WorldWideScience

Sample records for neural nets amanda

  1. Kunstige neurale net

    DEFF Research Database (Denmark)

    Hørning, Annette

    1994-01-01

    Artiklen beskæftiger sig med muligheden for at anvende kunstige neurale net i forbindelse med datamatisk procession af naturligt sprog, specielt automatisk talegenkendelse.......Artiklen beskæftiger sig med muligheden for at anvende kunstige neurale net i forbindelse med datamatisk procession af naturligt sprog, specielt automatisk talegenkendelse....

  2. Building Neural Net Software

    OpenAIRE

    Neto, João Pedro; Costa, José Félix

    1999-01-01

    In a recent paper [Neto et al. 97] we showed that programming languages can be translated on recurrent (analog, rational weighted) neural nets. The goal was not efficiency but simplicity. Indeed we used a number-theoretic approach to machine programming, where (integer) numbers were coded in a unary fashion, introducing a exponential slow down in the computations, with respect to a two-symbol tape Turing machine. Implementation of programming languages in neural nets turns to be not only theo...

  3. Texture Based Image Analysis With Neural Nets

    Science.gov (United States)

    Ilovici, Irina S.; Ong, Hoo-Tee; Ostrander, Kim E.

    1990-03-01

    In this paper, we combine direct image statistics and spatial frequency domain techniques with a neural net model to analyze texture based images. The resultant optimal texture features obtained from the direct and transformed image form the exemplar pattern of the neural net. The proposed approach introduces an automated texture analysis applied to metallography for determining the cooling rate and mechanical working of the materials. The results suggest that the proposed method enhances the practical applications of neural nets and texture extraction features.

  4. CDMA and TDMA based neural nets.

    Science.gov (United States)

    Herrero, J C

    2001-06-01

    CDMA and TDMA telecommunication techniques were established long time ago, but they have acquired a renewed presence due to the rapidly increasing mobile phones demand. In this paper, we are going to see they are suitable for neural nets, if we leave the concept "connection" between processing units and we adopt the concept "messages" exchanged between them. This may open the door to neural nets with a higher number of processing units and flexible configuration.

  5. Classification using Bayesian neural nets

    NARCIS (Netherlands)

    J.C. Bioch (Cor); O. van der Meer; R. Potharst (Rob)

    1995-01-01

    textabstractRecently, Bayesian methods have been proposed for neural networks to solve regression and classification problems. These methods claim to overcome some difficulties encountered in the standard approach such as overfitting. However, an implementation of the full Bayesian approach to

  6. Neural Nets for Scene Analysis

    Science.gov (United States)

    1992-09-01

    decision boundaries produced for the arificial database when prototypes are Se- feature 1 lected from reduced training set. ly selected from the 383...CLASSIFIER HIT MISS MOPOGIA CORRELATION LOW-LEVEL VISION IVARL&MCE NEURAL NE. (O D ILER) SE CORRELATION REUCE ETC.(OR I F RS)DI4ENSIONAIM AND TRAINING...A) = J11’, + tOi2Z2 + 61311’ (4) SPE Vol. 1608 mitalwg’t Robots and Coniutef Vision X (991)/501 - "X,, ,v ) X 1112 1P Pa P2 P2 .. 2 33 CL AS INPUT

  7. Results from AMANDA

    CERN Document Server

    Wiebusch, C; Bai, X; Barwick, S W; Becka, T; Becker, K H; Bertrand, D; Bernadini, E; Binon, Freddy G; Biron, A; Boser, S; Botner, O; Bouchta, A; Bouhali, O; Burgess, T; Carius, S; Castermans, T; Chen, A; Chirkin, D; Conrad, J; Cooley, J; Cowen, D F; Davour, A; De Clercq, C; De Young, T R; Desiati, P; Dewulf, J P; Doksus, P; Ekstrom, P; Feser, T; Gaisser, T K; Gaug, M; Gerhardt, L; Goldschmidt, A; Hallgren, A; Halzen, F; Hanson, K; Hardtke, R; Hauschildt, T; Hellwig, M; Herquet, P; Hill, G C; Hulth, P O; Hundertmark, S; Jacobsen, J; Karle, A; Koci, B; Köpke, L; Kowalski, M; Kühn, K; Lamoureux, J I; Leich, H; Leuthold, M J; Lindahl, P; Liubarsky, I; Madsen, J; Marciniewski, P; Matis, H S; McParland, C P; Minaeva, Y; Minocinovic, P; Mock, P C; Morse, R; Nahnhauer, R; Neunhoffer, T; Niessen, P; Nygren, D R; Ögelman, H B; Olbrechts, P; Pérez de los Heros, C; Pohl, A C; Price, P B; Przybylski, G T; Rawlins, K; Resconi, E; Rhode, W; Ribordy, M; Richter, S; Rodríguez-Martino, J; Ross, D; Sander, H G; Schmidt, T; Schneider, D; Schwarz, R; Silvestri, A; Solarz, M; Spiczak, G M; Spiering, C; Steele, D; Steffen, P; Stokstad, R G; Sudhoff, P; Sulanke, K H; Taboada, I; Thollander, L; Tilav, S; Walck, C; Weinheimer, C; Wiebusch, C; Wiedemann, C; Wischnewski, R; Wissing, H; Woschnagg, K; Yodh, G B; Young, S

    2002-01-01

    The Antarctic Muon and Neutrino Detector Array (AMANDA) is a high- energy neutrino telescope operating at the geographic South Pole. It is a lattice of photomultiplier tubes buried deep in the polar ice. The primary goal of this detector is to discover astrophysical sources of high energy neutrinos. We describe the detector methods of operation and present results from the AMANDA-B10 prototype. We demonstrate the improved sensitivity of the current AMANDA-II detector. We conclude with an outlook to the envisioned sensitivity of the future IceCube detector. (37 refs).

  8. Document analysis with neural net circuits

    Science.gov (United States)

    Graf, Hans Peter

    1994-01-01

    Document analysis is one of the main applications of machine vision today and offers great opportunities for neural net circuits. Despite more and more data processing with computers, the number of paper documents is still increasing rapidly. A fast translation of data from paper into electronic format is needed almost everywhere, and when done manually, this is a time consuming process. Markets range from small scanners for personal use to high-volume document analysis systems, such as address readers for the postal service or check processing systems for banks. A major concern with present systems is the accuracy of the automatic interpretation. Today's algorithms fail miserably when noise is present, when print quality is poor, or when the layout is complex. A common approach to circumvent these problems is to restrict the variations of the documents handled by a system. In our laboratory, we had the best luck with circuits implementing basic functions, such as convolutions, that can be used in many different algorithms. To illustrate the flexibility of this approach, three applications of the NET32K circuit are described in this short viewgraph presentation: locating address blocks, cleaning document images by removing noise, and locating areas of interest in personal checks to improve image compression. Several of the ideas realized in this circuit that were inspired by neural nets, such as analog computation with a low resolution, resulted in a chip that is well suited for real-world document analysis applications and that compares favorably with alternative, 'conventional' circuits.

  9. Beyond Pattern Recognition With Neural Nets

    Science.gov (United States)

    Arsenault, Henri H.; Macukow, Bohdan

    1989-02-01

    Neural networks are finding many areas of application. Although they are particularly well-suited for applications related to associative recall such as content-addressable memories, neural nets can perform many other applications ranging from logic operations to the solution of optimization problems. The training of a recently introduced model to perform boolean logical operations such as XOR is described. Such simple systems can be combined to perform any complex boolean operation. Any complex task consisting of parallel and serial operations including fuzzy logic that can be described in terms of input-output relations can be accomplished by combining modules such as the ones described here. The fact that some modules can carry out their functions even when their inputs contain erroneous data, and the fact that each module can carry out its functions in parallel with itself and other modules promises some interesting applications.

  10. Recent Results from AMANDA

    CERN Multimedia

    Wiebusch, C

    2001-01-01

    The main aim of the AMANDA-Experiment at the South Pole is the detection of High Energy (> TeV) Neutrinos of galactic or extra-galactic origin. For this reason large photomultipliers, mounted in pressure spheres, are deployed into the deep (> 1.5km) Antarctic glacier. These photomultipliers detect Cherenkov light emitted by charged secondary particles, which are produced in neutrino interactions inside or close to the detector.

  11. Real-time applications of neural nets

    Energy Technology Data Exchange (ETDEWEB)

    Spencer, J.E.

    1989-05-01

    Producing, accelerating and colliding very high power, low emittance beams for long periods is a formidable problem in real-time control. As energy has grown exponentially in time so has the complexity of the machines and their control systems. Similar growth rates have occurred in many areas, e.g., improved integrated circuits have been paid for with comparable increases in complexity. However, in this case, reliability, capability and cost have improved due to reduced size, high production and increased integration which allow various kinds of feedback. In contrast, most large complex systems (LCS) are perceived to lack such possibilities because only one copy is made. Neural nets, as a metaphor for LCS, suggest ways to circumvent such limitations. It is argued that they are logically equivalent to multi-loop feedback/forward control of faulty systems. While complimentary to AI, they mesh nicely with characteristics desired for real-time systems. Such issues are considered, examples given and possibilities discussed. 21 refs., 6 figs.

  12. Accelerator diagnosis and control by Neural Nets

    Energy Technology Data Exchange (ETDEWEB)

    Spencer, J.E.

    1989-01-01

    Neural Nets (NN) have been described as a solution looking for a problem. In the last conference, Artificial Intelligence (AI) was considered in the accelerator context. While good for local surveillance and control, its use for large complex systems (LCS) was much more restricted. By contrast, NN provide a good metaphor for LCS. It can be argued that they are logically equivalent to multi-loop feedback/forward control of faulty systems, and therefore provide an ideal adaptive control system. Thus, where AI may be good for maintaining a 'golden orbit,' NN should be good for obtaining it via a quantitative approach to 'look and adjust' methods like operator tweaking which use pattern recognition to deal with hardware and software limitations, inaccuracies or errors as well as imprecise knowledge or understanding of effects like annealing and hysteresis. Further, insights from NN allow one to define feasibility conditions for LCS in terms of design constraints and tolerances. Hardware and software implications are discussed and several LCS of current interest are compared and contrasted. 15 refs., 5 figs.

  13. 22nd Italian Workshop on Neural Nets

    CERN Document Server

    Bassis, Simone; Esposito, Anna; Morabito, Francesco

    2013-01-01

    This volume collects a selection of contributions which has been presented at the 22nd Italian Workshop on Neural Networks, the yearly meeting of the Italian Society for Neural Networks (SIREN). The conference was held in Italy, Vietri sul Mare (Salerno), during May 17-19, 2012. The annual meeting of SIREN is sponsored by International Neural Network Society (INNS), European Neural Network Society (ENNS) and IEEE Computational Intelligence Society (CIS). The book – as well as the workshop-  is organized in three main components, two special sessions and a group of regular sessions featuring different aspects and point of views of artificial neural networks and natural intelligence, also including applications of present compelling interest.

  14. Optical neural net for classifying imaging spectrometer data

    Science.gov (United States)

    Barnard, Etienne; Casasent, David P.

    1989-01-01

    The problem of determining the composition of an unknown input mixture from its measured spectrum, given the spectra of a number of elements, is studied. The Hopfield minimization procedure was used to express the determination of the compositions as a problem suitable for solution by neural nets. A mathematical description of the problem was developed and used as a basis for a neural network solution and an optical implementation.

  15. AMANDA: Status and latest Results

    CERN Document Server

    Ribordy, M; Ahrens, J; Albrecht, H; Bai, X; Bay, R; Bartelt, M; Barwick, S W; Becka, T; Becker, K H; Becker, J K; Bernardini, E; Bertrand, D; Boersma, D J; Boser, S; Botner, O; Bouchta, A; Bouhali, O; Braun, J; Burgess, C; Burgess, T; Castermans, T; Chirkin, D; Collin, B; Conrad, J; Cooley, J; Cowen, D F; Davour, A; De Clercq, C; De Young, T R; Desiati, P; Ekstrom, P; Feser, T; Gaisser, T K; Ganugapati, R; Geenen, H; Gerhardt, L; Goldschmidt, A; Gross, A; Hallgren, A; Halzen, F; Hanson, K; Hardtke, R; Harenberg, T; Hauschildt, T; Helbing, K; Hellwig, M; Herquet, P; Hill, G C; Hodges, J; Hubert, D; Hughey, B; Hulth, P O; Hultqvist, K; Hundertmark, S; Jacobsen, J; Kampert, K H; Karle, A; Kelley, J; Kestel, M; Köpke, L; Kowalski, M; Krasberg, M; Kühn, K; Leich, H; Leuthold, M; Liubarsky, I; Madsen, J; Mandli, K; Marciniewski, P; Matis, H S; McParland, C P; Messarius, T; Minaeva, Y; Miocinovic, P; Morse, R; Munich, K; Nahnhauer, R; Nam, J W; Neunhoffer, T; Niessen, P; Nygren, D R; Ögelman, H B; Olbrechts, P; Pérez de los Heros, C; Pohl, A C; Porrata, R; Price, P B; Przybylski, G T; Rawlins, K; Resconi, E; Rhode, W; Ribordy, M; Richter, S; Rodríguez-Martino, J; Sander, H G; Schinarakis, K; Schlenstedt, S; Schneider, D; Schwarz, R; Silvestri, A; Solarz, M; Spiczak, G M; Spiering, C; Stamatikos, M; Steele, D; Steffen, P; Stokstad, R G; Sulanke, K H; Taboada, I; Thollander, L; Tilav, S; Wagner, W; Walck, C; Walter, M; Wang, Y R; Wiebusch, C; Wischnewski, R; Wissing, H; Woschnagg, K; Yodh, G; Ribordy, Mathieu

    2004-01-01

    We briefly review some of the recent AMANDA results emphasizing the all flavor capabilities of the high energy neutrino telescope, important in the context of equal neutrino mixing from distant sources at Earth. Together with a report on a preliminary UHE neutrino flux limit, the course of our progress in the quest for point sources is described. Finally, a 1 year preliminary limit of AMANDA-II to neutralino cold dark matter (CDM) candidates, annihilating in the center of the Sun, for various MSSM parameter choices is presented and discussed.

  16. Classification of handwritten digits using a RAM neural net architecture

    DEFF Research Database (Denmark)

    Jørgensen, T.M.

    1997-01-01

    Results are reported on the task of recognizing handwritten digits without any advanced pre-processing. The result are obtained using a RAM-based neural network, making use of small receptive fields. Furthermore, a technique that introduces negative weights into the RAM net is reported. The results...

  17. Translating feedforward neural nets to SOM-like maps

    NARCIS (Netherlands)

    van der Zwaag, B.J.; Spaanenburg, Lambert; Slump, Cornelis H.

    A major disadvantage of feedforward neural networks is still the difficulty to gain insight into their internal functionality. This is much less the case for, e.g., nets that are trained unsupervised, such as Kohonen’s self-organizing feature maps (SOMs). These offer a direct view into the stored

  18. Physics Results from the AMANDA Neutrino Detector

    CERN Document Server

    Ahrens, J; Bai, X; Barouch, G; Barwick, S W; Bay, R C; Becka, T; Becker, K; Bertrand, D; Biron, A; Boser, S; Booth, J R A; Botner, O; Bouchta, A; Boyce, M M; Carius, S; Chen, A; Chirkin, D; Conrad, J; Cooley, J; Costa, C G S; Cowen, D F; De Clercq, C; De Young, T; Desiati, P; Dewulf, J P; Doksus, P; Edsjö, J; Ekstrom, P; Feser, T; Frère, J M; Gaug, M; Gerhardt, L; Goldschmidt, A; Hallgren, A; Halzen, F; Hanson, K; Hardtke, R; Hauschildt, T; Hellwig, M; Herquet, P; Hill, C G; Hulth, P O; Hundertmark, S; Jacobsen, J; Karle, A; Kim, J; Koci, B; Köpke, L; Kühn, K; Lamoureux, J I; Leich, H; Leuthold, M; Lindahl, P; Madsen, J; Marciniewski, P; Matis, H S; Minaeva, Y; Miocinovic, P; Morse, R; Neunhoffer, T; Niessen, P; Nygren, D R; Ogelman, H; Olbrechts, P; Perez de los Heros, C; Pohl, A; Price, P B; Przybylski, G T; Rawlins, K; Reed, C; Rhode, W; Ribordy, M; Richter, S; Martino, J R; Romenesko, P; Ross, D; Sander, H G; Schmidt, T; Schneider, D; Silvestri, A; Solarz, M; Spiczak, G M; Spiering, C; Starinsky, N; Steele, D; Steffen, P; Stokstad, R G; Sudhoff, P; Sulanke, K H; Taboada, I; Donckt, M V; Walck, C; Weinheimer, C; Wiebusch, C H; Wischnewski, R; Wissing, H; Woschnagg, K; Yodh, G; Young, S

    2001-01-01

    In the winter season of 2000, the AMANDA (Antarctic Muon And Neutrino Detector Array) detector was completed to its final state. We report on major physics results obtained from the AMANDA-B10 detector, as well as initial results of the full AMANDA-II detector.

  19. Computation and control with neural nets

    Energy Technology Data Exchange (ETDEWEB)

    Corneliusen, A.; Terdal, P.; Knight, T.; Spencer, J.

    1989-10-04

    As energies have increased exponentially with time so have the size and complexity of accelerators and control systems. NN may offer the kinds of improvements in computation and control that are needed to maintain acceptable functionality. For control their associative characteristics could provide signal conversion or data translation. Because they can do any computation such as least squares, they can close feedback loops autonomously to provide intelligent control at the point of action rather than at a central location that requires transfers, conversions, hand-shaking and other costly repetitions like input protection. Both computation and control can be integrated on a single chip, printed circuit or an optical equivalent that is also inherently faster through full parallel operation. For such reasons one expects lower costs and better results. Such systems could be optimized by integrating sensor and signal processing functions. Distributed nets of such hardware could communicate and provide global monitoring and multiprocessing in various ways e.g. via token, slotted or parallel rings (or Steiner trees) for compatibility with existing systems. Problems and advantages of this approach such as an optimal, real-time Turing machine are discussed. Simple examples are simulated and hardware implemented using discrete elements that demonstrate some basic characteristics of learning and parallelism. Future microprocessors' are predicted and requested on this basis. 19 refs., 18 figs.

  20. Fast neural net simulation with a DSP processor array.

    Science.gov (United States)

    Muller, U A; Gunzinger, A; Guggenbuhl, W

    1995-01-01

    This paper describes the implementation of a fast neural net simulator on a novel parallel distributed-memory computer. A 60-processor system, named MUSIC (multiprocessor system with intelligent communication), is operational and runs the backpropagation algorithm at a speed of 330 million connection updates per second (continuous weight update) using 32-b floating-point precision. This is equal to 1.4 Gflops sustained performance. The complete system with 3.8 Gflops peak performance consumes less than 800 W of electrical power and fits into a 19-in rack. While reaching the speed of modern supercomputers, MUSIC still can be used as a personal desktop computer at a researcher's own disposal. In neural net simulation, this gives a computing performance to a single user which was unthinkable before. The system's real-time interfaces make it especially useful for embedded applications.

  1. Artificial neural nets application in the cotton yarn industry

    Directory of Open Access Journals (Sweden)

    Gilberto Clóvis Antoneli

    2016-06-01

    Full Text Available The competitiveness in the yarn production sector has led companies to search for solutions to attain quality yarn at a low cost. Today, the difference between them, and thus the sector, is in the raw material, meaning processed cotton and its characteristics. There are many types of cotton with different characteristics due to its production region, harvest, storage and transportation. Yarn industries work with cotton mixtures, which makes it difficult to determine the quality of the yarn produced from the characteristics of the processed fibers. This study uses data from a conventional spinning, from a raw material made of 100% cotton, and presents a solution with artificial neural nets that determine the thread quality information, using the fibers’ characteristics values and settings of some process adjustments. In this solution a neural net of the type MultiLayer Perceptron with 11 entry neurons (8 characteristics of the fiber and 3 process adjustments, 7 output neurons (yarn quality and two types of training, Back propagation and Conjugate gradient descent. The selection and organization of the production data of the yarn industry of the cocamar® indústria de fios company are described, to apply the artificial neural nets developed. In the application of neural nets to determine yarn quality, one concludes that, although the ideal precision of absolute values is lacking, the presented solution represents an excellent tool to define yarn quality variations when modifying the raw material composition. The developed system enables a simulation to define the raw material percentage mixture to be processed in the plant using the information from the stocked cotton packs, thus obtaining a mixture that maintains the stability of the entire productive process.

  2. Neural Net Gains Estimation Based on an Equivalent Model

    Directory of Open Access Journals (Sweden)

    Karen Alicia Aguilar Cruz

    2016-01-01

    Full Text Available A model of an Equivalent Artificial Neural Net (EANN describes the gains set, viewed as parameters in a layer, and this consideration is a reproducible process, applicable to a neuron in a neural net (NN. The EANN helps to estimate the NN gains or parameters, so we propose two methods to determine them. The first considers a fuzzy inference combined with the traditional Kalman filter, obtaining the equivalent model and estimating in a fuzzy sense the gains matrix A and the proper gain K into the traditional filter identification. The second develops a direct estimation in state space, describing an EANN using the expected value and the recursive description of the gains estimation. Finally, a comparison of both descriptions is performed; highlighting the analytical method describes the neural net coefficients in a direct form, whereas the other technique requires selecting into the Knowledge Base (KB the factors based on the functional error and the reference signal built with the past information of the system.

  3. Neural system modeling and simulation using Hybrid Functional Petri Net.

    Science.gov (United States)

    Tang, Yin; Wang, Fei

    2012-02-01

    The Petri net formalism has been proved to be powerful in biological modeling. It not only boasts of a most intuitive graphical presentation but also combines the methods of classical systems biology with the discrete modeling technique. Hybrid Functional Petri Net (HFPN) was proposed specially for biological system modeling. An array of well-constructed biological models using HFPN yielded very interesting results. In this paper, we propose a method to represent neural system behavior, where biochemistry and electrical chemistry are both included using the Petri net formalism. We built a model for the adrenergic system using HFPN and employed quantitative analysis. Our simulation results match the biological data well, showing that the model is very effective. Predictions made on our model further manifest the modeling power of HFPN and improve the understanding of the adrenergic system. The file of our model and more results with their analysis are available in our supplementary material.

  4. Perineuronal net, CSPG receptor and their regulation of neural plasticity.

    Science.gov (United States)

    Miao, Qing-Long; Ye, Qian; Zhang, Xiao-Hui

    2014-08-25

    Perineuronal nets (PNNs) are reticular structures resulting from the aggregation of extracellular matrix (ECM) molecules around the cell body and proximal neurite of specific population of neurons in the central nervous system (CNS). Since the first description of PNNs by Camillo Golgi in 1883, the molecular composition, developmental formation and potential functions of these specialized extracellular matrix structures have only been intensively studied over the last few decades. The main components of PNNs are hyaluronan (HA), chondroitin sulfate proteoglycans (CSPGs) of the lectican family, link proteins and tenascin-R. PNNs appear late in neural development, inversely correlating with the level of neural plasticity. PNNs have long been hypothesized to play a role in stabilizing the extracellular milieu, which secures the characteristic features of enveloped neurons and protects them from the influence of malicious agents. Aberrant PNN signaling can lead to CNS dysfunctions like epilepsy, stroke and Alzheimer's disease. On the other hand, PNNs create a barrier which constrains the neural plasticity and counteracts the regeneration after nerve injury. Digestion of PNNs with chondroitinase ABC accelerates functional recovery from the spinal cord injury and restores activity-dependent mechanisms for modifying neuronal connections in the adult animals, indicating that PNN is an important regulator of neural plasticity. Here, we review recent progress in the studies on the formation of PNNs during early development and the identification of CSPG receptor - an essential molecular component of PNN signaling, along with a discussion on their unique regulatory roles in neural plasticity.

  5. Unfolding code for neutron spectrometry based on neural nets technology

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz R, J. M.; Vega C, H. R., E-mail: morvymm@yahoo.com.mx [Universidad Autonoma de Zacatecas, Unidad Academica de Ingenieria Electrica, Apdo. Postal 336, 98000 Zacatecas (Mexico)

    2012-10-15

    The most delicate part of neutron spectrometry, is the unfolding process. The derivation of the spectral information is not simple because the unknown is not given directly as a result of the measurements. The drawbacks associated with traditional unfolding procedures have motivated the need of complementary approaches. Novel methods based on Artificial Neural Networks have been widely investigated. In this work, a neutron spectrum unfolding code based on neural nets technology is presented. This unfolding code called Neutron Spectrometry and Dosimetry by means of Artificial Neural Networks was designed in a graphical interface under LabVIEW programming environment. The core of the code is an embedded neural network architecture, previously optimized by the {sup R}obust Design of Artificial Neural Networks Methodology{sup .} The main features of the code are: is easy to use, friendly and intuitive to the user. This code was designed for a Bonner Sphere System based on a {sup 6}Lil(Eu) neutron detector and a response matrix expressed in 60 energy bins taken from an International Atomic Energy Agency compilation. The main feature of the code is that as entrance data, only seven rate counts measurement with a Bonner spheres spectrometer are required for simultaneously unfold the 60 energy bins of the neutron spectrum and to calculate 15 dosimetric quantities, for radiation protection porpoises. This code generates a full report in html format with all relevant information. (Author)

  6. Webs, cell assemblies, and chunking in neural nets: introduction.

    Science.gov (United States)

    Wickelgren, W A

    1999-03-01

    This introduction to Wickelgren (1992), describes a theory of idea representation and learning in the cerebral cortex and seven properties of Hebb's (1949) formulation of cell assemblies that have played a major role in all such neural net models. Ideas are represented in the cerebral cortex by webs (innate cell assemblies), using sparse coding with sparse, all-or-none, innate linking. Recruiting a web to represent a new idea is called chunking. The innate links that bind the neurons of a web are basal dendritic synapses. Learning modifies the apical dendritic synapses that associate neurons in one web to neurons in another web.

  7. Results from the AMANDA detector

    CERN Document Server

    Ackermann, M; Albrecht, H; Bai, X; Bartelt, M; Barwick, S W; Bay, R; Becka, T; Becker, J K; Becker, K H; Bernardini, E; Bertrand, D; Boersma, D J; Boser, S; Botner, O; Bouchta, A; Bouhali, O; Braun, J; Burgess, C; Burgess, T; Castermans, T; Chirkin, D; Collin, B; Conrad, J; Cooley, J; Cowen, D F; Davour, A; De Clercq, C; Pérez de los Heros, C; De Young, T R; Desiati, P; Ekstrom, P; Feser, T; Gaisser, T K; Ganugapati, R; Geenen, H; Gerhardt, L; Goldschmidt, A; Gross, A; Hallgren, A; Halzen, F; Hanson, K; Hardtke, R; Harenberg, T; Hauschildt, T; Helbing, K; Hellwig, M; Herquet, P; Hill, G C; Hodges, J; Hubert, D; Hughey, B; Hulth, P O; Hultqvist, K; Hundertmark, S; Jacobsen, J; Kampert, K H; Karle, A; Kelley, J; Kestel, M; Köpke, L; Kowalski, M; Krasberg, M; Kühn, K; Leich, H; Leuthold, M; Liubarsky, I; Madsen, J; Mandli, K; Marciniewski, P; Martino, J R; Matis, H S; McParland, C P; Messarius, T; Minaeva, Y; Miocinovic, P; Morse, R; Munich, K; Nahnhauer, R; Nam, J W; Neunhoffer, T; Niessen, P; Nygren, D R; Ogelman, H; Olbrechts, P; Pohl, A C; Porrata, R; Price, P B; Przybylski, G T; Rawlins, K; Resconi, E; Rhode, W; Ribordy, M; Richter, S; Sander, H G; Schinarakis, K; Schlenstedt, S; Schneider, D; Schwarz, R; Silvestri, A; Solarz, M; Spiczak, G M; Spiering, C; Stamatikos, M; Steele, D; Steffen, P; Stokstad, R G; Sulanke, K H; Taboada, I; Thollander, L; Tilav, S; Wagner, W; Walck, C; Walter, M; Wang, Y R; Wiebusch, C; Wischnewski, R; Wissing, H; Woschnagg, K; Yodh, G

    2004-01-01

    The Antarctic Muon And Neutrino Detector Array (AMANDA) is a high- energy neutrino telescope based at the geographic south pole. It is a lattice of photomultiplier tubes buried deep in the polar ice, which is used as interaction and detection medium. The primary goal of this detector is the observation of astronomical sources of high-energy neutrinos. This paper shows the latest results of the search for a diffuse flux of extraterrestrial nu /sub mu /s with energies between 10/sup 11/ eV and 10/sup 18/ eV, nu /sub mu /s emitted from point sources and nu /sub mu /s from dark matter annihilation in the Earth and the Sun.

  8. Selected recent results from AMANDA

    CERN Document Server

    Andrés, E; Bai, X; Barouch, G; Barwick, S W; Bay, R C; Becker, K H; Bergström, L; Bertrand, D; Bierenbaum, D; Biron, A; Booth, J; Botner, O; Bouchta, A; Boyce, M M; Carius, S; Chen, A; Chirkin, D; Conrad, J; Cooley, J; Costa, C G S; Cowen, D F; Dailing, J; Dalberg, E; De Young, T R; Desiati, P; Dewulf, J P; Doksus, P; Edsjö, J; Ekstrom, P; Erlandsson, B; Feser, T; Gaug, M; Goldschmidt, A; Goobar, A; Gray, L; Haase, H; Hallgren, A; Halzen, F; Hanson, K; Hardtke, R; He, Y D; Hellwig, M; Heukenkamp, H; Hill, G C; Hulth, P O; Hundertmark, S; Jacobsen, J; Kandhadai, V; Karle, A; Kim, J; Koci, B; Köpke, L; Kowalski, M; Leich, H; Leuthold, M; Lindahl, P; Liubarsky, I; Loaiza, P; Lowder, D M; Ludvig, J; Madsen, J; Marciniewski, P; Matis, H S; Mihályi, A; Mikolajski, T; Miller, T C; Minaeva, Y; Miocinovic, P; Mock, P C; Morse, R; Neunhoffer, T; Newcomer, F M; Niessen, P; Nygren, D R; Ogelman, H; Heros, C P D L; Porrata, R; Price, P B; Rawlins, K; Reed, C; Rhode, W; Richards, A; Richter, S; Martino, J R; Romenesko, P; Ross, D; Rubinstein, H; Sander, H G; Scheider, T; Schmidt, T; Schneider, D; Schneider, E; Schwarzl, R; Silvestri, A; Solarz, M; Spiczak, G M; Spiering, C; Starinsky, N; Steele, D; Steffen, P; Stokstad, R G; Streicher, O; Sun, A; Taboada, I; Thollander, L; Thon, T; Tilav, S; Usechak, N; Donckt, M V; Walck, C; Weinheimer, C; Wiebusch, C; Wischnewski, R; Wissing, H; Woschnagg, K; Wu, W; Yodh, G; Young, S

    2001-01-01

    We present a selection of results based on data taken in 1997 with the 302-PMT Antarctic Muon and Neutrino Detector Array-B10 ("AMANDA-B10") array. Atmospheric neutrinos created in the northern hemisphere are observed indirectly through their charged current interactions which produce relativistic, Cherenkov-light-emitting upgoing muons in the South Pole ice cap. The reconstructed angular distribution of these events is in good agreement with expectation and demonstrates the viability of this ice-based device as a neutrino telescope. Studies of nearly vertical upgoing muons limit the available parameter space for WIMP dark matter under the assumption that WIMPS are trapped in the earth's gravitational potential well and annihilate with one another near the earth's center.

  9. Stability Training for Convolutional Neural Nets in LArTPC

    Science.gov (United States)

    Lindsay, Matt; Wongjirad, Taritree

    2017-01-01

    Convolutional Neural Nets (CNNs) are the state of the art for many problems in computer vision and are a promising method for classifying interactions in Liquid Argon Time Projection Chambers (LArTPCs) used in neutrino oscillation experiments. Despite the good performance of CNN's, they are not without drawbacks, chief among them is vulnerability to noise and small perturbations to the input. One solution to this problem is a modification to the learning process called Stability Training developed by Zheng et al. We verify existing work and demonstrate volatility caused by simple Gaussian noise and also that the volatility can be nearly eliminated with Stability Training. We then go further and show that a traditional CNN is also vulnerable to realistic experimental noise and that a stability trained CNN remains accurate despite noise. This further adds to the optimism for CNNs for work in LArTPCs and other applications.

  10. A taxonomy of Deep Convolutional Neural Nets for Computer Vision

    Directory of Open Access Journals (Sweden)

    Suraj eSrinivas

    2016-01-01

    Full Text Available Traditional architectures for solving computer vision problems and the degree of success they enjoyed have been heavily reliant on hand-crafted features. However, of late, deep learning techniques have offered a compelling alternative -- that of automatically learning problem-specific features. With this new paradigm, every problem in computer vision is now being re-examined from a deep learning perspective. Therefore, it has become important to understand what kind of deep networks are suitable for a given problem. Although general surveys of this fast-moving paradigm (i.e. deep-networks exist, a survey specific to computer vision is missing. We specifically consider one form of deep networks widely used in computer vision - convolutional neural networks (CNNs. We start with AlexNet'' as our base CNN and then examine the broad variations proposed over time to suit different applications. We hope that our recipe-style survey will serve as a guide, particularly for novice practitioners intending to use deep-learning techniques for computer vision.

  11. Multilayer neural-net robot controller with guaranteed tracking performance.

    Science.gov (United States)

    Lewis, F L; Yegildirek, A; Liu, K

    1996-01-01

    A multilayer neural-net (NN) controller for a general serial-link rigid robot arm is developed. The structure of the NN controller is derived using a filtered error/passivity approach. No off-line learning phase is needed for the proposed NN controller and the weights are easily initialized. The nonlinear nature of the NN, plus NN functional reconstruction inaccuracies and robot disturbances, mean that the standard delta rule using backpropagation tuning does not suffice for closed-loop dynamic control. Novel online weight tuning algorithms, including correction terms to the delta rule plus an added robust signal, guarantee bounded tracking errors as well as bounded NN weights. Specific bounds are determined, and the tracking error bound can be made arbitrarily small by increasing a certain feedback gain. The correction terms involve a second-order forward-propagated wave in the backpropagation network. New NN properties including the notions of a passive NN, a dissipative NN, and a robust NN are introduced.

  12. The Development of Animal Behavior: From Lorenz to Neural Nets

    Science.gov (United States)

    Bolhuis, Johan J.

    In the study of behavioral development both causal and functional approaches have been used, and they often overlap. The concept of ontogenetic adaptations suggests that each developmental phase involves unique adaptations to the environment of the developing animal. The functional concept of optimal outbreeding has led to further experimental evidence and theoretical models concerning the role of sexual imprinting in the evolutionary process of sexual selection. From a causal perspective it has been proposed that behavioral ontogeny involves the development of various kinds of perceptual, motor, and central mechanisms and the formation of connections among them. This framework has been tested for a number of complex behavior systems such as hunger and dustbathing. Imprinting is often seen as a model system for behavioral development in general. Recent advances in imprinting research have been the result of an interdisciplinary effort involving ethology, neuroscience, and experimental psychology, with a continual interplay between these approaches. The imprinting results are consistent with Lorenz' early intuitive suggestions and are also reflected in the architecture of recent neural net models.

  13. Temporal Modeling of Neural Net Input/Output Behaviors: The Case of XOR

    Directory of Open Access Journals (Sweden)

    Bernard P. Zeigler

    2017-01-01

    Full Text Available In the context of the modeling and simulation of neural nets, we formulate definitions for the behavioral realization of memoryless functions. The definitions of realization are substantively different for deterministic and stochastic systems constructed of neuron-inspired components. In contrast to earlier generations of neural net models, third generation spiking neural nets exhibit important temporal and dynamic properties, and random neural nets provide alternative probabilistic approaches. Our definitions of realization are based on the Discrete Event System Specification (DEVS formalism that fundamentally include temporal and probabilistic characteristics of neuron system inputs, state, and outputs. The realizations that we construct—in particular for the Exclusive Or (XOR logic gate—provide insight into the temporal and probabilistic characteristics that real neural systems might display. Our results provide a solid system-theoretical foundation and simulation modeling framework for the high-performance computational support of such applications.

  14. Neuron-Glia Interactions in Neural Plasticity: Contributions of Neural Extracellular Matrix and Perineuronal Nets

    Directory of Open Access Journals (Sweden)

    Egor Dzyubenko

    2016-01-01

    Full Text Available Synapses are specialized structures that mediate rapid and efficient signal transmission between neurons and are surrounded by glial cells. Astrocytes develop an intimate association with synapses in the central nervous system (CNS and contribute to the regulation of ion and neurotransmitter concentrations. Together with neurons, they shape intercellular space to provide a stable milieu for neuronal activity. Extracellular matrix (ECM components are synthesized by both neurons and astrocytes and play an important role in the formation, maintenance, and function of synapses in the CNS. The components of the ECM have been detected near glial processes, which abut onto the CNS synaptic unit, where they are part of the specialized macromolecular assemblies, termed perineuronal nets (PNNs. PNNs have originally been discovered by Golgi and represent a molecular scaffold deposited in the interface between the astrocyte and subsets of neurons in the vicinity of the synapse. Recent reports strongly suggest that PNNs are tightly involved in the regulation of synaptic plasticity. Moreover, several studies have implicated PNNs and the neural ECM in neuropsychiatric diseases. Here, we highlight current concepts relating to neural ECM and PNNs and describe an in vitro approach that allows for the investigation of ECM functions for synaptogenesis.

  15. Examples of Current and Future Uses of Neural-Net Image Processing for Aerospace Applications

    Science.gov (United States)

    Decker, Arthur J.

    2004-01-01

    Feed forward artificial neural networks are very convenient for performing correlated interpolation of pairs of complex noisy data sets as well as detecting small changes in image data. Image-to-image, image-to-variable and image-to-index applications have been tested at Glenn. Early demonstration applications are summarized including image-directed alignment of optics, tomography, flow-visualization control of wind-tunnel operations and structural-model-trained neural networks. A practical application is reviewed that employs neural-net detection of structural damage from interference fringe patterns. Both sensor-based and optics-only calibration procedures are available for this technique. These accomplishments have generated the knowledge necessary to suggest some other applications for NASA and Government programs. A tomography application is discussed to support Glenn's Icing Research tomography effort. The self-regularizing capability of a neural net is shown to predict the expected performance of the tomography geometry and to augment fast data processing. Other potential applications involve the quantum technologies. It may be possible to use a neural net as an image-to-image controller of an optical tweezers being used for diagnostics of isolated nano structures. The image-to-image transformation properties also offer the potential for simulating quantum computing. Computer resources are detailed for implementing the black box calibration features of the neural nets.

  16. ER fluid applications to vibration control devices and an adaptive neural-net controller

    Science.gov (United States)

    Morishita, Shin; Ura, Tamaki

    1993-07-01

    Four applications of electrorheological (ER) fluid to vibration control actuators and an adaptive neural-net control system suitable for the controller of ER actuators are described: a shock absorber system for automobiles, a squeeze film damper bearing for rotational machines, a dynamic damper for multidegree-of-freedom structures, and a vibration isolator. An adaptive neural-net control system composed of a forward model network for structural identification and a controller network is introduced for the control system of these ER actuators. As an example study of intelligent vibration control systems, an experiment was performed in which the ER dynamic damper was attached to a beam structure and controlled by the present neural-net controller so that the vibration in several modes of the beam was reduced with a single dynamic damper.

  17. Neural-net based real-time economic dispatch for thermal power plants

    Energy Technology Data Exchange (ETDEWEB)

    Djukanovic, M.; Milosevic, B. [Inst. Nikola Tesla, Belgrade (Yugoslavia). Dept. of Power Systems; Calovic, M. [Univ. of Belgrade (Yugoslavia). Dept. of Electrical Engineering; Sobajic, D.J. [Electric Power Research Inst., Palo Alto, CA (United States)

    1996-12-01

    This paper proposes the application of artificial neural networks to real-time optimal generation dispatch of thermal units. The approach can take into account the operational requirements and network losses. The proposed economic dispatch uses an artificial neural network (ANN) for generation of penalty factors, depending on the input generator powers and identified system load change. Then, a few additional iterations are performed within an iterative computation procedure for the solution of coordination equations, by using reference-bus penalty-factors derived from the Newton-Raphson load flow. A coordination technique for environmental and economic dispatch of pure thermal systems, based on the neural-net theory for simplified solution algorithms and improved man-machine interface is introduced. Numerical results on two test examples show that the proposed algorithm can efficiently and accurately develop optimal and feasible generator output trajectories, by applying neural-net forecasts of system load patterns.

  18. Deep Deformable Registration: Enhancing Accuracy by Fully Convolutional Neural Net

    OpenAIRE

    Ghosal, Sayan; Ray, Nilanjan

    2016-01-01

    Deformable registration is ubiquitous in medical image analysis. Many deformable registration methods minimize sum of squared difference (SSD) as the registration cost with respect to deformable model parameters. In this work, we construct a tight upper bound of the SSD registration cost by using a fully convolutional neural network (FCNN) in the registration pipeline. The upper bound SSD (UB-SSD) enhances the original deformable model parameter space by adding a heatmap output from FCNN. Nex...

  19. Fast neural-net based fake track rejection

    CERN Document Server

    De Cian, Michel; Seyfert, Paul; Stahl, Sascha

    2017-01-01

    A neural-network based algorithm to identify fake tracks in the LHCb pattern recognition is presented. This algorithm, called ghost probability, is fast enough to fit into the CPU time budget of the software trigger farm. It allows reducing the fake rate and consequently the combinatorics of the decay reconstructions, as well as the number of tracks that need to be processed by the particle identification algorithms. As a result, it strongly contributes to the achievement of having the same reconstruction online and offline in the LHCb experiment.

  20. Calibration and survey of AMANDA with the SPASE detectors

    Energy Technology Data Exchange (ETDEWEB)

    Ahrens, J.; Bai, X.; Barwick, S.W.; Bay, R.C.; Becka, T.; Becker, K.-H.; Bernardini, E.; Bertrand, D.; Binon, F.; Biron, A.; Boeser, S.; Botner, O.; Bouchta, A.; Bouhali, O.; Burgess, T.; Carius, S.; Castermans, T.; Chirkin, D.; Conrad, J.; Cooley, J.; Cowen, D.F.; Davour, A.; Clercq, C. de; De Young, T.; Desiati, P.; Dewulf, J.-P.; Dickinson, E.; Doksus, P.; Ekstroem, P.; Engel, R.; Evenson, P.; Feser, T.; Gaisser, T.K. E-mail: gaisser@bartol.udel.edu; Ganugapati, R.; Gaug, M.; Geenen, H.; Gerhardt, L.; Goldschmidt, A.; Hallgren, A.; Halzen, F.; Hanson, K.; Hardtke, R.; Hauschildt, T.; Hellwig, M.; Herquet, P.; Hill, G.C.; Hinton, J.A.; Hughey, B.; Hulth, P.O.; Hultqvist, K.; Hundertmark, S.; Jacobsen, J.; Karle, A.; Kim, J.; Koepke, L.; Kowalski, M.; Kuehn, K.; Lamoureux, J.I.; Leich, H.; Leuthold, M.; Lindahl, P.; Liubarsky, I.; Lloyd-Evans, J.; Madsen, J.; Mandli, K.; Marciniewski, P.; Martello, D.; Matis, H.S.; McParland, C.P.; Messarius, T.; Miller, T.C.; Minaeva, Y.; Miocinovic, P.; Mock, P.C.; Morse, R.; Neunhoeffer, T.; Niessen, P.; Nygren, D.R.; Oegelman, H.; Olbrechts, Ph.; Perez de los Heros, C.; Pohl, A.C.; Porrata, R.; Price, P.B.; Przybylski, G.T.; Rawlins, K.; Resconi, E.; Rhode, W.; Ribordy, M.; Richter, S.; Rochester, K.; Rodriguez Martino, J.; Romenesko, P.; Ross, D.; Sander, H.-G.; Schmidt, T.; Schinarakis, K.; Schlenstedt, S.; Schneider, D.; Schwarz, R.; Silvestri, A.; Solarz, M.; Spiczak, G.M.; Spiering, C.; Stamatikos, M.; Stanev, T.; Steele, D.; Steffen, P.; Stokstad, R.G.; Sulanke, K.-H.; Taboada, I.; Tilav, S.; Walck, C.; Wagner, W.; Wang, Y.-R.; Watson, A.A.; Weinheimer, C.; Wiebusch, C.H.; Wiedemann, C.; Wischnewski, R.; Wissing, H.; Woschnagg, K.; Wu, W.; Yodh, G.; Young, S

    2004-04-21

    We report on the analysis of air showers observed in coincidence by the Antarctic Muon and Neutrino detector array (AMANDA-B10) and the South Pole Air Shower Experiment (SPASE-1 and SPASE-2). We discuss the use of coincident events for calibration and survey of the deep AMANDA detector as well as the response of AMANDA to muon bundles. This analysis uses data taken during 1997 when both SPASE-1 and SPASE-2 were in operation to provide a stereo view of AMANDA.

  1. Calibration and survey of AMANDA with the SPASE detectors

    CERN Document Server

    Ahrens, J; Barwick, S W; Bay, R C; Becka, T; Becker, K H; Bernardini, E; Bertrand, E; Binon, F; Biron, A; Boser, S; Botner, O; Bouchta, A; Bouhali, O; Burgess, T; Carius, S; Castermans, T; Chirkin, D; Conrad, J; Cooley, J; Cowen, D F; Davour, A; De Clercq, C; De Young, T R; Desiati, P; Dewulf, J P; Dickinson, E; Doksus, P; Ekstrom, P; Engel, R; Evenson, P; Feser, T; Gaisser, T K; Ganugapati, R; Gaug, M; Geenen, H; Gerhardt, L; Goldschmidt, A; Hallgren, A; Halzen, F; Hanson, K; Hardtke, R; Hauschildt, T; Hellwig, M; Herquet, P; Hill, G C; Hinton, J A; Hughey, B; Hulth, P O; Hultqvist, K; Hundertmark, S; Jacobsen, J; Karle, A; Kim, J; Köpke, L; Kowalski, M; Kühn, K; Lamoureux, J I; Leich, H; Leuthold, M; Lindahl, P; Liubarsky, I; Lloyd Evans, J; Madsen, J; Mandli, K; Marciniewski, P; Martello, D; Matis, H S; McParland, C P; Messarius, T; Miller, T C; Minaeva, Y; Miocinovic, P; Mock, P C; Morse, R; Neunhoffer, T; Niessen, P; Nygren, D R; Ogelman, H; Olbrechts, P; Perez de los Heros, C; Pohl, A C; Porrata, R; Price, P B; Przybylski, G T; Rawlins, K; Resconi, E; Rhode, W; Ribordy, M; Richter, S; Rochester, K; Rodríguez-Martino, J; Romenesko, P; Ross, D; Sander, H G; Schinarakis, K; Schlenstedt, S; Schmidt, T; Schneider, D; Schwarz, R; Silvestri, A; Solarz, M; Spiczak, G M; Spiering, C; Stamatikos, M; Stanev, T; Steele, D; Steffen, P; Stokstad, R G; Sulanke, K H; Taboada, I; Tilav, S; Wagner, W; Walck, C; Wang, Y R; Watson, A A; Weinheimer, C; Wiebusch, C; Wiedemann, C; Wischnewski, R; Wissing, H; Woschnagg, K; Wu, W; Yodh, G; Young, S; 10.1016/j.nima.2003.12.007

    2004-01-01

    We report on the analysis of air showers observed in coincidence by the Antarctic Muon and Neutrino detector array (AMANDA-B10) and the South Pole Air Shower Experiment (SPASE-1 and SPASE-2). We discuss the use of coincident events for calibration and survey of the deep AMANDA detector as well as the response of AMANDA to muon bundles. This analysis uses data taken during 1997 when both SPASE-1 and SPASE-2 were in operation to provide a stereo view of AMANDA.

