Energy Technology Data Exchange (ETDEWEB)

This thesis investigates the application of artificial neural networks for the compression of image data. An algorithm is developed using the competitive learning paradigm which takes advantage of the parallel processing and classification capability of neural networks to produce an efficient implementation of vector quantization. Multi-Stage, tree searched, and classification vector quantization codebook design are adapted to the neural network design to reduce the computational cost and hardware requirements. The results show that the new algorithm provides a substantial reduction in computational costs and an improvement in performance.

British Library Electronic Table of Contents (United Kingdom)

This article presents the micro-electro-mechanical systems (MEMS) microrobot which demonstrates locomotion controlled by hardware neural networks (HNN). The size of the microrobot fabricated by the MEMS technology is 4 ? 4 ? 3.5 mm. The frame of the robot is made of silicon wafer, and it is equipped with a rotary-type actuator, a link mechanism, and six legs. The rotary-type actuator generates rotational movement by applying an electrical current to artificial muscle wires. The locomotion of the microrobot is obtained by the rotation of the rotary-type actuator. As in a living organism, the HNN realized robot control without using any software programs, A/D converters, or additional driving circuits. A central pattern generator (CPG) model was implemented as an HNN system to emulate the lo...

Science.gov (United States)

Not Available

Science.gov (United States)

Not Available

Energy Technology Data Exchange (ETDEWEB)

Multiple linear regression, principal component analysis, partial least squares, polynomial regression and artificial neural networks are popular techniques for process modeling. An industrial case study illustrates some of these technologies, with an emphasis on artificial neural networks. Experience with this and other projects indicates that while neural network models, combined with partial least squares when necessary, are an excellent tool for modeling, linear techniques may also be appropriate in some cases. Regardless of the specific method used, software analyzers are an attractive lower-cost alterative to hardware options in some monitoring applications. From a fundamental point of view, the result of chemical analysis can be considered as the dependent variable(s) of a process system having a number of independent variables. The ...

KoreaScience (Korea)

Full Text Available

International Nuclear Information System (INIS)

In this article, the ability of artificial neural networks in prediction of separation in steady two dimensional boundary layer flows is studied. Data for network training is extracted from numerical solution of an ODE obtained from Von Karman integral equation with approximate one parameter Pohlhousen velocity profile. As an appropriate neural network, a two layer radial basis generalized regression artificial neural network is used. The results shows good agreements between the overall behavior of the flow fields predicted by the artificial neural network and the actual flow fields for some cases. The method easily can be extended to unsteady separation and turbulent as well as compressible boundary layer flows. (author)

Energy Technology Data Exchange (ETDEWEB)

The catalytic liquefaction of a Chinese bituminous coal was simulated by artificial neural network. Three liquefaction variables, catalyst loading, reaction temperature and reaction time were used as inputs and tetrohydrofuran (THF) conversion and toluene (T) conversion were used as outputs. The artificial neural network, trained by the experimental data, could represent the liquefaction process, with a mean squared deviation of less than 0.025. 7 refs.,1 fig., 3 tabs.

Energy Technology Data Exchange (ETDEWEB)

This paper presents the application of artificial neural networks to adiabatic flame temperature prediction of hydrocarbon fuels. The investigation was conducted over a wide range of operating conditions in terms of fuel composition, pressure and temperature of reactants, fuel-air equivalence ratio and fuel vapour fraction. Several neural network models for predicting the flame temperature for different applicable fuel ranges were built and examined. The proper preparation of network training data and the appropriate choice of network parameters for achieving better prediction accuracy are discussed. The neural network prediction results were compared with those calculated by a thermodynamic and chemical equilibrium-based computer code - the NASA program CET89. It was shown that trained neural ...

Energy Technology Data Exchange (ETDEWEB)

Supplementing the collection of artificial neural network methodologies devised for monitoring energy producing installations, a general regression artificial neural network is proposed for the identification of the two-phase flow that occurs in the coolant channels of boiling water reactors. The utilization of a limited number of image features derived from radiography images affords the proposed approach with efficiency and non-invasiveness. Additionally, the application of counter-clustering to the input patterns prior to training accomplishes an 80% reduction in network size as well as in training and test time. Cross-validation tests confirm accurate on-line flow regime identification.

Energy Technology Data Exchange (ETDEWEB)

Target recognition requires the ability to distinguish targets from non-targets, a capability called one-class generalization. Many neural network pattern classifiers fail as one-class classifiers because they use open decision boundaries. To function as one-class classifier, a neural network must have three types of generalization: within-class, between-class, and out-of-class. We discuss these three types of generalization and identify neural network architectures that meet these requirements. We have applied our one-class classifier ideas to the problem of automatic target recognition in synthetic aperture radar. We have compared three neural network algorithms: Carpenter and Grossberg`s algorithmic version of the Adaptive Resonance Theory (ART-2A), Kohonen`s Learning Vector Quantization (LVQ), and Reilly and Cooper`s ...

Energy Technology Data Exchange (ETDEWEB)

As an application of ART2 neural networks, computer aided monitoring of pump efficiency is successfully examined for an industrial waste-liquid treatment process with measured data of valve openness and liquid flow rates. By running the neural networks in parallel, we confirm that accuracy to detect system changes is good, and the adjustment of classifier parameters is relatively easy. Investigating the resulting classes carefully, frequency of each class is correlated with pump efficiency. The relative amount of variables are also related to the classes. (author)

Energy Technology Data Exchange (ETDEWEB)

The detectors used in the TS93 balloon flight produced a large volume of information for each cosmic ray trigger. Some of the data was visual in nature, other portions contained energy deposition and timing information. The data sets are amenable to conventional analysis techniques but there is no assurance that conventional techniques make full use of subtle correlations and relations amongst the detector responses. With the advent of neural network technologies, particularly adept at classification of complex phenomena, it would seem appropriate to explore the utility of neural network techniques to classify particles observed with the instruments. In this paper neural network based methodology for signal/background discrimination in a cosmic ray space experiment is discussed. Results are presented for electron and positron classification in the TS93 flight ...

Energy Technology Data Exchange (ETDEWEB)

A new recurrent neural network power system stabilizer (RNNPSS) based on genetic algorithm (GA) was presented. It shows faster convergence than the linear quadratic regulator (LQR) stabilizer in a multi-machine power system, because the proposed GA based neural network was first trained off-line to determine the optimal values of the learning rates. Otherwise, the RNNPSS consists of just two layers. As such, the time consumption of the damping oscillations is lower than with conventional methods. In addition, the operating range of the RNNPSS is greater than that of the LQR and conventional three layer neural networks, since the RNNPSS can greatly reduce system complexity and effectively damp system oscillations. 9 refs., 7 figs.

Energy Technology Data Exchange (ETDEWEB)

This paper describes the structure of dynamic neuronal ensembles (DNEs). DNEs represent a new paradigm for learning, based on biological neural networks that use variable structures. We present a computational neural element that demonstrates biological neuron functionality such as neurotransmitter feedback absolute refractory period and multiple output potentials. More specifically, we will develop a network of neural elements that have the ability to dynamically strengthen, weaken, add and remove interconnections. We demonstrate that the DNE is capable of performing dynamic modifications to neuron connections and exhibiting biological neuron functionality. In addition to its applications for learning, DNEs provide an excellent environment for testing and analysis of biological neural systems. An example of habituation and hyper-sensitization in biological ...

British Library Electronic Table of Contents (United Kingdom)

Because the state of a free-floating space robot model is uncertain and sudden changes in the model parameters might undermine the stability of the system, this paper proposes a control strategy based on a variable structure neural integrated controller. This scheme does not need a precise space robot model, making use of the radial basis function neural network ability approach to learn about an uncertain model. The network weights are adjusted online in real-time. During the early period of the control phase and parameter changes, the variable structure controller compensates for the uncertain model which the neural network could not learn well. It also creates global asymptotic stability for the whole closed-loop system. Simulation results show that the controller can handle bad changea...

Energy Technology Data Exchange (ETDEWEB)

A novel approach is presented to extract relevant parameters associated with the energy loss of ejectiles from nuclear reactions obtained by digitizing the signals of a Bragg curve spectrometer. New and more powerful computational paradigms allow a more thorough pulse-shape analysis. This is fulfilled using a back-propagation artificial neural network as a pattern identifier. The known problem of over-training is discussed.

Energy Technology Data Exchange (ETDEWEB)

Acceptance Testing of the WRAP 1 Plant Control System Hardware will be conducted throughout the construction of WRAP I with the final testing on the Process Area hardware being completed in November 1996. The hardware tests will be broken out by the following functional areas; Local Control Units, Operator Control Stations in the WRAP Control Room, DMS Server, PCS Server, Operator Interface Units, printers, DNS terminals, WRAP Local Area Network/Communications, and bar code equipment. This document will contain completed copies of each of the hardware tests along with the applicable test logs and completed test exception reports.

Energy Technology Data Exchange (ETDEWEB)

Within this paper the potentialities of using networked embedded systems will be discussed. New embedded hardware with network connectivity allows remote administration and software updates of solar thermal system controllers via internet. System self analysis helps to minimize breakdown times by sending email and SMS to request maintenance staff. (orig.)

British Library Electronic Table of Contents (United Kingdom)

Timely detection of the pneumatic system problems is important in industry. Many techniques have been employed to solve this problem. In this paper, Genetic Algorithm (GA) based optimal configuration of neural networks is proposed for fault diagnostic of bottle filling systems. Back-propagation is used for neural networks algorithm. The back-propagation algorithm had six inputs and one output. A fitness function was designed to the minimize execution time of ANN model by keeping the number of hidden layer(s) and nodes as low as possible while the mean square error of estimated output error is minimized. The designed GA-ANN combination and the graphical user interface (GUI) eliminate the trial and error process for selection of the fastest and most accurate configuration. The performance of...

