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), ...

CERN Document Server

Methods and Procedures for the Verification and Validation of Artificial Neural Networks

Science.gov (United States)

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Science.gov (United States)

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CERN Document Server

We study quantized beamforming in wireless amplify-and-forward relay-interference networks with any number of transmitters, relays, and receivers. We design the quantizer of the channel state information to minimize the probability that at least one receiver incorrectly decodes its desired symbol(s). Correspondingly, we introduce a generalized diversity measure that encapsulates the conventional one as the first-order diversity. Additionally, it incorporates the second-order diversity, which is concerned with the transmitter power dependent logarithmic terms that appear in the error rate expression. First, we show that, regardless of the quantizer and the amount of feedback that is used, the relay-interference network suffers a second-order diversity loss compared to interference-free networks. Then, two different quantization schemes are ...

KoreaScience (Korea)

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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)

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)

Superheater corrosion causes vast annual losses to the power companies. If the corrosion could be reliably predicted, new power plants could be designed accordingly, and knowledge of fuel selection and determination of process conditions could be utilized to minimize superheater corrosion. If relations between inputs and the output are poorly known, conventional models depending on corrosion theories will fail. A prediction model based on a neural network is capable of learning from errors and improving its performance as the amount of data increases. The neural network developed during this study predicts superheater corrosion with 80 % accuracy at early stage of the project. (orig.) 10 refs.

Energy Technology Data Exchange (ETDEWEB)

In this paper an attempt is made to forecast load using fuzzy neural network (FNN) for an integrated power system. Here, the proposed system uses a two stage FNN for a short term peak and average load forecasting (STPALF). The first stage FNN deals with the load forecasting and the second stage algorithm can be worked independently for network security. This technique is used to forecast load accurately on week days as well as holidays, weekends and some special occasions considering historical data of load and weather information and also take necessary control action for network security.

Energy Technology Data Exchange (ETDEWEB)

A back-propagation neural network technique is used at JET to extract plasma parameters like ion temperature, rotation velocities or spectral line intensities from charge exchange (CX) spectra. It is shown that in the case of the C VI CX spectra, neural networks can give a good estimation (better than +-20% accuracy) for the main plasma parameters (Ti, V{sub rot}). Since the neural network approach involves no iterations or initial guesses the speed with which a spectrum is processed is so high (0.2 ms/spectrum) that real time analysis will be achieved in the near future. 4 refs., 8 figs.

Science.gov (United States)

A voice-tracking algorithm was developed and tested for the purposes of electronically separating the voice signals of simultaneous talkers. Many individuals suffer from hearing disorders that often inhibit their ability to focus on a single speaker in a multiple speaker environment (the cocktail party effect). Digital hearing aid technology makes it possible to implement complex algorithms for speech processing in both the time and frequency domains. In this work, an average magnitude difference function (AMDF) was performed on mixed voice signals in order to determine the fundamental frequencies present in the signals. A time prediction neural network was trained to recognize normal human voice inflection patterns, including rising, falling, rising-falling, and falling-rising patterns. The neural network was designed to track the fundamental frequency of a single talker based on the training ...

UK PubMed Central (United Kingdom)

An optical flow gradient algorithm was applied to spontaneously forming networks of neurons and glia in culture imaged by fluorescence optical microscopy in order to map functional calcium signaling...Full Text Available

Energy Technology Data Exchange (ETDEWEB)

This paper deals with the control of an electromechanical valves engine. The control uses neural networks in order to build a non-linear model of engine filing which depends on the driven inlets. The aim is to build this real-time model and to integrate this model to a control system which performs an iterative inversion. (J.S.)

CERN Document Server

Recently, applying the novel data mining techniques for evaluating enterprise financial distress has received much research alternation. Support Vector Machine (SVM) and back propagation neural (BPN) network has been applied successfully in many areas with excellent generalization results, such as rule extraction, classification and evaluation. In this paper, a model based on SVM with Gaussian RBF kernel is proposed here for enterprise financial distress evaluation. BPN network is considered one of the simplest and are most general methods used for supervised training of multilayered neural network. The comparative results show that through the difference between the performance measures is marginal; SVM gives higher precision and lower error rates.

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)

The classical stochastic approximation methods are shown to yield algorithms to solve several formulations of the PAC learning problem defined on the domain [o,1]{sup d}. Under some assumptions on different ability of the probability measure functions, simple algorithms to solve some PAC learning problems are proposed based on networks of non-polynomial units (e.g. artificial neural networks). Conditions on the sizes of these samples required to ensure the error bounds are derived using martingale inequalities.

International Nuclear Information System (INIS)

The aim of the study was to assess the usefulness of artificial neural networks (ANN) application in evaluation of scintimammography in the context of clinical data in the diagnosis of breast cancer. The results produced by ANN were compared with the diagnosis of two independent observers, nuclear medicine specialists. Material and methods: The clinical data and the numerical values derived from scintimammograms of 103 patients were the material for the study. The reference method was the result of histopathology study (core biopsy and /or FNB). Results: The overall sensitivity of physician diagnosis was 78% with specificity of 72%. The ANN produced 71% sensitivity and specificity of 73%. The physicians and ANN results were not significantly different (p=0.4619). Conclusions: Artificial neutral networks are useful tool in clinical diagnosis of breast cancer. (authors)

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...

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...

British Library Electronic Table of Contents (United Kingdom)

Frozen boiled shrimp and dried shrimp are among the high-value fishery products of Thailand. During the production of these products boiling is one of the most important steps that affects significantly the product physicochemical properties, especially the quantity and quality of proteins, which in turn affect other apparent properties perceived by consumers. The protein changes are, however, difficult to evaluate comparing to other typical physical properties of shrimp. The objective of this study was therefore to develop an artificial neural network (ANN) model to predict the protein changes of shrimp in terms of protein loss and protein denaturation as a function of the boiling conditions, namely, concentration of salt solution and boiling time, as well as a rather easily determined ch...