  2. ChemNet: A Transferable and Generalizable Deep Neural Network for Small-Molecule Property Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Goh, Garrett B.; Siegel, Charles M.; Vishnu, Abhinav; Hodas, Nathan O.

    2017-12-08

    With access to large datasets, deep neural networks through representation learning have been able to identify patterns from raw data, achieving human-level accuracy in image and speech recognition tasks. However, in chemistry, availability of large standardized and labelled datasets is scarce, and with a multitude of chemical properties of interest, chemical data is inherently small and fragmented. In this work, we explore transfer learning techniques in conjunction with the existing Chemception CNN model, to create a transferable and generalizable deep neural network for small-molecule property prediction. Our latest model, ChemNet learns in a semi-supervised manner from inexpensive labels computed from the ChEMBL database. When fine-tuned to the Tox21, HIV and FreeSolv dataset, which are 3 separate chemical tasks that ChemNet was not originally trained on, we demonstrate that ChemNet exceeds the performance of existing Chemception models, contemporary MLP models that trains on molecular fingerprints, and it matches the performance of the ConvGraph algorithm, the current state-of-the-art. Furthermore, as ChemNet has been pre-trained on a large diverse chemical database, it can be used as a universal “plug-and-play” deep neural network, which accelerates the deployment of deep neural networks for the prediction of novel small-molecule chemical properties.

  3. Intelligent control based on fuzzy logic and neural net theory

    Science.gov (United States)

    Lee, Chuen-Chien

    1991-01-01

    In the conception and design of intelligent systems, one promising direction involves the use of fuzzy logic and neural network theory to enhance such systems' capability to learn from experience and adapt to changes in an environment of uncertainty and imprecision. Here, an intelligent control scheme is explored by integrating these multidisciplinary techniques. A self-learning system is proposed as an intelligent controller for dynamical processes, employing a control policy which evolves and improves automatically. One key component of the intelligent system is a fuzzy logic-based system which emulates human decision making behavior. It is shown that the system can solve a fairly difficult control learning problem. Simulation results demonstrate that improved learning performance can be achieved in relation to previously described systems employing bang-bang control. The proposed system is relatively insensitive to variations in the parameters of the system environment.

  4. Geometrical approach to neural net control of movements and posture

    Science.gov (United States)

    Pellionisz, A. J.; Ramos, C. F.

    1993-01-01

    In one approach to modeling brain function, sensorimotor integration is described as geometrical mapping among coordinates of non-orthogonal frames that are intrinsic to the system; in such a case sensors represent (covariant) afferents and motor effectors represent (contravariant) motor efferents. The neuronal networks that perform such a function are viewed as general tensor transformations among different expressions and metric tensors determining the geometry of neural functional spaces. Although the non-orthogonality of a coordinate system does not impose a specific geometry on the space, this "Tensor Network Theory of brain function" allows for the possibility that the geometry is non-Euclidean. It is suggested that investigation of the non-Euclidean nature of the geometry is the key to understanding brain function and to interpreting neuronal network function. This paper outlines three contemporary applications of such a theoretical modeling approach. The first is the analysis and interpretation of multi-electrode recordings. The internal geometries of neural networks controlling external behavior of the skeletomuscle system is experimentally determinable using such multi-unit recordings. The second application of this geometrical approach to brain theory is modeling the control of posture and movement. A preliminary simulation study has been conducted with the aim of understanding the control of balance in a standing human. The model appears to unify postural control strategies that have previously been considered to be independent of each other. Third, this paper emphasizes the importance of the geometrical approach for the design and fabrication of neurocomputers that could be used in functional neuromuscular stimulation (FNS) for replacing lost motor control.

  5. 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.

  6. NIRFaceNet: A Convolutional Neural Network for Near-Infrared Face Identification

    Directory of Open Access Journals (Sweden)

    Min Peng

    2016-10-01

    Full Text Available Near-infrared (NIR face recognition has attracted increasing attention because of its advantage of illumination invariance. However, traditional face recognition methods based on NIR are designed for and tested in cooperative-user applications. In this paper, we present a convolutional neural network (CNN for NIR face recognition (specifically face identification in non-cooperative-user applications. The proposed NIRFaceNet is modified from GoogLeNet, but has a more compact structure designed specifically for the Chinese Academy of Sciences Institute of Automation (CASIA NIR database and can achieve higher identification rates with less training time and less processing time. The experimental results demonstrate that NIRFaceNet has an overall advantage compared to other methods in the NIR face recognition domain when image blur and noise are present. The performance suggests that the proposed NIRFaceNet method may be more suitable for non-cooperative-user applications.

  7. Tips From Former Smokers – Amanda

    Centers for Disease Control (CDC) Podcasts

    2014-07-07

    Amanda talks about the weeks her baby spent in a hospital incubator. Amanda smoked during her pregnancy, and her baby was born two months early.  Created: 7/7/2014 by Office on Smoking and Health, National Center for Chronic Disease Prevention and Health Promotion.   Date Released: 7/7/2014.

  8. BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment.

    Science.gov (United States)

    Kawahara, Jeremy; Brown, Colin J; Miller, Steven P; Booth, Brian G; Chau, Vann; Grunau, Ruth E; Zwicker, Jill G; Hamarneh, Ghassan

    2017-02-01

    We propose BrainNetCNN, a convolutional neural network (CNN) framework to predict clinical neurodevelopmental outcomes from brain networks. In contrast to the spatially local convolutions done in traditional image-based CNNs, our BrainNetCNN is composed of novel edge-to-edge, edge-to-node and node-to-graph convolutional filters that leverage the topological locality of structural brain networks. We apply the BrainNetCNN framework to predict cognitive and motor developmental outcome scores from structural brain networks of infants born preterm. Diffusion tensor images (DTI) of preterm infants, acquired between 27 and 46 weeks gestational age, were used to construct a dataset of structural brain connectivity networks. We first demonstrate the predictive capabilities of BrainNetCNN on synthetic phantom networks with simulated injury patterns and added noise. BrainNetCNN outperforms a fully connected neural-network with the same number of model parameters on both phantoms with focal and diffuse injury patterns. We then apply our method to the task of joint prediction of Bayley-III cognitive and motor scores, assessed at 18 months of age, adjusted for prematurity. We show that our BrainNetCNN framework outperforms a variety of other methods on the same data. Furthermore, BrainNetCNN is able to identify an infant's postmenstrual age to within about 2 weeks. Finally, we explore the high-level features learned by BrainNetCNN by visualizing the importance of each connection in the brain with respect to predicting the outcome scores. These findings are then discussed in the context of the anatomy and function of the developing preterm infant brain. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Self-Organizing Neural-Net Control of Ship's Horizontal Motion

    Energy Technology Data Exchange (ETDEWEB)

    Yang, X J; Zhao, X R [Automation College of Harbin Engineering University, Harbin 150001 (China)

    2006-10-15

    This paper describes the concept and an example of an adaptive neural-net controller system for ship's horizontal motion. The system consists of two parts, a real-world part and an imaginary-world part. The real-world part is a feedback control system for the actual ship. In the imaginary-world part, the model of ship and the controller are adjusted continuously in order to deal with changes of dynamic properties caused by disturbances and so on. In this paper, the adaptability of the controller system is investigated by controlling ship's horizontal motion including roll, yaw and sway. The results of simulation indicate that with selforganizing neural-net control, the mean square error of roll angle and yaw angle reduce to 0.92{sup 0}, and 0.74{sup 0} respectively. The control effect of SONC is better than conventional LQG controller.

  10. Deep neural nets as a method for quantitative structure-activity relationships.

    Science.gov (United States)

    Ma, Junshui; Sheridan, Robert P; Liaw, Andy; Dahl, George E; Svetnik, Vladimir

    2015-02-23

    Neural networks were widely used for quantitative structure-activity relationships (QSAR) in the 1990s. Because of various practical issues (e.g., slow on large problems, difficult to train, prone to overfitting, etc.), they were superseded by more robust methods like support vector machine (SVM) and random forest (RF), which arose in the early 2000s. The last 10 years has witnessed a revival of neural networks in the machine learning community thanks to new methods for preventing overfitting, more efficient training algorithms, and advancements in computer hardware. In particular, deep neural nets (DNNs), i.e. neural nets with more than one hidden layer, have found great successes in many applications, such as computer vision and natural language processing. Here we show that DNNs can routinely make better prospective predictions than RF on a set of large diverse QSAR data sets that are taken from Merck's drug discovery effort. The number of adjustable parameters needed for DNNs is fairly large, but our results show that it is not necessary to optimize them for individual data sets, and a single set of recommended parameters can achieve better performance than RF for most of the data sets we studied. The usefulness of the parameters is demonstrated on additional data sets not used in the calibration. Although training DNNs is still computationally intensive, using graphical processing units (GPUs) can make this issue manageable.

  11. MTDeep: Boosting the Security of Deep Neural Nets Against Adversarial Attacks with Moving Target Defense

    OpenAIRE

    Sengupta, Sailik; Chakraborti, Tathagata; Kambhampati, Subbarao

    2017-01-01

    Recent works on gradient-based attacks and universal perturbations can adversarially modify images to bring down the accuracy of state-of-the-art classification techniques based on deep neural networks to as low as 10\\% on popular datasets like MNIST and ImageNet. The design of general defense strategies against a wide range of such attacks remains a challenging problem. In this paper, we derive inspiration from recent advances in the fields of cybersecurity and multi-agent systems and propos...

  12. Practitioner Profile: An Interview With Amanda Mills

    Directory of Open Access Journals (Sweden)

    Amanda Mills

    2012-01-01

    Full Text Available For more than 25 years, Amanda Mills has been working with arts organizations across Canada and with artists of all kinds to assist them in achieving financial sanity. She has taught business management at the University of Victoria and has prepared thousands of tax returns for writers, visual artists, choreographers, actors, filmmakers, broadcasters, and creative entrepreneurs. Ten years ago, bringing together her work on trauma, with twenty years of business management, Mills founded Loose Change Financial Therapy – the place where money and feelings meet. Mills has presented Loose Change workshops for social workers, teachers, psychotherapists, artists, anti-poverty activists, sex trade workers, women’s groups, and the general public.  She has been a guest on major Canadian radio and television broadcasts and profiled in many major Canadian newspapers and periodicals. Mills is also a crisis counselor and co-wrote a bestselling book on recovering from trauma. A tax professional and business manager, she is certified as a financial counselor under the Bankruptcy and Insolvency Act. Mills is also currently completing a certificate in mediation.

  13. k-Same-Net: k-Anonymity with Generative Deep Neural Networks for Face Deidentification

    Directory of Open Access Journals (Sweden)

    Blaž Meden

    2018-01-01

    Full Text Available Image and video data are today being shared between government entities and other relevant stakeholders on a regular basis and require careful handling of the personal information contained therein. A popular approach to ensure privacy protection in such data is the use of deidentification techniques, which aim at concealing the identity of individuals in the imagery while still preserving certain aspects of the data after deidentification. In this work, we propose a novel approach towards face deidentification, called k-Same-Net, which combines recent Generative Neural Networks (GNNs with the well-known k-Anonymitymechanism and provides formal guarantees regarding privacy protection on a closed set of identities. Our GNN is able to generate synthetic surrogate face images for deidentification by seamlessly combining features of identities used to train the GNN model. Furthermore, it allows us to control the image-generation process with a small set of appearance-related parameters that can be used to alter specific aspects (e.g., facial expressions, age, gender of the synthesized surrogate images. We demonstrate the feasibility of k-Same-Net in comprehensive experiments on the XM2VTS and CK+ datasets. We evaluate the efficacy of the proposed approach through reidentification experiments with recent recognition models and compare our results with competing deidentification techniques from the literature. We also present facial expression recognition experiments to demonstrate the utility-preservation capabilities of k-Same-Net. Our experimental results suggest that k-Same-Net is a viable option for facial deidentification that exhibits several desirable characteristics when compared to existing solutions in this area.

  14. Practitioner Profile: An Interview with Amanda Clayman, LMSW, CFSW

    Directory of Open Access Journals (Sweden)

    Amanda Clayman

    2014-03-01

    Full Text Available Amanda Clayman, is a Licensed Master of Social Work and a Certified Financial Social Worker who helps individuals, couples, and families bring money into balance. Since 2006, Amanda has led the Financial Wellness Program at The Actors Fund, a national non-profit human services agency that supports professionals in performing arts and entertainment. She maintains a private financial wellness counseling practice in New York City and is a public speaker on life and money topics. Amanda's work has been featured in media outlets, such as the New York Times, the Wall Street Journal, SELF magazine, REAL SIMPLE magazine, Women's Health, Parenting, and Fit Pregnancy. She lives in Brooklyn with her husband and daughters.

  15. Neural-Net Based Optical NDE Method for Structural Health Monitoring

    Science.gov (United States)

    Decker, Arthur J.; Weiland, Kenneth E.

    2003-01-01

    This paper answers some performance and calibration questions about a non-destructive-evaluation (NDE) procedure that uses artificial neural networks to detect structural damage or other changes from sub-sampled characteristic patterns. The method shows increasing sensitivity as the number of sub-samples increases from 108 to 6912. The sensitivity of this robust NDE method is not affected by noisy excitations of the first vibration mode. A calibration procedure is proposed and demonstrated where the output of a trained net can be correlated with the outputs of the point sensors used for vibration testing. The calibration procedure is based on controlled changes of fastener torques. A heterodyne interferometer is used as a displacement sensor for a demonstration of the challenges to be handled in using standard point sensors for calibration.

  16. Investigation of neural-net based control strategies for improved power system dynamic performance

    Energy Technology Data Exchange (ETDEWEB)

    Sobajic, D.J. [Electric Power Research Institute, Palo Alto, CA (United States)

    1995-12-31

    The ability to accurately predict the behavior of a dynamic system is of essential importance in monitoring and control of complex processes. In this regard recent advances in neural-net base system identification represent a significant step toward development and design of a new generation of control tools for increased system performance and reliability. The enabling functionality is the one of accurate representation of a model of a nonlinear and nonstationary dynamic system. This functionality provides valuable new opportunities including: (1) The ability to predict future system behavior on the basis of actual system observations, (2) On-line evaluation and display of system performance and design of early warning systems, and (3) Controller optimization for improved system performance. In this presentation, we discuss the issues involved in definition and design of learning control systems and their impact on power system control. Several numerical examples are provided for illustrative purpose.

  17. Accelerometer signal-based human activity recognition using augmented autoregressive model coefficients and artificial neural nets.

    Science.gov (United States)

    Khan, A M; Lee, Y K; Kim, T S

    2008-01-01

    Automatic recognition of human activities is one of the important and challenging research areas in proactive and ubiquitous computing. In this work, we present some preliminary results of recognizing human activities using augmented features extracted from the activity signals measured using a single triaxial accelerometer sensor and artificial neural nets. The features include autoregressive (AR) modeling coefficients of activity signals, signal magnitude areas (SMA), and title angles (TA). We have recognized four human activities using AR coefficients (ARC) only, ARC with SMA, and ARC with SMA and TA. With the last augmented features, we have achieved the recognition rate above 99% for all four activities including lying, standing, walking, and running. With our proposed technique, real time recognition of some human activities is possible.

  18. Door and cabinet recognition using convolutional neural nets and real-time method fusion for handle detection and grasping

    DEFF Research Database (Denmark)

    Maurin, Adrian Llopart; Ravn, Ole; Andersen, Nils Axel

    2017-01-01

    In this paper we present a new method that robustly identifies doors, cabinets and their respective handles, with special emphasis on extracting useful features from handles to be then manipulated. The novelty of this system relies on the combination of a Convolutional Neural Net (CNN), as a form...

  19. Neural-net based coordinated stabilizing control for the exciter and governor loops of low head hydropower plants

    Energy Technology Data Exchange (ETDEWEB)

    Djukanovic, M.; Novicevic, M.; Dobrijevic, D.; Babic, B. [Electrical Engineering Inst. Nikola Tesla, Belgrade (Yugoslavia); Sobajic, D.J. [Electric Power Research Inst., Palo Alto, CA (United States); Pao, Y.H. [Case Western Reserve Univ., Cleveland, OH (United States)]|[AI WARE, Inc., Cleveland, OH (United States)

    1995-12-01

    This paper presents a design technique of a new adaptive optimal controller of the low head hydropower plant using artificial neural networks (ANN). The adaptive controller is to operate in real time to improve the generating unit transients through the exciter input, the guide vane position and the runner blade position. The new design procedure is based on self-organization and the predictive estimation capabilities of neural-nets implemented through the cluster-wise segmented associative memory scheme. The developed neural-net based controller (NNC) whose control signals are adjusted using the on-line measurements, can offer better damping effects for generator oscillations over a wide range of operating conditions than conventional controllers. Digital simulations of hydropower plant equipped with low head Kaplan turbine are performed and the comparisons of conventional excitation-governor control, state-space optimal control and neural-net based control are presented. Results obtained on the non-linear mathematical model demonstrate that the effects of the NNC closely agree with those obtained using the state-space multivariable discrete-time optimal controllers.

  20. NIRExpNet: Three-Stream 3D Convolutional Neural Network for Near Infrared Facial Expression Recognition

    Directory of Open Access Journals (Sweden)

    Zhan Wu

    2017-11-01

    Full Text Available Facial expression recognition (FER under active near-infrared (NIR illumination has the advantages of illumination invariance. In this paper, we propose a three-stream 3D convolutional neural network, named as NIRExpNet for NIR FER. The 3D structure of NIRExpNet makes it possible to extract automatically, not just spatial features, but also, temporal features. The design of multiple streams of the NIRExpNet enables it to fuse local and global facial expression features. To avoid over-fitting, the NIRExpNet has a moderate size to suit the Oulu-CASIA NIR facial expression database that is a medium-size database. Experimental results show that the proposed NIRExpNet outperforms some previous state-of-art methods, such as Histogram of Oriented Gradient to 3D (HOG 3D, Local binary patterns from three orthogonal planes (LBP-TOP, deep temporal appearance-geometry network (DTAGN, and adapt 3D Convolutional Neural Networks (3D CNN DAP.

  1. AMANDA Observations Constrain the Ultrahigh Energy Neutrino Flux

    Energy Technology Data Exchange (ETDEWEB)

    Halzen, Francis; /Wisconsin U., Madison; Hooper, Dan; /Fermilab

    2006-05-01

    A number of experimental techniques are currently being deployed in an effort to make the first detection of ultra-high energy cosmic neutrinos. To accomplish this goal, techniques using radio and acoustic detectors are being developed, which are optimally designed for studying neutrinos with energies in the PeV-EeV range and above. Data from the AMANDA experiment, in contrast, has been used to place limits on the cosmic neutrino flux at less extreme energies (up to {approx}10 PeV). In this letter, we show that by adopting a different analysis strategy, optimized for much higher energy neutrinos, the same AMANDA data can be used to place a limit competitive with radio techniques at EeV energies. We also discuss the sensitivity of the IceCube experiment, in various stages of deployment, to ultra-high energy neutrinos.

  2. Muon track reconstruction and data selection techniques in AMANDA

    Energy Technology Data Exchange (ETDEWEB)

    Ahrens, J.; Bai, X.; Bay, R.; Barwick, S.W.; Becka, T.; Becker, J.K.; Becker, K.-H.; Bernardini, E.; Bertrand, D.; Biron, A.; Boersma, D.J.; Boeser, S.; Botner, O.; Bouchta, A.; Bouhali, O.; Burgess, T.; Carius, S.; Castermans, T.; Chirkin, D.; Collin, B.; Conrad, J.; Cooley, J.; Cowen, D.F.; Davour, A.; De Clercq, C.; DeYoung, T.; Desiati, P.; Dewulf, J.-P.; Ekstroem, P.; Feser, T.; Gaug, M.; Gaisser, T.K.; Ganugapati, R.; Geenen, H.; Gerhardt, L.; Gross, A.; Goldschmidt, A.; Hallgren, A.; Halzen, F.; Hanson, K.; Hardtke, R.; Harenberg, T.; Hauschildt, T.; Helbing, K.; Hellwig, M.; Herquet, P.; Hill, G.C.; Hubert, D.; Hughey, B.; Hulth, P.O.; Hultqvist, K.; Hundertmark, S.; Jacobsen, J.; Karle, A.; Kestel, M.; Koepke, L.; Kowalski, M.; Kuehn, K.; Lamoureux, J.I.; Leich, H.; Leuthold, M.; Lindahl, P.; Liubarsky, I.; Madsen, J.; Marciniewski, P.; Matis, H.S.; McParland, C.P.; Messarius, T.; Minaeva, Y.; Miocinovic, P.; Mock, P.C.; Morse, R.; Muenich, K.S.; Nam, J.; Nahnhauer, R.; Neunhoeffer, T.; Niessen, P.; Nygren, D.R.; Oegelman, H.; Olbrechts, Ph.; Perez de los Heros, C.; Pohl, A.C.; Porrata, R.; Price, P.B.; Przybylski, G.T.; Rawlins, K.; Resconi, E.; Rhode, W.; Ribordy, M.; Richter, S.; Rodriguez Martino, J.; Ross, D.; Sander, H.-G.; Schinarakis, K.; Schlenstedt, S.; Schmidt, T.; Schneider, D.; Schwarz, R.; Silvestri, A.; Solarz, M.; Spiczak, G.M.; Spiering, C.; Stamatikos, M.; Steele, D.; Steffen, P.; Stokstad, R.G.; Sulanke, K.-H.; Streicher, O.; Taboada, I.; Thollander, L.; Tilav, S.; Wagner, W.; Walck, C.; Wang, Y.-R.; Wiebusch, C.H. E-mail: wiebusch@physik.uni-wuppertal.de; Wiedemann, C.; Wischnewski, R.; Wissing, H.; Woschnagg, K.; Yodh, G

    2004-05-21

    The Antarctic Muon And Neutrino Detector Array (AMANDA) is a high-energy neutrino telescope operating at the geographic South Pole. It is a lattice of photo-multiplier tubes buried deep in the polar ice between 1500 and 2000 m. The primary goal of this detector is to discover astrophysical sources of high-energy neutrinos. A high-energy muon neutrino coming through the earth from the Northern Hemisphere can be identified by the secondary muon moving upward through the detector. The muon tracks are reconstructed with a maximum likelihood method. It models the arrival times and amplitudes of Cherenkov photons registered by the photo-multipliers. This paper describes the different methods of reconstruction, which have been successfully implemented within AMANDA. Strategies for optimizing the reconstruction performance and rejecting background are presented. For a typical analysis procedure the direction of tracks are reconstructed with about 2 deg. accurac000.

  3. Modularity and Sparsity: Evolution of Neural Net Controllers in Physically Embodied Robots

    Directory of Open Access Journals (Sweden)

    Nicholas Livingston

    2016-12-01

    Full Text Available While modularity is thought to be central for the evolution of complexity and evolvability, it remains unclear how systems boot-strap themselves into modularity from random or fully integrated starting conditions. Clune et al. (2013 suggested that a positive correlation between sparsity and modularity is the prime cause of this transition. We sought to test the generality of this modularity-sparsity hypothesis by testing it for the first time in physically embodied robots. A population of ten Tadros — autonomous, surface-swimming robots propelled by a flapping tail — was used. Individuals varied only in the structure of their neural net control, a 2 x 6 x 2 network with recurrence in the hidden layer. Each of the 60 possible connections was coded in the genome, and could achieve one of three states: -1, 0, 1. Inputs were two light-dependent resistors and outputs were two motor control variables to the flapping tail, one for the frequency of the flapping and the other for the turning offset. Each Tadro was tested separately in a circular tank lit by a single overhead light source. Fitness was the amount of light gathered by a vertically oriented sensor that was disconnected from the controller net. Reproduction was asexual, with the top performer cloned and then all individuals entered into a roulette wheel selection process, with genomes mutated to create the offspring. The starting population of networks was randomly generated. Over ten generations, the population’s mean fitness increased two-fold. This evolution occurred in spite of an unintentional integer overflow problem in recurrent nodes in the hidden layer that caused outputs to oscillate. Our investigation of the oscillatory behavior showed that the mutual information of inputs and outputs was sufficient for the reactive behaviors observed. While we had predicted that both modularity and sparsity would follow the same trend as fitness, neither did so. Instead, selection gradients

  4. Prediction of Disease Causing Non-Synonymous SNPs by the Artificial Neural Network Predictor NetDiseaseSNP

    DEFF Research Database (Denmark)

    Johansen, Morten Bo; Gonzalez-Izarzugaza, Jose Maria; Brunak, Søren

    2013-01-01

    We have developed a sequence conservation-based artificial neural network predictor called NetDiseaseSNP which classifies nsSNPs as disease-causing or neutral. Our method uses the excellent alignment generation algorithm of SIFT to identify related sequences and a combination of 31 features...... assessing sequence conservation and the predicted surface accessibility to produce a single score which can be used to rank nsSNPs based on their potential to cause disease. NetDiseaseSNP classifies successfully disease-causing and neutral mutations. In addition, we show that NetDiseaseSNP discriminates...... cancer driver and passenger mutations satisfactorily. Our method outperforms other state-of-the-art methods on several disease/neutral datasets as well as on cancer driver/passenger mutation datasets and can thus be used to pinpoint and prioritize plausible disease candidates among nsSNPs for further...

  5. Auto-context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging.

    Science.gov (United States)

    Salehi, Seyed Sadegh Mohseni; Erdogmus, Deniz; Gholipour, Ali

    2017-06-28

    Brain extraction or whole brain segmentation is an important first step in many of the neuroimage analysis pipelines. The accuracy and robustness of brain extraction, therefore, is crucial for the accuracy of the entire brain analysis process. State-of-the-art brain extraction techniques rely heavily on the accuracy of alignment or registration between brain atlases and query brain anatomy, and/or make assumptions about the image geometry; therefore have limited success when these assumptions do not hold or image registration fails. With the aim of designing an accurate, learning-based, geometry-independent and registration-free brain extraction tool in this study, we present a technique based on an auto-context convolutional neural network (CNN), in which intrinsic local and global image features are learned through 2D patches of different window sizes. We consider two different architectures: 1) a voxelwise approach based on three parallel 2D convolutional pathways for three different directions (axial, coronal, and sagittal) that implicitly learn 3D image information without the need for computationally expensive 3D convolutions, and 2) a fully convolutional network based on the U-net architecture. Posterior probability maps generated by the networks are used iteratively as context information along with the original image patches to learn the local shape and connectedness of the brain to extract it from non-brain tissue. The brain extraction results we have obtained from our CNNs are superior to the recently reported results in the literature on two publicly available benchmark datasets, namely LPBA40 and OASIS, in which we obtained Dice overlap coefficients of 97.73% and 97.62%, respectively. Significant improvement was achieved via our auto-context algorithm. Furthermore, we evaluated the performance of our algorithm in the challenging problem of extracting arbitrarily-oriented fetal brains in reconstructed fetal brain magnetic resonance imaging (MRI

  6. TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions.

    Directory of Open Access Journals (Sweden)

    Zixuan Cang

    2017-07-01

    Full Text Available Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH method. ESPH represents 3D complex geometry by one-dimensional (1D topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN. We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes.weilab.math.msu.edu/TDL/.

  7. TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions

    Science.gov (United States)

    2017-01-01

    Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/ PMID:28749969

  8. Neural-Net Processing of Characteristic Patterns From Electronic Holograms of Vibrating Blades

    Science.gov (United States)

    Decker, Arthur J.

    1999-01-01

    Finite-element-model-trained artificial neural networks can be used to process efficiently the characteristic patterns or mode shapes from electronic holograms of vibrating blades. The models used for routine design may not yet be sufficiently accurate for this application. This document discusses the creation of characteristic patterns; compares model generated and experimental characteristic patterns; and discusses the neural networks that transform the characteristic patterns into strain or damage information. The current potential to adapt electronic holography to spin rigs, wind tunnels and engines provides an incentive to have accurate finite element models lor training neural networks.

  9. The AMANDA search for high energy neutrinos from gamma ray bursts

    CERN Document Server

    Hardtke, R

    2004-01-01

    We have searched three and a half years of AMANDA data for high energy muon neutrinos from gamma-ray bursts (GRBs). The data were recorded from 1997 through 1999 by the AMANDA-BIO detector and in 2000 by the AMANDA-II detector. AMANDA is a Cerenkov detector embedded 1.5 to 2 km deep in the transparent ice of the South Polar plateau. We searched for neutrino candidates from the direction of, and coincident with, GRBs detected by the Burst and Transient Source Experiment (BATSE). The current result is consistent with no signal. A preliminary event upper limit for GRB neutrino emission is presented as well as a description of AMANDA's cubic-kilometer successor, IceCube.

  10. Competition and Cooperation in Neural Nets : U.S.-Japan Joint Seminar

    CERN Document Server

    Arbib, Michael

    1982-01-01

    The human brain, wi th its hundred billion or more neurons, is both one of the most complex systems known to man and one of the most important. The last decade has seen an explosion of experimental research on the brain, but little theory of neural networks beyond the study of electrical properties of membranes and small neural circuits. Nonetheless, a number of workers in Japan, the United States and elsewhere have begun to contribute to a theory which provides techniques of mathematical analysis and computer simulation to explore properties of neural systems containing immense numbers of neurons. Recently, it has been gradually recognized that rather independent studies of the dynamics of pattern recognition, pattern format::ion, motor control, self-organization, etc. , in neural systems do in fact make use of common methods. We find that a "competition and cooperation" type of interaction plays a fundamental role in parallel information processing in the brain. The present volume brings together 23 papers ...

  11. Optics-Only Calibration of a Neural-Net Based Optical NDE Method for Structural Health Monitoring

    Science.gov (United States)

    Decker, Arthur J.

    2004-01-01

    A calibration process is presented that uses optical measurements alone to calibrate a neural-net based NDE method. The method itself detects small changes in the vibration mode shapes of structures. The optics-only calibration process confirms previous work that the sensitivity to vibration-amplitude changes can be as small as 10 nanometers. A more practical value in an NDE service laboratory is shown to be 50 nanometers. Both model-generated and experimental calibrations are demonstrated using two implementations of the calibration technique. The implementations are based on previously published demonstrations of the NDE method and an alternative calibration procedure that depends on comparing neural-net and point sensor measurements. The optics-only calibration method, unlike the alternative method, does not require modifications of the structure being tested or the creation of calibration objects. The calibration process can be used to test improvements in the NDE process and to develop a vibration-mode-independence of damagedetection sensitivity. The calibration effort was intended to support NASA s objective to promote safety in the operations of ground test facilities or aviation safety, in general, by allowing the detection of the gradual onset of structural changes and damage.

  12. Applying Artificial Neural Networks to Estimate Net Radiation at Surface Using the Synergy between GERB-SEVIRI and Ground Data

    Science.gov (United States)

    Geraldo Ferreira, A.; Soria, Emilio; Lopez-Baeza, Ernesto; Vila, Joan; Serrano, Antonio J.; Martinez, Marcelino; Velazquez Blazquez, Almudena; Clerbaux, Nicolas

    This paper describes the results obtained using Artificial Neural Networks (AAN) models to estimate the diurnal cycle of net radiation (Rn) at surface. The data used as input parameter in the AAN model were that measured by Geostationary Earth Radiation Budget (GERB-1) instrument, on board Meteosat 9 satellite. The data concerning Rn at the surface were collected at the Valencia Anchor Station (VAS), a ground reference meteorological station for the validation of low spatial resolution sensors situated near de city of Valencia, Spain. This data refers to the periods July 31st -August 6th 2006 and June 19th -August 18th 2007. Both, GERB-1 and VAS data are used to train and validate the AAN model. The same data set is also used to develop and validate a Multivariate Linear Regression (MLR) model. A comparison between the estimates provided by the AAN and the MLR models has been carried out; the results obtained with the neural model outperform the linear model. Moreover, the low values of the error indexes show that neural models can be used as an alternative methodology to make atmospheric corrections.

  13. Healing in forgiveness: A discussion with Amanda Lindhout and Katherine Porterfield, PhD

    Directory of Open Access Journals (Sweden)

    Katherine A. Porterfield

    2014-09-01

    Full Text Available In 2008, Amanda Lindhout was kidnapped by a group of extremists while traveling as a freelance journalist in Somalia. She and a colleague were held captive for more than 15 months, released only after their families paid a ransom. In this interview, Amanda discusses her experiences in captivity and her ongoing recovery from this experience with Katherine Porterfield, Ph.D. a clinical psychologist at the Bellevue/NYU Program for Survivors of Torture. Specifically, Amanda describes the childhood experiences that shaped her thirst for travel and knowledge, the conditions of her kidnapping, and her experiences after she was released from captivity. Amanda outlines the techniques that she employed to survive in the early aftermath of her capture, and how these coping strategies changed as her captivity lengthened. She reflects on her transition home, her recovery process, and her experiences with mental health professionals. Amanda's insights provide an example of resilience in the face of severe, extended trauma to researchers, clinicians, and survivors alike. The article ends with an discussion of the ways that Amanda's coping strategies and recovery process are consistent with existing resilience literature. Amanda's experiences as a hostage, her astonishing struggle for physical and mental survival, and her life after being freed are documented in her book, co-authored with Sara Corbett, A House in the Sky.

  14. Probabilistic and Other Neural Nets in Multi-Hole Probe Calibration and Flow Angularity Pattern Recognition

    Science.gov (United States)

    Baskaran, Subbiah; Ramachandran, Narayanan; Noever, David

    1998-01-01

    The use of probabilistic (PNN) and multilayer feed forward (MLFNN) neural networks are investigated for calibration of multi-hole pressure probes and the prediction of associated flow angularity patterns in test flow fields. Both types of networks are studied in detail for their calibration and prediction characteristics. The current formalism can be applied to any multi-hole probe, however the test results for the most commonly used five-hole Cone and Prism probe types alone are reported in this article.

  15. Review of Amanda E. Herbert, Female Alliances: Gender, Identity, and Friendship in Early Modern Britain

    Directory of Open Access Journals (Sweden)

    Angela Rehbein

    2015-03-01

    Full Text Available Review of Amanda E. Herbert, Female Alliances: Gender, Identity, and Friendship in Early Modern Britain. New Haven: Yale UP, 2014. xi, 256 pages: illustrations; 24 cm. ISBN 978-0-300-17740-4.

  16. The process of learning in neural net models with Poisson and Gauss connectivities.

    Science.gov (United States)

    Sivridis, L; Kotini, A; Anninos, P

    2008-01-01

    In this study we examined the dynamic behavior of isolated and non-isolated neural networks with chemical markers that follow a Poisson or Gauss distribution of connectivity. The Poisson distribution shows higher activity in comparison to the Gauss distribution although the latter has more connections that obliterated due to randomness. We examined 57 hematoxylin and eosin stained sections from an equal number of autopsy specimens with a diagnosis of "cerebral matter within normal limits". Neural counting was carried out in 5 continuous optic fields, with the use of a simple optical microscope connected to a computer (software programmer Nikon Act-1 vers-2). The number of neurons that corresponded to a surface was equal to 0.15 mm(2). There was a gradual reduction in the number of neurons as age increased. A mean value of 45.8 neurons /0.15 mm(2) was observed within the age range 21-25, 33 neurons /0.15 mm(2) within the age range 41-45, 19.3 neurons /0.15 mm(2) within the age range 56-60 years. After the age of 60 it was observed that the number of neurons per unit area stopped decreasing. A correlation was observed between these experimental findings and the theoretical neural model developed by professor Anninos and his colleagues. Equivalence between the mean numbers of neurons of the above mentioned age groups and the highest possible number of synaptic connections per neuron (highest number of synaptic connections corresponded to the age group 21-25) was created. We then used both inhibitory and excitatory post-synaptic potentials and applied these values to the Poisson and Gauss distributions, whereas the neuron threshold was varied between 3 and 5. According to the obtained phase diagrams, the hysteresis loops decrease as age increases. These findings were significant as the hysteresis loops can be regarded as the basis for short-term memory.

  17. Fast neural-net based fake track rejection in the LHCb reconstruction

    CERN Document Server

    De Cian, Michel; Seyfert, Paul; Stahl, Sascha

    2017-01-01

    A neural-network based algorithm to identify fake tracks in the LHCb pattern recognition is presented. This algorithm, called ghost probability, retains more than 99 % of well reconstructed tracks while reducing the number of fake tracks by 60 %. It is fast enough to fit into the CPU time budget of the software trigger farm and thus reduces the combinatorics of the decay reconstructions, as well as the number of tracks that need to be processed by the particle identification algorithms. As a result, it strongly contributes to the achievement of having the same reconstruction online and offline in the LHCb experiment in Run II of the LHC.

  18. LOGIC WITH EXCEPTION ON THE ALGEBRA OF FOURIER-DUAL OPERATIONS: NEURAL NET MECHANISM OF COGNITIVE DISSONANCE REDUCING

    Directory of Open Access Journals (Sweden)

    A. V. Pavlov

    2014-01-01

    Full Text Available A mechanism of cognitive dissonance reducing is demonstrated with approach for non-monotonic fuzzy-valued logics by Fourier-holography technique implementation developing. Cognitive dissonance occurs under perceiving of new information that contradicts to the existing subjective pattern of the outside world, represented by double Fourier-transform cascade with a hologram – neural layers interconnections matrix of inner information representation and logical conclusion. The hologram implements monotonic logic according to “General Modus Ponens” rule. New information is represented by a hologram of exclusion that implements interconnections of logical conclusion and exclusion for neural layers. The latter are linked by Fourier transform that determines duality of the algebra forming operations of conjunction and disjunction. Hologram of exclusion forms conclusion that is dual to the “General Modus Ponens” conclusion. It is shown, that trained for the main rule and exclusion system can be represented by two-layered neural network with separate interconnection matrixes for direct and inverse iterations. The network energy function is involved determining the cyclic dynamics character; dissipative factor causing convergence type of the dynamics is analyzed. Both “General Modus Ponens” and exclusion holograms recording conditions on the dynamics and convergence of the system are demonstrated. The system converges to a stable status, in which logical conclusion doesn’t depend on the inner information. Such kind of dynamics, leading to tolerance forming, is typical for ordinary kind of thinking, aimed at inner pattern of outside world stability. For scientific kind of thinking, aimed at adequacy of the inner pattern of the world, a mechanism is needed to stop the net relaxation; the mechanism has to be external relative to the model of logic. Computer simulation results for the learning conditions adequate to real holograms recording are

  19. From image edges to geons to viewpoint-invariant object models: a neural net implementation

    Science.gov (United States)

    Biederman, Irving; Hummel, John E.; Gerhardstein, Peter C.; Cooper, Eric E.

    1992-03-01

    Three striking and fundamental characteristics of human shape recognition are its invariance with viewpoint in depth (including scale), its tolerance of unfamiliarity, and its robustness with the actual contours present in an image (as long as the same convex parts [geons] can be activated). These characteristics are expressed in an implemented neural network model (Hummel & Biederman, 1992) that takes a line drawing of an object as input and generates a structural description of geons and their relations which is then used for object classification. The model's capacity for structural description derives from its solution to the dynamic binding problem of neural networks: independent units representing an object's parts (in terms of their shape attributes and interrelations) are bound temporarily when those attributes occur in conjunction in the system's input. Temporary conjunctions of attributes are represented by synchronized activity among the units representing those attributes. Specifically, the model induces temporal correlation in the firing of activated units to: (1) parse images into their constituent parts; (2) bind together the attributes of a part; and (3) determine the relations among the parts and bind them to the parts to which they apply. Because it conjoins independent units temporarily, dynamic binding allows tremendous economy of representation, and permits the representation to reflect an object's attribute structure. The model's recognition performance conforms well to recent results from shape priming experiments. Moreover, the manner in which the model's performance degrades due to accidental synchrony produced by an excess of phase sets suggests a basis for a theory of visual attention.

  20. BrainSegNet: a convolutional neural network architecture for automated segmentation of human brain structures.

    Science.gov (United States)

    Mehta, Raghav; Majumdar, Aabhas; Sivaswamy, Jayanthi

    2017-04-01

    Automated segmentation of cortical and noncortical human brain structures has been hitherto approached using nonrigid registration followed by label fusion. We propose an alternative approach for this using a convolutional neural network (CNN) which classifies a voxel into one of many structures. Four different kinds of two-dimensional and three-dimensional intensity patches are extracted for each voxel, providing local and global (context) information to the CNN. The proposed approach is evaluated on five different publicly available datasets which differ in the number of labels per volume. The obtained mean Dice coefficient varied according to the number of labels, for example, it is [Formula: see text] and [Formula: see text] for datasets with the least (32) and the most (134) number of labels, respectively. These figures are marginally better or on par with those obtained with the current state-of-the-art methods on nearly all datasets, at a reduced computational time. The consistently good performance of the proposed method across datasets and no requirement for registration make it attractive for many applications where reduced computational time is necessary.

  1. HAWC Analysis of the Crab Nebula Using Neural-Net Energy Reconstruction

    Science.gov (United States)

    Marinelli, Samuel; HAWC Collaboration

    2017-01-01

    The HAWC (High-Altitude Water-Cherenkov) experiment is a TeV γ-ray observatory located 4100 m above sea level on the Sierra Negra mountain in Puebla, Mexico. The detector consists of 300 water-filled tanks, each instrumented with 4 photomuliplier tubes that utilize the water-Cherenkov technique to detect atmospheric air showers produced by cosmic γ rays. Construction of HAWC was completed in March, 2015. The experiment's wide field of view (2 sr) and high duty cycle (> 95 %) make it a powerful survey instrument sensitive to pulsar wind nebulae, supernova remnants, active galactic nuclei, and other γ-ray sources. The mechanisms of particle acceleration at these sources can be studied by analyzing their energy spectra. To this end, we have developed an event-by-event energy-reconstruction algorithm employing an artificial neural network to estimate energies of primary γ rays. The Crab Nebula, the brightest source of TeV photons, makes an excellent calibration source for this technique. We will present preliminary results from an analysis of the Crab energy spectrum using this new energy-reconstruction method. This work was supported by the National Science Foundation.

  2. Data Normalization to Accelerate Training for Linear Neural Net to Predict Tropical Cyclone Tracks

    Directory of Open Access Journals (Sweden)

    Jian Jin

    2015-01-01

    Full Text Available When pure linear neural network (PLNN is used to predict tropical cyclone tracks (TCTs in South China Sea, whether the data is normalized or not greatly affects the training process. In this paper, min.-max. method and normal distribution method, instead of standard normal distribution, are applied to TCT data before modeling. We propose the experimental schemes in which, with min.-max. method, the min.-max. value pair of each variable is mapped to (−1, 1 and (0, 1; with normal distribution method, each variable’s mean and standard deviation pair is set to (0, 1 and (100, 1. We present the following results: (1 data scaled to the similar intervals have similar effects, no matter the use of min.-max. or normal distribution method; (2 mapping data to around 0 gains much faster training speed than mapping them to the intervals far away from 0 or using unnormalized raw data, although all of them can approach the same lower level after certain steps from their training error curves. This could be useful to decide data normalization method when PLNN is used individually.

  3. Generation of daily solar irradiation by means of artificial neural net works

    Energy Technology Data Exchange (ETDEWEB)

    Siqueira, Adalberto N.; Tiba, Chigueru; Fraidenraich, Naum [Departamento de Energia Nuclear, da Universidade Federal de Pernambuco, Av. Prof. Luiz Freire, 1000 - CDU, CEP 50.740-540 Recife, Pernambuco (Brazil)

    2010-11-15

    The present study proposes the utilization of Artificial Neural Networks (ANN) as an alternative for generating synthetic series of daily solar irradiation. The sequences were generated from the use of daily temporal series of a group of meteorological variables that were measured simultaneously. The data used were measured between the years of 1998 and 2006 in two temperate climate localities of Brazil, Ilha Solteira (Sao Paulo) and Pelotas (Rio Grande do Sul). The estimates were taken for the months of January, April, July and October, through two models which are distinguished regarding the use or nonuse of measured bright sunshine hours as an input variable. An evaluation of the performance of the 56 months of solar irradiation generated by way of ANN showed that by using the measured bright sunshine hours as an input variable (model 1), the RMSE obtained were less or equal to 23.2% being that of those, although 43 of those months presented RMSE less or equal to 12.3%. In the case of the model that did not use the measured bright sunshine hours but used a daylight length (model 2), RMSE were obtained that varied from 8.5% to 37.5%, although 38 of those months presented RMSE less or equal to 20.0%. A comparison of the monthly series for all of the years, achieved by means of the Kolmogorov-Smirnov test (to a confidence level of 99%), demonstrated that of the 16 series generated by ANN model only two, obtained by model 2 for the months of April and July in Pelotas, presented significant difference in relation to the distributions of the measured series and that all mean deviations obtained were inferior to 0.39 MJ/m{sup 2}. It was also verified that the two ANN models were able to reproduce the principal statistical characteristics of the frequency distributions of the measured series such as: mean, mode, asymmetry and Kurtosis. (author)

  4. A 3D Active Learning Application for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

    Science.gov (United States)

    van den Bergh, Jarrett; Schutz, Joey; Li, Alan; Chirayath, Ved

    2017-01-01

    NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive video game prototype for tablet and mobile devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using fluid lensing to create a dataset that will be used to train NeMO-Nets convolutional neural network. The application currently allows for users to classify preselected regions of coral in the Pacific and will be expanded to include additional regions captured using our NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as lower-resolution airborne remote sensing data from the ongoing NASA CORAL campaign. Active learning applications present a novel methodology for efficiently training large-scale Neural Networks wherein variances in identification can be rapidly mitigated against control data. NeMO-Net periodically checks users input against pre-classified coral imagery to gauge their accuracy and utilize in-game mechanics to provide classification training. Users actively communicate with a server and are requested to classify areas of coral for which other users had conflicting classifications and contribute their input to a larger database for ranking. In partnering with Mission Blue and IUCN, NeMO-Net leverages an international consortium of subject matter experts to classify areas of confusion identified by NeMO-Net and generate additional labels crucial for identifying decision boundary locations in coral reef assessment.

