WorldWideScience

Sample records for neural net technology

  1. 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)

  2. 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....

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. 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.

  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. 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. 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. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Neural recording and modulation technologies

    Science.gov (United States)

    Chen, Ritchie; Canales, Andres; Anikeeva, Polina

    2017-01-01

    In the mammalian nervous system, billions of neurons connected by quadrillions of synapses exchange electrical, chemical and mechanical signals. Disruptions to this network manifest as neurological or psychiatric conditions. Despite decades of neuroscience research, our ability to treat or even to understand these conditions is limited by the capability of tools to probe the signalling complexity of the nervous system. Although orders of magnitude smaller and computationally faster than neurons, conventional substrate-bound electronics do not recapitulate the chemical and mechanical properties of neural tissue. This mismatch results in a foreign-body response and the encapsulation of devices by glial scars, suggesting that the design of an interface between the nervous system and a synthetic sensor requires additional materials innovation. Advances in genetic tools for manipulating neural activity have fuelled the demand for devices that are capable of simultaneously recording and controlling individual neurons at unprecedented scales. Recently, flexible organic electronics and bio- and nanomaterials have been developed for multifunctional and minimally invasive probes for long-term interaction with the nervous system. In this Review, we discuss the design lessons from the quarter-century-old field of neural engineering, highlight recent materials-driven progress in neural probes and look at emergent directions inspired by the principles of neural transduction.

  13. 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.

  14. 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...

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Advanced Manufacturing Technologies (AMT): Advanced Near Net Shape Technology Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Develop and mature manufacturing technology to enable fabrication of single-piece integrally-stiffened launch vehicle structures to replace expensive, heavy, and...

  4. 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.

  5. Web Development Technology-PHP. How It Is Related To Web Development Technology ASP.NET

    Directory of Open Access Journals (Sweden)

    Manya Sharma

    2015-01-01

    Full Text Available ABSTRACT This paper tells about the technologies used in PHP and how they are related to ASP.NET. The paper begin with the introduction of PHP defining what and how technologies has been used in development of User Complaint Web Application. How thistechnology is related to ASP.NET in features such as implementation functionality validation and proactive behavior involved in validating user input from the browser providing users feedback overall time consumed in development and maintenance.

  6. 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.

  7. Fuzzy logic and neural network technologies

    Science.gov (United States)

    Villarreal, James A.; Lea, Robert N.; Savely, Robert T.

    1992-01-01

    Applications of fuzzy logic technologies in NASA projects are reviewed to examine their advantages in the development of neural networks for aerospace and commercial expert systems and control. Examples of fuzzy-logic applications include a 6-DOF spacecraft controller, collision-avoidance systems, and reinforcement-learning techniques. The commercial applications examined include a fuzzy autofocusing system, an air conditioning system, and an automobile transmission application. The practical use of fuzzy logic is set in the theoretical context of artificial neural systems (ANSs) to give the background for an overview of ANS research programs at NASA. The research and application programs include the Network Execution and Training Simulator and faster training algorithms such as the Difference Optimized Training Scheme. The networks are well suited for pattern-recognition applications such as predicting sunspots, controlling posture maintenance, and conducting adaptive diagnoses.

  8. Web Development Technology-PHP. How It Is Related To Web Development Technology ASP.NET

    National Research Council Canada - National Science Library

    Manya Sharma

    2015-01-01

    ABSTRACT This paper tells about the technologies used in PHP and how they are related to ASP.NET. The paper begin with the introduction of PHP defining what and how technologies has been used in development of User Complaint Web Application...

  9. 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...

  10. 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.

  11. 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.

  12. Application of artificial neural networks (ANNs) in wine technology.

    Science.gov (United States)

    Baykal, Halil; Yildirim, Hatice Kalkan

    2013-01-01

    In recent years, neural networks have turned out as a powerful method for numerous practical applications in a wide variety of disciplines. In more practical terms neural networks are one of nonlinear statistical data modeling tools. They can be used to model complex relationships between inputs and outputs or to find patterns in data. In food technology artificial neural networks (ANNs) are useful for food safety and quality analyses, predicting chemical, functional and sensory properties of various food products during processing and distribution. In wine technology, ANNs have been used for classification and for predicting wine process conditions. This review discusses the basic ANNs technology and its possible applications in wine technology.

  13. 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.

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. 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

  19. 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.

  20. Image Restoration Technology Based on Discrete Neural network

    Directory of Open Access Journals (Sweden)

    Zhou Duoying

    2015-01-01

    Full Text Available With the development of computer science and technology, the development of artificial intelligence advances rapidly in the field of image restoration. Based on the MATLAB platform, this paper constructs a kind of image restoration technology of artificial intelligence based on the discrete neural network and feedforward network, and carries out simulation and contrast of the restoration process by the use of the bionic algorithm. Through the application of simulation restoration technology, this paper verifies that the discrete neural network has a good convergence and identification capability in the image restoration technology with a better effect than that of the feedforward network. The restoration technology based on the discrete neural network can provide a reliable mathematical model for this field.

  1. Artificial Neural Networks and Instructional Technology.

    Science.gov (United States)

    Carlson, Patricia A.

    1991-01-01

    Artificial neural networks (ANN), part of artificial intelligence, are discussed. Such networks are fed sample cases (training sets), learn how to recognize patterns in the sample data, and use this experience in handling new cases. Two cognitive roles for ANNs (intelligent filters and spreading, associative memories) are examined. Prototypes…

  2. 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

  3. 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...

  4. Factors shaping effective utilization of health information technology in urban safety-net clinics.

    Science.gov (United States)

    George, Sheba; Garth, Belinda; Fish, Allison; Baker, Richard

    2013-09-01

    Urban safety-net clinics are considered prime targets for the adoption of health information technology innovations; however, little is known about their utilization in such safety-net settings. Current scholarship provides limited guidance on the implementation of health information technology into safety-net settings as it typically assumes that adopting institutions have sufficient basic resources. This study addresses this gap by exploring the unique challenges urban resource-poor safety-net clinics must consider when adopting and utilizing health information technology. In-depth interviews (N = 15) were used with key stakeholders (clinic chief executive officers, medical directors, nursing directors, chief financial officers, and information technology directors) from staff at four clinics to explore (a) nonhealth information technology-related clinic needs, (b) how health information technology may provide solutions, and (c) perceptions of and experiences with health information technology. Participants identified several challenges, some of which appear amenable to health information technology solutions. Also identified were requirements for effective utilization of health information technology including physical infrastructural improvements, funding for equipment/training, creation of user groups to share health information technology knowledge/experiences, and specially tailored electronic billing guidelines. We found that despite the potential benefit that can be derived from health information technologies, the unplanned and uninformed introduction of these tools into these settings might actually create more problems than are solved. From these data, we were able to identify a set of factors that should be considered when integrating health information technology into the existing workflows of low-resourced urban safety-net clinics in order to maximize their utilization and enhance the quality of health care in such settings.

  5. Utilizing Technology to Enhance Learning Environments: The Net Gen Student

    Science.gov (United States)

    Muhammad, Amanda J.; Mitova, Mariana A.; Wooldridge, Deborah G.

    2016-01-01

    It is essential for instructors to understand the importance of classroom technology so they can prepare to use it to personalize students' learning. Strategies for choosing effective electronic tools are presented, followed by specific suggestions for designing enhanced personalized learning using electronic tools.

  6. 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

  7. 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/.

  8. 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

  9. An overview on development of neural network technology

    Science.gov (United States)

    Lin, Chun-Shin

    1993-01-01

    The study has been to obtain a bird's-eye view of the current neural network technology and the neural network research activities in NASA. The purpose was two fold. One was to provide a reference document for NASA researchers who want to apply neural network techniques to solve their problems. Another one was to report out survey results regarding NASA research activities and provide a view on what NASA is doing, what potential difficulty exists and what NASA can/should do. In a ten week study period, we interviewed ten neural network researchers in the Langley Research Center and sent out 36 survey forms to researchers at the Johnson Space Center, Lewis Research Center, Ames Research Center and Jet Propulsion Laboratory. We also sent out 60 similar forms to educators and corporation researchers to collect general opinions regarding this field. Twenty-eight survey forms, 11 from NASA researchers and 17 from outside, were returned. Survey results were reported in our final report. In the final report, we first provided an overview on the neural network technology. We reviewed ten neural network structures, discussed the applications in five major areas, and compared the analog, digital and hybrid electronic implementation of neural networks. In the second part, we summarized known NASA neural network research studies and reported the results of the questionnaire survey. Survey results show that most studies are still in the development and feasibility study stage. We compared the techniques, application areas, researchers' opinions on this technology, and many aspects between NASA and non-NASA groups. We also summarized their opinions on difficulties encountered. Applications are considered the top research priority by most researchers. Hardware development and learning algorithm improvement are the next. The lack of financial and management support is among the difficulties in research study. All researchers agree that the use of neural networks could result in

  10. 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.

  11. 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 ...

  12. 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.

  13. Automation of Presentation Record Production Based on Rich-Media Technology Using SNT Petri Nets Theory

    Directory of Open Access Journals (Sweden)

    Ivo Martiník

    2015-01-01

    Full Text Available Rich-media describes a broad range of digital interactive media that is increasingly used in the Internet and also in the support of education. Last year, a special pilot audiovisual lecture room was built as a part of the MERLINGO (MEdia-rich Repository of LearnING Objects project solution. It contains all the elements of the modern lecture room determined for the implementation of presentation recordings based on the rich-media technologies and their publication online or on-demand featuring the access of all its elements in the automated mode including automatic editing. Property-preserving Petri net process algebras (PPPA were designed for the specification and verification of the Petri net processes. PPPA does not need to verify the composition of the Petri net processes because all their algebraic operators preserve the specified set of the properties. These original PPPA are significantly generalized for the newly introduced class of the SNT Petri process and agent nets in this paper. The PLACE-SUBST and ASYNC-PROC algebraic operators are defined for this class of Petri nets and their chosen properties are proved. The SNT Petri process and agent nets theory were significantly applied at the design, verification, and implementation of the programming system ensuring the pilot audiovisual lecture room functionality.

  14. Automation of Presentation Record Production Based on Rich-Media Technology Using SNT Petri Nets Theory.

    Science.gov (United States)

    Martiník, Ivo

    2015-01-01

    Rich-media describes a broad range of digital interactive media that is increasingly used in the Internet and also in the support of education. Last year, a special pilot audiovisual lecture room was built as a part of the MERLINGO (MEdia-rich Repository of LearnING Objects) project solution. It contains all the elements of the modern lecture room determined for the implementation of presentation recordings based on the rich-media technologies and their publication online or on-demand featuring the access of all its elements in the automated mode including automatic editing. Property-preserving Petri net process algebras (PPPA) were designed for the specification and verification of the Petri net processes. PPPA does not need to verify the composition of the Petri net processes because all their algebraic operators preserve the specified set of the properties. These original PPPA are significantly generalized for the newly introduced class of the SNT Petri process and agent nets in this paper. The PLACE-SUBST and ASYNC-PROC algebraic operators are defined for this class of Petri nets and their chosen properties are proved. The SNT Petri process and agent nets theory were significantly applied at the design, verification, and implementation of the programming system ensuring the pilot audiovisual lecture room functionality.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. Revenue-Maximizing Radio Access Technology Selection with Net Neutrality Compliance in Heterogeneous Wireless Networks

    Directory of Open Access Journals (Sweden)

    Elissar Khloussy

    2018-01-01

    Full Text Available The net neutrality principle states that users should have equal access to all Internet content and that Internet Service Providers (ISPs should not practice differentiated treatment on any of the Internet traffic. While net neutrality aims to restrain any kind of discrimination, it also grants exemption to a certain category of traffic known as specialized services (SS, by allowing the ISP to dedicate part of the resources for the latter. In this work, we consider a heterogeneous LTE/WiFi wireless network and we investigate revenue-maximizing Radio Access Technology (RAT selection strategies that are net neutrality-compliant, with exemption granted to SS traffic. Our objective is to find out how the bandwidth reservation for SS traffic would be made in a way that allows maximizing the revenue while being in compliance with net neutrality and how the choice of the ratio of reserved bandwidth would affect the revenue. The results show that reserving bandwidth for SS traffic in one RAT (LTE can achieve higher revenue. On the other hand, when the capacity is reserved across both LTE and WiFi, higher social benefit in terms of number of admitted users can be realized, as well as lower blocking probability for the Internet access traffic.

  1. 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.

  2. Neural computation and particle accelerators research, technology and applications

    CERN Document Server

    D'Arras, Horace

    2010-01-01

    This book discusses neural computation, a network or circuit of biological neurons and relatedly, particle accelerators, a scientific instrument which accelerates charged particles such as protons, electrons and deuterons. Accelerators have a very broad range of applications in many industrial fields, from high energy physics to medical isotope production. Nuclear technology is one of the fields discussed in this book. The development that has been reached by particle accelerators in energy and particle intensity has opened the possibility to a wide number of new applications in nuclear technology. This book reviews the applications in the nuclear energy field and the design features of high power neutron sources are explained. Surface treatments of niobium flat samples and superconducting radio frequency cavities by a new technique called gas cluster ion beam are also studied in detail, as well as the process of electropolishing. Furthermore, magnetic devises such as solenoids, dipoles and undulators, which ...

  3. 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.

  4. 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.

  5. 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.

  6. 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)

  7. Feature detection in satellite images using neural network technology

    Science.gov (United States)

    Augusteijn, Marijke F.; Dimalanta, Arturo S.

    1992-01-01

    A feasibility study of automated classification of satellite images is described. Satellite images were characterized by the textures they contain. In particular, the detection of cloud textures was investigated. The method of second-order gray level statistics, using co-occurrence matrices, was applied to extract feature vectors from image segments. Neural network technology was employed to classify these feature vectors. The cascade-correlation architecture was successfully used as a classifier. The use of a Kohonen network was also investigated but this architecture could not reliably classify the feature vectors due to the complicated structure of the classification problem. The best results were obtained when data from different spectral bands were fused.

  8. 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.

  9. 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.

  10. I-NET: interactive neuro-educational technology to accelerate skill learning.

    Science.gov (United States)

    Raphael, Giby; Berka, Chris; Popovic, Djordje; Chung, Gregory K W K; Nagashima, Sam O; Behneman, Adrienne; Davis, Gene; Johnson, Robin

    2009-01-01

    The learning of a novel task currently rely heavily on conventional classroom instruction with qualitative assessment and observation. Introduction of individualized tutorials with integrated neuroscience-based evaluation techniques could significantly accelerate skill acquisition and provide quantitative evidence of successful training. We have created a suite of adaptive and interactive neuro-educational technologies (I-NET) to increase the pace and efficiency of skill learning. It covers four major themes: 1) Integration of brain monitoring into paced instructional tutorials, 2) Identifying psychophysiological characteristics of expertise using a model population, 3) Developing sensor-based feedback to accelerate novice-to-expert transition, 4) Identifying neurocognitive factors that are predictive of skill acquisition to allow early triage and interventions. We selected rifle marksmanship training as the field of application. Rifle marksmanship is a core skill for the Army and Marine Corps and it involves a combination of classroom instructional learning and field practice involving instantiation of a well-defined set of sensory, motor and cognitive skills. The instrumentation that incorporates the I-NET technologies is called the Adaptive Peak Performance Trainer (APPT). Preliminary analysis of pilot study data for performance data from a novice population that used this device revealed an improved learning trajectory.

  11. 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....

  12. [The Identification of the Origin of Chinese Wolfberry Based on Infrared Spectral Technology and the Artificial Neural Network].

    Science.gov (United States)

    Li, Zhong; Liu, Ming-de; Ji, Shou-xiang

    2016-03-01

    The Fourier Transform Infrared Spectroscopy (FTIR) is established to find the geographic origins of Chinese wolfberry quickly. In the paper, the 45 samples of Chinese wolfberry from different places of Qinghai Province are to be surveyed by FTIR. The original data matrix of FTIR is pretreated with common preprocessing and wavelet transform. Compared with common windows shifting smoothing preprocessing, standard normal variation correction and multiplicative scatter correction, wavelet transform is an effective spectrum data preprocessing method. Before establishing model through the artificial neural networks, the spectra variables are compressed by means of the wavelet transformation so as to enhance the training speed of the artificial neural networks, and at the same time the related parameters of the artificial neural networks model are also discussed in detail. The survey shows even if the infrared spectroscopy data is compressed to 1/8 of its original data, the spectral information and analytical accuracy are not deteriorated. The compressed spectra variables are used for modeling parameters of the backpropagation artificial neural network (BP-ANN) model and the geographic origins of Chinese wolfberry are used for parameters of export. Three layers of neural network model are built to predict the 10 unknown samples by using the MATLAB neural network toolbox design error back propagation network. The number of hidden layer neurons is 5, and the number of output layer neuron is 1. The transfer function of hidden layer is tansig, while the transfer function of output layer is purelin. Network training function is trainl and the learning function of weights and thresholds is learngdm. net. trainParam. epochs=1 000, while net. trainParam. goal = 0.001. The recognition rate of 100% is to be achieved. It can be concluded that the method is quite suitable for the quick discrimination of producing areas of Chinese wolfberry. The infrared spectral analysis technology

  13. Citizen Management of Technology: A Science and Technology Studies approach to wireless networks and urban governance trough guifi.net

    Directory of Open Access Journals (Sweden)

    Yann Bona Beauvois

    2011-03-01

    Full Text Available Thesis presented at the Departament de Psicologia Social de la UAB by Yann Bona on December, 2010. Directed by Dr. Joan Pujol Tarrés.This dissertation explores the many ways in which citizens aiming to manage technologies in urban scape relate to public administrations. To accomplish it's task, it brings forward certain STS notions such as cosmopolitics, hybrid composition or technical democracy. On a general level, this thesis seeks an answer to Bruno Latour concern with what does it mean to conceive the technical as political?. We offer a set of conclusions based on what we choose to name a Sociotechnique of Public Policy .Our work relies on a case study focused on a free and open wireless network (located in Catalunya for the most part and called guifi.net that emerged from the desire and will of Civil Society wich, up to date, turns out to be the world's biggest free wireless network.

  14. 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.

  15. Retina neural circuitry seen with particle detector technology

    CERN Multimedia

    CERN Bulletin

    2010-01-01

    Using particle physics techniques, high energy physics researchers have recently provided new insight into neural circuits inside the retina. After uncovering a new type of retinal cell and mapping how the retina deals with colours, the team from Santa Cruz (US), Krakow and Glasgow is now turning its attention to more complex issues such as how the retina gets wired up and how the brain deals with the signals it receives from the retina. All this using technology derived from high-density, multistrip silicon detectors…   Seen from the point of view of a particle physicist, eyes are image detectors that can gather many different types of data: light and dark, different colours, motion, etc. In particular, the retina, a thin tissue that lines the back of the eye, is a biological pixel detector that detects light and converts it to electrical signals that travel through the optic nerve to the brain. Neurobiologists know that many different cell types are involved in these processes, but they...

  16. 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

  17. 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.

  18. 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.

  19. 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...

  20. THE USE OF NEURAL NETWORK TECHNOLOGY TO MODEL SWIMMING PERFORMANCE

    Directory of Open Access Journals (Sweden)

    António José Silva

    2007-03-01

    Full Text Available The aims of the present study were: to identify the factors which are able to explain the performance in the 200 meters individual medley and 400 meters front crawl events in young swimmers, to model the performance in those events using non-linear mathematic methods through artificial neural networks (multi-layer perceptrons and to assess the neural network models precision to predict the performance. A sample of 138 young swimmers (65 males and 73 females of national level was submitted to a test battery comprising four different domains: kinanthropometric evaluation, dry land functional evaluation (strength and flexibility, swimming functional evaluation (hydrodynamics, hydrostatic and bioenergetics characteristics and swimming technique evaluation. To establish a profile of the young swimmer non-linear combinations between preponderant variables for each gender and swim performance in the 200 meters medley and 400 meters font crawl events were developed. For this purpose a feed forward neural network was used (Multilayer Perceptron with three neurons in a single hidden layer. The prognosis precision of the model (error lower than 0.8% between true and estimated performances is supported by recent evidence. Therefore, we consider that the neural network tool can be a good approach in the resolution of complex problems such as performance modeling and the talent identification in swimming and, possibly, in a wide variety of sports

  1. NEURAL NETWORK TECHNOLOGY IN STUDY OF FOREIGN EXCHANGE MARKET

    Directory of Open Access Journals (Sweden)

    Eduard Dadyan

    2015-09-01

    Full Text Available In this paper we present the results of neural network analysis of the effect of significant factors on the quotation of the exchange rate on the example of the formation of the dollar in terms of «the turbulence of the economy» in Russia.

  2. Revenue-Maximizing Radio Access Technology Selection with Net Neutrality Compliance in Heterogeneous Wireless Networks

    OpenAIRE

    Khloussy, Elissar; Jiang, Yuming

    2018-01-01

    The net neutrality principle states that users should have equal access to all Internet content and that Internet Service Providers (ISPs) should not practice differentiated treatment on any of the Internet traffic. While net neutrality aims to restrain any kind of discrimination, it also grants exemption to a certain category of traffic known as specialized services (SS), by allowing the ISP to dedicate part of the resources for the latter. In this work, we consider a heterogeneous LTE/WiFi ...

  3. 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.

  4. A critical review on the applications of artificial neural networks in winemaking technology.

    Science.gov (United States)

    Moldes, O A; Mejuto, J C; Rial-Otero, R; Simal-Gandara, J

    2017-09-02

    Since their development in 1943, artificial neural networks were extended into applications in many fields. Last twenty years have brought their introduction into winery, where they were applied following four basic purposes: authenticity assurance systems, electronic sensory devices, production optimization methods, and artificial vision in image treatment tools, with successful and promising results. This work reviews the most significant approaches for neural networks in winemaking technologies with the aim of producing a clear and useful review document.