Energy Technology Data Exchange (ETDEWEB)

This paper presents a systematic approach for designing a self-tuning power system stabilizer (PSS) based on artificial neural network (ANN). An ANN is used for self-tuning the parameters of PSS in real-time. The nodes in the input layer of the ANN receive generator terminal active power (P), reactive power (Q), and voltage (V{sub t}), while the nodes in the output layer provide the optimum PSS parameters, e.g. stabilizing gain (K{sub STAB}), time constants (T{sub 1} and T{sub 2}). A new approach for the selection of number of neurons in the hidden layer has been proposed. Investigations reveal that the dynamic performance of the system with self-tuning PSS based on ANN (ST-ANNPSS) is quite robust over a wide range of loading conditions and equivalent reactance, X{sub e}. (Author)

British Library Electronic Table of Contents (United Kingdom)

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 differ...

British Library Electronic Table of Contents (United Kingdom)

The paper describes two schemes that follow the model of Lamarckian evolution and combine differential evolution (DE), which is a population-based stochastic global search method, with the local optimization algorithm of conjugate gradients (CG). In the first, each offspring is fine-tuned by CG before competing with their parents. In the other CG is used to improve both parents and offspring in a manner that is completely seamless for individuals that survive more than one generation. Experiments involved training weights of feed-forward neural networks to solve three synthetic and four real-life problems. In six out of seven cases the DE?CG hybrid, which preserves and uses information on each solution?s local optimization process, outperformed two recent variants of DE.

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.

Science.gov (United States)

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 signals were then attained based on the bispectrum technique, which could be regarded as an index actualizing forepart gear faults diagnosis. Both the back ...

UK PubMed Central (United Kingdom)

BackgroundThermostable bacterial lipases occupy a place of prominence among biocatalysts owing to their novel, multifold applications and resistance to high temperature and other...Full Text Available

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...

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 ...

Science.gov (United States)

Optogenetics, the ability to use light to activate and silence specific neuron types within neural networks in vivo and in vitro, is revolutionizing neuroscientists' capacity to understand how defined neural circuit elements contribute to normal and pathological brain functions. Typically, awake behaving experiments are conducted by inserting an optical fiber into the brain, tethered to a remote laser, or by utilizing an implanted light-emitting diode (LED), tethered to a remote power source. A fully wireless system would enable chronic or longitudinal experiments where long duration tethering is impractical, and would also support high-throughput experimentation. However, the high power requirements of light sources (LEDs, lasers), especially in the context of the extended illumination periods often desired in experiments, precludes battery-powered approaches from being widely applicable. We have developed a headborne ...

Energy Technology Data Exchange (ETDEWEB)

Organic modification of aerogel chemical formulations is known to transfer desirable hydrophobicity to lightweight solids. However, the effects of chemical modification on other material constants such as elasticity, compliance, and sound dampening present a difficult optimization problem. Here a statistical treatment of a 9-variable optimization is accomplished with multiple regression and an artificial neural network (ANN). The ANN shows 95 percent prediction success for the entire data set of elasticity, compared to a multidimensional linear regression which shows a maximum correlation coefficient, R=0.782. In this case, using the Number of Categories Criterion for the standard multiple regression, traditional statistical methods can distinguish fewer than 1.83 categories (high and low elasticity) and cannot group or cluster the data to give more refined partitions. A non-linear surface requires at least 3 categories (high, low, and medium ...

Science.gov (United States)

... Accession Number : ADA111683. Title : Coherency Effects on Retinal Neural Processes (ERG) of Pseudemys. Descriptive ...

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 ...

CERN Document Server

In general relativity, the fields on a black hole horizon are obtained from those in the bulk by pullback and restriction. Similarly, in quantum gravity, the quantized horizon degrees of freedom should result from restricting, or pulling-back, the quantized bulk degrees of freedom. This is not yet fully realized in the - otherwise very successful - quantization of isolated horizons in loop quantum gravity. In this work we outline a setting in which the quantum horizon degrees of freedom are simply components of the quantized bulk degrees of freedom. There is no need to quantize them separately. We present evidence that for a horizon of sphere topology, the resulting horizon theory is remarkably similar to what has been found before.

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...

Energy Technology Data Exchange (ETDEWEB)

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 {sub ij}(t)=-a{sub ij}(t)x{sub ij}(t)--bar B{sup kl}-bar Nr(i,j)B{sub ij}{sup kl}(t)f{sub ij}(x{sub kl}(t))x{sub ij}(t)--bar C{sup kl}-bar Nr(i,j)C{sub ij}{sup kl}(t)g{sub ij}(x{sub kl}(t-{tau}{sub kl}))x{sub ij}(t)+L{sub ij}(t)

British Library Electronic Table of Contents (United Kingdom)

Mechanomyography (MMG) is the muscle surface oscillations that are generated by the dimensional change of the contracting muscle fibers. Because MMG reflects the number of recruited motor units and their firing rates, just as electromyography (EMG) is influenced by these two factors, it can be used to estimate the force exerted by skeletal muscles. The aim of this study was to demonstrate the feasibility of MMG for estimating the elbow flexion force at the wrist under an isometric contraction by using an artificial neural network in comparison with EMG. We performed experiments with five subjects, and the force at the wrist and the MMG from the contributing muscles were recorded. It was found that MMG could be utilized to accurately estimate the isometric elbow flexion force based on the v...

Energy Technology Data Exchange (ETDEWEB)

This paper describes the weekly load forecasting expert system (named WLoFy) which was developed and implemented for korea electric power corporation(KEPCO). WLoFy was designed to provide user oriented features with a graphical user interface to improve the user interaction. The various forecasting models such as exponential smoothing, multiple regression, artificial neural networks, rule-based model, and relative coefficient model also have been included in WLofy to increase the forecasting accuracy. The simulation based on historical data shows that the weekly forecasting results from WLoFy is an improvement when compared to the results from the conventional methods. Especially the forecasting accuracy on special days has been improved remarkably. (author). 9 refs., 5 figs., 6 tabs.

