and build amazing apps with Xcode 5 Thanks to Apple's awesome Xcode development environment, you can create the next big app for Macs, iPhones, iPads, or iPod touches. Xcode 5 contains gigabytes of great stuff to help you develop for both OS X and iOS devices - things like sample code, utilities, companion applications, documentation, and more. And with Xcode 5 Developer Reference, you now have the ultimate step-by-step guide to it all. Immerse yourself in the heady and lucrative world of Apple app development, see how to tame the latest features and functions, and find loads of

  20. NUnit Pocket Reference

    CERN Document Server

    Hamilton, Bill

    2009-01-01

    The open source NUnit framework is an excellent way to test .NET code as it is written, saving hundreds of QA hours and headaches. Unfortunately, some of those hours saved can be wasted trying to master this popular but under-documented framework. Proof that good things come in small packages, the NUnit Pocket Reference is everything you need to get NUnit up and working for you. It's the only book you'll need on this popular and practical new open source framework.

  1. Coal Data: A reference

    International Nuclear Information System (INIS)

    1991-01-01

    The purpose of Coal Data: A Reference is to provide basic information on the mining and use of coal, an important source of energy in the United States. The report is written for a general audience. The goal is to cover basic material and strike a reasonable compromise between overly generalized statements and detailed analyses. The section ''Coal Terminology and Related Information'' provides additional information about terms mentioned in the text and introduces new terms. Topics covered are US coal deposits, resources and reserves, mining, production, employment and productivity, health and safety, preparation, transportation, supply and stocks, use, coal, the environment, and more. (VC)

  2. A novel word spotting method based on recurrent neural networks.

    Science.gov (United States)

    Frinken, Volkmar; Fischer, Andreas; Manmatha, R; Bunke, Horst

    2012-02-01

    Keyword spotting refers to the process of retrieving all instances of a given keyword from a document. In the present paper, a novel keyword spotting method for handwritten documents is described. It is derived from a neural network-based system for unconstrained handwriting recognition. As such it performs template-free spotting, i.e., it is not necessary for a keyword to appear in the training set. The keyword spotting is done using a modification of the CTC Token Passing algorithm in conjunction with a recurrent neural network. We demonstrate that the proposed systems outperform not only a classical dynamic time warping-based approach but also a modern keyword spotting system, based on hidden Markov models. Furthermore, we analyze the performance of the underlying neural networks when using them in a recognition task followed by keyword spotting on the produced transcription. We point out the advantages of keyword spotting when compared to classic text line recognition.

  3. Roaming Reference: Reinvigorating Reference through Point of Need Service

    Directory of Open Access Journals (Sweden)

    Kealin M. McCabe

    2011-11-01

    Full Text Available Roaming reference service was pursued as a way to address declining reference statistics. The service was staffed by librarians armed with iPads over a period of six months during the 2010-2011 academic year. Transactional statistics were collected in relation to query type (Research, Facilitative or Technology, location and approach (librarian to patron, patron to librarian or via chat widget. Overall, roaming reference resulted in an additional 228 reference questions, 67% (n=153 of which were research related. Two iterations of the service were implemented, roaming reference as a standalone service (Fall 2010 and roaming reference integrated with traditional reference desk duties (Winter 2011. The results demonstrate that although the Weller Library’s reference transactions are declining annually, they are not disappearing. For a roaming reference service to succeed, it must be a standalone service provided in addition to traditional reference services. The integration of the two reference models (roaming reference and reference desk resulted in a 56% decline in the total number of roaming reference questions from the previous term. The simple act of roaming has the potential to reinvigorate reference services as a whole, forcing librarians outside their comfort zones, allowing them to reach patrons at their point of need.

  4. AREVA - 2013 Reference document

    International Nuclear Information System (INIS)

    2014-01-01

    This Reference Document contains information on the AREVA group's objectives, prospects and development strategies, as well as estimates of the markets, market shares and competitive position of the AREVA group. Content: 1 - Person responsible for the Reference Document; 2 - Statutory auditors; 3 - Selected financial information; 4 - Description of major risks confronting the company; 5 - Information about the issuer; 6 - Business overview; 7 - Organizational structure; 8 - Property, plant and equipment; 9 - Situation and activities of the company and its subsidiaries; 10 - Capital resources; 11 - Research and development programs, patents and licenses; 12 - Trend information; 13 - Profit forecasts or estimates; 14 - Management and supervisory bodies; 15 - Compensation and benefits; 16 - Functioning of the management and supervisory bodies; 17 - Human resources information; 18 - Principal shareholders; 19 - Transactions with related parties; 20 - Financial information concerning assets, financial positions and financial performance; 21 - Additional information; 22 - Major contracts; 23 - Third party information, statements by experts and declarations of interest; 24 - Documents on display; 25 - Information on holdings; Appendix 1: report of the supervisory board chairman on the preparation and organization of the board's activities and internal control procedures; Appendix 2: statutory auditors' reports; Appendix 3: environmental report; Appendix 4: non-financial reporting methodology and independent third-party report on social, environmental and societal data; Appendix 5: ordinary and extraordinary general shareholders' meeting; Appendix 6: values charter; Appendix 7: table of concordance of the management report; glossaries

  5. Balinese Frame of Reference

    Directory of Open Access Journals (Sweden)

    I Nyoman Aryawibawa

    2016-04-01

    Full Text Available Abstract: Balinese Frame of Reference. Wassmann and Dasen (1998 did a study on the acquisition of Balinese frames of reference. They pointed out that, in addition to the dominant use of absolute system, the use of relative system was also observed. This article aims at verifying Wassmann and Dasen’ study. Employing monolingual Balinese speakers and using linguistic and non-linguistic tasks, Aryawibawa (2010, 2012, 2015 showed that Balinese subjects used an absolute system dominantly in responding the two tasks, e.g. The man is north/south/east/west of the car. Unlike Wassmann and Dasen’s results, no relative system was used by the subjects in solving the tasks. Instead of the relative system, an intrinsic system was also observed in this study, even though it was unfrequent. The article concludes that the absolute system was dominantly employed by Balinese speakers in describing spatial relations in Balinese. The use of the system seems to affect their cognitive functions.

  6. Antares Reference Telescope System

    International Nuclear Information System (INIS)

    Viswanathan, V.K.; Kaprelian, E.; Swann, T.; Parker, J.; Wolfe, P.; Woodfin, G.; Knight, D.

    1983-01-01

    Antares is a 24-beam, 40-TW carbon-dioxide laser-fusion system currently nearing completion at the Los Alamos National Laboratory. The 24 beams will be focused onto a tiny target (typically 300 to 1000 μm in diameter) located approximately at the center of a 7.3-m-diameter by 9.3-m-long vacuum (10 - 6 torr) chamber. The design goal is to position the targets to within 10 μm of a selected nominal position, which may be anywhere within a fixed spherical region 1 cm in diameter. The Antares Reference Telescope System is intended to help achieve this goal for alignment and viewing of the various targets used in the laser system. The Antares Reference Telescope System consists of two similar electro-optical systems positioned in a near orthogonal manner in the target chamber area of the laser. Each of these consists of four subsystems: (1) a fixed 9X optical imaging subsystem which produces an image of the target at the vidicon; (2) a reticle projection subsystem which superimposes an image of the reticle pattern at the vidicon; (3) an adjustable front-lighting subsystem which illuminates the target; and (4) an adjustable back-lighting subsystem which also can be used to illuminate the target. The various optical, mechanical, and vidicon design considerations and trade-offs are discussed. The final system chosen (which is being built) and its current status are described in detail

  7. Neural correlates of executive functions in patients with obesity.

    Science.gov (United States)

    Ho, Ming-Chou; Chen, Vincent Chin-Hung; Chao, Seh-Huang; Fang, Ching-Tzu; Liu, Yi-Chun; Weng, Jun-Cheng

    2018-01-01

    Obesity is one of the most challenging problems in human health and is recognized as an important risk factor for many chronic diseases. It remains unclear how the neural systems (e.g., the mesolimbic "reward" and the prefrontal "control" neural systems) are correlated with patients' executive function (EF), conceptualized as the integration of "cool" EF and "hot" EF. "Cool" EF refers to relatively abstract, non-affective operations such as inhibitory control and mental flexibility. "Hot" EF refers to motivationally significant affective operations such as affective decision-making. We tried to find the correlation between structural and functional neuroimaging indices and EF in obese patients. The study population comprised seventeen patients with obesity (seven males and 10 females, BMI = 37.99 ± 5.40, age = 31.82 ± 8.75 year-old) preparing to undergo bariatric surgery. We used noninvasive diffusion tensor imaging, generalized q-sampling imaging, and resting-state functional magnetic resonance imaging to examine the neural correlations between structural and functional neuroimaging indices and EF performances in patients with obesity. We reported that many brain areas are correlated to the patients' EF performances. More interestingly, some correlations may implicate the possible associations of EF and the incentive motivational effects of food. The neural correlation between the left precuneus and middle occipital gyrus and inhibitory control may suggest that patients with a better ability to detect appetitive food may have worse inhibitory control. Also, the neural correlation between the superior frontal blade and affective decision-making may suggest that patients' affective decision-making may be associated with the incentive motivational effects of food. Our results provide evidence suggesting neural correlates of EF in patients with obesity.

  8. Sacred Space.

    Science.gov (United States)

    Adelstein, Pamela

    2018-01-01

    A space can be sacred, providing those who inhabit a particular space with sense of transcendence-being connected to something greater than oneself. The sacredness may be inherent in the space, as for a religious institution or a serene place outdoors. Alternatively, a space may be made sacred by the people within it and events that occur there. As medical providers, we have the opportunity to create sacred space in our examination rooms and with our patient interactions. This sacred space can be healing to our patients and can bring us providers opportunities for increased connection, joy, and gratitude in our daily work.

  9. Sensor employing internal reference electrode

    DEFF Research Database (Denmark)

    2013-01-01

    The present invention concerns a novel internal reference electrode as well as a novel sensing electrode for an improved internal reference oxygen sensor and the sensor employing same.......The present invention concerns a novel internal reference electrode as well as a novel sensing electrode for an improved internal reference oxygen sensor and the sensor employing same....

  10. Endogenizing Prospect Theory's Reference Point

    OpenAIRE

    Ulrich Schmidt; Horst Zank

    2010-01-01

    In previous models of (cumulative) prospect theory reference-dependence of preferences is imposed beforehand and the location of the reference point is exogenously determined. This note provides a foundation of prospect theory, where reference-dependence is derived from preference conditions and a unique reference point arises endogenously.

  11. Neural Synchronization and Cryptography

    Science.gov (United States)

    Ruttor, Andreas

    2007-11-01

    Neural networks can synchronize by learning from each other. In the case of discrete weights full synchronization is achieved in a finite number of steps. Additional networks can be trained by using the inputs and outputs generated during this process as examples. Several learning rules for both tasks are presented and analyzed. In the case of Tree Parity Machines synchronization is much faster than learning. Scaling laws for the number of steps needed for full synchronization and successful learning are derived using analytical models. They indicate that the difference between both processes can be controlled by changing the synaptic depth. In the case of bidirectional interaction the synchronization time increases proportional to the square of this parameter, but it grows exponentially, if information is transmitted in one direction only. Because of this effect neural synchronization can be used to construct a cryptographic key-exchange protocol. Here the partners benefit from mutual interaction, so that a passive attacker is usually unable to learn the generated key in time. The success probabilities of different attack methods are determined by numerical simulations and scaling laws are derived from the data. They show that the partners can reach any desired level of security by just increasing the synaptic depth. Then the complexity of a successful attack grows exponentially, but there is only a polynomial increase of the effort needed to generate a key. Further improvements of security are possible by replacing the random inputs with queries generated by the partners.

  12. Neural Networks for Optimal Control

    DEFF Research Database (Denmark)

    Sørensen, O.

    1995-01-01

    Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....

  13. Neural networks at the Tevatron

    International Nuclear Information System (INIS)

    Badgett, W.; Burkett, K.; Campbell, M.K.; Wu, D.Y.; Bianchin, S.; DeNardi, M.; Pauletta, G.; Santi, L.; Caner, A.; Denby, B.; Haggerty, H.; Lindsey, C.S.; Wainer, N.; Dall'Agata, M.; Johns, K.; Dickson, M.; Stanco, L.; Wyss, J.L.

    1992-10-01

    This paper summarizes neural network applications at the Fermilab Tevatron, including the first online hardware application in high energy physics (muon tracking): the CDF and DO neural network triggers; offline quark/gluon discrimination at CDF; ND a new tool for top to multijets recognition at CDF

  14. Neural Networks for the Beginner.

    Science.gov (United States)

    Snyder, Robin M.

    Motivated by the brain, neural networks are a right-brained approach to artificial intelligence that is used to recognize patterns based on previous training. In practice, one would not program an expert system to recognize a pattern and one would not train a neural network to make decisions from rules; but one could combine the best features of…

  15. Concepts of space the history of theories of space in physics

    CERN Document Server

    Jammer, Max

    1993-01-01

    Historical surveys consider Judeo-Christian notions of space, Newtonian absolute space, perceptions from 18th century to the present, more. Numerous quotations and references. "Admirably compact and swiftly paced style." - Philosophy of Science.

  16. Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

    Science.gov (United States)

    Li, Zhijun; Su, Chun-Yi

    2013-09-01

    In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.