  5. 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.

  6. Net Warrior D10 Technology Report: Airborne Early Warning and Control (AEW&C) and Data Link Nodes

    Science.gov (United States)

    2012-04-01

    common. Unlike other distributed client/server technologies (e.g. CORBA), DDS does not rely on centralised repositories, specialised nodes or servers...derisking of TDL integration between systems being procured by the ADO. One example of such an activity involves the TDL integration of the WIRE and the...Conclusion The transformation to an Australian net centric force requires a shift in the way systems are procured , built and used, so that

  7. Application of the Wire Bonding Technology to a Flexible Neural Probe

    Science.gov (United States)

    Shimizu, Koichi; Nakanishi, Motofumi; Makikawa, Masaaki; Asajima, Syuzo; Konishi, Satoshi

    This paper proposes a novel neural probe using flexible metal wire for wire bonding on LSI chip. Wire bonding technology can provide a number of flexible wire arrays. The proposed neural probe is used for a nerve interface for functional electric stimulation (FES) technology which assists the paralysis of living body function by a spinal cord injury. The flexibility of probe will provide low invasive and safe neural interfaces for the nerve tissue from a long term view. We employ a combination of wire bonding and laser machining for the fabrication of aligned flexible probes. Aligned bonded flexible metal wires on electrodes are converted to probe arrays by cutting the bridge between electrodes. Typical dimension of a bonding wire is several tens μm in diameter and is suitable for neural probe to be inserted into nerve bundles. Needle shape is formed by electro-polishing of cut edge. Proposed method can be benefited by advantages of wire bonding as the widespread technology in electronics industry. Developed flexible neural probe based on the proposed technology is estimated as a nerve interface by inserting to a sciatic nerve of a rat.

  8. Neural network wavelet technology: A frontier of automation

    Science.gov (United States)

    Szu, Harold

    1994-01-01

    Neural networks are an outgrowth of interdisciplinary studies concerning the brain. These studies are guiding the field of Artificial Intelligence towards the, so-called, 6th Generation Computer. Enormous amounts of resources have been poured into R/D. Wavelet Transforms (WT) have replaced Fourier Transforms (FT) in Wideband Transient (WT) cases since the discovery of WT in 1985. The list of successful applications includes the following: earthquake prediction; radar identification; speech recognition; stock market forecasting; FBI finger print image compression; and telecommunication ISDN-data compression.

  9. 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

  10. Worldwide clean energy system technology using hydrogen (WE-NET). subtask 9. Investigation of innovative and leading technologies; Suiso riyo kokusai clean energy system gijutsu (WE-NET). subtask 9. Kakushinteki sendoteki gijutsu ni kansuru chosa kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    The WE-NET Project is a long-term project designed to ensure that an energy network technology using hydrogen becomes a reality not later than 2020. So the project cannot remain effective unless constant efforts are made to foresee future trends of technology and optimize it as the making of entire system for the project. In this project, new technologies which are not up for development are also investigated. Their feasibility should be studied, if necessary. From the foregoing point of view, new technologies are studied, collected and evaluated. Thus, useful suggestions and proposals may be made as to the course for the project to follow, as well as its research and development. Proposals highly evaluated up to FY 1995 are the hydrogen-oxygen internal-combustion Stirling`s engine, hydrogen production by solid oxide electrolysis, magnetic refrigeration technology for liquefaction of hydrogen, solar thermal hydrogen production with iron sponge technology, and hydrogen producing technology with photocatalyst. Conceptual investigation themes in FY 1996 are the hydrogen internal-combustion Stirling engine, solar thermal hydrogen production, phototransformation process, and high-temperature steam electrolysis. 9 figs., 54 tabs.

  11. 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.

  12. Questioning Faculty Use of Information Technology by Context of NETS-T Standards in Bologna Process

    Science.gov (United States)

    Elmas, Muzaffer

    2013-01-01

    Using technology in and out of class has been becoming more and more important recently. University settings also become more dependent to technology. Bologna process requires university and faculty diffuse and

  13. Assessment of cleaner electricity generation technologies for net CO{sub 2} mitigation in Thailand

    Energy Technology Data Exchange (ETDEWEB)

    Limmeechokchai, B.; Suksuntornsiri, P. [Thammasat University, Pathum Thani (Thailand)

    2007-02-15

    The choice of electricity generation technologies not only directly affects the amount of CO{sub 2} emission from the power sector, but also indirectly affects the economy-wide CO{sub 2} emission. It is because electricity is the basic requirement of economic sectors and final consumption within the economy. In Thailand, although the power development plan (PDP) has been planned for the committed capacity to meet the future electricity demand, there are some undecided electricity generation technologies that will be studied for technological options. The economy-wide CO{sub 2} mitigations between selecting cleaner power generation options instead of pulverized coal-thermal technology of the undecided capacity are assessed by energy input-output analysis (IOA). The decomposition of IOA presents the fuel-mix effect, input structural effect, and final demand effect by the change in technology of the undecided capacity. The cleaner technologies include biomass power generation, hydroelectricity and integrated gasification combined cycle (IGCC). Results of the analyses show that if the conventional pulverized coal technology is selected in the undecided capacity, the economy-wide CO{sub 2} emission would be increased from 223 million ton in 2006 to 406 million ton in 2016. Renewable technology presents better mitigation option for replacement of conventional pulverized coal technology than the cleaner coal technology. The major contributor of CO{sub 2} mitigation in cleaner coal technology is the fuel mix effect due to higher conversion efficiency.

  14. EDITORIAL: Special issue on optical neural engineering: advances in optical stimulation technology Special issue on optical neural engineering: advances in optical stimulation technology

    Science.gov (United States)

    Shoham, Shy; Deisseroth, Karl

    2010-08-01

    Neural engineering, itself an 'emerging interdisciplinary research area' [1] has undergone a sea change over the past few years with the emergence of exciting new optical technologies for monitoring, stimulating, inhibiting and, more generally, modulating neural activity. To a large extent, this change is driven by the realization of the promise and complementary strengths that emerging photo-stimulation tools offer to add to the neural engineer's toolbox, which has been almost exclusively based on electrical stimulation technologies. Notably, photo-stimulation is non-contact, can in some cases be genetically targeted to specific cell populations, can achieve high spatial specificity (cellular or even sub-cellular) in two or three dimensions, and opens up the possibility of large-scale spatial-temporal patterned stimulation. It also offers a seamless solution to the problem of cross-talk generated by simultaneous electrical stimulation and recording. As in other biomedical optics phenomena [2], photo-stimulation includes multiple possible modes of interaction between light and the target neurons, including a variety of photo-physical and photo-bio-chemical effects with various intrinsic components or exogenous 'sensitizers' which can be loaded into the tissue or genetically expressed. Early isolated reports of neural excitation with light date back to the late 19th century [3] and to Arvanitaki and Chalazonitis' work five decades ago [4]; however, the mechanism by which these and other direct photo-stimulation, inhibition and modulation events [5-7] took place is yet unclear, as is their short- and long-term safety profile. Photo-chemical photolysis of covalently 'caged' neurotransmitters [8, 9] has been widely used in cellular neuroscience research for three decades, including for exciting or inhibiting neural activity, and for mapping neural circuits. Technological developments now allow neurotransmitters to be uncaged with exquisite spatial specificity (down to

  15. 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.

  16. Research and industrialization of near-net rolling technology used in shaft parts

    Science.gov (United States)

    Hu, Zhenghuan; Wang, Baoyu; Zheng, Zhenhua

    2018-03-01

    Shaft part rolling is an efficient and green nearnet shaping technology offering many advantages, including high production efficiency, high material utilization rate, high product quality, and excellent production environment. In this paper, the features of shaft part rolling are introduced along with the working principles of two main shaft part rolling technologies, namely, cross wedge rolling (CWR) and skew rolling (SR). In relation to this technology, some R&D achievements gained by the University of Science and Technology Beijing are summarized. Finally, the latest developments in shaft part rolling are presented, including SR steel balls, precise forming of camshaft blank by CWR, SR phosphorous copper balls at room temperature, and CWR hollow axle sleeve. Although the shaft part rolling technology has been widely used in China, it only accounts for about 15% of applicable parts at present. Nevertheless, this technology has broad application prospects.

  17. 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

  18. 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.

  19. From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

    Science.gov (United States)

    Ross, Muriel D.

    1991-01-01

    The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

  20. Maximizing Residential Energy Savings: Net Zero Energy House (ZEH) Technology Pathways

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, R.; Roberts, D.

    2008-11-01

    To meet current U.S. Department of Energy zero-energy home performance goals, new technologies and solutions must increase whole-house efficiency savings by an additional 40% relative to those provided by best available components and systems.

  1. Prioritizing health system and disease burden factors: an evaluation of the net benefit of transferring health technology interventions to different districts in Zimbabwe.

    Science.gov (United States)

    Shamu, Shepherd; Rusakaniko, Simbarashe; Hongoro, Charles

    2016-01-01

    Health-care technologies (HCTs) play an important role in any country's health-care system. Zimbabwe's health-care system uses a lot of HCTs developed in other countries. However, a number of local factors have affected the absorption and use of these technologies. We therefore set out to test the hypothesis that the net benefit regression framework (NBRF) could be a helpful benefit testing model that enables assessment of intra-national variables in HCT transfer. We used an NBRF model to assess the benefits of transferring cost-effective technologies to different jurisdictions. We used the country's 57 administrative districts to proxy different jurisdictions. For the dependent variable, we combined the cost and effectiveness ratios with the districts' per capita health expenditure. The cost and effectiveness ratios were obtained from HIV/AIDS and malaria randomized controlled trials, which did either a prospective or retrospective cost-effectiveness analysis. The independent variables were district demographic and socioeconomic determinants of health. The study showed that intra-national variation resulted in different net benefits of the same health technology intervention if implemented in different districts in Zimbabwe. The study showed that population data, health data, infrastructure, demographic and health-seeking behavior had significant effects on the net margin benefit for the different districts. The net benefits also differed in terms of magnitude as a result of the local factors. Net benefit testing using local data is a very useful tool for assessing the transferability and further adoption of HCTs developed elsewhere. However, adopting interventions with a positive net benefit should also not be an end in itself. Information on positive or negative net benefit could also be used to ascertain either the level of future savings that a technology can realize or the level of investment needed for the particular technology to become beneficial.

  2. Translocalisation over the Net: Digitalisation, Information Technology and Local Cultures in Melanesia

    Science.gov (United States)

    Kupiainen, Jari

    2006-01-01

    In the Western Pacific, the People First Network project has since 2001 been building a growing network of rural email stations across the conflict-ridden Solomon Islands. These stations are based on robust technology and consist of solar panels, short-wave radios and compatible modems, laptop computers and printers to provide email communication…

  3. INTEGRATION OF FRACTAL AND NEURAL NETWORK TECHNOLOGIES IN PEDAGOGICAL MONITORING AND ASSESSMENT OF KNOWLEDGE OF TRAINEES

    Directory of Open Access Journals (Sweden)

    Svetlana N Dvoryatkina

    2017-12-01

    Full Text Available The possibility of statement and solution of the problem of searching of theoretical justification and development of efficient didactic mechanisms of the organization of process of pedagogical monitoring and assessment of level of knowledge of trainees can be based on convergence of the leading psychological and pedagogical, mathematical, and informational technologies with accounting of the modern achievements in science. In the article, the pedagogical expediency of realization of opportunities of means of informational technologies in monitoring and assessment of the composite mathematical knowledge, in the management of cognitive activity of students is proved. The ability to integrate fractal methods and neural network technologies in perfecting of a system of pedagogical monitoring of mathematical knowledge of trainees as a part of the automated training systems (ATS is investigated and realized in practice. It is proved that fractal methods increase the accuracy and depth of estimation of the level of proficiency of students and also complexes of intellectual operations of the integrative qualities allowing to master and apply cross-disciplinary knowledge and abilities in professional activity. Neural network technologies solve a problem of realization of the personal focused tutoring from positions of optimum individualization of mathematical education and self-realization of the person. The technology of projection of integrative system of pedagogical monitoring of knowledge of students includes the following stages: establishment of the required tutoring parameters; definition and preparation of input data for realization of integration of fractal and neural network technologies; development of the diagnostic module as a part of the block of an artificial intelligence of ATS, filling of the databases structured by system; start of system for obtaining the forecast. In development of the integrative automated system of pedagogical

  4. Using Technology of .Net Web Services in the Area of Automation

    Directory of Open Access Journals (Sweden)

    Martin Hnik

    2009-12-01

    Full Text Available This work deals with a technology for data exchange XML Web Services and its application to specific tasks. One of the applications created allows you to monitor and control the real thermal process through a number of client devices, independent of the operating system, the type or their location. The thermal process can be controlled, for example, by another process, a website or a mobile phone. The system is designed from its base and contains three main parts. The hardware part consists from a measuring card, actuators and temperature sensors. The core application is a server that is running the XML Web Service, Windows Service and SQL Server. Client software for mobile phones and web sites was also created.

  5. 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

  6. Mobile Technologies and the Incidence of Cyberbullying in Seven European Countries: Findings from Net Children Go Mobile

    Directory of Open Access Journals (Sweden)

    Brian O'Neill

    2015-04-01

    Full Text Available The harmful effects of bullying and harassment on children have long been of concern to parents, educators, and policy makers. The online world presents a new environment in which vulnerable children can be victimized and a space where perpetrators find new ways to perform acts of harassment. While online bullying is often considered to be an extension of persistent offline behavior, according to EU Kids Online (2011, the most common form of bullying is in person, face-to-face. With the rise in use of mobile Internet technologies, this balance is changing. Increased levels of use and more time spent online accessed through a variety of devices has increased children’s exposure to a range of online risks, including cyberbullying. This article presents the findings of the Net Children Go Mobile project, a cross-national study of children aged 9–16 in seven European countries. The research builds on the work of EU Kids Online and supports the identification of new trends in children’s online experiences of risk and safety. The study finds that while overall levels of bullying have remained relatively static, levels of online bullying have increased, particularly among younger teens. The relationship between cyberbullying and the use of mobile Internet technologies is examined and factors contributing to increased levels of cyberbullying are highlighted.

  7. Applicability of energy-positive net-zero water management in Alaska: technology status and case study.

    Science.gov (United States)

    Wu, Tingting; Englehardt, James D; Guo, Tianjiao; Gassie, Lucien; Dotson, Aaron

    2017-11-22

    Challenges of water and wastewater management in Alaska include the potential need for above-grade and freeze-protected piping, high unit energy costs and, in many rural areas, low population density and median annual income. However, recently developed net-zero water (NZW), i.e., nearly closed-loop, direct potable water reuse systems, can retain the thermal energy in municipal wastewater, producing warm treated potable water without the need for substantial water re-heating, heat pumping or transfer, or additional energy conversion. Consequently, these systems are projected to be capable of saving more energy than they use in water treatment and conveyance, in the temperate USA. In this paper, NZW technology is reviewed in terms of potential applicability in Alaska by performing a hypothetical case study for the city of Fairbanks, Alaska. Results of this paper study indicate that in municipalities of Alaska with local engineering and road access, the use of NZW systems may provide an energy-efficient water service option. In particular, case study modeling suggests hot water energy savings are equivalent to five times the energy used for treatment, much greater savings than in mid-latitudes, due largely to the substantially higher energy needed for heating water from a conventional treatment system and lack of need for freeze-protected piping. Further study of the applicability of NZW technology in cold regions, with expanded evaluation in terms of system-wide lifecycle cost, is recommended.

  8. Three-D Artificial Neural Network (3DANN) technology. Blueprint for the future

    Science.gov (United States)

    Carson, John

    1994-01-01

    Irvine Sensors Corporation (ISC), working closely with JPL under BMDO/ONR sponsorship, is developing a radically new neural computing technology. Primarily aimed at discrimination and target recognition for BMDO missile interceptor applications, it appears to have near term commercial applicability to such problems as handwriting and face recognition, just to name two. In its earliest form it will be able to perform inner product computation using 262 thousand 64x64 templates (weighted synapse arrays) where the 64(exp 5) weights can all be changed every millisecond. Internal switching provides an inherent capability to zoom, translate, or rotate the templates. The 3D silicon architecture is manufactured on a commercial, high volume DRAM production line at very low cost, enabling its commercialization. Two technology thrusts are beginning: in the first, the 64 layer capability of 3DANN-I will be extended to 1024 layers and beyond. In the second layer size will be shrunk to 2-3 millimeters to reduce layer costs. Our workshop goal is to expose this technology to the neural network community as an emerging tool for their use and to obtain their desire for its future development.

  9. The 3-D image recognition based on fuzzy neural network technology

    Science.gov (United States)

    Hirota, Kaoru; Yamauchi, Kenichi; Murakami, Jun; Tanaka, Kei

    1993-01-01

    Three dimensional stereoscopic image recognition system based on fuzzy-neural network technology was developed. The system consists of three parts; preprocessing part, feature extraction part, and matching part. Two CCD color camera image are fed to the preprocessing part, where several operations including RGB-HSV transformation are done. A multi-layer perception is used for the line detection in the feature extraction part. Then fuzzy matching technique is introduced in the matching part. The system is realized on SUN spark station and special image input hardware system. An experimental result on bottle images is also presented.

  10. 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

  11. Control of Greenhouse Gas Emissions by Optimal DER Technology Investment and Energy Management in Zero-Net-Energy Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Stadler, Michael; Siddiqui, Afzal; Marnay, Chris; Aki, Hirohisa; Lai, Judy

    2009-08-10

    The U.S. Department of Energy has launched the commercial building initiative (CBI) in pursuit of its research goal of achieving zero-net-energy commercial buildings (ZNEB), i.e. ones that produce as much energy as they use. Its objective is to make these buildings marketable by 2025 such that they minimize their energy use through cutting-edge, energy-efficiency technologies and meet their remaining energy needs through on-site renewable energy generation. This paper examines how such buildings may be implemented within the context of a cost- or CO2-minimizing microgrid that is able to adopt and operate various technologies: photovoltaic modules (PV) and other on-site generation, heat exchangers, solar thermal collectors, absorption chillers, and passive/demand-response technologies. A mixed-integer linear program (MILP) that has a multi-criteria objective function is used. The objective is minimization of a weighted average of the building's annual energy costs and CO2 emissions. The MILP's constraints ensure energy balance and capacity limits. In addition, constraining the building's energy consumed to equal its energy exports enables us to explore how energy sales and demand-response measures may enable compliance with the ZNEB objective. Using a commercial test site in northernCalifornia with existing tariff rates and technology data, we find that a ZNEB requires ample PV capacity installed to ensure electricity sales during the day. This is complemented by investment in energy-efficient combined heat and power (CHP) equipment, while occasional demand response shaves energy consumption. A large amount of storage is also adopted, which may be impractical. Nevertheless, it shows the nature of the solutions and costs necessary to achieve a ZNEB. Additionally, the ZNEB approach does not necessary lead to zero-carbon (ZC) buildings as is frequently argued. We also show a multi-objective frontier for the CA example, whichallows us to estimate the

  12. 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

  13. 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

  14. 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

  15. 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

  16. [Back-propagation neural network and genetic algorithm for multi-objective optimization of extraction technology of Cortex Fraxini].

    Science.gov (United States)

    Yang, Ming; Yu, Min-ying; Shi, Xiu-feng; Teng, Yan-ping

    2008-11-01

    To introduce Back-propagation (BP) neural network and genetic algorithm for multi-objective optimization of extraction technology of Cortex Fraxini. BP neural network was established and optimized with uniform design. Genetic algotithm was used for multi-objective optimization of extraction technology of cortex fraxini. the optimization of extraction was as follows: extraction temperature was 99 degrees C, concentration of EtOH was 50%, liquid-solid ratio was 7, extraction time was 94 min. The proportional error between predictive value and practical measured value was just -1.16% and -5.14%. Back-propagation neural network and genetic algorithm for multi-objective optimization of extraction technology of cortex fraxini is advisable.

  17. 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. "

  18. Sensitive and selective neural control using an intraneural multielectrode stimulation device in silicon technology

    NARCIS (Netherlands)

    Rutten, Wim; van Wier, H.J.; Put, J.H.M.; Meier, J.H.

    1988-01-01

    The ideal neural stimulatory information transducer must be able to activate individual neural fibers within a fascicular bundle, for example in a sensory or motor nerve. In a local approach using microelectrodes it is sufficient to apply current pulses to one neural node in order to reach the

  19. A wireless recording system that utilizes Bluetooth technology to transmit neural activity in freely moving animals.

    Science.gov (United States)

    Hampson, Robert E; Collins, Vernell; Deadwyler, Sam A

    2009-09-15

    A new wireless transceiver is described for recording individual neuron firing from behaving rats utilizing Bluetooth transmission technology and a processor onboard for discrimination of neuronal waveforms and associated time stamps. This universal brain activity transmitter (UBAT) is attached to rodents via a backpack and amplifier headstage and can transmit 16 channels of captured neuronal firing data via a Bluetooth transceiver chip over very large and unconstrained distances. The onboard microprocessor of the UBAT allows flexible online control over waveform isolation criteria via transceiver instruction and the two-way communication capacity allows for closed-loop applications between neural events and behavioral or physiological processes which can be modified by transceiver instructions. A detailed description of the multiplexer processing of channel data as well as examples of neuronal recordings in different behavioral testing contexts is provided to demonstrate the capacity for robust transmission within almost any laboratory environment. A major advantage of the UBAT is the long transmission range and lack of object-based line of sight interference afforded by Bluetooth technology, allowing flexible recording capabilities within multiple experimental paradigms without interruption. Continuous recordings over very large distance separations from the monitor station are demonstrated providing experimenters with recording advantages not previously available with other telemetry devices.

  20. 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.

  1. 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....