Energy Technology Data Exchange (ETDEWEB)

In this paper, a neural networks (NN) based adaptive sliding mode controller (SMC) is introduced. The selection of SMC feedback gains is normally based on one operating point and thus the performance of the controller away from the design operating point is, of necessity, a compromise. The adaptive SMC is proposed to overcome the limitations imposed on the effectiveness of the SMC under different operating conditions. Neural networks are used for online prediction of the optimal SMC gains when the operating point changes. The proposed method has been applied to a power system stabilizer (PSS) of a single machine power system. Simulation results are included to demonstrate the performance of the proposed control scheme.

CERN Document Server

The Elman artificial neural network (ANN) (feedback connection) was used for seismic data filtering. The recurrent connection that characterizes this network offers the advantage of storing values from the previous time step to be used in the current time step. The proposed structure has the advantage of training simplicity by a back-propagation algorithm (steepest descent). Several trials were addressed on synthetic (with 10% and 50% of random and Gaussian noise) and real seismic data using respectively 10 to 30 neurons and a minimum of 60 neurons in the hidden layer. Both an iteration number up to 4000 and arrest criteria were used to obtain satisfactory performances. Application of such networks on real data shows that the filtered seismic section was efficient. Adequate cross-validation test is done to ensure the performance of network on new data sets.

Science.gov (United States)

In this paper we propose a method for construction of feed-forward neural classifiers based on regularization and adaptive architectures. Using a penalized maximum likelihood scheme, we derive a modified form of the entropic error measure and an algebraic estimate of the test error. In conjunction with optimal brain damage pruning, a test error estimate is used to select the network architecture. The scheme is evaluated on four classification problems. PMID:12662736

Energy Technology Data Exchange (ETDEWEB)

In this paper, the combustible value (i.e. 100-Ash) and combustible recovery of coal flotation concentrate were predicted by regression and artificial neural network based on proximate and group macerals analysis. The regression method shows that the relationships between (a) in (ash), volatile matter and moisture (b) in (ash), in (liptinite), fusinite and vitrinite with combustible value can achieve the correlation coefficients (R{sup 2}) of 0.8 and 0.79, respectively. In addition, the input sets of (c) ash, volatile matter and moisture (d) ash, liptinite and fusinite can predict the combustible recovery with the correlation coefficients of 0.84 and 0.63, respectively. Feed-forward artificial neural network with 6-8-12-11-2-1 arrangement for moisture, ash and volatile matter input set was capable to estimate both combustible value and combustible recovery with correlation of 0.95. It was shown that the ...

UK PubMed Central (United Kingdom)

Synaptic gain control and information storage in neural networks are mediated by alterations in synaptic transmission, such as in long-term potentiation (LTP). Here, we show using both in...Full Text Available

UK PubMed Central (United Kingdom)

BackgroundWax esters are important ingredients in cosmetics, pharmaceuticals, lubricants and other chemical industries due to their excellent wetting property. Since the naturally...Full Text Available

Energy Technology Data Exchange (ETDEWEB)

The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and ...

Energy Technology Data Exchange (ETDEWEB)

A model-based technique incorporating neural networks has been developed for process monitoring. The technique is intended for processes where the uncertainty in the reference model is larger than desired but where process measurements providing additional information about the behavior of the system are available. This data is used to reduce the uncertainty of the model. The technique has been implemented in a real-time system for monitoring operational changes of mechanical equipment for use in predictive maintenance applications. Tests on a peristaltic pump were conducted and demonstrate the advantages of the proposed technique.

Energy Technology Data Exchange (ETDEWEB)

By characterising the microstructure, quantitative image analysis allows to draw conclusions on the mechanical properties of materials. On fine microstructures with low contrast, e.g. of hardened steels, texture analysis has to be applied for quantification. Feeding texture parameters according to Haralick into a trained neural network, a correlation between the microstructure and the hardness of the steels C45 and 100Cr6 can be achieved. (orig.)

International Nuclear Information System (INIS)

The paper provides a brief description of the fuel characterization for Fast Breeder Test Reactor (FBTR) and Prototype Fast Breeder Reactor (PFBR). The development and characterization of mechanical properties of Alloy D9 clad and wrapper tubes are discussed. The problems associated with fusion welding of Alloy D9 are outlined. Non-destructive characterization of cladding tubes by optimum encircling eddy current probes, on-line and off-line neural network methods is presented. Both the on-line and off-line neural network methods could readily detect and size defects specified by the designers

British Library Electronic Table of Contents (United Kingdom)

This work addresses the problem of estimating the direction-of-arrival (DOA) of two sources using an array of sensors. This problem is mostly useful in radar applications, where we have few targets at each range bin. Super-resolution algorithms, such as maximum likelihood (ML) estimation and multiple signal classification (MUSIC), have been applied to this problem, but the former involves high computation efforts, while the later has poor estimation performance for coherent sources. In this work, we propose a DOA estimation network, named RBF-AML, which combines the approximated ML (AML) estimator and a radial basis function (RBF) neural network (NN). In the proposed RBF-AML network, the entire two dimensional DOA space is divided into multiple sectors covered by RBF experts. The AML funct...

Energy Technology Data Exchange (ETDEWEB)

A tiered communications architecture for managing network traffic in a distributed system. Communication between client or control computers and a plurality of hardware devices is administered by agent and monitor devices whose activities are coordinated to reduce the number of open channels or sockets. The communications architecture also improves the transparency and scalability of the distributed system by reducing network mapping dependence. The architecture is desirably implemented in a proton beam therapy system to provide flexible security policies which improve patent safety and facilitate system maintenance and development.

Energy Technology Data Exchange (ETDEWEB)

This paper presents general considerations concerning the application of artificial neural networks algorithms, more specifically the back-propagation learning algorithm and feed-forward multi-layer networks, to several problems in power system. The main application in power systems is the load forecasting, and two solution methods are used to solve it. (author). 45 figs., 32 tabs., 144 refs.

CERN Document Server

Evolutionary artificial neural networks (EANNs) refer to a special class of artificial neural networks (ANNs) in which evolution is another fundamental form of adaptation in addition to learning. Evolutionary algorithms are used to adapt the connection weights, network architecture and learning algorithms according to the problem environment. Even though evolutionary algorithms are well known as efficient global search algorithms, very often they miss the best local solutions in the complex solution space. In this paper, we propose a hybrid meta-heuristic learning approach combining evolutionary learning and local search methods (using 1st and 2nd order error information) to improve the learning and faster convergence obtained using a direct evolutionary approach. The proposed technique is tested on three different chaotic time series and the test results are compared with some ...

Energy Technology Data Exchange (ETDEWEB)

This work presents a digital adaptive Power System Stabilizer (PSS) which operates in a gain scheduling scheme. It`s parameters are designed for a lot of different operating regions in a P x Q plane (active and reactive powers), and saved in a microcomputer real time control. During working, the PSS identifies the present region of operation, and synthesizes its damping signal in accordance with the parameters for that region. As an extension of the method, a neural PSS, which uses the set of parameters of each region as a standard set to train a neural network to form this PSS, is also proposed. The tests presented show good performance for both PSS, when compared to a conventional (non adaptive) one. (author) 10 refs., 5 figs., 1 tab.; e-mail: jalb at guama.cpgee.ufpa.br

British Library Electronic Table of Contents (United Kingdom)

Summary Humans discount the value of future rewards over time. Here we show using functional magnetic resonance imaging (fMRI) and neural coupling analyses that episodic future thinking reduces the rate of delay discounting through a modulation of neural decision-making and episodic future thinking networks. In addition to a standard control condition, real subject-specific episodic event cues were presented during a delay discounting task. Spontaneous episodic imagery during cue processing predicted how much subjects changed their preferences toward more future-minded choice behavior. Neural valuation signals in the anterior cingulate cortex and functional coupling of this region with hippocampus and amygdala predicted the degree to which future thinking modulated individual preference fu...

Energy Technology Data Exchange (ETDEWEB)

Results from ultimate analysis, proximate and petrographic analyses of a wide range of Kentucky coal samples were used to predict coal rank parameters (vitrinite maximum reflectance (R{sub max}) and gross calorific value (GCV)) using multivariable regression and artificial neural network (ANN) methods. Volatile matter, carbon, total sulfur, hydrogen and oxygen were used to predict both R{sub max} and GCV by regression and ANN. Multivariable regression equations to predict R{sub max} and GCV showed R{sup 2} = 0.77 and 0.69, respectively. Results from the ANN method with a 2-5-4-2 arrangement that simultaneously predicts GCV and R{sub max} showed R{sup 2} values of 0.84 and 0.90, respectively, for an independent test data set. The artificial neural network method can be appropriately used to predict R{sub max} and GCV when regression results do not have high accuracy. (author)

International Nuclear Information System (INIS)

An artificial neural network can be used as an intelligent controller to control non-linear, dynamic system through learning. It can easily accommodate non-linearities and time dependencies. Most common multi-layer feed-forward neural networks have drawbacks of large number of neurons and hidden layers required to deal with complex problems and require large training time. To overcome these drawbacks, a generalized neuron based non-linear controller has been developed and illustrated as a power system stabilizer. Studies on a five-machine power system show that the proposed controller can significantly improve the dynamic performance and provide good damping of the power system over a wide operating range.

British Library Electronic Table of Contents (United Kingdom)

The objective of this study is to develop an artificial neural network (ANN) model to predict the thermal conductivity of ethylene glycol-water solutions based on experimentally measured variables. The thermal conductivity of solutions at different concentrations and various temperatures was measured using the cylindrical cell method that physical properties of the solution are being determined fills the annular space between two concentric cylinders. During the experiment, heat flows in the radial direction outwards through the test liquid filled in the annual gap to cooling water. In the steady state, conduction inside the cell was described by the Fourier equation in cylindrical coordinates, with boundary conditions corresponding to heat transfer between the solution and cooling water. ...