  5. Use of genetic programming, logistic regression, and artificial neural nets to predict readmission after coronary artery bypass surgery.

    Science.gov (United States)

    Engoren, Milo; Habib, Robert H; Dooner, John J; Schwann, Thomas A

    2013-08-01

    As many as 14 % of patients undergoing coronary artery bypass surgery are readmitted within 30 days. Readmission is usually the result of morbidity and may lead to death. The purpose of this study is to develop and compare statistical and genetic programming models to predict readmission. Patients were divided into separate Construction and Validation populations. Using 88 variables, logistic regression, genetic programs, and artificial neural nets were used to develop predictive models. Models were first constructed and tested on the Construction populations, then validated on the Validation population. Areas under the receiver operator characteristic curves (AU ROC) were used to compare the models. Two hundred and two patients (7.6 %) in the 2,644 patient Construction group and 216 (8.0 %) of the 2,711 patient Validation group were re-admitted within 30 days of CABG surgery. Logistic regression predicted readmission with AU ROC = .675 ± .021 in the Construction group. Genetic programs significantly improved the accuracy, AU ROC = .767 ± .001, p genetic programming (AU ROC = .654 ± .001) was still trivially but statistically non-significantly better than that of the logistic regression (AU ROC = .644 ± .020, p = .61). Genetic programming and logistic regression provide alternative methods to predict readmission that are similarly accurate.

  6. Maximizng the sensitivity of a low threshold VHE gamma ray telescope by the use of neural nets and other methods

    Energy Technology Data Exchange (ETDEWEB)

    Kertzman, M.P. (Department of Physics and Astronomy, DePauw University Greencastle, Indiana 46135 (USA)); Sembroski, G.H. (Department of Physcis, Purdue University West Lafayette, Indiana 47907 (USA))

    1991-04-05

    Detailed 3-dimensional Monte-Carlo computer simulations of the Cherenkov photons produced by VHE (10 GeV to 10 TeV) gamma ray and proton induced air shower cascades are used to calculate the sensitivity and threshold of a ground-based, single-mount, multi-mirror, single photo-electron sensitive gamma ray telescope. Such a telescope is designed to have the lowest possible energy threshold for gamma ray induced air showers for a given light collection area. The sensitivity and energy threshold of this design are determined for various triggering configurations, and the sources and properties of background triggers are investigated. In particular, it is found that up to 40% of the background triggers are due to single muons produced by proton induced showers with primary energies in the 25 to 75 GeV range. Two methods for increasing the sensitivity of such a telescope by discrimination against the single muon induced triggers are investigated. The first uses small outrider telescopes triggering in coincidence with the main telescope. The second uses software implemented neural nets trained to identify muon induced triggers by use of the temporal shape of the Cherenkov light pulse.

  7. NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

    Science.gov (United States)

    Chirayath, Ved

    2017-01-01

    In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration

  8. Search for prompt neutrinos with AMANDA-II

    Energy Technology Data Exchange (ETDEWEB)

    Gozzini, Sara Rebecca

    2008-09-11

    The investigation performed in this work aims to identify and disentangle the signal of prompt neutrinos from the inclusive atmospheric spectrum. We have analysed data recorded in the years 2000-2003 by the AMANDA-II detector at the geographical South Pole. After a tight event selection, our sample is composed of about 4 . 10{sup 3} atmospheric neutrinos. Prompt neutrinos are decay products of heavy quark hadrons, which are produced in the collision of a cosmic ray particle with a nucleon in the atmosphere. The technique used to recognise prompt neutrinos is based on a simulated information of their energy spectrum, which appears harder than that of the conventional component from light quarks. Models accounting for different hadron production and decay schemes have been included in a Monte Carlo simulation and convoluted with the detector response, in order to reproduce the different spectra. The background of conventional events has been described with the Bartol 2006 tables. The energy spectrum of our data has been reconstructed through a numerical unfolding algorithm. The reconstruction is based on a Monte Carlo simulation and uses as an input three parameters of the neutrino track which are correlated with the energy of the event. Numerical regularisation is introduced to achieve a result free of unphysical oscillations, typical unfortunate feature of unfolding. The reconstructed data spectrum has been compared with different predictions using the model rejection factor technique. The prompt neutrino models differ in the choice of the hadron interaction model, the set of parton distribution functions and the numerical parameterisation of the fragmentation functions describing the transition from quark to hadrons. Here we considered mainly three classes of models, known in the literature as the Recombination Quark Parton Model, the Quark Gluon String Model and the Perturbative QCD model. Upper limits have been set on the expected flux predictions, based on our

  9. Design and realization of the AMANDA software trigger for the TWA data readout system; Entwurf und Realisierung des AMANDA-Softwaretriggers fuer das TWR-Datenauslese-System

    Energy Technology Data Exchange (ETDEWEB)

    Messarius, Timo

    2006-07-15

    The thesis begins with a short introduction in the theory of astroparticle physics. Especially the processes, which lead to signal respectively background events in neutrino detectors, are discussed. Thereafter follows the descripotion of the basing detection principle and the detectors AMANDA and IceCube. The following chapter considers the two data-acquisition systems of the AMANDA detector and explains the motivation for the construction of a new data-acquisition system. The newly designed trigger system is then extensively treated. First a completely on software basing system is discussed, and then the implemented version is considered more detailedly. A procedure to detect and to mark events from atmospheric muons directly on trigger level is presented.

  10. Tracking by Neural Nets

    CERN Document Server

    Jofrehei, Arash

    2015-01-01

    Current track reconstruction methods start with two points and then for each layer loop through all possible hits to find proper hits to add to that track. Another idea would be to use this large number of already reconstructed events and/or simulated data and train a machine on this data to find tracks given hit pixels. Training time could be long but real time tracking is really fast. Simulation might not be as realistic as real data but tracking efficiency is 100 percent for that while by using real data we would probably be limited to current efficiency. The fact that this approach can be a lot faster and even more efficient than current methods by using simulation data can make it a great alternative for current track reconstruction methods used in both triggering and tracking.

  11. A search for Gamma Ray Burst Neutrinos in AMANDA

    Science.gov (United States)

    Duvoort, M. R.

    2009-11-01

    To date, no neutrinos with energies in or above the GeV range have been identified from astrophysical objects. The aim of the two analyses described in this dissertation is to observe high-energy muon neutrinos from Gamma Ray Bursts (GRBs). GRBs are distant sources, which were discovered by satellites recording their flashes of high-energy electromagnetic radiation. In some cases, the gamma-ray flashes are followed by lower energy radiation. GRBs are observed to have a well localized position and a short duration. This allows us to reduce the background in searching the data of the AMANDA/IceCube detector for a possible signal. As no detection of those highly energetic neutrinos has succeeded so far, we aim to analyze our data in a rather unbiased way and limit the dependence on theoretical modelling of the GRB engine. To this end we filter the data using parameters which depend only weakly on the neutrino energy spectrum (unlike a previous analysis in Achterberg et al. (2007)). Besides this, we allow for a possible time di erence between the arrival time of the prompt photon emission and the neutrino signal: our analyses are sensitive to signals arriving within one hour of the satellite trigger time (whereas previous analyses followed an approach which is only sensitive for signals within ten minutes centered around the arrival of the prompt -s (Achterberg et al. 2008)). The two separate analyses presented here di er in one important aspect: in the analysis of the specific burst GRB080319B we analyze the data of one single GRB event for the presence of neutrinos from this GRB. The central assumption is that this ”brightest GRB observed to date” might produce a high-energy neutrino flux which is significantly higher than the average GRB neutrino flux. (This approach was also followed in the analysis of the data of GRB030329 (Stamatikos & et al. 2005).) The second analysis we present is based on stacking the data of multiple GRBs (with average properties) to

  12. Geochemical record of high emperor penguin populations during the Little Ice Age at Amanda Bay, Antarctica

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Tao, E-mail: huangt@ahu.edu.cn [School of Resources and Environmental Engineering, Anhui University, Hefei 230601 (China); School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026 (China); Yang, Lianjiao; Chu, Zhuding [School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026 (China); Sun, Liguang, E-mail: slg@ustc.edu.cn [School of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026 (China); Yin, Xijie [Third Institute of Oceanography, State Oceanic Administration, Xiamen 361005 (China)

    2016-09-15

    Emperor penguins (Aptenodytes forsteri) are sensitive to the Antarctic climate change because they breed on the fast sea ice. Studies of paleohistory for the emperor penguin are rare, due to the lack of archives on land. In this study, we obtained an emperor penguin ornithogenic sediment profile (PI) and performed geochronological, geochemical and stable isotope analyses on the sediments and feather remains. Two radiocarbon dates of penguin feathers in PI indicate that emperor penguins colonized Amanda Bay as early as CE 1540. By using the bio-elements (P, Se, Hg, Zn and Cd) in sediments and stable isotope values (δ{sup 15}N and δ{sup 13}C) in feathers, we inferred relative population size and dietary change of emperor penguins during the period of CE 1540–2008, respectively. An increase in population size with depleted N isotope ratios for emperor penguins on N island at Amanda Bay during the Little Ice Age (CE 1540–1866) was observed, suggesting that cold climate affected the penguin's breeding habitat, prey availability and thus their population and dietary composition. - Highlights: • Emperor penguin colonized at Amanda Bay, East Antarctic as early as AD 1540. • Populations of emperor penguin at Amanda Bay increase during the little ice age. • Depleted N isotope ratios of Emperor penguins during the LIA were observed.

  13. Search for neutrino-induced cascades with five years of AMANDA data

    NARCIS (Netherlands)

    Abbasi, R.; Abdou, Y.; Abu-Zayyad, T.; Actis, O.; Adams, J.; Aguilar, J.A.; Ahlers, M.; Andeen, K.; Auffenberg, J.; Bai, X.; Baker, M.; Barwick, S.W.; Bay, R.; Alba, J.L.B.; Beattie, K.; Beatty, J.J.; Bechet, S.; Becker, J.K.; Becker, K.H.; Benabderrahmane, M.L.; Berdermann, J.; Berghaus, P.; Berley, D.; Bernardini, E.; Bertrand, D.; Besson, D.Z.; Bissok, M.; Blaufuss, E.; Boersma, D.J.; Bohm, C.; Boser, S.; Botner, O.; Bradley, L.; Braun, J.; Buitirik, S.; Carson, M.; Chirkin, D.; Christy, B.; Clem, J.; Clevermann, F.; Cohen, S.; Colnard, C.; Cowen, D.F.; D'Agostino, M.V.; Danninger, M.; Davis, J.C.; Clercq, C. De; Demirors, L.; Depaepe, O.; Descamps, F.; Desiati, P.; Vries-Uiterweerd, G. de; DeYoung, T.; Diaz-Velez, J.C.; Dreyer, J.; Dumm, J.P.; Duvoort, M.R.; Ehrlich, R.; Eisch, J.; Ellsworth, R.W.; Engdegard, O.; Euler, S.; Evenson, P.A.; Fadiran, O.; Fazely, A.R.; Feusels, T.; Filimonov, K.; Finley, C.; Foerster, M.M.; Fox, B.D.; Franckowiak, A.; Franke, R.; Gaisser, T.K.; Gallagher, J.; Ganugapati, R.; Geisler, M.; Gerhardt, L.; Gladstone, L.; Glusenkamp, T.; Goldschmidt, A.; Goodman, J.A.; Grant, D.; Griesel, T.; Gross, A.; Grullon, S.; Gunasingha, R.M.; Gurtner, M.; Ha, C.; Hallgren, A.; Halzen, F.; Han, K.; Hanson, K.; Helbing, K.; Herquet, P.; Hickford, S.; Hill, G.C.; Hoffman, K.D.; Homeier, A.; Hoshina, K.; Hubert, D.; Lafebre, S.J.

    2011-01-01

    We report on the search for electromagnetic and hadronic showers ("cascades") produced by a diffuse flux of extraterrestrial neutrinos in the AMANDA neutrino telescope. Data for this analysis were recorded during 1001 days of detector livetime in the years 2000-2004. The observed event rates are

  14. Estimação do volume de árvores utilizando redes neurais artificiais Estimate of tree volume using artificial neural nets

    Directory of Open Access Journals (Sweden)

    Eric Bastos Gorgens

    2009-12-01

    Full Text Available Rede neural artificial consiste em um conjunto de unidades que contêm funções matemáticas, unidas por pesos. As redes são capazes de aprender, mediante modificação dos pesos sinápticos, e generalizar o aprendizado para outros arquivos desconhecidos. O projeto de redes neurais é composto por três etapas: pré-processamento, processamento e, por fim, pós-processamento dos dados. Um dos problemas clássicos que podem ser abordados por redes é a aproximação de funções. Nesse grupo, pode-se incluir a estimação do volume de árvores. Foram utilizados quatro arquiteturas diferentes, cinco pré-processamentos e duas funções de ativação. As redes que se apresentaram estatisticamente iguais aos dados observados também foram analisadas quanto ao resíduo e à distribuição dos volumes e comparadas com a estimação de volume pelo modelo de Schumacher e Hall. As redes neurais formadas por neurônios, cuja função de ativação era exponencial, apresentaram estimativas estatisticamente iguais aos dados observados. As redes treinadas com os dados normalizados pelo método da interpolação linear e equalizados tiveram melhor desempenho na estimação.The artificial neural network consists of a set of units containing mathematical functions connected by weights. Such nets are capable of learning by means of synaptic weight modification, generalizing learning for other unknown archives. The neural network project comprises three stages: pre-processing, processing and post-processing of data. One of the classical problems approached by networks is function approximation. Tree volume estimate can be included in this group. Four different architectures, five pre-processings and two activation functions were used. The nets which were statistically similar to the observed data were also analyzed in relation to residue and volume and compared to the volume estimate provided by the Schumacher and Hall equation. The neural nets formed by

  15. Multispectral confocal microscopy images and artificial neural nets to monitor the photosensitizer uptake and degradation in Candida albicans cells

    Science.gov (United States)

    Romano, Renan A.; Pratavieira, Sebastião.; da Silva, Ana P.; Kurachi, Cristina; Guimarães, Francisco E. G.

    2017-07-01

    This study clearly demonstrates that multispectral confocal microscopy images analyzed by artificial neural networks provides a powerful tool to real-time monitoring photosensitizer uptake, as well as photochemical transformations occurred.

  16. Net analyte signal-based simultaneous determination of antazoline and naphazoline using wavelength region selection by experimental design-neural networks.

    Science.gov (United States)

    Hemmateenejad, Bahram; Ghavami, Raoof; Miri, Ramin; Shamsipur, Majtaba

    2006-02-15

    Net analyte signal (NAS)-based multivariate calibration methods were employed for simultaneous determination of anthazoline and naphazoline. The NAS vectors calculated from the absorbance data of the drugs mixture were used as input for classical least squares (CLS), principal component and partial least squares regression PCR and PLS methods. A wavelength selection strategy was used to find the best wavelength region for each drug separately. As a new procedure, we proposed an experimental design-neural network strategy for wavelength region optimization. By use of a full factorial design method, some different wavelength regions were selected by taking into account different spectral parameters including the starting wavelength, the ending wavelength and the wavelength interval. The performance of all the multivariate calibration methods, in all selected wavelength regions for both drugs, was evaluated by calculating a fitness function based on the root mean square error of calibration and validation. A three-layered feed-forward artificial neural network (ANN) model with back-propagation learning algorithm was employed to model the nonlinear relationship between the spectral parameters and fitness of each regression method. From the resulted ANN models, the spectral regions in which lowest fitness could be obtained were chosen. Comparison of the results revealed that the net NAS-PLS resulted in lower prediction error than the other models. The proposed NAS-based calibration method was successfully applied to the simultaneous analyses of anthazoline and naphazoline in a commercial eye drop sample.

  17. NetTurnP – Neural Network Prediction of Beta-turns by Use of Evolutionary Information and Predicted Protein Sequence Features

    DEFF Research Database (Denmark)

    Petersen, Bent; Lundegaard, Claus; Petersen, Thomas Nordahl

    2010-01-01

    is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino......β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method...... NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which...

  18. Analisis Faktor-faktor Yang Mempengaruhi Perilaku Konsumen Dalam Keputusan Pembelian Produk Brownies Amanda Pada Konsumen Cabang Abdullah Lubis

    OpenAIRE

    Soelistiariny, Bebbie Rulita

    2011-01-01

    The study, entitled " analysis of the factors that influence consumer behavior in deciding whether to purchase Amanda House in consumer products Department Abdullah " Lubis. The purpose of this study to determine the effect on consumer behaviour, the product purchasing decisions on the consumer branch Amanda House Abdullah Lubis. Method of analysis uses descriptive and statistical analysis method that uses a few tools of linear regression analysis, testing, and a large simultaneous testin...

  19. NetTurnP--neural network prediction of beta-turns by use of evolutionary information and predicted protein sequence features.

    Directory of Open Access Journals (Sweden)

    Bent Petersen

    Full Text Available UNLABELLED: β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino acid sequence. The individual β-turn types I, I', II, II', VIII, VIa1, VIa2, VIba and IV have been predicted based on classifications by PROMOTIF, and the two-class prediction of β-turn or not is a superset comprised of all β-turn types. The performance is evaluated using a golden set of non-homologous sequences known as BT426. Our two-class prediction method achieves a performance of: MCC=0.50, Qtotal=82.1%, sensitivity=75.6%, PPV=68.8% and AUC=0.864. We have compared our performance to eleven other prediction methods that obtain Matthews correlation coefficients in the range of 0.17-0.47. For the type specific β-turn predictions, only type I and II can be predicted with reasonable Matthews correlation coefficients, where we obtain performance values of 0.36 and 0.31, respectively. CONCLUSION: The NetTurnP method has been implemented as a webserver, which is freely available at http://www.cbs.dtu.dk/services/NetTurnP/. NetTurnP is the only available webserver that allows submission of multiple sequences.

  20. Method for detecting neutrinos from internal shocks in GRB fireballs with AMANDA

    CERN Document Server

    Stamatikos, M

    2004-01-01

    Neutrino-based astronomy provides a new window on the most energetic processes in the universe. The discovery of high-energy (E >or= 10 /sup 14/ eV) muonic neutrinos (v/sub mu /) from gamma-ray bursts (GRBs) would confirm hadronic acceleration in the relativistic GRB- wind, validate the phenomenology of the canonical fireball model and possibly reveal an acceleration mechanism for the highest energy cosmic rays (CRs). The Antarctic Muon and Neutrino Detector Array (AMANDA) is the world's largest operational neutrino telescope with a PeV muon effective area (averaged over zenith angle) ~ 50,000 m/sup 2 /. AMANDA uses the natural ice at the geographic South Pole as a Cherenkov medium and has been successfully calibrated on the signal of atmospheric neutrinos (v/sub atm/). Contrary to previous diffuse searches, we describe an analysis based upon confronting AMANDA observations of individual GRBs, adequately modeled by fireball phenomenology, with the predictions of the canonical fireball model. The expected neut...

  1. Derivation of Surface Net Radiation at the Valencia Anchor Station from Top of the Atmosphere Gerb Fluxes by Means of Linear Models and Neural Networks

    Science.gov (United States)

    Geraldo Ferreira, A.; Lopez-Baeza, Ernesto; Velazquez Blazquez, Almudena; Soria-Olivas, Emilio; Serrano Lopez, Antonio J.; Gomez Chova, Juan

    2012-07-01

    In this work, Linear Models (LM) and Artificial Neural Networks (ANN) have been developed to estimate net radiation (RN) at the surface. The models have been developed and evaluated by using the synergy between Geostationary Earth Radiation Budget (GERB-1) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) data, both instruments onboard METEOSAT-9, and ``in situ'' measurements. The data used in this work, corresponding to August 2006 and June to August 2007, proceed from Top of the Atmosphere (TOA) broadband fluxes from GERB-1, every 15 min, and from net radiation at the surface measured, every 10 min, at the Valencia Anchor Station (VAS) area, having measured independently the shortwave and the longwave radiation components (downwelling and upwelling) for different land uses and land cover. The adjustment of both temporal resolutions for the satellite and in situ data was achieved by linear interpolation that showed less standard deviation than the cubic one. The LMs were developed and validated by using satellite TOA RN and ground station surface RN measurements, only considering cloudy free days selected from the ground data. The ANN model was developed both for cloudy and cloudy-free conditions using seven input variables selected for the training/validation sets, namely, hour, day, month, surface RN, solar zenith angle and TOA shortwave and longwave fluxes. Both, LMs and ANNs show remarkably good agreement when compared to surface RN measurements. Therefore, this methodology can be successfully applied to estimate RN at surface from GERB/SEVIRI data.

  2. Amanda Mordavsky Caleb. (Re)Creating Science in Nineteenth-Century Britain

    OpenAIRE

    Talairach-Vielmas, Laurence

    2017-01-01

    Voilà le pari un peu fou d’une publication qui réunit les articles d’un colloque organisé par l’Université de Sheffield en février 2006 : "Electrifying Experimentation : Science in Nineteenth-Century Britain". Le recueil d’Amanda Mordavsky Caleb regroupe 18 articles et est subdivisé en six sous-parties : les sciences naturelles, la médecine, la psychologie, les mathématiques, l’eugénisme et les sciences occultes. Dans chacune des parties, les articles proposent des études variées qui touchent...

  3. Symbiosis of a telemedicine and neural net's project as a new way of the decision of medical problems

    Science.gov (United States)

    Kasimov, Oleg V.; Karchenova, Elena V.; Maximova, Irina L.

    2007-05-01

    The new approach to training doctors which specialty means skill to distinguish various images - for example, doctors of beam diagnostics, pathologists, hematologists is possible. Telemedicine by means of opportunities of the Internet and video-conference is capable to create expert databases in the several world centers. Neural Networks (the Programs, being a part of the Artificial Intellect) - are trained to give out variants of possible interpretations of the set image on the basis of these expert databases. And the doctors trained the above-named specialties, spend not years and not tens years for achievement of an expert level of professionalism, saving time and greater means and societies for training. Having an opportunity diagnostics at the highest level, the medicine improves quality of a life of the patient, also saving its means.

  4. Time calibration of AMANDA three variations of a theme of T$_{0}$

    CERN Document Server

    Hanson, K

    2002-01-01

    The AMANDA-II neutrino telescope currently operating at the South Pole is an array of 677 optical modules (OMs) deployed in the ice at depths between 1200 m and 2300 m beneath the surface. Calibration of the timing offsets of each OM is effected primarily by means of in- ice light pulses transmitted via optical fibers from a surface YAG laser. Discriminator walk, which is significant due to the transmission of electrical signals over 2 km distances, is also calibrated using the YAG laser. Another way to calibrate the timing offsets is to use downgoing cosmic ray muons. This method has the advantages of fuller coverage and year-round availability, i.e., it can be done anytime the detector is taking data. Finally, preliminary results of a technique used to calibrate, with nanosecond precision, the local clocks in "digital optical modules" (DOMs), which digitize and timestamp PMT signals in situ, are presented using DOMs in operation in AMANDA-II. The DOM is part of the baseline design for the planned IceCube de...

  5. Search for Ultra High-Energy Neutrinos with AMANDA-II

    Energy Technology Data Exchange (ETDEWEB)

    IceCube Collaboration; Klein, Spencer; Ackermann, M.

    2007-11-19

    A search for diffuse neutrinos with energies in excess of 10{sup 5} GeV is conducted with AMANDA-II data recorded between 2000 and 2002. Above 10{sup 7} GeV, the Earth is essentially opaque to neutrinos. This fact, combined with the limited overburden of the AMANDA-II detector (roughly 1.5 km), concentrates these ultra high-energy neutrinos at the horizon. The primary background for this analysis is bundles of downgoing, high-energy muons from the interaction of cosmic rays in the atmosphere. No statistically significant excess above the expected background is seen in the data, and an upper limit is set on the diffuse all-flavor neutrino flux of E{sup 2} {Phi}{sub 90%CL} < 2.7 x 10{sup -7} GeV cm{sup -2}s{sup -1} sr{sup -1} valid over the energy range of 2 x 10{sup 5} GeV to 10{sup 9} GeV. A number of models which predict neutrino fluxes from active galactic nuclei are excluded at the 90% confidence level.

  6. Mapping the Spatial Distribution of Winter Crops at Sub-Pixel Level Using AVHRR NDVI Time Series and Neural Nets

    Directory of Open Access Journals (Sweden)

    Felix Rembold

    2013-03-01

    Full Text Available For large areas, it is difficult to assess the spatial distribution and inter-annual variation of crop acreages through field surveys. Such information, however, is of great value for governments, land managers, planning authorities, commodity traders and environmental scientists. Time series of coarse resolution imagery offer the advantage of global coverage at low costs, and are therefore suitable for large-scale crop type mapping. Due to their coarse spatial resolution, however, the problem of mixed pixels has to be addressed. Traditional hard classification approaches cannot be applied because of sub-pixel heterogeneity. We evaluate neural networks as a modeling tool for sub-pixel crop acreage estimation. The proposed methodology is based on the assumption that different cover type proportions within coarse pixels prompt changes in time profiles of remotely sensed vegetation indices like the Normalized Difference Vegetation Index (NDVI. Neural networks can learn the relation between temporal NDVI signatures and the sought crop acreage information. This learning step permits a non-linear unmixing of the temporal information provided by coarse resolution satellite sensors. For assessing the feasibility and accuracy of the approach, a study region in central Italy (Tuscany was selected. The task consisted of mapping the spatial distribution of winter crops abundances within 1 km AVHRR pixels between 1988 and 2001. Reference crop acreage information for network training and validation was derived from high resolution Thematic Mapper/Enhanced Thematic Mapper (TM/ETM+ images and official agricultural statistics. Encouraging results were obtained demonstrating the potential of the proposed approach. For example, the spatial distribution of winter crop acreage at sub-pixel level was mapped with a cross-validated coefficient of determination of 0.8 with respect to the reference information from high resolution imagery. For the eight years for which

  7. The Unification Space implemented as a localist neural net: predictions and error-tolerance in a constraint-based parser.

    Science.gov (United States)

    Vosse, Theo; Kempen, Gerard

    2009-12-01

    We introduce a novel computer implementation of the Unification-Space parser (Vosse and Kempen in Cognition 75:105-143, 2000) in the form of a localist neural network whose dynamics is based on interactive activation and inhibition. The wiring of the network is determined by Performance Grammar (Kempen and Harbusch in Verb constructions in German and Dutch. Benjamins, Amsterdam, 2003), a lexicalist formalism with feature unification as binding operation. While the network is processing input word strings incrementally, the evolving shape of parse trees is represented in the form of changing patterns of activation in nodes that code for syntactic properties of words and phrases, and for the grammatical functions they fulfill. The system is capable, at least qualitatively and rudimentarily, of simulating several important dynamic aspects of human syntactic parsing, including garden-path phenomena and reanalysis, effects of complexity (various types of clause embeddings), fault-tolerance in case of unification failures and unknown words, and predictive parsing (expectation-based analysis, surprisal effects). English is the target language of the parser described.

  8. Determination of the Atmospheric Neutrino Flux and Searches for New Physics with AMANDA-II

    Energy Technology Data Exchange (ETDEWEB)

    IceCube Collaboration; Klein, Spencer; Collaboration, IceCube

    2009-06-02

    The AMANDA-II detector, operating since 2000 in the deep ice at the geographic South Pole, has accumulated a large sample of atmospheric muon neutrinos in the 100 GeV to 10 TeV energy range. The zenith angle and energy distribution of these events can be used to search for various phenomenological signatures of quantum gravity in the neutrino sector, such as violation of Lorentz invariance (VLI) or quantum decoherence (QD). Analyzing a set of 5511 candidate neutrino events collected during 1387 days of livetime from 2000 to 2006, we find no evidence for such effects and set upper limits on VLI and QD parameters using a maximum likelihood method. Given the absence of evidence for new flavor-changing physics, we use the same methodology to determine the conventional atmospheric muon neutrino flux above 100 GeV.

  9. A Monte Carlo study of atmospheric muon-neutrinos in Amanda

    Energy Technology Data Exchange (ETDEWEB)

    Dalberg, E.

    1998-01-01

    The response of AMANDA detector to atmospheric muon-neutrinos has been simulated. The neutrino flux, which has its origin from cosmic ray interactions with the atmosphere, induce muons in the vicinity of the detector. These muons will be relativistic and emit Cerenkov photons which can be detected by the optical modules buried in the deep South Pole glacier ice. The aim of the simulations is to predict the trigger rates in the existing detector, as well as in future extensions. The efficiency to detect muons with different angles and energies is also studied. Some of the simulated events have been analysed and it is discussed how the quality of this analysis can be judged. 35 refs, 30 figs.

  10. Search for relativistic magnetic monopoles with the AMANDA-II detector

    Energy Technology Data Exchange (ETDEWEB)

    Wissing, Henrike

    2009-02-25

    Cherenkov emissions of magnetically charged particles passing through a transparent medium will exceed those of electrically charged particles by several orders of magnitude. The Antarctic Muon And Neutrino Detector Array (AMANDA), a neutrino telescope utilizing the glacial ice at the geographic South Pole as Cherenkov medium, is capable of efficiently detecting relativistic magnetic monopoles that may pass through its sensitive volume. This thesis presents the search for Cherenkov signatures from relativistic magnetic monopoles in data taken with AMANDA during the 2000. No such signal is observed in the data, and the analysis allows to place upper limits on the flux of relativistic magnetic monopoles. The limit obtained for monopoles reaching the detector from below the horizon, i.e., those monopoles that are capable of crossing the Earth, is the most stringent experimental constraint on the flux of magnetic monopoles to date: Dependent on the monopole speed, the flux limit (at 90% confidence level) varies between 3.8 x 10{sup -17} cm{sup -2}s{sup -1}sr{sup -1} (for monopoles moving at the vacuum speed of light) and 8.8 x 10{sup -16} cm{sup -2}s{sup -1}sr{sup -1} (for monopoles moving at a speed just above the Cherenkov threshold). The limit obtained for monopoles reaching the detector from above the horizon is less stringent by roughly an order of magnitude, owing to the much larger background from down-going atmospheric muons. This looser limit is valid for a larger class of magnetic monopoles, since the monopole's capability to pass through the Earth is not a requirement. (orig.)

  11. Using a multi-port architecture of neural-net associative memory based on the equivalency paradigm for parallel cluster image analysis and self-learning

    Science.gov (United States)

    Krasilenko, Vladimir G.; Lazarev, Alexander A.; Grabovlyak, Sveta K.; Nikitovich, Diana V.

    2013-01-01

    We consider equivalency models, including matrix-matrix and matrix-tensor and with the dual adaptive-weighted correlation, multi-port neural-net auto-associative and hetero-associative memory (MP NN AAM and HAP), which are equivalency paradigm and the theoretical basis of our work. We make a brief overview of the possible implementations of the MP NN AAM and of their architectures proposed and investigated earlier by us. The main base unit of such architectures is a matrix-matrix or matrix-tensor equivalentor. We show that the MP NN AAM based on the equivalency paradigm and optoelectronic architectures with space-time integration and parallel-serial 2D images processing have advantages such as increased memory capacity (more than ten times of the number of neurons!), high performance in different modes (1010 - 1012 connections per second!) And the ability to process, store and associatively recognize highly correlated images. Next, we show that with minor modifications, such MP NN AAM can be successfully used for highperformance parallel clustering processing of images. We show simulation results of using these modifications for clustering and learning models and algorithms for cluster analysis of specific images and divide them into categories of the array. Show example of a cluster division of 32 images (40x32 pixels) letters and graphics for 12 clusters with simultaneous formation of the output-weighted space allocated images for each cluster. We discuss algorithms for learning and self-learning in such structures and their comparative evaluations based on Mathcad simulations are made. It is shown that, unlike the traditional Kohonen self-organizing maps, time of learning in the proposed structures of multi-port neuronet classifier/clusterizer (MP NN C) on the basis of equivalency paradigm, due to their multi-port, decreases by orders and can be, in some cases, just a few epochs. Estimates show that in the test clustering of 32 1280- element images into 12

  12. Semantic Networks and Neural Nets.

    Science.gov (United States)

    1984-06-01

    TRAGEDIES . If John likes SCIENCE-FICTION more than SHAKESPEAREAN - TRAGEDIES then it is easy to see how SCIENCE-FICTION will be chosen as the answer...manner it is easy to see how in subsequent steps the fod may converge to [LITERARY-KIND ’AI with the choices being SCIENCE-FICTION and SHAKESPEAREAN

  13. Check of the accuracy of the relativity theory with atmospheric muon neutrinos from the AMANDA data of the years 2000 to 2003; Ueberpruefung der Genauigkeit der Relativitaetstheorie mit atmosphaerischen Myonneutrinos aus den AMANDA-Daten der Jahre 2000 bis 2003

    Energy Technology Data Exchange (ETDEWEB)

    Ahrens, J.C.

    2006-11-08

    Atmospheric neutrinos allow one to test the principles of the Theory of Relativity in particular Lorentz invariance and the equivalence principle. Small deviations from these principles could lead, according to some theories, to detectable neutrino oscillations. Such oscillation effects are analysed in this thesis, using the data collected by the AMANDA detector. The neutrino telescope AMANDA is located at the South Pole and embedded in the Antarctic ice shield at a depth between 1500 m and 2000 m. AMANDA detects muon neutrinos via the Cherenkov light of neutrino induced muons allowing the reconstruction of the original neutrino direction. From the data of the years 2000 to 2003, which contain about seven billion recorded events and which mainly consist of the background of atmospheric muons, a sample of 3401 neutrino induced events has been selected. No indication for alternative oscillation effects has been found. For maximal mixing angles, a lower limit for parameters which violate Lorentz invariance or the equivalence principle could be set to {delta}{beta}(2 vertical stroke {phi} vertical stroke {delta}{gamma}){<=}5.15.10{sup -27}. (orig)

  14. GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework.

    Science.gov (United States)

    Deng, Lei; Jiao, Peng; Pei, Jing; Wu, Zhenzhi; Li, Guoqi

    2018-02-02

    Although deep neural networks (DNNs) are being a revolutionary power to open up the AI era, the notoriously huge hardware overhead has challenged their applications. Recently, several binary and ternary networks, in which the costly multiply-accumulate operations can be replaced by accumulations or even binary logic operations, make the on-chip training of DNNs quite promising. Therefore there is a pressing need to build an architecture that could subsume these networks under a unified framework that achieves both higher performance and less overhead. To this end, two fundamental issues are yet to be addressed. The first one is how to implement the back propagation when neuronal activations are discrete. The second one is how to remove the full-precision hidden weights in the training phase to break the bottlenecks of memory/computation consumption. To address the first issue, we present a multi-step neuronal activation discretization method and a derivative approximation technique that enable the implementing the back propagation algorithm on discrete DNNs. While for the second issue, we propose a discrete state transition (DST) methodology to constrain the weights in a discrete space without saving the hidden weights. Through this way, we build a unified framework that subsumes the binary or ternary networks as its special cases, and under which a heuristic algorithm is provided at the website https://github.com/AcrossV/Gated-XNOR. More particularly, we find that when both the weights and activations become ternary values, the DNNs can be reduced to sparse binary networks, termed as gated XNOR networks (GXNOR-Nets) since only the event of non-zero weight and non-zero activation enables the control gate to start the XNOR logic operations in the original binary networks. This promises the event-driven hardware design for efficient mobile intelligence. We achieve advanced performance compared with state-of-the-art algorithms. Furthermore, the computational sparsity

  15. Neural network-based estimates of Southern Ocean net community production from in situ O2 / Ar and satellite observation: a methodological study

    Science.gov (United States)

    Chang, C.-H.; Johnson, N. C.; Cassar, N.

    2014-06-01

    Southern Ocean organic carbon export plays an important role in the global carbon cycle, yet its basin-scale climatology and variability are uncertain due to limited coverage of in situ observations. In this study, a neural network approach based on the self-organizing map (SOM) is adopted to construct weekly gridded (1° × 1°) maps of organic carbon export for the Southern Ocean from 1998 to 2009. The SOM is trained with in situ measurements of O2 / Ar-derived net community production (NCP) that are tightly linked to the carbon export in the mixed layer on timescales of one to two weeks and with six potential NCP predictors: photosynthetically available radiation (PAR), particulate organic carbon (POC), chlorophyll (Chl), sea surface temperature (SST), sea surface height (SSH), and mixed layer depth (MLD). This nonparametric approach is based entirely on the observed statistical relationships between NCP and the predictors and, therefore, is strongly constrained by observations. A thorough cross-validation yields three retained NCP predictors, Chl, PAR, and MLD. Our constructed NCP is further validated by good agreement with previously published, independent in situ derived NCP of weekly or longer temporal resolution through real-time and climatological comparisons at various sampling sites. The resulting November-March NCP climatology reveals a pronounced zonal band of high NCP roughly following the Subtropical Front in the Atlantic, Indian, and western Pacific sectors, and turns southeastward shortly after the dateline. Other regions of elevated NCP include the upwelling zones off Chile and Namibia, the Patagonian Shelf, the Antarctic coast, and areas surrounding the Islands of Kerguelen, South Georgia, and Crozet. This basin-scale NCP climatology closely resembles that of the satellite POC field and observed air-sea CO2 flux. The long-term mean area-integrated NCP south of 50° S from our dataset, 17.9 mmol C m-2 d-1, falls within the range of 8.3 to 24 mmol

  16. Neural network-based estimates of Southern Ocean net community production from in-situ O2 / Ar and satellite observation: a methodological study

    Science.gov (United States)

    Chang, C.-H.; Johnson, N. C.; Cassar, N.

    2013-10-01

    Southern Ocean organic carbon export plays an important role in the global carbon cycle, yet its basin-scale climatology and variability are uncertain due to limited coverage of in situ observations. In this study, a neural network approach based on the self-organizing map (SOM) is adopted to construct weekly gridded (1° × 1°) maps of organic carbon export for the Southern Ocean from 1998 to 2009. The SOM is trained with in situ measurements of O2 / Ar-derived net community production (NCP) that are tightly linked to the carbon export in the mixed layer on timescales of 1-2 weeks, and six potential NCP predictors: photosynthetically available radiation (PAR), particulate organic carbon (POC), chlorophyll (Chl), sea surface temperature (SST), sea surface height (SSH), and mixed layer depth (MLD). This non-parametric approach is based entirely on the observed statistical relationships between NCP and the predictors, and therefore is strongly constrained by observations. A thorough cross-validation yields three retained NCP predictors, Chl, PAR, and MLD. Our constructed NCP is further validated by good agreement with previously published independent in situ derived NCP of weekly or longer temporal resolution through real-time and climatological comparisons at various sampling sites. The resulting November-March NCP climatology reveals a pronounced zonal band of high NCP roughly following the subtropical front in the Atlantic, Indian and western Pacific sectors, and turns southeastward shortly after the dateline. Other regions of elevated NCP include the upwelling zones off Chile and Namibia, Patagonian Shelf, Antarctic coast, and areas surrounding the Islands of Kerguelen, South Georgia, and Crozet. This basin-scale NCP climatology closely resembles that of the satellite POC field and observed air-sea CO2 flux. The long-term mean area-integrated NCP south of 50° S from our dataset, 14 mmol C m-2 d-1, falls within the range of 8.3-24 mmol C m-2 d-1 from other model

  17. Multi-year search for a diffuse flxu of muon neutrinos with AMANDA-II

    Energy Technology Data Exchange (ETDEWEB)

    IceCube Collaboration; Klein, Spencer; Achterberg, A.; Collaboration, IceCube

    2008-04-13

    A search for TeV-PeV muon neutrinos from unresolved sources was performed on AMANDA-II data collected between 2000 and 2003 with an equivalent livetime of 807 days. This diffuse analysis sought to find an extraterrestrial neutrino flux from sources with non-thermal components. The signal is expected to have a harder spectrum than the atmospheric muon and neutrino backgrounds. Since no excess of events was seen in the data over the expected background, an upper limit of E{sup 2}{Phi}{sub 90%C.L.} < 7.4 x 10{sup -8} GeV cm{sup -2} s{sup -1} sr{sup -1} is placed on the diffuse flux of muon neutrinos with a {Phi} {proportional_to} E{sup -2} spectrum in the energy range 16 TeV to 2.5 PeV. This is currently the most sensitive {Phi} {proportional_to} E{sup -2} diffuse astrophysical neutrino limit. We also set upper limits for astrophysical and prompt neutrino models, all of which have spectra different than {Phi} {proportional_to} E{sup -2}.

  18. Net Locality

    DEFF Research Database (Denmark)

    de Souza e Silva, Adriana Araujo; Gordon, Eric

    Provides an introduction to the new theory of Net Locality and the profound effect on individuals and societies when everything is located or locatable. Describes net locality as an emerging form of location awareness central to all aspects of digital media, from mobile phones, to Google Maps...... of emerging technologies, from GeoCities to GPS, Wi-Fi, Wiki Me, and Google Android....

  19. Net Neutrality

    DEFF Research Database (Denmark)

    Savin, Andrej

    2017-01-01

    Repealing “net neutrality” in the US will have no bearing on Internet freedom or security there or anywhere else.......Repealing “net neutrality” in the US will have no bearing on Internet freedom or security there or anywhere else....

  20. Symbolic processing in neural networks

    OpenAIRE

    Neto, João Pedro; Hava T Siegelmann; Costa,J.Félix

    2003-01-01

    In this paper we show that programming languages can be translated into recurrent (analog, rational weighted) neural nets. Implementation of programming languages in neural nets turns to be not only theoretical exciting, but has also some practical implications in the recent efforts to merge symbolic and sub symbolic computation. To be of some use, it should be carried in a context of bounded resources. Herein, we show how to use resource bounds to speed up computations over neural nets, thro...

  1. Mothers, daughters and midlife (self)-discoveries: gender and aging in the Amanda Cross' Kate Fansler series.

    Science.gov (United States)

    Domínguez-Rué, Emma

    2012-12-01

    In the same way that many aspects of gender cannot be understood aside from their relationship to race, class, culture, nationality and/or sexuality, the interactions between gender and aging constitute an interesting field for academic research, without which we cannot gain full insight into the complex and multi-faceted nature of gender studies. Although the American writer and Columbia professor Carolyn Gold Heilbrun (1926-2003) is more widely known for her best-selling mystery novels, published under the pseudonym of Amanda Cross, she also authored remarkable pieces of non-fiction in which she asserted her long-standing commitment to feminism, while she also challenged established notions on women and aging and advocated for a reassessment of those negative views. To my mind, the Kate Fansler novels became an instrument to reach a massive audience of female readers who might not have read her non-fiction, but who were perhaps finding it difficult to reach fulfillment as women under patriarchy, especially upon reaching middle age. Taking her essays in feminism and literary criticism as a basis and her later fiction as substantiation to my argument, this paper will try to reveal the ways in which Heilbrun's seemingly more superficial and much more commercial mystery novels as Amanda Cross were used a catalyst that informed her feminist principles while vindicating the need to rethink about issues concerning literary representations of mature women and cultural stereotypes about motherhood. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. Analysis of Salinity Intrusion in the San Francisco Bay-Delta Using a GA-Optimized Neural Net, and Application of the Model to Prediction in the Elkhorn Slough Habitat

    Science.gov (United States)

    Thompson, D. E.; Rajkumar, T.

    2002-12-01

    The San Francisco Bay Delta is a large hydrodynamic complex that incorporates the Sacramento and San Joaquin Estuaries, the Suisan Marsh, and the San Francisco Bay proper. Competition exists for the use of this extensive water system both from the fisheries industry, the agricultural industry, and from the marine and estuarine animal species within the Delta. As tidal fluctuations occur, more saline water pushes upstream allowing fish to migrate beyond the Suisan Marsh for breeding and habitat occupation. However, the agriculture industry does not want extensive salinity intrusion to impact water quality for human and plant consumption. The balance is regulated by pumping stations located along the estuaries and reservoirs whereby flushing of fresh water keeps the saline intrusion at bay. The pumping schedule is driven by data collected at various locations within the Bay Delta and by numerical models that predict the salinity intrusion as part of a larger model of the system. The Interagency Ecological Program (IEP) for the San Francisco Bay / Sacramento-San Joaquin Estuary collects, monitors, and archives the data, and the Department of Water Resources provides a numerical model simulation (DSM2) from which predictions are made that drive the pumping schedule. A problem with DSM2 is that the numerical simulation takes roughly 16 hours to complete a prediction. We have created a neural net, optimized with a genetic algorithm, that takes as input the archived data from multiple gauging stations and predicts stage, salinity, and flow at the Carquinez Straits (at the downstream end of the Suisan Marsh). This model seems to be robust in its predictions and operates much faster than the current numerical DSM2 model. Because the Bay-Delta is strongly tidally driven, we used both Principal Component Analysis and Fast Fourier Transforms to discover dominant features within the IEP data. We then filtered out the dominant tidal forcing to discover non-primary tidal effects

  3. Measurement of the cosmic ray composition at the knee with the SPASE-2/AMANDA-B10 detectors

    CERN Document Server

    Ahrens, J; Andrés, E; Bai, X; Barwick, S W; Bay, R C; Becka, T; Becker, K H; Bernardini, E; Bertrand, D; Binon, F; Biron, A; Boersma, D J; Boser, S; Botner, O; Bouchta, A; Bouhali, O; Burgess, T; Carius, S; Castermans, T; Chirkin, D; Conrad, J; Cooley, J; Cowen, D F; Davour, A; De Clercq, C; De Young, T R; Desiati, P; Dewulf, J P; Dickinson, E; Ekstrom, P; Engel, R; Evenson, P; Feser, T; Gaisser, T K; Ganugapati, R; Gaug, M; Geenen, H; Gerhardt, L; Goldschmidt, A; Hallgren, A; Halzen, F; Hanson, K; Hardtke, R; Hauschildt, T; Hellwig, M; Herquet, P; Hill, G C; Hinton, J A; Hubert, D; Hughey, B; Hulth, P O; Hultqvist, K; Hundertmark, S; Jacobsen, J; Karle, A; Kim, J; Köpke, L; Kowalski, M; Kühn, K; Lamoureux, J I; Leich, H; Leuthold, M; Lindahl, P; Liubarsky, I; Lloyd Evans, J; Madsen, J; Mandli, K; Marciniewski, P; Martino, J R; Matis, H S; McParland, C P; Messarius, T; Miller, T C; Minaeva, Y; Miocinovic, P; Mock, P C; Morse, R; Nahnhauer, R; Neunhoffer, T; Niessen, P; Nygren, D R; Ogleman, H; Olbrechts, P; Pohl, A C; Porrata, R; Price, P B; Przybylski, G T; Rawlins, K; Resconi, E; Rhode, W; Ribordy, M; Richter, S; Rochester, K; Ross, D; Sander, H G; Schinarakis, K; Schlenstedt, S; Schmidt, T; Schneider, D; Schwarz, R; Silvestri, A; Solarz, M; Spiczak, G M; Spiering, C; Stamatikos, M; Stanev, T; Steele, D; Steffen, P; Stokstad, R G; Sulanke, K H; Taboada, I; Tilav, S; Wagner, W; Walck, C; Wang, Y R; Watson, A A; Wiebusch, C; Wiedemann, C; Wischnewski, R; Wissing, H; Woschnagg, K; Wu, W; Yodh, G; Young, S; Pérez de los Heros, C; 10.1016/j.astropartphys.2004.04.007

    2004-01-01

    The mass composition of high-energy cosmic rays at energies above 10 /sup 15/ eV can provide crucial information for the understanding of their origin. Air showers were measured simultaneously with the SPASE-2 air shower array and the AMANDA-B10 Cherenkov telescope at the South Pole. This combination has the advantage to sample almost all high-energy shower muons and is thus a new approach to the determination of the cosmic ray composition. The change in the cosmic ray mass composition was measured versus existing data from direct measurements at low energies. Our data show an increase of the mean log atomic mass by about 0.8 between 500 TeV and 5 PeV. This trend of an increasing mass through the "knee" region is robust against a variety of systematic effects.

