WorldWideScience

Sample records for hybrid computer identification

  1. Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.

    Science.gov (United States)

    Zhang, Jieru; Ju, Ying; Lu, Huijuan; Xuan, Ping; Zou, Quan

    2016-01-01

    Cancerlectins are cancer-related proteins that function as lectins. They have been identified through computational identification techniques, but these techniques have sometimes failed to identify proteins because of sequence diversity among the cancerlectins. Advanced machine learning identification methods, such as support vector machine and basic sequence features (n-gram), have also been used to identify cancerlectins. In this study, various protein fingerprint features and advanced classifiers, including ensemble learning techniques, were utilized to identify this group of proteins. We improved the prediction accuracy of the original feature extraction methods and classification algorithms by more than 10% on average. Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics.

  2. Security in hybrid cloud computing

    OpenAIRE

    Koudelka, Ondřej

    2016-01-01

    This bachelor thesis deals with the area of hybrid cloud computing, specifically with its security. The major aim of the thesis is to analyze and compare the chosen hybrid cloud providers. For the minor aim this thesis compares the security challenges of hybrid cloud as opponent to other deployment models. In order to accomplish said aims, this thesis defines the terms cloud computing and hybrid cloud computing in its theoretical part. Furthermore the security challenges for cloud computing a...

  3. Analog and hybrid computing

    CERN Document Server

    Hyndman, D E

    2013-01-01

    Analog and Hybrid Computing focuses on the operations of analog and hybrid computers. The book first outlines the history of computing devices that influenced the creation of analog and digital computers. The types of problems to be solved on computers, computing systems, and digital computers are discussed. The text looks at the theory and operation of electronic analog computers, including linear and non-linear computing units and use of analog computers as operational amplifiers. The monograph examines the preparation of problems to be deciphered on computers. Flow diagrams, methods of ampl

  4. Hybrid quantum computation

    International Nuclear Information System (INIS)

    Sehrawat, Arun; Englert, Berthold-Georg; Zemann, Daniel

    2011-01-01

    We present a hybrid model of the unitary-evolution-based quantum computation model and the measurement-based quantum computation model. In the hybrid model, part of a quantum circuit is simulated by unitary evolution and the rest by measurements on star graph states, thereby combining the advantages of the two standard quantum computation models. In the hybrid model, a complicated unitary gate under simulation is decomposed in terms of a sequence of single-qubit operations, the controlled-z gates, and multiqubit rotations around the z axis. Every single-qubit and the controlled-z gate are realized by a respective unitary evolution, and every multiqubit rotation is executed by a single measurement on a required star graph state. The classical information processing in our model requires only an information flow vector and propagation matrices. We provide the implementation of multicontrol gates in the hybrid model. They are very useful for implementing Grover's search algorithm, which is studied as an illustrative example.

  5. Hybrid soft computing approaches research and applications

    CERN Document Server

    Dutta, Paramartha; Chakraborty, Susanta

    2016-01-01

    The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load Dispatch by Various Hybrid Optimization Techniques, (b) An Application of Color Magnetic Resonance Brain Image Segmentation by ParaOptiMUSIG activation Function, (c) Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis,  (d) A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms, and (e) Hybridization of 2D-3D Images for Human Face Recognition. The elaborate findings of the chapters enhance the exhibition of the hybrid soft computing paradigm in the field of intelligent computing.

  6. Checkpointing for a hybrid computing node

    Science.gov (United States)

    Cher, Chen-Yong

    2016-03-08

    According to an aspect, a method for checkpointing in a hybrid computing node includes executing a task in a processing accelerator of the hybrid computing node. A checkpoint is created in a local memory of the processing accelerator. The checkpoint includes state data to restart execution of the task in the processing accelerator upon a restart operation. Execution of the task is resumed in the processing accelerator after creating the checkpoint. The state data of the checkpoint are transferred from the processing accelerator to a main processor of the hybrid computing node while the processing accelerator is executing the task.

  7. Identification of DNA viruses by membrane filter hybridization.

    OpenAIRE

    Stålhandske, P; Pettersson, U

    1982-01-01

    The use of membrane filter hybridization for the identification of DNA viruses is described. We designed and used a procedure for identification of herpes simplex virus. This method can discriminate between herpes simplex virus types 1 and 2 in a simple way.

  8. HTTR plant dynamic simulation using a hybrid computer

    International Nuclear Information System (INIS)

    Shimazaki, Junya; Suzuki, Katsuo; Nabeshima, Kunihiko; Watanabe, Koichi; Shinohara, Yoshikuni; Nakagawa, Shigeaki.

    1990-01-01

    A plant dynamic simulation of High-Temperature Engineering Test Reactor has been made using a new-type hybrid computer. This report describes a dynamic simulation model of HTTR, a hybrid simulation method for SIMSTAR and some results obtained from dynamics analysis of HTTR simulation. It concludes that the hybrid plant simulation is useful for on-line simulation on account of its capability of computation at high speed, compared with that of all digital computer simulation. With sufficient accuracy, 40 times faster computation than real time was reached only by changing an analog time scale for HTTR simulation. (author)

  9. Hybrid computing - Generalities and bibliography

    International Nuclear Information System (INIS)

    Neel, Daniele

    1970-01-01

    This note presents the content of a research thesis. It describes the evolution of hybrid computing systems, discusses the benefits and shortcomings of analogue or hybrid systems, discusses the building up of an hybrid system (requires properties), comments different possible uses, addresses the issues of language and programming, discusses analysis methods and scopes of application. An appendix proposes a bibliography on these issues and notably the different scopes of application (simulation, fluid dynamics, biology, chemistry, electronics, energy, errors, space, programming languages, hardware, mechanics, and optimisation of equations or processes, physics) [fr

  10. Generalised Computability and Applications to Hybrid Systems

    DEFF Research Database (Denmark)

    Korovina, Margarita V.; Kudinov, Oleg V.

    2001-01-01

    We investigate the concept of generalised computability of operators and functionals defined on the set of continuous functions, firstly introduced in [9]. By working in the reals, with equality and without equality, we study properties of generalised computable operators and functionals. Also we...... propose an interesting application to formalisation of hybrid systems. We obtain some class of hybrid systems, which trajectories are computable in the sense of computable analysis. This research was supported in part by the RFBR (grants N 99-01-00485, N 00-01- 00810) and by the Siberian Branch of RAS (a...... grant for young researchers, 2000)...

  11. Computer code MLCOSP for multiple-correlation and spectrum analysis with a hybrid computer

    International Nuclear Information System (INIS)

    Oguma, Ritsuo; Fujii, Yoshio; Usui, Hozumi; Watanabe, Koichi

    1975-10-01

    Usage of the computer code MLCOSP(Multiple Correlation and Spectrum) developed is described for a hybrid computer installed in JAERI Functions of the hybrid computer and its terminal devices are utilized ingeniously in the code to reduce complexity of the data handling which occurrs in analysis of the multivariable experimental data and to perform the analysis in perspective. Features of the code are as follows; Experimental data can be fed to the digital computer through the analog part of the hybrid computer by connecting with a data recorder. The computed results are displayed in figures, and hardcopies are taken when necessary. Series-messages to the code are shown on the terminal, so man-machine communication is possible. And further the data can be put in through a keyboard, so case study according to the results of analysis is possible. (auth.)

  12. Universal blind quantum computation for hybrid system

    Science.gov (United States)

    Huang, He-Liang; Bao, Wan-Su; Li, Tan; Li, Feng-Guang; Fu, Xiang-Qun; Zhang, Shuo; Zhang, Hai-Long; Wang, Xiang

    2017-08-01

    As progress on the development of building quantum computer continues to advance, first-generation practical quantum computers will be available for ordinary users in the cloud style similar to IBM's Quantum Experience nowadays. Clients can remotely access the quantum servers using some simple devices. In such a situation, it is of prime importance to keep the security of the client's information. Blind quantum computation protocols enable a client with limited quantum technology to delegate her quantum computation to a quantum server without leaking any privacy. To date, blind quantum computation has been considered only for an individual quantum system. However, practical universal quantum computer is likely to be a hybrid system. Here, we take the first step to construct a framework of blind quantum computation for the hybrid system, which provides a more feasible way for scalable blind quantum computation.

  13. Computing all hybridization networks for multiple binary phylogenetic input trees.

    Science.gov (United States)

    Albrecht, Benjamin

    2015-07-30

    The computation of phylogenetic trees on the same set of species that are based on different orthologous genes can lead to incongruent trees. One possible explanation for this behavior are interspecific hybridization events recombining genes of different species. An important approach to analyze such events is the computation of hybridization networks. This work presents the first algorithm computing the hybridization number as well as a set of representative hybridization networks for multiple binary phylogenetic input trees on the same set of taxa. To improve its practical runtime, we show how this algorithm can be parallelized. Moreover, we demonstrate the efficiency of the software Hybroscale, containing an implementation of our algorithm, by comparing it to PIRNv2.0, which is so far the best available software computing the exact hybridization number for multiple binary phylogenetic trees on the same set of taxa. The algorithm is part of the software Hybroscale, which was developed specifically for the investigation of hybridization networks including their computation and visualization. Hybroscale is freely available(1) and runs on all three major operating systems. Our simulation study indicates that our approach is on average 100 times faster than PIRNv2.0. Moreover, we show how Hybroscale improves the interpretation of the reported hybridization networks by adding certain features to its graphical representation.

  14. Microcantilver-based DNA hybridization sensors for Salmonella identification

    Directory of Open Access Journals (Sweden)

    Carlo Ricciardi

    2012-02-01

    Full Text Available The detection of pathogenic microorganisms in foods remains a challenging since the safety of foodstuffs has to be ensured by the food producing companies. Conventional methods for the detection and identification of bacteria mainly rely on specific microbiological and biochemical identification. Biomolecular methods, are commonly used as a support for traditional techniques, thanks to their high sensitivity, specificity and not excessive costs. However, new methods like biosensors for example, can be an exciting alternative to the more traditional tecniques for the detection of pathogens in food. In this study we report Salmonella enterica serotype Enteritidis DNA detection through a novel class of label-free biosensors: microcantilevers (MCs. In general, MCs can operate as a microbalance and is used to detect the mass of the entities anchored to the cantilever surface using the decrease in the resonant frequency. We use DNA hybridization as model reaction system and for this reason, specific single stranded probe DNA of the pathogen and three different DNA targets (single-stranded complementary DNA, PCR product and serial dilutions of DNA extracted from S. Enteritidis strains were applied. Two protocols were reported in order to allow the probe immobilization on cantilever surface: i MC surface was functionalized with 3-aminopropyltriethoxysilane and glutaraldehyde and an amino-modified DNA probe was used; ii gold-coated sensors and thiolated DNA probes were used in order to generate a covalent bonding (Th-Au. For the first one, measures after hybridization with the PCR product showed related frequency shift 10 times higher than hybridization with complementary probe and detectable signals were obtained at the concentrations of 103 and 106 cfu/mL after hybridization with bacterial DNA. There are currently optimizations of the second protocol, where preliminary results have shown to be more uniform and therefore more precise within each of the

  15. Input/output routines for a hybrid computer

    International Nuclear Information System (INIS)

    Izume, Akitada; Yodo, Terutaka; Sakama, Iwao; Sakamoto, Akira; Miyake, Osamu

    1976-05-01

    This report is concerned with data processing programs for a hybrid computer system. Especially pre-data processing of magnetic tapes which are recorded during the dynamic experiment by FACOM 270/25 data logging system in the 50 MW steam generator test facility is described in detail. The magnetic tape is a most effective recording medium for data logging, but recording formats of the magnetic tape are different between data logging systems. In our section, the final data analyses are performed by data in the disk of EAI-690 hybrid computer system, and to transfer all required information in magnetic tapes to the disk, the magnetic tape editing and data transit are necessary by sub-computer NEAC-3200 system. This report is written for users as a manual and reference hand book of pre-data processing between different type computers. (auth.)

  16. Adaptation and hybridization in computational intelligence

    CERN Document Server

    Jr, Iztok

    2015-01-01

      This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI. This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence –based algorithms.  

  17. On-line identification of hybrid systems using an adaptive growing and pruning RBF neural network

    DEFF Research Database (Denmark)

    Alizadeh, Tohid

    2008-01-01

    This paper introduces an adaptive growing and pruning radial basis function (GAP-RBF) neural network for on-line identification of hybrid systems. The main idea is to identify a global nonlinear model that can predict the continuous outputs of hybrid systems. In the proposed approach, GAP......-RBF neural network uses a modified unscented kalman filter (UKF) with forgetting factor scheme as the required on-line learning algorithm. The effectiveness of the resulting identification approach is tested and evaluated on a simulated benchmark hybrid system....

  18. Identification of chaotic systems by neural network with hybrid learning algorithm

    International Nuclear Information System (INIS)

    Pan, S.-T.; Lai, C.-C.

    2008-01-01

    Based on the genetic algorithm (GA) and steepest descent method (SDM), this paper proposes a hybrid algorithm for the learning of neural networks to identify chaotic systems. The systems in question are the logistic map and the Duffing equation. Different identification schemes are used to identify both the logistic map and the Duffing equation, respectively. Simulation results show that our hybrid algorithm is more efficient than that of other methods

  19. Hybrid parallel computing architecture for multiview phase shifting

    Science.gov (United States)

    Zhong, Kai; Li, Zhongwei; Zhou, Xiaohui; Shi, Yusheng; Wang, Congjun

    2014-11-01

    The multiview phase-shifting method shows its powerful capability in achieving high resolution three-dimensional (3-D) shape measurement. Unfortunately, this ability results in very high computation costs and 3-D computations have to be processed offline. To realize real-time 3-D shape measurement, a hybrid parallel computing architecture is proposed for multiview phase shifting. In this architecture, the central processing unit can co-operate with the graphic processing unit (GPU) to achieve hybrid parallel computing. The high computation cost procedures, including lens distortion rectification, phase computation, correspondence, and 3-D reconstruction, are implemented in GPU, and a three-layer kernel function model is designed to simultaneously realize coarse-grained and fine-grained paralleling computing. Experimental results verify that the developed system can perform 50 fps (frame per second) real-time 3-D measurement with 260 K 3-D points per frame. A speedup of up to 180 times is obtained for the performance of the proposed technique using a NVIDIA GT560Ti graphics card rather than a sequential C in a 3.4 GHZ Inter Core i7 3770.

  20. Wireless Hybrid Identification and Sensing Platform for Equipment Recovery (WHISPER), Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Advanced Systems & Technologies proposed WHISPER (Wireless Hybrid Identification and Sensing Platform for Equipment Recovery) solution to NASA's need for...

  1. Wireless Hybrid Identification and Sensing Platform for Equipment Recovery (WHISPER), Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Advanced Systems & Technologies proposed WHISPER (Wireless Hybrid Identification and Sensing Platform for Equipment Recovery) solution to NASA's need for...

  2. A hybrid approach to automatic de-identification of psychiatric notes.

    Science.gov (United States)

    Lee, Hee-Jin; Wu, Yonghui; Zhang, Yaoyun; Xu, Jun; Xu, Hua; Roberts, Kirk

    2017-11-01

    De-identification, or identifying and removing protected health information (PHI) from clinical data, is a critical step in making clinical data available for clinical applications and research. This paper presents a natural language processing system for automatic de-identification of psychiatric notes, which was designed to participate in the 2016 CEGS N-GRID shared task Track 1. The system has a hybrid structure that combines machine leaning techniques and rule-based approaches. The rule-based components exploit the structure of the psychiatric notes as well as characteristic surface patterns of PHI mentions. The machine learning components utilize supervised learning with rich features. In addition, the system performance was boosted with integration of additional data to the training set through domain adaptation. The hybrid system showed overall micro-averaged F-score 90.74 on the test set, second-best among all the participants of the CEGS N-GRID task. Copyright © 2017. Published by Elsevier Inc.

  3. Deterministic linear-optics quantum computing based on a hybrid approach

    International Nuclear Information System (INIS)

    Lee, Seung-Woo; Jeong, Hyunseok

    2014-01-01

    We suggest a scheme for all-optical quantum computation using hybrid qubits. It enables one to efficiently perform universal linear-optical gate operations in a simple and near-deterministic way using hybrid entanglement as off-line resources

  4. Deterministic linear-optics quantum computing based on a hybrid approach

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seung-Woo; Jeong, Hyunseok [Center for Macroscopic Quantum Control, Department of Physics and Astronomy, Seoul National University, Seoul, 151-742 (Korea, Republic of)

    2014-12-04

    We suggest a scheme for all-optical quantum computation using hybrid qubits. It enables one to efficiently perform universal linear-optical gate operations in a simple and near-deterministic way using hybrid entanglement as off-line resources.

  5. Hybrid computer modelling in plasma physics

    International Nuclear Information System (INIS)

    Hromadka, J; Ibehej, T; Hrach, R

    2016-01-01

    Our contribution is devoted to development of hybrid modelling techniques. We investigate sheath structures in the vicinity of solids immersed in low temperature argon plasma of different pressures by means of particle and fluid computer models. We discuss the differences in results obtained by these methods and try to propose a way to improve the results of fluid models in the low pressure area. There is a possibility to employ Chapman-Enskog method to find appropriate closure relations of fluid equations in a case when particle distribution function is not Maxwellian. We try to follow this way to enhance fluid model and to use it in hybrid plasma model further. (paper)

  6. A case of dual ectopy thyroid along the thyroglossal tract demonstrated on 99mTc-Pertechnatate hybrid single photon emission computed tomography/computed tomography

    International Nuclear Information System (INIS)

    Agarwal, Krishan Kant; Karunanithi, Sellam; Jain, Sachin; Tripathi, Madhavi

    2014-01-01

    Ectopic thyroid tissue (ETT) refers to the presence of thyroid tissue in locations other than the normal anterior neck region between the second and fourth tracheal cartilages. Multiple ectopia of the thyroid is extremely rare. Here we report a case of 10-year-old girl with anterior midline neck swelling and hypothyroidism with dual ectopia of thyroid gland without orthotopic thyroid gland. Planar 99 m-technetium pertechnatate scan identified ETT corresponding to the palpable neck swelling. Single photon emission computed tomography/computed tomography (SPECT/CT) demonstrated ETT in two locations, one corresponding to the palpable mass and another in the in the sublingual location. This case thus demonstrates the important role of hybrid SPECT/CT in the identification of dual ectopia along the thyroglossal tract

  7. Genetic identification of F1 and post-F1 serrasalmid juvenile hybrids in Brazilian aquaculture.

    Directory of Open Access Journals (Sweden)

    Diogo Teruo Hashimoto

    Full Text Available Juvenile fish trade monitoring is an important task on Brazilian fish farms. However, the identification of juvenile fish through morphological analysis is not feasible, particularly between interspecific hybrids and pure species individuals, making the monitoring of these individuals difficult. Hybrids can be erroneously identified as pure species in breeding facilities, which might reduce production on farms and negatively affect native populations due to escapes or stocking practices. In the present study, we used a multi-approach analysis (molecular and cytogenetic markers to identify juveniles of three serrasalmid species (Colossoma macropomum, Piaractus mesopotamicus and Piaractus brachypomus and their hybrids in different stocks purchased from three seed producers in Brazil. The main findings of this study were the detection of intergenus backcrossing between the hybrid ♀ patinga (P. mesopotamicus×P. brachypomus×♂ C. macropomum and the occurrence of one hybrid triploid individual. This atypical specimen might result from automixis, a mechanism that produces unreduced gametes in some organisms. Moreover, molecular identification indicated that hybrid individuals are traded as pure species or other types of interspecific hybrids, particularly post-F1 individuals. These results show that serrasalmid fish genomes exhibit high genetic heterogeneity, and multi-approach methods and regulators could improve the surveillance of the production and trade of fish species and their hybrids, thereby facilitating the sustainable development of fish farming.

  8. Accelerating Climate and Weather Simulations through Hybrid Computing

    Science.gov (United States)

    Zhou, Shujia; Cruz, Carlos; Duffy, Daniel; Tucker, Robert; Purcell, Mark

    2011-01-01

    Unconventional multi- and many-core processors (e.g. IBM (R) Cell B.E.(TM) and NVIDIA (R) GPU) have emerged as effective accelerators in trial climate and weather simulations. Yet these climate and weather models typically run on parallel computers with conventional processors (e.g. Intel, AMD, and IBM) using Message Passing Interface. To address challenges involved in efficiently and easily connecting accelerators to parallel computers, we investigated using IBM's Dynamic Application Virtualization (TM) (IBM DAV) software in a prototype hybrid computing system with representative climate and weather model components. The hybrid system comprises two Intel blades and two IBM QS22 Cell B.E. blades, connected with both InfiniBand(R) (IB) and 1-Gigabit Ethernet. The system significantly accelerates a solar radiation model component by offloading compute-intensive calculations to the Cell blades. Systematic tests show that IBM DAV can seamlessly offload compute-intensive calculations from Intel blades to Cell B.E. blades in a scalable, load-balanced manner. However, noticeable communication overhead was observed, mainly due to IP over the IB protocol. Full utilization of IB Sockets Direct Protocol and the lower latency production version of IBM DAV will reduce this overhead.

  9. CSP: A Multifaceted Hybrid Architecture for Space Computing

    Science.gov (United States)

    Rudolph, Dylan; Wilson, Christopher; Stewart, Jacob; Gauvin, Patrick; George, Alan; Lam, Herman; Crum, Gary Alex; Wirthlin, Mike; Wilson, Alex; Stoddard, Aaron

    2014-01-01

    Research on the CHREC Space Processor (CSP) takes a multifaceted hybrid approach to embedded space computing. Working closely with the NASA Goddard SpaceCube team, researchers at the National Science Foundation (NSF) Center for High-Performance Reconfigurable Computing (CHREC) at the University of Florida and Brigham Young University are developing hybrid space computers that feature an innovative combination of three technologies: commercial-off-the-shelf (COTS) devices, radiation-hardened (RadHard) devices, and fault-tolerant computing. Modern COTS processors provide the utmost in performance and energy-efficiency but are susceptible to ionizing radiation in space, whereas RadHard processors are virtually immune to this radiation but are more expensive, larger, less energy-efficient, and generations behind in speed and functionality. By featuring COTS devices to perform the critical data processing, supported by simpler RadHard devices that monitor and manage the COTS devices, and augmented with novel uses of fault-tolerant hardware, software, information, and networking within and between COTS devices, the resulting system can maximize performance and reliability while minimizing energy consumption and cost. NASA Goddard has adopted the CSP concept and technology with plans underway to feature flight-ready CSP boards on two upcoming space missions.

  10. Identification of Cannabis sativa L. using the 1-kbTHCA synthase-fluorescence in situ hybridization probe.

    Science.gov (United States)

    Jeangkhwoa, Pattraporn; Bandhaya, Achirapa; Umpunjun, Puangpaka; Chuenboonngarm, Ngarmnij; Panvisavas, Nathinee

    2017-03-01

    This study reports a successful application of fluorescence in situ hybridization (FISH) technique in the identification of Cannabis sativa L. cells recovered from fresh and dried powdered plant materials. Two biotin-16-dUTP-labeled FISH probes were designed from the Cannabis-specific tetrahydrocannabinolic acid synthase (THCAS) gene and the ITS region of the 45S rRNA gene. Specificity of probe-target hybridization was tested against the target and 4 non-target plant species, i.e., Humulus lupulus, Mitragyna speciosa, Papaver sp., and Nicotiana tabacum. The 1-kb THCA synthase hybridization probe gave Cannabis-specific hybridization signals, unlike the 700-bp Cannabis-ITS hybridization probe. Probe-target hybridization was also confirmed against 20 individual Cannabis plant samples. The 1-kb THCA synthase and 700-bp Cannabis-ITS hybridization probes clearly showed 2 hybridization signals per cell with reproducibility. The 1-kb THCA synthase probe did not give any FISH signal when tested against H. lupulus, its closely related member of the Canabaceae family. It was also showed that 1-kb THCA synthase FISH probe can be applied to identify small amount of dried powdered Cannabis material with an addition of rehydration step prior to the experimental process. This study provided an alternative identification method for Cannabis trace. Copyright © 2016. Published by Elsevier B.V.

  11. Computational methods for protein identification from mass spectrometry data.

    Directory of Open Access Journals (Sweden)

    Leo McHugh

    2008-02-01

    Full Text Available Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology.

  12. A Hybrid Scheduler for Many Task Computing in Big Data Systems

    Directory of Open Access Journals (Sweden)

    Vasiliu Laura

    2017-06-01

    Full Text Available With the rapid evolution of the distributed computing world in the last few years, the amount of data created and processed has fast increased to petabytes or even exabytes scale. Such huge data sets need data-intensive computing applications and impose performance requirements to the infrastructures that support them, such as high scalability, storage, fault tolerance but also efficient scheduling algorithms. This paper focuses on providing a hybrid scheduling algorithm for many task computing that addresses big data environments with few penalties, taking into consideration the deadlines and satisfying a data dependent task model. The hybrid solution consists of several heuristics and algorithms (min-min, min-max and earliest deadline first combined in order to provide a scheduling algorithm that matches our problem. The experimental results are conducted by simulation and prove that the proposed hybrid algorithm behaves very well in terms of meeting deadlines.

  13. Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm

    International Nuclear Information System (INIS)

    Sun, Zhe; Wang, Ning; Bi, Yunrui; Srinivasan, Dipti

    2015-01-01

    In this paper, a HADE (hybrid adaptive differential evolution) algorithm is proposed for the identification problem of PEMFC (proton exchange membrane fuel cell). Inspired by biological genetic strategy, a novel adaptive scaling factor and a dynamic crossover probability are presented to improve the adaptive and dynamic performance of differential evolution algorithm. Moreover, two kinds of neighborhood search operations based on the bee colony foraging mechanism are introduced for enhancing local search efficiency. Through testing the benchmark functions, the proposed algorithm exhibits better performance in convergent accuracy and speed. Finally, the HADE algorithm is applied to identify the nonlinear parameters of PEMFC stack model. Through experimental comparison with other identified methods, the PEMFC model based on the HADE algorithm shows better performance. - Highlights: • We propose a hybrid adaptive differential evolution algorithm (HADE). • The search efficiency is enhanced in low and high dimension search space. • The effectiveness is confirmed by testing benchmark functions. • The identification of the PEMFC model is conducted by adopting HADE.

  14. Sorting through the chaff, nDNA gene trees for phylogenetic inference and hybrid identification of annual sunflowers (Helianthus sect. Helianthus).

    Science.gov (United States)

    Moody, Michael L; Rieseberg, Loren H

    2012-07-01

    The annual sunflowers (Helianthus sect. Helianthus) present a formidable challenge for phylogenetic inference because of ancient hybrid speciation, recent introgression, and suspected issues with deep coalescence. Here we analyze sequence data from 11 nuclear DNA (nDNA) genes for multiple genotypes of species within the section to (1) reconstruct the phylogeny of this group, (2) explore the utility of nDNA gene trees for detecting hybrid speciation and introgression; and (3) test an empirical method of hybrid identification based on the phylogenetic congruence of nDNA gene trees from tightly linked genes. We uncovered considerable topological heterogeneity among gene trees with or without three previously identified hybrid species included in the analyses, as well as a general lack of reciprocal monophyly of species. Nonetheless, partitioned Bayesian analyses provided strong support for the reciprocal monophyly of all species except H. annuus (0.89 PP), the most widespread and abundant annual sunflower. Previous hypotheses of relationships among taxa were generally strongly supported (1.0 PP), except among taxa typically associated with H. annuus, apparently due to the paraphyly of the latter in all gene trees. While the individual nDNA gene trees provided a useful means for detecting recent hybridization, identification of ancient hybridization was problematic for all ancient hybrid species, even when linkage was considered. We discuss biological factors that affect the efficacy of phylogenetic methods for hybrid identification.

  15. Chromosome identification by new molecular markers and genomic in situ hybridization in the Triticum-Secale-Thinopyrum trigeneric hybrids.

    Science.gov (United States)

    Dai, Yi; Duan, Yamei; Chi, Dawn; Liu, Huiping; Huang, Shuai; Cao, Wenguang; Gao, Yong; Fedak, George; Chen, Jianmin

    2017-08-01

    It is very important to use chromosome-specific markers for identifying alien chromosomes in advanced generations of distant hybridization. The chromosome-specific markers of rye and Thinopyrum elongatum, as well as genomic in situ hybridization, were used to identify the alien chromosomes in eight lines that were derived from the crossing between Triticum trititrigia (AABBEE) and triticale (AABBRR). The results showed that four lines contained all rye chromosomes but no Th. elongatum chromosomes. The line RE36-1 contained all of the rye chromosomes except for chromosome 2R. The lines RE33-2 and RE62-1 contained all rye chromosomes and 1E and 5E translocated chromosome, respectively. The line RE24-4 contained 12 rye chromosomes plus a 7E chromosome or 12 rye chromosomes plus one R-E translocated chromosome. Chromosome identification in the above lines was consistent using chromosome-specific markers and genomic in situ hybridization. These chromosome-specific markers provide useful tools for detecting alien chromosomes in trigeneric hybrids, and these lines could be utilized as valuable germplasm in wheat improvement.

  16. Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing.

    Science.gov (United States)

    Kim, Hyunjun; Lee, Junhwa; Ahn, Eunjong; Cho, Soojin; Shin, Myoungsu; Sim, Sung-Han

    2017-09-07

    Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%.

  17. Hybrid computer optimization of systems with random parameters

    Science.gov (United States)

    White, R. C., Jr.

    1972-01-01

    A hybrid computer Monte Carlo technique for the simulation and optimization of systems with random parameters is presented. The method is applied to the simultaneous optimization of the means and variances of two parameters in the radar-homing missile problem treated by McGhee and Levine.

  18. Three-dimensional pseudo-random number generator for implementing in hybrid computer systems

    International Nuclear Information System (INIS)

    Ivanov, M.A.; Vasil'ev, N.P.; Voronin, A.V.; Kravtsov, M.Yu.; Maksutov, A.A.; Spiridonov, A.A.; Khudyakova, V.I.; Chugunkov, I.V.

    2012-01-01

    The algorithm for generating pseudo-random numbers oriented to implementation by using hybrid computer systems is considered. The proposed solution is characterized by a high degree of parallel computing [ru

  19. A hybrid approach to parameter identification of linear delay differential equations involving multiple delays

    Science.gov (United States)

    Marzban, Hamid Reza

    2018-05-01

    In this paper, we are concerned with the parameter identification of linear time-invariant systems containing multiple delays. The approach is based upon a hybrid of block-pulse functions and Legendre's polynomials. The convergence of the proposed procedure is established and an upper error bound with respect to the L2-norm associated with the hybrid functions is derived. The problem under consideration is first transformed into a system of algebraic equations. The least squares technique is then employed for identification of the desired parameters. Several multi-delay systems of varying complexity are investigated to evaluate the performance and capability of the proposed approximation method. It is shown that the proposed approach is also applicable to a class of nonlinear multi-delay systems. It is demonstrated that the suggested procedure provides accurate results for the desired parameters.

  20. Energy efficient hybrid computing systems using spin devices

    Science.gov (United States)

    Sharad, Mrigank

    Emerging spin-devices like magnetic tunnel junctions (MTJ's), spin-valves and domain wall magnets (DWM) have opened new avenues for spin-based logic design. This work explored potential computing applications which can exploit such devices for higher energy-efficiency and performance. The proposed applications involve hybrid design schemes, where charge-based devices supplement the spin-devices, to gain large benefits at the system level. As an example, lateral spin valves (LSV) involve switching of nanomagnets using spin-polarized current injection through a metallic channel such as Cu. Such spin-torque based devices possess several interesting properties that can be exploited for ultra-low power computation. Analog characteristic of spin current facilitate non-Boolean computation like majority evaluation that can be used to model a neuron. The magneto-metallic neurons can operate at ultra-low terminal voltage of ˜20mV, thereby resulting in small computation power. Moreover, since nano-magnets inherently act as memory elements, these devices can facilitate integration of logic and memory in interesting ways. The spin based neurons can be integrated with CMOS and other emerging devices leading to different classes of neuromorphic/non-Von-Neumann architectures. The spin-based designs involve `mixed-mode' processing and hence can provide very compact and ultra-low energy solutions for complex computation blocks, both digital as well as analog. Such low-power, hybrid designs can be suitable for various data processing applications like cognitive computing, associative memory, and currentmode on-chip global interconnects. Simulation results for these applications based on device-circuit co-simulation framework predict more than ˜100x improvement in computation energy as compared to state of the art CMOS design, for optimal spin-device parameters.

  1. Hybrid Computational Model for High-Altitude Aeroassist Vehicles, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — A hybrid continuum/noncontinuum computational model will be developed for analyzing the aerodynamics and heating on aeroassist vehicles. Unique features of this...

  2. Computational botany methods for automated species identification

    CERN Document Server

    Remagnino, Paolo; Wilkin, Paul; Cope, James; Kirkup, Don

    2017-01-01

    This book discusses innovative methods for mining information from images of plants, especially leaves, and highlights the diagnostic features that can be implemented in fully automatic systems for identifying plant species. Adopting a multidisciplinary approach, it explores the problem of plant species identification, covering both the concepts of taxonomy and morphology. It then provides an overview of morphometrics, including the historical background and the main steps in the morphometric analysis of leaves together with a number of applications. The core of the book focuses on novel diagnostic methods for plant species identification developed from a computer scientist’s perspective. It then concludes with a chapter on the characterization of botanists' visions, which highlights important cognitive aspects that can be implemented in a computer system to more accurately replicate the human expert’s fixation process. The book not only represents an authoritative guide to advanced computational tools fo...

  3. Accelerating Climate Simulations Through Hybrid Computing

    Science.gov (United States)

    Zhou, Shujia; Sinno, Scott; Cruz, Carlos; Purcell, Mark

    2009-01-01

    Unconventional multi-core processors (e.g., IBM Cell B/E and NYIDIDA GPU) have emerged as accelerators in climate simulation. However, climate models typically run on parallel computers with conventional processors (e.g., Intel and AMD) using MPI. Connecting accelerators to this architecture efficiently and easily becomes a critical issue. When using MPI for connection, we identified two challenges: (1) identical MPI implementation is required in both systems, and; (2) existing MPI code must be modified to accommodate the accelerators. In response, we have extended and deployed IBM Dynamic Application Virtualization (DAV) in a hybrid computing prototype system (one blade with two Intel quad-core processors, two IBM QS22 Cell blades, connected with Infiniband), allowing for seamlessly offloading compute-intensive functions to remote, heterogeneous accelerators in a scalable, load-balanced manner. Currently, a climate solar radiation model running with multiple MPI processes has been offloaded to multiple Cell blades with approx.10% network overhead.

  4. Evaluation of a Compact Hybrid Brain-Computer Interface System

    Directory of Open Access Journals (Sweden)

    Jaeyoung Shin

    2017-01-01

    Full Text Available We realized a compact hybrid brain-computer interface (BCI system by integrating a portable near-infrared spectroscopy (NIRS device with an economical electroencephalography (EEG system. The NIRS array was located on the subjects’ forehead, covering the prefrontal area. The EEG electrodes were distributed over the frontal, motor/temporal, and parietal areas. The experimental paradigm involved a Stroop word-picture matching test in combination with mental arithmetic (MA and baseline (BL tasks, in which the subjects were asked to perform either MA or BL in response to congruent or incongruent conditions, respectively. We compared the classification accuracies of each of the modalities (NIRS or EEG with that of the hybrid system. We showed that the hybrid system outperforms the unimodal EEG and NIRS systems by 6.2% and 2.5%, respectively. Since the proposed hybrid system is based on portable platforms, it is not confined to a laboratory environment and has the potential to be used in real-life situations, such as in neurorehabilitation.

  5. Reducing the Digital Divide among Children Who Received Desktop or Hybrid Computers for the Home

    Directory of Open Access Journals (Sweden)

    Gila Cohen Zilka

    2016-06-01

    Full Text Available Researchers and policy makers have been exploring ways to reduce the digital divide. Parameters commonly used to examine the digital divide worldwide, as well as in this study, are: (a the digital divide in the accessibility and mobility of the ICT infrastructure and of the content infrastructure (e.g., sites used in school; and (b the digital divide in literacy skills. In the present study we examined the degree of effectiveness of receiving a desktop or hybrid computer for the home in reducing the digital divide among children of low socio-economic status aged 8-12 from various localities across Israel. The sample consisted of 1,248 respondents assessed in two measurements. As part of the mixed-method study, 128 children were also interviewed. Findings indicate that after the children received desktop or hybrid computers, changes occurred in their frequency of access, mobility, and computer literacy. Differences were found between the groups: hybrid computers reduce disparities and promote work with the computer and surfing the Internet more than do desktop computers. Narrowing the digital divide for this age group has many implications for the acquisition of skills and study habits, and consequently, for the realization of individual potential. The children spoke about self improvement as a result of exposure to the digital environment, about a sense of empowerment and of improvement in their advantage in the social fabric. Many children expressed a desire to continue their education and expand their knowledge of computer applications, the use of software, of games, and more. Therefore, if there is no computer in the home and it is necessary to decide between a desktop and a hybrid computer, a hybrid computer is preferable.

