WorldWideScience

Sample records for networks based simplified

  1. A Simplified Multiband Sampling and Detection Method Based on MWC Structure for Mm Wave Communications in 5G Wireless Networks

    Directory of Open Access Journals (Sweden)

    Min Jia

    2015-01-01

    Full Text Available The millimeter wave (mm wave communications have been proposed to be an important part of the 5G mobile communication networks, and it will bring more difficulties to signal processing, especially signal sampling, and also cause more pressures on hardware devices. In this paper, we present a simplified sampling and detection method based on MWC structure by using the idea of blind source separation for mm wave communications, which can avoid the challenges of signal sampling brought by high frequencies and wide bandwidth for mm wave systems. This proposed method takes full advantage of the beneficial spectrum aliasing to achieve signal sampling at sub-Nyquist rate. Compared with the traditional MWC system, it provides the exact quantity of sampling channels which is far lower than that of MWC. In the reconstruction stage, the proposed method simplifies the computational complexity by exploiting simple linear operations instead of CS recovery algorithms and provides more stable performance of signal recovery. Moreover, MWC structure has the ability to apply to different bands used in mm wave communications by mixed processing, which is similar to spread spectrum technology.

  2. Pattern Classification using Simplified Neural Networks

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    In recent years, many neural network models have been proposed for pattern classification, function approximation and regression problems. This paper presents an approach for classifying patterns from simplified NNs. Although the predictive accuracy of ANNs is often higher than that of other methods or human experts, it is often said that ANNs are practically "black boxes", due to the complexity of the networks. In this paper, we have an attempted to open up these black boxes by reducing the complexity of the network. The factor makes this possible is the pruning algorithm. By eliminating redundant weights, redundant input and hidden units are identified and removed from the network. Using the pruning algorithm, we have been able to prune networks such that only a few input units, hidden units and connections left yield a simplified network. Experimental results on several benchmarks problems in neural networks show the effectiveness of the proposed approach with good generalization ability.

  3. A novel DNA sequence similarity calculation based on simplified pulse-coupled neural network and Huffman coding

    Science.gov (United States)

    Jin, Xin; Nie, Rencan; Zhou, Dongming; Yao, Shaowen; Chen, Yanyan; Yu, Jiefu; Wang, Quan

    2016-11-01

    A novel method for the calculation of DNA sequence similarity is proposed based on simplified pulse-coupled neural network (S-PCNN) and Huffman coding. In this study, we propose a coding method based on Huffman coding, where the triplet code was used as a code bit to transform DNA sequence into numerical sequence. The proposed method uses the firing characters of S-PCNN neurons in DNA sequence to extract features. Besides, the proposed method can deal with different lengths of DNA sequences. First, according to the characteristics of S-PCNN and the DNA primary sequence, the latter is encoded using Huffman coding method, and then using the former, the oscillation time sequence (OTS) of the encoded DNA sequence is extracted. Simultaneously, relevant features are obtained, and finally the similarities or dissimilarities of the DNA sequences are determined by Euclidean distance. In order to verify the accuracy of this method, different data sets were used for testing. The experimental results show that the proposed method is effective.

  4. Interferometric phase reconstruction using simplified coherence network

    Science.gov (United States)

    Zhang, Kui; Song, Ruiqing; Wang, Hui; Wu, Di; Wang, Hua

    2016-09-01

    Interferometric time-series analysis techniques, which extend the traditional differential radar interferometry, have demonstrated a strong capability for monitoring ground surface displacement. Such techniques are able to obtain the temporal evolution of ground deformation within millimeter accuracy by using a stack of synthetic aperture radar (SAR) images. In order to minimize decorrelation between stacked SAR images, the phase reconstruction technique has been developed recently. The main idea of this technique is to reform phase observations along a SAR stack by taking advantage of a maximum likelihood estimator which is defined on the coherence matrix estimated from each target. However, the phase value of a coherence matrix element might be considerably biased when its corresponding coherence is low. In this case, it will turn to an outlying sample affecting the corresponding phase reconstruction process. In order to avoid this problem, a new approach is developed in this paper. This approach considers a coherence matrix element to be an arc in a network. A so-called simplified coherence network (SCN) is constructed to decrease the negative impact of outlying samples. Moreover, a pointed iterative strategy is designed to resolve the transformed phase reconstruction problem defined on a SCN. For validation purposes, the proposed method is applied to 29 real SAR images. The results demonstrate that the proposed method has an excellent computational efficiency and could obtain more reliable phase reconstruction solutions compared to the traditional method using phase triangulation algorithm.

  5. Simplified Scheduling for Underwater Acoustic Networks

    Directory of Open Access Journals (Sweden)

    Wouter van Kleunen

    2013-01-01

    Full Text Available The acoustic propagation speed under water poses significant challenges to the design of underwater sensor networks and their medium access control protocols. Similar to the air, scheduling transmissions under water has significant impact on throughput, energy consumption, and reliability. In this paper we present an extended set of simplified scheduling constraints which allows easy scheduling of underwater acoustic communication. We also present two algorithms for scheduling communications, i.e. a centralized scheduling approach and a distributed scheduling approach. The centralized approach achieves the highest throughput while the distributed approach aims to minimize the computation and communication overhead. We further show how the centralized scheduling approach can be extended with transmission dependencies to reduce the end-to-end delay of packets. We evaluate the performance of the centralized and distributed scheduling approaches using simulation. The centralized approach outperforms the distributed approach in terms of throughput, however we also show the distributed approach has significant benefits in terms of communication and computational overhead required to setup the schedule. We propose a novel way of estimating the performance of scheduling approaches using the ratio of modulation time and propagation delay. We show the performance is largely dictated by this ratio, although the number of links to be scheduled also has a minor impact on the performance.

  6. A Hybrid Approach for Detecting Stego Content in Corporate Mail Using Neural Network Based Simplified-Data Encryption Standard Algorithm

    Directory of Open Access Journals (Sweden)

    P. T. Anitha

    2012-01-01

    Full Text Available Problem statement: The major growth of information technology is based on the security measures implemented. Steganography is a method which is used to give high level security. Approach: Today, email management and email authenticity must be unquestionable with strong chains of custody, constant availability and tamper-proof security. A secure communication can be achieved through neural based steganography. Email is insecure. Results: This research developed an application which can check the Email content of corporate mails by S-DES algorithm along with the neural networks back propagation approach. A new filtering algorithm is also developed which can used to extract only the JPG images from the corporate emails. Experimental research shows that this algorithm is more accurate and reliable than the conventional methods. Conclusion: We anticipate that this study can also give a clear picture of the current trends in Steganography and the experimental results indicate this method is valid in steganalysis. This method can be used for internet/network security.

  7. Simplified LQG Control with Neural Networks

    DEFF Research Database (Denmark)

    Sørensen, O.

    1997-01-01

    A new neural network application for non-linear state control is described. One neural network is modelled to form a Kalmann predictor and trained to act as an optimal state observer for a non-linear process. Another neural network is modelled to form a state controller and trained to produce...

  8. Simplified scheduling for underwater acoustic networks

    NARCIS (Netherlands)

    Kleunen, van Wouter; Meratnia, Nirvana; Havinga, Paul J.M.

    2013-01-01

    The acoustic propagation speed under water poses significant challenges to the design of underwater sensor networks and their medium access control protocols. Similar to the air, scheduling transmissions under water has significant impact on throughput, energy consumption, and reliability. In this p

  9. Simplified scheduling for underwater acoustic networks

    NARCIS (Netherlands)

    van Kleunen, W.A.P.; Meratnia, Nirvana; Havinga, Paul J.M.

    The acoustic propagation speed under water poses significant challenges to the design of underwater sensor networks and their medium access control protocols. Similar to the air, scheduling transmissions under water has significant impact on throughput, energy consumption, and reliability. In this

  10. Simplified design procedure for base isolation system

    Energy Technology Data Exchange (ETDEWEB)

    Takayama, Mineo; Tada, Hideyuki [Fukuoka Univ. (Japan). Faculty of Engineering

    1995-12-01

    This paper presents a simplified design procedure which incorporates an existing response prediction method for base isolated buildings into design methods for isolation devices (rubber bearings and hysteresis dampers). The procedure enables a designer to easily identify the relationship between tile seismic behavior of base-isolated buildings and the characteristics of isolation devices. The prediction method, proposed by Prof. Akiyama, is based on energy balance between the total input seismic energy and the energy absorbed by the isolation devices. The method is very accurate. The design methods for devices were developed by authors based on experimental and finite element analysis results.

  11. A Simplified Mobile Ad Hoc Network Structure for Helicopter Communication

    Directory of Open Access Journals (Sweden)

    Abdeldime Mohamed Salih Abdelgader

    2016-01-01

    Full Text Available There are a number of volunteer and statutory organizations who are capable of conducting an emergency response using helicopters. Rescue operations require a rapidly deployable high bandwidth network to coordinate necessary relief efforts between rescue teams on the ground and helicopters. Due to massive destruction and loss of services, ordinary communication infrastructures may collapse in these situations. Consequently, information exchange becomes one of the major challenges in these circumstances. Helicopters can be also employed for providing many services in rugged environments, military applications, and aerial photography. Ad hoc network can be used to provide alternative communication link between a set of helicopters, particularly in case of significant amount of data required to be shared. This paper addresses the ability of using ad hoc networks to support the communication between a set of helicopters. A simplified network structure model is presented and extensively discussed. Furthermore, a streamlined routing algorithm is proposed. Comprehensive simulations are conducted to evaluate the proposed routing algorithm.

  12. Simplified CBA Concept and Express Choice Method for Integrated Network Management System

    Directory of Open Access Journals (Sweden)

    Mohammad Al Rawajbeh

    2016-05-01

    Full Text Available The process of choosing and integrating a network management system (NMS to an existing computer network became a big question due to the complexity of used technologies and the variety of NMS options. Most of computer networks are being developed according to their internal rules in cloud environments. The use of NMS requires not only infrastructural changes, consequently increasing the cost of integration and maintenance, but also increases the risk of potential failures. In this paper, conception and method of express choice to implement and integrate a network management system are presented. Review of basic methods of cost analysis for IT systems is presented. The simplified conception of cost benefits analysis (CBA is utilized as a basis of the offered method. A final estimation is based on three groups of parameters: parameters of expected integration risk evaluation, expected effect and level of completed management tasks. The explanation of the method is provided via example.

  13. A simplified dynamic model for existing buildings using CTF and thermal network models

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Xinhua; Wang, Shengwei [Department of Building Services Engineering, The Hong Kong Polytechnic University (China)

    2008-09-15

    An alternative simplified building model is developed to describe existing building system aiming at providing performance benchmark for performance evaluation and diagnosis at building level and performance prediction for air-conditioning system optimal control. This model combines detailed physical models of building envelopes and a thermal network model of building internal mass. The detailed physical models are the CTF (Conduction Transfer Function) models of building envelopes based on the easily available detailed physical properties of exterior walls and roof. The thermal network model is the 2R2C model, and its parameters are estimated and optimized using genetic algorithm with short-term monitored operation data. The parameter optimization of the simplified building internal mass model (2R2C) and the simplified dynamic building model (i.e., CTF+2R2C model) are validated in a high-rising commercial office building under various weather conditions. This CTF+2R2C model is an alternative modeling approach for simulating the overall building dynamic thermal performance when CTF model is chosen to model the building envelope. (author)

  14. Simplifying Development and Management of Software-Defined Networks

    OpenAIRE

    Perešíni, Peter

    2016-01-01

    Computer networks are an important part of our life. Yet, they are traditionally hard to manage and operate. The recent shift to Software-Defined Networking (SDN) is promised to change the way in which the networks are run by their operators. However, SDN is still in its initial stage and as such it lags behind traditional networks in terms of correctness and reliability; both the properties being vitally important for the network operators. Meanwhile, general purpose computers were followin...

  15. Power flow tracing in a simplified highly renewable European electricity network

    CERN Document Server

    Tranberg, Bo; Rodriguez, Rolando A; Andresen, Gorm B; Schäfer, Mirko; Greiner, Martin

    2015-01-01

    The increasing transmission capacity needs in a future energy system raise the question how associated costs should be allocated to the users of a strengthened power grid. In contrast to straightforward oversimplified methods, a flow tracing based approach provides a fair and consistent nodal usage and thus cost assignment of transmission investments. This technique follows the power flow through the network and assigns the link capacity usage to the respective sources or sinks using a diffusion-like process, thus taking into account the underlying network structure and injection pattern. As a showcase, we apply power flow tracing to a simplified model of the European electricity grid with a high share of renewable wind and solar power generation, based on long-term weather and load data with an hourly temporal resolution.

  16. A simplified holography based superresolution system

    Science.gov (United States)

    Mudassar, Asloob Ahmad

    2015-12-01

    In this paper we are proposing a simple idea based on holography to achieve superresolution. The object is illuminated by three fibers which maintain the mutual coherence between the light waves. The object in-plane rotation along with fiber-based illumination is used to achieve superresolution. The object in a 4f optical system is illuminated by an on-axis fiber to make the central part of the object's spectrum to the pass through the limiting square-aperture placed at the Fourier plane and the corresponding hologram of the image is recorded at the image plane. The on-axis fiber is switched off and the two off axis fibers (one positioned on the vertical axis and the other positioned on diagonal) are switched on one by one for each orientation of the object position. Four orientations of object in-plane rotation are used differing in angle by 90°. This will allow the recording of eight holographic images in addition to the one recorded with on-axis fiber. The three fibers are at the vertices of a right angled isosceles triangle and are aligned toward the centre of the lens following the fiber plane to generate plane waves for object illumination. The nine holographic images are processed for construction of object's original spectrum, the inverse of which gives the super-resolved image of the original object. Mathematical modeling and simulations are reported.

  17. A simplified recurrent neural network for pseudoconvex optimization subject to linear equality constraints

    Science.gov (United States)

    Qin, Sitian; Fan, Dejun; Su, Peng; Liu, Qinghe

    2014-04-01

    In this paper, the optimization techniques for solving pseudoconvex optimization problems are investigated. A simplified recurrent neural network is proposed according to the optimization problem. We prove that the optimal solution of the optimization problem is just the equilibrium point of the neural network, and vice versa if the equilibrium point satisfies the linear constraints. The proposed neural network is proven to be globally stable in the sense of Lyapunov and convergent to an exact optimal solution of the optimization problem. A numerical simulation is given to illustrate the global convergence of the neural network. Applications in business and chemistry are given to demonstrate the effectiveness of the neural network.

  18. 76 FR 7102 - Simplified Network Application Processing System, On-line Registration and Account Maintenance

    Science.gov (United States)

    2011-02-09

    ... Regulatory Flexibility, Small Business, and Job Creation (January 18, 2011). DATES: Effective date: March 11... 12866 and Presidential Memorandum on Regulatory Flexibility, Small Business, and Job Creation (January... CIV. (b) Registration and use of BIS's Simplified Network Applications System--Redesign...

  19. Simplified Physics Based Models Research Topical Report on Task #2

    Energy Technology Data Exchange (ETDEWEB)

    Mishra, Srikanta; Ganesh, Priya

    2014-10-31

    We present a simplified-physics based approach, where only the most important physical processes are modeled, to develop and validate simplified predictive models of CO2 sequestration in deep saline formation. The system of interest is a single vertical well injecting supercritical CO2 into a 2-D layered reservoir-caprock system with variable layer permeabilities. We use a set of well-designed full-physics compositional simulations to understand key processes and parameters affecting pressure propagation and buoyant plume migration. Based on these simulations, we have developed correlations for dimensionless injectivity as a function of the slope of fractional-flow curve, variance of layer permeability values, and the nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. Similar correlations are also developed to predict the average pressure within the injection reservoir, and the pressure buildup within the caprock.

  20. A Simplified Self-Consistent Probabilities Framework to Characterize Percolation Phenomena on Interdependent Networks : An Overview

    CERN Document Server

    Feng, Ling; Hu, Yanqing

    2015-01-01

    Interdependent networks are ubiquitous in our society, ranging from infrastructure to economics, and the study of their cascading behaviors using percolation theory has attracted much attention in the recent years. To analyze the percolation phenomena of these systems, different mathematical frameworks have been proposed including generating functions, eigenvalues among some others. These different frameworks approach the phase transition behaviors from different angles, and have been very successful in shaping the different quantities of interest including critical threshold, size of the giant component, order of phase transition and the dynamics of cascading. These methods also vary in their mathematical complexity in dealing with interdependent networks that have additional complexity in terms of the correlation among different layers of networks or links. In this work, we review a particular approach of simple self-consistent probability equations, and illustrate that it can greatly simplify the mathemati...

  1. Evaluating performances of simplified physically based models for landslide susceptibility

    Directory of Open Access Journals (Sweden)

    G. Formetta

    2015-12-01

    Full Text Available Rainfall induced shallow landslides cause loss of life and significant damages involving private and public properties, transportation system, etc. Prediction of shallow landslides susceptible locations is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, and statistics. Usually to accomplish this task two main approaches are used: statistical or physically based model. Reliable models' applications involve: automatic parameters calibration, objective quantification of the quality of susceptibility maps, model sensitivity analysis. This paper presents a methodology to systemically and objectively calibrate, verify and compare different models and different models performances indicators in order to individuate and eventually select the models whose behaviors are more reliable for a certain case study. The procedure was implemented in package of models for landslide susceptibility analysis and integrated in the NewAge-JGrass hydrological model. The package includes three simplified physically based models for landslides susceptibility analysis (M1, M2, and M3 and a component for models verifications. It computes eight goodness of fit indices by comparing pixel-by-pixel model results and measurements data. Moreover, the package integration in NewAge-JGrass allows the use of other components such as geographic information system tools to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. The system was applied for a case study in Calabria (Italy along the Salerno-Reggio Calabria highway, between Cosenza and Altilia municipality. The analysis provided that among all the optimized indices and all the three models, the optimization of the index distance to perfect classification in the receiver operating characteristic plane (D2PC coupled with model M3 is the best modeling solution for our test case.

  2. Evaluating performances of simplified physically based models for landslide susceptibility

    Science.gov (United States)

    Formetta, G.; Capparelli, G.; Versace, P.

    2015-12-01

    Rainfall induced shallow landslides cause loss of life and significant damages involving private and public properties, transportation system, etc. Prediction of shallow landslides susceptible locations is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, and statistics. Usually to accomplish this task two main approaches are used: statistical or physically based model. Reliable models' applications involve: automatic parameters calibration, objective quantification of the quality of susceptibility maps, model sensitivity analysis. This paper presents a methodology to systemically and objectively calibrate, verify and compare different models and different models performances indicators in order to individuate and eventually select the models whose behaviors are more reliable for a certain case study. The procedure was implemented in package of models for landslide susceptibility analysis and integrated in the NewAge-JGrass hydrological model. The package includes three simplified physically based models for landslides susceptibility analysis (M1, M2, and M3) and a component for models verifications. It computes eight goodness of fit indices by comparing pixel-by-pixel model results and measurements data. Moreover, the package integration in NewAge-JGrass allows the use of other components such as geographic information system tools to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. The system was applied for a case study in Calabria (Italy) along the Salerno-Reggio Calabria highway, between Cosenza and Altilia municipality. The analysis provided that among all the optimized indices and all the three models, the optimization of the index distance to perfect classification in the receiver operating characteristic plane (D2PC) coupled with model M3 is the best modeling solution for our test case.

  3. Simplified neural networks for solving linear least squares and total least squares problems in real time.

    Science.gov (United States)

    Cichocki, A; Unbehauen, R

    1994-01-01

    In this paper a new class of simplified low-cost analog artificial neural networks with on chip adaptive learning algorithms are proposed for solving linear systems of algebraic equations in real time. The proposed learning algorithms for linear least squares (LS), total least squares (TLS) and data least squares (DLS) problems can be considered as modifications and extensions of well known algorithms: the row-action projection-Kaczmarz algorithm and/or the LMS (Adaline) Widrow-Hoff algorithms. The algorithms can be applied to any problem which can be formulated as a linear regression problem. The correctness and high performance of the proposed neural networks are illustrated by extensive computer simulation results.

  4. Effects of simplifying fracture network representation on inert chemical migration in fracture-controlled aquifers

    Science.gov (United States)

    Wellman, T.P.; Shapiro, A.M.; Hill, M.C.

    2009-01-01

    While it is widely recognized that highly permeable 'large-scale' fractures dominate chemical migration in many fractured aquifers, recent studies suggest that the pervasive 'small-scale' fracturing once considered of less significance can be equally important for characterizing the spatial extent and residence time associated with transport processes. A detailed examination of chemical migration through fracture-controlled aquifers is used to advance this conceptual understanding. The influence of fracture structure is evaluated by quantifying the effects to transport caused by a systematic removal of fractures from three-dimensional discrete fracture models whose attributes are derived from geologic and hydrologic conditions at multiple field sites. Results indicate that the effects to transport caused by network simplification are sensitive to the fracture network characteristics, degree of network simplification, and plume travel distance, but primarily in an indirect sense since correlation to individual attributes is limited. Transport processes can be 'enhanced' or 'restricted' from network simplification meaning that the elimination of fractures may increase or decrease mass migration, mean travel time, dispersion, and tailing of the concentration plume. The results demonstrate why, for instance, chemical migration may not follow the classic advection-dispersion equation where dispersion approximates the effect of the ignored geologic structure as a strictly additive process to the mean flow. The analyses further reveal that the prediction error caused by fracture network simplification is reduced by at least 50% using the median estimate from an ensemble of simplified fracture network models, and that the error from network simplification is at least 70% less than the stochastic variability from multiple realizations. Copyright 2009 by the American Geophysical Union.

  5. Simplified theory of plastic zones based on Zarka's method

    CERN Document Server

    Hübel, Hartwig

    2017-01-01

    The present book provides a new method to estimate elastic-plastic strains via a series of linear elastic analyses. For a life prediction of structures subjected to variable loads, frequently encountered in mechanical and civil engineering, the cyclically accumulated deformation and the elastic plastic strain ranges are required. The Simplified Theory of Plastic Zones (STPZ) is a direct method which provides the estimates of these and all other mechanical quantities in the state of elastic and plastic shakedown. The STPZ is described in detail, with emphasis on the fact that not only scientists but engineers working in applied fields and advanced students are able to get an idea of the possibilities and limitations of the STPZ. Numerous illustrations and examples are provided to support the reader's understanding.

  6. A random network based, node attraction facilitated network evolution method

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2016-03-01

    Full Text Available In present study, I present a method of network evolution that based on random network, and facilitated by node attraction. In this method, I assume that the initial network is a random network, or a given initial network. When a node is ready to connect, it tends to link to the node already owning the most connections, which coincides with the general rule (Barabasi and Albert, 1999 of node connecting. In addition, a node may randomly disconnect a connection i.e., the addition of connections in the network is accompanied by the pruning of some connections. The dynamics of network evolution is determined of the attraction factor Lamda of nodes, the probability of node connection, the probability of node disconnection, and the expected initial connectance. The attraction factor of nodes, the probability of node connection, and the probability of node disconnection are time and node varying. Various dynamics can be achieved by adjusting these parameters. Effects of simplified parameters on network evolution are analyzed. The changes of attraction factor Lamda can reflect various effects of the node degree on connection mechanism. Even the changes of Lamda only will generate various networks from the random to the complex. Therefore, the present algorithm can be treated as a general model for network evolution. Modeling results show that to generate a power-law type of network, the likelihood of a node attracting connections is dependent upon the power function of the node's degree with a higher-order power. Matlab codes for simplified version of the method are provided.

  7. Diagnosis of vertebral fractures in children: is a simplified algorithm-based qualitative technique reliable?

    Energy Technology Data Exchange (ETDEWEB)

    Adiotomre, E. [Sheffield Teaching Hospitals NHS Foundation Trust UK, Radiology Department, Sheffield (United Kingdom); Sheffield Children' s NHS Foundation Trust, Radiology Department, Sheffield (United Kingdom); Summers, L.; Digby, M. [University of Sheffield UK, Sheffield Medical School, Sheffield (United Kingdom); Allison, A.; Walters, S.J. [University of Sheffield UK, School of Health and Related Research, Sheffield (United Kingdom); Broadley, P.; Lang, I. [Sheffield Children' s NHS Foundation Trust, Radiology Department, Sheffield (United Kingdom); Offiah, A.C. [Sheffield Children' s NHS Foundation Trust, Radiology Department, Sheffield (United Kingdom); University of Sheffield UK, Academic Unit of Child Health, Sheffield (United Kingdom)

    2016-05-15

    Identification of osteoporotic vertebral fractures allows treatment opportunity reducing future risk. There is no agreed standardised method for diagnosing paediatric vertebral fractures. To evaluate the precision of a modified adult algorithm-based qualitative (ABQ) technique, applicable to children with primary or secondary osteoporosis. Three radiologists independently assessed lateral spine radiographs of 50 children with suspected reduction in bone mineral density using a modified ABQ scoring system and following simplification to include only clinically relevant parameters, a simplified ABQ score. A final consensus of all observers using simplified ABQ was performed as a reference standard for fracture characterisation. Kappa was calculated for interobserver agreement of the components of both scoring systems and intraobserver agreement of simplified ABQ based on a second read of 29 randomly selected images. Interobserver Kappa for modified ABQ scoring for fracture detection, severity and shape ranged from 0.34 to 0.49 Kappa for abnormal endplate and position assessment was 0.27 to 0.38. Inter- and intraobserver Kappa for simplified ABQ scoring for fracture detection and grade ranged from 0.37 to 0.46 and 0.45 to 0.56, respectively. Inter- and intraobserver Kappa for affected endplate ranged from 0.31 to 0.41 and 0.45 to 0.51, respectively. Subjectively, observers' felt simplified ABQ was easier and less time-consuming. Observer reliability of modified and simplified ABQ was similar, with slight to moderate agreement for fracture detection and grade/severity. Due to subjective preference for simplified ABQ, we suggest its use as a semi-objective measure of diagnosing paediatric vertebral fractures. (orig.)

  8. FloodAlert: a simplified radar-based EWS for urban flood warning

    OpenAIRE

    Llort Pavon, Xavier; Sánchez-Diezma Guijarro, Rafael; Rodríguez, Álvaro; De Sancho, David; Berenguer Ferrer, Marc; Sempere Torres, Daniel

    2014-01-01

    In this work we present FloodAlert, a simplified flood Early Warning System [EWS] based on the use of radar observations and radar nowcasting to issue local flood warnings. It is a web-based platform and it is complemented with a flexible and powerful dissemination module.

  9. A simplified gis-based model for large wood recruitment and connectivity in mountain basins

    Science.gov (United States)

    Franceschi, Silvia; Antonello, Andrea; Vela, Ana Lucia; Cavalli, Marco; Crema, Stefano; Comiti, Francesco; Tonon, Giustino

    2015-04-01

    During the last 50 years in the Alps the decline of the rural and forest economy and at the depopulation of the mountain areas caused the progressive abandon of the land in general and in particular of the riparian zones and the consequent increment of the vegetation extension. On one hand the wood increases the availability of organic matter and has positive effects on mountain river systems. However, during flooding events large woods that reach the stream cause the clogging of bridges with an increase of flood hazard. The approach to the evaluation of the availability of large wood during flooding events is still a challenge. There are models that simulate the propagation of the logs downstream, but the evaluation of the trees that can reach the stream is still done using simplified GIS procedures. These procedures are the base for our research which will include LiDAR derived information on vegetation to evaluate large wood recruitment extreme events. Within the last Google Summer of Code (2014) we developed a set of tools to evaluate large wood recruitment and propagation along the channel network based on a simplified methodology for monitoring and modeling large wood recruitment and transport in mountain basins implemented by Lucía et 2014. These tools are integrated in the JGrassTools project as a dedicated section in the Hydro-Geomorphology library. The section LWRecruitment contains 10 simple modules that allow the user to start from very simple information related to geomorphology, flooding areas and vegetation cover and obtain a map of the most probable critical sections on the streams. The tools cover the two main aspects related to the iteration of large wood with the rivers: the recruitment mechanisms and the propagation downstream. While the propagation tool is very simple and does not consider the hydrodynamic of the problem, the recruitment algorithms are more specific and consider the influence of hillslopes stability and the flooding extension

  10. A Hierarchical Sensor Network Based on Voronoi Diagram

    Institute of Scientific and Technical Information of China (English)

    SHANG Rui-qiang; ZHAO Jian-li; SUN Qiu-xia; WANG Guang-xing

    2006-01-01

    A hierarchical sensor network is proposed which places the sensing and routing capacity at different layer nodes.It thus simplifies the hardware design and reduces cost. Adopting Voronoi diagram in the partition of backbone network,a mathematical model of data aggregation based on hierarchical architecture is given. Simulation shows that the number of transmission data packages is sharply cut down in the network, thus reducing the needs in the bandwidth and energy resources and is thus well adapted to sensor networks.

  11. Simplified Atmospheric Dispersion Model andModel Based Real Field Estimation System ofAir Pollution

    Institute of Scientific and Technical Information of China (English)

    2015-01-01

    The atmospheric dispersion model has been well developed and applied in pollution emergency and prediction. Based on thesophisticated air diffusion model, this paper proposes a simplified model and some optimization about meteorological andgeological conditions. The model is suitable for what is proposed as Real Field Monitor and Estimation system. The principle ofsimplified diffusion model and its optimization is studied. The design of Real Field Monitor system based on this model and itsfundamental implementations are introduced.

  12. Recovering kinetics from a simplified protein folding model using replica exchange simulations: a kinetic network and effective stochastic dynamics.

    Science.gov (United States)

    Zheng, Weihua; Andrec, Michael; Gallicchio, Emilio; Levy, Ronald M

    2009-08-27

    We present an approach to recover kinetics from a simplified protein folding model at different temperatures using the combined power of replica exchange (RE), a kinetic network, and effective stochastic dynamics. While RE simulations generate a large set of discrete states with the correct thermodynamics, kinetic information is lost due to the random exchange of temperatures. We show how we can recover the kinetics of a 2D continuous potential with an entropic barrier by using RE-generated discrete states as nodes of a kinetic network. By choosing the neighbors and the microscopic rates between the neighbors appropriately, the correct kinetics of the system can be recovered by running a kinetic simulation on the network. We fine-tune the parameters of the network by comparison with the effective drift velocities and diffusion coefficients of the system determined from short-time stochastic trajectories. One of the advantages of the kinetic network model is that the network can be built on a high-dimensional discretized state space, which can consist of multiple paths not consistent with a single reaction coordinate.

  13. Cu Diffusion in Amorphous Ta2O5 Studied with a Simplified Neural Network Potential

    Science.gov (United States)

    Li, Wenwen; Ando, Yasunobu; Watanabe, Satoshi

    2017-10-01

    Understanding atomistic details of diffusion processes in amorphous structures is becoming increasingly important due to the recent advances in various information and energy devices. Atomistic simulations based on the density functional theory (DFT) represent a powerful approach; however, the development of a method characterized by both high reliability and computational efficiency remains a challenge. In this study, a simple neural network (NN) interatomic potential is constructed from the results of DFT simulations to investigate the diffusion of a single Cu atom in amorphous Ta2O5. The proposed technique is as accurate as the DFT in predicting hopping paths and the corresponding barrier energies in a given amorphous structure. Although the developed NN-based approach exhibited some limitations since it was constructed specifically for Cu, the obtained results showed that the NN potential was able to satisfactorily describe the Cu diffusion behavior. Thus, the Cu diffusion activation energy calculated at low temperatures (between 500 and 800 K) using kinetic Monte Carlo simulations and the NN potential matched the experimental data reasonably well.

  14. Simplified polarization demultiplexing based on Stokes vector analysis for intensity-modulation direct-detection systems

    Science.gov (United States)

    Zhou, Xinyu; Yan, Lianshan; Chen, Zhiyu; Yi, Anlin; Pan, Yan; Jiang, Lin; Pan, Wei; Luo, Bin

    2016-10-01

    A simple and effective polarization demultiplexing method is proposed based on the improved Stokes vector analysis and digital signal processor algorithm for the intensity-modulation direct-detection optical communication systems. Such a scheme could significantly simplify optical receivers with low system cost. The experimental results demonstrate the feasibility of our proposed method and show that only 1- and 1.7-dB power penalties are measured for 10- and 25-km transmissions compared to back-to-back case.

  15. Fabrication and assembly of MEMS accelerometer-based heart monitoring device with simplified, one step placement.

    Science.gov (United States)

    Tjulkins, Fjodors; Nguyen, Anh-Tuan Thai; Andreassen, Erik; Aasmundtveit, Knut; Hoivik, Nils; Hoff, Lars; Halvorsen, Per Steinar; Grymyr, Ole-Johannes; Imenes, Kristin

    2015-01-01

    An accelerometer-based heart monitoring system has been developed for real-time evaluation of heart wall movement. In this paper, assembly and fabrication of an improved device is presented along with system characterization and test data from an animal experiment. The new device is smaller and has simplified the implantation procedure compared to earlier prototypes. Leakage current recordings were well below those set by the corresponding standards.

  16. SIMPLIFIED SVPWM ALGORITHM BASED DIODE CLAMPED 3-LEVEL INVERTER FED DTC-IM DRIVE

    Directory of Open Access Journals (Sweden)

    C. HARI KRISHNA

    2012-05-01

    Full Text Available This paper presents a simplified space vector pulse width modulation (SVPWM based diode clamped threelevel inverter fed direct torque controlled (DTC induction motor drive. The space vector diagram of three-level inverter is simplified into two-level inverter. So the selection of switching sequences is done as conventional two-level SVPWM method. Thus, the proposed algorithm reduces the complexity involved in the PWM algorithm. To validate the proposed PWM lgorithm, several simulation studies have been carried and resultsare presented. From the results, it can be observed that the proposed algorithm reduces the total harmonic distortion (THD of the line current and line voltages when compared with the 2-level inverter fed induction motor drive.

  17. Evaluation of Creep-Fatigue Damage Based on Simplified Model Test Approach

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yanli [ORNL; Li, Tianlei [ORNL; Sham, Sam [ORNL; Jetter, Robert I [Consultant

    2013-01-01

    Current methods used in the ASME Code, Subsection NH for the evaluation of creep-fatigue damage are based on the separation of elevated temperature cyclic damage into two parts, creep damage and fatigue damage. This presents difficulties in both evaluation of test data and determination of cyclic damage in design. To avoid these difficulties, an alternative approach was identified, called the Simplified Model Test or SMT approach based on the use of creep-fatigue hold time test data from test specimens with elastic follow-up conservatively designed to bound the response of general structural components of interest. A key feature of the methodology is the use of the results of elastic analysis directly in design evaluation similar to current methods in the ASME Code, Subsection NB. Although originally developed for current material included in Subsection NH, recent interest in the application of Alloy 617 for components operating at very high temperatures has caused renewed interest in the SMT approach because it provides an alternative to the proposed restriction on the use of current Subsection NH simplified methods at very high temperatures. A comprehensive review and assessment of five representative simplified methods for creep-fatigue damage evaluation is presented in Asayama [1]. In this review the SMT methodology was identified as the best long term approach but the need for test data precluded its near term implementation. Asayama and Jetter [2] is a summary of the more comprehensive report by Asayama [1] with a summary of the SMT approach presented by Jetter [3].

  18. Fault diagnostics for turbo-shaft engine sensors based on a simplified on-board model.

    Science.gov (United States)

    Lu, Feng; Huang, Jinquan; Xing, Yaodong

    2012-01-01

    Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can't be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient.

  19. Fault Diagnostics for Turbo-Shaft Engine Sensors Based on a Simplified On-Board Model

    Science.gov (United States)

    Lu, Feng; Huang, Jinquan; Xing, Yaodong

    2012-01-01

    Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can't be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient. PMID:23112645

  20. Simplified Gating in Long Short-term Memory (LSTM) Recurrent Neural Networks

    OpenAIRE

    Lu, Yuzhen; Salem, Fathi M.

    2017-01-01

    The standard LSTM recurrent neural networks while very powerful in long-range dependency sequence applications have highly complex structure and relatively large (adaptive) parameters. In this work, we present empirical comparison between the standard LSTM recurrent neural network architecture and three new parameter-reduced variants obtained by eliminating combinations of the input signal, bias, and hidden unit signals from individual gating signals. The experiments on two sequence datasets ...

  1. Differences in surrogate threshold effect estimates between original and simplified correlation-based validation approaches.

    Science.gov (United States)

    Schürmann, Christoph; Sieben, Wiebke

    2016-03-30

    Surrogate endpoint validation has been well established by the meta-analytical correlation-based approach as outlined in the seminal work of Buyse et al. (Biostatistics, 2000). Surrogacy can be assumed if strong associations on individual and study levels can be demonstrated. Alternatively, if an effect on a true endpoint is to be predicted from a surrogate endpoint in a new study, the surrogate threshold effect (STE, Burzykowski and Buyse, Pharmaceutical Statistics, 2006) can be used. In practice, as individual patient data (IPD) are hard to obtain, some authors use only aggregate data and perform simplified regression analyses. We are interested in to what extent such simplified analyses are biased compared with the ones from a full model with IPD. To this end, we conduct a simulation study with IPD and compute STEs from full and simplified analyses for varying data situations in terms of number of studies, correlations, variances and so on. In the scenarios considered, we show that, for normally distributed patient data, STEs derived from ordinary (weighted) linear regression generally underestimate STEs derived from the original model, whereas meta-regression often results in overestimation. Therefore, if individual data cannot be obtained, STEs from meta-regression may be used as conservative alternatives, but ordinary (weighted) linear regression should not be used for surrogate endpoint validation. Copyright © 2015 John Wiley & Sons, Ltd.

  2. Simplified optical image encryption approach using single diffraction pattern in diffractive-imaging-based scheme.

    Science.gov (United States)

    Qin, Yi; Gong, Qiong; Wang, Zhipeng

    2014-09-08

    In previous diffractive-imaging-based optical encryption schemes, it is impossible to totally retrieve the plaintext from a single diffraction pattern. In this paper, we proposed a new method to achieve this goal. The encryption procedure can be completed by proceeding only one exposure, and the single diffraction pattern is recorded as ciphertext. For recovering the plaintext, a novel median-filtering-based phase retrieval algorithm, including two iterative cycles, has been developed. This proposal not only extremely simplifies the encryption and decryption processes, but also facilitates the storage and transmission of the ciphertext, and its effectiveness and feasibility have been demonstrated by numerical simulations.

  3. Social Network Analysis Based on Network Motifs

    OpenAIRE

    2014-01-01

    Based on the community structure characteristics, theory, and methods of frequent subgraph mining, network motifs findings are firstly introduced into social network analysis; the tendentiousness evaluation function and the importance evaluation function are proposed for effectiveness assessment. Compared with the traditional way based on nodes centrality degree, the new approach can be used to analyze the properties of social network more fully and judge the roles of the nodes effectively. I...

  4. Development of flood probability charts for urban drainage network in coastal areas through a simplified joint assessment approach

    Directory of Open Access Journals (Sweden)

    R. Archetti

    2011-10-01

    Full Text Available The operating conditions of urban drainage networks during storm events depend on the hydraulic conveying capacity of conduits and also on downstream boundary conditions. This is particularly true in coastal areas where the level of the receiving water body is directly or indirectly affected by tidal or wave effects. In such cases, not just different rainfall conditions (varying intensity and duration, but also different sea-levels and their effects on the network operation should be considered. This paper aims to study the behaviour of a seaside town storm sewer network, estimating the threshold condition for flooding and proposing a simplified method to assess the urban flooding severity as a function of climate variables. The case study is a portion of the drainage system of Rimini (Italy, implemented and numerically modelled by means of InfoWorks CS code. The hydraulic simulation of the sewerage system identified the percentage of nodes of the drainage system where flooding is expected to occur. Combining these percentages with both climate variables' values has lead to the definition of charts representing the combined degree of risk "rainfall-sea level" for the drainage system under investigation. A final comparison between such charts and the results obtained from a one-year rainfall-sea level time series has demonstrated the reliability of the analysis.

  5. Development of flood probability charts for urban drainage network in coastal areas through a simplified joint assessment approach

    Directory of Open Access Journals (Sweden)

    R. Archetti

    2011-04-01

    Full Text Available The operating conditions of urban drainage networks during storm events certainly depend on the hydraulic conveying capacity of conduits but also on downstream boundary conditions. This is particularly true in costal areas where the level of the receiving water body is directly or indirectly affected by tidal or wave effects. In such cases, not just different rainfall conditions (varying intensity and duration, but also different sea-levels and their effects on the network operation should be considered. This paper aims to study the behaviour of a seaside town storm sewer network, estimating the threshold condition for flooding and proposing a simplified method to assess the urban flooding severity as a function of either climate variables. The case study is a portion of the drainage system of Rimini (Italy, implemented and numerically modelled by means of InfoWorks CS code. The hydraulic simulation of the sewerage system has therefore allowed to identify the percentage of nodes of the drainage system where flooding is expected to occur. Combining these percentages with both climate variables values has lead to the definition charts representing the combined degree of risk "sea-rainfall" for the drainage system under investigation. A final comparison between such charts and the results obtained from a one-year sea-rainfall time series has confirmed the reliability of the analysis.

  6. Development of flood probability charts for urban drainage network in coastal areas through a simplified joint assessment approach

    Science.gov (United States)

    Archetti, R.; Bolognesi, A.; Casadio, A.; Maglionico, M.

    2011-10-01

    The operating conditions of urban drainage networks during storm events depend on the hydraulic conveying capacity of conduits and also on downstream boundary conditions. This is particularly true in coastal areas where the level of the receiving water body is directly or indirectly affected by tidal or wave effects. In such cases, not just different rainfall conditions (varying intensity and duration), but also different sea-levels and their effects on the network operation should be considered. This paper aims to study the behaviour of a seaside town storm sewer network, estimating the threshold condition for flooding and proposing a simplified method to assess the urban flooding severity as a function of climate variables. The case study is a portion of the drainage system of Rimini (Italy), implemented and numerically modelled by means of InfoWorks CS code. The hydraulic simulation of the sewerage system identified the percentage of nodes of the drainage system where flooding is expected to occur. Combining these percentages with both climate variables' values has lead to the definition of charts representing the combined degree of risk "rainfall-sea level" for the drainage system under investigation. A final comparison between such charts and the results obtained from a one-year rainfall-sea level time series has demonstrated the reliability of the analysis.

  7. A Simplified Short Term Load Forecasting Method Based on Sequential Patterns

    DEFF Research Database (Denmark)

    Kouzelis, Konstantinos; Bak-Jensen, Birgitte; Mahat, Pukar

    2014-01-01

    , require considerable expertise for model construction and re-construction. Consequently, they might be impractical to use in case multiple regional forecasts are to be conducted. In this perspective, a simplified hour-ahead load forecasting algorithm was created so as to provide an automated approach...... to the problem as an alternative to other established forecasting techniques. This algorithm is based on sequential patterns and, hence, the continuous data are discretized in order to compare recent to past patterns. Although some error due to discretization is introduced, the method performs adequately well...... in comparison with an ARIMA model....

  8. Methods and tools for simplified dynamic simulations in real time based on expression approximation

    Directory of Open Access Journals (Sweden)

    Štefan M.

    2007-10-01

    Full Text Available The core of this paper is the methodology of the dynamicalmodels’ simplification for the real time simulation. The simplified simulation models are based on neuro-fuzzymodelling approach, which was originally designed for predictive control-orientedmodelling of nonlinear dynamical systems. The two ways of the neuro-fuzzymodelling utilization are presented. First, the training of the predictive dynamical neuro-fuzzymodel and, second, the training of the statical approximation of the right-hand side of the system’s state space description. We demonstrate the results on the examples of nonlinear spring damper system and double pendulum.

  9. Simplified non-linear time-history analysis based on the Theory of Plasticity

    DEFF Research Database (Denmark)

    Costa, Joao Domingues

    2005-01-01

    is based on the Theory of Plasticity. Firstly, the formulation and the computational procedure to perform time-history analysis of a rigid-plastic single degree of freedom (SDOF) system are presented. The necessary conditions for the method to incorporate pinching as well as strength degradation......This paper aims at giving a contribution to the problem of developing simplified non-linear time-history (NLTH) analysis of structures which dynamical response is mainly governed by plastic deformations, able to provide designers with sufficiently accurate results. The method to be presented...

  10. Simplified non-linear time-history analysis based on the Theory of Plasticity

    DEFF Research Database (Denmark)

    Costa, Joao Domingues

    2005-01-01

    is based on the Theory of Plasticity. Firstly, the formulation and the computational procedure to perform time-history analysis of a rigid-plastic single degree of freedom (SDOF) system are presented. The necessary conditions for the method to incorporate pinching as well as strength degradation......This paper aims at giving a contribution to the problem of developing simplified non-linear time-history (NLTH) analysis of structures which dynamical response is mainly governed by plastic deformations, able to provide designers with sufficiently accurate results. The method to be presented...

  11. Prestack migration velocity analysis based on simplifi ed two-parameter moveout equation

    Institute of Scientific and Technical Information of China (English)

    Chen Hai-Feng; Li Xiang-Yang; Qian Zhong-Ping; Song Jian-Jun; Zhao Gui-Ling

    2016-01-01

    Stacking velocityVC2, vertical velocity ratioγ0, effective velocity ratioγef, and anisotropic parameterχef are correlated in the PS-converted-wave (PS-wave) anisotropic prestack Kirchhoff time migration (PKTM) velocity model and are thus difficult to independently determine. We extended the simplified two-parameter (stacking velocity VC2 and anisotropic parameterkef) moveout equation from stacking velocity analysis to PKTM velocity model updating and formed a new four-parameter (stacking velocityVC2, vertical velocity ratioγ0, effective velocity ratioγef, and anisotropic parameterkef) PS-wave anisotropic PKTM velocity model updating and processfl ow based on the simplifi ed two-parameter moveout equation. In the proposed method, first, the PS-wave two-parameter stacking velocity is analyzed to obtain the anisotropic PKTM initial velocity and anisotropic parameters; then, the velocity and anisotropic parameters are corrected by analyzing the residual moveout on common imaging point gathers after prestack time migration. The vertical velocity ratioγ0 of the prestack time migration velocity model is obtained with an appropriate method utilizing the P- and PS-wave stacked sections after level calibration. The initial effective velocity ratioγef is calculated using the Thomsen (1999) equation in combination with the P-wave velocity analysis; ultimately, the final velocity model of the effective velocity ratioγef is obtained by percentage scanning migration. This method simplifi es the PS-wave parameter estimation in high-quality imaging, reduces the uncertainty of multiparameter estimations, and obtains good imaging results in practice.

  12. Boundary-layer transition prediction using a simplified correlation-based model

    Directory of Open Access Journals (Sweden)

    Xia Chenchao

    2016-02-01

    Full Text Available This paper describes a simplified transition model based on the recently developed correlation-based γ-Reθt transition model. The transport equation of transition momentum thickness Reynolds number is eliminated for simplicity, and new transition length function and critical Reynolds number correlation are proposed. The new model is implemented into an in-house computational fluid dynamics (CFD code and validated for low and high-speed flow cases, including the zero pressure flat plate, airfoils, hypersonic flat plate and double wedge. Comparisons between the simulation results and experimental data show that the boundary-layer transition phenomena can be reasonably illustrated by the new model, which gives rise to significant improvements over the fully laminar and fully turbulent results. Moreover, the new model has comparable features of accuracy and applicability when compared with the original γ-Reθt model. In the meantime, the newly proposed model takes only one transport equation of intermittency factor and requires fewer correlations, which simplifies the original model greatly. Further studies, especially on separation-induced transition flows, are required for the improvement of the new model.

  13. Boundary-layer transition prediction using a simplified correlation-based model

    Institute of Scientific and Technical Information of China (English)

    Xia Chenchao; Chen Weifang

    2016-01-01

    This paper describes a simplified transition model based on the recently developed correlation-based c ? Reht transition model. The transport equation of transition momentum thick-ness Reynolds number is eliminated for simplicity, and new transition length function and critical Reynolds number correlation are proposed. The new model is implemented into an in-house com-putational fluid dynamics (CFD) code and validated for low and high-speed flow cases, including the zero pressure flat plate, airfoils, hypersonic flat plate and double wedge. Comparisons between the simulation results and experimental data show that the boundary-layer transition phenomena can be reasonably illustrated by the new model, which gives rise to significant improvements over the fully laminar and fully turbulent results. Moreover, the new model has comparable features of accuracy and applicability when compared with the original c ? Reht model. In the meantime, the newly proposed model takes only one transport equation of intermittency factor and requires fewer correlations, which simplifies the original model greatly. Further studies, especially on separation-induced transition flows, are required for the improvement of the new model.

  14. Definition and Experimental Validation of a Simplified Model for a Microgrid Thermal Network and its Integration into Energy Management Systems

    Directory of Open Access Journals (Sweden)

    Andrea Bonfiglio

    2016-11-01

    Full Text Available The present paper aims at defining a simplified but effective model of a thermal network that links the thermal power generation with the resulting temperature time profile in a heated or refrigerated environment. For this purpose, an equivalent electric circuit is proposed together with an experimental procedure to evaluate its input parameters. The paper also highlights the simplicity of implementation of the proposed model into a microgrid Energy Management System. This allows the optimal operation of the thermal network to be achieved on the basis of available data (desired temperature profile instead of a less realistic basis (such as the desired thermal power profile. The validation of the proposed model is performed on the Savona Campus Smart Polygeneration Microgrid (SPM with the following steps: (i identification of the parameters involved in the equivalent circuit (performed by minimizing the difference between the temperature profile, as calculated with the proposed model, and the measured one in a set of training days; (ii test of the model accuracy on a set of testing days (comparing the measured temperature profiles with the calculated ones; (iii implementation of the model into an Energy Management System in order to optimize the thermal generation starting from a desired temperature hourly profile.

  15. A simplified adaptive neural network prescribed performance controller for uncertain MIMO feedback linearizable systems.

    Science.gov (United States)

    Theodorakopoulos, Achilles; Rovithakis, George A

    2015-03-01

    In this paper, the problem of deriving a continuous, state-feedback controller for a class of multiinput multioutput feedback linearizable systems is considered with special emphasis on controller simplification and reduction of the overall design complexity with respect to the current state of the art. The proposed scheme achieves prescribed bounds on the transient and steady-state performance of the output tracking errors despite the uncertainty in system nonlinearities. Contrary to the current state of the art, however, only a single neural network is utilized to approximate a scalar function that partly incorporates the system nonlinearities. Furthermore, the loss of model controllability problem, typically introduced owing to approximation model singularities, is avoided without attaching additional complexity to the control or adaptive law. Simulations are performed to verify and clarify the theoretical findings.

  16. Turn-based evolution in a simplified model of artistic creative process

    DEFF Research Database (Denmark)

    Dahlstedt, Palle

    2015-01-01

    Evolutionary computation has often been presented as a possible model for creativity in computers. In this paper, evolution is discussed in the light of a theoretical model of human artistic process, recently presented by the author. Some crucial differences between human artistic creativity...... and natural evolution are observed and discussed, also in the light of other creative processes occurring in nature. As a tractable way to overcome these limitations, a new kind of evolutionary implementation of creativity is proposed, based on a simplified version of the previously presented model......, and the results of initial experiments are presented and discussed. Artistic creativity is here modeled as an iterated turn-based process, alternating between a conceptual representation and a material representation of the work-to-be. Evolutionary computation is proposed as a heuristic solution to the principal...

  17. Cellulose-based graft copolymers prepared by simplified electrochemically mediated ATRP

    Directory of Open Access Journals (Sweden)

    P. Chmielarz

    2017-02-01

    Full Text Available Brush-shaped block copolymer with a dual hydrophilic poly(acrylic acid-block-poly(oligo(ethylene glycol acrylate (PAA-b-POEGA arms was synthesized for the first time via a simplified electrochemically mediated ATRP (seATRP under both constant potential electrolysis and constant current electrolysis conditions, utilizing only 30 ppm of catalyst complex. The polymerization conditions were optimized to provide fast reactions while employing low catalyst concentrations and preparation of cellulose-based brush-like copolymers with narrow molecular weight distributions. The results from proton nuclear magnetic resonance (1H NMR spectral studies support the formation of cellulose-based graft (copolymers. It is expected that these new polymer brushes may find application as pH- and thermo-sensitive drug delivery systems.