Energy Technology Data Exchange (ETDEWEB)

This two-tomes book brings together the 108 presentations given at the first conference of the international institute of refrigeration (IIF/IIR) about air conditioning in high rise office buildings. The main themes are: general design and control systems, including split systems, radiant panels, fluctuating and gravity ventilation etc..; energy consumption, optimization and heat recovery; cold storage for peak shaving, including ice slurry circulation; indoor air quality; fire and smokes protection, protection against chimney effects and lighting spots; use of fuzzy logic and of neural networks. It includes also a description of the high rise building situation and works in progress in China, Japan and in some other countries. (J.S.)

British Library Electronic Table of Contents (United Kingdom)

Action potentials from the brain control the activity of spinal neural networks to produce, by as yet unknown mechanisms, a variety of motor behaviors. Particularly lacking are details on how identified descending neurons integrate diverse sensory inputs to generate specific locomotor patterns. We have examined the operations of the principal neurons in an intriguing midbrain nucleus, the nucleus of the medial longitudinal fasciculus (nMLF), in the larval zebrafish. The nMLF is the most rostral grouping of neurons that projects from the brain well into the spinal cord of teleost fishes, yet there is little direct physiological data available regarding its function. We report here that a distinct set of large, individually-identifiable neurons in nMLF (the MeL and MeM neurons) are activated...

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Not Available

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To keep up with the speeds of modern production lines, most machine vision applications require very powerful computers (often parallel-processing machines), which process millions of points of data in real time. The human brain performs approximately 100 billion logical floating-point operations each second. That is 400 times the speed of a Cray-1 supercomputer. The right software must be developed for parallel-processing computers. The NSF has awarded Rensselaer Polytechnic Institute (Troy, N.Y.) a $2 million grant for parallel- and image-processing software research. Over the last 15 years, Rensselaer has been conducting image-processing research, including work with high-definition TV (HDTV) and image coding and understanding. A similar NSF grant has been awarded to Michigan State University (East Lansing, Mich.) Neural networks are supposed to emulate human learning patterns. These networks and their hardware ...

International Nuclear Information System (INIS)

The aim of the study was the attempt to evaluate the influence of two different methods of cardiac perfusion SPECT reconstruction (FBP and ITW) on clinical efficacy in diagnosing the coronary artery disease as well as the cardiac ischemia detection in three areas of heart vascularized by main coronary arteries: LAD, LCX and RCA with the use of artificial neural networks (ANN). The study was performed retrospectively with the use of the diagnostic image records as well as clinical dataset of 43 patients. Myocardial perfusion stress/rest SPECT study and X-ray coronarography data were evaluated for each patient. The results of coronary angiography were considered the reference method. The cardiac SPECT data were reconstructed using the two different methods: filtered backprojection (FBP) and iterative Wallis method (ITW). The local perfusion deficits denominated in stress and rest study in three main vessel cardiac segments were the main input ...

CERN Document Server

Theory of quantum games is relatively new to the literature and its applications to various areas of research are being explored. It is a novel interpretation of strategies and decisions in quantum domain. In the earlier work on quantum games considerable attention was given to the resolution of dilemmas present in corresponding classical games. Two separate quantum schemes were presented by Eisert et al. and Marinatto and Weber to resolve dilemmas in Prisoners' Dilemma and Battle of Sexes games respectively. However for the latter scheme it was argued that dilemma was not resolved. We have modified the quantization scheme of Marinatto and Weber to resolve the dilemma. We have developed a generalized quantization scheme for two person non-zero sum games which reduces to the existing schemes under certain conditions. Applications of this generalized quantization scheme to quantum information theory are studied. Measurement ...

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The Weyl-Wigner prescription for quantization on Euclidean phase spaces makes essential use of Fourier duality. The extension of this property to more general phase spaces requires the use of Kac algebras, which provide the necessary background for the implementation of Fourier duality on general locally groups. Kac algebras - and the duality they incorporate are consequently examined as candidates for a general quantization framework extending the usual formalism. Using as a test case the simplest non-trivial phase space, the half-plane, it is shown how the structures present in the complete-plane case must be modified. Traces, for example, must be replaced by their noncommutative generalizations - weights - and the correspondence embodied in the Weyl-Wigner formalism is no more complete. Provided the underlying algebraic structure is suitably adapted to each case, Fourier duality is shown to be indeed a very powerful guide to the ...

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... This paper presents our research in neural learning for predicting ... Denote this feature set as F4. ... can be observed that the SOC curves generated by ...

CERN Document Server

Office Moves Involving Network Equipment

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PMID:17758994

Science.gov (United States)

PMID:15029781

International Nuclear Information System (INIS)

Lorentz invariant theory of second quantization of superluminal electromagnetic fields has been constructed in purely group theoretical manner by using the reduced expansion of four-vector fields for imaginary mass system in terms of standard helicity representations of Poincare group. It has been shown that the usual relationship of spin and statistics need not be inverted for Lorentz invariance of the theory of spin-1 tachyons. (author).

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The conductance in ferromagnetic Ni nano-wire is quantized in units of 2e{sup 2}/h in the absence of magnetic field, while the units switch to e{sup 2}/h in the magnetic field. The fractional units of 0.7e{sup 2}/h and 1.4e{sup 2}/h with and without magnetic field appear under the application of high bias-voltage. The spin polarization and bias-voltage play an important role in the electric conduction.

International Nuclear Information System (INIS)

Using the reduced WZNW formulation we analyse the classical W-orbit content of the space of classical solutions of the A_2 Toda theory. We define the quantized Toda field as a periodic primary field of the W-algebra satisfying the quantized equations of motion. We show that this local operator can be constructed consistently only in Hilbert space consisting of the representation corresponding to the minimal models of the W-algebra. (orig.).