  4. RESTful NET

    CERN Document Server

    Flanders, Jon

    2008-01-01

    RESTful .NET is the first book that teaches Windows developers to build RESTful web services using the latest Microsoft tools. Written by Windows Communication Foundation (WFC) expert Jon Flanders, this hands-on tutorial demonstrates how you can use WCF and other components of the .NET 3.5 Framework to build, deploy and use REST-based web services in a variety of application scenarios. RESTful architecture offers a simpler approach to building web services than SOAP, SOA, and the cumbersome WS- stack. And WCF has proven to be a flexible technology for building distributed systems not necessa

  5. Petri Nets

    Indian Academy of Sciences (India)

    Associate Professor of. Computer Science and. Automation at the Indian. Institute of Science,. Bangalore. His research interests are broadly in the areas of stochastic modeling and scheduling methodologies for future factories; and object oriented modeling. GENERAL I ARTICLE. Petri Nets. 1. Overview and Foundations.

  6. Petri Nets

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 8. Petri Nets - Overview and Foundations. Y Narahari. General Article Volume 4 Issue 8 August 1999 pp ... Author Affiliations. Y Narahari1. Department ot Computer Science and Automation, Indian Institute of Science, Bangalore 560 012, India.

  7. 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.

  8. Neural network technologies

    Science.gov (United States)

    Villarreal, James A.

    1991-01-01

    A whole new arena of computer technologies is now beginning to form. Still in its infancy, neural network technology is a biologically inspired methodology which draws on nature's own cognitive processes. The Software Technology Branch has provided a software tool, Neural Execution and Training System (NETS), to industry, government, and academia to facilitate and expedite the use of this technology. NETS is written in the C programming language and can be executed on a variety of machines. Once a network has been debugged, NETS can produce a C source code which implements the network. This code can then be incorporated into other software systems. Described here are various software projects currently under development with NETS and the anticipated future enhancements to NETS and the technology.

  9. NA-NET numerical analysis net

    Energy Technology Data Exchange (ETDEWEB)

    Dongarra, J. [Tennessee Univ., Knoxville, TN (United States). Dept. of Computer Science]|[Oak Ridge National Lab., TN (United States); Rosener, B. [Tennessee Univ., Knoxville, TN (United States). Dept. of Computer Science

    1991-12-01

    This report describes a facility called NA-NET created to allow numerical analysts (na) an easy method of communicating with one another. The main advantage of the NA-NET is uniformity of addressing. All mail is addressed to the Internet host ``na-net.ornl.gov`` at Oak Ridge National Laboratory. Hence, members of the NA-NET do not need to remember complicated addresses or even where a member is currently located. As long as moving members change their e-mail address in the NA-NET everything works smoothly. The NA-NET system is currently located at Oak Ridge National Laboratory. It is running on the same machine that serves netlib. Netlib is a separate facility that distributes mathematical software via electronic mail. For more information on netlib consult, or send the one-line message ``send index`` to netlib{at}ornl.gov. The following report describes the current NA-NET system from both a user`s perspective and from an implementation perspective. Currently, there are over 2100 members in the NA-NET. An average of 110 mail messages pass through this facility daily.

  10. NA-NET numerical analysis net

    Energy Technology Data Exchange (ETDEWEB)

    Dongarra, J. (Tennessee Univ., Knoxville, TN (United States). Dept. of Computer Science Oak Ridge National Lab., TN (United States)); Rosener, B. (Tennessee Univ., Knoxville, TN (United States). Dept. of Computer Science)

    1991-12-01

    This report describes a facility called NA-NET created to allow numerical analysts (na) an easy method of communicating with one another. The main advantage of the NA-NET is uniformity of addressing. All mail is addressed to the Internet host na-net.ornl.gov'' at Oak Ridge National Laboratory. Hence, members of the NA-NET do not need to remember complicated addresses or even where a member is currently located. As long as moving members change their e-mail address in the NA-NET everything works smoothly. The NA-NET system is currently located at Oak Ridge National Laboratory. It is running on the same machine that serves netlib. Netlib is a separate facility that distributes mathematical software via electronic mail. For more information on netlib consult, or send the one-line message send index'' to netlib{at}ornl.gov. The following report describes the current NA-NET system from both a user's perspective and from an implementation perspective. Currently, there are over 2100 members in the NA-NET. An average of 110 mail messages pass through this facility daily.

  11. Flexible body control using neural networks

    Science.gov (United States)

    Mccullough, Claire L.

    1992-01-01

    Progress is reported on the control of Control Structures Interaction suitcase demonstrator (a flexible structure) using neural networks and fuzzy logic. It is concluded that while control by neural nets alone (i.e., allowing the net to design a controller with no human intervention) has yielded less than optimal results, the neural net trained to emulate the existing fuzzy logic controller does produce acceptible system responses for the initial conditions examined. Also, a neural net was found to be very successful in performing the emulation step necessary for the anticipatory fuzzy controller for the CSI suitcase demonstrator. The fuzzy neural hybrid, which exhibits good robustness and noise rejection properties, shows promise as a controller for practical flexible systems, and should be further evaluated.

  12. Net Ecosystem Carbon Flux

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Net Ecosystem Carbon Flux is defined as the year-over-year change in Total Ecosystem Carbon Stock, or the net rate of carbon exchange between an ecosystem and the...

  13. Professional Enterprise NET

    CERN Document Server

    Arking, Jon

    2010-01-01

    Comprehensive coverage to help experienced .NET developers create flexible, extensible enterprise application code If you're an experienced Microsoft .NET developer, you'll find in this book a road map to the latest enterprise development methodologies. It covers the tools you will use in addition to Visual Studio, including Spring.NET and nUnit, and applies to development with ASP.NET, C#, VB, Office (VBA), and database. You will find comprehensive coverage of the tools and practices that professional .NET developers need to master in order to build enterprise more flexible, testable, and ext

  14. Neural network optimization, components, and design selection

    Science.gov (United States)

    Weller, Scott W.

    1991-01-01

    Neural Networks are part of a revived technology which has received a lot of hype in recent years. As is apt to happen in any hyped technology, jargon and predictions make its assimilation and application difficult. Nevertheless, Neural Networks have found use in a number of areas, working on non-trivial and non-contrived problems. For example, one net has been trained to "read", translating English text into phoneme sequences. Other applications of Neural Networks include data base manipulation and the solving of routing and classification types of optimization problems. It was their use in optimization that got me involved with Neural Networks. As it turned out, "optimization" used in this context was somewhat misleading, because while some network configurations could indeed solve certain kinds of optimization problems, the configuring or "training" of a Neural Network itself is an optimization problem, and most of the literature which talked about Neural Nets and optimization in the same breath did not speak to my goal of using Neural Nets to help solve lens optimization problems. I did eventually apply Neural Network to lens optimization, and I will touch on those results. The application of Neural Nets to the problem of lens selection was much more successful, and those results will dominate this paper.

  15. WaveNet

    Science.gov (United States)

    2015-10-30

    Coastal Inlets Research Program WaveNet WaveNet is a web-based, Graphical-User-Interface ( GUI ) data management tool developed for Corps coastal...generates tabular and graphical information for project planning and design documents. The WaveNet is a web-based GUI designed to provide users with a...data from different sources, and employs a combination of Fortran, Python and Matlab codes to process and analyze data for USACE applications

  16. Coloured Petri Nets

    DEFF Research Database (Denmark)

    Jensen, Kurt

    1991-01-01

    This paper describes how Coloured Petri Nets (CP-nets) have been developed — from being a promising theoretical model to being a full-fledged language for the design, specification, simulation, validation and implementation of large software systems (and other systems in which human beings and...... use of CP-nets — because it means that the function representation and the translations (which are a bit mathematically complex) no longer are parts of the basic definition of CP-nets. Instead they are parts of the invariant method (which anyway demands considerable mathematical skills...

  17. Game Coloured Petri Nets

    DEFF Research Database (Denmark)

    Westergaard, Michael

    2006-01-01

    This paper introduces the notion of game coloured Petri nets. This allows the modeler to explicitly model what parts of the model comprise the modeled system and what parts are the environment of the modeled system. We give the formal definition of game coloured Petri nets, a means of reachability...... analysis of this net class, and an application of game coloured Petri nets to automatically generate easy-to-understand visualizations of the model by exploiting the knowledge that some parts of the model are not interesting from a visualization perspective (i.e. they are part of the environment...

  18. Programming NET Web Services

    CERN Document Server

    Ferrara, Alex

    2007-01-01

    Web services are poised to become a key technology for a wide range of Internet-enabled applications, spanning everything from straight B2B systems to mobile devices and proprietary in-house software. While there are several tools and platforms that can be used for building web services, developers are finding a powerful tool in Microsoft's .NET Framework and Visual Studio .NET. Designed from scratch to support the development of web services, the .NET Framework simplifies the process--programmers find that tasks that took an hour using the SOAP Toolkit take just minutes. Programming .NET

  19. Annotating Coloured Petri Nets

    DEFF Research Database (Denmark)

    Lindstrøm, Bo; Wells, Lisa Marie

    2002-01-01

    -net. An example of such auxiliary information is a counter which is associated with a token to be able to do performance analysis. Modifying colour sets and arc inscriptions in a CP-net to support a specific use may lead to creation of several slightly different CP-nets – only to support the different uses...... a method which makes it possible to associate auxiliary information, called annotations, with tokens without modifying the colour sets of the CP-net. Annotations are pieces of information that are not essential for determining the behaviour of the system being modelled, but are rather added to support...

  20. Net zero water

    CSIR Research Space (South Africa)

    Lindeque, M

    2013-01-01

    Full Text Available Is it possible to develop a building that uses a net zero amount of water? In recent years it has become evident that it is possible to have buildings that use a net zero amount of electricity. This is possible when the building is taken off...

  1. SolNet

    DEFF Research Database (Denmark)

    Jordan, Ulrike; Vajen, Klaus; Bales, Chris

    2014-01-01

    SolNet, founded in 2006, is the first coordinated International PhD education program on Solar Thermal Engineering. The SolNet network is coordinated by the Institute of Thermal Engineering at Kassel University, Germany. The network offers PhD courses on solar heating and cooling, conference...

  2. Using fuzzy logic to integrate neural networks and knowledge-based systems

    Science.gov (United States)

    Yen, John

    1991-01-01

    Outlined here is a novel hybrid architecture that uses fuzzy logic to integrate neural networks and knowledge-based systems. The author's approach offers important synergistic benefits to neural nets, approximate reasoning, and symbolic processing. Fuzzy inference rules extend symbolic systems with approximate reasoning capabilities, which are used for integrating and interpreting the outputs of neural networks. The symbolic system captures meta-level information about neural networks and defines its interaction with neural networks through a set of control tasks. Fuzzy action rules provide a robust mechanism for recognizing the situations in which neural networks require certain control actions. The neural nets, on the other hand, offer flexible classification and adaptive learning capabilities, which are crucial for dynamic and noisy environments. By combining neural nets and symbolic systems at their system levels through the use of fuzzy logic, the author's approach alleviates current difficulties in reconciling differences between low-level data processing mechanisms of neural nets and artificial intelligence systems.

  3. Self-organization of neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Clark, J.W.; Winston, J.V.; Rafelski, J.

    1984-05-14

    The plastic development of a neural-network model operating autonomously in discrete time is described by the temporal modification of interneuronal coupling strengths according to momentary neural activity. A simple algorithm (brainwashing) is found which, applied to nets with initially quasirandom connectivity, leads to model networks with properties conducive to the simulation of memory and learning phenomena. 18 references, 2 figures.

  4. Pro NET Best Practices

    CERN Document Server

    Ritchie, Stephen D

    2011-01-01

    Pro .NET Best Practices is a practical reference to the best practices that you can apply to your .NET projects today. You will learn standards, techniques, and conventions that are sharply focused, realistic and helpful for achieving results, steering clear of unproven, idealistic, and impractical recommendations. Pro .NET Best Practices covers a broad range of practices and principles that development experts agree are the right ways to develop software, which includes continuous integration, automated testing, automated deployment, and code analysis. Whether the solution is from a free and

  5. Getting to Net Zero

    Energy Technology Data Exchange (ETDEWEB)

    2016-09-01

    The technology necessary to build net zero energy buildings (NZEBs) is ready and available today, however, building to net zero energy performance levels can be challenging. Energy efficiency measures, onsite energy generation resources, load matching and grid interaction, climatic factors, and local policies vary from location to location and require unique methods of constructing NZEBs. It is recommended that Components start looking into how to construct and operate NZEBs now as there is a learning curve to net zero construction and FY 2020 is just around the corner.

  6. Instant Lucene.NET

    CERN Document Server

    Heydt, Michael

    2013-01-01

    Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. A step-by-step guide that helps you to index, search, and retrieve unstructured data with the help of Lucene.NET.Instant Lucene.NET How-to is essential for developers new to Lucene and Lucene.NET who are looking to get an immediate foundational understanding of how to use the library in their application. It's assumed you have programming experience in C# already, but not that you have experience with search techniques such as information retrieval theory (although there will be a l

  7. Net Zero Energy Buildings

    DEFF Research Database (Denmark)

    Marszal, Anna Joanna; Bourrelle, Julien S.; Musall, Eike

    2010-01-01

    and identify possible renewable energy supply options which may be considered in calculations. Finally, the gap between the methodology proposed by each organisation and their respective national building code is assessed; providing an overview of the possible changes building codes will need to undergo......The international cooperation project IEA SHC Task 40 / ECBCS Annex 52 “Towards Net Zero Energy Solar Buildings”, attempts to develop a common understanding and to set up the basis for an international definition framework of Net Zero Energy Buildings (Net ZEBs). The understanding of such buildings...... parameters used in the calculations are discussed and the various renewable supply options considered in the methodologies are summarised graphically. Thus, the paper helps to understand different existing approaches to calculate energy balance in Net ZEBs, highlights the importance of variables selection...

  8. PhysioNet

    Data.gov (United States)

    U.S. Department of Health & Human Services — The PhysioNet Resource is intended to stimulate current research and new investigations in the study of complex biomedical and physiologic signals. It offers free...

  9. NetSig

    DEFF Research Database (Denmark)

    Horn, Heiko; Lawrence, Michael S; Chouinard, Candace R

    2018-01-01

    Methods that integrate molecular network information and tumor genome data could complement gene-based statistical tests to identify likely new cancer genes; but such approaches are challenging to validate at scale, and their predictive value remains unclear. We developed a robust statistic (Net......Sig) that integrates protein interaction networks with data from 4,742 tumor exomes. NetSig can accurately classify known driver genes in 60% of tested tumor types and predicts 62 new driver candidates. Using a quantitative experimental framework to determine in vivo tumorigenic potential in mice, we found that Net......Sig candidates induce tumors at rates that are comparable to those of known oncogenes and are ten-fold higher than those of random genes. By reanalyzing nine tumor-inducing NetSig candidates in 242 patients with oncogene-negative lung adenocarcinomas, we find that two (AKT2 and TFDP2) are significantly amplified...

  10. TideNet

    Science.gov (United States)

    2015-10-30

    query tide data sources in a desired geographic region of USA and its territories (Figure 1). Users can select a tide data source through the Google Map ...select data sources according to the desired geographic region. It uses the Google Map interface to display data from different sources. Recent...Coastal Inlets Research Program TideNet The TideNet is a web-based Graphical User Interface (GUI) that provides users with GIS mapping tools to

  11. Interaction Nets in Russian

    OpenAIRE

    Salikhmetov, Anton

    2013-01-01

    Draft translation to Russian of Chapter 7, Interaction-Based Models of Computation, from Models of Computation: An Introduction to Computability Theory by Maribel Fernandez. "In this chapter, we study interaction nets, a model of computation that can be seen as a representative of a class of models based on the notion of 'computation as interaction'. Interaction nets are a graphical model of computation devised by Yves Lafont in 1990 as a generalisation of the proof structures of linear logic...

  12. Programming NET 35

    CERN Document Server

    Liberty, Jesse

    2009-01-01

    Bestselling author Jesse Liberty and industry expert Alex Horovitz uncover the common threads that unite the .NET 3.5 technologies, so you can benefit from the best practices and architectural patterns baked into the new Microsoft frameworks. The book offers a Grand Tour" of .NET 3.5 that describes how the principal technologies can be used together, with Ajax, to build modern n-tier and service-oriented applications. "

  13. Neural network signal understanding for instrumentation

    DEFF Research Database (Denmark)

    Pau, L. F.; Johansen, F. S.

    1990-01-01

    A report is presented on the use of neural signal interpretation theory and techniques for the purpose of classifying the shapes of a set of instrumentation signals, in order to calibrate devices, diagnose anomalies, generate tuning/settings, and interpret the measurement results. Neural signal...... understanding research is surveyed, and the selected implementation and its performance in terms of correct classification rates and robustness to noise are described. Formal results on neural net training time and sensitivity to weights are given. A theory for neural control using functional link nets is given......, and an explanation facility designed to help neural signal understanding is described. The results are compared to those obtained with a knowledge-based signal interpretation system using the same instrument and data...

  14. La plataforma .NET

    OpenAIRE

    Fornas Estrada, Miquel

    2008-01-01

    L'aparició de la plataforma .NET Framework ha suposat un canvi molt important en la forma de crear i distribuir aplicacions, degut a que incorpora una sèrie d'innovacions tècniques i productives que simplifiquen molt les tasques necessàries per desenvolupar un projecte. La aparición de la plataforma. NET Framework ha supuesto un cambio muy importante en la forma de crear y distribuir aplicaciones, debido a que incorpora una serie de innovaciones técnicas y productivas que simplifican mucho...

  15. Biological Petri Nets

    CERN Document Server

    Wingender, E

    2011-01-01

    It was suggested some years ago that Petri nets might be well suited to modeling metabolic networks, overcoming some of the limitations encountered by the use of systems employing ODEs (ordinary differential equations). Much work has been done since then which confirms this and demonstrates the usefulness of this concept for systems biology. Petri net technology is not only intuitively understood by scientists trained in the life sciences, it also has a robust mathematical foundation and provides the required degree of flexibility. As a result it appears to be a very promising approach to mode

  16. Petri Nets-Applications

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 9. Petri Nets - Applications. Y Narahari. General Article Volume 4 Issue 9 September 1999 pp 44-52. Fulltext. Click here to view fulltext PDF. Permanent link: http://www.ias.ac.in/article/fulltext/reso/004/09/0044-0052. Author Affiliations. Y Narahari ...

  17. Safety nets or straitjackets?

    DEFF Research Database (Denmark)

    Ilsøe, Anna

    2012-01-01

    Does regulation of working hours at national and sector level impose straitjackets, or offer safety nets to employees seeking working time flexibility? This article compares legislation and collective agreements in the metal industries of Denmark, Germany and the USA. The industry has historically...

  18. Coloured Petri Nets

    CERN Document Server

    Jensen, Kurt

    2009-01-01

    Coloured Petri Nets (CPN) is a graphical language for modelling and validating concurrent and distributed systems, and other systems in which concurrency plays a major role. This book introduces the constructs of the CPN modelling language and presents the related analysis methods. It provides a comprehensive road map for the practical use of CPN.

  19. Boom Booom Net Radio

    DEFF Research Database (Denmark)

    Grimshaw, Mark Nicholas; Yong, Louisa; Dobie, Ian

    1999-01-01

    of an existing Internet radio station; Boom Booom Net Radio. Whilst necessity dictates some use of technology-related terminology, wherever possible we have endeavoured to keep such jargon to a minimum and to either explain it in the text or to provide further explanation in the appended glossary....

  20. Game Theory .net.

    Science.gov (United States)

    Shor, Mikhael

    2003-01-01

    States making game theory relevant and accessible to students is challenging. Describes the primary goal of GameTheory.net is to provide interactive teaching tools. Indicates the site strives to unite educators from economics, political and computer science, and ecology by providing a repository of lecture notes and tests for courses using…

  1. Coloured Petri Nets

    DEFF Research Database (Denmark)

    Jensen, Kurt; Kristensen, Lars Michael

    Coloured Petri Nets (CPN) is a graphical language for modelling and validating concurrent and distributed systems, and other systems in which concurrency plays a major role. The development of such systems is particularly challenging because of inherent intricacies like possible nondeterminism...

  2. Food Safety Nets:

    OpenAIRE

    Haggblade, Steven; Diallo, Boubacar; Staatz, John; Theriault, Veronique; Traoré, Abdramane

    2013-01-01

    Food and social safety nets have a history as long as human civilization. In hunter gatherer societies, food sharing is pervasive. Group members who prove unlucky in the short run, hunting or foraging, receive food from other households in anticipation of reciprocal consideration at a later time (Smith 1988). With the emergence of the first large sedentary civilizations in the Middle East, administrative systems developed specifically around food storage and distribution. The ancient Egyptian...

  3. Net technical assessment

    OpenAIRE

    Wegmann, David G.

    1989-01-01

    Approved for public release; distribution is unlimited. The present and near term military balance of power between the U.S. and the Soviet Union can be expressed in a variety of net assessments. One can examine the strategic nuclear balance, the conventional balance in Europe, the maritime balance, and many others. Such assessments are essential not only for policy making but for arms control purposes and future force structure planning. However, to project the future military balance, on...

  4. Using WordNet for Building WordNets

    CERN Document Server

    Farreres, X; Farreres, Xavier; Rodriguez, Horacio; Rigau, German

    1998-01-01

    This paper summarises a set of methodologies and techniques for the fast construction of multilingual WordNets. The English WordNet is used in this approach as a backbone for Catalan and Spanish WordNets and as a lexical knowledge resource for several subtasks.

  5. Universal approximation in p-mean by neural networks

    NARCIS (Netherlands)

    Burton, R.M; Dehling, H.G

    A feedforward neural net with d input neurons and with a single hidden layer of n neurons is given by [GRAPHICS] where a(j), theta(j), w(ji) is an element of R. In this paper we study the approximation of arbitrary functions f: R-d --> R by a neural net in an L-p(mu) norm for some finite measure mu

  6. Proof nets for lingusitic analysis

    NARCIS (Netherlands)

    Moot, R.C.A.

    2002-01-01

    This book investigates the possible linguistic applications of proof nets, redundancy free representations of proofs, which were introduced by Girard for linear logic. We will adapt the notion of proof net to allow the formulation of a proof net calculus which is soundand complete for the

  7. Teaching Tennis for Net Success.

    Science.gov (United States)

    Young, Bryce

    1989-01-01

    A program for teaching tennis to beginners, NET (Net Easy Teaching) is described. The program addresses three common needs shared by tennis students: active involvement in hitting the ball, clearing the net, and positive reinforcement. A sample lesson plan is included. (IAH)

  8. Net4Care Ecosystem Website

    DEFF Research Database (Denmark)

    Christensen, Henrik Bærbak; Hansen, Klaus Marius; Rasmussen, Morten

    2012-01-01

    is a tele-monitoring scenario in which Net4Care clients are deployed in a gateway in private homes. Medical devices then connect to these gateways and transmit their observations to a Net4Care server. In turn the Net4Care server creates valid clinical HL7 documents, stores them in a national XDS repository...

  9. Master Robotic Net

    Directory of Open Access Journals (Sweden)

    Vladimir Lipunov

    2010-01-01

    Full Text Available The main goal of the MASTER-Net project is to produce a unique fast sky survey with all sky observed over a single night down to a limiting magnitude of 19-20. Such a survey will make it possible to address a number of fundamental problems: search for dark energy via the discovery and photometry of supernovae (including SNIa, search for exoplanets, microlensing effects, discovery of minor bodies in the Solar System, and space-junk monitoring. All MASTER telescopes can be guided by alerts, and we plan to observe prompt optical emission from gamma-ray bursts synchronously in several filters and in several polarization planes.

  10. Art/Net/Work

    DEFF Research Database (Denmark)

    Andersen, Christian Ulrik; Lindstrøm, Hanne

    2006-01-01

    The seminar Art|Net|Work deals with two important changes in our culture. On one side, the network has become essential in the latest technological development. The Internet has entered a new phase, Web 2.0, including the occurrence of as ‘Wiki’s’, ‘Peer-2-Peer’ distribution, user controlled...... the praxis of the artist. We see different kinds of interventions and activism (including ‘hacktivism’) using the network as a way of questioning the invisible rules that govern public and semi-public spaces. Who ‘owns’ them? What kind of social relationships do they generate? On what principle...

  11. Helminth.net: expansions to Nematode.net and an introduction to Trematode.net

    Science.gov (United States)

    Martin, John; Rosa, Bruce A.; Ozersky, Philip; Hallsworth-Pepin, Kymberlie; Zhang, Xu; Bhonagiri-Palsikar, Veena; Tyagi, Rahul; Wang, Qi; Choi, Young-Jun; Gao, Xin; McNulty, Samantha N.; Brindley, Paul J.; Mitreva, Makedonka

    2015-01-01

    Helminth.net (http://www.helminth.net) is the new moniker for a collection of databases: Nematode.net and Trematode.net. Within this collection we provide services and resources for parasitic roundworms (nematodes) and flatworms (trematodes), collectively known as helminths. For over a decade we have provided resources for studying nematodes via our veteran site Nematode.net (http://nematode.net). In this article, (i) we provide an update on the expansions of Nematode.net that hosts omics data from 84 species and provides advanced search tools to the broad scientific community so that data can be mined in a useful and user-friendly manner and (ii) we introduce Trematode.net, a site dedicated to the dissemination of data from flukes, flatworm parasites of the class Trematoda, phylum Platyhelminthes. Trematode.net is an independent component of Helminth.net and currently hosts data from 16 species, with information ranging from genomic, functional genomic data, enzymatic pathway utilization to microbiome changes associated with helminth infections. The databases’ interface, with a sophisticated query engine as a backbone, is intended to allow users to search for multi-factorial combinations of species’ omics properties. This report describes updates to Nematode.net since its last description in NAR, 2012, and also introduces and presents its new sibling site, Trematode.net. PMID:25392426

  12. NETS FOR PEACH PROTECTED CULTIVATION

    Directory of Open Access Journals (Sweden)

    Evelia Schettini

    2012-06-01

    Full Text Available The aim of this paper was to investigate the radiometric properties of coloured nets used to protect a peach cultivation. The modifications of the solar spectral distribution, mainly in the R and FR wavelength band, influence plant photomorphogenesis by means of the phytochrome and cryptochrome. The phytochrome response is characterized in terms of radiation rate in the red wavelengths (R, 600-700 nm to that in the farred radiation (FR, 700-800 nm, i.e. the R/FR ratio. The effects of the blue radiation (B, 400-500 nm is investigated by the ratio between the blue radiation and the far-red radiation, i.e. the B/FR ratio. A BLUE net, a RED net, a YELLOW net, a PEARL net, a GREY net and a NEUTRAL net were tested in Bari (Italy, latitude 41° 05’ N. Peach trees were located in pots inside the greenhouses and in open field. The growth of the trees cultivated in open field was lower in comparison to the growth of the trees grown under the nets. The RED, PEARL, YELLOW and GREY nets increased the growth of the trees more than the other nets. The nets positively influenced the fruit characteristics, such as fruit weight and flesh firmness.

  13. NetPhosBac - A predictor for Ser/Thr phosphorylation sites in bacterial proteins

    DEFF Research Database (Denmark)

    Miller, Martin Lee; Soufi, Boumediene; Jers, Carsten

    2009-01-01

    predictors on bacterial systems. We used these large bacterial datasets and neural network algorithms to create the first bacteria-specific protein phosphorylation predictor: NetPhosBac. With respect to predicting bacterial phosphorylation sites, NetPhosBac significantly outperformed all benchmark predictors....... Moreover, NetPhosBac predictions of phosphorylation sites in E. coli proteins were experimentally verified on protein and site-specific levels. In conclusion, NetPhosBac clearly illustrates the advantage of taxa-specific predictors and we hope it will provide a useful asset to the microbiological community....

  14. 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.

  15. The equivalency between logic Petri workflow nets and workflow nets.

    Science.gov (United States)

    Wang, Jing; Yu, ShuXia; Du, YuYue

    2015-01-01

    Logic Petri nets (LPNs) can describe and analyze batch processing functions and passing value indeterminacy in cooperative systems. Logic Petri workflow nets (LPWNs) are proposed based on LPNs in this paper. Process mining is regarded as an important bridge between modeling and analysis of data mining and business process. Workflow nets (WF-nets) are the extension to Petri nets (PNs), and have successfully been used to process mining. Some shortcomings cannot be avoided in process mining, such as duplicate tasks, invisible tasks, and the noise of logs. The online shop in electronic commerce in this paper is modeled to prove the equivalence between LPWNs and WF-nets, and advantages of LPWNs are presented.

  16. Accelerated training for accurate neural net based load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Borsje, H.J.; Ling, B. [Stone and Webster Advanced Systems Development Services, Inc., Boston, MA (United States)

    1995-10-01

    A fast, accurate, robust and reliable load forecast method was developed, tested and demonstrated. The achieved prediction accuracy, based on a practical input parameters, matches or exceeds that of currently used methods. The time required to train the system is orders of magnitude shorter than other methods. This gives utility personnel the tools to refine local forecasts by quickly evaluating the effect of user selectable parameters. The conventional back propagation method can accurately predict the adaptive one-hour ahead forecast with reasonable learning requirements.

  17. Intelligent control aspects of fuzzy logic and neural nets

    CERN Document Server

    Harris, C J; Brown, M

    1993-01-01

    With increasing demands for high precision autonomous control over wide operating envelopes, conventional control engineering approaches are unable to adequately deal with system complexity, nonlinearities, spatial and temporal parameter variations, and with uncertainty. Intelligent Control or self-organising/learning control is a new emerging discipline that is designed to deal with problems. Rather than being model based, it is experiential based. Intelligent Control is the amalgam of the disciplines of Artificial Intelligence, Systems Theory and Operations Research. It uses most recent expe

  18. Coloured Petri Nets

    DEFF Research Database (Denmark)

    Jensen, Kurt; Kristensen, Lars Michael

    studies that illustrate the practical use of CPN modelling and validation for design, specification, simulation, verification and implementation in various application domains. Their presentation primarily aims at readers interested in the practical use of CPN. Thus all concepts and constructs are first......Coloured Petri Nets (CPN) is a graphical language for modelling and validating concurrent and distributed systems, and other systems in which concurrency plays a major role. The development of such systems is particularly challenging because of inherent intricacies like possible nondeterminism...... and the immense number of possible execution sequences. In this textbook, Jensen and Kristensen introduce the constructs of the CPN modelling language and present the related analysis methods in detail. They also provide a comprehensive road map for the practical use of CPN by showcasing selected industrial case...

  19. DARPA Neural Network Study: October 1987 - February 1988

    Science.gov (United States)

    1989-03-22

    8217Neural Net’ Models Allen Waxman, Boston University 10-20-1987: Mobile Robots vs. Neural Navigators 01-19-1988: Motion Computation In Vision 63...34Weight." Neurodynamics The study of the generation and propagation of synchronized neural activity in biological systems. 70 Neuron The nerve cells in...Malsburg, "Frank Rosenblatt: Principles of neurodynamics : Perceptrons and the theory of brain mechanisms," in Brain Theory, (G. Palm and A. Aertsen, eds

  20. WATER DEMAND PREDICTION USING ARTIFICIAL NEURAL ...

    African Journals Online (AJOL)

    This paper presents Hourly water demand prediction at the demand nodes of a water distribution network using NeuNet Pro 2.3 neural network software and the monitoring and control of water distribution using supervisory control. The case study is the Laminga Water Treatment Plant and its water distribution network, Jos.

  1. Towards semen quality assessment using neural networks

    DEFF Research Database (Denmark)

    Linneberg, Christian; Salamon, P.; Svarer, C.

    1994-01-01

    The paper presents the methodology and results from a neural net based classification of human sperm head morphology. The methodology uses a preprocessing scheme in which invariant Fourier descriptors are lumped into “energy” bands. The resulting networks are pruned using optimal brain damage...

  2. Cognitive And Neural Sciences Division 1992 Programs

    Science.gov (United States)

    1992-08-01

    Neuronal Micronets as Nodal Elements PRINCIPAL INVESTIGATOR: Thomas H. Brown Yale University Department of Psychology (203) 432-7008 R&T PROJECT CODE...of neural nets, and to develop a micronet architecture which captures the computations in neurons. Approach: Simulations will be conducted of the

  3. 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.

  4. NetOglyc: prediction of mucin type O-glycosylation sites based on sequence context and surface accessibility

    DEFF Research Database (Denmark)

    Hansen, Jan Erik; Lund, Ole; Tolstrup, Niels

    1998-01-01

    . A jury of artifical neural networks was trained to recognize the sequence context and surface accessibility of 299 known and verified mucin type O-glycosylation sites extracted from O-GLYCBASE. The cross-validated NetOglyc network system correctly found 83% of the glycosylated and 90% of the non...... on the amino acid sequence. The server addresses are http://www.cbs.dtu.dk/services/NetOGlyc/ and netOglyc@cbs.dtu.dk...

  5. Linear Logic on Petri Nets

    DEFF Research Database (Denmark)

    Engberg, Uffe Henrik; Winskel, Glynn

    This article shows how individual Petri nets form models of Girard's intuitionistic linear logic. It explores questions of expressiveness and completeness of linear logic with respect to this interpretation. An aim is to use Petri nets to give an understanding of linear logic and give some apprai...

  6. Reference Guide Microsoft.NET

    NARCIS (Netherlands)

    Zee M van der; Verspaij GJ; Rosbergen S; IMP; NMD

    2003-01-01

    Developers, administrators and managers can get more understanding of the .NET technology with this report. They can also make better choices how to use this technology. The report describes the results and conclusions of a study of the usability for the RIVM of this new generation .NET development

  7. Net neutrality and audiovisual services

    NARCIS (Netherlands)

    van Eijk, N.; Nikoltchev, S.

    2011-01-01

    Net neutrality is high on the European agenda. New regulations for the communication sector provide a legal framework for net neutrality and need to be implemented on both a European and a national level. The key element is not just about blocking or slowing down traffic across communication

  8. A Small Universal Petri Net

    Directory of Open Access Journals (Sweden)

    Dmitry A. Zaitsev

    2013-09-01

    Full Text Available A universal deterministic inhibitor Petri net with 14 places, 29 transitions and 138 arcs was constructed via simulation of Neary and Woods' weakly universal Turing machine with 2 states and 4 symbols; the total time complexity is exponential in the running time of their weak machine. To simulate the blank words of the weakly universal Turing machine, a couple of dedicated transitions insert their codes when reaching edges of the working zone. To complete a chain of a given Petri net encoding to be executed by the universal Petri net, a translation of a bi-tag system into a Turing machine was constructed. The constructed Petri net is universal in the standard sense; a weaker form of universality for Petri nets was not introduced in this work.

  9. Fuzzy Petri nets to model vision system decisions within a flexible manufacturing system

    Science.gov (United States)

    Hanna, Moheb M.; Buck, A. A.; Smith, R.

    1994-10-01

    The paper presents a Petri net approach to modelling, monitoring and control of the behavior of an FMS cell. The FMS cell described comprises a pick and place robot, vision system, CNC-milling machine and 3 conveyors. The work illustrates how the block diagrams in a hierarchical structure can be used to describe events at different levels of abstraction. It focuses on Fuzzy Petri nets (Fuzzy logic with Petri nets) including an artificial neural network (Fuzzy Neural Petri nets) to model and control vision system decisions and robot sequences within an FMS cell. This methodology can be used as a graphical modelling tool to monitor and control the imprecise, vague and uncertain situations, and determine the quality of the output product of an FMS cell.

  10. High-level Petri Nets

    DEFF Research Database (Denmark)

    High-level Petri nets are now widely used in both theoretical analysis and practical modelling of concurrent systems. The main reason for the success of this class of net models is that they make it possible to obtain much more succinct and manageable descriptions than can be obtained by means...... of low-level Petri nets - while, on the other hand, they still offer a wide range of analysis methods and tools. The step from low-level nets to high-level nets can be compared to the step from assembly languages to modern programming languages with an elaborated type concept. In low-level nets...... there is only one kind of token and this means that the state of a place is described by an integer (and in many cases even by a boolean). In high-level nets each token can carry a complex information/data - which, e.g., may describe the entire state of a process or a data base. Today most practical...

  11. LightNet: A Versatile, Standalone Matlab-based Environment for Deep Learning

    OpenAIRE

    Ye, Chengxi; Zhao, Chen; Yang, Yezhou; Fermuller, Cornelia; Aloimonos, Yiannis

    2016-01-01

    LightNet is a lightweight, versatile and purely Matlab-based deep learning framework. The idea underlying its design is to provide an easy-to-understand, easy-to-use and efficient computational platform for deep learning research. The implemented framework supports major deep learning architectures such as Multilayer Perceptron Networks (MLP), Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). The framework also supports both CPU and GPU computation, and the switch betwe...

  12. Automated Modeling of Microwave Structures by Enhanced Neural Networks

    Directory of Open Access Journals (Sweden)

    Z. Raida

    2006-12-01

    Full Text Available The paper describes the methodology of the automated creation of neural models of microwave structures. During the creation process, artificial neural networks are trained using the combination of the particle swarm optimization and the quasi-Newton method to avoid critical training problems of the conventional neural nets. In the paper, neural networks are used to approximate the behavior of a planar microwave filter (moment method, Zeland IE3D. In order to evaluate the efficiency of neural modeling, global optimizations are performed using numerical models and neural ones. Both approaches are compared from the viewpoint of CPU-time demands and the accuracy. Considering conclusions, methodological recommendations for including neural networks to the microwave design are formulated.

  13. Pro asynchronous programming with .NET

    CERN Document Server

    Blewett, Richard; Ltd, Rock Solid Knowledge

    2014-01-01

    Pro Asynchronous Programming with .NET teaches the essential skill of asynchronous programming in .NET. It answers critical questions in .NET application development, such as: how do I keep my program responding at all times to keep my users happy how do I make the most of the available hardware how can I improve performanceIn the modern world, users expect more and more from their applications and devices, and multi-core hardware has the potential to provide it. But it takes carefully crafted code to turn that potential into responsive, scalable applications.With Pro Asynchronous Programming

  14. Conformal Nets II: Conformal Blocks

    Science.gov (United States)

    Bartels, Arthur; Douglas, Christopher L.; Henriques, André

    2017-08-01

    Conformal nets provide a mathematical formalism for conformal field theory. Associated to a conformal net with finite index, we give a construction of the `bundle of conformal blocks', a representation of the mapping class groupoid of closed topological surfaces into the category of finite-dimensional projective Hilbert spaces. We also construct infinite-dimensional spaces of conformal blocks for topological surfaces with smooth boundary. We prove that the conformal blocks satisfy a factorization formula for gluing surfaces along circles, and an analogous formula for gluing surfaces along intervals. We use this interval factorization property to give a new proof of the modularity of the category of representations of a conformal net.

  15. Petri Net Tool Overview 1986

    DEFF Research Database (Denmark)

    Jensen, Kurt; Feldbrugge, Frits

    1987-01-01

    This paper provides an overview of the characteristics of all currently available net based tools. It is a compilation of information provided by tool authors or contact persons. A concise one page overview is provided as well....

  16. Understanding Net Zero Energy Buildings

    DEFF Research Database (Denmark)

    Salom, Jaume; Widén, Joakim; Candanedo, José

    2011-01-01

    Although several alternative definitions exist, a Net-Zero Energy Building (Net ZEB) can be succinctly described as a grid-connected building that generates as much energy as it uses over a year. The “net-zero” balance is attained by applying energy conservation and efficiency measures...... and by incorporating renewable energy systems. While based on annual balances, a complete description of a Net ZEB requires examining the system at smaller time-scales. This assessment should address: (a) the relationship between power generation and building loads and (b) the resulting interaction with the power grid....... This paper presents and categorizes quantitative indicators suitable to describe both aspects of the building’s performance. These indicators, named LMGI - Load Matching and Grid Interaction indicators, are easily quantifiable and could complement the output variables of existing building simulation tools...

  17. PolicyNet Publication System

    Data.gov (United States)

    Social Security Administration — The PolicyNet Publication System project will merge the Oracle-based Policy Repository (POMS) and the SQL-Server CAMP system (MSOM) into a new system with an Oracle...

  18. KM3NeT

    CERN Multimedia

    KM3NeT is a large scale next-generation neutrino telescope located in the deep waters of the Mediterranean Sea, optimized for the discovery of galactic neutrino sources emitting in the TeV energy region.

  19. Net Neutrality: Background and Issues

    National Research Council Canada - National Science Library

    Gilroy, Angele A

    2006-01-01

    .... The move to place restrictions on the owners of the networks that compose and provide access to the Internet, to ensure equal access and nondiscriminatory treatment, is referred to as "net neutrality...

  20. Petri Nets in Cryptographic Protocols

    DEFF Research Database (Denmark)

    Crazzolara, Federico; Winskel, Glynn

    2001-01-01

    A process language for security protocols is presented together with a semantics in terms of sets of events. The denotation of process is a set of events, and as each event specifies a set of pre and postconditions, this denotation can be viewed as a Petri net. By means of an example we illustrate...... how the Petri-net semantics can be used to prove security properties....

  1. The Economics of Net Neutrality

    OpenAIRE

    Hahn, Robert W.; Wallsten, Scott

    2006-01-01

    This essay examines the economics of "net neutrality" and broadband Internet access. We argue that mandating net neutrality would be likely to reduce economic welfare. Instead, the government should focus on creating competition in the broadband market by liberalizing more spectrum and reducing entry barriers created by certain local regulations. In cases where a broadband provider can exercise market power the government should use its antitrust enforcement authority to police anticompetitiv...

  2. Optical implementation of neural networks

    Science.gov (United States)

    Yu, Francis T. S.; Guo, Ruyan

    2002-12-01

    An adaptive optical neuro-computing (ONC) using inexpensive pocket size liquid crystal televisions (LCTVs) had been developed by the graduate students in the Electro-Optics Laboratory at The Pennsylvania State University. Although this neuro-computing has only 8×8=64 neurons, it can be easily extended to 16×20=320 neurons. The major advantages of this LCTV architecture as compared with other reported ONCs, are low cost and the flexibility to operate. To test the performance, several neural net models are used. These models are Interpattern Association, Hetero-association and unsupervised learning algorithms. The system design considerations and experimental demonstrations are also included.

  3. 26 CFR 1.904(f)-3 - Allocation of net operating losses and net capital losses.

    Science.gov (United States)

    2010-04-01

    ... 26 Internal Revenue 9 2010-04-01 2010-04-01 false Allocation of net operating losses and net....904(f)-3 Allocation of net operating losses and net capital losses. For rules relating to the allocation of net operating losses and net capital losses, see § 1.904(g)-3T. ...

  4. 29 CFR 4204.13 - Net income and net tangible assets tests.

    Science.gov (United States)

    2010-07-01

    ... 29 Labor 9 2010-07-01 2010-07-01 false Net income and net tangible assets tests. 4204.13 Section....13 Net income and net tangible assets tests. (a) General. The criteria under this section are that either— (1) Net income test. The purchaser's average net income after taxes for its three most recent...

  5. 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.

  6. Bio-inspired Artificial Intelligence: А Generalized Net Model of the Regularization Process in MLP

    Directory of Open Access Journals (Sweden)

    Stanimir Surchev

    2013-10-01

    Full Text Available Many objects and processes inspired by the nature have been recreated by the scientists. The inspiration to create a Multilayer Neural Network came from human brain as member of the group. It possesses complicated structure and it is difficult to recreate, because of the existence of too many processes that require different solving methods. The aim of the following paper is to describe one of the methods that improve learning process of Artificial Neural Network. The proposed generalized net method presents Regularization process in Multilayer Neural Network. The purpose of verification is to protect the neural network from overfitting. The regularization is commonly used in neural network training process. Many methods of verification are present, the subject of interest is the one known as Regularization. It contains function in order to set weights and biases with smaller values to protect from overfitting.

  7. Program Aids Simulation Of Neural Networks

    Science.gov (United States)

    Baffes, Paul T.

    1990-01-01

    Computer program NETS - Tool for Development and Evaluation of Neural Networks - provides simulation of neural-network algorithms plus software environment for development of such algorithms. Enables user to customize patterns of connections between layers of network, and provides features for saving weight values of network, providing for more precise control over learning process. Consists of translating problem into format using input/output pairs, designing network configuration for problem, and finally training network with input/output pairs until acceptable error reached. Written in C.

  8. A neural network simulation package in CLIPS

    Science.gov (United States)

    Bhatnagar, Himanshu; Krolak, Patrick D.; Mcgee, Brenda J.; Coleman, John

    1990-01-01

    The intrinsic similarity between the firing of a rule and the firing of a neuron has been captured in this research to provide a neural network development system within an existing production system (CLIPS). A very important by-product of this research has been the emergence of an integrated technique of using rule based systems in conjunction with the neural networks to solve complex problems. The systems provides a tool kit for an integrated use of the two techniques and is also extendible to accommodate other AI techniques like the semantic networks, connectionist networks, and even the petri nets. This integrated technique can be very useful in solving complex AI problems.

  9. The ImageNet Shuffle: Reorganized Pre-training for Video Event Detection

    NARCIS (Netherlands)

    Mettes, P.; Koelma, D.C.; Snoek, C.G.M.

    2016-01-01

    This paper strives for video event detection using a representation learned from deep convolutional neural networks. Different from the leading approaches, who all learn from the 1,000 classes defined in the ImageNet Large Scale Visual Recognition Challenge, we investigate how to leverage the

  10. Automatic slice identification in 3D medical images with a ConvNet regressor

    NARCIS (Netherlands)

    de Vos, Bob D.; Viergever, Max A.; de Jong, Pim A.; Išgum, Ivana

    2016-01-01

    Identification of anatomical regions of interest is a prerequisite in many medical image analysis tasks. We propose a method that automatically identifies a slice of interest (SOI) in 3D images with a convolutional neural network (ConvNet) regressor. In 150 chest CT scans two reference slices were

  11. Part 2: Prediktion, Simulering og Regulering med Neurale Netværk. Prediction, Simulation and Control using Neural Network

    DEFF Research Database (Denmark)

    Schiøler, Henrik

    til Del 1, idet de to rapporter kan opfattes som en enhed. Herefter introduceres de grundlæggende begreber inden for prediktion, samt for mål og integralteorien. Det beskrives, hvorledes neurale net kan fungere som ulinære prediktionsmodeller og den nødvendige teori for Multi Lags Perceptronen (MLP......) samt alternative strukturer baseret på Parzen Window estimationsmetoden, præsenteres med detaljerne af analysen henlagt til appendices. Herefter demonstreres ved en simpel test, hvorledes de forskellige nettyper fungerer i prediktionsanvendelser. Herefter er neurale net anvendt til simulering behandlet...... på tilsvarende måde, dog i en lidt forkortet udgave. Til sidst behandles, hvorledes de behandlede nettyper anvendes i en regulatorstruktur baseret på såkaldte Sliding mode control. Teorien for de neurale net er her den samme som for simulering. Det konkluderes at de alternative strukturer, baseret på...