  6. General hybrid projective complete dislocated synchronization with non-derivative and derivative coupling based on parameter identification in several chaotic and hyperchaotic systems

    International Nuclear Information System (INIS)

    Sun Jun-Wei; Shen Yi; Zhang Guo-Dong; Wang Yan-Feng; Cui Guang-Zhao

    2013-01-01

    According to the Lyapunov stability theorem, a new general hybrid projective complete dislocated synchronization scheme with non-derivative and derivative coupling based on parameter identification is proposed under the framework of drive-response systems. Every state variable of the response system equals the summation of the hybrid drive systems in the previous hybrid synchronization. However, every state variable of the drive system equals the summation of the hybrid response systems while evolving with time in our method. Complete synchronization, hybrid dislocated synchronization, projective synchronization, non-derivative and derivative coupling, and parameter identification are included as its special item. The Lorenz chaotic system, Rössler chaotic system, memristor chaotic oscillator system, and hyperchaotic Lü system are discussed to show the effectiveness of the proposed methods. (general)

  7. A Cost–Effective Computer-Based, Hybrid Motorised and Gravity ...

    African Journals Online (AJOL)

    A Cost–Effective Computer-Based, Hybrid Motorised and Gravity-Driven Material Handling System for the Mauritian Apparel Industry. ... Thus, many companies are investing significantly in a Research & Development department in order to design new techniques to improve worker's efficiency, and to decrease the amount ...

  8. Parameters identification and adaptive full state hybrid projective synchronization of chaotic (hyper-chaotic) systems

    International Nuclear Information System (INIS)

    Hu Manfeng; Xu Zhenyuan; Zhang Rong; Hu Aihua

    2007-01-01

    Based on the active control idea and the invariance principle of differential equations, a general scheme of adaptive full state hybrid projective synchronization (FSHPS) and parameters identification of a class of chaotic (hyper-chaotic) systems with linearly dependent uncertain parameters is proposed in this Letter. With this effective scheme parameters identification and FSHPS of chaotic and hyper-chaotic systems can be realized simultaneously. Numerical simulations on the chaotic Chen system and the hyper-chaotic Chen system are presented to verify the effectiveness of the proposed scheme

  9. Creation of hybrid optoelectronic systems for document identification

    Science.gov (United States)

    Muravsky, Leonid I.; Voronyak, Taras I.; Kulynych, Yaroslav P.; Maksymenko, Olexander P.; Pogan, Ignat Y.

    2001-06-01

    Use of security devices based on a joint transform correlator (JTC) architecture for identification of credit cards and other products is very promising. The experimental demonstration of the random phase encoding technique for security verification shows that hybrid JTCs can be successfully utilized. The random phase encoding technique provides a very high protection level of products and things to be identified. However, the realization of this technique is connected with overcoming of the certain practical problems. To solve some of these problems and simultaneously to improve the security of documents and other products, we propose to use a transformed phase mask (TPM) as an input object in an optical correlator. This mask is synthesized from a random binary pattern (RBP), which is directly used to fabricate a reference phase mask (RPM). To obtain the TPM, we previously separate the RBP on a several parts (for example, K parts) of an arbitrary shape and further fabricate the TPM from this transformed RBP. The fabricated TPM can be bonded as the optical mark to any product or thing to be identified. If the RPM and the TPM are placed on the optical correlator input, the first diffracted order of the output correlation signal is containing the K narrow autocorrelation peaks. The distances between the peaks and the peak's intensities can be treated as the terms of the identification feature vector (FV) for the TPM identification.

  10. A Review of Hybrid Brain-Computer Interface Systems

    Directory of Open Access Journals (Sweden)

    Setare Amiri

    2013-01-01

    Full Text Available Increasing number of research activities and different types of studies in brain-computer interface (BCI systems show potential in this young research area. Research teams have studied features of different data acquisition techniques, brain activity patterns, feature extraction techniques, methods of classifications, and many other aspects of a BCI system. However, conventional BCIs have not become totally applicable, due to the lack of high accuracy, reliability, low information transfer rate, and user acceptability. A new approach to create a more reliable BCI that takes advantage of each system is to combine two or more BCI systems with different brain activity patterns or different input signal sources. This type of BCI, called hybrid BCI, may reduce disadvantages of each conventional BCI system. In addition, hybrid BCIs may create more applications and possibly increase the accuracy and the information transfer rate. However, the type of BCIs and their combinations should be considered carefully. In this paper, after introducing several types of BCIs and their combinations, we review and discuss hybrid BCIs, different possibilities to combine them, and their advantages and disadvantages.

  11. Identification of bester hybrid and its parental species (♀ Huso huso Linnaeus, 1758 and ♂ Acipenser ruthenus Linnaeus, 1758 by nuclear markers

    Directory of Open Access Journals (Sweden)

    Andreea Dudu

    2015-05-01

    Full Text Available In Romania, sturgeon farming is gaining advance, different species being raised for commercial purposes and for restocking activities. A correct identification of individuals is imposed since severe ecological damages might occur if non-native species or hybrids are used for restocking. Such identification is required also for commercial reasons, the meat and caviar from different species having different prices. The aim of our study was to analyze two sturgeon species, Huso huso and Acipenser ruthenus and their interspecific hybrid - bester, using nuclear markers, in order to set up a molecular method for their accurate identification. The genetic pattern of the species was inferred from the analysis of nine microsatellite loci (LS19, LS34, LS39, LS54, AoxD234, AnacC11, LS68, Aox45 and Aox27 amplified by multiplex PCR reactions. The genotype data were analyzed with GENETIX v4.05 and STRUCTURE. The FCA analysis grouped the individuals in three distinct clusters corresponding to each of the pure species and to the interspecific hybrids. The admixture analysis performed in STRUCTURE also assigned three groups, confirming the results highlighted by FCA. We can conclude that the selected microsatellite markers allow the unambiguously identification of the bester hybrid and its genitor species from Romanian farms.

  12. Computational hybrid anthropometric paediatric phantom library for internal radiation dosimetry

    DEFF Research Database (Denmark)

    Xie, Tianwu; Kuster, Niels; Zaidi, Habib

    2017-01-01

    for children demonstrated that they follow the same trend when correlated with age. The constructed hybrid computational phantom library opens up the prospect of comprehensive radiation dosimetry calculations and risk assessment for the paediatric population of different age groups and diverse anthropometric...

  13. Hybrid Cloud Computing Environment for EarthCube and Geoscience Community

    Science.gov (United States)

    Yang, C. P.; Qin, H.

    2016-12-01

    The NSF EarthCube Integration and Test Environment (ECITE) has built a hybrid cloud computing environment to provides cloud resources from private cloud environments by using cloud system software - OpenStack and Eucalyptus, and also manages public cloud - Amazon Web Service that allow resource synchronizing and bursting between private and public cloud. On ECITE hybrid cloud platform, EarthCube and geoscience community can deploy and manage the applications by using base virtual machine images or customized virtual machines, analyze big datasets by using virtual clusters, and real-time monitor the virtual resource usage on the cloud. Currently, a number of EarthCube projects have deployed or started migrating their projects to this platform, such as CHORDS, BCube, CINERGI, OntoSoft, and some other EarthCube building blocks. To accomplish the deployment or migration, administrator of ECITE hybrid cloud platform prepares the specific needs (e.g. images, port numbers, usable cloud capacity, etc.) of each project in advance base on the communications between ECITE and participant projects, and then the scientists or IT technicians in those projects launch one or multiple virtual machines, access the virtual machine(s) to set up computing environment if need be, and migrate their codes, documents or data without caring about the heterogeneity in structure and operations among different cloud platforms.

  14. Hybrid computer simulation of the dynamics of the Hoger Onderwijs Reactor

    International Nuclear Information System (INIS)

    Moers, J.C.; Vries, J.W. de.

    1976-01-01

    A distributed parameter model for the dynamics of the Hoger Onderwijs Reactor (HOR) at Delft is presented. The neutronic and the thermodynamic part of this model have been separately implemented on the AD4-IBM1800 Hybrid Computer of the Delft University of Technology Computation Centre. A continuous Space/Discrete Time solution method has been employed. Some test results of the simulation are included

  15. Fatigue of hybrid glass/carbon composites: 3D computational studies

    DEFF Research Database (Denmark)

    Dai, Gaoming; Mishnaevsky, Leon

    2014-01-01

    3D computational simulations of fatigue of hybrid carbon/glass fiber reinforced composites is carried out using X-FEM and multifiber unit cell models. A new software code for the automatic generation of unit cell multifiber models of composites with randomly misaligned fibers of various properties...... and geometrical parameters is developed. With the use of this program code and the X-FEM method, systematic investigations of the effect of microstructure of hybrid composites (fraction of carbon versus glass fibers, misalignment, and interface strength) and the loading conditions (tensile versus compression...... cyclic loading effects) on fatigue behavior of the materials are carried out. It was demonstrated that the higher fraction of carbon fibers in hybrid composites is beneficial for the fatigue lifetime of the composites under tension-tension cyclic loading, but might have negative effect on the lifetime...

  16. Workflow Scheduling Using Hybrid GA-PSO Algorithm in Cloud Computing

    Directory of Open Access Journals (Sweden)

    Ahmad M. Manasrah

    2018-01-01

    Full Text Available Cloud computing environment provides several on-demand services and resource sharing for clients. Business processes are managed using the workflow technology over the cloud, which represents one of the challenges in using the resources in an efficient manner due to the dependencies between the tasks. In this paper, a Hybrid GA-PSO algorithm is proposed to allocate tasks to the resources efficiently. The Hybrid GA-PSO algorithm aims to reduce the makespan and the cost and balance the load of the dependent tasks over the heterogonous resources in cloud computing environments. The experiment results show that the GA-PSO algorithm decreases the total execution time of the workflow tasks, in comparison with GA, PSO, HSGA, WSGA, and MTCT algorithms. Furthermore, it reduces the execution cost. In addition, it improves the load balancing of the workflow application over the available resources. Finally, the obtained results also proved that the proposed algorithm converges to optimal solutions faster and with higher quality compared to other algorithms.

  17. 48 CFR 227.7203-10 - Contractor identification and marking of computer software or computer software documentation to...

    Science.gov (United States)

    2010-10-01

    ... operation of the software to display a restrictive rights legend or other license notice; and (2) Requires a... and marking of computer software or computer software documentation to be furnished with restrictive... Rights in Computer Software and Computer Software Documentation 227.7203-10 Contractor identification and...

  18. Autonomic Management of Application Workflows on Hybrid Computing Infrastructure

    Directory of Open Access Journals (Sweden)

    Hyunjoo Kim

    2011-01-01

    Full Text Available In this paper, we present a programming and runtime framework that enables the autonomic management of complex application workflows on hybrid computing infrastructures. The framework is designed to address system and application heterogeneity and dynamics to ensure that application objectives and constraints are satisfied. The need for such autonomic system and application management is becoming critical as computing infrastructures become increasingly heterogeneous, integrating different classes of resources from high-end HPC systems to commodity clusters and clouds. For example, the framework presented in this paper can be used to provision the appropriate mix of resources based on application requirements and constraints. The framework also monitors the system/application state and adapts the application and/or resources to respond to changing requirements or environment. To demonstrate the operation of the framework and to evaluate its ability, we employ a workflow used to characterize an oil reservoir executing on a hybrid infrastructure composed of TeraGrid nodes and Amazon EC2 instances of various types. Specifically, we show how different applications objectives such as acceleration, conservation and resilience can be effectively achieved while satisfying deadline and budget constraints, using an appropriate mix of dynamically provisioned resources. Our evaluations also demonstrate that public clouds can be used to complement and reinforce the scheduling and usage of traditional high performance computing infrastructure.

  19. Computational hybrid anthropometric paediatric phantom library for internal radiation dosimetry

    Science.gov (United States)

    Xie, Tianwu; Kuster, Niels; Zaidi, Habib

    2017-04-01

    Hybrid computational phantoms combine voxel-based and simplified equation-based modelling approaches to provide unique advantages and more realism for the construction of anthropomorphic models. In this work, a methodology and C++ code are developed to generate hybrid computational phantoms covering statistical distributions of body morphometry in the paediatric population. The paediatric phantoms of the Virtual Population Series (IT’IS Foundation, Switzerland) were modified to match target anthropometric parameters, including body mass, body length, standing height and sitting height/stature ratio, determined from reference databases of the National Centre for Health Statistics and the National Health and Nutrition Examination Survey. The phantoms were selected as representative anchor phantoms for the newborn, 1, 2, 5, 10 and 15 years-old children, and were subsequently remodelled to create 1100 female and male phantoms with 10th, 25th, 50th, 75th and 90th body morphometries. Evaluation was performed qualitatively using 3D visualization and quantitatively by analysing internal organ masses. Overall, the newly generated phantoms appear very reasonable and representative of the main characteristics of the paediatric population at various ages and for different genders, body sizes and sitting stature ratios. The mass of internal organs increases with height and body mass. The comparison of organ masses of the heart, kidney, liver, lung and spleen with published autopsy and ICRP reference data for children demonstrated that they follow the same trend when correlated with age. The constructed hybrid computational phantom library opens up the prospect of comprehensive radiation dosimetry calculations and risk assessment for the paediatric population of different age groups and diverse anthropometric parameters.

  20. Identification of computer graphics objects

    Directory of Open Access Journals (Sweden)

    Rossinskyi Yu.M.

    2016-04-01

    Full Text Available The article is devoted to the use of computer graphics methods in problems of creating drawings, charts, drafting, etc. The widespread use of these methods requires the development of efficient algorithms for the identification of objects of drawings. The article analyzes the model-making algorithms for this problem and considered the possibility of reducing the time using graphics editing operations. Editing results in such operations as copying, moving and deleting objects specified images. These operations allow the use of a reliable identification of images of objects methods. For information on the composition of the image of the object along with information about the identity and the color should include information about the spatial location and other characteristics of the object (the thickness and style of contour lines, fill style, and so on. In order to enable the pixel image analysis to structure the information it is necessary to enable the initial code image objects color. The article shows the results of the implementation of the algorithm of encoding object identifiers. To simplify the process of building drawings of any kind, and reduce time-consuming, method of drawing objects identification is proposed based on the use as the ID information of the object color.

  1. Study of an analog/logic processor for the design of an auto patch hybrid computer

    International Nuclear Information System (INIS)

    Koched, Hassen

    1976-01-01

    This paper presents the experimental study of an analog multiprocessor designed at SES/CEN-Saclay. An application of such a device as a basic component of an auto-patch hybrid computer is presented. First, the description of the processor, and a presentation of the theoretical concepts which governed the design of the processor are given. Experiments on an hybrid computer are then presented. Finally, different systems of automatic patching are presented, and conveniently modified, for the use of such a processor. (author) [fr

  2. An approach for identification of unknown viruses using sequencing-by-hybridization.

    Science.gov (United States)

    Katoski, Sarah E; Meyer, Hermann; Ibrahim, Sofi

    2015-09-01

    Accurate identification of biological threat agents, especially RNA viruses, in clinical or environmental samples can be challenging because the concentration of viral genomic material in a given sample is usually low, viral genomic RNA is liable to degradation, and RNA viruses are extremely diverse. A two-tiered approach was used for initial identification, then full genomic characterization of 199 RNA viruses belonging to virus families Arenaviridae, Bunyaviridae, Filoviridae, Flaviviridae, and Togaviridae. A Sequencing-by-hybridization (SBH) microarray was used to tentatively identify a viral pathogen then, the identity is confirmed by guided next-generation sequencing (NGS). After optimization and evaluation of the SBH and NGS methodologies with various virus species and strains, the approach was used to test the ability to identify viruses in blinded samples. The SBH correctly identified two Ebola viruses in the blinded samples within 24 hr, and by using guided amplicon sequencing with 454 GS FLX, the identities of the viruses in both samples were confirmed. SBH provides at relatively low-cost screening of biological samples against a panel of viral pathogens that can be custom-designed on a microarray. Once the identity of virus is deduced from the highest hybridization signal on the SBH microarray, guided (amplicon) NGS sequencing can be used not only to confirm the identity of the virus but also to provide further information about the strain or isolate, including a potential genetic manipulation. This approach can be useful in situations where natural or deliberate biological threat incidents might occur and a rapid response is required. © 2015 Wiley Periodicals, Inc.

  3. Implementing Molecular Dynamics for Hybrid High Performance Computers - 1. Short Range Forces

    International Nuclear Information System (INIS)

    Brown, W. Michael; Wang, Peng; Plimpton, Steven J.; Tharrington, Arnold N.

    2011-01-01

    The use of accelerators such as general-purpose graphics processing units (GPGPUs) have become popular in scientific computing applications due to their low cost, impressive floating-point capabilities, high memory bandwidth, and low electrical power requirements. Hybrid high performance computers, machines with more than one type of floating-point processor, are now becoming more prevalent due to these advantages. In this work, we discuss several important issues in porting a large molecular dynamics code for use on parallel hybrid machines - (1) choosing a hybrid parallel decomposition that works on central processing units (CPUs) with distributed memory and accelerator cores with shared memory, (2) minimizing the amount of code that must be ported for efficient acceleration, (3) utilizing the available processing power from both many-core CPUs and accelerators, and (4) choosing a programming model for acceleration. We present our solution to each of these issues for short-range force calculation in the molecular dynamics package LAMMPS. We describe algorithms for efficient short range force calculation on hybrid high performance machines. We describe a new approach for dynamic load balancing of work between CPU and accelerator cores. We describe the Geryon library that allows a single code to compile with both CUDA and OpenCL for use on a variety of accelerators. Finally, we present results on a parallel test cluster containing 32 Fermi GPGPUs and 180 CPU cores.

  4. Identification of natural images and computer-generated graphics based on statistical and textural features.

    Science.gov (United States)

    Peng, Fei; Li, Jiao-ting; Long, Min

    2015-03-01

    To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer-generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer-generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer-generated graphics. © 2014 American Academy of Forensic Sciences.

  5. Hybrid soft computing systems for electromyographic signals analysis: a review.

    Science.gov (United States)

    Xie, Hong-Bo; Guo, Tianruo; Bai, Siwei; Dokos, Socrates

    2014-02-03

    Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis.

  6. Hybrid computational phantoms of the male and female newborn patient: NURBS-based whole-body models

    International Nuclear Information System (INIS)

    Lee, Choonsik; Lodwick, Daniel; Hasenauer, Deanna; Williams, Jonathan L; Lee, Choonik; Bolch, Wesley E

    2007-01-01

    Anthropomorphic computational phantoms are computer models of the human body for use in the evaluation of dose distributions resulting from either internal or external radiation sources. Currently, two classes of computational phantoms have been developed and widely utilized for organ dose assessment: (1) stylized phantoms and (2) voxel phantoms which describe the human anatomy via mathematical surface equations or 3D voxel matrices, respectively. Although stylized phantoms based on mathematical equations can be very flexible in regard to making changes in organ position and geometrical shape, they are limited in their ability to fully capture the anatomic complexities of human internal anatomy. In turn, voxel phantoms have been developed through image-based segmentation and correspondingly provide much better anatomical realism in comparison to simpler stylized phantoms. However, they themselves are limited in defining organs presented in low contrast within either magnetic resonance or computed tomography images-the two major sources in voxel phantom construction. By definition, voxel phantoms are typically constructed via segmentation of transaxial images, and thus while fine anatomic features are seen in this viewing plane, slice-to-slice discontinuities become apparent in viewing the anatomy of voxel phantoms in the sagittal or coronal planes. This study introduces the concept of a hybrid computational newborn phantom that takes full advantage of the best features of both its stylized and voxel counterparts: flexibility in phantom alterations and anatomic realism. Non-uniform rational B-spline (NURBS) surfaces, a mathematical modeling tool traditionally applied to graphical animation studies, was adopted to replace the limited mathematical surface equations of stylized phantoms. A previously developed whole-body voxel phantom of the newborn female was utilized as a realistic anatomical framework for hybrid phantom construction. The construction of a hybrid

  7. Modelling the WWER-type reactor dynamics using a hybrid computer. Part 1

    International Nuclear Information System (INIS)

    Karpeta, C.

    Results of simulation studies into reactor and steam generator dynamics of a WWER type power plant are presented. Spatial kinetics of the reactor core is described by a nodal approximation to diffusion equations, xenon poisoning equations and heat transfer equations. The simulation of the reactor model dynamics was performed on a hybrid computer. Models of both a horizontal and a vertical steam generator were developed. The dynamics was investigated over a large range of power by computing the transients on a digital computer. (author)

  8. Carbon nanotube reinforced hybrid composites: Computational modeling of environmental fatigue and usability for wind blades

    DEFF Research Database (Denmark)

    Dai, Gaoming; Mishnaevsky, Leon

    2015-01-01

    The potential of advanced carbon/glass hybrid reinforced composites with secondary carbon nanotube reinforcement for wind energy applications is investigated here with the use of computational experiments. Fatigue behavior of hybrid as well as glass and carbon fiber reinforced composites...... with the secondary CNT reinforcements (especially, aligned tubes) present superior fatigue performances than those without reinforcements, also under combined environmental and cyclic mechanical loading. This effect is stronger for carbon composites, than for hybrid and glass composites....

  9. A Semiactive and Adaptive Hybrid Control System for a Tracked Vehicle Hydropneumatic Suspension Based on Disturbance Identification

    Directory of Open Access Journals (Sweden)

    Shousong Han

    2017-01-01

    Full Text Available The riding conditions for a high-speed tracked vehicle are quite complex. To enhance the adaptability of suspension systems to different riding conditions, a semiactive and self-adaptive hybrid control strategy based on disturbance velocity and frequency identification was proposed. A mathematical model of the semiactive, self-adaptive hybrid suspension control system, along with a performance evaluation function, was established. Based on a two-degree-of-freedom (DOF suspension system, the kinematic relations and frequency zero-crossing detection method were defined, and expressions for the disturbance velocity and disturbance frequency of the road were obtained. Optimal scheduling of the semiactive hybrid damping control gain (csky, cground, chybrid and self-adaptive control gain (cv under different disturbances were realized by exploiting the particle swarm multiobjective optimization algorithm. An experimental study using a carefully designed test rig was performed under a number of typical riding conditions of tracked vehicles, and the results showed that the proposed control strategy is capable of accurately recognizing different disturbances, shifting between control modes (semiactive/self-adaptive, and scheduling the damping control gain according to the disturbance identification outcomes; hence, the proposed strategy could achieve a good trade-off between ride comfort and ride safety and efficiently increase the overall performance of the suspension under various riding conditions.

  10. Hybrid soft computing systems for electromyographic signals analysis: a review

    Science.gov (United States)

    2014-01-01

    Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis. PMID:24490979

  11. OPTHYLIC: An Optimised Tool for Hybrid Limits Computation

    Science.gov (United States)

    Busato, Emmanuel; Calvet, David; Theveneaux-Pelzer, Timothée

    2018-05-01

    A software tool, computing observed and expected upper limits on Poissonian process rates using a hybrid frequentist-Bayesian CLs method, is presented. This tool can be used for simple counting experiments where only signal, background and observed yields are provided or for multi-bin experiments where binned distributions of discriminating variables are provided. It allows the combination of several channels and takes into account statistical and systematic uncertainties, as well as correlations of systematic uncertainties between channels. It has been validated against other software tools and analytical calculations, for several realistic cases.

  12. Identification of a novel interspecific hybrid yeast from a metagenomic spontaneously inoculated beer sample using Hi-C.

    Science.gov (United States)

    Smukowski Heil, Caiti; Burton, Joshua N; Liachko, Ivan; Friedrich, Anne; Hanson, Noah A; Morris, Cody L; Schacherer, Joseph; Shendure, Jay; Thomas, James H; Dunham, Maitreya J

    2018-01-01

    Interspecific hybridization is a common mechanism enabling genetic diversification and adaptation; however, the detection of hybrid species has been quite difficult. The identification of microbial hybrids is made even more complicated, as most environmental microbes are resistant to culturing and must be studied in their native mixed communities. We have previously adapted the chromosome conformation capture method Hi-C to the assembly of genomes from mixed populations. Here, we show the method's application in assembling genomes directly from an uncultured, mixed population from a spontaneously inoculated beer sample. Our assembly method has enabled us to de-convolute four bacterial and four yeast genomes from this sample, including a putative yeast hybrid. Downstream isolation and analysis of this hybrid confirmed its genome to consist of Pichia membranifaciens and that of another related, but undescribed, yeast. Our work shows that Hi-C-based metagenomic methods can overcome the limitation of traditional sequencing methods in studying complex mixtures of genomes. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  13. A hybrid source-driven method to compute fast neutron fluence in reactor pressure vessel - 017

    International Nuclear Information System (INIS)

    Ren-Tai, Chiang

    2010-01-01

    A hybrid source-driven method is developed to compute fast neutron fluence with neutron energy greater than 1 MeV in nuclear reactor pressure vessel (RPV). The method determines neutron flux by solving a steady-state neutron transport equation with hybrid neutron sources composed of peripheral fixed fission neutron sources and interior chain-reacted fission neutron sources. The relative rod-by-rod power distribution of the peripheral assemblies in a nuclear reactor obtained from reactor core depletion calculations and subsequent rod-by-rod power reconstruction is employed as the relative rod-by-rod fixed fission neutron source distribution. All fissionable nuclides other than U-238 (such as U-234, U-235, U-236, Pu-239 etc) are replaced with U-238 to avoid counting the fission contribution twice and to preserve fast neutron attenuation for heavy nuclides in the peripheral assemblies. An example is provided to show the feasibility of the method. Since the interior fuels only have a marginal impact on RPV fluence results due to rapid attenuation of interior fast fission neutrons, a generic set or one of several generic sets of interior fuels can be used as the driver and only the neutron sources in the peripheral assemblies will be changed in subsequent hybrid source-driven fluence calculations. Consequently, this hybrid source-driven method can simplify and reduce cost for fast neutron fluence computations. This newly developed hybrid source-driven method should be a useful and simplified tool for computing fast neutron fluence at selected locations of interest in RPV of contemporary nuclear power reactors. (authors)

  14. Innovative molecular approach to the identification of Colossoma macropomum and its hybrids

    Directory of Open Access Journals (Sweden)

    Fátima Gomes

    2012-06-01

    Full Text Available Tambaqui (Colossoma macropomum is the fish species most commonly raised in the Brazilian fish farms. The species is highly adaptable to captive conditions, and is both fast-growing and relatively fecund. In recent years, artificial breeding has produced hybrids with Characiform species, known as "Tambacu" and "Tambatinga". Identifying hybrids is a difficult process, given their morphological similarities with the parent species. This study presents an innovative molecular approach to the identification of hybrids based primarily on Multiplex PCR of a nuclear gene (α-Tropomyosin, which was tested on 93 specimens obtained from fish farms in northern Brazil. The sequencing of a 505-bp fragment of the Control Region (CR permitted the identification of the maternal lineage of the specimen, all of which corresponded to C. macropomum. Unexpectedly, only two CR haplotype were found in 93 samples, a very low genetic diversity for the pisciculture of Tambaqui. Multiplex PCR identified 42 hybrids, in contrast with 23 identified by the supplier on the basis of external morphology. This innovative tool has considerable potential for the development of the Brazilian aquaculture, given the possibility of the systematic identification of the genetic traits of both fry-producing stocks, and the fry and juveniles raised in farms.O Tambaqui (Colossoma macropomum é a espécie de peixe mais comumente cultivada em pisciculturas no Brasil. A espécie é altamente adaptada às condições de cativeiro, apresentando rápido crescimento e alta fecundidade. Nos últimos anos tem ocorrido o cruzamento artificial entre espécies de Characiformes, produzindo os híbridos "Tambacu" e "Tambatinga". A identificação de híbridos é uma tarefa difícil, em virtude da grande similaridade morfológica entre as espécies parentais. O presente estudo apresenta uma abordagem molecular inovadora para identificação de híbridos com base em PCR Multiplex de um gene nuclear (

  15. A Hybrid Computational Intelligence Approach Combining Genetic Programming And Heuristic Classification for Pap-Smear Diagnosis

    DEFF Research Database (Denmark)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan

    2001-01-01

    The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come...

  16. Course on hybrid calculation

    International Nuclear Information System (INIS)

    Weill, J.; Tellier; Bonnemay; Craigne; Chareton; Di Falco

    1969-02-01

    After a definition of hybrid calculation (combination of analogue and digital calculation) with a distinction between series and parallel hybrid computing, and a description of a hybrid computer structure and of task sharing between computers, this course proposes a description of hybrid hardware used in Saclay and Cadarache computing centres, and of operations performed by these systems. The next part addresses issues related to programming languages and software. The fourth part describes how a problem is organised for its processing on these computers. Methods of hybrid analysis are then addressed: resolution of optimisation problems, of partial differential equations, and of integral equations by means of different methods (gradient, maximum principle, characteristics, functional approximation, time slicing, Monte Carlo, Neumann iteration, Fischer iteration)

  17. MSM, an Efficient Workflow for Metabolite Identification Using Hybrid Linear Ion Trap Orbitrap Mass Spectrometer

    Science.gov (United States)

    Cho, Robert; Huang, Yingying; Schwartz, Jae C.; Chen, Yan; Carlson, Timothy J.; Ma, Ji

    2012-05-01

    Identification of drug metabolites can often yield important information regarding clearance mechanism, pharmacologic activity, or toxicity for drug candidate molecules. Additionally, the identification of metabolites can provide beneficial structure-activity insight to help guide lead optimization efforts towards molecules with optimal metabolic profiles. There are challenges associated with detecting and identifying metabolites in the presence of complex biological matrices, and new LC-MS technologies have been developed to meet these challenges. In this report, we describe the development of an experimental approach that applies unique features of the hybrid linear ion trap Orbitrap mass spectrometer to streamline in vitro and in vivo metabolite identification experiments. The approach, referred to as MSM, utilizes multiple collision cells, dissociation methods, mass analyzers, and detectors. With multiple scan types and different dissociation modes built into one experimental method, along with flexible post-acquisition analysis options, the MSM workflow offers an attractive option to fast and reliable identification of metabolites in different kinds of in vitro and in vivo samples. The MSM workflow was successfully applied to metabolite identification analysis of verapamil in both in vitro rat hepatocyte incubations and in vivo rat bile samples.

  18. 16th International Conference on Hybrid Intelligent Systems and the 8th World Congress on Nature and Biologically Inspired Computing

    CERN Document Server

    Haqiq, Abdelkrim; Alimi, Adel; Mezzour, Ghita; Rokbani, Nizar; Muda, Azah

    2017-01-01

    This book presents the latest research in hybrid intelligent systems. It includes 57 carefully selected papers from the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) and the 8th World Congress on Nature and Biologically Inspired Computing (NaBIC 2016), held on November 21–23, 2016 in Marrakech, Morocco. HIS - NaBIC 2016 was jointly organized by the Machine Intelligence Research Labs (MIR Labs), USA; Hassan 1st University, Settat, Morocco and University of Sfax, Tunisia. Hybridization of intelligent systems is a promising research field in modern artificial/computational intelligence and is concerned with the development of the next generation of intelligent systems. The conference’s main aim is to inspire further exploration of the intriguing potential of hybrid intelligent systems and bio-inspired computing. As such, the book is a valuable resource for practicing engineers /scientists and researchers working in the field of computational intelligence and artificial intelligence.

  19. Achieving a hybrid brain-computer interface with tactile selective attention and motor imagery

    Science.gov (United States)

    Ahn, Sangtae; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan

    2014-12-01

    Objective. We propose a new hybrid brain-computer interface (BCI) system that integrates two different EEG tasks: tactile selective attention (TSA) using a vibro-tactile stimulator on the left/right finger and motor imagery (MI) of left/right hand movement. Event-related desynchronization (ERD) from the MI task and steady-state somatosensory evoked potential (SSSEP) from the TSA task are retrieved and combined into two hybrid senses. Approach. One hybrid approach is to measure two tasks simultaneously; the features of each task are combined for testing. Another hybrid approach is to measure two tasks consecutively (TSA first and MI next) using only MI features. For comparison with the hybrid approaches, the TSA and MI tasks are measured independently. Main results. Using a total of 16 subject datasets, we analyzed the BCI classification performance for MI, TSA and two hybrid approaches in a comparative manner; we found that the consecutive hybrid approach outperformed the others, yielding about a 10% improvement in classification accuracy relative to MI alone. It is understood that TSA may play a crucial role as a prestimulus in that it helps to generate earlier ERD prior to MI and thus sustains ERD longer and to a stronger degree; this ERD may give more discriminative information than ERD in MI alone. Significance. Overall, our proposed consecutive hybrid approach is very promising for the development of advanced BCI systems.

  20. All-optical quantum computing with a hybrid solid-state processing unit

    International Nuclear Information System (INIS)

    Pei Pei; Zhang Fengyang; Li Chong; Song Heshan

    2011-01-01

    We develop an architecture of a hybrid quantum solid-state processing unit for universal quantum computing. The architecture allows distant and nonidentical solid-state qubits in distinct physical systems to interact and work collaboratively. All the quantum computing procedures are controlled by optical methods using classical fields and cavity QED. Our methods have a prominent advantage of the insensitivity to dissipation process benefiting from the virtual excitation of subsystems. Moreover, the quantum nondemolition measurements and state transfer for the solid-state qubits are proposed. The architecture opens promising perspectives for implementing scalable quantum computation in a broader sense that different solid-state systems can merge and be integrated into one quantum processor afterward.

  1. Near-term hybrid vehicle program, phase 1. Appendix B: Design trade-off studies report. Volume 3: Computer program listings

    Science.gov (United States)

    1979-01-01

    A description and listing is presented of two computer programs: Hybrid Vehicle Design Program (HYVELD) and Hybrid Vehicle Simulation Program (HYVEC). Both of the programs are modifications and extensions of similar programs developed as part of the Electric and Hybrid Vehicle System Research and Development Project.

  2. Hybrid epidemics--a case study on computer worm conficker.

    Directory of Open Access Journals (Sweden)

    Changwang Zhang

    Full Text Available Conficker is a computer worm that erupted on the Internet in 2008. It is unique in combining three different spreading strategies: local probing, neighbourhood probing, and global probing. We propose a mathematical model that combines three modes of spreading: local, neighbourhood, and global, to capture the worm's spreading behaviour. The parameters of the model are inferred directly from network data obtained during the first day of the Conficker epidemic. The model is then used to explore the tradeoff between spreading modes in determining the worm's effectiveness. Our results show that the Conficker epidemic is an example of a critically hybrid epidemic, in which the different modes of spreading in isolation do not lead to successful epidemics. Such hybrid spreading strategies may be used beneficially to provide the most effective strategies for promulgating information across a large population. When used maliciously, however, they can present a dangerous challenge to current internet security protocols.

  3. Hybrid epidemics--a case study on computer worm conficker.

    Science.gov (United States)

    Zhang, Changwang; Zhou, Shi; Chain, Benjamin M

    2015-01-01

    Conficker is a computer worm that erupted on the Internet in 2008. It is unique in combining three different spreading strategies: local probing, neighbourhood probing, and global probing. We propose a mathematical model that combines three modes of spreading: local, neighbourhood, and global, to capture the worm's spreading behaviour. The parameters of the model are inferred directly from network data obtained during the first day of the Conficker epidemic. The model is then used to explore the tradeoff between spreading modes in determining the worm's effectiveness. Our results show that the Conficker epidemic is an example of a critically hybrid epidemic, in which the different modes of spreading in isolation do not lead to successful epidemics. Such hybrid spreading strategies may be used beneficially to provide the most effective strategies for promulgating information across a large population. When used maliciously, however, they can present a dangerous challenge to current internet security protocols.

  4. Hybrid Epidemics—A Case Study on Computer Worm Conficker

    Science.gov (United States)

    Zhang, Changwang; Zhou, Shi; Chain, Benjamin M.

    2015-01-01

    Conficker is a computer worm that erupted on the Internet in 2008. It is unique in combining three different spreading strategies: local probing, neighbourhood probing, and global probing. We propose a mathematical model that combines three modes of spreading: local, neighbourhood, and global, to capture the worm’s spreading behaviour. The parameters of the model are inferred directly from network data obtained during the first day of the Conficker epidemic. The model is then used to explore the tradeoff between spreading modes in determining the worm’s effectiveness. Our results show that the Conficker epidemic is an example of a critically hybrid epidemic, in which the different modes of spreading in isolation do not lead to successful epidemics. Such hybrid spreading strategies may be used beneficially to provide the most effective strategies for promulgating information across a large population. When used maliciously, however, they can present a dangerous challenge to current internet security protocols. PMID:25978309

  5. Spatially hybrid computations for streamer discharges with generic features of pulled fronts: I. Planar fronts

    International Nuclear Information System (INIS)

    Li Chao; Ebert, Ute; Hundsdorfer, Willem

    2010-01-01

    Streamers are the first stage of sparks and lightning; they grow due to a strongly enhanced electric field at their tips; this field is created by a thin curved space charge layer. These multiple scales are already challenging when the electrons are approximated by densities. However, electron density fluctuations in the leading edge of the front and non-thermal stretched tails of the electron energy distribution (as a cause of X-ray emissions) require a particle model to follow the electron motion. But present computers cannot deal with all electrons in a fully developed streamer. Therefore, super-particle have to be introduced, which leads to wrong statistics and numerical artifacts. The method of choice is a hybrid computation in space where individual electrons are followed in the region of high electric field and low density while the bulk of the electrons is approximated by densities (or fluids). We here develop the hybrid coupling for planar fronts. First, to obtain a consistent flux at the interface between particle and fluid model in the hybrid computation, the widely used classical fluid model is replaced by an extended fluid model. Then the coupling algorithm and the numerical implementation of the spatially hybrid model are presented in detail, in particular, the position of the model interface and the construction of the buffer region. The method carries generic features of pulled fronts that can be applied to similar problems like large deviations in the leading edge of population fronts, etc.