  2. International Clean Energy System Using Hydrogen Conversion (WE-NET). subtask 4. Development of hydrogen production technology; Suiso riyo kokusai clean energy system gijutsu (WE-NET). subtask 4. Suiso seizo gijutsu no kaihatsu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    This paper describes development of hydrogen production technology as a part of the WE-NET project. For the solid polymer water electrolysis method higher in efficiency and lower in cost than the previous methods, 5 companies have developed element technologies for improving electrolysis cells and synthesis technologies of hot solid polymer electrolyte based on each proper catalyst electrode production method. In fiscal 1996, the initial study on large-scale systems by middle laboratory cells was made as well as improvement of electrolysis performance by small laboratory cells and endurance tests. Among the previous methods such as a hot press method (bonding of an ion exchange membrane to an electrode), an electroless plating method (preparation of porous surface onto a membrane electrode assembly), a zero gap method (preparation of high-efficiency high-current density cells), and a sintered porous electrode method (carrying of the mixture of catalytic powder and ion exchange resin-dissipated solution onto sintered metallic porous electrode surface), the former two methods were adopted for development of bench-scale cells as effective promising methods. 192 refs., 183 figs., 108 tabs.

  3. 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...

  4. 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

  5. Technologies enabling autologous neural stem cell-based therapies for neurodegenerative disease and injury

    Science.gov (United States)

    Bakhru, Sasha H.

    The intrinsic abilities of mammalian neural stem cells (NSCs) to self-renew, migrate over large distances, and give rise to all primary neural cell types of the brain offer unprecedented opportunity for cell-based treatment of neurodegenerative diseases and injuries. This thesis discusses development of technologies in support of autologous NSC-based therapies, encompassing harvest of brain tissue biopsies from living human patients; isolation of NSCs from harvested tissue; efficient culture and expansion of NSCs in 3D polymeric microcapsule culture systems; optimization of microcapsules as carriers for efficient in vivo delivery of NSCs; genetic engineering of NSCs for drug-induced, enzymatic release of transplanted NSCs from microcapsules; genetic engineering for drug-induced differentiation of NSCs into specific therapeutic cell types; and synthesis of chitosan/iron-oxide nanoparticles for labeling of NSCs and in vivo tracking by cellular MRI. Sub-millimeter scale tissue samples were harvested endoscopically from subventricular zone regions of living patient brains, secondary to neurosurgical procedures including endoscopic third ventriculostomy and ventriculoperitoneal shunt placement. On average, 12,000 +/- 3,000 NSCs were isolated per mm 3 of subventricular zone tissue, successfully demonstrated in 26 of 28 patients, ranging in age from one month to 68 years. In order to achieve efficient expansion of isolated NSCs to clinically relevant numbers (e.g. hundreds of thousands of cells in Parkinson's disease and tens of millions of cells in multiple sclerosis), an extracellular matrix-inspired, microcapsule-based culture platform was developed. Initial culture experiments with murine NSCs yielded unprecedented expansion folds of 30x in 5 days, from initially minute NSC populations (154 +/- 15 NSCs per 450 mum diameter capsule). Within 7 days, NSCs expanded as almost perfectly homogenous populations, with 94.9% +/- 4.1% of cultured cells staining positive for

  6. [Rapid Identification of Epicarpium Citri Grandis via Infrared Spectroscopy and Fluorescence Spectrum Imaging Technology Combined with Neural Network].

    Science.gov (United States)

    Pan, Sha-sha; Huang, Fu-rong; Xiao, Chi; Xian, Rui-yi; Ma, Zhi-guo

    2015-10-01

    To explore rapid reliable methods for detection of Epicarpium citri grandis (ECG), the experiment using Fourier Transform Attenuated Total Reflection Infrared Spectroscopy (FTIR/ATR) and Fluorescence Spectrum Imaging Technology combined with Multilayer Perceptron (MLP) Neural Network pattern recognition, for the identification of ECG, and the two methods are compared. Infrared spectra and fluorescence spectral images of 118 samples, 81 ECG and 37 other kinds of ECG, are collected. According to the differences in tspectrum, the spectra data in the 550-1 800 cm(-1) wavenumber range and 400-720 nm wavelength are regarded as the study objects of discriminant analysis. Then principal component analysis (PCA) is applied to reduce the dimension of spectroscopic data of ECG and MLP Neural Network is used in combination to classify them. During the experiment were compared the effects of different methods of data preprocessing on the model: multiplicative scatter correction (MSC), standard normal variable correction (SNV), first-order derivative(FD), second-order derivative(SD) and Savitzky-Golay (SG). The results showed that: after the infrared spectra data via the Savitzky-Golay (SG) pretreatment through the MLP Neural Network with the hidden layer function as sigmoid, we can get the best discrimination of ECG, the correct percent of training set and testing set are both 100%. Using fluorescence spectral imaging technology, corrected by the multiple scattering (MSC) results in the pretreatment is the most ideal. After data preprocessing, the three layers of the MLP Neural Network of the hidden layer function as sigmoid function can get 100% correct percent of training set and 96.7% correct percent of testing set. It was shown that the FTIR/ATR and fluorescent spectral imaging technology combined with MLP Neural Network can be used for the identification study of ECG and has the advantages of rapid, reliable effect.

  7. 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

  8. Proceedings of the Second Joint Technology Workshop on Neural Networks and Fuzzy Logic, volume 2

    Science.gov (United States)

    Lea, Robert N. (Editor); Villarreal, James A. (Editor)

    1991-01-01

    Documented here are papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by NASA and the University of Texas, Houston. Topics addressed included adaptive systems, learning algorithms, network architectures, vision, robotics, neurobiological connections, speech recognition and synthesis, fuzzy set theory and application, control and dynamics processing, space applications, fuzzy logic and neural network computers, approximate reasoning, and multiobject decision making.

  9. 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....

  10. Proceedings of the Second Joint Technology Workshop on Neural Networks and Fuzzy Logic, volume 1

    Science.gov (United States)

    Lea, Robert N. (Editor); Villarreal, James (Editor)

    1991-01-01

    Documented here are papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by NASA and the University of Houston, Clear Lake. The workshop was held April 11 to 13 at the Johnson Space Flight Center. Technical topics addressed included adaptive systems, learning algorithms, network architectures, vision, robotics, neurobiological connections, speech recognition and synthesis, fuzzy set theory and application, control and dynamics processing, space applications, fuzzy logic and neural network computers, approximate reasoning, and multiobject decision making.

  11. 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.

  12. 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.

  13. 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

  14. FY 1998 annual summary report on International Clean Energy Network Using Hydrogen Conversion (WE-NET) system technology. Subtask 9. Research and evaluation of innovative and leading technologies; 1998 nendo seika hokokusho. Suiso riyo kokusai clean energy system gijutsu (WE-NET) subtask 9 (kakushinteki, sendoteki gijutsu ni kansuru chosa kenkyu)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-03-01

    In order to make useful suggestions and proposals for the International Clean Energy Network Using Hydrogen Conversion (WE-NET) project and thereby to promote the research and development activities, the innovative and leading technologies have been studied, investigated and evaluated. In FY 1998, a total of 6 proposals were collected, and evaluated to prioritize for the conceptual studies. These are related to methanol-fueled power generation turbine system, conceptual design of high-efficiency production system for high-efficiency solar cell by the 10 GW/y scale production process, investigation of potential of wind power, CO2 recycling methanol fuel cell, investigation of catalysis materials for hydrogen combustion and catalytic combustion systems, development of reversible high-temperature steam electrolysis cell/solid oxide fuel cell by the synthesis from aqueous solutions, and mobile heat recovery hydrogen production system. Promising technologies to be reflected on the WE-NET project were examined, based on the new technologies acquired from the research and investigation so far. As a result, two candidates were selected; hydrogen liquefaction by magnetic refrigeration technology, and catalytic combustion gas turbine. (NEDO)

  15. Technology-facilitated depression care management among predominantly Latino diabetes patients within a public safety net care system: comparative effectiveness trial design.

    Science.gov (United States)

    Wu, Shinyi; Ell, Kathleen; Gross-Schulman, Sandra G; Sklaroff, Laura Myerchin; Katon, Wayne J; Nezu, Art M; Lee, Pey-Jiuan; Vidyanti, Irene; Chou, Chih-Ping; Guterman, Jeffrey J

    2014-03-01

    Health disparities in minority populations are well recognized. Hispanics and Latinos constitute the largest ethnic minority group in the United States; a significant proportion receives their care via a safety net. The prevalence of diabetes mellitus and comorbid depression is high among this group, but the uptake of evidence-based collaborative depression care management has been suboptimal. The study design and baseline characteristics of the enrolled sample in the Diabetes-Depression Care-management Adoption Trial (DCAT) establishes a quasi-experimental comparative effectiveness research clinical trial aimed at accelerating the adoption of collaborative depression care in safety net clinics. The study was conducted in collaboration with the Los Angeles County Department of Health Services at eight county-operated clinics. DCAT has enrolled 1406 low-income, predominantly Hispanic/Latino patients with diabetes to test a translational model of depression care management. This three-group study compares usual care with a collaborative care team support model and a technology-facilitated depression care model that provides automated telephonic depression screening and monitoring tailored to patient conditions and preferences. Call results are integrated into a diabetes disease management registry that delivers provider notifications, generates tasks, and issues critical alerts. All subjects receive comprehensive assessments at baseline, 6, 12, and 18 months by independent English-Spanish bilingual interviewers. Study outcomes include depression outcomes, treatment adherence, satisfaction, acceptance of assessment and monitoring technology, social and economic stress reduction, diabetes self-care management, health care utilization, and care management model cost and cost-effectiveness comparisons. DCAT's goal is to optimize depression screening, treatment, follow-up, outcomes, and cost savings to reduce health disparities. Copyright © 2013 Elsevier Inc. All rights

  16. Worldwide clean energy system technology using hydrogen (WE-NET). subtask 5. Development of hydrogen transfer and storage technology (research and development of technologies for hydrogen transport and storage by hydrogen absorbing alloys); Suiso riyo kokusai clean energy system gijutsu (WE-NET). subtask 5. Suiso yuso chozo gijutsu no kaihatsu (bunsan yuso chozoyo suiso kyuzo gokin no kaihatsu)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    This report describes a guiding principle of new hydrogen absorbing alloy design, case studies on the stationary hydrogen storage systems for multiple dwelling houses using hydrogen absorbing alloys and on the hydrogen fuel tank systems for a motor vehicle, and survey on development status in the world. As a result of the investigation of alloys, it was concluded that realization of hydrogen absorbing alloys with new target properties of the WE-NET Project is not easy through the current technology. It was found that two kinds of Mg-based and V-based high capacity materials must be selected as target alloys among current alloys, and that three techniques, i.e., ultra-fine microstructure, composite, and amorphousness, are effective for improving the hydrogen discharge property which has been a problem of these alloys. It was desired that the latest techniques are established by integrating these materials and techniques. It is necessary to promote the development of brake-through new materials by new concepts and technologies through the cooperation of national institutes, universities, and companies. 124 refs., 56 figs., 11 tabs.

  17. 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.

  18. Identification of the actual state and entity availability forecasting in power engineering using neural-network technologies

    Science.gov (United States)

    Protalinsky, O. M.; Shcherbatov, I. A.; Stepanov, P. V.

    2017-11-01

    A growing number of severe accidents in RF call for the need to develop a system that could prevent emergency situations. In a number of cases accident rate is stipulated by careless inspections and neglects in developing repair programs. Across the country rates of accidents are growing because of a so-called “human factor”. In this regard, there has become urgent the problem of identification of the actual state of technological facilities in power engineering using data on engineering processes running and applying artificial intelligence methods. The present work comprises four model states of manufacturing equipment of engineering companies: defect, failure, preliminary situation, accident. Defect evaluation is carried out using both data from SCADA and ASEPCR and qualitative information (verbal assessments of experts in subject matter, photo- and video materials of surveys processed using pattern recognition methods in order to satisfy the requirements). Early identification of defects makes possible to predict the failure of manufacturing equipment using mathematical techniques of artificial neural network. In its turn, this helps to calculate predicted characteristics of reliability of engineering facilities using methods of reliability theory. Calculation of the given parameters provides the real-time estimation of remaining service life of manufacturing equipment for the whole operation period. The neural networks model allows evaluating possibility of failure of a piece of equipment consistent with types of actual defects and their previous reasons. The article presents the grounds for a choice of training and testing samples for the developed neural network, evaluates the adequacy of the neural networks model, and shows how the model can be used to forecast equipment failure. There have been carried out simulating experiments using a computer and retrospective samples of actual values for power engineering companies. The efficiency of the developed

  19. An optical neural interface: in vivo control of rodent motor cortex with integrated fiberoptic and optogenetic technology

    Science.gov (United States)

    Aravanis, Alexander M.; Wang, Li-Ping; Zhang, Feng; Meltzer, Leslie A.; Mogri, Murtaza Z.; Schneider, M. Bret; Deisseroth, Karl

    2007-09-01

    Neural interface technology has made enormous strides in recent years but stimulating electrodes remain incapable of reliably targeting specific cell types (e.g. excitatory or inhibitory neurons) within neural tissue. This obstacle has major scientific and clinical implications. For example, there is intense debate among physicians, neuroengineers and neuroscientists regarding the relevant cell types recruited during deep brain stimulation (DBS); moreover, many debilitating side effects of DBS likely result from lack of cell-type specificity. We describe here a novel optical neural interface technology that will allow neuroengineers to optically address specific cell types in vivo with millisecond temporal precision. Channelrhodopsin-2 (ChR2), an algal light-activated ion channel we developed for use in mammals, can give rise to safe, light-driven stimulation of CNS neurons on a timescale of milliseconds. Because ChR2 is genetically targetable, specific populations of neurons even sparsely embedded within intact circuitry can be stimulated with high temporal precision. Here we report the first in vivo behavioral demonstration of a functional optical neural interface (ONI) in intact animals, involving integrated fiberoptic and optogenetic technology. We developed a solid-state laser diode system that can be pulsed with millisecond precision, outputs 20 mW of power at 473 nm, and is coupled to a lightweight, flexible multimode optical fiber, ~200 µm in diameter. To capitalize on the unique advantages of this system, we specifically targeted ChR2 to excitatory cells in vivo with the CaMKIIα promoter. Under these conditions, the intensity of light exiting the fiber (~380 mW mm-2) was sufficient to drive excitatory neurons in vivo and control motor cortex function with behavioral output in intact rodents. No exogenous chemical cofactor was needed at any point, a crucial finding for in vivo work in large mammals. Achieving modulation of behavior with optical control of

  20. 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.

  1. Fiscal 1997 survey report. Subtask 9 (hydrogen utilization worldwide clean energy system technology) (WE-NET) (survey/study on the innovative and leading technology); 1997 nendo seika hokokusho. Suiso riyo kokusai clean energy system gijutsu (WE-NET) subtask 9 kakushinteki, sendoteki gijutsu ni kansuru chosa kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-03-01

    For the purpose of giving useful suggestions/proposals to the course of WE-NET and contributing to the R and D, conducted were survey/collection/evaluation of new technologies. The paper described the fiscal 1997 results. The number of the proposals of new technology accumulated during fiscal 1993 to 1997 is 28. The proposals of new technology made in fiscal 1997 are hydrogen production effectively using solar energy by wavelength zone, hydrogen storage using fullerene, and the methanol power generation turbine system. Four technologies proposed in fiscal 1996 and 1997 were evaluated. The evaluation method requires two steps of the marking using the analytic hierarchy process (AHP) and the adjustment by the committee. The highly evaluated proposals out of those having been made were analysis/evaluation of hydrogen-oxygen internal-combustion Stirling engine, hydrogen production effectively using solar energy by wavelength zone, hydrogen production by solid oxide electrolysis, magnetic refrigeration method for hydrogen liquefaction, hydrogen production technology using photocatalyst, etc. The paper also stated the result of studying concepts of innovative/leading technologies in fiscal 1996. 4 figs., 29 tabs.

  2. Gestión Ciudadana de la Tecnología: Una aproximación desde los Science and Technology Studies a las redes wifi y la governance urbana a través de guifi.net Citizen Management of Technology: A Science and Technology Studies approach to wireless networks and urban governance trough guifi.net

    Directory of Open Access Journals (Sweden)

    Yann Bona Beauvois

    2011-03-01

    Full Text Available

    Tesis doctoral a cargo de Yann Bona presentada en el Departamento de Psicología Social de la Univesriddad Autónoma de Barcelona (UAB en diciembre del 2010. Dirigida por el Dr. Joan Pujol Tarrés.

    La tesis trata de ahondar en las formas en las que iniciativas ciudadanas que tienen por objeto la gestión de la tecnología en el espacio urbano se relacionan con las administraciones públicas. Lo hace a partir de nociones y conceptos de los STS tales como cosmopolítica, composición híbrida o democracia técnica. En síntesis, podemos decir que la tesis responde a la pregunta formulada por Bruno Latour de ¿qué significa hacer pasar la política del lado lo de la técnica?. Nosotros ofrecemos una propuesta centrada en lo que denominamos una sociotécnica de las políticas públicas.

    La tesis se basa en un estudio de caso centrado una red sin hilos libre y abierta (ubicada principalmente en Cataluña y llamada guifi.net surgida del deseo e iniciativa de la sociedad civil y que, hasta la fecha, es la más grande del mundo.

    Thesis presented at the Departament de Psicologia Social de la UAB by Yann Bona on December, 2010. Directed by Dr. Joan Pujol Tarrés.

    This dissertation explores the many ways in which citizens aiming to manage technologies in urban scape relate to public administrations. To accomplish it's task, it brings forward certain STS notions such as cosmopolitics, hybrid composition or technical democracy. On a general level, this thesis seeks an answer to Bruno Latour concern with what does it mean to conceive the technical as political?. We offer a set of conclusions based on what we choose to name a Sociotechnique of Public Policy .

    Our work relies on a case study focused on a free and open wireless network (located in Catalunya for the most part and called guifi.net that emerged from the desire and will of Civil Society wich, up to date, turns out to be the world's biggest free

  3. A Method for Assessing the Retention of Trace Elements in Human Body Using Neural Network Technology.

    Science.gov (United States)

    Tunakova, Yulia; Novikova, Svetlana; Ragimov, Aligejdar; Faizullin, Rashat; Valiev, Vsevolod

    2017-01-01

    Models that describe the trace element status formation in the human organism are essential for a correction of micromineral (trace elements) deficiency. A direct trace element retention assessment in the body is difficult due to the many internal mechanisms. The trace element retention is determined by the amount and the ratio of incoming and excreted substance. So, the concentration of trace elements in drinking water characterizes the intake, whereas the element concentration in urine characterizes the excretion. This system can be interpreted as three interrelated elements that are in equilibrium. Since many relationships in the system are not known, the use of standard mathematical models is difficult. The artificial neural network use is suitable for constructing a model in the best way because it can take into account all dependencies in the system implicitly and process inaccurate and incomplete data. We created several neural network models to describe the retentions of trace elements in the human body. On the model basis, we can calculate the microelement levels in the body, knowing the trace element levels in drinking water and urine. These results can be used in health care to provide the population with safe drinking water.

  4. 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

  5. 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

  6. Pipeline Bending Strain Measurement and Compensation Technology Based on Wavelet Neural Network

    Directory of Open Access Journals (Sweden)

    Rui Li

    2016-01-01

    Full Text Available The bending strain of long distance oil and gas pipelines may lead to instability of the pipeline and failure of materials, which seriously deteriorates the transportation security of oil and gas. To locate the position of the bending strain for maintenance, an Inertial Measurement Unit (IMU is usually adopted in a Pipeline Inspection Gauge (PIG. The attitude data of the IMU is usually acquired to calculate the bending strain in the pipe. However, because of the vibrations in the pipeline and other system noises, the resulting bending strain calculations may be incorrect. To improve the measurement precision, a method, based on wavelet neural network, was proposed. To test the proposed method experimentally, a PIG with the proposed method is used to detect a straight pipeline. It can be obtained that the proposed method has a better repeatability and convergence than the original method. Furthermore, the new method is more accurate than the original method and the accuracy of bending strain is raised by about 23% compared to original method. This paper provides a novel method for precisely inspecting bending strain of long distance oil and gas pipelines and lays a foundation for improving the precision of inspection of bending strain of long distance oil and gas pipelines.

  7. Application of Neural Network Technologies for Price Forecasting in the Liberalized Electricity Market

    Science.gov (United States)

    Gerikh, Valentin; Kolosok, Irina; Kurbatsky, Victor; Tomin, Nikita

    2009-01-01

    The paper presents the results of experimental studies concerning calculation of electricity prices in different price zones in Russia and Europe. The calculations are based on the intelligent software "ANAPRO" that implements the approaches based on the modern methods of data analysis and artificial intelligence technologies.

  8. 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...

  9. Applying artificial intelligence to astronomical databases - a surveyof applicable technology.

    Science.gov (United States)

    Rosenthal, D. A.

    This paper surveys several emerging technologies which are relevant to astronomical database issues such as interface technology, internal database representation, and intelligent data reduction aids. Among the technologies discussed are natural language understanding, frame and object representations, planning, pattern analysis, machine learning and the nascent study of simulated neural nets. These techniques will become increasingly important for astronomical research, and in particular, for applications with large databases.