  18. a Simplified Parameter Design Method for Transformation Optics-Based Metamaterial Innovative Cloak

    Science.gov (United States)

    Li, Ting-Hua; Huang, Ming; Yang, Jing-Jing; Lu, Jin; Cao, Hui-Lu

    2013-10-01

    Transformation optics-based innovative cloak which combines the virtues of both internal and external cloaks to enable arbitrary multi-objects hidden with visions and movements was first proposed by Huang et al. [Appl. Phys. Lett.101, 151901 (2012)]. But it is rather difficult to implement in practice, for the required material parameters vary with radius and even have singular values. To accelerate its practical realization but still keep good performance of invisibility, a simplified innovative cloak with only spatially varying axial parameter is developed via choosing appropriate transformation function. The advantage of such a cloak is that both radial and azimuthal parameters are constants, and all three components are nonsingular and finite. Full-wave simulation confirms the perfect cloaking effect of the cloak. Besides, the influences of metamaterials loss and parameter deviation on the performance of cloak are also investigated. This work provides a simple and feasible solution to push metamaterial-assisted innovative cloak more closely to the practice.

  19. Deployment dynamics of a simplified spinning IKAROS solar sail via absolute coordinate based method

    Institute of Scientific and Technical Information of China (English)

    Jiang Zhao; Qiang Tian; Hai-Yan Hu

    2013-01-01

    The spinning solar sail of large scale has been well developed in recent years.Such a solar sail can be considered as a rigid-flexible multibody system mainly composed of a spinning central rigid hub,a number of flexible thin tethers,sail membranes,and tip masses.A simplified interplanetary kite-craft accelerated by radiation of the Sun (IKAROS) model is established in this study by using the absolute-coordinate-based (ACB) method that combines the natural coordinate formulation (NCF) describing the central rigid hub and the absolute nodal coordinate formulation (ANCF) describing flexible parts.The initial configuration of the system in the second-stage deployment is determined through both dynamic and static analyses.The huge set of stiff equations of system dynamics is solved by using the generalized-alpha method,and thus the deployment dynamics of the system can be well understood.

  20. Simplified process model discovery based on role-oriented genetic mining.

    Science.gov (United States)

    Zhao, Weidong; Liu, Xi; Dai, Weihui

    2014-01-01

    Process mining is automated acquisition of process models from event logs. Although many process mining techniques have been developed, most of them are based on control flow. Meanwhile, the existing role-oriented process mining methods focus on correctness and integrity of roles while ignoring role complexity of the process model, which directly impacts understandability and quality of the model. To address these problems, we propose a genetic programming approach to mine the simplified process model. Using a new metric of process complexity in terms of roles as the fitness function, we can find simpler process models. The new role complexity metric of process models is designed from role cohesion and coupling, and applied to discover roles in process models. Moreover, the higher fitness derived from role complexity metric also provides a guideline for redesigning process models. Finally, we conduct case study and experiments to show that the proposed method is more effective for streamlining the process by comparing with related studies.

  1. A simplified staging system based on the radiological findings in different stages of ochronotic spondyloarthropathy

    Directory of Open Access Journals (Sweden)

    Isaac Jebaraj

    2013-01-01

    Full Text Available This study describes a group of 26 patients with ochronotic spondyloarthropathy who were on regular treatment and follow-up at a tertiary level hospital and proposes a simplified staging system for ochronotic spondyloarthropathy based on radiographic findings seen in the thoracolumbar spine. This proposed classification makes it easy to identify the stage of the disease and start the appropriate management at an early stage. Four progressive stages are described: an inflammatory stage (stage 1, the stage of early discal calcification (stage 2, the stage of fibrous ankylosis (stage 3, and the stage of bony ankylosis (stage 4. To our knowledge, this is the largest reported series of radiological description of spinal ochronosis, and emphasizes the contribution of the spine radiograph in the diagnosis and staging of the disease.

  2. Diffractive-imaging-based optical image encryption with simplified decryption from single diffraction pattern.

    Science.gov (United States)

    Qin, Yi; Wang, Zhipeng; Gong, Qiong

    2014-07-01

    In this paper, we propose a novel method for image encryption by employing the diffraction imaging technique. This method is in principle suitable for most diffractive-imaging-based optical encryption schemes, and a typical diffractive imaging architecture using three random phase masks in the Fresnel domain is taken for an example to illustrate it. The encryption process is rather simple because only a single diffraction intensity pattern is needed to be recorded, and the decryption procedure is also correspondingly simplified. To achieve this goal, redundant data are digitally appended to the primary image before a standard encrypting procedure. The redundant data serve as a partial input plane support constraint in a phase retrieval algorithm, which is employed for completely retrieving the plaintext. Simulation results are presented to verify the validity of the proposed approach.

  3. Evaluating the Validity of Simplified Chinese Version of LIWC in Detecting Psychological Expressions in Short Texts on Social Network Services.

    Science.gov (United States)

    Zhao, Nan; Jiao, Dongdong; Bai, Shuotian; Zhu, Tingshao

    2016-01-01

    The increasing need of automated analyzing web texts especially the short texts on Social Network Services (SNS) brings new demands of computerized text analysis instruments. The psychometric properties are the basis of the extensive use of these instruments such as the Linguistic Inquiry and Word Count (LIWC). For this study, Sina Weibo statuses were analyzed via rater coding and Simplified Chinese version of LIWC (SCLIWC), in order to evaluate the validity of SCLIWC in detecting psychological expressions in Weibo statuses (n = 60) and in identifying the psychological meaning of a single Weibo status (n = 11). Significant correlations between human ratings and SCLIWC scores and the high sensitivities of capturing single statuses with certain expressions identified by raters, proved the validity of SCLIWC in detecting psychological expressions. The results also suggested that, the efficiency of SCLIWC in detecting psychological expressions of SNS short texts could be higher if using status count scoring method, rather than the word count method as the common usage of LIWC. However, SCLIWC may not perform well in identifying the psychological meaning of a single piece of SNS short text because of its over-identification of target expressions. This study provided primary evidence of validity of SCLIWC, as well as the proper way of using it efficiently on SNS short texts.

  4. A simplified CT-based definition of the supraclavicular and infraclavicular nodal volumes in breast cancer.

    Science.gov (United States)

    Atean, I; Pointreau, Y; Ouldamer, L; Monghal, C; Bougnoux, A; Bera, G; Barillot, I

    2013-02-01

    The available contouring guidelines for the supraclavicular and infraclavicular lymph nodes appeared to be inadequate for their delineation on non-enhanced computed tomography (CT) scans. For this purpose, we developed delineation guidelines for the clinical target volumes (CTV) of these lymph nodes on non-enhanced CT-slices performed in the treatment position of breast cancer. A fresh female cadaver study as well as delineation and an anatomical descriptions review were performed to propose a simplified definition of the supra- and infraclavicular lymph nodes using readily identifiable anatomical structures. This definition was developed jointly by breast radiologists, breast surgeons, and radiation oncologists. To validate these guidelines, the primary investigator and seven radiation oncologists (observers) independently delineated 10 different nodal CTVs. The primary investigator contours were considered to be the gold standard contours. Contour accuracy and concordance were evaluated. Written guidelines for the delineation of supra- and infraclavicular lymph nodes CTVs were developed. Consistent contours with minimal variability existed between the delineated volumes; the mean kappa index was 0.83. The mean common contoured and additional contoured volumes were 84.6% and 18.5%, respectively. The mean overlap volume ratio was 0.71. Simplified CT-based atlas for delineation of the supra- and infraclavicular lymph nodes for locoregional irradiation of the breast on non-enhanced CT-scan, have been developed in this study. This atlas provides a consistent set of guidelines for delineating these volumes. Copyright © 2012 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

  5. Coach simplified structure modeling and optimization study based on the PBM method

    Science.gov (United States)

    Zhang, Miaoli; Ren, Jindong; Yin, Ying; Du, Jian

    2016-09-01

    For the coach industry, rapid modeling and efficient optimization methods are desirable for structure modeling and optimization based on simplified structures, especially for use early in the concept phase and with capabilities of accurately expressing the mechanical properties of structure and with flexible section forms. However, the present dimension-based methods cannot easily meet these requirements. To achieve these goals, the property-based modeling (PBM) beam modeling method is studied based on the PBM theory and in conjunction with the characteristics of coach structure of taking beam as the main component. For a beam component of concrete length, its mechanical characteristics are primarily affected by the section properties. Four section parameters are adopted to describe the mechanical properties of a beam, including the section area, the principal moments of inertia about the two principal axles, and the torsion constant of the section. Based on the equivalent stiffness strategy, expressions for the above section parameters are derived, and the PBM beam element is implemented in HyperMesh software. A case is realized using this method, in which the structure of a passenger coach is simplified. The model precision is validated by comparing the basic performance of the total structure with that of the original structure, including the bending and torsion stiffness and the first-order bending and torsional modal frequencies. Sensitivity analysis is conducted to choose design variables. The optimal Latin hypercube experiment design is adopted to sample the test points, and polynomial response surfaces are used to fit these points. To improve the bending and torsion stiffness and the first-order torsional frequency and taking the allowable maximum stresses of the braking and left turning conditions as constraints, the multi-objective optimization of the structure is conducted using the NSGA-II genetic algorithm on the ISIGHT platform. The result of the

  6. Evaluation of absorbed doses in voxel-based and simplified models for small animals.

    Science.gov (United States)

    Mohammadi, Akram; Kinase, Sakae; Saito, Kimiaki

    2012-07-01

    Internal dosimetry in non-human biota is desirable from the viewpoint of radiation protection of the environment. The International Commission on Radiological Protection (ICRP) proposed Reference Animals and Plants using simplified models, such as ellipsoids and spheres and calculated absorbed fractions (AFs) for whole bodies. In this study, photon and electron AFs in whole bodies of voxel-based rat and frog models have been calculated and compared with AFs in the reference models. It was found that the voxel-based and the reference frog (or rat) models can be consistent for the whole-body AFs within a discrepancy of 25%, as the source was uniformly distributed in the whole body. The specific absorbed fractions (SAFs) and S values were also evaluated in whole bodies and all organs of the voxel-based frog and rat models as the source was distributed in the whole body or skeleton. The results demonstrated that the whole-body SAFs reflect SAFs of all individual organs as the source was uniformly distributed per mass within the whole body by about 30% uncertainties with exceptions for body contour (up to -40%) for both electrons and photons due to enhanced radiation leakages, and for the skeleton for photons only (up to +185%) due to differences in the mass attenuation coefficients. For nuclides such as (90)Y and (90)Sr, which were concentrated in the skeleton, there were large differences between S values in the whole body and those in individual organs, however the whole-body S values for the reference models with the whole body as the source were remarkably similar to those for the voxel-based models with the skeleton as the source, within about 4 and 0.3%, respectively. It can be stated that whole-body SAFs or S values in simplified models without internal organs are not sufficient for accurate internal dosimetry because they do not reflect SAFs or S values of all individual organs as the source was not distributed uniformly in whole body. Thus, voxel-based models

  7. Using multi-matching system based on a simplified deformable model of the human iris for iris recognition

    Institute of Scientific and Technical Information of China (English)

    MING Xing; XU Tao; WANG Zheng-xuan

    2004-01-01

    A new method for iris recognition using a multi-matching system based on a simplified deformable model of the human iris was proposed. The method defined iris feature points and formed the feature space based on a wavelet transform. In the matching stage it worked in a crude manner. Driven by a simplified deformable iris model, the crude matching was refined. By means of such multi-matching system, the task of iris recognition was accomplished. This process can preserve the elastic deformation between an input iris image and a template and improve precision for iris recognition. The experimental results indicate the validity of this method.

  8. Synthesis and high content cell-based profiling of simplified analogues of the microtubule stabilizer (+)-discodermolide.

    Science.gov (United States)

    Minguez, Jose M; Giuliano, Kenneth A; Balachandran, Raghavan; Madiraju, Charitha; Curran, Dennis P; Day, Billy W

    2002-12-01

    (+)-Discodermolide, a C24:4, trihydroxylated, octamethyl, carbamate-bearing fatty acid lactone originally isolated from a Caribbean sponge, has proven to be the most potent of the microtubule-stabilizing agents. Recent studies suggest that it or its analogues may have advantages over other classes of microtubule-stabilizing agents. (+)-Discodermolide's complex molecular architecture has made structure-activity relationship analysis in this class of compounds a formidable task. The goal of this study was to prepare simplified analogues of (+)-discodermolide and to analyze their biological activities to expand structure-activity relationships. A small library of analogues was prepared wherein the (+)-discodermolide methyl groups at C-14 and C-16 and the C-7 hydroxyl were removed, and the lactone was replaced by simple esters. The library components were analyzed for microtubule-stabilizing actions in vitro, antiproliferative activity against a small panel of human carcinoma cells, and cell signaling, microtubule architecture and mitotic spindle alterations by a multiparameter fluorescence cell-based screening technique. The results show that even drastic structural simplification can lead to analogues with actions related to microtubule targeting and signal transduction, but that these subtle effects were illuminated only through the high information content cell-based screen.

  9. Heuristic evaluation of paper-based Web pages: a simplified inspection usability methodology.

    Science.gov (United States)

    Allen, Mureen; Currie, Leanne M; Bakken, Suzanne; Patel, Vimla L; Cimino, James J

    2006-08-01

    Online medical information, when presented to clinicians, must be well-organized and intuitive to use, so that the clinicians can conduct their daily work efficiently and without error. It is essential to actively seek to produce good user interfaces that are acceptable to the user. This paper describes the methodology used to develop a simplified heuristic evaluation (HE) suitable for the evaluation of screen shots of Web pages, the development of an HE instrument used to conduct the evaluation, and the results of the evaluation of the aforementioned screen shots. In addition, this paper presents examples of the process of categorizing problems identified by the HE and the technological solutions identified to resolve these problems. Four usability experts reviewed 18 paper-based screen shots and made a total of 108 comments. Each expert completed the task in about an hour. We were able to implement solutions to approximately 70% of the violations. Our study found that a heuristic evaluation using paper-based screen shots of a user interface was expeditious, inexpensive, and straightforward to implement.

  10. CONVERGENCE OF SIMPLIFIED AND STABILIZED MIXED ELEMENT FORMATS BASED ON BUBBLE FUNCTION FOR THE STOKES PROBLEM

    Institute of Scientific and Technical Information of China (English)

    罗振东; 朱江

    2002-01-01

    Two simplified and stabilized mixed element formats for the Stokes problem are derived by bubble function, and their convergence,i.e,error analysis, are proved.These formats can save more freedom degrees than other usual formats.

  11. The Tasse concept (thorium based accelerator driven system with simplified fuel cycle for long term energy production)

    Energy Technology Data Exchange (ETDEWEB)

    Berthou, V. [CEA Cadarache, 13 - Saint Paul lez Durance (France); Slessarev, I.; Salvatores, M. [IRI, TU Delft (Netherlands)

    2001-07-01

    Within the framework of the nuclear waste management studies, the ''one-component''. concept has to be considered as an attractive option in the long-term perspective. This paper proposes a new system called TASSE (''Thorium based Accelerator driven System with Simplified fuel cycle for long term Energy production''.), destined to the current French park renewal. The main idea of the TASSE concept is to simplify both the front and the back end of the fuel cycle, and his major goals are to provide electricity with low waste production, and with an economical competitiveness. (author)

  12. Teaching neurology to medical students with a simplified version of team-based learning.

    Science.gov (United States)

    Brich, Jochen; Jost, Meike; Brüstle, Peter; Giesler, Marianne; Rijntjes, Michel

    2017-08-08

    To compare the effect of a simplified version of team-based learning (sTBL), an active learning/small group instructional strategy, with that of the traditionally used small group interactive seminars on the acquisition of knowledge and clinical reasoning (CR) skills. Third- and fourth-year medical students (n = 122) were randomly distributed into 2 groups. A crossover design was used in which 2 neurologic topics were taught by sTBL and 2 by small group interactive seminars. Knowledge was assessed with a multiple-choice question examination (MCQE), CR skills with a key feature problem examination (KFPE). Questionnaires were used for further methodologic evaluation. No group differences were found in the MCQE results. sTBL instruction of the topic "acute altered mental status" was associated with a significantly better student performance in the KFPE (p = 0.008), with no differences in the other 3 topics covered. Although both teaching methods were highly rated by the students, a clear majority voted for sTBL as their preferred future teaching method. sTBL served as an equivalent alternative to small group interactive seminars for imparting knowledge and teaching CR skills, and was particularly advantageous for teaching CR in the setting of a complex neurologic topic. Furthermore, students reported a strong preference for the sTBL approach, making it a promising tool for effectively teaching neurology. © 2017 American Academy of Neurology.

  13. Simplified Process Model Discovery Based on Role-Oriented Genetic Mining

    Directory of Open Access Journals (Sweden)

    Weidong Zhao

    2014-01-01

    Full Text Available Process mining is automated acquisition of process models from event logs. Although many process mining techniques have been developed, most of them are based on control flow. Meanwhile, the existing role-oriented process mining methods focus on correctness and integrity of roles while ignoring role complexity of the process model, which directly impacts understandability and quality of the model. To address these problems, we propose a genetic programming approach to mine the simplified process model. Using a new metric of process complexity in terms of roles as the fitness function, we can find simpler process models. The new role complexity metric of process models is designed from role cohesion and coupling, and applied to discover roles in process models. Moreover, the higher fitness derived from role complexity metric also provides a guideline for redesigning process models. Finally, we conduct case study and experiments to show that the proposed method is more effective for streamlining the process by comparing with related studies.

  14. Location based Network Optimizations for Mobile Wireless Networks

    DEFF Research Database (Denmark)

    Nielsen, Jimmy Jessen

    selection in Wi-Fi networks and predictive handover optimization in heterogeneous wireless networks. The investigations in this work have indicated that location based network optimizations are beneficial compared to typical link measurement based approaches. Especially the knowledge of geographical...

  15. Evaluating performance of simplified physically based models for shallow landslide susceptibility

    Science.gov (United States)

    Formetta, Giuseppe; Capparelli, Giovanna; Versace, Pasquale

    2016-11-01

    Rainfall-induced shallow landslides can lead to loss of life and significant damage to private and public properties, transportation systems, etc. Predicting locations that might be susceptible to shallow landslides is a complex task and involves many disciplines: hydrology, geotechnical science, geology, hydrogeology, geomorphology, and statistics. Two main approaches are commonly used: statistical or physically based models. Reliable model applications involve automatic parameter calibration, objective quantification of the quality of susceptibility maps, and model sensitivity analyses. This paper presents a methodology to systemically and objectively calibrate, verify, and compare different models and model performance indicators in order to identify and select the models whose behavior is the most reliable for particular case studies.The procedure was implemented in a package of models for landslide susceptibility analysis and integrated in the NewAge-JGrass hydrological model. The package includes three simplified physically based models for landslide susceptibility analysis (M1, M2, and M3) and a component for model verification. It computes eight goodness-of-fit indices by comparing pixel-by-pixel model results and measurement data. The integration of the package in NewAge-JGrass uses other components, such as geographic information system tools, to manage input-output processes, and automatic calibration algorithms to estimate model parameters. The system was applied for a case study in Calabria (Italy) along the Salerno-Reggio Calabria highway, between Cosenza and Altilia. The area is extensively subject to rainfall-induced shallow landslides mainly because of its complex geology and climatology. The analysis was carried out considering all the combinations of the eight optimized indices and the three models. Parameter calibration, verification, and model performance assessment were performed by a comparison with a detailed landslide inventory map for the

  16. Cloud networking understanding cloud-based data center networks

    CERN Document Server

    Lee, Gary

    2014-01-01

    Cloud Networking: Understanding Cloud-Based Data Center Networks explains the evolution of established networking technologies into distributed, cloud-based networks. Starting with an overview of cloud technologies, the book explains how cloud data center networks leverage distributed systems for network virtualization, storage networking, and software-defined networking. The author offers insider perspective to key components that make a cloud network possible such as switch fabric technology and data center networking standards. The final chapters look ahead to developments in architectures

  17. Text-Based Recall and Extra-Textual Generations Resulting from Simplified and Authentic Texts

    Science.gov (United States)

    Crossley, Scott A.; McNamara, Danielle S.

    2016-01-01

    This study uses a moving windows self-paced reading task to assess text comprehension of beginning and intermediate-level simplified texts and authentic texts by L2 learners engaged in a text-retelling task. Linear mixed effects (LME) models revealed statistically significant main effects for reading proficiency and text level on the number of…

  18. Sinc-function based Network

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1999-01-01

    The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...

  19. Sinc-function based Network

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1998-01-01

    The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...

  20. Multimodal Medical Image Fusion Framework Based on Simplified PCNN in Nonsubsampled Contourlet Transform Domain

    Directory of Open Access Journals (Sweden)

    Nianyi Wang

    2013-06-01

    Full Text Available In this paper, we present a new medical image fusion algorithm based on nonsubsampled contourlet transform (NSCT and spiking cortical model (SCM. The flexible multi-resolution, anisotropy, and directional expansion characteristics of NSCT are associated with global coupling and pulse synchronization features of SCM. Considering the human visual system characteristics, two different fusion rules are used to fuse the low and high frequency sub-bands respectively. Firstly, maximum selection rule (MSR is used to fuse low frequency coefficients. Secondly, spatial frequency (SF is applied to motivate SCM network rather than using coefficients value directly, and then the time matrix of SCM is set as criteria to select coefficients of high frequency subband. The effectiveness of the proposed algorithm is achieved by the comparison with existing fusion methods.

  1. Network-based functional enrichment

    Directory of Open Access Journals (Sweden)

    Poirel Christopher L

    2011-11-01

    Full Text Available Abstract Background Many methods have been developed to infer and reason about molecular interaction networks. These approaches often yield networks with hundreds or thousands of nodes and up to an order of magnitude more edges. It is often desirable to summarize the biological information in such networks. A very common approach is to use gene function enrichment analysis for this task. A major drawback of this method is that it ignores information about the edges in the network being analyzed, i.e., it treats the network simply as a set of genes. In this paper, we introduce a novel method for functional enrichment that explicitly takes network interactions into account. Results Our approach naturally generalizes Fisher’s exact test, a gene set-based technique. Given a function of interest, we compute the subgraph of the network induced by genes annotated to this function. We use the sequence of sizes of the connected components of this sub-network to estimate its connectivity. We estimate the statistical significance of the connectivity empirically by a permutation test. We present three applications of our method: i determine which functions are enriched in a given network, ii given a network and an interesting sub-network of genes within that network, determine which functions are enriched in the sub-network, and iii given two networks, determine the functions for which the connectivity improves when we merge the second network into the first. Through these applications, we show that our approach is a natural alternative to network clustering algorithms. Conclusions We presented a novel approach to functional enrichment that takes into account the pairwise relationships among genes annotated by a particular function. Each of the three applications discovers highly relevant functions. We used our methods to study biological data from three different organisms. Our results demonstrate the wide applicability of our methods. Our algorithms are

  2. Phenomenological theory of a renormalized simplified model based on time-convolutionless mode-coupling theory near the glass transition

    Science.gov (United States)

    Tokuyama, Michio

    2017-01-01

    The renormalized simplified model is proposed to investigate indirectly how the static structure factor plays an important role in renormalizing a quadratic nonlinear term in the ideal mode-coupling memory function near the glass transition. The renormalized simplified recursion equation is then derived based on the time-convolutionless mode-coupling theory (TMCT) proposed recently by the present author. This phenomenological approach is successfully applied to check from a unified point of view how strong liquids are different from fragile liquids. The simulation results for those two types of liquids are analyzed consistently by the numerical solutions of the recursion equation. Then, the control parameter dependence of the renormalized nonlinear exponent in both types of liquids is fully investigated. Thus, it is shown that there exists a novel difference between the universal behavior in strong liquids and that in fragile liquids not only for their transport coefficients but also for their dynamics.

  3. FUZZY REQUIREMENT BASED STRATEGY OF QoS SERVICE FOR BROADBAND TELECOMMUNICATION NETWORKS

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A fuzzy requirement based strategy for QoS service in broadband networks was presented. With the analysis of QoS service in ATM networks and broadband IP networks, it gave a requirement-based strategy for QoS service application with Fuzzy language evaluation principles. The requirement parameters are chosen according to the WANT/COST rule, and a fuzzy set is constructed to realize the fuzzy determinant. The simulation results show that it is useful to evaluate the QoS service in broadband networks, and to effectively simplify the access protocols and solve the billing issues in broadband networks.

  4. Simplified Reversed Chloroquines To Overcome Malaria Resistance to Quinoline-Based Drugs.

    Science.gov (United States)

    Gunsaru, Bornface; Burgess, Steven J; Morrill, Westin; Kelly, Jane X; Shomloo, Shawheen; Smilkstein, Martin J; Liebman, Katherine; Peyton, David H

    2017-05-01

    Building on our earlier work of attaching a chemosensitizer (reversal agent) to a known drug pharmacophore, we have now expanded the structure-activity relationship study to include simplified versions of the chemosensitizer. The change from two aromatic rings in this head group to a single ring does not appear to detrimentally affect the antimalarial activity of the compounds. Data from in vitro heme binding and β-hematin inhibition assays suggest that the single aromatic RCQ compounds retain activities against Plasmodium falciparum similar to those of CQ, although other mechanisms of action may be relevant to their activities. Copyright © 2017 Gunsaru et al.

  5. Multiplexing scheme for simplified entanglement-based large-alphabet quantum key distribution

    CERN Document Server

    Dada, Adetunmise C

    2015-01-01

    We propose a practical quantum cryptographic scheme which combines high information capacity, such as provided by high-dimensional quantum entanglement, with the simplicity of a two-dimensional Clauser-Horne-Shimony-Holt (CHSH) Bell test for security verification. By applying a state combining entanglement in a two-dimensional degree of freedom, such as photon polarization, with high-dimensional correlations in another degree of freedom, such as photon orbital angular momentum (OAM) or path, the scheme provides a considerably simplified route towards security verification in quantum key distribution (QKD) aimed at exploiting high-dimensional quantum systems for increased secure key rates. It also benefits from security against collective attacks and is feasible using currently available technologies.

  6. Evaporation Erosion During the Relay Contact Breaking Process Based on a Simplified Arc Model

    Institute of Scientific and Technical Information of China (English)

    CUI Xinglei; ZHOU Xue; ZHAI Guofu; PENG Xiyuan

    2016-01-01

    Evaporation erosion of the contacts is one of the fundamental failure mechanisms for relays.In this paper,the evaporation erosion characteristics are investigated for the copper contact pair breaking a resistive direct current (dc) 30 V/10 A circuit in the air.Molten pool simulation of thc contacts is coupled with the gas dynamics to cMculate the evaporation rate.A simplified arc model is constructed to obtain the contact voltage and current variations with time for the prediction of the current density and the heat flux distributions flowing from the arc into the contacts.The evaporation rate and mass variations with time during the breaking process are presented.Experiments are carried out to verify the simulation results.

  7. A numerical simulation of wheel spray for simplified vehicle model based on discrete phase method

    Directory of Open Access Journals (Sweden)

    Xingjun Hu

    2015-07-01

    Full Text Available Road spray greatly affects vehicle body soiling and driving safety. The study of road spray has attracted increasing attention. In this article, computational fluid dynamics software with widely used finite volume method code was employed to investigate the numerical simulation of spray induced by a simplified wheel model and a modified square-back model proposed by the Motor Industry Research Association. Shear stress transport k-omega turbulence model, discrete phase model, and Eulerian wall-film model were selected. In the simulation process, the phenomenon of breakup and coalescence of drops were considered, and the continuous and discrete phases were treated as two-way coupled in momentum and turbulent motion. The relationship between the vehicle external flow structure and body soiling was also discussed.

  8. Identification of biochemical network modules based on shortest retroactive distances.

    Directory of Open Access Journals (Sweden)

    Gautham Vivek Sridharan

    2011-11-01

    Full Text Available Modularity analysis offers a route to better understand the organization of cellular biochemical networks as well as to derive practically useful, simplified models of these complex systems. While there is general agreement regarding the qualitative properties of a biochemical module, there is no clear consensus on the quantitative criteria that may be used to systematically derive these modules. In this work, we investigate cyclical interactions as the defining characteristic of a biochemical module. We utilize a round trip distance metric, termed Shortest Retroactive Distance (ShReD, to characterize the retroactive connectivity between any two reactions in a biochemical network and to group together network components that mutually influence each other. We evaluate the metric on two types of networks that feature feedback interactions: (i epidermal growth factor receptor (EGFR signaling and (ii liver metabolism supporting drug transformation. For both networks, the ShReD partitions found hierarchically arranged modules that confirm biological intuition. In addition, the partitions also revealed modules that are less intuitive. In particular, ShReD-based partition of the metabolic network identified a 'redox' module that couples reactions of glucose, pyruvate, lipid and drug metabolism through shared production and consumption of NADPH. Our results suggest that retroactive interactions arising from feedback loops and metabolic cycles significantly contribute to the modularity of biochemical networks. For metabolic networks, cofactors play an important role as allosteric effectors that mediate the retroactive interactions.

  9. Neural Network based Consumption Forecasting

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    2016-01-01

    This paper describe a Neural Network based method for consumption forecasting. This work has been financed by the The ENCOURAGE project. The aims of The ENCOURAGE project is to develop embedded intelligence and integration technologies that will directly optimize energy use in buildings and enable...

  10. Feature extraction for deep neural networks based on decision boundaries

    Science.gov (United States)

    Woo, Seongyoun; Lee, Chulhee

    2017-05-01

    Feature extraction is a process used to reduce data dimensions using various transforms while preserving the discriminant characteristics of the original data. Feature extraction has been an important issue in pattern recognition since it can reduce the computational complexity and provide a simplified classifier. In particular, linear feature extraction has been widely used. This method applies a linear transform to the original data to reduce the data dimensions. The decision boundary feature extraction method (DBFE) retains only informative directions for discriminating among the classes. DBFE has been applied to various parametric and non-parametric classifiers, which include the Gaussian maximum likelihood classifier (GML), the k-nearest neighbor classifier, support vector machines (SVM) and neural networks. In this paper, we apply DBFE to deep neural networks. This algorithm is based on the nonparametric version of DBFE, which was developed for neural networks. Experimental results with the UCI database show improved classification accuracy with reduced dimensionality.

  11. A simplified fracture network model for studying the efficiency of a single well semi open loop heat exchanger in fractured crystalline rock

    Science.gov (United States)

    de La Bernardie, Jérôme; de Dreuzy, Jean-Raynald; Bour, Olivier; Thierion, Charlotte; Ausseur, Jean-Yves; Lesuer, Hervé; Le Borgne, Tanguy

    2016-04-01

    Geothermal energy is a renewable energy source particularly attractive due to associated low greenhouse gas emission rates. Crystalline rocks are in general considered of poor interest for geothermal applications at shallow depths (energy storage at these shallow depths is still remaining very challenging because of the complexity of fractured media. The purpose of this study is to test the possibility of efficient thermal energy storage in shallow fractured rocks with a single well semi open loop heat exchanger (standing column well). For doing so, a simplified numerical model of fractured media is considered with few fractures. Here we present the different steps for building the model and for achieving the sensitivity analysis. First, an analytical and dimensional study on the equations has been achieved to highlight the main parameters that control the optimization of the system. In a second step, multiphysics software COMSOL was used to achieve numerical simulations in a very simplified model of fractured media. The objective was to test the efficiency of such a system to store and recover thermal energy depending on i) the few parameters controlling fracture network geometry (size and number of fractures) and ii) the frequency of cycles used to store and recover thermal energy. The results have then been compared to reference shallow geothermal systems already set up for porous media. Through this study, relationships between structure, heat exchanges and storage may be highlighted.

  12. Simplifying Multiproject Scheduling Problem Based on Design Structure Matrix and Its Solution by an Improved aiNet Algorithm

    Directory of Open Access Journals (Sweden)

    Chunhua Ju

    2012-01-01

    Full Text Available Managing multiple project is a complex task involving the unrelenting pressures of time and cost. Many studies have proposed various tools and techniques for single-project scheduling; however, the literature further considering multimode or multiproject issues occurring in the real world is rather scarce. In this paper, design structure matrix (DSM and an improved artificial immune network algorithm (aiNet are developed to solve a multi-mode resource-constrained scheduling problem. Firstly, the DSM is used to simplify the mathematic model of multi-project scheduling problem. Subsequently, aiNet algorithm comprised of clonal selection, negative selection, and network suppression is adopted to realize the local searching and global searching, which will assure that it has a powerful searching ability and also avoids the possible combinatorial explosion. Finally, the approach is tested on a set of randomly cases generated from ProGen. The computational results validate the effectiveness of the proposed algorithm comparing with other famous metaheuristic algorithms such as genetic algorithm (GA, simulated annealing algorithm (SA, and ant colony optimization (ACO.

  13. A derivative based simplified phase tracker for a single fringe pattern demodulation

    Science.gov (United States)

    Deepan, B.; Quan, C.; Tay, C. J.

    2016-08-01

    In this paper, a novel fringe demodulation method for the estimation of phase and its first-order derivative from a closed-fringe interferogram is proposed. The proposed method determines the phase derivatives in both x&y directions from fringe orientation and density. The phase derivatives are subsequently used to determine phase values using a novel simplified phase tracker. In the phase tracking model, the complexity of the cost function is reduced using predetermined derivatives so computation time required for phase tracking is reduced considerably. The proposed model is more robust while dealing with saddle points in fringes than the conventional phase tracker model. Hence it does not require any specialized scanning strategy. The proposed method is validated with simulated and experimental fringe patterns (obtained using electronic speckle pattern interferometry and optical holographic interferometry) and a comparison study is carried out with conventional regularized phase tracker. The simulation results show that the proposed method has good accuracy and requires less computation time than existing phase-tracking algorithms. The experimental results demonstrate the robustness of the proposed method against speckle noise and its practical applicability for static and dynamic applications.

  14. Identification of reciprocal causality between non-alcoholic fatty liver disease and metabolic syndrome by a simplified Bayesian network in a Chinese population

    Science.gov (United States)

    Zhang, Yongyuan; Zhang, Tao; Zhang, Chengqi; Tang, Fang; Zhong, Nvjuan; Li, Hongkai; Song, Xinhong; Lin, Haiyan; Liu, Yanxun; Xue, Fuzhong

    2015-01-01

    Objectives It remains unclear whether non-alcoholic fatty liver disease (NAFLD) is a cause or a consequence of metabolic syndrome (MetS). We proposed a simplified Bayesian network (BN) and attempted to confirm their reciprocal causality. Setting Bidirectional longitudinal cohorts (subcohorts A and B) were designed and followed up from 2005 to 2011 based on a large-scale health check-up in a Chinese population. Participants Subcohort A (from NAFLD to MetS, n=8426) included the participants with or without NAFLD at baseline to follow-up the incidence of MetS, while subcohort B (from MetS to NAFLD, n=16 110) included the participants with or without MetS at baseline to follow-up the incidence of NAFLD. Results Incidence densities were 2.47 and 17.39 per 100 person-years in subcohorts A and B, respectively. Generalised estimating equation analyses demonstrated that NAFLD was a potential causal factor for MetS (relative risk, RR, 95% CI 5.23, 3.50 to 7.81), while MetS was also a factor for NAFLD (2.55, 2.23 to 2.92). A BN with 5 simplification strategies was used for the reciprocal causal inference. The BN's causal inference illustrated that the total effect of NAFLD on MetS (attributable risks, AR%) was 2.49%, while it was 19.92% for MetS on NAFLD. The total effect of NAFLD on MetS components was different, with dyslipidemia having the greatest (AR%, 10.15%), followed by obesity (7.63%), diabetes (3.90%) and hypertension (3.51%). Similar patterns were inferred for MetS components on NAFLD, with obesity having the greatest (16.37%) effect, followed by diabetes (10.85%), dyslipidemia (10.74%) and hypertension (7.36%). Furthermore, the most important causal pathway from NAFLD to MetS was that NAFLD led to elevated GGT, then to MetS components, while the dominant causal pathway from MetS to NAFLD began with dyslipidaemia. Conclusions The findings suggest a reciprocal causality between NAFLD and MetS, and the effect of MetS on NAFLD is significantly greater than that of

  15. Wireless next generation networks a virtue-based trust model

    CERN Document Server

    Harvey, Melissa

    2014-01-01

    This SpringerBrief proposes a trust model motivated by virtue epistemology, addressing the need for a more efficient and flexible trust model for wireless next generation networks. This theory of trust simplifies the computation and communication overhead of strictly cognitive-computational models of trust. Both the advantages and the challenges of virtue-based trust models are discussed. This brief offers new research and a general theory of rationality that enables users to interpret trust and reason as complementary mechanisms that guide our rational conduct at two different epistemic level

  16. Simplified seismic collapse capacity-based evaluation and design of frame buildings with and without supplemental damping systems

    Science.gov (United States)

    Hamidia, Mohammad Javad

    A simplified procedure is developed for estimating the seismic sidesway collapse capacity of frame building structures. The procedure is then extended to quantify the seismic collapse capacity of buildings incorporating supplemental damping systems. The proposed procedure is based on a robust database of seismic peak displacement responses of viscously damped nonlinear single-degree-of-freedom systems for various seismic intensities and uses nonlinear static (pushover) analysis without the need for nonlinear time history dynamic analysis. The proposed procedure is assessed by comparing its collapse capacity predictions on 1470 different building models with those obtained from incremental nonlinear dynamic analyses. A straightforward unifying collapse capacity based design procedure aimed at achieving a pre-determined probability of collapse under maximum considered earthquake event is also introduced for structures equipped with viscous dampers (linear and nonlinear) and hysteretic dampers. The proposed simplified procedure offers a simple, yet efficient, computational/analytical tool that is capable of predicting collapse capacities with acceptable accuracy for a wide variety of frame building structures incorporate several types of supplemental damping systems.

  17. Laptops simplified

    CERN Document Server

    Shoup, Kate

    2011-01-01

    A step-by-step visual guide to choosing and using a laptop Laptops continue to outsell desktop computers. Whether you're thinking of purchasing a laptop or already own one, this colorful, visual guide is packed with information you need to know. Large, full-color screen shots and step-by-step instructions show you how to choose the right laptop for your needs and how to use Windows 7 and Office 2010, connect to wireless networks, stay safe online, extend battery life, connect mobile devices, and so much more.Laptops are rapidly becoming the computer of choice; this easy-to-follow visual guide

  18. Network fingerprint: a knowledge-based characterization of biomedical networks

    Science.gov (United States)

    Cui, Xiuliang; He, Haochen; He, Fuchu; Wang, Shengqi; Li, Fei; Bo, Xiaochen

    2015-01-01

    It can be difficult for biomedical researchers to understand complex molecular networks due to their unfamiliarity with the mathematical concepts employed. To represent molecular networks with clear meanings and familiar forms for biomedical researchers, we introduce a knowledge-based computational framework to decipher biomedical networks by making systematic comparisons to well-studied “basic networks”. A biomedical network is characterized as a spectrum-like vector called “network fingerprint”, which contains similarities to basic networks. This knowledge-based multidimensional characterization provides a more intuitive way to decipher molecular networks, especially for large-scale network comparisons and clustering analyses. As an example, we extracted network fingerprints of 44 disease networks in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The comparisons among the network fingerprints of disease networks revealed informative disease-disease and disease-signaling pathway associations, illustrating that the network fingerprinting framework will lead to new approaches for better understanding of biomedical networks. PMID:26307246

  19. Host Event Based Network Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Jonathan Chugg

    2013-01-01

    The purpose of INL’s research on this project is to demonstrate the feasibility of a host event based network monitoring tool and the effects on host performance. Current host based network monitoring tools work on polling which can miss activity if it occurs between polls. Instead of polling, a tool could be developed that makes use of event APIs in the operating system to receive asynchronous notifications of network activity. Analysis and logging of these events will allow the tool to construct the complete real-time and historical network configuration of the host while the tool is running. This research focused on three major operating systems commonly used by SCADA systems: Linux, WindowsXP, and Windows7. Windows 7 offers two paths that have minimal impact on the system and should be seriously considered. First is the new Windows Event Logging API, and, second, Windows 7 offers the ALE API within WFP. Any future work should focus on these methods.

  20. CNEM: Cluster Based Network Evolution Model

    Directory of Open Access Journals (Sweden)

    Sarwat Nizamani

    2015-01-01

    Full Text Available This paper presents a network evolution model, which is based on the clustering approach. The proposed approach depicts the network evolution, which demonstrates the network formation from individual nodes to fully evolved network. An agglomerative hierarchical clustering method is applied for the evolution of network. In the paper, we present three case studies which show the evolution of the networks from the scratch. These case studies include: terrorist network of 9/11 incidents, terrorist network of WMD (Weapons Mass Destruction plot against France and a network of tweets discussing a topic. The network of 9/11 is also used for evaluation, using other social network analysis methods which show that the clusters created using the proposed model of network evolution are of good quality, thus the proposed method can be used by law enforcement agencies in order to further investigate the criminal networks

  1. Sensor selection for received signal strength-based source localization in wireless sensor networks

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Generally, localization is a nonlinear problem, while linearization is used to simplify this problem. Reasonable approximations could be achieved when signal-to-noise ratio (SNR) is large enough. Energy is a critical resource in wireless sensor networks, and system lifetime needs to be prolonged through the use of energy efficient strategies during system operation. In this paper, a closed-form solution for received signal strength (RSS)-based source localization in wireless sensor network (WSN) is obtained...

  2. On Tree-Based Phylogenetic Networks.

    Science.gov (United States)

    Zhang, Louxin

    2016-07-01

    A large class of phylogenetic networks can be obtained from trees by the addition of horizontal edges between the tree edges. These networks are called tree-based networks. We present a simple necessary and sufficient condition for tree-based networks and prove that a universal tree-based network exists for any number of taxa that contains as its base every phylogenetic tree on the same set of taxa. This answers two problems posted by Francis and Steel recently. A byproduct is a computer program for generating random binary phylogenetic networks under the uniform distribution model.

  3. Coupled third-order simplified spherical harmonics and diffusion equation-based fluorescence tomographic imaging of liver cancer

    Science.gov (United States)

    Chen, Xueli; Sun, Fangfang; Yang, Defu; Liang, Jimin

    2015-09-01

    For fluorescence tomographic imaging of small animals, the liver is usually regarded as a low-scattering tissue and is surrounded by adipose, kidneys, and heart, all of which have a high scattering property. This leads to a breakdown of the diffusion equation (DE)-based reconstruction method as well as a heavy computational burden for the simplified spherical harmonics equation (SPN). Coupling the SPN and DE provides a perfect balance between the imaging accuracy and computational burden. The coupled third-order SPN and DE (CSDE)-based reconstruction method is developed for fluorescence tomographic imaging. This is achieved by doubly using the CSDE for the excitation and emission processes of the fluorescence propagation. At the same time, the finite-element method and hybrid multilevel regularization strategy are incorporated in inverse reconstruction. The CSDE-based reconstruction method is first demonstrated with a digital mouse-based liver cancer simulation, which reveals superior performance compared with the SPN and DE-based methods. It is more accurate than the DE-based method and has lesser computational burden than the SPN-based method. The feasibility of the proposed approach in applications of in vivo studies is also illustrated with a liver cancer mouse-based in situ experiment, revealing its potential application in whole-body imaging of small animals.

  4. Clinical implementation of a GPU-based simplified Monte Carlo method for a treatment planning system of proton beam therapy.

    Science.gov (United States)

    Kohno, R; Hotta, K; Nishioka, S; Matsubara, K; Tansho, R; Suzuki, T

    2011-11-21

    We implemented the simplified Monte Carlo (SMC) method on graphics processing unit (GPU) architecture under the computer-unified device architecture platform developed by NVIDIA. The GPU-based SMC was clinically applied for four patients with head and neck, lung, or prostate cancer. The results were compared to those obtained by a traditional CPU-based SMC with respect to the computation time and discrepancy. In the CPU- and GPU-based SMC calculations, the estimated mean statistical errors of the calculated doses in the planning target volume region were within 0.5% rms. The dose distributions calculated by the GPU- and CPU-based SMCs were similar, within statistical errors. The GPU-based SMC showed 12.30-16.00 times faster performance than the CPU-based SMC. The computation time per beam arrangement using the GPU-based SMC for the clinical cases ranged 9-67 s. The results demonstrate the successful application of the GPU-based SMC to a clinical proton treatment planning.

  5. Location-Based Services in Vehicular Networks

    Science.gov (United States)

    Wu, Di

    2013-01-01

    Location-based services have been identified as a promising communication paradigm in highly mobile and dynamic vehicular networks. However, existing mobile ad hoc networking cannot be directly applied to vehicular networking due to differences in traffic conditions, mobility models and network topologies. On the other hand, hybrid architectures…

  6. Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch

    Directory of Open Access Journals (Sweden)

    Tao Huang

    2016-01-01

    Full Text Available Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture.

  7. Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch.

    Science.gov (United States)

    Huang, Tao; Yan, Siyu; Yang, Fan; Pan, Tian; Liu, Jiang

    2016-01-19

    Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture.

  8. A simplified concentration series to produce a pair of 2D asynchronous spectra based on the DAOSD approach

    Science.gov (United States)

    Kang, Xiaoyan; He, Anqi; Guo, Ran; Zhai, Yanjun; Xu, Yizhuang; Noda, Isao; Wu, Jinguang

    2016-11-01

    We propose a substantially simplified approach to construct a pair of 2D asynchronous spectra based on the DAOSD approach proposed in our previous papers. By using a new concentration series, only three 1D spectra are used to generate a pair of 2D correlation spectra together with two reference spectra. By using this method, the previous problem of labor intensive traditional DAOSD approach has been successfully addressed. We apply the new approach to characterize intermolecular interaction between acetonitrile and butanone dissolved in carbon tetrachloride. The existence of intermolecular interaction between the two solutes can be confirmed by the presence of a cross peak in the resultant 2D IR spectra. In addition, the absence of cross peak around (2254, 2292) in Ψbutanone provides another experimental evidence to reveal the intrinsic relationship between the Ctbnd N stretching band and an overtone band (δCH3+νC-C).

  9. Fold-Hopf bifurcation in a simplified four-neuron BAM (bidirectional associative memory) neural network with two delays

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The bidirectional associative memory (BAM) neural network with four neurons and two delays is considered in the present paper.A linear stability analysis for the trivial equilibrium is firstly employed to provide a possible critical point at which a zero and a pair of pure imaginary eigenvalues occur in the corresponding characteristic equation.A fold-Hopf bifurcation is proved to happen at this critical point by the nonlinear analysis.The coupling strength and the delay are considered as bifurcation parameters to investigate the dynamical behaviors derived from the fold-Hopf bifurcation.Various dynamical behaviours are qualitatively classified in the neighbourhood of the fold-Hopf bifurcation point by using the center manifold reduction (CMR) together with the normal form.The bifurcating periodic solutions are expressed analytically in an approximate form.The validity of the results is shown by their consistency with the numerical simulation.

  10. A Proactive Strategy for Safe Human-Robot Collaboration based on a Simplified Risk Analysis

    Directory of Open Access Journals (Sweden)

    Audun Sanderud

    2015-01-01

    Full Text Available In an increasing demand for human-robot collaboration systems, the need for safe robots is crucial. This paper presents a proactive strategy to enable an awareness of the current risk for the robot. The awareness is based upon a map of historically occupied space by the operator. The map is built based on a risk evaluation of each pose presented by the operator. The risk evaluation results in a risk field that can be used to evaluate the risk of a collaborative task. Based on this risk field, a control algorithm that constantly reduces the current risk within its task constraints was developed. Kinematic redundancy was exploited for simultaneous task performance within task constraints, and risk minimization. Sphere-based geometric models were used both for the human and robot. The strategy was tested in simulation, and implemented and experimentally tested on a NACHI MR20 7-axes industrial robot.

  11. Distribution Network Fault Diagnosis Method Based on Granular Computing-BP

    Directory of Open Access Journals (Sweden)

    CHEN Zhong-xiao

    2013-01-01

    Full Text Available To deal with the complexity and uncertainty of distribution network fault information, a method of fault diagnosis based on granular computing and BP is proposed. This method uses attribute reduction advantages of granular computing theory and self-learning and knowledge acquisition ability of BP neural network. It put granular computing theory as the front-end processor of the BP neural network, namely simplify primitive information making use of granular computing reduction, and according to the concepts of relative granularity and significance of attributes based on binary granular computing are proposed to select input of BP, thereby reducing solving scale, and then construct neural network based on the minimum attribute sets, using BP neural network to model and parameter identify, reduce the BP study training time, improve the accuracy of the fault diagnosis. The distribution network example verifies the rationality and effectiveness of the proposed method.

  12. Network based automation for SMEs

    DEFF Research Database (Denmark)

    Shahabeddini Parizi, Mohammad; Radziwon, Agnieszka

    2017-01-01

    could be obtained through network interaction. Based on two extreme cases of SMEs representing low-tech industry and an in-depth analysis of their manufacturing facilities this paper presents how collaboration between firms embedded in a regional ecosystem could result in implementation of new...... automation solutions. The empirical data collection involved application of a combination of comparative case study method with action research elements. This article provides an outlook over the challenges in implementing technological improvements and the way how it could be resolved in collaboration......, this paper develops and discusses a set of guidelines for systematic productivity improvement within an innovative collaboration in regards to automation processes in SMEs....

  13. A network approach based on cliques

    Science.gov (United States)

    Fadigas, I. S.; Pereira, H. B. B.

    2013-05-01

    The characterization of complex networks is a procedure that is currently found in several research studies. Nevertheless, few studies present a discussion on networks in which the basic element is a clique. In this paper, we propose an approach based on a network of cliques. This approach consists not only of a set of new indices to capture the properties of a network of cliques but also of a method to characterize complex networks of cliques (i.e., some of the parameters are proposed to characterize the small-world phenomenon in networks of cliques). The results obtained are consistent with results from classical methods used to characterize complex networks.

  14. Simplifying Hill-based muscle models through generalized extensible fuzzy heuristic implementation

    Science.gov (United States)

    O'Brien, Amy J.

    2006-04-01

    Traditional dynamic muscle models based on work initially published by A. V. Hill in 1938 often rely on high-order systems of differential equations. While such models are very accurate and effective, they do not typically lend themselves to modification by clinicians who are unfamiliar with biomedical engineering and advanced mathematics. However, it is possible to develop a fuzzy heuristic implementation of a Hill-based model-the Fuzzy Logic Implemented HIll-based (FLIHI) muscle model-that offers several advantages over conventional state equation approaches. Because a fuzzy system is oriented by design to describe a model in linguistics rather than ordinary differential equation-based mathematics, the resulting fuzzy model can be more readily modified and extended by medical practitioners. It also stands to reason that a well-designed fuzzy inference system can be implemented with a degree of generalizability not often encountered in traditional state space models. Taking electromyogram (EMG) as one input to muscle, FLIHI is tantamount to a fuzzy EMG-to-muscle force estimator that captures dynamic muscle properties while providing robustness to partial or noisy data. One goal behind this approach is to encourage clinicians to rely on the model rather than assuming that muscle force as an output maps directly to smoothed EMG as an input. FLIHI's force estimate is more accurate than assuming force equal to smoothed EMG because FLIHI provides a transfer function that accounts for muscle's inherent nonlinearity. Furthermore, employing fuzzy logic should provide FLIHI with improved robustness over traditional mathematical approaches.

  15. A Network Coding Based Routing Protocol for Underwater Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xin Guan

    2012-04-01

    Full Text Available Due to the particularities of the underwater environment, some negative factors will seriously interfere with data transmission rates, reliability of data communication, communication range, and network throughput and energy consumption of underwater sensor networks (UWSNs. Thus, full consideration of node energy savings, while maintaining a quick, correct and effective data transmission, extending the network life cycle are essential when routing protocols for underwater sensor networks are studied. In this paper, we have proposed a novel routing algorithm for UWSNs. To increase energy consumption efficiency and extend network lifetime, we propose a time-slot based routing algorithm (TSR.We designed a probability balanced mechanism and applied it to TSR. The theory of network coding is introduced to TSBR to meet the requirement of further reducing node energy consumption and extending network lifetime. Hence, time-slot based balanced network coding (TSBNC comes into being. We evaluated the proposed time-slot based balancing routing algorithm and compared it with other classical underwater routing protocols. The simulation results show that the proposed protocol can reduce the probability of node conflicts, shorten the process of routing construction, balance energy consumption of each node and effectively prolong the network lifetime.

  16. A simplified calculation procedure for mass isotopomer distribution analysis (MIDA) based on multiple linear regression.