  12. On the reliability of the nervous (Nv) nets

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V.; Frigo, J.R.; Moore, K.R.

    1998-12-31

    This paper investigates the reliability of a particular class of neural networks, the Nervous Nets (Nv). This is the class of nonsymmetric ring oscillator networks of inverters coupled through variable delays. They have been successfully applied to controlling walking robots, while many other applications will shortly be mentioned. The authors will then explain the robustness of Nv nets in the sense of their highly reliable functioning--which has been observed through many experiments. For doing that the authors will show that although the Nv net has an exponential number of periodic points, only a small (still exponential) part are stable, while all the others are saddle points. The ratio between the number of stable and periodic points quickly vanishes to zero as the number of nodes is increased, as opposed to classical finite state machines--where this ratio is relatively constant. These show that the Nv net will always converge quickly to a stable oscillatory state--a fact not true in general for finite state machines.

  13. TimeNET Optimization Environment

    Directory of Open Access Journals (Sweden)

    Christoph Bodenstein

    2015-12-01

    Full Text Available In this paper a novel tool for simulation-based optimization and design-space exploration of Stochastic Colored Petri nets (SCPN is introduced. The working title of this tool is TimeNET Optimization Environment (TOE. Targeted users of this tool are people modeling complex systems with SCPNs in TimeNET who want to find parameter sets that are optimal for a certain performance measure (fitness function. It allows users to create and simulate sets of SCPNs and to run different optimization algorithms based on parameter variation. The development of this tool was motivated by the need to automate and speed up tests of heuristic optimization algorithms to be applied for SCPN optimization. A result caching mechanism is used to avoid recalculations.

  14. Implementing NetScaler VPX

    CERN Document Server

    Sandbu, Marius

    2014-01-01

    An easy-to-follow guide with detailed step-by step-instructions on how to implement the different key components in NetScaler, with real-world examples and sample scenarios.If you are a Citrix or network administrator who needs to implement NetScaler in your virtual environment to gain an insight on its functionality, this book is ideal for you. A basic understanding of networking and familiarity with some of the different Citrix products such as XenApp or XenDesktop is a prerequisite.

  15. Net4Care PHMR Library

    DEFF Research Database (Denmark)

    2014-01-01

    The Net4Care PHMR library contains a) A GreenCDA approach for constructing a data object representing a PHMR document: SimpleClinicalDocument, and b) A Builder which can produce a XML document representing a valid Danish PHMR (following the MedCom profile) document from the SimpleClinicalDocument......The Net4Care PHMR library contains a) A GreenCDA approach for constructing a data object representing a PHMR document: SimpleClinicalDocument, and b) A Builder which can produce a XML document representing a valid Danish PHMR (following the MedCom profile) document from the Simple...

  16. Pro DLR in NET 4

    CERN Document Server

    Wu, Chaur

    2011-01-01

    Microsoft's Dynamic Language Runtime (DLR) is a platform for running dynamic languages such as Ruby and Python on an equal footing with compiled languages such as C#. Furthermore, the runtime is the foundation for many useful software design and architecture techniques you can apply as you develop your .NET applications. Pro DLR in .NET 4 introduces you to the DLR, showing how you can use it to write software that combines dynamic and static languages, letting you choose the right tool for the job. You will learn the core DLR components such as LINQ expressions, call sites, binders, and dynami

  17. Hierarchies in Coloured Petri Nets

    DEFF Research Database (Denmark)

    Huber, Peter; Jensen, Kurt; Shapiro, Robert M.

    1991-01-01

    The paper shows how to extend Coloured Petri Nets with a hierarchy concept. The paper proposes five different hierarchy constructs, which allow the analyst to structure large CP-nets as a set of interrelated subnets (called pages). The paper discusses the properties of the proposed hierarchy...... constructs, and it illustrates them by means of two examples. The hierarchy constructs can be used for theoretical considerations, but their main use is to describe and analyse large real-world systems. All of the hierarchy constructs are supported by the editing and analysis facilities in the CPN Palette...

  18. Neural Tube Defects

    Science.gov (United States)

    ... vitamin, before and during pregnancy prevents most neural tube defects. Neural tube defects are usually diagnosed before the infant is ... or imaging tests. There is no cure for neural tube defects. The nerve damage and loss of function ...

  19. 2D neural hardware versus 3D biological ones

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V.

    1998-12-31

    This paper will present important limitations of hardware neural nets as opposed to biological neural nets (i.e. the real ones). The author starts by discussing neural structures and their biological inspirations, while mentioning the simplifications leading to artificial neural nets. Going further, the focus will be on hardware constraints. The author will present recent results for three different alternatives of implementing neural networks: digital, threshold gate, and analog, while the area and the delay will be related to neurons' fan-in and weights' precision. Based on all of these, it will be shown why hardware implementations cannot cope with their biological inspiration with respect to their power of computation: the mapping onto silicon lacking the third dimension of biological nets. This translates into reduced fan-in, and leads to reduced precision. The main conclusion is that one is faced with the following alternatives: (1) try to cope with the limitations imposed by silicon, by speeding up the computation of the elementary silicon neurons; (2) investigate solutions which would allow one to use the third dimension, e.g. using optical interconnections.

  20. Characterization of NvLWamide-like neurons reveals stereotypy in Nematostella nerve net development.

    Science.gov (United States)

    Havrilak, Jamie A; Faltine-Gonzalez, Dylan; Wen, Yiling; Fodera, Daniella; Simpson, Ayanna C; Magie, Craig R; Layden, Michael J

    2017-11-15

    The organization of cnidarian nerve nets is traditionally described as diffuse with randomly arranged neurites that show minimal reproducibility between animals. However, most observations of nerve nets are conducted using cross-reactive antibodies that broadly label neurons, which potentially masks stereotyped patterns produced by individual neuronal subtypes. Additionally, many cnidarians species have overt structures such as a nerve ring, suggesting higher levels of organization and stereotypy exist, but mechanisms that generated that stereotypy are unknown. We previously demonstrated that NvLWamide-like is expressed in a small subset of the Nematostella nerve net and speculated that observing a few neurons within the developing nerve net would provide a better indication of potential stereotypy. Here we document NvLWamide-like expression more systematically. NvLWamide-like is initially expressed in the typical neurogenic salt and pepper pattern within the ectoderm at the gastrula stage, and expression expands to include endodermal salt and pepper expression at the planula larval stage. Expression persists in both ectoderm and endoderm in adults. We characterized our NvLWamide-like::mCherry transgenic reporter line to visualize neural architecture and found that NvLWamide-like is expressed in six neural subtypes identifiable by neural morphology and location. Upon completing development the numbers of neurons in each neural subtype are minimally variable between animals and the projection patterns of each subtype are consistent. Furthermore, between the juvenile polyp and adult stages the number of neurons for each subtype increases. We conclude that development of the Nematostella nerve net is stereotyped between individuals. Our data also imply that one aspect of generating adult cnidarian nervous systems is to modify the basic structural architecture generated in the juvenile by increasing neural number proportionally with size. Copyright © 2017 The Authors

  1. Application of a neural network for reflectance spectrum classification

    Science.gov (United States)

    Yang, Gefei; Gartley, Michael

    2017-05-01

    Traditional reflectance spectrum classification algorithms are based on comparing spectrum across the electromagnetic spectrum anywhere from the ultra-violet to the thermal infrared regions. These methods analyze reflectance on a pixel by pixel basis. Inspired by high performance that Convolution Neural Networks (CNN) have demonstrated in image classification, we applied a neural network to analyze directional reflectance pattern images. By using the bidirectional reflectance distribution function (BRDF) data, we can reformulate the 4-dimensional into 2 dimensions, namely incident direction × reflected direction × channels. Meanwhile, RIT's micro-DIRSIG model is utilized to simulate additional training samples for improving the robustness of the neural networks training. Unlike traditional classification by using hand-designed feature extraction with a trainable classifier, neural networks create several layers to learn a feature hierarchy from pixels to classifier and all layers are trained jointly. Hence, the our approach of utilizing the angular features are different to traditional methods utilizing spatial features. Although training processing typically has a large computational cost, simple classifiers work well when subsequently using neural network generated features. Currently, most popular neural networks such as VGG, GoogLeNet and AlexNet are trained based on RGB spatial image data. Our approach aims to build a directional reflectance spectrum based neural network to help us to understand from another perspective. At the end of this paper, we compare the difference among several classifiers and analyze the trade-off among neural networks parameters.

  2. Statistical Physics, Neural Networks, Brain Studies

    OpenAIRE

    TOULOUSE, Gérard

    2014-01-01

    An overview of some aspects of a vast domain, located at the crossroads of physics, biology and computer science is presented: 1) During the last fifteen years, physicists advancing along various pathways have come into contact with biology (computational neurosciences) and engineering (formal neural nets). 2) This move may actually be viewed as one component in a larger picture. A prominent trend of recent years, observable over many countries, has been the establishment of interdis...

  3. D.NET case study

    International Development Research Centre (IDRC) Digital Library (Canada)

    lremy

    developing products, marketing tools and building capacity of the grass root telecentre workers. D.Net recognized that it had several ideas worth developing into small interventions that would make big differences, but resource constraints were a barrier for scaling-up these initiatives. More demands, limited resources.

  4. Surgery for GEP-NETs

    DEFF Research Database (Denmark)

    Knigge, Ulrich; Hansen, Carsten Palnæs

    2012-01-01

    Surgery is the only treatment that may cure the patient with gastroentero-pancreatic (GEP) neuroendocrine tumours (NET) and neuroendocrine carcinomas (NEC) and should always be considered as first line treatment if R0/R1 resection can be achieved. The surgical and interventional procedures for GEP...

  5. Net Neutrality in the Netherlands

    NARCIS (Netherlands)

    van Eijk, N.

    2014-01-01

    The Netherlands is among the first countries that have put specific net neutrality standards in place. The decision to implement specific regulation was influenced by at least three factors. The first was the prevailing social and academic debate, partly due to developments in the United States. The

  6. Complexity Metrics for Workflow Nets

    DEFF Research Database (Denmark)

    Lassen, Kristian Bisgaard; van der Aalst, Wil M.P.

    2009-01-01

    Process modeling languages such as EPCs, BPMN, flow charts, UML activity diagrams, Petri nets, etc.\\ are used to model business processes and to configure process-aware information systems. It is known that users have problems understanding these diagrams. In fact, even process engineers and system...

  7. Caught in the Net: Perineuronal Nets and Addiction

    Directory of Open Access Journals (Sweden)

    Megan Slaker

    2016-01-01

    Full Text Available Exposure to drugs of abuse induces plasticity in the brain and creates persistent drug-related memories. These changes in plasticity and persistent drug memories are believed to produce aberrant motivation and reinforcement contributing to addiction. Most studies have explored the effect drugs of abuse have on pre- and postsynaptic cells and astrocytes; however, more recently, attention has shifted to explore the effect these drugs have on the extracellular matrix (ECM. Within the ECM are unique structures arranged in a net-like manner, surrounding a subset of neurons called perineuronal nets (PNNs. This review focuses on drug-induced changes in PNNs, the molecules that regulate PNNs, and the expression of PNNs within brain circuitry mediating motivation, reward, and reinforcement as it pertains to addiction.

  8. Army Net Zero Prove Out. Army Net Zero Training Report

    Science.gov (United States)

    2014-11-20

    sensors were strategically placed throughout the installation by magnetically attaching them to water main valve stems. The sensors check sound...Recycle Wrap  Substitutes for Packaging Materials  Re-Use of Textiles and Linens  Setting Printers to Double-Sided Printing Net Zero Waste...can effectively achieve source reduction. Clean and Re-Use Shop Rags - Shop rags represent a large textile waste stream at many installations. As a

  9. Army Net Zero Prove Out. Net Zero Waste Best Practices

    Science.gov (United States)

    2014-11-20

    Anaerobic Digesters – Although anaerobic digestion is not a new technology and has been used on a large-scale basis in wastewater treatment , the...technology and has been used on a large-scale basis in wastewater treatment , the use of the technology should be demonstrated with other...approaches can be used for cardboard and cellulose -based packaging materials. This approach is in line with the Net Zero Waste hierarchy in terms of

  10. End-to-end unsupervised deformable image registration with a convolutional neural network

    NARCIS (Netherlands)

    de Vos, Bob D.; Berendsen, Floris; Viergever, Max A.; Staring, Marius; Išgum, Ivana

    2017-01-01

    In this work we propose a deep learning network for deformable image registration (DIRNet). The DIRNet consists of a convolutional neural network (ConvNet) regressor, a spatial transformer, and a resampler. The ConvNet analyzes a pair of fixed and moving images and outputs parameters for the spatial

  11. Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

    DEFF Research Database (Denmark)

    Hjerrild, Majbrit; Stensballe, Allan; Rasmussen, Thomas E

    2011-01-01

    Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein...

  12. [Neural repair].

    Science.gov (United States)

    Kitada, Masaaki; Dezawa, Mari

    2008-05-01

    Recent progress of stem cell biology gives us the hope for neural repair. We have established methods to specifically induce functional Schwann cells and neurons from bone marrow stromal cells (MSCs). The effectiveness of these induced cells was evaluated by grafting them either into peripheral nerve injury, spinal cord injury, or Parkinson' s disease animal models. MSCs-derived Schwann cells supported axonal regeneration and re-constructed myelin to facilitate the functional recovery in peripheral and spinal cord injury. MSCs-derived dopaminergic neurons integrated into host striatum and contributed to behavioral repair. In this review, we introduce the differentiation potential of MSCs and finally discuss about their benefits and drawbacks of these induction systems for cell-based therapy in neuro-traumatic and neuro-degenerative diseases.

  13. The use of artificial neural networks in experimental data acquisition and aerodynamic design

    Science.gov (United States)

    Meade, Andrew J., Jr.

    1991-01-01

    It is proposed that an artificial neural network be used to construct an intelligent data acquisition system. The artificial neural networks (ANN) model has a potential for replacing traditional procedures as well as for use in computational fluid dynamics validation. Potential advantages of the ANN model are listed. As a proof of concept, the author modeled a NACA 0012 airfoil at specific conditions, using the neural network simulator NETS, developed by James Baffes of the NASA Johnson Space Center. The neural network predictions were compared to the actual data. It is concluded that artificial neural networks can provide an elegant and valuable class of mathematical tools for data analysis.

  14. Forecasting macroeconomic variables using neural network models and three automated model selection techniques

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl; Teräsvirta, Timo

    2016-01-01

    When forecasting with neural network models one faces several problems, all of which influence the accuracy of the forecasts. First, neural networks are often hard to estimate due to their highly nonlinear structure. To alleviate the problem, White (2006) presented a solution (QuickNet...

  15. HANPP Collection: Human Appropriation of Net Primary Productivity as a Percentage of Net Primary Productivity

    Data.gov (United States)

    National Aeronautics and Space Administration — The Human Appropriation of Net Primary Productivity (HANPP) as a Percentage of Net Primary Productivity (NPP) portion of the Human Appropriation of Net Primary...

  16. Hydrodynamic characteristics of plane netting used for aquaculture net cages in uniform current

    National Research Council Canada - National Science Library

    DONG, SHUCHUANG; HU, FUXIANG; KUMAZAWA, TAISEI; SIODE, DAISUKE; TOKAI, TADASHI

    2016-01-01

      The hydrodynamic characteristics of polyethylene (PE) netting and chain link wire netting with different types of twine diameter and mesh size for aquaculture net cages were examined by experiments in a flume tank...

  17. Neural Networks in Antennas and Microwaves: A Practical Approach

    Directory of Open Access Journals (Sweden)

    Z. Raida

    2001-12-01

    Full Text Available Neural networks are electronic systems which can be trained toremember behavior of a modeled structure in given operational points,and which can be used to approximate behavior of the structure out ofthe training points. These approximation abilities of neural nets aredemonstrated on modeling a frequency-selective surface, a microstriptransmission line and a microstrip dipole. Attention is turned to theaccuracy and to the efficiency of neural models. The association ofneural models and genetic algorithms, which can provide a global designtool, is discussed.

  18. Isolated unit tests in .Net

    OpenAIRE

    Haukilehto, Tero

    2013-01-01

    In this thesis isolation in unit testing is studied to get a precise picture of the isolation frameworks available for .Net environment. At the beginning testing is discussed in theory with the benefits and the problems it may have been linked with. The theory includes software development in general in connection with testing. Theory of isolation is also described before the actual isolation frameworks are represented. Common frameworks are described in more detail and comparable informa...

  19. Flow Pattern Identification of Horizontal Two-Phase Refrigerant Flow Using Neural Networks

    Science.gov (United States)

    2015-12-31

    making classification difficult. Consequently, Table 5 shows neural net - work classification results for nine flow patterns. The number of runs...AFRL-RQ-WP-TP-2016-0079 FLOW PATTERN IDENTIFICATION OF HORIZONTAL TWO-PHASE REFRIGERANT FLOW USING NEURAL NETWORKS (POSTPRINT) Abdeel J... NEURAL NETWORKS (POSTPRINT) 5a. CONTRACT NUMBER In-house 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62203F 6. AUTHOR(S) Abdeel J. Roman and

  20. Design and regularization of neural networks: the optimal use of a validation set

    DEFF Research Database (Denmark)

    Larsen, Jan; Hansen, Lars Kai; Svarer, Claus

    1996-01-01

    We derive novel algorithms for estimation of regularization parameters and for optimization of neural net architectures based on a validation set. Regularisation parameters are estimated using an iterative gradient descent scheme. Architecture optimization is performed by approximative...... combinatorial search among the relevant subsets of an initial neural network architecture by employing a validation set based optimal brain damage/surgeon (OBD/OBS) or a mean field combinatorial optimization approach. Numerical results with linear models and feed-forward neural networks demonstrate...

  1. Event hierarchies in DanNet

    DEFF Research Database (Denmark)

    Pedersen, Bolette Sandford; Nimb, Sanni

    2008-01-01

    Artiklen omhandler udarbejdelsen af et verbumshierarki i det leksikalsk-semantiske ordnet, DanNet.......Artiklen omhandler udarbejdelsen af et verbumshierarki i det leksikalsk-semantiske ordnet, DanNet....

  2. The Uniframe .Net Web Service Discovery Service

    National Research Council Canada - National Science Library

    Berbeco, Robert W

    2003-01-01

    Microsoft .NET allows the creation of distributed systems in a seamless manner Within NET small, discrete applications, referred to as Web services, are utilized to connect to each other or larger applications...

  3. Long Term RadNet Quality Data

    Data.gov (United States)

    U.S. Environmental Protection Agency — This RadNet Quality Data Asset includes all data since initiation and when ERAMS was expanded to become RadNet, name changed to reflect new mission. This includes...

  4. PsychoNet: a psycholinguistc commonsense ontology

    OpenAIRE

    Mohtasseb, Haytham; Ahmed, Amr

    2010-01-01

    Ontologies have been widely accepted as the most advanced knowledge representation model. This paper introduces PsychoNet, a new knowledgebase that forms the link between psycholinguistic taxonomy, existing in LIWC, and its semantic textual representation in the form of commonsense semantic ontology, represented by ConceptNet. The integration of LIWC and ConceptNet and the added functionalities facilitate employing ConceptNet in psycholinguistic studies. Furthermore, it simplifies utilization...

  5. Neural Network and Letter Recognition.

    Science.gov (United States)

    Lee, Hue Yeon

    Neural net architectures and learning algorithms that recognize hand written 36 alphanumeric characters are studied. The thin line input patterns written in 32 x 32 binary array are used. The system is comprised of two major components, viz. a preprocessing unit and a Recognition unit. The preprocessing unit in turn consists of three layers of neurons; the U-layer, the V-layer, and the C -layer. The functions of the U-layer is to extract local features by template matching. The correlation between the detected local features are considered. Through correlating neurons in a plane with their neighboring neurons, the V-layer would thicken the on-cells or lines that are groups of on-cells of the previous layer. These two correlations would yield some deformation tolerance and some of the rotational tolerance of the system. The C-layer then compresses data through the 'Gabor' transform. Pattern dependent choice of center and wavelengths of 'Gabor' filters is the cause of shift and scale tolerance of the system. Three different learning schemes had been investigated in the recognition unit, namely; the error back propagation learning with hidden units, a simple perceptron learning, and a competitive learning. Their performances were analyzed and compared. Since sometimes the network fails to distinguish between two letters that are inherently similar, additional ambiguity resolving neural nets are introduced on top of the above main neural net. The two dimensional Fourier transform is used as the preprocessing and the perceptron is used as the recognition unit of the ambiguity resolver. One hundred different person's handwriting sets are collected. Some of these are used as the training sets and the remainders are used as the test sets. The correct recognition rate of the system increases with the number of training sets and eventually saturates at a certain value. Similar recognition rates are obtained for the above three different learning algorithms. The minimum error

  6. 78 FR 72451 - Net Investment Income Tax

    Science.gov (United States)

    2013-12-02

    ... Revenue Service 26 CFR Part 1 RIN 1545-BL74 Net Investment Income Tax AGENCY: Internal Revenue Service...). These regulations provide guidance on the computation of net investment income. The regulations affect... lesser of: (A) The individual's net investment income for such taxable year, or (B) the excess (if any...

  7. 47 CFR 69.302 - Net investment.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 3 2010-10-01 2010-10-01 false Net investment. 69.302 Section 69.302... Apportionment of Net Investment § 69.302 Net investment. (a) Investment in Accounts 2001, 1220 and Class B Rural...) Investment in Accounts 2002, 2003 and to the extent such inclusions are allowed by this Commission, Account...

  8. 47 CFR 65.450 - Net income.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 3 2010-10-01 2010-10-01 false Net income. 65.450 Section 65.450... OF RETURN PRESCRIPTION PROCEDURES AND METHODOLOGIES Exchange Carriers § 65.450 Net income. (a) Net income shall consist of all revenues derived from the provision of interstate telecommunications services...

  9. 47 CFR 65.500 - Net income.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 3 2010-10-01 2010-10-01 false Net income. 65.500 Section 65.500... OF RETURN PRESCRIPTION PROCEDURES AND METHODOLOGIES Interexchange Carriers § 65.500 Net income. The net income methodology specified in § 65.450 shall be utilized by all interexchange carriers that are...

  10. NetBeans IDE 8 cookbook

    CERN Document Server

    Salter, David

    2014-01-01

    If you're a Java developer of any level using NetBeans and want to learn how to get the most out of NetBeans, then this book is for you. Learning how to utilize NetBeans will provide a firm foundation for your Java application development.

  11. Characterizing behavioural congruences for Petri nets

    DEFF Research Database (Denmark)

    Nielsen, Mogens; Priese, Lutz; Sassone, Vladimiro

    1995-01-01

    We exploit a notion of interface for Petri nets in order to design a set of net combinators. For such a calculus of nets, we focus on the behavioural congruences arising from four simple notions of behaviour, viz., traces, maximal traces, step, and maximal step traces, and from the corresponding...

  12. 27 CFR 4.37 - Net contents.

    Science.gov (United States)

    2010-04-01

    ... the volume of wine within the container, except that the following tolerances shall be allowed: (1... THE TREASURY LIQUORS LABELING AND ADVERTISING OF WINE Labeling Requirements for Wine § 4.37 Net contents. (a) Statement of net contents. The net contents of wine for which a standard of fill is...

  13. Reconstruction of neutron spectra through neural networks; Reconstruccion de espectros de neutrones mediante redes neuronales

    Energy Technology Data Exchange (ETDEWEB)

    Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E. [Cuerpo Academico de Radiobiologia, Estudios Nucleares, Universidad Autonoma de Zacatecas, A.P. 336, 98000 Zacatecas (Mexico)] e-mail: rvega@cantera.reduaz.mx [and others

    2003-07-01

    A neural network has been used to reconstruct the neutron spectra starting from the counting rates of the detectors of the Bonner sphere spectrophotometric system. A group of 56 neutron spectra was selected to calculate the counting rates that would produce in a Bonner sphere system, with these data and the spectra it was trained the neural network. To prove the performance of the net, 12 spectra were used, 6 were taken of the group used for the training, 3 were obtained of mathematical functions and those other 3 correspond to real spectra. When comparing the original spectra of those reconstructed by the net we find that our net has a poor performance when reconstructing monoenergetic spectra, this attributes it to those characteristic of the spectra used for the training of the neural network, however for the other groups of spectra the results of the net are appropriate with the prospective ones. (Author)

  14. NET 40 Generics Beginner's Guide

    CERN Document Server

    Mukherjee, Sudipta

    2012-01-01

    This is a concise, practical guide that will help you learn Generics in .NET, with lots of real world and fun-to-build examples and clear explanations. It is packed with screenshots to aid your understanding of the process. This book is aimed at beginners in Generics. It assumes some working knowledge of C# , but it isn't mandatory. The following would get the most use out of the book: Newbie C# developers struggling with Generics. Experienced C++ and Java Programmers who are migrating to C# and looking for an alternative to other generic frameworks like STL and JCF would find this book handy.

  15. The Net Reclassification Index (NRI)

    DEFF Research Database (Denmark)

    Pepe, Margaret S.; Fan, Jing; Feng, Ziding

    2015-01-01

    The Net Reclassification Index (NRI) is a very popular measure for evaluating the improvement in prediction performance gained by adding a marker to a set of baseline predictors. However, the statistical properties of this novel measure have not been explored in depth. We demonstrate the alarming...... marker is proven to erroneously yield a positive NRI. Some insight into this phenomenon is provided. Since large values for the NRI statistic may simply be due to use of poorly fitting risk models, we suggest caution in using the NRI as the basis for marker evaluation. Other measures of prediction...

  16. Part 1: Ulineær Regression med Neurale Netværk. Nonlinear Regression using Neural Network

    DEFF Research Database (Denmark)

    Schiøler, Henrik

    baggrunden for iværksættelsen af projektet. Har beskrives forskellige publikationer, der forslår anvendelsen af neurale net inden for forskellige delområder af proceskontrol. En central erkendelse er her at de neurale net alle steder fungerer ved at approximere eller estimere forskellige relevante funktioner....... Herefter introducered de grundlæggende begreber omkring neurale net og Multi Lags Perceptronen (MLP). Den nødvendige teori for MLP til approximation og konsistent estimation af funktioner beskrives med detajler henlagt til appendix og en væsentlig ulempe, der mindsker den praktiske relevans af denne teori......Denne rapport er 1.del af den samlede dokumentation for Ph.D. arbejdet. Den samlede dokumentation består af to dele. Disse dele er: · Del 1: "Ulineære regression med neurale netværk · Del 2: "Prediktion, simulering og regulering med neurale netværk Rapporten indleder med en beskrivelse af...

  17. Bayesian regularization of neural networks.

    Science.gov (United States)

    Burden, Frank; Winkler, Dave

    2008-01-01

    Bayesian regularized artificial neural networks (BRANNs) are more robust than standard back-propagation nets and can reduce or eliminate the need for lengthy cross-validation. Bayesian regularization is a mathematical process that converts a nonlinear regression into a "well-posed" statistical problem in the manner of a ridge regression. The advantage of BRANNs is that the models are robust and the validation process, which scales as O(N2) in normal regression methods, such as back propagation, is unnecessary. These networks provide solutions to a number of problems that arise in QSAR modeling, such as choice of model, robustness of model, choice of validation set, size of validation effort, and optimization of network architecture. They are difficult to overtrain, since evidence procedures provide an objective Bayesian criterion for stopping training. They are also difficult to overfit, because the BRANN calculates and trains on a number of effective network parameters or weights, effectively turning off those that are not relevant. This effective number is usually considerably smaller than the number of weights in a standard fully connected back-propagation neural net. Automatic relevance determination (ARD) of the input variables can be used with BRANNs, and this allows the network to "estimate" the importance of each input. The ARD method ensures that irrelevant or highly correlated indices used in the modeling are neglected as well as showing which are the most important variables for modeling the activity data. This chapter outlines the equations that define the BRANN method plus a flowchart for producing a BRANN-QSAR model. Some results of the use of BRANNs on a number of data sets are illustrated and compared with other linear and nonlinear models.

  18. Introduction to neural networks

    CERN Document Server

    James, Frederick E

    1994-02-02

    1. Introduction and overview of Artificial Neural Networks. 2,3. The Feed-forward Network as an inverse Problem, and results on the computational complexity of network training. 4.Physics applications of neural networks.

  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. A neural network architecture for implementation of expert systems for real time monitoring

    Science.gov (United States)

    Ramamoorthy, P. A.

    1991-01-01

    Since neural networks have the advantages of massive parallelism and simple architecture, they are good tools for implementing real time expert systems. In a rule based expert system, the antecedents of rules are in the conjunctive or disjunctive form. We constructed a multilayer feedforward type network in which neurons represent AND or OR operations of rules. Further, we developed a translator which can automatically map a given rule base into the network. Also, we proposed a new and powerful yet flexible architecture that combines the advantages of both fuzzy expert systems and neural networks. This architecture uses the fuzzy logic concepts to separate input data domains into several smaller and overlapped regions. Rule-based expert systems for time critical applications using neural networks, the automated implementation of rule-based expert systems with neural nets, and fuzzy expert systems vs. neural nets are covered.

  1. -Net Approach to Sensor -Coverage

    Directory of Open Access Journals (Sweden)

    Fusco Giordano

    2010-01-01

    Full Text Available Wireless sensors rely on battery power, and in many applications it is difficult or prohibitive to replace them. Hence, in order to prolongate the system's lifetime, some sensors can be kept inactive while others perform all the tasks. In this paper, we study the -coverage problem of activating the minimum number of sensors to ensure that every point in the area is covered by at least sensors. This ensures higher fault tolerance, robustness, and improves many operations, among which position detection and intrusion detection. The -coverage problem is trivially NP-complete, and hence we can only provide approximation algorithms. In this paper, we present an algorithm based on an extension of the classical -net technique. This method gives an -approximation, where is the number of sensors in an optimal solution. We do not make any particular assumption on the shape of the areas covered by each sensor, besides that they must be closed, connected, and without holes.

  2. Modeling EEG Waveforms with Semi-Supervised Deep Belief Nets: Fast Classification and Anomaly Measurement

    OpenAIRE

    Wulsin, D. F.; Gupta, J.R; Mani, R; Blanco, J. A.; Litt, B.

    2011-01-01

    Clinical electroencephalography (EEG) records vast amounts of human complex data yet is still reviewed primarily by human readers. Deep Belief Nets (DBNs) are a relatively new type of multi-layer neural network commonly tested on two-dimensional image data, but are rarely applied to times-series data such as EEG. We apply DBNs in a semi-supervised paradigm to model EEG waveforms for classification and anomaly detection. DBN performance was comparable to standard classifiers on our EEG dataset...

  3. NETS - Danish participation. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Alsen, S. (Grontmij - Carl Bro, Glostrup (Denmark)); Theel, C. (Baltic Sea Solutions, Holeby (Denmark))

    2008-12-15

    Within the NICe-funded project 'Nordic Environmental Technology Solutions (NETS)' a new type of networking at the Nordic level was organized in order to jointly exploit the rapidly growing market potential in the environmental technology sector. The project aimed at increased and professionalized commercialization of Nordic Cleantech in energy and water business segments through 1) closer cooperation and joint marketing activities, 2) a website, 3) cleantech product information via brochures and publications 4) and participating in relevant trade fairs and other industry events. Facilitating business-to-business activities was another core task for the NETS project partners from Norway, Sweden, Finland and Denmark with the aim to encourage total solutions for combined Cleantech system offers. The project has achieved to establish a Cleantech register of 600 Nordic Cleantech companies, a network of 86 member enterprises, produced several publications and brochures for direct technology promotion and a website for direct access to company profiles and contact data. The project partners have attended 14 relevant international Cleantech trade fairs and conferences and facilitated business-to-business contacts added by capacity building offers through two company workshops. The future challenge for the project partners and Nordic Cleantech will be to coordinate the numerous efforts within the Nordic countries in order to reach concerted action and binding of member companies for reliable services, an improved visibility and knowledge exchange. With Cleantech's growing market influence and public awareness, the need to develop total solutions is increasing likewise. Marketing efforts should be encouraged cross-sectional and cross-border among the various levels of involved actors from both the public and the private sector. (au)

  4. ANOMALY NETWORK INTRUSION DETECTION SYSTEM BASED ON DISTRIBUTED TIME-DELAY NEURAL NETWORK (DTDNN

    Directory of Open Access Journals (Sweden)

    LAHEEB MOHAMMAD IBRAHIM

    2010-12-01

    Full Text Available In this research, a hierarchical off-line anomaly network intrusion detection system based on Distributed Time-Delay Artificial Neural Network is introduced. This research aims to solve a hierarchical multi class problem in which the type of attack (DoS, U2R, R2L and Probe attack detected by dynamic neural network. The results indicate that dynamic neural nets (Distributed Time-Delay Artificial Neural Network can achieve a high detection rate, where the overall accuracy classification rate average is equal to 97.24%.

  5. Application and Theory of Petri Nets

    DEFF Research Database (Denmark)

    This volume contains the proceedings of the 13th International Conference onApplication and Theory of Petri Nets, held in Sheffield, England, in June 1992. The aim of the Petri net conferences is to create a forum for discussing progress in the application and theory of Petri nets. Typically....... Balbo and W. Reisig, 18 submitted papers, and seven project papers. The submitted papers and project presentations were selectedby the programme committee and a panel of referees from a large number of submissions....

  6. Are You Neutral About Net Neutrality

    Science.gov (United States)

    2007-06-20

    Information Resources Management College National Defense University Are You Neutral About Net Neutrality ? A presentation for Systems & Software...author uses Verizon FiOS for phone, TV, and internet service 3 Agenda Net Neutrality —Through 2 Lenses Who Are the Players & What Are They Saying...Medical Treatment Mini-Case Studies Updates Closing Thoughts 4 Working Definitions of Net Neutrality "Network Neutrality" is the concept that

  7. Factors associated with mosquito net use by individuals in households owning nets in Ethiopia

    Directory of Open Access Journals (Sweden)

    Graves Patricia M

    2011-12-01

    Full Text Available Abstract Background Ownership of insecticidal mosquito nets has dramatically increased in Ethiopia since 2006, but the proportion of persons with access to such nets who use them has declined. It is important to understand individual level net use factors in the context of the home to modify programmes so as to maximize net use. Methods Generalized linear latent and mixed models (GLLAMM were used to investigate net use using individual level data from people living in net-owning households from two surveys in Ethiopia: baseline 2006 included 12,678 individuals from 2,468 households and a sub-sample of the Malaria Indicator Survey (MIS in 2007 included 14,663 individuals from 3,353 households. Individual factors (age, sex, pregnancy; net factors (condition, age, net density; household factors (number of rooms [2006] or sleeping spaces [2007], IRS, women's knowledge and school attendance [2007 only], wealth, altitude; and cluster level factors (rural or urban were investigated in univariate and multi-variable models for each survey. Results In 2006, increased net use was associated with: age 25-49 years (adjusted (a OR = 1.4, 95% confidence interval (CI 1.2-1.7 compared to children U5; female gender (aOR = 1.4; 95% CI 1.2-1.5; fewer nets with holes (Ptrend = 0.002; and increasing net density (Ptrend [all nets in HH good] = 1.6; 95% CI 1.2-2.1; increasing net density (Ptrend [per additional space] = 0.6, 95% CI 0.5-0.7; more old nets (aOR [all nets in HH older than 12 months] = 0.5; 95% CI 0.3-0.7; and increasing household altitude (Ptrend Conclusion In both surveys, net use was more likely by women, if nets had fewer holes and were at higher net per person density within households. School-age children and young adults were much less likely to use a net. Increasing availability of nets within households (i.e. increasing net density, and improving net condition while focusing on education and promotion of net use, especially in school-age children

  8. Pro Agile NET Development with Scrum

    CERN Document Server

    Blankenship, Jerrel; Millett, Scott

    2011-01-01

    Pro Agile .NET Development with SCRUM guides you through a real-world ASP.NET project and shows how agile methodology is put into practice. There is plenty of literature on the theory behind agile methodologies, but no book on the market takes the concepts of agile practices and applies these in a practical manner to an end-to-end ASP.NET project, especially the estimating, requirements and management aspects of a project. Pro Agile .NET Development with SCRUM takes you through the initial stages of a project - gathering requirements and setting up an environment - through to the development a

  9. Pro ASP.NET MVC 4

    CERN Document Server

    Freeman, Adam

    2012-01-01

    The ASP.NET MVC 4 Framework is the latest evolution of Microsoft's ASP.NET web platform. It provides a high-productivity programming model that promotes cleaner code architecture, test-driven development, and powerful extensibility, combined with all the benefits of ASP.NET. ASP.NET MVC 4 contains a number of significant advances over previous versions. New mobile and desktop templates (employing adaptive rendering) are included together with support for jQuery Mobile for the first time. New display modes allow your application to select views based on the browser that's making the request whi

  10. Professional Visual Basic 2010 and .NET 4

    CERN Document Server

    Sheldon, Bill; Sharkey, Kent

    2010-01-01

    Intermediate and advanced coverage of Visual Basic 2010 and .NET 4 for professional developers. If you've already covered the basics and want to dive deep into VB and .NET topics that professional programmers use most, this is your book. You'll find a quick review of introductory topics-always helpful-before the author team of experts moves you quickly into such topics as data access with ADO.NET, Language Integrated Query (LINQ), security, ASP.NET web programming with Visual Basic, Windows workflow, threading, and more. You'll explore all the new features of Visual Basic 2010 as well as all t

  11. NASA Net Zero Energy Buildings Roadmap

    Energy Technology Data Exchange (ETDEWEB)

    Pless, S.; Scheib, J.; Torcellini, P.; Hendron, B.; Slovensky, M.

    2014-10-01

    In preparation for the time-phased net zero energy requirement for new federal buildings starting in 2020, set forth in Executive Order 13514, NASA requested that the National Renewable Energy Laboratory (NREL) to develop a roadmap for NASA's compliance. NASA detailed a Statement of Work that requested information on strategic, organizational, and tactical aspects of net zero energy buildings. In response, this document presents a high-level approach to net zero energy planning, design, construction, and operations, based on NREL's first-hand experience procuring net zero energy construction, and based on NREL and other industry research on net zero energy feasibility. The strategic approach to net zero energy starts with an interpretation of the executive order language relating to net zero energy. Specifically, this roadmap defines a net zero energy acquisition process as one that sets an aggressive energy use intensity goal for the building in project planning, meets the reduced demand goal through energy efficiency strategies and technologies, then adds renewable energy in a prioritized manner, using building-associated, emission- free sources first, to offset the annual energy use required at the building; the net zero energy process extends through the life of the building, requiring a balance of energy use and production in each calendar year.

  12. Towards a Standard for Modular Petri Nets

    DEFF Research Database (Denmark)

    Kindler, Ekkart; Petrucci, Laure

    2009-01-01

    When designing complex systems, mechanisms for structuring, composing, and reusing system components are crucial. Today, there are many approaches for equipping Petri nets with such mechanisms. In the context of defining a standard interchange format for Petri nets, modular PNML was defined....... Moreover, we present and discuss some more advanced features of modular Petri nets that could be included in the standard. This way, we provide a formal foundation and a basis for a discussion of features to be included in the upcoming standard of a module concept for Petri nets in general and for high...

  13. Experiments and simulation of a net closing mechanism for tether-net capture of space debris

    Science.gov (United States)

    Sharf, Inna; Thomsen, Benjamin; Botta, Eleonora M.; Misra, Arun K.

    2017-10-01

    This research addresses the design and testing of a debris containment system for use in a tether-net approach to space debris removal. The tether-net active debris removal involves the ejection of a net from a spacecraft by applying impulses to masses on the net, subsequent expansion of the net, the envelopment and capture of the debris target, and the de-orbiting of the debris via a tether to the chaser spacecraft. To ensure a debris removal mission's success, it is important that the debris be successfully captured and then, secured within the net. To this end, we present a concept for a net closing mechanism, which we believe will permit consistently successful debris capture via a simple and unobtrusive design. This net closing system functions by extending the main tether connecting the chaser spacecraft and the net vertex to the perimeter and around the perimeter of the net, allowing the tether to actuate closure of the net in a manner similar to a cinch cord. A particular embodiment of the design in a laboratory test-bed is described: the test-bed itself is comprised of a scaled-down tether-net, a supporting frame and a mock-up debris. Experiments conducted with the facility demonstrate the practicality of the net closing system. A model of the net closure concept has been integrated into the previously developed dynamics simulator of the chaser/tether-net/debris system. Simulations under tether tensioning conditions demonstrate the effectiveness of the closure concept for debris containment, in the gravity-free environment of space, for a realistic debris target. The on-ground experimental test-bed is also used to showcase its utility for validating the dynamics simulation of the net deployment, and a full-scale automated setup would make possible a range of validation studies of other aspects of a tether-net debris capture mission.

  14. Investment Valuation Analysis with Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Hüseyin İNCE

    2017-07-01

    Full Text Available This paper shows that discounted cash flow and net present value, which are traditional investment valuation models, can be combined with artificial neural network model forecasting. The main inputs for the valuation models, such as revenue, costs, capital expenditure, and their growth rates, are heavily related to sector dynamics and macroeconomics. The growth rates of those inputs are related to inflation and exchange rates. Therefore, predicting inflation and exchange rates is a critical issue for the valuation output. In this paper, the Turkish economy’s inflation rate and the exchange rate of USD/TRY are forecast by artificial neural networks and implemented to the discounted cash flow model. Finally, the results are benchmarked with conventional practices.

  15. Matrix representation of a Neural Network

    DEFF Research Database (Denmark)

    Christensen, Bjørn Klint

    Processing, by David Rummelhart (Rummelhart 1986) for an easy-to-read introduction. What the paper does explain is how a matrix representation of a neural net allows for a very simple implementation. The matrix representation is introduced in (Rummelhart 1986, chapter 9), but only for a two-layer linear...... network and the feedforward algorithm. This paper develops the idea further to three-layer non-linear networks and the backpropagation algorithm. Figure 1 shows the layout of a three-layer network. There are I input nodes, J hidden nodes and K output nodes all indexed from 0. Bias-node for the hidden...

  16. HANPP Collection: Human Appropriation of Net Primary Productivity as a Percentage of Net Primary Productivity

    Data.gov (United States)

    National Aeronautics and Space Administration — The Human Appropriation of Net Primary Productivity (HANPP) as a Percentage of Net Primary Product (NPP) portion of the HANPP Collection represents a map identifying...

  17. Price smarter on the Net.

    Science.gov (United States)

    Baker, W; Marn, M; Zawada, C

    2001-02-01

    Companies generally have set prices on the Internet in two ways. Many start-ups have offered untenably low prices in a rush to capture first-mover advantage. Many incumbents have simply charged the same prices on-line as they do off-line. Either way, companies are missing a big opportunity. The fundamental value of the Internet lies not in lowering prices or making them consistent but in optimizing them. After all, if it's easy for customers to compare prices on the Internet, it's also easy for companies to track customers' behavior and adjust prices accordingly. The Net lets companies optimize prices in three ways. First, it lets them set and announce prices with greater precision. Different prices can be tested easily, and customers' responses can be collected instantly. Companies can set the most profitable prices, and they can tap into previously hidden customer demand. Second, because it's so easy to change prices on the Internet, companies can adjust prices in response to even small fluctuations in market conditions, customer demand, or competitors' behavior. Third, companies can use the clickstream data and purchase histories that it collects through the Internet to segment customers quickly. Then it can offer segment-specific prices or promotions immediately. By taking full advantage of the unique possibilities afforded by the Internet to set prices with precision, adapt to changing circumstances quickly, and segment customers accurately, companies can get their pricing right. It's one of the ultimate drivers of e-business success.

  18. Feature to prototype transition in neural networks

    Science.gov (United States)

    Krotov, Dmitry; Hopfield, John

    Models of associative memory with higher order (higher than quadratic) interactions, and their relationship to neural networks used in deep learning are discussed. Associative memory is conventionally described by recurrent neural networks with dynamical convergence to stable points. Deep learning typically uses feedforward neural nets without dynamics. However, a simple duality relates these two different views when applied to problems of pattern classification. From the perspective of associative memory such models deserve attention because they make it possible to store a much larger number of memories, compared to the quadratic case. In the dual description, these models correspond to feedforward neural networks with one hidden layer and unusual activation functions transmitting the activities of the visible neurons to the hidden layer. These activation functions are rectified polynomials of a higher degree rather than the rectified linear functions used in deep learning. The network learns representations of the data in terms of features for rectified linear functions, but as the power in the activation function is increased there is a gradual shift to a prototype-based representation, the two extreme regimes of pattern recognition known in cognitive psychology. Simons Center for Systems Biology.

  19. 78 FR 72393 - Net Investment Income Tax

    Science.gov (United States)

    2013-12-02

    ... Investment Income Tax; Final and Proposed Rules #0;#0;Federal Register / Vol. 78, No. 231 / Monday, December... Parts 1 and 602 RIN 1545-BK44 Net Investment Income Tax AGENCY: Internal Revenue Service (IRS), Treasury... Investment Income Tax and the computation of Net Investment Income. The regulations affect individuals...

  20. 77 FR 72611 - Net Investment Income Tax

    Science.gov (United States)

    2012-12-05

    ... December 5, 2012 Part V Department of the Treasury Internal Revenue Service 26 CFR Part 1 Net Investment... Investment Income Tax AGENCY: Internal Revenue Service (IRS), Treasury. ACTION: Notice of proposed rulemaking...) the individual's net investment income for such taxable year, or (B) the excess (if any) of (i) the...

  1. Net analyte signal based statistical quality control

    NARCIS (Netherlands)

    Skibsted, E.T.S.; Boelens, H.F.M.; Westerhuis, J.A.; Smilde, A.K.; Broad, N.W.; Rees, D.R.; Witte, D.T.

    2005-01-01

    Net analyte signal statistical quality control (NAS-SQC) is a new methodology to perform multivariate product quality monitoring based on the net analyte signal approach. The main advantage of NAS-SQC is that the systematic variation in the product due to the analyte (or property) of interest is

  2. Asynchronous stream processing with S-Net

    NARCIS (Netherlands)

    Grelck, C.; Scholz, S.-B.; Shafarenko, A.