  6. Autumn Algorithm-Computation of Hybridization Networks for Realistic Phylogenetic Trees.

    Science.gov (United States)

    Huson, Daniel H; Linz, Simone

    2018-01-01

    A minimum hybridization network is a rooted phylogenetic network that displays two given rooted phylogenetic trees using a minimum number of reticulations. Previous mathematical work on their calculation has usually assumed the input trees to be bifurcating, correctly rooted, or that they both contain the same taxa. These assumptions do not hold in biological studies and "realistic" trees have multifurcations, are difficult to root, and rarely contain the same taxa. We present a new algorithm for computing minimum hybridization networks for a given pair of "realistic" rooted phylogenetic trees. We also describe how the algorithm might be used to improve the rooting of the input trees. We introduce the concept of "autumn trees", a nice framework for the formulation of algorithms based on the mathematics of "maximum acyclic agreement forests". While the main computational problem is hard, the run-time depends mainly on how different the given input trees are. In biological studies, where the trees are reasonably similar, our parallel implementation performs well in practice. The algorithm is available in our open source program Dendroscope 3, providing a platform for biologists to explore rooted phylogenetic networks. We demonstrate the utility of the algorithm using several previously studied data sets.

  7. Maze learning by a hybrid brain-computer system.

    Science.gov (United States)

    Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

    2016-09-13

    The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

  8. Maze learning by a hybrid brain-computer system

    Science.gov (United States)

    Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

    2016-09-01

    The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

  9. COED Transactions, Vol. X, No. 9, September 1978. Use of the Analog/Hybrid Computer in Boundary Layer and Convection Studies.

    Science.gov (United States)

    Mitchell, Eugene E., Ed.

    In certain boundary layer or natural convection work, where a similarity transformation is valid, the equations can be reduced to a set of nonlinear ordinary differential equations. They are therefore well-suited to a fast solution on an analog/hybrid computer. This paper illustrates such usage of the analog/hybrid computer by a set of…

  10. Computation of the Lyapunov exponents in the compass-gait model under OGY control via a hybrid Poincaré map

    International Nuclear Information System (INIS)

    Gritli, Hassène; Belghith, Safya

    2015-01-01

    Highlights: • A numerical calculation method of the Lyapunov exponents in the compass-gait model under OGY control is proposed. • A new linearization method of the impulsive hybrid dynamics around a one-periodic hybrid limit cycle is achieved. • We develop a simple analytical expression of a controlled hybrid Poincaré map. • A dimension reduction of the hybrid Poincaré map is realized. • We describe the numerical computation procedure of the Lyapunov exponents via the designed hybrid Poincaré map. - Abstract: This paper aims at providing a numerical calculation method of the spectrum of Lyapunov exponents in a four-dimensional impulsive hybrid nonlinear dynamics of a passive compass-gait model under the OGY control approach by means of a controlled hybrid Poincaré map. We present a four-dimensional simplified analytical expression of such hybrid map obtained by linearizing the uncontrolled impulsive hybrid nonlinear dynamics around a desired one-periodic passive hybrid limit cycle. In order to compute the spectrum of Lyapunov exponents, a dimension reduction of the controlled hybrid Poincaré map is realized. The numerical calculation of the spectrum of Lyapunov exponents using the reduced-dimension controlled hybrid Poincaré map is given in detail. In order to show the effectiveness of the developed method, the spectrum of Lyapunov exponents is calculated as the slope (bifurcation) parameter varies and hence used to predict the walking dynamics behavior of the compass-gait model under the OGY control.

  11. A novel hybrid approach with multidimensional-like effects for compressible flow computations

    Science.gov (United States)

    Kalita, Paragmoni; Dass, Anoop K.

    2017-07-01

    A multidimensional scheme achieves good resolution of strong and weak shocks irrespective of whether the discontinuities are aligned with or inclined to the grid. However, these schemes are computationally expensive. This paper achieves similar effects by hybridizing two schemes, namely, AUSM and DRLLF and coupling them through a novel shock switch that operates - unlike existing switches - on the gradient of the Mach number across the cell-interface. The schemes that are hybridized have contrasting properties. The AUSM scheme captures grid-aligned (and strong) shocks crisply but it is not so good for non-grid-aligned weaker shocks, whereas the DRLLF scheme achieves sharp resolution of non-grid-aligned weaker shocks, but is not as good for grid-aligned strong shocks. It is our experience that if conventional shock switches based on variables like density, pressure or Mach number are used to combine the schemes, the desired effect of crisp resolution of grid-aligned and non-grid-aligned discontinuities are not obtained. To circumvent this problem we design a shock switch based - for the first time - on the gradient of the cell-interface Mach number with very impressive results. Thus the strategy of hybridizing two carefully selected schemes together with the innovative design of the shock switch that couples them, affords a method that produces the effects of a multidimensional scheme with a lower computational cost. It is further seen that hybridization of the AUSM scheme with the recently developed DRLLFV scheme using the present shock switch gives another scheme that provides crisp resolution for both shocks and boundary layers. Merits of the scheme are established through a carefully selected set of numerical experiments.

  12. Computation of hybrid static potentials in SU(3 lattice gauge theory

    Directory of Open Access Journals (Sweden)

    Reisinger Christian

    2018-01-01

    Full Text Available We compute hybrid static potentials in SU(3 lattice gauge theory. We present a method to automatically generate a large set of suitable creation operators with defined quantum numbers from elementary building blocks. We show preliminary results for several channels and discuss, which structures of the gluonic flux tube seem to be realized by the ground states in these channels.

  13. Energy Management Strategy for Hybrid Electric Vehicle Based on Driving Condition Identification Using KGA-Means

    Directory of Open Access Journals (Sweden)

    Shuxian Li

    2018-06-01

    Full Text Available In order to solve the problem related to adaptive energy management strategies based on driving condition identification being difficult to be applied to a real hybrid electric vehicle (HEV controller, this paper proposes an energy management strategy by combining the driving condition identification algorithm based on genetic optimized K-means clustering algorithm (KGA-means, and the equivalent consumption minimization strategy (ECMS. The simulation results show that compared with ECMS, the energy management strategy proposed in this article drives the engine working point closer to the best efficiency curve, and smooths out the state of charge (SOC change and better maintains the SOC in a highly efficient area. As a result, the vehicle fuel consumption reduces by 6.84%.

  14. Hybrid CFD/CAA Modeling for Liftoff Acoustic Predictions

    Science.gov (United States)

    Strutzenberg, Louise L.; Liever, Peter A.

    2011-01-01

    This paper presents development efforts at the NASA Marshall Space flight Center to establish a hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) simulation system for launch vehicle liftoff acoustics environment analysis. Acoustic prediction engineering tools based on empirical jet acoustic strength and directivity models or scaled historical measurements are of limited value in efforts to proactively design and optimize launch vehicles and launch facility configurations for liftoff acoustics. CFD based modeling approaches are now able to capture the important details of vehicle specific plume flow environment, identifY the noise generation sources, and allow assessment of the influence of launch pad geometric details and sound mitigation measures such as water injection. However, CFD methodologies are numerically too dissipative to accurately capture the propagation of the acoustic waves in the large CFD models. The hybrid CFD/CAA approach combines the high-fidelity CFD analysis capable of identifYing the acoustic sources with a fast and efficient Boundary Element Method (BEM) that accurately propagates the acoustic field from the source locations. The BEM approach was chosen for its ability to properly account for reflections and scattering of acoustic waves from launch pad structures. The paper will present an overview of the technology components of the CFD/CAA framework and discuss plans for demonstration and validation against test data.

  15. The UF family of hybrid phantoms of the developing human fetus for computational radiation dosimetry

    International Nuclear Information System (INIS)

    Maynard, Matthew R; Geyer, John W; Bolch, Wesley; Aris, John P; Shifrin, Roger Y

    2011-01-01

    Historically, the development of computational phantoms for radiation dosimetry has primarily been directed at capturing and representing adult and pediatric anatomy, with less emphasis devoted to models of the human fetus. As concern grows over possible radiation-induced cancers from medical and non-medical exposures of the pregnant female, the need to better quantify fetal radiation doses, particularly at the organ-level, also increases. Studies such as the European Union's SOLO (Epidemiological Studies of Exposed Southern Urals Populations) hope to improve our understanding of cancer risks following chronic in utero radiation exposure. For projects such as SOLO, currently available fetal anatomic models do not provide sufficient anatomical detail for organ-level dose assessment. To address this need, two fetal hybrid computational phantoms were constructed using high-quality magnetic resonance imaging and computed tomography image sets obtained for two well-preserved fetal specimens aged 11.5 and 21 weeks post-conception. Individual soft tissue organs, bone sites and outer body contours were segmented from these images using 3D-DOCTOR(TM) and then imported to the 3D modeling software package Rhinoceros(TM) for further modeling and conversion of soft tissue organs, certain bone sites and outer body contours to deformable non-uniform rational B-spline surfaces. The two specimen-specific phantoms, along with a modified version of the 38 week UF hybrid newborn phantom, comprised a set of base phantoms from which a series of hybrid computational phantoms was derived for fetal ages 8, 10, 15, 20, 25, 30, 35 and 38 weeks post-conception. The methodology used to construct the series of phantoms accounted for the following age-dependent parameters: (1) variations in skeletal size and proportion, (2) bone-dependent variations in relative levels of bone growth, (3) variations in individual organ masses and total fetal masses and (4) statistical percentile variations in

  16. Applications integration in a hybrid cloud computing environment: modelling and platform

    Science.gov (United States)

    Li, Qing; Wang, Ze-yuan; Li, Wei-hua; Li, Jun; Wang, Cheng; Du, Rui-yang

    2013-08-01

    With the development of application services providers and cloud computing, more and more small- and medium-sized business enterprises use software services and even infrastructure services provided by professional information service companies to replace all or part of their information systems (ISs). These information service companies provide applications, such as data storage, computing processes, document sharing and even management information system services as public resources to support the business process management of their customers. However, no cloud computing service vendor can satisfy the full functional IS requirements of an enterprise. As a result, enterprises often have to simultaneously use systems distributed in different clouds and their intra enterprise ISs. Thus, this article presents a framework to integrate applications deployed in public clouds and intra ISs. A run-time platform is developed and a cross-computing environment process modelling technique is also developed to improve the feasibility of ISs under hybrid cloud computing environments.

  17. Cloud computing-based energy optimization control framework for plug-in hybrid electric bus

    International Nuclear Information System (INIS)

    Yang, Chao; Li, Liang; You, Sixiong; Yan, Bingjie; Du, Xian

    2017-01-01

    Considering the complicated characteristics of traffic flow in city bus route and the nonlinear vehicle dynamics, optimal energy management integrated with clustering and recognition of driving conditions in plug-in hybrid electric bus is still a challenging problem. Motivated by this issue, this paper presents an innovative energy optimization control framework based on the cloud computing for plug-in hybrid electric bus. This framework, which includes offline part and online part, can realize the driving conditions clustering in offline part, and the energy management in online part. In offline part, utilizing the operating data transferred from a bus to the remote monitoring center, K-means algorithm is adopted to cluster the driving conditions, and then Markov probability transfer matrixes are generated to predict the possible operating demand of the bus driver. Next in online part, the current driving condition is real-time identified by a well-trained support vector machine, and Markov chains-based driving behaviors are accordingly selected. With the stochastic inputs, stochastic receding horizon control method is adopted to obtain the optimized energy management of hybrid powertrain. Simulations and hardware-in-loop test are carried out with the real-world city bus route, and the results show that the presented strategy could greatly improve the vehicle fuel economy, and as the traffic flow data feedback increases, the fuel consumption of every plug-in hybrid electric bus running in a specific bus route tends to be a stable minimum. - Highlights: • Cloud computing-based energy optimization control framework is proposed. • Driving cycles are clustered into 6 types by K-means algorithm. • Support vector machine is employed to realize the online recognition of driving condition. • Stochastic receding horizon control-based energy management strategy is designed for plug-in hybrid electric bus. • The proposed framework is verified by simulation and hard

  18. An online hybrid brain-computer interface combining multiple physiological signals for webpage browse.

    Science.gov (United States)

    Long Chen; Zhongpeng Wang; Feng He; Jiajia Yang; Hongzhi Qi; Peng Zhou; Baikun Wan; Dong Ming

    2015-08-01

    The hybrid brain computer interface (hBCI) could provide higher information transfer rate than did the classical BCIs. It included more than one brain-computer or human-machine interact paradigms, such as the combination of the P300 and SSVEP paradigms. Research firstly constructed independent subsystems of three different paradigms and tested each of them with online experiments. Then we constructed a serial hybrid BCI system which combined these paradigms to achieve the functions of typing letters, moving and clicking cursor, and switching among them for the purpose of browsing webpages. Five subjects were involved in this study. They all successfully realized these functions in the online tests. The subjects could achieve an accuracy above 90% after training, which met the requirement in operating the system efficiently. The results demonstrated that it was an efficient system capable of robustness, which provided an approach for the clinic application.

  19. Automatic Identification and Reconstruction of the Right Phrenic Nerve on Computed Tomography

    OpenAIRE

    Bamps, Kobe; Cuypers, Céline; Polmans, Pieter; Claesen, Luc; Koopman, Pieter

    2016-01-01

    An automatic computer algorithm was successfully constructed, enabling identification and reconstruction of the right phrenic nerve on high resolution coronary computed tomography scans. This could lead to a substantial reduction in the incidence of phrenic nerve paralysis during pulmonary vein isolation using ballon techniques.

  20. Modelling of data uncertainties on hybrid computers

    Energy Technology Data Exchange (ETDEWEB)

    Schneider, Anke (ed.)

    2016-06-15

    The codes d{sup 3}f and r{sup 3}t are well established for modelling density-driven flow and nuclide transport in the far field of repositories for hazardous material in deep geological formations. They are applicable in porous media as well as in fractured rock or mudstone, for modelling salt- and heat transport as well as a free groundwater surface. Development of the basic framework of d{sup 3}f and r{sup 3}t had begun more than 20 years ago. Since that time significant advancements took place in the requirements for safety assessment as well as for computer hardware development. The period of safety assessment for a repository of high-level radioactive waste was extended to 1 million years, and the complexity of the models is steadily growing. Concurrently, the demands on accuracy increase. Additionally, model and parameter uncertainties become more and more important for an increased understanding of prediction reliability. All this leads to a growing demand for computational power that requires a considerable software speed-up. An effective way to achieve this is the use of modern, hybrid computer architectures which requires basically the set-up of new data structures and a corresponding code revision but offers a potential speed-up by several orders of magnitude. The original codes d{sup 3}f and r{sup 3}t were applications of the software platform UG /BAS 94/ whose development had begun in the early nineteennineties. However, UG had recently been advanced to the C++ based, substantially revised version UG4 /VOG 13/. To benefit also in the future from state-of-the-art numerical algorithms and to use hybrid computer architectures, the codes d{sup 3}f and r{sup 3}t were transferred to this new code platform. Making use of the fact that coupling between different sets of equations is natively supported in UG4, d{sup 3}f and r{sup 3}t were combined to one conjoint code d{sup 3}f++. A direct estimation of uncertainties for complex groundwater flow models with the

  1. Hybrid magic state distillation for universal fault-tolerant quantum computation

    OpenAIRE

    Zheng, Wenqiang; Yu, Yafei; Pan, Jian; Zhang, Jingfu; Li, Jun; Li, Zhaokai; Suter, Dieter; Zhou, Xianyi; Peng, Xinhua; Du, Jiangfeng

    2014-01-01

    A set of stabilizer operations augmented by some special initial states known as 'magic states', gives the possibility of universal fault-tolerant quantum computation. However, magic state preparation inevitably involves nonideal operations that introduce noise. The most common method to eliminate the noise is magic state distillation (MSD) by stabilizer operations. Here we propose a hybrid MSD protocol by connecting a four-qubit H-type MSD with a five-qubit T-type MSD, in order to overcome s...

  2. A hybrid model for the computationally-efficient simulation of the cerebellar granular layer

    Directory of Open Access Journals (Sweden)

    Anna eCattani

    2016-04-01

    Full Text Available The aim of the present paper is to efficiently describe the membrane potential dynamics of neural populations formed by species having a high density difference in specific brain areas. We propose a hybrid model whose main ingredients are a conductance-based model (ODE system and its continuous counterpart (PDE system obtained through a limit process in which the number of neurons confined in a bounded region of the brain tissue is sent to infinity. Specifically, in the discrete model, each cell is described by a set of time-dependent variables, whereas in the continuum model, cells are grouped into populations that are described by a set of continuous variables.Communications between populations, which translate into interactions among the discrete and the continuous models, are the essence of the hybrid model we present here. The cerebellum and cerebellum-like structures show in their granular layer a large difference in the relative density of neuronal species making them a natural testing ground for our hybrid model. By reconstructing the ensemble activity of the cerebellar granular layer network and by comparing our results to a more realistic computational network, we demonstrate that our description of the network activity, even though it is not biophysically detailed, is still capable of reproducing salient features of neural network dynamics. Our modeling approach yields a significant computational cost reduction by increasing the simulation speed at least $270$ times. The hybrid model reproduces interesting dynamics such as local microcircuit synchronization, traveling waves, center-surround and time-windowing.

  3. Hybrid cloud and cluster computing paradigms for life science applications.

    Science.gov (United States)

    Qiu, Judy; Ekanayake, Jaliya; Gunarathne, Thilina; Choi, Jong Youl; Bae, Seung-Hee; Li, Hui; Zhang, Bingjing; Wu, Tak-Lon; Ruan, Yang; Ekanayake, Saliya; Hughes, Adam; Fox, Geoffrey

    2010-12-21

    Clouds and MapReduce have shown themselves to be a broadly useful approach to scientific computing especially for parallel data intensive applications. However they have limited applicability to some areas such as data mining because MapReduce has poor performance on problems with an iterative structure present in the linear algebra that underlies much data analysis. Such problems can be run efficiently on clusters using MPI leading to a hybrid cloud and cluster environment. This motivates the design and implementation of an open source Iterative MapReduce system Twister. Comparisons of Amazon, Azure, and traditional Linux and Windows environments on common applications have shown encouraging performance and usability comparisons in several important non iterative cases. These are linked to MPI applications for final stages of the data analysis. Further we have released the open source Twister Iterative MapReduce and benchmarked it against basic MapReduce (Hadoop) and MPI in information retrieval and life sciences applications. The hybrid cloud (MapReduce) and cluster (MPI) approach offers an attractive production environment while Twister promises a uniform programming environment for many Life Sciences applications. We used commercial clouds Amazon and Azure and the NSF resource FutureGrid to perform detailed comparisons and evaluations of different approaches to data intensive computing. Several applications were developed in MPI, MapReduce and Twister in these different environments.

  4. The UF family of hybrid phantoms of the developing human fetus for computational radiation dosimetry

    Energy Technology Data Exchange (ETDEWEB)

    Maynard, Matthew R; Geyer, John W; Bolch, Wesley [Department of Nuclear and Radiological Engineering, University of Florida, Gainesville, FL (United States); Aris, John P [Department of Anatomy and Cell Biology, University of Florida, Gainesville, FL (United States); Shifrin, Roger Y, E-mail: wbolch@ufl.edu [Department of Radiology, University of Florida, Gainesville, FL (United States)

    2011-08-07

    Historically, the development of computational phantoms for radiation dosimetry has primarily been directed at capturing and representing adult and pediatric anatomy, with less emphasis devoted to models of the human fetus. As concern grows over possible radiation-induced cancers from medical and non-medical exposures of the pregnant female, the need to better quantify fetal radiation doses, particularly at the organ-level, also increases. Studies such as the European Union's SOLO (Epidemiological Studies of Exposed Southern Urals Populations) hope to improve our understanding of cancer risks following chronic in utero radiation exposure. For projects such as SOLO, currently available fetal anatomic models do not provide sufficient anatomical detail for organ-level dose assessment. To address this need, two fetal hybrid computational phantoms were constructed using high-quality magnetic resonance imaging and computed tomography image sets obtained for two well-preserved fetal specimens aged 11.5 and 21 weeks post-conception. Individual soft tissue organs, bone sites and outer body contours were segmented from these images using 3D-DOCTOR(TM) and then imported to the 3D modeling software package Rhinoceros(TM) for further modeling and conversion of soft tissue organs, certain bone sites and outer body contours to deformable non-uniform rational B-spline surfaces. The two specimen-specific phantoms, along with a modified version of the 38 week UF hybrid newborn phantom, comprised a set of base phantoms from which a series of hybrid computational phantoms was derived for fetal ages 8, 10, 15, 20, 25, 30, 35 and 38 weeks post-conception. The methodology used to construct the series of phantoms accounted for the following age-dependent parameters: (1) variations in skeletal size and proportion, (2) bone-dependent variations in relative levels of bone growth, (3) variations in individual organ masses and total fetal masses and (4) statistical percentile variations

  5. Hybrid Brain–Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review

    OpenAIRE

    Hong, Keum-Shik; Khan, Muhammad Jawad

    2017-01-01

    In this article, non-invasive hybrid brain–computer interface (hBCI) technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG), due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spec...

  6. The UF family of reference hybrid phantoms for computational radiation dosimetry

    International Nuclear Information System (INIS)

    Lee, Choonsik; Lodwick, Daniel; Hurtado, Jorge; Pafundi, Deanna; Williams, Jonathan L; Bolch, Wesley E

    2010-01-01

    Computational human phantoms are computer models used to obtain dose distributions within the human body exposed to internal or external radiation sources. In addition, they are increasingly used to develop detector efficiencies for in vivo whole-body counters. Two classes of computational human phantoms have been widely utilized for dosimetry calculation: stylized and voxel phantoms that describe human anatomy through mathematical surface equations and 3D voxel matrices, respectively. Stylized phantoms are flexible in that changes to organ position and shape are possible given avoidance of region overlap, while voxel phantoms are typically fixed to a given patient anatomy, yet can be proportionally scaled to match individuals of larger or smaller stature, but of equivalent organ anatomy. Voxel phantoms provide much better anatomical realism as compared to stylized phantoms which are intrinsically limited by mathematical surface equations. To address the drawbacks of these phantoms, hybrid phantoms based on non-uniform rational B-spline (NURBS) surfaces have been introduced wherein anthropomorphic flexibility and anatomic realism are both preserved. Researchers at the University of Florida have introduced a series of hybrid phantoms representing the ICRP Publication 89 reference newborn, 15 year, and adult male and female. In this study, six additional phantoms are added to the UF family of hybrid phantoms-those of the reference 1 year, 5 year and 10 year child. Head and torso CT images of patients whose ages were close to the targeted ages were obtained under approved protocols. Major organs and tissues were segmented from these images using an image processing software, 3D-DOCTOR(TM). NURBS and polygon mesh surfaces were then used to model individual organs and tissues after importing the segmented organ models to the 3D NURBS modeling software, Rhinoceros(TM). The phantoms were matched to four reference datasets: (1) standard anthropometric data, (2) reference

  7. Preliminary Study on Hybrid Computational Phantom for Radiation Dosimetry Based on Subdivision Surface

    International Nuclear Information System (INIS)

    Jeong, Jong Hwi; Choi, Sang Hyoun; Cho, Sung Koo; Kim, Chan Hyeong

    2007-01-01

    The anthropomorphic computational phantoms are classified into two groups. One group is the stylized phantoms, or MIRD phantoms, which are based on mathematical representations of the anatomical structures. The shapes and positions of the organs and tissues in these phantoms can be adjusted by changing the coefficients of the equations in use. The other group is the voxel phantoms, which are based on tomographic images of a real person such as CT, MR and serially sectioned color slice images from a cadaver. Obviously, the voxel phantoms represent the anatomical structures of a human body much more realistically than the stylized phantoms. A realistic representation of anatomical structure is very important for an accurate calculation of radiation dose in the human body. Consequently, the ICRP recently has decided to use the voxel phantoms for the forthcoming update of the dose conversion coefficients. However, the voxel phantoms also have some limitations: (1) The topology and dimensions of the organs and tissues in a voxel model are extremely difficult to change, and (2) The thin organs, such as oral mucosa and skin, cannot be realistically modeled unless the voxel resolution is prohibitively high. Recently, a new approach has been implemented by several investigators. The investigators converted their voxel phantoms to hybrid computational phantoms based on NURBS (Non-Uniform Rational B-Splines) surface, which is smooth and deformable. It is claimed that these new phantoms have the flexibility of the stylized phantom along with the realistic representations of the anatomical structures. The topology and dimensions of the anatomical structures can be easily changed as necessary. Thin organs can be modeled without affecting computational speed or memory requirement. The hybrid phantoms can be also used for 4-D Monte Carlo simulations. In this preliminary study, the external shape of a voxel phantom (i.e., skin), HDRK-Man, was converted to a hybrid computational

  8. OPTICAL correlation identification technology applied in underwater laser imaging target identification

    Science.gov (United States)

    Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

    2012-01-01

    The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve

  9. Hybrid EEG—Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal

    Directory of Open Access Journals (Sweden)

    Malik M. Naeem Mannan

    2016-02-01

    Full Text Available Contamination of eye movement and blink artifacts in Electroencephalogram (EEG recording makes the analysis of EEG data more difficult and could result in mislead findings. Efficient removal of these artifacts from EEG data is an essential step in improving classification accuracy to develop the brain-computer interface (BCI. In this paper, we proposed an automatic framework based on independent component analysis (ICA and system identification to identify and remove ocular artifacts from EEG data by using hybrid EEG and eye tracker system. The performance of the proposed algorithm is illustrated using experimental and standard EEG datasets. The proposed algorithm not only removes the ocular artifacts from artifactual zone but also preserves the neuronal activity related EEG signals in non-artifactual zone. The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts from EEG data. Additionally, results demonstrate that the proposed algorithm can achieve lower relative error and higher mutual information values between corrected EEG and artifact-free EEG data.

  10. Numerical methodologies for investigation of moderate-velocity flow using a hybrid computational fluid dynamics - molecular dynamics simulation approach

    International Nuclear Information System (INIS)

    Ko, Soon Heum; Kim, Na Yong; Nikitopoulos, Dimitris E.; Moldovan, Dorel; Jha, Shantenu

    2014-01-01

    Numerical approaches are presented to minimize the statistical errors inherently present due to finite sampling and the presence of thermal fluctuations in the molecular region of a hybrid computational fluid dynamics (CFD) - molecular dynamics (MD) flow solution. Near the fluid-solid interface the hybrid CFD-MD simulation approach provides a more accurate solution, especially in the presence of significant molecular-level phenomena, than the traditional continuum-based simulation techniques. It also involves less computational cost than the pure particle-based MD. Despite these advantages the hybrid CFD-MD methodology has been applied mostly in flow studies at high velocities, mainly because of the higher statistical errors associated with low velocities. As an alternative to the costly increase of the size of the MD region to decrease statistical errors, we investigate a few numerical approaches that reduce sampling noise of the solution at moderate-velocities. These methods are based on sampling of multiple simulation replicas and linear regression of multiple spatial/temporal samples. We discuss the advantages and disadvantages of each technique in the perspective of solution accuracy and computational cost.

  11. Taxonomic Identification of Mediterranean Pines and Their Hybrids Based on the High Resolution Melting (HRM) and trnL Approaches: From Cytoplasmic Inheritance to Timber Tracing

    Science.gov (United States)

    Ganopoulos, Ioannis; Aravanopoulos, Filippos; Madesis, Panagiotis; Pasentsis, Konstantinos; Bosmali, Irene; Ouzounis, Christos; Tsaftaris, Athanasios

    2013-01-01

    Fast and accurate detection of plant species and their hybrids using molecular tools will facilitate the assessment and monitoring of local biodiversity in an era of climate and environmental change. Herein, we evaluate the utility of the plastid trnL marker for species identification applied to Mediterranean pines (Pinus spp.). Our results indicate that trnL is a very sensitive marker for delimiting species biodiversity. Furthermore, High Resolution Melting (HRM) analysis was exploited as a molecular fingerprint for fast and accurate discrimination of Pinus spp. DNA sequence variants. The trnL approach and the HRM analyses were extended to wood samples of two species (Pinus nigra and Pinus sylvestris) with excellent results, congruent to those obtained using leaf tissue. Both analyses demonstrate that hybrids from the P. brutia (maternal parent) × P. halepensis (paternal parent) cross, exhibit the P. halepensis profile, confirming paternal plastid inheritance in Group Halepensis pines. Our study indicates that a single one-step reaction method and DNA marker are sufficient for the identification of Mediterranean pines, their hybrids and the origin of pine wood. Furthermore, our results underline the potential for certain DNA regions to be used as novel biological information markers combined with existing morphological characters and suggest a relatively reliable and open taxonomic system that can link DNA variation to phenotype-based species or hybrid assignment status and direct taxa identification from recalcitrant tissues such as wood samples. PMID:23577179

  12. Site-specific identification of heparan and chondroitin sulfate glycosaminoglycans in hybrid proteoglycans.

    Science.gov (United States)

    Noborn, Fredrik; Gomez Toledo, Alejandro; Green, Anders; Nasir, Waqas; Sihlbom, Carina; Nilsson, Jonas; Larson, Göran

    2016-10-03

    Heparan sulfate (HS) and chondroitin sulfate (CS) are complex polysaccharides that regulate important biological pathways in virtually all metazoan organisms. The polysaccharides often display opposite effects on cell functions with HS and CS structural motifs presenting unique binding sites for specific ligands. Still, the mechanisms by which glycan biosynthesis generates complex HS and CS polysaccharides required for the regulation of mammalian physiology remain elusive. Here we present a glycoproteomic approach that identifies and differentiates between HS and CS attachment sites and provides identity to the core proteins. Glycopeptides were prepared from perlecan, a complex proteoglycan known to be substituted with both HS and CS chains, further digested with heparinase or chondroitinase ABC to reduce the HS and CS chain lengths respectively, and thereafter analyzed by nLC-MS/MS. This protocol enabled the identification of three consensus HS sites and one hybrid site, carrying either a HS or a CS chain. Inspection of the amino acid sequence at the hybrid attachment locus indicates that certain peptide motifs may encode for the chain type selection process. This analytical approach will become useful when addressing fundamental questions in basic biology specifically in elucidating the functional roles of site-specific glycosylations of proteoglycans.

  13. Recent advances in swarm intelligence and evolutionary computation

    CERN Document Server

    2015-01-01

    This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference f...

  14. Obtaining of interspecific hybrids for pea introgressive breeding

    Directory of Open Access Journals (Sweden)

    Sergey Vasilevich Bobkov

    2015-09-01

    Full Text Available Background. Overcoming of reproductive isolation, identification and transfer of agronomic value genes from wild relatives into cultivated pea genomes is an important task for pea introgressive breeding. Materials and methods. Reciprocal hybridization of cultivated pea with wide set of P. fulvum accessions was conducted. Identification of hybrids was carried out with use of biochemical and morphological markers. Identification of unique protein was conducted with use of electrophoretic spectra of mature seeds. Results. Pea interspecific hybrids were obtained in two reciprocal directions of crosses. Cross efficiency in Р. sativum × P. fulvum and P. fulvum × Р. sativum combinations was 36 % and 7 %, respectively. All tested seeds in crosses Р. sativum × P. fulvum were hybrids. Crosses in direction P. fulvum × Р. sativum led to formation of puny seeds restricted in embryo growth. Protein markers of one seed derived in cross P. fulvum × Р. sativum proved its hybrid nature. Morphological markers demonstrated that plant derived from another cross was also a hybrid. Culture of immature embryos was developed for recovering plants in interspecific crosses. Morphogenic calli and regenerated plants were obtained in culture of immature embryos P. fulvum (И592589 × Р. sativum (Aest. Identification of unique protein 7 of P. fulvum was conducted. Inheritance of that protein was proved as monogenic dominant. Conclusion. Efficiency of hybridization in combination P. fulvum × Р. sativum was significantly less in compare to reciprocal one. All products of that cross combination were tested as hybrids. Unique protein 7 of P. fulvum was revealed as a result of mature seed electrophoretic spectra analysis. Inheritance of that protein was determined as monogenic dominant.

  15. A hybrid computer simulation of reactor spatial dynamics

    International Nuclear Information System (INIS)

    Hinds, H.W.

    1977-08-01

    The partial differential equations describing the one-speed spatial dynamics of thermal neutron reactors were converted to a set of ordinary differential equations, using finite-difference approximations for the spatial derivatives. The variables were then normalized to a steady-state reference condition in a novel manner, to yield an equation set particularly suitable for implementation on a hybrid computer. One Applied Dynamics AD/FIVE analog-computer console is capable of solving, all in parallel, up to 30 simultaneous differential equations. This corresponds roughly to eight reactor nodes, each with two active delayed-neutron groups. To improve accuracy, an increase in the number of nodes is usually required. Using the Hsu-Howe multiplexing technique, an 8-node, one-dimensional module was switched back and forth between the left and right halves of the reactor, to simulate a 16-node model, also in one dimension. These two versions (8 or 16 nodes) of the model were tested on benchmark problems of the loss-of-coolant type, which were also solved using the digital code FORSIM, with two energy groups and 26 nodes. Good agreement was obtained between the two solution techniques. (author)

  16. Performance dependence of hybrid x-ray computed tomography/fluorescence molecular tomography on the optical forward problem.

    Science.gov (United States)

    Hyde, Damon; Schulz, Ralf; Brooks, Dana; Miller, Eric; Ntziachristos, Vasilis

    2009-04-01

    Hybrid imaging systems combining x-ray computed tomography (CT) and fluorescence tomography can improve fluorescence imaging performance by incorporating anatomical x-ray CT information into the optical inversion problem. While the use of image priors has been investigated in the past, little is known about the optimal use of forward photon propagation models in hybrid optical systems. In this paper, we explore the impact on reconstruction accuracy of the use of propagation models of varying complexity, specifically in the context of these hybrid imaging systems where significant structural information is known a priori. Our results demonstrate that the use of generically known parameters provides near optimal performance, even when parameter mismatch remains.

  17. Identification of rice hybrids using microsatellite and RAPD markers

    African Journals Online (AJOL)

    STORAGESEVER

    2009-05-18

    May 18, 2009 ... presence of slower migrating heteroduplex DNA is, there- fore, useful for detection of heterozygous individuals. Maintenance of hybrid seeds conformity in high level is essential for exploitation of hybrid vigor. Therefore, test- ing the hybrid seed purity is necessarily required before its release into the market.