    Science.gov (United States)

    Fernández-Fernández, Mario; Rodríguez-González, Pablo; García Alonso, J Ignacio

    2016-10-01

    We have developed a novel, rapid and easy calculation procedure for Mass Isotopomer Distribution Analysis based on multiple linear regression which allows the simultaneous calculation of the precursor pool enrichment and the fraction of newly synthesized labelled proteins (fractional synthesis) using linear algebra. To test this approach, we used the peptide RGGGLK as a model tryptic peptide containing three subunits of glycine. We selected glycine labelled in two (13) C atoms ((13) C2 -glycine) as labelled amino acid to demonstrate that spectral overlap is not a problem in the proposed methodology. The developed methodology was tested first in vitro by changing the precursor pool enrichment from 10 to 40% of (13) C2 -glycine. Secondly, a simulated in vivo synthesis of proteins was designed by combining the natural abundance RGGGLK peptide and 10 or 20% (13) C2 -glycine at 1 : 1, 1 : 3 and 3 : 1 ratios. Precursor pool enrichments and fractional synthesis values were calculated with satisfactory precision and accuracy using a simple spreadsheet. This novel approach can provide a relatively rapid and easy means to measure protein turnover based on stable isotope tracers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  17. A simplified spectrometer based on a fast digital oscilloscope for the measurement of high energy $\\gamma$-rays

    CERN Document Server

    Markochev, S S

    2014-01-01

    A simplified digital spectrometer for the study of $\\gamma$-rays with energies up to $\\sim100$ MeV is presented and tested. The spectrometer is only consisted of a fast digital oscilloscope and three scintillation detectors which can work in single or in coincidence modes: two BGO-detectors comprising $\\varnothing\\,7.62\\times7.62$ cm BGO-crystalls and one plastic detector which includes an organic polystyrene-based scintillator. The basic properties of the spectrometer (energy resolution, time resolution, $\\gamma$-rays detection efficiency) were studied exhaustively also using a Geant4-based Monte-Carlo simulation. Several numerical algorithms for processing of waveforms in offline mode were proposed and tested to perform digital timing, pulse area measurement and processing of pile-up events without rejection. As a result, the spectrometer demonstrated $\\sim10\\%$ better energy resolution than was obtained by a common 10-bit CAMAC ADC with the same detectors. And the developed algorithm based on the pulse sha...

  18. Network Traffic Prediction based on Particle Swarm BP Neural Network

    Directory of Open Access Journals (Sweden)

    Yan Zhu

    2013-11-01

    Full Text Available The traditional BP neural network algorithm has some bugs such that it is easy to fall into local minimum and the slow convergence speed. Particle swarm optimization is an evolutionary computation technology based on swarm intelligence which can not guarantee global convergence. Artificial Bee Colony algorithm is a global optimum algorithm with many advantages such as simple, convenient and strong robust. In this paper, a new BP neural network based on Artificial Bee Colony algorithm and particle swarm optimization algorithm is proposed to optimize the weight and threshold value of BP neural network. After network traffic prediction experiment, we can conclude that optimized BP network traffic prediction based on PSO-ABC has high prediction accuracy and has stable prediction performance.

  19. Lumbar joint torque estimation based on simplified motion measurement using multiple inertial sensors.

    Science.gov (United States)

    Miyajima, Saori; Tanaka, Takayuki; Imamura, Yumeko; Kusaka, Takashi

    2015-01-01

    We estimate lumbar torque based on motion measurement using only three inertial sensors. First, human motion is measured by a 6-axis motion tracking device that combines a 3-axis accelerometer and a 3-axis gyroscope placed on the shank, thigh, and back. Next, the lumbar joint torque during the motion is estimated by kinematic musculoskeletal simulation. The conventional method for estimating joint torque uses full body motion data measured by an optical motion capture system. However, in this research, joint torque is estimated by using only three link angles of the body, thigh, and shank. The utility of our method was verified by experiments. We measured motion of bendung knee and waist simultaneously. As the result, we were able to estimate the lumbar joint torque from measured motion.

  20. Simplified floor-area-based energy-moisture-economic model for residential buildings

    Science.gov (United States)

    Martinez, Luis A.

    In the United States, 21% of all energy is used in residential buildings (40% of which is for heating and cooling homes). Promising improvements in residential building energy efficiency are underway such as the Building America Program and the Passive House Concept. The ability of improving energy efficiency in buildings is enhanced by building energy modeling tools, which are well advanced and established but lack generality (each building has to be modeled individually) and require high cost, which limits many residential buildings from taking advantage of such powerful tools. This dissertation attempts to develop guidelines based on a per-building-floor-area basis for designing residential buildings that achieve maximum energy efficiency and minimum life cycle cost. Energy and moisture-mass conservation principles were formulated for residential buildings on a per-building-floor-area basis. This includes thermal energy balance, moisture-mass conservation and life cycle cost. The analysis also includes the effects of day-lighting, initial cost estimation and escalation rates. The model was implemented on Excel so it is available for broader audiences and was validated using the standard BESTEST validation procedure for energy models yielding satisfactory results for different scenarios, within a 90% confidence interval. Using the model, parametric optimization studies were conducted in order to study how each variable affects energy and life cycle cost. An efficient whole-building optimization procedure was developed to determine the optimal design based on key design parameters. Whole-building optimization studies were conducted for 12 climate zones using four different criteria: minimum energy consumption, minimum life cycle cost (35 years) using constant energy costs and minimum life cycle cost (35 years) varying escalation rates (-5%, 10%). Conclusions and recommendations were inferred on how to design an optimal house, using each criterion and for all

  1. WLAN indoor location method based on artificial neural network

    Institute of Scientific and Technical Information of China (English)

    Zhou Mu; Sun Ying; Xu Yubin; Deng Zhian; Meng Weixiao

    2010-01-01

    WLAN indoor location method based on artificial neural network (ANN) is analyzed.A three layer feed-forward ANN model offers the benefits of reducing time cost of the layout of an indoor location system, saving storage cost of the radio map establishment and enhancing real-time capacity in the on-line phase.According to the analysis of SNR distributions of recorded beacon signal samples and discussion about the multi-mode phenomenon, the one map method is proposed for the purpose of simplifying ANN input values and increasing location performances.Based on the simulations and comparison analysis with other two typical indoor location methods, K-nearest neighbor (KNN) and probability, the feasibility and effectiveness of ANN-based indoor location method are verified with average location error of 2.37m and location accuracy of 78.6% in 3m.

  2. ENERGY AWARE NETWORK: BAYESIAN BELIEF NETWORKS BASED DECISION MANAGEMENT SYSTEM

    Directory of Open Access Journals (Sweden)

    Santosh Kumar Chaudhari

    2011-06-01

    Full Text Available A Network Management System (NMS plays a very important role in managing an ever-evolving telecommunication network. Generally an NMS monitors & maintains the health of network elements. The growing size of the network warrants extra functionalities from the NMS. An NMS provides all kinds of information about networks which can be used for other purposes apart from monitoring & maintaining networks like improving QoS & saving energy in the network. In this paper, we add another dimension to NMS services, namely, making an NMS energy aware. We propose a Decision Management System (DMS framework which uses a machine learning technique called Bayesian Belief Networks (BBN, to make the NMS energy aware. The DMS is capable of analysing and making control decisions based on network traffic. We factor in the cost of rerouting and power saving per port. Simulations are performed on standard network topologies, namely, ARPANet and IndiaNet. It is found that ~2.5-6.5% power can be saved.

  3. A Fast Method for Embattling Optimization of Ground-Based Radar Surveillance Network

    Science.gov (United States)

    Jiang, H.; Cheng, H.; Zhang, Y.; Liu, J.

    A growing number of space activities have created an orbital debris environment that poses increasing impact risks to existing space systems and human space flight. For the safety of in-orbit spacecraft, a lot of observation facilities are needed to catalog space objects, especially in low earth orbit. Surveillance of Low earth orbit objects are mainly rely on ground-based radar, due to the ability limitation of exist radar facilities, a large number of ground-based radar need to build in the next few years in order to meet the current space surveillance demands. How to optimize the embattling of ground-based radar surveillance network is a problem to need to be solved. The traditional method for embattling optimization of ground-based radar surveillance network is mainly through to the detection simulation of all possible stations with cataloged data, and makes a comprehensive comparative analysis of various simulation results with the combinational method, and then selects an optimal result as station layout scheme. This method is time consuming for single simulation and high computational complexity for the combinational analysis, when the number of stations increases, the complexity of optimization problem will be increased exponentially, and cannot be solved with traditional method. There is no better way to solve this problem till now. In this paper, target detection procedure was simplified. Firstly, the space coverage of ground-based radar was simplified, a space coverage projection model of radar facilities in different orbit altitudes was built; then a simplified objects cross the radar coverage model was established according to the characteristics of space objects orbit motion; after two steps simplification, the computational complexity of the target detection was greatly simplified, and simulation results shown the correctness of the simplified results. In addition, the detection areas of ground-based radar network can be easily computed with the

  4. Simplified method to predict mutual interactions of human transcription factors based on their primary structure

    KAUST Repository

    Schmeier, Sebastian

    2011-07-05

    Background: Physical interactions between transcription factors (TFs) are necessary for forming regulatory protein complexes and thus play a crucial role in gene regulation. Currently, knowledge about the mechanisms of these TF interactions is incomplete and the number of known TF interactions is limited. Computational prediction of such interactions can help identify potential new TF interactions as well as contribute to better understanding the complex machinery involved in gene regulation. Methodology: We propose here such a method for the prediction of TF interactions. The method uses only the primary sequence information of the interacting TFs, resulting in a much greater simplicity of the prediction algorithm. Through an advanced feature selection process, we determined a subset of 97 model features that constitute the optimized model in the subset we considered. The model, based on quadratic discriminant analysis, achieves a prediction accuracy of 85.39% on a blind set of interactions. This result is achieved despite the selection for the negative data set of only those TF from the same type of proteins, i.e. TFs that function in the same cellular compartment (nucleus) and in the same type of molecular process (transcription initiation). Such selection poses significant challenges for developing models with high specificity, but at the same time better reflects real-world problems. Conclusions: The performance of our predictor compares well to those of much more complex approaches for predicting TF and general protein-protein interactions, particularly when taking the reduced complexity of model utilisation into account. © 2011 Schmeier et al.

  5. Ecofriendly and Simplified Synthetic Route for Polysulfone-based Solid-State Alkaline Electrolyte Membrane

    Directory of Open Access Journals (Sweden)

    Nittaya Pantamas

    2012-01-01

    Full Text Available Problem statement: Recently the alkaline system for fuel cell enhance their presence because of possibility of no-precious-metal catalyst and low over potential at cathode reaction. The anion exchange membrane for alkaline membrane fuel cell should be a key technology in order to achieve the practical performance as fuel cells. Alkaline anion exchange membranes of high ionic conductivities are made from polysulfone by adding a chloromethyl pendant group to the polysulfone, follow by reacting the chloromethyl group with amine to form quarternary ammonium pendant groups which act as the counter ion for hydroxide anion. Chloromethyl methyl ether, N,N-dimethylformamide and methanol are commonly used as agent for providing excellent conversions, but they are now considered to be carcinogenic. To avoid the use of such hazardous materials, in our work we used paraformaldehyde, chlorotrimethylsilane, N-methylpyrrolidone and ethanol as agent for providing conversion. Approach: Polysulfone (PS was chloromethylated using chlorotrimethylsilane as a chloromethylation reagent, resulting in the formation of Chloromethylated Polysulfone (CMPS. CMPS was converted to a quaternized form using trimethylamine and precipitated into ethanol. The powder was dissolved in N-methylpyrrolidone, followed by aminated with a 25 wt% trimethylamine. Results: The resulting solution was cast onto a flat glass plate and dried in an oven. The membrane was immersed in KOH solution for 24 h to replace the Cl- anion in the polymer with OH-. Conclusion: The swelling behavior of polysulfone-based solid-state alkaline electrolyte membrane was closely related to the degree of water uptake (25 WU%, 7.5 SD% and the ion-exchange capacity was 1.05 mmol g-1, which is sufficient for electrolyte membranes used in alkaline fuel cells.

  6. Inference of Gene Regulatory Network Based on Local Bayesian Networks.

    Science.gov (United States)

    Liu, Fei; Zhang, Shao-Wu; Guo, Wei-Feng; Wei, Ze-Gang; Chen, Luonan

    2016-08-01

    The inference of gene regulatory networks (GRNs) from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN) methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN), to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI) to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI) significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only effectively reduce

  7. A simplified early-warning system for imminent landslide prediction based on failure index fragility curves developed through numerical analysis

    Directory of Open Access Journals (Sweden)

    Ugur Ozturk

    2016-07-01

    Full Text Available Early-warning systems (EWSs are crucial to reduce the risk of landslide, especially where the structural measures are not fully capable of preventing the devastating impact of such an event. Furthermore, designing and successfully implementing a complete landslide EWS is a highly complex task. The main technical challenges are linked to the definition of heterogeneous material properties (geotechnical and geomechanical parameters as well as a variety of the triggering factors. In addition, real-time data processing creates a significant complexity, since data collection and numerical models for risk assessment are time consuming tasks. Therefore, uncertainties in the physical properties of a landslide together with the data management represent the two crucial deficiencies in an efficient landslide EWS. Within this study the application is explored of the concept of fragility curves to landslides; fragility curves are widely used to simulate systems response to natural hazards, i.e. floods or earthquakes. The application of fragility curves to landslide risk assessment is believed to simplify emergency risk assessment; even though it cannot substitute detailed analysis during peace-time. A simplified risk assessment technique can remove some of the unclear features and decrease data processing time. The method is based on synthetic samples which are used to define the approximate failure thresholds for landslides, taking into account the materials and the piezometric levels. The results are presented in charts. The method presented in this paper, which is called failure index fragility curve (FIFC, allows assessment of the actual real-time risk in a case study that is based on the most appropriate FIFC. The application of an FIFC to a real case is presented as an example. This method to assess the landslide risk is another step towards a more integrated dynamic approach to a potential landslide prevention system. Even if it does not define

  8. Multi-Objective Optimization and Analysis Model of Sintering Process Based on BP Neural Network

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jun-hong; XIE An-guo; SHEN Feng-man

    2007-01-01

    A multi-objective optimization and analysis model of the sintering process based on BP neural network is presented. Genetic algorithms are combined to simplify the BP neural network, which can reduce the learning time and increase the forecasting accuracy of the network model. This model has been experimented in the sintering process, and the production cost, the energy consumption, the quality (revolving intensity), and the output are considered at the same time. Moreover, the relation between some factors and the multi-objectives has been analyzed, and the results are consistent with the process. Different objectives are emphasized at different practical periods, and this can provide a theoretical basis for the manager.

  9. Competition Based Neural Networks for Assignment Problems

    Institute of Scientific and Technical Information of China (English)

    李涛; LuyuanFang

    1991-01-01

    Competition based neural networks have been used to solve the generalized assignment problem and the quadratic assignment problem.Both problems are very difficult and are ε approximation complete.The neural network approach has yielded highly competitive performance and good performance for the quadratic assignment problem.These neural networks are guaranteed to produce feasible solutions.

  10. Durer-pentagon-based complex network

    Directory of Open Access Journals (Sweden)

    Rui Hou

    2016-04-01

    Full Text Available A novel Durer-pentagon-based complex network was constructed by adding a centre node. The properties of the complex network including the average degree, clustering coefficient, average path length, and fractal dimension were determined. The proposed complex network is small-world and fractal.

  11. FLOOD ROUTING BASED ON NETWORK CODING (NCF)

    OpenAIRE

    HOSSEIN BALOOCHIAN; MOZAFAR BAGMOHAMMADI

    2010-01-01

    Most of the energy in a sensor network is used for transmission of data packets. For this reason, optimization of energy consumption is of utmost importance in these networks. This paper presents NCF, a flood routing protocol based on network coding. Simulations show that in addition to eliminating the drawbacks of traditional flooding methods, like the explosion phenomenon, NCF increases the lifetime of the network by at least 20% and decreases the number of packet transmissions. Another adv...

  12. Agent-based modeling and network dynamics

    CERN Document Server

    Namatame, Akira

    2016-01-01

    The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...

  13. Laws of Network Value

    Directory of Open Access Journals (Sweden)

    Juan M.C. Larrosa

    2016-12-01

    Full Text Available The valuation of a social network is an issue that has been addressed based on simplifying approaches. Various value laws have been stipulated, which are largely atheoretical but have been effectively used to estimate the potential economic value of social network-based firms. This review highlights the various contributions used in the recent literature on networks valuation laws.

  14. A Complete and Simplified Datasheet-Based Model of PV Cells in Variable Environmental Conditions for Circuit Simulation

    Directory of Open Access Journals (Sweden)

    Silvano Vergura

    2016-04-01

    Full Text Available The paper proposes two mathematical models of a photo-voltaic (PV cell—the complete model and the simplified model—which can be used also for modeling a PV module or a PV string under any environmental condition. Both of them are based on the well-known five-parameters model, while the approach allows to write a new descriptive equation, whose terms are functions of the information always available in the modern datasheet of a PV module’s manufacturer. This implies that no pre-processing of the datasheet parameters is needed to use the proposed model, whichever the solar irradiance and the cell/module temperature are. Moreover, these models are interpreted from a circuital point of view, providing the electrical circuits constituted only by basic electrical components. Particularly, in order to take into account the variability of the environment parameters, several variable resistors and voltage-controlled sources are used. The proposed models are tested with the datasheet parameters of commercial PV modules.

  15. RELAY ALGORITHM BASED ON NETWORK CODING IN WIRELESS LOCAL NETWORK

    Institute of Scientific and Technical Information of China (English)

    Wang Qi; Wang Qingshan; Wang Dongxue

    2013-01-01

    The network coding is a new technology in the field of information in 21st century.It could enhance the network throughput and save the energy consumption,and is mainly based on the single transmission rate.However,with the development of wireless network and equipment,wireless local network MAC protocols have already supported the multi-rate transmission.This paper investigates the optimal relay selection problem based on network coding.Firstly,the problem is formulated as an optimization problem.Moreover,a relay algorithm based on network coding is proposed and the transmission time gain of our algorithm over the traditional relay algorithm is analyzed.Lastly,we compare total transmission time and the energy consumption of our proposed algorithm,Network Coding with Relay Assistance (NCRA),Transmission Request (TR),and the Direct Transmission (DT) without relay algorithm by adopting IEEE 802.11b.The simulation results demonstrate that our algorithm that improves the coding opportunity by the cooperation of the relay nodes leads to the transmission time decrease of up to 17% over the traditional relay algorithms.

  16. Honeypot based Secure Network System

    Directory of Open Access Journals (Sweden)

    Yogendra Kumar Jain

    2011-02-01

    Full Text Available A honeypot is a non-production system, design to interact with cyber-attackers to collect intelligence on attack techniques and behaviors. There has been great amount of work done in the field of networkintrusion detection over the past three decades. With networks getting faster and with the increasing dependence on the Internet both at the personal and commercial level, intrusion detection becomes a challenging process. The challenge here is not only to be able to actively monitor large numbers of systems, but also to be able to react quickly to different events. Before deploying a honeypot it is advisable to have a clear idea of what the honeypot should and should not do. There should be clear understandingof the operating systems to be used and services (like a web server, ftp server etc a honeypot will run. The risks involved should be taken into consideration and methods to tackle or reduce these risks should be understood. It is also advisable to have a plan on what to do should the honeypot be compromised. In case of production honeypots, a honeypot policy addressing security issues should be documented. Any legal issues with respect to the honeypots or their functioning should also be taken into consideration. In this paper we explain the relatively new concept of “honeypot.” Honeypots are a computer specifically designed to help learn the motives, skills and techniques of the hacker community and also describes in depth the concepts of honeypots and their contribution to the field of network security. The paper then proposes and designs an intrusion detection tool based on some of the existing intrusion detection techniques and the concept of honeypots.

  17. Network Medicine: A Network-based Approach to Human Diseases

    Science.gov (United States)

    Ghiassian, Susan Dina

    With the availability of large-scale data, it is now possible to systematically study the underlying interaction maps of many complex systems in multiple disciplines. Statistical physics has a long and successful history in modeling and characterizing systems with a large number of interacting individuals. Indeed, numerous approaches that were first developed in the context of statistical physics, such as the notion of random walks and diffusion processes, have been applied successfully to study and characterize complex systems in the context of network science. Based on these tools, network science has made important contributions to our understanding of many real-world, self-organizing systems, for example in computer science, sociology and economics. Biological systems are no exception. Indeed, recent studies reflect the necessity of applying statistical and network-based approaches in order to understand complex biological systems, such as cells. In these approaches, a cell is viewed as a complex network consisting of interactions among cellular components, such as genes and proteins. Given the cellular network as a platform, machinery, functionality and failure of a cell can be studied with network-based approaches, a field known as systems biology. Here, we apply network-based approaches to explore human diseases and their associated genes within the cellular network. This dissertation is divided in three parts: (i) A systematic analysis of the connectivity patterns among disease proteins within the cellular network. The quantification of these patterns inspires the design of an algorithm which predicts a disease-specific subnetwork containing yet unknown disease associated proteins. (ii) We apply the introduced algorithm to explore the common underlying mechanism of many complex diseases. We detect a subnetwork from which inflammatory processes initiate and result in many autoimmune diseases. (iii) The last chapter of this dissertation describes the

  18. Assessment of simplified ratio-based approaches for quantification of PET [(11)C]PBR28 data.

    Science.gov (United States)

    Matheson, Granville J; Plavén-Sigray, Pontus; Forsberg, Anton; Varrone, Andrea; Farde, Lars; Cervenka, Simon

    2017-12-01

    Kinetic modelling with metabolite-corrected arterial plasma is considered the gold standard for quantification of [(11)C]PBR28 binding to the translocator protein (TSPO), since there is no brain region devoid of TSPO that can serve as reference. The high variability in binding observed using this method has motivated the use of simplified ratio-based approaches such as standardised uptake value ratios (SUVRs) and distribution volume (VT) ratios (DVRs); however, the reliability of these measures and their relationship to VT have not been sufficiently evaluated. Data from a previously published [(11)C]PBR28 test-retest study in 12 healthy subjects were reanalysed. VT was estimated using a two-tissue compartment model. SUVR and DVR values for the frontal cortex were calculated using the whole brain and cerebellum as denominators. Test-retest reliability was assessed for all measures. Interregional correlations were performed for SUV and VT, and principal component analysis (PCA) was applied. Lastly, correlations between ratio-based outcomes and VT were assessed. Reliability was high for VT, moderate to high for SUV and SUVR, and poor for DVR. Very high interregional correlations were observed for both VT and SUV (all R (2) > 85%). The PCA showed that almost all variance (>98%) was explained by a single component. Ratio-based methods correlated poorly with VT (all R (2) < 34%, divided by genotype). The reliability was good for SUVR, but poor for DVR. Both outcomes showed little to no association with VT, questioning their validity. The high interregional correlations for VT and SUV suggest that after dividing by a denominator region, most of the biologically relevant signal is lost. These observations imply that results from TSPO PET studies using SUVR or DVR estimates should be interpreted with caution.

  19. Distribution network planning algorithm based on Hopfield neural network

    Institute of Scientific and Technical Information of China (English)

    GAO Wei-xin; LUO Xian-jue

    2005-01-01

    This paper presents a new algorithm based on Hopfield neural network to find the optimal solution for an electric distribution network. This algorithm transforms the distribution power network-planning problem into a directed graph-planning problem. The Hopfield neural network is designed to decide the in-degree of each node and is in combined application with an energy function. The new algorithm doesn't need to code city streets and normalize data, so the program is easier to be realized. A case study applying the method to a district of 29 street proved that an optimal solution for the planning of such a power system could be obtained by only 26 iterations. The energy function and algorithm developed in this work have the following advantages over many existing algorithms for electric distribution network planning: fast convergence and unnecessary to code all possible lines.

  20. Community Based Networks and 5G

    DEFF Research Database (Denmark)

    Williams, Idongesit

    2016-01-01

    The deployment of previous wireless standards has provided more benefits for urban dwellers than rural dwellers. 5G deployment may not be different. This paper identifies that Community Based Networks as carriers that deserve recognition as potential 5G providers may change this. The argument...... is hinged on a research aimed at understanding how and why Community Based Networks deploy telecom and Broadband infrastructure. The study was a qualitative study carried out inductively using Grounded Theory. Six cases were investigated.Two Community Based Network Mobilization models were identified....... The findings indicate that 5G connectivity can be extended to rural areas by these networks, via heterogenous networks. Hence the delivery of 5G data rates delivery via Wireless WAN in rural areas can be achieved by utilizing the causal factors of the identified models for Community Based Networks....

  1. Simplified voxel based and automatic VOl analysis of C-11 PIB uptake using a ligand and subject specific PET templates

    Energy Technology Data Exchange (ETDEWEB)

    Chae, S. Y.; Lee, J. H.; Oh, S. J. [Asan Medical Center, Seoul (Korea, Republic of)] (and others)

    2007-07-01

    We developed simplified analysing method of C-11 PIB PET using a ligand and subject specific PET templates and evaluated the usefulness of this method by comparing standard MR-based methods in Alzheimer disease (AD). We studied 7 patients with AD (71.5{+-}11.5, M/F=3/4) and 5 normal controls (68.4{+-}8.9, M/F=1/4) with C-11 PIB PET and T1 MRI. 90-min dynamic PET scan was performed after injection of C-11 PIB (370 MBq). Region to cerebellar ratio image (ratio image) was obtained from 60-90 min image and distribution volume ratio image (DVR image) was obtained from 90-min dynamic image using a Logan graphical analysis. Ligand and subject specific PET templates were created by spatial normalization of MR coregistered ratio images of AD and normal group to T1 MR MNI template using SPM2. We compared the outcome of voxel based and automatic VOl analysis employing 3 parametric images: MR template based spatially normalized MR coregistered DVR image (MR-DVR image), MR template based normalized MR coregistered ratio image (MR-ratio image), AD and normal group specific PET template based normalized ratio image (PET-ratio image) in all subjects. Voxel based analyses using 3 parametric images revealed significantly increased PIB retention in several brain regions such as both orbitofrontal and temporoparietal cortices and posterior cingulated gyri of AD compared to normal (FDR<0.05), however, the z-values of these regions were more higher in PET- and MR-ratio images than in MR-DVR image. Automatic VOl analyses using 3 parametric images also revealed significantly increased PIB retention values in same regions of AD (p<0.05). PIB retention values in PET-ratio images were significantly correlated with those in MR-ratio images (R=0.96, slope=0.99, p<0.001) and also MR-DVR images (R=0.95, slope = 1.8, p<0.001). Voxel based and automatic VOl analysis can be simply and accurately performed in a single static C-11 PIB PET image using a ligand and subject specific PET templates

  2. Development of a Networked Thumb Print-Based Staff Attendance Management System

    OpenAIRE

    Tolulope Awode; Oluwagbemiga Shoewu; Oluwabukola Mayowa Ishola; Segun O. Olatinwo

    2016-01-01

    This paper focuses on the development of a networked thumb print-based attendance management system. Now, more than ever, it has become necessary to give more thought to the methods of time and attendance management. The traditional time clock, manual attendance registering often no longer makes sense and simply does not meet the needs of the modern work environment. This system offers a comprehensive software solution that will streamline company's operations, and simplify timekeeping. Nowad...

  3. Optical OFDM-based Data Center Networks

    Directory of Open Access Journals (Sweden)

    Christoforos Kachris

    2013-07-01

    Full Text Available Cloud computing and web emerging application has created the need for more powerful data centers with high performance interconnection networks.Current data center networks,based on electronic packet switches,will not be able to satisfy the required communication bandwidth of emerging applications without consuming excessive power.Optical interconnercts have gained attention recently as a promising solution offering high throughput,low latency and reduced energy cosumption compared to current networks based in commidity switches.This paper presents a novel architecture for data center networks based on optical OFDM using Wavelength Selective Swithces(WSS. The OFDM-based solution provides high throughput,reduced latency and fine grain bandwidth allocation. A heuristic algorithm for the bandwidth allocation is presented and evaluated in terms of utilization. The power analysis shows that the proposed scheme is almost 60% more energy efficient compared to the current networks based on eommodity switches.

  4. Simplified production and concentration of HIV-1-based lentiviral vectors using HYPERFlask vessels and anion exchange membrane chromatography

    Science.gov (United States)

    Kutner, Robert H; Puthli, Sharon; Marino, Michael P; Reiser, Jakob

    2009-01-01

    Background During the past twelve years, lentiviral (LV) vectors have emerged as valuable tools for transgene delivery because of their ability to transduce nondividing cells and their capacity to sustain long-term transgene expression in target cells in vitro and in vivo. However, despite significant progress, the production and concentration of high-titer, high-quality LV vector stocks is still cumbersome and costly. Methods Here we present a simplified protocol for LV vector production on a laboratory scale using HYPERFlask vessels. HYPERFlask vessels are high-yield, high-performance flasks that utilize a multilayered gas permeable growth surface for efficient gas exchange, allowing convenient production of high-titer LV vectors. For subsequent concentration of LV vector stocks produced in this way, we describe a facile protocol involving Mustang Q anion exchange membrane chromatography. Results Our results show that unconcentrated LV vector stocks with titers in excess of 108 transduction units (TU) per ml were obtained using HYPERFlasks and that these titers were higher than those produced in parallel using regular 150-cm2 tissue culture dishes. We also show that up to 500 ml of an unconcentrated LV vector stock prepared using a HYPERFlask vessel could be concentrated using a single Mustang Q Acrodisc with a membrane volume of 0.18 ml. Up to 5.3 × 1010 TU were recovered from a single HYPERFlask vessel. Conclusion The protocol described here is easy to implement and should facilitate high-titer LV vector production for preclinical studies in animal models without the need for multiple tissue culture dishes and ultracentrifugation-based concentration protocols. PMID:19220915

  5. Speciation and cysteine-simplified physiological-based extraction technique (SBET) bioaccesibility of heavy metals in biosolids.

    Science.gov (United States)

    Tongesayi, Tsanangurayi; Dasilva, Patricia; Dilger, Katharine; Hollingsworth, Tristan; Mooney, Melissa

    2011-01-01

    Cysteine residues on proteins have a high affinity for metals yet formulations used to determine bioaccessibility do not contain cysteine or thiol-containing molecules. As a result, we used a cysteine-simplified physiological-based extraction technique (SBET) and, the conventional glycine-SBET to determine bioaccesibility of selected heavy metals in biosolids and compared the data. We also determined speciation of the selected metals in the biosolids to assess further the health risk posed the use of biosolids as a soil amendment in agricultural soils. Samples, including a certified reference standard were analyzed using x-ray fluorescence and flame atomic absorption. Bioaccessibility was higher in cysteine-SBET than glycine-SBET, and regression data show that the two methods give different sets of results. We proposed a bioaccessibility model that involves cysteine and the hydrogen ion complementing each other to dissolve metals. The model also includes a three mode-bioavailability mechanism: absorption of free metal ions; ligand-mediated transport of metal ions from solution; and ligand-mediated transport of metal ions directly from the biosolids into the cell. Low pH in the gut increases bioaccessibility but reduces bioavailability due to protonation of receptor ligands. With the exception of Fe, bioaccessibility was directly correlated to the sequential extraction availability which followed the order: Mn(90.3 %)>Zn(50.3 %)>Cd(26.5 %)>Cu(24.9 %)>Fe(0.367 %). We calculated bioavailability from bioaccessibility using literature estimates of percent bioavailabilities. The order of abundance of the analyzed metals in the biosolids was as follows: Fe>Mn>Zn>Cu>Pb>Cd.

  6. Robustness in semantic networks based on cliques

    Science.gov (United States)

    Grilo, M.; Fadigas, I. S.; Miranda, J. G. V.; Cunha, M. V.; Monteiro, R. L. S.; Pereira, H. B. B.

    2017-04-01

    Here, we present a study on how the structure of semantic networks based on cliques (specifically, article titles) behaves when vertex removal strategies (i.e., random and uniform vertex removal - RUR, highest degree vertex removal - HDR, and highest intermediation centrality vertex removal - HICR) are applied to this type of network. We propose a method for calculation of the average size of the small components and we identify the existence of a fraction (fp) where the topological structure of the network changes. Semantic networks based on cliques maintain the small-world phenomenon when subjected to RUR, HDR and HICR for fractions of removed vertices less than or equal to fp.

  7. Community Based Networks and 5G

    DEFF Research Database (Denmark)

    Williams, Idongesit

    2016-01-01

    The deployment of previous wireless standards has provided more benefits for urban dwellers than rural dwellers. 5G deployment may not be different. This paper identifies that Community Based Networks as carriers that deserve recognition as potential 5G providers may change this. The argument....... The findings indicate that 5G connectivity can be extended to rural areas by these networks, via heterogenous networks. Hence the delivery of 5G data rates delivery via Wireless WAN in rural areas can be achieved by utilizing the causal factors of the identified models for Community Based Networks....

  8. Feature-Based Classification of Networks

    CERN Document Server

    Barnett, Ian; Kuijjer, Marieke L; Mucha, Peter J; Onnela, Jukka-Pekka

    2016-01-01

    Network representations of systems from various scientific and societal domains are neither completely random nor fully regular, but instead appear to contain recurring structural building blocks. These features tend to be shared by networks belonging to the same broad class, such as the class of social networks or the class of biological networks. At a finer scale of classification within each such class, networks describing more similar systems tend to have more similar features. This occurs presumably because networks representing similar purposes or constructions would be expected to be generated by a shared set of domain specific mechanisms, and it should therefore be possible to classify these networks into categories based on their features at various structural levels. Here we describe and demonstrate a new, hybrid approach that combines manual selection of features of potential interest with existing automated classification methods. In particular, selecting well-known and well-studied features that ...

  9. Inference of Gene Regulatory Network Based on Local Bayesian Networks.

    Directory of Open Access Journals (Sweden)

    Fei Liu

    2016-08-01

    Full Text Available The inference of gene regulatory networks (GRNs from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN, to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only

  10. An immunity based network security risk estimation

    Institute of Scientific and Technical Information of China (English)

    LI Tao

    2005-01-01

    According to the relationship between the antibody concentration and the pathogen intrusion intensity, here we present an immunity-based model for the network security risk estimation (Insre). In Insre, the concepts and formal definitions of self,nonself, antibody, antigen and lymphocyte in the network security domain are given. Then the mathematical models of the self-tolerance, the clonal selection, the lifecycle of mature lymphocyte, immune memory and immune surveillance are established. Building upon the above models, a quantitative computation model for network security risk estimation,which is based on the calculation of antibody concentration, is thus presented. By using Insre, the types and intensity of network attacks, as well as the risk level of network security, can be calculated quantitatively and in real-time. Our theoretical analysis and experimental results show that Insre is a good solution to real-time risk evaluation for the network security.

  11. Testing of a simplified LED based vis/NIR system for rapid ripeness evaluation of white grape (Vitis vinifera L.) for Franciacorta wine.

    Science.gov (United States)

    Giovenzana, Valentina; Civelli, Raffaele; Beghi, Roberto; Oberti, Roberto; Guidetti, Riccardo

    2015-11-01

    The aim of this work was to test a simplified optical prototype for a rapid estimation of the ripening parameters of white grape for Franciacorta wine directly in field. Spectral acquisition based on reflectance at four wavelengths (630, 690, 750 and 850 nm) was proposed. The integration of a simple processing algorithm in the microcontroller software would allow to visualize real time values of spectral reflectance. Non-destructive analyses were carried out on 95 grape bunches for a total of 475 berries. Samplings were performed weekly during the last ripening stages. Optical measurements were carried out both using the simplified system and a portable commercial vis/NIR spectrophotometer, as reference instrument for performance comparison. Chemometric analyses were performed in order to extract the maximum useful information from optical data. Principal component analysis (PCA) was performed for a preliminary evaluation of the data. Correlations between the optical data matrix and ripening parameters (total soluble solids content, SSC; titratable acidity, TA) were carried out using partial least square (PLS) regression for spectra and using multiple linear regression (MLR) for data from the simplified device. Classification analysis were also performed with the aim of discriminate ripe and unripe samples. PCA, MLR and classification analyses show the effectiveness of the simplified system in separating samples among different sampling dates and in discriminating ripe from unripe samples. Finally, simple equations for SSC and TA prediction were calculated. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. A simplified model for generating sequences of global solar radiation data for isolated sites: Using artificial neural network and a library of Markov transition matrices approach

    Energy Technology Data Exchange (ETDEWEB)

    Mellit, A. [University Center of Medea, Institute of Engineering Sciences, Department of Electronics, Ain Dahab, Mdea 26000 (Algeria); Benghanem, M. [University of Sciences Technology Houari Boumediene (USTHB), Faculty of Electrical Engineering, El-Alia, P.O. Box 32, Algiers 16111 (Algeria); Arab, A. Hadj [Development Center of Renewable Energy (CDER), P.O. Box 62, Bouzareah, Algiers 16000 (Algeria); Guessoum, A. [Faculty of Science Engineering, Department of Electronics, Blida University, Blida (Algeria)

    2005-11-01

    The purpose of this work is to develop a hybrid model which will be used to predict the daily global solar radiation data by combining between an artificial neural network (ANN) and a library of Markov transition matrices (MTM) approach. Developed model can generate a sequence of global solar radiation data using a minimum of input data (latitude, longitude and altitude), especially in isolated sites. A data base of daily global solar radiation data has been collected from 60 meteorological stations in Algeria during 1991-2000. Also a typical meteorological year (TMY) has been built from this database. Firstly, a neural network block has been trained based on 60 known monthly solar radiation data from the TMY. In this way, the network was trained to accept and even handle a number of unusual cases. The neural network can generate the monthly solar radiation data. Secondly, these data have been divided by corresponding extraterrestrial value in order to obtain the monthly clearness index values. Based on these monthly clearness indexes and using a library of MTM block we can generate the sequences of daily clearness indexes. Known data were subsequently used to investigate the accuracy of the prediction. Furthermore, the unknown validation data set produced very accurate prediction; with an RMSE error not exceeding 8% between the measured and predicted data. A correlation coefficient ranging from 90% and 92% have been obtained; also this model has been compared to the traditional models AR, ARMA, Markov chain, MTM and measured data. Results obtained indicate that the proposed model can successfully be used for the estimation of the daily solar radiation data for any locations in Algeria by using as input the altitude, the longitude, and the latitude. Also, the model can be generalized for any location in the world. An application of sizing PV systems in isolated sites has been applied in order to confirm the validity of this model. (author)

  13. IP Network Management Model Based on NGOSS

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jin-yu; LI Hong-hui; LIU Feng

    2004-01-01

    This paper addresses a management model for IP network based on Next Generation Operation Support System (NGOSS). It makes the network management on the base of all the operation actions of ISP, It provides QoS to user service through the whole path by providing end-to-end Service Level Agreements (SLA) management through whole path. Based on web and coordination technology, this paper gives an implement architecture of this model.

  14. Prototyping Web Services based Network Monitoring

    NARCIS (Netherlands)

    Drevers, Thomas; van de Meent, R.; Pras, Aiko; Harjo, J.; Moltchanov, D.; Silverajan, B.

    Web services is one of the emerging approaches in network management. This paper describes the design and implementation of four Web services based network monitoring prototypes. Each prototype follows a speci��?c approach to retrieve management data, ranging from retrieving a single management

  15. Modeling the interdependent network based on two-mode networks

    Science.gov (United States)

    An, Feng; Gao, Xiangyun; Guan, Jianhe; Huang, Shupei; Liu, Qian

    2017-10-01

    Among heterogeneous networks, there exist obviously and closely interdependent linkages. Unlike existing research primarily focus on the theoretical research of physical interdependent network model. We propose a two-layer interdependent network model based on two-mode networks to explore the interdependent features in the reality. Specifically, we construct a two-layer interdependent loan network and develop several dependent features indices. The model is verified to enable us to capture the loan dependent features of listed companies based on loan behaviors and shared shareholders. Taking Chinese debit and credit market as case study, the main conclusions are: (1) only few listed companies shoulder the main capital transmission (20% listed companies occupy almost 70% dependent degree). (2) The control of these key listed companies will be more effective of avoiding the spreading of financial risks. (3) Identifying the companies with high betweenness centrality and controlling them could be helpful to monitor the financial risk spreading. (4) The capital transmission channel among Chinese financial listed companies and Chinese non-financial listed companies are relatively strong. However, under greater pressure of demand of capital transmission (70% edges failed), the transmission channel, which constructed by debit and credit behavior, will eventually collapse.

  16. Certain investigations on the reduction of side lobe level of an uniform linear antenna array using biogeography based optimization technique with sinusoidal migration model and simplified-BBO

    Indian Academy of Sciences (India)

    T S Jeyali Laseetha; R Sukanesh

    2014-02-01

    In this paper, we propose biogeography based optimization technique, with linear and sinusoidal migration models and simplified biogeography based optimization (S-BBO), for uniformly spaced linear antenna array synthesis to maximize the reduction of side lobe level (SLL). This paper explores biogeography theory. It generalizes two migration models in BBO namely, linear migration model and sinusoidal migration model. The performance of SLL reduction in ULA is investigated. Our performance study shows that among the two, sinusoidal migration model is a promising candidate for optimization. In our work, simplified – BBO algorithmis also deployed. This determines an optimum set value for amplitude excitations of antenna array elements that generate a radiation pattern with maximum side lobe level reduction. Our detailed investigation also shows that sinusoidal migration model of BBO performs better compared to the other evolutionary algorithms discussed in this paper.

  17. Trust Based Routing in Ad Hoc Network

    Science.gov (United States)

    Talati, Mikita V.; Valiveti, Sharada; Kotecha, K.

    Ad Hoc network often termed as an infrastructure-less, self- organized or spontaneous network.The execution and survival of an ad-hoc network is solely dependent upon the cooperative and trusting nature of its nodes. However, this naive dependency on intermediate nodes makes the ad-hoc network vulnerable to passive and active attacks by malicious nodes and cause inflict severe damage. A number of protocols have been developed to secure ad-hoc networks using cryptographic schemes, but all rely on the presence of trust authority. Due to mobility of nodes and limitation of resources in wireless network one interesting research area in MANET is routing. This paper offers various trust models and trust based routing protocols to improve the trustworthiness of the neighborhood.Thus it helps in selecting the most secure and trustworthy route from the available ones for the data transfer.

  18. Model-based control of networked systems

    CERN Document Server

    Garcia, Eloy; Montestruque, Luis A

    2014-01-01

    This monograph introduces a class of networked control systems (NCS) called model-based networked control systems (MB-NCS) and presents various architectures and control strategies designed to improve the performance of NCS. The overall performance of NCS considers the appropriate use of network resources, particularly network bandwidth, in conjunction with the desired response of the system being controlled.   The book begins with a detailed description of the basic MB-NCS architecture that provides stability conditions in terms of state feedback updates . It also covers typical problems in NCS such as network delays, network scheduling, and data quantization, as well as more general control problems such as output feedback control, nonlinear systems stabilization, and tracking control.   Key features and topics include: Time-triggered and event-triggered feedback updates Stabilization of uncertain systems subject to time delays, quantization, and extended absence of feedback Optimal control analysis and ...

  19. Evaluation of the reproductive performance of rabbits does fed a half-simplified diet based on cassava byproducts

    Directory of Open Access Journals (Sweden)

    Andréia Fróes Galuci Oliveira

    2011-11-01

    Full Text Available A total of 70 five-month-old female New Zealand White rabbits were assigned in a completely randomized design, over three reproductive cycles, with two treatments: a reference diet and a half-simplified diet containing 79.83% cassava byproduct. The study evaluated body weight and feed intake of does, feed cost, number and total body weight of kits at kindling and weaning per female during three cycles, number and percentage of mortality/female/cycle, and weight gain of kits from birth to weaning. No interaction was observed between the diets and among the reproductive cycles for any evaluated characteristics. The body weight of does at the moment of weaning was similar in both groups for all three reproductive cycles. However, does fed the half-simplified diet had lower feed intake during the three reproductive cycles and, consequently, more reproductive flaws. The number of kits at weaning, body weight of kits at kindling and weaning, weight gain of kits from birth to weaning, and total body weight of kits at weaning were lower for the group of does fed the half-simplified diet and, consequently, there was a higher number and percentage of dead kits in this group. The total numbers of kits at kindling and weaning and total body weight of kits at birth during all three reproductive cycles were similar between the groups; however, total body weight of weaning rabbits was higher for the animals receiving the reference diet. It is possible to conclude that although the use of the half-simplified diet decreases the reproductive performance of does, it reduces feed cost per kg of body weight by 23.63% compared with the reference diet, proving to be a viable nutritional option for rabbit production.

  20. An attractor-based complexity measurement for Boolean recurrent neural networks.

    Science.gov (United States)

    Cabessa, Jérémie; Villa, Alessandro E P

    2014-01-01

    We provide a novel refined attractor-based complexity measurement for Boolean recurrent neural networks that represents an assessment of their computational power in terms of the significance of their attractor dynamics. This complexity measurement is achieved by first proving a computational equivalence between Boolean recurrent neural networks and some specific class of ω-automata, and then translating the most refined classification of ω-automata to the Boolean neural network context. As a result, a hierarchical classification of Boolean neural networks based on their attractive dynamics is obtained, thus providing a novel refined attractor-based complexity measurement for Boolean recurrent neural networks. These results provide new theoretical insights to the computational and dynamical capabilities of neural networks according to their attractive potentialities. An application of our findings is illustrated by the analysis of the dynamics of a simplified model of the basal ganglia-thalamocortical network simulated by a Boolean recurrent neural network. This example shows the significance of measuring network complexity, and how our results bear new founding elements for the understanding of the complexity of real brain circuits.

  1. An attractor-based complexity measurement for Boolean recurrent neural networks.

    Directory of Open Access Journals (Sweden)

    Jérémie Cabessa

    Full Text Available We provide a novel refined attractor-based complexity measurement for Boolean recurrent neural networks that represents an assessment of their computational power in terms of the significance of their attractor dynamics. This complexity measurement is achieved by first proving a computational equivalence between Boolean recurrent neural networks and some specific class of ω-automata, and then translating the most refined classification of ω-automata to the Boolean neural network context. As a result, a hierarchical classification of Boolean neural networks based on their attractive dynamics is obtained, thus providing a novel refined attractor-based complexity measurement for Boolean recurrent neural networks. These results provide new theoretical insights to the computational and dynamical capabilities of neural networks according to their attractive potentialities. An application of our findings is illustrated by the analysis of the dynamics of a simplified model of the basal ganglia-thalamocortical network simulated by a Boolean recurrent neural network. This example shows the significance of measuring network complexity, and how our results bear new founding elements for the understanding of the complexity of real brain circuits.

  2. Dynamics-based centrality for directed networks

    Science.gov (United States)

    Masuda, Naoki; Kori, Hiroshi

    2010-11-01

    Determining the relative importance of nodes in directed networks is important in, for example, ranking websites, publications, and sports teams, and for understanding signal flows in systems biology. A prevailing centrality measure in this respect is the PageRank. In this work, we focus on another class of centrality derived from the Laplacian of the network. We extend the Laplacian-based centrality, which has mainly been applied to strongly connected networks, to the case of general directed networks such that we can quantitatively compare arbitrary nodes. Toward this end, we adopt the idea used in the PageRank to introduce global connectivity between all the pairs of nodes with a certain strength. Numerical simulations are carried out on some networks. We also offer interpretations of the Laplacian-based centrality for general directed networks in terms of various dynamical and structural properties of networks. Importantly, the Laplacian-based centrality defined as the stationary density of the continuous-time random walk with random jumps is shown to be equivalent to the absorption probability of the random walk with sinks at each node but without random jumps. Similarly, the proposed centrality represents the importance of nodes in dynamics on the original network supplied with sinks but not with random jumps.

  3. Clustering in mobile ad hoc network based on neural network

    Institute of Scientific and Technical Information of China (English)

    CHEN Ai-bin; CAI Zi-xing; HU De-wen

    2006-01-01

    An on-demand distributed clustering algorithm based on neural network was proposed. The system parameters and the combined weight for each node were computed, and cluster-heads were chosen using the weighted clustering algorithm, then a training set was created and a neural network was trained. In this algorithm, several system parameters were taken into account, such as the ideal node-degree, the transmission power, the mobility and the battery power of the nodes. The algorithm can be used directly to test whether a node is a cluster-head or not. Moreover, the clusters recreation can be speeded up.

  4. Analysis of effect factors-based stochastic network planning model

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Looking at all the indeterminate factors as a whole and regarding activity durations as independent random variables,the traditional stochastic network planning models ignore the inevitable relationship and dependence among activity durations when more than one activity is possibly affected by the same indeterminate factors.On this basis of analysis of indeterminate effect factors of durations,the effect factors-based stochastic network planning (EFBSNP) model is proposed,which emphasizes on the effects of not only logistic and organizational relationships,but also the dependent relationships,due to indeterminate factors among activity durations on the project period.By virtue of indeterminate factor analysis the model extracts and describes the quantitatively indeterminate effect factors,and then takes into account the indeterminate factors effect schedule by using the Monte Carlo simulation technique.The method is flexible enough to deal with effect factors and is coincident with practice.A software has been developed to simplify the model-based calculation,in VisualStudio.NET language.Finally,a case study is included to demonstrate the applicability of the proposed model and comparison is made with some advantages over the existing models.

  5. Building a Network Based Laboratory Environment

    Directory of Open Access Journals (Sweden)

    Sea Shuan Luo

    2009-12-01

    Full Text Available This paper presents a comparative study about the development of a network based laboratory environment in the “Unix introduction” course for the undergraduate students. The study results and the response from the students from 2005 to 2006 will be used to better understand what kind of method is more suitable for students. We also use the data collected to adjust our teaching strategy and try to build up a network based laboratory environment.

  6. Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks

    Directory of Open Access Journals (Sweden)

    Ming Li

    2016-09-01

    Full Text Available Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE, and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes.

  7. Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks.

    Science.gov (United States)

    Li, Ming; Chen, Pengpeng; Gao, Shouwan

    2016-09-13

    Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes.

  8. Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks

    Science.gov (United States)

    Li, Ming; Chen, Pengpeng; Gao, Shouwan

    2016-01-01

    Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes. PMID:27649170

  9. A Developed Network Layer Handover Based Wireless Networks

    Directory of Open Access Journals (Sweden)

    Ali Safa Sadiq

    2015-02-01

    Full Text Available This paper proposes an Advanced Mobility Handover (AMH scheme based on Wireless Local Area Networks (WLANs by developing a network layer handover procedure which triggers messages to be sent to the next access point. The proposed AMH scheme performs the network handover process, which is represented by binding update procedure in advance during the time mobile node is still connected to the current AP in the link layer. Furthermore, a unique home IPv6 address is developed to maintain an IP communication with other corresponding nodes without a care-of-address during mobile node$'$s roaming process. This can contribute significantly to reducing network layer handover delays and signaling costs by eliminate the process of obtaining a new care-of-address and processing the handover of network layer in advance while the mobile node is still communicating with the current access point. Eventually, the conducted OMNET++ simulated scenario shows that the proposed AMH scheme performs the best in terms of reducing the handover delay as compared to the state of the art.

  10. Role-based similarity in directed networks

    CERN Document Server

    Cooper, Kathryn

    2010-01-01

    The widespread relevance of increasingly complex networks requires methods to extract meaningful coarse-grained representations of such systems. For undirected graphs, standard community detection methods use criteria largely based on density of connections to provide such representations. We propose a method for grouping nodes in directed networks based on the role of the nodes in the network, understood in terms of patterns of incoming and outgoing flows. The role groupings are obtained through the clustering of a similarity matrix, formed by the distances between feature vectors that contain the number of in and out paths of all lengths for each node. Hence nodes operating in a similar flow environment are grouped together although they may not themselves be densely connected. Our method, which includes a scale factor that reveals robust groupings based on increasingly global structure, provides an alternative criterion to uncover structure in networks where there is an implicit flow transfer in the system...