International Nuclear Information System (INIS)

The stunning, intricate interaction between the visual, vestibular and optomotor systems--each a miracle on its own--ensures maintenance of orientation in space as well as visual recognition and target selection despite a host of sensory conflicts and adversary disturbances. Their main goals are to keep a target of interest on the fovea by either maintaining or shifting the direction of gaze in order to produce an accurate internal representation of the visual surroundings, in particular the selected target, and to continuously mirror the spatial relationship between these various visual elements and the self. Not surprising, the implementation of this host of elaborate neural networks encompasses almost every part of the brain, including the brainstem, cerebellum, extrapyramidal system and many areas of the cerebral cortex. Thus far, these systems are among the best investigated in brain research; and enormous knowledge was amassed over the ...

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Short communication.

Energy Technology Data Exchange (ETDEWEB)

Validation of nuclear power reactor signals is often performed by comparing signal prototypes with the actual reactor signals. The signal prototypes are often computed based on empirical data. The implementation of an estimation algorithm which can make predictions on limited data is an important issue. A new machine learning algorithm called support vector machines (SVMS) recently developed by Vladimir Vapnik and his coworkers enables a high level of generalization with finite high-dimensional data. The improved generalization in comparison with standard methods like neural networks is due mainly to the following characteristics of the method. The input data space is transformed into a high-dimensional feature space using a kernel function, and the learning problem is formulated as a convex quadratic programming problem with a unique solution. In this paper the authors have applied the SVM method for data-based state estimation in nuclear ...

Energy Technology Data Exchange (ETDEWEB)

The use of electricity is indispensable to modern life. As Macao Special Administrative Region becomes a gaming and tourism center in Asia, modeling the consumption of electricity is critical to Macao's economic development. The purposes of this paper are to conduct an extensive literature review on modeling of electricity consumption, and to identify key climatic, demographic, economic and/or industrial factors that may affect the electricity consumption of a country/city. It was identified that the five factors, namely temperature, population, the number of tourists, hotel room occupancy and days per month, could be used to characterize Macao's monthly electricity consumption. Three selected approaches including multiple regression, artificial neural network (ANN) and wavelet ANN were used to derive mathematical models of the electricity consumption. The accuracy of these models was assessed by using the mean squared error ...

Energy Technology Data Exchange (ETDEWEB)

Model-based approaches to pattern recognition and machine vision have been proposed to overcome the exorbitant training requirements of earlier computational paradigms. However, uncertainties in data were found to lead to a combinatorial explosion of the computational complexity. This issue is related here to the roles of a priori knowledge vs. adaptive learning. What is the a-priori knowledge representation that supports learning? I introduce Modeling Field Theory (MFT), a model-based neural network whose adaptive learning is based on a priori models. These models combine deterministic, fuzzy, and statistical aspects to account for a priori knowledge, its fuzzy nature, and data uncertainties. In the process of learning, a priori fuzzy concepts converge to crisp or probabilistic concepts. The MFT is a convergent dynamical system of only linear computational complexity. Fuzzy logic turns out to be essential for reducing the combinatorial ...

Energy Technology Data Exchange (ETDEWEB)

The project aim is to model the hybrid plant at Vaesthamnsverket in Helsingborg using artificial neural networks (ANN) and integrating the ANN models, for online condition monitoring and thermoeconomic optimization, at Vaesthamnsverket. The definition of a hybrid plant is that it uses more than one fuel, in this case a natural gas fuelled gas turbine with heat recovery steam generator (HRSG) and a biomass fuelled steam boiler with steam turbine. The project is a continuation of previous projects where ANN training was done with operational data from the plant. The ANN models have, if required, been updated to better suit the purpose of this project. The thermoeconomic optimization takes into account current electricity prices, taxes, fuel prices etc. and calculates the current production cost along with the 'predicted' production cost. The tool also has a built in feature of predicting when a compressor wash is economically ...

CERN Document Server

We investigate the profound relation between the equations of biological evolution and quantum mechanics by writing a biologically inspired equation for the stochastic dynamics of an ensemble of particles. Interesting behavior is observed which is related to a new type of stochastic quantization. We find that the probability distribution of the ensemble of particles can be decomposed into eigenfunctions associated to a discrete spectrum of eigenvalues. In absence of interactions between the particles, the out-of-equilibrium dynamics asymptotically relaxes towards the fundamental state. This phenomenon can be related with the Fisher theorem in biology. On the contrary, in presence of scattering processes the evolution reaches a steady state in which the distribution of the ensemble of particles is characterized by a Bose-Einstein statistics. In order to show a concrete example of this stochastic quantization we have solved explicitly the case in ...

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

International Nuclear Information System (INIS)

The phase space of quantized systems that contain tachyons has been investigated. Interpretation difficulties and unexpected divergences are found when it is considered the volume of Lorentz-invariant phase space. These problems can be overcome, however, at the expense of Lorentz invariance.

International Nuclear Information System (INIS)

This paper reports on Monte Carlo path integral simulations of a Bianchi Type IX cosmology which yield a wave function which reflects the known chaotic dynamics of the classical system and predicts a significant probability for a correlation between large universe volume and large anisotropy.

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Not Available

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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

CERN Document Server

A theory of nonunitary-invertible as well as unitary canonical transformations is formulated in the context of Weyl's phase space representations. Exact solutions of the transformation kernels and the phase space propagators are given for the three fundamental canonical maps as fractional-linear, gauge and contact (point) transformations. Under the nonlinear maps a phase space representation is mapped to another phase space representation thereby extending the standard concept of covariance. This extended covariance allows Dirac-Jordan transformation theory to naturally emerge from the Hilbert space representations in the Weyl quantization.

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)

No abstract prepared.

Science.gov (United States)

... in artificial intelligence, human physiology and biomedical prosthesis. ... central and peripheral nerve systems [1 ... CMOS circuit interface for multiplexed ...

CERN Document Server

Networked Digital Library of Theses and Dissertations

British Library Electronic Table of Contents (United Kingdom)

Summary 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 ...