Energy Technology Data Exchange (ETDEWEB)

A novel non-invasive approach to the on-line identification of BWR two-phase flow regimes is investigated. The proposed approach receives neutron radiography images of coolant flow recordings as its input and performs feature extraction on each image via simple and directly computable statistical operators. The extracted features are subsequently used as inputs to an ensemble of self-organizing maps whose outputs demonstrate swift and accurate classification of each image into its corresponding flow regime. The novelty of the approach lies in the use of the self-organizing map which generates the different classes by itself, according to feature similarity of the corresponding images; this contrasts traditional artificial neural networks where the user has to define both the number of distinct classes as well as to supply separate training vectors for each class.

British Library Electronic Table of Contents (United Kingdom)

A marine propulsion system is a very complicated system composed of many mechanical components. As a result, the vibration signal of a gearbox in the system is strongly coupled with the vibration signatures of other components including a diesel engine and main shaft. It is therefore imperative to assess the coupling effect on diagnostic reliability in the process of gear fault diagnosis. For this reason, a fault detection and diagnosis method based on bispectrum analysis and artificial neural networks (ANNs) was proposed for the gearbox with consideration given to the impact of the other components in marine propulsion systems. To monitor the gear conditions, the bispectrum analysis was first employed to detect gear faults. The amplitude-frequency plots containing gear characteristic sign...

Energy Technology Data Exchange (ETDEWEB)

Density is useful in deducing the spatial structure of coals. In this paper, nitrogen has been used instead of the commonly employed helium, for the gas displacement pycnometer based density determination of a number of coals of Indian origin. The results show that the nitrogen-based densities are always higher than the helium-based ones. Also, empirical relationships between the helium-based and nitrogen-based coal densities have been developed by two modeling methods, namely, multi-variable regression and artificial neural networks. Although the two models have fared well, the neural network model exhibits a relatively better prediction accuracy and generalization performance than the regression model. This study thus demonstrates that nitrogen, which is cheaper and easily available, can be used gainfully as the probe gas for estimating the true density of coals. 23 refs., 1 fig., 3 tabs.

Energy Technology Data Exchange (ETDEWEB)

The aim of this study is to develop the methodology which enables to identify the mechanical properties of element such as stress intensity factor by using the AE parameters. Considering the multivariate and nonlinear properties of AE parameters such as ringdown count, rise time, energy, event duration and peak amplitude from fatigue cracks of machine element the principal component regression(PCR) and artificial neural network(ANN) models for the estimation of stress intensity factor were developed and validated. The AE parameters were found to be very significant to estimate the stress intensity factor. Since the statistical values including correlation coefficients, standard mr of calibration, standard error of prediction and bias were stable, the PCR and ANN models for stress intensity factor were very robust. The performance of ANN model for unknown data of stress intensity factor was better than that of PCR model

Energy Technology Data Exchange (ETDEWEB)

In the present scenario of market driven business, power supply has become more like a commodity. Reliable and quality power need to be ensured to meet customer requirements. In such a situation, it is extremely important that transmission line faults be identified accurately, reliably and in quick time. Advanced signal processing tools such as discrete wavelet transform (DWT) can be used very effectively for parameterisation and characterization of the fault signals. On the other hand, properly configured neural network (NN) can be utilized for classification of the faults based on the DWT signal. The present contribution uses electromagnetic transient program (EMTP) for modeling of a real transmission system and MATLAB for DWT and NN. Various types of faults have been simulated at different locations along the transmission line and an attempt has been made to correctly identify and locate the fault. (author)

Energy Technology Data Exchange (ETDEWEB)

A power system stabilizer based on GMV (Generalized Minimum Variance), one of the adaptive control techniques, is developed to enhance the dynamic performances of a power system using an Artificial Neural Network (ANN). The stabilizer consists of two parts. One part is Inverse Dynamics Neural Networks (IDNN), which is trained to identify the inverse dynamics of controlled plant and used as a one-step ahead controller, or inverse controller. The other part is Adaptive Reference Model (ARM), which prevents excessive controller output. The ARM produces the modified reference value by minimizing a cost function recursively on the assumption that the IDNN perfectly identifies the controlled plant. The IDNN is used in the minimization procedure to calculate the sensitivities. The proposed controller is simulated in a typical one-machine-infinite-bus power system to show its effectiveness to damp sustained low ...

CERN Document Server

In mobile ad hoc networks (MANET), nodes usually belong to different authorities and pursue different goals. In order to maximize their own performance, nodes in such networks tend to be selfish and are not willing to forward packets for benefit of others. Meanwhile, some nodes may behave maliciously and try to disrupt the network through wasting other nodes resources in a very large scale. In this article, we present a reputation-based attack resistant cooperation stimulation (RACS) system which ensures that damage caused by malicious nodes can be bounded and cooperation among the selfish nodes can be enforced. Mathematical analyses of the system as well as the simulation results have confirmed effectiveness of our proposed system. RACS is completely self-organizing and distributed. It does not require any tamper-proof hardware or central management policy.

CERN Document Server

In Internet Routing, the static shortest path (SP) problem has been addressed using well known intelligent optimization techniques like artificial neural networks, genetic algorithms (GAs) and particle swarm optimization. Advancement in wireless communication lead more and more mobile wireless networks, such as mobile networks [mobile ad hoc networks (MANETs)] and wireless sensor networks. Dynamic nature of the network is the main characteristic of MANET. Therefore, the SP routing problem in MANET turns into dynamic optimization problem (DOP). Here the nodes ae made aware of the environmental condition, thereby making it intelligent, which goes as the input for GA. The implementation then uses GAs with immigrants and memory schemes to solve the dynamic SP routing problem (DSPRP) in MANETS. In our paper, once the network ...

Science.gov (United States)

University research group with research areas: * Land based and submersible autonomous robots, (UUVs: AUVs and ROVs); * Controllers, electronics, sensor design and fusion, motion control; * Guidance and navigation of underwater vehicles; * AI, neural networks, fuzzy logic, subsumption control, behaviour based control; * Optical fibre and ultrasonic sensors for proximal object detection; * Robot arm control, visual servoing; * Imaging sonar applications; * Simulator development: UUV simulator; imaging sonar simulator; Aircraft/flight simulator.

Energy Technology Data Exchange (ETDEWEB)

A knowledge based system for pitting corrosion is presented. It can be used for material selection for specific pitting corrosion conditions or to check the suitability of a chosen material. The user can enter his own knowledge. The expert system is an integration of traditional expert system technology and neural networks. (orig.)

British Library Electronic Table of Contents (United Kingdom)

Energy consumption is a perennial issue in the design of wireless sensor networks (WSNs) which typically rely on portable sources like batteries for power. Recent advances in ambient energy harvesting technology have made it a potential and promising alternative source of energy for powering WSNs. By using energy harvesters with supercapacitors, WSNs are able to operate perpetually until hardware failure and in places where batteries are hard or impossible to replace. In this paper, we study the performance of different medium access control (MAC) schemes based on CSMA and polling techniques for WSNs which are solely powered by ambient energy harvesting using energy harvesters. We base the study on (i) network throughput (S), which is the rate of sensor data received by the sink, (ii) fair...

British Library Electronic Table of Contents (United Kingdom)

In vibration control field, magneto-rheological (MR) fluid dampers are semi-active control devices that have recently begun to receive more attention. This paper presents a nonlinear black-box model (BBM) and an inverse black-box model (IBBM) for the identification of a MR fluid damper and their application to design a novel force-sensorless control method for any damping system using that damper. The nonlinear model named 'black-box' is a simple direct modeling method which was designed based on fuzzy-neural technique. Characteristics of the damper in study are directly estimated through a fuzzy mapping system. In order to improve the model accuracy, neural network technique including back-propagation and gradient descent method were used to train the fuzzy parameters to minimize the mode...

British Library Electronic Table of Contents (United Kingdom)

This manuscript is a contribution on the modeling of H.263 traffic in multipoint videoconference sessions over IP Networks. Our study includes analysis and modeling assessment of extensive data gathered during realistic videoconference sessions between commercial H.263-compliant terminal clients (with different videoconference software packages installed). All terminal clients were communicating through a Multipoint Control Unit (software or hardware MCU) at `switched presence' mode and for comparative purposes the same typical videoconference content (a person speaking, with mild movement and occasional zoom/span) was used. The analysis of the H.263 data at the frame level suggests that the traffic from the different terminals to the MCU can be represented by a stationary stochastic proce...

Energy Technology Data Exchange (ETDEWEB)

The generation of a defined swivel momentum in car door hinges depends on numerous constructional and technical manufacturing parameters. If these parameters and their influence are to be investigated, then in addition to detailed experiments with variations in the parameters, methods are also required which enable the measuring data produced to be assessed in such a way that, in general, the non-linear relationships between initial and target size can be described sufficiently accurately. This paper explains the parameter reduction necessary in the experimental investigation, gives the results of the data assessment with conventional statistical methods and describes in particular the use of artificial neural networks (ANN) to construct so-called 'neuro hinge models' on the basis of the data resulting from the experiments. Parameter variations can be simulated with the hinge models and in this way optimal constructional and ...

Energy Technology Data Exchange (ETDEWEB)

With using artificial neural networks (ANNs), an analytical study related to the heated length effect on critical heat flux (CHF) has been carried out to make an improvement of the CHF prediction accuracy based on local condition correlations or table. It has been carried out to suggest a feasible criterion of the threshold length-to-diameter (L/D) value in which heated length could affect CHF. And within the criterion, a L/D correction factor has been developed through conventional regression. In order to validate the developed L/D correction factor, CHF experiments for various heated lengths have been carried out under low and intermediate pressure conditions. The developed threshold L/D correlation provides a new feasible criterion of L/D threshold value. The developed correction factor gives a reasonable accuracy for the original database, showing the error of -2.18% for average and 27.75% for RMS, and promising results for new experimental ...