  11. Rule-Based Network Service Provisioning

    Directory of Open Access Journals (Sweden)

    Rudy Deca

    2012-10-01

    Full Text Available Due to the unprecedented development of networks, manual network service provisioning is becoming increasingly risky, error-prone, expensive, and time-consuming. To solve this problem,rule-based methods can provide adequate leverage for automating various network management tasks. This paper presents a rule-based solution for automated network service provisioning. The proposed approach captures configuration data interdependencies using high-level, service-specific, user-configurable rules. We focus on the service validation task, which is illustrated by means of a case study.Based on numerical results, we analyse the influence of the network-level complexity factors and rule descriptive features on the rule efficiency. This analysis shows the operators how to increase rule efficiency while keeping the rules simple and the rule set compact. We present a technique that allows operators to increase the error coverage, and we show that high error coverage scales well when the complexity of networks and services increases.We reassess the correlation function between specific rule efficiency and rule complexity metrics found in previous work, and show that this correlation function holds for various sizes, types, and complexities of networks and services.

  12. Simplifying Massive Contour Maps

    DEFF Research Database (Denmark)

    Arge, Lars; Deleuran, Lasse Kosetski; Mølhave, Thomas;

    2012-01-01

    We present a simple, efficient and practical algorithm for constructing and subsequently simplifying contour maps from massive high-resolution DEMs, under some practically realistic assumptions on the DEM and contours.......We present a simple, efficient and practical algorithm for constructing and subsequently simplifying contour maps from massive high-resolution DEMs, under some practically realistic assumptions on the DEM and contours....

  13. Network-based Database Course

    DEFF Research Database (Denmark)

    Nielsen, J.N.; Knudsen, Morten; Nielsen, Jens Frederik Dalsgaard

    A course in database design and implementation has been de- signed, utilizing existing network facilities. The course is an elementary course for students of computer engineering. Its purpose is to give the students a theoretical database knowledge as well as practical experience with design...... and implementation. A tutorial relational database and the students self-designed databases are implemented on the UNIX system of Aalborg University, thus giving the teacher the possibility of live demonstrations in the lecture room, and the students the possibility of interactive learning in their working rooms...

  14. Network-based Database Course

    DEFF Research Database (Denmark)

    Nielsen, J.N.; Knudsen, Morten; Nielsen, Jens Frederik Dalsgaard

    A course in database design and implementation has been de- signed, utilizing existing network facilities. The course is an elementary course for students of computer engineering. Its purpose is to give the students a theoretical database knowledge as well as practical experience with design...... and implementation. A tutorial relational database and the students self-designed databases are implemented on the UNIX system of Aalborg University, thus giving the teacher the possibility of live demonstrations in the lecture room, and the students the possibility of interactive learning in their working rooms...

  15. Network Intrusion Detection based on GMKL Algorithm

    Directory of Open Access Journals (Sweden)

    Li Yuxiang

    2013-06-01

    Full Text Available According to the 31th statistical reports of China Internet network information center (CNNIC, by the end of December 2012, the number of Chinese netizens has reached 564 million, and the scale of mobile Internet users also reached 420 million. But when the network brings great convenience to people's life, it also brings huge threat in the life of people. So through collecting and analyzing the information in the computer system or network we can detect any possible behaviors that can damage the availability, integrity and confidentiality of the computer resource, and make timely treatment to these behaviors which have important research significance to improve the operation environment of network and network service. At present, the Neural Network, Support Vector machine (SVM and Hidden Markov Model, Fuzzy inference and Genetic Algorithms are introduced into the research of network intrusion detection, trying to build a healthy and secure network operation environment. But most of these algorithms are based on the total sample and it also hypothesizes that the number of the sample is infinity. But in the field of network intrusion the collected data often cannot meet the above requirements. It often shows high latitudes, variability and small sample characteristics. For these data using traditional machine learning methods are hard to get ideal results. In view of this, this paper proposed a Generalized Multi-Kernel Learning method to applied to network intrusion detection. The Generalized Multi-Kernel Learning method can be well applied to large scale sample data, dimension complex, containing a large number of heterogeneous information and so on. The experimental results show that applying GMKL to network attack detection has high classification precision and low abnormal practical precision.

  16. Automated implementation of rule-based expert systems with neural networks for time-critical applications

    Science.gov (United States)

    Ramamoorthy, P. A.; Huang, Song; Govind, Girish

    1991-01-01

    In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed.

  17. Identifying network public opinion leaders based on Markov Logic Networks.

    Science.gov (United States)

    Zhang, Weizhe; Li, Xiaoqiang; He, Hui; Wang, Xing

    2014-01-01

    Public opinion emergencies have important effect on social activities. Recognition of special communities like opinion leaders can contribute to a comprehensive understanding of the development trend of public opinion. In this paper, a network opinion leader recognition method based on relational data was put forward, and an opinion leader recognition system integrating public opinion data acquisition module, data characteristic selection, and fusion module as well as opinion leader discovery module based on Markov Logic Networks was designed. The designed opinion leader recognition system not only can overcome the incomplete data acquisition and isolated task of traditional methods, but also can recognize opinion leaders comprehensively with considerations to multiple problems by using the relational model. Experimental results demonstrated that, compared with the traditional methods, the proposed method can provide a more accurate opinion leader recognition and has good noise immunity.

  18. 基于粒计算的SDG模型简化方法%The Simplified Method of SDG Model Based on Granular Computing

    Institute of Scientific and Technical Information of China (English)

    王培鑫; 田娟; 谢刚

    2012-01-01

    本文针对传统简化SDG模型方法存在简化不精、人工经验要求多的问题,提出了一种基于粒计算的SDG模型简化方法。该方法利用二进制粒矩阵约简节点组成的条件属性中的节点,在不影响完备性的前提下,达到简化模型的目的。最后以除氧器系统为例验证此方法的可行性。%In this paper, the author propose a simplified method of SDG model based on granular computing to solve problems which are the simplification is not refinded and a lots specialistic experience is required. Without affecting the completeness of SDG model, this method make use of bit granular matrix(BGrM) to simplify condition’s attributes for simplifying model. Finally, the deaerator system is as an example to verify the feasibility of this method.

  19. Handwritten digits recognition based on immune network

    Science.gov (United States)

    Li, Yangyang; Wu, Yunhui; Jiao, Lc; Wu, Jianshe

    2011-11-01

    With the development of society, handwritten digits recognition technique has been widely applied to production and daily life. It is a very difficult task to solve these problems in the field of pattern recognition. In this paper, a new method is presented for handwritten digit recognition. The digit samples firstly are processed and features extraction. Based on these features, a novel immune network classification algorithm is designed and implemented to the handwritten digits recognition. The proposed algorithm is developed by Jerne's immune network model for feature selection and KNN method for classification. Its characteristic is the novel network with parallel commutating and learning. The performance of the proposed method is experimented to the handwritten number datasets MNIST and compared with some other recognition algorithms-KNN, ANN and SVM algorithm. The result shows that the novel classification algorithm based on immune network gives promising performance and stable behavior for handwritten digits recognition.

  20. An Improved Interconnection Network Based on NIN

    Institute of Scientific and Technical Information of China (English)

    Li Fei; Li Zhi-tang

    2004-01-01

    The Novel Interconnection Network (NIN)based on inverted-graph topology and crossbar switch is a kind of lower latency and higher throughput interconnection network. But it bas a vital disadvantage, high hardware complexity. In order to reduce system hardware cost, an improved NIN (ININ) structure is proposed. As same as NIN,ININ has constant network diameter. Besides of keeping ad vantages of NIN, hardware cost of ININ is lower than NIN.Furthermore, we design a new deadlock-free routing algorithm for the improved NIN.

  1. Noise Image Filtering Method Based on Simplified PCNN%基于简化PCNN的脉冲噪声滤波

    Institute of Scientific and Technical Information of China (English)

    郭旭展; 姚建峰

    2015-01-01

    基于脉冲耦合神经网络,提出了一种有效的脉冲噪声图像滤波算法。利用 PCNN相似群神经元同步发放脉冲的特性检测噪声点,并利用中值滤波对噪声点进行滤波。仿真表明,该方法对不同强度的噪声图像均体现了较好的滤波性能,在去噪效果和运行效率上同其它方法相比具有明显优势。%Based on Pulse Coupled Neural networks ,an effective pulse noise image filtering method is proposed .Synchro‐nous pulses were burst by using the similar groups of neurons in a PCNN ,whereby the noise pixels are detected;then me‐dian filtering method filtered the noise in a noise image .Simulation results show that the proposed method has excellent filtering performance for the noise images of different noise intensity ,the proposed method has remarkable superiority over other ones in both simulation performance and running efficiency .

  2. A precise clock distribution network for MRPC-based experiments

    Science.gov (United States)

    Wang, S.; Cao, P.; Shang, L.; An, Q.

    2016-06-01

    In high energy physics experiments, the MRPC (Multi-Gap Resistive Plate Chamber) detectors are widely used recently which can provide higher-resolution measurement for particle identification. However, the application of MRPC detectors leads to a series of challenges in electronics design with large number of front-end electronic channels, especially for distributing clock precisely. To deal with these challenges, this paper presents a universal scheme of clock transmission network for MRPC-based experiments with advantages of both precise clock distribution and global command synchronization. For precise clock distributing, the clock network is designed into a tree architecture with two stages: the first one has a point-to-multipoint long range bidirectional distribution with optical channels and the second one has a fan-out structure with copper link inside readout crates. To guarantee the precision of clock frequency or phase, the r-PTP (reduced Precision Time Protocol) and the DDMTD (digital Dual Mixer Time Difference) methods are used for frequency synthesis, phase measurement and adjustment, which is implemented by FPGA (Field Programmable Gate Array) in real-time. In addition, to synchronize global command execution, based upon this clock distribution network, synchronous signals are coded with clock for transmission. With technique of encoding/decoding and clock data recovery, signals such as global triggers or system control commands, can be distributed to all front-end channels synchronously, which greatly simplifies the system design. The experimental results show that both the clock jitter (RMS) and the clock skew can be less than 100 ps.

  3. The Integrated Control-Mechanism in ATM-Based Networks

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Survivability is one of the important issues in ATM-based networks since even a single network element failure may cause a serious data loss. This paper introduces a new restoration mechanism based on multi-layer ATM survivable network management architecture. This mechanism integrates the general control and restoration control by establishing the Working VPs logical network, Backup VPs logical network and spare logical network in order to optimally utilize the network resources while maintaining the restoration requirements.

  4. A segmentation method of color blindness detection image based on simplified PCNN%一种基于简化PCNN的色盲检测图分割方法

    Institute of Scientific and Technical Information of China (English)

    郭业才; 蒋峰; 龚溪

    2013-01-01

    在色盲检测图及脉冲耦合神经网络(pulse-coupled neural networks,简称PCNN)的基础上,提出一种基于简化PCNN模型的色盲检测图分割方法,该方法首先根据欧式距离计算彩色图像色差,通过设定一个合适的阈值,将与红色相似的颜色替换成白色,初步分离图像中的目标与背景,对预处理后的色盲检测图像,用典型的PCNN简化模型对其红色分量进行分割,最后用形态学闭运算优化得到最终的分割结果.实验结果表明,该方法能准确分割出色盲图像中的图形,且简单有效.%On the basis of the color blindness detection images and pulse coupled neural network (PCNN) , a segmentation method of color blindness detection image based on simplified PCNN was proposed. In this proposed method, the chromatic aberration was computed by Euclidean distance, the color similar to red was replaced with white by setting an appropriate threshold, then the target and background of image were preliminary separated, and the red component after pretreatment was segmented via using the typical simplified PCNN model, and finally the segmentation image was optimized by morphological closing operation. The experimental results showed that the method not only could accurately segment the color blindness images but also was simple and effective.

  5. Optimization with artificial neural network systems - A mapping principle and a comparison to gradient based methods

    Science.gov (United States)

    Leong, Harrison Monfook

    1988-01-01

    General formulae for mapping optimization problems into systems of ordinary differential equations associated with artificial neural networks are presented. A comparison is made to optimization using gradient-search methods. The performance measure is the settling time from an initial state to a target state. A simple analytical example illustrates a situation where dynamical systems representing artificial neural network methods would settle faster than those representing gradient-search. Settling time was investigated for a more complicated optimization problem using computer simulations. The problem was a simplified version of a problem in medical imaging: determining loci of cerebral activity from electromagnetic measurements at the scalp. The simulations showed that gradient based systems typically settled 50 to 100 times faster than systems based on current neural network optimization methods.

  6. A network-based dynamical ranking system

    CERN Document Server

    Motegi, Shun

    2012-01-01

    Ranking players or teams in sports is of practical interests. From the viewpoint of networks, a ranking system is equivalent a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score (i.e., strength) of a player, for example, depends on time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. Our ranking system, also interpreted as a centrality measure for directed temporal networks, has two parameters. One parameter represents the exponential decay rate of the past score, and the other parameter controls the effect of indirect wins on the score. We derive a set of linear online update equ...

  7. Multiuser detector based on wavelet networks

    Institute of Scientific and Technical Information of China (English)

    王伶; 焦李成; 陶海红; 刘芳

    2004-01-01

    Multiple access interference (MAI) and near-far problem are two major obstacles in DS-CDMA systems.Combining wavelet neural networks and two matched filters, the novel multiuser detector, which is based on multiple variable function estimation wavelet networks over single path asynchronous channel and space-time channel respectively is presented. Excellent localization characteristics of wavelet functions in both time and frequency domains allowed hierarchical multiple resolution learning of input-output data mapping. The mathematic frame of the neural networks and error back ward propagation algorithm are introduced. The complexity of the multiuser detector only depends on that of wavelet networks. With numerical simulations and performance analysis, it indicates that the multiuser detector has excellent performance in eliminating MAI and near-far resistance.

  8. Neural Network Based 3D Surface Reconstruction

    Directory of Open Access Journals (Sweden)

    Vincy Joseph

    2009-11-01

    Full Text Available This paper proposes a novel neural-network-based adaptive hybrid-reflectance three-dimensional (3-D surface reconstruction model. The neural network combines the diffuse and specular components into a hybrid model. The proposed model considers the characteristics of each point and the variant albedo to prevent the reconstructed surface from being distorted. The neural network inputs are the pixel values of the two-dimensional images to be reconstructed. The normal vectors of the surface can then be obtained from the output of the neural network after supervised learning, where the illuminant direction does not have to be known in advance. Finally, the obtained normal vectors can be applied to integration method when reconstructing 3-D objects. Facial images were used for training in the proposed approach

  9. Designing Network-based Business Model Ontology

    DEFF Research Database (Denmark)

    Hashemi Nekoo, Ali Reza; Ashourizadeh, Shayegheh; Zarei, Behrouz

    2015-01-01

    Survival on dynamic environment is not achieved without a map. Scanning and monitoring of the market show business models as a fruitful tool. But scholars believe that old-fashioned business models are dead; as they are not included the effect of internet and network in themselves. This paper...... is going to propose e-business model ontology from the network point of view and its application in real world. The suggested ontology for network-based businesses is composed of individuals` characteristics and what kind of resources they own. also, their connections and pre-conceptions of connections...... such as shared-mental model and trust. However, it mostly covers previous business model elements. To confirm the applicability of this ontology, it has been implemented in business angel network and showed how it works....

  10. FWS Interest Simplified

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — These boundaries are simplified from the U.S. Fish and Wildlife Service Real Estate Interest data layer containing polygons representing tracts of land (parcels) in...

  11. Stealth Supersymmetry Simplified

    CERN Document Server

    Fan, JiJi; Pinner, David; Reece, Matthew; Ruderman, Joshua T

    2015-01-01

    In Stealth Supersymmetry, bounds on superpartners from direct searches can be notably weaker than in standard supersymmetric scenarios, due to suppressed missing energy. We present a set of simplified models of Stealth Supersymmetry that motivate 13 TeV LHC searches. We focus on simplified models within the Natural Supersymmetry framework, in which the gluino, stop, and Higgsino are assumed to be lighter than other superpartners. Our simplified models exhibit novel decay patterns that differ significantly from topologies of the Minimal Supersymmetric Standard Model, with and without $R$-parity. We determine limits on stops and gluinos from searches at the 8 TeV LHC. Existing searches constitute a powerful probe of Stealth Supersymmetry gluinos with certain topologies. However, we identify simplified models where the gluino can be considerably lighter than 1 TeV. Stops are significantly less constrained in Stealth Supersymmetry than the MSSM, and we have identified novel stop decay topologies that are complete...

  12. FWS Interest Simplified

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — These boundaries are simplified from the U.S. Fish and Wildlife Service Real Estate Interest data layer containing polygons representing tracts of land (parcels) in...

  13. Network Entropy Based on Topology Configuration and Its Computation to Random Networks

    Institute of Scientific and Technical Information of China (English)

    LI Ji; WANG Bing-Hong; WANG Wen-Xu; ZHOU Tao

    2008-01-01

    A definition of network entropy is presented, and as an example, the relationship between the value of network entropy of ER network model and the connect probability p as well as the total nodes N is discussed. The theoretical result and the simulation result based on the network entropy of the ER network are in agreement well with each other. The result indicated that different from the other network entropy reported before, the network entropy defined here has an obvious difference from different type of random networks or networks having different total nodes. Thus, this network entropy may portray the characters of complex networks better. It is also pointed out that, with the aid of network entropy defined, the concept of equilibrium networks and the concept of non-equilibrium networks may be introduced, and a quantitative measurement to describe the deviation to equilibrium state of a complex network is carried out.

  14. p53 transactivation and the impact of mutations, cofactors and small molecules using a simplified yeast-based screening system.

    Directory of Open Access Journals (Sweden)

    Virginia Andreotti

    Full Text Available BACKGROUND: The p53 tumor suppressor, which is altered in most cancers, is a sequence-specific transcription factor that is able to modulate the expression of many target genes and influence a variety of cellular pathways. Inactivation of the p53 pathway in cancer frequently occurs through the expression of mutant p53 protein. In tumors that retain wild type p53, the pathway can be altered by upstream modulators, particularly the p53 negative regulators MDM2 and MDM4. METHODOLOGY/PRINCIPAL FINDINGS: Given the many factors that might influence p53 function, including expression levels, mutations, cofactor proteins and small molecules, we expanded our previously described yeast-based system to provide the opportunity for efficient investigation of their individual and combined impacts in a miniaturized format. The system integrates i variable expression of p53 proteins under the finely tunable GAL1,10 promoter, ii single copy, chromosomally located p53-responsive and control luminescence reporters, iii enhanced chemical uptake using modified ABC-transporters, iv small-volume formats for treatment and dual-luciferase assays, and v opportunities to co-express p53 with other cofactor proteins. This robust system can distinguish different levels of expression of WT and mutant p53 as well as interactions with MDM2 or 53BP1. CONCLUSIONS/SIGNIFICANCE: We found that the small molecules Nutlin and RITA could both relieve the MDM2-dependent inhibition of WT p53 transactivation function, while only RITA could impact p53/53BP1 functional interactions. PRIMA-1 was ineffective in modifying the transactivation capacity of WT p53 and missense p53 mutations. This dual-luciferase assay can, therefore, provide a high-throughput assessment tool for investigating a matrix of factors that can influence the p53 network, including the effectiveness of newly developed small molecules, on WT and tumor-associated p53 mutants as well as interacting proteins.

  15. Autonomous robot behavior based on neural networks

    Science.gov (United States)

    Grolinger, Katarina; Jerbic, Bojan; Vranjes, Bozo

    1997-04-01

    The purpose of autonomous robot is to solve various tasks while adapting its behavior to the variable environment, expecting it is able to navigate much like a human would, including handling uncertain and unexpected obstacles. To achieve this the robot has to be able to find solution to unknown situations, to learn experienced knowledge, that means action procedure together with corresponding knowledge on the work space structure, and to recognize working environment. The planning of the intelligent robot behavior presented in this paper implements the reinforcement learning based on strategic and random attempts for finding solution and neural network approach for memorizing and recognizing work space structure (structural assignment problem). Some of the well known neural networks based on unsupervised learning are considered with regard to the structural assignment problem. The adaptive fuzzy shadowed neural network is developed. It has the additional shadowed hidden layer, specific learning rule and initialization phase. The developed neural network combines advantages of networks based on the Adaptive Resonance Theory and using shadowed hidden layer provides ability to recognize lightly translated or rotated obstacles in any direction.

  16. A simplified computational memory model from information processing

    Science.gov (United States)

    Zhang, Lanhua; Zhang, Dongsheng; Deng, Yuqin; Ding, Xiaoqian; Wang, Yan; Tang, Yiyuan; Sun, Baoliang

    2016-11-01

    This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracting memory function and simulating memory information processing. At first meta-memory is defined to express the neuron or brain cortices based on the biology and graph theories, and we develop an intra-modular network with the modeling algorithm by mapping the node and edge, and then the bi-modular network is delineated with intra-modular and inter-modular. At last a polynomial retrieval algorithm is introduced. In this paper we simulate the memory phenomena and functions of memorization and strengthening by information processing algorithms. The theoretical analysis and the simulation results show that the model is in accordance with the memory phenomena from information processing view.

  17. Overlapping Community Detection based on Network Decomposition

    Science.gov (United States)

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-04-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms.

  18. Need Based Network Traffic Collection

    Science.gov (United States)

    2015-02-15

    release, distribution unlimited. 13. SUPPLEMENTARY NOTES The original document contains color images. 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY ...material is based upon work funded and supported by Department of Homeland Security Department of Defense under Contract No. FA8721-05-C-0003 with...Corruption #6 UDP: DNS DoS/DDoS Floods #8 DP: Remote Connections DoS/D,DoS Crashes #7 UDP: VoiiP Q I e Software Engineering Institute I Carnegie Mellon Uni

  19. The risk early-warning of gas hazard in coal mine based on Rough Set-neural network

    Institute of Scientific and Technical Information of China (English)

    TIAN Shui-cheng; WANG Li

    2007-01-01

    This article proposed the risk early-warning model of gas hazard based on Rough Set and neural network. The attribute quantity was reduced by Rough Set, the main characteristic attributes were withdrawn, the complexity of neural network system and the computing time was reduced, as well. Because of fault-tolerant ability, parallel processing ability, anti-jamming ability and processing non-linear problem ability of neural network system, the methods of Rough Set and neural network were combined. The examples research indicate: applying Rough Set and BP neural network to the gas hazard risk early-warning coal mines in coal mine, the BPNN structure is greatly simplified, the network computation quantity is reduced and the convergence rate is speed up.

  20. Application of functional-link neural network in evaluation of sublayer suspension based on FWD test

    Institute of Scientific and Technical Information of China (English)

    陈瑜; 张起森

    2004-01-01

    Several methods for evaluating the sublayer suspension beneath old pavement with falling weight deflectormeter(FWD), were summarized and the respective advantages and disadvantages were analyzed. Based on these methods, the evaluation principles were improved and a new type of the neural network, functional-link neural network was proposed to evaluate the sublayer suspension with FWD test results. The concept of function link, learning method of functional-link neural network and the establishment process of neural network model were studied in detail. Based on the old pavement over-repairing engineering of Kaiping section, Guangdong Province in G325 National Highway, the application of functional-link neural network in evaluation of sublayer suspension beneath old pavement based on FWD test data on the spot was investigated. When learning rate is 0.1 and training cycles are 405, the functional-link network error is less than 0.0001, while the optimum chosen 4-8-1 BP needs over 10000 training cycles to reach the same accuracy with less precise evaluation results. Therefore, in contrast to common BP neural network,the functional-link neural network adopts single layer structure to learn and calculate, which simplifies the network, accelerates the convergence speed and improves the accuracy. Moreover the trained functional-link neural network can be adopted to directly evaluate the sublayer suspension based on FWD test data on the site. Engineering practice indicates that the functional-link neural model gains very excellent results and effectively guides the pavement over-repairing construction.

  1. Application of detecting algorithm based on network

    Institute of Scientific and Technical Information of China (English)

    张凤斌; 杨永田; 江子扬; 孙冰心

    2004-01-01

    Because currently intrusion detection systems cannot detect undefined intrusion behavior effectively,according to the robustness and adaptability of the genetic algorithms, this paper integrates the genetic algorithms into an intrusion detection system, and a detection algorithm based on network traffic is proposed. This algorithm is a real-time and self-study algorithm and can detect undefined intrusion behaviors effectively.

  2. Location-based Forwarding in Vehicular Networks

    NARCIS (Netherlands)

    Klein Wolterink, W.

    2013-01-01

    In this thesis we focus on location-based message forwarding in vehicular networks to support intelligent transportation systems (ITSs). ITSs are transport systems that utilise information and communication technologies to increase their level of automation, in this way levering the performance of

  3. Fast and Near-Optimal Timing-Driven Cell Sizing under Cell Area and Leakage Power Constraints Using a Simplified Discrete Network Flow Algorithm

    Directory of Open Access Journals (Sweden)

    Huan Ren

    2013-01-01

    Full Text Available We propose a timing-driven discrete cell-sizing algorithm that can address total cell size and/or leakage power constraints. We model cell sizing as a “discretized” mincost network flow problem, wherein available sizes of each cell are modeled as nodes. Flow passing through a node indicates the choice of the corresponding cell size, and the total flow cost reflects the timing objective function value corresponding to these choices. Compared to other discrete optimization methods for cell sizing, our method can obtain near-optimal solutions in a time-efficient manner. We tested our algorithm on ISCAS’85 benchmarks, and compared our results to those produced by an optimal dynamic programming- (DP- based method. The results show that compared to the optimal method, the improvements to an initial sizing solution obtained by our method is only 1% (3% worse when using a 180 nm (90 nm library, while being 40–60 times faster. We also obtained results for ISPD’12 cell-sizing benchmarks, under leakage power constraint, and compared them to those of a state-of-the-art approximate DP method (optimal DP runs out of memory for the smallest of these circuits. Our results show that we are only 0.9% worse than the approximate DP method, while being more than twice as fast.

  4. SAR ATR Based on Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Tian Zhuangzhuang

    2016-06-01

    Full Text Available This study presents a new method of Synthetic Aperture Radar (SAR image target recognition based on a convolutional neural network. First, we introduce a class separability measure into the cost function to improve this network’s ability to distinguish between categories. Then, we extract SAR image features using the improved convolutional neural network and classify these features using a support vector machine. Experimental results using moving and stationary target acquisition and recognition SAR datasets prove the validity of this method.

  5. Directivity of a simplified aeroengine

    OpenAIRE

    Mattei, Pierre-Olivier

    2006-01-01

    International audience; This paper presents theoretical and numerical results on the high frequency directivity of an aeroengine under flight conditions. In this paper, two different theories, based on a Kirchhoff approximation for semi-infinite cylinders, are combined to obtain the far field sound pressure radiated into the whole surrounding space. Although the geometric description of the engine is simplified - in particular, the annular exhaust is not taken into account - it includes some ...

  6. Computer vision-based method for classification of wheat grains using artificial neural network.

    Science.gov (United States)

    Sabanci, Kadir; Kayabasi, Ahmet; Toktas, Abdurrahim

    2017-06-01

    A simplified computer vision-based application using artificial neural network (ANN) depending on multilayer perceptron (MLP) for accurately classifying wheat grains into bread or durum is presented. The images of 100 bread and 100 durum wheat grains are taken via a high-resolution camera and subjected to pre-processing. The main visual features of four dimensions, three colors and five textures are acquired using image-processing techniques (IPTs). A total of 21 visual features are reproduced from the 12 main features to diversify the input population for training and testing the ANN model. The data sets of visual features are considered as input parameters of the ANN model. The ANN with four different input data subsets is modelled to classify the wheat grains into bread or durum. The ANN model is trained with 180 grains and its accuracy tested with 20 grains from a total of 200 wheat grains. Seven input parameters that are most effective on the classifying results are determined using the correlation-based CfsSubsetEval algorithm to simplify the ANN model. The results of the ANN model are compared in terms of accuracy rate. The best result is achieved with a mean absolute error (MAE) of 9.8 × 10(-6) by the simplified ANN model. This shows that the proposed classifier based on computer vision can be successfully exploited to automatically classify a variety of grains. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  7. Network Based High Speed Product Innovation

    DEFF Research Database (Denmark)

    Lindgren, Peter

    In the first decade of the 21st century, New Product Development has undergone major changes in the way NPD is managed and organised. This is due to changes in technology, market demands, and in the competencies of companies. As a result NPD organised in different forms of networks is predicted...... to be of ever-increasing importance to many different kinds of companies. This happens at the same times as the share of new products of total turnover and earnings is increasing at unprecedented speed in many firms and industries. The latter results in the need for very fast innovation and product development...... - a need that can almost only be resolved by organising NPD in some form of network configuration. The work of Peter Lindgren is on several aspects of network based high speed product innovation and contributes to a descriptive understanding of this phenomenon as well as with normative theory on how NPD...

  8. Quantum networks based on cavity QED

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, Stephan; Bochmann, Joerg; Figueroa, Eden; Hahn, Carolin; Kalb, Norbert; Muecke, Martin; Neuzner, Andreas; Noelleke, Christian; Reiserer, Andreas; Uphoff, Manuel; Rempe, Gerhard [Max-Planck-Institut fuer Quantenoptik, Hans-Kopfermann-Strasse 1, 85748 Garching (Germany)

    2014-07-01

    Quantum repeaters require an efficient interface between stationary quantum memories and flying photons. Single atoms in optical cavities are ideally suited as universal quantum network nodes that are capable of sending, storing, retrieving, and even processing quantum information. We demonstrate this by presenting an elementary version of a quantum network based on two identical nodes in remote, independent laboratories. The reversible exchange of quantum information and the creation of remote entanglement are achieved by exchange of a single photon. Quantum teleportation is implemented using a time-resolved photonic Bell-state measurement. Quantum control over all degrees of freedom of the single atom also allows for the nondestructive detection of flying photons and the implementation of a quantum gate between the spin state of the atom and the polarization of a photon upon its reflection from the cavity. Our approach to quantum networking offers a clear perspective for scalability and provides the essential components for the realization of a quantum repeater.

  9. Networked control and supervision system based on LonWorks fieldbus and Intranet/Internet

    Institute of Scientific and Technical Information of China (English)

    WU Min; ZHAO Hong; LIU Guo-ping; SHE Jin-hua

    2007-01-01

    A networked control and supervision system (NCSS) based on LonWorks fieldbus and Intranet/Internet was designed,which was composed of the universal intelligent control nodes (ICNs), the visual control and supervision configuration platforms (VCCP and VSCP) and an Intranet/Internet-based remote supervision platform (RSP). The ICNs were connected to field devices,such as sensors, actuators and controllers. The VCCP and VSCP were implemented by means of a graphical programming environment and network management so as to simplify the tasks of programming and maintaining the ICNs. The RSP was employed to perform the remote supervision function, which was based on a three-layer browser/server(B/S) structure mode. The validity of the NCSS was demonstrated by laboratory experiments.

  10. SOFM Neural Network Based Hierarchical Topology Control for Wireless Sensor Networks

    OpenAIRE

    2014-01-01

    Well-designed network topology provides vital support for routing, data fusion, and target tracking in wireless sensor networks (WSNs). Self-organization feature map (SOFM) neural network is a major branch of artificial neural networks, which has self-organizing and self-learning features. In this paper, we propose a cluster-based topology control algorithm for WSNs, named SOFMHTC, which uses SOFM neural network to form a hierarchical network structure, completes cluster head selection by the...

  11. Community structure of complex networks based on continuous neural network

    Science.gov (United States)

    Dai, Ting-ting; Shan, Chang-ji; Dong, Yan-shou

    2017-09-01

    As a new subject, the research of complex networks has attracted the attention of researchers from different disciplines. Community structure is one of the key structures of complex networks, so it is a very important task to analyze the community structure of complex networks accurately. In this paper, we study the problem of extracting the community structure of complex networks, and propose a continuous neural network (CNN) algorithm. It is proved that for any given initial value, the continuous neural network algorithm converges to the eigenvector of the maximum eigenvalue of the network modularity matrix. Therefore, according to the stability of the evolution of the network symbol will be able to get two community structure.

  12. Convolutional Neural Network Based dem Super Resolution

    Science.gov (United States)

    Chen, Zixuan; Wang, Xuewen; Xu, Zekai; Hou, Wenguang

    2016-06-01

    DEM super resolution is proposed in our previous publication to improve the resolution for a DEM on basis of some learning examples. Meanwhile, the nonlocal algorithm is introduced to deal with it and lots of experiments show that the strategy is feasible. In our publication, the learning examples are defined as the partial original DEM and their related high measurements due to this way can avoid the incompatibility between the data to be processed and the learning examples. To further extent the applications of this new strategy, the learning examples should be diverse and easy to obtain. Yet, it may cause the problem of incompatibility and unrobustness. To overcome it, we intend to investigate a convolutional neural network based method. The input of the convolutional neural network is a low resolution DEM and the output is expected to be its high resolution one. A three layers model will be adopted. The first layer is used to detect some features from the input, the second integrates the detected features to some compressed ones and the final step transforms the compressed features as a new DEM. According to this designed structure, some learning DEMs will be taken to train it. Specifically, the designed network will be optimized by minimizing the error of the output and its expected high resolution DEM. In practical applications, a testing DEM will be input to the convolutional neural network and a super resolution will be obtained. Many experiments show that the CNN based method can obtain better reconstructions than many classic interpolation methods.

  13. Discriminant and concurrent validity of a simplified DSM-based structured diagnostic instrument for the assessment of autism spectrum disorders in youth and young adults

    Directory of Open Access Journals (Sweden)

    Joshi Gagan

    2011-12-01

    Full Text Available Abstract Background To evaluate the concurrent and discriminant validity of a brief DSM-based structured diagnostic interview for referred individuals with autism spectrum disorders (ASDs. Methods To test concurrent validity, we assessed the structured interview's agreement in 123 youth with the expert clinician assessment and the Social Responsiveness Scale (SRS. Discriminant validity was examined using 1563 clinic-referred youth. Results The structured diagnostic interview and SRS were highly sensitive indicators of the expert clinician assessment. Equally strong was the agreement between the structured interview and SRS. We found evidence for high specificity for the structured interview. Conclusions A simplified DSM-based ASD structured diagnostic interview could serve as a useful diagnostic aid in the assessment of subjects with ASDs in clinical and research settings.

  14. Modeling acquaintance networks based on balance theory

    Directory of Open Access Journals (Sweden)

    Vukašinović Vida

    2014-09-01

    Full Text Available An acquaintance network is a social structure made up of a set of actors and the ties between them. These ties change dynamically as a consequence of incessant interactions between the actors. In this paper we introduce a social network model called the Interaction-Based (IB model that involves well-known sociological principles. The connections between the actors and the strength of the connections are influenced by the continuous positive and negative interactions between the actors and, vice versa, the future interactions are more likely to happen between the actors that are connected with stronger ties. The model is also inspired by the social behavior of animal species, particularly that of ants in their colony. A model evaluation showed that the IB model turned out to be sparse. The model has a small diameter and an average path length that grows in proportion to the logarithm of the number of vertices. The clustering coefficient is relatively high, and its value stabilizes in larger networks. The degree distributions are slightly right-skewed. In the mature phase of the IB model, i.e., when the number of edges does not change significantly, most of the network properties do not change significantly either. The IB model was found to be the best of all the compared models in simulating the e-mail URV (University Rovira i Virgili of Tarragona network because the properties of the IB model more closely matched those of the e-mail URV network than the other models

  15. Simplifying EU environmental legislation

    DEFF Research Database (Denmark)

    Anker, Helle Tegner

    2014-01-01

    The recent review of the EIA Directive was launched as part of the ‘better regulation’ agenda with the purpose to simplify procedures and reduce administrative burdens. This was combined with an attempt to further harmonise procedures in order address shortcomings in the Directive and to overcome...

  16. Network-based recommendation algorithms: A review

    CERN Document Server

    Yu, Fei; Gillard, Sebastien; Medo, Matus

    2015-01-01

    Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on users' past preferences to choose new items that might be appreciated by a given individual user. While many approaches to recommendation exist, the approach based on a network representation of the input data has gained considerable attention in the past. We review here a broad range of network-based recommendation algorithms and for the first time compare their performance on three distinct real datasets. We present recommendation topics that go beyond the mere question of which algorithm to use - such as the possible influence of recommendation on the evolution of systems that use it - and finally discuss open research directions and challenges.

  17. Network-based recommendation algorithms: A review

    Science.gov (United States)

    Yu, Fei; Zeng, An; Gillard, Sébastien; Medo, Matúš

    2016-06-01

    Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on users' past preferences to choose new items that might be appreciated by a given individual user. While many approaches to recommendation exist, the approach based on a network representation of the input data has gained considerable attention in the past. We review here a broad range of network-based recommendation algorithms and for the first time compare their performance on three distinct real datasets. We present recommendation topics that go beyond the mere question of which algorithm to use-such as the possible influence of recommendation on the evolution of systems that use it-and finally discuss open research directions and challenges.

  18. Network Tomography Based on Additive Metrics

    CERN Document Server

    Ni, Jian

    2008-01-01

    Inference of the network structure (e.g., routing topology) and dynamics (e.g., link performance) is an essential component in many network design and management tasks. In this paper we propose a new, general framework for analyzing and designing routing topology and link performance inference algorithms using ideas and tools from phylogenetic inference in evolutionary biology. The framework is applicable to a variety of measurement techniques. Based on the framework we introduce and develop several polynomial-time distance-based inference algorithms with provable performance. We provide sufficient conditions for the correctness of the algorithms. We show that the algorithms are consistent (return correct topology and link performance with an increasing sample size) and robust (can tolerate a certain level of measurement errors). In addition, we establish certain optimality properties of the algorithms (i.e., they achieve the optimal $l_\\infty$-radius) and demonstrate their effectiveness via model simulation.

  19. On the Simplify Management for Campus Network at College%高校校园网简化管理方案的探讨

    Institute of Scientific and Technical Information of China (English)

    周晓华

    2015-01-01

    高校校园网20多年间经历了由简至繁的发展历程."繁"曾经是高校校园网从管理向运营演进的必然趋势,但现阶段 "繁"已经成为信息化发展的拦路石. 通过简化校园网的管理结构,可降低校园网服务支撑所需的资源投入,通过简化校园网的运维工作,可提升信息服务的时效性,提高管理效率和管理效果,通过简化校园网的资源整合工作,可让有特色的信息服务快速、高效、优质的服务于校园网用户. 因此,化繁为简是助力高校校园网从运营向服务转型的首要目标.%Campus network has developed for 20 years, experiencing the process from simple to complex. Although complex is the inevitable trend for campus network from management to operation, at present complex has become an obstacle to informatization. Simplifing the management structure could lower the resource investment for network service support on campus. Simplifing the operation maintenance could enhance effectiveness for information service, management and effect. Simplifing the resource integration of campus network could make distinctive, speedy, effective, good-qualified information serve campus network user. Therefore, making complex simple is the first goal to push campus network from operation type to service type.

  20. Neural Network-Based Hyperspectral Algorithms

    Science.gov (United States)

    2016-06-07

    Neural Network-Based Hyperspectral Algorithms Walter F. Smith, Jr. and Juanita Sandidge Naval Research Laboratory Code 7340, Bldg 1105 Stennis Space...our effort is development of robust numerical inversion algorithms , which will retrieve inherent optical properties of the water column as well as...validate the resulting inversion algorithms with in-situ data and provide estimates of the error bounds associated with the inversion algorithm . APPROACH

  1. Community detection based on network communicability

    Science.gov (United States)

    Estrada, Ernesto

    2011-03-01

    We propose a new method for detecting communities based on the concept of communicability between nodes in a complex network. This method, designated as N-ComBa K-means, uses a normalized version of the adjacency matrix to build the communicability matrix and then applies K-means clustering to find the communities in a graph. We analyze how this method performs for some pathological cases found in the analysis of the detection limit of communities and propose some possible solutions on the basis of the analysis of the ratio of local to global densities in graphs. We use four different quality criteria for detecting the best clustering and compare the new approach with the Girvan-Newman algorithm for the analysis of two "classical" networks: karate club and bottlenose dolphins. Finally, we analyze the more challenging case of homogeneous networks with community structure, for which the Girvan-Newman completely fails in detecting any clustering. The N-ComBa K-means approach performs very well in these situations and we applied it to detect the community structure in an international trade network of miscellaneous manufactures of metal having these characteristics. Some final remarks about the general philosophy of community detection are also discussed.

  2. Real-time network traffic classification technique for wireless local area networks based on compressed sensing

    Science.gov (United States)

    Balouchestani, Mohammadreza

    2017-05-01

    Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.

  3. Operator constraint principle for simplifying atmospheric dynamical equations

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Based on the qualitative theory of atmospheric dynamical equations, a new method for simplifying equations, the operator constraint principle, is presented. The general rule of the method and its mathematical strictness are discussed. Moreover, the way that how to use the method to simplify equations rationally and how to get the simplified equations with harmonious and consistent dynamics is given.

  4. Neural Network Model Based Cluster Head Selection for Power Control

    Directory of Open Access Journals (Sweden)

    Krishan Kumar

    2011-01-01

    Full Text Available Mobile ad-hoc network has challenge of the limited power to prolong the lifetime of the network, because power is a valuable resource in mobile ad-hoc network. The status of power consumption should be continuously monitored after network deployment. In this paper, we propose coverage aware neural network based power control routing with the objective of maximizing the network lifetime. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage. The simulation results show that the proposed scheme can be used in wide area of applications in mobile ad-hoc network.

  5. Self-organized Collaboration Network Model Based on Module Emerging

    Science.gov (United States)

    Yang, Hongyong; Lu, Lan; Liu, Qiming

    Recently, the studies of the complex network have gone deep into many scientific fields, such as computer science, physics, mathematics, sociology, etc. These researches enrich the realization for complex network, and increase understands for the new characteristic of complex network. Based on the evolvement characteristic of the author collaboration in the scientific thesis, a self-organized network model of the scientific cooperation network is presented by module emerging. By applying the theoretical analysis, it is shown that this network model is a scale-free network, and the strength degree distribution and the module degree distribution of the network nodes have the same power law. In order to make sure the validity of the theoretical analysis for the network model, we create the computer simulation and demonstration collaboration network. By analyzing the data of the network, the results of the demonstration network and the computer simulation are consistent with that of the theoretical analysis of the model.

  6. Reality based scenarios facilitate knowledge network development.

    Science.gov (United States)

    Manning, J; Broughton, V; McConnell, E A

    1995-03-01

    The challenge in nursing education is to create a learning environment that enables students to learn new knowledge, access previously acquired information from a variety of disciplines, and apply this newly constructed knowledge to the complex and constantly changing world of practice. Faculty at the University of South Australia, School of Nursing, City Campus describe the use of reality based scenarios to acquire domain-specific knowledge and develop well connected associative knowledge networks, both of which facilitate theory based practice and the student's transition to the role of registered nurse.

  7. Structure Properties of Koch Networks Based on Networks Dynamical Systems

    CERN Document Server

    Zhai, Yinhu; Wang, Shaohui

    2016-01-01

    We introduce an informative labeling algorithm for the vertices of a family of Koch networks. Each of the labels is consisted of two parts, the precise position and the time adding to Koch networks. The shortest path routing between any two vertices is determined only on the basis of their labels, and the routing is calculated only by few computations. The rigorous solutions of betweenness centrality for every node and edge are also derived by the help of their labels. Furthermore, the community structure in Koch networks is studied by the current and voltage characteristics of its resistor networks.

  8. Network Lifetime Extension Based On Network Coding Technique In Underwater Acoustic Sensor Networks

    Directory of Open Access Journals (Sweden)

    Padmavathy.T.V

    2012-06-01

    Full Text Available Underwater acoustic sensor networks (UWASNs are playing a lot of interest in ocean applications, such as ocean pollution monitoring, ocean animal surveillance, oceanographic data collection, assisted- navigation, and offshore exploration, UWASN is composed of underwater sensors that engage sound to transmit information collected in the ocean. The reason to utilize sound is that radio frequency (RF signals used by terrestrial sensor networks (TWSNs can merely transmit a few meters in the water. Unfortunately, the efficiency of UWASNs is inferior to that of the terrestrial sensor networks (TWSNs. Some of the challenges in under water communication are propagation delay, high bit error rate and limited bandwidth. Our aim is to minimize the power consumption and to improve the reliability of data transmission by finding the optimum number of clusters based on energy consumption.

  9. Stochastic methods for measurement-based network control

    NARCIS (Netherlands)

    Ellens, W.

    2015-01-01

    The main task of network administrators is to ensure that their network functions properly. Whether they manage a telecommunication or a road network, they generally base their decisions on the analysis of measurement data. Inspired by such network control applications, this dissertation investigate

  10. Reliability-Based Optimization for Maintenance Management in Bridge Networks

    OpenAIRE

    Hu, Xiaofei

    2014-01-01

    This dissertation addresses the problem of optimizing maintenance, repair and reconstruction decisions for bridge networks. Incorporating network topologies into bridge management problems is computationally difficult. Because of the interdependencies among networked bridges, they have to be analyzed together. Simulation-based numerical optimization techniques adopted in past research are limited to networks of moderate sizes. In this dissertation, novel approaches are developed to dete...

  11. NASSN: a NAS-based storage network

    Institute of Scientific and Technical Information of China (English)

    HAN De-zhi

    2007-01-01

    With the digital information and application requirement on the Internet increasing fleetly nowadays,it is urgent to work out a network storage system with a large capacity, a high availability and scalability. To solve the above-mentioned issues, a NAS-based storage network ( for short NASSN) has been designed. Firstly,the NASSN integrates multi-NAS,iNAS (an iSCSI-based NAS) and enterprise SAN with the help of storage virtualization, which can provide a greater capacity and better scalability. Secondly, the NASSN can provide high availability with the help of server and storage subsystem redundancy technologies. Thirdly, the NASSN simultaneously serves for both the file I/O and the block L/O with the help of an iSCSI module, which has the advantages of NAS and SAN. Finally, the NASSN can provide higher I/O speed by a high network-attached channel which implements the direct data transfer between the storage device and client. In the experiments, the NASSN has ultra-high-throughput for both of the file I/O requests and the block I/O requests.

  12. Receiver Based Traffic Control Mechanism to Protect Low Capacity Network in Infrastructure Based Wireless Mesh Network

    Science.gov (United States)

    Gilani, Syed Sherjeel Ahmad; Zubair, Muhammad; Khan, Zeeshan Shafi

    Infrastructure-based Wireless Mesh Networks are emerging as an affordable, robust, flexible and scalable technology. With the advent of Wireless Mesh Networks (WMNs) the dream of connecting multiple technology based networks seems to come true. A fully secure WMN is still a challenge for the researchers. In infrastructure-based WMNs almost all types of existing Wireless Networks like Wi-Fi, Cellular, WiMAX, and Sensor etc can be connected through Wireless Mesh Routers (WMRs). This situation can lead to a security problem. Some nodes can be part of the network with high processing power, large memory and least energy issues while others may belong to a network having low processing power, small memory and serious energy limitations. The later type of the nodes is very much vulnerable to targeted attacks. In our research we have suggested to set some rules on the WMR to mitigate these kinds of targeted flooding attacks. The WMR will then share those set of rules with other WMRs for Effective Utilization of Resources.

  13. A Cluster- Based Secure Active Network Environment

    Institute of Scientific and Technical Information of China (English)

    CHEN Xiao-lin; ZHOU Jing-yang; DAI Han; LU Sang-lu; CHEN Gui-hai

    2005-01-01

    We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or trusted by privileged users is executed in the secure execution environment (EE) of the active router, while others are executed in the secure EE of the nodes in the distributed shared memory (DSM) cluster. With the supports of a multi-process Java virtual machine and KeyNote, untrusted active packets are controlled to securely consume resource. The DSM consistency management makes that active packets can be parallelly processed in the DSM cluster as if they were processed one by one in ANTS (Active Network Transport System). We demonstrate that CSANE has good security and scalability, but imposing little changes on traditional routers.

  14. Predicting Scientific Success Based on Coauthorship Networks

    CERN Document Server

    Sarigöl, Emre; Scholtes, Ingo; Garas, Antonios; Schweitzer, Frank

    2014-01-01

    We address the question to what extent the success of scientific articles is due to social influence. Analyzing a data set of over 100000 publications from the field of Computer Science, we study how centrality in the coauthorship network differs between authors who have highly cited papers and those who do not. We further show that a machine learning classifier, based only on coauthorship network centrality measures at time of publication, is able to predict with high precision whether an article will be highly cited five years after publication. By this we provide quantitative insight into the social dimension of scientific publishing - challenging the perception of citations as an objective, socially unbiased measure of scientific success.

  15. Simplified seismic risk analysis

    Energy Technology Data Exchange (ETDEWEB)

    Pellissetti, Manuel; Klapp, Ulrich [AREVA NP GmbH, Erlangen (Germany)

    2011-07-01

    Within the context of probabilistic safety analysis (PSA) for nuclear power plants (NPP's), seismic risk assessment has the purpose to demonstrate that the contribution of seismic events to overall risk is not excessive. The most suitable vehicle for seismic risk assessment is a full scope seismic PSA (SPSA), in which the frequency of core damage due to seismic events is estimated. An alternative method is represented by seismic margin assessment (SMA), which aims at showing sufficient margin between the site-specific safe shutdown earthquake (SSE) and the actual capacity of the plant. Both methods are based on system analysis (fault-trees and event-trees) and hence require fragility estimates for safety relevant systems, structures and components (SSC's). If the seismic conditions at a specific site of a plant are not very demanding, then it is reasonable to expect that the risk due to seismic events is low. In such cases, the cost-benefit ratio for performing a full scale, site-specific SPSA or SMA will be excessive, considering the ultimate objective of seismic risk analysis. Rather, it will be more rational to rely on a less comprehensive analysis, used as a basis for demonstrating that the risk due to seismic events is not excessive. The present paper addresses such a simplified approach to seismic risk assessment which is used in AREVA to: - estimate seismic risk in early design stages, - identify needs to extend the design basis, - define a reasonable level of seismic risk analysis Starting from a conservative estimate of the overall plant capacity, in terms of the HCLPF (High Confidence of Low Probability of Failure), and utilizing a generic value for the variability, the seismic risk is estimated by convolution of the hazard and the fragility curve. Critical importance is attached to the selection of the plant capacity in terms of the HCLPF, without performing extensive fragility calculations of seismically relevant SSC's. A suitable basis

  16. UTILITY OF SIMPLIFIED LABANOTATION

    OpenAIRE

    Maria del Pilar Naranjo

    2016-01-01

    After using simplified Labanotation as a didactic tool for some years, the author can conclude that it accomplishes at least three main functions: efficiency of rehearsing time, social recognition and broadening of the choreographic consciousness of the dancer. The doubts of the dancing community about the issue of ‘to write or not to write’ are highly determined by the contexts and their own choreographic evolution, but the utility of Labanotation, as a tool for knowledge, is undeniable.

  17. UTILITY OF SIMPLIFIED LABANOTATION

    Directory of Open Access Journals (Sweden)

    Maria del Pilar Naranjo

    2016-02-01

    Full Text Available After using simplified Labanotation as a didactic tool for some years, the author can conclude that it accomplishes at least three main functions: efficiency of rehearsing time, social recognition and broadening of the choreographic consciousness of the dancer. The doubts of the dancing community about the issue of ‘to write or not to write’ are highly determined by the contexts and their own choreographic evolution, but the utility of Labanotation, as a tool for knowledge, is undeniable.

  18. Fuzzy Neural Network Based Traffic Prediction and Congestion Control in High-Speed Networks

    Institute of Scientific and Technical Information of China (English)

    费翔; 何小燕; 罗军舟; 吴介一; 顾冠群

    2000-01-01

    Congestion control is one of the key problems in high-speed networks, such as ATM. In this paper, a kind of traffic prediction and preventive congestion control scheme is proposed using neural network approach. Traditional predictor using BP neural network has suffered from long convergence time and dissatisfying error. Fuzzy neural network developed in this paper can solve these problems satisfactorily. Simulations show the comparison among no-feedback control scheme,reactive control scheme and neural network based control scheme.

  19. A Scalable Policy and SNMP Based Network Management Framework

    Institute of Scientific and Technical Information of China (English)

    LIU Su-ping; DING Yong-sheng

    2009-01-01

    Traditional SNMP-based network management can not deal with the task of managing large-scaled distributed network,while policy-based management is one of the effective solutions in network and distributed systems management. However,cross-vendor hardware compatibility is one of the limitations in policy-based management. Devices existing in current network mostly support SNMP rather than Common Open Policy Service (COPS) protocol. By analyzing traditional network management and policy-based network management, a scalable network management framework is proposed. It is combined with Internet Engineering Task Force (IETF) framework for policybased management and SNMP-based network management. By interpreting and translating policy decision to SNMP message,policy can be executed in traditional SNMP-based device.