British Library Electronic Table of Contents (United Kingdom)

This paper presents a supernetwork equilibrium model integrating supply chain networks with a transport network, namely, a supply chain-transport supernetwork equilibrium model. The model takes into account the behaviour of freight carriers and transport network users to endogenously determine the transport costs generated in the supply chain networks. The interaction between transport network and supply chain networks can also be examined. Results of the numerical tests reveal that the improvement of transport network could enhance the efficiency of supply chain networks. The paper makes contributions to modelling of supply chain networks as well as to that of transport networks.

Energy Technology Data Exchange (ETDEWEB)

Methods, systems, and products are disclosed for determining a bisection bandwidth for a multi-node data communications network that include: partitioning nodes in the network into a first sub-network and a second sub-network in dependence upon a topology of the network; sending, by each node in the first sub-network to a destination node in the second sub-network, a first message having a predetermined message size; receiving, by each node in the first sub-network from a source node in the second sub-network, a second message; measuring, by each node in the first sub-network, the elapsed communications time between the sending of the first message and the receiving of the second message; selecting the longest elapsed communications time; and calculating the bisection bandwidth ...

International Nuclear Information System (INIS)

Computer programs have been written to allow the analysis of different types of eddy-current probes and their performance under different steam generators test conditions. The probe types include the differential bobbin probe, the absolute bobbin probe, the pancake probe and the reflection probe. The generator test conditions include tube supports, copper deposits, magnetite deposits, denting, wastage, pitting, cracking, and intergranular attack. These studies are based mostly on computed values, with the limited number of test specimens available used to verify the computed results. The instrument readings were computed for a complete matrix of the different test conditions, and then the test conditions determined as a function of the readings by a least-squares technique. A comparison was made of the errors in fit and instrument drift for the different probe types. The computations of the change in instrument reading due to the defects have led to an inversion technique in which the ...

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... 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

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

CERN Document Server

The Lie algebra so(2n+1) and the Lie superalgebra osp(1/2n) are quantized in terms of 3n generators, called preoscillator generators. Apart from n "Cartan" elements the preoscillator generators are deformed para-Fermi operators in the case of so(2n+1) and deformed para-Bose operators in the case of osp(1/2n). The corresponding deformed universal enveloping algebras U_q[so(2n+1)] and U_q[osp(1/2n)] are the same as those defined in terms of Chevalley operators. The name "preoscillator" is to indicate that in a certain representation these operators reduce to the known deformed Fermi and Bose operators.

CERN Document Server

Numerical results on the translocation of long biopolymers through mid-sized and wide pores are presented. The simulations are based on a novel methodology which couples molecular motion to a mesoscopic fluid solvent. Thousands of events of long polymers (up to 8000 monomers) are monitored as they pass through nanopores. Comparison between the different pore sizes shows that wide pores can host a larger number of multiple biopolymer segments, as compared to smaller pores. The simulations provide clear evidence of folding quantization in the translocation process as the biopolymers undertake multi-folded configurations, characterized by a well-defined integer number of folds. Accordingly, the translocation time is no longer represented by a single-exponent power law dependence on the length, as it is the case for single-file translocation through narrow pores. The folding quantization increases with the biopolymer length, while the rate of ...

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

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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

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No abstract prepared.

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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 ...

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... 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)

The wave equation of a spinless tachyon is studied in Schwarzschild space-time. In contrast to earlier approaches to the problem, it is shown that tachyonic static solutions satisfy a simple second-order linear differential equation regardless of the mass of the black hole and the mass parameter of the tachyon. Physical implication of the present approach is discussed. Using Langer modification of the WKB (Wentzel-Kramers-Brillouin) boundary condition an expression similar to the Bohr-Sommerfeld quantization condition is derived.

CERN Document Server

Canonical gravity in real Ashtekar-Barbero variables is generalized to allow for fermionic matter. The resulting torsion changes several expressions in Holst's original vacuum analysis, which are explicitly displayed here. This in turn requires adaptations to the known canonical (loop) quantization of gravity coupled to fermions, which is discussed on the basis of the classical analysis.

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A typical incident response pits technicians against networks that aren't prepared forensically. [1, 2] If practitioners do consider collecting network forensic data, they face a choice between expending extraordinary effort (time and money) collecting forensically sound data, or simply restoring the network as quickly as possible. In this context, the concept of organizational network forensic readiness has emerged. This paper proposes a methodology for "operationalizing" organizational network forensic readiness. The methodology, and the theoretical analysis that led to its development, are offered as a conceptual framework for thinking about more efficient, proactive approaches to digital forensics on networks.

CERN Document Server

Integrated femtocell/macrocell networks, comprising a conventional cellular network overlaid with femtocells, offer an economically appealing way to improve coverage, quality of service, and access network capacity. The key element to successful femtocells/macrocell integration lies in its self-organizing capability. Provisioning of quality of service is the main technical challenge of the femtocell/macrocell integrated networks, while the main administrative challenge is the choice of the proper evolutionary path from the existing macrocellular networks to the integrated network. In this article, we introduce three integrated network architectures which, while increasing the access capacity, they also reduce the deployment and operational costs. Then, we discuss a number of technical issues, which are key to making such integration a ...

Science.gov (United States)

This manual is intended to provide a free resource on essential network security concepts for non-technical managers of small libraries. Managers of other small nonprofit or community organizations will also benefit from it. An introduction defines network security; outlines three goals of network security; discusses why a library should be concerned with network security; and describes limits of this work. The manual is divided into three main parts. Part One features the management issues related to network security: analyzing risk, developing a security plan and policy, the funding requirements libraries can expect in operating their networks, and implementing adequate security. Part Two describes the areas of computer networks that need to be secured, and provides a description of many of the security measures necessary for adequate ...

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. ...