Energy Technology Data Exchange (ETDEWEB)

Distance protection, differential protection and directional comparison schemes are presently used for protecting transmission lines. Directional comparison relays are set to respond to faults in the protection zone without intentional time delay and are, therefore, used where high-speed fault clearing is needed. Artificial Neural Networks (ANNs) can handle most situations which cannot be defined sufficiently for finding a deterministic solution. The design and testing of an ANN for directional comparison protection of transmission lines are presented in this paper. Training patterns were generated using voltage and current samples for faults at various locations along a transmission line. The faults were simulated using an electromagnetic transient program and a sample three-phase power system. The performance of the proposed discriminator was checked using data simulated for testing and the fault data recorded from 240 kV and 500 kV lines. ...

Science.gov (United States)

The removal of Reactive Black 5 dye in an aqueous solution by electrocoagulation (EC) as well as addition of flocculant was investigated. The effect of operational parameters, i.e. current density, treatment time, solution conductivity and polymer dosage, was investigated. Two models, namely the artificial neural network (ANN) and the response surface method (RSM), were used to model the effect of independent variables on percentage of dye removal. The findings of this work showed that current density, treatment time and dosage of polymer had the most significant effect on percentage of dye removal (p0.8). PMID:21411950

International Nuclear Information System (INIS)

Continuum events represent an eminent source of background in any e+e- experiment. As these have a higher branching ratio than BB-bar events (at BaBar this ratio is estimated to about 3.5) or ?+?- events, efficient continuum background suppression is essential in many analyses. Using Artificial Neural Networks and the Nearest Neighbor Method we developed several selectors which, based only on the global event shape variables, efficiently tag BB-bar events and ?+?- events against the continuum background. These selectors could then be combined with the channel specific information in various types of analyses. The study was done using a parametric Monte Carlo.

Energy Technology Data Exchange (ETDEWEB)

The effects of proximate and ultimate analysis, maceral content, and coal rank (R{sub max}) for a wide range of Kentucky coal samples from calorific value of 4320 to 14960 (BTU/lb) (10.05 to 34.80 MJ/kg) on Hardgrove Grindability Index (HGI) have been investigated by multivariable regression and artificial neural network methods (ANN). The stepwise least square mathematical method shows that the relationship between (a) Moisture, ash, volatile matter, and total sulfur; (b) ln (total sulfur), hydrogen, ash, ln ((oxygen + nitrogen)/carbon) and moisture; (c) ln (exinite), semifusinite, micrinite, macrinite, resinite, and R{sub max} input sets with HGI in linear condition can achieve the correlation coefficients (R{sup 2}) of 0.77, 0.75, and 0.81, respectively. The ANN, which adequately recognized the characteristics of the coal samples, can predict HGI with correlation coefficients of 0.89, 0.89 and 0.95 respectively in testing process. It was ...

KoreaScience (Korea)

Full Text Available

Energy Technology Data Exchange (ETDEWEB)

Eaton, in partnership with Oak Ridge National Laboratory and the Electric Power Research Institute (EPRI) has completed a project that applies a combination of wireless sensor network (WSN) technology, anticipatory theory, and a near-term value proposition based on diagnostics and process uptime to ensure the security and reliability of critical electrical power infrastructure. Representatives of several Eaton business units have been engaged to ensure a viable commercialization plan. Tennessee Valley Authority (TVA), American Electric Power (AEP), PEPCO, and Commonwealth Edison were recruited as partners to confirm and refine the requirements definition from the perspective of the utilities that actually operate the facilities to be protected. Those utilities have cooperated with on-site field tests as the project proceeds. Accomplishments of this project included: (1) the design, modeling, and simulation of the anticipatory wireless sensor ...

CERN Document Server

Because of the stochastic nature of traffic requirement matrix, it is very difficult to get the optimal traffic distribution to minimize the delay even with adaptive routing protocol in a fixed connection network where capacity already defined for each link. Hence there is a requirement to define such a method, which could generate the optimal solution very quickly and efficiently. This paper presenting a new concept to provide the adaptive optimal traffic distribution for dynamic condition of traffic matrix using nature based intelligence methods. With the defined load and fixed capacity of links, average delay for packet has minimized with various variations of evolutionary programming and particle swarm optimization. Comparative study has given over their performance in terms of converging speed. Universal approximation capability, the key feature of feed forward neural network has applied to predict the flow ...

Science.gov (United States)

Autism is a pervasive developmental condition, characterized by impairments in non-verbal communication, social relationships and stereotypical patterns of behavior. A large body of evidence suggests that several aspects of face processing are impaired in autism, including anomalies in gaze processing, memory for facial identity and recognition of facial expressions of emotion. In search of neural markers of anomalous face processing in autism, much interest has focused on a network of brain regions that are implicated in social cognition and face processing. In this review, we will focus on three such regions, namely the STS for its role in processing gaze and facial movements, the FFA in face detection and identification and the amygdala in processing facial expressions of emotion. Much evidence suggests that a better understanding of the normal development of these specialized regions is essential for discovering the ...

Science.gov (United States)

... A control design methodology enabling the adaptive neural augmentation. ... As an example, the problem of designing a neural augmentation system. ...

International Nuclear Information System (INIS)

This system provides data logging facility for axial profile and dynamic profile experiments during low power physics experiments. The data from Cobalt Self Powered Neutron Detectors (SPNDs) are logged via hardware consisting of PC plug-in cards and data of vanadium SPNDs are logged from the Flux Mapping System (FMS) network (multicast data). The data along with programmable details of the experiment is transferred to an Access Database. The system provides online displays and extensive reports from the Access Database as per the requirement from Reactor Physicists. This paper briefly describes the evolvement of requirements (from the experience of operation of TAPS 4 to TAPS 3), software architecture and design. (author)

Energy Technology Data Exchange (ETDEWEB)

The present invention is a fully connected feed forward network that includes at least one hidden layer 16. The hidden layer 16 includes nodes 20 in which the output of the node is fed back to that node as an input with a unit delay produced by a delay device 24 occurring in the feedback path 22 (local feedback). Each node within each layer also receives a delayed output (crosstalk) produced by a delay unit 36 from all the other nodes within the same layer 16. The node performs a transfer function operation based on the inputs from the previous layer and the delayed outputs. The network can be implemented as analog or digital or within a general purpose processor. Two teaching methods can be used: (1) back propagation of weight calculation that includes the local feedback and the crosstalk or (2) more preferably a feed forward gradient decent which immediately follows the output computations and which also includes the local feedback and the ...

British Library Electronic Table of Contents (United Kingdom)

Serotonin is an important signaling molecule involved in the control of feeding in flies and other animals. In this study, a potential neurohemal release site for serotonin and the effects of exogenous serotonin on protein feeding were examined in the black blow fly, Phormia regina. A dense network of varicose neural processes exhibiting serotonin-like immunoreactivity was identified on the dorsal region of the thoracico-abdominal ganglion in P. regina. This dorsal region of the central nervous system is a likely site for the release of serotonin into the hemolymph. Circulating serotonin may have multiple systemic effects on fly physiology, including modulating or regulating feeding related processes and diuresis. Injections of exogenous serotonin reduced protein meal size in female flies ...

British Library Electronic Table of Contents (United Kingdom)

Electric supply industry is facing deregulation all over the world. Under deregulated power supply scenario, power transmission congestion has become more intensified and recurrent, as compared to conventional regulated power system. Congestion may lead to violation of voltage or transmission capacity limits, thus threatens the power system security and reliability. Also the growing congestion may lead to unanticipated divergent electricity pricing. Owing to these facts congestion management has become a crucial issue in the deregulated power system scenario. Fast and precise prediction of nodal congestion prices in real time deregulated/spot power market may enable market participants and system operators to keep pace with the congestion by taking preventive measures like transaction resc...

British Library Electronic Table of Contents (United Kingdom)

In the emerging restructured power system, the congestion management (CM) has become extremely important in order to ensure the security and reliability of the system. In addition to this, lack of CM can impose a hindrance in electricity trading. This paper presents a novel, growing radial basis function neural network (GRBFNN)-based approach for CM. For achieving CM, Nodal congestion price (NCP) forecasting is performed in real time competitive power market. NCP forecasting is an effective way of price-based preventive CM as it directly indicates the presence as well as the severity of the congestion in the system. In present paper, GRBFNN has been developed for NCP forecasting dividing the whole power system into various congestion zones. An unsupervised learning vector quantization (VQ)...

International Nuclear Information System (INIS)

By using the continuation theorem of coincidence degree theory and constructing suitable Lyapunov functions, we study the existence and stability of periodic solution for shunting inhibitory cellular neural networks (SICNNs) with delays x-bar _i_j(t)=-a_i_j(t)x_i_j(t)--bar B"k"l-bar Nr(i,j)B_i_j"k"l(t)f_i_j(x_k_l(t))x_i_j(t)--bar C"k"l-bar Nr(i,j)C_i_j"k"l(t)g_i_j(x_k_l(t-#tau#_k_l))x_i_j(t)+L_i_j(t).

DEFF Research Database (Denmark)

A seasonal forecasting technique to produce probabilistic and deterministic streamflow forecasts for 23 basins in Norway and northern Sweden is developed in this work. Large scale circulation and moisture fields, forecasted by the ECHAM4.5 model 4 months in advance, are used to forecast spring flows. The technique includes model output statistics (MOS) based on a non-linear Neural Network (NN) approach. Results show that streamflow forecasts from Global Circulation Model (GCM) predictions, for the Scandinavia region are viable and highest skill values were found for basins located in south-western Norway. The physical interpretation of the forecasting skill is that stations close to the Norwegian coast are directly exposed to prevailing winds from the Atlantic ocean, which constitute the principal source of predictive information from the atmosphere on the seasonal timescale.