  10. Energy indicators for electricity production : comparing technologies and the nature of the indicators Energy Payback Ratio (EPR), Net Energy Ratio (NER) and Cumulative Energy Demand (CED). [Oestfoldforskning AS

    Energy Technology Data Exchange (ETDEWEB)

    Raadal, Hanne Lerche [Ostfold research, Fredrikstad (Norway); Modahl, Ingunn Saur [Ostfold research, Fredrikstad (Norway); Bakken, Tor Haakon [SINTEF Energy, Trondheim (Norway)

    2012-11-01

    CEDREN (Centre for Environmental Design of Renewable Energy) is founded by The Research Council of Norway and energy companies and is one of eight centres that were part of the scheme Centre for Environment-friendly Energy Research (FME) when the scheme was launched in 2009. The main objective of CEDREN is to develop and communicate design solutions for transforming renewable energy sources to the desired energy products, and at the same time address the environmental and societal challenges at local, regional, national and global levels. CEDREN's board initiated in 2011 a pilot project on the topics 'Energy Pay-back Ratio (EPR)', 'Ecosystem services' and 'multi-criteria analysis (MCA)' in order to investigate the possible use of these concepts/indices in the management of regulated river basins and as tools to benchmark strategies for the development of energy projects/resources. The energy indicator part (documented in this report) has aimed at reviewing the applicability of different energy efficiency indicators, as such, in the strategic management and development of energy resources, and to compare and benchmark technologies for production of electricity. The main findings from this pilot study is also reported in a policy memo (in Norwegian), that is available at www.cedren.no. The work carried out in this project will be continued in the succeeding research project EcoManage, which was granted by the Research Council of Norway's RENERGI programme in December 2011. Energy indicators: Several energy indicators for extraction and delivery of an energy product (e.g. transport fuel, heat, electricity etc.) exist today. The main objective of such indicators is to give information about the energy efficiency of the needed extraction and transforming processes throughout the value chain related to the delivered energy product. In this project the indicators Energy Payback Ratio (EPR), Net Energy Ration (NER) and Cumulative

  11. An Empirical Study of Neural Network-Based Audience Response Technology in a Human Anatomy Course for Pharmacy Students.

    Science.gov (United States)

    Fernández-Alemán, José Luis; López-González, Laura; González-Sequeros, Ofelia; Jayne, Chrisina; López-Jiménez, Juan José; Carrillo-de-Gea, Juan Manuel; Toval, Ambrosio

    2016-04-01

    This paper presents an empirical study of a formative neural network-based assessment approach by using mobile technology to provide pharmacy students with intelligent diagnostic feedback. An unsupervised learning algorithm was integrated with an audience response system called SIDRA in order to generate states that collect some commonality in responses to questions and add diagnostic feedback for guided learning. A total of 89 pharmacy students enrolled on a Human Anatomy course were taught using two different teaching methods. Forty-four students employed intelligent SIDRA (i-SIDRA), whereas 45 students received the same training but without using i-SIDRA. A statistically significant difference was found between the experimental group (i-SIDRA) and the control group (traditional learning methodology), with T (87) = 6.598, p SIDRA and the methodology used during the process of learning anatomy (M = 4.59). The new empirical contribution presented in this paper allows instructors to perform post hoc analyses of each particular student's progress to ensure appropriate training.

  12. Neural correlates of Early Stone Age toolmaking: technology, language and cognition in human evolution.

    Science.gov (United States)

    Stout, Dietrich; Toth, Nicholas; Schick, Kathy; Chaminade, Thierry

    2008-06-12

    Archaeological and palaeontological evidence from the Early Stone Age (ESA) documents parallel trends of brain expansion and technological elaboration in human evolution over a period of more than 2Myr. However, the relationship between these defining trends remains controversial and poorly understood. Here, we present results from a positron emission tomography study of functional brain activation during experimental ESA (Oldowan and Acheulean) toolmaking by expert subjects. Together with a previous study of Oldowan toolmaking by novices, these results document increased demands for effective visuomotor coordination and hierarchical action organization in more advanced toolmaking. This includes an increased activation of ventral premotor and inferior parietal elements of the parietofrontal praxis circuits in both the hemispheres and of the right hemisphere homologue of Broca's area. The observed patterns of activation and of overlap with language circuits suggest that toolmaking and language share a basis in more general human capacities for complex, goal-directed action. The results are consistent with coevolutionary hypotheses linking the emergence of language, toolmaking, population-level functional lateralization and association cortex expansion in human evolution.

  13. Fiscal 1997 survey report. Subtask 6 (hydrogen utilization worldwide clean energy system technology) (WE-NET) (development of technology of low temperature materials); 1997 nendo seika hokokusho. Suiso riyo kokusai clean energy system gijutsu (WE-NET) subtask 6 teion zairyo gijutsu no kaihatsu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-03-01

    The paper described the results of the development of technology of low temperature materials in the fiscal 1997 WE-NET. Using experimental equipment for materials under the atmosphere of liquid hydrogen, an experiment on mechanical characteristics under the liquid hydrogen atmosphere (20K) was conducted of the base materials of candidate steels (SUS304L, SUS316L and A5083). In material evaluation experiments (tension/fracture toughness/fracture tests), characteristic behaviors of the materials were shown which are different from those shown in the environment of liquid He (4k), etc. Even if the amount of {delta} ferrite in the metal welded of the stainless steel is small, approximately 1%, the degradation of low temperature toughness occurred. Welded joints of stainless steel by submerged arc welding and MAG welding were in now way inferior in tension characteristic to those by TIG welding, but were inferior in toughness ranging from room temperature to extremely low temperature. As to aluminum alloys, materials excellent in extremely-low temperature toughness were able to be found. Under the low temperature hydrogen gas atmosphere, the lower the strain rate is, the higher the hydrogen brittleness susceptibility is around 220K (extremely large hydrogen brittleness temperature) (SUS304L). In the hydrogen gas of 100 atm, hydrogen invades the material at 100degC, but does not at 77k. 38 refs., 173 figs., 48 tabs.

  14. Fiscal 1997 survey report. Subtask 3 (hydrogen utilization worldwide clean system technology) (WE-NET) (total system conceptual design/safety measures/evaluation technology); 1997 nendo seika hokokusho. Suiso riyo kokusai clean energy system gijutsu (WE-NET) subtask 3 zentai system gainen sekkei - anzen taisaku hyoka gijutsu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-03-01

    Concerning the study of safety measures in WE-NET, the paper described the fiscal 1997 results. For drawing up a policy for safety design, technology of preserving hydrogen at high temperature/pressure, continuing collecting information on existing plants (liquid hydrogen, LNG). Investigating manuals of NASA and NASDA and also referring to people`s opinions at chemical plants, etc., the study entered into the setting-up of the safety policy and design standards. Examples of anomalies/accidents were extracted, and classification/arrangement were commenced of the measures for anomalies of detection/prevention/protection. Toward the diffusion of hydrogen and the enhancement and unification of explosion/fire simulation models, the extraction of problems has been almost finished. The second mini work shop on safety was held in the U.S., and exchanges of information were made among researchers of each country. All agreed on the importance of collecting data as the base of safety standards. As to safety measures in various tests using combustor evaluation experimental facilities, experimental equipment for materials under liquid hydrogen and experimental equipment of thermal insulation under liquid hydrogen, problems were extracted between researchers and people concerned with safety measures, and the measures to solve them were studied. 18 refs., 31 figs., 10 tabs.

  15. 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.

  16. FY 1998 annual summary report on International Clean Energy Network Using Hydrogen Conversion (WE-NET) system technology. Subtask 2. Examination and promotion of measures to obtain international understanding and cooperation; 1998 nendo seika hokokusho. Suiso riyo kokusai clean energy system gijutsu (WE-NET) subtask 2 (kokusai kyoryoku shuishin no tame no chosa kento)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-03-01

    Described herein are the results of examination and promotion of measures to obtain international understanding and cooperation, and examination and development of measures to promote international exchange of technical information, conducted in the FY 1998 continuously from the previous year, with the object to realize the International Clean Energy Network Using Hydrogen Conversion (WE-NET) project. In the FY 1998, the English version of the 1997 annual summary report was distributed to a total of about 150 overseas organizations. The WE-NET project activities were presented to the 12th World Hydrogen Energy Conference, International Joint Power Generation Conference held in 1998 by American Society of Mechanical Engineers, and 2nd International Symposium on Advanced Energy Conversion Systems and Related Technologies. For the examination and development of measures to promote international exchange of technical information, the contracting party of Japan for the Hydrogen Implementation Agreement with IEA has been shifted from the government of Japan to NEDO. NEDO has been representing Japan for various workshops on the tasks. The hydrogen projects conducted by Germany and USA were also surveyed. The WE-NET project homepage was opened in June, 1998. (NEDO)

  17. 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.

  18. 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.

  19. 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....

  20. High-density microelectrode array recordings and real-time spike sorting for closed-loop experiments: an emerging technology to study neural plasticity.

    Science.gov (United States)

    Franke, Felix; Jäckel, David; Dragas, Jelena; Müller, Jan; Radivojevic, Milos; Bakkum, Douglas; Hierlemann, Andreas

    2012-01-01

    Understanding plasticity of neural networks is a key to comprehending their development and function. A powerful technique to study neural plasticity includes recording and control of pre- and post-synaptic neural activity, e.g., by using simultaneous intracellular recording and stimulation of several neurons. Intracellular recording is, however, a demanding technique and has its limitations in that only a small number of neurons can be stimulated and recorded from at the same time. Extracellular techniques offer the possibility to simultaneously record from larger numbers of neurons with relative ease, at the expenses of increased efforts to sort out single neuronal activities from the recorded mixture, which is a time consuming and error prone step, referred to as spike sorting. In this mini-review, we describe recent technological developments in two separate fields, namely CMOS-based high-density microelectrode arrays, which also allow for extracellular stimulation of neurons, and real-time spike sorting. We argue that these techniques, when combined, will provide a powerful tool to study plasticity in neural networks consisting of several thousand neurons in vitro.

  1. 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.

  2. Multimedia Information eXchange for I-NET, Inc. at the Kennedy Space Center: A continuing study of the application of worldwideweb technology

    Science.gov (United States)

    Metcalf, David

    1995-01-01

    Multimedia Information eXchange (MIX) is a multimedia information system that accommodates multiple data types and provides consistency across platforms. Information from all over the world can be accessed quickly and efficiently with the Internet-based system. I-NET's MIX uses the World Wide Web and Mosaic graphical user interface. Mosaic is available on all platforms used at I-NET's Kennedy Space Center (KSC) facilities. Key information system design concepts and benefits are reviewed. The MIX system also defines specific configuration and helper application parameters to ensure consistent operations across the entire organization. Guidelines and procedures for other areas of importance in information systems design are also addressed. Areas include: code of ethics, content, copyright, security, system administration, and support.

  3. 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...

  4. 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

  5. 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

  6. "Watts per person" paradigm to design net zero energy buildings: Examining technology interventions and integrating occupant feedback to reduce plug loads in a commercial building

    Science.gov (United States)

    Yagi Kim, Mika

    As building envelopes have improved due to more restrictive energy codes, internal loads have increased largely due to the proliferation of computers, electronics, appliances, imaging and audio visual equipment that continues to grow in commercial buildings. As the dependency on the internet for information and data transfer increases, the electricity demand will pose a challenge to design and operate Net Zero Energy Buildings (NZEBs). Plug Loads (PLs) as a proportion of the building load has become the largest non-regulated building energy load and represents the third highest electricity end-use in California's commercial office buildings, accounting for 23% of the total building electricity consumption (Ecova 2011,2). In the Annual Energy Outlook 2008 (AEO2008), prepared by the Energy Information Administration (EIA) that presents long-term projections of energy supply and demand through 2030 states that office equipment and personal computers are the "fastest growing electrical end uses" in the commercial sector. This thesis entitled "Watts Per Person" Paradigm to Design Net Zero Energy Buildings, measures the implementation of advanced controls and behavioral interventions to study the reduction of PL energy use in the commercial sector. By integrating real world data extracted from an energy efficient commercial building of its energy use, the results produce a new methodology on estimating PL energy use by calculating based on "Watts Per Person" and analyzes computational simulation methods to design NZEBs.

  7. 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.

  8. Problem-Solving Skills Among Precollege Students in Clinical Immunology and Microbiology: Classifying Strategies with a Rubric and Artificial Neural Network Technology

    Science.gov (United States)

    KANOWITH-KLEIN, SUSAN; STAVE, MEL; STEVENS, RON; CASILLAS, ADRIAN M.

    2001-01-01

    Educators emphasize the importance of problem solving that enables students to apply current knowledge and understanding in new ways to previously unencountered situations. Yet few methods are available to visualize and then assess such skills in a rapid and efficient way. Using a software system that can generate a picture (i.e., map) of students’ strategies in solving problems, we investigated methods to classify problem-solving strategies of high school students who were studying infectious and noninfectious diseases. Using maps that indicated items students accessed to solve a software simulation as well as the sequence in which items were accessed, we developed a rubric to score the quality of the student performances and also applied artificial neural network technology to cluster student performances into groups of related strategies. Furthermore, we established that a relationship existed between the rubric and neural network results, suggesting that the quality of a problem-solving strategy could be predicted from the cluster of performances in which it was assigned by the network. Using artificial neural networks to assess students’ problem-solving strategies has the potential to permit the investigation of the problem-solving performances of hundreds of students at a time and provide teachers with a valuable intervention tool capable of identifying content areas in which students have specific misunderstandings, gaps in learning, or misconceptions. PMID:23653541

  9. ALPHABET SIGN LANGUAGE RECOGNITION USING LEAP MOTION TECHNOLOGY AND RULE BASED BACKPROPAGATION-GENETIC ALGORITHM NEURAL NETWORK (RBBPGANN

    Directory of Open Access Journals (Sweden)

    Wijayanti Nurul Khotimah

    2017-01-01

    Full Text Available Sign Language recognition was used to help people with normal hearing communicate effectively with the deaf and hearing-impaired. Based on survey that conducted by Multi-Center Study in Southeast Asia, Indonesia was on the top four position in number of patients with hearing disability (4.6%. Therefore, the existence of Sign Language recognition is important. Some research has been conducted on this field. Many neural network types had been used for recognizing many kinds of sign languages. However, their performance are need to be improved. This work focuses on the ASL (Alphabet Sign Language in SIBI (Sign System of Indonesian Language which uses one hand and 26 gestures. Here, thirty four features were extracted by using Leap Motion. Further, a new method, Rule Based-Backpropagation Genetic Al-gorithm Neural Network (RB-BPGANN, was used to recognize these Sign Languages. This method is combination of Rule and Back Propagation Neural Network (BPGANN. Based on experiment this pro-posed application can recognize Sign Language up to 93.8% accuracy. It was very good to recognize large multiclass instance and can be solution of overfitting problem in Neural Network algorithm.

  10. 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

  11. Fiscal 1998 research report on International Clean Energy Network using Hydrogen Conversion (WE-NET). Subtask 2. Research on promotion of international cooperation (research on standardization of hydrogen energy technologies); 1998 nendo suiso riyo kokusai clean energy system gijutsu (WE-NET) sub task. 2. Kokusai kyoryoku suishin no tame no chosa kento (suiso energy gijutsu hyojunka ni kansuru chosa kento)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-03-01

    This report summarizes the fiscal 1998 research result on the basic research on standardization of hydrogen energy technologies, and ISO/TC197. As for the standardization, in relation to the hydrogen station in the WE-NET second phase research, the laws related to handling of gaseous hydrogen, and the basic issues on facility and safe handling were studied. As for ISO/TC197, the following draft standards were examined: Fuel supply system interface for liquid hydrogen vehicles, fuel tank for liquid hydrogen vehicles, container for liquid hydrogen transport, specification of hydrogen fuel, hydrogen fuel supply facility for air ports, gaseous hydrogen and hydrogen mixture fuel system for vehicles, gaseous hydrogen fuel connector for vehicles, gaseous hydrogen fuel tank for vehicles, and basic items for hydrogen system safety. Final examination of the fuel supply system interface for liquid hydrogen vehicles, and the specification of hydrogen fuel was finished, and these are scheduled to be registered for ISO. (NEDO)

  12. 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...

  13. 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...

  14. 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...

  15. 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.

  16. 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…

  17. 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...

  18. 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...

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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...

  5. 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...

  6. 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...

  7. 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

  8. 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

  9. 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...

  10. Fiscal 1997 survey report. Subtask 4 (hydrogen utilization worldwide clean energy system technology) (WE-NET) (development of hydrogen production technology); 1997 nendo seika hokokusho. Suiso riyo kokusai clean energy system gijutsu (WE-NET) subtask 4 suiso seizo gijutsu no kaihatsu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-03-01

    As a WE-NET subtask, a study has been conducted of the solid polyelectrolyte water electrolysis method by which higher efficiency and lower cost hydrogen production is expected than in the conventional hydrogen production method. Production methods of electrode, electrolyte, etc. were studied. In the electroless plating method, the manufacturing process of membrane-electrode assemblies was realized in a large area of 2500 cm{sup 2} by the porous-surfaced method by studying manufacturing conditions for slurry membrane/membrane assembly/electroless plating processes. In the hot-press method, the refining degree and dispersibility of iridium dioxide powder were studied to improve characteristics of anode catalyst. A method was developed to form polyelectrolyte coatings homogeneously on the surface of electrode layer catalytic powder, and a large area of 2500 cm{sup 2} was realized. Beside the performance test using large single cells, FS was conducted to discuss optimum operating conditions and optimum structures of plants. Both methods indicated the performance exceeding the energy conversion efficiency of 90%, a WE-NET target, at current density of 1A/cm{sup 2} and electrolysis temperature of 80degC. A key was found to a bench-scale development (electrode area of 2500 cm{sup 2}, about 5 layers) to be planned in fiscal 1998. 136 figs., 50 tabs.

  11. Achievement report for fiscal 2000 on the phase II research and development for the hydrogen utilizing international clean energy system technology (WE-NET). Task 1. Investigations and researched on system assessment; 2000 nendo suiso riyo kokusai clean energy system gijutsu (WE-NET) dai 2 ki kenkyu kaihatsu. Task 1. System hyoka ni kansuru chosa kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-03-01

    This paper describes the achievements in fiscal 2000 from the WE-NET Phase II for Task-1. Technologies drawing attentions relate to fuel cell driven automobiles and hybrid automobiles in the field of utilizing hydrogen derived from reproducible energies and fossil energies, and fuel cell co-generation and micro gas turbine co-generation in the field of electric power generation. Hydrogen reformed from gasoline on board the automobile as the fuel for fuel cell driven automobiles, hydrogen as a by-product of coke furnace off-gas (COG), and reproducible energy hydrogen have the same fuel consumption performance as in the hybrid automobiles. Particularly the COG is low in cost, and has large supply potential. Liquefied hydrogen is as promising as compressed hydrogen in view of the cost for automotive hydrogen supply stations. What has high economic performance as the self-sustaining systems for islands are photovoltaic and wind power generation, and the system using hydrogen as the secondary energy. Since much of the reproducible energies is used for electric power demand in Japan, the by-product hydrogen and the reformed hydrogen in an amount of 9.3 billion Nm{sup 3}/year would take care of majority of the demand in view of the short time period. For a longer time span, hydrogen originated from the reproduced energies in the Pan-Pacific Region should be introduced. (NEDO)

  12. 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

  13. 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.

  14. 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...

  15. 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...

  16. 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.

  17. 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)

  18. 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.

  19. 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 ...

  20. 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...

  1. 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.

  2. 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…

  3. 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...

  4. Assembling traces, or the conservation of net art

    NARCIS (Netherlands)

    Dekker, A.

    2014-01-01

    Net art is built and distributed through a complex, intricate, and interrelated system of networks that presents an assemblage of art, technology, politics, and social relations ‐ all merged and related to form a variable entity. In the last decade a discussion on how to conserve net art emerged in

  5. THE EVALUATION SYSTEM OF DESIGN SOLUTIONS FOR RESIDENTIAL PROPERTY ON THE PRE-INVESTMENT STAGE THROUGH NEURAL NETWORK TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    G. D. Kostsikava

    2016-01-01

    Full Text Available Ever since the Soviet Union design solutions were evaluated according to different criteria and indicators. At the present stage of evaluation systems of design solutions stands systemengineering doctrine is allocated. It is complemented by the theory of efficiency and financial sustainability investment project in view of the general market concept. Also great attention is paid to the virtual object modeling. It is urgent to include the behavior prediction of an investment construction project model at each stage of its life cycle. The high cost of all phases of this life cycle makes it necessary to calculate the feasibility of the investment. Very urgent to do it as accurately as possible and before we start of design works on the stage of the investment plan evaluation. Belarus has legislated pre-investment stage of construction project development. To evaluate the design solution at this stage is necessary to develop an investment justification, a project management plan and a business plan. They will evaluate and will compare several options for future objects by the complex. This requires not only time, but considerable financial costs. In order to optimize the process to develop an evaluation system design solutions based on existing projects. It allows the customer (investor choose design solutions to build the object without developing of pre-design documentations for several options. This system it is advisable to try out the example of apartment house building with the assistance of the national fund of project documentation and objects-analogues data bank. The developed evaluation system of design solutions for residential real estate objects in the pre-investment stage is supposed to use the theory of neural networks and neyroprogramming. This system bases on the input parameters projects. The hidden layer neurons are trained to choose suitable projects of apartment houses with their classification. The projects will be classified

  6. Worldwide clean energy system technology using hydrogen (WE-NET). Subtask 5. Development of hydrogen transfer and storage technology (development of various common equipment); Suiso riyo kokusai clean energy system gijutsu (WE-NET). subtask 5. Suiso yuso chozo gijutsu no kaihatsu (kakushu kyotsu kikirui no kaihatsu)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    This report describes large pumps for liquid hydrogen, large-size vacuum-insulated tubes, valves for liquid hydrogen, and instrumentation equipment. In the WE-NET Project, large pumps for liquid hydrogen are to be used for feeding pressurized liquid hydrogen to the combustors in power generative facilities as well as transferring large amounts of liquid hydrogen in liquefying facilities, and to or from tankers, etc. As a result of the examination, axial flow pump and mixed flow pump are to be applied to the large pumps, and centrifugal pump is to be applied to the pressurized pump. A vertical shaft wet motor pump which is directly connected to wound-rotor induction motor has been adopted as a basic specification. For the large-size vacuum-insulated tubes, examination has been conducted with the emphasis on method of relaxing the thermal stress from the viewpoint of transferring the liquid hydrogen at large flow-rate and cryogenic temperature in a stable and safe manner over long distances. It has been shown that the development of marine loading arm is indispensable. For the valves for liquid hydrogen, a ball valve and a butterfly valve, which are operated pneumatically, have been investigated. For the instrumentation equipment, level sensor for tanks, flow meter, and method of leakage detection have been examined. 315 refs., 50 figs., 16 tabs.