UK PubMed Central (United Kingdom)

This paper describes how a computerized MIS is used to assist HMO management to conduct utilization and quality of care review activities in a prepaid medical care network. The HMO is a ‘network’...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 ...

Science.gov (United States)

Cyber attacks on a hospital's computer network is a new crime to be reckoned with. Should your hospital consider internet insurance? The author explains this new phenomenon and presents a risk assessment for determining network vulnerabilities. PMID:11951384

CERN Document Server

Many mobile ad hoc network protocols use simple flooding, in order to adapt to changes in time varying network topology. Most of the times, a network-wide flood results in redundant packets and increases network congestion, probability of packet collision, low utilization of available bandwidth, and most important, higher power consumption. In this paper, we propose a new cross-layer broadcast scheme to minimize broadcast traffic in mobile ad hoc networks. Our scheme is based on use of received signal strength indicator, RSSI, value to reduce the number of broadcast packets. The effectiveness of the proposed technique is verified using simulations.

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.

Energy Technology Data Exchange (ETDEWEB)

We study free and self-interacting scalar quantum field theories in a flat Robertson-Walker metric in the functional Schroedinger picture. We discuss Schroedinger picture quantization, relating it to conventional Heisenberg picture quantization. For the interacting theory, we introduce the time-dependent Gaussian approximation to study time evolution of pure and mixed states and we establish renormalizability of the approximation. We also study the question of computing a finite, renormalized energy-momentum tensor for both the free and the interacting theory in the Gaussian appproximation. Using the adiabatic expansion, we show that the entire subtration necessary to make the the energy-momentum tensor finite in the free theory can be written in terms of covariantly conserved tensors. We further show that the same subtraction is sufficient to make the energy-momentum tensor finite in the Gaussian approximation for the interacting theory ...

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, ...

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

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

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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 ...

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... 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.

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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 ...

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

CERN Document Server

The Rabi Hamiltonian, describing the coupling of a two-level system to a single quantized boson mode, is studied in the Bargmann-Fock representation. The corresponding system of differential equations is transformed into a canonical form in which all regular singularities between zero and infinity have been removed. The canonical or Birkhoff-transformed equations give rise to a two-dimensional eigenvalue problem, involving the energy and a transformational parameter which affects the coupling strength. The known isolated exact solutions of the Rabi Hamiltonian are found to correspond to the uncoupled form of the canonical system.

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Cadmium sulfide particles have been synthesized in the aqueous medium using the amino acid histidine as a stabilizing agent. These particles demonstrate the phenomenon of size quantization effect. The fluorescence of histidine-stabilized CdS was found to be enhanced and quenched by the addition of DNA bases adenine and guanine, respectively. The fluorescence enhancement of CdS in the presence of adenine has been explained on the basis of interaction between the quantum dot stabilizer and the amino group of adenine. Quenching of CdS fluorescence by guanine occurs due to interaction of the substrate with the quantum dot surface.

CERN Document Server

In this paper we have investigated the performance of PSO Particle Swarm Optimization based clustering on few real world data sets and one artificial data set. The performances are measured by two metric namely quantization error and inter-cluster distance. The K means clustering algorithm is first implemented for all data sets, the results of which form the basis of comparison of PSO based approaches. We have explored different variants of PSO such as gbest, lbest ring, lbest vonneumann and Hybrid PSO for comparison purposes. The results reveal that PSO based clustering algorithms perform better compared to K means in all data sets.

Energy Technology Data Exchange (ETDEWEB)

This monograph gives a detailed and pedagogical account of the geometry of rigid superspace and supersymmetric Yang-Mills theories. While the core of the text is concerned with the classical theory, the quantization and anomaly problem are briefly discussed following a comprehensive introduction to BRS differential algebras and their field theoretical applications. Among the treated topics are invariant forms and vector fields on superspace, the matrix-representation of the super-Poincare group, invariant connections on reductive homogeneous spaces and the supermetric approach. Various aspects of the subject are discussed for the first time in textbook and are consistently presented in a unified geometric formalism.

UK PubMed Central (United Kingdom)

During development, multipotent neural precursors give rise to oligodendrocyte progenitor cells (OPCs), which migrate and divide to produce additional OPCs. Near the end of embryogenesis and...Full Text Available

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Hypercapnia is often used as vasodilatory challenge in clinical applications and basic research. In functional magnetic resonance imaging (fMRI), elevated CO₂ is applied to derive stimulus-induced...Full Text Available

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In utero electroporation is widely used to study neuronal development and function by introducing plasmid DNA into neural progenitors during embryogenesis. This is an effective and...Full Text Available

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Percutaneous radiofrequency ablation is the treatment of choice for osteoid osteoma of the appendicular skeleton. However, difficulties in localizing the lesion in the spine and its proximity to neural...Full Text Available

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1. Previous studies have shown that electrical stimulation (ES) of the guinea-pig cochlea causes a neurally mediated increase in cochlear blood flow (CBF). It is known that the centrifugal neuronal...Full Text Available

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The kinetic parameters of single bonds between neural cell adhesion molecules were determined from atomic force microscope measurements of the forced dissociation of the homophilic protein-protein bonds....Full Text Available

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An influential neural model of face perception suggests that the posterior superior temporal sulcus (STS) is sensitive to those aspects of faces that produce transient visual changes, including facial...Full Text Available

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The destiny of the mitotically active cells of the subventricular zone (SVZ) in adult rodents is to migrate to the olfactory bulb, where they contribute to the replacement of granular and periglomerular...Full Text Available

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During asymmetric mitosis, both in male Drosophila germline stem cells and in mouse embryo neural progenitors, the mother centrosome is retained by the self-renewed cell; hence suggesting...Full Text Available

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A century ago, Cajal noted striking similarities between the neural circuits that underlie vision in vertebrates and flies. Over the past few decades, structural and functional studies have...Full Text Available

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Stem cell therapies for neurodegenerative disorders require accurate delivery of the transplanted cells to the sites of damage. Numerous studies have established that fluid injections to the hippocampus...Full Text Available

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The neuromodulatory function of dopamine (DA) is an inherent feature of nervous systems of all animals. To learn more about the function of neural DA in Drosophila, we generated mutant...Full Text Available

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Even in healthy individuals, aging leads to deterioration in visual acuity, contrast sensitivity, visual field, and dark adaptation. Little is known about the neural mechanisms that drive the...Full Text Available

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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 ...