Energy Technology Data Exchange (ETDEWEB)

An artificial neural network (ANN), trained as an inverse of the controlled plant, to function as a power system stabilizer (PSS) is presented in this paper. In order to make the proposed ANN PSS work properly, it was trained over the full working range of the generating unit with a large variety of disturbances. Data used to train the ANN PSS consists of the control input and the synchronous machine response with an adaptive PSS (APSS) controlling the generator. During training, the ANN was required to memorize the reverse input/output mapping of the synchronous machine. After the training, the output of the synchronous machine was applied as the input of the ANN PSS and the output of the ANN PSS was used as the control signal. Simulation results show that the proposed ANN PSS can provide good damping of the power system over a wide operating range and significantly improve the system performance.

Science.gov (United States)

Readout integrated circuits (ROICs) for focal plane arrays (FPAs) have become increasingly complex to meet the needs of modern infrared systems. BAE Systems has pioneered a number of advanced signal processing architectures for FPA ROICs. Demonstrated signal processing capabilities of BAE Systems FPAs include analog-to-digital conversion, offset subtraction, individual pixel automatic gain compensation, transient noise suppression, on-FPA defect deselection, reconfigurable pixels, spatial neural network processing and subframe noise averaging. BAE Systems FPA advanced signal processing is not just for demonstrations, but is used in many of their deliverable FPAs, improving real system performance.

Science.gov (United States)

Not Available

Science.gov (United States)

Not Available

Energy Technology Data Exchange (ETDEWEB)

Previous work shows the presence of scale invariance and long-range correlations in ongoing and spontaneous activity of large scale brain responses (i.e. EEG), and such scaling behavior can also be modulated by simple sensory stimulus. However, little is known whether such alteration but not destruction in scaling properties also occurs during complex cognitive processing and if neuroplasticity plays any role in mediating such changes. In this study, we addressed these issues by investigating scaling properties of multivariate EEG signals obtained from two broad groups - artists and non-artists - while they performed complex tasks of perception and mental imagery of visual art objects. We found that brain regions showing increased correlation properties from rest were similar for both tasks, suggesting that brain networks responsible for visual perception are reactivated for mental imagery. Further, we observed that the two groups could be differentiated by scaling ...

International Nuclear Information System (INIS)

Growing of PV for electricity generation is one of the highest in the field of the renewable energies and this tendency is expected to continue in the next years. Due to the various seasonal, hourly and daily changes in climate, it is relatively difficult to find a suitable analytic model for predicting the performance of a grid-connected photovoltaic (GCPV) plant. In this paper, an artificial neural network is used for modelling and predicting the power produced by a 20 kWp GCPV plant installed on the roof top of the municipality of Trieste (latitude 45 deg. 40'N, longitude 13 deg. 46'E), Italy. An experimental database of climate (irradiance and air temperature) and electrical (power delivered to the grid) data from January 29th to May 25th 2009 has been used. Two ANN models have been developed and implemented on experimental climate and electrical data. The first one is a multivariate model based on the solar irradiance and the air ...

UK PubMed Central (United Kingdom)

The temporal synchrony of auditory and visual signals is known to affect the perception of an external event, yet it is unclear what neural mechanisms underlie the influence of temporal synchrony...Full Text Available

KoreaScience (Korea)

Full Text Available

CERN Document Server

Local access network technologies

KoreaScience (Korea)

Full Text Available

KoreaScience (Korea)

Full Text Available

Science.gov (United States)

PMID:17758994

Science.gov (United States)

PMID:15029781

Energy Technology Data Exchange (ETDEWEB)

Development Service Order {number_sign}90025 requested recommendations for computer hardware, operating systems, and software development utilities based on current and future SIMON software requirements. Since SIMON`s main objective is to be dispatched on missions by an operator with little computer experience, ``user friendly`` hardware and software interfaces are required. Other design criteria include: a fluid software development environment, and hardware and operating systems with minimal maintenance requirements. Also, the hardware should be expandable; extra processor boards should be easily integrated into the existing system. And finally, the use of well established standards for hardware and software should be implemented where practical.

International Nuclear Information System (INIS)

Research highlights: #-># The building occupancy affecting the cooling load prediction is studied. #-># PENN model is adopted in this study for predicting the building cooling load. #-># Statistical approach is adopted to result a less prejudice prediction performance. #-># Results show that occupancy data can significantly improve the prediction. -- Abstract: Building cooling load prediction is one of the key factors in the success of energy-saving measures. Many computational models available in the industry today have been developed from either forward or inverse modeling approaches. However, most of these models require extensive computer resources and involve lengthy computation. This paper discusses the use of data-driven intelligent approaches, a probabilistic entropy-based neural (PENN) model to predict the cooling load of a building. Although it is common knowledge that the presence and activity of building occupants have a significant impact ...

DEFF Research Database (Denmark)

Udgivelsesdato: 2007/7

Energy Technology Data Exchange (ETDEWEB)

A method of kinetic analysis applicable to non-isothermal oxidation processes of ceramic nanocomposites is presented using Ti-Si-C-N powder as the substrate. The nanoparticle size and phase composition were determined using high-resolution transmission electron microscopy and X-ray diffraction (XRD). Thermogravimetric measurements were carried out for powder samples in dry air in the temperature range 298-1770 K. The following heating rates were applied: 3, 5, 10, 20 K min{sup -1}. Mass spectrometry was used to analyze gaseous oxidation products and solid products were identified by the XRD technique. The Coats-Redfern equation was applied for the kinetic analysis. For each stage of the oxidation kinetic models, the best accuracy was achieved using a series of criteria, and then the A and E parameters of the Arrhenius equations were estimated. Both linear regression and artificial neural networks were applied in testing kinetic models.

International Nuclear Information System (INIS)

Aiming at the non-stationary characteristics of differential pressure fluctuation signals of gas-liquid two-phase flow, and the slow convergence of learning and liability of dropping into local minima for BP neural networks, flow regime identification method based on Singular Value Decomposition (SVD) and Least Square Support Vector Machine (LS-SVM) is presented. First of all, the Empirical Mode Decomposition (EMD) method is used to decompose the differential pressure fluctuation signals of gas-liquid two-phase flow into a number of stationary Intrinsic Mode Functions (IMFs) components from which the initial feature vector matrix is formed. By applying the singular vale decomposition technique to the initial feature vector matrixes, the singular values are obtained. Finally, the singular values serve as the flow regime characteristic vector to be LS-SVM classifier and flow regimes are identified by the output of the classifier. The ...

Science.gov (United States)

Cancer is a severe threat to human health. Early detection is considered the best way to increase the chance for survival. While the traditional cancer detection method, biopsy, is invasive, noninvasive optical diagnostic techniques are revolutionizing the way that cancer is diagnosed. Reflectance spectroscopy is one of these optical spectroscopy techniques showing promise as a diagnostic tool for pre-cancer detection. When a neoplasia occurs in tissue, morphologic and biochemical changes happen in the tissue, which in turn results in the change of optical properties and reflectance spectroscopy. Therefore, a pre-cancer can be detected by extracting optical properties from reflectance spectroscopy. This dissertation described the construction of a fiberoptic based reflectance system and the development of a series of modeling studies. This research is aimed at establishing an improved understanding of the optical properties of mucosal tissues by analyzing reflectance signals at ...

Energy Technology Data Exchange (ETDEWEB)

Installation of the major hardware subsystems for MFTF is nearing completion. These subsystems include the Fusion Chamber System, the eighty KV Neutral Beam System, the Superconducting Magnet System, and the Personnel Safety System. The Local Controls group has undertaken a uniform aproach to implementing the control systems for all of these hardware subsystems. This approach has two major aspects: (1) to provide a stand-alone computer control system with a remote, portable terminal so that computer control can be provided at the site of the hardware for initial testing, (2) to provide hardware simulators so that the complicated MFTF computer control system can be tested independent of the hardware. The software and hardware tools which were developed to carry out this plan will be described. Our experiences with bringing up subsystems containing up to 900 ...

Science.gov (United States)

An intemted approach to building a networking infrastructure is an absolute necessiry for meeting the multidisciplinary science networking requirements of ...

Science.gov (United States)

Not Available

Science.gov (United States)

Not Available

UK PubMed Central (United Kingdom)

The economics of medical computer networks are presented in context with the patient care and administrative goals of medical networks. Design alternatives and network topologies are discussed with...Full Text Available

UK PubMed Central (United Kingdom)

Failures in cortical control of fronto-striatal neural circuits may underpin impulsive and compulsive acts. In this narrative review, we explore these behaviors from the perspective of neural processes...Full Text Available

UK PubMed Central (United Kingdom)

Congenital deformities involving the coverings of the nervous system are called neural tube defects (NTDs). NTD can be classified as neurulation defects, which occur by stage 12, and postneurulation...Full Text Available

UK PubMed Central (United Kingdom)

We present an algorithm to identify individual neural spikes observed on high-density multi-electrode arrays (MEAs). Our method can distinguish large numbers of distinct neural units, even when spikes...Full Text Available

UK PubMed Central (United Kingdom)

The tendency for some individuals to partake in high-risk behaviors (eg, substance abuse, gambling, risky sexual activities) is a matter of great public health concern, yet the characteristics and neural...Full Text Available

Energy Technology Data Exchange (ETDEWEB)

Development Service Order {number sign}90025 requested recommendations for computer hardware, operating systems, and software development utilities based on current and future SIMON software requirements. Since SIMON's main objective is to be dispatched on missions by an operator with little computer experience, user friendly'' hardware and software interfaces are required. Other design criteria include: a fluid software development environment, and hardware and operating systems with minimal maintenance requirements. Also, the hardware should be expandable; extra processor boards should be easily integrated into the existing system. And finally, the use of well established standards for hardware and software should be implemented where practical.

CERN Document Server

At present, the mostly used and developed mechanism is hardware virtualization which provides a common platform to run multiple operating systems and applications in independent partitions. More precisely, it is all about resource virtualization as the term hardware virtualization is emphasized. In this paper, the aim is to find out the advantages and limitations of current virtualization techniques, analyze their cost and performance and also depict which forthcoming hardware virtualization techniques will able to provide efficient solutions for multiprocessor operating systems. This is done by making a methodical literature survey and statistical analysis of the benchmark reports provided by SPEC (Standard Performance Evaluation Corporation) and TPC (Transaction processing Performance Council). Finally, this paper presents the current aspects of hardware virtualization which will help the IT managers ...