  17. Reference Specifications for SAVOIR Avionics Elements

    Science.gov (United States)

    Hult, Torbjorn; Lindskog, Martin; Roques, Remi; Planche, Luc; Brunjes, Bernhard; Dellandrea, Brice; Terraillon, Jean-Loup

    2012-08-01

    Space industry and Agencies have been recognizing already for quite some time the need to raise the level of standardisation in the spacecraft avionics systems in order to increase efficiency and reduce development cost and schedule. This also includes the aspect of increasing competition in global space business, which is a challenge that European space companies are facing at all stages of involvement in the international markets.A number of initiatives towards this vision are driven both by the industry and ESA’s R&D programmes. However, today an intensified coordination of these activities is required in order to achieve the necessary synergy and to ensure they converge towards the shared vision. It has been proposed to federate these initiatives under the common Space Avionics Open Interface Architecture (SAVOIR) initiative. Within this initiative, the approach based on reference architectures and building blocks plays a key role.Following the principles outlined above, the overall goal of the SAVOIR is to establish a streamlined onboard architecture in order to standardize the development of avionics systems for space programmes. This reflects the need to increase efficiency and cost-effectiveness in the development process as well as account the trend towards more functionality implemented by the onboard building blocks, i.e. HW and SW components, and more complexity for the overall space mission objectives.

  18. A Novel Handwritten Letter Recognizer Using Enhanced Evolutionary Neural Network

    Science.gov (United States)

    Mahmoudi, Fariborz; Mirzashaeri, Mohsen; Shahamatnia, Ehsan; Faridnia, Saed

    This paper introduces a novel design for handwritten letter recognition by employing a hybrid back-propagation neural network with an enhanced evolutionary algorithm. Feeding the neural network consists of a new approach which is invariant to translation, rotation, and scaling of input letters. Evolutionary algorithm is used for the global search of the search space and the back-propagation algorithm is used for the local search. The results have been computed by implementing this approach for recognizing 26 English capital letters in the handwritings of different people. The computational results show that the neural network reaches very satisfying results with relatively scarce input data and a promising performance improvement in convergence of the hybrid evolutionary back-propagation algorithms is exhibited.

  19. Feed forward neural networks modeling for K-P interactions

    International Nuclear Information System (INIS)

    El-Bakry, M.Y.

    2003-01-01

    Artificial intelligence techniques involving neural networks became vital modeling tools where model dynamics are difficult to track with conventional techniques. The paper make use of the feed forward neural networks (FFNN) to model the charged multiplicity distribution of K-P interactions at high energies. The FFNN was trained using experimental data for the multiplicity distributions at different lab momenta. Results of the FFNN model were compared to that generated using the parton two fireball model and the experimental data. The proposed FFNN model results showed good fitting to the experimental data. The neural network model performance was also tested at non-trained space and was found to be in good agreement with the experimental data

  20. Neural-fuzzy control of adept one SCARA

    International Nuclear Information System (INIS)

    Er, M.J.; Toh, B.H.; Toh, B.Y.

    1998-01-01

    This paper presents an Intelligent Control Strategy for the Adept One SCARA (Selective Compliance Assembly Robot Arm). It covers the design and simulation study of a Neural-Fuzzy Controller (NFC) for the SCARA with a view of tracking a predetermined trajectory of motion in the joint space. The SCARA was simulated as a three-axis manipulator with the dynamics of the tool (fourth link) neglected and the mass of the load incorporated into the mass of the third link. The overall performance of the control system under different conditions, namely variation in playload, variations in coefficients of static, dynamic and viscous friction and different trajectories were studied and comparison made with an existing Neural Network Controller and two Computed Torque Controllers. The NFC was shown to be robust and is able to overcome the drawback of the existing Neural Network Controller

  1. AREVA 2009 reference document

    International Nuclear Information System (INIS)

    2009-01-01

    This Reference Document contains information on the AREVA group's objectives, prospects and development strategies. It contains information on the markets, market shares and competitive position of the AREVA group. This information provides an adequate picture of the size of these markets and of the AREVA group's competitive position. Content: 1 - Person responsible for the Reference Document and Attestation by the person responsible for the Reference Document; 2 - Statutory and Deputy Auditors; 3 - Selected financial information; 4 - Risks: Risk management and coverage, Legal risk, Industrial and environmental risk, Operating risk, Risk related to major projects, Liquidity and market risk, Other risk; 5 - Information about the issuer: History and development, Investments; 6 - Business overview: Markets for nuclear power and renewable energies, AREVA customers and suppliers, Overview and strategy of the group, Business divisions, Discontinued operations: AREVA Transmission and Distribution; 7 - Organizational structure; 8 - Property, plant and equipment: Principal sites of the AREVA group, Environmental issues that may affect the issuer's; 9 - Analysis of and comments on the group's financial position and performance: Overview, Financial position, Cash flow, Statement of financial position, Events subsequent to year-end closing for 2009; 10 - Capital Resources; 11 - Research and development programs, patents and licenses; 12 -trend information: Current situation, Financial objectives; 13 - Profit forecasts or estimates; 14 - Administrative, management and supervisory bodies and senior management; 15 - Compensation and benefits; 16 - Functioning of corporate bodies; 17 - Employees; 18 - Principal shareholders; 19 - Transactions with related parties: French state, CEA, EDF group; 20 - Financial information concerning assets, financial positions and financial performance; 21 - Additional information: Share capital, Certificate of incorporation and by-laws; 22 - Major

  2. Stochastic Nonlinear Evolutional Model of the Large-Scaled Neuronal Population and Dynamic Neural Coding Subject to Stimulation

    International Nuclear Information System (INIS)

    Wang Rubin; Yu Wei

    2005-01-01

    In this paper, we investigate how the population of neuronal oscillators deals with information and the dynamic evolution of neural coding when the external stimulation acts on it. Numerically computing method is used to describe the evolution process of neural coding in three-dimensioned space. The numerical result proves that only the suitable stimulation can change the coupling structure and plasticity of neurons

  3. Neural fields theory and applications

    CERN Document Server

    Graben, Peter; Potthast, Roland; Wright, James

    2014-01-01

    With this book, the editors present the first comprehensive collection in neural field studies, authored by leading scientists in the field - among them are two of the founding-fathers of neural field theory. Up to now, research results in the field have been disseminated across a number of distinct journals from mathematics, computational neuroscience, biophysics, cognitive science and others. Starting with a tutorial for novices in neural field studies, the book comprises chapters on emergent patterns, their phase transitions and evolution, on stochastic approaches, cortical development, cognition, robotics and computation, large-scale numerical simulations, the coupling of neural fields to the electroencephalogram and phase transitions in anesthesia. The intended readership are students and scientists in applied mathematics, theoretical physics, theoretical biology, and computational neuroscience. Neural field theory and its applications have a long-standing tradition in the mathematical and computational ...

  4. Artificial neural networks in NDT

    International Nuclear Information System (INIS)

    Abdul Aziz Mohamed

    2001-01-01

    Artificial neural networks, simply known as neural networks, have attracted considerable interest in recent years largely because of a growing recognition of the potential of these computational paradigms as powerful alternative models to conventional pattern recognition or function approximation techniques. The neural networks approach is having a profound effect on almost all fields, and has been utilised in fields Where experimental inter-disciplinary work is being carried out. Being a multidisciplinary subject with a broad knowledge base, Nondestructive Testing (NDT) or Nondestructive Evaluation (NDE) is no exception. This paper explains typical applications of neural networks in NDT/NDE. Three promising types of neural networks are highlighted, namely, back-propagation, binary Hopfield and Kohonen's self-organising maps. (Author)

  5. Short-Term Load Forecasting Model Based on Quantum Elman Neural Networks

    Directory of Open Access Journals (Sweden)

    Zhisheng Zhang

    2016-01-01

    Full Text Available Short-term load forecasting model based on quantum Elman neural networks was constructed in this paper. The quantum computation and Elman feedback mechanism were integrated into quantum Elman neural networks. Quantum computation can effectively improve the approximation capability and the information processing ability of the neural networks. Quantum Elman neural networks have not only the feedforward connection but also the feedback connection. The feedback connection between the hidden nodes and the context nodes belongs to the state feedback in the internal system, which has formed specific dynamic memory performance. Phase space reconstruction theory is the theoretical basis of constructing the forecasting model. The training samples are formed by means of K-nearest neighbor approach. Through the example simulation, the testing results show that the model based on quantum Elman neural networks is better than the model based on the quantum feedforward neural network, the model based on the conventional Elman neural network, and the model based on the conventional feedforward neural network. So the proposed model can effectively improve the prediction accuracy. The research in the paper makes a theoretical foundation for the practical engineering application of the short-term load forecasting model based on quantum Elman neural networks.

  6. Racial bias in neural empathic responses to pain.

    Directory of Open Access Journals (Sweden)

    Luis Sebastian Contreras-Huerta

    Full Text Available Recent studies have shown that perceiving the pain of others activates brain regions in the observer associated with both somatosensory and affective-motivational aspects of pain, principally involving regions of the anterior cingulate and anterior insula cortex. The degree of these empathic neural responses is modulated by racial bias, such that stronger neural activation is elicited by observing pain in people of the same racial group compared with people of another racial group. The aim of the present study was to examine whether a more general social group category, other than race, could similarly modulate neural empathic responses and perhaps account for the apparent racial bias reported in previous studies. Using a minimal group paradigm, we assigned participants to one of two mixed-race teams. We use the term race to refer to the Chinese or Caucasian appearance of faces and whether the ethnic group represented was the same or different from the appearance of the participant' own face. Using fMRI, we measured neural empathic responses as participants observed members of their own group or other group, and members of their own race or other race, receiving either painful or non-painful touch. Participants showed clear group biases, with no significant effect of race, on behavioral measures of implicit (affective priming and explicit group identification. Neural responses to observed pain in the anterior cingulate cortex, insula cortex, and somatosensory areas showed significantly greater activation when observing pain in own-race compared with other-race individuals, with no significant effect of minimal groups. These results suggest that racial bias in neural empathic responses is not influenced by minimal forms of group categorization, despite the clear association participants showed with in-group more than out-group members. We suggest that race may be an automatic and unconscious mechanism that drives the initial neural responses to

  7. Racial Bias in Neural Empathic Responses to Pain

    Science.gov (United States)

    Contreras-Huerta, Luis Sebastian; Baker, Katharine S.; Reynolds, Katherine J.; Batalha, Luisa; Cunnington, Ross

    2013-01-01

    Recent studies have shown that perceiving the pain of others activates brain regions in the observer associated with both somatosensory and affective-motivational aspects of pain, principally involving regions of the anterior cingulate and anterior insula cortex. The degree of these empathic neural responses is modulated by racial bias, such that stronger neural activation is elicited by observing pain in people of the same racial group compared with people of another racial group. The aim of the present study was to examine whether a more general social group category, other than race, could similarly modulate neural empathic responses and perhaps account for the apparent racial bias reported in previous studies. Using a minimal group paradigm, we assigned participants to one of two mixed-race teams. We use the term race to refer to the Chinese or Caucasian appearance of faces and whether the ethnic group represented was the same or different from the appearance of the participant' own face. Using fMRI, we measured neural empathic responses as participants observed members of their own group or other group, and members of their own race or other race, receiving either painful or non-painful touch. Participants showed clear group biases, with no significant effect of race, on behavioral measures of implicit (affective priming) and explicit group identification. Neural responses to observed pain in the anterior cingulate cortex, insula cortex, and somatosensory areas showed significantly greater activation when observing pain in own-race compared with other-race individuals, with no significant effect of minimal groups. These results suggest that racial bias in neural empathic responses is not influenced by minimal forms of group categorization, despite the clear association participants showed with in-group more than out-group members. We suggest that race may be an automatic and unconscious mechanism that drives the initial neural responses to observed pain in

  8. 14 CFR 221.200 - Content and explanation of abbreviations, reference marks and symbols.

    Science.gov (United States)

    2010-01-01

    ..., reference marks and symbols. 221.200 Section 221.200 Aeronautics and Space OFFICE OF THE SECRETARY... § 221.200 Content and explanation of abbreviations, reference marks and symbols. (a) Content. The format..., reference marks and symbols. Abbreviations, reference marks and symbols which are used in the tariff shall...

  9. Areva - 2016 Reference document

    International Nuclear Information System (INIS)

    2017-01-01

    Areva supplies high added-value products and services to support the operation of the global nuclear fleet. The company is present throughout the entire nuclear cycle, from uranium mining to used fuel recycling, including nuclear reactor design and operating services. Areva is recognized by utilities around the world for its expertise, its skills in cutting-edge technologies and its dedication to the highest level of safety. Areva's 36,000 employees are helping build tomorrow's energy model: supplying ever safer, cleaner and more economical energy to the greatest number of people. This Reference Document contains information on Areva's objectives, prospects and development strategies. It contains estimates of the markets, market shares and competitive position of Areva

  10. A reference tristimulus colorimeter

    Science.gov (United States)

    Eppeldauer, George P.

    2002-06-01

    A reference tristimulus colorimeter has been developed at NIST with a transmission-type silicon trap detector (1) and four temperature-controlled filter packages to realize the Commission Internationale de l'Eclairage (CIE) x(λ), y(λ) and z(λ) color matching functions (2). Instead of lamp standards, high accuracy detector standards are used for the colorimeter calibration. A detector-based calibration procedure is being suggested for tristimulus colorimeters wehre the absolute spectral responsivity of the tristimulus channels is determined. Then, color (spectral) correct and peak (amplitude) normalization are applied to minimize uncertainties caused by the imperfect realizations of the CIE functions. As a result of the corrections, the chromaticity coordinates of stable light sources with different spectral power distributions can be measured with uncertainties less than 0.0005 (k=1).

  11. Tank characterization reference guide

    International Nuclear Information System (INIS)

    De Lorenzo, D.S.; DiCenso, A.T.; Hiller, D.B.; Johnson, K.W.; Rutherford, J.H.; Smith, D.J.; Simpson, B.C.