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PMID:21398174

Science.gov (United States)

PMID:12556767

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Not Available

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"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).

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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...

CERN Document Server

Mobile entities with wireless links are able to form a mobile ad-hoc network. Such an infrastructureless network does not have to be administrated. However, self-organizing principles have to be applied to deal with upcoming problems, e.g. information dissemination. These kinds of problems are not easy to tackle, requiring complex algorithms. Moreover, the usefulness of pure ad-hoc networks is arguably limited. Hence, enthusiasm for mobile ad-hoc networks, which could eliminate the need for any fixed infrastructure, has been damped. The goal is to overcome the limitations of pure ad-hoc networks by augmenting them with instant Internet access, e.g. via integration of UMTS respectively GSM links. However, this raises multiple questions at the technical as well as the organizational level. Motivated by characteristics of small-world networks that describe an ...

Science.gov (United States)

Information security involves many branches of effort, including information assurance, host level security, physical security, and network security. Computer network security methods and implementations are given a top-down description to permit a medically focused audience to anchor this information to their daily practice. The depth of detail of network functionality and security measures, like that of the study of human anatomy, can be highly involved. Presented at the level of major gross anatomical systems, this paper will focus on network backbone implementation and perimeter defenses, then diagnostic tools, and finally the user practices (the human element). Physical security measures, though significant, have been defined as beyond the scope of this presentation.

Energy Technology Data Exchange (ETDEWEB)

Use of a broadband Local Area Network (LAN) for transmission of classified and secure unclassified information requires monitoring capabilities which are sensitive to discrete segments of the network frequency spectrum. A viable monitoring system must be capable of detecting possible intrusion attempts or network malfunctions and alerting operating and security personnel. This report documents the results of an evaluation of the Magnavox CATV Systems Inc. Digital System Sentry software for network monitoring. Recommendations are made on its possible future role in broadband LAN security monitoring throughout the Nuclear Weapons Complex.

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As network bandwidth continues to grow and longer paths are used to exchange large scientific data between storage systems and GRID computation, it has become increasingly obvious that there is a need to deploy a packet drop avoidance mechanism into network transmission protocols. Current end-to-end congestion avoidance mechanisms used in Transmission Control Protocol (TCP) have worked well on low bandwidth delay product networks, but with newer high-bandwidth delay networks they have shown to be inefficient and prone to unstable. This is largely due to increased network bandwidth coupled with changes in internet traffic patterns. These changes come from a variety of new network applications that are being developed to take advantage of the increased network bandwidth. This paper will examine the end-to-end congestion avoidance mechanism and ...

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A system and method for generating global asynchronous signals in a computing structure. Particularly, a global interrupt and barrier network is implemented that implements logic for generating global interrupt and barrier signals for controlling global asynchronous operations performed by processing elements at selected processing nodes of a computing structure in accordance with a processing algorithm; and includes the physical interconnecting of the processing nodes for communicating the global interrupt and barrier signals to the elements via low-latency paths. The global asynchronous signals respectively initiate interrupt and barrier operations at the processing nodes at times selected for optimizing performance of the processing algorithms. In one embodiment, the global interrupt and barrier network is implemented in a scalable, massively parallel supercomputing device structure comprising a plurality of processing nodes interconnected ...

CERN Document Server

We consider network coding for networks experiencing worst-case bit-flip errors, and argue that this is a reasonable model for highly dynamic wireless network transmissions. We demonstrate that in this setup prior network error-correcting schemes can be arbitrarily far from achieving the optimal network throughput. We propose a new metric for errors under this model. Using this metric, we prove a new Hamming-type upper bound on the network capacity. We also show a commensurate lower bound based on GV-type codes that can be used for error-correction. The codes used to attain the lower bound are non-coherent (do not require prior knowledge of network topology). The end-to-end nature of our design enables our codes to be overlaid on classical distributed random linear network codes. Further, we free internal nodes from ...

CERN Document Server

Tensor network states are used to approximate ground states of local Hamiltonians on a lattice in D spatial dimensions. Different types of tensor network states can be seen to generate different geometries. Matrix product states (MPS) in D=1 dimensions, as well as projected entangled pair states (PEPS) in D>1 dimensions, reproduce the D-dimensional physical geometry of the lattice model; in contrast, the multi-scale entanglement renormalization ansatz (MERA) generates a (D+1)-dimensional holographic geometry. Here we focus on homogeneous tensor networks, where all the tensors in the network are copies of the same tensor, and argue that certain structural properties of the resulting many-body states are preconditioned by the geometry of the tensor network and are therefore largely independent of the choice of variational parameters. Indeed, the asymptotic decay of correlations in ...

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The Advanced Networking Integration Department at Sandia National Laboratories has used the annual Supercomputing conference sponsored by the IEEE and ACM for the past three years as a forum to demonstrate and focus communication and networking developments. For Supercomputing `95, Sandia elected: to demonstrate the functionality and capability of an AT&T Globeview 20Gbps Asynchronous Transfer Mode (ATM) switch, which represents the core of Sandia`s corporate network, to build and utilize a three node 622 megabit per second Paragon network, and to extend the DOD`s ACTS ATM Internet from Sandia, New Mexico to the conference`s show floor in San Diego, California, for video demonstrations. This paper documents those accomplishments, discusses the details of their implementation, and describes how these demonstrations supports Sandia`s overall strategies in ATM networking.