  18. Parallel Computing Characteristics of CUPID code under MPI and Hybrid environment

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jae Ryong; Yoon, Han Young [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Jeon, Byoung Jin; Choi, Hyoung Gwon [Seoul National Univ. of Science and Technology, Seoul (Korea, Republic of)

    2014-05-15

    In this paper, a characteristic of parallel algorithm is presented for solving an elliptic type equation of CUPID via domain decomposition method using the MPI and the parallel performance is estimated in terms of a scalability which shows the speedup ratio. In addition, the time-consuming pattern of major subroutines is studied. Two different grid systems are taken into account: 40,000 meshes for coarse system and 320,000 meshes for fine system. Since the matrix of the CUPID code differs according to whether the flow is single-phase or two-phase, the effect of matrix shape is evaluated. Finally, the effect of the preconditioner for matrix solver is also investigated. Finally, the hybrid (OpenMP+MPI) parallel algorithm is introduced and discussed in detail for solving pressure solver. Component-scale thermal-hydraulics code, CUPID has been developed for two-phase flow analysis, which adopts a three-dimensional, transient, three-field model, and parallelized to fulfill a recent demand for long-transient and highly resolved multi-phase flow behavior. In this study, the parallel performance of the CUPID code was investigated in terms of scalability. The CUPID code was parallelized with domain decomposition method. The MPI library was adopted to communicate the information at the neighboring domain. For managing the sparse matrix effectively, the CSR storage format is used. To take into account the characteristics of the pressure matrix which turns to be asymmetric for two-phase flow, both single-phase and two-phase calculations were run. In addition, the effect of the matrix size and preconditioning was also investigated. The fine mesh calculation shows better scalability than the coarse mesh because the number of coarse mesh does not need to decompose the computational domain excessively. The fine mesh can be present good scalability when dividing geometry with considering the ratio between computation and communication time. For a given mesh, single-phase flow

  19. Accident identification system with automatic detection of abnormal condition using quantum computation

    International Nuclear Information System (INIS)

    Nicolau, Andressa dos Santos; Schirru, Roberto; Lima, Alan Miranda Monteiro de

    2011-01-01

    Transient identification systems have been proposed in order to maintain the plant operating in safe conditions and help operators in make decisions in emergency short time interval with maximum certainty associated. This article presents a system, time independent and without the use of an event that can be used as a starting point for t = 0 (reactor scram, for instance), for transient/accident identification of a pressurized water nuclear reactor (PWR). The model was developed in order to be able to recognize the normal condition and three accidents of the design basis list of the Nuclear Power Plant Angra 2, postulated in the Final Safety Analysis Report (FSAR). Were used several sets of process variables in order to establish a minimum set of variables considered necessary and sufficient. The optimization step of the identification algorithm is based upon the paradigm of Quantum Computing. In this case, the optimization metaheuristic Quantum Inspired Evolutionary Algorithm (QEA) was implemented and works as a data mining tool. The results obtained with the QEA without the time variable are compatible to the techniques in the reference literature, for the transient identification problem, with less computational effort (number of evaluations). This system allows a solution that approximates the ideal solution, the Voronoi Vectors with only one partition for the classes of accidents with robustness. (author)

  20. Solving Problems in Various Domains by Hybrid Models of High Performance Computations

    Directory of Open Access Journals (Sweden)

    Yurii Rogozhin

    2014-03-01

    Full Text Available This work presents a hybrid model of high performance computations. The model is based on membrane system (P~system where some membranes may contain quantum device that is triggered by the data entering the membrane. This model is supposed to take advantages of both biomolecular and quantum paradigms and to overcome some of their inherent limitations. The proposed approach is demonstrated through two selected problems: SAT, and image retrieving.

  1. Contours identification of elements in a cone beam computed tomography for investigating maxillary cysts

    Science.gov (United States)

    Chioran, Doina; Nicoarǎ, Adrian; Roşu, Şerban; Cǎrligeriu, Virgil; Ianeş, Emilia

    2013-10-01

    Digital processing of two-dimensional cone beam computer tomography slicesstarts by identification of the contour of elements within. This paper deals with the collective work of specialists in medicine and applied mathematics in computer science on elaborating and implementation of algorithms in dental 2D imagery.

  2. UPTF test instrumentation. Measurement system identification, engineering units and computed parameters

    International Nuclear Information System (INIS)

    Sarkar, J.; Liebert, J.; Laeufer, R.

    1992-11-01

    This updated version of the previous report /1/ contains, besides additional instrumentation needed for 2D/3D Programme, the supplementary instrumentation in the inlet plenum of SG simulator and hot and cold leg of broken loop, the cold leg of intact loops and the upper plenum to meet the requirements (Test Phase A) of the UPTF Programme, TRAM, sponsored by the Federal Minister of Research and Technology (BMFT) of the Federal Republic of Germany. For understanding, the derivation and the description of the identification codes for the entire conventional and advanced measurement systems classifying the function, and the equipment unit, key, as adopted in the conventional power plants, have been included. Amendments have also been made to the appendices. In particular, the list of measurement systems covering the measurement identification code, instrument, measured quantity, measuring range, band width, uncertainty and sensor location has been updated and extended to include the supplementary instrumentation. Beyond these amendments, the uncertainties of measurements have been precisely specified. The measurement identification codes which also stand for the identification of the corresponding measured quantities in engineering units and the identification codes derived therefrom for the computed parameters have been adequately detailed. (orig.)

  3. Cloth-based hybridization array system for expanded identification of the animal species origin of derived materials in feeds.

    Science.gov (United States)

    Murphy, Johanna; Armour, Jennifer; Blais, Burton W

    2007-12-01

    A cloth-based hybridization array system (CHAS) previously developed for the detection of animal species for which prohibited materials have been specified (cattle, sheep, goat, elk, and deer) has been expanded to include the detection of animal species for which there are no prohibitions (pig and horse) in Canadian and American animal feeds. Animal species were identified by amplification of mitochondrial DNA sequences by PCR and subsequent hybridization of the amplicons with an array of species-specific oligonucleotide capture probes immobilized on a polyester cloth support, followed by an immunoenzymatic assay of the bound PCR products. The CHAS permitted sensitive and specific detection of meat meals from different animal species blended in a grain-based feed and should provide a useful adjunct to microscopic examination for the identification of prohibited materials in animal feeds.

  4. Proposing Hybrid Architecture to Implement Cloud Computing in Higher Education Institutions Using a Meta-synthesis Appro

    Directory of Open Access Journals (Sweden)

    hamid reza bazi

    2017-12-01

    Full Text Available Cloud computing is a new technology that considerably helps Higher Education Institutions (HEIs to develop and create competitive advantage with inherent characteristics such as flexibility, scalability, accessibility, reliability, fault tolerant and economic efficiency. Due to the numerous advantages of cloud computing, and in order to take advantage of cloud computing infrastructure, services of universities and HEIs need to migrate to the cloud. However, this transition involves many challenges, one of which is lack or shortage of appropriate architecture for migration to the technology. Using a reliable architecture for migration ensures managers to mitigate risks in the cloud computing technology. Therefore, organizations always search for suitable cloud computing architecture. In previous studies, these important features have received less attention and have not been achieved in a comprehensive way. The aim of this study is to use a meta-synthesis method for the first time to analyze the previously published studies and to suggest appropriate hybrid cloud migration architecture (IUHEC. We reviewed many papers from relevant journals and conference proceedings. The concepts extracted from these papers are classified to related categories and sub-categories. Then, we developed our proposed hybrid architecture based on these concepts and categories. The proposed architecture was validated by a panel of experts and Lawshe’s model was used to determine the content validity. Due to its innovative yet user-friendly nature, comprehensiveness, and high security, this architecture can help HEIs have an effective migration to cloud computing environment.

  5. Hybrid and hierarchical nanoreinforced polymer composites: Computational modelling of structure–properties relationships

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon; Dai, Gaoming

    2014-01-01

    by using computational micromechanical models. It is shown that while glass/carbon fibers hybrid composites clearly demonstrate higher stiffness and lower weight with increasing the carbon content, they can have lower strength as compared with usual glass fiber polymer composites. Secondary...... nanoreinforcement can drastically increase the fatigue lifetime of composites. Especially, composites with the nanoplatelets localized in the fiber/matrix interface layer (fiber sizing) ensure much higher fatigue lifetime than those with the nanoplatelets in the matrix....

  6. Computational modeling of electrically conductive networks formed by graphene nanoplatelet-carbon nanotube hybrid particles

    KAUST Repository

    Mora Cordova, Angel

    2018-01-30

    One strategy to ensure that nanofiller networks in a polymer composite percolate at low volume fractions is to promote segregation. In a segregated structure, the concentration of nanofillers is kept low in some regions of the sample. In turn, the concentration in remaining regions is much higher than the average concentration of the sample. This selective placement of the nanofillers ensures percolation at low average concentration. One original strategy to promote segregation is by tuning the shape of the nanofillers. We use a computational approach to study the conductive networks formed by hybrid particles obtained by growing carbon nanotubes (CNTs) on graphene nanoplatelets (GNPs). The objective of this study is (1) to show that the higher electrical conductivity of these composites is due to the hybrid particles forming a segregated structure and (2) to understand which parameters defining the hybrid particles determine the efficiency of the segregation. We construct a microstructure to observe the conducting paths and determine whether a segregated structure has indeed been formed inside the composite. A measure of efficiency is presented based on the fraction of nanofillers that contribute to the conductive network. Then, the efficiency of the hybrid-particle networks is compared to those of three other networks of carbon-based nanofillers in which no hybrid particles are used: only CNTs, only GNPs, and a mix of CNTs and GNPs. Finally, some parameters of the hybrid particle are studied: the CNT density on the GNPs, and the CNT and GNP geometries. We also present recommendations for the further improvement of a composite\\'s conductivity based on these parameters.

  7. Computational modeling of electrically conductive networks formed by graphene nanoplatelet-carbon nanotube hybrid particles

    KAUST Repository

    Mora Cordova, Angel; Han, Fei; Lubineau, Gilles

    2018-01-01

    One strategy to ensure that nanofiller networks in a polymer composite percolate at low volume fractions is to promote segregation. In a segregated structure, the concentration of nanofillers is kept low in some regions of the sample. In turn, the concentration in remaining regions is much higher than the average concentration of the sample. This selective placement of the nanofillers ensures percolation at low average concentration. One original strategy to promote segregation is by tuning the shape of the nanofillers. We use a computational approach to study the conductive networks formed by hybrid particles obtained by growing carbon nanotubes (CNTs) on graphene nanoplatelets (GNPs). The objective of this study is (1) to show that the higher electrical conductivity of these composites is due to the hybrid particles forming a segregated structure and (2) to understand which parameters defining the hybrid particles determine the efficiency of the segregation. We construct a microstructure to observe the conducting paths and determine whether a segregated structure has indeed been formed inside the composite. A measure of efficiency is presented based on the fraction of nanofillers that contribute to the conductive network. Then, the efficiency of the hybrid-particle networks is compared to those of three other networks of carbon-based nanofillers in which no hybrid particles are used: only CNTs, only GNPs, and a mix of CNTs and GNPs. Finally, some parameters of the hybrid particle are studied: the CNT density on the GNPs, and the CNT and GNP geometries. We also present recommendations for the further improvement of a composite's conductivity based on these parameters.

  8. PWR hybrid computer model for assessing the safety implications of control systems

    International Nuclear Information System (INIS)

    Smith, O.L.; Renier, J.P.; Difilippo, F.C.; Clapp, N.E.; Sozer, A.; Booth, R.S.; Craddick, W.G.; Morris, D.G.

    1986-03-01

    The ORNL study of safety-related aspects of nuclear power plant control systems consists of two interrelated tasks: (1) failure mode and effects analysis (FMEA) that identified single and multiple component failures that might lead to significant plant upsets and (2) computer models that used these failures as initial conditions and traced the dynamic impact on the control system and remainder of the plant. This report describes the simulation of Oconee Unit 1, the first plant analyzed. A first-principles, best-estimate model was developed and implemented on a hybrid computer consisting of AD-4 analog and PDP-10 digital machines. Controls were placed primarily on the analog to use its interactive capability to simulate operator action. 48 refs., 138 figs., 15 tabs

  9. Simultaneous detection of P300 and steady-state visually evoked potentials for hybrid brain-computer interface.

    Science.gov (United States)

    Combaz, Adrien; Van Hulle, Marc M

    2015-01-01

    We study the feasibility of a hybrid Brain-Computer Interface (BCI) combining simultaneous visual oddball and Steady-State Visually Evoked Potential (SSVEP) paradigms, where both types of stimuli are superimposed on a computer screen. Potentially, such a combination could result in a system being able to operate faster than a purely P300-based BCI and encode more targets than a purely SSVEP-based BCI. We analyse the interactions between the brain responses of the two paradigms, and assess the possibility to detect simultaneously the brain activity evoked by both paradigms, in a series of 3 experiments where EEG data are analysed offline. Despite differences in the shape of the P300 response between pure oddball and hybrid condition, we observe that the classification accuracy of this P300 response is not affected by the SSVEP stimulation. We do not observe either any effect of the oddball stimulation on the power of the SSVEP response in the frequency of stimulation. Finally results from the last experiment show the possibility of detecting both types of brain responses simultaneously and suggest not only the feasibility of such hybrid BCI but also a gain over pure oddball- and pure SSVEP-based BCIs in terms of communication rate.

  10. Improved signal processing approaches in an offline simulation of a hybrid brain–computer interface

    Science.gov (United States)

    Brunner, Clemens; Allison, Brendan Z.; Krusienski, Dean J.; Kaiser, Vera; Müller-Putz, Gernot R.; Pfurtscheller, Gert; Neuper, Christa

    2012-01-01

    In a conventional brain–computer interface (BCI) system, users perform mental tasks that yield specific patterns of brain activity. A pattern recognition system determines which brain activity pattern a user is producing and thereby infers the user’s mental task, allowing users to send messages or commands through brain activity alone. Unfortunately, despite extensive research to improve classification accuracy, BCIs almost always exhibit errors, which are sometimes so severe that effective communication is impossible. We recently introduced a new idea to improve accuracy, especially for users with poor performance. In an offline simulation of a “hybrid” BCI, subjects performed two mental tasks independently and then simultaneously. This hybrid BCI could use two different types of brain signals common in BCIs – event-related desynchronization (ERD) and steady-state evoked potentials (SSEPs). This study suggested that such a hybrid BCI is feasible. Here, we re-analyzed the data from our initial study. We explored eight different signal processing methods that aimed to improve classification and further assess both the causes and the extent of the benefits of the hybrid condition. Most analyses showed that the improved methods described here yielded a statistically significant improvement over our initial study. Some of these improvements could be relevant to conventional BCIs as well. Moreover, the number of illiterates could be reduced with the hybrid condition. Results are also discussed in terms of dual task interference and relevance to protocol design in hybrid BCIs. PMID:20153371

  11. Heterotic computing: exploiting hybrid computational devices.

    Science.gov (United States)

    Kendon, Viv; Sebald, Angelika; Stepney, Susan

    2015-07-28

    Current computational theory deals almost exclusively with single models: classical, neural, analogue, quantum, etc. In practice, researchers use ad hoc combinations, realizing only recently that they can be fundamentally more powerful than the individual parts. A Theo Murphy meeting brought together theorists and practitioners of various types of computing, to engage in combining the individual strengths to produce powerful new heterotic devices. 'Heterotic computing' is defined as a combination of two or more computational systems such that they provide an advantage over either substrate used separately. This post-meeting collection of articles provides a wide-ranging survey of the state of the art in diverse computational paradigms, together with reflections on their future combination into powerful and practical applications. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  12. Hybrid simulation of scatter intensity in industrial cone-beam computed tomography

    International Nuclear Information System (INIS)

    Thierry, R.; Miceli, A.; Hofmann, J.; Flisch, A.; Sennhauser, U.

    2009-01-01

    A cone-beam computed tomography (CT) system using a 450 kV X-ray tube has been developed to challenge the three-dimensional imaging of parts of the automotive industry in short acquisition time. Because the probability of detecting scattered photons is high regarding the energy range and the area of detection, a scattering correction becomes mandatory for generating reliable images with enhanced contrast detectability. In this paper, we present a hybrid simulator for the fast and accurate calculation of the scattering intensity distribution. The full acquisition chain, from the generation of a polyenergetic photon beam, its interaction with the scanned object and the energy deposit in the detector is simulated. Object phantoms can be spatially described in form of voxels, mathematical primitives or CAD models. Uncollided radiation is treated with a ray-tracing method and scattered radiation is split into single and multiple scattering. The single scattering is calculated with a deterministic approach accelerated with a forced detection method. The residual noisy signal is subsequently deconvoluted with the iterative Richardson-Lucy method. Finally the multiple scattering is addressed with a coarse Monte Carlo (MC) simulation. The proposed hybrid method has been validated on aluminium phantoms with varying size and object-to-detector distance, and found in good agreement with the MC code Geant4. The acceleration achieved by the hybrid method over the standard MC on a single projection is approximately of three orders of magnitude.

  13. Computational modeling of electrically conductive networks formed by graphene nanoplatelet-carbon nanotube hybrid particles

    Science.gov (United States)

    Mora, A.; Han, F.; Lubineau, G.

    2018-04-01

    One strategy to ensure that nanofiller networks in a polymer composite percolate at low volume fractions is to promote segregation. In a segregated structure, the concentration of nanofillers is kept low in some regions of the sample. In turn, the concentration in the remaining regions is much higher than the average concentration of the sample. This selective placement of the nanofillers ensures percolation at low average concentration. One original strategy to promote segregation is by tuning the shape of the nanofillers. We use a computational approach to study the conductive networks formed by hybrid particles obtained by growing carbon nanotubes (CNTs) on graphene nanoplatelets (GNPs). The objective of this study is (1) to show that the higher electrical conductivity of these composites is due to the hybrid particles forming a segregated structure and (2) to understand which parameters defining the hybrid particles determine the efficiency of the segregation. We construct a microstructure to observe the conducting paths and determine whether a segregated structure has indeed been formed inside the composite. A measure of efficiency is presented based on the fraction of nanofillers that contribute to the conductive network. Then, the efficiency of the hybrid-particle networks is compared to those of three other networks of carbon-based nanofillers in which no hybrid particles are used: only CNTs, only GNPs, and a mix of CNTs and GNPs. Finally, some parameters of the hybrid particle are studied: the CNT density on the GNPs, and the CNT and GNP geometries. We also present recommendations for the further improvement of a composite’s conductivity based on these parameters.

  14. Applications of hybrid time-frequency methods in nonlinear structural dynamics

    International Nuclear Information System (INIS)

    Politopoulos, I.; Piteau, Ph.; Borsoi, L.; Antunes, J.

    2014-01-01

    This paper presents a study on methods which may be used to compute the nonlinear response of systems whose linear properties are determined in the frequency or Laplace domain. Typically, this kind of situation may arise in soil-structure and fluid-structure interaction problems. In particular three methods are investigated: (a) the hybrid time-frequency method, (b) the computation of the convolution integral which requires an inverse Fourier or Laplace transform of the system's transfer function, and (c) the identification of an equivalent system defined in the time domain which may be solved with classical time integration methods. These methods are illustrated by their application to some simple, one degree of freedom, non-linear systems and their advantages and drawbacks are highlighted. (authors)

  15. Use of 99mTc-sestamibi Single-photon Emission Computed Tomography / X-ray Computed Tomography in the Diagnosis of Hybrid Oncocytic / Chromophobe Tumor in a Pediatric Patient.

    Science.gov (United States)

    Almassi, Nima; Gorin, Michael A; Purysko, Andrei S; Rowe, Steven P; Kaouk, Jihad; Allaf, Mohamad E; Campbell, Steven C; Rhee, Audrey

    2018-03-01

    The differential diagnosis of solid renal neoplasms in adolescence includes aggressive malignancy and indolent oncocytic tumors, which are typically indistinguishable using conventional imaging. We report the use of 99m Tc-sestamibi single-photon emission computed tomography / x-ray computed tomography (SPECT/CT) in characterizing enhancing renal neoplasms in a pediatric patient. Genetic testing suggested a hereditary syndrome associated with aggressive malignancy, whereas renal mass biopsy suggested an oncocytic tumor. 99m Tc-sestamibi SPECT/CT indicated probable oncocytomas or hybrid oncocytic / chomophobe tumors. Enucleative resection was performed with final pathology demonstrating hybrid oncocytic / chomophobe tumors. This case highlights the potential utility of 99m Tc-sestamibi SPECT/CT in characterizing indeterminate enhancing renal neoplasm in pediatric patients. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. A simplified computational fluid-dynamic approach to the oxidizer injector design in hybrid rockets

    Science.gov (United States)

    Di Martino, Giuseppe D.; Malgieri, Paolo; Carmicino, Carmine; Savino, Raffaele

    2016-12-01

    Fuel regression rate in hybrid rockets is non-negligibly affected by the oxidizer injection pattern. In this paper a simplified computational approach developed in an attempt to optimize the oxidizer injector design is discussed. Numerical simulations of the thermo-fluid-dynamic field in a hybrid rocket are carried out, with a commercial solver, to investigate into several injection configurations with the aim of increasing the fuel regression rate and minimizing the consumption unevenness, but still favoring the establishment of flow recirculation at the motor head end, which is generated with an axial nozzle injector and has been demonstrated to promote combustion stability, and both larger efficiency and regression rate. All the computations have been performed on the configuration of a lab-scale hybrid rocket motor available at the propulsion laboratory of the University of Naples with typical operating conditions. After a preliminary comparison between the two baseline limiting cases of an axial subsonic nozzle injector and a uniform injection through the prechamber, a parametric analysis has been carried out by varying the oxidizer jet flow divergence angle, as well as the grain port diameter and the oxidizer mass flux to study the effect of the flow divergence on heat transfer distribution over the fuel surface. Some experimental firing test data are presented, and, under the hypothesis that fuel regression rate and surface heat flux are proportional, the measured fuel consumption axial profiles are compared with the predicted surface heat flux showing fairly good agreement, which allowed validating the employed design approach. Finally an optimized injector design is proposed.

  17. A hybrid NIRS-EEG system for self-paced brain computer interface with online motor imagery.

    Science.gov (United States)

    Koo, Bonkon; Lee, Hwan-Gon; Nam, Yunjun; Kang, Hyohyeong; Koh, Chin Su; Shin, Hyung-Cheul; Choi, Seungjin

    2015-04-15

    For a self-paced motor imagery based brain-computer interface (BCI), the system should be able to recognize the occurrence of a motor imagery, as well as the type of the motor imagery. However, because of the difficulty of detecting the occurrence of a motor imagery, general motor imagery based BCI studies have been focusing on the cued motor imagery paradigm. In this paper, we present a novel hybrid BCI system that uses near infrared spectroscopy (NIRS) and electroencephalography (EEG) systems together to achieve online self-paced motor imagery based BCI. We designed a unique sensor frame that records NIRS and EEG simultaneously for the realization of our system. Based on this hybrid system, we proposed a novel analysis method that detects the occurrence of a motor imagery with the NIRS system, and classifies its type with the EEG system. An online experiment demonstrated that our hybrid system had a true positive rate of about 88%, a false positive rate of 7% with an average response time of 10.36 s. As far as we know, there is no report that explored hemodynamic brain switch for self-paced motor imagery based BCI with hybrid EEG and NIRS system. From our experimental results, our hybrid system showed enough reliability for using in a practical self-paced motor imagery based BCI. Copyright © 2014 Elsevier B.V. All rights reserved.

  18. Resource-Efficient, Hierarchical Auto-Tuning of a Hybrid Lattice Boltzmann Computation on the Cray XT4

    International Nuclear Information System (INIS)

    Williams, Samuel; Carter, Jonathan; Oliker, Leonid; Shalf, John; Yelick, Katherine

    2009-01-01

    We apply auto-tuning to a hybrid MPI-pthreads lattice Boltzmann computation running on the Cray XT4 at National Energy Research Scientific Computing Center (NERSC). Previous work showed that multicore-specific auto-tuning can improve the performance of lattice Boltzmann magnetohydrodynamics (LBMHD) by a factor of 4x when running on dual- and quad-core Opteron dual-socket SMPs. We extend these studies to the distributed memory arena via a hybrid MPI/pthreads implementation. In addition to conventional auto-tuning at the local SMP node, we tune at the message-passing level to determine the optimal aspect ratio as well as the correct balance between MPI tasks and threads per MPI task. Our study presents a detailed performance analysis when moving along an isocurve of constant hardware usage: fixed total memory, total cores, and total nodes. Overall, our work points to approaches for improving intra- and inter-node efficiency on large-scale multicore systems for demanding scientific applications

  19. FMT-XCT: in vivo animal studies with hybrid fluorescence molecular tomography-X-ray computed tomography.

    Science.gov (United States)

    Ale, Angelique; Ermolayev, Vladimir; Herzog, Eva; Cohrs, Christian; de Angelis, Martin Hrabé; Ntziachristos, Vasilis

    2012-06-01

    The development of hybrid optical tomography methods to improve imaging performance has been suggested over a decade ago and has been experimentally demonstrated in animals and humans. Here we examined in vivo performance of a camera-based hybrid fluorescence molecular tomography (FMT) system for 360° imaging combined with X-ray computed tomography (XCT). Offering an accurately co-registered, information-rich hybrid data set, FMT-XCT has new imaging possibilities compared to stand-alone FMT and XCT. We applied FMT-XCT to a subcutaneous 4T1 tumor mouse model, an Aga2 osteogenesis imperfecta model and a Kras lung cancer mouse model, using XCT information during FMT inversion. We validated in vivo imaging results against post-mortem planar fluorescence images of cryoslices and histology data. Besides offering concurrent anatomical and functional information, FMT-XCT resulted in the most accurate FMT performance to date. These findings indicate that addition of FMT optics into the XCT gantry may be a potent upgrade for small-animal XCT systems.

  20. Apps for Angiosperms: The Usability of Mobile Computers and Printed Field Guides for UK Wild Flower and Winter Tree Identification

    Science.gov (United States)

    Stagg, Bethan C.; Donkin, Maria E.

    2017-01-01

    We investigated usability of mobile computers and field guide books with adult botanical novices, for the identification of wildflowers and deciduous trees in winter. Identification accuracy was significantly higher for wildflowers using a mobile computer app than field guide books but significantly lower for deciduous trees. User preference…

  1. A Program for the Identification of the Enterobacteriaceae for Use in Teaching the Principles of Computer Identification of Bacteria.

    Science.gov (United States)

    Hammonds, S. J.

    1990-01-01

    A technique for the numerical identification of bacteria using normalized likelihoods calculated from a probabilistic database is described, and the principles of the technique are explained. The listing of the computer program is included. Specimen results from the program, and examples of how they should be interpreted, are given. (KR)

  2. Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines.

    Science.gov (United States)

    Ma, Ping; Lien, Fue-Sang; Yee, Eugene

    2017-01-01

    This paper develops a computational acoustic beamforming (CAB) methodology for identification of sources of small wind turbine noise. This methodology is validated using the case of the NACA 0012 airfoil trailing edge noise. For this validation case, the predicted acoustic maps were in excellent conformance with the results of the measurements obtained from the acoustic beamforming experiment. Following this validation study, the CAB methodology was applied to the identification of noise sources generated by a commercial small wind turbine. The simulated acoustic maps revealed that the blade tower interaction and the wind turbine nacelle were the two primary mechanisms for sound generation for this small wind turbine at frequencies between 100 and 630 Hz.

  3. Optimization of a continuous hybrid impeller mixer via computational fluid dynamics.

    Science.gov (United States)

    Othman, N; Kamarudin, S K; Takriff, M S; Rosli, M I; Engku Chik, E M F; Meor Adnan, M A K

    2014-01-01

    This paper presents the preliminary steps required for conducting experiments to obtain the optimal operating conditions of a hybrid impeller mixer and to determine the residence time distribution (RTD) using computational fluid dynamics (CFD). In this paper, impeller speed and clearance parameters are examined. The hybrid impeller mixer consists of a single Rushton turbine mounted above a single pitched blade turbine (PBT). Four impeller speeds, 50, 100, 150, and 200 rpm, and four impeller clearances, 25, 50, 75, and 100 mm, were the operation variables used in this study. CFD was utilized to initially screen the parameter ranges to reduce the number of actual experiments needed. Afterward, the residence time distribution (RTD) was determined using the respective parameters. Finally, the Fluent-predicted RTD and the experimentally measured RTD were compared. The CFD investigations revealed that an impeller speed of 50 rpm and an impeller clearance of 25 mm were not viable for experimental investigations and were thus eliminated from further analyses. The determination of RTD using a k-ε turbulence model was performed using CFD techniques. The multiple reference frame (MRF) was implemented and a steady state was initially achieved followed by a transient condition for RTD determination.

  4. Combination of microautoradiography and fluorescence in situ hybridization for identification of microorganisms degrading xenobiotic contaminants.

    Science.gov (United States)

    Yang, Yanru; Zarda, Annatina; Zeyer, Josef

    2003-12-01

    One of the central topics in environmental bioremediation research is to identify microorganisms that are capable of degrading the contaminants of interest. Here we report application of combined microautoradiography (MAR) and fluorescence in situ hybridization (FISH). The method has previously been used in a number of systems; however, here we demonstrate its feasibility in studying the degradation of xenobiotic compounds. With a model system (coculture of Pseudomonas putida B2 and Sphingomonas stygia incubated with [14C] o-nitrophenol), combination of MAR and FISH was shown to be able to successfully identify the microorganisms degrading o-nitrophenol. Compared with the conventional techniques, MAR-FISH allows fast and accurate identification of the microorganisms involved in environmental contaminant degradation.

  5. A hybrid optical switch architecture to integrate IP into optical networks to provide flexible and intelligent bandwidth on demand for cloud computing

    Science.gov (United States)

    Yang, Wei; Hall, Trevor J.

    2013-12-01

    The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users. As a consequence, the nature of the Internet traffic has been fundamentally transformed from a pure packet-based pattern to today's predominantly flow-based pattern. Cloud computing has also brought about an unprecedented growth in the Internet traffic. In this paper, a hybrid optical switch architecture is presented to deal with the flow-based Internet traffic, aiming to offer flexible and intelligent bandwidth on demand to improve fiber capacity utilization. The hybrid optical switch is capable of integrating IP into optical networks for cloud-based traffic with predictable performance, for which the delay performance of the electronic module in the hybrid optical switch architecture is evaluated through simulation.

  6. Symmetric and asymmetric hybrid cryptosystem based on compressive sensing and computer generated holography

    Science.gov (United States)

    Ma, Lihong; Jin, Weimin

    2018-01-01

    A novel symmetric and asymmetric hybrid optical cryptosystem is proposed based on compressive sensing combined with computer generated holography. In this method there are six encryption keys, among which two decryption phase masks are different from the two random phase masks used in the encryption process. Therefore, the encryption system has the feature of both symmetric and asymmetric cryptography. On the other hand, because computer generated holography can flexibly digitalize the encrypted information and compressive sensing can significantly reduce data volume, what is more, the final encryption image is real function by phase truncation, the method favors the storage and transmission of the encryption data. The experimental results demonstrate that the proposed encryption scheme boosts the security and has high robustness against noise and occlusion attacks.

  7. Identification of Enhancers In Human: Advances In Computational Studies

    KAUST Repository

    Kleftogiannis, Dimitrios A.

    2016-03-24

    Roughly ~50% of the human genome, contains noncoding sequences serving as regulatory elements responsible for the diverse gene expression of the cells in the body. One very well studied category of regulatory elements is the category of enhancers. Enhancers increase the transcriptional output in cells through chromatin remodeling or recruitment of complexes of binding proteins. Identification of enhancer using computational techniques is an interesting area of research and up to now several approaches have been proposed. However, the current state-of-the-art methods face limitations since the function of enhancers is clarified, but their mechanism of function is not well understood. This PhD thesis presents a bioinformatics/computer science study that focuses on the problem of identifying enhancers in different human cells using computational techniques. The dissertation is decomposed into four main tasks that we present in different chapters. First, since many of the enhancer’s functions are not well understood, we study the basic biological models by which enhancers trigger transcriptional functions and we survey comprehensively over 30 bioinformatics approaches for identifying enhancers. Next, we elaborate more on the availability of enhancer data as produced by different enhancer identification methods and experimental procedures. In particular, we analyze advantages and disadvantages of existing solutions and we report obstacles that require further consideration. To mitigate these problems we developed the Database of Integrated Human Enhancers (DENdb), a centralized online repository that archives enhancer data from 16 ENCODE cell-lines. The integrated enhancer data are also combined with many other experimental data that can be used to interpret the enhancers content and generate a novel enhancer annotation that complements the existing integrative annotation proposed by the ENCODE consortium. Next, we propose the first deep-learning computational

  8. Noise Threshold and Resource Cost of Fault-Tolerant Quantum Computing with Majorana Fermions in Hybrid Systems.

    Science.gov (United States)

    Li, Ying

    2016-09-16

    Fault-tolerant quantum computing in systems composed of both Majorana fermions and topologically unprotected quantum systems, e.g., superconducting circuits or quantum dots, is studied in this Letter. Errors caused by topologically unprotected quantum systems need to be corrected with error-correction schemes, for instance, the surface code. We find that the error-correction performance of such a hybrid topological quantum computer is not superior to a normal quantum computer unless the topological charge of Majorana fermions is insusceptible to noise. If errors changing the topological charge are rare, the fault-tolerance threshold is much higher than the threshold of a normal quantum computer and a surface-code logical qubit could be encoded in only tens of topological qubits instead of about 1,000 normal qubits.

  9. Developing a personal computer based expert system for radionuclide identification

    International Nuclear Information System (INIS)

    Aarnio, P.A.; Hakulinen, T.T.

    1990-01-01

    Several expert system development tools are available for personal computers today. We have used one of the LISP-based high end tools for nearly two years in developing an expert system for identification of gamma sources. The system contains a radionuclide database of 2055 nuclides and 48000 gamma transitions with a knowledge base of about sixty rules. This application combines a LISP-based inference engine with database management and relatively heavy numerical calculations performed using C-language. The most important feature needed has been the possibility to use LISP and C together with the more advanced object oriented features of the development tool. Main difficulties have been long response times and the big amount (10-16 MB) of computer memory required

  10. Evaluation of a polymerase chain reaction reverse hybridization line probe assay for the detection and identification of medically important fungi in bronchoalveolar lavage fluids.

    NARCIS (Netherlands)

    Meletiadis, J.; Melchers, W.J.G.; Meis, J.F.G.M.; Hurk, P.J.J.C. van den; Jannes, G.; Verweij, P.E.

    2003-01-01

    An assay system in which polymerase chain reaction (PCR) amplification of the ITS-1 region of ribosomal DNA (rDNA) is combined with a reverse-hybridization line probe assay (LiPA) was used for the identification of six Candida species and four Aspergillus species in pure cultures of clinical

  11. Requirements for Control Room Computer-Based Procedures for use in Hybrid Control Rooms

    Energy Technology Data Exchange (ETDEWEB)

    Le Blanc, Katya Lee [Idaho National Lab. (INL), Idaho Falls, ID (United States); Oxstrand, Johanna Helene [Idaho National Lab. (INL), Idaho Falls, ID (United States); Joe, Jeffrey Clark [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-05-01

    Many plants in the U.S. are currently undergoing control room modernization. The main drivers for modernization are the aging and obsolescence of existing equipment, which typically results in a like-for-like replacement of analogue equipment with digital systems. However, the modernization efforts present an opportunity to employ advanced technology that would not only extend the life, but enhance the efficiency and cost competitiveness of nuclear power. Computer-based procedures (CBPs) are one example of near-term advanced technology that may provide enhanced efficiencies above and beyond like for like replacements of analog systems. Researchers in the LWRS program are investigating the benefits of advanced technologies such as CBPs, with the goal of assisting utilities in decision making during modernization projects. This report will describe the existing research on CBPs, discuss the unique issues related to using CBPs in hybrid control rooms (i.e., partially modernized analog control rooms), and define the requirements of CBPs for hybrid control rooms.

  12. Hybrid Methods in Designing Sierpinski Gasket Antennas

    Directory of Open Access Journals (Sweden)

    Mudrik Alaydrus

    2010-12-01

    Full Text Available Sierpinki gasket antennas as example of fractal antennas show multiband characteristics. The computer simulation of Sierpinksi gasket monopole with finite ground needs prohibitively large computer memory and more computational time. Hybrid methods consist of surface integral equation method and physical optics or uniform geometrical theory of diffraction should alleviate this computational burdens. The so-called full hybridization of the different methods with modifying the incoming electromagnetic waves in case of hybrid method surface integral equation method and physical optics and modification of the Greens function for hybrid method surface integral equation method and uniform geometrical theory of diffraction plays the central role in the observation. Comparison between results of different methods are given and also measurements of three Sierpinksi gasket antennas. The multiband characteristics of the antennas still can be seen with some reduction and enhancement of resonances.

  13. Identification of flooded area from satellite images using Hybrid Kohonen Fuzzy C-Means sigma classifier

    Directory of Open Access Journals (Sweden)

    Krishna Kant Singh

    2017-06-01

    Full Text Available A novel neuro fuzzy classifier Hybrid Kohonen Fuzzy C-Means-σ (HKFCM-σ is proposed in this paper. The proposed classifier is a hybridization of Kohonen Clustering Network (KCN with FCM-σ clustering algorithm. The network architecture of HKFCM-σ is similar to simple KCN network having only two layers, i.e., input and output layer. However, the selection of winner neuron is done based on FCM-σ algorithm. Thus, embedding the features of both, a neural network and a fuzzy clustering algorithm in the classifier. This hybridization results in a more efficient, less complex and faster classifier for classifying satellite images. HKFCM-σ is used to identify the flooding that occurred in Kashmir area in September 2014. The HKFCM-σ classifier is applied on pre and post flooding Landsat 8 OLI images of Kashmir to detect the areas that were flooded due to the heavy rainfalls of September, 2014. The classifier is trained using the mean values of the various spectral indices like NDVI, NDWI, NDBI and first component of Principal Component Analysis. The error matrix was computed to test the performance of the method. The method yields high producer’s accuracy, consumer’s accuracy and kappa coefficient value indicating that the proposed classifier is highly effective and efficient.