    1994-09-01

    Characterization of the Hanford Site high-level waste storage tanks supports safety issue resolution; operations and maintenance requirements; and retrieval, pretreatment, vitrification, and disposal technology development. Technical, historical, and programmatic information about the waste tanks is often scattered among many sources, if it is documented at all. This Tank Characterization Reference Guide, therefore, serves as a common location for much of the generic tank information that is otherwise contained in many documents. The report is intended to be an introduction to the issues and history surrounding the generation, storage, and management of the liquid process wastes, and a presentation of the sampling, analysis, and modeling activities that support the current waste characterization. This report should provide a basis upon which those unfamiliar with the Hanford Site tank farms can start their research

  12. Neural basis of individualistic and collectivistic views of self.

    Science.gov (United States)

    Chiao, Joan Y; Harada, Tokiko; Komeda, Hidetsugu; Li, Zhang; Mano, Yoko; Saito, Daisuke; Parrish, Todd B; Sadato, Norihiro; Iidaka, Tetsuya

    2009-09-01

    Individualism and collectivism refer to cultural values that influence how people construe themselves and their relation to the world. Individualists perceive themselves as stable entities, autonomous from other people and their environment, while collectivists view themselves as dynamic entities, continually defined by their social context and relationships. Despite rich understanding of how individualism and collectivism influence social cognition at a behavioral level, little is known about how these cultural values modulate neural representations underlying social cognition. Using cross-cultural functional magnetic resonance imaging (fMRI), we examined whether the cultural values of individualism and collectivism modulate neural activity within medial prefrontal cortex (MPFC) during processing of general and contextual self judgments. Here, we show that neural activity within the anterior rostral portion of the MPFC during processing of general and contextual self judgments positively predicts how individualistic or collectivistic a person is across cultures. These results reveal two kinds of neural representations of self (eg, a general self and a contextual self) within MPFC and demonstrate how cultural values of individualism and collectivism shape these neural representations. 2008 Wiley-Liss, Inc.

  13. Realistic thermodynamic and statistical-mechanical measures for neural synchronization.

    Science.gov (United States)

    Kim, Sang-Yoon; Lim, Woochang

    2014-04-15

    Synchronized brain rhythms, associated with diverse cognitive functions, have been observed in electrical recordings of brain activity. Neural synchronization may be well described by using the population-averaged global potential VG in computational neuroscience. The time-averaged fluctuation of VG plays the role of a "thermodynamic" order parameter O used for describing the synchrony-asynchrony transition in neural systems. Population spike synchronization may be well visualized in the raster plot of neural spikes. The degree of neural synchronization seen in the raster plot is well measured in terms of a "statistical-mechanical" spike-based measure Ms introduced by considering the occupation and the pacing patterns of spikes. The global potential VG is also used to give a reference global cycle for the calculation of Ms. Hence, VG becomes an important collective quantity because it is associated with calculation of both O and Ms. However, it is practically difficult to directly get VG in real experiments. To overcome this difficulty, instead of VG, we employ the instantaneous population spike rate (IPSR) which can be obtained in experiments, and develop realistic thermodynamic and statistical-mechanical measures, based on IPSR, to make practical characterization of the neural synchronization in both computational and experimental neuroscience. Particularly, more accurate characterization of weak sparse spike synchronization can be achieved in terms of realistic statistical-mechanical IPSR-based measure, in comparison with the conventional measure based on VG. Copyright © 2014. Published by Elsevier B.V.

  14. Areva, reference document 2006

    International Nuclear Information System (INIS)

    2006-01-01

    This reference document contains information on the AREVA group's objectives, prospects and development strategies, particularly in Chapters 4 and 7. It contains information on the markets, market shares and competitive position of the AREVA group. Content: - 1 Person responsible for the reference document and persons responsible for auditing the financial statements; - 2 Information pertaining to the transaction (Not applicable); - 3 General information on the company and its share capital: Information on AREVA, on share capital and voting rights, Investment certificate trading, Dividends, Organization chart of AREVA group companies, Equity interests, Shareholders' agreements; - 4 Information on company operations, new developments and future prospects: Overview and strategy of the AREVA group, The Nuclear Power and Transmission and Distribution markets, The energy businesses of the AREVA group, Front End division, Reactors and Services division, Back End division, Transmission and Distribution division, Major contracts, The principal sites of the AREVA group, AREVA's customers and suppliers, Sustainable Development and Continuous Improvement, Capital spending programs, Research and development programs, intellectual property and trademarks, Risk and insurance; - 5 Assets - Financial position - Financial performance: Analysis of and comments on the group's financial position and performance, 2006 Human Resources Report, Environmental Report, Consolidated financial statements, Notes to the consolidated financial statements, AREVA SA financial statements, Notes to the corporate financial statements; 6 - Corporate Governance: Composition and functioning of corporate bodies, Executive compensation, Profit-sharing plans, AREVA Values Charter, Annual Combined General Meeting of Shareholders of May 3, 2007; 7 - Recent developments and future prospects: Events subsequent to year-end closing for 2006, Outlook; 8 - Glossary; 9 - Table of concordance

  15. Areva reference document 2007

    International Nuclear Information System (INIS)

    2008-01-01

    This reference document contains information on the AREVA group's objectives, prospects and development strategies, particularly in Chapters 4 and 7. It contains also information on the markets, market shares and competitive position of the AREVA group. Content: 1 - Person responsible for the reference document and persons responsible for auditing the financial statements; 2 - Information pertaining to the transaction (not applicable); 3 - General information on the company and its share capital: Information on Areva, Information on share capital and voting rights, Investment certificate trading, Dividends, Organization chart of AREVA group companies, Equity interests, Shareholders' agreements; 4 - Information on company operations, new developments and future prospects: Overview and strategy of the AREVA group, The Nuclear Power and Transmission and Distribution markets, The energy businesses of the AREVA group, Front End division, Reactors and Services division, Back End division, Transmission and Distribution division, Major contracts 140 Principal sites of the AREVA group, AREVA's customers and suppliers, Sustainable Development and Continuous Improvement, Capital spending programs, Research and Development programs, Intellectual Property and Trademarks, Risk and insurance; 5 - Assets financial position financial performance: Analysis of and comments on the group's financial position and performance, Human Resources report, Environmental report, Consolidated financial statements 2007, Notes to the consolidated financial statements, Annual financial statements 2007, Notes to the corporate financial statements; 6 - Corporate governance: Composition and functioning of corporate bodies, Executive compensation, Profit-sharing plans, AREVA Values Charter, Annual Ordinary General Meeting of Shareholders of April 17, 2008; 7 - Recent developments and future prospects: Events subsequent to year-end closing for 2007, Outlook; Glossary; table of concordance

  16. Kontrol Kecepatan Motor Induksi menggunakan Algoritma Backpropagation Neural Network

    Directory of Open Access Journals (Sweden)

    MUHAMMAD RUSWANDI DJALAL

    2017-07-01

    Full Text Available ABSTRAKBanyak strategi kontrol berbasis kecerdasan buatan telah diusulkan dalam penelitian seperti Fuzzy Logic dan Artificial Neural Network (ANN. Tujuan dari penelitian ini adalah untuk mendesain sebuah kontrol agar kecepatan motor induksi dapat diatur sesuai kebutuhan serta membandingkan kinerja motor induksi tanpa kontrol dan dengan kontrol. Dalam penelitian ini diusulkan sebuah metode artificial neural network untuk mengontrol kecepatan motor induksi tiga fasa. Kecepatan referensi motor diatur pada kecepatan 140 rad/s, 150 rad/s, dan 130 rad/s. Perubahan kecepatan diatur pada setiap interval 0.3 detik dan waktu simulasi maksimum adalah 0,9 detik. Kasus 1 tanpa kontrol, menunjukkan respon torka dan kecepatan dari motor induksi tiga fasa tanpa kontrol. Meskipun kecepatan motor induksi tiga fasa diatur berubah pada setiap 0,3 detik tidak akan mempengaruhi torka. Selain itu, motor induksi tiga fasa tanpa kontrol memiliki kinerja yang buruk dikarenakan kecepatan motor induksi tidak dapat diatur sesuai dengan kebutuhan. Kasus 2 dengan control backpropagation neural network, meskipun kecepatan motor induksi tiga fasa berubah pada setiap 0.3 detik tidak akan mempengaruhi torsi. Selain itu, kontrol backpropagation neural network memiliki kinerja yang baik dikarenakan kecepatan motor induksi dapat diatur sesuai dengan kebutuhan.Kata kunci: Backpropagation Neural Network (BPNN, NN Training, NN Testing, Motor.ABSTRACTMany artificial intelligence-based control strategies have been proposed in research such as Fuzzy Logic and Artificial Neural Network (ANN. The purpose of this research was design a control for the induction motor speed that could be adjusted as needed and compare the performance of induction motor without control and with control. In this research, it was proposed an artificial neural network method to control the speed of three-phase induction motors. The reference speed of motor was set at the rate of 140 rad / s, 150 rad / s, and 130

  17. Neural systems for tactual memories.

    Science.gov (United States)

    Bonda, E; Petrides, M; Evans, A

    1996-04-01

    1. The aim of this study was to investigate the neural systems involved in the memory processing of experiences through touch. 2. Regional cerebral blood flow was measured with positron emission tomography by means of the water bolus H2(15)O methodology in human subjects as they performed tasks involving different levels of tactual memory. In one of the experimental tasks, the subjects had to palpate nonsense shapes to match each one to a previously learned set, thus requiring constant reference to long-term memory. The other experimental task involved judgements of the recent recurrence of shapes during the scanning period. A set of three control tasks was used to control for the type of exploratory movements and sensory processing inherent in the two experimental tasks. 3. Comparisons of the distribution of activity between the experimental and the control tasks were carried out by means of the subtraction method. In relation to the control conditions, the two experimental tasks requiring memory resulted in significant changes within the posteroventral insula and the central opercular region. In addition, the task requiring recall from long-term memory yielded changes in the perirhinal cortex. 4. The above findings demonstrated that a ventrally directed parietoinsular pathway, leading to the posteroventral insula and the perirhinal cortex, constitutes a system by which long-lasting representations of tactual experiences are formed. It is proposed that the posteroventral insula is involved in tactual feature analysis, by analogy with the similar role of the inferotemporal cortex in vision, whereas the perirhinal cortex is further involved in the integration of these features into long-lasting representations of somatosensory experiences.

  18. PID Neural Network Based Speed Control of Asynchronous Motor Using Programmable Logic Controller

    Directory of Open Access Journals (Sweden)

    MARABA, V. A.

    2011-11-01

    Full Text Available This paper deals with the structure and characteristics of PID Neural Network controller for single input and single output systems. PID Neural Network is a new kind of controller that includes the advantages of artificial neural networks and classic PID controller. Functioning of this controller is based on the update of controller parameters according to the value extracted from system output pursuant to the rules of back propagation algorithm used in artificial neural networks. Parameters obtained from the application of PID Neural Network training algorithm on the speed model of the asynchronous motor exhibiting second order linear behavior were used in the real time speed control of the motor. Programmable logic controller (PLC was used as real time controller. The real time control results show that reference speed successfully maintained under various load conditions.

  19. Oscillatory activity reflects differential use of spatial reference frames by sighted and blind individuals in tactile attention.

    Science.gov (United States)

    Schubert, Jonathan T W; Buchholz, Verena N; Föcker, Julia; Engel, Andreas K; Röder, Brigitte; Heed, Tobias

    2015-08-15

    Touch can be localized either on the skin in anatomical coordinates, or, after integration with posture, in external space. Sighted individuals are thought to encode touch in both coordinate systems concurrently, whereas congenitally blind individuals exhibit a strong bias for using anatomical coordinates. We investigated the neural correlates of this differential dominance in the use of anatomical and external reference frames by assessing oscillatory brain activity during a tactile spatial attention task. The EEG was recorded while sighted and congenitally blind adults received tactile stimulation to uncrossed and crossed hands while detecting rare tactile targets at one cued hand only. In the sighted group, oscillatory alpha-band activity (8-12Hz) in the cue-target interval was reduced contralaterally and enhanced ipsilaterally with uncrossed hands. Hand crossing attenuated the degree of posterior parietal alpha-band lateralization, indicating that attention deployment was affected by external spatial coordinates. Beamforming suggested that this posture effect originated in the posterior parietal cortex. In contrast, cue-related lateralization of central alpha-band as well as of beta-band activity (16-24Hz) were unaffected by hand crossing, suggesting that these oscillations exclusively encode anatomical coordinates. In the blind group, central alpha-band activity was lateralized, but did not change across postures. The pattern of beta-band activity was indistinguishable between groups. Because the neural mechanisms for posterior alpha-band generation seem to be linked to developmental vision, we speculate that the lack of this neural mechanism in blind individuals is related to their preferred use of anatomical over external spatial codes in sensory processing. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. The perception of peripersonal space in right and left brain damage hemiplegic patients

    Directory of Open Access Journals (Sweden)

    Angela eBartolo

    2014-01-01

    Full Text Available Peripersonal space, as opposed to extrapersonal space, is the space that contains reachable objects and in which multisensory and sensorimotor integration is enhanced. Thus, the perception of peripersonal space requires combining information on the spatial properties of the environment with information on the current capacity to act. In support of this, recent studies have provided converging evidences that perceiving objects in peripersonal space activates a neural network overlapping with that subtending voluntary motor action and motor imagery. Other studies have also underlined the dominant role of the right hemisphere in motor planning and of the left hemisphere in on-line motor guiding, respectively. In the present study, we investigated the effect of a right or left hemiplegia in the perception of peripersonal space. 16 hemiplegic patients with brain damage to the left (LH or right (RH hemisphere and 8 matched healthy controls (HC performed a colour discrimination, a motor imagery and a reachability judgment task. Analyses of response times and accuracy revealed no variation among the three groups in the colour discrimination task, suggesting the absence of any specific perceptual or decisional deficits in the patient groups. In contrast, the patient groups revealed longer response times in the motor imagery task when performed in reference to the hemiplegic arm (RH and LH or to the healthy arm (RH. Moreover, RH group showed longer response times in the reachability judgement task, but only for stimuli located at the boundary of peripersonal space, which was furthermore significantly reduced in size. Considered together, these results confirm the crucial role of the motor system in motor imagery task and the perception of peripersonal space. They also revealed that right hemisphere damage has a more detrimental effect on reachability estimates, suggesting that motor planning processes contribute specifically to the perception of

  1. Space nuclear reactor safety

    International Nuclear Information System (INIS)

    Damon, D.; Temme, M.; Brown, N.