  20. Simplifying gene trees for easier comprehension

    OpenAIRE

    Mundry Marvin; Lott Paul-Ludwig; Sassenberg Christoph; Lorkowski Stefan; Fuellen Georg

    2006-01-01

    Abstract Background In the genomic age, gene trees may contain large amounts of data making them hard to read and understand. Therefore, an automated simplification is important. Results We present a simplification tool for gene trees called TreeSimplifier. Based on species tree information and HUGO gene names, it summarizes "monophyla". These monophyla correspond to subtrees of the gene tree where the evolution of a gene follows species phylogeny, and they are simplified to single leaves in ...

  1. Model-based dynamic control and optimization of gas networks

    Energy Technology Data Exchange (ETDEWEB)

    Hofsten, Kai

    2001-07-01

    This work contributes to the research on control, optimization and simulation of gas transmission systems to support the dispatch personnel at gas control centres for the decision makings in the daily operation of the natural gas transportation systems. Different control and optimization strategies have been studied. The focus is on the operation of long distance natural gas transportation systems. Stationary optimization in conjunction with linear model predictive control using state space models is proposed for supply security, the control of quality parameters and minimization of transportation costs for networks offering transportation services. The result from the stationary optimization together with a reformulation of a simplified fluid flow model formulates a linear dynamic optimization model. This model is used in a finite time control and state constrained linear model predictive controller. The deviation from the control and the state reference determined from the stationary optimization is penalized quadratically. Because of the time varying status of infrastructure, the control space is also generally time varying. When the average load is expected to change considerably, a new stationary optimization is performed, giving a new state and control reference together with a new dynamic model that is used for both optimization and state estimation. Another proposed control strategy is a control and output constrained nonlinear model predictive controller for the operation of gas transmission systems. Here, the objective is also the security of the supply, quality control and minimization of transportation costs. An output vector is defined, which together with a control vector are both penalized quadratically from their respective references in the objective function. The nonlinear model predictive controller can be combined with a stationary optimization. At each sampling instant, a non convex nonlinear programming problem is solved giving a local minimum

  2. Wireless Sensor Network Based Smart Parking System

    National Research Council Canada - National Science Library

    Jeffrey Joseph; Roshan Gajanan Patil; Skanda Kumar Kaipu Narahari; Yogish Didagi; Jyotsna Bapat; Debabrata Das

    2014-01-01

    ... system. Wireless Sensor Networks are one such class of networks, which meet these criteria. These networks consist of spatially distributed sensor motes which work in a co-operative manner to sense and control the environment...

  3. Network-based analysis of proteomic profiles

    KAUST Repository

    Wong, Limsoon

    2016-01-26

    Mass spectrometry (MS)-based proteomics is a widely used and powerful tool for profiling systems-wide protein expression changes. It can be applied for various purposes, e.g. biomarker discovery in diseases and study of drug responses. Although RNA-based high-throughput methods have been useful in providing glimpses into the underlying molecular processes, the evidences they provide are indirect. Furthermore, RNA and corresponding protein levels have been known to have poor correlation. On the other hand, MS-based proteomics tend to have consistency issues (poor reproducibility and inter-sample agreement) and coverage issues (inability to detect the entire proteome) that need to be urgently addressed. In this talk, I will discuss how these issues can be addressed by proteomic profile analysis techniques that use biological networks (especially protein complexes) as the biological context. In particular, I will describe several techniques that we have been developing for network-based analysis of proteomics profile. And I will present evidence that these techniques are useful in identifying proteomics-profile analysis results that are more consistent, more reproducible, and more biologically coherent, and that these techniques allow expansion of the detected proteome to uncover and/or discover novel proteins.

  4. Curation-Based Network Marketing: Strategies for Network Growth and Electronic Word-of-Mouth Diffusion

    Science.gov (United States)

    Church, Earnie Mitchell, Jr.

    2013-01-01

    In the last couple of years, a new aspect of online social networking has emerged, in which the strength of social network connections is based not on social ties but mutually shared interests. This dissertation studies these "curation-based" online social networks (CBN) and their suitability for the diffusion of electronic word-of-mouth…

  5. Effects of five-minute internet-based cognitive behavioral therapy and simplified emotion-focused mindfulness on depressive symptoms: a randomized controlled trial.

    Science.gov (United States)

    Noguchi, Remi; Sekizawa, Yoichi; So, Mirai; Yamaguchi, Sosei; Shimizu, Eiji

    2017-03-04

    Notwithstanding a high expectation for internet-based cognitive behavioral therapy (iCBT) for reducing depressive symptoms, many of iCBT programs have limitations such as temporary effects and high drop-out rates, possibly due to their complexity. We examined the effects of a free, simplified, 5-minute iCBT program by comparing it with a simplified emotion-focused mindfulness (sEFM) exercise and with a waiting list control group. A total of 974 participants, who were recruited using the website of a market research company, were randomly assigned to the iCBT group, the sEFM group, and the control group. Those in the intervention arms performed each exercise for 5 weeks. The primary outcome measure was the Center for Epidemiological Studies Depression scale (CES-D) at postintervention. Secondary outcome measures were the Patient Health Questionnaire-9 (PHQ-9) and the Generalized Anxiety Disorder-7 scale (GAD-7). Intention-to-treat analyses were conducted. During postintervention assessment, there were no significant differences between the intervention arms and the control group in the CES-D, although the difference between the iCBT arm and control group was close to significance (p = 0.05) in favor of iCBT. There was a significant difference in the PHQ-9 in favor of the sEFM group compared with the control group. There were no significant differences in outcome measures between the three groups at the 6-week follow-up. Although both iCBT and sEFM have the potential to temporarily reduce depressive symptoms, substantial improvements are required to enhance and maintain their effects. This trial is registered with the UMIN Clinical Trial Registry (UMIN-CTR) (ID: UMIN000015097 ) on 1 October 2014.

  6. Dynamic Object Identification with SOM-based neural networks

    Directory of Open Access Journals (Sweden)

    Aleksey Averkin

    2014-03-01

    Full Text Available In this article a number of neural networks based on self-organizing maps, that can be successfully used for dynamic object identification, is described. Unique SOM-based modular neural networks with vector quantized associative memory and recurrent self-organizing maps as modules are presented. The structured algorithms of learning and operation of such SOM-based neural networks are described in details, also some experimental results and comparison with some other neural networks are given.

  7. Wind farm control for stabilisation of electrical networks based on passivity

    Science.gov (United States)

    Fernández, R. D.; Mantz, R. J.; Battaiotto, P. E.

    2010-01-01

    This article presents a control strategy for wind farms equipped with doubly fed induction generators (DFIG) operating in a network with a complex load. As is known from vector control theory, DFIG are able to generate active and reactive powers in an independent way. Therefore, taking into account a unitary power factor, a wind farm control law based on the passivity theory is proposed looking for damping frequency oscillations after a network disturbance. Then, different practical considerations allow to simplify the obtained expression in order to achieve a feasible control law. The last one is added to the normal operating power reference of the wind farm established by a Supervisory Control. Finally, some simulations are shown to support the theoretical considerations.

  8. CMDX©-based single source information system for simplified quality management and clinical research in prostate cancer

    Science.gov (United States)

    2012-01-01

    Background Histopathological evaluation of prostatectomy specimens is crucial to decision-making and prediction of patient outcomes in prostate cancer (PCa). Topographical information regarding PCa extension and positive surgical margins (PSM) is essential for clinical routines, quality assessment, and research. However, local hospital information systems (HIS) often do not support the documentation of such information. Therefore, we investigated the feasibility of integrating a cMDX-based pathology report including topographical information into the clinical routine with the aims of obtaining data, performing analysis and generating heat maps in a timely manner, while avoiding data redundancy. Methods We analyzed the workflow of the histopathological evaluation documentation process. We then developed a concept for a pathology report based on a cMDX data model facilitating the topographical documentation of PCa and PSM; the cMDX SSIS is implemented within the HIS of University Hospital Muenster. We then generated a heat map of PCa extension and PSM using the data. Data quality was assessed by measuring the data completeness of reports for all cases, as well as the source-to-database error. We also conducted a prospective study to compare our proposed method with recent retrospective and paper-based studies according to the time required for data analysis. Results We identified 30 input fields that were applied to the cMDX-based data model and the electronic report was integrated into the clinical workflow. Between 2010 and 2011, a total of 259 reports were generated with 100% data completeness and a source-to-database error of 10.3 per 10,000 fields. These reports were directly reused for data analysis, and a heat map based on the data was generated. PCa was mostly localized in the peripheral zone of the prostate. The mean relative tumor volume was 16.6%. The most PSM were localized in the apical region of the prostate. In the retrospective study, 1623 paper-based

  9. Experimental performance evaluation of software defined networking (SDN) based data communication networks for large scale flexi-grid optical networks.

    Science.gov (United States)

    Zhao, Yongli; He, Ruiying; Chen, Haoran; Zhang, Jie; Ji, Yuefeng; Zheng, Haomian; Lin, Yi; Wang, Xinbo

    2014-04-21

    Software defined networking (SDN) has become the focus in the current information and communication technology area because of its flexibility and programmability. It has been introduced into various network scenarios, such as datacenter networks, carrier networks, and wireless networks. Optical transport network is also regarded as an important application scenario for SDN, which is adopted as the enabling technology of data communication networks (DCN) instead of general multi-protocol label switching (GMPLS). However, the practical performance of SDN based DCN for large scale optical networks, which is very important for the technology selection in the future optical network deployment, has not been evaluated up to now. In this paper we have built a large scale flexi-grid optical network testbed with 1000 virtual optical transport nodes to evaluate the performance of SDN based DCN, including network scalability, DCN bandwidth limitation, and restoration time. A series of network performance parameters including blocking probability, bandwidth utilization, average lightpath provisioning time, and failure restoration time have been demonstrated under various network environments, such as with different traffic loads and different DCN bandwidths. The demonstration in this work can be taken as a proof for the future network deployment.

  10. A simplified indirect bonding technique

    Directory of Open Access Journals (Sweden)

    Radha Katiyar

    2014-01-01

    Full Text Available With the advent of lingual orthodontics, indirect bonding technique has become an integral part of practice. It involves placement of brackets initially on the models and then their transfer to teeth with the help of transfer trays. Problems encountered with current indirect bonding techniques used are (1 the possibility of adhesive flash remaining around the base of the brackets which requires removal (2 longer time required for the adhesive to gain enough bond strength for secure tray removal. The new simplified indirect bonding technique presented here overcomes both these problems.

  11. Simplified Flood Inundation Mapping Based On Flood Elevation-Discharge Rating Curves Using Satellite Images in Gauged Watersheds

    Directory of Open Access Journals (Sweden)

    Younghun Jung

    2014-05-01

    Full Text Available This study suggests an approach to obtain flood extent boundaries using spatial analysis based on Landsat-5 Thematic Mapper imageries and the digital elevation model. The suggested approach firstly extracts the flood inundation areas using the ISODATA image-processing algorithm from four Landsat 5TM imageries. Then, the ground elevations at the intersections of the extracted flood extent boundaries and the specified river cross sections are read from the digital elevation to estimate the elevation-discharge relationship. Lastly, the flood extent is generated based on the estimated elevation-discharge relationship. The methodology was tested over two river reaches in Indiana, United States. The estimated elevation-discharge relationship showed a good match with the correlation coefficients varying between 0.82 and 0.99. In addition, self-validation was also performed for the estimated spatial extent of the flood by comparing it to the waterbody extracted from the Landsat images used to develop the elevation-discharge relationship. The result indicated that the match between the estimated and the extracted flood extents was better with higher flood magnitude. We expect that the suggested methodology will help under-developed and developing countries to obtain flood maps, which have difficulties getting flood maps through traditional approaches based on computer modeling.

  12. Bayesian Network Based XP Process Modelling

    Directory of Open Access Journals (Sweden)

    Mohamed Abouelela

    2010-07-01

    Full Text Available A Bayesian Network based mathematical model has been used for modelling Extreme Programmingsoftware development process. The model is capable of predicting the expected finish time and theexpected defect rate for each XP release. Therefore, it can be used to determine the success/failure of anyXP Project. The model takes into account the effect of three XP practices, namely: Pair Programming,Test Driven Development and Onsite Customer practices. The model’s predictions were validated againsttwo case studies. Results show the precision of our model especially in predicting the project finish time.

  13. All Pass Network Based MSO Using OTRA

    Directory of Open Access Journals (Sweden)

    Rajeshwari Pandey

    2015-01-01

    Full Text Available This paper presents multiphase sinusoidal oscillators (MSOs using operational transresistance amplifier (OTRA based all pass networks. Both even and odd phase oscillations of equal amplitudes which are equally spaced in phase can be produced using single all pass section per phase. The proposed MSOs provide voltage output and can readily be used for driving voltage input circuits without increasing component count. The effect of nonideality of OTRA on the circuit performance is also analysed. The functionality of the proposed circuit is verified through PSPICE simulations.

  14. WEB BASED LEARNING OF COMPUTER NETWORK COURSE

    Directory of Open Access Journals (Sweden)

    Hakan KAPTAN

    2004-04-01

    Full Text Available As a result of developing on Internet and computer fields, web based education becomes one of the area that many improving and research studies are done. In this study, web based education materials have been explained for multimedia animation and simulation aided Computer Networks course in Technical Education Faculties. Course content is formed by use of university course books, web based education materials and technology web pages of companies. Course content is formed by texts, pictures and figures to increase motivation of students and facilities of learning some topics are supported by animations. Furthermore to help working principles of routing algorithms and congestion control algorithms simulators are constructed in order to interactive learning

  15. Networking activities in technology-based entrepreneurial teams

    DEFF Research Database (Denmark)

    Neergaard, Helle

    2005-01-01

    Based on social network theoy, this article investigates the distribution of networking roles and responsibilities in entrepreneurial founding teams. Its focus is on the team as a collection of individuals, thus allowing the research to address differences in networking patterns. It identifies six...... central networking activities and shows that not all founding team members are equally active 'networkers'. The analyses show that team members prioritize different networking activities and that one member in particular has extensive networking activities whereas other memebrs of the team are more...

  16. Modeling online social networks based on preferential linking

    Institute of Scientific and Technical Information of China (English)

    Hu Hai-Bo; Guo Jin-Li; Chen Jun

    2012-01-01

    We study the phenomena of preferential linking in a large-scale evolving online social network and find that the linear preference holds for preferential creation,preferential acceptance,and preferential attachment.Based on the linear preference,we propose an analyzable model,which illustrates the mechanism of network growth and reproduces the process of network evolution.Our simulations demonstrate that the degree distribution of the network produced by the model is in good agreement with that of the real network.This work provides a possible bridge between the micro-mechanisms of network growth and the macrostructures of online social networks.

  17. A family of quantization based piecewise linear filter networks

    DEFF Research Database (Denmark)

    Sørensen, John Aasted

    1992-01-01

    A family of quantization-based piecewise linear filter networks is proposed. For stationary signals, a filter network from this family is a generalization of the classical Wiener filter with an input signal and a desired response. The construction of the filter network is based on quantization of...

  18. Resilient Disaster Network Based on Software Defined Cognitive Wireless Network Technology

    Directory of Open Access Journals (Sweden)

    Goshi Sato

    2015-01-01

    Full Text Available In order to temporally recover the information network infrastructure in disaster areas from the Great East Japan Earthquake in 2011, various wireless network technologies such as satellite IP network, 3G, and Wi-Fi were effectively used. However, since those wireless networks are individually introduced and installed but not totally integrated, some of networks were congested due to the sudden network traffic generation and unbalanced traffic distribution, and eventually the total network could not effectively function. In this paper, we propose a disaster resilient network which integrates various wireless networks into a cognitive wireless network that users can use as an access network to the Internet at the serious disaster occurrence. We designed and developed the disaster resilient network based on software defined network (SDN technology to automatically select the best network link and route among the possible access networks to the Internet by periodically monitoring their network states and evaluate those using extended AHP method. In order to verify the usefulness of our proposed system, a prototype system is constructed and its performance is evaluated.

  19. 75 FR 28223 - Simplified Proceedings

    Science.gov (United States)

    2010-05-20

    ... HEALTH REVIEW COMMISSION 29 CFR Part 2700 Simplified Proceedings AGENCY: Federal Mine Safety and Health... proposing a rule to simplify the procedures for handling certain civil penalty proceedings. DATES: Written... three copies of their comments. Electronic comments should state ``Comments on Simplified...

  20. 75 FR 81459 - Simplified Proceedings

    Science.gov (United States)

    2010-12-28

    ... HEALTH REVIEW COMMISSION 29 CFR Part 2700 Simplified Proceedings AGENCY: Federal Mine Safety and Health... simplify the procedures for handling certain civil penalty proceedings. DATES: The final rule takes effect... ``Comments on Simplified Proceedings'' in the subject line and be sent to mmccord@fmshrc.gov . FOR...

  1. Effect of mobility models on infrastructure based wireless networks ...

    African Journals Online (AJOL)

    Effect of mobility models on infrastructure based wireless networks. ... In this paper, the effect of handoff procedure on the performance of random mobile nodes in wireless networks was investigated. Mobility of node is defined ... Article Metrics.

  2. Evaluation of the effects of the screen based on an analytical solution of a simplified MIT system

    Science.gov (United States)

    Yin, W.; Dekdouk, B.; Ktistis, C.; Peyton, A. J.

    2010-04-01

    Magnetic induction tomography (MIT) is a technology that reconstructs cross sectional conductivity distribution of an object from mutual impedance measurements of coils distributed around the object. In high frequency and low conductivity applications, an outer screen is generally used to confine the magnetic fields and to prevent electromagnetic interference from outside. However, the screen will alter the sensing and excitation field, hence the sensitivity distribution of the coil array. Therefore, the design parameters of the screen (thickness, distance to coil, materials) are important to the performance of the sensor system. This paper presents a simple method based on an analytical solution for the evaluation of the effects of the screen. The advantage of the approach includes efficient modelling of thin screens and physical insights into the effects of the screen.

  3. Numerical simulation of aerodynamic derivatives and critical wind speed for long-span bridges based on simplified steady wind field

    Science.gov (United States)

    Xin, Dabo; Ou, Jinping

    2007-06-01

    Combining the computational fluid dynamics-based numerical simulation with the forced vibration technique for extraction of aerodynamic derivatives, an approach for calculating the aerodynamic derivatives and the critical flutter wind speed for long-span bridges is presented in this paper. The RNG k-ɛ turbulent model is introduced to establish the governing equations, including the continuity equation and the Navier-Stokes equations, for solving the wind flow field around a two-dimensional bridge section. To illustrate the effectiveness and accuracy of the proposed approach, a simple application to the Hume Bridge in China is provided, and the numerical results show that the aerodynamic derivatives and the critical flutter wind speed obtained agree well with the wind tunnel test results.

  4. Numerical simulation of aerodynamic derivatives and critical wind speed for long-span bridges based on simplified steady wind field

    Institute of Scientific and Technical Information of China (English)

    Xin Dabo; Ou Jinping

    2007-01-01

    Combining the computational fluid dynamics-based numerical simulation with the forced vibration technique for extraction of aerodynamic derivatives, an approach for calculating the aerodynamic derivatives and the critical flutter wind speed for long-span bridges is presented in this paper. The RNG κ-ε turbulent model is introduced to establish the governing equations, including the continuity equation and the Navier-Stokes equations, for solving the wind flow field around a two-dimensional bridge section. To illustrate the effectiveness and accuracy of the proposed approach, a simple application to the Hume Bridge in China is provided, and the numerical results show that the aerodynamic derivatives and the critical flutter wind speed obtained agree well with the wind tunnel test results.

  5. Design of a Broadband Electrical Impedance Matching Network for Piezoelectric Ultrasound Transducers Based on a Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Jianfei An

    2014-04-01

    Full Text Available An improved method based on a genetic algorithm (GA is developed to design a broadband electrical impedance matching network for piezoelectric ultrasound transducer. A key feature of the new method is that it can optimize both the topology of the matching network and perform optimization on the components. The main idea of this method is to find the optimal matching network in a set of candidate topologies. Some successful experiences of classical algorithms are absorbed to limit the size of the set of candidate topologies and greatly simplify the calculation process. Both binary-coded GA and real-coded GA are used for topology optimization and components optimization, respectively. Some calculation strategies, such as elitist strategy and clearing niche method, are adopted to make sure that the algorithm can converge to the global optimal result. Simulation and experimental results prove that matching networks with better performance might be achieved by this improved method.

  6. Design of a broadband electrical impedance matching network for piezoelectric ultrasound transducers based on a genetic algorithm.

    Science.gov (United States)

    An, Jianfei; Song, Kezhu; Zhang, Shuangxi; Yang, Junfeng; Cao, Ping

    2014-04-16

    An improved method based on a genetic algorithm (GA) is developed to design a broadband electrical impedance matching network for piezoelectric ultrasound transducer. A key feature of the new method is that it can optimize both the topology of the matching network and perform optimization on the components. The main idea of this method is to find the optimal matching network in a set of candidate topologies. Some successful experiences of classical algorithms are absorbed to limit the size of the set of candidate topologies and greatly simplify the calculation process. Both binary-coded GA and real-coded GA are used for topology optimization and components optimization, respectively. Some calculation strategies, such as elitist strategy and clearing niche method, are adopted to make sure that the algorithm can converge to the global optimal result. Simulation and experimental results prove that matching networks with better performance might be achieved by this improved method.

  7. Creating Web Pages Simplified

    CERN Document Server

    Wooldridge, Mike

    2011-01-01

    The easiest way to learn how to create a Web page for your family or organization Do you want to share photos and family lore with relatives far away? Have you been put in charge of communication for your neighborhood group or nonprofit organization? A Web page is the way to get the word out, and Creating Web Pages Simplified offers an easy, visual way to learn how to build one. Full-color illustrations and concise instructions take you through all phases of Web publishing, from laying out and formatting text to enlivening pages with graphics and animation. This easy-to-follow visual guide sho

  8. Office 2013 simplified

    CERN Document Server

    Marmel, Elaine

    2013-01-01

    A basic introduction to learn Office 2013 quickly, easily, and in full color Office 2013 has new features and tools to master, and whether you're upgrading from an earlier version or using the Office applications for the first time, you'll appreciate this simplified approach. Offering a clear, visual style of learning, this book provides you with concise, step-by-step instructions and full-color screen shots that walk you through the applications in the Microsoft Office 2013 suite: Word, Excel, PowerPoint, Outlook, and Publisher.Shows you how to tackle dozens of Office 2013

  9. Windows 8 simplified

    CERN Document Server

    McFedries, Paul

    2012-01-01

    The easiest way for visual learners to get started with Windows 8 The popular Simplified series makes visual learning easier than ever, and with more than 360,000 copies sold, previous Windows editions are among the bestselling Visual books. This guide goes straight to the point with easy-to-follow, two-page tutorials for each task. With full-color screen shots and step-by-step directions, it gets beginners up and running on the newest version of Windows right away. Learn to work with the new interface and improved Internet Explorer, manage files, share your computer, and much more. Perfect fo

  10. Effective String Theory Simplified

    CERN Document Server

    Hellerman, Simeon; Maltz, Jonathan; Swanson, Ian

    2014-01-01

    In this set of notes we simplify the formulation of the Poincar\\'e invariant effective string theory in D dimensions by adding an intrinsic metric and embedding its dynamics into the Polyakov formalism. We apply this formalism to classify operators order by order in the inverse physical length of the string, in a fully gauge-invariant framework. We use this classification to discuss universality and nonuniversalty of observables up to and including next-to-next-to-leading order in the long string expansion.

  11. Implant success!!!.....simplified

    Directory of Open Access Journals (Sweden)

    Luthra Kaushal

    2009-01-01

    Full Text Available The endeavor towards life-like restoration has helped nurture new vistas in the art and science of implant dentistry. The protocol of "restoration-driven implant placement" ensures that the implant is an apical extension of the ideal future restoration and not the opposite. Meticulous pre-implant evaluation of soft and hard tissues, diagnostic cast and use of aesthetic wax-up and radiographic template combined with surgical template can simplify the intricate roadmap for appropriate implant treatment. By applying the harmony of artistic skill, scientific knowledge and clinical expertise, we can simply master the outstanding implant success in requisites of aesthetics, phonetics and function.

  12. Windows 10 simplified

    CERN Document Server

    McFedries, Paul

    2015-01-01

    Learn Windows 10 quickly and painlessly with this beginner's guide Windows 10 Simplified is your absolute beginner's guide to the ins and outs of Windows. Fully updated to cover Windows 10, this highly visual guide covers all the new features in addition to the basics, giving you a one-stop resource for complete Windows 10 mastery. Every page features step-by-step screen shots and plain-English instructions that walk you through everything you need to know, no matter how new you are to Windows. You'll master the basics as you learn how to navigate the user interface, work with files, create

  13. Paper-based Synthetic Gene Networks

    Science.gov (United States)

    Pardee, Keith; Green, Alexander A.; Ferrante, Tom; Cameron, D. Ewen; DaleyKeyser, Ajay; Yin, Peng; Collins, James J.

    2014-01-01

    Synthetic gene networks have wide-ranging uses in reprogramming and rewiring organisms. To date, there has not been a way to harness the vast potential of these networks beyond the constraints of a laboratory or in vivo environment. Here, we present an in vitro paper-based platform that provides a new venue for synthetic biologists to operate, and a much-needed medium for the safe deployment of engineered gene circuits beyond the lab. Commercially available cell-free systems are freeze-dried onto paper, enabling the inexpensive, sterile and abiotic distribution of synthetic biology-based technologies for the clinic, global health, industry, research and education. For field use, we create circuits with colorimetric outputs for detection by eye, and fabricate a low-cost, electronic optical interface. We demonstrate this technology with small molecule and RNA actuation of genetic switches, rapid prototyping of complex gene circuits, and programmable in vitro diagnostics, including glucose sensors and strain-specific Ebola virus sensors. PMID:25417167

  14. Artificial organic networks artificial intelligence based on carbon networks

    CERN Document Server

    Ponce-Espinosa, Hiram; Molina, Arturo

    2014-01-01

    This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: ·        approximation; ·        inference; ·        clustering; ·        control; ·        class...

  15. Communication Network Architectures Based on Ethernet Passive Optical Network for Offshore Wind Power Farms

    Directory of Open Access Journals (Sweden)

    Mohamed A. Ahmed

    2016-03-01

    Full Text Available Nowadays, with large-scale offshore wind power farms (WPFs becoming a reality, more efforts are needed to maintain a reliable communication network for WPF monitoring. Deployment topologies, redundancy, and network availability are the main items to enhance the communication reliability between wind turbines (WTs and control centers. Traditional communication networks for monitoring and control (i.e., supervisory control and data acquisition (SCADA systems using switched gigabit Ethernet will not be sufficient for the huge amount of data passing through the network. In this paper, the optical power budget, optical path loss, reliability, and network cost of the proposed Ethernet Passive Optical Network (EPON-based communication network for small-size offshore WPFs have been evaluated for five different network architectures. The proposed network model consists of an optical network unit device (ONU deployed on the WT side for collecting data from different internal networks. All ONUs from different WTs are connected to a central optical line terminal (OLT, placed in the control center. There are no active electronic elements used between the ONUs and the OLT, which reduces the costs and complexity of maintenance and deployment. As fiber access networks without any protection are characterized by poor reliability, three different protection schemes have been configured, explained, and discussed. Considering the cost of network components, the total implementation expense of different architectures with, or without, protection have been calculated and compared. The proposed network model can significantly contribute to the communication network architecture for next generation WPFs.

  16. Simplified Models for LHC New Physics Searches

    Energy Technology Data Exchange (ETDEWEB)

    Alves, Daniele; /SLAC; Arkani-Hamed, Nima; /Princeton, Inst. Advanced Study; Arora, Sanjay; /Rutgers U., Piscataway; Bai, Yang; /SLAC; Baumgart, Matthew; /Johns Hopkins U.; Berger, Joshua; /Cornell U., Phys. Dept.; Buckley, Matthew; /Fermilab; Butler, Bart; /SLAC; Chang, Spencer; /Oregon U. /UC, Davis; Cheng, Hsin-Chia; /UC, Davis; Cheung, Clifford; /UC, Berkeley; Chivukula, R.Sekhar; /Michigan State U.; Cho, Won Sang; /Tokyo U.; Cotta, Randy; /SLAC; D' Alfonso, Mariarosaria; /UC, Santa Barbara; El Hedri, Sonia; /SLAC; Essig, Rouven, (ed.); /SLAC; Evans, Jared A.; /UC, Davis; Fitzpatrick, Liam; /Boston U.; Fox, Patrick; /Fermilab; Franceschini, Roberto; /LPHE, Lausanne /Pittsburgh U. /Argonne /Northwestern U. /Rutgers U., Piscataway /Rutgers U., Piscataway /Carleton U. /CERN /UC, Davis /Wisconsin U., Madison /SLAC /SLAC /SLAC /Rutgers U., Piscataway /Syracuse U. /SLAC /SLAC /Boston U. /Rutgers U., Piscataway /Seoul Natl. U. /Tohoku U. /UC, Santa Barbara /Korea Inst. Advanced Study, Seoul /Harvard U., Phys. Dept. /Michigan U. /Wisconsin U., Madison /Princeton U. /UC, Santa Barbara /Wisconsin U., Madison /Michigan U. /UC, Davis /SUNY, Stony Brook /TRIUMF; /more authors..

    2012-06-01

    This document proposes a collection of simplified models relevant to the design of new-physics searches at the LHC and the characterization of their results. Both ATLAS and CMS have already presented some results in terms of simplified models, and we encourage them to continue and expand this effort, which supplements both signature-based results and benchmark model interpretations. A simplified model is defined by an effective Lagrangian describing the interactions of a small number of new particles. Simplified models can equally well be described by a small number of masses and cross-sections. These parameters are directly related to collider physics observables, making simplified models a particularly effective framework for evaluating searches and a useful starting point for characterizing positive signals of new physics. This document serves as an official summary of the results from the 'Topologies for Early LHC Searches' workshop, held at SLAC in September of 2010, the purpose of which was to develop a set of representative models that can be used to cover all relevant phase space in experimental searches. Particular emphasis is placed on searches relevant for the first {approx} 50-500 pb{sup -1} of data and those motivated by supersymmetric models. This note largely summarizes material posted at http://lhcnewphysics.org/, which includes simplified model definitions, Monte Carlo material, and supporting contacts within the theory community. We also comment on future developments that may be useful as more data is gathered and analyzed by the experiments.

  17. Network-Aware DHT-Based P2P Systems

    Science.gov (United States)

    Fayçal, Marguerite; Serhrouchni, Ahmed

    P2P networks lay over existing IP networks and infrastructure. This chapter investigates the relation between both layers, details the motivations for network awareness in P2P systems, and elucidates the requirements P2P systems have to meet for efficient network awareness. Since new P2P systems are mostly based on DHTs, we also present and analyse DHT-based architectures. And after a brief presentation of different existing network-awareness solutions, the chapter goes on effective cooperation between P2P traffic and network providers' business agreements, and introduces emerging DHT-based P2P systems that are network aware through a semantic defined for resource sharing. These new systems ensure also a certain context-awareness. So, they are analyzed and compared before an open end on prospects of network awareness in P2P systems.

  18. Developing network-based services in the NHS.

    Science.gov (United States)

    Conner, M

    2001-01-01

    Networks, based upon informal relationships, have ensured that care was delivered to patients for many years. This informal organisation of care, based upon personal relationships, ensures that where the bureaucratic organisation fails the patient, health professionals' work together to network the resources the patient needs. Networks are not new. Formalising networks and recognising their potential to deliver seamless care is new. The NHS must ensure that networks are developed, allowing them freedom from bureaucracy to reach their potential. The Northern and Yorkshire Learning Alliance (NYLA) was established as part of the Northern and Yorkshire health community's efforts to radically improve care. The NYLA operates as a network with a small team of change experts working to develop change management and service improvement capacity across 10,000 square miles. As a network based organisation the team has learned many lessons, which may inform the development of clinical networks in England.

  19. Cloud computing can simplify HIT infrastructure management.

    Science.gov (United States)

    Glaser, John

    2011-08-01

    Software as a Service (SaaS), built on cloud computing technology, is emerging as the forerunner in IT infrastructure because it helps healthcare providers reduce capital investments. Cloud computing leads to predictable, monthly, fixed operating expenses for hospital IT staff. Outsourced cloud computing facilities are state-of-the-art data centers boasting some of the most sophisticated networking equipment on the market. The SaaS model helps hospitals safeguard against technology obsolescence, minimizes maintenance requirements, and simplifies management.

  20. Congestion Control for ATM Networks Based on Diagonal Recurrent Neural Networks

    Institute of Scientific and Technical Information of China (English)

    HuangYunxian; YanWei

    1997-01-01

    An adaptive control model and its algorithms based on simple diagonal recurrent neural networks are presented for the dynamic congestion control in broadband ATM networks.Two simple dynamic queuing models of real networks are used to test the performance of the suggested control scheme.

  1. Study on the Cost Calculation of Local Fixed Telecom Network Based on Unbundled Network Elements

    Institute of Scientific and Technical Information of China (English)

    XU Liang; LIANG Xiong-jian; HUANG Xiu-qing

    2005-01-01

    In this paper, according to the practical condition of local fixed telecom network, based on the method of the realistic total element long-run incremental cost, the practical methods of dividing the network elements, calculating the cost of network elements and services are given, to provide reference for the cost calculation in telecom industry.

  2. Wavelet Neural Network Based Traffic Prediction for Next Generation Network

    Institute of Scientific and Technical Information of China (English)

    Zhao Qigang; Li Qunzhan; He Zhengyou

    2005-01-01

    By using netflow traffic collecting technology, some traffic data for analysis are collected from a next generation network (NGN) operator. To build a wavelet basis neural network (NN), the Sigmoid function is replaced with the wavelet in NN. Then the wavelet multiresolution analysis method is used to decompose the traffic signal, and the decomposed component sequences are employed to train the NN. By using the methods, an NGN traffic prediction model is built to predict one day's traffic. The experimental results show that the traffic prediction method of wavelet NN is more accurate than that without using wavelet in the NGN traffic forecasting.

  3. Network-Based and Binless Frequency Analyses.

    Directory of Open Access Journals (Sweden)

    Sybil Derrible

    Full Text Available We introduce and develop a new network-based and binless methodology to perform frequency analyses and produce histograms. In contrast with traditional frequency analysis techniques that use fixed intervals to bin values, we place a range ±ζ around each individual value in a data set and count the number of values within that range, which allows us to compare every single value of a data set with one another. In essence, the methodology is identical to the construction of a network, where two values are connected if they lie within a given a range (±ζ. The value with the highest degree (i.e., most connections is therefore assimilated to the mode of the distribution. To select an optimal range, we look at the stability of the proportion of nodes in the largest cluster. The methodology is validated by sampling 12 typical distributions, and it is applied to a number of real-world data sets with both spatial and temporal components. The methodology can be applied to any data set and provides a robust means to uncover meaningful patterns and trends. A free python script and a tutorial are also made available to facilitate the application of the method.

  4. Network video transmission system based on SOPC

    Science.gov (United States)

    Zhang, Zhengbing; Deng, Huiping; Xia, Zhenhua

    2008-03-01

    Video systems have been widely used in many fields such as conferences, public security, military affairs and medical treatment. With the rapid development of FPGA, SOPC has been paid great attentions in the area of image and video processing in recent years. A network video transmission system based on SOPC is proposed in this paper for the purpose of video acquisition, video encoding and network transmission. The hardware platform utilized to design the system is an SOPC board of model Altera's DE2, which includes an FPGA chip of model EP2C35F672C6, an Ethernet controller and a video I/O interface. An IP core, known as Nios II embedded processor, is used as the CPU of the system. In addition, a hardware module for format conversion of video data, and another module to realize Motion-JPEG have been designed with Verilog HDL. These two modules are attached to the Nios II processor as peripheral equipments through the Avalon bus. Simulation results show that these two modules work as expected. Uclinux including TCP/IP protocol as well as the driver of Ethernet controller is chosen as the embedded operating system and an application program scheme is proposed.

  5. Flexible Tube-Based Network Control Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The Innovation Laboratory, Inc. builds a control system which controls the topology of an air traffic flow network and the network flow properties which enables Air...

  6. Hopfield neural network based on ant system

    Institute of Scientific and Technical Information of China (English)

    洪炳镕; 金飞虎; 郭琦

    2004-01-01

    Hopfield neural network is a single layer feedforward neural network. Hopfield network requires some control parameters to be carefully selected, else the network is apt to converge to local minimum. An ant system is a nature inspired meta heuristic algorithm. It has been applied to several combinatorial optimization problems such as Traveling Salesman Problem, Scheduling Problems, etc. This paper will show an ant system may be used in tuning the network control parameters by a group of cooperated ants. The major advantage of this network is to adjust the network parameters automatically, avoiding a blind search for the set of control parameters.This network was tested on two TSP problems, 5 cities and 10 cities. The results have shown an obvious improvement.

  7. Network-based drugs and biomarkers

    DEFF Research Database (Denmark)

    Erler, Janine Terra; Linding, Rune

    2010-01-01

    The structure and dynamics of protein signalling networks governs cell decision processes and the formation of tissue boundaries. Complex diseases such as cancer and diabetes are diseases of such networks. Therefore approaches that can give insight into how these networks change during disease pr...... associated technologies. We then focus on the multivariate nature of cellular networks and how this has implications for biomarker and drug discovery using cancer metastasis as an example....

  8. Decentralized network management based on mobile agent

    Institute of Scientific and Technical Information of China (English)

    李锋; 冯珊

    2004-01-01

    The mobile agent technology can be employed effectively for the decentralized management of complex networks. We show how the integration of mobile agent with legacy management protocol, such as simple network management protocol (SNMP), leads to decentralized management architecture. HostWatcher is a framework that allows mobile agents to roam network, collect and process data, and perform certain adaptive actions. A prototype system is built and a quantitative analysis underlines the benefits in respect to reducing network load.

  9. Road Network Generalization Based on Float CAR Tracking

    Science.gov (United States)

    Zhou, Cheng; Li, Wenjing; Jia, Hongguo

    2016-06-01

    Road generalization is not only helpful to simplify complicated road networks but can also satisfy the needs of reasonable display of roads under varying scales, thus offering basis for updating and grading urban roads. This paper proposes a selection method for road network generalization by integrating road-associated vehicle trajectory dynamic properties and road features and calculating the importance of urban roads. First of all, the location and motion information of floating vehicles are associated to relevant roads to generate the dynamic properties of roads. Then, the dynamic and static properties of roads are analyzed, and the cluster analysis is conducted to the trajectory points at road intersections to obtain the importance of some road intersections there are vehicles passing by. Afterwards, the weights of roads are calculated using the dominance rough set, the roads are ranked by weight and the practical significance of ranking results is analyzed. Finally, the selection rules for the basic framework of road network are determined to meet with different requirements and guarantee both connectivity and completeness of road networks. The results show that the relative importance of roads is made clear by taking advantage of the rough set and the generalized road network highlights the distribution and connection of urban main roads.

  10. The Research on Web Service based Network Management

    Directory of Open Access Journals (Sweden)

    Wenli Dong

    2010-07-01

    Full Text Available This paper proposes Web Service based network management. The Web Service based network management system is analyzed. It consists of network management layer, collaborative management implementation layer, and management function layer mainly. The complex management network tasks can be accomplished respectively by more than one Web Service distributed on Internet and the Web Services interchange information based on XML message. The SNMP/XML gateway and the translation between GDMO/ASN.1 and XML/Schema are designed and implemented to implement the integration between the legacy network management systems and the network management developed by Web Service technologies. The service management in Web Service based network management is discussed. Service composition/re-composition in Web Service based network management is analyzed based on the QoS requirements negotiation between the network management requirements and the statement of Web Service and network, OWL-S being used to described the network management requirements to discover the suitable Web Service, BPEL being used to describe the Web Service composition.

  11. Analysis of neural networks through base functions

    NARCIS (Netherlands)

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

    Problem statement. Despite their success-story, neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more

  12. Analysis of Neural Networks through Base Functions

    NARCIS (Netherlands)

    Zwaag, van der B.J.; Slump, C.H.; Spaanenburg, L.

    2002-01-01

    Problem statement. Despite their success-story, neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more

  13. Personalized Network-Based Treatments in Oncology

    DEFF Research Database (Denmark)

    Robin, Xavier; Creixell, Pau; Radetskaya, Oxana;

    2013-01-01

    Network medicine aims at unraveling cell signaling networks to propose personalized treatments for patients suffering from complex diseases. In this short review, we show the relevance of network medicine to cancer treatment by outlining the potential convergence points of the most recent technol...

  14. Overlapping Communities Detection Based on Link Partition in Directed Networks

    Directory of Open Access Journals (Sweden)

    Qingyu Zou

    2013-09-01

    Full Text Available Many complex systems can be described as networks to comprehend both the structure and the function. Community structure is one of the most important properties of complex networks. Detecting overlapping communities in networks have been more attention in recent years, but the most of approaches to this problem have been applied to the undirected networks. This paper presents a novel approach based on link partition to detect overlapping communities structure in directed networks. In contrast to previous researches focused on grouping nodes, our algorithm defines communities as groups of directed links rather than nodes with the purpose of nodes naturally belong to more than one community. This approach can identify a suitable number of overlapping communities without any prior knowledge about the community in directed networks. We evaluate our algorithm on a simple artificial network and several real-networks. Experimental results demonstrate that the algorithm proposed is efficient for detecting overlapping communities in directed networks.  

  15. Design of M&C Network based on the Internet

    Institute of Scientific and Technical Information of China (English)

    Qi,Chang; Huang,Tianshu

    2005-01-01

    A new industry Internet system structure, "M&C Network Node" is presented and designed to construct an M&C network based on the Internet. The "M&C Network Node" has powerful communication and control abilities referring to the wide and complicate M&C network. By using the largely invisible and highly reliable field bus LonWorks, all the local M&C stations installed in the industrial field are integrated into one "M&C Network Node". For connecting the heterogeneous PLC instruments to the LonWorks network a serial adapter (RS232 standard) is designed. The adapter can be seen as the internal communication interface of the "M&C Network Node".The Ethernet interface of the "M&C Network Node" is realized by an Ethernet adapter, which is also designed. The hardware components and the two kinds communication interfaces of this"M&C Network Node" are described in detail in this paper.

  16. Document categorization using multilingual associative networks based on Wikipedia

    NARCIS (Netherlands)

    Bloom, Niels; Theune, Mariet; de Jong, Franciska M.G.

    Associative networks are a connectionist language model with the ability to categorize large sets of documents. In this research we combine monolingual associative networks based on Wikipedia to create a larger, multilingual associative network, using the cross-lingual connections between Wikipedia

  17. Document categorization using multilingual associative networks based on Wikipedia

    NARCIS (Netherlands)

    Bloom, Niels; Theune, Mariet; de Jong, Franciska M.G.

    2015-01-01

    Associative networks are a connectionist language model with the ability to categorize large sets of documents. In this research we combine monolingual associative networks based on Wikipedia to create a larger, multilingual associative network, using the cross-lingual connections between Wikipedia

  18. Document categorization using multilingual associative networks based on Wikipedia

    NARCIS (Netherlands)

    Bloom, Niels; Theune, Mariët; Jong, de Franciska

    2015-01-01

    Associative networks are a connectionist language model with the ability to categorize large sets of documents. In this research we combine monolingual associative networks based on Wikipedia to create a larger, multilingual associative network, using the cross-lingual connections between Wikipedia

  19. SOLVING INVERSE KINEMATICS OF REDUNDANT MANIPULATOR BASED ON NEURAL NETWORK

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    For the redundant manipulators, neural network is used to tackle the velocity inverse kinematics of robot manipulators. The neural networks utilized are multi-layered perceptions with a back-propagation training algorithm. The weight table is used to save the weights solving the inverse kinematics based on the different optimization performance criteria. Simulations verify the effectiveness of using neural network.

  20. A Direct Feedback Control Based on Fuzzy Recurrent Neural Network

    Institute of Scientific and Technical Information of China (English)

    李明; 马小平

    2002-01-01

    A direct feedback control system based on fuzzy-recurrent neural network is proposed, and a method of training weights of fuzzy-recurrent neural network was designed by applying modified contract mapping genetic algorithm. Computer simul ation results indicate that fuzzy-recurrent neural network controller has perfect dynamic and static performances .

  1. Prediction based chaos control via a new neural network

    Energy Technology Data Exchange (ETDEWEB)

    Shen Liqun [School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001 (China)], E-mail: liqunshen@gmail.com; Wang Mao [Space Control and Inertia Technology Research Center, Harbin Institute of Technology, Harbin 150001 (China); Liu Wanyu [School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001 (China); Sun Guanghui [Space Control and Inertia Technology Research Center, Harbin Institute of Technology, Harbin 150001 (China)

    2008-11-17

    In this Letter, a new chaos control scheme based on chaos prediction is proposed. To perform chaos prediction, a new neural network architecture for complex nonlinear approximation is proposed. And the difficulty in building and training the neural network is also reduced. Simulation results of Logistic map and Lorenz system show the effectiveness of the proposed chaos control scheme and the proposed neural network.

  2. Multivalued associative memories based on recurrent networks.

    Science.gov (United States)

    Chiueh, T D; Tsai, H K

    1993-01-01

    A multivalued neural associative memory model based on a recurrent network structure is proposed. This model adopts the same principle proposed in the authors' previous work, the exponential correlation associative memories (ECAM). The model also has a very high storage capacity and strong error-correction capability. The major components of the new model include a weighted average process and some similarity-measure computation. As in ECAM, in order to enhance the differences among the weights and make the largest weights more overwhelming, the new model incorporates a nonlinear function in the calculation of weights. Several possible similarity measures suitable for this model are suggested. Simulation results of the performance of the new model with different measures show that, loaded with 500 64-component patterns, the model can sustain noise with power about one fifth to three fifths of the average signal power.

  3. Multispectral thermometry based on neural network

    Institute of Scientific and Technical Information of China (English)

    孙晓刚; 戴景民

    2003-01-01

    In order to overcome the effect of the assumption between emissivity and wavelength on the measurement of true temperature and spectral emissivity for most engineering materials, a neural network based method is proposed for data processing while a blackbody furnace and three optical filters with known spectral transmittance curves were used to make up a true target. The experimental results show that the calculated temperatures are in good agreement with the temperature of the blackbody furnace, and the calculated spectral emissivity curves are in good agreement with the spectral transmittance curves of the filters. The method proposed has been proved to be an effective method for solving the problem of true temperature and emissivity measurement, and it can overcome the effect of the assumption between emissivity and wavelength on the measurement of true temperature and spectral emissivity for most engineering materials.

  4. The Cyclic Model Simplified

    CERN Document Server

    Steinhardt, P J; Steinhardt, Paul J.; Turok, Neil

    2004-01-01

    The Cyclic Model attempts to resolve the homogeneity, isotropy, and flatness problems and generate a nearly scale-invariant spectrum of fluctuations during a period of slow contraction that precedes a bounce to an expanding phase. Here we describe at a conceptual level the recent developments that have greatly simplified our understanding of the contraction phase and the Cyclic Model overall. The answers to many past questions and criticisms are now understood. In particular, we show that the contraction phase has equation of state w>1 and that contraction with w>1 has a surprisingly similar properties to inflation with w < -1/3. At one stroke, this shows how the model is different from inflation and why it may work just as well as inflation in resolving cosmological problems.

  5. Simplified Distributed Computing

    Science.gov (United States)

    Li, G. G.

    2006-05-01

    The distributed computing runs from high performance parallel computing, GRID computing, to an environment where idle CPU cycles and storage space of numerous networked systems are harnessed to work together through the Internet. In this work we focus on building an easy and affordable solution for computationally intensive problems in scientific applications based on existing technology and hardware resources. This system consists of a series of controllers. When a job request is detected by a monitor or initialized by an end user, the job manager launches the specific job handler for this job. The job handler pre-processes the job, partitions the job into relative independent tasks, and distributes the tasks into the processing queue. The task handler picks up the related tasks, processes the tasks, and puts the results back into the processing queue. The job handler also monitors and examines the tasks and the results, and assembles the task results into the overall solution for the job request when all tasks are finished for each job. A resource manager configures and monitors all participating notes. A distributed agent is deployed on all participating notes to manage the software download and report the status. The processing queue is the key to the success of this distributed system. We use BEA's Weblogic JMS queue in our implementation. It guarantees the message delivery and has the message priority and re-try features so that the tasks never get lost. The entire system is built on the J2EE technology and it can be deployed on heterogeneous platforms. It can handle algorithms and applications developed in any languages on any platforms. J2EE adaptors are provided to manage and communicate the existing applications to the system so that the applications and algorithms running on Unix, Linux and Windows can all work together. This system is easy and fast to develop based on the industry's well-adopted technology. It is highly scalable and heterogeneous. It is

  6. Arresting Strategy Based on Dynamic Criminal Networks Changing over Time

    Directory of Open Access Journals (Sweden)

    Junqing Yuan

    2013-01-01

    Full Text Available We investigate a sequence of dynamic criminal networks on a time series based on the dynamic network analysis (DNA. According to the change of networks’ structure, networks’ variation trend is analyzed to forecast its future structure. Finally, an optimal arresting time and priority list are designed based on our analysis. Better results can be expected than that based on social network analysis (SNA.

  7. Network Based Prediction Model for Genomics Data Analysis*

    OpenAIRE

    Huang, Ying; Wang, Pei

    2012-01-01

    Biological networks, such as genetic regulatory networks and protein interaction networks, provide important information for studying gene/protein activities. In this paper, we propose a new method, NetBoosting, for incorporating a priori biological network information in analyzing high dimensional genomics data. Specially, we are interested in constructing prediction models for disease phenotypes of interest based on genomics data, and at the same time identifying disease susceptible genes. ...

  8. A practice-based research network on the survival of ceramic inlay/onlay restorations.

    Science.gov (United States)

    Collares, Kauê; Corrêa, Marcos B; Laske, Mark; Kramer, Enno; Reiss, Bernd; Moraes, Rafael R; Huysmans, Marie-Charlotte D N J M; Opdam, Niek J M

    2016-05-01

    To evaluate prospectively the longevity of ceramic inlay/onlay restorations placed in a web-based practice-based research network and to investigate risk factors associated with restoration failures. Data were collected by a practice-based research network called Ceramic Success Analysis (CSA). 5791 inlay/onlay ceramic restorations were placed in 5523 patients by 167 dentists between 1994 and 2014 in their dental practices. For each restoration specific information related to the tooth, procedures and materials used were recorded. Annual failure rates (AFRs) were calculated and variables associated with failure were assessed by a multivariate Cox-regression analysis with shared frailty. The mean observation time was 3 years (maximum 15 years) of clinical service, and AFRs at 3 and 10 years follow up were calculated as 1.0% and 1.6%. Restorations with cervical outline in dentin showed a 78% higher risk for failure compared to restorations with margins in enamel. The presence of a liner or base of glass-ionomer cement resulted in a risk for failure twice as large as that of restorations without liner or base material. Restorations performed with simplified adhesive systems (2-step etch-and-rinse and 1-step self-etch) presented a risk of failure 142% higher than restorations performed with adhesives with bonding resin as a separate step (3-step etch-and-rinse and 2-step self-etch). 220 failures were recorded and the most predominant reason for failure was fracture of the restoration or tooth (44.5%). Ceramic inlay/onlay restorations made from several glass ceramic materials and applied by a large number of dentists showed a good survival. Deep cervical cavity outline, presence of a glass ionomer lining cement, and use of simplified adhesive systems were risk factors for survival. Copyright © 2016 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

  9. Reproducibility of automated simplified voxel-based analysis of PET amyloid ligand [{sup 11}C]PIB uptake using 30-min scanning data

    Energy Technology Data Exchange (ETDEWEB)

    Aalto, Sargo [University of Turku and Turku University Hospital, Turku PET Centre, Turku (Finland); Aabo Akademi University, Department of Psychology, Turku (Finland); University of Turku, Turku PET Centre, P.O. Box 52, Turku (Finland); Scheinin, Noora M.; Naagren, Kjell; Rinne, Juha O. [University of Turku and Turku University Hospital, Turku PET Centre, Turku (Finland); Kemppainen, Nina M. [University of Turku and Turku University Hospital, Turku PET Centre, Turku (Finland); Turku University Hospital, Department of Neurology, Turku (Finland); Kailajaervi, Marita [University of Turku, Department of Pharmacology and Clinical Research Services Turku (CRST), Turku (Finland); GE Healthcare, Turku Imanet, Turku (Finland); Leinonen, Mika [4-Pharma Ltd, Turku (Finland); Scheinin, Mika [University of Turku, Department of Pharmacology and Clinical Research Services Turku (CRST), Turku (Finland)

    2009-10-15

    Positron emission tomography (PET) with {sup 11}C-labelled Pittsburgh compound B ([{sup 11}C]PIB) enables the quantitation of {beta}-amyloid accumulation in the brain of patients with Alzheimer's disease (AD). Voxel-based image analysis techniques conducted in a standard brain space provide an objective, rapid and fully automated method to analyze [{sup 11}C]PIB PET data. The purpose of this study was to evaluate both region- and voxel-level reproducibility of automated and simplified [{sup 11}C]PIB quantitation when using only 30 min of imaging data. Six AD patients and four healthy controls were scanned twice with an average interval of 6 weeks. To evaluate the feasibility of short scanning (convenient for AD patients), [{sup 11}C]PIB uptake was quantitated using 30 min of imaging data (60 to 90 min after tracer injection) for region-to-cerebellum ratio calculations. To evaluate the reproducibility, a test-retest design was used to derive absolute variability (VAR) estimates and intraclass correlation coefficients at both region-of-interest (ROI) and voxel level. The reproducibility both at the region level (VAR 0.9-5.5%) and at the voxel level (VAR 4.2-6.4%) was good to excellent. Based on the variability estimates obtained, power calculations indicated that 90% power to obtain statistically significant difference can be achieved using a sample size of five subjects per group when a 15% change from baseline (increase or decrease) in [{sup 11}C]PIB accumulation in the frontal cortex is anticipated in one group compared to no change in another group. Our results showed that an automated analysis method based on an efficient scanning protocol provides reproducible results for [{sup 11}C]PIB uptake and appears suitable for PET studies aiming at the quantitation of amyloid accumulation in the brain of AD patients for the evaluation of progression and treatment effects. (orig.)