Science.gov (United States)

OF VOCALIZED SPEECH THROUGH. ANALYSIS OF NEURAL SIGNALS. " SYNTHETIC TELEPATHY- WIRELESS. TRANSMISSION OF DECODED. THOUGHTS. " IMPLANTABLE MEMORY-ELIMINATES ...

Science.gov (United States)

... strategies. Computer and network security deals with cryptography, authentication, and attacks on software. Information ...

Science.gov (United States)

Not Available

International Nuclear Information System (INIS)

This article is about the network security defence method and technique at IHEP. Including: the experience, research result and application in network outlet security, server security, local network security, network security monitoring and collecting evidence, anti-virus etc

Science.gov (United States)

The effects of high-intensity pulsed electromagnetic stimulation (HIPEMS) on proliferation and differentiation of neonatal rat neural stem cells in vitro were investigated. Neural stem cells derived from neonatal rats were exposed to 0.1 Hz, 0.5-10 Tesla (T) [8 groups of B-I, respectively], 5 stimuli of HIPEMF. The sham exposure controls were correspondingly established. Inverted phase contrast microscope was used to observe the cultured cells, MTT assay to detect the viability of the cells as expressed by absorbance (A) value, and flow cytometry to measure differentiation of neural stem cells. The results showed that A values of neural stem cells in both 3.0 T and 4.0 T groups were significantly higher than the other groups 24 to 168 h post HPEMS, indicating a strong promotion of the growth of neural stem cells (PHPEMS groups was the same as that in control group (P>0.05). It ...

Energy Technology Data Exchange (ETDEWEB)

Two geochemical surveys were conducted in 1992 and 2000 respectively in the Yimeng Uplift of the Ordos Basin, China. The earlier survey grid had 1 x 5km spacing and the later survey grid had 0.5 x 0.5km spacing. The acid-extractable hydrocarbons of both surveys show similar geochemical trends. However, the anomalies obtained with traditional statistical methods do not correlate with existing oil/gas fields. This study reveals two problems in the data and their processing. The first one is interference caused by the variation of soil composition. We applied a wavelet-analysis-based method to eliminate this interference in the data of the later survey. The second is that micro-seepage anomalies did not identify existing oil/gas fields and seepage anomalies related with faults had not been previously recognized. We modified the logic multiplication cluster analysis and applied a multi-fractal model and a back propagation artificial neural network ...

Energy Technology Data Exchange (ETDEWEB)

Accurate lung tumor tracking in real time is a keystone to image-guided radiotherapy of lung cancers. Existing lung tumor tracking approaches can be roughly grouped into three categories: (1) deriving tumor position from external surrogates; (2) tracking implanted fiducial markers fluoroscopically or electromagnetically; (3) fluoroscopically tracking lung tumor without implanted fiducial markers. The first approach suffers from insufficient accuracy, while the second may not be widely accepted due to the risk of pneumothorax. Previous studies in fluoroscopic markerless tracking are mainly based on template matching methods, which may fail when the tumor boundary is unclear in fluoroscopic images. In this paper we propose a novel markerless tumor tracking algorithm, which employs the correlation between the tumor position and surrogate anatomic features in the image. The positions of the surrogate features are not directly tracked; instead, we use principal component analysis of regions ...

Energy Technology Data Exchange (ETDEWEB)

This paper describes a new approach to development of software for highly integrated software-hardware systems such as used for data acquisition and control. This approach, called the Object Oriented Software Bus (OSB), is a way to develop software according to a common specification similar to the way interface hardware has been developed since the advent of bus structures for minicomputers and microcomputers. Key concept of the OSB is extension of the common use of objects to support user interface and data analysis functions to the development of software objects that directly correspond to real- world hardware interfaces and modules.

DEFF Research Database (Denmark)

This paper presents the concept of a biological inspired reconfigurable hardware cell architecture which supports self-organisation and self-healing. Two fundamental processes in biology, namely fertilization-to-birth and cell self-healing have inspired the development of this cell architecture. In biology as well as in our hardware cell architecture it is the DNA which enables these processes. We propose a platform based on the electronic DNA (eDNA) and show through simulation, its capabilities as a new generation of robust reconfigurable hardware platforms. We have created a Java based simulator to simulate our self-organisation and self-healing algorithms and the results obtained from this looks promising.

Science.gov (United States)

(e.g. enclosed cooktop with built in emissions capture and treatment) . " Test hardware in laboratory, reduced pressure and analog habitat. " Objective 1. ...

Science.gov (United States)

... of the loop filter based on ... algorithms, including delta-sigma approaches, routinely uses double-precision floating point number representations for ...

Science.gov (United States)

... was released and three prototype contracts were awarded by TACOM on 18 January 1989, to General Motors Corporation, PACCAR, and Osh Kosh ...

Science.gov (United States)

... UNCLASSIFIED The 60 Minute Network Security Guide ... 15. SUBJECT TERMS IATAC Collection; information security; network security 16. ...

UK PubMed Central (United Kingdom)

This article is a story of networking of palliative care at the corporate level. This gives an insight that if you have will and dedication then you can imagine and make it true that networking can...Full Text Available

Science.gov (United States)

... TITLE (Indlude Security Classifkcation) Human Factors in Network Security 12. ... FIELD GROUP SUBGROUP Human Factors, Network, Security 19. ...

British Library Electronic Table of Contents (United Kingdom)

Transforming growth factor beta (TGF-@b) has a crucial role in the differentiation of ectodermal cells to neural or epidermal precursors. TGF-@b and bone morphogenetic protein molecules (BMPs) are involved in many developmental processes, including cell proliferation and differentiation, apoptosis, mitotic arrest and intercellular interactions during morphogenesis. Additionally, the failure of central thymic tolerance mechanisms, leading to T cells with a skewed autoreactive response, is being described as a contributor in inflammatory processes in autoimmune diseases such as multiple sclerosis. Since TGF-@b and BMP proteins are crucial for the development of the neural system and the thymus, as well as for the differentiation of T cells, it is essential to further investigate their role i...

International Science & Technology Center (ISTC)

Morphological, Electrophysiological and Behavioral Investigations of the Nervous Tissue Developed from the Embryonic Matrix Zone Cells of the Dorsolateral Walls of Lateral Ventricles, Implanted into the Lesioned Regions of the Adult Rat's Brain

UK PubMed Central (United Kingdom)

The potential of radiolabelled phenylpiperazines as agents for the detection and therapy of tumours of neural crest origin was evaluated by in vitro pharmacological studies with human neuroblastoma...Full Text Available

Science.gov (United States)

No abstract prepared.

Energy Technology Data Exchange (ETDEWEB)

Short communication.

UK PubMed Central (United Kingdom)

We study the statistical properties of a variety of diverse real-world networks. We present evidence of the occurrence of three classes of small-world networks: (a) scale-free networks,...Full Text Available

Energy Technology Data Exchange (ETDEWEB)

There is a rapidly growing need to evaluate sensor network functionality and performance in the context of the larger environment of infrastructure and applications in which the sensor network is organically embedded. This need, which is motivated by complex applications related to national security operations, leads to a paradigm fundamentally different from that of traditional data networks. In the sensor networks of interest to us, the network dynamics depend strongly on sensor activity, which in turn is triggered by events in the environment. Because the behavior of sensor networks is sensitive to these driving phenomena, the integrity of the sensed observations, measurements and resource usage by the network can widely vary. It is therefore imperative to accurately capture the environmental phenomena, and drive the simulation of the ...

Energy Technology Data Exchange (ETDEWEB)

The basic function of a Power System Stabilizer (PSS) is to add damping to the generator rotor oscillations by controlling its excitation using auxiliary stabilizing signals. To provide damping, the stabilizer must produce a component of electrical torque in phase with the rotor speed deviations. This paper introduces the hardware specifications and various functions of microprocessor (TMS320C32)-based digital PSS to provide the damping torque. (author). 3 refs., 6 figs.

Science.gov (United States)

... MAGMA © : A LIQUID SOFTWARE APPROACH TO FAULT TOLERANCE, COMPUTER NETWORK SECURITY, AND SURVIVABLE NETWORKING ...

Science.gov (United States)

Computer And Network Security: Information For Everyone: This presentation was originally prepared as the 14th talk in a series known as "The Programmer's ...

Science.gov (United States)

... Accession Number : ADA326934. Title : Analyzing and Improving Stochastic Network Security: A Multicriteria Prescriptive Risk Analysis Model. ...

Energy Technology Data Exchange (ETDEWEB)

What kind of hardware and software should be used to interface GPIB devices with the existing computer system. One idea was to use a commercially available Multibus card, BLC 8488 from National Semiconductor, whose on-board Z80 would manage the GPIB read/write functions and handshakes. With this card, one could make a hardware system which would consist of (1) CAMAC 080, (2) Multibus crate, (3) M. Shea's M68000, (4) M080, (5) BLC 8488 and (6) memory board. And the software considered for such a hardware package was GAS, which had been an established software package for communication between the ACNET computer system and smart CAMAC modules. However, a second idea was to put everything on a two-wide CAMAC module. The author pursued the second idea and came up with a two-wide CAMAC module called C488. The author describes the hardware - block diagrams, circuit blocks, front panel and ...