    1990-01-01

    Definition of safety requirements and design features of the SP-100 space reactor power system has been guided by a mission risk analysis. The analysis quantifies risk from accidental radiological consequences for a reference mission. Results show that the radiological risk from a space reactor can be made very low. The total mission risk from radiological consequences for a shuttle-launched, earth orbit SP-100 mission is estimated to be 0.05 Person-REM (expected values) based on a 1 mREM/yr de Minimus dose. Results are given for each mission phase. The safety benefits of specific design features are evaluated through risk sensitivity analyses

  2. Neural Representation. A Survey-Based Analysis of the Notion

    Directory of Open Access Journals (Sweden)

    Oscar Vilarroya

    2017-08-01

    Full Text Available The word representation (as in “neural representation”, and many of its related terms, such as to represent, representational and the like, play a central explanatory role in neuroscience literature. For instance, in “place cell” literature, place cells are extensively associated with their role in “the representation of space.” In spite of its extended use, we still lack a clear, universal and widely accepted view on what it means for a nervous system to represent something, on what makes a neural activity a representation, and on what is re-presented. The lack of a theoretical foundation and definition of the notion has not hindered actual research. My aim here is to identify how active scientists use the notion of neural representation, and eventually to list a set of criteria, based on actual use, that can help in distinguishing between genuine or non-genuine neural-representation candidates. In order to attain this objective, I present first the results of a survey of authors within two domains, place-cell and multivariate pattern analysis (MVPA research. Based on the authors’ replies, and on a review of neuroscientific research, I outline a set of common properties that an account of neural representation seems to require. I then apply these properties to assess the use of the notion in two domains of the survey, place-cell and MVPA studies. I conclude by exploring a shift in the notion of representation suggested by recent literature.

  3. The use of global image characteristics for neural network pattern recognitions

    Science.gov (United States)

    Kulyas, Maksim O.; Kulyas, Oleg L.; Loshkarev, Aleksey S.

    2017-04-01

    The recognition system is observed, where the information is transferred by images of symbols generated by a television camera. For descriptors of objects the coefficients of two-dimensional Fourier transformation generated in a special way. For solution of the task of classification the one-layer neural network trained on reference images is used. Fast learning of a neural network with a single neuron calculation of coefficients is applied.

  4. Chaos-based encryption keys and neural key-store for cloud-hosted data confidentiality

    CSIR Research Space (South Africa)

    Mosola, NN

    2017-09-01

    Full Text Available learning and cryptography, using neural networks. In their research, [7] proposes artificial intelligence techniques to invent cryptosystems to curb eavesdropping. The research proposes two artificial neural networks for develop a cryptographic... or UP. REFERENCES [1] A. Shawish and M. Salama, 2014. Cloud Computing: Paradigms and Technologies, F. Xhafa and N. Bessis (eds.), Inter-cooperative Collective Intelligence: Techniques and Applications, Studies in Computational Intelligence 495, DOI...

  5. Template-based procedures for neural network interpretation.

    Science.gov (United States)

    Alexander, J A.; Mozer, M C.

    1999-04-01

    Although neural networks often achieve impressive learning and generalization performance, their internal workings are typically all but impossible to decipher. This characteristic of the networks, their opacity, is one of the disadvantages of connectionism compared to more traditional, rule-oriented approaches to artificial intelligence. Without a thorough understanding of the network behavior, confidence in a system's results is lowered, and the transfer of learned knowledge to other processing systems - including humans - is precluded. Methods that address the opacity problem by casting network weights in symbolic terms are commonly referred to as rule extraction techniques. This work describes a principled approach to symbolic rule extraction from standard multilayer feedforward networks based on the notion of weight templates, parameterized regions of weight space corresponding to specific symbolic expressions. With an appropriate choice of representation, we show how template parameters may be efficiently identified and instantiated to yield the optimal match to the actual weights of a unit. Depending on the requirements of the application domain, the approach can accommodate n-ary disjunctions and conjunctions with O(k) complexity, simple n-of-m expressions with O(k(2)) complexity, or more general classes of recursive n-of-m expressions with O(k(L+2)) complexity, where k is the number of inputs to an unit and L the recursion level of the expression class. Compared to other approaches in the literature, our method of rule extraction offers benefits in simplicity, computational performance, and overall flexibility. Simulation results on a variety of problems demonstrate the application of our procedures as well as the strengths and the weaknesses of our general approach.

  6. Interacting neural networks

    Science.gov (United States)

    Metzler, R.; Kinzel, W.; Kanter, I.

    2000-08-01

    Several scenarios of interacting neural networks which are trained either in an identical or in a competitive way are solved analytically. In the case of identical training each perceptron receives the output of its neighbor. The symmetry of the stationary state as well as the sensitivity to the used training algorithm are investigated. Two competitive perceptrons trained on mutually exclusive learning aims and a perceptron which is trained on the opposite of its own output are examined analytically. An ensemble of competitive perceptrons is used as decision-making algorithms in a model of a closed market (El Farol Bar problem or the Minority Game. In this game, a set of agents who have to make a binary decision is considered.); each network is trained on the history of minority decisions. This ensemble of perceptrons relaxes to a stationary state whose performance can be better than random.

  7. Neural circuitry and immunity

    Science.gov (United States)

    Pavlov, Valentin A.; Tracey, Kevin J.

    2015-01-01

    Research during the last decade has significantly advanced our understanding of the molecular mechanisms at the interface between the nervous system and the immune system. Insight into bidirectional neuroimmune communication has characterized the nervous system as an important partner of the immune system in the regulation of inflammation. Neuronal pathways, including the vagus nerve-based inflammatory reflex are physiological regulators of immune function and inflammation. In parallel, neuronal function is altered in conditions characterized by immune dysregulation and inflammation. Here, we review these regulatory mechanisms and describe the neural circuitry modulating immunity. Understanding these mechanisms reveals possibilities to use targeted neuromodulation as a therapeutic approach for inflammatory and autoimmune disorders. These findings and current clinical exploration of neuromodulation in the treatment of inflammatory diseases defines the emerging field of Bioelectronic Medicine. PMID:26512000

  8. Neural Darwinism and consciousness.

    Science.gov (United States)

    Seth, Anil K; Baars, Bernard J

    2005-03-01

    Neural Darwinism (ND) is a large scale selectionist theory of brain development and function that has been hypothesized to relate to consciousness. According to ND, consciousness is entailed by reentrant interactions among neuronal populations in the thalamocortical system (the 'dynamic core'). These interactions, which permit high-order discriminations among possible core states, confer selective advantages on organisms possessing them by linking current perceptual events to a past history of value-dependent learning. Here, we assess the consistency of ND with 16 widely recognized properties of consciousness, both physiological (for example, consciousness is associated with widespread, relatively fast, low amplitude interactions in the thalamocortical system), and phenomenal (for example, consciousness involves the existence of a private flow of events available only to the experiencing subject). While no theory accounts fully for all of these properties at present, we find that ND and its recent extensions fare well.

  9. Stock prices forecasting based on wavelet neural networks with PSO

    OpenAIRE

    Wang Kai-Cheng; Yang Chi-I; Chang Kuei-Fang

    2017-01-01

    This research examines the forecasting performance of wavelet neural network (WNN) model using published stock data obtained from Financial Times Stock Exchange (FTSE) Taiwan Stock Exchange (TWSE) 50 index, also known as Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX), hereinafter referred to as Taiwan 50. Our WNN model uses particle swarm optimization (PSO) to choose the appropriate initial network values for different companies. The findings come with two advantages. First...

  10. Design spaces

    DEFF Research Database (Denmark)

    2005-01-01

    Digital technologies and media are becoming increasingly embodied and entangled in the spaces and places at work and at home. However, our material environment is more than a geometric abstractions of space: it contains familiar places, social arenas for human action. For designers, the integration...... of digital technology with space poses new challenges that call for new approaches. Creative alternatives to traditional systems methodologies are called for when designers use digital media to create new possibilities for action in space. Design Spaces explores how design and media art can provide creative...... alternatives for integrating digital technology with space. Connecting practical design work with conceptual development and theorizing, art with technology, and usesr-centered methods with social sciences, Design Spaces provides a useful research paradigm for designing ubiquitous computing. This book...

  11. Human Embryonic Stem Cells: A Model for the Study of Neural Development and Neurological Diseases

    Directory of Open Access Journals (Sweden)

    Piya Prajumwongs

    2016-01-01

    Full Text Available Although the mechanism of neurogenesis has been well documented in other organisms, there might be fundamental differences between human and those species referring to species-specific context. Based on principles learned from other systems, it is found that the signaling pathways required for neural induction and specification of human embryonic stem cells (hESCs recapitulated those in the early embryo development in vivo at certain degree. This underscores the usefulness of hESCs in understanding early human neural development and reinforces the need to integrate the principles of developmental biology and hESC biology for an efficient neural differentiation.

  12. Global asymptotic stability of Cohen-Grossberg neural networks with constant and variable delays

    International Nuclear Information System (INIS)

    Wu Wei; Cui Baotong; Huang Min

    2007-01-01

    Global asymptotic stability of Cohen-Grossberg neural networks with constant and variable delays is studied. Some sufficient conditions for the neural networks are proposed to guarantee the global asymptotic convergence by using different Lyapunov functionals. Our criteria represent an extension of the existing results in literatures. A comparison between our results and the previous results admits that our results establish a new set of stability criteria for delayed Cohen-Grossberg neural networks. Those conditions are less restrictive than those given in the earlier reference

  13. Modified-hybrid optical neural network filter for multiple object recognition within cluttered scenes

    Science.gov (United States)

    Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.

    2009-08-01

    Motivated by the non-linear interpolation and generalization abilities of the hybrid optical neural network filter between the reference and non-reference images of the true-class object we designed the modifiedhybrid optical neural network filter. We applied an optical mask to the hybrid optical neural network's filter input. The mask was built with the constant weight connections of a randomly chosen image included in the training set. The resulted design of the modified-hybrid optical neural network filter is optimized for performing best in cluttered scenes of the true-class object. Due to the shift invariance properties inherited by its correlator unit the filter can accommodate multiple objects of the same class to be detected within an input cluttered image. Additionally, the architecture of the neural network unit of the general hybrid optical neural network filter allows the recognition of multiple objects of different classes within the input cluttered image by modifying the output layer of the unit. We test the modified-hybrid optical neural network filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. The filter is shown to exhibit with a single pass over the input data simultaneously out-of-plane rotation, shift invariance and good clutter tolerance. It is able to successfully detect and classify correctly the true-class objects within background clutter for which there has been no previous training.

  14. AREVA - 2012 Reference document

    International Nuclear Information System (INIS)

    2013-03-01

    After a presentation of the person responsible for this Reference Document, of statutory auditors, and of a summary of financial information, this report address the different risk factors: risk management and coverage, legal risk, industrial and environmental risk, operational risk, risk related to major projects, liquidity and market risk, and other risks (related to political and economic conditions, to Group's structure, and to human resources). The next parts propose information about the issuer, a business overview (markets for nuclear power and renewable energies, customers and suppliers, group's strategy, operations), a brief presentation of the organizational structure, a presentation of properties, plants and equipment (principal sites, environmental issues which may affect these items), analysis and comments on the group's financial position and performance, a presentation of capital resources, a presentation of research and development activities (programs, patents and licenses), a brief description of financial objectives and profit forecasts or estimates, a presentation of administration, management and supervision bodies, a description of the operation of corporate bodies, an overview of personnel, of principal shareholders, and of transactions with related parties, a more detailed presentation of financial information concerning assets, financial positions and financial performance. Addition information regarding share capital is given, as well as an indication of major contracts, third party information, available documents, and information on holdings

  15. Reference thorium fuel cycle

    International Nuclear Information System (INIS)

    Driggers, F.E.

    1978-08-01

    In the reference fuel cycle for the TFCT program, fissile U will be denatured by mixing with 238 U; the plants will be located in secure areas, with Pu being recycled within these secure areas; Th will be recycled with recovered U and Pu; the head end will handle a variety of core and blanket fuel assembly designs for LWRs and HWRs; the fuel may be a homogeneous mixture either of U and Th oxide pellets or sol-gel microspheres; the cladding will be Zircaloy; and MgO may be added to the fuel to improve Th dissolution. Th is being considered as the fertile component of fuel in order to increase proliferation resistance. Spent U recovered from Th-based fuels must be re-enriched before recycle to prevent very rapid buildup of 238 U. Stainless steel will be considered as a backup to Zircaloy cladding in case Zr is incompatible with commercial aqueous dissolution. Storage of recovered irradiated Th will be considered as a backup to its use in the recycle of recovered Pu and U. Estimates are made of the time for introducing the Th fuel cycle into the LWR power industry. Since U fuel exposures in LWRs are likely to increase from 30,000 to 50,000 MWD/MT, the Th reprocessing plant should also be designed for Th fuel with 50,000 MWD/MT exposure

  16. Sensor Characteristics Reference Guide

    Energy Technology Data Exchange (ETDEWEB)

    Cree, Johnathan V.; Dansu, A.; Fuhr, P.; Lanzisera, Steven M.; McIntyre, T.; Muehleisen, Ralph T.; Starke, M.; Banerjee, Pranab; Kuruganti, T.; Castello, C.