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We describe a large class of chemical reaction networks, those endowed with a subtle structural property called concordance. We show that the class of concordant networks coincides precisely with the class of networks which, when taken with any weakly monotonic kinetics, invariably give rise to kinetic systems that are injective --- a quality that, among other things, precludes the possibility of switch-like transitions between distinct positive steady states. We also provide persistence characteristics of concordant networks, instability implications of discordance, and consequences of stronger variants of concordance. Some of our results are in the spirit of recent ones by Banaji and Craciun, but here we do not require that every species suffer a degradation reaction. This is especially important in studying biochemical networks, for which it is rare to have all species degrade.

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To determine if barbiturates would protect brain at high doses of radiation, survival rates in rats that received whole-brain x-irradiation during pentobarbital- or lidocaine-induced anesthesia were compared with those of control animals that received no medication and of animals anesthetized with ketamine. The animals were shielded so that respiratory and digestive tissues would not be damaged by the radiation. Survival rates in rats that received whole-brain irradiation as a single 7500-rad dose under pentobarbital- or lidocaine-induced anesthesia was increased from between from 0% and 20% to between 45% and 69% over the 40 days of observation compared with the other two groups (p less than 0.007). Ketamine anesthesia provided no protection. There were no notable differential effects upon non-neural tissues, suggesting that pentobarbital afforded protection through modulation of ambient neural activity during radiation exposure. ...

International Nuclear Information System (INIS)

Over the last few years it has become increasingly clear that low energy, but high precision experiments provide a powerful and complementary window to physics beyond the Standard Model. In this note we illuminate this by using minicharged particles as an example. We argue that minicharged particles arise naturally in extensions of the Standard Model. Compatibility with charge quantization arguments suggests that minicharged particles typically arise together with a massless hidden sector U(1) gauge field. We present several low energy experiments employing strong lasers, electric and magnetic fields that can be used to search for (light) minicharged particles and their accompanying U(1) gauge boson.

CERN Document Server

The full theory and the semiclassical description of loop quantum cosmology (LQC) have been studied in the Friedmann-Robertson-Walker and Bianchi I models. As an extension to include both anisotropy and intrinsic curvature, this paper investigates the cosmological model of Kantowski-Sachs spacetime with a free massless scalar field at the level of phenomenological dynamics with the LQC discreteness corrections. The LQC corrections are implemented in two different improved quantization schemes. In both schemes, the big bang and big crunch singularities of the classical solution are resolved and replaced by the big bounces when the area or volume scale factor approaches the critical values in the Planck regime measured by the reference of the scalar field momentum. Symmetries of scaling are also noted and suggest that the fundamental spatial scale (area gap) may give rise to a temporal scale. The bouncing scenarios are in an analogous fashion of the Bianchi I model, ...

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The development of nano/molecular devices will require atomic-sized electrical contacts or nano metric conductors for wiring. As metal nano wires exhibit quantized conductance at room temperature, quantum transport effects will play an important role in the practical implementation of nano devices. As copper is currently used as interconnecting metal in standard microelectronics, the characterization of Cu nano wire properties deserves special attention. In this work, we show a detailed study of structural and electronic properties of atomic-sized Cu wires. In particular, we have established a complete correlation between the conductance and the structure by associating real-time atomic resolution transmission electron microscopy imaging with molecular dynamic simulations, conductance measurements and conductance calculations. Our study has revealed the structural relaxation of Cu wires forming a pentagonal atomic arrangement along the [110] direction that allows a ...

CERN Document Server

In this paper we examine the relationship between covariance and unitarity for quantum gravity in Ashtekar variables. A usual description would discard half of the original Lorentz group, in exchange for the resulting simplifications of general relativity. We start by quantizing a trivial SL(2,C) gauge theory resulting in a nonunitary covariant theory. By the addition of a total time derivative we transform this into a unitary theory of the Ashtekar description of gravity with complete accountability of the degrees of freedom. We find that covariance on the spacetime level bears a direct relationship to covariance on the level ofthe quantum fields themselves. This procedure can in principle be applied to any totally constrained system, and bears a resemblance to the Gupta--Bleuler method. Finally, we make some observation regarding the loop representation of the SL(2,C) connection.

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The effective approach to quantum dynamics allows a reformulation of the Dirac quantization procedure for constrained systems in terms of an infinite-dimensional constrained system of classical type. For semiclassical approximations, the quantum constrained system can be truncated to finite size and solved by the reduced phase space or gauge-fixing methods. In particular, the classical feasibility of local internal times is directly generalized to quantum systems, overcoming the main difficulties associated with the general problem of time in the semiclassical realm. The key features of local internal times and the procedure of patching global solutions using overlapping intervals of local internal times are described and illustrated by two quantum mechanical examples. The choice of time is tantamount to a choice of gauge at the effective level and changing the clock is, therefore, equivalent to a gauge transformation. This article complements the conceptual ...

Science.gov (United States)

We report the characteristics of visible vertical cavity surface emitting laser diodes. Wafers are grown such that the Fabry--Perot resonance wavelength changes with position from 690 to 620 nm, overlapping to varying degrees with the [ital n]=1 and [ital n]=2 quantum well gain peaks at [similar to]670 and 650 nm. Gain guided devices are tested across the entire wafer, and pulsed room temperature lasing is observed from 634.6 to 663.2 nm. Our results suggest that gain contributions from the second quantized state are required to overcome high cavity losses in order to achieve lasing.

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There is a thermal range for the operation of neural circuits beyond which nervous system function is compromised. Locusta migratoria is native to the semiarid regions of the world and provides an excellent model for studying neural phenomena. In this organism previous exposure to sublethal high temperatures (heat shock, HS) can protect neuronal function against future hyperthermia but, unlike many organisms, the profound physiological adaptations are not accompanied by a robust increase of Hsp70 transcript or protein in the nervous system. We compared Hsp70 increase following HS in the tissues of isolated and gregarious locusts to investigate the effect of population density. We also localized Hsp70 in the metathoracic ganglion (MTG) of gregarious locusts to determine if HS affects Hsp70 ...