  10. Graphlet-based Characterization of Directed Networks

    Science.gov (United States)

    Sarajlić, Anida; Malod-Dognin, Noël; Yaveroğlu, Ömer Nebil; Pržulj, Nataša

    2016-10-01

    We are flooded with large-scale, dynamic, directed, networked data. Analyses requiring exact comparisons between networks are computationally intractable, so new methodologies are sought. To analyse directed networks, we extend graphlets (small induced sub-graphs) and their degrees to directed data. Using these directed graphlets, we generalise state-of-the-art network distance measures (RGF, GDDA and GCD) to directed networks and show their superiority for comparing directed networks. Also, we extend the canonical correlation analysis framework that enables uncovering the relationships between the wiring patterns around nodes in a directed network and their expert annotations. On directed World Trade Networks (WTNs), our methodology allows uncovering the core-broker-periphery structure of the WTN, predicting the economic attributes of a country, such as its gross domestic product, from its wiring patterns in the WTN for up-to ten years in the future. It does so by enabling us to track the dynamics of a country’s positioning in the WTN over years. On directed metabolic networks, our framework yields insights into preservation of enzyme function from the network wiring patterns rather than from sequence data. Overall, our methodology enables advanced analyses of directed networked data from any area of science, allowing domain-specific interpretation of a directed network’s topology.

  11. Network-based drugs and biomarkers.

    Science.gov (United States)

    Erler, Janine T; Linding, Rune

    2010-01-01

    The structure and dynamics of protein signalling networks governs cell decision processes and the formation of tissue boundaries. Complex diseases such as cancer and diabetes are diseases of such networks. Therefore approaches that can give insight into how these networks change during disease progression are crucial for better understanding, detection and intervention. The era of network medicine has begun; however, there are fundamental principles associated with molecular networks that are essential to consider for this field to succeed. Here, we introduce network biology and some of its associated technologies. We then focus on the multivariate nature of cellular networks and how this has implications for biomarker and drug discovery using cancer metastasis as an example.

  12. Reputation-based Telecommunication Network Selection

    CERN Document Server

    Seigneur, Jean-Marc

    2010-01-01

    Nowadays, mobile users can switch between different available networks, for example, nearby WiFi networks or their standard mobile operator network. Soon it will be extended to other operators. However, unless telecommunication operators can directly benefit from allowing a user to switch to another operator, operators have an incentive to keep their network quality of service confidential to avoid that their users decide to switch to another network. In contrast, in a user-centric way, the users should be allowed to share their observations regarding the networks that they have used. In this paper, we present our work in progress towards attack-resistant sharing of quality of service information and network provider reputation among mobile users.

  13. Dependable Emergency-Response Networking Based on Retaskable Network Infrastructures

    Science.gov (United States)

    2008-04-01

    routing follows a slightly modified version of the AODV protocol [PR99]. The primary drawback of AODV compared to DSR and some other routing ...require the entire route to be piggy-backed on the routing request packet. As was the case with the pre- vious protocols , we adapt AODV to take advantage...unsuitable for ERN scenarios, we showed that the AODV routing protocol used in mobile ad-hoc networks can support ERN services on popular types of net-

  14. Simplified Pavement Design for LPAs: Introduction to PaveXpress

    OpenAIRE

    2015-01-01

    Simplified Pavement Design for LPA's; An introduction to and use of PaveXpress, a simplified, free, web-based pavement design scoping tool for roadway and parking lot pavements. The system was developed by Pavia Systems in partnership with the National Asphalt Pavement Association. PaveXpress creates technical sound pavement structural designs for flexible and rigid pavements based on widely accepted industry standards from the Association of State Highway Officials (AASHTO). The simplified p...

  15. Simplified Pavement Design for LPAs: Introduction to PaveXpress

    OpenAIRE

    Bonte, Dudley

    2015-01-01

    Simplified Pavement Design for LPA's; An introduction to and use of PaveXpress, a simplified, free, web-based pavement design scoping tool for roadway and parking lot pavements. The system was developed by Pavia Systems in partnership with the National Asphalt Pavement Association. PaveXpress creates technical sound pavement structural designs for flexible and rigid pavements based on widely accepted industry standards from the Association of State Highway Officials (AASHTO). The simplified p...

  16. Community Detection for Multiplex Social Networks Based on Relational Bayesian Networks

    DEFF Research Database (Denmark)

    Jiang, Jiuchuan; Jaeger, Manfred

    2014-01-01

    Many techniques have been proposed for community detection in social networks. Most of these techniques are only designed for networks defined by a single relation. However, many real networks are multiplex networks that contain multiple types of relations and different attributes on the nodes....... In this paper we propose to use relational Bayesian networks for the specification of probabilistic network models, and develop inference techniques that solve the community detection problem based on these models. The use of relational Bayesian networks as a flexible high-level modeling framework enables us...... to express different models capturing different aspects of community detection in multiplex networks in a coherent manner, and to use a single inference mechanism for all models....

  17. An Improved Car-Following Model in Vehicle Networking Based on Network Control

    Directory of Open Access Journals (Sweden)

    D. Y. Kong

    2014-01-01

    Full Text Available Vehicle networking is a system to realize information interoperability between vehicles and people, vehicles and roads, vehicles and vehicles, and cars and transport facilities, through the network information exchange, in order to achieve the effective monitoring of the vehicle and traffic flow. Realizing information interoperability between vehicles and vehicles, which can affect the traffic flow, is an important application of network control system (NCS. In this paper, a car-following model using vehicle networking theory is established, based on network control principle. The car-following model, which is an improvement of the traditional traffic model, describes the traffic in vehicle networking condition. The impact that vehicle networking has on the traffic flow is quantitatively assessed in a particular scene of one-way, no lane changing highway. The examples show that the capacity of the road is effectively enhanced by using vehicle networking.

  18. SIMPLIFIED MATHEMATICAL MODEL OF SMALL SIZED UNMANNED AIRCRAFT VEHICLE LAYOUT

    Directory of Open Access Journals (Sweden)

    2016-01-01

    Full Text Available Strong reduction of new aircraft design period using new technology based on artificial intelligence is the key problem mentioned in forecasts of leading aerospace industry research centers. This article covers the approach to devel- opment of quick aerodynamic design methods based on artificial intelligence neural system. The problem is being solved for the classical scheme of small sized unmanned aircraft vehicle (UAV. The principal parts of the method are the mathe- matical model of layout, layout generator of this type of aircraft is built on aircraft neural networks, automatic selection module for cleaning variety of layouts generated in automatic mode, robust direct computational fluid dynamics method, aerodynamic characteristics approximators on artificial neural networks.Methods based on artificial neural networks have intermediate position between computational fluid dynamics methods or experiments and simplified engineering approaches. The use of ANN for estimating aerodynamic characteris-tics put limitations on input data. For this task the layout must be presented as a vector with dimension not exceeding sev-eral hundred. Vector components must include all main parameters conventionally used for layouts description and com- pletely replicate the most important aerodynamics and structural properties.The first stage of the work is presented in the paper. Simplified mathematical model of small sized UAV was developed. To estimate the range of geometrical parameters of layouts the review of existing vehicle was done. The result of the work is the algorithm and computer software for generating the layouts based on ANN technolo-gy. 10000 samples were generated and the dataset containig geometrical and aerodynamic characteristics of layoutwas created.

  19. DESIGN AND IMPLEMENTATION OF ROLE BASE ACCESS CONTROL SYSTEM FOR NETWORK RESOURCES

    Directory of Open Access Journals (Sweden)

    S.R. Kodituwakku

    2010-11-01

    Full Text Available Role Based Access Control is very useful for providing a high level description of access control for organizational applications. This paper proposes a role based framework that deals with security problems in an intranet environment. The proposed framework protects intranet resources from unauthorized users. The salient feature of the framework is that it allows intranet users to access only authorized resources. It consists of two kinds of role hierarchies: global role hierarchy and local role hierarchy, and two levels of permissions: server permission and object permission. They simplify the way of structuring authority and responsibility in the whole intranet and the allocation of privileges for different objects within a particular server. The proposed framework is implemented over Windows platform and tested for the validity. The test results indicated that it can successfully be used to control accessing network objects.

  20. A Neural Networks-Based Hybrid Routing Protocol for Wireless Mesh Networks

    Directory of Open Access Journals (Sweden)

    Nenad Kojić

    2012-06-01

    Full Text Available The networking infrastructure of wireless mesh networks (WMNs is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide users with high-bandwidth networks over a specific coverage area. The main problems affecting these networks are changes in network topology and link quality. In order to provide regular functioning, the routing protocol has the main influence in WMN implementations. In this paper we suggest a new routing protocol for WMN, based on good results of a proactive and reactive routing protocol, and for that reason it can be classified as a hybrid routing protocol. The proposed solution should avoid flooding and creating the new routing metric. We suggest the use of artificial logic—i.e., neural networks (NNs. This protocol is based on mobile agent technologies controlled by a Hopfield neural network. In addition to this, our new routing metric is based on multicriteria optimization in order to minimize delay and blocking probability (rejected packets or their retransmission. The routing protocol observes real network parameters and real network environments. As a result of artificial logic intelligence, the proposed routing protocol should maximize usage of network resources and optimize network performance.

  1. A Neural Networks-Based Hybrid Routing Protocol for Wireless Mesh Networks

    Science.gov (United States)

    Kojić, Nenad; Reljin, Irini; Reljin, Branimir

    2012-01-01

    The networking infrastructure of wireless mesh networks (WMNs) is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide users with high-bandwidth networks over a specific coverage area. The main problems affecting these networks are changes in network topology and link quality. In order to provide regular functioning, the routing protocol has the main influence in WMN implementations. In this paper we suggest a new routing protocol for WMN, based on good results of a proactive and reactive routing protocol, and for that reason it can be classified as a hybrid routing protocol. The proposed solution should avoid flooding and creating the new routing metric. We suggest the use of artificial logic—i.e., neural networks (NNs). This protocol is based on mobile agent technologies controlled by a Hopfield neural network. In addition to this, our new routing metric is based on multicriteria optimization in order to minimize delay and blocking probability (rejected packets or their retransmission). The routing protocol observes real network parameters and real network environments. As a result of artificial logic intelligence, the proposed routing protocol should maximize usage of network resources and optimize network performance. PMID:22969360

  2. A neural networks-based hybrid routing protocol for wireless mesh networks.

    Science.gov (United States)

    Kojić, Nenad; Reljin, Irini; Reljin, Branimir

    2012-01-01

    The networking infrastructure of wireless mesh networks (WMNs) is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide users with high-bandwidth networks over a specific coverage area. The main problems affecting these networks are changes in network topology and link quality. In order to provide regular functioning, the routing protocol has the main influence in WMN implementations. In this paper we suggest a new routing protocol for WMN, based on good results of a proactive and reactive routing protocol, and for that reason it can be classified as a hybrid routing protocol. The proposed solution should avoid flooding and creating the new routing metric. We suggest the use of artificial logic-i.e., neural networks (NNs). This protocol is based on mobile agent technologies controlled by a Hopfield neural network. In addition to this, our new routing metric is based on multicriteria optimization in order to minimize delay and blocking probability (rejected packets or their retransmission). The routing protocol observes real network parameters and real network environments. As a result of artificial logic intelligence, the proposed routing protocol should maximize usage of network resources and optimize network performance.

  3. Identification of sources of pollution and contamination in water distribution networks based on pattern recognition

    Institute of Scientific and Technical Information of China (English)

    Tao TAO; Ying-jun LU; Xiang FU; Kun-lun XIN

    2012-01-01

    An intrusion of contaminants into the water distribution network (WDN) can occur through storage tanks (via animals.dust-carrying bacteria,and infiltration) and pipes.A sensor network could yield useful observations that help identify the location of the source,the strength,the time of occurrence.and the duration of contamination.This paper proposes a methodology for identifying the contamination sources in a water distribution system,which identifies the key characteristics of contamination.such as location,starting time.and injection rates at different time intervals.Based on simplified hypotheses and associated with a high computational efficiency.the methodology is designed to be a simple and easy-to-use tool for water companies to ensure rapid identification of the contamination sources,The proposed methodology identifies the characteristics of pollution sources by matching the dynamic patterns of the simulated and measured concentrations.The application of this methodology to a literature network and a real WDN are illustrated with the aid of an example.The results showed that if contaminants are transported from the sources to the sensors at intervals,then this method can identify the most possible ones from candidate pollution sources.However,if the contamination data is minimal,a greater number of redundant contamination source nodes will be present.Consequently,more data from different sensors obtained through network monitoring are required to effectively use this method for locating multi-sources of contamination in the WDN.

  4. Network Security Enhancement through Honeypot based Systems

    Directory of Open Access Journals (Sweden)

    S Deepa Lakshmi

    2015-02-01

    Full Text Available Computer Networks and Internet has become very famous nowadays since it satisfies people with varying needs by providing variety of appropriate services. Computer Networks have revolutionized our use of computers. Online bills, shopping, transactions and many other essential activities performed on the go by just a single click from our homes. Though it is a boon in this era, it also has its own risks and weaknesses too. Industries need to tussle to provide security to their networks and indeed not possible to offer a cent per cent security due to the intangible intelligence of hackers intruding into the network. This paper exploits the concept of honeypots for providing security to networks of industries which may not have custom intrusion detection systems or firewalls. The proposed model captures the various techniques used by hackers and creates a log of all hacker activities. Thus using this log, the production network system can be prevented from attackers.

  5. Network-based production quality control

    Science.gov (United States)

    Kwon, Yongjin; Tseng, Bill; Chiou, Richard

    2007-09-01

    This study investigates the feasibility of remote quality control using a host of advanced automation equipment with Internet accessibility. Recent emphasis on product quality and reduction of waste stems from the dynamic, globalized and customer-driven market, which brings opportunities and threats to companies, depending on the response speed and production strategies. The current trends in industry also include a wide spread of distributed manufacturing systems, where design, production, and management facilities are geographically dispersed. This situation mandates not only the accessibility to remotely located production equipment for monitoring and control, but efficient means of responding to changing environment to counter process variations and diverse customer demands. To compete under such an environment, companies are striving to achieve 100%, sensor-based, automated inspection for zero-defect manufacturing. In this study, the Internet-based quality control scheme is referred to as "E-Quality for Manufacturing" or "EQM" for short. By its definition, EQM refers to a holistic approach to design and to embed efficient quality control functions in the context of network integrated manufacturing systems. Such system let designers located far away from the production facility to monitor, control and adjust the quality inspection processes as production design evolves.

  6. The Simplified Posterior Interosseous Flap.

    Science.gov (United States)

    Cavadas, Pedro C; Thione, Alessandro; Rubí, Carlos

    2016-09-01

    Several technical modifications have been described to avoid complications and simplify dissection. The authors describe some technical tips that make posterior interosseous flap dissection safer and more straightforward.

  7. The guitar chord-generating algorithm based on complex network

    Science.gov (United States)

    Ren, Tao; Wang, Yi-fan; Du, Dan; Liu, Miao-miao; Siddiqi, Awais

    2016-02-01

    This paper aims to generate chords for popular songs automatically based on complex network. Firstly, according to the characteristics of guitar tablature, six chord networks of popular songs by six pop singers are constructed and the properties of all networks are concluded. By analyzing the diverse chord networks, the accompaniment regulations and features are shown, with which the chords can be generated automatically. Secondly, in terms of the characteristics of popular songs, a two-tiered network containing a verse network and a chorus network is constructed. With this network, the verse and chorus can be composed respectively with the random walk algorithm. Thirdly, the musical motif is considered for generating chords, with which the bad chord progressions can be revised. This method can make the accompaniments sound more melodious. Finally, a popular song is chosen for generating chords and the new generated accompaniment sounds better than those done by the composers.

  8. An algorithm for motif-based network design

    CERN Document Server

    Mäki-Marttunen, Tuomo

    2016-01-01

    A determinant property of the structure of a biological network is the distribution of local connectivity patterns, i.e., network motifs. In this work, a method for creating directed, unweighted networks while promoting a certain combination of motifs is presented. This motif-based network algorithm starts with an empty graph and randomly connects the nodes by advancing or discouraging the formation of chosen motifs. The in- or out-degree distribution of the generated networks can be explicitly chosen. The algorithm is shown to perform well in producing networks with high occurrences of the targeted motifs, both ones consisting of 3 nodes as well as ones consisting of 4 nodes. Moreover, the algorithm can also be tuned to bring about global network characteristics found in many natural networks, such as small-worldness and modularity.

  9. A simplified technique for determining the rotational motion of a satellite based on the onboard measurements of the angular velocity and magnetic field of the Earth

    Science.gov (United States)

    Abrashkin, V. I.; Voronov, K. E.; Piyakov, I. V.; Puzin, Yu. Ya.; Sazonov, V. V.; Syomkin, N. D.; Chebukov, S. Yu.

    2016-09-01

    The mathematical model, which allowed us to reconstruct the rotational motion of the Bion M-1 and Foton M-4 satellites by processing the measurements of onboard magnetometers and the angular velocity sensor, is sufficiently detailed and accurate. If we slightly lower the requirements for accuracy and transfer to a rougher model, i.e., we will not update the biases in measurements of the angular velocity component, then the measurement processing technique can be significantly simplified. The volume of calculations in minimizing the functional of the least-square technique is reduced; the most complicated part of calculations is performed using the standard procedure of computational linear algebra. This simplified technique is described below, and the examples of its application for reconstructing the rotational motion of the Foton M-4 satellite are presented. A noticeable distinction in the reconstructions of motion, constructed by simplified and more exact techniques, is revealed in processing the measurements over time intervals longer than 4 hours.

  10. Carrier ethernet network control plane based on the Next Generation Network

    DEFF Research Database (Denmark)

    Fu, Rong; Wang, Yanmeng; Berger, Michael Stubert

    2008-01-01

    architecture of the next generation network (NGN). As an essential candidate among the NGN transport technologies, the definition of Carrier Ethernet (CE) is also introduced here. The second part of this paper depicts the contribution on the T-MPLS based Carrier Ethernet network with control plane based on NGN...

  11. Packet scheduling for OFDMA based relay networks

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The combination of relay networks with orthogonal frequency division multiple access (OFDMA) has been proposed as a promising solution for the next generation wireless system. Considering different traffic classes and user quality of service (QoS), three efficient scheduling algorithms are introduced in such networks. The round-robin (RR) algorithm in relay networks serves as a performance benchmark. Numerical results show that the proposed algorithms achieve significant improvement on system throughput and decrease system packet loss rate, compared with the RR and absence of relaying system (traditional network). Furthermore, comparisons have been carried out among the three proposed algorithms.

  12. Simplified Approach to Inspection Planning

    DEFF Research Database (Denmark)

    Bloch, Allan; Sørensen, John Dalsgaard; Faber, M. H.

    2000-01-01

    A simplified and practically applicable approach for risk based inspection planning of fatigue sensitive structural details is presented. The basic idea behind the approach is that the fatigue sensitive details are categorized according to their stress intensity factors and their design fatigue l...... of steel structures. The validity of the proposed approach is illustrated through a study regarding inspection planning of offshore structures....... life to service life ratio, i.e. the fatigue design factor (FDF) and SN curve. When the reserve strength ratio (RSR) and the corresponding probability of total structural failure given fatigue failure of the considered detail is known it is possible to make a generic description of fatigue sensitive...... structural details and thereby develop pre-made inspection plans in tables which depend on relative cost of inspections, repairs and failures. Due to the simplicity of the format of the developed inspection plans the proposed approach has a high potential in code making for the design and maintenance...

  13. Simplified SIMPs and the LHC

    Energy Technology Data Exchange (ETDEWEB)

    Daci, N.; Bruyn, I. De; Lowette, S. [Inter-University Institute for High Energies, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels (Belgium); Tytgat, M.H.G.; Zaldivar, B. [Service de Physique Théorique, Université Libre de Bruxelles, Boulevard du Triomphe, CP225, 1050 Brussels (Belgium)

    2015-11-17

    The existence of Dark Matter (DM) in the form of Strongly Interacting Massive Particles (SIMPs) may be motivated by astrophysical observations that challenge the classical Cold DM scenario. Other observations greatly constrain, but do not completely exclude, the SIMP alternative. The signature of SIMPs at the LHC may consist of neutral, hadron-like, trackless jets produced in pairs. We show that the absence of charged content can provide a very efficient tool to suppress dijet backgrounds at the LHC, thus enhancing the sensitivity to a potential SIMP signal. We illustrate this using a simplified SIMP model and present a detailed feasibility study based on simulations, including a dedicated detector response parametrization. We evaluate the expected sensitivity to various signal scenarios and tentatively consider the exclusion limits on the SIMP elastic cross section with nucleons.

  14. Evidence That Calls-Based and Mobility Networks Are Isomorphic.

    Directory of Open Access Journals (Sweden)

    Michele Coscia

    Full Text Available Social relations involve both face-to-face interaction as well as telecommunications. We can observe the geography of phone calls and of the mobility of cell phones in space. These two phenomena can be described as networks of connections between different points in space. We use a dataset that includes billions of phone calls made in Colombia during a six-month period. We draw the two networks and find that the call-based network resembles a higher order aggregation of the mobility network and that both are isomorphic except for a higher spatial decay coefficient of the mobility network relative to the call-based network: when we discount distance effects on the call connections with the same decay observed for mobility connections, the two networks are virtually indistinguishable.

  15. Network Access Control for Location-Based Mobile Services in Heterogeneous Wireless Networks

    Directory of Open Access Journals (Sweden)

    Dae-Young Kim

    2017-01-01

    Full Text Available Recent advances in information communication technology and software have enabled mobile terminals to employ various capabilities as a smartphone. They adopt multiple interfaces for wireless communication and run as a portable computer. Mobile services are also transferred from voice to data. Mobile terminals can access Internet for data services anytime anywhere. By using location-based information, improved mobile services are enabled in heterogeneous networks. In the mobile service environment, it is required that mobile terminals should efficiently use wireless network resources. In addition, because video stream becomes a major service among the data services of mobile terminals in heterogeneous networks, the necessity of the efficient network access control for heterogeneous wireless networks is raised as an important topic. That is, quality of services of the location-based video stream is determined by the network access control. Therefore, this paper proposes a novel network access control in the heterogeneous wireless networks. The proposed method estimates the network status with Naïve Bayesian Classifier and performs network access control according to the estimated network status. Thus, it improves data transmission efficiency to satisfy the quality of services. The efficiency of the proposed method is validated through the extensive computer simulation.

  16. Gossip Based Routing Protocol Design for Ad Hoc Networks

    OpenAIRE

    Toqeer Mahmood; Tabbassam Nawaz; Rehan Ashraf; Syed M. Adnan Shah

    2012-01-01

    A spontaneously mannered decentralized network with no formal infrastructure and limited in temporal and spatial extent where each node communicate with each other over a wireless channel and is willing to forward data for other nodes is called as Wireless Ad Hoc network. In this research study, we proposed a routing strategy based on gossip based routing approach that follows the proactive routing with some treatment for wireless Ad Hoc network. The analytical verification of our proposed id...

  17. Network capacity with probit-based stochastic user equilibrium problem

    Science.gov (United States)

    Lu, Lili; Wang, Jian; Zheng, Pengjun; Wang, Wei

    2017-01-01

    Among different stochastic user equilibrium (SUE) traffic assignment models, the Logit-based stochastic user equilibrium (SUE) is extensively investigated by researchers. It is constantly formulated as the low-level problem to describe the drivers’ route choice behavior in bi-level problems such as network design, toll optimization et al. The Probit-based SUE model receives far less attention compared with Logit-based model albeit the assignment result is more consistent with drivers’ behavior. It is well-known that due to the identical and irrelevant alternative (IIA) assumption, the Logit-based SUE model is incapable to deal with route overlapping problem and cannot account for perception variance with respect to trips. This paper aims to explore the network capacity with Probit-based traffic assignment model and investigate the differences of it is with Logit-based SUE traffic assignment models. The network capacity is formulated as a bi-level programming where the up-level program is to maximize the network capacity through optimizing input parameters (O-D multiplies and signal splits) while the low-level program is the Logit-based or Probit-based SUE problem formulated to model the drivers’ route choice. A heuristic algorithm based on sensitivity analysis of SUE problem is detailed presented to solve the proposed bi-level program. Three numerical example networks are used to discuss the differences of network capacity between Logit-based SUE constraint and Probit-based SUE constraint. This study finds that while the network capacity show different results between Probit-based SUE and Logit-based SUE constraints, the variation pattern of network capacity with respect to increased level of travelers’ information for general network under the two type of SUE problems is the same, and with certain level of travelers’ information, both of them can achieve the same maximum network capacity. PMID:28178284

  18. Validation of Gene Regulatory Network Inference Based on Controllability

    Directory of Open Access Journals (Sweden)

    Edward eDougherty

    2013-12-01

    Full Text Available There are two distinct issues regarding network validation: (1 Does an inferred network provide good predictions relative to experimental data? (2 Does a network inference algorithm applied within a certain network model framework yield networks that are accurate relative to some criterion of goodness? The first issue concerns scientific validation and the second concerns algorithm validation. In this paper we consider inferential validation relative to controllability; that is, if an inference procedure is applied to synthetic data generated from a gene regulatory network and an intervention procedure is designed on the inferred network, how well does it perform on the true network? The reasoning behind such a criterion is that, if our purpose is to use gene regulatory networks to design therapeutic intervention strategies, then we are not concerned with network fidelity, per se, but only with our ability to design effective interventions based on the inferred network. We will consider the problem from the perspectives of stationary control, which involves designing a control policy to be applied over time based on the current state of the network, with the decision procedure itself being time independent. {The objective of a control policy is to optimally reduce the total steady-state probability mass of the undesirable states (phenotypes, which is equivalent to optimally increasing the total steady-state mass of the desirable states. Based on this criterion we compare several proposed network inference procedures. We will see that inference procedure psi may perform poorer than inference procedure xi relative to inferring the full network structure but perform better than xi relative to controllability. Hence, when one is aiming at a specific application, it may be wise to use an objective-based measure of inference validity.

  19. A Spectrum Handoff Scheme for Optimal Network Selection in NEMO Based Cognitive Radio Vehicular Networks

    Directory of Open Access Journals (Sweden)

    Krishan Kumar

    2017-01-01

    Full Text Available When a mobile network changes its point of attachments in Cognitive Radio (CR vehicular networks, the Mobile Router (MR requires spectrum handoff. Network Mobility (NEMO in CR vehicular networks is concerned with the management of this movement. In future NEMO based CR vehicular networks deployment, multiple radio access networks may coexist in the overlapping areas having different characteristics in terms of multiple attributes. The CR vehicular node may have the capability to make call for two or more types of nonsafety services such as voice, video, and best effort simultaneously. Hence, it becomes difficult for MR to select optimal network for the spectrum handoff. This can be done by performing spectrum handoff using Multiple Attributes Decision Making (MADM methods which is the objective of the paper. The MADM methods such as grey relational analysis and cost based methods are used. The application of MADM methods provides wider and optimum choice among the available networks with quality of service. Numerical results reveal that the proposed scheme is effective for spectrum handoff decision for optimal network selection with reduced complexity in NEMO based CR vehicular networks.

  20. Stabilization of model-based networked control systems

    Science.gov (United States)

    Miranda, Francisco; Abreu, Carlos; Mendes, Paulo M.

    2016-06-01

    A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network trafic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtain an optimal feedback control is also presented.

  1. Ethernet-based Mass Volume Train Security Detection Network

    Directory of Open Access Journals (Sweden)

    D. Q. He

    2013-07-01

    Full Text Available As the existing train communication network transmission rate is low, large capacity status and fault diagnosis data, the event log data, passenger information which are stored in different vehicles equipments, it is difficult to realize fault diagnosis and intelligent maintenance efficiently and timely. Based on the train level and vehicle level Ethernet network, this paper will focus on network construction technology and real-time performance of mass volume onboard security detection network. The research results will improve control and network function of train.

  2. Cancer classification based on gene expression using neural networks.

    Science.gov (United States)

    Hu, H P; Niu, Z J; Bai, Y P; Tan, X H

    2015-12-21

    Based on gene expression, we have classified 53 colon cancer patients with UICC II into two groups: relapse and no relapse. Samples were taken from each patient, and gene information was extracted. Of the 53 samples examined, 500 genes were considered proper through analyses by S-Kohonen, BP, and SVM neural networks. Classification accuracy obtained by S-Kohonen neural network reaches 91%, which was more accurate than classification by BP and SVM neural networks. The results show that S-Kohonen neural network is more plausible for classification and has a certain feasibility and validity as compared with BP and SVM neural networks.

  3. A simplified traveling ionospheric disturbance (TID) specification model based on TID Detector Built In Texas (TIDDBIT) and GPS total electron content (TEC) measurements.

    Science.gov (United States)

    Duly, T. M.; Crowley, G.; Azeem, I.

    2015-12-01

    There is currently a great deal of interest in Traveling Ionospheric Disturbances (TIDs) from both an observational and modeling perspective, especially as they apply to operational systems that rely on nowcasting the ionospheric state. ASTRA has developed a new observational system to measure TID characteristics called TIDDBIT (TID Detector Built in Texas). TIDDBIT is a fully digital HF Doppler sounder that uses CW signals across a spaced array. TIDDBIT systems have been deployed in Texas, Virginia, Florida, Hawaii, and Peru. TIDDBIT measures the entire wave packet, including the horizontal and vertical phase propagation speeds as a function of TID period from the acoustic (1-min) to the gravity wave (10-90 min) part of the spectrum. It is desirable to be able to use these data to specify the TID structure not only at the measurement height, but to extend it in 3D to greater and lower heights, and beyond the immediate vicinity of the TIDDBIT system. We present a simplified model to specify TIDs based on the ion continuity equation for plasma density (Hooke 1970). Linearity of the neutral wind perturbations is assumed, and the different spectral components of the measured TID perturbations are added linearly. We use TID observations from the TIDDBIT sounder in Virginia and Peru as input into the model, and develop a 4D regional specification (spanning ~500 x 500 km in the horizontal direction and 90-1000 km altitude range) of both the perturbed electron density and the perturbed neutral wind from the corresponding atmospheric gravity wave (AGW). The model is also applied to TID measurements derived by GPS TEC measurements from the continental United States during the 11 March 2011 Tohoku Earthquake to study the theoretical launch angle of AGWs from the west coast of the United States.

  4. Analysis and Simulation of the Simplified Aircraft-Based Paired Approach Concept With the ALAS Alerting Algorithm in Conjunction With Echelon and Offset Strategies

    Science.gov (United States)

    Torres-Pomales, Wilfredo; Madden, Michael M.; Butler, Rickey W.; Perry, Raleigh B.

    2014-01-01

    This report presents analytical and simulation results of an investigation into proposed operational concepts for closely spaced parallel runways, including the Simplified Aircraft-based Paired Approach (SAPA) with alerting and an escape maneuver, MITRE?s echelon spacing and no escape maneuver, and a hybrid concept aimed at lowering the visibility minima. We found that the SAPA procedure can be used at 950 ft separations or higher with next-generation avionics and that 1150 ft separations or higher is feasible with current-rule compliant ADS-B OUT. An additional 50 ft reduction in runway separation for the SAPA procedure is possible if different glideslopes are used. For the echelon concept we determined that current generation aircraft cannot conduct paired approaches on parallel paths using echelon spacing on runways less than 1400 ft apart and next-generation aircraft will not be able to conduct paired approach on runways less than 1050 ft apart. The hybrid concept added alerting and an escape maneuver starting 1 NM from the threshold when flying the echelon concept. This combination was found to be effective, but the probability of a collision can be seriously impacted if the turn component of the escape maneuver has to be disengaged near the ground (e.g. 300 ft or below) due to airport buildings and surrounding terrain. We also found that stabilizing the approach path in the straight-in segment was only possible if the merge point was at least 1.5 to 2 NM from the threshold unless the total system error can be sufficiently constrained on the offset path and final turn.

  5. Policy-based network management with SNMP

    NARCIS (Netherlands)

    Boros, S.

    2000-01-01

    This paper presents a way of managing configuration of network elements via a set of high-level rules or business policies rather than managing device by device. First, there is a need for abstraction of the capabilities of the individual devices, thus switching the control to network level. The ben

  6. Networks as Power Bases for School Improvement

    Science.gov (United States)

    Moore, Tessa A.; Kelly, Michael P.

    2009-01-01

    Although there is limited research into the success of primary school networking initiatives in the UK, there is a drive at national government level for promoting school collaborative working arrangements as a catalyst for whole-school improvement. This paper discusses the findings from research into two such initiatives: "Networked Learning…

  7. Simplified Serial Bus Based on Time-Triggered Architecture%基于时间触发的精简串行总线技术

    Institute of Scientific and Technical Information of China (English)

    吕富勇; 李永新; 卜雄洙; 于葛亮; 蒋杏国

    2011-01-01

    针对事件触发机制应用到小型分布式测试系统中,存在控制命令复杂、需要主控制器的不足,提出一种基于时间触发的精简串行总线技术.详细分析总线系统的组成、信号线定义、总线系统基本特征、数据格式以及总线系统的时分多路访问(Time division multiple access,TDMA)通信控制机制.重点介绍时间触发功能的TDMA时序管理机的实现方法,进行基于硬件描述语言Verilog-hdl的软件设计,并进行仿真.仿真结果显示,TDMA时序管理机可实现系统多节点时槽分配管理功能,采用该时序管理机有利于实现基于时间触发的总线控制方案、构建小型分布式测试系统.%Applying event-triggered method in the small scaled distributed test system exposes its defect of complicated control and shortage of a main processor. Simplified serial bus based on time-triggered architecture is proposed. The composition of the bus system, the definitions of the bus signal line, the basic characteristics of the bus system, the data format and the time division multiple access(TDMA) communication control mechanism are carefully analyzed. The method of how to realize the TDMA time management machine based on time-triggered architecture is introduced. And the software based on the hardware description language Verilog-hdl is designed. Simulation and the results show that the TDMA time management machine realizes the function of time slot allotment management. With the time management machine, the bus control design based on time triggered architecture can be easily carried out, and a brief effective small scaled distributed test system can be constructed.

  8. A Network Formation Model Based on Subgraphs

    CERN Document Server

    Chandrasekhar, Arun

    2016-01-01

    We develop a new class of random-graph models for the statistical estimation of network formation that allow for substantial correlation in links. Various subgraphs (e.g., links, triangles, cliques, stars) are generated and their union results in a network. We provide estimation techniques for recovering the rates at which the underlying subgraphs were formed. We illustrate the models via a series of applications including testing for incentives to form cross-caste relationships in rural India, testing to see whether network structure is used to enforce risk-sharing, testing as to whether networks change in response to a community's exposure to microcredit, and show that these models significantly outperform stochastic block models in matching observed network characteristics. We also establish asymptotic properties of the models and various estimators, which requires proving a new Central Limit Theorem for correlated random variables.

  9. Network Anomaly Detection Based on Wavelet Analysis

    Directory of Open Access Journals (Sweden)

    Ali A. Ghorbani

    2008-11-01

    Full Text Available Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

  10. Estimating the Capacity of Urban Transportation Networks with an Improved Sensitivity Based Method

    Directory of Open Access Journals (Sweden)

    Muqing Du

    2015-01-01

    Full Text Available The throughput of a given transportation network is always of interest to the traffic administrative department, so as to evaluate the benefit of the transportation construction or expansion project before its implementation. The model of the transportation network capacity formulated as a mathematic programming with equilibrium constraint (MPEC well defines this problem. For practical applications, a modified sensitivity analysis based (SAB method is developed to estimate the solution of this bilevel model. The high-efficient origin-based (OB algorithm is extended for the precise solution of the combined model which is integrated in the network capacity model. The sensitivity analysis approach is also modified to simplify the inversion of the Jacobian matrix in large-scale problems. The solution produced in every iteration of SAB is restrained to be feasible to guarantee the success of the heuristic search. From the numerical experiments, the accuracy of the derivatives for the linear approximation could significantly affect the converging of the SAB method. The results also show that the proposed method could obtain good suboptimal solutions from different starting points in the test examples.

  11. Implementation of neural network based non-linear predictive

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

    1998-01-01

    -linear systems. GPC is model-based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis on an efficient Quasi...

  12. Implementation of neural network based non-linear predictive control

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

    1999-01-01

    of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...

  13. J2EE-based integrated telecom network management

    Science.gov (United States)

    Xia, Zhongwu; Wei, Guo

    2004-04-01

    The paper will present a J2EE-based architecture of integrated telecom network management system, and also will introduce the MVC(Model, View and Control) design pattern in the architecture. Using J2EE and MVC design pattern, we can easily build multiple user interfaces (included Web-based), flexible, manageable, and extensible network management system.

  14. Improving Student Engagement Using Course-Based Social Networks

    Science.gov (United States)

    Imlawi, Jehad Mohammad

    2013-01-01

    This study proposes an engagement model that supports use of course-based online social networks for engaging student, and hence, improving their educational outcomes. This research demonstrates that instructors who create course-based online social networks to communicate with students can increase the student engagement in these online social…

  15. Improving Student Engagement Using Course-Based Social Networks

    Science.gov (United States)

    Imlawi, Jehad Mohammad

    2013-01-01

    This study proposes an engagement model that supports use of course-based online social networks for engaging student, and hence, improving their educational outcomes. This research demonstrates that instructors who create course-based online social networks to communicate with students can increase the student engagement in these online social…

  16. A New SDH-Based ATM Network Survivability Escalation Mechanism

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This paper investigates survivability escalation strategies in multi-layers transport networks such as ATM/SDH/WDM networks, and presents oriented-failures and oriented-traffic escalation mechanisms. Furthermore, We present a new survivability Escalation strategy for SDH-Based ATM transport networks, which addresses difficult problem for resources sharing pool(RSP) among different layers restoration mechanisms. In this paper, we also present integer programming (IP) model for the resources sharing pool (RSP) design problem and the node simulation model for escalation Node. The simulation results show that the proposed ESP is very efficient. The proposed model can be easily extended for other types of multi-layer networks, such as WDM-based ATM networks or WDM-based SDH networks.

  17. Protein Structure Network-based Drug Design.

    Science.gov (United States)

    Liang, Zhongjie; Hu, Guang

    2016-01-01

    Although structure-based drug design (SBDD) has become an indispensable tool in drug discovery for a long time, it continues to pose major challenges to date. With the advancement of "omics" techniques, systems biology has enriched SBDD into a new era, called polypharmacology, in which multi-targets drug or drug combination is designed to fight complex diseases. As a preliminary tool in systems biology, protein structure networks (PSNs) treat a protein as a set of residues linked by edges corresponding to the intramolecular interactions existing in folded structures between the residues. The PSN offers a computationally efficient tool to study the structure and function of proteins, and thus may facilitate structurebased drug design. Herein, we provide an overview of recent advances in PSNs, from predicting functionally important residues, to charactering protein-protein interactions and allosteric communication paths. Furthermore, we discuss potential pharmacological applications of PSN concepts and tools, and highlight the application to two families of drug targets, GPCRs and Hsp90. Although the application of PSNs as a framework for computer-aided drug discovery has been limited to date, we put forward the potential utility value in the near future and propose the PSNs could also serve as a new tool for polypharmacology research.

  18. Generic simplified simulation model for DFIG with active crowbar

    Energy Technology Data Exchange (ETDEWEB)

    Buendia, Francisco Jimenez [Gamesa Innovation and Technology, Sarriguren, Navarra (Spain). Technology Dept.; Barrasa Gordo, Borja [Assystem Iberia, Bilbao, Vizcaya (Spain)

    2012-07-01

    Simplified models for transient stability studies are a general requirement for transmission system operators to wind turbine (WTG) manufacturers. Those models must represent the performance of the WTGs for transient stability studies, mainly voltage dips originated by short circuits in the electrical network. Those models are implemented in simulation software as PSS/E, DigSilent or PSLF. Those software platforms allow simulation of transients in large electrical networks with thousands of busses, generators and loads. The high complexity of the grid requires that the models inserted into the grid should be simplified in order to allow the simulations being executed as fast as possible. The development of a model which is simplified enough to be integrated in those complex grids and represent the performance of WTG is a challenge. The IEC TC88 working group has developed generic models for different types of generators, among others for WTGs using doubly fed induction generators (DFIG). This paper will focus in an extension of the models for DFIG WTGs developed in IEC in order to be able to represent the simplified model of DFIG with an active crowbar, which is required to withstand voltage dips without disconnecting from the grid. This paper improves current generic model of Type 3 for DFIG adding a simplified version of the generator including crowbar functionality and a simplified version of the crowbar firing. In addition, this simplified model is validated by correlation with voltage dip field test from a real wind turbine. (orig.)

  19. Utility-based bandwidth allocation algorithm for heterogeneous wireless networks

    Institute of Scientific and Technical Information of China (English)

    CHAI Rong; WANG XiuJuan; CHEN QianBin; SVENSSON Tommy

    2013-01-01

    In next generation wireless network (NGWN), mobile users are capable of connecting to the core network through various heterogeneous wireless access networks, such as cellular network, wireless metropolitan area network (WMAN), wireless local area network (WLAN), and ad hoc network. NGWN is expected to provide high-bandwidth connectivity with guaranteed quality-of-service to mobile users in a seamless manner; however, this desired function demands seamless coordination of the heterogeneous radio access network (RAN) technologies. In recent years, some researches have been conducted to design radio resource management (RRM) architectures and algorithms for NGWN; however, few studies stress the problem of joint network performance optimization, which is an essential goal for a cooperative service providing scenario. Furthermore, while some authors consider the competition among the service providers, the QoS requirements of users and the resource competition within access networks are not fully considered. In this paper, we present an interworking integrated network architecture, which is responsible for monitoring the status information of different radio access technologies (RATs) and executing the resource allocation algorithm. Within this architecture, the problem of joint bandwidth allocation for heterogeneous integrated networks is formulated based on utility function theory and bankruptcy game theory. The proposed bandwidth allocation scheme comprises two successive stages, i.e., service bandwidth allocation and user bandwidth allocation. At the service bandwidth allocation stage, the optimal amount of bandwidth for different types of services in each network is allocated based on the criterion of joint utility maximization. At the user bandwidth allocation stage, the service bandwidth in each network is optimally allocated among users in the network according to bankruptcy game theory. Numerical results demonstrate the efficiency of

  20. Process-based network decomposition reveals backbone motif structure.

    Science.gov (United States)

    Wang, Guanyu; Du, Chenghang; Chen, Hao; Simha, Rahul; Rong, Yongwu; Xiao, Yi; Zeng, Chen

    2010-06-08

    A central challenge in systems biology today is to understand the network of interactions among biomolecules and, especially, the organizing principles underlying such networks. Recent analysis of known networks has identified small motifs that occur ubiquitously, suggesting that larger networks might be constructed in the manner of electronic circuits by assembling groups of these smaller modules. Using a unique process-based approach to analyzing such networks, we show for two cell-cycle networks that each of these networks contains a giant backbone motif spanning all the network nodes that provides the main functional response. The backbone is in fact the smallest network capable of providing the desired functionality. Furthermore, the remaining edges in the network form smaller motifs whose role is to confer stability properties rather than provide function. The process-based approach used in the above analysis has additional benefits: It is scalable, analytic (resulting in a single analyzable expression that describes the behavior), and computationally efficient (all possible minimal networks for a biological process can be identified and enumerated).

  1. Image-Based Structural Modeling of the Cardiac Purkinje Network

    Directory of Open Access Journals (Sweden)

    Benjamin R. Liu

    2015-01-01

    Full Text Available The Purkinje network is a specialized conduction system within the heart that ensures the proper activation of the ventricles to produce effective contraction. Its role during ventricular arrhythmias is less clear, but some experimental studies have suggested that the Purkinje network may significantly affect the genesis and maintenance of ventricular arrhythmias. Despite its importance, few structural models of the Purkinje network have been developed, primarily because current physical limitations prevent examination of the intact Purkinje network. In previous modeling efforts Purkinje-like structures have been developed through either automated or hand-drawn procedures, but these networks have been created according to general principles rather than based on real networks. To allow for greater realism in Purkinje structural models, we present a method for creating three-dimensional Purkinje networks based directly on imaging data. Our approach uses Purkinje network structures extracted from photographs of dissected ventricles and projects these flat networks onto realistic endocardial surfaces. Using this method, we create models for the combined ventricle-Purkinje system that can fully activate the ventricles through a stimulus delivered to the Purkinje network and can produce simulated activation sequences that match experimental observations. The combined models have the potential to help elucidate Purkinje network contributions during ventricular arrhythmias.

  2. Visualization of Complex Networks Based on Dyadic Curvelet Transform

    Directory of Open Access Journals (Sweden)

    Kaoru Hirota

    2006-07-01

    Full Text Available A visualization method is proposed for understanding the structure of complex networks based on an extended Curvelet transform named Dyadic Curvelet Transform (DClet. The proposed visualization method comes to answer specific questions about structures of complex networks by mapping data into orthogonal localized events with a directional component via the Cartesian sampling sets of detail coefficients. It behaves in the same matter as human visual system, seeing in terms of segments and distinguishing them by scale and orientation. Compressing the network is another fact. The performance of the proposed method is evaluated by two different networks with structural properties of small world networks with N = 16 vertices, and a globally coupled network with size N = 1024 and 523 776 edges. As the most large scale real networks are not fully connected, it is tested on the telecommunication network of Iran as a real extremely complex network with 92 intercity switching vertices, 706 350 E1 traffic channels and 315 525 transmission channels. It is shown that the proposed method performs as a simulation tool for successfully design of network and establishing the necessary group sizes. It can clue the network designer in on all structural properties that network has.

  3. Research of multi-path routing based on network coding in space information networks

    Directory of Open Access Journals (Sweden)

    Yu Geng

    2014-06-01

    Full Text Available A multi-path routing algorithm based on network coding is proposed for combating long propagation delay and high bit error rate of space information networks. On the basis of traditional multi-path routing, the algorithm uses a random linear network coding strategy to code data packets. Code number is determined by the next hop link status and the number of current received packets sent by the upstream node together. The algorithm improves retransmission and cache mechanisms through using redundancy caused by network coding. Meanwhile, the algorithm also adopts the flow distribution strategy based on time delay to balance network load. Simulation results show that the proposed routing algorithm can effectively improve packet delivery rate, reduce packet delay, and enhance network performance.

  4. Accuracy of a simplified equation for energy expenditure based on bedside volumetric carbon dioxide elimination measurement - A two-center study

    NARCIS (Netherlands)

    N.M. Mehta (Nilesh M.); C.D. Smallwood (Craig D.); K.F.M. Joosten (Koen); J.M. Hulst (Jessie); R.C. Tasker (Robert); C.P. Duggan (Christopher P.)

    2015-01-01

    textabstractBackground & aims: Accurate assessment of resting energy expenditure (REE) and metabolic state is essential to optimize nutrient intake in critically ill patients. We aimed to examine the accuracy of a simplified equation for predicting REE using carbon dioxide elimination (VCO2) values.

  5. Digestibilidade aparente dos nutrientes de dietas simplificadas baseadas em forragens para coelhos em crescimento Apparent digestibility of nutrients of simplified diets based on forages for growing rabbits

    Directory of Open Access Journals (Sweden)

    W.M. Ferreira

    2007-04-01

    Full Text Available Avaliaram-se os efeitos de dietas simplificadas à base de forragens sobre a digestibilidade aparente dos nutrientes em coelhos Nova Zelândia branco. As dietas experimentais foram: referência (REF, feno de alfafa (FAL, feno das folhas de rami (FRA, feno das folhas de amoreira (FAM e feno do terço superior da rama da mandioca (FMA. A digestibilidade das dietas foi influenciada pelo tipo de alimento estudado; a FMA apresentou coeficientes de digestibilidade inferiores às demais dietas para todos os princípios nutritivos analisados. Para a dieta FAM, os coeficientes de digestibilidade aparente dos princípios nutritivos foram maiores (P0,05. Os valores estimados de energia digestível (kcal ED/kg MS e proteína digestível (%PD/MS foram, respectivamente, para o feno de alfafa: 2285,27 e 16,04; feno das folhas de rami: 1857,88 e 16,37; feno das folhas de amoreira: 2838,48 e 15,12 e feno do terço superior da mandioca: 2155,55 e 10,57.The effect of simplified diets based on forages on the apparent digestibility in white New Zealand rabbits was evaluated. The treatments were based on the following diets: reference (REF, hay of alfalfa (FAL, hay of rami leaves (FRA, hay of mulberry leaves (FAM and hay of upper to 1/3 aereal part of cassava (FMA. The type of food affected the digestibility of the diets. The FMA diet showed low coefficients of digestibility in comparison to the other diets for all the analyzed nutrients. For the FAM diet the coefficients of apparent digestibility of the nutrients had higher values (P0.05. The estimated values of digestible energy (kcal DE/kg DM and digestible protein (%DP/DM were, respectively, 2285.27 and 16.04 for alfalfa hay, 1857.88 and 16.37 for hay of rami leaves, 2838.48 and 15.12 for hay of mulberry leaves and 2155.55 and 10.57 for hay of upper to 1/3 aereal part of cassava.

  6. Development of a Networked Thumb Print-Based Staff Attendance Management System

    Directory of Open Access Journals (Sweden)

    Tolulope Awode

    2016-07-01

    Full Text Available This paper focuses on the development of a networked thumb print-based attendance management system. Now, more than ever, it has become necessary to give more thought to the methods of time and attendance management. The traditional time clock, manual attendance registering often no longer makes sense and simply does not meet the needs of the modern work environment. This system offers a comprehensive software solution that will streamline company's operations, and simplify timekeeping. Nowadays, the need of a solution for Time and Attendance in the modern company is a necessity. It is important to be able to manage and control the workers by means of a system of control of times and schedules.

  7. Mining human mobility in location-based social networks

    CERN Document Server

    Gao, Huiji

    2015-01-01

    In recent years, there has been a rapid growth of location-based social networking services, such as Foursquare and Facebook Places, which have attracted an increasing number of users and greatly enriched their urban experience. Typical location-based social networking sites allow a user to ""check in"" at a real-world POI (point of interest, e.g., a hotel, restaurant, theater, etc.), leave tips toward the POI, and share the check-in with their online friends. The check-in action bridges the gap between real world and online social networks, resulting in a new type of social networks, namely l

  8. Space-Based Voice over IP Networks

    Science.gov (United States)

    Nguyen, Sam P.; Okino, Clayton; Walsh, William; Clare, Loren

    2007-01-01

    In human space exploration missions (e.g. a return to the Moon and for future missions to Mars), there will be a need to provide voice communications services. In this work we focus on the performance of Voice over IP (VoIP) techniques applied to space networks, where long range latencies, simplex links, and significant bit error rates occur. Link layer and network layer overhead issues are examined. Finally, we provide some discussion on issues related to voice conferencing in the space network environment.