  7. 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...

  8. 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...

  9. NETS ettevõtlusprogrammi äriideede konkurss

    Index Scriptorium Estoniae

    2006-01-01

    NETS (New Entrepreneurs in Technology and Science) ettevõtlusprogrammi raames toimuvale äriideede konkursile on osalema oodatud ettevõtjad, teadlased ja üliõpilased, et luua uusi tooteid ja teenuseid ettevõtluses

  10. 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.

  11. WheelchairNet

    Science.gov (United States)

    ... collaboration with Joseph Kenchi and the Socio Economic Empowerment of Persons with Disabilities (SEEPD) Program, facilitated a ... Department of Rehabilitation Science and Technology in the School of Rehabilitation Science and Technology at the University ...

  12. 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

  13. 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

  14. 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)

  15. 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...

  16. Fiscal 1997 survey report. Subtask 2 (hydrogen utilization worldwide clean energy system technology) (WE-NET) (survey/study for the promotion of international cooperation); 1997 nendo seika hokokusho. Suiso riyo kokusai clean energy system gijutsu (WE-NET) subtask 2 (kokusai kyoryoku suishin no tame no choa kento)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-03-01

    The survey was aimed at developing the WE-NET as a joint project worldwide by taking concrete measures such PR activities to obtain international understanding and cooperation of WE-NET based on the survey/grasp of researches of research institutes in each country and the developmental trend of hydrogen energy in each of the main countries. Implementing a `long-term vision for the WE-NET international cooperation,` the following measures were taken in fiscal 1997. PR activities were positively developed which coped with the worldwide increasing interest in WE-NET such as delivery to overseas institutions of the fiscal 1996 survey report in English summarized by NEDO and information exchanges, and participation in international conferences and presentation of the research results. From a standpoint of positively proceeding with the international technical information exchange, the following were conducted following fiscal 1996: 1) the evaluation study jointly made with Stanford University of effects of reducing air pollution by introducing hydrogen cars, 2) survey on the U.S. hydrogen project, and 3) preparation for opening of the WE-NET internet home pages. 17 figs., 18 tabs.

  17. Evaluating the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks

    Science.gov (United States)

    Ortiz-Rodríguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.; Solís Sánches, L. O.; Miranda, R. Castañeda; Cervantes Viramontes, J. M.; Vega-Carrillo, H. R.

    2013-07-01

    In this work the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks is evaluated. The first one code based on traditional iterative procedures and called Neutron spectrometry and dosimetry from the Universidad Autonoma de Zacatecas (NSDUAZ) use the SPUNIT iterative algorithm and was designed to unfold neutron spectrum and calculate 15 dosimetric quantities and 7 IAEA survey meters. The main feature of this code is the automated selection of the initial guess spectrum trough a compendium of neutron spectrum compiled by the IAEA. The second one code known as Neutron spectrometry and dosimetry with artificial neural networks (NDSann) is a code designed using neural nets technology. The artificial intelligence approach of neural net does not solve mathematical equations. By using the knowledge stored at synaptic weights on a neural net properly trained, the code is capable to unfold neutron spectrum and to simultaneously calculate 15 dosimetric quantities, needing as entrance data, only the rate counts measured with a Bonner spheres system. Similarities of both NSDUAZ and NSDann codes are: they follow the same easy and intuitive user's philosophy and were designed in a graphical interface under the LabVIEW programming environment. Both codes unfold the neutron spectrum expressed in 60 energy bins, calculate 15 dosimetric quantities and generate a full report in HTML format. Differences of these codes are: NSDUAZ code was designed using classical iterative approaches and needs an initial guess spectrum in order to initiate the iterative procedure. In NSDUAZ, a programming routine was designed to calculate 7 IAEA instrument survey meters using the fluence-dose conversion coefficients. NSDann code use artificial neural networks for solving the ill-conditioned equation system of neutron spectrometry problem through synaptic weights of a properly trained neural network. Contrary to iterative procedures, in neural

  18. 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.

  19. 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

  20. 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.

  1. Values in the Net Neutrality Debate: Applying Content Analysis to Testimonies from Public Hearings

    Science.gov (United States)

    Cheng, An-Shou

    2012-01-01

    The Net neutrality debate is an important telecommunications policy issue that closely tied to technological innovation, economic development, and information access. Existing studies on Net neutrality have focused primarily on technological requirements, economic analysis, and regulatory justifications. Since values, technology, and policy are…

  2. 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....

  3. Fiscal 1997 survey report. Subtask 5 (hydrogen utilization worldwide clean energy system technology) (WE-NET) (development of hydrogen transportation/storage technology. 2. development of the liquid hydrogen transportation tanker); 1997 nendo seika hokokusho. Suiso riyo kokusai clean energy system gijutsu (WE-NET) subtask 5 suiso yuso chozo gijutsu no kaihatsu dai 2 hen ekitai suiso yuso tanker no kaihatsu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-03-01

    Technology development is being conducted for construction of the long distance transportation tanker of large quantity liquid hydrogen. In fiscal 1997, test pieces of thermal insulating materials to be planned for fiscal 1998 were designed and studied. The purpose of the test is to confirm thermal insulating performance and behaviors of each material under the temperature of liquid hydrogen. The inside of the outer tank of the experimental equipment was held at vacuum of 10{sup -6} to 10{sup -7} Torr to exclude thermal convection effects and evaluate only heat coming from heater through the test piece. The heat from the heater at the lower part of the test piece is through the test piece and makes the liquid hydrogen of the upper tank evaporate. Thermal conductivity of the test piece is calculated from the evaporation quantity. As to PUF (polyurethane foam) panels, studied were reformation preventive measures, influential evaluation of the side transfer heat quantity, and the time required for vacuuming. In the vacuum panel, study subjects were extracted on the selection of core materials, reformation preventive measures, deterioration with age, the practical manufacturing method of experimental panels, etc. As to the super insulation, subjects were studied on the performance measuring method/accuracy, measures against heat transfer from the inside of the experimental equipment, control of the vacuum degree, etc. 10 refs., 45 figs., 6 tabs.

  4. Achievement report for fiscal 2000 on the phase II research and development for hydrogen utilizing international clean energy system technology (WE-NET). Task 9. Development of liquid hydrogen transportation and storage technologies - 1; 2000 nendo suiso riyo kokusai clean energy system gijutsu (WE-NET) dai 2 ki kenkyu kaihatsu. Task 9. Ekitai suiso yuso chozo gijutsu no kaihatsu - 1

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-03-01

    This paper describes the achievements in fiscal 2000 from the development of liquid hydrogen transportation and storage technologies. Discussions were given on the following three types of specimens as the heat insulation performance test structures: the vacuum panel type (polyurethane foam coated with SUS sheet, while the inside is kept in the vacuum state); the solid vacuum type (combination of polyurethane foam with vacuum heat insulation); and the powder under normal pressure type (a structure in which the ambient of powder pearlite heat insulating material becomes the atmospheric pressure, whereas a SUS case is set up to separate vacuum layer of the test apparatus from atmosphere layer of the specimen, with the SUS case filled with pearlite). Adding the two types of specimens used in the previous fiscal year, five test specimens in total were discussed on the result of the performance tests to advance the database management. As a low temperature strength test for the insulating materials, the compression test was performed on a microsphere being a kind of solid vacuum (normal pressure) heat insulating materials at room temperature, the liquid nitrogen temperature and in liquid hydrogen atmosphere. The compression strength under liquid hydrogen is 1,044 MPa, which is two times greater than the normal temperature strength of 496 MPa, representing the compression strength rising in proportion with temperature drop. Problems were extracted in developing a small capacity liquid hydrogen transportation and storage system. (NEDO)

  5. 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.

  6. 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.

  7. Genetic and epigenetic drivers of neuroendocrine tumours (NET).

    Science.gov (United States)

    Di Domenico, Annunziata; Wiedmer, Tabea; Marinoni, Ilaria; Perren, Aurel

    2017-09-01

    Neuroendocrine tumours (NET) of the gastrointestinal tract and the lung are a rare and heterogeneous group of tumours. The molecular characterization and the clinical classification of these tumours have been evolving slowly and show differences according to organs of origin. Novel technologies such as next-generation sequencing revealed new molecular aspects of NET over the last years. Notably, whole-exome/genome sequencing (WES/WGS) approaches underlined the very low mutation rate of well-differentiated NET of all organs compared to other malignancies, while the engagement of epigenetic changes in driving NET evolution is emerging. Indeed, mutations in genes encoding for proteins directly involved in chromatin remodelling, such as DAXX and ATRX are a frequent event in NET. Epigenetic changes are reversible and targetable; therefore, an attractive target for treatment. The discovery of the mechanisms underlying the epigenetic changes and the implication on gene and miRNA expression in the different subgroups of NET may represent a crucial change in the diagnosis of this disease, reveal new therapy targets and identify predictive markers. Molecular profiles derived from omics data including DNA mutation, methylation, gene and miRNA expression have already shown promising results in distinguishing clinically and molecularly different subtypes of NET. In this review, we recapitulate the major genetic and epigenetic characteristics of pancreatic, lung and small intestinal NET and the affected pathways. We also discuss potential epigenetic mechanisms leading to NET development. © 2017 Society for Endocrinology.

  8. 77 FR 20888 - Proposed Information Collection (Income, Net Worth, and Employment Statement) Activity: Comment...

    Science.gov (United States)

    2012-04-06

    ... AFFAIRS Proposed Information Collection (Income, Net Worth, and Employment Statement) Activity: Comment... forms of information technology. Title: Income, Net Worth, and Employment Statement. OMB Control Number... to obtain current employment, dependency, and family income and net worth information to determine a...

  9. 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.

  10. 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

  11. Communication Technologies for Vehicles

    DEFF Research Database (Denmark)

    Vinel, Alexey

    This book constitutes the proceedings of the 8th International Workshop on Communication Technologies for Vehicles, Nets4Cars/Nets4Trains/Nets4Aircraft 2015, held in Sousse, Tunisia, in May 2015. The 20 papers presented in this volume were carefully reviewed and selected from 27 submissions. The ...

  12. 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.

  13. 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...

  14. 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

  15. TasselNet: counting maize tassels in the wild via local counts regression network.

    Science.gov (United States)

    Lu, Hao; Cao, Zhiguo; Xiao, Yang; Zhuang, Bohan; Shen, Chunhua

    2017-01-01

    Accurately counting maize tassels is important for monitoring the growth status of maize plants. This tedious task, however, is still mainly done by manual efforts. In the context of modern plant phenotyping, automating this task is required to meet the need of large-scale analysis of genotype and phenotype. In recent years, computer vision technologies have experienced a significant breakthrough due to the emergence of large-scale datasets and increased computational resources. Naturally image-based approaches have also received much attention in plant-related studies. Yet a fact is that most image-based systems for plant phenotyping are deployed under controlled laboratory environment. When transferring the application scenario to unconstrained in-field conditions, intrinsic and extrinsic variations in the wild pose great challenges for accurate counting of maize tassels, which goes beyond the ability of conventional image processing techniques. This calls for further robust computer vision approaches to address in-field variations. This paper studies the in-field counting problem of maize tassels. To our knowledge, this is the first time that a plant-related counting problem is considered using computer vision technologies under unconstrained field-based environment. With 361 field images collected in four experimental fields across China between 2010 and 2015 and corresponding manually-labelled dotted annotations, a novel Maize Tassels Counting (MTC) dataset is created and will be released with this paper. To alleviate the in-field challenges, a deep convolutional neural network-based approach termed TasselNet is proposed. TasselNet can achieve good adaptability to in-field variations via modelling the local visual characteristics of field images and regressing the local counts of maize tassels. Extensive results on the MTC dataset demonstrate that TasselNet outperforms other state-of-the-art approaches by large margins and achieves the overall best counting

  16. Hardware safety net

    National Research Council Canada - National Science Library

    Mario Apicella

    2003-01-01

      Voom Technologies' PCI card, ISIR (Instant Save Instant Restore), works with ATA disk drives and promises to quickly revive a computer impaired by a virus, damaging update, corrupted configuration file, or other software illness...

  17. Net-zero building

    CSIR Research Space (South Africa)

    Van Wyk, Llewellyn V

    2013-01-01

    Full Text Available of interventions where innovative technologies could realise substantial building performance improvements. A central challenge to construction and building performance is located in the practice of constructing a building on the project site using a combination...

  18. 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.

  19. Dynamics and design of space nets for orbital capture

    CERN Document Server

    Yang, Leping; Zhen, Ming; Liu, Haitao

    2017-01-01

    This book covers the topics of theoretical principles, dynamics model and algorithm, mission analysis, system design and experimental studies of space nets system, aiming to provide an initial framework in this field and serve as a ready reference for those interested. Space nets system represents a forefront field in future development of aerospace technologies. However, it involves new challenges and problems such as nonlinear and distorted nets structure, complex rigid flexible coupling dynamics, orbital transfer of space flexible composite and dynamics control. Currently, no comprehensive books on space nets dynamics and design are available, so potential readers can get to know the working mechanism, dynamics elements, and mission design of the space nets system from a Chinese perspective.

  20. Professional ASP.NET 4 in C# and VB

    CERN Document Server

    Evjen, Bill; Rader, Devin

    2010-01-01

    This book was written to introduce you to the features and capabilities that ASP.NET 4 offers, as well as to give you an explanation of the foundation that ASP.NET provides. We assume you have a general understanding of Web technologies, such as previous versions of ASP.NET, Active Server Pages 2.0/3.0, or JavaServer Pages. If you understand the basics of Web programming, you should not have much trouble following along with this book's content. If you are brand new to ASP.NET, be sure to check out Beginning ASP.NET 4: In C# and VB by Imar Spaanjaars (Wiley Publishing, Inc., 2010) to help you

  1. 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.

  2. 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...

  3. 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

  4. 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.

  5. Near Net Shape Manufacturing of New Titanium Powders for Industry

    Energy Technology Data Exchange (ETDEWEB)

    None

    2009-05-01

    This factsheet describes a research project whose goal is to develop a manufacturing technology to process new titanium powders into fully consolidated near net shape components for industrial applications. This will be achieved using various technologies, including press and sinter, pneumatic isostatic forging (PIF), hot isostatic pressing (HIP), and adiabatic compaction.

  6. 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...

  7. 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

  8. Radar: Human Safety Net

    Science.gov (United States)

    Ritz, John M.

    2016-01-01

    Radar is a technology that can be used to detect distant objects not visible to the human eye. A predecessor of radar, called the telemobiloscope, was first used to detect ships in the fog in 1904 off the German coast. Many scientists have worked on the development and refinement of radar (Hertz with electromagnetic waves; Popov with determining…

  9. 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...

  10. 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

  11. 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.

  12. 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.

  13. Satellite image analysis using neural networks

    Science.gov (United States)

    Sheldon, Roger A.

    1990-01-01

    The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, SIANN (Satellite Image Analysis using Neural Networks) that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed was completed and applied to climatological data.

  14. NetWorking News

    DEFF Research Database (Denmark)

    Fritsch, Jonas; Iversen, Ole Sejer; Dindler, Christian

    with adults or children. However there is a need for new methods to support communication and collaboration between designers and children. This article proposes a new method for understandings children’s appropriation of new technology in an interactive workshop setting. The method, which we call...... the Networking News workshop, offers an opportunity to make first hand studies of children’s IT supported social activities in an informal classroom setting....

  15. 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...

  16. 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...

  17. 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.

  18. 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

  19. 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.

  20. Fuzzy neural networks: theory and applications

    Science.gov (United States)

    Gupta, Madan M.

    1994-10-01

    During recent years, significant advances have been made in two distinct technological areas: fuzzy logic and computational neural networks. The theory of fuzzy logic provides a mathematical framework to capture the uncertainties associated with human cognitive processes, such as thinking and reasoning. It also provides a mathematical morphology to emulate certain perceptual and linguistic attributes associated with human cognition. On the other hand, the computational neural network paradigms have evolved in the process of understanding the incredible learning and adaptive features of neuronal mechanisms inherent in certain biological species. Computational neural networks replicate, on a small scale, some of the computational operations observed in biological learning and adaptation. The integration of these two fields, fuzzy logic and neural networks, have given birth to an emerging technological field -- fuzzy neural networks. Fuzzy neural networks, have the potential to capture the benefits of these two fascinating fields, fuzzy logic and neural networks, into a single framework. The intent of this tutorial paper is to describe the basic notions of biological and computational neuronal morphologies, and to describe the principles and architectures of fuzzy neural networks. Towards this goal, we develop a fuzzy neural architecture based upon the notion of T-norm and T-conorm connectives. An error-based learning scheme is described for this neural structure.

  1. NeuroMEMS: Neural Probe Microtechnologies

    Directory of Open Access Journals (Sweden)

    Sam Musallam

    2008-10-01

    Full Text Available Neural probe technologies have already had a significant positive effect on our understanding of the brain by revealing the functioning of networks of biological neurons. Probes are implanted in different areas of the brain to record and/or stimulate specific sites in the brain. Neural probes are currently used in many clinical settings for diagnosis of brain diseases such as seizers, epilepsy, migraine, Alzheimer’s, and dementia. We find these devices assisting paralyzed patients by allowing them to operate computers or robots using their neural activity. In recent years, probe technologies were assisted by rapid advancements in microfabrication and microelectronic technologies and thus are enabling highly functional and robust neural probes which are opening new and exciting avenues in neural sciences and brain machine interfaces. With a wide variety of probes that have been designed, fabricated, and tested to date, this review aims to provide an overview of the advances and recent progress in the microfabrication techniques of neural probes. In addition, we aim to highlight the challenges faced in developing and implementing ultralong multi-site recording probes that are needed to monitor neural activity from deeper regions in the brain. Finally, we review techniques that can improve the biocompatibility of the neural probes to minimize the immune response and encourage neural growth around the electrodes for long term implantation studies.

  2. Technology

    Directory of Open Access Journals (Sweden)

    Xu Jing

    2016-01-01

    Full Text Available The traditional answer card reading method using OMR (Optical Mark Reader, most commonly, OMR special card special use, less versatile, high cost, aiming at the existing problems proposed a method based on pattern recognition of the answer card identification method. Using the method based on Line Segment Detector to detect the tilt of the image, the existence of tilt image rotation correction, and eventually achieve positioning and detection of answers to the answer sheet .Pattern recognition technology for automatic reading, high accuracy, detect faster

  3. 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....

  4. 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...

  5. 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...

  6. 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.

  7. 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...

  8. Radiation Behavior of Analog Neural Network Chip

    Science.gov (United States)

    Langenbacher, H.; Zee, F.; Daud, T.; Thakoor, A.

    1996-01-01

    A neural network experiment conducted for the Space Technology Research Vehicle (STRV-1) 1-b launched in June 1994. Identical sets of analog feed-forward neural network chips was used to study and compare the effects of space and ground radiation on the chips. Three failure mechanisms are noted.

  9. 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....

  10. 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...

  11. Mars MetNet Mission - Martian Atmospheric Observational Post Network

    Science.gov (United States)

    Harri, A.-M.; Haukka, H.; Aleksashkin, S.; Arruego, I.; Schmidt, W.; Genzer, M.; Vazquez, L.; Siikonen, T.; Palin, M.

    2017-09-01

    A 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.

  12. Beginning DotNetNuke Skinning and Design

    CERN Document Server

    Hay, Andrew

    2011-01-01

    DotNetNuke is an open source framework built on top of the ASP.Net platform. While this system offers an impressive set of out-of-the-box features for public and private sites, it also includes a compelling story for folks who want to present a unique look and feel to visitors. The skinning engine inside of DotNetNuke has strengthened over the course of several years and hundreds of thousands of registered users. The success of its skin and module developer community is another key indicator of the depth and breadth of this technology. The Core Team responsible for the DotNetNuke brand has gon

  13. 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.

  14. Professional ASP.NET 4.5 in C# and VB

    CERN Document Server

    Gaylord, Jason N; Rastogi, Pranav; Miranda, Todd; Hanselman, Scott

    2013-01-01

    The all-new approach for experienced ASP.NET professionals! ASP.NET is Microsoft's technology for building dynamically generated web pages from database content. Originally introduced in 2002, ASP.NET has undergone many changes in multiple versions and iterations as developers have gained a decade of experience with this popular technology. With that decade of experience, this edition of the book presents a fresh, new overhauled approach. A new focus on how to build ASP.NET sites and applications relying on field-tested reliable methodsIntegration of ""One A

  15. 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. ...

  16. 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...

  17. 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.

  18. 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.

  19. Emerging trends in neuro engineering and neural computation

    CERN Document Server

    Lee, Kendall; Garmestani, Hamid; Lim, Chee

    2017-01-01

    This book focuses on neuro-engineering and neural computing, a multi-disciplinary field of research attracting considerable attention from engineers, neuroscientists, microbiologists and material scientists. It explores a range of topics concerning the design and development of innovative neural and brain interfacing technologies, as well as novel information acquisition and processing algorithms to make sense of the acquired data. The book also highlights emerging trends and advances regarding the applications of neuro-engineering in real-world scenarios, such as neural prostheses, diagnosis of neural degenerative diseases, deep brain stimulation, biosensors, real neural network-inspired artificial neural networks (ANNs) and the predictive modeling of information flows in neuronal networks. The book is broadly divided into three main sections including: current trends in technological developments, neural computation techniques to make sense of the neural behavioral data, and application of these technologie...