    2013-04-01

    The Buildings Technologies Office (BTO), within the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), is initiating a new program in Sensor and Controls. The vision of this program is: • Buildings operating automatically and continuously at peak energy efficiency over their lifetimes and interoperating effectively with the electric power grid. • Buildings that are self-configuring, self-commissioning, self-learning, self-diagnosing, self-healing, and self-transacting to enable continuous peak performance. • Lower overall building operating costs and higher asset valuation. The overarching goal is to capture 30% energy savings by enhanced management of energy consuming assets and systems through development of cost-effective sensors and controls. One step in achieving this vision is the publication of this Sensor Characteristics Reference Guide. The purpose of the guide is to inform building owners and operators of the current status, capabilities, and limitations of sensor technologies. It is hoped that this guide will aid in the design and procurement process and result in successful implementation of building sensor and control systems. DOE will also use this guide to identify research priorities, develop future specifications for potential market adoption, and provide market clarity through unbiased information

  17. Uranium tailings reference materials

    International Nuclear Information System (INIS)

    Smith, C.W.; Steger, H.F.; Bowman, W.S.

    1984-01-01

    Samples of uranium tailings from Bancroft and Elliot Lake, Ontario, and from Beaverlodge and Rabbit Lake, Saskatchewan, have been prepared as compositional reference materials at the request of the National Uranium Tailings Research Program. The four samples, UTS-1 to UTS-4, were ground to minus 104 μm, each mixed in one lot and bottled in 200-g units for UTS-1 to UTS-3 and in 100-g units for UTS-4. The materials were tested for homogeneity with respect to uranium by neutron activation analysis and to iron by an acid-decomposition atomic absorption procedure. In a free choice analytical program, 18 laboratories contributed results for one or more of total iron, titanium, aluminum, calcium, barium, uranium, thorium, total sulphur, and sulphate for all four samples, and for nickel and arsenic in UTS-4 only. Based on a statistical analysis of the data, recommended values were assigned to all elements/constituents, except for sulphate in UTS-3 and nickel in UTS-4. The radioactivity of thorium-230, radium-226, lead-210, and polonium-210 in UTS-1 to UTS-4 and of thorium-232, radium-228, and thorium-228 in UTS-1 and UTS-2 was determined in a radioanalytical program composed of eight laboratories. Recommended values for the radioactivities and associated parameters were calculated by a statistical treatment of the results

  18. Space, time and causality

    International Nuclear Information System (INIS)

    Lucas, J.R.

    1984-01-01

    Originating from lectures given to first year undergraduates reading physics and philosophy or mathematics and philosophy, formal logic is applied to issues and the elucidation of problems in space, time and causality. No special knowledge of relativity theory or quantum mechanics is needed. The text is interspersed with exercises and each chapter is preceded by a suggested 'preliminary reading' and followed by 'further reading' references. (U.K.)

  19. Color in interior spaces

    OpenAIRE

    Demirörs, Müge Bozbeyli

    1992-01-01

    Ankara : The Department of Interior Architecture and Environmental Design and the Institute of Fine Arts of Bilkent University, 1992. Thesis (Master's) -- -Bilkent University, 1992. Includes bibliographical references leaves 95-99. Color can be approached from different perspectives and disciplines such as, biology, theory, technology, and psychology. This thesis discusses color, from the stand point of interior spaces, which to some extent involves most of these discipli...

  20. Program Helps Simulate Neural Networks

    Science.gov (United States)

    Villarreal, James; Mcintire, Gary

    1993-01-01

    Neural Network Environment on Transputer System (NNETS) computer program provides users high degree of flexibility in creating and manipulating wide variety of neural-network topologies at processing speeds not found in conventional computing environments. Supports back-propagation and back-propagation-related algorithms. Back-propagation algorithm used is implementation of Rumelhart's generalized delta rule. NNETS developed on INMOS Transputer(R). Predefines back-propagation network, Jordan network, and reinforcement network to assist users in learning and defining own networks. Also enables users to configure other neural-network paradigms from NNETS basic architecture. Small portion of software written in OCCAM(R) language.

  1. Artificial Neural Network Analysis System

    Science.gov (United States)

    2001-02-27

    Contract No. DASG60-00-M-0201 Purchase request no.: Foot in the Door-01 Title Name: Artificial Neural Network Analysis System Company: Atlantic... Artificial Neural Network Analysis System 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Powell, Bruce C 5d. PROJECT NUMBER 5e. TASK NUMBER...34) 27-02-2001 Report Type N/A Dates Covered (from... to) ("DD MON YYYY") 28-10-2000 27-02-2001 Title and Subtitle Artificial Neural Network Analysis

  2. Cooperating attackers in neural cryptography.

    Science.gov (United States)

    Shacham, Lanir N; Klein, Einat; Mislovaty, Rachel; Kanter, Ido; Kinzel, Wolfgang

    2004-06-01

    A successful attack strategy in neural cryptography is presented. The neural cryptosystem, based on synchronization of neural networks by mutual learning, has been recently shown to be secure under different attack strategies. The success of the advanced attacker presented here, called the "majority-flipping attacker," does not decay with the parameters of the model. This attacker's outstanding success is due to its using a group of attackers which cooperate throughout the synchronization process, unlike any other attack strategy known. An analytical description of this attack is also presented, and fits the results of simulations.

  3. Reference Atmosphere for Mercury

    Science.gov (United States)

    Killen, Rosemary M.

    2002-01-01

    We propose that Ar-40 measured in the lunar atmosphere and that in Mercury's atmosphere is due to current diffusion into connected pore space within the crust. Higher temperatures at Mercury, along with more rapid loss from the atmosphere will lead to a smaller column abundance of argon at Mercury than at the Moon, given the same crustal abundance of potassium. Because the noble gas abundance in the Hermean atmosphere represents current effusion, it is a direct measure of the crustal potassium abundance. Ar-40 in the atmospheres of the planets is a measure of potassium abundance in the interiors, since Ar-40 is a product of radiogenic decay of K-40 by electron capture with the subsequent emission of a 1.46 eV gamma-ray. Although the Ar-40 in the Earth's atmosphere is expected to have accumulated since the late bombardment, Ar-40 in the atmospheres of Mercury and the Moon is eroded quickly by photoionization and electron impact ionization. Thus, the argon content in the exospheres of the Moon and Mercury is representative of current effusion rather than accumulation over the lifetime of the planet.

  4. The Molecular Basis of Neural Memory. Part 7: Neural Intelligence (NI versus Artificial Intelligence (AI

    Directory of Open Access Journals (Sweden)

    Gerard Marx

    2017-07-01

    Full Text Available The link of memory to intelligence is incontestable, though the development of electronic artifacts with memory has confounded cognitive and computer scientists’ conception of memory and its relevance to “intelligence”. We propose two categories of “Intelligence”: (1 Logical (objective — mathematics, numbers, pattern recognition, games, programmable in binary format. (2 Emotive (subjective — sensations, feelings, perceptions, goals desires, sociability, sex, food, love. The 1st has been reduced to computational algorithms of which we are well versed, witness global technology and the internet. The 2nd relates to the mysterious process whereby (psychic emotive states are achieved by neural beings sensing, comprehending, remembering and dealing with their surroundings. Many theories and philosophies have been forwarded to rationalize this process, but as neuroscientists, we remain dissatisfied. Our own musings on universal neural memory, suggest a tripartite mechanism involving neurons interacting with their surroundings, notably the neural extracellular matrix (nECM with dopants [trace metals and neurotransmitters (NTs]. In particular, the NTs are the molecular encoders of emotive states. We have developed a chemographic representation of such a molecular code.To quote Longuet-Higgins, “Perhaps it is time for the term ‘artificial intelligence’ to be replaced by something more modest and less provisional”. We suggest “artifact intelligence” (ARTI or “machine intelligence” (MI, neither of which imply emulation of emotive neural processes, but simply refer to the ‘demotive’ (lacking emotive quality capability of electronic artifacts that employ a recall function, to calculate algorithms.

  5. Using Dual Process Models to Examine Impulsivity Throughout Neural Maturation.

    Science.gov (United States)

    Leshem, Rotem

    2016-01-01

    The multivariate construct of impulsivity is examined through neural systems and connections that comprise the executive functioning system. It is proposed that cognitive and behavioral components of impulsivity can be divided into two distinct groups, mediated by (1) the cognitive control system: deficits in top-down cognitive control processes referred to as action/cognitive impulsivity and (2) the socioemotional system: related to bottom-up affective/motivational processes referred to as affective impulsivity. Examination of impulsivity from a developmental viewpoint can guide future research, potentially enabling the selection of more effective interventions for impulsive individuals, based on the cognitive components requiring improvement.

  6. ENRAF gauge reference level calculations

    Energy Technology Data Exchange (ETDEWEB)

    Huber, J.H., Fluor Daniel Hanford

    1997-02-06

    This document describes the method for calculating reference levels for Enraf Series 854 Level Detectors as installed in the tank farms. The reference level calculation for each installed level gauge is contained herein.

  7. Global Reference Tables Services Architecture

    Data.gov (United States)

    Social Security Administration — This database stores the reference and transactional data used to provide a data-driven service access method to certain Global Reference Table (GRT) service tables.

  8. Genetics Home Reference: PURA syndrome

    Science.gov (United States)

    ... TJ, Vreeburg M, Rouhl RPW, Stevens SJC, Stegmann APA, Schieving J, Pfundt R, van Dijk K, Smeets ... article on PubMed Central More from Genetics Home Reference Bulletins Genetics Home Reference Celebrates Its 15th Anniversary ...

  9. Space Commercialization

    Science.gov (United States)

    Martin, Gary L.

    2011-01-01

    A robust and competitive commercial space sector is vital to continued progress in space. The United States is committed to encouraging and facilitating the growth of a U.S. commercial space sector that supports U.S. needs, is globally competitive, and advances U.S. leadership in the generation of new markets and innovation-driven entrepreneurship. Energize competitive domestic industries to participate in global markets and advance the development of: satellite manufacturing; satellite-based services; space launch; terrestrial applications; and increased entrepreneurship. Purchase and use commercial space capabilities and services to the maximum practical extent Actively explore the use of inventive, nontraditional arrangements for acquiring commercial space goods and services to meet United States Government requirements, including measures such as public-private partnerships, . Refrain from conducting United States Government space activities that preclude, discourage, or compete with U.S. commercial space activities. Pursue potential opportunities for transferring routine, operational space functions to the commercial space sector where beneficial and cost-effective.

  10. Adaptive Neural Control for Space Structure Vibration Suppression.

    Science.gov (United States)

    1996-08-01

    based implementations is the subject of the next chapter. 17 ANC Final Report Kam VdI k (~k)A .. loco[ Excitation --Control ON 1 15 20 25 30 Figure 2...must’write something to the update register to cause ~ 1* a conversion. * #def ine MODE OxOOOO 1* Keep things in range * #def ine NAXDA 2048 #define DASENS

  11. Creative-Dynamics Approach To Neural Intelligence

    Science.gov (United States)

    Zak, Michail A.

    1992-01-01

    Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

  12. Areva - 2014 Reference document

    International Nuclear Information System (INIS)

    2015-01-01

    Areva supplies high added-value products and services to support the operation of the global nuclear fleet. The company is present throughout the entire nuclear cycle, from uranium mining to used fuel recycling, including nuclear reactor design and operating services. Areva is recognized by utilities around the world for its expertise, its skills in cutting-edge technologies and its dedication to the highest level of safety. Areva's 44,000 employees are helping build tomorrow's energy model: supplying ever safer, cleaner and more economical energy to the greatest number of people. This Reference Document contains information on Areva's objectives, prospects and development strategies. It contains estimates of the markets, market shares and competitive position of Areva. Contents: 1 - Person responsible; 2 - Statutory auditors; 3 - Selected financial information; 4 - Risk factors; 5 - Information about the issuer; 6 - Business overview; 7 - Organizational structure; 8 - Property, plant and equipment; 9 - Analysis of and comments on the group's financial position and performance; 10 - Capital resources; 11 - Research and development programs, patents and licenses; 12 - Trend information; 13 - Profit forecasts; 14 - Administrative, management and supervisory bodies and senior management; 15 - Compensation and benefits; 16 - Functioning of administrative, management and supervisory bodies and senior management; 17 - Employees; 18 - Principal shareholders; 19 - Transactions with related parties; 20 - Financial information concerning assets, financial positions and financial performance; 21 - Additional information; 22 - Major contracts; 23 - Third party information, statements by experts and declarations of interest; 24 - Documents on display; 25 - information on holdings; appendix: Report of the Chairman of the Board of Directors on governance, internal control procedures and risk management, Statutory Auditors' report, Corporate social

  13. Kerlinger's Criterial Referents Theory Revisited.

    Science.gov (United States)

    Zak, Itai; Birenbaum, Menucha

    1980-01-01

    Kerlinger's criterial referents theory of attitudes was tested cross-culturally by administering an education attitude referents summated-rating scale to 713 individuals in Israel. The response pattern to criterial and noncriterial referents was examined. Results indicated empirical cross-cultural validity of theory, but questioned measuring…

  14. Fundamentals of Managing Reference Collections

    Science.gov (United States)

    Singer, Carol A.