  14. Computer-aided identification of polymorphism sets diagnostic for groups of bacterial and viral genetic variants

    Directory of Open Access Journals (Sweden)

    Huygens Flavia

    2007-08-01

    Full Text Available Abstract Background Single nucleotide polymorphisms (SNPs and genes that exhibit presence/absence variation have provided informative marker sets for bacterial and viral genotyping. Identification of marker sets optimised for these purposes has been based on maximal generalized discriminatory power as measured by Simpson's Index of Diversity, or on the ability to identify specific variants. Here we describe the Not-N algorithm, which is designed to identify small sets of genetic markers diagnostic for user-specified subsets of known genetic variants. The algorithm does not treat the user-specified subset and the remaining genetic variants equally. Rather Not-N analysis is designed to underpin assays that provide 0% false negatives, which is very important for e.g. diagnostic procedures for clinically significant subgroups within microbial species. Results The Not-N algorithm has been incorporated into the "Minimum SNPs" computer program and used to derive genetic markers diagnostic for multilocus sequence typing-defined clonal complexes, hepatitis C virus (HCV subtypes, and phylogenetic clades defined by comparative genome hybridization (CGH data for Campylobacter jejuni, Yersinia enterocolitica and Clostridium difficile. Conclusion Not-N analysis is effective for identifying small sets of genetic markers diagnostic for microbial sub-groups. The best results to date have been obtained with CGH data from several bacterial species, and HCV sequence data.

  15. Optimization of a Continuous Hybrid Impeller Mixer via Computational Fluid Dynamics

    Directory of Open Access Journals (Sweden)

    N. Othman

    2014-01-01

    Full Text Available This paper presents the preliminary steps required for conducting experiments to obtain the optimal operating conditions of a hybrid impeller mixer and to determine the residence time distribution (RTD using computational fluid dynamics (CFD. In this paper, impeller speed and clearance parameters are examined. The hybrid impeller mixer consists of a single Rushton turbine mounted above a single pitched blade turbine (PBT. Four impeller speeds, 50, 100, 150, and 200 rpm, and four impeller clearances, 25, 50, 75, and 100 mm, were the operation variables used in this study. CFD was utilized to initially screen the parameter ranges to reduce the number of actual experiments needed. Afterward, the residence time distribution (RTD was determined using the respective parameters. Finally, the Fluent-predicted RTD and the experimentally measured RTD were compared. The CFD investigations revealed that an impeller speed of 50 rpm and an impeller clearance of 25 mm were not viable for experimental investigations and were thus eliminated from further analyses. The determination of RTD using a k-ε turbulence model was performed using CFD techniques. The multiple reference frame (MRF was implemented and a steady state was initially achieved followed by a transient condition for RTD determination.

  16. Two molecular markers based on mitochondrial genomes for varieties identification of the northern snakehead (Channa argus) and blotched snakehead (Channa maculata) and their reciprocal hybrids.

    Science.gov (United States)

    Xincheng, Zhang; Kunci, Chen; Xinping, Zhu; Jian, Zhao; Qing, Luo; Xiaoyou, Hong; Wei, Li; Fengfang, Xiao

    2015-08-01

    The northern snakehead (Channa argus) and blotched snakehead (Channa maculata) and their reciprocal hybrids have played important roles in the Chinese freshwater aquaculture industry, with an annual production in China exceeding 400 thousand tons. While these are popular aquaculture breeds in China, it is not easy to identify northern snakehead, blotched snakehead, and their hybrids. Thus, a method should be developed to identify these varieties. To distinguish between the reciprocal hybrids (C. argus ♀ × C. maculata ♂ and C. maculata ♀ × C. argus ♂), the mitochondrial genome sequences of northern snakehead and blotched snakehead and their reciprocal hybrids were compared. Following the alignment and analysis of mtDNA sequences of northern snakehead, blotched snakehead and their hybrids, two pairs of specific primers were designed based on identified differences ranging from 12S rRNA to 16S rRNA gene. The BY1 primers amplified the same bands in the blotched snakehead and the hybrid (C. maculata ♀ × C. argus ♂), while producing no products in northern snakehead and the hybrid (C. argus ♀ × C. maculata ♂). Amplification with WY1 yielded the opposite results. Then, 30 individuals per fish were randomized to verify the primers, and the results showed that the primers were specific for breeds, as intended. The specific primers can not only simply distinguish between two kinds of hybrids, but also rapidly identify the two parents. This study provides a method of molecular marker identification to identify reciprocal hybrids.

  17. Identification of warm day and cool night conditions induced flowering-related genes in a Phalaenopsis orchid hybrid by suppression subtractive hybridization.

    Science.gov (United States)

    Li, D M; Lü, F B; Zhu, G F; Sun, Y B; Xu, Y C; Jiang, M D; Liu, J W; Wang, Z

    2014-02-14

    The influence of warm day and cool night conditions on induction of spikes in Phalaenopsis orchids has been studied with respect to photosynthetic efficiency, metabolic cycles and physiology. However, molecular events involved in spike emergence induced by warm day and cool night conditions are not clearly understood. We examined gene expression induced by warm day and cool night conditions in the Phalaenopsis hybrid Fortune Saltzman through suppression subtractive hybridization, which allowed identification of flowering-related genes in warm day and cool night conditions in spikes and leaves at vegetative phase grown under warm daily temperatures. In total, 450 presumably regulated expressed sequence tags (ESTs) were identified and classified into functional categories, including metabolism, development, transcription factor, signal transduction, transportation, cell defense, and stress. Furthermore, database comparisons revealed a notable number of Phalaenopsis hybrid Fortune Saltzman ESTs that matched genes with unknown function. The expression profiles of 24 genes (from different functional categories) have been confirmed by quantitative real-time PCR in induced spikes and juvenile apical leaves. The results of the real-time PCR showed that, compared to the vegetative apical leaves, the transcripts of genes encoding flowering locus T, AP1, AP2, KNOX1, knotted1-like homeobox protein, R2R3-like MYB, adenosine kinase 2, S-adenosylmethionine synthetase, dihydroflavonol 4-reductase, and naringenin 3-dioxygenase accumulated significantly higher levels, and genes encoding FCA, retrotransposon protein Ty3 and C3HC4-type RING finger protein accumulated remarkably lower levels in spikes of early developmental stages. These results suggested that the genes of two expression changing trends may play positive and negative roles in the early floral transition of Phalaenopsis orchids. In conclusion, spikes induced by warm day and cool night conditions were complex in

  18. Data of NODDI diffusion metrics in the brain and computer simulation of hybrid diffusion imaging (HYDI acquisition scheme

    Directory of Open Access Journals (Sweden)

    Chandana Kodiweera

    2016-06-01

    Full Text Available This article provides NODDI diffusion metrics in the brains of 52 healthy participants and computer simulation data to support compatibility of hybrid diffusion imaging (HYDI, “Hybrid diffusion imaging” [1] acquisition scheme in fitting neurite orientation dispersion and density imaging (NODDI model, “NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain” [2]. HYDI is an extremely versatile diffusion magnetic resonance imaging (dMRI technique that enables various analyzes methods using a single diffusion dataset. One of the diffusion data analysis methods is the NODDI computation, which models the brain tissue with three compartments: fast isotropic diffusion (e.g., cerebrospinal fluid, anisotropic hindered diffusion (e.g., extracellular space, and anisotropic restricted diffusion (e.g., intracellular space. The NODDI model produces microstructural metrics in the developing brain, aging brain or human brain with neurologic disorders. The first dataset provided here are the means and standard deviations of NODDI metrics in 48 white matter region-of-interest (ROI averaging across 52 healthy participants. The second dataset provided here is the computer simulation with initial conditions guided by the first dataset as inputs and gold standard for model fitting. The computer simulation data provide a direct comparison of NODDI indices computed from the HYDI acquisition [1] to the NODDI indices computed from the originally proposed acquisition [2]. These data are related to the accompanying research article “Age Effects and Sex Differences in Human Brain White Matter of Young to Middle-Aged Adults: A DTI, NODDI, and q-Space Study” [3].

  19. Recent Advances on Hybrid Intelligent Systems

    CERN Document Server

    Melin, Patricia; Kacprzyk, Janusz

    2013-01-01

    This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algo...

  20. Semiempirical Quantum Chemical Calculations Accelerated on a Hybrid Multicore CPU-GPU Computing Platform.

    Science.gov (United States)

    Wu, Xin; Koslowski, Axel; Thiel, Walter

    2012-07-10

    In this work, we demonstrate that semiempirical quantum chemical calculations can be accelerated significantly by leveraging the graphics processing unit (GPU) as a coprocessor on a hybrid multicore CPU-GPU computing platform. Semiempirical calculations using the MNDO, AM1, PM3, OM1, OM2, and OM3 model Hamiltonians were systematically profiled for three types of test systems (fullerenes, water clusters, and solvated crambin) to identify the most time-consuming sections of the code. The corresponding routines were ported to the GPU and optimized employing both existing library functions and a GPU kernel that carries out a sequence of noniterative Jacobi transformations during pseudodiagonalization. The overall computation times for single-point energy calculations and geometry optimizations of large molecules were reduced by one order of magnitude for all methods, as compared to runs on a single CPU core.

  1. PWR hybrid computer model for assessing the safety implications of control systems

    International Nuclear Information System (INIS)

    Smith, O.L.; Booth, R.S.; Clapp, N.E.; DiFilippo, F.C.; Renier, J.P.; Sozer, A.

    1985-01-01

    The ORNL study of safety-related aspects of control systems consists of two interrelated tasks, (1) a failure mode and effects analysis that, in part, identifies single and multiple component failures that may lead to significant plant upsets, and (2) a hybrid computer model that uses these failures as initial conditions and traces the dynamic impact on the control system and remainder of the plant. The second task is reported here. The initial step in model development was to define a suitable interface between the FMEA and computer simulation tasks. This involved identifying primary plant components that must be simulated in dynamic detail and secondary components that can be treated adequately by the FMEA alone. The FMEA in general explores broader spectra of initiating events that may collapse into a reduced number of computer runs. A portion of the FMEA includes consideration of power supply failures. Consequences of the transients may feedback on the initiating causes, and there may be an interactive relationship between the FMEA and the computer simulation. Since the thrust of this program is to investigate control system behavior, the controls are modeled in detail to accurately reproduce characteristic response under normal and off-normal transients. The balance of the model, including neutronics, thermohydraulics and component submodels, is developed in sufficient detail to provide a suitable support for the control system

  2. Hybrid Brain–Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review

    Science.gov (United States)

    Hong, Keum-Shik; Khan, Muhammad Jawad

    2017-01-01

    In this article, non-invasive hybrid brain–computer interface (hBCI) technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG), due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spectroscopy (fNIRS), electromyography (EMG), electrooculography (EOG), and eye tracker. Three main purposes of hybridization are to increase the number of control commands, improve classification accuracy and reduce the signal detection time. Currently, such combinations of EEG + fNIRS and EEG + EOG are most commonly employed. Four principal components (i.e., hardware, paradigm, classifiers, and features) relevant to accuracy improvement are discussed. In the case of brain signals, motor imagination/movement tasks are combined with cognitive tasks to increase active brain–computer interface (BCI) accuracy. Active and reactive tasks sometimes are combined: motor imagination with steady-state evoked visual potentials (SSVEP) and motor imagination with P300. In the case of reactive tasks, SSVEP is most widely combined with P300 to increase the number of commands. Passive BCIs, however, are rare. After discussing the hardware and strategies involved in the development of hBCI, the second part examines the approaches used to increase the number of control commands and to enhance classification accuracy. The future prospects and the extension of hBCI in real-time applications for daily life scenarios are provided. PMID:28790910

  3. Hybrid Brain-Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review.

    Science.gov (United States)

    Hong, Keum-Shik; Khan, Muhammad Jawad

    2017-01-01

    In this article, non-invasive hybrid brain-computer interface (hBCI) technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG), due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spectroscopy (fNIRS), electromyography (EMG), electrooculography (EOG), and eye tracker. Three main purposes of hybridization are to increase the number of control commands, improve classification accuracy and reduce the signal detection time. Currently, such combinations of EEG + fNIRS and EEG + EOG are most commonly employed. Four principal components (i.e., hardware, paradigm, classifiers, and features) relevant to accuracy improvement are discussed. In the case of brain signals, motor imagination/movement tasks are combined with cognitive tasks to increase active brain-computer interface (BCI) accuracy. Active and reactive tasks sometimes are combined: motor imagination with steady-state evoked visual potentials (SSVEP) and motor imagination with P300. In the case of reactive tasks, SSVEP is most widely combined with P300 to increase the number of commands. Passive BCIs, however, are rare. After discussing the hardware and strategies involved in the development of hBCI, the second part examines the approaches used to increase the number of control commands and to enhance classification accuracy. The future prospects and the extension of hBCI in real-time applications for daily life scenarios are provided.

  4. Hybrid Brain–Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review

    Directory of Open Access Journals (Sweden)

    Keum-Shik Hong

    2017-07-01

    Full Text Available In this article, non-invasive hybrid brain–computer interface (hBCI technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG, due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spectroscopy (fNIRS, electromyography (EMG, electrooculography (EOG, and eye tracker. Three main purposes of hybridization are to increase the number of control commands, improve classification accuracy and reduce the signal detection time. Currently, such combinations of EEG + fNIRS and EEG + EOG are most commonly employed. Four principal components (i.e., hardware, paradigm, classifiers, and features relevant to accuracy improvement are discussed. In the case of brain signals, motor imagination/movement tasks are combined with cognitive tasks to increase active brain–computer interface (BCI accuracy. Active and reactive tasks sometimes are combined: motor imagination with steady-state evoked visual potentials (SSVEP and motor imagination with P300. In the case of reactive tasks, SSVEP is most widely combined with P300 to increase the number of commands. Passive BCIs, however, are rare. After discussing the hardware and strategies involved in the development of hBCI, the second part examines the approaches used to increase the number of control commands and to enhance classification accuracy. The future prospects and the extension of hBCI in real-time applications for daily life scenarios are provided.

  5. Morphological identification of Lucilia sericata, Lucilia cuprina and their hybrids (Diptera, Calliphoridae)

    Science.gov (United States)

    Williams, Kirstin A.; Villet, Martin H.

    2014-01-01

    Abstract Hybrids of Lucilia sericata and Lucilia cuprina have been shown to exist in previous studies using molecular methods, but no study has shown explicitly that these hybrids can be identified morphologically. Published morphological characters used to identify L. sericata and L. cuprina were reviewed, and then scored and tested using specimens of both species and known hybrids. Ordination by multi-dimensional scaling indicated that the species were separable, and that hybrids resembled L. cuprina, whatever their origin. Discriminant function analysis of the characters successfully separated the specimens into three unambiguous groups – L. sericata, L. cuprina and hybrids. The hybrids were morphologically similar irrespective of whether they were from an ancient introgressed lineage or more modern. This is the first evidence that hybrids of these two species can be identified from their morphology. The usefulness of the morphological characters is also discussed and photographs of several characters are included to facilitate their assessment. PMID:25061373

  6. Development of the method of aggregation to determine the current storage area using computer vision and radiofrequency identification

    Science.gov (United States)

    Astafiev, A.; Orlov, A.; Privezencev, D.

    2018-01-01

    The article is devoted to the development of technology and software for the construction of positioning and control systems in industrial plants based on aggregation to determine the current storage area using computer vision and radiofrequency identification. It describes the developed of the project of hardware for industrial products positioning system in the territory of a plant on the basis of radio-frequency grid. It describes the development of the project of hardware for industrial products positioning system in the plant on the basis of computer vision methods. It describes the development of the method of aggregation to determine the current storage area using computer vision and radiofrequency identification. Experimental studies in laboratory and production conditions have been conducted and described in the article.

  7. What will be eventually true of polymomial hybrid automata

    DEFF Research Database (Denmark)

    Fränzle, Martin

    2001-01-01

    Hybrid automata have been introduced in both control engineering and computer science as a formal model for the dynamics of hybrid discrete-continuous systems. While computability issues concerning safety properties have been extensively studied, liveness properties have remained largely uninvest......Hybrid automata have been introduced in both control engineering and computer science as a formal model for the dynamics of hybrid discrete-continuous systems. While computability issues concerning safety properties have been extensively studied, liveness properties have remained largely...... uninvestigated. In this article, we investigate decidability of state recurrence and of progress properties. First, we show that state recurrence and progress are in general undecidable for polynomial hybrid automata. Then, we demonstrate that they are closely related for hybrid automata subject to a simple...... model of noise, even though these automata are infinite-state systems. Based on this, we augment a semi-decision procedure for recurrence with a semi-decision method for length-boundedness of paths in such a way that we obtain an automatic verification method for progress properties of linear...

  8. Establishment of hybridized focus measure functions as a universal method for autofocusing

    Science.gov (United States)

    Shah, Mohammad Imran; Mishra, Smriti; Rout, Chittaranjan

    2017-12-01

    Exact focusing is essential for any automatic image capturing system. Performances of focus measure functions (FMFs) used for autofocusing are sensitive to image contents and imaging systems. Therefore, identification of universal FMF assumes a lot of significance. Eight FMFs were hybridized in pairs of two and implemented simultaneously on a single stack to calculate the hybrid focus measure. In total, 28 hybrid FMFs (HFMFs) and eight FMFs were implemented on stacks of images from three different imaging modalities. Performance of FMFs was found to the best at 50% region sampling. Accuracy, focus error, and false maxima were calculated to evaluate the performance of each FMF. Nineteen HFMFs provided >90% accuracy. Image distortion (noise, contrast, saturation, illumination, etc.) was performed to evaluate robustness of HFMFs. Hybrid of tenengrad variance and steerable filter-based (VGRnSFB) FMFs was identified as the most robust and accurate function with an accuracy of ≥90% and a relatively lower focus error and false maxima rate. Sharpness of focus curve of VGRnSFB along with eight individual FMFs was also computed to determine the efficacy of HFMF for the optimization process. VGRnSFB HFMF may be implemented for automated capturing of an image for any imaging system.

  9. Electric/Hybrid Vehicle Simulation

    Science.gov (United States)

    Slusser, R. A.; Chapman, C. P.; Brennand, J. P.

    1985-01-01

    ELVEC computer program provides vehicle designer with simulation tool for detailed studies of electric and hybrid vehicle performance and cost. ELVEC simulates performance of user-specified electric or hybrid vehicle under user specified driving schedule profile or operating schedule. ELVEC performs vehicle design and life cycle cost analysis.

  10. Hybrid-augmented intelligence:collaboration and cognition

    Institute of Scientific and Technical Information of China (English)

    Nan-ning ZHENG; Zi-yi LIU; Peng-ju REN; Yong-qiang MA; Shi-tao CHEN; Si-yu YU; Jian-ru XUE

    2017-01-01

    The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models:one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.

  11. COED Transactions, Vol. X, No. 10, October 1978. Simulation of a Sampled-Data System on a Hybrid Computer.

    Science.gov (United States)

    Mitchell, Eugene E., Ed.

    The simulation of a sampled-data system is described that uses a full parallel hybrid computer. The sampled data system simulated illustrates the proportional-integral-derivative (PID) discrete control of a continuous second-order process representing a stirred-tank. The stirred-tank is simulated using continuous analog components, while PID…

  12. ANIBAL - a Hybrid Computer Language for EAI 680-PDP 8/I, FPP 12

    DEFF Research Database (Denmark)

    Højberg, Kristian Søe

    1974-01-01

    and special hybrid computer commands. ANIBAL consists of a general-purpose analog interface subroutine ANI and the macro processor 8BAL (DECUS NO 8-497A.1). When a source program with FORTRAN and 8BAL statements is processed, the FORTRAN statements are transferred unchanged, while the 8BAL code is translated...... essentially to ANI sub-routine calls, which are defined in a macro library. The resulting code is translated by the standard FORTRAN compiler. The language is very flexible as the instructions can be changed and commands can be added to or excluded from the library ....

  13. Identification of pine hybrids using SSR loci.: scientific paper | Doyle ...

    African Journals Online (AJOL)

    We have screened 11 microsatellite markers developed in other Pinus species for their ability to produce fingerprints in the Pinus elliottii x Pinus caribaea hybrid as well as their ability to determine gene flow and parental contribution in this hybrid. We found that cross-species amplification was possible with two thirds of the ...

  14. Fluorescence In Situ Hybridization with Peptide Nucleic Acid Probes for Rapid Identification of Candida albicans Directly from Blood Culture Bottles

    Science.gov (United States)

    Rigby, Susan; Procop, Gary W.; Haase, Gerhard; Wilson, Deborah; Hall, Geraldine; Kurtzman, Cletus; Oliveira, Kenneth; Von Oy, Sabina; Hyldig-Nielsen, Jens J.; Coull, James; Stender, Henrik

    2002-01-01

    A new fluorescence in situ hybridization (FISH) method that uses peptide nucleic acid (PNA) probes for identification of Candida albicans directly from positive-blood-culture bottles in which yeast was observed by Gram staining (herein referred to as yeast-positive blood culture bottles) is described. The test (the C. albicans PNA FISH method) is based on a fluorescein-labeled PNA probe that targets C. albicans 26S rRNA. The PNA probe is added to smears made directly from the contents of the blood culture bottle and hybridized for 90 min at 55°C. Unhybridized PNA probe is removed by washing of the mixture (30 min), and the smears are examined by fluorescence microscopy. The specificity of the method was confirmed with 23 reference strains representing phylogenetically related yeast species and 148 clinical isolates covering the clinically most significant yeast species, including C. albicans (n = 72), C. dubliniensis (n = 58), C. glabrata (n = 5), C. krusei (n = 2), C. parapsilosis (n = 4), and C. tropicalis (n = 3). The performance of the C. albicans PNA FISH method as a diagnostic test was evaluated with 33 routine and 25 simulated yeast-positive blood culture bottles and showed 100% sensitivity and 100% specificity. It is concluded that this 2.5-h method for the definitive identification of C. albicans directly from yeast-positive blood culture bottles provides important information for optimal antifungal therapy and patient management. PMID:12037084

  15. Advancing surgical guidance : from (hybrid) molecule to man and beyond

    NARCIS (Netherlands)

    Berg, van den N.S.

    2016-01-01

    The work described in this thesis shows how intraoperative lesion identification can be improved via the introduction of (hybrid) tracers and optimised (hybrid) imaging modalities capable of detecting this tracers. In part one, the reader is introduced to the concept of fluorescence image-guided

  16. Heart dosimetry in radiotherapy with hybrid computational phantoms

    International Nuclear Information System (INIS)

    Moignier, Cyril

    2014-01-01

    Cardiovascular diseases following radiotherapy are major secondary late effects raising questions among the scientific community, especially regarding the dose-effect relationship and confounding risk factors (chemotherapy, cholesterolemia, age at treatment, blood pressure,..). Post-radiation coronary diseases are one of the main causes of cardiac morbidity. Some approximations are made when coronary doses due to radiotherapy are estimated, especially regarding the morphology. For retrospective studies with old medical records, only radiographs are usually available with sometimes some contours made with a simulator. For recent medical records, CT scans displaying the anatomy in 3D are used for radiotherapy simulation but do not allow the coronary artery visualization due to low resolution and contrast. Currently, coronary doses are barely assessed in clinical practice, and when it is done, anatomical prior knowledge is generally used. This thesis proposes an original approach based on hybrid computational phantoms to study coronary artery doses following radiotherapy for left-side breast cancer and Hodgkin lymphoma. During the thesis, a method inserting hybrid computational phantoms in a DICOM format into the treatment planning system has been developed and validated. It has been adapted and tested in conditions where only radiographs provide anatomical information, as with old medical records for left side breast radiotherapy. The method has also been adapted to perform precise dose reconstructions to the coronary artery for patients treated for a mediastinal Hodgkin lymphoma and diagnosed with coronary stenosis through a coroscanner. A case-control study was carried out and the risk of coronary stenosis on a coronary artery segment was assessed to be multiplied by 1.049 at each additional gray on the median dose to the coronary artery segment. For recent medical records, coronary doses uncertainties related to an approach by anatomical prior knowledge

  17. Genome-wide identification of the regulatory targets of a transcription factor using biochemical characterization and computational genomic analysis

    Directory of Open Access Journals (Sweden)

    Jolly Emmitt R

    2005-11-01

    Full Text Available Abstract Background A major challenge in computational genomics is the development of methodologies that allow accurate genome-wide prediction of the regulatory targets of a transcription factor. We present a method for target identification that combines experimental characterization of binding requirements with computational genomic analysis. Results Our method identified potential target genes of the transcription factor Ndt80, a key transcriptional regulator involved in yeast sporulation, using the combined information of binding affinity, positional distribution, and conservation of the binding sites across multiple species. We have also developed a mathematical approach to compute the false positive rate and the total number of targets in the genome based on the multiple selection criteria. Conclusion We have shown that combining biochemical characterization and computational genomic analysis leads to accurate identification of the genome-wide targets of a transcription factor. The method can be extended to other transcription factors and can complement other genomic approaches to transcriptional regulation.

  18. An Efficient Framework for EEG Analysis with Application to Hybrid Brain Computer Interfaces Based on Motor Imagery and P300

    Directory of Open Access Journals (Sweden)

    Jinyi Long

    2017-01-01

    Full Text Available The hybrid brain computer interface (BCI based on motor imagery (MI and P300 has been a preferred strategy aiming to improve the detection performance through combining the features of each. However, current methods used for combining these two modalities optimize them separately, which does not result in optimal performance. Here, we present an efficient framework to optimize them together by concatenating the features of MI and P300 in a block diagonal form. Then a linear classifier under a dual spectral norm regularizer is applied to the combined features. Under this framework, the hybrid features of MI and P300 can be learned, selected, and combined together directly. Experimental results on the data set of hybrid BCI based on MI and P300 are provided to illustrate competitive performance of the proposed method against other conventional methods. This provides an evidence that the method used here contributes to the discrimination performance of the brain state in hybrid BCI.

  19. EEG Classification for Hybrid Brain-Computer Interface Using a Tensor Based Multiclass Multimodal Analysis Scheme.

    Science.gov (United States)

    Ji, Hongfei; Li, Jie; Lu, Rongrong; Gu, Rong; Cao, Lei; Gong, Xiaoliang

    2016-01-01

    Electroencephalogram- (EEG-) based brain-computer interface (BCI) systems usually utilize one type of changes in the dynamics of brain oscillations for control, such as event-related desynchronization/synchronization (ERD/ERS), steady state visual evoked potential (SSVEP), and P300 evoked potentials. There is a recent trend to detect more than one of these signals in one system to create a hybrid BCI. However, in this case, EEG data were always divided into groups and analyzed by the separate processing procedures. As a result, the interactive effects were ignored when different types of BCI tasks were executed simultaneously. In this work, we propose an improved tensor based multiclass multimodal scheme especially for hybrid BCI, in which EEG signals are denoted as multiway tensors, a nonredundant rank-one tensor decomposition model is proposed to obtain nonredundant tensor components, a weighted fisher criterion is designed to select multimodal discriminative patterns without ignoring the interactive effects, and support vector machine (SVM) is extended to multiclass classification. Experiment results suggest that the proposed scheme can not only identify the different changes in the dynamics of brain oscillations induced by different types of tasks but also capture the interactive effects of simultaneous tasks properly. Therefore, it has great potential use for hybrid BCI.

  20. Integration of Computed Tomography and Three-Dimensional Echocardiography for Hybrid Three-Dimensional Printing in Congenital Heart Disease.

    Science.gov (United States)

    Gosnell, Jordan; Pietila, Todd; Samuel, Bennett P; Kurup, Harikrishnan K N; Haw, Marcus P; Vettukattil, Joseph J

    2016-12-01

    Three-dimensional (3D) printing is an emerging technology aiding diagnostics, education, and interventional, and surgical planning in congenital heart disease (CHD). Three-dimensional printing has been derived from computed tomography, cardiac magnetic resonance, and 3D echocardiography. However, individually the imaging modalities may not provide adequate visualization of complex CHD. The integration of the strengths of two or more imaging modalities has the potential to enhance visualization of cardiac pathomorphology. We describe the feasibility of hybrid 3D printing from two imaging modalities in a patient with congenitally corrected transposition of the great arteries (L-TGA). Hybrid 3D printing may be useful as an additional tool for cardiologists and cardiothoracic surgeons in planning interventions in children and adults with CHD.

  1. Automated DNA electrophoresis, hybridization and detection

    International Nuclear Information System (INIS)

    Zapolski, E.J.; Gersten, D.M.; Golab, T.J.; Ledley, R.S.

    1986-01-01

    A fully automated, computer controlled system for nucleic acid hybridization analysis has been devised and constructed. In practice, DNA is digested with restriction endonuclease enzyme(s) and loaded into the system by pipette; 32 P-labelled nucleic acid probe(s) is loaded into the nine hybridization chambers. Instructions for all the steps in the automated process are specified by answering questions that appear on the computer screen at the start of the experiment. Subsequent steps are performed automatically. The system performs horizontal electrophoresis in agarose gel, fixed the fragments to a solid phase matrix, denatures, neutralizes, prehybridizes, hybridizes, washes, dries and detects the radioactivity according to the specifications given by the operator. The results, printed out at the end, give the positions on the matrix to which radioactivity remains hybridized following stringent washing

  2. Molecular identification of hybrids from a former hot spot of Potamogeton hybrid diversity

    Czech Academy of Sciences Publication Activity Database

    Kaplan, Zdeněk; Fehrer, Judith

    2013-01-01

    Roč. 105, Feb 2013 (2013), s. 34-40 ISSN 0304-3770 R&D Projects: GA ČR GA206/09/0291 Institutional support: RVO:67985939 Keywords : hybridization * taxonomy * diversity Subject RIV: EF - Botanics Impact factor: 1.471, year: 2013

  3. Hybrid rocket engine, theoretical model and experiment

    Science.gov (United States)

    Chelaru, Teodor-Viorel; Mingireanu, Florin

    2011-06-01

    The purpose of this paper is to build a theoretical model for the hybrid rocket engine/motor and to validate it using experimental results. The work approaches the main problems of the hybrid motor: the scalability, the stability/controllability of the operating parameters and the increasing of the solid fuel regression rate. At first, we focus on theoretical models for hybrid rocket motor and compare the results with already available experimental data from various research groups. A primary computation model is presented together with results from a numerical algorithm based on a computational model. We present theoretical predictions for several commercial hybrid rocket motors, having different scales and compare them with experimental measurements of those hybrid rocket motors. Next the paper focuses on tribrid rocket motor concept, which by supplementary liquid fuel injection can improve the thrust controllability. A complementary computation model is also presented to estimate regression rate increase of solid fuel doped with oxidizer. Finally, the stability of the hybrid rocket motor is investigated using Liapunov theory. Stability coefficients obtained are dependent on burning parameters while the stability and command matrixes are identified. The paper presents thoroughly the input data of the model, which ensures the reproducibility of the numerical results by independent researchers.

  4. Cardiac hybrid imaging

    Energy Technology Data Exchange (ETDEWEB)

    Gaemperli, Oliver [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); University Hospital Zurich, Nuclear Cardiology, Cardiovascular Center, Zurich (Switzerland); Kaufmann, Philipp A. [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); Alkadhi, Hatem [University Hospital Zurich, Institute of Diagnostic and Interventional Radiology, Zurich (Switzerland)

    2014-05-15

    Hybrid cardiac single photon emission computed tomography (SPECT)/CT imaging allows combined assessment of anatomical and functional aspects of cardiac disease. In coronary artery disease (CAD), hybrid SPECT/CT imaging allows detection of coronary artery stenosis and myocardial perfusion abnormalities. The clinical value of hybrid imaging has been documented in several subsets of patients. In selected groups of patients, hybrid imaging improves the diagnostic accuracy to detect CAD compared to the single imaging techniques. Additionally, this approach facilitates functional interrogation of coronary stenoses and guidance with regard to revascularization procedures. Moreover, the anatomical information obtained from CT coronary angiography or coronary artery calcium scores (CACS) adds prognostic information over perfusion data from SPECT. The use of cardiac hybrid imaging has been favoured by the dissemination of dedicated hybrid systems and the release of dedicated image fusion software, which allow simple patient throughput for hybrid SPECT/CT studies. Further technological improvements such as more efficient detector technology to allow for low-radiation protocols, ultra-fast image acquisition and improved low-noise image reconstruction algorithms will be instrumental to further promote hybrid SPECT/CT in research and clinical practice. (orig.)

  5. Specification and Verification of Hybrid System

    International Nuclear Information System (INIS)

    Widjaja, Belawati H.

    1997-01-01

    Hybrid systems are reactive systems which intermix between two components, discrete components and continuous components. The continuous components are usually called plants, subject to disturbances which cause the state variables of the systems changing continuously by physical laws and/or by the control laws. The discrete components can be digital computers, sensor and actuators controlled by programs. These programs are designed to select, control and supervise the behavior of the continuous components. Specification and verification of hybrid systems has recently become an active area of research in both computer science and control engineering, many papers concerning hybrid system have been published. This paper gives a design methodology for hybrid systems as an example to the specification and verification of hybrid systems. The design methodology is based on the cooperation between two disciplines, control engineering and computer science. The methodology brings into the design of control loops and decision loops. The external behavior of control loops are specified in a notation which is understandable by the two disciplines. The design of control loops which employed theory of differential equation is done by control engineers, and its correctness is also guaranteed analytically or experimentally by control engineers. The decision loops are designed in computing science based on the specifications of control loops. The verification of systems requirements can be done by computing scientists using a formal reasoning mechanism. For illustrating the proposed design, a problem of balancing an inverted pendulum which is a popular experiment device in control theory is considered, and the Mean Value Calculus is chosen as a formal notation for specifying the control loops and designing the decision loops

  6. The theory of hybrid stochastic algorithms

    International Nuclear Information System (INIS)

    Duane, S.; Kogut, J.B.

    1986-01-01

    The theory of hybrid stochastic algorithms is developed. A generalized Fokker-Planck equation is derived and is used to prove that the correct equilibrium distribution is generated by the algorithm. Systematic errors following from the discrete time-step used in the numerical implementation of the scheme are computed. Hybrid algorithms which simulate lattice gauge theory with dynamical fermions are presented. They are optimized in computer simulations and their systematic errors and efficiencies are studied. (orig.)

  7. Nonlinear identification of process dynamics using neural networks

    International Nuclear Information System (INIS)

    Parlos, A.G.; Atiya, A.F.; Chong, K.T.

    1992-01-01

    In this paper the nonlinear identification of process dynamics encountered in nuclear power plant components is addressed, in an input-output sense, using artificial neural systems. A hybrid feedforward/feedback neural network, namely, a recurrent multilayer perceptron, is used as the model structure to be identified. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard backpropagation learning algorithm is modified, and it is used for the supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying process dynamics is investigated via the case study of a U-tube steam generator. The response of representative steam generator is predicted using a neural network, and it is compared to the response obtained from a sophisticated computer model based on first principles. The transient responses compare well, although further research is warranted to determine the predictive capabilities of these networks during more severe operational transients and accident scenarios

  8. Possibilities of the new hybrid technology single photon emission computer technology/computer tomography (SPECT/CT) and the first impressions of its application

    International Nuclear Information System (INIS)

    Kostadinova, I.

    2010-01-01

    With the help of the new hybrid technique SPECT/ CT it is possible, using the only investigation, to acquire a combine image of the investigated organ, visualizing its function and structure. Combining the possibilities of the new multimodality method, which combines the possibilities of the Single Photon Emission Computer Tomography - SPECT and Computer Tomography - CT, it is possible to precisely localize the pathologically changed organs function. With the further combination of the tomographic gamma camera with diagnostic CT, a detailed morphological evaluation of the finding was possible. The main clinical application of the new hybrid diagnostic is in the fields of cardiology, oncology, orthopedics with more and more extension of those, not connected with oncology, such as - thyroid, parathyroid, brain (especially localization of the epileptic foci), visualization of local infection and recently for the purposes of the radiotherapy planning. According to the literature data, around 35% of SPECT-investigations have to be combined with CT in order to increase the specificity of the diagnosis, which changes the interpretation of the result in 56% of the cases. After installation of the SPECT/CT camera in the University hospital 'Alexandrovska' in January 2009, the following changes have been done: the number of the investigated patients have increased, including number of heart, thyroid (especially scintigraphy with 131I), bones and parathyroid glands. As a result of the application of the hybrid technique, a shortage of the investigated time was realized and a decrease prize in comparison with the individual application of the investigations. Summarizing the literature data and the preliminary impression of the first multimodality scanner in our country in the University hospital 'Alexandrovska' it could be said, that there is continuously increasing information for the new clinical applications of SPECT/CT. It is now accepted, that its usage will increase in

  9. Learning Support Assessment Study of a Computer Simulation for the Development of Microbial Identification Strategies

    Directory of Open Access Journals (Sweden)

    Tristan E. Johnson

    2009-12-01

    Full Text Available This paper describes a study that examined how microbiology students construct knowledge of bacterial identification while using a computer simulation. The purpose of this study was to understand how the simulation affects the cognitive processing of students during thinking, problem solving, and learning about bacterial identification and to determine how the simulation facilitates the learning of a domain-specific problem-solving strategy. As part of an upper-division microbiology course, five students participated in several simulation assignments. The data were collected using think-aloud protocol and video action logs as the students used the simulation. The analysis revealed two major themes that determined the performance of the students: Simulation Usage—how the students used the software features and Problem-Solving Strategy Development—the strategy level students started with and the skill level they achieved when they completed their use of the simulation. Several conclusions emerged from the analysis of the data: (i The simulation affects various aspects of cognitive processing by creating an environment that makes it possible to practice the application of a problem-solving strategy. The simulation was used as an environment that allowed students to practice the cognitive skills required to solve an unknown. (ii Identibacter (the computer simulation may be considered to be a cognitive tool to facilitate the learning of a bacterial identification problem-solving strategy. (iii The simulation characteristics did support student learning of a problem-solving strategy. (iv Students demonstrated problem-solving strategy development specific to bacterial identification. (v Participants demonstrated an improved performance from their repeated use of the simulation.