  20. Flexible and Organic Neural Interfaces: A Review

    Directory of Open Access Journals (Sweden)

    Nicolò Lago

    2017-12-01

    Full Text Available Neural interfaces are a fundamental tool to interact with neurons and to study neural networks by transducing cellular signals into electronics signals and vice versa. State-of-the-art technologies allow both in vivo and in vitro recording of neural activity. However, they are mainly made of stiff inorganic materials that can limit the long-term stability of the implant due to infection and/or glial scars formation. In the last decade, organic electronics is digging its way in the field of bioelectronics and researchers started to develop neural interfaces based on organic semiconductors, creating more flexible and conformable neural interfaces that can be intrinsically biocompatible. In this manuscript, we are going to review the latest achievements in flexible and organic neural interfaces for the recording of neuronal activity.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. Achievement report for fiscal 2000 on the phase II research and development for hydrogen utilizing international clean energy system technology (WE-NET). Task 10. Development of low-temperature materials; 2000 nendo suiso riyo kokusai clean energy system gijutsu (WE-NET) dai 2 ki kenkyu kaihatsu. Task 10. Teion zairyo no kaihatsu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-03-01

    This paper describes the achievements in fiscal 2000 from the development of candidate low-temperature materials for liquid hydrogen transportation and storage (including mother materials and welds) for WE-NET. Evaluation tests were performed on material properties (mechanical properties, low-temperature embrittlement, and hydrogen embrittlement sensitivity) under room temperature and low temperature regions including liquid hydrogen atmosphere. Low temperature toughness of welds was assessed particularly to identify characteristics of different welding methods developed newly for improvements. The stainless steels and the mother materials of aluminum alloy selected as the candidates have sufficient characteristics even under the liquid hydrogen atmosphere, but the welds have lower low-temperature toughness, requiring improvement. For the stainless steels, since the amount of {delta} ferrite in welds affects greatly the low-temperature toughness, adoption of complete austenite type welding metal is effective. The reduced pressure electron beam welding method can enhance drastically the low-temperature toughness of stainless steel. For the aluminum alloy, it can be one of the alternatives to use an alloy system with composition of high low-temperature toughness. The friction stir welding method for the aluminum alloy was found to provide extremely high low-temperature toughness, which can be evaluated as a new welding method. (NEDO)

  6. A neural network approach for the evaluation of the innovation outcomes of value co-creation practices in technology-driven firms

    DEFF Research Database (Denmark)

    di Tollo, Giacomo; Tanev, Stoyan

    2010-01-01

    Value co-creation is an emerging marketing and innovation paradigm describing a broader opening of the firm to its customers by providing them with the opportunity to become active participants in the design and development of personalized products, services and experiences. The aim of the present......-creation components and the frequency of firms’ online comments about their new products, processes and services. The present work focuses on using an Artificial Neural Network (ANN) approach to understand if the extent of value co-creation activities can be thought of as an indicator of the perception of innovation...

  7. 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...

  8. 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.

  9. Optimizing neural network models: motivation and case studies

    OpenAIRE

    Harp, S A; T. Samad

    2012-01-01

    Practical successes have been achieved  with neural network models in a variety of domains, including energy-related industry. The large, complex design space presented by neural networks is only minimally explored in current practice. The satisfactory results that nevertheless have been obtained testify that neural networks are a robust modeling technology; at the same time, however, the lack of a systematic design approach implies that the best neural network models generally  rem...

  10. 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.

  11. Information and Announcements SciDev.Net: An Essential Science ...

    Indian Academy of Sciences (India)

    the role of science and technology in the social and economic growth of developing countries. Visit the website to find out more: www.scidev.net. The website: The website covers key science, health and environmental issues, including. HIV/AIDS, climate change, agricultural biotechnology, the brain drain and biodiversity.

  12. Support to SciDev.Net | IDRC - International Development Research ...

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

    IDRC funding for SciDev.Net (SDN), will enhance the not-for profit organization's ability to provide reliable and authoritative information about science and technology in the developing world as it transitions to a self-sustaining business. The funding will continue to support SDN's service and capacity-building activities, ...

  13. Implementation architecture and multithreaded runtime system of S-Net

    NARCIS (Netherlands)

    Grelck, C.; Penczek, F.; Scholz, S.-B.; Chitil, O.

    2011-01-01

    S-Net is a declarative coordination language and component technology aimed at modern multi-core/many-core architectures and systems-on-chip. It builds on the concept of stream processing to structure networks of communicating asynchronous components, which can be implemented using a conventional

  14. Give Your Old-School Curriculum a NETS Makeover

    Science.gov (United States)

    LaMaster, Jen

    2012-01-01

    Integrating digital age technology into an industrial age educational system is hard enough. Imagine introducing ed tech to a 450-year-old Jesuit educational paradigm. Find out how to seamlessly combine the NETS with a centuries-old framework to create an effective ed tech strategic plan. This article describes how the author successfully…

  15. 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.

  16. 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...

  17. 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

  18. 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...

  19. 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 ...

  20. 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.

  1. 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

  2. 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.

  3. 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...

  4. 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.

  5. 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...

  6. 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

  7. 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...

  8. Using O*NET Based Higher Education Job Descriptions for Resume Development

    Science.gov (United States)

    Manzi, P. A.; Roe, J.; Pierre-Louis, D.

    2011-01-01

    The purpose of this three part article is to illustrate to career development professionals and students who are graduates of higher education MS and Ed.D/Ph.D programs, how to use the O*NET to develop an effective resume. The O*NET provides detailed information about work tasks, knowledge and skills, and in some titles, tools and technology where…

  9. 9 CFR 442.2 - Definitions and procedures for determining net weight compliance.

    Science.gov (United States)

    2010-01-01

    ... 9 Animals and Animal Products 2 2010-01-01 2010-01-01 false Definitions and procedures for determining net weight compliance. 442.2 Section 442.2 Animals and Animal Products FOOD SAFETY AND INSPECTION... Standards and Technology (NIST) Handbook 133, “Checking the Net Contents of Packaged Goods,” Fourth Edition...

  10. An Efficient Scalable Work-Stealing Runtime for Macro Data Flow Processing Using S-Net

    NARCIS (Netherlands)

    Gijsbers, B.; Grelck, C.

    2014-01-01

    S-Net is a declarative coordination language and component technology aimed at radically facilitating software engineering for modern parallel compute systems by near-complete separation of concerns between application (component) engineering and concurrency orchestration. S-Net builds on the

  11. 75 FR 39621 - Proposed Information Collection (Income-Net Worth and Employment Statement) Activity: Comment...

    Science.gov (United States)

    2010-07-09

    ... From the Federal Register Online via the Government Publishing Office DEPARTMENT OF VETERANS AFFAIRS Proposed Information Collection (Income-Net Worth and Employment Statement) Activity: Comment... forms of information technology. Title: Income-Net Worth and Employment Statement. OMB Control Number...

  12. A neutron spectrum unfolding computer code based on artificial neural networks

    Science.gov (United States)

    Ortiz-Rodríguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.; Cervantes Viramontes, J. M.; Vega-Carrillo, H. R.

    2014-02-01

    The Bonner Spheres Spectrometer consists of a thermal neutron sensor placed at the center of a number of moderating polyethylene spheres of different diameters. From the measured readings, information can be derived about the spectrum of the neutron field where measurements were made. Disadvantages of the Bonner system are the weight associated with each sphere and the need to sequentially irradiate the spheres, requiring long exposure periods. Provided a well-established response matrix and adequate irradiation conditions, 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 Intelligence, mainly Artificial Neural Networks, have been widely investigated. In this work, a neutron spectrum unfolding code based on neural nets technology is presented. This code is called Neutron Spectrometry and Dosimetry with Artificial Neural networks unfolding code that was designed in a graphical interface. The core of the code is an embedded neural network architecture previously optimized using the robust design of artificial neural networks methodology. The main features of the code are: easy to use, friendly and intuitive to the user. This code was designed for a Bonner Sphere System based on a 6LiI(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, for unfolding the neutron spectrum, only seven rate counts measured with seven Bonner spheres are required; simultaneously the code calculates 15 dosimetric quantities as well as the total flux for radiation protection purposes. This code generates a full report with all information of the unfolding in

  13. 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.

  14. 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

  15. 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

  16. 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...

  17. [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.

  18. 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.

  19. 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...

  20. REAL-TIME VIDEO SCALING BASED ON CONVOLUTION NEURAL NETWORK ARCHITECTURE

    Directory of Open Access Journals (Sweden)

    S Safinaz

    2017-08-01

    Full Text Available In recent years, video super resolution techniques becomes mandatory requirements to get high resolution videos. Many super resolution techniques researched but still video super resolution or scaling is a vital challenge. In this paper, we have presented a real-time video scaling based on convolution neural network architecture to eliminate the blurriness in the images and video frames and to provide better reconstruction quality while scaling of large datasets from lower resolution frames to high resolution frames. We compare our outcomes with multiple exiting algorithms. Our extensive results of proposed technique RemCNN (Reconstruction error minimization Convolution Neural Network shows that our model outperforms the existing technologies such as bicubic, bilinear, MCResNet and provide better reconstructed motioning images and video frames. The experimental results shows that our average PSNR result is 47.80474 considering upscale-2, 41.70209 for upscale-3 and 36.24503 for upscale-4 for Myanmar dataset which is very high in contrast to other existing techniques. This results proves our proposed model real-time video scaling based on convolution neural network architecture’s high efficiency and better performance.

  1. 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...

  2. 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...

  3. 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

  4. 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.

  5. Beginning ASP.NET 4.5 in VB

    CERN Document Server

    MacDonald, Matthew

    2012-01-01

    This book is the most comprehensive and up to date introduction to ASP.NET ever written. Focusing solely on Visual Basic, with no code samples duplicated in other languages, award winning author Matthew MacDonald introduces you to the very latest thinking and best practices for the ASP.NET 4.5 technology.Assuming no prior coding experience, you'll be taught everything you need to know from the ground up.  Starting from first principals, you'll learn the skills you need to be an effective ASP.NET developer who is ready to progress to more sophisticated projects and professional work.You'll be t

  6. Beginning ASP.NET 4.5 in C#

    CERN Document Server

    MacDonald, Matthew

    2012-01-01

    This book is the most comprehensive and up to date introduction to ASP.NET ever written. Focussing solely on C#, with no code samples duplicated in other languages, award winning author Matthew MacDonald introduces you to the very latest thinking and best practices for the ASP.NET 4.5 technology.Assuming no prior coding experience, you'll be taught everything you need to know from the ground up.  Starting from first principals, you'll learn the skills you need to be an effective ASP.NET developer who is ready to progress to more sophisticated projects and professional work. You'll be taught ho

  7. Net Neutrality in Canada and what it means for libraries

    Directory of Open Access Journals (Sweden)

    Alex Guindon

    2010-06-01

    Full Text Available Net Neutrality, the idea that the Internet should be provided to all without discrimination based on content or applications, has been an important policy issue in the last few years. A lack of net neutrality could negatively impact libraries, intellectual freedom, cultural diversity, and the right to privacy. This paper looks at the issues that underline the net neutrality debate and describes how they are shaped by the different actors that are concerned with the future of the Internet. Technological issues, such as traffic shaping by Internet Service Providers, and legal issues in the context of Canada’s Telecommunications Act, are also addressed. Finally, the paper reviews the recent CRTC policy on Internet Traffic Management Practices.

  8. 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...

  9. Non-invasive neural stimulation

    Science.gov (United States)

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

    2017-05-01

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

  10. 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

  11. 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...

  12. Analysis of technologies for natural gas transportation in Brazil: results comparison of the application of payback and NPV (Net Present Value) methods; Analise de tecnologias de transporte de gas natural no Brasil: comparacao dos resultados da aplicacao dos metodos 'payback' e VPL (Valor Presente Liquido)

    Energy Technology Data Exchange (ETDEWEB)

    Baioco, Juliana Souza; Santarem, Clarissa Andrade [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Dept. de Engenharia de Petroleo; Bone, Rosemarie Broeker; Ferreira Filho, Virgilio Jose Martins [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Dept. de Engenharia Industrial

    2008-07-01

    The increased demand for natural gas leads to global integration of markets, leading to decisions that cover the various technologies of transportation, noting the specific locations. The transport of natural gas considered more traditional (Liquefied Natural Gas and Pipeline) often unviable economically areas of operation due to cost. In this case, there are alternative technologies to reduce those costs. The article is to compare the technologies of transport, using the methodology of the Net Present Value (VPL) to identify one that has more positive VPL, which is the most profitable. Thus, in search of validate the results of SUBERO et al. (2004) for gas transport by Pipelines, Liquefied Natural Gas and Compressed Natural Gas. In addition, they are compared these results with the method of VPL and with the economic analysis presented in using the payback period of CHANG (2001) and SANTAREM et al. (2007). It was found that the results obtained in Brazil were identical to those obtained by CHANG (2001) and SUBERO et al. (2007), saving only some differences in magnitude due to the specific characteristics of the Brazilian economy. In other words, for the Brazilian case, the technology of Compressed Natural Gas (CNG) was the most economically viable with the method of VPL, followed by technology, Pipeline and Liquefied Natural Gas (LNG), regardless of the interest rates of 10% and 6.5% and periods of 20 and 30 years. The contribution of this work is to show that despite of the method, payback or VPL, the various alternatives for transporting natural gas to Brazil have the same ranking and economic viability. (author)

  13. Hydrogen utilization international clean energy system technology (WE-NET). Subtask 8. Research and development of hydrogen combustion turbines (development of ultra-high temperature materials); Suiso riyo kokusai clean energy system (WE-NET). Subtask 8. Suiso nensho turbine no kenkyu kaihatsu chokoon zairyo no kaihatsu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    The paper described the result of the fiscal 1996 development of ultra-high temperature materials for parts of hydrogen combustion turbines, as part of the hydrogen utilization technology, which have excellent environmental protectivity and remarkably high efficiency. By the optimized solution heat treatment of monocrystal alloy developed in the previous fiscal year, obtained was strength property the same as the existing super alloys. As to FRC, pore size and strength property of SiC organic hybrid were made clear. ODS alloy cooling blades and heat insulation coating were studied, and YSZ was found to be most excellent as coating material. Concerning intermetallic compounds, the applicability to ultra-high temperatures up to 1700degC was not obtained. For improvement of heat resistance and environment resistance, adopted were highly compacting SiC matrix and BN coatings. Al2O3 was excellent in long-time stability. In the 1600degC steam corrosion test on multiplex structural materials with Al2O3 as surface material, chemical stability was confirmed. Three-dimensional woven fiber reinforced composite materials of C/C{center_dot}CMC were trially produced by changing the fiber orientation, and improvement in ultra-high temperature thermal shock resistance was confirmed. A study was made of spot observation of the specimen surface by laser microscope, and development was conducted of a temperature measuring method with no influence of radiant heat. 44 refs., 250 figs., 40 tabs.

  14. Hydrogen utilization international clean energy system technology (WE-NET). Subtask 8. Development of hydrogen combustion turbines (development of the main component devices such as turbine blades and rotors); Suiso riyo kokusai clean energy system gijutsu (WE-NET). Subtask 8. Suiso nensho turbine no kaihatsu (turbine yoku, rotor nado shuyo kosei kiki no kaihatsu)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    The paper described the result of the fiscal 1996 development relating to hydrogen combustion turbines, as one of the hydrogen utilization technologies, which have excellent environmentality and are expected of remarkably high efficiency. In the film cooling system of first-stage moving/stationary blades, the smaller the pitch of film pore is, the higher the mean cooling efficiency becomes, indicating 0.7 at maximum. As compared with the conventional shower head type, the metal temperature can be reduced 30-40degC. In the recovery type inner (convection) cooling system, by reducing the blade number, the consumption amount of coolant can be reduced 6% in stationary blade and 13% in moving blade, as compared with the result of the preceding year. In the element test of the hybrid cooling system, film cooling efficiency was actually measured by the porous module test equipment, and the result well agreed with the calculation result. In the water cooling system, studied were water (stationary blade) and vapor (moving blade) of the closed cooling structure for realization of a cycle efficiency of 60%. In rotor/disk cooling, analyses were made of seal characteristic grasp tests and characteristics of the rotor. The effect of deflection in the mainstream was small. Besides, proper value of the seal overlapping amount could be obtained. 6 refs., 368 figs., 55 tabs.

  15. 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....

  16. 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...

  17. 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...

  18. 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...

  19. 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

  20. Fiscal 1997 survey report. Subtask 2 (hydrogen utilization worldwide clean energy system technology) (WE-NET) (survey/study for the promotion of international cooperation; survey/study on the standardization for hydrogen energy technology); 1997 nendo seika hokokusho. Suiso riyo kokusai clean energy system gijutsu (WE-NET) subtask 2 kokusai kyoryoku suishin no tame no chosa kento (suiso energy gijutsu hyojunka ni kansuru chosa kento)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-03-01

    In relation to the basic study of the standardization for hydrogen energy technology and ISO/TC197, the results of the fiscal 1997 survey were summarized. From fiscal 1994 through 1996, in the wide-range field related to hydrogen energy technology, the survey of the present situation of the related standards/laws was made and the needs/subjects of standardization to be studied in the future were extracted. At the present stage, however, it is still early to enter into the stage of discussing the standardization. Therefore, in this fiscal year, only in the field of the storage/transportation/handling of liquid hydrogen, standards/laws abroad and in Japan were comparatively investigated for the basic study toward the standardization. Further, concerning ISO/TC197, studies were proceeded with of the liquid hydrogen land vehicle fueling system interface/fuel tanks/transportation containers/hydrogen fuel product specifications/airport hydrogen fueling facilities. Some are at the stage of drafting the international standard. Three drafts for the new standard were added such as gaseous hydrogen/hydrogen blend vehicular fuel systems, gaseous hydrogen fuel tanks, and basic requirements for safety of hydrogen systems. The standardization is indispensable to introducing the developed technology to the commercialization. 9 refs., 5 figs., 13 tabs.

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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.

  6. 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...

  7. 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...

  8. Net-Shape HIP Powder Metallurgy Components for Rocket Engines

    Science.gov (United States)

    Bampton, Cliff; Goodin, Wes; VanDaam, Tom; Creeger, Gordon; James, Steve

    2005-01-01

    True net shape consolidation of powder metal (PM) by hot isostatic pressing (HIP) provides opportunities for many cost, performance and life benefits over conventional fabrication processes for large rocket engine structures. Various forms of selectively net-shape PM have been around for thirty years or so. However, it is only recently that major applications have been pursued for rocket engine hardware fabricated in the United States. The method employs sacrificial metallic tooling (HIP capsule and shaped inserts), which is removed from the part after HIP consolidation of the powder, by selective acid dissolution. Full exploitation of net-shape PM requires innovative approaches in both component design and materials and processing details. The benefits include: uniform and homogeneous microstructure with no porosity, irrespective of component shape and size; elimination of welds and the associated quality and life limitations; removal of traditional producibility constraints on design freedom, such as forgeability and machinability, and scale-up to very large, monolithic parts, limited only by the size of existing HIP furnaces. Net-shape PM HIP also enables fabrication of complex configurations providing additional, unique functionalities. The progress made in these areas will be described. Then critical aspects of the technology that still require significant further development and maturation will be discussed from the perspective of an engine systems builder and end-user of the technology.

  9. Materials processing with de Laval spray-forming nozzles: Net-shape applications

    Energy Technology Data Exchange (ETDEWEB)

    McHugh, K.M. [Idaho National Engineering Lab., Idaho Falls, ID (United States)

    1994-12-31

    Spray forming is a materials processing technology in which a bulk liquid metal is converted to a spray of fine droplets and deposited onto a substrate or pattern to form a near-net-shape solid. Benefits include property improvement through rapid solidification of metals, near-net-shape fabrication, and process simplification through the elimination of unit operations. The Idaho National Engineering Laboratory has developed a unique spray-forming method, the Controlled Aspiration Process (CAP), to produce near-net-shape solids and coatings of metals, polymers, and composite materials using de Laval nozzles. The application of this technology for the production of tooling and microelectromechanical systems is described.

  10. Data systems and computer science: Neural networks base R/T program overview

    Science.gov (United States)

    Gulati, Sandeep

    1991-01-01

    The research base, in the U.S. and abroad, for the development of neural network technology is discussed. The technical objectives are to develop and demonstrate adaptive, neural information processing concepts. The leveraging of external funding is also discussed.

  11. Neural network models: Insights and prescriptions from practical applications

    Energy Technology Data Exchange (ETDEWEB)

    Samad, T. [Honeywell Technology Center, Minneapolis, MN (United States)

    1995-12-31

    Neural networks are no longer just a research topic; numerous applications are now testament to their practical utility. In the course of developing these applications, researchers and practitioners have been faced with a variety of issues. This paper briefly discusses several of these, noting in particular the rich connections between neural networks and other, more conventional technologies. A more comprehensive version of this paper is under preparation that will include illustrations on real examples. Neural networks are being applied in several different ways. Our focus here is on neural networks as modeling technology. However, much of the discussion is also relevant to other types of applications such as classification, control, and optimization.