Energy Technology Data Exchange (ETDEWEB)

Consolidation of spent fuel is under active consideration as the US Department of Energy plans to dispose of spent fuel. During consolidation, the fuel pins are removed from an intact fuel assembly and repackaged into a more compact configuration. After repackaging, approximately 30 kg of residual spent fuel assembly hardware per assembly remains that is also radioactive and requires disposal. Understanding the nature of this secondary waste stream is critical to designing a system that will properly handle, package, store, and dispose of the waste. This report presents a methodology for estimating the radionuclide inventory in irradiated spent fuel hardware. Ratios are developed that allow the use of ORIGEN2 computer code calculations to be applied to regions that are outside the fueled region. The ratios are based on the analysis of samples of irradiated hardware from spent fuel assemblies. The results of this research ...

Energy Technology Data Exchange (ETDEWEB)

Conversion of the microprocessors and software for the Mold Heating and Cooling (MHAC) pump package control systems was initiated to allow required system enhancements and provide data communications capabilities with the Plastics Information and Control System (PICS). The existing microprocessor-based control systems for the pump packages use an Intel 8088-based microprocessor board with a maximum of 64 Kbytes of program memory. The requirements for the system conversion were developed, and hardware has been selected to allow maximum reuse of existing hardware and software while providing the required additional capabilities and capacity. The new hardware will incorporate an Intel 80286-based microprocessor board with an 80287 math coprocessor, the system includes additional memory, I/O, and RS232 communication ports.

CERN Document Server

Connectivity and capacity are two fundamental properties of wireless multi-hop networks. The scalability of these properties has been a primary concern for which asymptotic analysis is a useful tool. Three related but logically distinct network models are often considered in the asymptotic analysis, i.e. the dense network model, the extended network model and the infinite network model, which consider respectively a network deployed in a finite area with a sufficiently large node density, a network deployed in a sufficiently large area with a fixed node density, and a network deployed in $\\Re^{2}$ with a sufficiently large node density. The infinite network model originated from continuum percolation theory and asymptotic results obtained from the infinite network model have ...

British Library Electronic Table of Contents (United Kingdom)

Summary: Analysis of biological networks requires assessing the statistical significance of network-based predictions by using a realistic null model. However, the existing network null model, switch randomization, is unsuitable for metabolic networks, as it does not include physical constraints and generates unrealistic reactions. We present JMassBalance, a tool for mass-balanced randomization and analysis of metabolic networks. The tool allows efficient generation of large sets of randomized networks under the physical constraint of mass balance. In addition, various structural properties of the original and randomized networks can be calculated, facilitating the identification of the salient properties of metabolic networks with a biologically meaningful null model. Availability and Imp...

Science.gov (United States)

These are some interesting sites that will help you to understand networking and how it can benefit you. These sites contain sound so you may want to wear headphones if you are in a classroom. Learn how the internet began and the basics of the www. Learn why a network is useful. Jans network contains the important concepts of networking, Work through section 7 to learn about different types of connections, transmissions, media, and configurations. Then take the quiz at the end to see how ...

Energy Technology Data Exchange (ETDEWEB)

With the advent of powerful, widely-available mathematical software, combined with ever-faster computer hardware, we are approaching a day when both the discovery and proof of mathematical facts can be done in a computer-assisted manner. his article presents several specific examples of this new paradigm in action.

British Library Electronic Table of Contents (United Kingdom)

The precedence effect (PE) is thought to be beneficial for proper localization and perception of sounds. The majority of recent physiological studies focus on the neural discharges correlated with PE in the inferior colliculus (IC). Pentobarbital anesthesia is widely used in physiological studies. However, little is known of the effect of pentobarbital on the discharge of neurons in PE. Neuronal responses in the IC from 23 male SD rats were recorded by standard extracellular recording techniques following presentation of 4ms white noise bursts, presented from either or both of two loud speakers, at different interstimulus delays (ISDs). The neural responses were recorded for off-line analysis before or after intraperitoneal administration of pentobarbital at a loading or maintenance dose. ...

International Nuclear Information System (INIS)

The method of syndrome coding for data compression read out from multiwire proportional chambers that has been previously proposed is generalized in case of its application to registration of the coordinates of events detected. The questions of execution of arithmetic and algebraic operations on the Galois field elements and their hardware implementation are considered. The method of computation is presented of a specialized processor for parallel computing the coordinates of three sparks. The estimate of its speed is equal to 185 ns. Data compression, data selection and coordinate calculations are performed without use of memory elements and timing pulses.

Science.gov (United States)

In this work feed hardware for fed-batch cultivation is presented (broth recycle feed injection system or BRFIS). BRFIS proved superior to conventional submerged or dripped feed systems in reducing dissolved oxygen (DO) oscillations during Escherichia coli fed-batch cultivation (5 min coefficient of variation of 0.7% for BRFIS as compared to 26% or greater for conventional feeding hardware in a 2 L test reactor). Hence, BRFIS is useful for fed-batch cultivation systems where the DO signal is used in measurement or control. PMID:12675613

Energy Technology Data Exchange (ETDEWEB)

This paper describes and analyzes a dithering technique for accurately specifying small values of opacity ({alpha}) that would normally not be possible because of the limited number of bits available in the alpha channel of graphics hardware. This dithering technique addresses problems related to compositing numerous low-opacity semitransparent polygons to create volumetric effects with graphics hardware. The paper also describes the causes and a possible solution to artifacts that arise from parallel or distributed volume rendering using bricking on multiple GPU's.

UK PubMed Central (United Kingdom)

Synthetic gene networks can be used to control gene expression and cellular phenotypes in a variety of applications. In many instances, however, such networks can behave unreliably due to gene expression...Full Text Available

Science.gov (United States)

Materials World Network: Cooperative Activity in Materials Research between US Investigators and ... Program Title: Materials World Network: Cooperative Activity in Materials Research between US ...

UK PubMed Central (United Kingdom)

A high-speed fiber-based network for the transmission and display of digitized full-motion cardiac images has been developed. Based on Asynchronous Transfer Mode (ATM), the network is scaleable, meaning...Full Text Available

Energy Technology Data Exchange (ETDEWEB)

This document is the Final Report for the project. Improvements in SISCOM II Technology. It consists of a brief description of the activities carried out during the project, and several Annexes that explain in a deeper way each result. SISCOM II is the main telemetry system currently in use in the Spanish underground coal mining, but it was developed ten years ago and needed a technological update, which was the objective of this project. The aims of the project were: - To develop Hardware and Software for the Outstations currently used (maintenance developments) - To design new hardware and software, easier to use in the current and new applications of SISCOM II Both objectives were met, although not in the way originally intended. The main results were: In the field of old Outstations update: - A new set of boards for the old Outstations was developed - Outstations`s firmware was updated for the new hardware In the field ...

CERN Document Server

The capability of nodes to broadcast their message to the entire wireless network when nodes employ cooperation is considered. We employ an asymptotic analysis using an extended random network setting and show that the broadcast performance strongly depends on the path loss exponent of the medium. In particular, as the size of the random network grows, the probability of broadcast in a one-dimensional network goes to zero for path loss exponents larger than one, and goes to a nonzero value for path loss exponents less than one. In two-dimensional networks, the same behavior is observed for path loss exponents above and below two, respectively.

Science.gov (United States)

... VALIDATING NETWORK SECURITY POLICIES VIA STATIC ANALYSIS OF ROUTER ACL CONFIGURATION by Eric Gregory Wen Wei Wong ...

CERN Document Server

Understanding the dependence and interplay between architecture and function in biological networks has great relevance to disease progression, biological fabrication and biological systems in general. Recent research in complex systems and networks, presents methods to properly mine the architectural interdependence in networks. Guided by such work, we propose methods to associate organism characteristics with network topology by analyzing a large number of architectural patterns. We adopt an automated approach using 11 topological metrics from complex networks to characterize a collection of various kinds of biological networks. Principal component analysis and clustering allow us to extract the indispensable, independent and informative metrics. Using hierarchical linear modeling, we observe that organism characteristics associate with these metrics, ...

Science.gov (United States)

... LIFO queue descipline outperforms FIFO in ... We consider here the stochastic network system ... All-terminal Undirected Rational Network Reliability ...

Science.gov (United States)

Recently SSBRP network security planning was formalized with the production of several .... The SSBRP Network Security. Policy was written ...

Science.gov (United States)

voluntarily provided by you. Network Traffic Logs In the course of ensuring network security and consistent service for all users, the University employs software programs to...

International Nuclear Information System (INIS)

The Superconducting super Collider Laboratory is a complex of particle accelerators being built in Ellis County, Texas. It will have a dedicated global communications network that will deliver control messages and provide for general data acquisition. This network will connect thousands of computer nodes over a very large geographic area. In order to meet the demanding availability requirements being levied on the system, it will need comprehensive network management. A large number of the computer nodes are embedded systems that traditionally do not support network management services. This presents unique challenges to standard network management practices. The Simple Network Management Protocol, SNMP, is widely accepted by industry as a tool to manage network devices. In this paper the authors examine the performance characteristics and ...

Science.gov (United States)

... execute the samples The NSA's 60 Minute Network Security Guide [NSA02], part of the Supporting Document guides section ...

Science.gov (United States)

This paper proposes an approach that mitigates the problem of verification of network security system properties over concurrent processes.

Science.gov (United States)

of a stochastic network can be a. PERT-type network. After the terminal countdown, ...... pictorial representation of a single channel queueing system ...

CERN Document Server

Network tomography aims at inferring internal network characteristics based on measurements at the edge of the network. In loss tomography, in particular, the characteristic of interest is the loss rate of individual links. There is a significant body of work dedicated to this problem using multicast and/or unicast end-to-end probes. Independently, recent advances in network coding have shown that there are several advantages from allowing intermediate nodes to process and combine, in addition to just forward, packets. In this paper, we pose the problem of loss tomography in networks that have network coding capabilities. We design a framework for estimating link loss rates, which leverages network coding capabilities and we show that it improves several aspects of tomography, including the identifiability of links, the tradeoff between ...

Science.gov (United States)

We advance a tentative composite model for computer security at JPL, together with inter and intra networking with other NASA centers and overseas clients.