  10. A hybrid computation method for determining fluctuations of temperature in branched structures

    International Nuclear Information System (INIS)

    Czomber, L.

    1982-01-01

    A hybrid computation method for determining temperature fluctuations at discrete points of slab like geometries is developed on the basis of a new formulation of the finite difference method. For this purpose, a new finite difference method is combined with an exact solution of the heat equation within the range of values of the Laplace transformation. Whereas the exact solution can be applied to arbitraryly large ranges, the finite difference formulation is given for structural ranges which need finer discretization. The boundary conditions of the exact solution are substituted by finite difference terms for the boundary residual flow or an internal heat source, depending on the problem. The resulting system of conditional equations contains only the node parameters of the finite difference method. (orig.) [de

  11. Hybridization relics complicate barcode-based identification of species in earthworms.

    Science.gov (United States)

    Dupont, L; Porco, D; Symondson, W O C; Roy, V

    2016-07-01

    Introgressive hybridization results in mito-nuclear discordance which could obscure the delimitation of closely related taxa. Although such events are increasingly reported, they have been poorly studied in earthworms. Here, we propose a method for investigating the degree of introgressive hybridization between three taxa of the Allolobophora chlorotica aggregate within two field populations (N = 67 and N = 105) using a reference data set including published DNA barcoding and microsatellite data of all known A. chlorotica lineages (N = 85). For this, we used both molecular phylogenetic and population genetic approaches. The test of correspondence between mitochondrial cytochrome c oxidase I (COI) lineages and clusters of nuclear microsatellite genotypes allowed individuals to be sorted in three categories (matching, admixed and nonmatching) and additional markers (mitochondrial NADH dehydrogenase subunit 1, nuclear Histone 3 and Internal transcribed Spacer Region 2) were used for phylogenetic reconstructions in order to check assignments. Although 15 admixed individuals were observed, no early-generation hybrids were detected within the two populations. Interestingly, 14 nonmatching individuals (i.e. with a mtDNA haplotype that did not correspond to their nuclear cluster) were detected, a pattern that would result after multiple generations of unidirectional hybridization of female from one taxon to male of the other taxon. Because earthworms are simultaneous hermaphrodites, these events of unidirectional hybridization suggest sterility of the male function in several crosses and highlight that some individuals can be misidentified if reliance is placed on COI barcodes alone. These findings could improve the use of these barcodes in earthworms for species delineation. © 2016 John Wiley & Sons Ltd.

  12. Hybrid MPI/OpenMP parallelization of the explicit Volterra integral equation solver for multi-core computer architectures

    KAUST Repository

    Al Jarro, Ahmed

    2011-08-01

    A hybrid MPI/OpenMP scheme for efficiently parallelizing the explicit marching-on-in-time (MOT)-based solution of the time-domain volume (Volterra) integral equation (TD-VIE) is presented. The proposed scheme equally distributes tested field values and operations pertinent to the computation of tested fields among the nodes using the MPI standard; while the source field values are stored in all nodes. Within each node, OpenMP standard is used to further accelerate the computation of the tested fields. Numerical results demonstrate that the proposed parallelization scheme scales well for problems involving three million or more spatial discretization elements. © 2011 IEEE.

  13. Treatment of early and late reflections in a hybrid computer model for room acoustics

    DEFF Research Database (Denmark)

    Naylor, Graham

    1992-01-01

    The ODEON computer model for acoustics in large rooms is intended for use both in design (by predicting room acoustical indices quickly and easily) and in research (by forming the basis of an auralization system and allowing study of various room acoustical phenomena). These conflicting demands...... preclude the use of both ``pure'' image source and ``pure'' particle tracing methods. A hybrid model has been developed, in which rays discover potential image sources up to a specified order. Thereafter, the same ray tracing process is used in a different way to rapidly generate a dense reverberant decay...

  14. Proteomic Analysis of Pachytene Spermatocytes of Sterile Hybrid Male Mice.

    Science.gov (United States)

    Wang, Lu; Guo, Yueshuai; Liu, Wenjing; Zhao, Weidong; Song, Gendi; Zhou, Tao; Huang, Hefeng; Guo, Xuejiang; Sun, Fei

    2016-09-01

    Incompatibilities in interspecific hybrids, such as reduced hybrid fertility and lethality, are common features resulting from reproductive isolation that lead to speciation. Subspecies crosses of house mice produce offspring in which one sex is infertile or absent, yet the molecular mechanisms of hybrid sterility are poorly understood. In this study, we observed extensive asynapsis of chromosomes and disturbance of the sex body in pachytene spermatocytes of sterile F1 males (PWK/Ph female × C57BL/6J male). We report the high-confidence identification of 4005 proteins in the pachytene spermatocytes of fertile F1 males (PWK/Ph male × C57BL/6J female) and sterile F1 males (PWK/Ph female × C57BL/6J male), of which 215 were upregulated and 381 were downregulated. Bioinformatics analysis of the proteome led to the identification of 43 and 59 proteins known to be essential for male meiosis and spermatogenesis in mice, respectively. Characterization of the proteome of pachytene spermatocytes associated with hybrid male sterility provides an inventory of proteins that is useful for understanding meiosis and the mechanisms of hybrid male infertility. © 2016 by the Society for the Study of Reproduction, Inc.

  15. Genetic Identification of Hyalodaphnia Species and Interspecific Hybrids

    NARCIS (Netherlands)

    Billiones, R.; Brehm, G.M.; Klee, J.; Schwenk, K.

    2004-01-01

    Species of the genus Daphnia, in particular the subgenus Hyalodaphnia, represent a taxonomically problematic group due to their phenotypic plasticity, local races and the formation of interspecific hybrids and backcrosses. In this study, we present a genetic approach utilising nuclear DNA to

  16. A Study on a Hybrid Approach for Diagnosing Faults in Nuclear Power Plant

    International Nuclear Information System (INIS)

    Yang, M.; Zhang, Z.J.; Peng, M.J.; Yan, S.Y.; Wang, H.; Ouyang, J.

    2006-01-01

    Proper and rapid identification of malfunctions is of premier importance for the safe operation of Nuclear Power Plants (NPP). Many monitoring or/and diagnosis methodologies based on artificial and computational intelligence have been proposed to aid operator to understand system problems, perform trouble-shooting action and reduce human error under serious pressure. However, because no single method is adequate to handle all requirements for diagnostic system, hybrid approaches where different methods work in conjunction to solve parts of the problem interest researchers greatly. In this study, Multilevel Flow Models (MFM) and Artificial Neural Network (ANN) are proposed and employed to develop a fault diagnosis system with the intention of improving the success rate of recognition on the one hand, and improving the understandability of diagnostic process and results on the other hand. Several simulation cases were conducted for evaluating the performance of the proposed diagnosis system. The simulation results validated the effectiveness of the proposed hybrid approach. (authors)

  17. Implementation of a cell-wise block-Gauss-Seidel iterative method for SN transport on a hybrid parallel computer architecture

    International Nuclear Information System (INIS)

    Rosa, Massimiliano; Warsa, James S.; Perks, Michael

    2011-01-01

    We have implemented a cell-wise, block-Gauss-Seidel (bGS) iterative algorithm, for the solution of the S_n transport equations on the Roadrunner hybrid, parallel computer architecture. A compute node of this massively parallel machine comprises AMD Opteron cores that are linked to a Cell Broadband Engine™ (Cell/B.E.)"1. LAPACK routines have been ported to the Cell/B.E. in order to make use of its parallel Synergistic Processing Elements (SPEs). The bGS algorithm is based on the LU factorization and solution of a linear system that couples the fluxes for all S_n angles and energy groups on a mesh cell. For every cell of a mesh that has been parallel decomposed on the higher-level Opteron processors, a linear system is transferred to the Cell/B.E. and the parallel LAPACK routines are used to compute a solution, which is then transferred back to the Opteron, where the rest of the computations for the S_n transport problem take place. Compared to standard parallel machines, a hundred-fold speedup of the bGS was observed on the hybrid Roadrunner architecture. Numerical experiments with strong and weak parallel scaling demonstrate the bGS method is viable and compares favorably to full parallel sweeps (FPS) on two-dimensional, unstructured meshes when it is applied to optically thick, multi-material problems. As expected, however, it is not as efficient as FPS in optically thin problems. (author)

  18. Verification of a hybrid adjoint methodology in Titan for single photon emission computed tomography - 316

    International Nuclear Information System (INIS)

    Royston, K.; Haghighat, A.; Yi, C.

    2010-01-01

    The hybrid deterministic transport code TITAN is being applied to a Single Photon Emission Computed Tomography (SPECT) simulation of a myocardial perfusion study. The TITAN code's hybrid methodology allows the use of a discrete ordinates solver in the phantom region and a characteristics method solver in the collimator region. Currently we seek to validate the adjoint methodology in TITAN for this application using a SPECT model that has been created in the MCNP5 Monte Carlo code. The TITAN methodology was examined based on the response of a single voxel detector placed in front of the heart with and without collimation. For the case without collimation, the TITAN response for single voxel-sized detector had a -9.96% difference relative to the MCNP5 response. To simulate collimation, the adjoint source was specified in directions located within the collimator acceptance angle. For a single collimator hole with a diameter matching the voxel dimension, a difference of -0.22% was observed. Comparisons to groupings of smaller collimator holes of two different sizes resulted in relative differences of 0.60% and 0.12%. The number of adjoint source directions within an acceptance angle was increased and showed no significant change in accuracy. Our results indicate that the hybrid adjoint methodology of TITAN yields accurate solutions greater than a factor of two faster than MCNP5. (authors)

  19. Identification of human rotavirus serotype by hybridization to polymerase chain reaction-generated probes derived from a hyperdivergent region of the gene encoding outer capsid protein VP7

    International Nuclear Information System (INIS)

    Flores, J.; Sears, J.; Schael, I.P.; White, L.; Garcia, D.; Lanata, C.; Kapikian, A.Z.

    1990-01-01

    We have synthesized 32 P-labeled hybridization probes from a hyperdivergent region (nucleotides 51 to 392) of the rotavirus gene encoding the VP7 glycoprotein by using the polymerase chain reaction method. Both RNA (after an initial reverse transcription step) and cloned cDNA from human rotavirus serotypes 1 through 4 could be used as templates to amplify this region. High-stringency hybridization of each of the four probes to rotavirus RNAs dotted on nylon membranes allowed the specific detection of corresponding sequences and thus permitted identification of the serotype of the strains dotted. The procedure was useful when applied to rotaviruses isolated from field studies

  20. Identification of human rotavirus serotype by hybridization to polymerase chain reaction-generated probes derived from a hyperdivergent region of the gene encoding outer capsid protein VP7

    Energy Technology Data Exchange (ETDEWEB)

    Flores, J.; Sears, J.; Schael, I.P.; White, L.; Garcia, D.; Lanata, C.; Kapikian, A.Z. (National Institutes of Health, Bethesda, MD (USA))

    1990-08-01

    We have synthesized {sup 32}P-labeled hybridization probes from a hyperdivergent region (nucleotides 51 to 392) of the rotavirus gene encoding the VP7 glycoprotein by using the polymerase chain reaction method. Both RNA (after an initial reverse transcription step) and cloned cDNA from human rotavirus serotypes 1 through 4 could be used as templates to amplify this region. High-stringency hybridization of each of the four probes to rotavirus RNAs dotted on nylon membranes allowed the specific detection of corresponding sequences and thus permitted identification of the serotype of the strains dotted. The procedure was useful when applied to rotaviruses isolated from field studies.

  1. Techniques of DNA hybridization detect small numbers of mycobacteria with no cross-hybridization with non-mycobacterial respiratory organisms

    International Nuclear Information System (INIS)

    Shoemaker, S.A.; Fisher, J.H.; Scoggin, C.H.

    1985-01-01

    The traditional methods used in identifying mycobacteria, such as acid-fast bacillus stains and culture, are often time-consuming, insensitive, and nonspecific. As part of an ongoing program to improve diagnosis and characterization of mycobacteria, the authors have found that deoxyribonucleic acid (DNA) hybridization techniques using isotopically labeled, single-stranded, total DNA can be used to detect as little as 10(-4) micrograms of Mycobacterium tuberculosis (MTb) DNA. This amount of DNA represents approximately 2 X 10(4) genomes. They have also shown the MTb DNA is sufficiently different from the DNA of non-mycobacterial microorganisms such that cross-hybridization with MTb DNA does not occur under the hybridization conditions employed. The authors speculate that DNA hybridization techniques may allow the rapid, sensitive, and specific identification of mycobacteria

  2. Wind-Diesel Hybrid Systems for Russia's Northern Territories

    Energy Technology Data Exchange (ETDEWEB)

    Gevorgian, V.; Touryan, K. [National Renewable Energy Laboratory (US); Bezrukikh, P. [Ministry of Fuel and Energy of Russian Federation (RU); Bezrukikh, P. Jr.; Karghiev, V. [Intersolarcenter

    1999-10-20

    This paper will summarize the DOE/Russian Ministry of Fuel and Energy (MF and E) activities in Russia's Northern Territories in the field of hybrid wind-diesel power systems over the last three years (1997-1999). The National Renewable Energy Laboratory (NREL) supplied technical assistance to the project, including resource assessment, system design, site identification, training and system monitoring. As a result, several wind-diesel systems have been installed and are operating in the Arkhangelsk/Murmansk regions and in Chukotka. NREL designed and provided sets of data acquisition equipment to monitor several of the first pilot wind-diesel systems. NREL's computer simulation models are being used for performance data analysis and optimizing of future system configurations.

  3. Identification of double-yolked duck egg using computer vision.

    Directory of Open Access Journals (Sweden)

    Long Ma

    Full Text Available The double-yolked (DY egg is quite popular in some Asian countries because it is considered as a sign of good luck, however, the double yolk is one of the reasons why these eggs fail to hatch. The usage of automatic methods for identifying DY eggs can increase the efficiency in the poultry industry by decreasing egg loss during incubation or improving sale proceeds. In this study, two methods for DY duck egg identification were developed by using computer vision technology. Transmittance images of DY and single-yolked (SY duck eggs were acquired by a CCD camera to identify them according to their shape features. The Fisher's linear discriminant (FLD model equipped with a set of normalized Fourier descriptors (NFDs extracted from the acquired images and the convolutional neural network (CNN model using primary preprocessed images were built to recognize duck egg yolk types. The classification accuracies of the FLD model for SY and DY eggs were 100% and 93.2% respectively, while the classification accuracies of the CNN model for SY and DY eggs were 98% and 98.8% respectively. The CNN-based algorithm took about 0.12 s to recognize one sample image, which was slightly faster than the FLD-based (about 0.20 s. Finally, this work compared two classification methods and provided the better method for DY egg identification.

  4. Rapid Identification of Staphylococcus aureus Directly from Blood Cultures by Fluorescence In Situ Hybridization with Peptide Nucleic Acid Probes

    Science.gov (United States)

    Oliveira, Kenneth; Procop, Gary W.; Wilson, Deborah; Coull, James; Stender, Henrik

    2002-01-01

    A new fluorescence in situ hybridization (FISH) method with peptide nucleic acid (PNA) probes for identification of Staphylococcus aureus directly from positive blood culture bottles that contain gram-positive cocci in clusters (GPCC) is described. The test (the S. aureus PNA FISH assay) is based on a fluorescein-labeled PNA probe that targets a species-specific sequence of the 16S rRNA of S. aureus. Evaluations with 17 reference strains and 48 clinical isolates, including methicillin-resistant and methicillin-susceptible S. aureus species, coagulase-negative Staphylococcus species, and other clinically relevant and phylogenetically related bacteria and yeast species, showed that the assay had 100% sensitivity and 96% specificity. Clinical trials with 87 blood cultures positive for GPCC correctly identified 36 of 37 (97%) of the S. aureus-positive cultures identified by standard microbiological methods. The positive and negative predictive values were 100 and 98%, respectively. It is concluded that this rapid method (2.5 h) for identification of S. aureus directly from blood culture bottles that contain GPCC offers important information for optimal antibiotic therapy. PMID:11773123

  5. Computational analysis on plug-in hybrid electric motorcycle chassis

    Science.gov (United States)

    Teoh, S. J.; Bakar, R. A.; Gan, L. M.

    2013-12-01

    Plug-in hybrid electric motorcycle (PHEM) is an alternative to promote sustainability lower emissions. However, the PHEM overall system packaging is constrained by limited space in a motorcycle chassis. In this paper, a chassis applying the concept of a Chopper is analysed to apply in PHEM. The chassis 3dimensional (3D) modelling is built with CAD software. The PHEM power-train components and drive-train mechanisms are intergraded into the 3D modelling to ensure the chassis provides sufficient space. Besides that, a human dummy model is built into the 3D modelling to ensure the rider?s ergonomics and comfort. The chassis 3D model then undergoes stress-strain simulation. The simulation predicts the stress distribution, displacement and factor of safety (FOS). The data are used to identify the critical point, thus suggesting the chassis design is applicable or need to redesign/ modify to meet the require strength. Critical points mean highest stress which might cause the chassis to fail. This point occurs at the joints at triple tree and bracket rear absorber for a motorcycle chassis. As a conclusion, computational analysis predicts the stress distribution and guideline to develop a safe prototype chassis.

  6. A hybrid FDTD-Rayleigh integral computational method for the simulation of the ultrasound measurement of proximal femur.

    Science.gov (United States)

    Cassereau, Didier; Nauleau, Pierre; Bendjoudi, Aniss; Minonzio, Jean-Gabriel; Laugier, Pascal; Bossy, Emmanuel; Grimal, Quentin

    2014-07-01

    The development of novel quantitative ultrasound (QUS) techniques to measure the hip is critically dependent on the possibility to simulate the ultrasound propagation. One specificity of hip QUS is that ultrasounds propagate through a large thickness of soft tissue, which can be modeled by a homogeneous fluid in a first approach. Finite difference time domain (FDTD) algorithms have been widely used to simulate QUS measurements but they are not adapted to simulate ultrasonic propagation over long distances in homogeneous media. In this paper, an hybrid numerical method is presented to simulate hip QUS measurements. A two-dimensional FDTD simulation in the vicinity of the bone is coupled to the semi-analytic calculation of the Rayleigh integral to compute the wave propagation between the probe and the bone. The method is used to simulate a setup dedicated to the measurement of circumferential guided waves in the cortical compartment of the femoral neck. The proposed approach is validated by comparison with a full FDTD simulation and with an experiment on a bone phantom. For a realistic QUS configuration, the computation time is estimated to be sixty times less with the hybrid method than with a full FDTD approach. Copyright © 2013 Elsevier B.V. All rights reserved.

  7. A hyperspectral X-ray computed tomography system for enhanced material identification

    Science.gov (United States)

    Wu, Xiaomei; Wang, Qian; Ma, Jinlei; Zhang, Wei; Li, Po; Fang, Zheng

    2017-08-01

    X-ray computed tomography (CT) can distinguish different materials according to their absorption characteristics. The hyperspectral X-ray CT (HXCT) system proposed in the present work reconstructs each voxel according to its X-ray absorption spectral characteristics. In contrast to a dual-energy or multi-energy CT system, HXCT employs cadmium telluride (CdTe) as the x-ray detector, which provides higher spectral resolution and separate spectral lines according to the material's photon-counter working principle. In this paper, a specimen containing ten different polymer materials randomly arranged was adopted for material identification by HXCT. The filtered back-projection algorithm was applied for image and spectral reconstruction. The first step was to sort the individual material components of the specimen according to their cross-sectional image intensity. The second step was to classify materials with similar intensities according to their reconstructed spectral characteristics. The results demonstrated the feasibility of the proposed material identification process and indicated that the proposed HXCT system has good prospects for a wide range of biomedical and industrial nondestructive testing applications.

  8. Hybrid Donor-Dot Devices made using Top-down Ion Implantation for Quantum Computing

    Science.gov (United States)

    Bielejec, Edward; Bishop, Nathan; Carroll, Malcolm

    2012-02-01

    We present progress towards fabricating hybrid donor -- quantum dots (QD) for quantum computing. These devices will exploit the long coherence time of the donor system and the surface state manipulation associated with a QD. Fabrication requires detection of single ions implanted with 10's of nanometer precision. We show in this talk, 100% detection efficiency for single ions using a single ion Geiger mode avalanche (SIGMA) detector integrated into a Si MOS QD process flow. The NanoImplanter (nI) a focused ion beam system is used for precision top-down placement of the implanted ion. This machine has a 10 nm resolution combined with a mass velocity filter, allowing for the use of multi-species liquid metal ion sources (LMIS) to implant P and Sb ions, and a fast blanking and chopping system for single ion implants. The combination of the nI and integration of the SIGMA with the MOS QD process flow establishes a path to fabricate hybrid single donor-dot devices. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

  9. Identification of hybrid node and link communities in complex networks.

    Science.gov (United States)

    He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

    2015-03-02

    Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

  10. Identification of hybrid node and link communities in complex networks

    Science.gov (United States)

    He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

    2015-03-01

    Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

  11. TAREAN: a computational tool for identification and characterization of satellite DNA from unassembled short reads

    Czech Academy of Sciences Publication Activity Database

    Novák, Petr; Ávila Robledillo, Laura; Koblížková, Andrea; Vrbová, Iva; Neumann, Pavel; Macas, Jiří

    2017-01-01

    Roč. 45, č. 12 (2017), č. článku e111. ISSN 0305-1048 R&D Projects: GA ČR GBP501/12/G090; GA MŠk(CZ) LM2015047 Institutional support: RVO:60077344 Keywords : in-situ hybridization * repetitive sequences * tandem repeats * vicia-faba Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 10.162, year: 2016

  12. [Feasibility and acceptance of computer-based assessment for the identification of psychosocially distressed patients in routine clinical care].

    Science.gov (United States)

    Sehlen, Susanne; Ott, Martin; Marten-Mittag, Birgitt; Haimerl, Wolfgang; Dinkel, Andreas; Duehmke, Eckhart; Klein, Christian; Schaefer, Christof; Herschbach, Peter

    2012-07-01

    This study investigated feasibility and acceptance of computer-based assessment for the identification of psychosocial distress in routine radiotherapy care. 155 cancer patients were assessed using QSC-R10, PO-Bado-SF and Mach-9. The congruence between computerized tablet PC and conventional paper assessment was analysed in 50 patients. The agreement between the 2 modes was high (ICC 0.869-0.980). Acceptance of computer-based assessment was very high (>95%). Sex, age, education, distress and Karnofsky performance status (KPS) did not influence acceptance. Computerized assessment was rated more difficult by older patients (p = 0.039) and patients with low KPS (p = 0.020). 75.5% of the respondents supported referral for psycho-social intervention for distressed patients. The prevalence of distress was 27.1% (QSC-R10). Computer-based assessment allows easy identification of distressed patients. Level of staff involvement is low, and the results are quickly available for care providers. © Georg Thieme Verlag KG Stuttgart · New York.

  13. Identification and quantification of Bifidobacterium species isolated from food with genus-specific 16S rRNA-targeted probes by colony hybridization and PCR.

    Science.gov (United States)

    Kaufmann, P; Pfefferkorn, A; Teuber, M; Meile, L

    1997-04-01

    A Bifidobacterium genus-specific target sequence in the V9 variable region of the 16S rRNA has been elaborated and was used to develop a hybridization probe. The specificity of this probe, named lm3 (5'-CGGGTGCTI*CCCACTTTCATG-3'), was used to identify all known type strains and distinguish them from other bacteria. All of the 30 type strains of Bifidobacterium which are available at the German culture collection Deutsche Sammlung von Mikroorganismen und Zellkulturen, 6 commercially available production strains, and 34 closely related relevant strains (as negative controls) were tested. All tested bifidobacteria showed distinct positive signals by colony hybridization, whereas all negative controls showed no distinct dots except Gardnerella vaginalis DSM4944 and Propionibacterium freudenreichii subsp. shermanii DSM4902, which gave slight signals. Furthermore, we established a method for isolation and identification of bifidobacteria from food by using a PCR assay without prior isolation of DNA but breaking the cells with proteinase K. By this method, all Bifidobacterium strains lead to a DNA product of the expected size. We also established a quick assay to quantitatively measure Bifidobacterium counts in food and feces by dilution plating and colony hybridization. We were able to demonstrate that 2.1 x 10(6) to 2.3 x 10(7) colonies/g of sour milk containing bifidobacteria hybridized with the specific nucleotide probe. With these two methods, genus-specific colony hybridization and genus-specific PCR, it is now possible to readily and accurately detect any bifidobacteria in food and fecal samples and to discriminate between them and members of other genera.

  14. Genetic molecular analysis of Coffea arabica (Rubiaceae hybrids using SRAP markers

    Directory of Open Access Journals (Sweden)

    Manoj Kumar Mishra

    2011-06-01

    Full Text Available In Coffea arabica (arabica coffee, the phenotypic as well as genetic variability has been found low because of the narrow genetic basis and self fertile nature of the species. Because of high similarity in phenotypic appearance among the majority of arabica collections, selection of parental lines for inter-varietals hybridization and identification of resultant hybrids at an early stage of plant growth is difficult. DNA markers are known to be reliable in identifying closely related cultivars and hybrids. Sequence Related Amplified Polymorphism (SRAP is a new molecular marker technology developed based on PCR. In this paper, sixty arabica-hybrid progenies belonging to six crosses were analyzed using 31 highly polymorphic SRAP markers. The analysis revealed seven types of SRAP marker profiles which are useful in discriminating the parents and hybrids. The number of bands amplified per primer pair ranges from 6.13 to 8.58 with average number of seven bands. Among six hybrid combinations, percentage of bands shared between hybrids and their parents ranged from 66.29% to 85.71% with polymorphic bands varied from 27.64% to 60.0%. Percentage of hybrid specific fragments obtained in various hybrid combinations ranged from 0.71% to 10.86% and ascribed to the consequence of meiotic recombination. Based on the similarity index calculation, it was observed that F1 hybrids share maximum number of bands with the female parent compared to male parent. The results obtained in the present study revealed the effectiveness of SRAP technique in cultivar identification and hybrid analysis in this coffee species. Rev. Biol. Trop. 59 (2: 607-617. Epub 2011 June 01.

  15. Computational identification of 18 micrornas and their targets in three species of rose

    International Nuclear Information System (INIS)

    Baloch, I.A.; Barozai, M.Y.K.; Achakzai, A.K.K.

    2015-01-01

    MicroRNAs (miRNAs) are non-protein coding, small endogenous RNAs. Their length ranges from 18-26 nucleotides (nt). The miRNAs convergence property becomes a rational approach for the hunt of novel miRNAs in other organisms by homology search. As presently very little miRNAs are reported for rose species, so this study deals with the identification of miRNAs in different species of rose. Consequently 18 miRNA belonging to 17 miRNA families were identified in 3 species of rose (Rosa hybrid, Rosa chinensis and Rosa virginiana). All of the identified miRNA families (miR156, 160, 164, 166, 398, 482, 831, 837, 838, 841, 847, 3436, 3627, 6135, 6285, 6287 and 6288) are being reported for the first time in rose. Precursors of the identified miRNAs form stable minimum free energy (MFE) stem-loop structures and the mature miRNAs are found in the stem portions of their corresponding precursors. 11 putative targets of the miRNAs have also been identified. The identified targets are various proteins including transcription factors. Identification of 18 miRNAs will be supportive to explore the gene regulation phenomenon in various species of roses and it will be a good contribution for understanding the post transcriptional gene regulation in various stages of the life cycles of roses. (author)

  16. A Hybrid Soft-computing Method for Image Analysis of Digital Plantar Scanners.

    Science.gov (United States)

    Razjouyan, Javad; Khayat, Omid; Siahi, Mehdi; Mansouri, Ali Alizadeh

    2013-01-01

    Digital foot scanners have been developed in recent years to yield anthropometrists digital image of insole with pressure distribution and anthropometric information. In this paper, a hybrid algorithm containing gray level spatial correlation (GLSC) histogram and Shanbag entropy is presented for analysis of scanned foot images. An evolutionary algorithm is also employed to find the optimum parameters of GLSC and transform function of the membership values. Resulting binary images as the thresholded images are undergone anthropometric measurements taking in to account the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper. Running computation time and the effects of GLSC parameters are investigated in the simulation results.

  17. SU-E-T-13: A Feasibility Study of the Use of Hybrid Computational Phantoms for Improved Historical Dose Reconstruction in the Study of Late Radiation Effects for Hodgkin's Lymphoma

    Energy Technology Data Exchange (ETDEWEB)

    Petroccia, H; O' Reilly, S; Bolch, W [J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL (United States); Mendenhall, N; Li, Z; Slopsema, R [Radiation Oncology, University of Florida Proton Therapy Institute, Jacksonville, FL (United States)

    2014-06-01

    Purpose: Radiation-induced cancer effects are well-documented following radiotherapy. Further investigation is needed to more accurately determine a dose-response relationship for late radiation effects. Recent dosimetry studies tend to use representative patients (Taylor 2009) or anthropomorphic phantoms (Wirth 2008) for estimating organ mean doses. In this study, we compare hybrid computational phantoms to patient-specific voxel phantoms to test the accuracy of University of Florida Hybrid Phantom Library (UFHP Library) for historical dose reconstructions. Methods: A cohort of 10 patients with CT images was used to reproduce the data that was collected historically for Hodgkin's lymphoma patients (i.e. caliper measurements and photographs). Four types of phantoms were generated to show a range of refinement from reference hybrid-computational phantom to patient-specific phantoms. Each patient is matched to a reference phantom from the UFHP Library based on height and weight. The reference phantom is refined in the anterior/posterior direction to create a ‘caliper-scaled phantom’. A photograph is simulated using a surface rendering from segmented CT images. Further refinement in the lateral direction is performed using ratios from a simulated-photograph to create a ‘photograph and caliper-scaled phantom’; breast size and position is visually adjusted. Patient-specific hybrid phantoms, with matched organ volumes, are generated and show the capabilities of the UF Hybrid Phantom Library. Reference, caliper-scaled, photograph and caliper-scaled, and patient-specific hybrid phantoms are compared with patient-specific voxel phantoms to determine the accuracy of the study. Results: Progression from reference phantom to patient specific hybrid shows good agreement with the patient specific voxel phantoms. Each stage of refinement shows an overall trend of improvement in dose accuracy within the study, which suggests that computational phantoms can show

  18. Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads.

    Science.gov (United States)

    Giuliani, C; Agostinelli, A; Di Nardo, F; Fioretti, S; Burattini, L

    2016-01-01

    Electrocardiographic (ECG) T-wave endpoint (Tend) identification suffers lack of reliability due to the presence of noise and variability among leads. Tend identification can be improved by using global repolarization waveforms obtained by combining several leads. The dominant T-wave (DTW) is a global repolarization waveform that proved to improve Tend identification when computed using the 15 (I to III, aVr, aVl, aVf, V1 to V6, X, Y, Z) leads usually available in clinics, of which only 8 (I, II, V1 to V6) are independent. The aim of the present study was to evaluate if the 8 independent leads are sufficient to obtain a DTW which allows a reliable Tend identification. To this aim Tend measures automatically identified from 15-dependent-lead DTWs of 46 control healthy subjects (CHS) and 103 acute myocardial infarction patients (AMIP) were compared with those obtained from 8-independent-lead DTWs. Results indicate that Tend distributions have not statistically different median values (CHS: 340 ms vs. 340 ms, respectively; AMIP: 325 ms vs. 320 ms, respectively), besides being strongly correlated (CHS: ρ=0.97, AMIP: 0.88; Pautomatic Tend identification from DTW, the 8 independent leads can be used without a statistically significant loss of accuracy but with a significant decrement of computational effort. The lead dependence of 7 out of 15 leads does not introduce a significant bias in the Tend determination from 15 dependent lead DTWs.

  19. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

    Science.gov (United States)

    Falat, Lukas; Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  20. Dynamic modelling of an adsorption storage tank using a hybrid approach combining computational fluid dynamics and process simulation

    Science.gov (United States)

    Mota, J.P.B.; Esteves, I.A.A.C.; Rostam-Abadi, M.

    2004-01-01

    A computational fluid dynamics (CFD) software package has been coupled with the dynamic process simulator of an adsorption storage tank for methane fuelled vehicles. The two solvers run as independent processes and handle non-overlapping portions of the computational domain. The codes exchange data on the boundary interface of the two domains to ensure continuity of the solution and of its gradient. A software interface was developed to dynamically suspend and activate each process as necessary, and be responsible for data exchange and process synchronization. This hybrid computational tool has been successfully employed to accurately simulate the discharge of a new tank design and evaluate its performance. The case study presented here shows that CFD and process simulation are highly complementary computational tools, and that there are clear benefits to be gained from a close integration of the two. ?? 2004 Elsevier Ltd. All rights reserved.

  1. Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation

    Science.gov (United States)

    2018-01-01

    Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site. PMID:29370230

  2. Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation.

    Directory of Open Access Journals (Sweden)

    Hazlee Azil Illias

    Full Text Available Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM with modified evolutionary particle swarm optimisation (EPSO algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO-Time Varying Acceleration Coefficient (TVAC technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site.

  3. Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation.

    Science.gov (United States)

    Illias, Hazlee Azil; Zhao Liang, Wee

    2018-01-01

    Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site.

  4. Cardiovascular dosimetry using hybrid computational phantoms after external radiotherapy

    International Nuclear Information System (INIS)

    Moignier, Alexandra

    2014-01-01

    Cardiovascular diseases following radiotherapy are major secondary late effects raising questions among the scientific community, especially regarding the dose-effect relationship and confounding risk factors (chemotherapy, cholesterolemia, age at treatment, blood pressure,..). Post-radiation coronary diseases are one of the main causes of cardiac morbidity. Some approximations are made when coronary doses due to radiotherapy are estimated, especially regarding the morphology. For retrospective studies with old medical records, only radiographs are usually available with sometimes some contours made with a simulator. For recent medical records, CT scans displaying the anatomy in 3D are used for radiotherapy simulation but do not allow the coronary artery visualization due to low resolution and contrast. Currently, coronary doses are barely assessed in clinical practice, and when it is done, anatomical prior knowledge is generally used. This thesis proposes an original approach based on hybrid computational phantoms to study coronary artery doses following radiotherapy for left-side breast cancer and Hodgkin lymphoma. During the thesis, a method inserting hybrid computational phantoms in a DICOM format into the treatment planning system has been developed and validated. It has been adapted and tested in conditions where only radiographs provide anatomical information, as with old medical records for left side breast radiotherapy. The method has also been adapted to perform precise dose reconstructions to the coronary artery for patients treated for a mediastinal Hodgkin lymphoma and diagnosed with coronary stenosis through a coro-scanner. A case-control study was carried out and the risk of coronary stenosis on a coronary artery segment was assessed to be multiplied by 1.049 at each additional gray on the median dose to the coronary artery segment. For recent medical records, coronary doses uncertainties related to an approach by anatomical prior knowledge

  5. Reverse sample genome probing, a new technique for identification of bacteria in environmental samples by DNA hybridization, and its application to the identification of sulfate-reducing bacteria in oil field samples

    International Nuclear Information System (INIS)

    Voordouw, G.; Voordouw, J.K.; Karkhoff-Schweizer, R.R.; Fedorak, P.M.; Westlake, D.W.S.