  9. Carrying Network Accessing Architecture and Strategy Based on Business Differentiation

    Directory of Open Access Journals (Sweden)

    Yanyan Han

    2013-07-01

    Full Text Available Due to the abilities of real-time sensing and information sharing, Wireless Sensor Network (WSN has been applied in more and more fields. Basing on the emergence of Internet of Things (IoT, the issue about heterogeneous network integration is becoming more important. We first analyze the new businesses that arise recently for cell phone users as well as the potential effect on carrying network. After that we mainly discuss the influence on traditional carrying network for WSN accessing and taking concurrent businesses as the study case, common access architecture from WSN to carrying network is constructed, which makes use of business differentiation. Furthermore, we propose the idea of tortuous access from WSN to the gateway in the carrying network to avoid congested paths with simulation and verification. Finally, we conclude the possible impacts for the integration of these two networks and present possible solutions.

  10. Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Yunpeng Wang

    2014-01-01

    Full Text Available We present an improved ant colony algorithm-based approach to assess the vulnerability of a road network and identify the critical infrastructures. This approach improves computational efficiency and allows for its applications in large-scale road networks. This research involves defining the vulnerability conception, modeling the traffic utility index and the vulnerability of the road network, and identifying the critical infrastructures of the road network. We apply the approach to a simple test road network and a real road network to verify the methodology. The results show that vulnerability is directly related to traffic demand and increases significantly when the demand approaches capacity. The proposed approach reduces the computational burden and may be applied in large-scale road network analysis. It can be used as a decision-supporting tool for identifying critical infrastructures in transportation planning and management.

  11. Available Bandwidth Estimation Strategy Based on the Network Allocation Vector

    Directory of Open Access Journals (Sweden)

    Hongtao Liu

    2012-12-01

    Full Text Available Available bandwidth is of great importance to network Quality of Service assurance, network load balancing, streaming media rate control, routing, and congestion control, etc.. In this paper, the available bandwidth estimation strategy based on the Network Allocation Vector for Wireless Sensor Networks is proposed. According to the size of the average contention window, network nodes predict the probability of collision in process of frame transmission, and then estimate the number of retransmission. Through the collection of Hello packets periodically sent by neighbors, nodes obtain their Network Allocation Vector, and then estimate the available bandwidth. The simulation results show that the strategy is simple and effective, can accurately estimate the collision of data frames as well as the available bandwidth of Wireless Sensor Networks.

  12. Congestion Avoidance in IP Based CDMA Radio Access Network

    Directory of Open Access Journals (Sweden)

    Syed Shakeel Hashmi

    2011-02-01

    Full Text Available CDMA is an important air interface technologies for cellular wireless networks. As CDMAbasedcellular networks mature, the current point-to-point links will evolve to an IP-based Radio AccessNetwork (RAN. mechanisms must be designed to control the IP Radio Access Network congestion.This Paper implements a congestion control mechanism using Router control and channelcontrol method for IP-RAN on CDMA cellular network. The Router control mechanism uses the featuresof CDMA networks using active Queue Management technique to reduce delay and to minimize thecorrelated losses. The Random Early Detection Active Queue Management scheme (REDAQM is to berealized for the router control for data transmission over the radio network using routers as the channel.The channel control mechanism control the congestion by bifurcating the access channel into multiplelayer namely RACH, BCCH and DCH for data accessing. The proposed paper work is realized usingMatlab platform.

  13. Multiagent Based Information Dissemination in Vehicular Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    S.S. Manvi

    2009-01-01

    Full Text Available Vehicular Ad hoc Networks (VANETs are a compelling application of ad hoc networks, because of the potential to access specific context information (e.g. traffic conditions, service updates, route planning and deliver multimedia services (Voice over IP, in-car entertainment, instant messaging, etc.. This paper proposes an agent based information dissemination model for VANETs. A two-tier agent architecture is employed comprising of the following: 1 'lightweight', network-facing, mobile agents; 2 'heavyweight', application-facing, norm-aware agents. The limitations of VANETs lead us to consider a hybrid wireless network architecture that includes Wireless LAN/Cellular and ad hoc networking for analyzing the proposed model. The proposed model provides flexibility, adaptability and maintainability for traffic information dissemination in VANETs as well as supports robust and agile network management. The proposed model has been simulated in various network scenarios to evaluate the effectiveness of the approach.

  14. Linearizing Control of Induction Motor Based on Networked Control Systems

    Institute of Scientific and Technical Information of China (English)

    Jun Ren; Chun-Wen Li; De-Zong Zhao

    2009-01-01

    A new approach to speed control of induction motors is developed by introducing networked control systems (NCSs) into the induction motor driving system. The control strategy is to stabilize and track the rotor speed of the induction motor when the network time delay occurs in the transport medium of network data. First, a feedback linearization method is used to achieve input-output linearization and decoupling control of the induction motor driving system based on rotor flux model, and then the characteristic of network data is analyzed in terms of the inherent network time delay. A networked control model of an induction motor is established. The sufficient condition of asymptotic stability for the networked induction motor driving system is given, and the state feedback controller is obtained by solving the linear matrix inequalities (LMIs). Simulation results verify the efficiency of the proposed scheme.

  15. A New Network Robustness Topology Measure based on Information Theory

    CERN Document Server

    Schieber, Tiago A; Frery, Alejandro C; Rosso, Osvaldo A; Pardalos, Panos M; Ravetti, Martin G

    2014-01-01

    A crucial challenge in network theory is to study how robust a network is when facing failures or attacks. In this work, we propose a novel methodology to measure the topological resilience and robustness of a network based on Information Theory quantifiers. This measure can be used with any probability distribution able to represent the network's properties. In particular, we analyze the efficiency in capturing small perturbations in the network's topology when using the degree and distance distributions. Theoretical examples and real networks are used to study the performance of this methodology. Although both cases show to be able to detect any single topological change, the distance distribution seems to be more consistent to reflect the network structural deviations. In all cases, the novel resilience and robustness measures computed by using the distance distribution reflect better the consequences of the failures, outperforming other methods.

  16. Time Series Prediction based on Hybrid Neural Networks

    Directory of Open Access Journals (Sweden)

    S. A. Yarushev

    2016-01-01

    Full Text Available In this paper, we suggest to use hybrid approach to time series forecasting problem. In first part of paper, we create a literature review of time series forecasting methods based on hybrid neural networks and neuro-fuzzy approaches. Hybrid neural networks especially effective for specific types of applications such as forecasting or classification problem, in contrast to traditional monolithic neural networks. These classes of problems include problems with different characteristics in different modules. The main part of paper create a detailed overview of hybrid networks benefits, its architectures and performance under traditional neural networks. Hybrid neural networks models for time series forecasting are discussed in the paper. Experiments with modular neural networks are given.

  17. Optimization-based topology identification of complex networks

    Institute of Scientific and Technical Information of China (English)

    Tang Sheng-Xue; Chen Li; He Yi-Gang

    2011-01-01

    In many cases,the topological structures of a complex network are unknown or uncertain,and it is of significance to identify the exact topological structure.An optimization-based method of identifying the topological structure of a complex network is proposed in this paper.Identification of the exact network topological structure is converted into a minimal optimization problem by using the estimated network.Then,an improved quantum-behaved particle swarm optimization algorithm is used to solve the optimization problem.Compared with the previous adaptive synchronizationbased method,the proposed method is simple and effective and is particularly valid to identify the topological structure of synchronization complex networks.In some cases where the states of a complex network are only partially observable,the exact topological structure of a network can also be identified by using the proposed method.Finally,numerical simulations are provided to show the effectiveness of the proposed method.

  18. Evolving Chart Pattern Sensitive Neural Network Based Forex Trading Agents

    CERN Document Server

    Sher, Gene I

    2011-01-01

    Though machine learning has been applied to the foreign exchange market for quiet some time now, and neural networks have been shown to yield good results, in modern approaches neural network systems are optimized through the traditional methods, and their input signals are vectors containing prices and other indicator elements. The aim of this paper is twofold, the presentation and testing of the application of topology and weight evolving artificial neural network (TWEANN) systems to automated currency trading, and the use of chart images as input to a geometrical regularity aware indirectly encoded neural network systems. This paper presents the benchmark results of neural network based automated currency trading systems evolved using TWEANNs, and compares the generalization capabilities of these direct encoded neural networks which use the standard price vector inputs, and the indirect (substrate) encoded neural networks which use chart images as input. The TWEANN algorithm used to evolve these currency t...

  19. Network-level optimization method for road network maintenance programming based on network efficiency

    Institute of Scientific and Technical Information of China (English)

    张林雪; 秦进; 贺钰昕; 叶勇; 倪玲霖

    2015-01-01

    To maintain their capacity, transportation infrastructures are in need of regular maintenance and rehabilitation. The major challenge facing transportation engineers is the network-level policies to maintain the deteriorating roads at an acceptable level of serviceability. In this work, a quantitative transportation network efficiency measure is presented and then how to determine optimally network-level road maintenance policy depending on the road importance to the network performance has been demonstrated. The examples show that the different roads should be set different maintenance time points in terms of the retention capacities of the roads, because the different roads play different roles in network and have different important degrees to the network performance. This network-level road maintenance optimization method could not only save lots of infrastructure investments, but also ensure the service level of the existing transportation system.

  20. Dynamical complexity in the perception-based network formation model

    Science.gov (United States)

    Jo, Hang-Hyun; Moon, Eunyoung

    2016-12-01

    Many link formation mechanisms for the evolution of social networks have been successful to reproduce various empirical findings in social networks. However, they have largely ignored the fact that individuals make decisions on whether to create links to other individuals based on cost and benefit of linking, and the fact that individuals may use perception of the network in their decision making. In this paper, we study the evolution of social networks in terms of perception-based strategic link formation. Here each individual has her own perception of the actual network, and uses it to decide whether to create a link to another individual. An individual with the least perception accuracy can benefit from updating her perception using that of the most accurate individual via a new link. This benefit is compared to the cost of linking in decision making. Once a new link is created, it affects the accuracies of other individuals' perceptions, leading to a further evolution of the actual network. As for initial actual networks, we consider both homogeneous and heterogeneous cases. The homogeneous initial actual network is modeled by Erdős-Rényi (ER) random networks, while we take a star network for the heterogeneous case. In any cases, individual perceptions of the actual network are modeled by ER random networks with controllable linking probability. Then the stable link density of the actual network is found to show discontinuous transitions or jumps according to the cost of linking. As the number of jumps is the consequence of the dynamical complexity, we discuss the effect of initial conditions on the number of jumps to find that the dynamical complexity strongly depends on how much individuals initially overestimate or underestimate the link density of the actual network. For the heterogeneous case, the role of the highly connected individual as an information spreader is also discussed.

  1. Model-based dynamic control and optimization of gas networks

    Energy Technology Data Exchange (ETDEWEB)

    Hofsten, Kai

    2001-07-01

    This work contributes to the research on control, optimization and simulation of gas transmission systems to support the dispatch personnel at gas control centres for the decision makings in the daily operation of the natural gas transportation systems. Different control and optimization strategies have been studied. The focus is on the operation of long distance natural gas transportation systems. Stationary optimization in conjunction with linear model predictive control using state space models is proposed for supply security, the control of quality parameters and minimization of transportation costs for networks offering transportation services. The result from the stationary optimization together with a reformulation of a simplified fluid flow model formulates a linear dynamic optimization model. This model is used in a finite time control and state constrained linear model predictive controller. The deviation from the control and the state reference determined from the stationary optimization is penalized quadratically. Because of the time varying status of infrastructure, the control space is also generally time varying. When the average load is expected to change considerably, a new stationary optimization is performed, giving a new state and control reference together with a new dynamic model that is used for both optimization and state estimation. Another proposed control strategy is a control and output constrained nonlinear model predictive controller for the operation of gas transmission systems. Here, the objective is also the security of the supply, quality control and minimization of transportation costs. An output vector is defined, which together with a control vector are both penalized quadratically from their respective references in the objective function. The nonlinear model predictive controller can be combined with a stationary optimization. At each sampling instant, a non convex nonlinear programming problem is solved giving a local minimum

  2. Distribution Network Design--literature study based

    OpenAIRE

    Li, Ang

    2012-01-01

    The focus of this research is companies' outbound distribution network design in supply chain management. Within the present competitive market, it is a fundamental importance for companies to achieve high level business performance with an effective supply chain. Outbound distribution network design as an important part in supply chain management, to a large extent decides whether companies can fulfill customers' requirement or not. Therefore, such a study is important for manufacturers and ...

  3. Social Recommender Systems Based on Coupling Network Structure Analysis

    CERN Document Server

    Hu, Xiao; Chen, Xiaolong; Zhang, Zi-Ke

    2012-01-01

    The past few years has witnessed the great success of recommender systems, which can significantly help users find relevant and interesting items for them in the information era. However, a vast class of researches in this area mainly focus on predicting missing links in bipartite user-item networks (represented as behavioral networks). Comparatively, the social impact, especially the network structure based properties, is relatively lack of study. In this paper, we firstly obtain five corresponding network-based features, including user activity, average neighbors' degree, clustering coefficient, assortative coefficient and discrimination, from social and behavioral networks, respectively. A hybrid algorithm is proposed to integrate those features from two respective networks. Subsequently, we employ a machine learning process to use those features to provide recommendation results in a binary classifier method. Experimental results on a real dataset, Flixster, suggest that the proposed method can significan...

  4. A Network- Based VPN Architecture Using Virtual Routing

    Institute of Scientific and Technical Information of China (English)

    ZHANG Bao-liang; HU Han-ping; WU Xiao-gang; KONG Tao

    2005-01-01

    A network-based Virtual Private Network (VPN) architecture by using fundamental routing mechanism is proposed. This network is a virtual overlay network based on the relay of IP-in-IP tunneling of virtual routing modules.The packet format employs the encapsulation of IPSec ESP (Encapsulating Security Payload), an impact path code and an extended DS (Differentiated Services) code to support multi-path routing and QoS. Comparing with other models of VPN, this network system can be deployed in the current network with little investment, and it is easy to implement.The simulation result shows its performance is better than the traditional VPN system of black box mode.

  5. A network monitor for HTTPS protocol based on proxy

    Science.gov (United States)

    Liu, Yangxin; Zhang, Lingcui; Zhou, Shuguang; Li, Fenghua

    2016-10-01

    With the explosive growth of harmful Internet information such as pornography, violence, and hate messages, network monitoring is essential. Traditional network monitors is based mainly on bypass monitoring. However, we can't filter network traffic using bypass monitoring. Meanwhile, only few studies focus on the network monitoring for HTTPS protocol. That is because HTTPS data is in the encrypted traffic, which makes it difficult to monitor. This paper proposes a network monitor for HTTPS protocol based on proxy. We adopt OpenSSL to establish TLS secure tunes between clients and servers. Epoll is used to handle a large number of concurrent client connections. We also adopt Knuth- Morris-Pratt string searching algorithm (or KMP algorithm) to speed up the search process. Besides, we modify request packets to reduce the risk of errors and modify response packets to improve security. Experiments show that our proxy can monitor the content of all tested HTTPS websites efficiently with little loss of network performance.

  6. Grid Computing based on Game Optimization Theory for Networks Scheduling

    Directory of Open Access Journals (Sweden)

    Peng-fei Zhang

    2014-05-01

    Full Text Available The resource sharing mechanism is introduced into grid computing algorithm so as to solve complex computational tasks in heterogeneous network-computing problem. However, in the Grid environment, it is required for the available resource from network to reasonably schedule and coordinate, which can get a good workflow and an appropriate network performance and network response time. In order to improve the performance of resource allocation and task scheduling in grid computing method, a game model based on non-cooperation game is proposed. Setting the time and cost of user’s resource allocation can increase the performance of networks, and incentive resource of networks uses an optimization scheduling algorithm, which minimizes the time and cost of resource scheduling. Simulation experiment results show the feasibility and suitability of model. In addition, we can see from the experiment result that model-based genetic algorithm is the best resource scheduling algorithm

  7. Multiobjective H2/H∞ synthetic gene network design based on promoter libraries.

    Science.gov (United States)

    Wu, Chih-Hung; Zhang, Weihei; Chen, Bor-Sen

    2011-10-01

    employed to simplify the HJI-constrained optimization problem to an equivalent linear matrix inequality (LMI)-constrained optimization problem, which can be easily solved by selecting an adequate promoter set from the redefined promoter libraries using the LMI toolbox in Matlab. Based on the confirmation of in silico design examples, we can select an adequate promoter set from the redefined promoter libraries to achieve the multiobjective H(2)/H(∞) reference tracking design. The proposed method can reduce the number of trial-and-error experiments in selecting an adequate promoter set for a synthetic gene network with desired behaviors. With the rapid increase of promoter libraries, this systematic method will accelerate progress of synthetic biology design.

  8. An efficient algorithm for solving supply chain network equilibria and equivalent supernetwork based traffic network equilibria

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    This paper is concerned with the algorithm of the supply chain network equilibrium model and its equivalent supernetwork based traffic network equilibrium model with elastic demands. Both models are further written as nonlinear complementarity problems. Semismooth least squares reformulations of the complementarity problems are presented and their convergence properties are investigated. Considering the drawbacks of Quasi-Newton method (using the Fischer-Burmeister function), a semi-smooth Levenberg-Marquardt-type method is proposed to solve the problems. Numerical examples show that the Levenberg-Marquardt-type method can solve the supply chain network equilibrium model and its equivalent supernetwork based traffic network equilibrium model significantly, and is more efficient than the Quasi Newton method and the modified projection method. Furthermore, the Levenberg-Marquardt-type method with the equivalent supernetwork based complementarity formulation can be implemented faster than with the supply chain network equilibrium complementarity formulation.

  9. Digital security technology simplified.

    Science.gov (United States)

    Scaglione, Bernard J

    2007-01-01

    Digital security technology is making great strides in replacing analog and other traditional security systems including CCTV card access, personal identification and alarm monitoring applications. Like any new technology, the author says, it is important to understand its benefits and limitations before purchasing and installing, to ensure its proper operation and effectiveness. This article is a primer for security directors on how digital technology works. It provides an understanding of the key components which make up the foundation for digital security systems, focusing on three key aspects of the digital security world: the security network, IP cameras and IP recorders.

  10. A simple network agreement-based approach for combining evidences in a heterogeneous sensor network

    Directory of Open Access Journals (Sweden)

    Raúl Eusebio-Grande

    2015-12-01

    Full Text Available In this research we investigate how the evidences provided by both static and mobile nodes that are part of a heterogenous sensor network can be combined to have trustworthy results. A solution relying on a network agreement-based approach was implemented and tested.

  11. Fuzzy neural network image filter based on GA

    Institute of Scientific and Technical Information of China (English)

    刘涵; 刘丁; 李琦

    2004-01-01

    A new nonlinear image filter using fuzzy neural network based on genetic algorithm is proposed. The learning of network parameters is performed by genetic algorithm with the efficient binary encoding scheme. In the following,fuzzy reasoning embedded in the network aims at restoring noisy pixels without degrading the quality of fine details. It is shown by experiments that the filter is very effective in removing impulse noise and significantly outperforms conventional filters.

  12. LTE/MVNO NETWORKS STRUCTURE OPTIMIZATION BASED ON TENSOR DECOMPOSITION

    OpenAIRE

    Strelkovskaya, Iryna; Solovskaya, Iryna

    2015-01-01

    The usage of tensor methods on the decomposition basis is offered for the tasks solution of structure optimization for LTE/MVNO networks mobile communication. The choice problem of optimum topology of e-Node B base stations connectionsin the radio access of E-UTRAN/LTE network was solved. The assessment problem of QoS quality characteristics of complex LTE/MVNO network architecture was solved.

  13. A Neural Network-Based Interval Pattern Matcher

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2015-07-01

    Full Text Available One of the most important roles in the machine learning area is to classify, and neural networks are very important classifiers. However, traditional neural networks cannot identify intervals, let alone classify them. To improve their identification ability, we propose a neural network-based interval matcher in our paper. After summarizing the theoretical construction of the model, we take a simple and a practical weather forecasting experiment, which show that the recognizer accuracy reaches 100% and that is promising.

  14. A Neural Network-Based Interval Pattern Matcher

    OpenAIRE

    Jing Lu; Shengjun Xue; Xiakun Zhang; Yang Han

    2015-01-01

    One of the most important roles in the machine learning area is to classify, and neural networks are very important classifiers. However, traditional neural networks cannot identify intervals, let alone classify them. To improve their identification ability, we propose a neural network-based interval matcher in our paper. After summarizing the theoretical construction of the model, we take a simple and a practical weather forecasting experiment, which show that the recognizer accuracy reaches...

  15. MOVING TARGETS PATTERN RECOGNITION BASED ON THE WAVELET NEURAL NETWORK

    Institute of Scientific and Technical Information of China (English)

    Ge Guangying; Chen Lili; Xu Jianjian

    2005-01-01

    Based on pattern recognition theory and neural network technology, moving objects automatic detection and classification method integrating advanced wavelet analysis are discussed in detail. An algorithm of moving targets pattern recognition on the combination of inter-frame difference and wavelet neural network is presented. The experimental results indicate that the designed BP wavelet network using this algorithm can recognize and classify moving targets rapidly and effectively.

  16. Decoupling Control Method Based on Neural Network for Missiles

    Institute of Scientific and Technical Information of China (English)

    ZHAN Li; LUO Xi-shuang; ZHANG Tian-qiao

    2005-01-01

    In order to make the static state feedback nonlinear decoupling control law for a kind of missile to be easy for implementation in practice, an improvement is discussed. The improvement method is to introduce a BP neural network to approximate the decoupling control laws which are designed for different aerodynamic characteristic points, so a new decoupling control law based on BP neural network is produced after the network training. The simulation results on an example illustrate the approach obtained feasible and effective.

  17. A Hybrid Model for Short-Term Wind Power Forecasting Based on MIV, Tversky Model and GA-BP Neural Network

    Directory of Open Access Journals (Sweden)

    Zeng Jie

    2016-01-01

    Full Text Available Wind power forecasting, which is necessary for wind farm, is significant to the dispatch of power grid since the characteristics of wind change intermittently. In this paper, a hybrid model for short-term wind power forecasting based on MIV, Tversky model and GA-BP neural network is formulated. The Mean Impact Value (MIV method is used to monitor the input variable of BP neural network which will simplify the neural network model and reduce the training time. And the Tversky model is used for cluster analysis, which keeps watch over the similar training set of BP neural network. In addition, the Genetic Algorithm (GA is used to optimize the initial weights and thresholds of BP neural network to achieve the global optimization. Simulation results show that the method combined with MIV, Tversky and GA-BP can improve the accuracy of short-term wind power forecasting.

  18. Security Evaluation of Power Network Information System Based on Analytic Network Process

    Directory of Open Access Journals (Sweden)

    Jianchang Lu

    2013-04-01

    Full Text Available After the building of the power network, many enterprises are faced with a potential information security issue, the unstable factors threaten to the normal operation of the network information system, which is caused by the computer network defects. Aiming at this point, potential security dangers of power network information system were analyzed. Then an index system based on the security evaluation of power network information systems was established. Applying the analytic network process to get the weights of each index, the evaluation process can be accessed by fuzzy comprehensive evaluation method. The weights of each index are decided by ANP, which can remedy the defects of analytic hierarchy process that the interaction among indexes cannot be reflected. Example analysis is performed by the Super Decisions software to verify feasibility and effectiveness of the proposed evaluation model mentioned in the paper.

  19. SNMS: an intelligent transportation system network architecture based on WSN and P2P network

    Institute of Scientific and Technical Information of China (English)

    LI Li; LIU Yuan-an; TANG Bi-hua

    2007-01-01

    With the development of city road networks, the question of how to obtain information about the roads is becoming more and more important. In this article, sensor network with mobile station (SNMS), a novel two-tiered intelligent transportation system (ITS) network architecture based on wireless sensor network (WSN) and peer-to-peer (P2P) network, is proposed to provide significant traffic information about the road and thereby, assist travelers to take optimum decisions when they are driving. A detailed explanation with regard to the strategy of each level as well as the design of two main components in the network, sensor unit (SU) and mobile station (MS), is presented. Finally, a representative scenario is described to display the operation of the system.

  20. User Equilibrium Exchange Allocation Algorithm Based on Super Network

    Directory of Open Access Journals (Sweden)

    Peiyi Dong

    2013-12-01

    Full Text Available The theory of super network is an effective method to various traffic networks with means of multiple decision-making. It provides us with a favorable pricing decision tool for it combines a practical transport network with the space pricing decision. Spatial price equilibrium problem has always been the important research direction of the Transport Economics and regional transportation planning. As to how to combine the two, this paper presents the user equilibrium exchange allocation algorithm based on super network, which successfully keep the classical spatial price equilibrium problems (SPE into a super-network analysis framework. Through super-network analysis, we can add two virtual nodes in the network, which correspond to the virtual supply node and the super-super-demand virtual node, analysis the user equivalence with the SPE equilibrium and find the concrete steps of users exchange allocation algorithm based on super-network equilibrium. Finally, we carried out experiments to verify. The experiments show that: through the user equilibrium exchange SPE allocation algorithm based on super-network, we can get the steady-state equilibrium solution, which demonstrate that the algorithm is reasonable.

  1. Ultra-fast computation of electronic spectra for large systems by tight-binding based simplified Tamm-Dancoff approximation (sTDA-xTB)

    Science.gov (United States)

    Grimme, Stefan; Bannwarth, Christoph

    2016-08-01

    The computational bottleneck of the extremely fast simplified Tamm-Dancoff approximated (sTDA) time-dependent density functional theory procedure [S. Grimme, J. Chem. Phys. 138, 244104 (2013)] for the computation of electronic spectra for large systems is the determination of the ground state Kohn-Sham orbitals and eigenvalues. This limits such treatments to single structures with a few hundred atoms and hence, e.g., sampling along molecular dynamics trajectories for flexible systems or the calculation of chromophore aggregates is often not possible. The aim of this work is to solve this problem by a specifically designed semi-empirical tight binding (TB) procedure similar to the well established self-consistent-charge density functional TB scheme. The new special purpose method provides orbitals and orbital energies of hybrid density functional character for a subsequent and basically unmodified sTDA procedure. Compared to many previous semi-empirical excited state methods, an advantage of the ansatz is that a general eigenvalue problem in a non-orthogonal, extended atomic orbital basis is solved and therefore correct occupied/virtual orbital energy splittings as well as Rydberg levels are obtained. A key idea for the success of the new model is that the determination of atomic charges (describing an effective electron-electron interaction) and the one-particle spectrum is decoupled and treated by two differently parametrized Hamiltonians/basis sets. The three-diagonalization-step composite procedure can routinely compute broad range electronic spectra (0-8 eV) within minutes of computation time for systems composed of 500-1000 atoms with an accuracy typical of standard time-dependent density functional theory (0.3-0.5 eV average error). An easily extendable parametrization based on coupled-cluster and density functional computed reference data for the elements H-Zn including transition metals is described. The accuracy of the method termed sTDA-xTB is first

  2. Simplified Predictive Models for CO2 Sequestration Performance Assessment: Research Topical Report on Task #4 - Reduced-Order Method (ROM) Based Models

    Energy Technology Data Exchange (ETDEWEB)

    Mishra, Srikanta; Jin, Larry; He, Jincong; Durlofsky, Louis

    2015-06-30

    Reduced-order models provide a means for greatly accelerating the detailed simulations that will be required to manage CO2 storage operations. In this work, we investigate the use of one such method, POD-TPWL, which has previously been shown to be effective in oil reservoir simulation problems. This method combines trajectory piecewise linearization (TPWL), in which the solution to a new (test) problem is represented through a linearization around the solution to a previously-simulated (training) problem, with proper orthogonal decomposition (POD), which enables solution states to be expressed in terms of a relatively small number of parameters. We describe the application of POD-TPWL for CO2-water systems simulated using a compositional procedure. Stanford’s Automatic Differentiation-based General Purpose Research Simulator (AD-GPRS) performs the full-order training simulations and provides the output (derivative matrices and system states) required by the POD-TPWL method. A new POD-TPWL capability introduced in this work is the use of horizontal injection wells that operate under rate (rather than bottom-hole pressure) control. Simulation results are presented for CO2 injection into a synthetic aquifer and into a simplified model of the Mount Simon formation. Test cases involve the use of time-varying well controls that differ from those used in training runs. Results of reasonable accuracy are consistently achieved for relevant well quantities. Runtime speedups of around a factor of 370 relative to full- order AD-GPRS simulations are achieved, though the preprocessing needed for POD-TPWL model construction corresponds to the computational requirements for about 2.3 full-order simulation runs. A preliminary treatment for POD-TPWL modeling in which test cases differ from training runs in terms of geological parameters (rather than well controls) is also presented. Results in this case involve only small differences between

  3. Representations in neural network based empirical potentials

    Science.gov (United States)

    Cubuk, Ekin D.; Malone, Brad D.; Onat, Berk; Waterland, Amos; Kaxiras, Efthimios

    2017-07-01

    Many structural and mechanical properties of crystals, glasses, and biological macromolecules can be modeled from the local interactions between atoms. These interactions ultimately derive from the quantum nature of electrons, which can be prohibitively expensive to simulate. Machine learning has the potential to revolutionize materials modeling due to its ability to efficiently approximate complex functions. For example, neural networks can be trained to reproduce results of density functional theory calculations at a much lower cost. However, how neural networks reach their predictions is not well understood, which has led to them being used as a "black box" tool. This lack of understanding is not desirable especially for applications of neural networks in scientific inquiry. We argue that machine learning models trained on physical systems can be used as more than just approximations since they had to "learn" physical concepts in order to reproduce the labels they were trained on. We use dimensionality reduction techniques to study in detail the representation of silicon atoms at different stages in a neural network, which provides insight into how a neural network learns to model atomic interactions.

  4. Self-organized topology of recurrence-based complex networks.

    Science.gov (United States)

    Yang, Hui; Liu, Gang

    2013-12-01

    With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., "what is the self-organizing geometry of a recurrence network?" and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks.

  5. Self-organized topology of recurrence-based complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Hui, E-mail: huiyang@usf.edu; Liu, Gang [Complex Systems Monitoring, Modeling and Analysis Laboratory, University of South Florida, Tampa, Florida 33620 (United States)

    2013-12-15

    With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., “what is the self-organizing geometry of a recurrence network?” and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks.

  6. Gradient-based Taxis Algorithms for Network Robotics

    OpenAIRE

    Blum, Christian; Hafner, Verena V.

    2014-01-01

    Finding the physical location of a specific network node is a prototypical task for navigation inside a wireless network. In this paper, we consider in depth the implications of wireless communication as a measurement input of gradient-based taxis algorithms. We discuss how gradients can be measured and determine the errors of this estimation. We then introduce a gradient-based taxis algorithm as an example of a family of gradient-based, convergent algorithms and discuss its convergence in th...

  7. Practical Network-Based Techniques for Mobile Positioning in UMTS

    Directory of Open Access Journals (Sweden)

    Borkowski Jakub

    2006-01-01

    Full Text Available This paper presents results of research on network-based positioning for UMTS (universal mobile telecommunication system. Two new applicable network-based cellular location methods are proposed and assessed by field measurements and simulations. The obtained results indicate that estimation of the position at a sufficient accuracy for most of the location-based services does not have to involve significant changes in the terminals and in the network infrastructure. In particular, regular UMTS terminals can be used in the presented PCM (pilot correlation method, while the other proposed method - the ECID+RTT (cell identification + round trip time requires only minor software updates in the network and user equipment. The performed field measurements of the PCM reveal that in an urban network, of users can be located with an accuracy of m. In turn, simulations of the ECID+RTT report accuracy of m– m for of the location estimates in an urban scenario.

  8. Effective information spreading based on local information in correlated networks

    CERN Document Server

    Gao, Lei; Pan, Liming; Tang, Ming; Zhang, Hai-Feng

    2016-01-01

    Using network-based information to facilitate information spreading is an essential task for spreading dynamics in complex networks, which will benefit the promotion of technical innovations, healthy behaviors, new products, etc. Focusing on degree correlated networks, we propose a preferential contact strategy based on the local network structure and local informed density to promote the information spreading. During the spreading process, an informed node will preferentially select a contact target among its neighbors, basing on their degrees or local informed densities. By extensively implementing numerical simulations in synthetic and empirical networks, we find that when only consider the local structure information, the convergence time of information spreading will be remarkably reduced if low-degree neighbors are favored as contact targets. Meanwhile, the minimum convergence time depends non-monotonically on degree-degree correlation, and moderate correlation coefficients result in most efficient info...

  9. Network-Based Practical Consensus of Heterogeneous Nonlinear Multiagent Systems.

    Science.gov (United States)

    Ding, Lei; Zheng, Wei Xing

    2016-09-07

    This paper studies network-based practical leader-following consensus problem of heterogeneous multiagent systems with Lipschitz nonlinear dynamics under both fixed and switching topologies. Considering the effect of network-induced delay, a network-based leader-following consensus protocol with heterogeneous gain matrix is proposed for each follower agent. By employing Lyapunov-Krasovskii method, a sufficient condition for designing the network-based consensus controller gain is derived such that the leader-following consensus error exponentially converges to a bounded region under a fixed topology. Correspondingly, the proposed design approach is then extended to the case of switching topology. Two numerical examples with networked Chua's circuits are given to show the efficiency of the design method proposed in this paper.

  10. Effective information spreading based on local information in correlated networks

    Science.gov (United States)

    Gao, Lei; Wang, Wei; Pan, Liming; Tang, Ming; Zhang, Hai-Feng

    2016-12-01

    Using network-based information to facilitate information spreading is an essential task for spreading dynamics in complex networks. Focusing on degree correlated networks, we propose a preferential contact strategy based on the local network structure and local informed density to promote the information spreading. During the spreading process, an informed node will preferentially select a contact target among its neighbors, basing on their degrees or local informed densities. By extensively implementing numerical simulations in synthetic and empirical networks, we find that when only consider the local structure information, the convergence time of information spreading will be remarkably reduced if low-degree neighbors are favored as contact targets. Meanwhile, the minimum convergence time depends non-monotonically on degree-degree correlation, and a moderate correlation coefficient results in the most efficient information spreading. Incorporating the local informed density information into contact strategy, the convergence time of information spreading can be further reduced, and be minimized by an moderately preferential selection.

  11. A Novel Active Network Architecture Based on Extensible Services Router

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    Active networks are a new kind of packet-switched networks in which packets have code fragments that are executed on the intermediary nodes (routers). The code can extend or modify the foundation architecture of a network. In this paper, the authors present a novel active network architecture combined with advantages of two major active networks technology based on extensible services router. The architecture consists of extensible service router, active extensible components server and key distribution center (KDC). Users can write extensible service components with programming interface. At the present time, we have finished the extensible services router prototype system based on Highly Efficient Router Operating System (HEROS), active extensible components server and KDC prototype system based on Linux.

  12. Image Restoration Technology Based on Discrete Neural network

    Directory of Open Access Journals (Sweden)

    Zhou Duoying

    2015-01-01

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

  13. Heterogeneous network architectures

    DEFF Research Database (Denmark)

    Christiansen, Henrik Lehrmann

    2006-01-01

    Future networks will be heterogeneous! Due to the sheer size of networks (e.g., the Internet) upgrades cannot be instantaneous and thus heterogeneity appears. This means that instead of trying to find the olution, networks hould be designed as being heterogeneous. One of the key equirements here...... is flexibility. This thesis investigates such heterogeneous network architectures and how to make them flexible. A survey of algorithms for network design is presented, and it is described how using heuristics can increase the speed. A hierarchical, MPLS based network architecture is described...... and it is discussed that it is advantageous to heterogeneous networks and illustrated by a number of examples. Modeling and simulation is a well-known way of doing performance evaluation. An approach to event-driven simulation of communication networks is presented and mixed complexity modeling, which can simplify...

  14. Identifying key nodes in multilayer networks based on tensor decomposition

    Science.gov (United States)

    Wang, Dingjie; Wang, Haitao; Zou, Xiufen

    2017-06-01

    The identification of essential agents in multilayer networks characterized by different types of interactions is a crucial and challenging topic, one that is essential for understanding the topological structure and dynamic processes of multilayer networks. In this paper, we use the fourth-order tensor to represent multilayer networks and propose a novel method to identify essential nodes based on CANDECOMP/PARAFAC (CP) tensor decomposition, referred to as the EDCPTD centrality. This method is based on the perspective of multilayer networked structures, which integrate the information of edges among nodes and links between different layers to quantify the importance of nodes in multilayer networks. Three real-world multilayer biological networks are used to evaluate the performance of the EDCPTD centrality. The bar chart and ROC curves of these multilayer networks indicate that the proposed approach is a good alternative index to identify real important nodes. Meanwhile, by comparing the behavior of both the proposed method and the aggregated single-layer methods, we demonstrate that neglecting the multiple relationships between nodes may lead to incorrect identification of the most versatile nodes. Furthermore, the Gene Ontology functional annotation demonstrates that the identified top nodes based on the proposed approach play a significant role in many vital biological processes. Finally, we have implemented many centrality methods of multilayer networks (including our method and the published methods) and created a visual software based on the MATLAB GUI, called ENMNFinder, which can be used by other researchers.

  15. INDUCTION OF DECISION TREES BASED ON A FUZZY NEURAL NETWORK

    Institute of Scientific and Technical Information of China (English)

    Tang Bin; Hu Guangrui; Mao Xiaoquan

    2002-01-01

    Based on a fuzzy neural network, the letter presents an approach for the induction of decision trees. The approach makes use of the weights of fuzzy mappings in the fuzzy neural network which has been trained. It can realize the optimization of fuzzy decision trees by branch cutting, and improve the ratio of correctness and efficiency of the induction of decision trees.

  16. Deflection routing scheme for GMPLS-based OBS networks

    DEFF Research Database (Denmark)

    Eid, Arafat; Mahmood, Waqar; Alomar, Anwar

    2010-01-01

    is not applicable in such an integrated solution. This is due to the existence of already established Label Switched Paths (LSPs) between edge nodes in a GMPLS-based OBS network which guide the Data Burst Headers (DBHs) through the network. In this paper we propose a novel deflection routing scheme which can...

  17. Soft silicone based interpenetrating networks as materials for actuators

    DEFF Research Database (Denmark)

    Yu, Liyun; Gonzalez, Lidia; Hvilsted, Søren

    2014-01-01

    A new approach based on silicone interpenetrating networks with orthogonal chemistries has been investigated with focus on developing soft and flexible elastomers with high energy densities and small viscous losses. The interpenetrating networks are made as simple two pot mixtures as for the comm...

  18. Connected Dominating Set Based Topology Control in Wireless Sensor Networks

    Science.gov (United States)

    He, Jing

    2012-01-01

    Wireless Sensor Networks (WSNs) are now widely used for monitoring and controlling of systems where human intervention is not desirable or possible. Connected Dominating Sets (CDSs) based topology control in WSNs is one kind of hierarchical method to ensure sufficient coverage while reducing redundant connections in a relatively crowded network.…

  19. Rate adaptation in ad hoc networks based on pricing

    CSIR Research Space (South Africa)

    Awuor, F

    2011-09-01

    Full Text Available to transmit at high power leading to abnormal interference in the network hence degrades network performance (i.e. low data rates, loss of connectivity among others). In this paper, the authors propose rate adaptation based on pricing (RAP) algorithm...

  20. Ring-based All-Optical Datacenter Networks

    DEFF Research Database (Denmark)

    Fagertun, Anna Manolova; Berger, Michael Stübert; Ruepp, Sarah Renée

    2015-01-01

    Ring-based generic network architecture for all-optical datacenters is proposed, offering highly scalable interconnection network with reduced cabling complexity. Simulations show improved performance compared to all-optical fat-tree datacenter architecture with 40%-99% improved connection request...

  1. Connected Dominating Set Based Topology Control in Wireless Sensor Networks

    Science.gov (United States)

    He, Jing

    2012-01-01

    Wireless Sensor Networks (WSNs) are now widely used for monitoring and controlling of systems where human intervention is not desirable or possible. Connected Dominating Sets (CDSs) based topology control in WSNs is one kind of hierarchical method to ensure sufficient coverage while reducing redundant connections in a relatively crowded network.…

  2. Anomaly-based Network Intrusion Detection Methods

    Directory of Open Access Journals (Sweden)

    Pavel Nevlud

    2013-01-01

    Full Text Available The article deals with detection of network anomalies. Network anomalies include everything that is quite different from the normal operation. For detection of anomalies were used machine learning systems. Machine learning can be considered as a support or a limited type of artificial intelligence. A machine learning system usually starts with some knowledge and a corresponding knowledge organization so that it can interpret, analyse, and test the knowledge acquired. There are several machine learning techniques available. We tested Decision tree learning and Bayesian networks. The open source data-mining framework WEKA was the tool we used for testing the classify, cluster, association algorithms and for visualization of our results. The WEKA is a collection of machine learning algorithms for data mining tasks.

  3. Pictographic steganography based on social networking websites

    Directory of Open Access Journals (Sweden)

    Feno Heriniaina RABEVOHITRA

    2016-01-01

    Full Text Available Steganography is the art of communication that does not let a third party know that the communication channel exists. It has always been influenced by the way people communicate and with the explosion of social networking websites, it is likely that these will be used as channels to cover the very existence of communication between different entities. In this paper, we present a new effective pictographic steganographic channel. We make use of the huge amount of photos available online as communication channels. We are exploiting the ubiquitousness of those social networking platforms to propel a powerful and pragmatic protocol. Our novel scheme exploiting social networking websites is robust against active and malicious.

  4. Gossip Based Routing Protocol Design for Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Toqeer Mahmood

    2012-01-01

    Full Text Available A spontaneously mannered decentralized network with no formal infrastructure and limited in temporal and spatial extent where each node communicate with each other over a wireless channel and is willing to forward data for other nodes is called as Wireless Ad Hoc network. In this research study, we proposed a routing strategy based on gossip based routing approach that follows the proactive routing with some treatment for wireless Ad Hoc network. The analytical verification of our proposed idea shows that it is a better approach based on gossip routing.

  5. Digital Watermarking Algorithm Based on Wavelet Transform and Neural Network

    Institute of Scientific and Technical Information of China (English)

    WANG Zhenfei; ZHAI Guangqun; WANG Nengchao

    2006-01-01

    An effective blind digital watermarking algorithm based on neural networks in the wavelet domain is presented. Firstly, the host image is decomposed through wavelet transform. The significant coefficients of wavelet are selected according to the human visual system (HVS) characteristics. Watermark bits are added to them. And then effectively cooperates neural networks to learn the characteristics of the embedded watermark related to them. Because of the learning and adaptive capabilities of neural networks, the trained neural networks almost exactly recover the watermark from the watermarked image. Experimental results and comparisons with other techniques prove the effectiveness of the new algorithm.

  6. Two port network analysis for three impedance based oscillators

    KAUST Repository

    Said, Lobna A.

    2011-12-01

    Two-port network representations are applied to analyze complex networks which can be dissolved into sub-networks connected in series, parallel or cascade. In this paper, the concept of two-port network has been studied for oscillators. Three impedance oscillator based on two port concept has been analyzed using different impedance structures. The effect of each structure on the oscillation condition and the frequency of oscillation have been introduced. Two different implementations using MOS and BJT have been introduced. © 2011 IEEE.

  7. Generating weighted community networks based on local events

    Institute of Scientific and Technical Information of China (English)

    Xu Qi-Xin; Xu Xin-Jian

    2009-01-01

    realistic networks have community structures, namely, a network consists of groups of nodes within which links are dense but among which links are sparse. This paper proposes a growing network model based on local processes, the addition of new nodes intra-community and new links intra- or inter-community. Also, it utilizes the preferential attachment for building connections determined by nodes' strengths, which evolves dynamically during the growth of the system. The resulting network reflects the intrinsic community structure with generalized power-law distributions of nodes' degrees and strengths.

  8. Network-based approach to online cursive script recognition.

    Science.gov (United States)

    Sin, B K; Ha, J Y; Oh, S C; Kim, J H

    1999-01-01

    The idea of combining the network of HMMs and the dynamic programming-based search is highly relevant to online handwriting recognition. The word model of HMM network can be systematically constructed by concatenating letter and ligature HMM's while sharing common ones. Character recognition in such a network can be defined as the task of best aligning a given input sequence to the best path in the network. One distinguishing feature of the approach is that letter segmentation is obtained simultaneously with recognition but no extra computation is required.

  9. Contractor Prequalification Based on Neural Networks

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jin-long; YANG Lan-rong

    2002-01-01

    Contractor Prequalification involves the screening of contractors by a project owner, according to a given set of criteria, in order to determine their competence to perform the work if awarded the construction contract. This paper introduces the capabilities of neural networks in solving problems related to contractor prequalification. The neural network systems for contractor prequalification has an input vector of 8 components and an output vector of 1 component. The output vector represents whether a contractor is qualified or not qualified to submit a bid on a project.

  10. Declarative Networking

    CERN Document Server

    Loo, Boon Thau

    2012-01-01

    Declarative Networking is a programming methodology that enables developers to concisely specify network protocols and services, which are directly compiled to a dataflow framework that executes the specifications. Declarative networking proposes the use of a declarative query language for specifying and implementing network protocols, and employs a dataflow framework at runtime for communication and maintenance of network state. The primary goal of declarative networking is to greatly simplify the process of specifying, implementing, deploying and evolving a network design. In addition, decla

  11. Synchronization criteria based on a general complex dynamical network model

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jian-lin; WANG Chang-jian; XU Cong-fu

    2008-01-01

    Many complex dynamical networks display synchronization phenomena. We introduce a general complex dynamical network model. The model is equivalent to a simple vector model of adopting the Kronecker product. Some synchronization criteria, including time-variant networks and time-varying networks, are deduced based on Lyapunov's stability theory, and they are proven on the condition of obtaining a certain synchronous solution of an isolated cell. In particular, the inner-coupling matrix directly determines the synchronization of the time-invariant network; while for a time-varying periodic dynamical network, the asymptotic stability of a synchronous solution is determined by a constant matrix which is related to the fundamental solution matrices of the linearization system. Finally, illustrative examples are given to validate the results.

  12. Electronic Commerce Logistics Network Optimization Based on Swarm Intelligent Algorithm

    Directory of Open Access Journals (Sweden)

    Yabing Jiao

    2013-09-01

    Full Text Available This article establish an efficient electronic commerce logistics operation system to reduce distribution costs and build a logistics network operation model based on around the B2C electronic commerce enterprise logistics network operation system. B2C electronic commerce transactions features in the enterprise network platform. To solve the NP-hard problem this article use hybrid ant colony algorithm, particle swarm algorithm and group swarm intelligence algorithm to get a best solution. According to the intelligent algorithm, design of electronic commerce logistics network optimization system, enter the national 22 electronic commerce logistics network for validation. Through the experiment to verify the optimized logistics cost greatly decreased. This research can help B2C electronic commerce enterprise logistics network to optimize decision-making under the premise of ensuring the interests of consumers and service levels also can be an effective way for enterprises to improve the efficiency of logistics services and reduce operation costs

  13. A layer reduction based community detection algorithm on multiplex networks

    Science.gov (United States)

    Wang, Xiaodong; Liu, Jing

    2017-04-01

    Detecting hidden communities is important for the analysis of complex networks. However, many algorithms have been designed for single layer networks (SLNs) while just a few approaches have been designed for multiplex networks (MNs). In this paper, we propose an algorithm based on layer reduction for detecting communities on MNs, which is termed as LRCD-MNs. First, we improve a layer reduction algorithm termed as neighaggre to combine similar layers and keep others separated. Then, we use neighaggre to find the community structure hidden in MNs. Experiments on real-life networks show that neighaggre can obtain higher relative entropy than the other algorithm. Moreover, we apply LRCD-MNs on some real-life and synthetic multiplex networks and the results demonstrate that, although LRCD-MNs does not have the advantage in terms of modularity, it can obtain higher values of surprise, which is used to evaluate the quality of partitions of a network.

  14. Impulsive Neural Networks Algorithm Based on the Artificial Genome Model

    Directory of Open Access Journals (Sweden)

    Yuan Gao

    2014-05-01

    Full Text Available To describe gene regulatory networks, this article takes the framework of the artificial genome model and proposes impulsive neural networks algorithm based on the artificial genome model. Firstly, the gene expression and the cell division tree are applied to generate spiking neurons with specific attributes, neural network structure, connection weights and specific learning rules of each neuron. Next, the gene segment duplications and divergence model are applied to design the evolutionary algorithm of impulsive neural networks at the level of the artificial genome. The dynamic changes of developmental gene regulatory networks are controlled during the whole evolutionary process. Finally, the behavior of collecting food for autonomous intelligent agent is simulated, which is driven by nerves. Experimental results demonstrate that the algorithm in this article has the evolutionary ability on large-scale impulsive neural networks

  15. Distributed query processing in flash-based sensor networks

    Institute of Scientific and Technical Information of China (English)

    Jianliang XU; Xueyan TANG; Wang-Chien LEE

    2008-01-01

    Wireless sensor networks are used in a large array of applications to capture,collect,and analyze physical environmental data.Many existing sensor systems instruct sensor nodes to report their measurements to central repositories outside the network,which is expensive in energy cost.Recent technological advances in flash memory have given rise to the development of storagecentric sensor networks,where sensor nodes are equipped with high-capacity flash memory storage such that sensor data can b.e stored and managed inside the network to reduce expensive communication.This novel architecture calls for new data management techniques to fully exploit distributed in-network data storage.This paper describes some of our research on distributed query processing in such flash-based sensor networks.Of particular interests are the issues that arise in the design of storage management and indexing structures combining sensor system workload and read/write/erase characteristics of flash memory.

  16. Graph-based pigment network detection in skin images

    Science.gov (United States)

    Sadeghi, M.; Razmara, M.; Ester, M.; Lee, T. K.; Atkins, M. S.

    2010-03-01

    Detecting pigmented network is a crucial step for melanoma diagnosis. In this paper, we present a novel graphbased pigment network detection method that can find and visualize round structures belonging to the pigment network. After finding sharp changes of the luminance image by an edge detection function, the resulting binary image is converted to a graph, and then all cyclic sub-graphs are detected. Theses cycles represent meshes that belong to the pigment network. Then, we create a new graph of the cyclic structures based on their distance. According to the density ratio of the new graph of the pigment network, the image is classified as "Absent" or "Present". Being Present means that a pigment network is detected in the skin lesion. Using this approach, we achieved an accuracy of 92.6% on five hundred unseen images.

  17. Access Network Selection Based on Fuzzy Logic and Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Mohammed Alkhawlani

    2008-01-01

    Full Text Available In the next generation of heterogeneous wireless networks (HWNs, a large number of different radio access technologies (RATs will be integrated into a common network. In this type of networks, selecting the most optimal and promising access network (AN is an important consideration for overall networks stability, resource utilization, user satisfaction, and quality of service (QoS provisioning. This paper proposes a general scheme to solve the access network selection (ANS problem in the HWN. The proposed scheme has been used to present and design a general multicriteria software assistant (SA that can consider the user, operator, and/or the QoS view points. Combined fuzzy logic (FL and genetic algorithms (GAs have been used to give the proposed scheme the required scalability, flexibility, and simplicity. The simulation results show that the proposed scheme and SA have better and more robust performance over the random-based selection.

  18. Rumor Diffusion in an Interests-Based Dynamic Social Network

    Directory of Open Access Journals (Sweden)

    Mingsheng Tang

    2013-01-01

    Full Text Available To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1 positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2 with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3 a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4 a network with a smaller clustering coefficient has a larger efficiency.