  12. 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)

  13. Energy-Saving Melting and Revert Reduction Technology (E-SMARRT): Use of Laser Engineered Net Shaping for Rapid Manufacturing of Dies with Protective Coatings and Improved Thermal Management

    Energy Technology Data Exchange (ETDEWEB)

    Brevick, Jerald R. [Ohio State University

    2014-06-13

    retained as the exterior layer of the tooling, while commercially pure copper was chosen for the interior structure of the tooling. The tooling was fabricated by traditional machining of the copper substrate, and H13 powder was deposited on the copper via the Laser Engineered Net Shape (LENSTM) process. The H13 deposition layer was then final machined by traditional methods. Two tooling components were designed and fabricated; a thermal fatigue test specimen, and a core for a commercial aluminum high pressure die casting tool. The bimetallic thermal fatigue specimen demonstrated promising performance during testing, and the test results were used to improve the design and LENS TM deposition methods for subsequent manufacture of the commercial core. Results of the thermal finite element analysis for the thermal fatigue test specimen indicate that it has the ability to lose heat to the internal water cooling passages, and to external spray cooling, significantly faster than a monolithic H13 thermal fatigue sample. The commercial core is currently in the final stages of fabrication, and will be evaluated in an actual production environment at Shiloh Die casting. In this research, the feasibility of designing and fabricating copper/H13 bimetallic die casting tooling via LENS TM processing, for the purpose of improving die casting process efficiency, is demonstrated.

  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. Cortical neural prosthetics.

    Science.gov (United States)

    Schwartz, Andrew B

    2004-01-01

    Control of prostheses using cortical signals is based on three elements: chronic microelectrode arrays, extraction algorithms, and prosthetic effectors. Arrays of microelectrodes are permanently implanted in cerebral cortex. These arrays must record populations of single- and multiunit activity indefinitely. Information containing position and velocity correlates of animate movement needs to be extracted continuously in real time from the recorded activity. Prosthetic arms, the current effectors used in this work, need to have the agility and configuration of natural arms. Demonstrations using closed-loop control show that subjects change their neural activity to improve performance with these devices. Adaptive-learning algorithms that capitalize on these improvements show that this technology has the capability of restoring much of the arm movement lost with immobilizing deficits.

  17. 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...

  18. NetF-producing Clostridium perfringens: Clonality and plasmid pathogenicity loci analysis.

    Science.gov (United States)

    Mehdizadeh Gohari, Iman; Kropinski, Andrew M; Weese, Scott J; Whitehead, Ashley E; Parreira, Valeria R; Boerlin, Patrick; Prescott, John F

    2017-04-01

    Clostridium perfringens is an important cause of foal necrotizing enteritis and canine acute hemorrhagic diarrhea. A major virulence determinant of the strains associated with these diseases appears to be a beta-sheet pore-forming toxin, NetF, encoded within a pathogenicity locus (NetF locus) on a large tcp-conjugative plasmid. Strains producing NetF also produce the putative toxin NetE, encoded within the same pathogenicity locus, as well as CPE enterotoxin and CPB2 on a second plasmid, and sometimes the putative toxin NetG within a pathogenicity locus (NetG locus) on another separate large conjugative plasmid. Previous genome sequences of two netF-positive C. perfringens showed that they both shared three similar plasmids, including the NetF/NetE and CPE/CPB2 toxins-encoding plasmids mentioned above and a putative bacteriocin-encoding plasmid. The main purpose of this study was to determine whether all NetF-producing strains share this common plasmid profile and whether their distinct NetF and CPE pathogenicity loci are conserved. To answer this question, 15 equine and 15 canine netF-positive isolates of C. perfringens were sequenced using Illumina Hiseq2000 technology. In addition, the clonal relationships among the NetF-producing strains were evaluated by core genome multilocus sequence typing (cgMLST). The data obtained showed that all NetF-producing strains have a common plasmid profile and that the defined pathogenicity loci on the plasmids are conserved in all these strains. cgMLST analysis showed that the NetF-producing C. perfringens strains belong to two distinct clonal complexes. The pNetG plasmid was absent from isolates of one of the clonal complexes, and there were minor but consistent differences in the NetF/NetE and CPE/CPB2 plasmids between the two clonal complexes. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Software Evolution in the context of .Net Framework

    OpenAIRE

    Walid, Rohaimi

    2007-01-01

    This paper discusses the process of software evolution and especially software migration in the context of .NET Technologies. Actually most of the companies that uses legacy systems implemented with procedural languages as C, Visual Basic and so on, meet some problems when new requirement specifications have to be integrated. One possibility to deal with this situation is to choose a good migration strategy from these legacy systems towards new Object Oriented design. There are some migration...

  20. Net Children Go Mobile:Initial findings from Ireland

    OpenAIRE

    O'Neill, Brian; Dinh, Thuy

    2014-01-01

    Net Children Go Mobile is a two-year research project funded under the European Commission’s Safer Internet Programme. Seven countries participate: Demark, Italy, Romania, United Kingdom, Ireland, Portugal and Belgium. The project uses quantitative and qualitative methodologies to investigate access and use, risks and opportunities of mobile internet use. This report presents the initial findings of the survey of children and young people’s use of mobile internet technologies in Ireland. 5...

  1. 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.

  2. Tecnologias da informação e comunicação e formação de professores: sobre rede e escolas Information and communication technologies and teacher training: about net and schools

    Directory of Open Access Journals (Sweden)

    Katia Morosov Alonso

    2008-10-01

    Full Text Available A temática das tecnologias da informação e comunicação (TIC, aliada à formação dos professores, suscita reflexões sobre a natureza do trabalho pedagógico, com base nas mediações técnicas e no desenvolvimento do processo formativo dos profissionais da educação nesse contexto. De fato, o uso de recursos tecnológicos sofisticados não tem assegurado transformações nas práticas pedagógicas nas escolas. O objetivo deste artigo se centra na análise desse fator, considerando que a lógica estabelecida pelas TIC implica trabalho em rede, lógica muito diferente do realizado nas e pelas escolas atualmente. É na fronteira dessas lógicas que são observados espaços que poderiam apoiar menos reducionismos no entendimento sobre TIC e formação docente.The subject matter: information and communication tecnologies (ICT associated to teachers' training stir up reflexions about the nature of pedagogical work based on technical mediations and about the development of the formative process of education professionals in this context. Indeed, the use of sophisticated technological resources has not guaranteed transformations in pedagogical practices in schools. The objective of this article is focused on the analysis of this factor, considering that the logic established by the ICT, and more recently, the converging of the media and the web, imply work on-line, a very different logic from the one currently applied in and by the schools. It is within the border of these logics that are foreseen spaces which could support less reductionism in the understanding about ICTs and teachers' training.

  3. Genetic, epigenetic, and environmental contributions to neural tube closure.

    Science.gov (United States)

    Wilde, Jonathan J; Petersen, Juliette R; Niswander, Lee

    2014-01-01

    The formation of the embryonic brain and spinal cord begins as the neural plate bends to form the neural folds, which meet and adhere to close the neural tube. The neural ectoderm and surrounding tissues also coordinate proliferation, differentiation, and patterning. This highly orchestrated process is susceptible to disruption, leading to neural tube defects (NTDs), a common birth defect. Here, we highlight genetic and epigenetic contributions to neural tube closure. We describe an online database we created as a resource for researchers, geneticists, and clinicians. Neural tube closure is sensitive to environmental influences, and we discuss disruptive causes, preventative measures, and possible mechanisms. New technologies will move beyond candidate genes in small cohort studies toward unbiased discoveries in sporadic NTD cases. This will uncover the genetic complexity of NTDs and critical gene-gene interactions. Animal models can reveal the causative nature of genetic variants, the genetic interrelationships, and the mechanisms underlying environmental influences.

  4. 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.

  5. 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.

  6. 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.

  7. Spacecraft Neural Network Control System Design using FPGA

    OpenAIRE

    Hanaa T. El-Madany; Faten H. Fahmy; Ninet M. A. El-Rahman; Hassen T. Dorrah

    2011-01-01

    Designing and implementing intelligent systems has become a crucial factor for the innovation and development of better products of space technologies. A neural network is a parallel system, capable of resolving paradigms that linear computing cannot. Field programmable gate array (FPGA) is a digital device that owns reprogrammable properties and robust flexibility. For the neural network based instrument prototype in real time application, conventional specific VLSI neural chip design suffer...

  8. Neural Networks for Modeling and Control of Particle Accelerators

    CERN Document Server

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

    2016-01-01

    We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

  9. Professional WCF 4 Windows Communication Foundation with NET 4

    CERN Document Server

    Cibraro, Pablo; Cozzolino, Fabio

    2010-01-01

    A guide to architecting, designing, and building distributed applications with Windows Communication Foundation. Windows Communication Foundation is the .NET technology that is used to build service-oriented applications, exchange messages in various communication scenarios, and run workflows. This guide enables developers to create state-of-the-art applications using this technology. Written by a team of Microsoft MVPs and WCF experts, this book explains how the pieces of WCF 4.0 build on each other to provide a comprehensive framework to support distributed enterprise applications. Experienc

  10. -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.

  11. Hydrogen utilization international clean energy system technology (WE-NET). Subtask 5. Development of technology of hydrogen transportation/storage (3rd edition, development of liquid hydrogen storage equipment, report on results of Air Liquide); Suiso riyo kokusai clean energy system gijutsu (WE-NET). Subtask 5. Suiso yuso chozo gijutsu no kaihatsu (daisanpen ekitai suiso chozo setsubi no kaihatsu Air Liquide sha seika hokoku)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    In the fiscal 1995 study, items were searched which are keys to the design of a liquid hydrogen tanker of a capacity of 200,000m{sup 3}. Among those, the basic concepts were summarized which are necessary for the design of a liquid hydrogen tanker in terms of safety, and the extraporation of the existing low temperature technology into the large liquid hydrogen tank was studied. When adopting safety conditions of IGC Code applied to LNG to the liquid hydrogen tanker, it is necessary to limit the discharge amount of hydrogen to 3 kg/s. When considering safety at fire, for keeping safety of the same level as that of the LNG tanker, it is not appropriate to adopt the conventional vacuum insulation liquid hydrogen tank. In the fiscal 1995 study, 7 kinds of concept of the insulation structure were assumed, and it was concluded that BOR of 0.04-0.23/d was obtained. Also in fiscal 1996, the large liquid hydrogen tank was studied. For insulation of the large liquid hydrogen tank, the structure is most promising where AEROSIL bag or homogeneous AEROSIL is substituted for a forming heat insulating material of 4 design, but further study is needed for selection of the optimum heat insulating structure. 9 figs., 6 tabs.

  12. 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...

  13. The KM3NeT Digital Optical Module

    Science.gov (United States)

    Vivolo, Daniele

    2016-04-01

    KM3NeT is a European deep-sea multidisciplinary research infrastructure in the Mediterranean Sea. It will host a km3-scale neutrino telescope and dedicated instruments for long-term and continuous measurements for Earth and Sea sciences. The KM3NeT neutrino telescope is a 3-dimensional array of Digital Optical Modules, suspended in the sea by means of vertical string structures, called Detection Units, supported by two pre-stretched Dyneema ropes, anchored to the seabed and kept taut with a system of buoys. The Digital Optical Module represents the active part of the neutrino telescope. It is composed by a 17-inch, 14 mm thick borosilicate glass (Vitrovex) spheric vessel housing 31 photomultiplier tubes with 3-inch photocathode diameter and the associated front-end and readout electronics. The technical solution adopted for the KM3NeT optical modules is characterized by an innovative design, considering that existing neutrino telescopes, Baikal, IceCube and ANTARES, all use large photomultipliers, typically with a diameter of 8″ or 10″. It offers several advantages: higher sensitive surface (1260 cm2), weaker sensitivity to Earth's magnetic field, better distinction between single-photon and multi-photon events (photon counting) and directional information with an almost isotropic field of view. In this contribution the design and the performance of the KM3NeT Digital Optical Modules are discussed, with a particular focus on enabling technologies and integration procedure.

  14. Mars MetNet Mission - Martian Atmospheric Observational Post Network

    Science.gov (United States)

    Hari, Ari-Matti; Haukka, Harri; Aleksashkin, Sergey; Arruego, Ignacio; Schmidt, Walter; Genzer, Maria; Vazquez, Luis; Siikonen, Timo; Palin, Matti

    2017-04-01

    A 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. Strawman Scientific Payload The strawman payload of the two MNL precursor models includes the following instruments: Atmospheric instruments: - MetBaro Pressure device - MetHumi Humidity device - MetTemp Temperature sensors Optical devices: - PanCam Panoramic - MetSIS Solar irradiance sensor with OWLS optical wireless system for data transfer - DS Dust sensor Composition and Structure Devices: Tri-axial magnetometer MOURA Tri-axial System Accelerometer The descent processes dynamic properties are monitored by a special 3-axis

  15. 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%.

  16. 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....

  17. 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

  18. 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

  19. [Medical use of artificial neural networks].

    Science.gov (United States)

    Molnár, B; Papik, K; Schaefer, R; Dombóvári, Z; Fehér, J; Tulassay, Z

    1998-01-04

    The main aim of the research in medical diagnostics is to develop more exact, cost-effective and handsome systems, procedures and methods for supporting the clinicians. In their paper the authors introduce a new method that recently came into the focus referred to as artificial neural networks. Based on the literature of the past 5-6 years they give a brief review--highlighting the most important ones--showing the idea behind neural networks, what they are used for in the medical field. The definition, structure and operation of neural networks are discussed. In the application part they collect examples in order to give an insight in the neural network application research. It is emphasised that in the near future basically new diagnostic equipment can be developed based on this new technology in the field of ECG, EEG and macroscopic and microscopic image analysis systems.

  20. 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

  1. 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

  2. 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

  3. 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...

  4. Neural networks and applications tutorial

    Science.gov (United States)

    Guyon, I.

    1991-09-01

    The importance of neural networks has grown dramatically during this decade. While only a few years ago they were primarily of academic interest, now dozens of companies and many universities are investigating the potential use of these systems and products are beginning to appear. The idea of building a machine whose architecture is inspired by that of the brain has roots which go far back in history. Nowadays, technological advances of computers and the availability of custom integrated circuits, permit simulations of hundreds or even thousands of neurons. In conjunction, the growing interest in learning machines, non-linear dynamics and parallel computation spurred renewed attention in artificial neural networks. Many tentative applications have been proposed, including decision systems (associative memories, classifiers, data compressors and optimizers), or parametric models for signal processing purposes (system identification, automatic control, noise canceling, etc.). While they do not always outperform standard methods, neural network approaches are already used in some real world applications for pattern recognition and signal processing tasks. The tutorial is divided into six lectures, that where presented at the Third Graduate Summer Course on Computational Physics (September 3-7, 1990) on Parallel Architectures and Applications, organized by the European Physical Society: (1) Introduction: machine learning and biological computation. (2) Adaptive artificial neurons (perceptron, ADALINE, sigmoid units, etc.): learning rules and implementations. (3) Neural network systems: architectures, learning algorithms. (4) Applications: pattern recognition, signal processing, etc. (5) Elements of learning theory: how to build networks which generalize. (6) A case study: a neural network for on-line recognition of handwritten alphanumeric characters.

  5. Development of net energy ratio for quad-generation pathways

    DEFF Research Database (Denmark)

    Rudra, Souman; Rosendahl, Lasse; Kumar, Amit

    2012-01-01

    The conversion of biomass to four different outputs via gasification and catalytic methanation is a renewable technology that could reduce the use of fossil fuels and GHG emissions. This study investigates the energy aspects of producing electricity, heat, methanol and methane. The Gas Technology......-based power, heat, methanol and methane production pathway using GTI technology. Since more efficient alternatives exist for the generation of heat and electricity from biomass, it is argued that syngas is best used for methanol production. The aim of this study was to evaluate the energy performance...... Institute (GTI) gasifier and Circulating Fluidized Bed (CFB) technologies are used for this quad generation process. Three different biomass feedstocks are considered in this study. The net energy ratio for six different pathways having the range of between 1.3–9.3. The lowest limit corresponds to the straw...

  6. Intelligent Controls for Net-Zero Energy Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Li, Haorong; Cho, Yong; Peng, Dongming

    2011-10-30

    The goal of this project is to develop and demonstrate enabling technologies that can empower homeowners to convert their homes into net-zero energy buildings in a cost-effective manner. The project objectives and expected outcomes are as follows: • To develop rapid and scalable building information collection and modeling technologies that can obtain and process “as-built” building information in an automated or semiautomated manner. • To identify low-cost measurements and develop low-cost virtual sensors that can monitor building operations in a plug-n-play and low-cost manner. • To integrate and demonstrate low-cost building information modeling (BIM) technologies. • To develop decision support tools which can empower building owners to perform energy auditing and retrofit analysis. • To develop and demonstrate low-cost automated diagnostics and optimal control technologies which can improve building energy efficiency in a continual manner.

  7. Multiple image sensor data fusion through artificial neural networks

    Science.gov (United States)

    With multisensor data fusion technology, the data from multiple sensors are fused in order to make a more accurate estimation of the environment through measurement, processing and analysis. Artificial neural networks are the computational models that mimic biological neural networks. With high per...

  8. Advances in Artificial Neural Networks - Methodological Development and Application

    Science.gov (United States)

    Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other ne...

  9. 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.

  10. Photonics-oriented data transmission network for the KM3NeT prototype detector

    NARCIS (Netherlands)

    van der Hoek, M.M.; Mos, S.; Schmelling, J.W.; Hogenbirk, J.; Heine, E.; Jansweijer, P.; Kieft, G.; Peek, H.; Timmer, P.; de Wolf, E.

    2013-01-01

    The design of the readout and data acquisition system of the future KM3NeT neutrino telescope employs 10 Gbps photonic technologies for data transmission to shore. The photonic architecture can handle standard transmission protocols. The generic scheme is based on DWDM technology using lasers on

  11. 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.

  12. 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...

  13. Neural Network Enhanced Structure Determination of Osteoporosis, Immune System, and Radiation Repair Proteins Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed innovation will utilize self learning neural network technology to determine the structure of osteoporosis, immune system disease, and excess radiation...

  14. 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...

  15. 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.

  16. 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.

  17. The Economic Phenomena of Net Games and of Bit Coins in China

    OpenAIRE

    Wang, Hanlin

    2013-01-01

    This paper mainly deals with a special but highly-developing industry in China, net game industry. Due to the significant construction and improvement have been happening at China since 30 years ago, and the influence of traditional culture, population boom or demographic dividend and the invasion of western technologies and cultures, net game industry, which has been only existing for less than 15 years at China, has become one of most profitable industries and changed the living of millions...

  18. Modeling and Performance Evaluation of Internet of Things based on Petri Nets and Behavior Expression

    OpenAIRE

    Lin Chen; Linxiang Shi; Wen'an Tan

    2012-01-01

    Modeling and performance evaluation plays an important role on the theoretical research and technology improvement of the Internet of Things (IoT). In the study, the modeling and performance evaluation method based on Petri Nets and behavior expression is presented. Firstly, according to the system information flow chart, the constraint relationship between places and transitions are identified and then graphic Extended Stochastic Petri Nets model is built up; next, the behavior expression me...

  19. Army Net Zero Prove Out. Net Zero Energy Best Practices

    Science.gov (United States)

    2014-11-18

    energy which is then used to drive a heat engine to generate electrical power. Geothermal Power – These systems use thermal energy generated and...stored in the earth as a generating source for electricity. Several pilot installations are investigating this technology by conducting geothermal ...concentrate solar thermal energy which is then used to drive a heat engine to generate electrical power. • Geothermal Power - These systems use thermal energy

  20. Towards a magnetoresistive platform for neural signal recording

    Science.gov (United States)

    Sharma, P. P.; Gervasoni, G.; Albisetti, E.; D'Ercoli, F.; Monticelli, M.; Moretti, D.; Forte, N.; Rocchi, A.; Ferrari, G.; Baldelli, P.; Sampietro, M.; Benfenati, F.; Bertacco, R.; Petti, D.

    2017-05-01

    A promising strategy to get deeper insight on brain functionalities relies on the investigation of neural activities at the cellular and sub-cellular level. In this framework, methods for recording neuron electrical activity have gained interest over the years. Main technological challenges are associated to finding highly sensitive detection schemes, providing considerable spatial and temporal resolution. Moreover, the possibility to perform non-invasive assays would constitute a noteworthy benefit. In this work, we present a magnetoresistive platform for the detection of the action potential propagation in neural cells. Such platform allows, in perspective, the in vitro recording of neural signals arising from single neurons, neural networks and brain slices.

  1. Research on image registration based on D-Nets

    Science.gov (United States)

    Wu, Cengceng; Liu, Zhaoguang; Cheng, Hongtan

    2017-06-01

    Image registration is the key technology of digital imaging applications, it is used widely. We researched the image registration techniques in this paper. Based on the basis of D-Nets image registration algorithms, we propose a new innovation. We turn first to process image, so we can get synthetic images of original images and enhanced images. Then we extract SIFT feature in the original image. Next, in order to reduce noise of the image, we use the Gauss filter to process the synthesized image. Then we do experiments with synthetic images in the process of image registration. In this process, we use the D-Nets algorithm to achieve. Compared to the existing method, it can greatly improve the accuracy and recall.

  2. 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...

  3. 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...

  4. 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

  5. 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

  6. 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.

  7. 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...

  8. 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....

  9. 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...

  10. 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

  11. 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.

  12. 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…

  13. 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...

  14. 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…

  15. 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...

  16. 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...

  17. 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.

  18. 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.

  19. Artificial Neural Networks and Gene Expression Programing based age estimation using facial features

    Directory of Open Access Journals (Sweden)

    Baddrud Z. Laskar

    2015-10-01

    Full Text Available This work is about estimating human age automatically through analysis of facial images. It has got a lot of real-world applications. Due to prompt advances in the fields of machine vision, facial image processing, and computer graphics, automatic age estimation via faces in computer is one of the dominant topics these days. This is due to widespread real-world applications, in areas of biometrics, security, surveillance, control, forensic art, entertainment, online customer management and support, along with cosmetology. As it is difficult to estimate the exact age, this system is to estimate a certain range of ages. Four sets of classifications have been used to differentiate a person’s data into one of the different age groups. The uniqueness about this study is the usage of two technologies i.e., Artificial Neural Networks (ANN and Gene Expression Programing (GEP to estimate the age and then compare the results. New methodologies like Gene Expression Programing (GEP have been explored here and significant results were found. The dataset has been developed to provide more efficient results by superior preprocessing methods. This proposed approach has been developed, tested and trained using both the methods. A public data set was used to test the system, FG-NET. The quality of the proposed system for age estimation using facial features is shown by broad experiments on the available database of FG-NET.