    2010-01-01

    We present the rationale and design of S-Net, a coordination language for asynchronous stream processing. The language achieves a near-complete separation between the application code, written in any conventional programming language, and the coordination/communication code written in S-Net. Our

  3. Using the MVC architecture on . NET platform

    OpenAIRE

    Ježek, David

    2011-01-01

    This thesis deals with usage of MVC (Model View Controller) technology in web development on ASP.NET platform from Microsoft. Mainly it deals with latest version of framework ASP.NET MVC 3. First part describes MVC architecture and the second describes usage of MVC in certain parts of web application an comparing with PHP.

  4. Analysis of Petri Nets and Transition Systems

    Directory of Open Access Journals (Sweden)

    Eike Best

    2015-08-01

    Full Text Available This paper describes a stand-alone, no-frills tool supporting the analysis of (labelled place/transition Petri nets and the synthesis of labelled transition systems into Petri nets. It is implemented as a collection of independent, dedicated algorithms which have been designed to operate modularly, portably, extensibly, and efficiently.

  5. 27 CFR 7.27 - Net contents.

    Science.gov (United States)

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Net contents. 7.27 Section 7.27 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE BUREAU, DEPARTMENT OF... the net contents are displayed by having the same blown, branded, or burned in the container in...

  6. Petri nets and other models of concurrency

    DEFF Research Database (Denmark)

    Nielsen, Mogens; Sassone, Vladimiro

    1998-01-01

    This paper retraces, collects, and summarises contributions of the authors - in collaboration with others - on the theme of Petri nets and their categorical relationships to other models of concurrency.......This paper retraces, collects, and summarises contributions of the authors - in collaboration with others - on the theme of Petri nets and their categorical relationships to other models of concurrency....

  7. Delta Semantics Defined By Petri Nets

    DEFF Research Database (Denmark)

    Jensen, Kurt; Kyng, Morten; Madsen, Ole Lehrmann

    This report is identical to an earlier version of May 1978 except that Chapter 5 has been revised. A new paper: "A Petri Net Definition of a System Description Language", DAIMI, April 1979, 20 pages, extends the Petri net model to include a data state representing the program variables. Delta...

  8. Net neutrality and inflation of traffic

    NARCIS (Netherlands)

    Peitz, M.; Schütt, Florian

    Under strict net neutrality Internet service providers (ISPs) are required to carry data without any differentiation and at no cost to the content provider. We provide a simple framework with a monopoly ISP to evaluate the short-run effects of different net neutrality rules. Content differs in its

  9. Net Neutrality and Inflation of Traffic

    NARCIS (Netherlands)

    Peitz, M.; Schütt, F.

    2015-01-01

    Under strict net neutrality Internet service providers (ISPs) are required to carry data without any differentiation and at no cost to the content provider. We provide a simple framework with a monopoly ISP to evaluate different net neutrality rules. Content differs in its sensitivity to delay.

  10. The Net Neutrality Debate: The Basics

    Science.gov (United States)

    Greenfield, Rich

    2006-01-01

    Rich Greenfield examines the basics of today's net neutrality debate that is likely to be an ongoing issue for society. Greenfield states the problems inherent in the definition of "net neutrality" used by Common Cause: "Network neutrality is the principle that Internet users should be able to access any web content they choose and…

  11. Dynamic response of the thermometric net radiometer

    Science.gov (United States)

    J. D. Wilson; W. J. Massman; G. E. Swaters

    2009-01-01

    We computed the dynamic response of an idealized thermometric net radiometer, when driven by an oscillating net longwave radiation intended roughly to simulate rapid fluctuations of the radiative environment such as might be expected during field use of such devices. The study was motivated by curiosity as to whether non-linearity of the surface boundary conditions...

  12. Teaching and Learning with the Net Generation

    Science.gov (United States)

    Barnes, Kassandra; Marateo, Raymond C.; Ferris, S. Pixy

    2007-01-01

    As the Net Generation places increasingly greater demands on educators, students and teachers must jointly consider innovative ways of teaching and learning. In this, educators are supported by the fact that the Net Generation wants to learn. However, these same educators should not fail to realize that this generation learns differently from…

  13. Verification of Timed-Arc Petri Nets

    DEFF Research Database (Denmark)

    Jacobsen, Lasse; Jacobsen, Morten; Møller, Mikael Harkjær

    2011-01-01

    Timed-Arc Petri Nets (TAPN) are an extension of the classical P/T nets with continuous time. Tokens in TAPN carry an age and arcs between places and transitions are labelled with time intervals restricting the age of tokens available for transition firing. The TAPN model posses a number...

  14. A Brief Introduction to Coloured Petri Nets

    DEFF Research Database (Denmark)

    Jensen, Kurt

    1997-01-01

    Coloured Petri Nets (CP-nets or CPN) is a graphical oriented language for design, specification, simulation and verification of systems. It is in particular well- suited for systems in which communication, synchronisation and resource sharing are important. Typical examples of application areas a...

  15. Gill net and trammel net selectivity in the northern Aegean Sea, Turkey

    Directory of Open Access Journals (Sweden)

    F. Saadet Karakulak

    2008-09-01

    Full Text Available Fishing trials were carried out with gill nets and trammel nets in the northern Aegean Sea from March 2004 to February 2005. Four different mesh sizes for the gill nets and the inner panel of trammel nets (16, 18, 20 and 22 mm bar length were used. Selectivity parameters for the five most economically important species, bogue (Boops boops, annular sea bream (Diplodus annularis, striped red mullet (Mullus surmuletus, axillary sea bream (Pagellus acarne and blotched picarel (Spicara maena, caught by the two gears were estimated. The SELECT method was used to estimate the selectivity parameters of a variety of models. Catch composition and catch proportion of several species were different in gill and trammel nets. The length frequency distributions of the species caught by the two gears were significantly different. The bi-modal model selectivity curve gave the best fit for gill net and trammel net data, and there was little difference between the modal lengths of these nets. However, a clear difference was found in catching efficiency. The highest catch rates were obtained with the trammel net. Given that many discard species and small fish are caught by gill nets and trammel nets with a mesh size of 16 mm, it is clear that these nets are not appropriate for fisheries. Consequently, the best mesh size for multispecies fisheries is 18 mm. This mesh size will considerably reduce the numbers of small sized individuals and discard species in the catch.

  16. 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.

  17. Discrete, continuous, and hybrid petri nets

    CERN Document Server

    David, René

    2004-01-01

    Petri nets do not designate a single modeling formalism. In fact, newcomers to the field confess sometimes to be a little puzzled by the diversity of formalisms that are recognized under this "umbrella". Disregarding some extensions to the theoretical modeling capabilities, and looking at the level of abstraction of the formalisms, Condition/Event, Elementary, Place/Transition, Predicate/Transition, Colored, Object Oriented... net systems are frequently encountered in the literature. On the other side, provided with appropriate interpretative extensions, Controled Net Systems, Marking Diagrams (the Petri net generalization of State Diagrams), or the many-many variants in which time can be explicitly incorporated -Time(d), Deterministic, (Generalized) Stochastic, Fuzzy...- are defined. This represents another way to define practical formalisms that can be obtained by the "cro- product" of the two mentioned dimensions. Thus Petri nets constitute a modeling paradigm, understandable in a broad sense as "the total...

  18. Flare Occurrence Prediction based on Convolution Neural Network using SOHO MDI data

    Science.gov (United States)

    Yi, Kangwoo; Moon, Yong-Jae; Park, Eunsu; Shin, Seulki

    2017-08-01

    In this study we apply Convolution Neural Network(CNN) to solar flare occurrence prediction with various parameter options using the 00:00 UT MDI images from 1996 to 2010 (total 4962 images). We assume that only X, M and C class flares correspond to “flare occurrence” and the others to “non-flare”. We have attempted to look for the best options for the models with two CNN pre-trained models (AlexNet and GoogLeNet), by modifying training images and changing hyper parameters. Our major results from this study are as follows. First, the flare occurrence predictions are relatively good with about 80 % accuracies. Second, both flare prediction models based on AlexNet and GoogLeNet have similar results but AlexNet is faster than GoogLeNet. Third, modifying the training images to reduce the projection effect is not effective.

  19. On limited fan-in optimal neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V.; Makaruk, H.E. [Los Alamos National Lab., NM (United States); Draghici, S. [Wayne State Univ., Detroit, MI (United States). Vision and Neural Networks Lab.

    1998-03-01

    Because VLSI implementations do not cope well with highly interconnected nets the area of a chip growing as the cube of the fan-in--this paper analyses the influence of limited fan in on the size and VLSI optimality of such nets. Two different approaches will show that VLSI- and size-optimal discrete neural networks can be obtained for small (i.e. lower than linear) fan-in values. They have applications to hardware implementations of neural networks. The first approach is based on implementing a certain sub class of Boolean functions, IF{sub n,m} functions. The authors will show that this class of functions can be implemented in VLSI optimal (i.e., minimizing AT{sup 2}) neural networks of small constant fan ins. The second approach is based on implementing Boolean functions for which the classical Shannon`s decomposition can be used. Such a solution has already been used to prove bounds on neural networks with fan-ins limited to 2. They generalize the result presented there to arbitrary fan-in, and prove that the size is minimized by small fan in values, while relative minimum size solutions can be obtained for fan-ins strictly lower than linear. Finally, a size-optimal neural network having small constant fan-ins will be suggested for IF{sub n,m} functions.

  20. 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.

  1. Pro visual C++/CLI and the net 35 platform

    CERN Document Server

    Fraser, Stephen

    2008-01-01

    Pro Visual C++/CLI and the .NET 3.5 Platform is about writing .NET applications using C++/CLI. While readers are learning the ins and outs of .NET application development, they will also be learning the syntax of C++, both old and new to .NET. Readers will also gain a good understanding of the .NET architecture. This is truly a .NET book applying C++ as its development language not another C++ syntax book that happens to cover .NET.

  2. Forecasting volatility with neural regression: a contribution to model adequacy.

    Science.gov (United States)

    Refenes, A N; Holt, W T

    2001-01-01

    Neural nets' usefulness for forecasting is limited by problems of overfitting and the lack of rigorous procedures for model identification, selection and adequacy testing. This paper describes a methodology for neural model misspecification testing. We introduce a generalization of the Durbin-Watson statistic for neural regression and discuss the general issues of misspecification testing using residual analysis. We derive a generalized influence matrix for neural estimators which enables us to evaluate the distribution of the statistic. We deploy Monte Carlo simulation to compare the power of the test for neural and linear regressors. While residual testing is not a sufficient condition for model adequacy, it is nevertheless a necessary condition to demonstrate that the model is a good approximation to the data generating process, particularly as neural-network estimation procedures are susceptible to partial convergence. The work is also an important step toward developing rigorous procedures for neural model identification, selection and adequacy testing which have started to appear in the literature. We demonstrate its applicability in the nontrivial problem of forecasting implied volatility innovations using high-frequency stock index options. Each step of the model building process is validated using statistical tests to verify variable significance and model adequacy with the results confirming the presence of nonlinear relationships in implied volatility innovations.

  3. Consciousness and neural plasticity

    DEFF Research Database (Denmark)

    In contemporary consciousness studies the phenomenon of neural plasticity has received little attention despite the fact that neural plasticity is of still increased interest in neuroscience. We will, however, argue that neural plasticity could be of great importance to consciousness studies....... If consciousness is related to neural processes it seems, at least prima facie, that the ability of the neural structures to change should be reflected in a theory of this relationship "Neural plasticity" refers to the fact that the brain can change due to its own activity. The brain is not static but rather...... a dynamic entity, which physical structure changes according to its use and environment. This change may take the form of growth of new neurons, the creation of new networks and structures, and change within network structures, that is, changes in synaptic strengths. Plasticity raises questions about...

  4. Fuzzy and neural control

    Science.gov (United States)

    Berenji, Hamid R.

    1992-01-01

    Fuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which can start with an approximate control knowledge base and refine it through reinforcement learning.

  5. What Is Neural Plasticity?

    Science.gov (United States)

    von Bernhardi, Rommy; Bernhardi, Laura Eugenín-von; Eugenín, Jaime

    2017-01-01

    "Neural plasticity" refers to the capacity of the nervous system to modify itself, functionally and structurally, in response to experience and injury. As the various chapters in this volume show, plasticity is a key component of neural development and normal functioning of the nervous system, as well as a response to the changing environment, aging, or pathological insult. This chapter discusses how plasticity is necessary not only for neural networks to acquire new functional properties, but also for them to remain robust and stable. The article also reviews the seminal proposals developed over the years that have driven experiments and strongly influenced concepts of neural plasticity.

  6. 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...

  7. A neural flow estimator

    DEFF Research Database (Denmark)

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

    1995-01-01

    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......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...

  8. Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

    DEFF Research Database (Denmark)

    Hjerrild, M.; Stensballe, A.; Rasmussen, T.E.

    2004-01-01

    Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein...... kinase A (PKA) phosphorylation sites. The neural network was trained with a positive set of 258 experimentally verified PKA phosphorylation sites. The predictions by NetPhosK were! validated using four novel PKA substrates: Necdin, RFX5, En-2, and Wee 1. The four proteins were phosphorylated by PKA...... in vitro and 13 PKA phosphorylation sites were identified by mass spectrometry. NetPhosK was 100% sensitive and 41% specific in predicting PKA sites in the four proteins. These results demonstrate the potential of using integrated computational and experimental methods for detailed investigations...

  9. KONVERGENSI DALAM PROGRAM NET CITIZEN JOURNALISM

    Directory of Open Access Journals (Sweden)

    Rhafidilla Vebrynda

    2017-06-01

    Full Text Available Di dalam artikel ini, peneliti ingin melihat perkembangan teknologi di Indonesia sebagai sebuah peluang untuk menjalankan sebuah program berita berbasis video kiriman masyarakat. Perkembangan teknologi tersebut adalah teknologi penyiaran, teknologi sosial media dan teknologi dalam proses produksi sebuah video. Di Indonesia, jumlah televisi semakin banyak. Setiap stasiun televisi harus bersaing untuk dapat bertahan hidup. Net TV merupakan sebuah stasiun televisi baru di Indonesia yang harus memiliki berbagai program unggulan baru agar dapat bersaing dengan televisi lainnya yang sudah ada. Net TV menggunakan berbagai platform media untuk menjalankan program Net Citizen Journalism (Net CJ. Penggunaan berbagai platform media dikenal dengan istilah multiplatform dan secara teoritis dikenal dengan istilah konvergensi. Konvergensi yaitu saat meleburnya domain-domain dalam berbagai media komunikasi. Artikel ini menggunakan metode studi kasus untuk melihat bagaimana konvergensi terjadi dalam proses pengelolaan program Net CJ. Teknik pengumpulan data adalah dengan wawancara mendalam, observasi dan studi dokumen. Wawancara mendalam dilakukan dari tiga sudut pandang yaitu dari pengelola program, pengguna/audience dan pengamat media. Penelitian ini menemukan bahwa dengan menggunakan berbagai platform media yang fungsinya berbeda, memiliki satu tujuan yang sama yaitu untuk menjalankan program Net CJ. Adapun berbagai platform dalam proses produksi program yaitu tayangan TV konvensional, streaming TV, website, aplikasi Net CJ, facebook, twitter, instagram dan path. Konvergensi media dijalankan dalam dua proses, yaitu proses produksi dan proses promosi program berita.

  10. Net Neutrality: Media Discourses and Public Perception

    Directory of Open Access Journals (Sweden)

    Christine Quail

    2010-01-01

    Full Text Available This paper analyzes media and public discourses surrounding net neutrality, with particular attention to public utility philosophy, from a critical perspective. The article suggests that further public education about net neutrality would be beneficial. The first portion of this paper provides a survey of the existing literature surrounding net neutrality, highlighting the contentious debate between market-based and public interest perspectives. In order to contextualize the debate, an overview of public utility philosophy is provided, shedding light on how the Internet can be conceptualized as a public good. Following this discussion, an analysis of mainstream media is presented, exploring how the media represents the issue of net neutrality and whether or not the Internet is discussed through the lens of public utility. To further examine how the net neutrality debate is being addressed, and to see the potential impacts of media discourses on the general public, the results of a focus group are reported and analyzed. Finally, a discussion assesses the implications of the net neutrality debate as presented through media discourses, highlighting the future of net neutrality as an important policy issue.

  11. Approximation methods for stochastic petri nets

    Science.gov (United States)

    Jungnitz, Hauke Joerg

    1992-01-01

    Stochastic Marked Graphs are a concurrent decision free formalism provided with a powerful synchronization mechanism generalizing conventional Fork Join Queueing Networks. In some particular cases the analysis of the throughput can be done analytically. Otherwise the analysis suffers from the classical state explosion problem. Embedded in the divide and conquer paradigm, approximation techniques are introduced for the analysis of stochastic marked graphs and Macroplace/Macrotransition-nets (MPMT-nets), a new subclass introduced herein. MPMT-nets are a subclass of Petri nets that allow limited choice, concurrency and sharing of resources. The modeling power of MPMT is much larger than that of marked graphs, e.g., MPMT-nets can model manufacturing flow lines with unreliable machines and dataflow graphs where choice and synchronization occur. The basic idea leads to the notion of a cut to split the original net system into two subnets. The cuts lead to two aggregated net systems where one of the subnets is reduced to a single transition. A further reduction leads to a basic skeleton. The generalization of the idea leads to multiple cuts, where single cuts can be applied recursively leading to a hierarchical decomposition. Based on the decomposition, a response time approximation technique for the performance analysis is introduced. Also, delay equivalence, which has previously been introduced in the context of marked graphs by Woodside et al., Marie's method and flow equivalent aggregation are applied to the aggregated net systems. The experimental results show that response time approximation converges quickly and shows reasonable accuracy in most cases. The convergence of Marie's method and flow equivalent aggregation are applied to the aggregated net systems. The experimental results show that response time approximation converges quickly and shows reasonable accuracy in most cases. The convergence of Marie's is slower, but the accuracy is generally better. Delay

  12. Visual Studio 2010 and NET 4 Six-in-One

    CERN Document Server

    Novak, Istvan; Granicz, Adam

    2010-01-01

    Complete coverage of all key .NET 4 and Visual Studio 2010 languages and technologies. .NET 4 is Microsoft's latest version of their core programming platform, and Visual Studio 2010 is the toolset that helps write .NET 4 applications. This comprehensive resource offers one-stop shopping for all you need to know to get productive with .NET 4. Experienced author and .NET guru Mitchel Sellers reviews all the important new features of .NET 4, including .NET charting and ASP.NET charting, ASP.NET dynamic data and jQuery, and the addition of F# as a supported package language. The expansive coverag

  13. Application and Theory of Petri Nets

    DEFF Research Database (Denmark)

    , the conferences have 150-200 participants, one third of these coming from industry and the rest from universities and research institutions. The 1992 conference was organized by the School of Computing and Management Sciences at Sheffield City Polytechnic, England. The volume contains twoinvited papers, by G......This volume contains the proceedings of the 13th International Conference onApplication and Theory of Petri Nets, held in Sheffield, England, in June 1992. The aim of the Petri net conferences is to create a forum for discussing progress in the application and theory of Petri nets. Typically...

  14. Performance Analysis using Coloured Petri Nets

    DEFF Research Database (Denmark)

    Wells, Lisa Marie

    an explicit separation between modelling the behaviour of a system and monitoring the behaviour of the model. As a result, cleaner and more understandable models can be created. The third paper presents a novel method for adding auxiliary information to coloured Petri net models. Coloured Petri nets models...... in a very limited and predictable manner, and it is easy to enable and disable the auxiliary information. The fourth paper is a case study in which the performance of a web server was analysed using coloured Petri nets. This case study has shown that it is relatively easy to analyse the performance...

  15. The KM3NeT project

    Energy Technology Data Exchange (ETDEWEB)

    Katz, U.F., E-mail: katz@physik.uni-erlangen.d [Erlangen Centre for Astroparticle Physics (ECAP), University of Erlangen-Nuernberg, Erwin-Rommel-Str. 1, 91058 Erlangen (Germany)

    2011-01-21

    The KM3NeT research infrastructure in the deep Mediterranean Sea will host a multi-cubic-kilometre neutrino telescope and provide connectivity for continuous, long-term measurements of earth and sea sciences, such as geology, marine biology and oceanography. The KM3NeT neutrino telescope will complement the IceCube telescope currently being installed at the South Pole in its field of view and surpass its sensitivity by a substantial factor. In this document the major aspects of the KM3NeT technical design are described and the expected physics sensitivity is discussed. Finally, the expected time line towards construction is presented.

  16. The net neutrality debate on Twitter

    Directory of Open Access Journals (Sweden)

    Wolf J. Schünemann

    2015-12-01

    Full Text Available The internet has been seen as a medium that empowers individual political actors in relation to established political elites and media gatekeepers. The present article discusses this “net empowerment hypothesis” and tests it empirically by analysing Twitter communication on the regulation of net neutrality. We extracted 503.839 tweets containing #NetNeutrality posted between January and March 2015 and analysed central developments and the network structure of the debate. The empirical results show that traditional actors from media and politics still maintain a central role.

  17. Neural Networks: Implementations and Applications

    NARCIS (Netherlands)

    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

  18. Planning long lasting insecticide treated net campaigns: should households' existing nets be taken into account?

    Science.gov (United States)

    Yukich, Joshua; Bennett, Adam; Keating, Joseph; Yukich, Rudy K; Lynch, Matt; Eisele, Thomas P; Kolaczinski, Kate

    2013-06-14

    Mass distribution of long-lasting insecticide treated bed nets (LLINs) has led to large increases in LLIN coverage in many African countries. As LLIN ownership levels increase, planners of future mass distributions face the challenge of deciding whether to ignore the nets already owned by households or to take these into account and attempt to target individuals or households without nets. Taking existing nets into account would reduce commodity costs but require more sophisticated, and potentially more costly, distribution procedures. The decision may also have implications for the average age of nets in use and therefore on the maintenance of universal LLIN coverage over time. A stochastic simulation model based on the NetCALC algorithm was used to determine the scenarios under which it would be cost saving to take existing nets into account, and the potential effects of doing so on the age profile of LLINs owned. The model accounted for variability in timing of distributions, concomitant use of continuous distribution systems, population growth, sampling error in pre-campaign coverage surveys, variable net 'decay' parameters and other factors including the feasibility and accuracy of identifying existing nets in the field. Results indicate that (i) where pre-campaign coverage is around 40% (of households owning at least 1 LLIN), accounting for existing nets in the campaign will have little effect on the mean age of the net population and (ii) even at pre-campaign coverage levels above 40%, an approach that reduces LLIN distribution requirements by taking existing nets into account may have only a small chance of being cost-saving overall, depending largely on the feasibility of identifying nets in the field. Based on existing literature the epidemiological implications of such a strategy is likely to vary by transmission setting, and the risks of leaving older nets in the field when accounting for existing nets must be considered. Where pre-campaign coverage

  19. Planning long lasting insecticide treated net campaigns: should households’ existing nets be taken into account?

    Science.gov (United States)

    2013-01-01

    Background Mass distribution of long-lasting insecticide treated bed nets (LLINs) has led to large increases in LLIN coverage in many African countries. As LLIN ownership levels increase, planners of future mass distributions face the challenge of deciding whether to ignore the nets already owned by households or to take these into account and attempt to target individuals or households without nets. Taking existing nets into account would reduce commodity costs but require more sophisticated, and potentially more costly, distribution procedures. The decision may also have implications for the average age of nets in use and therefore on the maintenance of universal LLIN coverage over time. Methods A stochastic simulation model based on the NetCALC algorithm was used to determine the scenarios under which it would be cost saving to take existing nets into account, and the potential effects of doing so on the age profile of LLINs owned. The model accounted for variability in timing of distributions, concomitant use of continuous distribution systems, population growth, sampling error in pre-campaign coverage surveys, variable net ‘decay’ parameters and other factors including the feasibility and accuracy of identifying existing nets in the field. Results Results indicate that (i) where pre-campaign coverage is around 40% (of households owning at least 1 LLIN), accounting for existing nets in the campaign will have little effect on the mean age of the net population and (ii) even at pre-campaign coverage levels above 40%, an approach that reduces LLIN distribution requirements by taking existing nets into account may have only a small chance of being cost-saving overall, depending largely on the feasibility of identifying nets in the field. Based on existing literature the epidemiological implications of such a strategy is likely to vary by transmission setting, and the risks of leaving older nets in the field when accounting for existing nets must be considered

  20. Neural network optimization, components, and design selection

    Science.gov (United States)

    Weller, Scott W.

    1990-07-01

    Neural Networks are part of a revived technology which has received a lot of hype in recent years. As is apt to happen in any hyped technology, jargon and predictions make its assimilation and application difficult. Nevertheless, Neural Networks have found use in a number of areas, working on non-trivial and noncontrived problems. For example, one net has been trained to "read", translating English text into phoneme sequences. Other applications of Neural Networks include data base manipulation and the solving of muting and classification types of optimization problems. Neural Networks are constructed from neurons, which in electronics or software attempt to model but are not constrained by the real thing, i.e., neurons in our gray matter. Neurons are simple processing units connected to many other neurons over pathways which modify the incoming signals. A single synthetic neuron typically sums its weighted inputs, runs this sum through a non-linear function, and produces an output. In the brain, neurons are connected in a complex topology: in hardware/software the topology is typically much simpler, with neurons lying side by side, forming layers of neurons which connect to the layer of neurons which receive their outputs. This simplistic model is much easier to construct than the real thing, and yet can solve real problems. The information in a network, or its "memory", is completely contained in the weights on the connections from one neuron to another. Establishing these weights is called "training" the network. Some networks are trained by design -- once constructed no further learning takes place. Other types of networks require iterative training once wired up, but are not trainable once taught Still other types of networks can continue to learn after initial construction. The main benefit to using Neural Networks is their ability to work with conflicting or incomplete ("fuzzy") data sets. This ability and its usefulness will become evident in the following

  1. 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…

  2. RadNet Air Quality (Deployable) Data

    Data.gov (United States)

    U.S. Environmental Protection Agency — RadNet Deployable Monitoring is designed to collect radiological and meteorological information and data asset needed to establish the impact of radiation levels on...

  3. A Lightweight TwiddleNet Portal

    National Research Council Canada - National Science Library

    Rimikis, Antonios M

    2008-01-01

    TwiddleNet is a distributed architecture of personal servers that harnesses the power of the mobile devices, enabling real time information and file sharing of multiple data types from commercial-off-the-shelf platforms...

  4. Homology Groups of a Pipeline Petri Net

    Directory of Open Access Journals (Sweden)

    A. A. Husainov

    2013-01-01

    Full Text Available Petri net is said to be elementary if every place can contain no more than one token. In this paper, it is studied topological properties of the elementary Petri net for a pipeline consisting of n functional devices. If the work of the functional devices is considered continuous, we can come to some topological space of “intermediate” states. In the paper, it is calculated the homology groups of this topological space. By induction on n, using the Addition Sequence for homology groups of semicubical sets, it is proved that in dimension 0 and 1 the integer homology groups of these nets are equal to the group of integers, and in the remaining dimensions are zero. Directed homology groups are studied. A connection of these groups with deadlocks and newsletters is found. This helps to prove that all directed homology groups of the pipeline elementary Petri nets are zeroth.

  5. Net accumulation of the Greenland ice sheet

    DEFF Research Database (Denmark)

    Kiilsholm, Sissi; Christensen, Jens Hesselbjerg; Dethloff, Klaus

    2003-01-01

    improvement compared to the driving OAGCM. Estimates of the regional net balance are also better represented by the RCM. In the future climate the net balance for the Greenland Ice Sheet is reduced in all the simulation, but discrepancies between the amounts when based on ECHAM4/OPYC3 and HIRHAM are found....... In both scenarios, the estimated melt rates are larger in HIRHAM than in the driving model....

  6. Mastering AngularJD for .NET developers

    CERN Document Server

    Majid, Mohammad Wadood

    2015-01-01

    This book is envisioned for traditional developers and programmers who want to develop client-side applications using the AngularJS framework and ASP.NET Web API 2 with Visual Studio. .NET developers who have already built web applications or web services and who have a fundamental knowledge of HTML, JavaScript, and CSS and want to explore single-page applications will also find this guide useful. Basic knowledge of AngularJS would be helpful.

  7. .NET 4.5 parallel extensions

    CERN Document Server

    Freeman, Bryan

    2013-01-01

    This book contains practical recipes on everything you will need to create task-based parallel programs using C#, .NET 4.5, and Visual Studio. The book is packed with illustrated code examples to create scalable programs.This book is intended to help experienced C# developers write applications that leverage the power of modern multicore processors. It provides the necessary knowledge for an experienced C# developer to work with .NET parallelism APIs. Previous experience of writing multithreaded applications is not necessary.

  8. A Lightweight TwiddleNet Portal

    Science.gov (United States)

    2008-03-01

    designed to exploit the multiple networking modalities available in the current generation of smartphones . TwiddleNet enables well-organized and well...of Sonopia and will have a comprehensive review of the service in the coming weeks [12]. Twango, which was acquired by Nokia in July 2007, is an...EXPERIMENTATION As already mentioned the main purpose of this thesis is the development of a TwiddleNet portal running on a smartphone or a PDA, which can allow

  9. CCS - and its relationship to net theory

    DEFF Research Database (Denmark)

    Nielsen, Mogens

    1987-01-01

    In this paper we give a short introduction to Milner's Calculus for Communicating Systems - a paradigm for concurrent computation. We put special emphasis on the basic concepts and tools from the underlying "algebraic approach", and their relationship to the approach to concurrency within net...... theory. Furthermore, we provide an operational version of the language CCS with "true concurrency" in the sense of net theory, and a discussion of the possible use of such a marriage of the two theories of concurrency....

  10. Visual Studio 2013 and .NET 4.5 expert cookbook

    CERN Document Server

    Sur, Abhishek

    2014-01-01

    If you are a Visual Studio 2013 or .NET developer who would like to sharpen your existing skill set and adapt to new .NET technologies, this is the book for you. A basic understanding of .NET and C# is required.

  11. HANPP Collection: Global Patterns in Net Primary Productivity (NPP)

    Data.gov (United States)

    National Aeronautics and Space Administration — The Global Patterns in Net Primary Productivity (NPP) portion of the Human Appropriation of Net Primary Productivity (HANPP) Collection maps the net amount of solar...

  12. 1991 IEEE International Joint Conference on Neural Networks, Singapore, Nov. 18-21, 1991, Proceedings. Vols. 1-3

    Energy Technology Data Exchange (ETDEWEB)

    1991-01-01

    The present conference the application of neural networks to associative memories, neurorecognition, hybrid systems, supervised and unsupervised learning, image processing, neurophysiology, sensation and perception, electrical neurocomputers, optimization, robotics, machine vision, sensorimotor control systems, and neurodynamics. Attention is given to such topics as optimal associative mappings in recurrent networks, self-improving associative neural network models, fuzzy activation functions, adaptive pattern recognition with sparse associative networks, efficient question-answering in a hybrid system, the use of abstractions by neural networks, remote-sensing pattern classification, speech recognition with guided propagation, inverse-step competitive learning, and rotational quadratic function neural networks. Also discussed are electrical load forecasting, evolutionarily stable and unstable strategies, the capacity of recurrent networks, neural net vs control theory, perceptrons for image recognition, storage capacity of bidirectional associative memories, associative random optimization for control, automatic synthesis of digital neural architectures, self-learning robot vision, and the associative dynamics of chaotic neural networks.

  13. 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.

  14. ASP.NET web API build RESTful web applications and services on the .NET framework

    CERN Document Server

    Kanjilal, Joydip

    2013-01-01

    This book is a step-by-step, practical tutorial with a simple approach to help you build RESTful web applications and services on the .NET framework quickly and efficiently.This book is for ASP.NET web developers who want to explore REST-based services with C# 5. This book contains many real-world code examples with explanations whenever necessary. Some experience with C# and ASP.NET 4 is expected.

  15. Freeze-out conditions from net-proton and net-charge fluctuations at RHIC

    Energy Technology Data Exchange (ETDEWEB)

    Alba, Paolo; Alberico, Wanda [Department of Physics, Torino University and INFN, Sezione di Torino, via P. Giuria 1, 10125 Torino (Italy); Bellwied, Rene [Department of Physics, University of Houston, Houston, TX 77204 (United States); Bluhm, Marcus [Department of Physics, Torino University and INFN, Sezione di Torino, via P. Giuria 1, 10125 Torino (Italy); Department of Physics, North Carolina State University, Raleigh, NC 27695 (United States); Mantovani Sarti, Valentina [Department of Physics, Torino University and INFN, Sezione di Torino, via P. Giuria 1, 10125 Torino (Italy); Nahrgang, Marlene [Department of Physics, Duke University, Durham, NC 27708-0305 (United States); Frankfurt Institute for Advanced Studies (FIAS), Ruth-Moufang-Str. 1, 60438 Frankfurt am Main (Germany); Ratti, Claudia [Department of Physics, Torino University and INFN, Sezione di Torino, via P. Giuria 1, 10125 Torino (Italy)

    2014-11-10

    We calculate ratios of higher-order susceptibilities quantifying fluctuations in the number of net-protons and in the net-electric charge using the Hadron Resonance Gas (HRG) model. We take into account the effect of resonance decays, the kinematic acceptance cuts in rapidity, pseudo-rapidity and transverse momentum used in the experimental analysis, as well as a randomization of the isospin of nucleons in the hadronic phase. By comparing these results to the latest experimental data from the STAR Collaboration, we determine the freeze-out conditions from net-electric charge and net-proton distributions and discuss their consistency.

  16. 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.

  17. Modest net autotrophy in the oligotrophic ocean

    Science.gov (United States)

    Letscher, Robert T.; Moore, J. Keith

    2017-04-01

    The metabolic state of the oligotrophic subtropical ocean has long been debated. Net community production (NCP) represents the balance of autotrophic carbon fixation with heterotrophic respiration. Many in vitro NCP estimates based on oxygen incubation methods and the corresponding scaling relationships used to predict the ecosystem metabolic balance have suggested the ocean gyres to be net heterotrophic; however, all in situ NCP methods find net autotrophy. Reconciling net heterotrophy requires significant allochthonous inputs of organic carbon to the oligotrophic gyres to sustain a preponderance of respiration over in situ production. Here we use the first global ecosystem-ocean circulation model that contains representation of the three allochthonous carbon sources to the open ocean, to show that the five oligotrophic gyres exhibit modest net autotrophy throughout the seasonal cycle. Annually integrated rates of NCP vary in the range 1.5-2.2 mol O2 m-2 yr-1 across the five gyre systems; however, seasonal NCP rates are as low as 1 ± 0.5 mmol O2 m-2 d-1 for the North Atlantic. Volumetric NCP rates are heterotrophic below the 10% light level; however, they become net autotrophic when integrated over the euphotic zone. Observational uncertainties when measuring these modest autotrophic NCP rates as well as the metabolic diversity encountered across space and time complicate the scaling up of in vitro measurements to the ecosystem scale and may partially explain the previous reports of net heterotrophy. The oligotrophic ocean is autotrophic at present; however, it could shift toward seasonal heterotrophy in the future as rising temperatures stimulate respiration.

  18. SCYNet. Testing supersymmetric models at the LHC with neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Bechtle, Philip; Belkner, Sebastian; Hamer, Matthias [Universitaet Bonn, Bonn (Germany); Dercks, Daniel [Universitaet Hamburg, Hamburg (Germany); Keller, Tim; Kraemer, Michael; Sarrazin, Bjoern; Schuette-Engel, Jan; Tattersall, Jamie [RWTH Aachen University, Institute for Theoretical Particle Physics and Cosmology, Aachen (Germany)

    2017-10-15

    SCYNet (SUSY Calculating Yield Net) is a tool for testing supersymmetric models against LHC data. It uses neural network regression for a fast evaluation of the profile likelihood ratio. Two neural network approaches have been developed: one network has been trained using the parameters of the 11-dimensional phenomenological Minimal Supersymmetric Standard Model (pMSSM-11) as an input and evaluates the corresponding profile likelihood ratio within milliseconds. It can thus be used in global pMSSM-11 fits without time penalty. In the second approach, the neural network has been trained using model-independent signature-related objects, such as energies and particle multiplicities, which were estimated from the parameters of a given new physics model. (orig.)

  19. SCYNet: testing supersymmetric models at the LHC with neural networks

    Science.gov (United States)

    Bechtle, Philip; Belkner, Sebastian; Dercks, Daniel; Hamer, Matthias; Keller, Tim; Krämer, Michael; Sarrazin, Björn; Schütte-Engel, Jan; Tattersall, Jamie

    2017-10-01

    SCYNet (SUSY Calculating Yield Net) is a tool for testing supersymmetric models against LHC data. It uses neural network regression for a fast evaluation of the profile likelihood ratio. Two neural network approaches have been developed: one network has been trained using the parameters of the 11-dimensional phenomenological Minimal Supersymmetric Standard Model (pMSSM-11) as an input and evaluates the corresponding profile likelihood ratio within milliseconds. It can thus be used in global pMSSM-11 fits without time penalty. In the second approach, the neural network has been trained using model-independent signature-related objects, such as energies and particle multiplicities, which were estimated from the parameters of a given new physics model.

  20. GAN-Assisted Two-Stream Neural Network for High-Resolution Remote Sensing Image Classification

    Directory of Open Access Journals (Sweden)

    Yiting Tao

    2017-12-01

    Full Text Available Using deep learning to improve the capabilities of high-resolution satellite images has emerged recently as an important topic in automatic classification. Deep networks track hierarchical high-level features to identify objects; however, enhancing the classification accuracy from low-level features is often disregarded. We therefore proposed a two-stream deep-learning neural network strategy, with a main stream utilizing fine spatial-resolution panchromatic images to retain low-level information under a supervised residual network structure. An auxiliary line employed an unsupervised net to extract high-level abstract and discriminative features from multispectral images to supplement the spectral information in the main stream. Various feature extraction types from the neural network were selected and jointed in the novel net, as the combined high- and low-level features could provide a superior solution to image classification. In traditional convolutional neural networks, increased network depth might not influence the network performance perceptibly; however, we introduced a residual neural network to develop the expressive ability of the deeper net, increasing the role of net depth in feature extraction. To enhance feature robustness, we proposed a novel consolidation part in feature extraction. An adversarial net improved the feature extraction capabilities and aided digging the inherent and discriminative features from data, with increased extraction efficacy. Tests on satellite images indicated the high overall accuracy of our novel net, verifying that net depth or number of convolution kernels affected the classification capability. Various comparative tests proved the structural rationality for our two-stream structure.

  1. SOCIAL NET: A CASE STUDY OF THE UNIVERSITY NET OF POPULAR COOPERATIVES TECHNOLOGICAL INCUBATORS (PCTIS NET FROM THE INTERACTION AMONG THE INCUBATORS

    Directory of Open Access Journals (Sweden)

    Marília Matos Pereira Lopes

    2014-07-01

    Full Text Available The objective of this assignment was to identify if the University Net of Popular Cooperatives Technological Incubators (PCTIs Net is a social net. The research was an exploratory nature study with descriptive character, the technical procedure of the present research was the case study. The questionnaire was applied in 82% of the incubators belonging to the PCTIs Net, and interviews. The information acquired through the questionnaire was gathered and tabulated to compose the characterization of the net incubators and the social analyzer. With the Pajek program was created the social analyzer and the centralizing box. Was performed to compare the results with previous work Rennó et al. (2010 proposed that the same goal using a different approach. Ending the analysis guided by the characteristics of a social net, it was observed that the PCTIs Net is a social net, however it was emphasized that the existing communication is a point where the net needs to be fortified.

  2. Activation of PAD4 in NET formation

    Directory of Open Access Journals (Sweden)

    Amanda eRohrbach

    2012-11-01

    Full Text Available Peptidyl arginine deiminases, or PADs, convert arginine residues to the non-ribosomally encoded amino acid citrulline in a variety of protein substrates. PAD4 is expressed in granulocytes and is essential for the formation of neutrophil extracellular traps (NETs via PAD4-mediated histone citrullination. Citrullination of histones is thought to promote NET formation by inducing chromatin decondensation and facilitating the expulsion of chromosomal DNA that is coated with antimicrobial molecules. Numerous stimuli have been reported to lead to PAD4 activation and NET formation. However, how this signaling process proceeds and how PAD4 becomes activated in cells is largely unknown. Herein, we describe the various stimuli and signaling pathways that have been implicated in PAD4 activation and NET formation, including the role of reactive oxygen species generation. To provide a foundation for the above discussion, we first describe PAD4 structure and function, and how these studies led to the development of PAD-specific inhibitors. A comprehensive survey of the receptors and signaling pathways that regulate PAD4 activation will be important for our understanding of innate immunity, and the identification of signaling intermediates in PAD4 activation may also lead to the generation of pharmaceuticals to target NET-related pathogenesis.

  3. The net charge at interfaces between insulators

    Science.gov (United States)

    Bristowe, N. C.; Littlewood, P. B.; Artacho, Emilio

    2011-03-01

    The issue of the net charge at insulating oxide interfaces is briefly reviewed with the ambition of dispelling myths of such charges being affected by covalency and related charge density effects. For electrostatic analysis purposes, the net charge at such interfaces is defined by the counting of discrete electrons and core ion charges, and by the definition of the reference polarization of the separate, unperturbed bulk materials. The arguments are illustrated for the case of a thin film of LaAlO3 over SrTiO3 in the absence of free carriers, for which the net charge is exactly 0.5e per interface formula unit, if the polarization response in both materials is referred to zero bulk values. Further consequences of the argument are extracted for structural and chemical alterations of such interfaces, in which internal rearrangements are distinguished from extrinsic alterations (changes of stoichiometry, redox processes), only the latter affecting the interfacial net charge. The arguments are reviewed alongside the proposal of Stengel and Vanderbilt (2009 Phys. Rev. B 80 241103) of using formal polarization values instead of net interfacial charges, based on the interface theorem of Vanderbilt and King-Smith (1993 Phys. Rev. B 48 4442-55). Implications for non-centrosymmetric materials are discussed, as well as for interfaces for which the charge mismatch is an integer number of polarization quanta.

  4. Automating Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob L.; Hohimer, Ryan E.; White, Amanda M.

    2006-01-22

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  5. Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob; Hohimer, Ryan E.; White, Amanda M.

    2006-06-06

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  6. Development of net cage acoustic alarm system

    Science.gov (United States)

    Hong, Shih-Wei; Wei, Ruey-Chang

    2004-05-01

    In recent years, the fishery production has been drastically decreased in Taiwan, mainly due to overfishing and coast pollution; therefore, fishermen and corporations are encouraged by government to invest in ocean net cage aquaculture. However, the high-price fishes in the net cage are often coveted, so incidences of fish stealing and net cage breaking were found occasionally, which cause great economical loss. Security guards or a visual monitoring system has limited effect, especially in the night when these intrusions occur. This study is based on acoustic measure to build a net cage alarm system, which includes the sonobuoy and monitor station on land. The sonobuoy is a passive sonar that collects the sounds near the net cage and transmits the suspected signal to the monitor station. The signals are analyzed by the control program on the personal computer in the monitor station, and the alarms at different stages could be activated by the sound levels and durations of the analyzed data. To insure long hours of surveillance, a solar panel is applied to charge the battery, and a photodetector is used to activate the system.

  7. The NeuroDevNet vision.

    Science.gov (United States)

    Goldowitz, Dan; McArthur, Dawn

    2011-03-01

    The NeuroDevNet Network of Centres of Excellence has created the first trans-Canada effort devoted to the study of brain development from basic to clinical to societal perspectives. NeuroDevNet's vision is to accelerate efforts to (i) understand normal brain development; (ii) enhance our ability to make diagnoses of when normal development goes awry; and (iii) develop interventions to improve or prevent neurodevelopmental disorders. An early diagnosis coupled with the right therapies, The NeuroDevNet Network of Centres of Excellence has created the first trans-Canada effort devoted to the study of brain development from basic to clinical to societal perspectives. NeuroDevNet's vision is to accelerate efforts to (i) understand normal brain development; (ii) enhance our ability to make diagnoses of when normal development goes awry; and (iii) develop interventions to improve or prevent neurodevelopmental disorders. An early diagnosis coupled with the right therapies, Demonstration Projects. Funds were also allocated for an Opportunities Initiative. There is a wide of expertise amongst NeuroDevNet members. Researchers are supported by the management centre, three Platforms (Imaging; Genetics/ Epigenetics; Animal Models) and three Cores (Neuroethics; Neuroinformatics; Knowledge Translation). We emphasize multidisciplinary training of young researchers to advance the understanding of brain disorders that affect children. Copyright © 2011 Elsevier Inc. All rights reserved.

  8. The net charge at interfaces between insulators

    Energy Technology Data Exchange (ETDEWEB)

    Bristowe, N C; Littlewood, P B [Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, J J Thomson Avenue, Cambridge CB3 0HE (United Kingdom); Artacho, Emilio, E-mail: ncb30@cam.ac.uk [Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ (United Kingdom)

    2011-03-02

    The issue of the net charge at insulating oxide interfaces is briefly reviewed with the ambition of dispelling myths of such charges being affected by covalency and related charge density effects. For electrostatic analysis purposes, the net charge at such interfaces is defined by the counting of discrete electrons and core ion charges, and by the definition of the reference polarization of the separate, unperturbed bulk materials. The arguments are illustrated for the case of a thin film of LaAlO{sub 3} over SrTiO{sub 3} in the absence of free carriers, for which the net charge is exactly 0.5e per interface formula unit, if the polarization response in both materials is referred to zero bulk values. Further consequences of the argument are extracted for structural and chemical alterations of such interfaces, in which internal rearrangements are distinguished from extrinsic alterations (changes of stoichiometry, redox processes), only the latter affecting the interfacial net charge. The arguments are reviewed alongside the proposal of Stengel and Vanderbilt (2009 Phys. Rev. B 80 241103) of using formal polarization values instead of net interfacial charges, based on the interface theorem of Vanderbilt and King-Smith (1993 Phys. Rev. B 48 4442-55). Implications for non-centrosymmetric materials are discussed, as well as for interfaces for which the charge mismatch is an integer number of polarization quanta. (viewpoint)

  9. 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...

  10. [Neural codes for perception].

    Science.gov (United States)

    Romo, R; Salinas, E; Hernández, A; Zainos, A; Lemus, L; de Lafuente, V; Luna, R

    This article describes experiments designed to show the neural codes associated with the perception and processing of tactile information. The results of these experiments have shown the neural activity correlated with tactile perception. The neurones of the primary somatosensory cortex (S1) represent the physical attributes of tactile perception. We found that these representations correlated with tactile perception. By means of intracortical microstimulation we demonstrated the causal relationship between S1 activity and tactile perception. In the motor areas of the frontal lobe is to be found the connection between sensorial and motor representation whilst decisions are being taken. S1 generates neural representations of the somatosensory stimuli which seen to be sufficient for tactile perception. These neural representations are subsequently processed by central areas to S1 and seem useful in perception, memory and decision making.