    2012-01-01

    Whether a library's reference collection is large or small, it needs constant attention. Singer's book offers information and insight on best practices for reference collection management, no matter the size, and shows why managing without a plan is a recipe for clutter and confusion. In this very practical guide, reference librarians will learn:…

  15. Knowledge Management and Reference Services

    Science.gov (United States)

    Gandhi, Smiti

    2004-01-01

    Many corporations are embracing knowledge management (KM) to capture the intellectual capital of their employees. This article focuses on KM applications for reference work in libraries. It defines key concepts of KM, establishes a need for KM for reference services, and reviews various KM initiatives for reference services.

  16. Schroedinger--Dirac spaces of entire functions

    International Nuclear Information System (INIS)

    De Branges, L.

    1977-01-01

    A study is made of some Hilbert spaces of entire function which appear in the quantum mechanical theory of the hydrogen atoms. These spaces are examples in the theory of Hilbert spaces whose elements are entire functions and which have certain given properties. 1 reference

  17. Determining the confidence levels of sensor outputs using neural networks

    International Nuclear Information System (INIS)

    Broten, G.S.; Wood, H.C.

    1995-01-01

    This paper describes an approach for determining the confidence level of a sensor output using multi-sensor arrays, sensor fusion and artificial neural networks. The authors have shown in previous work that sensor fusion and artificial neural networks can be used to learn the relationships between the outputs of an array of simulated partially selective sensors and the individual analyte concentrations in a mixture of analyses. Other researchers have shown that an array of partially selective sensors can be used to determine the individual gas concentrations in a gaseous mixture. The research reported in this paper shows that it is possible to extract confidence level information from an array of partially selective sensors using artificial neural networks. The confidence level of a sensor output is defined as a numeric value, ranging from 0% to 100%, that indicates the confidence associated with a output of a given sensor. A three layer back-propagation neural network was trained on a subset of the sensor confidence level space, and was tested for its ability to generalize, where the confidence level space is defined as all possible deviations from the correct sensor output. A learning rate of 0.1 was used and no momentum terms were used in the neural network. This research has shown that an artificial neural network can accurately estimate the confidence level of individual sensors in an array of partially selective sensors. This research has also shown that the neural network's ability to determine the confidence level is influenced by the complexity of the sensor's response and that the neural network is able to estimate the confidence levels even if more than one sensor is in error. The fundamentals behind this research could be applied to other configurations besides arrays of partially selective sensors, such as an array of sensors separated spatially. An example of such a configuration could be an array of temperature sensors in a tank that is not in

  18. Optical implementation of a feature-based neural network with application to automatic target recognition

    Science.gov (United States)

    Chao, Tien-Hsin; Stoner, William W.

    1993-01-01

    An optical neural network based on the neocognitron paradigm is introduced. A novel aspect of the architecture design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by feeding back the ouput of the feature correlator interatively to the input spatial light modulator and by updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved. A detailed system description is provided. Experimental demonstrations of a two-layer neural network for space-object discrimination is also presented.

  19. Automatic target recognition using a feature-based optical neural network

    Science.gov (United States)

    Chao, Tien-Hsin

    1992-01-01

    An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

  20. An Adaptive Critic Approach to Reference Model Adaptation

    Science.gov (United States)

    Krishnakumar, K.; Limes, G.; Gundy-Burlet, K.; Bryant, D.

    2003-01-01

    Neural networks have been successfully used for implementing control architectures for different applications. In this work, we examine a neural network augmented adaptive critic as a Level 2 intelligent controller for a C- 17 aircraft. This intelligent control architecture utilizes an adaptive critic to tune the parameters of a reference model, which is then used to define the angular rate command for a Level 1 intelligent controller. The present architecture is implemented on a high-fidelity non-linear model of a C-17 aircraft. The goal of this research is to improve the performance of the C-17 under degraded conditions such as control failures and battle damage. Pilot ratings using a motion based simulation facility are included in this paper. The benefits of using an adaptive critic are documented using time response comparisons for severe damage situations.

  1. Process for forming synapses in neural networks and resistor therefor

    Science.gov (United States)

    Fu, Chi Y.

    1996-01-01

    Customizable neural network in which one or more resistors form each synapse. All the resistors in the synaptic array are identical, thus simplifying the processing issues. Highly doped, amorphous silicon is used as the resistor material, to create extremely high resistances occupying very small spaces. Connected in series with each resistor in the array is at least one severable conductor whose uppermost layer has a lower reflectivity of laser energy than typical metal conductors at a desired laser wavelength.

  2. Neural network based method for conversion of solar radiation data

    International Nuclear Information System (INIS)

    Celik, Ali N.; Muneer, Tariq

    2013-01-01

    Highlights: ► Generalized regression neural network is used to predict the solar radiation on tilted surfaces. ► The above network, amongst many such as multilayer perceptron, is the most successful one. ► The present neural network returns a relative mean absolute error value of 9.1%. ► The present model leads to a mean absolute error value of estimate of 14.9 Wh/m 2 . - Abstract: The receiving ends of the solar energy conversion systems that generate heat or electricity from radiation is usually tilted at an optimum angle to increase the solar incident on the surface. Solar irradiation data measured on horizontal surfaces is readily available for many locations where such solar energy conversion systems are installed. Various equations have been developed to convert solar irradiation data measured on horizontal surface to that on tilted one. These equations constitute the conventional approach. In this article, an alternative approach, generalized regression type of neural network, is used to predict the solar irradiation on tilted surfaces, using the minimum number of variables involved in the physical process, namely the global solar irradiation on horizontal surface, declination and hour angles. Artificial neural networks have been successfully used in recent years for optimization, prediction and modeling in energy systems as alternative to conventional modeling approaches. To show the merit of the presently developed neural network, the solar irradiation data predicted from the novel model was compared to that from the conventional approach (isotropic and anisotropic models), with strict reference to the irradiation data measured in the same location. The present neural network model was found to provide closer solar irradiation values to the measured than the conventional approach, with a mean absolute error value of 14.9 Wh/m 2 . The other statistical values of coefficient of determination and relative mean absolute error also indicate the

  3. Assessing Landslide Hazard Using Artificial Neural Network

    DEFF Research Database (Denmark)

    Farrokhzad, Farzad; Choobbasti, Asskar Janalizadeh; Barari, Amin

    2011-01-01

    failure" which is main concentration of the current research and "liquefaction failure". Shear failures along shear planes occur when the shear stress along the sliding surfaces exceed the effective shear strength. These slides have been referred to as landslide. An expert system based on artificial...... and factor of safety. It can be stated that the trained neural networks are capable of predicting the stability of slopes and safety factor of landslide hazard in study area with an acceptable level of confidence. Landslide hazard analysis and mapping can provide useful information for catastrophic loss...... reduction, and assist in the development of guidelines for sustainable land use planning. The analysis is used to identify the factors that are related to landslides and to predict the landslide hazard in the future based on such a relationship....

  4. Neural complexity, dissociation, and schizophrenia

    Czech Academy of Sciences Publication Activity Database

    Bob, P.; Šusta, M.; Chládek, Jan; Glaslová, K.; Fedor-Ferybergh, P.

    2007-01-01

    Roč. 13, č. 10 (2007), HY1-5 ISSN 1234-1010 Institutional research plan: CEZ:AV0Z20650511 Keywords : neural complexity * dissociation * schizophrenia Subject RIV: FH - Neurology Impact factor: 1.607, year: 2007

  5. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: - Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. - Amongst numerous training algorithms, only four algorithms are examined, all...... in a recursive form (sample updating). The simplest is the Back Probagation Error Algorithm, and the most complex is the recursive Prediction Error Method using a Gauss-Newton search direction. - Over-fitting is often considered to be a serious problem when training neural networks. This problem is specifically...

  6. Artificial intelligence: Deep neural reasoning

    Science.gov (United States)

    Jaeger, Herbert

    2016-10-01

    The human brain can solve highly abstract reasoning problems using a neural network that is entirely physical. The underlying mechanisms are only partially understood, but an artificial network provides valuable insight. See Article p.471

  7. Optical Neural Network Classifier Architectures

    National Research Council Canada - National Science Library

    Getbehead, Mark

    1998-01-01

    We present an adaptive opto-electronic neural network hardware architecture capable of exploiting parallel optics to realize real-time processing and classification of high-dimensional data for Air...

  8. Memristor-based neural networks

    International Nuclear Information System (INIS)

    Thomas, Andy

    2013-01-01

    The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent progress in the experimental realization of memristive devices has renewed interest in artificial neural networks. The resistance of a memristive system depends on its past states and exactly this functionality can be used to mimic the synaptic connections in a (human) brain. After a short introduction to memristors, we present and explain the relevant mechanisms in a biological neural network, such as long-term potentiation and spike time-dependent plasticity, and determine the minimal requirements for an artificial neural network. We review the implementations of these processes using basic electric circuits and more complex mechanisms that either imitate biological systems or could act as a model system for them. (topical review)

  9. Learning Spaces

    CERN Document Server

    Falmagne, Jean-Claude

    2011-01-01

    Learning spaces offer a rigorous mathematical foundation for practical systems of educational technology. Learning spaces generalize partially ordered sets and are special cases of knowledge spaces. The various structures are investigated from the standpoints of combinatorial properties and stochastic processes. Leaning spaces have become the essential structures to be used in assessing students' competence of various topics. A practical example is offered by ALEKS, a Web-based, artificially intelligent assessment and learning system in mathematics and other scholarly fields. At the heart of A

  10. Implantable Neural Interfaces for Sharks

    Science.gov (United States)

    2007-05-01

    technology for recording and stimulating from the auditory and olfactory sensory nervous systems of the awake, swimming nurse shark , G. cirratum (Figures...overlay of the central nervous system of the nurse shark on a horizontal MR image. Implantable Neural Interfaces for Sharks ...Neural Interfaces for Characterizing Population Responses to Odorants and Electrical Stimuli in the Nurse Shark , Ginglymostoma cirratum.” AChemS Abs

  11. What are artificial neural networks?

    DEFF Research Database (Denmark)

    Krogh, Anders

    2008-01-01

    Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb......Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb...

  12. Phase Diagram of Spiking Neural Networks

    Directory of Open Access Journals (Sweden)

    Hamed eSeyed-Allaei

    2015-03-01

    Full Text Available In computer simulations of spiking neural networks, often it is assumed that every two neurons of the network are connected by a probablilty of 2%, 20% of neurons are inhibitory and 80% are excitatory. These common values are based on experiments, observations. but here, I take a different perspective, inspired by evolution. I simulate many networks, each with a different set of parameters, and then I try to figure out what makes the common values desirable by nature. Networks which are configured according to the common values, have the best dynamic range in response to an impulse and their dynamic range is more robust in respect to synaptic weights. In fact, evolution has favored networks of best dynamic range. I present a phase diagram that shows the dynamic ranges of different networks of different parameteres. This phase diagram gives an insight into the space of parameters -- excitatory to inhibitory ratio, sparseness of connections and synaptic weights. It may serve as a guideline to decide about the values of parameters in a simulation of spiking neural network.

  13. Evaluating Lyapunov exponent spectra with neural networks

    International Nuclear Information System (INIS)

    Maus, A.; Sprott, J.C.

    2013-01-01

    Highlights: • Cross-correlation is employed to remove spurious Lyapunov exponents from a spectrum. • Neural networks are shown to accurately model Lyapunov exponent spectra. • Neural networks compare favorably to local linear fits in modeling Lyapunov exponents. • Numerical experiments are performed with time series of varying length and noise. • Methods perform reasonably well on discrete time series. -- Abstract: A method using discrete cross-correlation for identifying and removing spurious Lyapunov exponents when embedding experimental data in a dimension greater than the original system is introduced. The method uses a distribution of calculated exponent values produced by modeling a single time series many times or multiple instances of a time series. For this task, global models are shown to compare favorably to local models traditionally used for time series taken from the Hénon map and delayed Hénon map, especially when the time series are short or contaminated by noise. An additional merit of global modeling is its ability to estimate the dynamical and geometrical properties of the original system such as the attractor dimension, entropy, and lag space, although consideration must be taken for the time it takes to train the global models

  14. Portable Rule Extraction Method for Neural Network Decisions Reasoning

    Directory of Open Access Journals (Sweden)

    Darius PLIKYNAS

    2005-08-01

    Full Text Available Neural network (NN methods are sometimes useless in practical applications, because they are not properly tailored to the particular market's needs. We focus thereinafter specifically on financial market applications. NNs have not gained full acceptance here yet. One of the main reasons is the "Black Box" problem (lack of the NN decisions explanatory power. There are though some NN decisions rule extraction methods like decompositional, pedagogical or eclectic, but they suffer from low portability of the rule extraction technique across various neural net architectures, high level of granularity, algorithmic sophistication of the rule extraction technique etc. The authors propose to eliminate some known drawbacks using an innovative extension of the pedagogical approach. The idea is exposed by the use of a widespread MLP neural net (as a common tool in the financial problems' domain and SOM (input data space clusterization. The feedback of both nets' performance is related and targeted through the iteration cycle by achievement of the best matching between the decision space fragments and input data space clusters. Three sets of rules are generated algorithmically or by fuzzy membership functions. Empirical validation of the common financial benchmark problems is conducted with an appropriately prepared software solution.