  20. Net Shape Technology in Aerospace Structures. Volume 1.

    Science.gov (United States)

    1986-11-01

    composed o f man \\ smll decta-ilI parIt s maid cI n sta I f: J1r om o ne p re cisi o n ’or-g In g. The cst I im tcd savNIn)g s -Ic h i c \\ e d M...metal I I orgy materialIs baised onl ra pid sol idi ficatIIon tech nology . Conser\\ at I nn ofC miatcr Ial s i n its own ri gh t is not genicrall a 1 1P r

  1. 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...

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. An overview of Bayesian methods for neural spike train analysis.

    Science.gov (United States)

    Chen, Zhe

    2013-01-01

    Neural spike train analysis is an important task in computational neuroscience which aims to understand neural mechanisms and gain insights into neural circuits. With the advancement of multielectrode recording and imaging technologies, it has become increasingly demanding to develop statistical tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed.

  8. An Overview of Bayesian Methods for Neural Spike Train Analysis

    Directory of Open Access Journals (Sweden)

    Zhe Chen

    2013-01-01

    Full Text Available Neural spike train analysis is an important task in computational neuroscience which aims to understand neural mechanisms and gain insights into neural circuits. With the advancement of multielectrode recording and imaging technologies, it has become increasingly demanding to develop statistical tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed.

  9. 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...

  10. 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.

  11. Feasibility of Achieving a Zero-Net-Energy, Zero-Net-Cost Homes

    Energy Technology Data Exchange (ETDEWEB)

    Al-Beaini, S.; Borgeson, S.; Coffery, B.; Gregory, D.; Konis, K.; Scown, C.; Simjanovic, J.; Stanley, J.; Strogen, B.; Walker, I.

    2009-09-01

    A green building competition, to be known as the Energy Free Home Challenge (EFHC), is scheduled to be opened to teams around the world in 2010. This competition will encourage both design innovation and cost reduction, by requiring design entries to meet 'zero net energy' and 'zero net cost' criteria. For the purposes of this competition, a 'zero net energy' home produces at least as much energy as it purchases over the course of a year, regardless of the time and form of the energy (e.g., electricity, heat, or fuel) consumed or produced. A 'zero net cost' home is no more expensive than a traditional home of comparable size and comfort, when evaluated over the course of a 30-year mortgage. In other words, the 'green premium' must have a payback period less than 30 years, based on the value of energy saved. The overarching goal of the competition is to develop affordable, high-performance homes that can be mass-produced at a large scale, and are able to meet occupant needs in harsh climates (as can be found where the competition will be held in Illinois). This report outlines the goals of the competition, and gauges their feasibility using both modeling results and published data. To ensure that the established rules are challenging, yet reasonable, this report seeks to refine the competition goals after exploring their feasibility through case studies, cost projections, and energy modeling. The authors of this report conducted a survey of the most progressive home energy-efficiency practices expected to appear in competition design submittals. In Appendix A, a summary can be found of recent projects throughout the United States, Canada, Germany, Switzerland, Sweden and Japan, where some of the most progressive technologies have been implemented. As with past energy efficient home projects, EFHC competitors will incorporate a multitude of energy efficiency measures into their home designs. The authors believe that

  12. Final Technical Report - Autothermal Styrene Manufacturing Process with Net Export of Energy

    Energy Technology Data Exchange (ETDEWEB)

    Trubac, Robert , E.; Lin, Feng; Ghosh, Ruma: Greene, Marvin

    2011-11-29

    The overall objectives of the project were to: (a) develop an economically competitive processing technology for styrene monomer (SM) that would reduce process energy requirements by a minimum 25% relative to those of conventional technology while achieving a minimum 10% ROI; and (b) advance the technology towards commercial readiness. This technology is referred to as OMT (Oxymethylation of Toluene). The unique energy savings feature of the OMT technology would be replacement of the conventional benzene and ethylene feedstocks with toluene, methane in natural gas and air or oxygen, the latter of which have much lower specific energy of production values. As an oxidative technology, OMT is a net energy exporter rather than a net energy consumer like the conventional ethylbenzene/styrene (EB/SM) process. OMT plants would ultimately reduce the cost of styrene monomer which in turn will decrease the costs of polystyrene making it perhaps more cost competitive with competing polymers such as polypropylene.

  13. Neural mechanisms of social dominance

    Directory of Open Access Journals (Sweden)

    Noriya eWatanabe

    2015-06-01

    Full Text Available In a group setting, individuals’ perceptions of their own level of dominance or of the dominance level of others, and the ability to adequately control their behavior based on these perceptions are crucial for living within a social environment. Recent advances in neural imaging and molecular technology have enabled researchers to investigate the neural substrates that support the perception of social dominance and the formation of a social hierarchy in humans. At the systems’ level, recent studies showed that dominance perception is represented in broad brain regions which include the amygdala, hippocampus, striatum, and various cortical networks such as the prefrontal, and parietal cortices. Additionally, neurotransmitter systems such as the dopaminergic and serotonergic systems, modulate and are modulated by the formation of the social hierarchy in a group. While these monoamine systems have a wide distribution and multiple functions, it was recently found that the Neuropeptide B/W contributes to the perception of dominance and is present in neurons that have a limited projection primarily to the amygdala. The present review discusses the specific roles of these neural regions and neurotransmitter systems in the perception of dominance and in hierarchy formation.

  14. 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.

  15. 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...

  16. 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...

  17. Energy performance of net-zero and near net-zero energy homes in New England

    Science.gov (United States)

    Thomas, Walter D.

    Net-Zero Energy Homes (NZEHs) are homes that consume no more energy than they produce on site during the course of a year. They are well insulated and sealed, use energy efficient appliances, lighting, and mechanical equipment, are designed to maximize the benefits from day lighting, and most often use a combination of solar hot water, passive solar and photovoltaic (PV) panels to produce their on-site energy. To date, NZEHs make up a miniscule percentage of homes in the United States, and of those, few have had their actual performance measured and analyzed once built and occupied. This research focused on 19 NZEHs and near net-zero energy homes (NNZEHs) built in New England. This set of homes had varying designs, numbers of occupants, and installed technologies for energy production, space heating and cooling, and domestic hot water systems. The author worked with participating homeowners to collect construction and systems specifications, occupancy information, and twelve months of energy consumption, production and cost measurements, in order to determine whether the homes reached their respective energy performance design goals. The author found that six out of ten NZEHs achieved net-zero energy or better, while all nine of the NNZEHs achieved an energy density (kWh/ft 2/person) at least half as low as the control house, also built in New England. The median construction cost for the 19 homes was 155/ft 2 vs. 110/ft2 for the US average, their average monthly energy cost was 84% below the average for homes in New England, and their estimated CO2 emissions averaged 90% below estimated CO2 emissions from the control house. Measured energy consumption averaged 14% below predictions for the NZEHs and 38% above predictions for the NNZEHs, while generated energy was within +/- 10% of predicted for 17 out of 18 on-site PV systems. Based on these results, the author concludes that these types of homes can meet or exceed their designed energy performance (depending on

  18. 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...

  19. 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.

  20. 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.

  1. 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

  2. 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...

  3. 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...

  4. 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.

  5. 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.

  6. OGC NetCDF specifications: Towards a unified Interface for Earth Observation data in the Geospatial Information domain

    Science.gov (United States)

    Nativi, S.; Domenico, B.

    2016-12-01

    The purpose of the OGC netCDF Standardization Working Group (SWG) is to extend further the existing netCDF standard with extension modules for additional data models, encodings, and conventions. The scope is to use netCDF as a unified model and interface for encoding and accessing multidisciplinary Geosciences data. This has facilitated the interoperability across the diverse Geoscience disciplines in the geospatial information area. OGC netCDF SWG has developed a primer document to provide an overview of the current OGC netCDF standards suite and describe the possible extensions. These extensions have been recognized to fill the gap between the netCDF Community (e.g. Climate Changes, Atmospheric and Oceanography Communities) and the Geospatial Information Community (e.g. GIS, Geo-Web, etc.). This is pursued by supporting modeling and encoding of digital geospatial information representing space/time-varying phenomena. OGC netCDF SWG, has recently recognized a set of useful specifications (e.g. semantics, conventions, and encodings) to be specified for improving interoperability among the systems using the netCDF technology. They address important requirements coming from the netCDF Community and consider the present geospatial information landscape, i.e. ISO standards, CF conventions, the other OGC specifications, W3C specification for spatial data on the Web, etc. The main netCDF developments and related challenges considered by the presentation are: (Discovery) Metadata conventions; Advanced «Reference» conventions; Earth Observation Conventions; Semi-structured Encodings.

  7. 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

  8. Hands on with ASP.NET MVC covering MVC 6

    CERN Document Server

    Sahay, Rahul

    2014-01-01

    MVC (Model-View-Controller) is the popular Microsoft technology which enables you to build dynamic, data-driven, mobile websites, TDD site. Hands-On with ASP.NET MVC is not only written for those who are going to have affair with MVC for the 1st time, rather it is written in such a way that even experienced professional will love reading this book. This book covers all the tiny steps on using MVC at its best. With complete practical tutorials to illustrate the concepts, you will step by step build one End to End application which covers below mentioned techniques - Controllers, Views, Models,

  9. 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

  10. 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

  11. AN-CASE NET-CENTRIC modeling and simulation

    Science.gov (United States)

    Baskinger, Patricia J.; Chruscicki, Mary Carol; Turck, Kurt

    2009-05-01

    The objective of mission training exercises is to immerse the trainees into an environment that enables them to train like they would fight. The integration of modeling and simulation environments that can seamlessly leverage Live systems, and Virtual or Constructive models (LVC) as they are available offers a flexible and cost effective solution to extending the "war-gaming" environment to a realistic mission experience while evolving the development of the net-centric enterprise. From concept to full production, the impact of new capabilities on the infrastructure and concept of operations, can be assessed in the context of the enterprise, while also exposing them to the warfighter. Training is extended to tomorrow's tools, processes, and Tactics, Techniques and Procedures (TTPs). This paper addresses the challenges of a net-centric modeling and simulation environment that is capable of representing a net-centric enterprise. An overview of the Air Force Research Laboratory's (AFRL) Airborne Networking Component Architecture Simulation Environment (AN-CASE) is provide as well as a discussion on how it is being used to assess technologies for the purpose of experimenting with new infrastructure mechanisms that enhance the scalability and reliability of the distributed mission operations environment.

  12. Neural simulations on multi-core architectures

    Directory of Open Access Journals (Sweden)

    Hubert Eichner

    2009-07-01

    Full Text Available Neuroscience is witnessing increasing knowledge about the anatomy and electrophysiological properties of neurons and their connectivity, leading to an ever increasing computational complexity of neural simulations. At the same time, a rather radical change in personal computer technology emerges with the establishment of multi-cores: high-density, explicitly parallel processor architectures for both high performance as well as standard desktop computers. This work introduces strategies for the parallelization of biophysically realistic neural simulations based on the compartmental modeling technique and results of such an implementation, with a strong focus on multi-core architectures and automation, i. e. user-transparent load balancing.

  13. EDITORIAL: Focus on the neural interface Focus on the neural interface

    Science.gov (United States)

    Durand, Dominique M.

    2009-10-01

    The possibility of an effective connection between neural tissue and computers has inspired scientists and engineers to develop new ways of controlling and obtaining information from the nervous system. These applications range from `brain hacking' to neural control of artificial limbs with brain signals. Notwithstanding the significant advances in neural prosthetics in the last few decades and the success of some stimulation devices such as cochlear prosthesis, neurotechnology remains below its potential for restoring neural function in patients with nervous system disorders. One of the reasons for this limited impact can be found at the neural interface and close attention to the integration between electrodes and tissue should improve the possibility of successful outcomes. The neural interfaces research community consists of investigators working in areas such as deep brain stimulation, functional neuromuscular/electrical stimulation, auditory prostheses, cortical prostheses, neuromodulation, microelectrode array technology, brain-computer/machine interfaces. Following the success of previous neuroprostheses and neural interfaces workshops, funding (from NIH) was obtained to establish a biennial conference in the area of neural interfaces. The first Neural Interfaces Conference took place in Cleveland, OH in 2008 and several topics from this conference have been selected for publication in this special section of the Journal of Neural Engineering. Three `perspectives' review the areas of neural regeneration (Corredor and Goldberg), cochlear implants (O'Leary et al) and neural prostheses (Anderson). Seven articles focus on various aspects of neural interfacing. One of the most popular of these areas is the field of brain-computer interfaces. Fraser et al, report on a method to generate robust control with simple signal processing algorithms of signals obtained with electrodes implanted in the brain. One problem with implanted electrode arrays, however, is that

  14. Neural engineering from advanced biomaterials to 3D fabrication techniques

    CERN Document Server

    Kaplan, David

    2016-01-01

    This book covers the principles of advanced 3D fabrication techniques, stem cells and biomaterials for neural engineering. Renowned contributors cover topics such as neural tissue regeneration, peripheral and central nervous system repair, brain-machine interfaces and in vitro nervous system modeling. Within these areas, focus remains on exciting and emerging technologies such as highly developed neuroprostheses and the communication channels between the brain and prostheses, enabling technologies that are beneficial for development of therapeutic interventions, advanced fabrication techniques such as 3D bioprinting, photolithography, microfluidics, and subtractive fabrication, and the engineering of implantable neural grafts. There is a strong focus on stem cells and 3D bioprinting technologies throughout the book, including working with embryonic, fetal, neonatal, and adult stem cells and a variety of sophisticated 3D bioprinting methods for neural engineering applications. There is also a strong focus on b...

  15. 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…

  16. 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...

  17. 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...

  18. 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.

  19. Effects of Net Metering on the Use of Small-Scale Wind Systems in the United States

    Energy Technology Data Exchange (ETDEWEB)

    Forsyth, T. L.; Pedden, M.; Gagliano, T.

    2002-11-01

    Factors such as technological advancements, steadily decreasing costs, consumer demand, and state and federal policies are combining to make wind energy the world's fastest growing energy source. State and federal policies are facilitating the growth of the domestic, large-scale wind power market; however, small-scale wind projects (those with a capacity of less than 100 kilowatts[kW]) still face challenges in many states. Net metering, also referred to as net billing, is one particular policy that states are implementing to encourage the use of small renewable energy systems. Net metering allows individual, grid-tied customers who generate electricity using a small renewable energy system to receive credit from their utility for any excess power they generate beyond what they consume. Under most state rules, residential, commercial, and industrial customers are eligible for net metering; however, some states restrict eligibility to particular customer classes. This paper illustrates how net metering programs in certain states vary considerably in terms of how customers are credited for excess power they generate; the type and size of eligible technologies and whether the utility; the state, or some other entity administers the program. This paper focuses on10 particular states where net metering policies are in place. It analyzes how the different versions of these programs affect the use of small-scale wind technologies and whether some versions are more favorable to this technology than others. The choice of citizens in some states to net meter with photovoltaics is also examined.

  20. 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....

  1. 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.

  2. .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.

  3. 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

  4. 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....

  5. The KM3NeT Digital Optical Module

    Directory of Open Access Journals (Sweden)

    Vivolo Daniele

    2016-01-01

    Full Text Available KM3NeT is a European deep-sea multidisciplinary research infrastructure in the Mediterranean Sea. It will host a km3-scale neutrino telescope and dedicated instruments for long-term and continuous measurements for Earth and Sea sciences. The KM3NeT neutrino telescope is a 3-dimensional array of Digital Optical Modules, suspended in the sea by means of vertical string structures, called Detection Units, supported by two pre-stretched Dyneema ropes, anchored to the seabed and kept taut with a system of buoys. The Digital Optical Module represents the active part of the neutrino telescope. It is composed by a 17-inch, 14 mm thick borosilicate glass (Vitrovex spheric vessel housing 31 photomultiplier tubes with 3-inch photocathode diameter and the associated front-end and readout electronics. The technical solution adopted for the KM3NeT optical modules is characterized by an innovative design, considering that existing neutrino telescopes, Baikal, IceCube and ANTARES, all use large photomultipliers, typically with a diameter of 8″ or 10″. It offers several advantages: higher sensitive surface (1260 cm2, weaker sensitivity to Earth's magnetic field, better distinction between single-photon and multi-photon events (photon counting and directional information with an almost isotropic field of view. In this contribution the design and the performance of the KM3NeT Digital Optical Modules are discussed, with a particular focus on enabling technologies and integration procedure.

  6. 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...

  7. 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.

  8. 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.

  9. Automatic fishing net detection and recognition based on optical gated viewing for underwater obstacle avoidance

    Science.gov (United States)

    Liu, Xiaoquan; Wang, Xinwei; Ren, Pengdao; Cao, Yinan; Zhou, Yan; Liu, Yuliang

    2017-08-01

    An automatic fishing net detection and recognition method for underwater obstacle avoidance is proposed. In the method, optical gated viewing technology is utilized to obtain high-resolution fishing net images and extend detection distance by suppressing water backscattering and background noise. The fishing net recognition is based on the proposed histograms of slope lines (HSLs) descriptors plus a support vector machine classifier. The extraction of HSL descriptors includes five steps of contrast-limited adaptive histogram equalization, the Gaussian low-pass filtering, the Canny detection, the Hough transform, and weighted vote. In the proof experiments, the detection distance of the fishing net reaches 5.7 attenuation length and the recognition accuracy reaches 93.79%.

  10. 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.

  11. Pax7 lineage contributions to the mammalian neural crest.

    Directory of Open Access Journals (Sweden)

    Barbara Murdoch

    Full Text Available Neural crest cells are vertebrate-specific multipotent cells that contribute to a variety of tissues including the peripheral nervous system, melanocytes, and craniofacial bones and cartilage. Abnormal development of the neural crest is associated with several human maladies including cleft/lip palate, aggressive cancers such as melanoma and neuroblastoma, and rare syndromes, like Waardenburg syndrome, a complex disorder involving hearing loss and pigment defects. We previously identified the transcription factor Pax7 as an early marker, and required component for neural crest development in chick embryos. In mammals, Pax7 is also thought to play a role in neural crest development, yet the precise contribution of Pax7 progenitors to the neural crest lineage has not been determined.Here we use Cre/loxP technology in double transgenic mice to fate map the Pax7 lineage in neural crest derivates. We find that Pax7 descendants contribute to multiple tissues including the cranial, cardiac and trunk neural crest, which in the cranial cartilage form a distinct regional pattern. The Pax7 lineage, like the Pax3 lineage, is additionally detected in some non-neural crest tissues, including a subset of the epithelial cells in specific organs.These results demonstrate a previously unappreciated widespread distribution of Pax7 descendants within and beyond the neural crest. They shed light regarding the regionally distinct phenotypes observed in Pax3 and Pax7 mutants, and provide a unique perspective into the potential roles of Pax7 during disease and development.

  12. 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.

  13. 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.

  14. 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.

  15. 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.)

  16. 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.

  17. Tecnoactivism. The political experience of Riereta.net

    Directory of Open Access Journals (Sweden)

    Blanca Callén

    2011-03-01

    Full Text Available This Thesis's summary explores the political and epistemological proposal that emerges from Free Software development made from Riereta.net. From the ethnography of this project, we analyse its contributions to knowledge production and to social studies of science and technology. This allows us to define the experience as a 'techno-epistemic workshop' in which new forms of organization, objects and epistemic practices coexist with other traditional ones, such as typical of laboratories and other techno-scientific institutions. Its description as “technoactivist” reveals its critical and politicizing potential in the field of technology and knowledge production. In a second moment, we explore its political potential in the light of Social Movements' Theories and other ones related to political philosophy. In conclusion, the experience of Riereta offers us new ways of understanding the collective political action, its objects and agents.

  18. The Strategies of Academic Library to Serve Net-Generation

    Directory of Open Access Journals (Sweden)

    candra pratama setiawan

    2018-01-01

    Full Text Available The fast developments in information and communication technology have rapidly shaped and created enormous changes in the way people live and use libraries. The generation who grow in this era is called net generation. Academic libraries, where the majority of the users are the netgeneration, have started to implement the concept of hybrid library as a response of the technological advances. The trend of digital collections usage is getting increase, on the other hand, the number of library visitor is getting lower significantly. The condition make librarians afraid of being abandoned by its users, whereas libraries still have many physical collections. This paper is written as a result of simple observation in some libraries where the needs of netgeneration has accomodated. The concept of library as place, and library marketing offer the solutions to deal with the problem. Libraries can develop and provide some facilities that suitable with the net-generation characteristics. In addition, libraries can create some events to promote their services even the collections to attract the users to visit library.

  19. On sparsely connected optimal neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V. [Los Alamos National Lab., NM (United States); Draghici, S. [Wayne State Univ., Detroit, MI (United States)

    1997-10-01

    This paper uses two different approaches to show that VLSI- and size-optimal discrete neural networks are obtained for small fan-in values. These have applications to hardware implementations of neural networks, but also reveal an intrinsic limitation of digital VLSI technology: its inability to cope with highly connected structures. The first approach is based on implementing F{sub n,m} functions. The authors 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. In order to estimate the area (A) and the delay (T) of such networks, the following cost functions will be used: (i) the connectivity and the number-of-bits for representing the weights and thresholds--for good estimates of the area; and (ii) the fan-ins and the length of the wires--for good approximates of the delay. 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 the size of fan-in 2 neural networks. They will generalize the result presented there to arbitrary fan-in, and prove that the size is minimized by small fan-in values. Finally, a size-optimal neural network of small constant fan-ins will be suggested for F{sub n,m} functions.

  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.