UK PubMed Central (United Kingdom)

The central nervous system regulates peripheral immune responses via the vagus nerve, the primary neural component of the cholinergic anti-inflammatory pathway. Electrical stimulation of the...Full Text Available

UK PubMed Central (United Kingdom)

BackgroundThe variety of ways in which faces are categorized makes face recognition challenging for both synthetic and biological vision systems. Here we focus on two face processing...Full Text Available

UK PubMed Central (United Kingdom)

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past...Full Text Available

UK PubMed Central (United Kingdom)

Background and purpose:The chicken anterior mesenteric artery contains an outer longitudinal smooth muscle layer, whose neural regulation remains to be elucidated. ATP evokes a depolarization...Full Text Available

UK PubMed Central (United Kingdom)

The CNS can exhibit features of inflammation in response to injury, infection or disease, whereby resident cells generate inflammatory mediators, including cytokines, prostaglandins, free radicals and...Full Text Available

UK PubMed Central (United Kingdom)

Ten subjects balanced their own body or a mechanically equivalent unstable inverted pendulum by hand, through a compliant spring linkage. Their balancing process was always characterized by repeated...Full Text Available

UK PubMed Central (United Kingdom)

Blindness leads to a major reorganization of neural pathways associated with touch. Because incoming somatosensory information influences motor output, it is plausible that motor plasticity occurs in...Full Text Available

UK PubMed Central (United Kingdom)

A prevailing theory proposes that the brain's two visual pathways, the ventral and dorsal, lead to differing visual processing and world representations for conscious perception than those for action....Full Text Available

UK PubMed Central (United Kingdom)

Humans are remarkably adept at identifying individuals by the sound of their voice, a behavior supported by the nervous system’s ability to integrate information from voice and speech...Full Text Available

UK PubMed Central (United Kingdom)

Proprioceptive sensory signals inform the CNS of the consequences of motor acts, but effective motor planning involves internal neural systems capable of anticipating actual sensory feedback....Full Text Available

UK PubMed Central (United Kingdom)

Backgroundoscillatory activity, which can be separated in background and oscillatory burst pattern activities, is supposed to be representative of local synchronies of neural assemblies....Full Text Available

UK PubMed Central (United Kingdom)

The mammalian reoviruses have provided a valuable model for studying the pathogenesis of viral infections of the central nervous system (CNS). We have used this model to study the effect of antibody...Full Text Available

British Library Electronic Table of Contents (United Kingdom)

We review visually guided behaviors in larval zebrafish and summarise what is known about the neural processing that results in these behaviors, paying particular attention to the progress made in the last 2 years. Using the examples of the optokinetic reflex, the optomotor response, prey tracking and the visual startle response, we illustrate how the larval zebrafish presents us with a very promising model vertebrate system that allows neurocientists to integrate functional and behavioral studies and from which we can expect illuminating insights in the near future.

Energy Technology Data Exchange (ETDEWEB)

This report describes the results obtained during Stage 13 of a long-term research and development program concerning the development of diagnostics and monitoring methods for nuclear reactors. A brief proposal for the continuation of this program in Stage 14 is also given at the end of the report. The program executed in Stage 13 consists of three parts and the work performed in each part is summarized below. 1. Study of criticality, neutron kinetics and neutron noise in molten salt reactors (MSR). Although the original goal of the investigations of the MSR in Stage 13 was to calculate the neutron noise induced by the fluctuations of the fuel temperature, the study, solution and interpretation of the static problem, as well as to define an approximate version of the point kinetic approximation was necessary to perform. As it turned out, these tasks in themselves were more involved, and also very edifying, to solve. Hence, in this report, we confine the study of the reactor physics of ...

Science.gov (United States)

PMID:21398174

Science.gov (United States)

PMID:12556767

Science.gov (United States)

Not Available

CERN Multimedia

"Network Physics, the only provider of physics-based network management products, today announced an additional venture round of $6 million in funding, as well as the addition of David Jones as president and CEO and Tom Dunn as vice president of sales and business development" (1 page).

Energy Technology Data Exchange (ETDEWEB)

Implementing a successful local area network for a publications work-group isn't as simple as the scarcity of information on the subject would suggest. Making a network work for your requires careful planning, developing and acquiring network expertise, transforming your group's patterns of working together, and carefully managing the human and technological resources.

ScienceCinema

...english uh ? that's quite motor ...

British Library Electronic Table of Contents (United Kingdom)

Recent supply chain reengineering efforts have focused on integrating firms? production, inventory and replenishment activities with the help of communication networks. While communication networks and supply chain integration facilitate optimization of traditional supply chain functions, they also exacerbate the information security risk: communication networks propagate security breaches from one firm to another, and supply chain integration causes breach on one firm to affect other firms in the supply chain. We study the impact of network security vulnerability and supply chain integration on firms? incentives to invest in information security. We find that even though an increase in either the degree of network vulnerability or the degree of supply chain integration increases the secur...

Energy Technology Data Exchange (ETDEWEB)

The objective of this research project is to demonstrate sensing, communication, information and control technologies to achieve a seamless integration of multivendor distributed energy resource (DER) units at aggregation levels that meet individual user requirements for facility operations (residential, commercial, industrial, manufacturing, etc.) and further serve as resource options for electric and natural gas utilities. The fully demonstrated DER aggregation system with embodiment of communication and control technologies will lead to real-time, interactive, customer-managed service networks to achieve greater customer value. Work on this Advanced Communication and Control Project (ACCP) consists of a two-phase approach for an integrated demonstration of communication and control technologies to achieve a seamless integration of DER units to reach progressive levels of aggregated power output. Phase I involved design and proof-of-design, and Phase II involves ...

International Nuclear Information System (INIS)

The layout of the network with its frequency and transmission power control shows how the time behaviour of power plants and consumers determines the frequency curve during sudden power disturbances. As for switching processes in the network for the turbine, network operation entails loads due to shock-like disturbance functions to which one should not normally respond by switching off. The interception controllers are therefore adjusted via a simulation model by which the vibrations of the turbine rotor can be modelled in real time under different network loads. (GL).

CERN Document Server

A complex network approach on a rough fracture is developed. In this manner, some hidden metric spaces (similarity measurements) between apertures profiles are set up and a general evolutionary network in two directions (in parallel and perpendicular to the shear direction) is constructed. Also, an algorithm (COmplex Networks on Apertures: CONA) is proposed in which evolving of a network is accomplished using preferential detachments and attachments of edges (based on a competition and game manner) while the number of nodes is fixed. Also, evolving of clustering coefficients and number of edges display similar patterns as well as are appeared in shear stress, hydraulic conductivity and dilation changes, which can be engaged to estimate shear strength distribution of asperities.

Energy Technology Data Exchange (ETDEWEB)

A probabilistic method for assessing the profitability of reactive power compensation devices such as capacitors, static VAR compensators and generators, which improve network security, was described. Since network development is limited by environmental constraints, power networks are operated close to their limits. Because of this fact transmission network planning increasingly relies on techno-economic models to improve network security and profitability. The proposed method consists of analyzing large numbers of constrained power system states, extracted from power system simulation exercises. The paper describes details of the method and provides an example of a numerical application on a part of the French power transmission system. 10 refs., 8 figs.

Energy Technology Data Exchange (ETDEWEB)

NIF target diagnostics are being developed to observe and measure the extreme physics of targets irradiated by the 192-beam laser. The response time of target materials can be on the order of 100ps--the time it takes light to travel 3 cm--temperatures more than 100 times hotter than the surface of the sun, and pressures that exceed 109 atmospheres. Optical and x-ray diagnostics were developed and fielded to observe and record the results of the first 4-beam experiments at NIF. Hard and soft x-ray spectra were measured, and time-integrated and gated x-ray images of hydrodynamics experiments were recorded. Optical diagnostics recorded backscatter from the target, and VISAR laser velocimetry measurements were taken of laser-shocked target surfaces. Additional diagnostics are being developed and commissioned to observe and diagnose ignition implosions, including various neutron and activation diagnostics. NIF's diagnostics are being developed at LLNL and with collaborators at ...

Energy Technology Data Exchange (ETDEWEB)

The CPCU steam distribution network is supplemented by a return network for the condensation water. The data system installed in 1988 provides, for the real time, management of the function of the two networks and a reduction in production costs. For the steam, data required in the network, the boiler houses and from external sources are processed by local network of five microprocessors and permit: - with time delay: technical and economic production optimizing calculations, or forecasts, for the following day, of the total required output and the procedure necessary for supplying this at the lowest cost; - in real time: on the basis of the forecasts for the previous day, creating the production instructions for the boiler houses and the instructions for the network remote control elements; - in case of an unexpected occurrence: immediate creation of new ...

CERN Document Server

The field of digital libraries (DLs) coalesced in 1994: the first digital library conferences were held that year, awareness of the World Wide Web was accelerating, and the National Science Foundation awarded $24 Million (U.S.) for the Digital Library Initiative (DLI). In this paper we examine the state of the DL domain after a decade of activity by applying social network analysis to the co-authorship network of the past ACM, IEEE, and joint ACM/IEEE digital library conferences. We base our analysis on a common binary undirectional network model to represent the co-authorship network, and from it we extract several established network measures. We also introduce a weighted directional network model to represent the co-authorship network, for which we define $AuthorRank$ as an indicator of the impact of an individual author in the ...

Energy Technology Data Exchange (ETDEWEB)

The Los Alamos Nuclear Material Accounting and Safeguards System (MASS) is a near-real-time accountability system for bulk materials, discrete items, and material undergoing dynamic processing. MASS has evolved from an eighty-column card based process control system to a very sophisticated computer system. The security of the MASS computer system is provide through various access controls. There are two kinds of access control to be addressed. They are physical access control to the hardware which make up the system, and access control to the software. There are many features which provide a measure of security to the hardware that will be discussed. Access to the software is controlled by a security password. Access to various transaction activities in the system is controlled through the level of MASS user privilege. Details of MASS user privilege will be discussed.