  15. Neural representations of emotion are organized around abstract event features.

    Science.gov (United States)

    Skerry, Amy E; Saxe, Rebecca

    2015-08-03

    Research on emotion attribution has tended to focus on the perception of overt expressions of at most five or six basic emotions. However, our ability to identify others' emotional states is not limited to perception of these canonical expressions. Instead, we make fine-grained inferences about what others feel based on the situations they encounter, relying on knowledge of the eliciting conditions for different emotions. In the present research, we provide convergent behavioral and neural evidence concerning the representations underlying these concepts. First, we find that patterns of activity in mentalizing regions contain information about subtle emotional distinctions conveyed through verbal descriptions of eliciting situations. Second, we identify a space of abstract situation features that well captures the emotion discriminations subjects make behaviorally and show that this feature space outperforms competing models in capturing the similarity space of neural patterns in these regions. Together, the data suggest that our knowledge of others' emotions is abstract and high dimensional, that brain regions selective for mental state reasoning support relatively subtle distinctions between emotion concepts, and that the neural representations in these regions are not reducible to more primitive affective dimensions such as valence and arousal. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Comparing Models GRM, Refraction Tomography and Neural Network to Analyze Shallow Landslide

    Directory of Open Access Journals (Sweden)

    Armstrong F. Sompotan

    2011-11-01

    Full Text Available Detailed investigations of landslides are essential to understand fundamental landslide mechanisms. Seismic refraction method has been proven as a useful geophysical tool for investigating shallow landslides. The objective of this study is to introduce a new workflow using neural network in analyzing seismic refraction data and to compare the result with some methods; that are general reciprocal method (GRM and refraction tomography. The GRM is effective when the velocity structure is relatively simple and refractors are gently dipping. Refraction tomography is capable of modeling the complex velocity structures of landslides. Neural network is found to be more potential in application especially in time consuming and complicated numerical methods. Neural network seem to have the ability to establish a relationship between an input and output space for mapping seismic velocity. Therefore, we made a preliminary attempt to evaluate the applicability of neural network to determine velocity and elevation of subsurface synthetic models corresponding to arrival times. The training and testing process of the neural network is successfully accomplished using the synthetic data. Furthermore, we evaluated the neural network using observed data. The result of the evaluation indicates that the neural network can compute velocity and elevation corresponding to arrival times. The similarity of those models shows the success of neural network as a new alternative in seismic refraction data interpretation.

  17. Neural Net Safety Monitor Design

    Science.gov (United States)

    Larson, Richard R.

    2007-01-01

    The National Aeronautics and Space Administration (NASA) at the Dryden Flight Research Center (DFRC) has been conducting flight-test research using an F-15 aircraft (figure 1). This aircraft has been specially modified to interface a neural net (NN) controller as part of a single-string Airborne Research Test System (ARTS) computer with the existing quad-redundant flight control system (FCC) shown in figure 2. The NN commands are passed to FCC channels 2 and 4 and are cross channel data linked (CCDL) to the other computers as shown. Numerous types of fault-detection monitors exist in the FCC when the NN mode is engaged; these monitors would cause an automatic disengagement of the NN in the event of a triggering fault. Unfortunately, these monitors still may not prevent a possible NN hard-over command from coming through to the control laws. Therefore, an additional and unique safety monitor was designed for a single-string source that allows authority at maximum actuator rates but protects the pilot and structural loads against excessive g-limits in the case of a NN hard-over command input. This additional monitor resides in the FCCs and is executed before the control laws are computed. This presentation describes a floating limiter (FL) concept1 that was developed and successfully test-flown for this program (figure 3). The FL computes the rate of change of the NN commands that are input to the FCC from the ARTS. A window is created with upper and lower boundaries, which is constantly floating and trying to stay centered as the NN command rates are changing. The limiter works by only allowing the window to move at a much slower rate than those of the NN commands. Anywhere within the window, however, full rates are allowed. If a rate persists in one direction, it will eventually hit the boundary and be rate-limited to the floating limiter rate. When this happens, a persistent counter begins and after a limit is reached, a NN disengage command is generated. The

  18. Neural correlates of hate.

    Directory of Open Access Journals (Sweden)

    Semir Zeki

    Full Text Available In this work, we address an important but unexplored topic, namely the neural correlates of hate. In a block-design fMRI study, we scanned 17 normal human subjects while they viewed the face of a person they hated and also faces of acquaintances for whom they had neutral feelings. A hate score was obtained for the object of hate for each subject and this was used as a covariate in a between-subject random effects analysis. Viewing a hated face resulted in increased activity in the medial frontal gyrus, right putamen, bilaterally in premotor cortex, in the frontal pole and bilaterally in the medial insula. We also found three areas where activation correlated linearly with the declared level of hatred, the right insula, right premotor cortex and the right fronto-medial gyrus. One area of deactivation was found in the right superior frontal gyrus. The study thus shows that there is a unique pattern of activity in the brain in the context of hate. Though distinct from the pattern of activity that correlates with romantic love, this pattern nevertheless shares two areas with the latter, namely the putamen and the insula.

  19. neural control system

    International Nuclear Information System (INIS)

    Elshazly, A.A.E.

    2002-01-01

    Automatic power stabilization control is the desired objective for any reactor operation , especially, nuclear power plants. A major problem in this area is inevitable gap between a real plant ant the theory of conventional analysis and the synthesis of linear time invariant systems. in particular, the trajectory tracking control of a nonlinear plant is a class of problems in which the classical linear transfer function methods break down because no transfer function can represent the system over the entire operating region . there is a considerable amount of research on the model-inverse approach using feedback linearization technique. however, this method requires a prices plant model to implement the exact linearizing feedback, for nuclear reactor systems, this approach is not an easy task because of the uncertainty in the plant parameters and un-measurable state variables . therefore, artificial neural network (ANN) is used either in self-tuning control or in improving the conventional rule-based exper system.the main objective of this thesis is to suggest an ANN, based self-learning controller structure . this method is capable of on-line reinforcement learning and control for a nuclear reactor with a totally unknown dynamics model. previously, researches are based on back- propagation algorithm . back -propagation (BP), fast back -propagation (FBP), and levenberg-marquardt (LM), algorithms are discussed and compared for reinforcement learning. it is found that, LM algorithm is quite superior

  20. Experimental evidence of a chaotic region in a neural pacemaker

    Energy Technology Data Exchange (ETDEWEB)

    Gu, Hua-Guang, E-mail: guhuaguang@tongji.edu.cn [School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai 200092 (China); Department of Electronic Engineering, City University of Hong Kong, Hong Kong SAR (China); Jia, Bing [School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai 200092 (China); Chen, Guan-Rong [Department of Electronic Engineering, City University of Hong Kong, Hong Kong SAR (China)

    2013-03-15

    In this Letter, we report the finding of period-adding scenarios with chaos in firing patterns, observed in biological experiments on a neural pacemaker, with fixed extra-cellular potassium concentration at different levels and taken extra-cellular calcium concentration as the bifurcation parameter. The experimental bifurcations in the two-dimensional parameter space demonstrate the existence of a chaotic region interwoven with the periodic region thereby forming a period-adding sequence with chaos. The behavior of the pacemaker in this region is qualitatively similar to that of the Hindmarsh–Rose neuron model in a well-known comb-shaped chaotic region in two-dimensional parameter spaces.

  1. Dynamics of neural networks with continuous attractors

    Science.gov (United States)

    Fung, C. C. Alan; Wong, K. Y. Michael; Wu, Si

    2008-10-01

    We investigate the dynamics of continuous attractor neural networks (CANNs). Due to the translational invariance of their neuronal interactions, CANNs can hold a continuous family of stationary states. We systematically explore how their neutral stability facilitates the tracking performance of a CANN, which is believed to have wide applications in brain functions. We develop a perturbative approach that utilizes the dominant movement of the network stationary states in the state space. We quantify the distortions of the bump shape during tracking, and study their effects on the tracking performance. Results are obtained on the maximum speed for a moving stimulus to be trackable, and the reaction time to catch up an abrupt change in stimulus.

  2. The Neural Correlates of Humor Creativity.

    Science.gov (United States)

    Amir, Ori; Biederman, Irving

    2016-01-01

    Unlike passive humor appreciation, the neural correlates of real-time humor creation have been unexplored. As a case study for creativity, humor generation uniquely affords a reliable assessment of a creative product's quality with a clear and relatively rapid beginning and end, rendering it amenable to neuroimaging that has the potential for reflecting individual differences in expertise. Professional and amateur "improv" comedians and controls viewed New Yorker cartoon drawings while being scanned. For each drawing, they were instructed to generate either a humorous or a mundane caption. Greater comedic experience was associated with decreased activation in the striatum and medial prefrontal cortex (mPFC), but increased activation in temporal association regions (TMP). Less experienced comedians manifested greater activation of mPFC, reflecting their deliberate search through TMP association space. Professionals, by contrast, tend to reap the fruits of their spontaneous associations with reduced reliance on top-down guided search.

  3. The Neural Correlates of Humor Creativity

    Directory of Open Access Journals (Sweden)

    Ori Amir

    2016-11-01

    Full Text Available Unlike passive humor appreciation, the neural correlates of real-time humor creation have been unexplored. As a case study for creativity, humor generation uniquely affords a reliable assessment of a creative product’s quality with a clear and relatively rapid beginning and end, rendering it amenable to neuroimaging that has the potential for reflecting individual differences in expertise. Professional and amateur improv comedians and controls viewed New Yorker cartoon drawings while being scanned. For each drawing, they were instructed to generate either a humorous or a mundane caption. Greater comedic experience was associated with decreased activation in the striatum and medial prefrontal cortex (mPFC, but increased activation in temporal association regions (TMP. Less experienced comedians manifested greater activation of mPFC, reflecting their deliberate search through TMP association space. Professionals, by contrast, tend to reap the fruits of their spontaneous associations with reduced reliance on top-down guided search.

  4. Flood routing modelling with Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    R. Peters

    2006-01-01

    Full Text Available For the modelling of the flood routing in the lower reaches of the Freiberger Mulde river and its tributaries the one-dimensional hydrodynamic modelling system HEC-RAS has been applied. Furthermore, this model was used to generate a database to train multilayer feedforward networks. To guarantee numerical stability for the hydrodynamic modelling of some 60 km of streamcourse an adequate resolution in space requires very small calculation time steps, which are some two orders of magnitude smaller than the input data resolution. This leads to quite high computation requirements seriously restricting the application – especially when dealing with real time operations such as online flood forecasting. In order to solve this problem we tested the application of Artificial Neural Networks (ANN. First studies show the ability of adequately trained multilayer feedforward networks (MLFN to reproduce the model performance.

  5. The Neural Correlates of Humor Creativity

    Science.gov (United States)

    Amir, Ori; Biederman, Irving

    2016-01-01

    Unlike passive humor appreciation, the neural correlates of real-time humor creation have been unexplored. As a case study for creativity, humor generation uniquely affords a reliable assessment of a creative product’s quality with a clear and relatively rapid beginning and end, rendering it amenable to neuroimaging that has the potential for reflecting individual differences in expertise. Professional and amateur “improv” comedians and controls viewed New Yorker cartoon drawings while being scanned. For each drawing, they were instructed to generate either a humorous or a mundane caption. Greater comedic experience was associated with decreased activation in the striatum and medial prefrontal cortex (mPFC), but increased activation in temporal association regions (TMP). Less experienced comedians manifested greater activation of mPFC, reflecting their deliberate search through TMP association space. Professionals, by contrast, tend to reap the fruits of their spontaneous associations with reduced reliance on top-down guided search. PMID:27932965

  6. Space Microbiology

    Science.gov (United States)

    Horneck, Gerda; Klaus, David M.; Mancinelli, Rocco L.

    2010-01-01

    Summary: The responses of microorganisms (viruses, bacterial cells, bacterial and fungal spores, and lichens) to selected factors of space (microgravity, galactic cosmic radiation, solar UV radiation, and space vacuum) were determined in space and laboratory simulation experiments. In general, microorganisms tend to thrive in the space flight environment in terms of enhanced growth parameters and a demonstrated ability to proliferate in the presence of normally inhibitory levels of antibiotics. The mechanisms responsible for the observed biological responses, however, are not yet fully understood. A hypothesized interaction of microgravity with radiation-induced DNA repair processes was experimentally refuted. The survival of microorganisms in outer space was investigated to tackle questions on the upper boundary of the biosphere and on the likelihood of interplanetary transport of microorganisms. It was found that extraterrestrial solar UV radiation was the most deleterious factor of space. Among all organisms tested, only lichens (Rhizocarpon geographicum and Xanthoria elegans) maintained full viability after 2 weeks in outer space, whereas all other test systems were inactivated by orders of magnitude. Using optical filters and spores of Bacillus subtilis as a biological UV dosimeter, it was found that the current ozone layer reduces the biological effectiveness of solar UV by 3 orders of magnitude. If shielded against solar UV, spores of B. subtilis were capable of surviving in space for up to 6 years, especially if embedded in clay or meteorite powder (artificial meteorites). The data support the likelihood of interplanetary transfer of microorganisms within meteorites, the so-called lithopanspermia hypothesis. PMID:20197502

  7. Space psychology

    Science.gov (United States)

    Parin, V. V.; Gorbov, F. D.; Kosmolinskiy, F. P.

    1974-01-01

    Psychological selection of astronauts considers mental responses and adaptation to the following space flight stress factors: (1) confinement in a small space; (2) changes in three dimensional orientation; (3) effects of altered gravity and weightlessness; (4) decrease in afferent nerve pulses; (5) a sensation of novelty and danger; and (6) a sense of separation from earth.