    1991-01-01

    A novel method for identification of bacteria in environmental samples by DNA hybridization is presented. It is based on the fact that, even within a genus, the genomes of different bacteria may have little overall sequence homology. This allows the use of the labeled genomic DNA of a given bacterium (referred to as a standard) to probe for its presence and that of bacteria with highly homologous genomes in total DNA obtained from an environmental sample. Alternatively, total DNA extracted from the sample can be labeled and used to probe filters on which denatured chromosomal DNA from relevant bacterial standards has been spotted. The latter technique is referred to as reverse sample genome probing, since it is the reverse of the usual practice of deriving probes from reference bacteria for analyzing a DNA sample. Reverse sample genome probing allows identification of bacteria in a sample in a single step once a master filter with suitable standards has been developed. Application of reverse sample genome probing to the identification of sulfate-reducing bacteria in 31 samples obtained primarily from oil fields in the province of Alberta has indicated that there are at least 20 genotypically different sulfate-reducing bacteria in these samples

  6. A hybrid method for the computation of quasi-3D seismograms.

    Science.gov (United States)

    Masson, Yder; Romanowicz, Barbara

    2013-04-01

    The development of powerful computer clusters and efficient numerical computation methods, such as the Spectral Element Method (SEM) made possible the computation of seismic wave propagation in a heterogeneous 3D earth. However, the cost of theses computations is still problematic for global scale tomography that requires hundreds of such simulations. Part of the ongoing research effort is dedicated to the development of faster modeling methods based on the spectral element method. Capdeville et al. (2002) proposed to couple SEM simulations with normal modes calculation (C-SEM). Nissen-Meyer et al. (2007) used 2D SEM simulations to compute 3D seismograms in a 1D earth model. Thanks to these developments, and for the first time, Lekic et al. (2011) developed a 3D global model of the upper mantle using SEM simulations. At the local and continental scale, adjoint tomography that is using a lot of SEM simulation can be implemented on current computers (Tape, Liu et al. 2009). Due to their smaller size, these models offer higher resolution. They provide us with images of the crust and the upper part of the mantle. In an attempt to teleport such local adjoint tomographic inversions into the deep earth, we are developing a hybrid method where SEM computation are limited to a region of interest within the earth. That region can have an arbitrary shape and size. Outside this region, the seismic wavefield is extrapolated to obtain synthetic data at the Earth's surface. A key feature of the method is the use of a time reversal mirror to inject the wavefield induced by distant seismic source into the region of interest (Robertsson and Chapman 2000). We compute synthetic seismograms as follow: Inside the region of interest, we are using regional spectral element software RegSEM to compute wave propagation in 3D. Outside this region, the wavefield is extrapolated to the surface by convolution with the Green's functions from the mirror to the seismic stations. For now, these

  7. The hierarchical expert tuning of PID controllers using tools of soft computing.

    Science.gov (United States)

    Karray, F; Gueaieb, W; Al-Sharhan, S

    2002-01-01

    We present soft computing-based results pertaining to the hierarchical tuning process of PID controllers located within the control loop of a class of nonlinear systems. The results are compared with PID controllers implemented either in a stand alone scheme or as a part of conventional gain scheduling structure. This work is motivated by the increasing need in the industry to design highly reliable and efficient controllers for dealing with regulation and tracking capabilities of complex processes characterized by nonlinearities and possibly time varying parameters. The soft computing-based controllers proposed are hybrid in nature in that they integrate within a well-defined hierarchical structure the benefits of hard algorithmic controllers with those having supervisory capabilities. The controllers proposed also have the distinct features of learning and auto-tuning without the need for tedious and computationally extensive online systems identification schemes.

  8. Parallel adaptation of general three-dimensional hybrid meshes

    International Nuclear Information System (INIS)

    Kavouklis, Christos; Kallinderis, Yannis

    2010-01-01

    A new parallel dynamic mesh adaptation and load balancing algorithm for general hybrid grids has been developed. The meshes considered in this work are composed of four kinds of elements; tetrahedra, prisms, hexahedra and pyramids, which poses a challenge to parallel mesh adaptation. Additional complexity imposed by the presence of multiple types of elements affects especially data migration, updates of local data structures and interpartition data structures. Efficient partition of hybrid meshes has been accomplished by transforming them to suitable graphs and using serial graph partitioning algorithms. Communication among processors is based on the faces of the interpartition boundary and the termination detection algorithm of Dijkstra is employed to ensure proper flagging of edges for refinement. An inexpensive dynamic load balancing strategy is introduced to redistribute work load among processors after adaptation. In particular, only the initial coarse mesh, with proper weighting, is balanced which yields savings in computation time and relatively simple implementation of mesh quality preservation rules, while facilitating coarsening of refined elements. Special algorithms are employed for (i) data migration and dynamic updates of the local data structures, (ii) determination of the resulting interpartition boundary and (iii) identification of the communication pattern of processors. Several representative applications are included to evaluate the method.

  9. Identification of interspecific hybrids between loquat (eriobotrya japonica lindl.) and bengal loquat (e. bengalensis hook.)

    International Nuclear Information System (INIS)

    Wang, Y.; Deng, Q.; Zeng, J.; Zhang, J.

    2017-01-01

    Loquat (Eriobotrya japonica Lindl.) is an important subtropical fruit; however, loquat fruitlets are vulnerable to cold injury in winter, which significantly decreases loquat yield in most production regions. In the present study, two loquat cultivars ('Dawuxing' and '4-1-5') and one wild loquat (E. bengalensis Hook., Bengal loquat), were used for interspecific hybridization to produce hybrids with characteristics of spring blooming to avoid cold injury of fruitlets. Hybrid seedlings were derived from direct cross (loquat as female parent and Bengal loquat as male parent) and reciprocal cross. The authenticity of 47 hybrid seedlings was confirmed using inter-simple sequence repeat (ISSR) molecular markers; and leaf morphological characteristics of the hybrid offspring and parents were preliminarily studied and compared. The results suggested that 23 true direct cross hybrids and 12 true reciprocal cross hybrids were obtained, with hybrid authenticity rates of 100 and 50.0%, respectively. Thus, a novel method of distant hybridization for loquat breeding was developed, and with their various genetic and morphological characteristics these hybrids could be valuable germplasms for horticultural use. (author)

  10. Identification of High-Risk Plaques Destined to Cause Acute Coronary Syndrome Using Coronary Computed Tomographic Angiography and Computational Fluid Dynamics.

    Science.gov (United States)

    Lee, Joo Myung; Choi, Gilwoo; Koo, Bon-Kwon; Hwang, Doyeon; Park, Jonghanne; Zhang, Jinlong; Kim, Kyung-Jin; Tong, Yaliang; Kim, Hyun Jin; Grady, Leo; Doh, Joon-Hyung; Nam, Chang-Wook; Shin, Eun-Seok; Cho, Young-Seok; Choi, Su-Yeon; Chun, Eun Ju; Choi, Jin-Ho; Nørgaard, Bjarne L; Christiansen, Evald H; Niemen, Koen; Otake, Hiromasa; Penicka, Martin; de Bruyne, Bernard; Kubo, Takashi; Akasaka, Takashi; Narula, Jagat; Douglas, Pamela S; Taylor, Charles A; Kim, Hyo-Soo

    2018-03-14

    We investigated the utility of noninvasive hemodynamic assessment in the identification of high-risk plaques that caused subsequent acute coronary syndrome (ACS). ACS is a critical event that impacts the prognosis of patients with coronary artery disease. However, the role of hemodynamic factors in the development of ACS is not well-known. Seventy-two patients with clearly documented ACS and available coronary computed tomographic angiography (CTA) acquired between 1 month and 2 years before the development of ACS were included. In 66 culprit and 150 nonculprit lesions as a case-control design, the presence of adverse plaque characteristics (APC) was assessed and hemodynamic parameters (fractional flow reserve derived by coronary computed tomographic angiography [FFR CT ], change in FFR CT across the lesion [△FFR CT ], wall shear stress [WSS], and axial plaque stress) were analyzed using computational fluid dynamics. The best cut-off values for FFR CT , △FFR CT , WSS, and axial plaque stress were used to define the presence of adverse hemodynamic characteristics (AHC). The incremental discriminant and reclassification abilities for ACS prediction were compared among 3 models (model 1: percent diameter stenosis [%DS] and lesion length, model 2: model 1 + APC, and model 3: model 2 + AHC). The culprit lesions showed higher %DS (55.5 ± 15.4% vs. 43.1 ± 15.0%; p stress than nonculprit lesions (all p values statistic [c-index] 0.789 vs. 0.747; p = 0.014) and reclassification abilities (category-free net reclassification index 0.287; p = 0.047; relative integrated discrimination improvement 0.368; p < 0.001) than model 2. Lesions with both APC and AHC showed significantly higher risk of the culprit for subsequent ACS than those with no APC/AHC (hazard ratio: 11.75; 95% confidence interval: 2.85 to 48.51; p = 0.001) and with either APC or AHC (hazard ratio: 3.22; 95% confidence interval: 1.86 to 5.55; p < 0.001). Noninvasive hemodynamic assessment enhanced

  11. Hybrid SPECT/CT imaging in neurology.

    Science.gov (United States)

    Ciarmiello, Andrea; Giovannini, Elisabetta; Meniconi, Martina; Cuccurullo, Vincenzo; Gaeta, Maria Chiara

    2014-01-01

    In recent years, the SPECT/CT hybrid modality has led to a rapid development of imaging techniques in nuclear medicine, opening new perspectives for imaging staff and patients as well. However, while, the clinical role of positron emission tomography-computed tomography (PET-CT) is well consolidated, the diffusion and the consequent value of single-photon emission tomography-computed tomography (SPECT-CT) has yet to be weighed, Hence, there is a need for a careful analysis, comparing the "potential" benefits of the hybrid modality with the "established" ones of the standalone machine. The aim of this article is to analyze the impact of this hybrid tool on the diagnosis of diseases of the central nervous system, comparing strengths and weaknesses of both modalities through the use of SWOT analysis.

  12. A Hybrid Soft-computing Method for Image Analysis of Digital Plantar Scanners

    Science.gov (United States)

    Razjouyan, Javad; Khayat, Omid; Siahi, Mehdi; Mansouri, Ali Alizadeh

    2013-01-01

    Digital foot scanners have been developed in recent years to yield anthropometrists digital image of insole with pressure distribution and anthropometric information. In this paper, a hybrid algorithm containing gray level spatial correlation (GLSC) histogram and Shanbag entropy is presented for analysis of scanned foot images. An evolutionary algorithm is also employed to find the optimum parameters of GLSC and transform function of the membership values. Resulting binary images as the thresholded images are undergone anthropometric measurements taking in to account the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper. Running computation time and the effects of GLSC parameters are investigated in the simulation results. PMID:24083133

  13. COMPARATIVE ANALYSIS OF METHODS FOR IDENTIFICATION OF NONTUBERCULOUS MYCOBACTERIA ISOLATED FROM CLINICAL MATERIAL

    Directory of Open Access Journals (Sweden)

    A. V. Lyamin

    2017-01-01

    Full Text Available Recently there has been a significant increase in the incidence of mycobacteriosis, which is due to an increase in the proportion of immunosuppressed patients, the presence of these various comorbid conditions, as well as the improvement of diagnostic methods. Selecting the most accurate method of identification is extremely important in determining treatment strategy of patients. The aim of the study was to conduct a comparative analysis of modern methods of identification NTMB isolated from clinical specimens in 2015 in the Samara region. The work was carried out identification of 78 strains of microorganisms. Laboratory diagnosis was carried out using the DNA hybridization method and MALDI-ToF mass spectrometry. When microbial identification using MALDI-ToF mass spectrometry was isolated 16 strains (20.5% M. kansasii; 11 strains (14.1% M. avium and M. fortuitum; 9 strains (11.5% M. gordonae; strain 3 (3.8% M. peregrinum, M. szulgai, M. chimera intracellulare group, strain 2 (2.6% M. abscessus, M. septicum, M. paragordonae, M. senegalence, 1 strain (1.3% M. chelonae, M. frederiksbergense, M. monacense, M. lentiflavum. By using mass spectrometry, it was identified 15 types NTMB compared with 9 types — by DNA hybridization. Full match identification results was observed only in 45 (57.7% strains of divergent strains were found in 16 (20.5%. Most often when using the DNA hybridization method, discrepancy was detected in slow-growing cultures (9 strains with a predominance of microorganisms identified as M. gordonae. Among the representatives of fast-growing NTMB, seven investigations were identified in the identification, more often among representatives of the M. fortuitum and M. peregrinum groups. Particular attention should be paid to the identification of the M. kansasii strain by a molecular genetic method, which mass spectrometry was defined as M. bovis. Both cultures of M. tuberculosis complex, which were identified by MALDI

  14. HOC Based Blind Identification of Hydroturbine Shaft Volterra System

    Directory of Open Access Journals (Sweden)

    Bing Bai

    2017-01-01

    Full Text Available In order to identify the quadratic Volterra system simplified from the hydroturbine shaft system, a blind identification method based on the third-order cumulants and a reversely recursive method are proposed. The input sequence of the system under consideration is an unobservable independent identically distributed (i.i.d., zero-mean and non-Gaussian stationary signal, and the observed signals are the superposition of the system output signal and Gaussian noise. To calculate the third-order moment of the output signal, a computer loop judgment method is put forward to determine the coefficient. When using optimization method to identify the time domain kernels, we combined the traditional optimization algorithm (direct search method with genetic algorithm (GA and constituted the hybrid genetic algorithm (HGA. Finally, according to the prototype observation signal and the time domain kernel parameters obtained from identification, the input signal of the system can be gained recursively. To test the proposed method, three numerical experiments and engineering application have been carried out. The results show that the method is applicable to the blind identification of the hydroturbine shaft system and has strong universality; the input signal obtained by the reversely recursive method can be approximately taken as the random excitation acted on the runner of the hydroturbine shaft system.

  15. Shoal bass hybridization in the Chattahoochee River Basin near Atlanta, Georgia

    Science.gov (United States)

    Taylor, Andrew T.; Tringali, Michael D.; O'Rourke, Patrick M.; Long, James M.

    2018-01-01

    The shoal bass (Micropterus cataractae) is a sportfish endemic to the Apalachicola-Chattahoochee-Flint Basin of the southeastern United States. Introgression with several non-native congeners poses a pertinent threat to shoal bass conservation, particularly in the altered habitats of the Chattahoochee River. Our primary objective was to characterize hybridization in shoal bass populations near Atlanta, Georgia, including a population inhabiting Big Creek and another in the main stem Chattahoochee River below Morgan Falls Dam (MFD). A secondary objective was to examine the accuracy of phenotypic identifications below MFD based on a simplified suite of characters examined in the field. Fish were genotyped with 16 microsatellite DNA markers, and results demonstrated that at least four black bass species were involved in introgressive hybridization. Of 62 fish genotyped from Big Creek, 27% were pure shoal bass and 65% represented either F1 hybrids of shoal bass x smallmouth bass (M. dolomieu) or unidirectional backcrosses towards shoal bass. Of 29 fish genotyped below MFD and downstream at Cochran Shoals, 45% were pure shoal bass. Six hybrid shoal bass included both F1 hybrids and backcrosses with non-natives including Alabama bass (M. henshalli), spotted bass (M. punctulatus), and smallmouth bass. Shoal bass alleles comprised only 21% of the overall genomic composition in Big Creek and 31% below MFD (when combined with Cochran Shoals). Phenotypic identification below MFD resulted in an overall correct classification rate of 86% when discerning pure shoal bass from all other non-natives and hybrids. Results suggest that although these two shoal bass populations feature some of the highest introgression rates documented, only a fleeting opportunity may exist to conserve pure shoal bass in both populations. Continued supplemental stocking of pure shoal bass below MFD appears warranted to thwart increased admixture among multiple black bass taxa, and a similar stocking

  16. A Hybrid Supervised/Unsupervised Machine Learning Approach to Solar Flare Prediction

    Science.gov (United States)

    Benvenuto, Federico; Piana, Michele; Campi, Cristina; Massone, Anna Maria

    2018-01-01

    This paper introduces a novel method for flare forecasting, combining prediction accuracy with the ability to identify the most relevant predictive variables. This result is obtained by means of a two-step approach: first, a supervised regularization method for regression, namely, LASSO is applied, where a sparsity-enhancing penalty term allows the identification of the significance with which each data feature contributes to the prediction; then, an unsupervised fuzzy clustering technique for classification, namely, Fuzzy C-Means, is applied, where the regression outcome is partitioned through the minimization of a cost function and without focusing on the optimization of a specific skill score. This approach is therefore hybrid, since it combines supervised and unsupervised learning; realizes classification in an automatic, skill-score-independent way; and provides effective prediction performances even in the case of imbalanced data sets. Its prediction power is verified against NOAA Space Weather Prediction Center data, using as a test set, data in the range between 1996 August and 2010 December and as training set, data in the range between 1988 December and 1996 June. To validate the method, we computed several skill scores typically utilized in flare prediction and compared the values provided by the hybrid approach with the ones provided by several standard (non-hybrid) machine learning methods. The results showed that the hybrid approach performs classification better than all other supervised methods and with an effectiveness comparable to the one of clustering methods; but, in addition, it provides a reliable ranking of the weights with which the data properties contribute to the forecast.

  17. A hybrid computational strategy to address WGS variant analysis in >5000 samples.

    Science.gov (United States)

    Huang, Zhuoyi; Rustagi, Navin; Veeraraghavan, Narayanan; Carroll, Andrew; Gibbs, Richard; Boerwinkle, Eric; Venkata, Manjunath Gorentla; Yu, Fuli

    2016-09-10

    The decreasing costs of sequencing are driving the need for cost effective and real time variant calling of whole genome sequencing data. The scale of these projects are far beyond the capacity of typical computing resources available with most research labs. Other infrastructures like the cloud AWS environment and supercomputers also have limitations due to which large scale joint variant calling becomes infeasible, and infrastructure specific variant calling strategies either fail to scale up to large datasets or abandon joint calling strategies. We present a high throughput framework including multiple variant callers for single nucleotide variant (SNV) calling, which leverages hybrid computing infrastructure consisting of cloud AWS, supercomputers and local high performance computing infrastructures. We present a novel binning approach for large scale joint variant calling and imputation which can scale up to over 10,000 samples while producing SNV callsets with high sensitivity and specificity. As a proof of principle, we present results of analysis on Cohorts for Heart And Aging Research in Genomic Epidemiology (CHARGE) WGS freeze 3 dataset in which joint calling, imputation and phasing of over 5300 whole genome samples was produced in under 6 weeks using four state-of-the-art callers. The callers used were SNPTools, GATK-HaplotypeCaller, GATK-UnifiedGenotyper and GotCloud. We used Amazon AWS, a 4000-core in-house cluster at Baylor College of Medicine, IBM power PC Blue BioU at Rice and Rhea at Oak Ridge National Laboratory (ORNL) for the computation. AWS was used for joint calling of 180 TB of BAM files, and ORNL and Rice supercomputers were used for the imputation and phasing step. All other steps were carried out on the local compute cluster. The entire operation used 5.2 million core hours and only transferred a total of 6 TB of data across the platforms. Even with increasing sizes of whole genome datasets, ensemble joint calling of SNVs for low

  18. Modelling dependable systems using hybrid Bayesian networks

    International Nuclear Information System (INIS)

    Neil, Martin; Tailor, Manesh; Marquez, David; Fenton, Norman; Hearty, Peter

    2008-01-01

    A hybrid Bayesian network (BN) is one that incorporates both discrete and continuous nodes. In our extensive applications of BNs for system dependability assessment, the models are invariably hybrid and the need for efficient and accurate computation is paramount. We apply a new iterative algorithm that efficiently combines dynamic discretisation with robust propagation algorithms on junction tree structures to perform inference in hybrid BNs. We illustrate its use in the field of dependability with two example of reliability estimation. Firstly we estimate the reliability of a simple single system and next we implement a hierarchical Bayesian model. In the hierarchical model we compute the reliability of two unknown subsystems from data collected on historically similar subsystems and then input the result into a reliability block model to compute system level reliability. We conclude that dynamic discretisation can be used as an alternative to analytical or Monte Carlo methods with high precision and can be applied to a wide range of dependability problems

  19. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Directory of Open Access Journals (Sweden)

    Lukas Falat

    2016-01-01

    Full Text Available This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  20. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Science.gov (United States)

    Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450

  1. Hybrid and Electric Advanced Vehicle Systems Simulation

    Science.gov (United States)

    Beach, R. F.; Hammond, R. A.; Mcgehee, R. K.

    1985-01-01

    Predefined components connected to represent wide variety of propulsion systems. Hybrid and Electric Advanced Vehicle System (HEAVY) computer program is flexible tool for evaluating performance and cost of electric and hybrid vehicle propulsion systems. Allows designer to quickly, conveniently, and economically predict performance of proposed drive train.

  2. A hybrid computational method for the discovery of novel reproduction-related genes.

    Science.gov (United States)

    Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong

    2015-01-01

    Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.

  3. Hybrid automata models of cardiac ventricular electrophysiology for real-time computational applications.

    Science.gov (United States)

    Andalam, Sidharta; Ramanna, Harshavardhan; Malik, Avinash; Roop, Parthasarathi; Patel, Nitish; Trew, Mark L

    2016-08-01

    Virtual heart models have been proposed for closed loop validation of safety-critical embedded medical devices, such as pacemakers. These models must react in real-time to off-the-shelf medical devices. Real-time performance can be obtained by implementing models in computer hardware, and methods of compiling classes of Hybrid Automata (HA) onto FPGA have been developed. Models of ventricular cardiac cell electrophysiology have been described using HA which capture the complex nonlinear behavior of biological systems. However, many models that have been used for closed-loop validation of pacemakers are highly abstract and do not capture important characteristics of the dynamic rate response. We developed a new HA model of cardiac cells which captures dynamic behavior and we implemented the model in hardware. This potentially enables modeling the heart with over 1 million dynamic cells, making the approach ideal for closed loop testing of medical devices.

  4. Hardware in the loop platform development for hybrid vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Wilhelm, E. [ETH Zurich, Zurich (Switzerland); Fowler, E.; Stevens, M.B. [Waterloo Univ., ON (Canada). Dept. of Chemical Engineering; Fraser, M.W. [Waterloo Univ., ON (Canada). Dept. of Mechanical Engineering

    2007-07-01

    This paper described a hardware-in-the-loop (HIL) validation simulation system designed to evaluate hybrid control strategies. The system was designed to reduce development costs and improve the safety of hybrid vehicle control systems. Model-based design processes for power trains typically include a series of processes to assess the real time and physical limitations of control systems prior to in-vehicle testing. The study used a 70 kW nickel metal hydride battery; a 67 kW 3-phase induction traction motor; and, a high voltage DC-DC converter within a fuel cell Chevrolet Equinox. Two physical vehicle controllers were used to interface with the virtual vehicle simulation in real time. System performance was monitored with a supervisory computer. A software in the loop (SIL) process was conducted to assess torque control and regenerative braking algorithm validation. An analysis of the controller code showed that a Simulink-native integrator block was updating too slowly. A custom integration term calculation was written. The charge control was then validated and tuned. It was concluded that use of the HIL system mitigated the risk of component damage through the identification and correction of unstable control logic. 10 refs., 2 tabs., 10 figs.

  5. A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network.

    Science.gov (United States)

    Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

    2012-01-01

    From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins.

  6. CERPI and CEREL, two computer codes for the automatic identification and determination of gamma emitters in thermal-neutron-activated samples

    International Nuclear Information System (INIS)

    Giannini, M.; Oliva, P.R.; Ramorino, M.C.

    1979-01-01

    A computer code that automatically analyzes gamma-ray spectra obtained with Ge(Li) detectors is described. The program contains such features as automatic peak location and fitting, determination of peak energies and intensities, nuclide identification, and calculation of masses and errors. Finally, the results obtained with this computer code for a lunar sample are reported and briefly discussed

  7. A quadratic kernel for computing the hybridization number of multiple trees

    NARCIS (Netherlands)

    L.J.J. van Iersel (Leo); S. Linz

    2012-01-01

    htmlabstractIt has recently been shown that the NP-hard problem of calculating the minimum number of hybridization events that is needed to explain a set of rooted binary phylogenetic trees by means of a hybridization network is fixed-parameter tractable if an instance of the problem consists of

  8. Tracking alien chromosome in sativa background by genomic in situ hybridization

    International Nuclear Information System (INIS)

    Abbasi, F.M.; Iqbal, M.; Salim, M.

    2004-01-01

    Genomic in situ hybridization (GISH) was used to look into the genomic constitution of monosomic alien -addition line derived from O. sativa x O. brachyantha. Biotin label genomic DNA from O. brachyantha was used as probe. The probe hybridized to the brachyantha chromosome. No detectable hybridization signal was observed on sativa chromosomes. This differential painting of chromosome enables us to unequivocally discriminate brachyantha chromosome from those of sativa. Results showed the usefulness of GISH in the identification of a single alien chromosome in the sativa background. (author)

  9. A boundary integral method for numerical computation of radar cross section of 3D targets using hybrid BEM/FEM with edge elements

    Science.gov (United States)

    Dodig, H.

    2017-11-01

    This contribution presents the boundary integral formulation for numerical computation of time-harmonic radar cross section for 3D targets. Method relies on hybrid edge element BEM/FEM to compute near field edge element coefficients that are associated with near electric and magnetic fields at the boundary of the computational domain. Special boundary integral formulation is presented that computes radar cross section directly from these edge element coefficients. Consequently, there is no need for near-to-far field transformation (NTFFT) which is common step in RCS computations. By the end of the paper it is demonstrated that the formulation yields accurate results for canonical models such as spheres, cubes, cones and pyramids. Method has demonstrated accuracy even in the case of dielectrically coated PEC sphere at interior resonance frequency which is common problem for computational electromagnetic codes.

  10. Original Framework for Optimizing Hybrid Energy Supply

    Directory of Open Access Journals (Sweden)

    Amevi Acakpovi

    2016-01-01

    Full Text Available This paper proposes an original framework for optimizing hybrid energy systems. The recent growth of hybrid energy systems in remote areas across the world added to the increasing cost of renewable energy has triggered the inevitable development of hybrid energy systems. Hybrid energy systems always pose a problem of optimization of cost which has been approached with different perspectives in the recent past. This paper proposes a framework to guide the techniques of optimizing hybrid energy systems in general. The proposed framework comprises four stages including identification of input variables for energy generation, establishment of models of energy generation by individual sources, development of artificial intelligence, and finally summation of selected sources. A case study of a solar, wind, and hydro hybrid system was undertaken with a linear programming approach. Substantial results were obtained with regard to how load requests were constantly satisfied while minimizing the cost of electricity. The developed framework gained its originality from the fact that it has included models of individual sources of energy that even make the optimization problem more complex. This paper also has impacts on the development of policies which will encourage the integration and development of renewable energies.

  11. Identification of control targets in Boolean molecular network models via computational algebra.

    Science.gov (United States)

    Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; Laubenbacher, Reinhard

    2016-09-23

    Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system. This paper presents a method for the identification of potential intervention targets in Boolean molecular network models using algebraic techniques. The approach exploits an algebraic representation of Boolean networks to encode the control candidates in the network wiring diagram as the solutions of a system of polynomials equations, and then uses computational algebra techniques to find such controllers. The control methods in this paper are validated through the identification of combinatorial interventions in the signaling pathways of previously reported control targets in two well studied systems, a p53-mdm2 network and a blood T cell lymphocyte granular leukemia survival signaling network. Supplementary data is available online and our code in Macaulay2 and Matlab are available via http://www.ms.uky.edu/~dmu228/ControlAlg . This paper presents a novel method for the identification of intervention targets in Boolean network models. The results in this paper show that the proposed methods are useful and efficient for moderately large networks.

  12. A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI.

    Science.gov (United States)

    Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

    2015-10-01

    In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e. , internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature.

  13. Degradation of ciprofloxacin antibiotic by Homogeneous Fenton oxidation: Hybrid AHP-PROMETHEE method, optimization, biodegradability improvement and identification of oxidized by-products.

    Science.gov (United States)

    Salari, Marjan; Rakhshandehroo, Gholam Reza; Nikoo, Mohammad Reza

    2018-09-01

    The main purpose of this experimental study was to optimize Homogeneous Fenton oxidation (HFO) and identification of oxidized by-products from degradation of Ciprofloxacin (CIP) using hybrid AHP-PROMETHEE, Response Surface Methodology (RSM) and High Performance Liquid Chromatography coupled with Mass Spectrometry (HPLC-MS). At the first step, an assessment was made for performances of two catalysts (FeSO 4 ·7H 2 O and FeCl 2 ·4H 2 O) based on hybrid AHP-PROMETHEE decision making method. Then, RSM was utilized to examine and optimize the influence of different variables including initial CIP concentration, Fe 2+ concentration, [H 2 O 2 ]/[ Fe 2+ ] mole ratio and initial pH as independent variables on CIP removal, COD removal, and sludge to iron (SIR) as the response functions in a reaction time of 25 min. Weights of the mentioned responses as well as cost criteria were determined by AHP model based on pairwise comparison and then used as inputs to PROMETHEE method to develop hybrid AHP-PROMETHEE. Based on net flow results of this hybrid model, FeCl 2 ·4H 2 O was more efficient because of its less environmental stability as well as lower SIR production. Then, optimization of experiments using Central Composite Design (CCD) under RSM was performed with the FeCl 2 ·4H 2 O catalyst. Biodegradability of wastewater was determined in terms of BOD 5 /COD ratio, showing that HFO process is able to improve wastewater biodegradability from zero to 0.42. Finally, the main intermediaries of degradation and degradation pathways of CIP were investigated with (HPLC-MS). Major degradation pathways from hydroxylation of both piperazine and quinolonic rings, oxidation and cleavage of the piperazine ring, and defluorination (OH/F substitution) were suggested. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. Performance Assessment of the CapitalBio Mycobacterium Identification Array System for Identification of Mycobacteria

    Science.gov (United States)

    Liu, Jingbo; Yan, Zihe; Han, Min; Han, Zhijun; Jin, Lingjie; Zhao, Yanlin

    2012-01-01

    The CapitalBio Mycobacterium identification microarray system is a rapid system for the detection of Mycobacterium tuberculosis. The performance of this system was assessed with 24 reference strains, 486 Mycobacterium tuberculosis clinical isolates, and 40 clinical samples and then compared to the “gold standard” of DNA sequencing. The CapitalBio Mycobacterium identification microarray system showed highly concordant identification results of 100% and 98.4% for Mycobacterium tuberculosis complex (MTC) and nontuberculous mycobacteria (NTM), respectively. The sensitivity and specificity of the CapitalBio Mycobacterium identification array for identification of Mycobacterium tuberculosis isolates were 99.6% and 100%, respectively, for direct detection and identification of clinical samples, and the overall sensitivity was 52.5%. It was 100% for sputum, 16.7% for pleural fluid, and 10% for bronchoalveolar lavage fluid, respectively. The total assay was completed in 6 h, including DNA extraction, PCR, and hybridization. The results of this study confirm the utility of this system for the rapid identification of mycobacteria and suggest that the CapitalBio Mycobacterium identification array is a molecular diagnostic technique with high sensitivity and specificity that has the capacity to quickly identify most mycobacteria. PMID:22090408

  15. Genome-wide Studies of Mycolic Acid Bacteria: Computational Identification and Analysis of a Minimal Genome

    KAUST Repository

    Kamanu, Frederick Kinyua

    2012-12-01

    The mycolic acid bacteria are a distinct suprageneric group of asporogenous Grampositive, high GC-content bacteria, distinguished by the presence of mycolic acids in their cell envelope. They exhibit great diversity in their cell and morphology; although primarily non-pathogens, this group contains three major pathogens Mycobacterium leprae, Mycobacterium tuberculosis complex, and Corynebacterium diphtheria. Although the mycolic acid bacteria are a clearly defined group of bacteria, the taxonomic relationships between its constituent genera and species are less well defined. Two approaches were tested for their suitability in describing the taxonomy of the group. First, a Multilocus Sequence Typing (MLST) experiment was assessed and found to be superior to monophyletic (16S small ribosomal subunit) in delineating a total of 52 mycolic acid bacterial species. Phylogenetic inference was performed using the neighbor-joining method. To further refine phylogenetic analysis and to take advantage of the widespread availability of bacterial genome data, a computational framework that simulates DNA-DNA hybridisation was developed and validated using multiscale bootstrap resampling. The tool classifies microbial genomes based on whole genome DNA, and was deployed as a web-application using PHP and Javascript. It is accessible online at http://cbrc.kaust.edu.sa/dna_hybridization/ A third study was a computational and statistical methods in the identification and analysis of a putative minimal mycolic acid bacterial genome so as to better understand (1) the genomic requirements to encode a mycolic acid bacterial cell and (2) the role and type of genes and genetic elements that lead to the massive increase in genome size in environmental mycolic acid bacteria. Using a reciprocal comparison approach, a total of 690 orthologous gene clusters forming a putative minimal genome were identified across 24 mycolic acid bacterial species. In order to identify new potential drug

  16. A Game-Theoretic approach to Fault Diagnosis of Hybrid Systems

    Directory of Open Access Journals (Sweden)

    Davide Bresolin

    2011-06-01

    Full Text Available Physical systems can fail. For this reason the problem of identifying and reacting to faults has received a large attention in the control and computer science communities. In this paper we study the fault diagnosis problem for hybrid systems from a game-theoretical point of view. A hybrid system is a system mixing continuous and discrete behaviours that cannot be faithfully modeled neither by using a formalism with continuous dynamics only nor by a formalism including only discrete dynamics. We use the well known framework of hybrid automata for modeling hybrid systems, and we define a Fault Diagnosis Game on them, using two players: the environment and the diagnoser. The environment controls the evolution of the system and chooses whether and when a fault occurs. The diagnoser observes the external behaviour of the system and announces whether a fault has occurred or not. Existence of a winning strategy for the diagnoser implies that faults can be detected correctly, while computing such a winning strategy corresponds to implement a diagnoser for the system. We will show how to determine the existence of a winning strategy, and how to compute it, for some decidable classes of hybrid automata like o-minimal hybrid automata.

  17. Hybrid architecture for building secure sensor networks

    Science.gov (United States)

    Owens, Ken R., Jr.; Watkins, Steve E.

    2012-04-01

    Sensor networks have various communication and security architectural concerns. Three approaches are defined to address these concerns for sensor networks. The first area is the utilization of new computing architectures that leverage embedded virtualization software on the sensor. Deploying a small, embedded virtualization operating system on the sensor nodes that is designed to communicate to low-cost cloud computing infrastructure in the network is the foundation to delivering low-cost, secure sensor networks. The second area focuses on securing the sensor. Sensor security components include developing an identification scheme, and leveraging authentication algorithms and protocols that address security assurance within the physical, communication network, and application layers. This function will primarily be accomplished through encrypting the communication channel and integrating sensor network firewall and intrusion detection/prevention components to the sensor network architecture. Hence, sensor networks will be able to maintain high levels of security. The third area addresses the real-time and high priority nature of the data that sensor networks collect. This function requires that a quality-of-service (QoS) definition and algorithm be developed for delivering the right data at the right time. A hybrid architecture is proposed that combines software and hardware features to handle network traffic with diverse QoS requirements.

  18. Hybrid classifiers methods of data, knowledge, and classifier combination

    CERN Document Server

    Wozniak, Michal

    2014-01-01

    This book delivers a definite and compact knowledge on how hybridization can help improving the quality of computer classification systems. In order to make readers clearly realize the knowledge of hybridization, this book primarily focuses on introducing the different levels of hybridization and illuminating what problems we will face with as dealing with such projects. In the first instance the data and knowledge incorporated in hybridization were the action points, and then a still growing up area of classifier systems known as combined classifiers was considered. This book comprises the aforementioned state-of-the-art topics and the latest research results of the author and his team from Department of Systems and Computer Networks, Wroclaw University of Technology, including as classifier based on feature space splitting, one-class classification, imbalance data, and data stream classification.

  19. Hybrid logic on linear structures: expressivity and complexity

    NARCIS (Netherlands)

    Franceschet, M.; de Rijke, M.; Schlingoff, B.-H.

    2003-01-01

    We investigate expressivity and complexity of hybrid logics on linear structures. Hybrid logics are an enrichment of modal logics with certain first-order features which are algorithmically well behaved. Therefore, they are well suited for the specification of certain properties of computational

  20. Solving Problem of Graph Isomorphism by Membrane-Quantum Hybrid Model

    Directory of Open Access Journals (Sweden)

    Artiom Alhazov

    2015-10-01

    Full Text Available This work presents the application of new parallelization methods based on membrane-quantum hybrid computing to graph isomorphism problem solving. Applied membrane-quantum hybrid computational model was developed by authors. Massive parallelism of unconventional computing is used to implement classic brute force algorithm efficiently. This approach does not suppose any restrictions of considered graphs types. The estimated performance of the model is less then quadratic that makes a very good result for the problem of \\textbf{NP} complexity.

  1. Hybrid computational phantoms of the 15-year male and female adolescent: Applications to CT organ dosimetry for patients of variable morphometry

    International Nuclear Information System (INIS)

    Lee, Choonsik; Lodwick, Daniel; Williams, Jonathan L.; Bolch, Wesley E.