  19. Evaluating conducting network based transparent electrodes from geometrical considerations

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Ankush [Chemistry and Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, 560064 Bangalore (India); Kulkarni, G. U., E-mail: guk@cens.res.in [Centre for Nano and Soft Matter Sciences, 560013 Bangalore (India)

    2016-01-07

    Conducting nanowire networks have been developed as viable alternative to existing indium tin oxide based transparent electrode (TE). The nature of electrical conduction and process optimization for electrodes have gained much from the theoretical models based on percolation transport using Monte Carlo approach and applying Kirchhoff's law on individual junctions and loops. While most of the literature work pertaining to theoretical analysis is focussed on networks obtained from conducting rods (mostly considering only junction resistance), hardly any attention has been paid to those made using template based methods, wherein the structure of network is neither similar to network obtained from conducting rods nor similar to well periodic geometry. Here, we have attempted an analytical treatment based on geometrical arguments and applied image analysis on practical networks to gain deeper insight into conducting networked structure particularly in relation to sheet resistance and transmittance. Many literature examples reporting networks with straight or curvilinear wires with distributions in wire width and length have been analysed by treating the networks as two dimensional graphs and evaluating the sheet resistance based on wire density and wire width. The sheet resistance values from our analysis compare well with the experimental values. Our analysis on various examples has revealed that low sheet resistance is achieved with high wire density and compactness with straight rather than curvilinear wires and with narrower wire width distribution. Similarly, higher transmittance for given sheet resistance is possible with narrower wire width but of higher thickness, minimal curvilinearity, and maximum connectivity. For the purpose of evaluating active fraction of the network, the algorithm was made to distinguish and quantify current carrying backbone regions as against regions containing only dangling or isolated wires. The treatment can be helpful in

  20. Ontology-Based Peer Exchange Network (OPEN)

    Science.gov (United States)

    Dong, Hui

    2010-01-01

    In current Peer-to-Peer networks, distributed and semantic free indexing is widely used by systems adopting "Distributed Hash Table" ("DHT") mechanisms. Although such systems typically solve a. user query rather fast in a deterministic way, they only support a very narrow search scheme, namely the exact hash key match. Furthermore, DHT systems put…

  1. Ontology-Based Peer Exchange Network (OPEN)

    Science.gov (United States)

    Dong, Hui

    2010-01-01

    In current Peer-to-Peer networks, distributed and semantic free indexing is widely used by systems adopting "Distributed Hash Table" ("DHT") mechanisms. Although such systems typically solve a. user query rather fast in a deterministic way, they only support a very narrow search scheme, namely the exact hash key match. Furthermore, DHT systems put…

  2. Cloud-based Networked Visual Servo Control

    DEFF Research Database (Denmark)

    Wu, Haiyan; Lu, Lei; Chen, Chih-Chung

    2013-01-01

    scheduling is validated in an object tracking scenario on a 14 degree-of-freedom dual-arm robot. Experimental results show the superior performance of our approach. In particular the communication network load is substantially reduced by means of the scheduling strategy without performance degradation....

  3. Social networking for web-based communities

    NARCIS (Netherlands)

    Issa, T.; Kommers, P.A.M.

    2013-01-01

    In the 21st century, a new technology was introduced to facilitate communication, collaboration, and interaction between individuals and businesses. This technology is called social networking; this technology is now part of Internet commodities like email, browsing and blogging. From the 20th centu

  4. Certificate Based Security Services in Adhoc Sensor Network

    Directory of Open Access Journals (Sweden)

    Shahin Fatima

    2014-10-01

    Full Text Available The paper entitled “CERTIFICATE BASED SECURITY SERVICES IN ADHOC SENSOR NETWORK” proposed an approach in which the aim is to find the method for authentication which is more energy efficient and reduces the transmission time of the network. MANETs are of dynamic topology and have no predefined infrastructure. Due to its dynamic topology this network is prone to various kinds of vulnerable attacks. Sensor networks are battery operated and is a major concern. Methods on ID based Authentication consumes more network bandwidth and increases the computation and transmission time of the network. So for better operation, authentication must be the major factor of concern. In this paper a method for authentication in adhoc sensor network is proposed which is based on certificate based security services. Here we will make use of X.509 certificate format. In this some modification is made to the certificate format such that the transmission time and energy consumption of the network is reduced. Our proposed model will provide authentication among nodes and security in MANET. The proposed work is implemented in MATLAB and the result will show the effectiveness of proposed certificate in MANET. The objective of certificate based authentication is to ensure that messages can be read by authorized person only. It also overcomes the non repudiation attacks thereby minimizing the computation and shows how energy varies by making changes in certificate of node.

  5. Hemispheric asymmetry of electroencephalography-based functional brain networks.

    Science.gov (United States)

    Jalili, Mahdi

    2014-11-12

    Electroencephalography (EEG)-based functional brain networks have been investigated frequently in health and disease. It has been shown that a number of graph theory metrics are disrupted in brain disorders. EEG-based brain networks are often studied in the whole-brain framework, where all the nodes are grouped into a single network. In this study, we studied the brain networks in two hemispheres and assessed whether there are any hemispheric-specific patterns in the properties of the networks. To this end, resting state closed-eyes EEGs from 44 healthy individuals were processed and the network structures were extracted separately for each hemisphere. We examined neurophysiologically meaningful graph theory metrics: global and local efficiency measures. The global efficiency did not show any hemispheric asymmetry, whereas the local connectivity showed rightward asymmetry for a range of intermediate density values for the constructed networks. Furthermore, the age of the participants showed significant direct correlations with the global efficiency of the left hemisphere, but only in the right hemisphere, with local connectivity. These results suggest that only local connectivity of EEG-based functional networks is associated with brain hemispheres.

  6. Hierarchical Compressed Sensing for Cluster Based Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Vishal Krishna Singh

    2016-02-01

    Full Text Available Data transmission consumes significant amount of energy in large scale wireless sensor networks (WSNs. In such an environment, reducing the in-network communication and distributing the load evenly over the network can reduce the overall energy consumption and maximize the network lifetime significantly. In this work, the aforementioned problem of network lifetime and uneven energy consumption in large scale wireless sensor networks is addressed. This work proposes a hierarchical compressed sensing (HCS scheme to reduce the in-network communication during the data gathering process. Co-related sensor readings are collected via a hierarchical clustering scheme. A compressed sensing (CS based data processing scheme is devised to transmit the data from the source to the sink. The proposed HCS is able to identify the optimal position for the application of CS to achieve reduced and similar number of transmissions on all the nodes in the network. An activity map is generated to validate the reduced and uniformly distributed communication load of the WSN. Based on the number of transmissions per data gathering round, the bit-hop metric model is used to analyse the overall energy consumption. Simulation results validate the efficiency of the proposed method over the existing CS based approaches.

  7. The Quake-Catcher Network: An Innovative Community-Based Seismic Network

    Science.gov (United States)

    Saltzman, J.; Cochran, E. S.; Lawrence, J. F.; Christensen, C. M.

    2009-12-01

    The Quake-Catcher Network (QCN) is a volunteer computing seismic network that engages citizen scientists, teachers, and museums to participate in the detection of earthquakes. In less than two years, the network has grown to over 1000 participants globally and continues to expand. QCN utilizes Micro-Electro-Mechanical System (MEMS) accelerometers, in laptops and external to desktop computers, to detect moderate to large earthquakes. One goal of the network is to involve K-12 classrooms and museums by providing sensors and software to introduce participants to seismology and community-based scientific data collection. The Quake-Catcher Network provides a unique opportunity to engage participants directly in the scientific process, through hands-on activities that link activities and outcomes to their daily lives. Partnerships with teachers and museum staff are critical to growth of the Quake Catcher Network. Each participating institution receives a MEMS accelerometer to connect, via USB, to a computer that can be used for hands-on activities and to record earthquakes through a distributed computing system. We developed interactive software (QCNLive) that allows participants to view sensor readings in real time. Participants can also record earthquakes and download earthquake data that was collected by their sensor or other QCN sensors. The Quake-Catcher Network combines research and outreach to improve seismic networks and increase awareness and participation in science-based research in K-12 schools.

  8. Revisiting the Simplified Bernoulli Equation

    Science.gov (United States)

    Heys, Jeffrey J; Holyoak, Nicole; Calleja, Anna M; Belohlavek, Marek; Chaliki, Hari P

    2010-01-01

    Background: The assessment of the severity of aortic valve stenosis is done by either invasive catheterization or non-invasive Doppler Echocardiography in conjunction with the simplified Bernoulli equation. The catheter measurement is generally considered more accurate, but the procedure is also more likely to have dangerous complications. Objective: The focus here is on examining computational fluid dynamics as an alternative method for analyzing the echo data and determining whether it can provide results similar to the catheter measurement. Methods: An in vitro heart model with a rigid orifice is used as a first step in comparing echocardiographic data, which uses the simplified Bernoulli equation, catheterization, and echocardiographic data, which uses computational fluid dynamics (i.e., the Navier-Stokes equations). Results: For a 0.93cm2 orifice, the maximum pressure gradient predicted by either the simplified Bernoulli equation or computational fluid dynamics was not significantly different from the experimental catheter measurement (p > 0.01). For a smaller 0.52cm2 orifice, there was a small but significant difference (p < 0.01) between the simplified Bernoulli equation and the computational fluid dynamics simulation, with the computational fluid dynamics simulation giving better agreement with experimental data for some turbulence models. Conclusion: For this simplified, in vitro system, the use of computational fluid dynamics provides an improvement over the simplified Bernoulli equation with the biggest improvement being seen at higher valvular stenosis levels. PMID:21625471

  9. A network-based dynamical ranking system for competitive sports

    Science.gov (United States)

    Motegi, Shun; Masuda, Naoki

    2012-12-01

    From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.

  10. Software-defined Radio Based Measurement Platform for Wireless Networks.

    Science.gov (United States)

    Chao, I-Chun; Lee, Kang B; Candell, Richard; Proctor, Frederick; Shen, Chien-Chung; Lin, Shinn-Yan

    2015-10-01

    End-to-end latency is critical to many distributed applications and services that are based on computer networks. There has been a dramatic push to adopt wireless networking technologies and protocols (such as WiFi, ZigBee, WirelessHART, Bluetooth, ISA100.11a, etc.) into time-critical applications. Examples of such applications include industrial automation, telecommunications, power utility, and financial services. While performance measurement of wired networks has been extensively studied, measuring and quantifying the performance of wireless networks face new challenges and demand different approaches and techniques. In this paper, we describe the design of a measurement platform based on the technologies of software-defined radio (SDR) and IEEE 1588 Precision Time Protocol (PTP) for evaluating the performance of wireless networks.

  11. Evolution based on chromosome affinity from a network perspective

    Science.gov (United States)

    Monteiro, R. L. S.; Fontoura, J. R. A.; Carneiro, T. K. G.; Moret, M. A.; Pereira, H. B. B.

    2014-06-01

    Recent studies have focused on models to simulate the complex phenomenon of evolution of species. Several studies have been performed with theoretical models based on Darwin's theories to associate them with the actual evolution of species. However, none of the existing models include the affinity between individuals using network properties. In this paper, we present a new model based on the concept of affinity. The model is used to simulate the evolution of species in an ecosystem composed of individuals and their relationships. We propose an evolutive algorithm that incorporates the degree centrality and efficiency network properties to perform the crossover process and to obtain the network topology objective, respectively. Using a real network as a starting point, we simulate its evolution and compare its results with the results of 5788 computer-generated networks.

  12. Enhanced Weight based DSR for Mobile Ad Hoc Networks

    Science.gov (United States)

    Verma, Samant; Jain, Sweta

    2011-12-01

    Routing in ad hoc network is a great problematic, since a good routing protocol must ensure fast and efficient packet forwarding, which isn't evident in ad hoc networks. In literature there exists lot of routing protocols however they don't include all the aspects of ad hoc networks as mobility, device and medium constraints which make these protocols not efficient for some configuration and categories of ad hoc networks. Thus in this paper we propose an improvement of Weight Based DSR in order to include some of the aspects of ad hoc networks as stability, remaining battery power, load and trust factor and proposing a new approach Enhanced Weight Based DSR.

  13. Efficient learning strategy of Chinese characters based on network approach

    CERN Document Server

    Yan, Xiao-Yong; Di, Zengru; Havlin, Shlomo; Wu, Jinshan

    2013-01-01

    Based on network analysis of hierarchical structural relations among Chinese characters, we develop an efficient learning strategy of Chinese characters. We regard a more efficient learning method if one learns the same number of useful Chinese characters in less effort or time. We construct a node-weighted network of Chinese characters, where character usage frequencies are used as node weights. Using this hierarchical node-weighted network, we propose a new learning method, the distributed node weight (DNW) strategy, which is based on a new measure of nodes' importance that takes into account both the weight of the nodes and the hierarchical structure of the network. Chinese character learning strategies, particularly their learning order, are analyzed as dynamical processes over the network. We compare the efficiency of three theoretical learning methods and two commonly used methods from mainstream Chinese textbooks, one for Chinese elementary school students and the other for students learning Chinese as...

  14. Simplifying gene trees for easier comprehension

    Directory of Open Access Journals (Sweden)

    Mundry Marvin

    2006-04-01

    Full Text Available Abstract Background In the genomic age, gene trees may contain large amounts of data making them hard to read and understand. Therefore, an automated simplification is important. Results We present a simplification tool for gene trees called TreeSimplifier. Based on species tree information and HUGO gene names, it summarizes "monophyla". These monophyla correspond to subtrees of the gene tree where the evolution of a gene follows species phylogeny, and they are simplified to single leaves in the gene tree. Such a simplification may fail, for example, due to genes in the gene tree that are misplaced. In this way, misplaced genes can be identified. Optionally, our tool glosses over a limited degree of "paraphyly" in a further simplification step. In both simplification steps, species can be summarized into groups and treated as equivalent. In the present study we used our tool to derive a simplified tree of 397 leaves from a tree of 1138 leaves. Comparing the simplified tree to a "cartoon tree" created manually, we note that both agree to a high degree. Conclusion Our automatic simplification tool for gene trees is fast, accurate, and effective. It yields results of similar quality as manual simplification. It should be valuable in phylogenetic studies of large protein families. The software is available at http://www.uni-muenster.de/Bioinformatics/services/treesim/.

  15. Simplifying gene trees for easier comprehension.

    Science.gov (United States)

    Lott, Paul-Ludwig; Mundry, Marvin; Sassenberg, Christoph; Lorkowski, Stefan; Fuellen, Georg

    2006-04-27

    In the genomic age, gene trees may contain large amounts of data making them hard to read and understand. Therefore, an automated simplification is important. We present a simplification tool for gene trees called TreeSimplifier. Based on species tree information and HUGO gene names, it summarizes "monophyla". These monophyla correspond to subtrees of the gene tree where the evolution of a gene follows species phylogeny, and they are simplified to single leaves in the gene tree. Such a simplification may fail, for example, due to genes in the gene tree that are misplaced. In this way, misplaced genes can be identified. Optionally, our tool glosses over a limited degree of "paraphyly" in a further simplification step. In both simplification steps, species can be summarized into groups and treated as equivalent. In the present study we used our tool to derive a simplified tree of 397 leaves from a tree of 1138 leaves. Comparing the simplified tree to a "cartoon tree" created manually, we note that both agree to a high degree. Our automatic simplification tool for gene trees is fast, accurate, and effective. It yields results of similar quality as manual simplification. It should be valuable in phylogenetic studies of large protein families. The software is available at http://www.uni-muenster.de/Bioinformatics/services/treesim/.

  16. The harmonics detection method based on neural network applied ...

    African Journals Online (AJOL)

    user

    Keywords: Artificial Neural Networks (ANN), p-q theory, (SAPF), Harmonics, Total Harmonic Distortion. 1. ... Recently, some methods based on artificial intelligence have been applied In order to improve ..... The effect is the reduction of.

  17. Network-Based Material Requirements Planning (NBMRP) in ...

    African Journals Online (AJOL)

    Network-Based Material Requirements Planning (NBMRP) in Product Development Project. ... delays during the execution stage due to poor material supply programmes. ... and uninterrupted scheduled flow throughout the project life cycle.

  18. NETWORK-CENTRIC WARFARE AND SOME PARTICULAR ASPECTS OF LOGISTICS BASED ON NETWORKING

    Directory of Open Access Journals (Sweden)

    Petrişor JALBĂ

    2015-04-01

    Full Text Available Within the framework of the current revolution in military affairs, at the End of the Cold War a new concept was born: the concept of War Based on Computer Networking or NCW Network Centric-Warfare which was established as a central element of modern military operations. Determined by theprogress recorded in the field of communication systems of all types, technology of information (HI-Tech, IT, war based on computer networking brings a change in the war paradigm and its inherent components In this respect, logistics based on computer networking represents one of the ways in which the reality of the battlefield is preserved which enhances the joint perspective upon the military forces.

  19. Comparison and combination of a hemodynamics/biomarkers-based model with simplified PESI score for prognostic stratification of acute pulmonary embolism: findings from a real world study

    Directory of Open Access Journals (Sweden)

    Luca Masotti

    2015-11-01

    Full Text Available Background: Prognostic stratification is of utmost importance for management of acute Pulmonary Embolism (PE in clinical practice. Many prognostic models have been proposed, but which is the best prognosticator in real life remains unclear. The aim of our study was to compare and combine the predictive values of the hemodynamics/biomarkers based prognostic model proposed by European Society of Cardiology (ESC in 2008 and simplified PESI score (sPESI. Methods: Data records of 452 patients discharged for acute PE from Internal Medicine wards of Tuscany (Italy were analysed. The ESC model and sPESI were retrospectively calculated and compared by using Areas under Receiver Operating Characteristics (ROC Curves (AUCs and finally the combination of the two models was tested in hemodinamically stable patients. All cause and PE-related in-hospital mortality and fatal or major bleedings were the analyzed endpoints Results: All cause in-hospital mortality was 25% (16.6% PE related in high risk, 8.7% (4.7% in intermediate risk and 3.8% (1.2% in low risk patients according to ESC model. All cause in-hospital mortality was 10.95% (5.75% PE related in patients with sPESI score and #8805;1 and 0% (0% in sPESI score 0. Predictive performance of sPESI was not significantly different compared with 2008 ESC model both for all cause (AUC sPESI 0.711, 95% CI: 0.661-0.758 versus ESC 0.619, 95% CI: 0.567-0.670, difference between AUCs 0.0916, p=0.084 and for PE-related mortality (AUC sPESI 0.764, 95% CI: 0.717-0.808 versus ESC 0.650, 95% CI: 0.598-0.700, difference between AUCs 0.114, p=0.11. Fatal or major bleedings occurred in 4.30% of high risk, 1.60% of intermediate risk and 2.50% of low risk patients according to 2008 ESC model, whereas these occurred in 1.80% of high risk and 1.45% of low risk patients according to sPESI, respectively. Predictive performance for fatal or major bleeding between two models was not significantly different (AUC sPESI 0.658, 95% CI

  20. Content-Based Multi-Channel Network Coding Algorithm in the Millimeter-Wave Sensor Network

    Directory of Open Access Journals (Sweden)

    Kai Lin

    2016-07-01

    Full Text Available With the development of wireless technology, the widespread use of 5G is already an irreversible trend, and millimeter-wave sensor networks are becoming more and more common. However, due to the high degree of complexity and bandwidth bottlenecks, the millimeter-wave sensor network still faces numerous problems. In this paper, we propose a novel content-based multi-channel network coding algorithm, which uses the functions of data fusion, multi-channel and network coding to improve the data transmission; the algorithm is referred to as content-based multi-channel network coding (CMNC. The CMNC algorithm provides a fusion-driven model based on the Dempster-Shafer (D-S evidence theory to classify the sensor nodes into different classes according to the data content. By using the result of the classification, the CMNC algorithm also provides the channel assignment strategy and uses network coding to further improve the quality of data transmission in the millimeter-wave sensor network. Extensive simulations are carried out and compared to other methods. Our simulation results show that the proposed CMNC algorithm can effectively improve the quality of data transmission and has better performance than the compared methods.

  1. Content-Based Multi-Channel Network Coding Algorithm in the Millimeter-Wave Sensor Network.

    Science.gov (United States)

    Lin, Kai; Wang, Di; Hu, Long

    2016-07-01

    With the development of wireless technology, the widespread use of 5G is already an irreversible trend, and millimeter-wave sensor networks are becoming more and more common. However, due to the high degree of complexity and bandwidth bottlenecks, the millimeter-wave sensor network still faces numerous problems. In this paper, we propose a novel content-based multi-channel network coding algorithm, which uses the functions of data fusion, multi-channel and network coding to improve the data transmission; the algorithm is referred to as content-based multi-channel network coding (CMNC). The CMNC algorithm provides a fusion-driven model based on the Dempster-Shafer (D-S) evidence theory to classify the sensor nodes into different classes according to the data content. By using the result of the classification, the CMNC algorithm also provides the channel assignment strategy and uses network coding to further improve the quality of data transmission in the millimeter-wave sensor network. Extensive simulations are carried out and compared to other methods. Our simulation results show that the proposed CMNC algorithm can effectively improve the quality of data transmission and has better performance than the compared methods.

  2. Belief Function Based Decision Fusion for Decentralized Target Classification in Wireless Sensor Networks.

    Science.gov (United States)

    Zhang, Wenyu; Zhang, Zhenjiang

    2015-08-19

    Decision fusion in sensor networks enables sensors to improve classification accuracy while reducing the energy consumption and bandwidth demand for data transmission. In this paper, we focus on the decentralized multi-class classification fusion problem in wireless sensor networks (WSNs) and a new simple but effective decision fusion rule based on belief function theory is proposed. Unlike existing belief function based decision fusion schemes, the proposed approach is compatible with any type of classifier because the basic belief assignments (BBAs) of each sensor are constructed on the basis of the classifier's training output confusion matrix and real-time observations. We also derive explicit global BBA in the fusion center under Dempster's combinational rule, making the decision making operation in the fusion center greatly simplified. Also, sending the whole BBA structure to the fusion center is avoided. Experimental results demonstrate that the proposed fusion rule has better performance in fusion accuracy compared with the naïve Bayes rule and weighted majority voting rule.

  3. Convolutional Network Coding Based on Matrix Power Series Representation

    CERN Document Server

    Guo, Wangmei; Sun, Qifu Tyler

    2011-01-01

    In this paper, convolutional network coding is formulated by means of matrix power series representation of the local encoding kernel (LEK) matrices and global encoding kernel (GEK) matrices to establish its theoretical fundamentals for practical implementations. From the encoding perspective, the GEKs of a convolutional network code (CNC) are shown to be uniquely determined by its LEK matrix $K(z)$ if $K_0$, the constant coefficient matrix of $K(z)$, is nilpotent. This will simplify the CNC design because a nilpotent $K_0$ suffices to guarantee a unique set of GEKs. Besides, the relation between coding topology and $K(z)$ is also discussed. From the decoding perspective, the main theme is to justify that the first $L+1$ terms of the GEK matrix $F(z)$ at a sink $r$ suffice to check whether the code is decodable at $r$ with delay $L$ and to start decoding if so. The concomitant decoding scheme avoids dealing with $F(z)$, which may contain infinite terms, as a whole and hence reduces the complexity of decodabil...

  4. ADAPTIVE GOSSIP BASED PROTOCOL FOR ENERGY EFFICIENT MOBILE ADHOC NETWORK

    OpenAIRE

    S. Rajeswari; Venkataramani, Y.

    2012-01-01

    In Gossip Sleep Protocol, network performance is enhanced based on energy resource. But energy conservation is achieved with the reduced throughput. In this paper, it has been proposed a new Protocol for Mobile Ad hoc Network to achieve reliability with energy conservation. Based on the probability (p) values, the value of sleep nodes is fixed initially. The probability value can be adaptively adjusted by Remote Activated Switch during the transmission process. The adaptiveness of gossiping p...

  5. Image watermarking capacity analysis based on Hopfield neural network

    Institute of Scientific and Technical Information of China (English)

    Fan Zhang(张帆); Hongbin Zhang(张鸿宾)

    2004-01-01

    In watermarking schemes, watermarking can be viewed as a form of communication problems. Almost all of previous works on image watermarking capacity are based on information theory, using Shannon formula to calculate the capacity of watermarking. In this paper, we present a blind watermarking algorithm using Hopfield neural network, and analyze watermarking capacity based on neural network. In our watermarking algorithm, watermarking capacity is decided by attraction basin of associative memory.

  6. Contribution to a proposition for a long term development of nuclear energy: the TASSE concept (Thorium based Accelerator driven System with Simplified fuel cycle for long term Energy Production); Contribution a une proposition d'un developpement a long terme de l'energie nucleaire: le concept TASSE (Thorium based Accelerator driven System with Simplified fuel cycle for long term Energy Production)

    Energy Technology Data Exchange (ETDEWEB)

    Berthou, V

    2000-10-30

    Nuclear industry creates waste which are in the middle of the discussion concerning the Nuclear Energy future. At this time, important decisions for the Energy production must be taken, so numerous researches are conducted within the framework of the Bataille law. The goal of these studies is to find a range of solutions concerning the waste management. An innovative system, called TASSE (Thorium based Accelerator driven System with Simplified fuel cycle for long term Energy production), is studied in this thesis. This reactor is included in a long term strategy, and is destined for the renewal of the reactor park. In the first part of this work, the main characteristics of TASSE have been defined. They are commensurate with some specific requirements such as: to insure a large time to the Nuclear Energy, to reduce the waste production in an important way, to eliminate waste already stocked in the present park, to insure the non proliferation, and to be economically competitive. Neutronics studies of TASSE have been done. A calculation procedure has been developed to reach the system equilibrium state. Several types of molten salts as well as a pebble-bed fuel have been studied. Thus, an optimal fuel has been brought out in regard to some parameters such as the burn up level, the spectrum, the waste toxicity, the cycle type. Eventually, various TASSE core layout have been envisaged. (author)

  7. Theory of fractional order elements based impedance matching networks

    KAUST Repository

    Radwan, Ahmed G.

    2011-03-01

    Fractional order circuit elements (inductors and capacitors) based impedance matching networks are introduced for the first time. In comparison to the conventional integer based L-type matching networks, fractional matching networks are much simpler and versatile. Any complex load can be matched utilizing a single series fractional element, which generally requires two elements for matching in the conventional approach. It is shown that all the Smith chart circles (resistance and reactance) are actually pairs of completely identical circles. They appear to be single for the conventional integer order case, where the identical circles completely overlap each other. The concept is supported by design equations and impedance matching examples. © 2010 IEEE.

  8. Finding Important Nodes in Social Networks Based on Modified Pagerank

    Directory of Open Access Journals (Sweden)

    Li-qing Qiu

    2014-01-01

    Full Text Available Important nodes are individuals who have huge influence on social network. Finding important nodes in social networks is of great significance for research on the structure of the social networks. Based on the core idea of Pagerank, a new ranking method is proposed by considering the link similarity between the nodes. The key concept of the method is the use of the link vector which records the contact times between nodes. Then the link similarity is computed based on the vectors through the similarity function. The proposed method incorporates the link similarity into original Pagerank. The experiment results show that the proposed method can get better performance.

  9. Caption detection from video sequence based on fuzzy neural networks

    Science.gov (United States)

    Gao, Xinbo; Xin, Hong; Li, Jie

    2001-09-01

    Caption graphically superimposed in video frames can provide important indexing information. The automatic detection and recognition of video captions can be of great help in querying topics of interest in digital news library. To detect the caption from video sequence, we present algorithms based on fuzzy clustering neural networks. Since neural networks have the capabilities of learning and self-organizing and parallel computing mechanism, with the great increasing of digital images and video databases, neural networks based techniques become more efficient and popular tools for multimedia processing. Experimental results show that our caption detection scheme is effective and robust.

  10. Optimal Design of Two Road Networks Based on their Properties

    Institute of Scientific and Technical Information of China (English)

    Ming-zhe Li; Yan Zhang

    2007-01-01

    In this paper,we discuss some fundamental properties of two idealized typical networks,namely,grid type and radial-circular type.The discussion is based on SPCP(Shortest Path Counting Problem),which reflects the traffic density of a road segment.Furthermore,we compare their effectiveness based on the obtained results of the above two road networks,and suggest some proposals on the design of car lanes by considering the direction of a road segment in relation to these road networks.

  11. BP Network Based Users' Interest Model in Mining WWW Cache

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    By analyzing the WWW Cache model, we bring forward a user-interest description method based on the fuzzy theory and user-interest inferential relations based on BP(back propagation) neural network. By this method, the users' interest in the WWW cache can be described and the neural network of users' interest can be constructed by positive spread of interest and the negative spread of errors. This neural network can infer the users' interest. This model is not the simple extension of the simple interest model, but the round improvement of the model and its related algorithm.

  12. Network Traffic Anomalies Identification Based on Classification Methods

    Directory of Open Access Journals (Sweden)

    Donatas Račys

    2015-07-01

    Full Text Available A problem of network traffic anomalies detection in the computer networks is analyzed. Overview of anomalies detection methods is given then advantages and disadvantages of the different methods are analyzed. Model for the traffic anomalies detection was developed based on IBM SPSS Modeler and is used to analyze SNMP data of the router. Investigation of the traffic anomalies was done using three classification methods and different sets of the learning data. Based on the results of investigation it was determined that C5.1 decision tree method has the largest accuracy and performance and can be successfully used for identification of the network traffic anomalies.

  13. Coverage analysis for sensor networks based on Clifford algebra

    Institute of Scientific and Technical Information of China (English)

    XIE WeiXin; CAO WenMing; MENG Shan

    2008-01-01

    The coverage performance is the foundation of information acquisition in distrib-uted sensor networks. The previously proposed coverage work was mostly based on unit disk coverage model or ball coverage model in 2D or 3D space, respectively. However, most methods cannot give a homogeneous coverage model for targets with hybrid types. This paper presents a coverage analysis approach for sensor networks based on Clifford algebra and establishes a homogeneous coverage model for sensor networks with hybrid types of targets. The effectiveness of the approach is demonstrated with examples.

  14. Coal mine gas monitoring system based on wireless sensor network

    Institute of Scientific and Technical Information of China (English)

    WANG Jian; WANG Ru-lin; WANG Xue-min; SHEN Chuan-he

    2007-01-01

    Based on the nowadays'condition.it is urgent that the gas detection cable communication system must be replaced by the wireless communication systems.The wireless sensors distributed in the environment can achieve the intelligent gas monitoring system.Apply with multilayer data fuse to design working tactics,and import the artificial neural networks to analyze detecting result.The wireless sensors system communicates with the controI center through the optical fiber cable.All the gas sensor nodes distributed in coal mine are combined into an intelligent,flexible structure wireless network system.forming coal mine gas monitoring system based on wireless sensor network.

  15. Underwater Acoustic Networks: Channel Models and Network Coding based Lower Bound to Transmission Power for Multicast

    CERN Document Server

    Lucani, Daniel E; Stojanovic, Milica

    2008-01-01

    The goal of this paper is two-fold. First, to establish a tractable model for the underwater acoustic channel useful for network optimization in terms of convexity. Second, to propose a network coding based lower bound for transmission power in underwater acoustic networks, and compare this bound to the performance of several network layer schemes. The underwater acoustic channel is characterized by a path loss that depends strongly on transmission distance and signal frequency. The exact relationship among power, transmission band, distance and capacity for the Gaussian noise scenario is a complicated one. We provide a closed-form approximate model for 1) transmission power and 2) optimal frequency band to use, as functions of distance and capacity. The model is obtained through numerical evaluation of analytical results that take into account physical models of acoustic propagation loss and ambient noise. Network coding is applied to determine a lower bound to transmission power for a multicast scenario, fo...

  16. Creative elements: network-based predictions of active centres in proteins, cellular and social networks

    CERN Document Server

    Csermely, Peter

    2008-01-01

    Active centres and hot spots of proteins have a paramount importance in enzyme action, protein complex formation and drug design. Recently a number of publications successfully applied the analysis of residue networks to predict active centres in proteins. Most real-world networks show a number of properties, such as small-worldness or scale-free degree distribution, which are rather general features of networks from molecules to the society. Based on extensive analogies I propose that the existing findings and methodology enable us to detect active centres in cells, social networks and ecosystems. Members of these active centres are creative elements of the respective networks, which may help them to survive unprecedented, novel challenges, and play a key role in the development, survival and evolvability of complex systems.

  17. Improving Network Performance with Affinity based Mobility Model in Opportunistic Network

    CERN Document Server

    Batabyal, Suvadip; 10.5121/ijwmn.2012.4213

    2012-01-01

    Opportunistic network is a type of Delay Tolerant Network which is characterized by intermittent connectivity amongst the nodes and communication largely depends upon the mobility of the participating nodes. The network being highly dynamic, traditional MANET protocols cannot be applied and the nodes must adhere to store-carry-forward mechanism. Nodes do not have the information about the network topology, number of participating nodes and the location of the destination node. Hence, message transfer reliability largely depends upon the mobility pattern of the nodes. In this paper we have tried to find the impact of RWP (Random Waypoint) mobility on packet delivery ratio. We estimate mobility factors like number of node encounters, contact duration(link time) and inter-contact time which in turn depends upon parameters like playfield area (total network area), number of nodes, node velocity, bit-rate and RF range of the nodes. We also propose a restricted form of RWP mobility model, called the affinity based ...

  18. Neural-networks-based Modelling and a Fuzzy Neural Networks Controller of MCFC

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Molten Carbonate Fuel Cells (MCFC) are produced with a highly efficient and clean power generation technology which will soon be widely utilized. The temperature characters of MCFC stack are briefly analyzed. A radial basis function (RBF) neural networks identification technology is applied to set up the temperature nonlinear model of MCFC stack, and the identification structure, algorithm and modeling training process are given in detail. A fuzzy controller of MCFC stack is designed. In order to improve its online control ability, a neural network trained by the I/O data of a fuzzy controller is designed. The neural networks can memorize and expand the inference rules of the fuzzy controller and substitute for the fuzzy controller to control MCFC stack online. A detailed design of the controller is given. The validity of MCFC stack modelling based on neural networks and the superior performance of the fuzzy neural networks controller are proved by Simulations.

  19. Hybrid Network Defense Model Based on Fuzzy Evaluation

    Directory of Open Access Journals (Sweden)

    Ying-Chiang Cho

    2014-01-01

    Full Text Available With sustained and rapid developments in the field of information technology, the issue of network security has become increasingly prominent. The theme of this study is network data security, with the test subject being a classified and sensitive network laboratory that belongs to the academic network. The analysis is based on the deficiencies and potential risks of the network’s existing defense technology, characteristics of cyber attacks, and network security technologies. Subsequently, a distributed network security architecture using the technology of an intrusion prevention system is designed and implemented. In this paper, first, the overall design approach is presented. This design is used as the basis to establish a network defense model, an improvement over the traditional single-technology model that addresses the latter’s inadequacies. Next, a distributed network security architecture is implemented, comprising a hybrid firewall, intrusion detection, virtual honeynet projects, and connectivity and interactivity between these three components. Finally, the proposed security system is tested. A statistical analysis of the test results verifies the feasibility and reliability of the proposed architecture. The findings of this study will potentially provide new ideas and stimuli for future designs of network security architecture.

  20. A Mobile Network Planning Tool Based on Data Analytics

    Directory of Open Access Journals (Sweden)

    Jessica Moysen

    2017-01-01

    Full Text Available Planning future mobile networks entails multiple challenges due to the high complexity of the network to be managed. Beyond 4G and 5G networks are expected to be characterized by a high densification of nodes and heterogeneity of layers, applications, and Radio Access Technologies (RAT. In this context, a network planning tool capable of dealing with this complexity is highly convenient. The objective is to exploit the information produced by and already available in the network to properly deploy, configure, and optimise network nodes. This work presents such a smart network planning tool that exploits Machine Learning (ML techniques. The proposed approach is able to predict the Quality of Service (QoS experienced by the users based on the measurement history of the network. We select Physical Resource Block (PRB per Megabit (Mb as our main QoS indicator to optimise, since minimizing this metric allows offering the same service to users by consuming less resources, so, being more cost-effective. Two cases of study are considered in order to evaluate the performance of the proposed scheme, one to smartly plan the small cell deployment in a dense indoor scenario and a second one to timely face a detected fault in a macrocell network.

  1. An FPGA-based Torus Communication Network

    CERN Document Server

    Pivanti, Marcello; Simma, Hubert

    2010-01-01

    We describe the design and FPGA implementation of a 3D torus network (TNW) to provide nearest-neighbor communications between commodity multi-core processors. The aim of this project is to build up tightly interconnected and scalable parallel systems for scientific computing. The design includes the VHDL code to implement on latest FPGA devices a network processor, which can be accessed by the CPU through a PCIe interface and which controls the external PHYs of the physical links. Moreover, a Linux driver and a library implementing custom communication APIs are provided. The TNW has been successfully integrated in two recent parallel machine projects, QPACE and AuroraScience. We describe some details of the porting of the TNW for the AuroraScience system and report performance results.

  2. An FPGA-based torus communication network

    Energy Technology Data Exchange (ETDEWEB)

    Pivanti, Marcello; Schifano, Sebastiano Fabio [INFN, Ferrara (Italy); Ferrara Univ. (Italy); Simma, Hubert [DESY, Zeuthen (Germany). John von Neumann-Institut fuer Computing NIC

    2011-02-15

    We describe the design and FPGA implementation of a 3D torus network (TNW) to provide nearest-neighbor communications between commodity multi-core processors. The aim of this project is to build up tightly interconnected and scalable parallel systems for scientific computing. The design includes the VHDL code to implement on latest FPGA devices a network processor, which can be accessed by the CPU through a PCIe interface and which controls the external PHYs of the physical links. Moreover, a Linux driver and a library implementing custom communication APIs are provided. The TNW has been successfully integrated in two recent parallel machine projects, QPACE and AuroraScience. We describe some details of the porting of the TNW for the AuroraScience system and report performance results. (orig.)

  3. Neural Networks for Model-Based Recognition

    Science.gov (United States)

    1991-06-12

    network. November 23, 1990 -21:52 IDRAFT 17 where X P is the pseudo inverse of Xo. The coefficients of Rpt can also be obtained using three ADALINEs ...the pseudo inverse or an ADALINE . 5 Convergence and Comparison of the Two Mean Field Approaches In the 2-D problem, both mean field approaches MFAI...Also small time steps have to be taken to avoid oscillations November 23, 1990 - 21:52 DRAFT 18 Figure 12: ADALINE for calculation of R. and

  4. Pictographic steganography based on social networking websites

    OpenAIRE

    Feno Heriniaina RABEVOHITRA; Xiaofeng Liao

    2016-01-01

    Steganography is the art of communication that does not let a third party know that the communication channel exists. It has always been influenced by the way people communicate and with the explosion of social networking websites, it is likely that these will be used as channels to cover the very existence of communication between different entities. In this paper, we present a new effective pictographic steganographic channel. We make use of the huge amount of photos available online as com...

  5. Compressed Sensing-Based Multiuser Cooperative Networks

    Institute of Scientific and Technical Information of China (English)

    付晓梅; 崔阳然

    2016-01-01

    To avoid interference, compressed sensing is introduced into multiuser cooperative network. A coopera-tive compressed sensing and amplify-and-forward(CCS-AF)scheme is proposed, and it is proved that the channel capacity increases compared with the traditional cooperative scheme by considering the CCS-AF transmission ma-trix as the measurement matrix. Moreover, a new power allocation algorithm among the relays is proposed to im-prove the channel capacity. Numerical results validate the effectiveness of the proposed scheme.

  6. Image-based Localization using Hourglass Networks

    OpenAIRE

    Melekhov, Iaroslav; Ylioinas, Juha; Kannala, Juho; Rahtu, Esa

    2017-01-01

    In this paper, we propose an encoder-decoder convolutional neural network (CNN) architecture for estimating camera pose (orientation and location) from a single RGB-image. The architecture has a hourglass shape consisting of a chain of convolution and up-convolution layers followed by a regression part. The up-convolution layers are introduced to preserve the fine-grained information of the input image. Following the common practice, we train our model in end-to-end manner utilizing transfer ...

  7. Reliability analysis of cluster-based ad-hoc networks

    Energy Technology Data Exchange (ETDEWEB)

    Cook, Jason L. [Quality Engineering and System Assurance, Armament Research Development Engineering Center, Picatinny Arsenal, NJ (United States); Ramirez-Marquez, Jose Emmanuel [School of Systems and Enterprises, Stevens Institute of Technology, Castle Point on Hudson, Hoboken, NJ 07030 (United States)], E-mail: Jose.Ramirez-Marquez@stevens.edu

    2008-10-15

    The mobile ad-hoc wireless network (MAWN) is a new and emerging network scheme that is being employed in a variety of applications. The MAWN varies from traditional networks because it is a self-forming and dynamic network. The MAWN is free of infrastructure and, as such, only the mobile nodes comprise the network. Pairs of nodes communicate either directly or through other nodes. To do so, each node acts, in turn, as a source, destination, and relay of messages. The virtue of a MAWN is the flexibility this provides; however, the challenge for reliability analyses is also brought about by this unique feature. The variability and volatility of the MAWN configuration makes typical reliability methods (e.g. reliability block diagram) inappropriate because no single structure or configuration represents all manifestations of a MAWN. For this reason, new methods are being developed to analyze the reliability of this new networking technology. New published methods adapt to this feature by treating the configuration probabilistically or by inclusion of embedded mobility models. This paper joins both methods together and expands upon these works by modifying the problem formulation to address the reliability analysis of a cluster-based MAWN. The cluster-based MAWN is deployed in applications with constraints on networking resources such as bandwidth and energy. This paper presents the problem's formulation, a discussion of applicable reliability metrics for the MAWN, and illustration of a Monte Carlo simulation method through the analysis of several example networks.

  8. Topological Embedding Feature Based Resource Allocation in Network Virtualization

    Directory of Open Access Journals (Sweden)

    Hongyan Cui

    2014-01-01

    Full Text Available Virtualization provides a powerful way to run multiple virtual networks on a shared substrate network, which needs accurate and efficient mathematical models. Virtual network embedding is a challenge in network virtualization. In this paper, considering the degree of convergence when mapping a virtual network onto substrate network, we propose a new embedding algorithm based on topology mapping convergence-degree. Convergence-degree means the adjacent degree of virtual network’s nodes when they are mapped onto a substrate network. The contributions of our method are as below. Firstly, we map virtual nodes onto the substrate nodes with the maximum convergence-degree. The simulation results show that our proposed algorithm largely enhances the network utilization efficiency and decreases the complexity of the embedding problem. Secondly, we define the load balance rate to reflect the load balance of substrate links. The simulation results show our proposed algorithm achieves better load balance. Finally, based on the feature of star topology, we further improve our embedding algorithm and make it suitable for application in the star topology. The test result shows it gets better performance than previous works.

  9. Sewage flow optimization algorithm for large-scale urban sewer networks based on network community division

    Institute of Scientific and Technical Information of China (English)

    Lihui CEN; Yugeng XI

    2008-01-01

    By considering the flow control of urban sewer networks to minimize the electricity consumption of pumping stations.a decomposition-coordination strategy for energy savings based on network community division is developed in this paper. A mathematical model characterizing the smady-state flow of urball sewer networks is first constructed,consisting of a set of algebraic equations with the structure transportation capacities captured as constraints.Since the sewer networks have no apparent natural hierarchical structure in general.it is very difficult to identify the clustered groups.A fast network division approach through calculating the betweenness of each edge is successfully applied to identify the groups and a sewer network with arbitrary configuration could be then decomposed into subnetworks.By integrating the coupling constraints of the subnetworks.the original problem is separated into N optimization subproblems in accordance with the network decomposition.Each subproblem is solved locally and the solutions to the subproblems are coordinated to form an appropriate global solution.Finally,an application to a specified large-scale sewer network is also investigated to demonstrate the validity of the proposed algorithm.

  10. Degree-based attacks and defense strategies in complex networks

    Science.gov (United States)

    Yehezkel, Aviv; Cohen, Reuven

    2012-12-01

    We study the stability of random scale-free networks to degree-dependent attacks. We present analytical and numerical results to compute the critical fraction pc of nodes that need to be removed for destroying the network under this attack for different attack parameters. We study the effect of different defense strategies, based on the addition of a constant number of links on network robustness. We test defense strategies based on adding links to either low degree, middegree or high degree nodes. We find using analytical results and simulations that the middegree nodes defense strategy leads to the largest improvement to the network robustness against degree-based attacks. We also test these defense strategies on an internet autonomous systems map and obtain similar results.

  11. Web Pre-fetching Model Based on Concept Association Network

    Institute of Scientific and Technical Information of China (English)

    XUHuanqing; WANGYongcheng

    2004-01-01

    With the enormous growth of information on the web, Internet has become one of the most important information sources. However, limited by the network bandwidth, users always suffer from long time waiting. Web pre-fetching is one of the most popular strategies,which are proposed for reducing the perceived access delay and improving the service quality of web server. This paper presents a pre-fetching model based on concept as sociation network, which mines concept association relationships that are implied in user access patterns and employs online learning and oitiine mining algorithm to construct the user-oriented concept association network. Using concept association network, pre-fetching model makes semantics-based pre-fetching decisions in the client side.This model implements the concept-based analysis on user access patterns and improves the prediction accuracy. Experimental results show that the proposed pre-fetching model has better general performance.

  12. Passivity-based control and estimation in networked robotics

    CERN Document Server

    Hatanaka, Takeshi; Fujita, Masayuki; Spong, Mark W

    2015-01-01

    Highlighting the control of networked robotic systems, this book synthesizes a unified passivity-based approach to an emerging cross-disciplinary subject. Thanks to this unified approach, readers can access various state-of-the-art research fields by studying only the background foundations associated with passivity. In addition to the theoretical results and techniques,  the authors provide experimental case studies on testbeds of robotic systems  including networked haptic devices, visual robotic systems,  robotic network systems and visual sensor network systems. The text begins with an introduction to passivity and passivity-based control together with the other foundations needed in this book. The main body of the book consists of three parts. The first examines how passivity can be utilized for bilateral teleoperation and demonstrates the inherent robustness of the passivity-based controller against communication delays. The second part emphasizes passivity’s usefulness for visual feedback control ...

  13. Research of Collaborative Filtering Recommendation Algorithm based on Network Structure

    Directory of Open Access Journals (Sweden)

    Hui PENG

    2013-10-01

    Full Text Available This paper combines the classic collaborative filtering algorithm with personalized recommendation algorithm based on network structure. For the data sparsity and malicious behavior problems of traditional collaborative filtering algorithm, the paper introduces a new kind of social network-based collaborative filtering algorithm. In order to improve the accuracy of the personalized recommendation technology, we first define empty state in the state space of multi-dimensional semi-Markov processes and obtain extended multi-dimensional semi-Markov processes which are combined with social network analysis theory, and then we get social network information flow model. The model describes the flow of information between the members of the social network. So, we propose collaborative filtering algorithm based on social network information flow model. The algorithm uses social network information and combines user trust with user interest and find nearest neighbors of the target user and then forms a project recommended to improve the accuracy of recommended. Compared with the traditional collaborative filtering algorithm, the algorithm can effectively alleviate the sparsity and malicious behavior problem, and significantly improve the quality of the recommendation system recommended.

  14. Predicting links based on knowledge dissemination in complex network

    Science.gov (United States)

    Zhou, Wen; Jia, Yifan

    2017-04-01

    Link prediction is the task of mining the missing links in networks or predicting the next vertex pair to be connected by a link. A lot of link prediction methods were inspired by evolutionary processes of networks. In this paper, a new mechanism for the formation of complex networks called knowledge dissemination (KD) is proposed with the assumption of knowledge disseminating through the paths of a network. Accordingly, a new link prediction method-knowledge dissemination based link prediction (KDLP)-is proposed to test KD. KDLP characterizes vertex similarity based on knowledge quantity (KQ) which measures the importance of a vertex through H-index. Extensive numerical simulations on six real-world networks demonstrate that KDLP is a strong link prediction method which performs at a higher prediction accuracy than four well-known similarity measures including common neighbors, local path index, average commute time and matrix forest index. Furthermore, based on the common conclusion that an excellent link prediction method reveals a good evolving mechanism, the experiment results suggest that KD is a considerable network evolving mechanism for the formation of complex networks.

  15. FUZZY LOGIC BASED ENERGY EFFICIENT PROTOCOL IN WIRELESS SENSOR NETWORKS

    Directory of Open Access Journals (Sweden)

    Zhan Wei Siew

    2012-12-01

    Full Text Available Wireless sensor networks (WSNs have been vastly developed due to the advances in microelectromechanical systems (MEMS using WSN to study and monitor the environments towards climates changes. In environmental monitoring, sensors are randomly deployed over the interest area to periodically sense the physical environments for a few months or even a year. Therefore, to prolong the network lifetime with limited battery capacity becomes a challenging issue. Low energy adaptive cluster hierarchical (LEACH is the common clustering protocol that aim to reduce the energy consumption by rotating the heavy workload cluster heads (CHs. The CHs election in LEACH is based on probability model which will lead to inefficient in energy consumption due to least desired CHs location in the network. In WSNs, the CHs location can directly influence the network energy consumption and further affect the network lifetime. In this paper, factors which will affect the network lifetime will be presented and the demonstration of fuzzy logic based CH selection conducted in base station (BS will also be carried out. To select suitable CHs that will prolong the network first node dies (FND round and consistent throughput to the BS, energy level and distance to the BS are selected as fuzzy inputs.

  16. Efficient Vector-Based Forwarding for Underwater Sensor Networks

    Directory of Open Access Journals (Sweden)

    Peng Xie

    2010-01-01

    Full Text Available Underwater Sensor Networks (UWSNs are significantly different from terrestrial sensor networks in the following aspects: low bandwidth, high latency, node mobility, high error probability, and 3-dimensional space. These new features bring many challenges to the network protocol design of UWSNs. In this paper, we tackle one fundamental problem in UWSNs: robust, scalable, and energy efficient routing. We propose vector-based forwarding (VBF, a geographic routing protocol. In VBF, the forwarding path is guided by a vector from the source to the target, no state information is required on the sensor nodes, and only a small fraction of the nodes is involved in routing. To improve the robustness, packets are forwarded in redundant and interleaved paths. Further, a localized and distributed self-adaptation algorithm allows the nodes to reduce energy consumption by discarding redundant packets. VBF performs well in dense networks. For sparse networks, we propose a hop-by-hop vector-based forwarding (HH-VBF protocol, which adapts the vector-based approach at every hop. We evaluate the performance of VBF and HH-VBF through extensive simulations. The simulation results show that VBF achieves high packet delivery ratio and energy efficiency in dense networks and HH-VBF has high packet delivery ratio even in sparse networks.

  17. Caries treatment in a dental practice-based research network

    DEFF Research Database (Denmark)

    Gilbert, Gregg H; Gordan, Valeria V; Funkhouser, Ellen M

    2012-01-01

    OBJECTIVES: Practice-based research networks (PBRNs) provide a venue to foster evidence-based care. We tested the hypothesis that a higher level of participation in a dental PBRN is associated with greater stated change toward evidence-based practice. METHODS: A total of 565 dental PBRN...

  18. Network Applications for Group-Based Learning: Is More Better?

    Science.gov (United States)

    Veen, Jan; Collis, Betty; Jones, Val

    2003-01-01

    Group-based learning is being introduced into many settings in higher education. Is this a sustainable development with respect to the resources required? Under what conditions can group-based learning be applied successfully in distance education and in increasingly flexible campus-based learning? Can networked support facilitate and enrich…

  19. Traffic control based on dahlin algorithm and neural network prediction in TAM networks

    Institute of Scientific and Technical Information of China (English)

    沈伟; 冯瑞; 邵惠鹤

    2004-01-01

    The propagation delay in networks has a great adverse effect on rate-based traffic control. This paper proposes the composite control based on Dab lin algorithm feedback control and neural network feedforward predictive compensation online for ABR (available bit rate) communication in ATM (asynchronous transfer mode) networks, which can overcome the adverse effect caused by the delay on the control rapidity and stability better. The theoretical analysis and simulation research show that the scheme can make sources respond to the changes of network status rapidly, avoid the congestion effectively and utilize the bandwidth sufficiently. Compared with PID (proportional-integral-derivative) control, cell loss rate is much lower, link utilization rate is much higher, and required buffer capacity is much smaller.

  20. Development of Novel Random Network Theory-Based Approaches to Identify Network Interactions among Nitrifying Bacteria

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Cindy

    2015-07-17

    The interactions among different microbial populations in a community could play more important roles in determining ecosystem functioning than species numbers and their abundances, but very little is known about such network interactions at a community level. The goal of this project is to develop novel framework approaches and associated software tools to characterize the network interactions in microbial communities based on high throughput, large scale high-throughput metagenomics data and apply these approaches to understand the impacts of environmental changes (e.g., climate change, contamination) on network interactions among different nitrifying populations and associated microbial communities.