  8. Borel Spaces

    CERN Document Server

    Berberian, S K

    2002-01-01

    A detailed exposition of G.W. Mackey's theory of Borel spaces (standard, substandard, analytic), based on results in Chapter 9 of Bourbaki's General Topology. Appended are five informal lectures on the subject (given at the CIMPA/ICPAM Summer School, Nice, 1986), sketching the connection between Borel spaces and representations of operator algebras.

  9. Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

    Science.gov (United States)

    Takiyama, Ken

    2017-12-01

    How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

  10. Space engineering

    Science.gov (United States)

    Alexander, Harold L.

    1991-01-01

    Human productivity was studied for extravehicular tasks performed in microgravity, particularly including in-space assembly of truss structures and other large objects. Human factors research probed the anthropometric constraints imposed on microgravity task performance and the associated workstation design requirements. Anthropometric experiments included reach envelope tests conducted using the 3-D Acoustic Positioning System (3DAPS), which permitted measuring the range of reach possible for persons using foot restraints in neutral buoyancy, both with and without space suits. Much neutral buoyancy research was conducted using the support of water to simulate the weightlessness environment of space. It became clear over time that the anticipated EVA requirement associated with the Space Station and with in-space construction of interplanetary probes would heavily burden astronauts, and remotely operated robots (teleoperators) were increasingly considered to absorb the workload. Experience in human EVA productivity led naturally to teleoperation research into the remote performance of tasks through human controlled robots.

  11. Theory of Neural Information Processing Systems

    International Nuclear Information System (INIS)

    Galla, Tobias

    2006-01-01

    existing textbook literature, so that this discussion will be very much appreciated. The book is of an exceptionally high quality in all aspects. In my view, the style of presentation and the inclusion of recent aspects of the topic alone make the book a welcomed addition to the existing literature. It is well structured and the material covered was chosen with care. While focusing on quantitative aspects of the subject, the authors adopt a comprehensive style of presentation, being precise, but not pedantic. The student who is not familiar with the field might find the breadth of the book overwhelming at first, but will soon appreciate its pedagogical value. All mathematical derivations are performed and explained step by step for the student to follow, and they are illustrated by many concrete examples and results from computer simulations in well-presented and clear figures. If a student wants to get his hands on the mathematical tools of neural networks theory then this book is a good place to learn from. A set of instructive and valuable exercises complements each chapter (hints are given, but maybe it would have been nice to provide additional brief sample solutions in an appendix). I very much enjoyed the outlook sections at the end of each of the five parts, putting the material covered into its historical context and providing further references. In summary, students of a quantitative discipline will find in this book a clear and self-contained introduction to the subject, lecturers might use it to design postgraduate courses, and finally it will provide a valuable reference for researchers working in the area. This book can be expected to be an asset for all types of readers, even if they already own a book on neural networks. Anyone with a serious interest in the theoretical aspects of the field would be making a mistake not to have a copy on their shelves. (book review)

  12. Tight Reference Frame–Independent Quantum Teleportation

    Directory of Open Access Journals (Sweden)

    Dominic Verdon

    2017-01-01

    Full Text Available We give a tight scheme for teleporting a quantum state between two parties whose reference frames are misaligned by an action of a finite symmetry group. Unlike previously proposed schemes, ours requires no additional tokens or data to be passed between the participants; the same amount of classical information is transferred as for ordinary quantum teleportation, and the Hilbert space of the entangled resource is of the same size. In the terminology of Peres and Scudo, our protocol relies on classical communication of unspeakable information.

  13. Generalized frame of reference with null congruence

    International Nuclear Information System (INIS)

    Ferrarese, G.; Antonelli, R.

    2000-01-01

    The paper derives the main properties of a generalized frame of reference with a null congruence (light flux), by means of adapted non-holonomic techniques; then it studies the geometry of the space-time in terms of non-orthogonal projection: longitudinal and transverse covariant derivatives and corresponding commutation formulae, decomposition of the Riemann and gravitational tensors, lie derivatives of the Ricci rotation coefficients, transverse Bianchi identity. Application to the (absolute and relative) light flux: kinematical characteristics and screen, Sachs theorems etc. are also given

  14. Validation of neural spike sorting algorithms without ground-truth information.

    Science.gov (United States)

    Barnett, Alex H; Magland, Jeremy F; Greengard, Leslie F

    2016-05-01

    The throughput of electrophysiological recording is growing rapidly, allowing thousands of simultaneous channels, and there is a growing variety of spike sorting algorithms designed to extract neural firing events from such data. This creates an urgent need for standardized, automatic evaluation of the quality of neural units output by such algorithms. We introduce a suite of validation metrics that assess the credibility of a given automatic spike sorting algorithm applied to a given dataset. By rerunning the spike sorter two or more times, the metrics measure stability under various perturbations consistent with variations in the data itself, making no assumptions about the internal workings of the algorithm, and minimal assumptions about the noise. We illustrate the new metrics on standard sorting algorithms applied to both in vivo and ex vivo recordings, including a time series with overlapping spikes. We compare the metrics to existing quality measures, and to ground-truth accuracy in simulated time series. We provide a software implementation. Metrics have until now relied on ground-truth, simulated data, internal algorithm variables (e.g. cluster separation), or refractory violations. By contrast, by standardizing the interface, our metrics assess the reliability of any automatic algorithm without reference to internal variables (e.g. feature space) or physiological criteria. Stability is a prerequisite for reproducibility of results. Such metrics could reduce the significant human labor currently spent on validation, and should form an essential part of large-scale automated spike sorting and systematic benchmarking of algorithms. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. Genetic algorithms used to optimize an artificial neural network design used in neutron spectrometry

    International Nuclear Information System (INIS)

    Arteaga A, T.; Ortiz R, J. M.; Vega C, H. R.

    2016-10-01

    Artificial neural networks (Ann) are widely used; it which consist of an input layer, one or more hidden layers and an output layer; these layers contain neurons and each has connections called weights, where the knowledge are allowed and let to Ann solve problems proposed. These Ann is used to reconstruction of the energy spectrum of neutrons from count rates and develop Bonner sphere neutron dosimetry. Currently, we have developed Ann with high performance and generalization ability. Determine your optimal architecture is usually a difficult task, an exhaustive search of all possible combinations of parameters is rarely possible further training of the neural network with random initial weights can cause two major drawbacks: it can stuck in local minima or converge very slowly. In this project it will be used Genetic Algorithms (Ga); which are based on the principle or analogy of evolution through natural selection and has shown to be very effective in optimizing complex search functions and large spaces or to find a near optimal overall efficiency. The aim is to decrease the architecture in number of hidden neurons and therefore the total number of connections is reducing. The benefits obtained by optimizing the network are that the number of connections would be considerably smaller and thus the computational complexity, hardware integration, resources will be lower such that will allow to be even more viable implemented. To use the Ga three problems must be solve: 1) coding the problem into chromosomes. 2) Construct a fitness function. 3) Proper selection of genetic operators; crossover, selection, mutation. As a result, the scientific knowledge obtained can to be applied to similar problems having a reference parameters used and their impact on the optimization would to be generated. It concluded that the input layer and output are subject to the problem; the Ga propose the optimal number of neurons in the hidden layer without losing the quality of the

  16. Fractional Hopfield Neural Networks: Fractional Dynamic Associative Recurrent Neural Networks.

    Science.gov (United States)

    Pu, Yi-Fei; Yi, Zhang; Zhou, Ji-Liu

    2017-10-01

    This paper mainly discusses a novel conceptual framework: fractional Hopfield neural networks (FHNN). As is commonly known, fractional calculus has been incorporated into artificial neural networks, mainly because of its long-term memory and nonlocality. Some researchers have made interesting attempts at fractional neural networks and gained competitive advantages over integer-order neural networks. Therefore, it is naturally makes one ponder how to generalize the first-order Hopfield neural networks to the fractional-order ones, and how to implement FHNN by means of fractional calculus. We propose to introduce a novel mathematical method: fractional calculus to implement FHNN. First, we implement fractor in the form of an analog circuit. Second, we implement FHNN by utilizing fractor and the fractional steepest descent approach, construct its Lyapunov function, and further analyze its attractors. Third, we perform experiments to analyze the stability and convergence of FHNN, and further discuss its applications to the defense against chip cloning attacks for anticounterfeiting. The main contribution of our work is to propose FHNN in the form of an analog circuit by utilizing a fractor and the fractional steepest descent approach, construct its Lyapunov function, prove its Lyapunov stability, analyze its attractors, and apply FHNN to the defense against chip cloning attacks for anticounterfeiting. A significant advantage of FHNN is that its attractors essentially relate to the neuron's fractional order. FHNN possesses the fractional-order-stability and fractional-order-sensitivity characteristics.

  17. Space polypropulsion

    Science.gov (United States)

    Kellett, B. J.; Griffin, D. K.; Bingham, R.; Campbell, R. N.; Forbes, A.; Michaelis, M. M.

    2008-05-01

    Hybrid space propulsion has been a feature of most space missions. Only the very early rocket propulsion experiments like the V2, employed a single form of propulsion. By the late fifties multi-staging was routine and the Space Shuttle employs three different kinds of fuel and rocket engines. During the development of chemical rockets, other forms of propulsion were being slowly tested, both theoretically and, relatively slowly, in practice. Rail and gas guns, ion engines, "slingshot" gravity assist, nuclear and solar power, tethers, solar sails have all seen some real applications. Yet the earliest type of non-chemical space propulsion to be thought of has never been attempted in space: laser and photon propulsion. The ideas of Eugen Saenger, Georgii Marx, Arthur Kantrowitz, Leik Myrabo, Claude Phipps and Robert Forward remain Earth-bound. In this paper we summarize the various forms of nonchemical propulsion and their results. We point out that missions beyond Saturn would benefit from a change of attitude to laser-propulsion as well as consideration of hybrid "polypropulsion" - which is to say using all the rocket "tools" available rather than possibly not the most appropriate. We conclude with three practical examples, two for the next decades and one for the next century; disposal of nuclear waste in space; a grand tour of the Jovian and Saturnian moons - with Huygens or Lunoxod type, landers; and eventually mankind's greatest space dream: robotic exploration of neighbouring planetary systems.

  18. Does bilingualism contribute to cognitive reserve? Cognitive and neural perspectives.

    Science.gov (United States)

    Guzmán-Vélez, Edmarie; Tranel, Daniel

    2015-01-01

    Cognitive reserve refers to how individuals actively utilize neural resources to cope with neuropathology to maintain cognitive functioning. The present review aims to critically examine the literature addressing the relationship between bilingualism and cognitive reserve to elucidate whether bilingualism delays the onset of cognitive and behavioral manifestations of dementia. Potential neural mechanisms behind this relationship are discussed. PubMed and PsycINFO databases were searched (through January 2014) for original research articles in English or Spanish languages. The following search strings were used as keywords for study retrieval: "bilingual AND reserve," "reserve AND neural mechanisms," and "reserve AND multilingualism." Growing scientific evidence suggests that lifelong bilingualism contributes to cognitive reserve and delays the onset of Alzheimer's disease symptoms, allowing bilingual individuals affected by Alzheimer's disease to live an independent and richer life for a longer time than their monolingual counterparts. Lifelong bilingualism is related to more efficient use of brain resources that help individuals maintain cognitive functioning in the presence of neuropathology. We propose multiple putative neural mechanisms through which lifelong bilinguals cope with neuropathology. The roles of immigration status, education, age of onset, proficiency, and frequency of language use on the relationship between cognitive reserve and bilingualism are considered. Implications of these results for preventive practices and future research are discussed. PsycINFO Database Record (c) 2015 APA, all rights reserved.

  19. Does Bilingualism Contribute to Cognitive Reserve? Cognitive and Neural Perspectives

    Science.gov (United States)

    Guzmán-Vélez, Edmarie; Tranel, Daniel

    2015-01-01

    Objective Cognitive reserve refers to how individuals actively utilize neural resources to cope with neuropathology in order to maintain cognitive functioning. The present review aims to critically examine the literature addressing the relationship between bilingualism and cognitive reserve in order to elucidate whether bilingualism delays the onset of cognitive and behavioral manifestations of dementia. Potential neural mechanisms behind this relationship are discussed. Method Pubmed and PsychINFO databases were searched (through January 2014) for original research articles in English or Spanish languages. The following search strings were employed as keywords for study retrieval: ‘bilingual AND reserve’, ‘reserve AND neural mechanisms’, and ‘reserve AND multilingualism’. Results Growing scientific evidence suggests that lifelong bilingualism contributes to cognitive reserve and delays the onset of Alzheimer's disease symptoms, allowing bilingual individuals affected by Alzheimer's disease to live an independent and richer life for a longer time than their monolingual counterparts. Lifelong bilingualism is related to more efficient use of brain resources that help individuals maintain cognitive functioning in the presence of neuropathology. We propose multiple putative neural mechanisms through which lifelong bilinguals cope with neuropathology. The roles of immigration status, education, age of onset, proficiency and frequency of language use on the relationship between cognitive reserve and bilingualism are considered. Conclusions Implications of these results for preventive practices and future research are discussed. PMID:24933492

  20. Measuring space radiation shielding effectiveness

    OpenAIRE

    Bahadori Amir; Semones Edward; Ewert Michael; Broyan James; Walker Steven

    2017-01-01

    Passive radiation shielding is one strategy to mitigate the problem of space radiation exposure. While space vehicles are constructed largely of aluminum, polyethylene has been demonstrated to have superior shielding characteristics for both galactic cosmic rays and solar particle events due to the high hydrogen content. A method to calculate the shielding effectiveness of a material relative to reference material from Bragg peak measurements performed using energetic heavy charged particles ...