  11. Neural Oscillators Programming Simplified

    Directory of Open Access Journals (Sweden)

    Patrick McDowell

    2012-01-01

    Full Text Available The neurological mechanism used for generating rhythmic patterns for functions such as swallowing, walking, and chewing has been modeled computationally by the neural oscillator. It has been widely studied by biologists to model various aspects of organisms and by computer scientists and robotics engineers as a method for controlling and coordinating the gaits of walking robots. Although there has been significant study in this area, it is difficult to find basic guidelines for programming neural oscillators. In this paper, the authors approach neural oscillators from a programmer’s point of view, providing background and examples for developing neural oscillators to generate rhythmic patterns that can be used in biological modeling and robotics applications.

  12. Association mapping utilizing diverse barley lines reveals net form net blotch seedling resistance/susceptibility loci

    Science.gov (United States)

    Pyrenophora teres f. teres is a necrotrophic fungal pathogen and the causal agent of the economically important foliar disease net form net blotch (NFNB) of barley. The deployment of effective and durable resistance against P. teres f. teres has been hindered by the complexity of quantitative resist...

  13. ConvNet-Based Localization of Anatomical Structures in 3-D Medical Images.

    Science.gov (United States)

    de Vos, Bob D; Wolterink, Jelmer M; de Jong, Pim A; Leiner, Tim; Viergever, Max A; Isgum, Ivana

    2017-07-01

    Localization of anatomical structures is a prerequisite for many tasks in a medical image analysis. We propose a method for automatic localization of one or more anatomical structures in 3-D medical images through detection of their presence in 2-D image slices using a convolutional neural network (ConvNet). A single ConvNet is trained to detect the presence of the anatomical structure of interest in axial, coronal, and sagittal slices extracted from a 3-D image. To allow the ConvNet to analyze slices of different sizes, spatial pyramid pooling is applied. After detection, 3-D bounding boxes are created by combining the output of the ConvNet in all slices. In the experiments, 200 chest CT, 100 cardiac CT angiography (CTA), and 100 abdomen CT scans were used. The heart, ascending aorta, aortic arch, and descending aorta were localized in chest CT scans, the left cardiac ventricle in cardiac CTA scans, and the liver in abdomen CT scans. Localization was evaluated using the distances between automatically and manually defined reference bounding box centroids and walls. The best results were achieved in the localization of structures with clearly defined boundaries (e.g., aortic arch) and the worst when the structure boundary was not clearly visible (e.g., liver). The method was more robust and accurate in localization multiple structures.

  14. Weakly Supervised PatchNets: Describing and Aggregating Local Patches for Scene Recognition.

    Science.gov (United States)

    Wang, Zhe; Wang, Limin; Wang, Yali; Zhang, Bowen; Qiao, Yu

    2017-02-09

    Traditional feature encoding scheme (e.g., Fisher vector) with local descriptors (e.g., SIFT) and recent convolutional neural networks (CNNs) are two classes of successful methods for image recognition. In this paper, we propose a hybrid representation, which leverages the discriminative capacity of CNNs and the simplicity of descriptor encoding schema for image recognition, with a focus on scene recognition. To this end, we make three main contributions from the following aspects. First, we propose a patch-level and end-to-end architecture to model the appearance of local patches, called PatchNet. PatchNet is essentially a customized network trained in a weakly supervised manner, which uses the image-level supervision to guide the patch-level feature extraction. Second, we present a hybrid visual representation, called VSAD, by utilizing the robust feature representations of PatchNet to describe local patches and exploiting the semantic probabilities of PatchNet to aggregate these local patches into a global representation. Third, based on the proposed VSAD representation, we propose a new state-of-the-art scene recognition approach, which achieves an excellent performance on two standard benchmarks: MIT Indoor67 (86.2%) and SUN397 (73.0%).

  15. Towards Self-Managed Executable Petri Nets

    DEFF Research Database (Denmark)

    Hansen, Klaus Marius; Zhang, Weishan; Ingstrup, Mads

    2008-01-01

    An issue in self-managed systems is that different abstractions and programming models are used on different architectural layers, leading to systems that are harder to build and understand. To alleviate this, we introduce a self-management approach which combines high-level Petri nets...... with the capability of distributed communication among nets. Organized in a three-layer goal management, change management, and component control architecture this allows for self-management in distributed systems. We validate the approach through the Flamenco/CPN middleware that allows for self-management of service......-oriented pervasive computing systems through the runtime interpretation of colored Petri nets. The current work focuses on the change management and component control layers....

  16. Professional ASP.NET MVC 2

    CERN Document Server

    Galloway, Jon; Haack, Phil

    2010-01-01

    Top-selling MVC book from a top team at Microsoft—now fully updated!. ASP.NET MVC 2.0 is now available and shipping with Visual Studio 2010 and .NET 4. A new update to Microsoft's Model-View-Controller technologies, MVC 2.0 enables developers to build dynamic, data-driven Web sites. This in-depth book shows you step-by-step how to use MVC 2.0. You'll learn both the theory behind MVC 2.0, as well as walk through practical tutorials, where you'll create a real-world application. Topics include transitioning from ASP.NET development, as well as an overview of related tools and technologies, inclu

  17. .net core application lifecycle on Openshift

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    # .net core application lifecycle on Openshift I will show an example of a lifecycle of an OpenShift application with an emphasis on the continuous integration and deployment. The application compatible with [.net Standard](https://docs.microsoft.com/en-us/dotnet/standard/net-standard) can be easily deployed on OpenShift using [Source2Image](https://docs.openshift.com/enterprise/3.0/architecture/core_concepts/builds_and_image_streams.html#source-build) functionality, which doesn't require developers to maintain docker images of the application. I will also present how to efficiently integrate this feature into GitLab pipelines with an automated deployment of the "review" environment, as one its parts.

  18. Application and Theory of Petri Nets

    DEFF Research Database (Denmark)

    This volume contains the proceedings of the 13th International Conference onApplication and Theory of Petri Nets, held in Sheffield, England, in June 1992. The aim of the Petri net conferences is to create a forum for discussing progress in the application and theory of Petri nets. Typically......, the conferences have 150-200 participants, one third of these coming from industry and the rest from universities and research institutions. The 1992 conference was organized by the School of Computing and Management Sciences at Sheffield City Polytechnic, England. The volume contains twoinvited papers, by G....... Balbo and W. Reisig, 18 submitted papers, and seven project papers. The submitted papers and project presentations were selectedby the programme committee and a panel of referees from a large number of submissions....

  19. Chapter 17: Estimating Net Savings: Common Practices

    Energy Technology Data Exchange (ETDEWEB)

    Violette, D. M.; Rathbun, P.

    2014-09-01

    This chapter focuses on the methods used to estimate net energy savings in evaluation, measurement, and verification (EM&V) studies for energy efficiency (EE) programs. The chapter provides a definition of net savings, which remains an unsettled topic both within the EE evaluation community and across the broader public policy evaluation community, particularly in the context of attribution of savings to particular program. The chapter differs from the measure-specific Uniform Methods Project (UMP) chapters in both its approach and work product. Unlike other UMP resources that provide recommended protocols for determining gross energy savings, this chapter describes and compares the current industry practices for determining net energy savings, but does not prescribe particular methods.

  20. 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.

  1. 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.

  2. Neural network applications

    Science.gov (United States)

    Padgett, Mary L.; Desai, Utpal; Roppel, T.A.; White, Charles R.

    1993-01-01

    A design procedure is suggested for neural networks which accommodates the inclusion of such knowledge-based systems techniques as fuzzy logic and pairwise comparisons. The use of these procedures in the design of applications combines qualitative and quantitative factors with empirical data to yield a model with justifiable design and parameter selection procedures. The procedure is especially relevant to areas of back-propagation neural network design which are highly responsive to the use of precisely recorded expert knowledge.

  3. NEMEFO: NEural MEteorological FOrecast

    Energy Technology Data Exchange (ETDEWEB)

    Pasero, E.; Moniaci, W.; Meindl, T.; Montuori, A. [Polytechnic of Turin (Italy). Dept. of Electronics

    2004-07-01

    Artificial Neural Systems are a well-known technique used to classify and recognize objects. Introducing the time dimension they can be used to forecast numerical series. NEMEFO is a ''nowcasting'' tool, which uses both statistical and neural systems to forecast meteorological data in a restricted area close to a meteorological weather station in a short time range (3 hours). Ice, fog, rain are typical events which can be anticipated by NEMEFO. (orig.)

  4. Adaptive Near-Optimal Multiuser Detection Using a Stochastic and Hysteretic Hopfield Net Receiver

    Directory of Open Access Journals (Sweden)

    Gábor Jeney

    2003-01-01

    Full Text Available This paper proposes a novel adaptive MUD algorithm for a wide variety (practically any kind of interference limited systems, for example, code division multiple access (CDMA. The algorithm is based on recently developed neural network techniques and can perform near optimal detection in the case of unknown channel characteristics. The proposed algorithm consists of two main blocks; one estimates the symbols sent by the transmitters, the other identifies each channel of the corresponding communication links. The estimation of symbols is carried out either by a stochastic Hopfield net (SHN or by a hysteretic neural network (HyNN or both. The channel identification is based on either the self-organizing feature map (SOM or the learning vector quantization (LVQ. The combination of these two blocks yields a powerful real-time detector with near optimal performance. The performance is analyzed by extensive simulations.

  5. The transition from No Net Loss to a Net Gain of biodiversity is far from trivial

    DEFF Research Database (Denmark)

    Bull, Joseph William; Brownlie, S.

    2017-01-01

    The objectives of No Net Loss and Net Gain have emerged as key principles in conservation policy. Both give rise to mechanisms by which certain unavoidable biodiversity losses associated with development are quantified, and compensated with comparable gains (e.g. habitat restoration). The former...... seeks a neutral outcome for biodiversity after losses and gains are accounted for, and the latter seeks an improved outcome. Policy-makers often assume that the transition from one to the other is straightforward and essentially a question of the amount of compensation provided. Consequently, companies...... increasingly favour Net Gain type commitments, and financial institutions make lending conditional on either objective, depending on the habitat involved. We contend, however, that achieving Net Gain is fundamentally different to achieving No Net Loss, and moving from one to the other is less trivial than...

  6. NetPhosYeast: prediction of protein phosphorylation sites in yeast

    DEFF Research Database (Denmark)

    Ingrell, C.R.; Miller, Martin Lee; Jensen, O.N.

    2007-01-01

    We here present a neural network-based method for the prediction of protein phosphorylation sites in yeast-an important model organism for basic research. Existing protein phosphorylation site predictors are primarily based on mammalian data and show reduced sensitivity on yeast phosphorylation...... sites compared to those in humans, suggesting the need for an yeast-specific phosphorylation site predictor. NetPhosYeast achieves a correlation coefficient close to 0.75 with a sensitivity of 0.84 and specificity of 0.90 and outperforms existing predictors in the identification of phosphorylation sites...

  7. Character Recognition Using Genetically Trained Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Diniz, C.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1998-10-01

    Computationally intelligent recognition of characters and symbols addresses a wide range of applications including foreign language translation and chemical formula identification. The combination of intelligent learning and optimization algorithms with layered neural structures offers powerful techniques for character recognition. These techniques were originally developed by Sandia National Laboratories for pattern and spectral analysis; however, their ability to optimize vast amounts of data make them ideal for character recognition. An adaptation of the Neural Network Designer soflsvare allows the user to create a neural network (NN_) trained by a genetic algorithm (GA) that correctly identifies multiple distinct characters. The initial successfid recognition of standard capital letters can be expanded to include chemical and mathematical symbols and alphabets of foreign languages, especially Arabic and Chinese. The FIN model constructed for this project uses a three layer feed-forward architecture. To facilitate the input of characters and symbols, a graphic user interface (GUI) has been developed to convert the traditional representation of each character or symbol to a bitmap. The 8 x 8 bitmap representations used for these tests are mapped onto the input nodes of the feed-forward neural network (FFNN) in a one-to-one correspondence. The input nodes feed forward into a hidden layer, and the hidden layer feeds into five output nodes correlated to possible character outcomes. During the training period the GA optimizes the weights of the NN until it can successfully recognize distinct characters. Systematic deviations from the base design test the network's range of applicability. Increasing capacity, the number of letters to be recognized, requires a nonlinear increase in the number of hidden layer neurodes. Optimal character recognition performance necessitates a minimum threshold for the number of cases when genetically training the net. And, the

  8. APIs de seguridad en .NET Framework

    OpenAIRE

    Domínguez Ruiz, Abel

    2014-01-01

    Este trabajo hace un estudio de algunas de las herramientas de seguridad disponibles en .Net Framework así como la forma de usarlas en un desarrollo web bajo la metodología de desarrollo de ASP.NET siguiendo el modelo Vista-Controlador y usando como entorno de desarrollo Visual Studio. Además de repasar las herramientas disponibles y la forma de uso se ha desarrollado también una aplicación de ejemplo: ItemCoteca-Web; en la que se demuestra cómo resolver el registro de usuarios, la autenticac...

  9. An ECNO semantics for Petri nets

    DEFF Research Database (Denmark)

    Kindler, Ekkart

    2012-01-01

    The Event Coordination Notation (ECNO) allows modelling the behaviour of software on top of structural software models - and to generate program code from these models fully automatically. ECNO distinguishes between the local behaviour of elements (objects) and the global behaviour, which denes t...... work. In this paper, we will show that the ECNO, in turn, can be used for modelling the behaviour of Petri nets in a simple and concise way. What is more, we will show that the ECNO semantics of Place/Transition Systems can easily be extended to so-called signal-event nets....

  10. Introducing NET 40 With Visual Studio 2010

    CERN Document Server

    Mackey, A

    2010-01-01

    Microsoft is introducing a large number of changes to the way that the .NET Framework operates. Familiar technologies are being altered, best practices replaced, and developer methodologies adjusted. Many developers find it hard to keep up with the pace of change across .NET's ever-widening array of technologies. You may know what's happening in C#, but how about the Azure cloud? How is that going to affect your work? What are the limitations of the new pLINQ syntax? What you need is a roadmap. A guide to help you see the innovations that matter and to give you a head start on the opportunitie

  11. Deep Belief Nets for Topic Modeling

    DEFF Research Database (Denmark)

    Maaløe, Lars; Arngren, Morten; Winther, Ole

    2015-01-01

    -formative. In this paper we describe large-scale content based collaborative filtering for digital publishing. To solve the digital publishing recommender problem we compare two approaches: latent Dirichlet allocation (LDA) and deep be-lief nets (DBN) that both find low-dimensional latent representations for documents....... Efficient retrieval can be carried out in the latent representation. We work both on public benchmarks and digital media content provided by Issuu, an on-line publishing platform. This article also comes with a newly developed deep belief nets toolbox for topic modeling tailored towards performance...

  12. Performance Analysis Using Coloured Petri Nets

    DEFF Research Database (Denmark)

    Wells, Lisa Marie

    2002-01-01

    This paper provides an overview of improved facilities for performance analysis using coloured Petri nets. Coloured Petri nets is a formal method that is well suited for modeling and analyzing large and complex systems. The paper describes steps that have been taken to make a distinction between...... modeling the behavior of a system and observing the behavior of a model. Performance-related facilities are discussed, including facilities for collecting data, running multiple simulations, generating statistically reliable simulation output, and comparing alternative system configurations....

  13. Net Gain: A New Method for Preventing Malaria Deaths | CRDI ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    A finely spun net could prevent as many as one-third of all child deaths in Africa, reports IDRC's new publication, Net Gain. Studies conducted in Gambia, Ghana, and Kenya show that the insecticide-treated mosquito net reduced the mortality rate of children under 5 years of age by up to 63 percent. Net Gain reviews and ...

  14. Neural estimation of kinetic rate constants from dynamic PET-scans

    DEFF Research Database (Denmark)

    Fog, Torben L.; Nielsen, Lars Hupfeldt; Hansen, Lars Kai

    1994-01-01

    A feedforward neural net is trained to invert a simple three compartment model describing the tracer kinetics involved in the metabolism of [18F]fluorodeoxyglucose in the human brain. The network can estimate rate constants from positron emission tomography sequences and is about 50 times faster...... than direct fitting of rate constants using the parametrized transients of the compartment model...

  15. Robust Total Retina Thickness Segmentation in Optical Coherence Tomography Images using Convolutional Neural Networks

    NARCIS (Netherlands)

    Venhuizen, F.G.; Ginneken, B. van; Liefers, B.J.; Grinsven, M.J.J.P. van; Fauser, S.; Hoyng, C.B.; Theelen, T.; Sanchez, C.I.

    2017-01-01

    We developed a fully automated system using a convolutional neural network (CNN) for total retina segmentation in optical coherence tomography (OCT) that is robust to the presence of severe retinal pathology. A generalized U-net network architecture was introduced to include the large context needed

  16. Robust total retina thickness segmentation in optical coherence tomography images using convolutional neural networks

    NARCIS (Netherlands)

    Venhuizen, F.G.; Ginneken, B. van; Liefers, B.J.; Grinsven, M.J.J.P. van; Fauser, S.; Hoyng, C.B.; Theelen, T.; Sanchez, C.I.

    2017-01-01

    We developed a fully automated system using a convolutional neural network (CNN) for total retina segmentation in optical coherence tomography (OCT) that is robust to the presence of severe retinal pathology. A generalized U-net network architecture was introduced to include the large context needed

  17. Mars MetNet Mission Status

    Science.gov (United States)

    Harri, Ari-Matti; Aleksashkin, Sergei; Arruego, Ignacio; Schmidt, Walter; Genzer, Maria; Vazquez, Luis; Haukka, Harri

    2015-04-01

    New kind of planetary exploration mission for Mars is under development in collaboration between the Finnish Meteorological Institute (FMI), Lavochkin Association (LA), Space Research Institute (IKI) and Institutio Nacional de Tecnica Aerospacial (INTA). The Mars MetNet mission is based on a new semi-hard landing vehicle called MetNet Lander (MNL). The scientific payload of the Mars MetNet Precursor [1] mission is divided into three categories: Atmospheric instruments, Optical devices and Composition and structure devices. Each of the payload instruments will provide significant insights in to the Martian atmospheric behavior. The key technologies of the MetNet Lander have been qualified and the electrical qualification model (EQM) of the payload bay has been built and successfully tested. 1. MetNet Lander The MetNet landing vehicles are using an inflatable entry and descent system instead of rigid heat shields and parachutes as earlier semi-hard landing devices have used. This way the ratio of the payload mass to the overall mass is optimized. The landing impact will burrow the payload container into the Martian soil providing a more favorable thermal environment for the electronics and a suitable orientation of the telescopic boom with external sensors and the radio link antenna. It is planned to deploy several tens of MNLs on the Martian surface operating at least partly at the same time to allow meteorological network science. 2. Scientific Payload The payload of the two MNL precursor models includes the following instruments: Atmospheric instruments: 1. MetBaro Pressure device 2. MetHumi Humidity device 3. MetTemp Temperature sensors Optical devices: 1. PanCam Panoramic 2. MetSIS Solar irradiance sensor with OWLS optical wireless system for data transfer 3. DS Dust sensor The descent processes dynamic properties are monitored by a special 3-axis accelerometer combined with a 3-axis gyrometer. The data will be sent via auxiliary beacon antenna throughout the

  18. Markets, voucher subsidies and free nets combine to achieve high bed net coverage in rural Tanzania

    Directory of Open Access Journals (Sweden)

    Gerrets Rene PM

    2008-06-01

    Full Text Available Abstract Background Tanzania has a well-developed network of commercial ITN retailers. In 2004, the government introduced a voucher subsidy for pregnant women and, in mid 2005, helped distribute free nets to under-fives in small number of districts, including Rufiji on the southern coast, during a child health campaign. Contributions of these multiple insecticide-treated net delivery strategies existing at the same time and place to coverage in a poor rural community were assessed. Methods Cross-sectional household survey in 6,331 members of randomly selected 1,752 households of 31 rural villages of Demographic Surveillance System in Rufiji district, Southern Tanzania was conducted in 2006. A questionnaire was administered to every consenting respondent about net use, treatment status and delivery mechanism. Findings Net use was 62.7% overall, 87.2% amongst infants (0 to1 year, 81.8% amongst young children (>1 to 5 years, 54.5% amongst older children (6 to 15 years and 59.6% amongst adults (>15 years. 30.2% of all nets had been treated six months prior to interview. The biggest source of nets used by infants was purchase from the private sector with a voucher subsidy (41.8%. Half of nets used by young children (50.0% and over a third of those used by older children (37.2% were obtained free of charge through the vaccination campaign. The largest source of nets amongst the population overall was commercial purchase (45.1% use and was the primary means for protecting adults (60.2% use. All delivery mechanisms, especially sale of nets at full market price, under-served the poorest but no difference in equity was observed between voucher-subsidized and freely distributed nets. Conclusion All three delivery strategies enabled a poor rural community to achieve net coverage high enough to yield both personal and community level protection for the entire population. Each of them reached their relevant target group and free nets only temporarily

  19. EVo: Net Shape RTM Production Line

    OpenAIRE

    Sven Torstrick; Felix Kruse; Martin Wiedemann

    2016-01-01

    EVo research platform is operated by the Center for Lightweight-Production-Technology of the German Aerospace Center in Stade. Its objective is technology demonstration of a fully automated RTM (Resin Transfer Molding) production line for composite parts in large quantities. Process steps include cutting and ply handling, draping, stacking, hot-forming, preform-trimming to net shape, resin injection, curing and demolding.

  20. The Lotto and Expected Net Revenue

    OpenAIRE

    Scoggins, John F.

    1995-01-01

    A multiperiod model (based on sales from the Florida Lotto) is used to estimate revenue and probability that the grand prize will roll over. Results indicate that allocating a greater percentage of ticket sales to the grand prize increases net revenue.

  1. Integrating phenotype ontologies with PhenomeNET

    KAUST Repository

    Rodriguez-Garcia, Miguel Angel

    2017-12-19

    Background Integration and analysis of phenotype data from humans and model organisms is a key challenge in building our understanding of normal biology and pathophysiology. However, the range of phenotypes and anatomical details being captured in clinical and model organism databases presents complex problems when attempting to match classes across species and across phenotypes as diverse as behaviour and neoplasia. We have previously developed PhenomeNET, a system for disease gene prioritization that includes as one of its components an ontology designed to integrate phenotype ontologies. While not applicable to matching arbitrary ontologies, PhenomeNET can be used to identify related phenotypes in different species, including human, mouse, zebrafish, nematode worm, fruit fly, and yeast. Results Here, we apply the PhenomeNET to identify related classes from two phenotype and two disease ontologies using automated reasoning. We demonstrate that we can identify a large number of mappings, some of which require automated reasoning and cannot easily be identified through lexical approaches alone. Combining automated reasoning with lexical matching further improves results in aligning ontologies. Conclusions PhenomeNET can be used to align and integrate phenotype ontologies. The results can be utilized for biomedical analyses in which phenomena observed in model organisms are used to identify causative genes and mutations underlying human disease.

  2. Soundness of Timed-Arc Workflow Nets

    DEFF Research Database (Denmark)

    Mateo, Jose Antonio; Srba, Jiri; Sørensen, Mathias Grund

    2014-01-01

    Analysis of workflow processes with quantitative aspects like timing is of interest in numerous time-critical applications. We suggest a workflow model based on timed-arc Petri nets and study the foundational problems of soundness and strong (time-bounded) soundness. We explore the decidability o...

  3. Dahl: Time ripe for DHS net assessment

    OpenAIRE

    2016-01-01

    Article review Center for Homeland Defense and Security instructor Erik Dahl urges the Department of Homeland Security to follow a practice of its military counterparts and establish an Office of Net Assessment that would gauge future threats and the nation's ability to mitigate them.

  4. Regular Event Structures and Finite Petri Nets

    DEFF Research Database (Denmark)

    Nielsen, M.; Thiagarajan, P.S.

    2002-01-01

    We present the notion of regular event structures and conjecture that they correspond exactly to finite 1-safe Petri nets. We show that the conjecture holds for the conflict-free case. Even in this restricted setting, the proof is non-trivial and involves a natural subclass of regular event...

  5. Net escapement of Antartic krill in trawls

    DEFF Research Database (Denmark)

    Krafft, B.A.; Krag, Ludvig Ahm; Herrmann, Bent

    This document describes the aims and methodology of a three year project (commenced in 2012) entitled Net Escapement of Antarctic krill in Trawls (NEAT). The study will include a morphology based mathematical modeling (FISHSELECT) of different sex and maturity groups of Antarctic krill (Euphausia...

  6. BioNet Digital Communications Framework

    Science.gov (United States)

    Gifford, Kevin; Kuzminsky, Sebastian; Williams, Shea

    2010-01-01

    BioNet v2 is a peer-to-peer middleware that enables digital communication devices to talk to each other. It provides a software development framework, standardized application, network-transparent device integration services, a flexible messaging model, and network communications for distributed applications. BioNet is an implementation of the Constellation Program Command, Control, Communications and Information (C3I) Interoperability specification, given in CxP 70022-01. The system architecture provides the necessary infrastructure for the integration of heterogeneous wired and wireless sensing and control devices into a unified data system with a standardized application interface, providing plug-and-play operation for hardware and software systems. BioNet v2 features a naming schema for mobility and coarse-grained localization information, data normalization within a network-transparent device driver framework, enabling of network communications to non-IP devices, and fine-grained application control of data subscription band width usage. BioNet directly integrates Disruption Tolerant Networking (DTN) as a communications technology, enabling networked communications with assets that are only intermittently connected including orbiting relay satellites and planetary rover vehicles.

  7. Programming C# Building NET Applications with C#

    CERN Document Server

    Liberty, Jesse

    2009-01-01

    Programming C#, the top-selling book on Microsoft's high-performance C# programming language, is now in its fourth edition. Aimed at experienced programmers and web developers, this comprehensive guide focuses on the features and programming patterns that are unique to C#, and fundamental to the programming of web services and web applications on Microsoft's .NET platform.

  8. NetBench. Automated Network Performance Testing

    CERN Document Server

    Cadeddu, Mattia

    2016-01-01

    In order to evaluate the operation of high performance routers, CERN has developed the NetBench software to run benchmarking tests by injecting various traffic patterns and observing the network devices behaviour in real-time. The tool features a modular design with a Python based console used to inject traffic and collect the results in a database, and a web user

  9. Petri Nets as Models of Linear Logic

    DEFF Research Database (Denmark)

    Engberg, Uffe Henrik; Winskel, Glynn

    1990-01-01

    The chief purpose of this paper is to appraise the feasibility of Girad's linear logic as a specification language for parallel processes. To this end we propose an interpretation of linear logic in Petri nets, with respect to which we investigate the expressive power of the logic...

  10. OK-Net Arable online knowledge platform

    DEFF Research Database (Denmark)

    Rasmussen, Ilse Ankjær; Jensen, Allan Leck; Jørgensen, Margit Styrbæk

    2017-01-01

    The complexity of organic farming requires farmers to have a very high level of knowledge and skills, but exchange on organic farming techniques remains limited. In order to increase productivity and quality in organic arable cropping in Europe, the thematic network OK-Net Arable under Horizon 20...

  11. Musings on Sketches, Artists, and Mosquito Nets

    Centers for Disease Control (CDC) Podcasts

    2014-09-23

    Byron Breedlove reads his essay Musings on Sketches, Artists, and Mosquito Nets about the art of James Whistler and the transmission of vector borne diseases.  Created: 9/23/2014 by National Center for Emerging and Zoonotic Infectious Diseases (NCEZID).   Date Released: 10/20/2014.

  12. Educating College Students of the Net Generation

    Science.gov (United States)

    Worley, Karen

    2011-01-01

    Faculty and administrators of higher education today face a challenge with their student populations, many of whom are part of what is known as the net generation. As students become more technologically advanced, faculty must be technologically ready to meet the needs of students. Many college faculty and administrators are from earlier…

  13. State Space Methods for Timed Petri Nets

    DEFF Research Database (Denmark)

    Christensen, Søren; Jensen, Kurt; Mailund, Thomas

    2001-01-01

    We present two recently developed state space methods for timed Petri nets. The two methods reconciles state space methods and time concepts based on the introduction of a global clock and associating time stamps to tokens. The first method is based on an equivalence relation on states which makes...

  14. Average Costs versus Net Present Value

    NARCIS (Netherlands)

    E.A. van der Laan (Erwin); R.H. Teunter (Ruud)

    2000-01-01

    textabstractWhile the net present value (NPV) approach is widely accepted as the right framework for studying production and inventory control systems, average cost (AC) models are more widely used. For the well known EOQ model it can be verified that (under certain conditions) the AC approach gives

  15. PatterNet: a system to learn compact physical design pattern representations for pattern-based analytics

    Science.gov (United States)

    Lutich, Andrey

    2017-07-01

    This research considers the problem of generating compact vector representations of physical design patterns for analytics purposes in semiconductor patterning domain. PatterNet uses a deep artificial neural network to learn mapping of physical design patterns to a compact Euclidean hyperspace. Distances among mapped patterns in this space correspond to dissimilarities among patterns defined at the time of the network training. Once the mapping network has been trained, PatterNet embeddings can be used as feature vectors with standard machine learning algorithms, and pattern search, comparison, and clustering become trivial problems. PatterNet is inspired by the concepts developed within the framework of generative adversarial networks as well as the FaceNet. Our method facilitates a deep neural network (DNN) to learn directly the compact representation by supplying it with pairs of design patterns and dissimilarity among these patterns defined by a user. In the simplest case, the dissimilarity is represented by an area of the XOR of two patterns. Important to realize that our PatterNet approach is very different to the methods developed for deep learning on image data. In contrast to "conventional" pictures, the patterns in the CAD world are the lists of polygon vertex coordinates. The method solely relies on the promise of deep learning to discover internal structure of the incoming data and learn its hierarchical representations. Artificial intelligence arising from the combination of PatterNet and clustering analysis very precisely follows intuition of patterning/optical proximity correction experts paving the way toward human-like and human-friendly engineering tools.

  16. Conducting Polymers for Neural Prosthetic and Neural Interface Applications

    Science.gov (United States)

    2015-01-01

    Neural interfacing devices are an artificial mechanism for restoring or supplementing the function of the nervous system lost as a result of injury or disease. Conducting polymers (CPs) are gaining significant attention due to their capacity to meet the performance criteria of a number of neuronal therapies including recording and stimulating neural activity, the regeneration of neural tissue and the delivery of bioactive molecules for mediating device-tissue interactions. CPs form a flexible platform technology that enables the development of tailored materials for a range of neuronal diagnostic and treatment therapies. In this review the application of CPs for neural prostheses and other neural interfacing devices are discussed, with a specific focus on neural recording, neural stimulation, neural regeneration, and therapeutic drug delivery. PMID:26414302

  17. Modeling safety requirements of an FMS using Petri-nets

    Science.gov (United States)

    Hanna, Moheb M.; Buck, A. A.; Smith, R.

    1993-08-01

    This paper is concerned with the modelling of safety requirements using Petri nets as a tool to model and simulate a Flexible Manufacturing System (FMS). The FMS cell described comprises a pick and place robot, a multi-head drilling machine together with a vision system and illustrates how the hierarchical structure of Petri nets can be used to ensure that all fail- safe requirements are satisfied; block diagrams together with fully detailed example Petri nets are given. The work demonstrates the use of cell and robot control Petro nets together with robot subnets for the x, y and z axes and associated output nets; the control and output nets are linked together with a safety net. Individual machines are linked with the control and safety nets of an FMS at cell level. The paper also illustrates how a Petri net can act as a decision maker during image inspection and identifies the unsafe conditions that can arise within an FMS.

  18. A new variant of Petri net controlled grammars

    Science.gov (United States)

    Jan, Nurhidaya Mohamad; Turaev, Sherzod; Fong, Wan Heng; Sarmin, Nor Haniza

    2015-10-01

    A Petri net controlled grammar is a Petri net with respect to a context-free grammar where the successful derivations of the grammar can be simulated using the occurrence sequences of the net. In this paper, we introduce a new variant of Petri net controlled grammars, called a place-labeled Petri net controlled grammar, which is a context-free grammar equipped with a Petri net and a function which maps places of the net to productions of the grammar. The language consists of all terminal strings that can be obtained by parallelly applying multisets of the rules which are the images of the sets of the input places of transitions in a successful occurrence sequence of the Petri net. We study the effect of the different labeling strategies to the computational power and establish lower and upper bounds for the generative capacity of place-labeled Petri net controlled grammars.

  19. Hyperbolic Hopfield neural networks.

    Science.gov (United States)

    Kobayashi, M

    2013-02-01

    In recent years, several neural networks using Clifford algebra have been studied. Clifford algebra is also called geometric algebra. Complex-valued Hopfield neural networks (CHNNs) are the most popular neural networks using Clifford algebra. The aim of this brief is to construct hyperbolic HNNs (HHNNs) as an analog of CHNNs. Hyperbolic algebra is a Clifford algebra based on Lorentzian geometry. In this brief, a hyperbolic neuron is defined in a manner analogous to a phasor neuron, which is a typical complex-valued neuron model. HHNNs share common concepts with CHNNs, such as the angle and energy. However, HHNNs and CHNNs are different in several aspects. The states of hyperbolic neurons do not form a circle, and, therefore, the start and end states are not identical. In the quantized version, unlike complex-valued neurons, hyperbolic neurons have an infinite number of states.

  20. Neural Semantic Encoders.

    Science.gov (United States)

    Munkhdalai, Tsendsuren; Yu, Hong

    2017-04-01

    We present a memory augmented neural network for natural language understanding: Neural Semantic Encoders. NSE is equipped with a novel memory update rule and has a variable sized encoding memory that evolves over time and maintains the understanding of input sequences through read, compose and write operations. NSE can also access multiple and shared memories. In this paper, we demonstrated the effectiveness and the flexibility of NSE on five different natural language tasks: natural language inference, question answering, sentence classification, document sentiment analysis and machine translation where NSE achieved state-of-the-art performance when evaluated on publically available benchmarks. For example, our shared-memory model showed an encouraging result on neural machine translation, improving an attention-based baseline by approximately 1.0 BLEU.

  1. One-step electro-spinning/netting technique for controllably preparing polyurethane nano-fiber/net.

    Science.gov (United States)

    Hu, Juanping; Wang, Xianfeng; Ding, Bin; Lin, Jinyou; Yu, Jianyong; Sun, Gang

    2011-11-01

    Electro-spinning/netting (ESN) as a cutting-edge technique evokes much interest because of its ability in the one-step preparation of versatile nano-fiber/net (NFN) membranes. Here, a controllable fabrication of polyurethane (PU) NFN membranes with attractive structures, consisting of common electrospun nanofibers and two-dimensional (2D) soap bubble-like structured nano-nets via an ESN process is reported. The unique nanoscaled NFN architecture can be finely controlled by regulating the solution properties and several ESN process parameters. The versatile PU nano-nets comprising interlinked nanowires with ultrathin diameters (5-40 nm) mean that the NFN structured membranes possess several excellent characteristics, such as an extremely large specific surface area, high porosity and large stacking density, which would be particularly useful for applications in ultrafiltration, special protective clothing, ultrasensitive sensors, catalyst support and so on. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Energy Dependence of Moments of Net-Proton, Net-Kaon, and Net-Charge Multiplicity Distributions at STAR

    CERN Document Server

    ,

    2016-01-01

    One of the main goals of the RHIC Beam Energy Scan (BES) program is to study the QCD phase structure, which includes the search for the QCD critical point, over a wide range of chemical potential. Theoretical calculations predict that fluctuations of conserved quantities, such as baryon number (B), charge (Q), and strangeness (S), are sensitive to the correlation length of the dynamical system. Experimentally, higher moments of multiplicity distributions have been utilized to search for the QCD critical point in heavy-ion collisions. In this paper, we report recent efficiency-corrected cumulants and cumulants ratios of the net- proton, net-kaon, and net-charge multiplicity distributions in Au+Au collisions at 7.7, 11.5, 14.5, 19.6, 27, 39, 62.4, and 200 GeV collected in the years 2010, 2011, and 2014 with STAR at RHIC. The centrality and energy dependence of the cumulants up to the fourth order, as well as their ratios, are presented. Furthermore, the comparisons with baseline calculations (Poisson) and non-c...

  3. The neural crest and neural crest cells: discovery and significance ...

    Indian Academy of Sciences (India)

    In this paper I provide a brief overview of the major phases of investigation into the neural crest and the major players involved, discuss how the origin of the neural crest relates to the origin of the nervous system in vertebrate embryos, discuss the impact on the germ-layer theory of the discovery of the neural crest and of ...

  4. DЕTERMINATION OF THE DRUM MILLS’ ENGINE CAPACITY BY USING NEURAL NETWORK WITH SUBORDINATE INPUT PARAMETERS

    Directory of Open Access Journals (Sweden)

    Teodora HRISTOVA

    2012-05-01

    Full Text Available A successful experiment has been done to train the neural network to determine the drum mills’ engine capacity by using the program „QwikNet 2.23”. As a result we get a trained neural network with a maximum error of 1.00619.10-5 which can be used for assessing the capacity of the electric motors of drum mills and can be considered an accurate mathematical model

  5. 2006 Net Centric Operations Conference - Facilitating Net Centric Operations and Warfare

    Science.gov (United States)

    2006-03-16

    Moderator: Lt Col Kenneth Lang, USAF, Chief, Net Centric Transformational Operations, C4 Transformation Division (US JFCOM/J69) Panelists...of Interest (US JFCOM/J61) - Mr. Troy Turner, Section Head, C4 Interoperability (ACT) - COL Kelly Mayes, USA, Director, Campaign Planning...Deliverables NCAT NIF SCOPE Net Centric Assessment Tools (includes SCOPE & PFCs evaluation) Conceptual Architecture Framework Standards PFCs: Building Codes

  6. Linking a domain thesaurus to WordNet and conversion to WordNet-LMF

    OpenAIRE

    Toral, Antonio; Monachini, Monica; Soria, Claudia; Cuadros Oller, Montserrat; Rigau Claramunt, German; Bosma, Wauter; Vossen, Piek

    2010-01-01

    We present a methodology to link domain thesauri to general-domain lexica. This is applied in the framework of the KYOTO project to link the Species2000 thesaurus to the synsets of the English WordNet. Moreover, we study the formalisation of this thesaurus according to the ISO LMF standard and its dialect WordNet-LMF. This conversion will allow Species2000 to communicate with the other resources available in the KYOTO architecture. Peer Reviewed

  7. Classification of breast cancer cytological specimen using convolutional neural network

    Science.gov (United States)

    Żejmo, Michał; Kowal, Marek; Korbicz, Józef; Monczak, Roman

    2017-01-01

    The paper presents a deep learning approach for automatic classification of breast tumors based on fine needle cytology. The main aim of the system is to distinguish benign from malignant cases based on microscopic images. Experiment was carried out on cytological samples derived from 50 patients (25 benign cases + 25 malignant cases) diagnosed in Regional Hospital in Zielona Góra. To classify microscopic images, we used convolutional neural networks (CNN) of two types: GoogLeNet and AlexNet. Due to the very large size of images of cytological specimen (on average 200000 × 100000 pixels), they were divided into smaller patches of size 256 × 256 pixels. Breast cancer classification usually is based on morphometric features of nuclei. Therefore, training and validation patches were selected using Support Vector Machine (SVM) so that suitable amount of cell material was depicted. Neural classifiers were tuned using GPU accelerated implementation of gradient descent algorithm. Training error was defined as a cross-entropy classification loss. Classification accuracy was defined as the percentage ratio of successfully classified validation patches to the total number of validation patches. The best accuracy rate of 83% was obtained by GoogLeNet model. We observed that more misclassified patches belong to malignant cases.

  8. 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....

  9. 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.

  10. Nanoelectronics enabled chronic multimodal neural platform in a mouse ischemic model.

    Science.gov (United States)

    Luan, Lan; Sullender, Colin T; Li, Xue; Zhao, Zhengtuo; Zhu, Hanlin; Wei, Xiaoling; Xie, Chong; Dunn, Andrew K

    2017-12-04

    Despite significant advancements of optical imaging techniques for mapping hemodynamics in small animal models, it remains challenging to combine imaging with spatially resolved electrical recording of individual neurons especially for longitudinal studies. This is largely due to the strong invasiveness to the living brain from the penetrating electrodes and their limited compatibility with longitudinal imaging. We implant arrays of ultraflexible nanoelectronic threads (NETs) in mice for neural recording both at the brain surface and intracortically, which maintain great tissue compatibility chronically. By mounting a cranial window atop of the NET arrays that allows for chronic optical access, we establish a multimodal platform that combines spatially resolved electrical recording of neural activity and laser speckle contrast imaging (LSCI) of cerebral blood flow (CBF) for longitudinal studies. We induce peri-infarct depolarizations (PIDs) by targeted photothrombosis, and show the ability to detect its occurrence and propagation through spatiotemporal variations in both extracellular potentials and CBF. We also demonstrate chronic tracking of single-unit neural activity and CBF over days after photothrombosis, from which we observe reperfusion and increased firing rates. This multimodal platform enables simultaneous mapping of neural activity and hemodynamic parameters at the microscale for quantitative, longitudinal comparisons with minimal perturbation to the baseline neurophysiology. The ability to spatiotemporally resolve and chronically track CBF and neural electrical activity in the same living brain region has broad applications for studying the interplay between neural and hemodynamic responses in health and in cerebrovascular and neurological pathologies. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Control of 12-Cylinder Camless Engine with Neural Networks

    Directory of Open Access Journals (Sweden)

    Ashhab Moh’d Sami

    2017-01-01

    Full Text Available The 12-cyliner camless engine breathing process is modeled with artificial neural networks (ANN’s. The inputs to the net are the intake valve lift (IVL and intake valve closing timing (IVC whereas the output of the net is the cylinder air charge (CAC. The ANN is trained with data collected from an engine simulation model which is based on thermodynamics principles and calibrated against real engine data. A method for adapting single-output feed-forward neural networks is proposed and applied to the camless engine ANN model. As a consequence the overall 12-cyliner camless engine feedback controller is upgraded and the necessary changes are implemented in order to contain the adaptive neural network with the objective of tracking the cylinder air charge (driver’s torque demand while minimizing the pumping losses (increasing engine efficiency. All the needed measurements are extracted only from the two conventional and inexpensive sensors, namely, the mass air flow through the throttle body (MAF and the intake manifold absolute pressure (MAP sensors. The feedback controller’s capability is demonstrated through computer simulation.

  12. Fuzzy net present value for engineering analysis

    Directory of Open Access Journals (Sweden)

    Ali Nazeri

    2012-10-01

    Full Text Available Cash flow analysis is one of the most popular methods for investigating the outcome of an economical project. The costs and benefits of a construction project are often involved with uncertainty and it is not possible to find a precise value for a particular project. In this paper, we present a simple method to calculate the net present value of a cash flow when both costs and benefits are given as triangular numbers. The proposed model of this paper uses Delphi method to figure out the fair values of all costs and revenues and then using fizzy programming techniques, it calculates the fuzzy net present value. The implementation of the proposed model is demonstrated using a simple example.

  13. Design and evaluation of net radiometers

    Science.gov (United States)

    Fritschen, Leo J.; Fritschen, Charles L.

    Net radiometer designs were evaluated with respect to long and short wave sensitivities and to the effect of ambient wind on the signal. The design features of the instrument with the best overall performance include: equal sensitivity to long and short wave radiation, a thermal pile which is thermally isolated from the frame, a white guard ring, pathways for internal circulation between the top and bottom hemispheres, and self-supporting windshields. The windshields have O-ring seals, a ball joint is provided for ease of leveling, and ample desiccant is enclosed in the mounting pipe. Under a high radiant load, the net radiometer signal decreased by 2.5, 3.7, and 4.3 percent at wind speeds of 12.5, 4.6, and 7.5 m/s.

  14. Multi-net optimization of VLSI interconnect

    CERN Document Server

    Moiseev, Konstantin; Wimer, Shmuel

    2015-01-01

    This book covers layout design and layout migration methodologies for optimizing multi-net wire structures in advanced VLSI interconnects. Scaling-dependent models for interconnect power, interconnect delay and crosstalk noise are covered in depth, and several design optimization problems are addressed, such as minimization of interconnect power under delay constraints, or design for minimal delay in wire bundles within a given routing area. A handy reference or a guide for design methodologies and layout automation techniques, this book provides a foundation for physical design challenges of interconnect in advanced integrated circuits.  • Describes the evolution of interconnect scaling and provides new techniques for layout migration and optimization, focusing on multi-net optimization; • Presents research results that provide a level of design optimization which does not exist in commercially-available design automation software tools; • Includes mathematical properties and conditions for optimal...

  15. Automatic pipeline operation using Petri Nets

    Energy Technology Data Exchange (ETDEWEB)

    Moreira, Guilherme O. [PETROBRAS TRANSPORTE S.A., Rio de Janeiro, RJ (Brazil)

    2009-07-01

    A pipeline operation requires several actions, attention and time from the control room operator in each of its operating phases. This article proposition is to use automation as something more than a remote control, drastically reducing the number of repetitive and routine actions needed from the operator to start and stop the system, granting more time for system supervision, decision making during critical conditions and avoiding errors caused due to the need of several actions being executed in a short period of time. To achieve these objectives the pipeline operation will be modeled as a Petri Net consisting of states, event and actions. A methodology for converting this Petri Net into a Ladder controller code will also be proposed. (author)

  16. AstroNet-II International Final Conference

    CERN Document Server

    Masdemont, Josep

    2016-01-01

    These are the proceedings of the "AstroNet-II International Final Conference". This conference was one of the last milestones of the Marie-Curie Research Training Network on Astrodynamics "AstroNet-II", that has been funded by the European Commission under the Seventh Framework Programme. The aim of the conference, and thus this book, is to communicate work on astrodynamics problems to an international and specialised audience. The results are presented by both members of the network and invited specialists. The topics include: trajectory design and control, attitude control, structural flexibility of spacecraft and formation flying. The book addresses a readership across the traditional boundaries between mathematics, engineering and industry by offering an interdisciplinary and multisectorial overview of the field.

  17. Neural Network Approach

    African Journals Online (AJOL)

    Efficient management of hydropower reservoir can only be realized when there is sufficient understanding of interactions existing between reservoir variables and energy generation. Reservoir inflow, storage, reservoir elevation, turbine release, net generating had, plant use coefficient, tail race level and evaporation losses ...

  18. Neural nets with varying topology for high-energy particle recognition: an outlook of computational dynamics

    Science.gov (United States)

    Perrone, Antonio L.; Messi, Roberto; Pasqualucci, Enrico; Basti, Gianfranco

    1993-09-01

    With respect to Rosenblatt linear perceptron, a classical limitation theorem demonstrated by M. Minsky and S. Papert is discussed. This theorem, '$PSIOne-in-a-box', ultimately concern the intrinsic limitations of parallel calculations in pattern calculations in pattern recognition problems. We demonstrate a possible solution of this limitation problem by substituting the static definition of characteristic functions and of their domains in the 'geometrical' perceptron, with their dynamic definition. This dynamics consists in the mutual redefinition of the characteristic function and of its domain depending on the matching with the input. We show an application of this 'dynamic' perceptron scheme in particle tracks recognition in high energy physics. Actually, this algorithm is being used for real time automatic triggering of ADONE e+e- storage ring (Frascati, Rome) to evaluate the neutron time-like electromagnetic form factor in the context of 'Fenice' collaboration by Italian Institute of Nuclear Physics (INFN).

  19. Generalization performance of neural nets in the presence of noisy data

    Science.gov (United States)

    Klenin, Marjorie

    1992-12-01

    An outstanding problem in the study of adaptive learning is overspecialization of the learning system, and its consequent inability to handle new data correctly. A means of addressing this difficulty is described here. When used in conjunction with standard processes such as backpropagation, it identifies the level of corruption of the training sample, and thus provides a `best fit' to the entire domain of interest, rather than to the training sample alone. This is accomplished by a combination of simulated annealing, bootstrap estimation, and analysis methods derived from statistical mechanics. Its advantage is that data need not be reserved for an independent test set, and thus all available samples are used. A modified generalization error, defined through a thermalization parameter on the training set, provides a measure of the sample space consistent with the network function. A criterion for optimal match between network and sample set is obtained from the requirement that generalization error and training error be consistent. Numerical results are presented for examples which illustrate several distinct forms of data corruption. A quantity analogous to the specific heat in thermodynamic systems is found to exhibit anomalies at values of training error near the onset of overtraining.

  20. Drag &Drop, Multiphysics & Neural Net-based Lab-on-Chip Optimization Software Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The overall objective of this project is to develop a drag and drop, component library (fluidic lego) based, system simulation and optimization software for entire...

  1. BASS Net: Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification

    Science.gov (United States)

    Santara, Anirban; Mani, Kaustubh; Hatwar, Pranoot; Singh, Ankit; Garg, Ankur; Padia, Kirti; Mitra, Pabitra

    2017-09-01

    Deep learning based landcover classification algorithms have recently been proposed in literature. In hyperspectral images (HSI) they face the challenges of large dimensionality, spatial variability of spectral signatures and scarcity of labeled data. In this article we propose an end-to-end deep learning architecture that extracts band specific spectral-spatial features and performs landcover classification. The architecture has fewer independent connection weights and thus requires lesser number of training data. The method is found to outperform the highest reported accuracies on popular hyperspectral image data sets.

  2. Log Defect Recognition Using CT-images and Neural Net Classifiers

    Science.gov (United States)

    Daniel L. Schmoldt; Pei Li; A. Lynn Abbott

    1995-01-01

    Although several approaches have been introduced to automatically identify internal log defects using computed tomography (CT) imagery, most of these have been feasibility efforts and consequently have had several limitations: (1) reports of classification accuracy are largely subjective, not statistical, (2) there has been no attempt to achieve real-time operation,...

  3. A Comparison of Rule-Based, K-Nearest Neighbor, and Neural Net Classifiers for Automated

    Science.gov (United States)

    Tai-Hoon Cho; Richard W. Conners; Philip A. Araman

    1991-01-01

    Over the last few years the authors have been involved in research aimed at developing a machine vision system for locating and identifying surface defects on materials. The particular problem being studied involves locating surface defects on hardwood lumber in a species independent manner. Obviously, the accurate location and identification of defects is of paramount...

  4. EVo: Net Shape RTM Production Line

    Directory of Open Access Journals (Sweden)

    Sven Torstrick

    2016-04-01

    Full Text Available EVo research platform is operated by the Center for Lightweight-Production-Technology of the German Aerospace Center in Stade. Its objective is technology demonstration of a fully automated RTM (Resin Transfer Molding production line for composite parts in large quantities. Process steps include cutting and ply handling, draping, stacking, hot-forming, preform-trimming to net shape, resin injection, curing and demolding.

  5. Status of KM3NeT

    Directory of Open Access Journals (Sweden)

    Riccobene G.

    2016-01-01

    Full Text Available The recent observation of cosmic neutrinos by IceCube has pushed the quest towards the identification of cosmic sources of high-energy particles. The KM3NeT Collaboration is now ready to launch the massive construction of detection units to be installed in deep sea to build a km-cubic size neutrino telescope. The main elements of the detector, the status of the project and the expected perfomances are briefly reported.

  6. A Petri Nets Model for Blockchain Analysis

    OpenAIRE

    Pinna, Andrea; Tonelli, Roberto; Orrú, Matteo; Marchesi, Michele

    2017-01-01

    A Blockchain is a global shared infrastructure where cryptocurrency transactions among addresses are recorded, validated and made publicly available in a peer- to-peer network. To date the best known and important cryptocurrency is the bitcoin. In this paper we focus on this cryptocurrency and in particular on the modeling of the Bitcoin Blockchain by using the Petri Nets formalism. The proposed model allows us to quickly collect information about identities owning Bitcoin addresses and to re...

  7. AREVA net income: 649 million euros

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2007-03-15

    This document presents the financial statements for 2006 of Areva group: net income: 649 million euros; backlog up by 24.6% to 25.6 billion euros; steady growth of sales revenue: + 7.3%1 to 10.863 billion euros; operating income of 407 million euros: excellent divisional performance and constitution of a significant provision for the OL3 project in Finland; dividend proposed to Annual General Meeting of Shareholders: 8.46 euros per share.

  8. Deep learning with convolutional neural networks for EEG decoding and visualization.

    Science.gov (United States)

    Schirrmeister, Robin Tibor; Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

    2017-11-01

    Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but a better understanding of how to design and train ConvNets for end-to-end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task-related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG-based brain mapping. Hum Brain Mapp 38:5391-5420, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  9. Deep learning with convolutional neural networks for EEG decoding and visualization

    Science.gov (United States)

    Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

    2017-01-01

    Abstract Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end‐to‐end EEG analysis, but a better understanding of how to design and train ConvNets for end‐to‐end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task‐related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG‐based brain mapping. Hum Brain Mapp 38:5391–5420, 2017. © 2017 Wiley Periodicals, Inc. PMID:28782865

  10. Readmissions at a public safety net hospital.

    Directory of Open Access Journals (Sweden)

    Eri Shimizu

    Full Text Available OBJECTIVE: We aimed to determine factors related to avoidability of 30-day readmissions at our public, safety net hospital in the United States (US. METHODS: We prospectively reviewed medical records of adult internal medicine patients with scheduled and unscheduled 30-day readmissions. We also interviewed patients if they were available. An independent panel used pre-specified, objective criteria to adjudicate potential avoidability. RESULTS: Of 153 readmissions evaluated, 68% were unscheduled. Among these, 67% were unavoidable, primarily due to disease progression and development of new diagnoses. Scheduled readmissions accounted for 32% of readmissions and most (69% were clinically appropriate and unavoidable. The scheduled but avoidable readmissions (31% were attributed largely to limited resources in our healthcare system. CONCLUSIONS: Most readmissions at our public, safety net hospital were unavoidable, even among our unscheduled readmissions. Surprisingly, one-third of our overall readmissions were scheduled, the majority reflecting appropriate management strategies designed to reduce unnecessary hospital days. The scheduled but avoidable readmissions were due to constrained access to non-emergent, expensive procedures that are typically not reimbursed given our system's payor mix, a problem which likely plague other safety net systems. These findings suggest that readmissions do not necessarily reflect inadequate medical care, may reflect resource constraints that are unlikely to be addressable in systems caring for a large burden of uninsured patients, and merit individualized review.

  11. Protein crystallization image classification with elastic net

    Science.gov (United States)

    Hung, Jeffrey; Collins, John; Weldetsion, Mehari; Newland, Oliver; Chiang, Eric; Guerrero, Steve; Okada, Kazunori

    2014-03-01

    Protein crystallization plays a crucial role in pharmaceutical research by supporting the investigation of a protein's molecular structure through X-ray diffraction of its crystal. Due to the rare occurrence of crystals, images must be manually inspected, a laborious process. We develop a solution incorporating a regularized, logistic regression model for automatically evaluating these images. Standard image features, such as shape context, Gabor filters and Fourier transforms, are first extracted to represent the heterogeneous appearance of our images. Then the proposed solution utilizes Elastic Net to select relevant features. Its L1-regularization mitigates the effects of our large dataset, and its L2- regularization ensures proper operation when the feature number exceeds the sample number. A two-tier cascade classifier based on naïve Bayes and random forest algorithms categorized the images. In order to validate the proposed method, we experimentally compare it with naïve Bayes, linear discriminant analysis, random forest, and their two-tier cascade classifiers, by 10-fold cross validation. Our experimental results demonstrate a 3-category accuracy of 74%, outperforming other models. In addition, Elastic Net better reduces the false negatives responsible for a high, domain specific risk. To the best of our knowledge, this is the first attempt to apply Elastic Net to classifying protein crystallization images. Performance measured on a large pharmaceutical dataset also fared well in comparison with those presented in the previous studies, while the reduction of the high-risk false negatives is promising.

  12. The arithmetic symmetry of monoatomic 2-nets.

    Science.gov (United States)

    Fadda, G; Zanzotto, G

    2000-01-01

    A recent paper [Pitteri & Zanzotto (1998). Acta Cryst. A54, 359-373] has proposed a framework for the study of the 'arithmetic symmetry' of multilattices (discrete triply periodic point sets in the affine space). The classical approach to multilattice symmetry considers the well known 'space groups', that is, the groups of affine isometries leaving a multilattice invariant. The ensuing classification counts 219 affine conjugacy (or isomorphism) classes of space groups in three dimensions, and 17 classes in two dimensions ('plane groups'). The arithmetic criterion gives a finer classification of multilattice symmetry than space (or plane) groups do. This paper is concerned with the systematic investigation of the arithmetic symmetry of multilattices in the simplest nontrivial case, that is, monoatomic 2-nets (planar lattices with two identical atoms in their unit cell). We show the latter to belong to five distinct arithmetic types. We also give the complete description of a fundamental domain for the action of the global symmetry group of 2-nets on the space of 2-net metrics.

  13. 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....

  14. 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...

  15. Neural Tube Defects

    Science.gov (United States)

    ... pregnancies each year in the United States. A baby’s neural tube normally develops into the brain and spinal cord. ... fluid in the brain. This is called hydrocephalus. Babies with this condition are treated with surgery to insert a tube (called a shunt) into the brain. The shunt ...

  16. Learning of N-layers neural network

    Directory of Open Access Journals (Sweden)

    Vladimír Konečný

    2005-01-01

    Full Text Available In the last decade we can observe increasing number of applications based on the Artificial Intelligence that are designed to solve problems from different areas of human activity. The reason why there is so much interest in these technologies is that the classical way of solutions does not exist or these technologies are not suitable because of their robustness. They are often used in applications like Business Intelligence that enable to obtain useful information for high-quality decision-making and to increase competitive advantage.One of the most widespread tools for the Artificial Intelligence are the artificial neural networks. Their high advantage is relative simplicity and the possibility of self-learning based on set of pattern situations.For the learning phase is the most commonly used algorithm back-propagation error (BPE. The base of BPE is the method minima of error function representing the sum of squared errors on outputs of neural net, for all patterns of the learning set. However, while performing BPE and in the first usage, we can find out that it is necessary to complete the handling of the learning factor by suitable method. The stability of the learning process and the rate of convergence depend on the selected method. In the article there are derived two functions: one function for the learning process management by the relative great error function value and the second function when the value of error function approximates to global minimum.The aim of the article is to introduce the BPE algorithm in compact matrix form for multilayer neural networks, the derivation of the learning factor handling method and the presentation of the results.

  17. Bed net ownership in Kenya: the impact of 3.4 million free bed nets

    Directory of Open Access Journals (Sweden)

    Vulule John

    2010-06-01

    Full Text Available Abstract Background In July and September 2006, 3.4 million long-lasting insecticide-treated bed nets (LLINs were distributed free in a campaign targeting children 0-59 months old (CU5s in the 46 districts with malaria in Kenya. A survey was conducted one month after the distribution to evaluate who received campaign LLINs, who owned insecticide-treated bed nets and other bed nets received through other channels, and how these nets were being used. The feasibility of a distribution strategy aimed at a high-risk target group to meet bed net ownership and usage targets is evaluated. Methods A stratified, two-stage cluster survey sampled districts and enumeration areas with probability proportional to size. Handheld computers (PDAs with attached global positioning systems (GPS were used to develop the sampling frame, guide interviewers back to chosen households, and collect survey data. Results In targeted areas, 67.5% (95% CI: 64.6, 70.3% of all households with CU5s received campaign LLINs. Including previously owned nets, 74.4% (95% CI: 71.8, 77.0% of all households with CU5s had an ITN. Over half of CU5s (51.7%, 95% CI: 48.8, 54.7% slept under an ITN during the previous evening. Nearly forty percent (39.1% of all households received a campaign net, elevating overall household ownership of ITNs to 50.7% (95% CI: 48.4, 52.9%. Conclusions The campaign was successful in reaching the target population, families with CU5s, the risk group most vulnerable to malaria. Targeted distribution strategies will help Kenya approach indicator targets, but will need to be combined with other strategies to achieve desired population coverage levels.

  18. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation.

    Science.gov (United States)

    Badrinarayanan, Vijay; Kendall, Alex; Cipolla, Roberto

    2017-12-01

    We present a novel and practical deep fully convolutional neural network architecture for semantic pixel-wise segmentation termed SegNet. This core trainable segmentation engine consists of an encoder network, a corresponding decoder network followed by a pixel-wise classification layer. The architecture of the encoder network is topologically identical to the 13 convolutional layers in the VGG16 network [1] . The role of the decoder network is to map the low resolution encoder feature maps to full input resolution feature maps for pixel-wise classification. The novelty of SegNet lies is in the manner in which the decoder upsamples its lower resolution input feature map(s). Specifically, the decoder uses pooling indices computed in the max-pooling step of the corresponding encoder to perform non-linear upsampling. This eliminates the need for learning to upsample. The upsampled maps are sparse and are then convolved with trainable filters to produce dense feature maps. We compare our proposed architecture with the widely adopted FCN [2] and also with the well known DeepLab-LargeFOV [3] , DeconvNet [4] architectures. This comparison reveals the memory versus accuracy trade-off involved in achieving good segmentation performance. SegNet was primarily motivated by scene understanding applications. Hence, it is designed to be efficient both in terms of memory and computational time during inference. It is also significantly smaller in the number of trainable parameters than other competing architectures and can be trained end-to-end using stochastic gradient descent. We also performed a controlled benchmark of SegNet and other architectures on both road scenes and SUN RGB-D indoor scene segmentation tasks. These quantitative assessments show that SegNet provides good performance with competitive inference time and most efficient inference memory-wise as compared to other architectures. We also provide a Caffe implementation of SegNet and a web demo at http://mi.eng.cam.ac.uk/projects/segnet.

  19. Net Shape Rapid Manufacturing Using Nano Encapsulated Powders Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This Phase II program is developing NET Shape components from Encapsulated Powders. Significant advances in Phase I for various materials and in net shape processing...

  20. GALILEO PROBE NET FLUX RADIOMETER DATA V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — The Galileo Probe Net Flux Radiometer (NFR) measured net and upward radiation fluxes in Jupiter's atmosphere between about 0.44 bars and 14 bars, using five spectral...

  1. Observations of NC stop nets for bottlenose dolphin takes

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — To observe the NC stop net fishery to document the entanglement of bottlenose dolphins and movement of dolphins around the nets.

  2. RadNet Air Data From Little Rock, AR

    Science.gov (United States)

    This page presents radiation air monitoring and air filter analysis data for Little Rock, AR from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

  3. HANPP Collection: Global Patterns in Net Primary Productivity (NPP)

    Data.gov (United States)

    National Aeronautics and Space Administration — The Global Patterns in Net Primary Productivity (NPP) portion of the HANPP Collection maps the net amount of solar energy converted to plant organic matter through...

  4. RadNet Air Data From Pittsburgh, PA

    Science.gov (United States)

    This page presents radiation air monitoring and air filter analysis data for Pittsburgh, PA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

  5. RadNet Air Data From Montgomery, AL

    Science.gov (United States)

    This page presents radiation air monitoring and air filter analysis data for Montgomery, AL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

  6. RadNet Air Data From Toledo, OH

    Science.gov (United States)

    This page presents radiation air monitoring and air filter analysis data for Toledo, OH from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

  7. Global Estimated Net Migration Grids by Decade: 1970-2000

    Data.gov (United States)

    National Aeronautics and Space Administration — The Global Estimated Net Migration by Decade: 1970-2000 data set provides estimates of net migration over the three decades from 1970 to 2000. Because of the lack of...

  8. Java EE 7 development with NetBeans 8

    CERN Document Server

    Heffelfinger, David R

    2015-01-01

    The book is aimed at Java developers who wish to develop Java EE applications while taking advantage of NetBeans functionality to automate repetitive tasks. Familiarity with NetBeans or Java EE is not assumed.

  9. RadNet Air Data From Honolulu, HI

    Science.gov (United States)

    This page presents radiation air monitoring and air filter analysis data for Honolulu, HI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

  10. RadNet Air Quality (Fixed Station) Data

    Data.gov (United States)

    U.S. Environmental Protection Agency — RadNet is a national network of monitoring stations that regularly collect air for analysis of radioactivity. The RadNet network, which has stations in each State,...

  11. Efficient convex-elastic net algorithm to solve the Euclidean traveling salesman problem.

    Science.gov (United States)

    Al-Mulhem, M; Al-Maghrabi, T

    1998-01-01

    This paper describes a hybrid algorithm that combines an adaptive-type neural network algorithm and a nondeterministic iterative algorithm to solve the Euclidean traveling salesman problem (E-TSP). It begins with a brief introduction to the TSP and the E-TSP. Then, it presents the proposed algorithm with its two major components: the convex-elastic net (CEN) algorithm and the nondeterministic iterative improvement (NII) algorithm. These two algorithms are combined into the efficient convex-elastic net (ECEN) algorithm. The CEN algorithm integrates the convex-hull property and elastic net algorithm to generate an initial tour for the E-TSP. The NII algorithm uses two rearrangement operators to improve the initial tour given by the CEN algorithm. The paper presents simulation results for two instances of E-TSP: randomly generated tours and tours for well-known problems in the literature. Experimental results are given to show that the proposed algorithm ran find the nearly optimal solution for the E-TSP that outperform many similar algorithms reported in the literature. The paper concludes with the advantages of the new algorithm and possible extensions.

  12. The Detection and Prevention of Deadlock in Petri Nets

    Science.gov (United States)

    Hu, Wensong; Zhu, Yuyuan; Lei, Jie

    This article introduces the basic knowledge of Petri net at first, then analyzes two methods about the detection of deadlock in Petri nets. One is based upon the net structure; the other is based upon reachability tree and the article describes the steps of the arithmetic about it. Besides, the article summarizes the method based upon basic siphon theory for the prevention of deadlock in Petri nets and gives out examples for application.

  13. Nets, Boats and Fishing in the Roman World

    DEFF Research Database (Denmark)

    Bekker-Nielsen, Tønnes

    2002-01-01

    Ithas been claimed that in Roman times, net fishing was a shore-based technology, but a study of literary sources and pictorial evidence, mainly mosaics, show that net fishing from boats was widespread throughout the first four centuries AD.......Ithas been claimed that in Roman times, net fishing was a shore-based technology, but a study of literary sources and pictorial evidence, mainly mosaics, show that net fishing from boats was widespread throughout the first four centuries AD....

  14. SkyNet: Modular nuclear reaction network library

    Science.gov (United States)

    Lippuner, Jonas; Roberts, Luke F.

    2017-10-01

    The general-purpose nuclear reaction network SkyNet evolves the abundances of nuclear species under the influence of nuclear reactions. SkyNet can be used to compute the nucleosynthesis evolution in all astrophysical scenarios where nucleosynthesis occurs. Any list of isotopes can be evolved and SkyNet supports various different types of nuclear reactions. SkyNet is modular, permitting new or existing physics, such as nuclear reactions or equations of state, to be easily added or modified.

  15. Translating Colored Control Flow Nets into Readable Java via Annotated Java Workflow Nets

    DEFF Research Database (Denmark)

    Lassen, Kristian Bisgaard; Tjell, Simon

    2007-01-01

    In this paper, we present a method for developing Java applications from Colored Control Flow Nets (CCFNs), which is a special kind of Colored Petri Nets (CPNs) that we introduce. CCFN makes an explicit distinction between the representation of: The system, the environment of the system, and the ......In this paper, we present a method for developing Java applications from Colored Control Flow Nets (CCFNs), which is a special kind of Colored Petri Nets (CPNs) that we introduce. CCFN makes an explicit distinction between the representation of: The system, the environment of the system......, and the interface between the system and the environment. Our translation maps CCFNs into Anno- tated Java Workflow Nets (AJWNs) as an intermediate step, and these AJWNs are finally mapped to Java. CCFN is intended to enforce the modeler to describe the system in an imperative manner which makes the subsequent...... translation to Java easier to define. The translation to Java preserves data dependencies and control-flow aspects of the source CCFN. This paper contributes to the model-driven software development paradigm, by showing how to model a system, environment, and their interface, as a CCFN and presenting a fully...

  16. Cast net design characteristics, catch composition and selectivity in ...

    African Journals Online (AJOL)

    Cast net design characteristics, construction, operational techniques and selectivity in Lagos lagoon, Nigeria was examined between September and December 2005. Netting materials for cast net construction in Lagos lagoon were monofilament nylon, poly-ethylene (PE) and polyester (PES). The conventional ratio 1:2 of ...

  17. 7 CFR 1221.16 - Net market price.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 10 2010-01-01 2010-01-01 false Net market price. 1221.16 Section 1221.16 Agriculture... INFORMATION ORDER Sorghum Promotion, Research, and Information Order Definitions § 1221.16 Net market price. Net market price means the sales price, or other value, per volumetric unit, received by a producer...

  18. 7 CFR 1220.115 - Net market price.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 10 2010-01-01 2010-01-01 false Net market price. 1220.115 Section 1220.115... CONSUMER INFORMATION Soybean Promotion and Research Order Definitions § 1220.115 Net market price. The term net market price means— (a) except as provided in paragraph (b) of this section, the sales price, or...

  19. 7 CFR 1221.17 - Net market value.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 10 2010-01-01 2010-01-01 false Net market value. 1221.17 Section 1221.17 Agriculture... INFORMATION ORDER Sorghum Promotion, Research, and Information Order Definitions § 1221.17 Net market value. Net market value means: (a) Except as provided in paragraph (b)and (c) of this section, the value...

  20. 17 CFR 190.07 - Calculation of allowed net equity.

    Science.gov (United States)

    2010-04-01

    ... equity. 190.07 Section 190.07 Commodity and Securities Exchanges COMMODITY FUTURES TRADING COMMISSION BANKRUPTCY § 190.07 Calculation of allowed net equity. Allowed net equity shall be computed as follows: (a) Allowed claim. The allowed net equity claim of a customer shall be equal to the aggregate of the funded...

  1. Coloured Petri Net Refinement Specification and Correctness Proof with Coq

    Science.gov (United States)

    Choppy, Christine; Mayero, Micaela; Petrucci, Laure

    2009-01-01

    In this work, we address the formalisation of symmetric nets, a subclass of coloured Petri nets, refinement in COQ. We first provide a formalisation of the net models, and of their type refinement in COQ. Then the COQ proof assistant is used to prove the refinement correctness lemma. An example adapted from a protocol example illustrates our work.

  2. Theory of net analyte signal vectors in inverse regression

    DEFF Research Database (Denmark)

    Bro, R.; Andersen, Charlotte Møller

    2003-01-01

    The. net analyte signal and the net analyte signal vector are useful measures in building and optimizing multivariate calibration models. In this paper a theory for their use in inverse regression is developed. The theory of net analyte signal was originally derived from classical least squares...

  3. 47 CFR 32.7990 - Nonregulated net income.

    Science.gov (United States)

    2010-10-01

    ... shall be recorded on separate books of account for such operations. Only the net of the total revenues... 47 Telecommunication 2 2010-10-01 2010-10-01 false Nonregulated net income. 32.7990 Section 32... Nonregulated net income. (a) This account shall be used by those companies who offer nonregulated activities...

  4. 26 CFR 1.823-4 - Net premiums.

    Science.gov (United States)

    2010-04-01

    ... 26 Internal Revenue 8 2010-04-01 2010-04-01 false Net premiums. 1.823-4 Section 1.823-4 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) INCOME TAX (CONTINUED) INCOME....823-4 Net premiums. Net premiums are one of the items used, together with the gross amount of income...

  5. 47 CFR 32.4341 - Net deferred tax liability adjustments.

    Science.gov (United States)

    2010-10-01

    ... income tax charges and credits pertaining to Account 32.4361, Deferred tax regulatory adjustments—net. (b... carryforward net operating losses and carryforward investment tax credits expected to reduce future taxes... carryforward net operating losses and carryforward investment tax credits previously recorded in this account...

  6. 47 CFR 32.1500 - Other jurisdictional assets-net.

    Science.gov (United States)

    2010-10-01

    ... account shall be recorded net of any applicable income tax effects and shall be supported by subsidiary... 47 Telecommunication 2 2010-10-01 2010-10-01 false Other jurisdictional assets-net. 32.1500....1500 Other jurisdictional assets—net. This account shall include the cumulative impact on assets of...

  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. Adaptive control using a hybrid-neural model: application to a polymerisation reactor

    Directory of Open Access Journals (Sweden)

    Cubillos F.

    2001-01-01

    Full Text Available This work presents the use of a hybrid-neural model for predictive control of a plug flow polymerisation reactor. The hybrid-neural model (HNM is based on fundamental conservation laws associated with a neural network (NN used to model the uncertain parameters. By simulations, the performance of this approach was studied for a peroxide-initiated styrene tubular reactor. The HNM was synthesised for a CSTR reactor with a radial basis function neural net (RBFN used to estimate the reaction rates recursively. The adaptive HNM was incorporated in two model predictive control strategies, a direct synthesis scheme and an optimum steady state scheme. Tests for servo and regulator control showed excellent behaviour following different setpoint variations, and rejecting perturbations. The good generalisation and training capacities of hybrid models, associated with the simplicity and robustness characteristics of the MPC formulations, make an attractive combination for the control of a polymerisation reactor.

  9. Identification of Complex Dynamical Systems with Neural Networks (2/2)

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

  10. Identification of Complex Dynamical Systems with Neural Networks (1/2)

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

  11. A microarray gene expression data classification using hybrid back propagation neural network

    Directory of Open Access Journals (Sweden)

    Vimaladevi M.

    2014-01-01

    Full Text Available Classification of cancer establishes appropriate treatment and helps to decide the diagnosis. Cancer expands progressively from an alteration in a cell's genetic structure. This change (mutation results in cells with uncontrolled growth patterns. In cancer classification, the approach, Back propagation is sufficient and also it is a universal technique of training artificial neural networks. It is also called supervised learning method. It needs many dataset for input and output for making up the training set. The back propagation method may execute the function of collaborate multiple parties. In existing method, collaborative learning is limited and it considers only two parties. The proposed collaborative function can perform well and problems can be solved by utilizing the power of cloud computing. This technical note applies hybrid models of Back Propagation Neural networks (BPN and fast Genetic Algorithms (GA to estimate the feature selection in gene expression data. The proposed research work examines many feature selection algorithms which are “fragile”; that is, the superiority of their results varies broadly over data sets. By this research, it is suggested that this is due to higherorder interactions between features causing restricted minima in search space in which the algorithm becomes attentive. GAs may escape from such minima by chance, because works are highly stochastic. A neural net classifier with a genetic algorithm, using the GA to select features for classification by the neural net and incorporating the net as part of the objective function of the GA.

  12. Prediction of proteasome cleavage motifs by neural networks

    DEFF Research Database (Denmark)

    Kesimir, C.; Nussbaum, A.K.; Schild, H.

    2002-01-01

    physiological conditions. Our algorithm has been trained not only on in vitro data, but also on MHC Class I ligand data, which reflect a combination of immunoproteasome and constitutive proteasome specificity. This feature, together with the use of neural networks, a non-linear classification technique, make...... the prediction of MHC Class I ligand boundaries more accurate: 65% of the cleavage sites and 85% of the non-cleavage sites are correctly determined. Moreover, we show that the neural networks trained on the constitutive proteasome data learns a specificity that differs from that of the networks trained on MHC...... Class I molecules. Here we demonstrate that such an approach produces an accurate prediction of the CTL the epitopes in HIV Nef. The method is available at www.cbs.dtu.dk/services/NetChop/....

  13. Online radicalization: the net or the netizen?

    Directory of Open Access Journals (Sweden)

    Femi Richard Omotoyinbo

    2014-10-01

    Full Text Available Purpose - Radicalization has gained some unusual prominence in the academic circles; maintaining a generic existence not only in the political sector. And with the advent of the Information Communication Technology (ICT, radicalization has begun to have some virtual dimension even in the remotest of human communities. This study seeks to mobilize a universal awareness on the collective urgency to oppose Online Radicalization (a radicalization that happens through the internet due to its propensity to engendering conflicts. It also aims at identifying the principal cause of online radicalization and steer a clear course for a practical reversal in the systems of online radicalization.Design/methodology/approach - The study is divided into three primary parts. The general notion of radicalization is the focus of the first part; which is further analysed into the levels of online radicalization with its accompanying developments and segments. The second part utilizes analytic and historical method to pinpoint the principal cause of online radicalization amidst the suspected causal factors (the Net and the Netizen. The final part analytically focuses on the Netizen (a user/citizen of the internet as the primary cause of online radicalization, and how the global community can bring about a corresponding change in the Net by the application of some measures on the Netizen.Findings - By virtue of the analytic plus historical methods employed by this study; it was initially identified that radicalization is basically having two versions which are online and offline. Further emphasis on the online version reveals that its existence is only made possible by the availability of the internet (the Net. Since the Net is a global phenomenon online radicalization is considered to be worldwide: a menace of globalization. However, the study later indicated that the Net is a facilitator and a cause of online radicalization. A view was deduced that the Netizen is

  14. LSF restoration by means of a neural network

    CERN Document Server

    Burstein, P

    1999-01-01

    The LSF restoration problem is written as a Maximum Entropy one, where the constraint on the restoration energy is dictated by the 'Discrepancy Principle'. The ME solution is found by means of a continuous-Hopfield neural network which reduces the energy of the output misfit, and maximizes the restoration entropy at the same time. A positive learning parameter controls the constraint compliance. Prior knowledge insertion into the net's algorithm, such as prior LSF models, upper bounds, etc. is presented. Simulations, both with computer generated and experimental data are carried out. The results are compared to those of the Least Squares method. Sensitivity of constraint fulfillment is analyzed.

  15. Traditional Nets Interfere with the Uptake of Long-Lasting Insecticidal Nets in the Peruvian Amazon: The Relevance of Net Preference for Achieving High Coverage and Use

    OpenAIRE

    Koen Peeters Grietens; Joan Muela Ribera; Veronica Soto; Alex Tenorio; Sarah Hoibak; Angel Rosas Aguirre; Elizabeth Toomer; Hugo Rodriguez; Alejandro Llanos Cuentas; Umberto D'Alessandro; Dionicia Gamboa; Annette Erhart

    2013-01-01

    BACKGROUND: While coverage of long-lasting insecticide-treated nets (LLIN) has steadily increased, a growing number of studies report gaps between net ownership and use. We conducted a mixed-methods social science study assessing the importance of net preference and use after Olyset(R) LLINs were distributed through a mass campaign in rural communities surrounding Iquitos, the capital city of the Amazonian region of Peru. METHODS: The study was conducted in the catchment area of the Paujil a...

  16. Pro WF Windows Workflow in NET 40

    CERN Document Server

    Bukovics, Bruce

    2010-01-01

    Windows Workflow Foundation (WF) is a revolutionary part of the .NET 4 Framework that allows you to orchestrate human and system interactions as a series of workflows that can be easily mapped, analyzed, adjusted, and implemented. As business problems become more complex, the need for workflow-based solutions has never been more evident. WF provides a simple and consistent way to model and implement complex problems. As a developer, you focus on developing the business logic for individual workflow tasks. The runtime handles the execution of those tasks after they have been composed into a wor

  17. Stochastic petri nets for wireless networks

    CERN Document Server

    Lei, Lei; Zhong, Zhangdui

    2015-01-01

    This SpringerBrief presents research in the application of Stochastic Petri Nets (SPN) to the performance evaluation of wireless networks under bursty traffic. It covers typical Quality-of-Service performance metrics such as mean throughput, average delay and packet dropping probability. Along with an introduction of SPN basics, the authors introduce the key motivation and challenges of using SPN to analyze the resource sharing performance in wireless networks. The authors explain two powerful modeling techniques that treat the well-known state space explosion problem: model decomposition and

  18. MathSciNet i kemija

    OpenAIRE

    Dravec-Braun, J.

    2006-01-01

    MathSciNet je svjetski poznata bibliografska i citatna baza matematièkih publikacija. Ona je elektronièka inaèica referativnog èasopisa Mathematical Reviews i Current mathematical publications koje izdaje American Mathematical Society. SadrÞi bibliografske podatke publikacija izdanih u razdoblju od 1940. do danas. Veæina èlanaka i drugih publikacija recenzirana je, pa se uz bibliografske referencije nalazi kritièki prikaz, saÞetak (Review Text).

  19. Net Generation's Learning Styles in Nursing Education.

    Science.gov (United States)

    Christodoulou, Eleni; Kalokairinou, Athina

    2015-01-01

    Numerous surveys have confirmed that emerging technologies and Web 2.0 tools have been a defining feature in the lives of current students, estimating that there is a fundamental shift in the way young people communicate, socialize and learn. Nursing students in higher education are characterized as digital literate with distinct traits which influence their learning styles. Millennials exhibit distinct learning preferences such as teamwork, experiential activities, structure, instant feedback and technology integration. Higher education institutions should be aware of the implications of the Net Generation coming to university and be prepared to meet their expectations and learning needs.

  20. Learning AngularJS for .NET developers

    CERN Document Server

    Pop, Alex

    2014-01-01

    This is a step-by-step, example-driven guide that uses a gradual introduction of concepts; most of the chapters also contain an annotated exploration of how to build a specific part of a production-ready application. If you are a .NET developer that has already built web applications or web services with a fundamental knowledge of HTML, JavaScript, and CSS, and want to explore single-page applications, then this book will give you a great start. The frameworks, tools, and libraries mentioned here will make you productive and minimize the friction usually associated with building server-side we

  1. 47 CFR 36.506 - Net current deferred operating income taxes-Account 4100, Net noncurrent deferred operating...

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 2 2010-10-01 2010-10-01 false Net current deferred operating income taxes-Account 4100, Net noncurrent deferred operating income taxes-Account 4340. 36.506 Section 36.506... operating income taxes—Account 4100, Net noncurrent deferred operating income taxes—Account 4340. (a...

  2. 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.

  3. Neural tube defects

    Directory of Open Access Journals (Sweden)

    M.E. Marshall

    1981-09-01

    Full Text Available Neural tube defects refer to any defect in the morphogenesis of the neural tube, the most common types being spina bifida and anencephaly. Spina bifida has been recognised in skeletons found in north-eastern Morocco and estimated to have an age of almost 12 000 years. It was also known to the ancient Greek and Arabian physicians who thought that the bony defect was due to the tumour. The term spina bifida was first used by Professor Nicolai Tulp of Amsterdam in 1652. Many other terms have been used to describe this defect, but spina bifida remains the most useful general term, as it describes the separation of the vertebral elements in the midline.

  4. A Graphical Query Language for Querying Petri Nets

    Science.gov (United States)

    Xiao, Lan; Zheng, Li; Xiao, Jian; Huang, Yi

    As the number of business process models increases, providing business analysts and IT experts with a query langue for querying business process models is of great practical value. This paper uses Petri net as business process modeling language and develops Petri Net Query Language (PNQL), a graphical query language for Petri nets. The syntax and semantics of PNQL are formally studied. PNQL allows users to get not only the perfectly matched Petri nets but also the Petri nets with high similarity. The complexity of PNQL is studied.

  5. Computer Tools for Construction, Modification and Analysis of Petri Nets

    DEFF Research Database (Denmark)

    Jensen, Kurt

    1987-01-01

    The practical use of Petri nets is — just as any other description technique — very dependent on the existence of adequate computer tools, which may assist the user to cope with the many details of a large description. For Petri nets there is a need for tools supporting construction of nets......, as well as modification and analysis. Graphical work stations provide the opportunity to work — not only with textual representations of Petri nets — but also directly with the graphical representations. This paper describes some of the different kinds of tools which are needed in the Petri net area...

  6. Reachability Trees for High-level Petri Nets

    DEFF Research Database (Denmark)

    Jensen, Kurt; Jensen, Arne M.; Jepsen, Leif Obel

    1986-01-01

    High-level Petri nets have been introduced as a powerful net type by which it is possible to handle rather complex systems in a succinct and manageable way. The success of high-level Petri nets is undebatable when we speak about description, but there is still much work to be done to establish...... the necessary analysis methods. In other papers it is shown how to generalize the concept of place- and transition invariants from place/transition nets to high-level Petri nets. Our present paper contributes to this with a generalization of reachability trees, which is one of the other important analysis...

  7. Neural networks for triggering

    Energy Technology Data Exchange (ETDEWEB)

    Denby, B. (Fermi National Accelerator Lab., Batavia, IL (USA)); Campbell, M. (Michigan Univ., Ann Arbor, MI (USA)); Bedeschi, F. (Istituto Nazionale di Fisica Nucleare, Pisa (Italy)); Chriss, N.; Bowers, C. (Chicago Univ., IL (USA)); Nesti, F. (Scuola Normale Superiore, Pisa (Italy))

    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.

  8. 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. .

  9. Neurally-mediated sincope.

    Science.gov (United States)

    Can, I; Cytron, J; Jhanjee, R; Nguyen, J; Benditt, D G

    2009-08-01

    Syncope is a syndrome characterized by a relatively sudden, temporary and self-terminating loss of consciousness; the causes may vary, but they have in common a temporary inadequacy of cerebral nutrient flow, usually due to a fall in systemic arterial pressure. However, while syncope is a common problem, it is only one explanation for episodic transient loss of consciousness (TLOC). Consequently, diagnostic evaluation should start with a broad consideration of real or seemingly real TLOC. Among those patients in whom TLOC is deemed to be due to ''true syncope'', the focus may then reasonably turn to assessing the various possible causes; in this regard, the neurally-mediated syncope syndromes are among the most frequently encountered. There are three common variations: vasovagal syncope (often termed the ''common'' faint), carotid sinus syndrome, and the so-called ''situational faints''. Defining whether the cause is due to a neurally-mediated reflex relies heavily on careful history taking and selected testing (e.g., tilt-test, carotid massage). These steps are important. Despite the fact that neurally-mediated faints are usually relatively benign from a mortality perspective, they are nevertheless only infrequently an isolated event; neurally-mediated syncope tends to recur, and physical injury resulting from falls or accidents, diminished quality-of-life, and possible restriction from employment or avocation are real concerns. Consequently, defining the specific form and developing an effective treatment strategy are crucial. In every case the goal should be to determine the cause of syncope with sufficient confidence to provide patients and family members with a reliable assessment of prognosis, recurrence risk, and treatment options.

  10. The Neural Noisy Channel

    OpenAIRE

    Yu, Lei; Blunsom, Phil; Dyer, Chris; Grefenstette, Edward; Kocisky, Tomas

    2016-01-01

    We formulate sequence to sequence transduction as a noisy channel decoding problem and use recurrent neural networks to parameterise the source and channel models. Unlike direct models which can suffer from explaining-away effects during training, noisy channel models must produce outputs that explain their inputs, and their component models can be trained with not only paired training samples but also unpaired samples from the marginal output distribution. Using a latent variable to control ...

  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. Gapped sequence alignment using artificial neural networks: application to the MHC class I system

    DEFF Research Database (Denmark)

    Andreatta, Massimo; Nielsen, Morten

    2016-01-01

    . On this relatively simple system, we developed a sequence alignment method based on artificial neural networks that allows insertions and deletions in the alignment. Results: We show that prediction methods based on alignments that include insertions and deletions have significantly higher performance than methods...... the length profile of different MHC molecules, and quantified the reduction of the experimental effort required to identify potential epitopes using our prediction algorithm. Availability and implementation: The NetMHC-4.0 method for the prediction of peptide-MHC class I binding affinity using gapped...... sequence alignment is publicly available at: http://www.cbs.dtu.dk/services/NetMHC-4.0....

  13. Population preference of net texture prior to bed net trial in Kala-Azar-endemic areas.

    Directory of Open Access Journals (Sweden)

    Murari L Das

    Full Text Available Prior to a community-based efficacy trial of long-lasting insecticidal nets (LLINs in the prevention of visceral leishmaniasis (VL; also called kala-azar, a pilot study on preference of tools was held in endemic areas of India and Nepal in September 2005.LLINs made of polyester and polyethylene were distributed to 60 participants, who used the nets sequentially for 7 d. Acceptability and preference were evaluated via indirect indicators through questionnaires at three defined time points before and after use of the LLINs and through focus group discussions (FGDs. In the latter, preferences for color and size were also assessed. Untreated bed nets were owned by 87% of the households prior to the study. All users liked textures of both LLIN types after 7 d of use, but had a slight preference for those made of polyester if they were to recommend a LLIN to relatives or friends (p<0.05, mainly because of their relatively greater softness in comparison to polyethylene LLINs. Users reported that both net types reduced mosquito bites and number of insects, including sand fly (bhusana; genus Phlebotomus, inside the house. Side effects were minor and disappeared quickly.The large-scale intervention trial considered the preferences of the study population to decide on the best tool of intervention--light-blue, rectangular, polyester LLINs of different sizes.

  14. The effect of netting solidity ratio and inclined angle on the hydrodynamic characteristics of knotless polyethylene netting

    Science.gov (United States)

    Tang, Hao; Hu, Fuxiang; Xu, Liuxiong; Dong, Shuchuang; Zhou, Cheng; Wang, Xuefang

    2017-10-01

    Knotless polyethylene (PE) netting has been widely used in aquaculture cages and fishing gears, especially in Japan. In this study, the hydrodynamic coefficient of six knotless PE netting panels with different solidity ratios were assessed in a flume tank under various attack angles of netting from 0° (parallel to flow) to 90° (perpendicular to flow) and current speeds from 40 cm s-1 to 130 cm s-1. It was found that the drag coefficient was related to Reynolds number, solidity ratio and attack angle of netting. The solidity ratio was positively related with drag coefficient for netting panel perpendicular to flow, whereas when setting the netting panel parallel to the flow the opposite result was obtained. For netting panels placed at an angle to the flow, the lift coefficient reached the maximum at an attack angle of 50° and then decreased as the attack angle further increased. The solidity ratio had a dual influence on drag coefficient of inclined netting panels. Compared to result in the literature, the normal drag coefficient of knotless PE netting measured in this study is larger than that of nylon netting or Dyneema netting.

  15. Development of Novel Gas Brand Anti-Piracy System based on BP Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Wang, L [School of Aeronautics and Astronautics, Tongji University, Shanghai (China); Zhang, Y Y [Chinese-German School of Postgraduate Studies, Tongji University (China); Ding, L [Chinese-German School of Postgraduate Studies, Tongji University (China)

    2006-10-15

    The Wireless-net Close-loop gas brand anti-piracy system introduced in this paper is a new type of brand piracy technical product based on BP neural network. It is composed by gas brand piracy label possessing gas exhalation resource, ARM embedded gas-detector, GPRS wireless module and data base of merchandise information. First, the system obtains the information on the special label through gas sensor array ,then the attained signals are transferred into ARM Embedded board and identified by artificial neural network, and finally turns back the outcome of data collection and identification to the manufactures with the help of GPRS module.

  16. Development of Novel Gas Brand Anti-Piracy System based on BP Neural Networks

    Science.gov (United States)

    Wang, L.; Zhang, Y. Y.; Ding, L.

    2006-10-01

    The Wireless-net Close-loop gas brand anti-piracy system introduced in this paper is a new type of brand piracy technical product based on BP neural network. It is composed by gas brand piracy label possessing gas exhalation resource, ARM embedded gas-detector, GPRS wireless module and data base of merchandise information. First, the system obtains the information on the special label through gas sensor array ,then the attained signals are transferred into ARM Embedded board and identified by artificial neural network, and finally turns back the outcome of data collection and identification to the manufactures with the help of GPRS module.

  17. Direct Photon Identification with Artificial Neural Network in the Photon Spectrometer PHOS

    CERN Document Server

    Bogolyubsky, M Yu; Sadovsky, S A; Kharlov, Yu.V.

    2003-01-01

    A neural network method is developed to discriminate direct photons from the neutral pion background in the PHOS spectrometer of the ALICE experiment at the LHC collider. The neural net has been trained to distinguish different classes of events by analyzing the energy-profile tensor of a cluster in its eigen vector coordinate system. Monte-Carlo simulations show that this method diminishes by an order of magnitude the probability of $\\pi^0$-meson misidentification as a photon with respect to the direct photon identification efficiency in the energy range up to 120 GeV.

  18. Dynamic control of ROV`s making use of the neural network concept

    Energy Technology Data Exchange (ETDEWEB)

    Ooi, Tadashi; Yoshida, Yuki; Takahashi, Yoshiaki; Kidoushi, Hideki [Ishikawajima-Harima Heavy Industries Co., Ltd., Tokyo (Japan)

    1994-12-31

    An attempt is made to combine the classical controller with the concept of neural network, the result of which is a control system that they have named the Robust Adaptive Neural-net Controller (RANC). The RANC identifies the dynamic characteristics of the remotely operated vehicle (ROV) including its ambient environment involving cyclic disturbances such as forces induced by waves, and organizes automatically an optimized controller. A tank experiment is described in which the RANC is set to maintain a model ROV at a prescribed depth of water under artificially generated wave disturbance.

  19. Neural Correlates of Stimulus Reportability

    OpenAIRE

    Hulme, Oliver J.; Friston, Karl F.; Zeki, Semir

    2009-01-01

    Most experiments on the “neural correlates of consciousness” employ stimulus reportability as an operational definition of what is consciously perceived. The interpretation of such experiments therefore depends critically on understanding the neural basis of stimulus reportability. Using a high volume of fMRI data, we investigated the neural correlates of stimulus reportability using a partial report object detection paradigm. Subjects were presented with a random array of circularly arranged...

  20. [Artificial neural networks in Neurosciences].

    Science.gov (United States)

    Porras Chavarino, Carmen; Salinas Martínez de Lecea, José María

    2011-11-01

    This article shows that artificial neural networks are used for confirming the relationships between physiological and cognitive changes. Specifically, we explore the influence of a decrease of neurotransmitters on the behaviour of old people in recognition tasks. This artificial neural network recognizes learned patterns. When we change the threshold of activation in some units, the artificial neural network simulates the experimental results of old people in recognition tasks. However, the main contributions of this paper are the design of an artificial neural network and its operation inspired by the nervous system and the way the inputs are coded and the process of orthogonalization of patterns.