    2008-01-01

    Currently, two classes of the computational phantoms have been developed for dosimetry calculation: (1) stylized (or mathematical) and (2) voxel (or tomographic) phantoms describing human anatomy through mathematical surface equations and three-dimensional labeled voxel matrices, respectively. Mathematical surface equations in stylized phantoms provide flexibility in phantom design and alteration, but the resulting anatomical description is, in many cases, not very realistic. Voxel phantoms display far better anatomical realism, but they are limited in terms of their ability to alter organ shape, position, and depth, as well as body posture. A new class of computational phantoms - called hybrid phantoms - takes advantage of the best features of stylized and voxel phantoms - flexibility and anatomical realism, respectively. In the current study, hybrid computational phantoms representing reference 15-year male and female body anatomy and anthropometry are presented. For the male phantom, organ contours were extracted from the University of Florida (UF) 14-year series B male voxel phantom, while for the female phantom, original computed tomography (CT) data from two 14-year female patients were used. Polygon mesh models for the major organs and tissues were reconstructed for nonuniform rational B-spline (NURBS) surface modeling. The resulting NURBS/polygon mesh models representing body contour and internal anatomy were matched to anthropometric data and reference organ mass data provided by the Centers for Disease Control and Prevention (CDC) and the International Commission on Radiation Protection (ICRP), respectively. Finally, two hybrid 15-year male and female phantoms were completed where a total of eight anthropometric data categories were matched to standard values within 4% and organ masses matched to ICRP data within 1% with the exception of total skin. To highlight the flexibility of the hybrid phantoms, 10th and 90th weight percentile 15-year male and

  2. CERPI and CEREL, two computer codes for the automatic identification and determination of gamma emitters in thermal neutron activated samples

    International Nuclear Information System (INIS)

    Giannini, M.; Oliva, P.R.; Ramorino, C.

    1978-01-01

    A description is given of a computer code which automatically analyses gamma-ray spectra obtained with Ge(Li) detectors. The program contains features as automatic peak location and fitting, determination of peak energies and intensities, nuclide identification and calculation of masses and errors. Finally the results obtained with our computer code for a lunar sample are reported and briefly discussed

  3. An efficient method for hybrid density functional calculation with spin-orbit coupling

    Science.gov (United States)

    Wang, Maoyuan; Liu, Gui-Bin; Guo, Hong; Yao, Yugui

    2018-03-01

    In first-principles calculations, hybrid functional is often used to improve accuracy from local exchange correlation functionals. A drawback is that evaluating the hybrid functional needs significantly more computing effort. When spin-orbit coupling (SOC) is taken into account, the non-collinear spin structure increases computing effort by at least eight times. As a result, hybrid functional calculations with SOC are intractable in most cases. In this paper, we present an approximate solution to this problem by developing an efficient method based on a mixed linear combination of atomic orbital (LCAO) scheme. We demonstrate the power of this method using several examples and we show that the results compare very well with those of direct hybrid functional calculations with SOC, yet the method only requires a computing effort similar to that without SOC. The presented technique provides a good balance between computing efficiency and accuracy, and it can be extended to magnetic materials.

  4. Computer-assisted photo identification outperforms visible implant elastomers in an endangered salamander, Eurycea tonkawae.

    Directory of Open Access Journals (Sweden)

    Nathan F Bendik

    Full Text Available Despite recognition that nearly one-third of the 6300 amphibian species are threatened with extinction, our understanding of the general ecology and population status of many amphibians is relatively poor. A widely-used method for monitoring amphibians involves injecting captured individuals with unique combinations of colored visible implant elastomer (VIE. We compared VIE identification to a less-invasive method - computer-assisted photographic identification (photoID - in endangered Jollyville Plateau salamanders (Eurycea tonkawae, a species with a known range limited to eight stream drainages in central Texas. We based photoID on the unique pigmentation patterns on the dorsal head region of 1215 individual salamanders using identification software Wild-ID. We compared the performance of photoID methods to VIEs using both 'high-quality' and 'low-quality' images, which were taken using two different camera types and technologies. For high-quality images, the photoID method had a false rejection rate of 0.76% compared to 1.90% for VIEs. Using a comparable dataset of lower-quality images, the false rejection rate was much higher (15.9%. Photo matching scores were negatively correlated with time between captures, suggesting that evolving natural marks could increase misidentification rates in longer term capture-recapture studies. Our study demonstrates the utility of large-scale capture-recapture using photo identification methods for Eurycea and other species with stable natural marks that can be reliably photographed.

  5. Control of a nursing bed based on a hybrid brain-computer interface.

    Science.gov (United States)

    Nengneng Peng; Rui Zhang; Haihua Zeng; Fei Wang; Kai Li; Yuanqing Li; Xiaobin Zhuang

    2016-08-01

    In this paper, we propose an intelligent nursing bed system which is controlled by a hybrid brain-computer interface (BCI) involving steady-state visual evoked potential (SSVEP) and P300. Specifically, the hybrid BCI includes an asynchronous brain switch based on SSVEP and P300, and a P300-based BCI. The brain switch is used to turn on/off the control system of the electric nursing bed through idle/control state detection, whereas the P300-based BCI is for operating the nursing bed. At the beginning, the user may focus on one group of flashing buttons in the graphic user interface (GUI) of the brain switch, which can simultaneously evoke SSVEP and P300, to switch on the control system. Here, the combination of SSVEP and P300 is used for improving the performance of the brain switch. Next, the user can control the nursing bed using the P300-based BCI. The GUI of the P300-based BCI includes 10 flashing buttons, which correspond to 10 functional operations, namely, left-side up, left-side down, back up, back down, bedpan open, bedpan close, legs up, legs down, right-side up, and right-side down. For instance, he/she can focus on the flashing button "back up" in the GUI of the P300-based BCI to activate the corresponding control such that the nursing bed is adjusted up. Eight healthy subjects participated in our experiment, and obtained an average accuracy of 93.75% and an average false positive rate (FPR) of 0.15 event/min. The effectiveness of our system was thus demonstrated.

  6. A Hybrid Task Graph Scheduler for High Performance Image Processing Workflows.

    Science.gov (United States)

    Blattner, Timothy; Keyrouz, Walid; Bhattacharyya, Shuvra S; Halem, Milton; Brady, Mary

    2017-12-01

    Designing applications for scalability is key to improving their performance in hybrid and cluster computing. Scheduling code to utilize parallelism is difficult, particularly when dealing with data dependencies, memory management, data motion, and processor occupancy. The Hybrid Task Graph Scheduler (HTGS) improves programmer productivity when implementing hybrid workflows for multi-core and multi-GPU systems. The Hybrid Task Graph Scheduler (HTGS) is an abstract execution model, framework, and API that increases programmer productivity when implementing hybrid workflows for such systems. HTGS manages dependencies between tasks, represents CPU and GPU memories independently, overlaps computations with disk I/O and memory transfers, keeps multiple GPUs occupied, and uses all available compute resources. Through these abstractions, data motion and memory are explicit; this makes data locality decisions more accessible. To demonstrate the HTGS application program interface (API), we present implementations of two example algorithms: (1) a matrix multiplication that shows how easily task graphs can be used; and (2) a hybrid implementation of microscopy image stitching that reduces code size by ≈ 43% compared to a manually coded hybrid workflow implementation and showcases the minimal overhead of task graphs in HTGS. Both of the HTGS-based implementations show good performance. In image stitching the HTGS implementation achieves similar performance to the hybrid workflow implementation. Matrix multiplication with HTGS achieves 1.3× and 1.8× speedup over the multi-threaded OpenBLAS library for 16k × 16k and 32k × 32k size matrices, respectively.

  7. Burnup calculation for a tokamak commercial hybrid reactor

    International Nuclear Information System (INIS)

    Feng Kaiming; Xie Zhongyou

    1990-08-01

    A computer code ISOGEN-III and its associated data library BULIB have been developed for fusion-fission hybrid reactor burnup calculations. These are used to calcuate burnup of a tokamak commercial hybrid reactor. The code and library are introduced briefly, and burnup calculation results are given

  8. Pulmonary Nodule Volumetry at Different Low Computed Tomography Radiation Dose Levels With Hybrid and Model-Based Iterative Reconstruction: A Within Patient Analysis.

    Science.gov (United States)

    den Harder, Annemarie M; Willemink, Martin J; van Hamersvelt, Robbert W; Vonken, Evertjan P A; Schilham, Arnold M R; Lammers, Jan-Willem J; Luijk, Bart; Budde, Ricardo P J; Leiner, Tim; de Jong, Pim A

    2016-01-01

    The aim of the study was to determine the effects of dose reduction and iterative reconstruction (IR) on pulmonary nodule volumetry. In this prospective study, 25 patients scheduled for follow-up of pulmonary nodules were included. Computed tomography acquisitions were acquired at 4 dose levels with a median of 2.1, 1.2, 0.8, and 0.6 mSv. Data were reconstructed with filtered back projection (FBP), hybrid IR, and model-based IR. Volumetry was performed using semiautomatic software. At the highest dose level, more than 91% (34/37) of the nodules could be segmented, and at the lowest dose level, this was more than 83%. Thirty-three nodules were included for further analysis. Filtered back projection and hybrid IR did not lead to significant differences, whereas model-based IR resulted in lower volume measurements with a maximum difference of -11% compared with FBP at routine dose. Pulmonary nodule volumetry can be accurately performed at a submillisievert dose with both FBP and hybrid IR.

  9. Linear equations and rap battles: how students in a wired classroom utilized the computer as a resource to coordinate personal and mathematical positional identities in hybrid spaces

    Science.gov (United States)

    Langer-Osuna, Jennifer

    2015-03-01

    This paper draws on the constructs of hybridity, figured worlds, and cultural capital to examine how a group of African-American students in a technology-driven, project-based algebra classroom utilized the computer as a resource to coordinate personal and mathematical positional identities during group work. Analyses of several vignettes of small group dynamics highlight how hybridity was established as the students engaged in multiple on-task and off-task computer-based activities, each of which drew on different lived experiences and forms of cultural capital. The paper ends with a discussion on how classrooms that make use of student-led collaborative work, and where students are afforded autonomy, have the potential to support the academic engagement of students from historically marginalized communities.

  10. Species delineation and hybrid identification using diagnostic nuclear markers for Plectropomus leopardus and Plectropomus maculatus

    KAUST Repository

    He, Song

    2018-06-01

    Diagnostic molecular markers are an essential tool in the study of species’ ecology and evolution, particularly in closely related and sympatric species. Furthermore, the increasing awareness of wild-hybrids has led to a renewed interest in rapid diagnostic assays. Here, we test the ability of two mitochondrial (Cytb and COI) and two nuclear markers (ETS2 and TMO-4c4) to confidently discriminate purebred P. leopardus and P. maculatus and their first-generation hybrids. A sample of 48 purebred individuals and 91 interspecific hybrids were used in this study and their delineation confirmed using a set of microsatellite markers. Our results indicate mitochondrial markers could not distinguish even between species but both nuclear markers confidently identified species and first-generation hybrids. However, later-generation hybrids could not always be confidently identified due to on-going introgression between species. Our findings provide a robust tool to distinguish purebred individuals and interspecific hybrids in a pair of species with an unexpectedly high incidence of hybridization. The quick species discrimination abilities provided by these diagnostic markers are important for stock assessment and recruitment studies of these important fishery species.

  11. Species delineation and hybrid identification using diagnostic nuclear markers for Plectropomus leopardus and Plectropomus maculatus

    KAUST Repository

    He, Song; Harrison, Hugo B.; Berumen, Michael L.

    2018-01-01

    Diagnostic molecular markers are an essential tool in the study of species’ ecology and evolution, particularly in closely related and sympatric species. Furthermore, the increasing awareness of wild-hybrids has led to a renewed interest in rapid diagnostic assays. Here, we test the ability of two mitochondrial (Cytb and COI) and two nuclear markers (ETS2 and TMO-4c4) to confidently discriminate purebred P. leopardus and P. maculatus and their first-generation hybrids. A sample of 48 purebred individuals and 91 interspecific hybrids were used in this study and their delineation confirmed using a set of microsatellite markers. Our results indicate mitochondrial markers could not distinguish even between species but both nuclear markers confidently identified species and first-generation hybrids. However, later-generation hybrids could not always be confidently identified due to on-going introgression between species. Our findings provide a robust tool to distinguish purebred individuals and interspecific hybrids in a pair of species with an unexpectedly high incidence of hybridization. The quick species discrimination abilities provided by these diagnostic markers are important for stock assessment and recruitment studies of these important fishery species.

  12. Cognitive Computing for Security.

    Energy Technology Data Exchange (ETDEWEB)

    Debenedictis, Erik [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rothganger, Fredrick [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Aimone, James Bradley [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Marinella, Matthew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Evans, Brian Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Warrender, Christina E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mickel, Patrick [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-12-01

    Final report for Cognitive Computing for Security LDRD 165613. It reports on the development of hybrid of general purpose/ne uromorphic computer architecture, with an emphasis on potential implementation with memristors.

  13. Optimizing Hybrid Spreading in Metapopulations.

    OpenAIRE

    Zhang, C.; Zhou, S.; Miller, J. C.; Cox, I. J.; Chain, B. M.

    2015-01-01

    Epidemic spreading phenomena are ubiquitous in nature and society. Examples include the spreading of diseases, information, and computer viruses. Epidemics can spread by local spreading, where infected nodes can only infect a limited set of direct target nodes and global spreading, where an infected node can infect every other node. In reality, many epidemics spread using a hybrid mixture of both types of spreading. In this study we develop a theoretical framework for studying hybrid epidemic...

  14. Optimizing Hybrid Spreading in Metapopulations

    OpenAIRE

    Zhang, Changwang; Zhou, Shi; Miller, Joel C.; Cox, Ingemar J.; Chain, Benjamin M.

    2014-01-01

    Epidemic spreading phenomena are ubiquitous in nature and society. Examples include the spreading of diseases, information, and computer viruses. Epidemics can spread by local spreading, where infected nodes can only infect a limited set of direct target nodes and global spreading, where an infected node can infect every other node. In reality, many epidemics spread using a hybrid mixture of both types of spreading. In this study we develop a theoretical framework for studying hybrid epidemic...

  15. Adaptive hybrid brain-computer interaction: ask a trainer for assistance!

    Science.gov (United States)

    Müller-Putz, Gernot R; Steyrl, David; Faller, Josef

    2014-01-01

    In applying mental imagery brain-computer interfaces (BCIs) to end users, training is a key part for novice users to get control. In general learning situations, it is an established concept that a trainer assists a trainee to improve his/her aptitude in certain skills. In this work, we want to evaluate whether we can apply this concept in the context of event-related desynchronization (ERD) based, adaptive, hybrid BCIs. Hence, in a first session we merged the features of a high aptitude BCI user, a trainer, and a novice user, the trainee, in a closed-loop BCI feedback task and automatically adapted the classifier over time. In a second session the trainees operated the system unassisted. Twelve healthy participants ran through this protocol. Along with the trainer, the trainees achieved a very high overall peak accuracy of 95.3 %. In the second session, where users operated the BCI unassisted, they still achieved a high overall peak accuracy of 83.6%. Ten of twelve first time BCI users successfully achieved significantly better than chance accuracy. Concluding, we can say that this trainer-trainee approach is very promising. Future research should investigate, whether this approach is superior to conventional training approaches. This trainer-trainee concept could have potential for future application of BCIs to end users.

  16. Insect-computer hybrid legged robot with user-adjustable speed, step length and walking gait.

    Science.gov (United States)

    Cao, Feng; Zhang, Chao; Choo, Hao Yu; Sato, Hirotaka

    2016-03-01

    We have constructed an insect-computer hybrid legged robot using a living beetle (Mecynorrhina torquata; Coleoptera). The protraction/retraction and levation/depression motions in both forelegs of the beetle were elicited by electrically stimulating eight corresponding leg muscles via eight pairs of implanted electrodes. To perform a defined walking gait (e.g., gallop), different muscles were individually stimulated in a predefined sequence using a microcontroller. Different walking gaits were performed by reordering the applied stimulation signals (i.e., applying different sequences). By varying the duration of the stimulation sequences, we successfully controlled the step frequency and hence the beetle's walking speed. To the best of our knowledge, this paper presents the first demonstration of living insect locomotion control with a user-adjustable walking gait, step length and walking speed. © 2016 The Author(s).

  17. Genetic networks and soft computing.

    Science.gov (United States)

    Mitra, Sushmita; Das, Ranajit; Hayashi, Yoichi

    2011-01-01

    The analysis of gene regulatory networks provides enormous information on various fundamental cellular processes involving growth, development, hormone secretion, and cellular communication. Their extraction from available gene expression profiles is a challenging problem. Such reverse engineering of genetic networks offers insight into cellular activity toward prediction of adverse effects of new drugs or possible identification of new drug targets. Tasks such as classification, clustering, and feature selection enable efficient mining of knowledge about gene interactions in the form of networks. It is known that biological data is prone to different kinds of noise and ambiguity. Soft computing tools, such as fuzzy sets, evolutionary strategies, and neurocomputing, have been found to be helpful in providing low-cost, acceptable solutions in the presence of various types of uncertainties. In this paper, we survey the role of these soft methodologies and their hybridizations, for the purpose of generating genetic networks.

  18. Optimizing hybrid spreading in metapopulations.

    Science.gov (United States)

    Zhang, Changwang; Zhou, Shi; Miller, Joel C; Cox, Ingemar J; Chain, Benjamin M

    2015-04-29

    Epidemic spreading phenomena are ubiquitous in nature and society. Examples include the spreading of diseases, information, and computer viruses. Epidemics can spread by local spreading, where infected nodes can only infect a limited set of direct target nodes and global spreading, where an infected node can infect every other node. In reality, many epidemics spread using a hybrid mixture of both types of spreading. In this study we develop a theoretical framework for studying hybrid epidemics, and examine the optimum balance between spreading mechanisms in terms of achieving the maximum outbreak size. We show the existence of critically hybrid epidemics where neither spreading mechanism alone can cause a noticeable spread but a combination of the two spreading mechanisms would produce an enormous outbreak. Our results provide new strategies for maximising beneficial epidemics and estimating the worst outcome of damaging hybrid epidemics.

  19. A HYBRID HEURISTIC ALGORITHM FOR THE CLUSTERED TRAVELING SALESMAN PROBLEM

    Directory of Open Access Journals (Sweden)

    Mário Mestria

    2016-04-01

    Full Text Available ABSTRACT This paper proposes a hybrid heuristic algorithm, based on the metaheuristics Greedy Randomized Adaptive Search Procedure, Iterated Local Search and Variable Neighborhood Descent, to solve the Clustered Traveling Salesman Problem (CTSP. Hybrid Heuristic algorithm uses several variable neighborhood structures combining the intensification (using local search operators and diversification (constructive heuristic and perturbation routine. In the CTSP, the vertices are partitioned into clusters and all vertices of each cluster have to be visited contiguously. The CTSP is -hard since it includes the well-known Traveling Salesman Problem (TSP as a special case. Our hybrid heuristic is compared with three heuristics from the literature and an exact method. Computational experiments are reported for different classes of instances. Experimental results show that the proposed hybrid heuristic obtains competitive results within reasonable computational time.

  20. Design tradeoff studies and sensitivity analysis. Appendices B1-B4. [HYBRID

    Energy Technology Data Exchange (ETDEWEB)

    1979-05-25

    These four appendices to the report on the Near-Term Hybrid Vehicle (NTHV) report contain information on: HYBRID computer program documentation; material substitution study for advanced hybrid vehicles; NTHV market potential; battery compartment weight distribution; and vehicle handling dynamics. (LCL)

  1. Fluorescent Molecular Rotor-in-Paraffin Waxes for Thermometry and Biometric Identification.

    Science.gov (United States)

    Jin, Young-Jae; Dogra, Rubal; Cheong, In Woo; Kwak, Giseop

    2015-07-08

    Novel thermoresponsive sensor systems consisting of a molecular rotor (MR) and paraffin wax (PW) were developed for various thermometric and biometric identification applications. Polydiphenylacetylenes (PDPAs) coupled with long alkyl chains were used as MRs, and PWs of hydrocarbons having 16-20 carbons were utilized as phase-change materials. The PDPAs were successfully dissolved in the molten PWs and did not act as an impurity that prevents phase transition of the PWs. These PDPA-in-PW hybrids had almost the same enthalpies and phase-transition temperatures as the corresponding pure PWs. The hybrids exhibited highly reversible fluorescence (FL) changes at the critical temperatures during phase transition of the PWs. These hybrids were impregnated into common filter paper in the molten state by absorption or were encapsulated into urea resin to enhance their mechanical integrity and cyclic stability during repeated use. The wax papers could be utilized in highly advanced applications including FL image writing/erasing, an array-type thermo-indicator, and fingerprint/palmprint identification. The present findings should facilitate the development of novel fluorescent sensor systems for biometric identification and are potentially applicable for biological and biomedical thermometry.

  2. Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment.

    Science.gov (United States)

    Abdullahi, Mohammed; Ngadi, Md Asri

    2016-01-01

    Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS) has been shown to perform competitively with Particle Swarm Optimization (PSO). The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA) based SOS (SASOS) in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs) which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.

  3. Hybrid Symbiotic Organisms Search Optimization Algorithm for Scheduling of Tasks on Cloud Computing Environment.

    Directory of Open Access Journals (Sweden)

    Mohammed Abdullahi

    Full Text Available Cloud computing has attracted significant attention from research community because of rapid migration rate of Information Technology services to its domain. Advances in virtualization technology has made cloud computing very popular as a result of easier deployment of application services. Tasks are submitted to cloud datacenters to be processed on pay as you go fashion. Task scheduling is one the significant research challenges in cloud computing environment. The current formulation of task scheduling problems has been shown to be NP-complete, hence finding the exact solution especially for large problem sizes is intractable. The heterogeneous and dynamic feature of cloud resources makes optimum task scheduling non-trivial. Therefore, efficient task scheduling algorithms are required for optimum resource utilization. Symbiotic Organisms Search (SOS has been shown to perform competitively with Particle Swarm Optimization (PSO. The aim of this study is to optimize task scheduling in cloud computing environment based on a proposed Simulated Annealing (SA based SOS (SASOS in order to improve the convergence rate and quality of solution of SOS. The SOS algorithm has a strong global exploration capability and uses fewer parameters. The systematic reasoning ability of SA is employed to find better solutions on local solution regions, hence, adding exploration ability to SOS. Also, a fitness function is proposed which takes into account the utilization level of virtual machines (VMs which reduced makespan and degree of imbalance among VMs. CloudSim toolkit was used to evaluate the efficiency of the proposed method using both synthetic and standard workload. Results of simulation showed that hybrid SOS performs better than SOS in terms of convergence speed, response time, degree of imbalance, and makespan.

  4. Genomics for greater efficiency in pigeonpea hybrid breeding

    Directory of Open Access Journals (Sweden)

    Rachit K Saxena

    2015-10-01

    Full Text Available Cytoplasmic genic male sterility based hybrid technology has demonstrated its immense potential in increasing the productivity of various crops, including pigeonpea. This technology has shown promise for breaking the long-standing yield stagnation in pigeonpea. There are difficulties in commercial hybrid seed production due to non-availability of field-oriented technologies such as time-bound assessment of genetic purity of hybrid seeds. Besides this, there are other routine breeding activities which are labour oriented and need more resources. These include breeding and maintenance of new fertility restorers and maintainer lines, diversification of cytoplasm, and incorporation of biotic and abiotic stress resistances. The recent progress in genomics research could accelerate the existing traditional efforts to strengthen the hybrid breeding technology. Marker based seed purity assessment, identification of heterotic groups; selection of new fertility restorers are few areas which have already been initiated. In this paper efforts have been made to identify critical areas and opportunities where genomics can play a leading role and assist breeders in accelerating various activities related to breeding and commercialization of pigeonpea hybrids.

  5. 15th International conference on Hybrid Intelligent Systems

    CERN Document Server

    Han, Sang; Al-Sharhan, Salah; Liu, Hongbo

    2016-01-01

    This book is devoted to the hybridization of intelligent systems which is a promising research field of modern computational intelligence concerned with the development of the next generation of intelligent systems. This Volume contains the papers presented in the Fifteenth International conference on Hybrid Intelligent Systems (HIS 2015) held in Seoul, South Korea during November 16-18, 2015. The 26 papers presented in this Volume were carefully reviewed and selected from 90 paper submissions. The Volume will be a valuable reference to researchers, students and practitioners in the computational intelligence field.

  6. Identification of superior parents and hybrids from diallel crosses of bread wheat (triticum aestivum l.)

    International Nuclear Information System (INIS)

    Baloch, M.J.; Rajper, T.A.; Jatoi, W.A.

    2013-01-01

    Five parents of bread wheat (Triticum aestivum L.) viz. TD-1, SKD-1, Marvi, Moomal and Mehran were crossed in a half diallel design; hence 10 F 1 hybrids were developed. Parents alongwith hybrids were evaluated for combining ability and heterosis for tillers/plant, spike length, spike density, grains/spike, grain yield/plant and seed index. The experiment was conducted in a randomized complete block design with four replications at Botanical Garden, Department of Plant Breeding and Genetics, Sindh Agriculture University,Tandojam, during 2010. The analysis of variance due to genotypes, parents, hybrids and parents vs. hybrids was significant for all the characters which revealed presence of significant amount of genetic variability in the material. The results also indicated significant differences among the parents for their general combining ability (GCA) and hybrids for specific combining ability (SCA) suggesting the importance of both additive and non-additive genes in the expression of traits studied. The greater magnitude of SCA variances over GCA were recorded for tillers/plant, grains/spike and grain yield/plant which indicated the importance of additive gene action while the involvement of non-additive genes was evident in the inheritance of spike length, spike density and seed index. Among the parents, generally TD-I, Mehran, Moomal and Marvi were the best general combiners for tillers/plant, spike length, spike density, grains/spike, grain yield/plant and seed index. Whereas, the hybrids like SKD-1 x Mehran, Marvi x Mehran, Marvix Moomal and TD-I x SKD-I were the best specific combiners for majority of yield traits. Positive heterosis was expressed by the hybrid SKD-1 x Moomal for tillers per plant; TD-I x Moomal for spike length; TD-1 x SKD-I for grains per spike; Marvi x Mehran for spike density and Marvi x Moomal for seed index. The best parents and hybrids could be effectively utilized in hybridization and selection programmes and also for hybrid crop

  7. [The value of multimodal imaging by single photon emission computed tomography associated to X ray computed tomography (SPECT-CT) in the management of differentiated thyroid carcinoma: about 156 cases].

    Science.gov (United States)

    Mhiri, Aida; El Bez, Intidhar; Slim, Ihsen; Meddeb, Imène; Yeddes, Imene; Ghezaiel, Mohamed; Gritli, Saïd; Ben Slimène, Mohamed Faouzi

    2013-10-01

    Single photon emission computed tomography combined with a low dose computed tomography (SPECT-CT), is a hybrid imaging integrating functional and anatomical data. The purpose of our study was to evaluate the contribution of the SPECTCT over traditional planar imaging of patients with differentiated thyroid carcinoma (DTC). Post therapy 131IWhole body scan followed by SPECTCT of the neck and thorax, were performed in 156 patients with DTC. Among these 156 patients followed for a predominantly papillary, the use of fusion imaging SPECT-CT compared to conventional planar imaging allowed us to correct our therapeutic approach in 26.9 % (42/156 patients), according to the protocols of therapeutic management of our institute. SPECT-CT is a multimodal imaging providing better identification and more accurate anatomic localization of the foci of radioiodine uptake with impact on therapeutic management.

  8. Computer game as a tool for training the identification of phonemic length.

    Science.gov (United States)

    Pennala, Riitta; Richardson, Ulla; Ylinen, Sari; Lyytinen, Heikki; Martin, Maisa

    2014-12-01

    Computer-assisted training of Finnish phonemic length was conducted with 7-year-old Russian-speaking second-language learners of Finnish. Phonemic length plays a different role in these two languages. The training included game activities with two- and three-syllable word and pseudo-word minimal pairs with prototypical vowel durations. The lowest accuracy scores were recorded for two-syllable words. Accuracy scores were higher for the minimal pairs with larger rather than smaller differences in duration. Accuracy scores were lower for long duration than for short duration. The ability to identify quantity degree was generalized to stimuli used in the identification test in two of the children. Ideas for improving the game are introduced.

  9. Multilevel hybrid Chernoff tau-leap

    KAUST Repository

    Moraes, Alvaro

    2015-04-08

    In this work, we extend the hybrid Chernoff tau-leap method to the multilevel Monte Carlo (MLMC) setting. Inspired by the work of Anderson and Higham on the tau-leap MLMC method with uniform time steps, we develop a novel algorithm that is able to couple two hybrid Chernoff tau-leap paths at different levels. Using dual-weighted residual expansion techniques, we also develop a new way to estimate the variance of the difference of two consecutive levels and the bias. This is crucial because the computational work required to stabilize the coefficient of variation of the sample estimators of both quantities is often unaffordable for the deepest levels of the MLMC hierarchy. Our method bounds the global computational error to be below a prescribed tolerance, TOL, within a given confidence level. This is achieved with nearly optimal computational work. Indeed, the computational complexity of our method is of order O(TOL−2), the same as with an exact method, but with a smaller constant. Our numerical examples show substantial gains with respect to the previous single-level approach and the Stochastic Simulation Algorithm.

  10. Multilevel hybrid Chernoff tau-leap

    KAUST Repository

    Moraes, Alvaro; Tempone, Raul; Vilanova, Pedro

    2015-01-01

    In this work, we extend the hybrid Chernoff tau-leap method to the multilevel Monte Carlo (MLMC) setting. Inspired by the work of Anderson and Higham on the tau-leap MLMC method with uniform time steps, we develop a novel algorithm that is able to couple two hybrid Chernoff tau-leap paths at different levels. Using dual-weighted residual expansion techniques, we also develop a new way to estimate the variance of the difference of two consecutive levels and the bias. This is crucial because the computational work required to stabilize the coefficient of variation of the sample estimators of both quantities is often unaffordable for the deepest levels of the MLMC hierarchy. Our method bounds the global computational error to be below a prescribed tolerance, TOL, within a given confidence level. This is achieved with nearly optimal computational work. Indeed, the computational complexity of our method is of order O(TOL−2), the same as with an exact method, but with a smaller constant. Our numerical examples show substantial gains with respect to the previous single-level approach and the Stochastic Simulation Algorithm.

  11. Prediction of monthly regional groundwater levels through hybrid soft-computing techniques

    Science.gov (United States)

    Chang, Fi-John; Chang, Li-Chiu; Huang, Chien-Wei; Kao, I.-Feng

    2016-10-01

    Groundwater systems are intrinsically heterogeneous with dynamic temporal-spatial patterns, which cause great difficulty in quantifying their complex processes, while reliable predictions of regional groundwater levels are commonly needed for managing water resources to ensure proper service of water demands within a region. In this study, we proposed a novel and flexible soft-computing technique that could effectively extract the complex high-dimensional input-output patterns of basin-wide groundwater-aquifer systems in an adaptive manner. The soft-computing models combined the Self Organized Map (SOM) and the Nonlinear Autoregressive with Exogenous Inputs (NARX) network for predicting monthly regional groundwater levels based on hydrologic forcing data. The SOM could effectively classify the temporal-spatial patterns of regional groundwater levels, the NARX could accurately predict the mean of regional groundwater levels for adjusting the selected SOM, the Kriging was used to interpolate the predictions of the adjusted SOM into finer grids of locations, and consequently the prediction of a monthly regional groundwater level map could be obtained. The Zhuoshui River basin in Taiwan was the study case, and its monthly data sets collected from 203 groundwater stations, 32 rainfall stations and 6 flow stations during 2000 and 2013 were used for modelling purpose. The results demonstrated that the hybrid SOM-NARX model could reliably and suitably predict monthly basin-wide groundwater levels with high correlations (R2 > 0.9 in both training and testing cases). The proposed methodology presents a milestone in modelling regional environmental issues and offers an insightful and promising way to predict monthly basin-wide groundwater levels, which is beneficial to authorities for sustainable water resources management.

  12. Disease processes as hybrid dynamical systems

    Directory of Open Access Journals (Sweden)

    Pietro Liò

    2012-08-01

    Full Text Available We investigate the use of hybrid techniques in complex processes of infectious diseases. Since predictive disease models in biomedicine require a multiscale approach for understanding the molecule-cell-tissue-organ-body interactions, heterogeneous methodologies are often employed for describing the different biological scales. Hybrid models provide effective means for complex disease modelling where the action and dosage of a drug or a therapy could be meaningfully investigated: the infection dynamics can be classically described in a continuous fashion, while the scheduling of multiple treatment discretely. We define an algebraic language for specifying general disease processes and multiple treatments, from which a semantics in terms of hybrid dynamical system can be derived. Then, the application of control-theoretic tools is proposed in order to compute the optimal scheduling of multiple therapies. The potentialities of our approach are shown in the case study of the SIR epidemic model and we discuss its applicability on osteomyelitis, a bacterial infection affecting the bone remodelling system in a specific and multiscale manner. We report that formal languages are helpful in giving a general homogeneous formulation for the different scales involved in a multiscale disease process; and that the combination of hybrid modelling and control theory provides solid grounds for computational medicine.

  13. Evaluation of the UF/NCI hybrid computational phantoms for use in organ dosimetry of pediatric patients undergoing fluoroscopically guided cardiac procedures

    Science.gov (United States)

    Marshall, Emily L.; Borrego, David; Tran, Trung; Fudge, James C.; Bolch, Wesley E.

    2018-03-01

    Epidemiologic data demonstrate that pediatric patients face a higher relative risk of radiation induced cancers than their adult counterparts at equivalent exposures. Infants and children with congenital heart defects are a critical patient population exposed to ionizing radiation during life-saving procedures. These patients will likely incur numerous procedures throughout their lifespan, each time increasing their cumulative radiation absorbed dose. As continued improvements in long-term prognosis of congenital heart defect patients is achieved, a better understanding of organ radiation dose following treatment becomes increasingly vital. Dosimetry of these patients can be accomplished using Monte Carlo radiation transport simulations, coupled with modern anatomical patient models. The aim of this study was to evaluate the performance of the University of Florida/National Cancer Institute (UF/NCI) pediatric hybrid computational phantom library for organ dose assessment of patients that have undergone fluoroscopically guided cardiac catheterizations. In this study, two types of simulations were modeled. A dose assessment was performed on 29 patient-specific voxel phantoms (taken as representing the patient’s true anatomy), height/weight-matched hybrid library phantoms, and age-matched reference phantoms. Two exposure studies were conducted for each phantom type. First, a parametric study was constructed by the attending pediatric interventional cardiologist at the University of Florida to model the range of parameters seen clinically. Second, four clinical cardiac procedures were simulated based upon internal logfiles captured by a Toshiba Infinix-i Cardiac Bi-Plane fluoroscopic unit. Performance of the phantom library was quantified by computing both the percent difference in individual organ doses, as well as the organ dose root mean square values for overall phantom assessment between the matched phantoms (UF/NCI library or reference) and the patient

  14. Computational lymphatic node models in pediatric and adult hybrid phantoms for radiation dosimetry

    International Nuclear Information System (INIS)

    Lee, Choonsik; Lamart, Stephanie; Moroz, Brian E

    2013-01-01

    We developed models of lymphatic nodes for six pediatric and two adult hybrid computational phantoms to calculate the lymphatic node dose estimates from external and internal radiation exposures. We derived the number of lymphatic nodes from the recommendations in International Commission on Radiological Protection (ICRP) Publications 23 and 89 at 16 cluster locations for the lymphatic nodes: extrathoracic, cervical, thoracic (upper and lower), breast (left and right), mesentery (left and right), axillary (left and right), cubital (left and right), inguinal (left and right) and popliteal (left and right), for different ages (newborn, 1-, 5-, 10-, 15-year-old and adult). We modeled each lymphatic node within the voxel format of the hybrid phantoms by assuming that all nodes have identical size derived from published data except narrow cluster sites. The lymph nodes were generated by the following algorithm: (1) selection of the lymph node site among the 16 cluster sites; (2) random sampling of the location of the lymph node within a spherical space centered at the chosen cluster site; (3) creation of the sphere or ovoid of tissue representing the node based on lymphatic node characteristics defined in ICRP Publications 23 and 89. We created lymph nodes until the pre-defined number of lymphatic nodes at the selected cluster site was reached. This algorithm was applied to pediatric (newborn, 1-, 5-and 10-year-old male, and 15-year-old males) and adult male and female ICRP-compliant hybrid phantoms after voxelization. To assess the performance of our models for internal dosimetry, we calculated dose conversion coefficients, called S values, for selected organs and tissues with Iodine-131 distributed in six lymphatic node cluster sites using MCNPX2.6, a well validated Monte Carlo radiation transport code. Our analysis of the calculations indicates that the S values were significantly affected by the location of the lymph node clusters and that the values increased for

  15. Construction, implementation and testing of an image identification system using computer vision methods for fruit flies with economic importance (Diptera: Tephritidae).

    Science.gov (United States)

    Wang, Jiang-Ning; Chen, Xiao-Lin; Hou, Xin-Wen; Zhou, Li-Bing; Zhu, Chao-Dong; Ji, Li-Qiang

    2017-07-01

    Many species of Tephritidae are damaging to fruit, which might negatively impact international fruit trade. Automatic or semi-automatic identification of fruit flies are greatly needed for diagnosing causes of damage and quarantine protocols for economically relevant insects. A fruit fly image identification system named AFIS1.0 has been developed using 74 species belonging to six genera, which include the majority of pests in the Tephritidae. The system combines automated image identification and manual verification, balancing operability and accuracy. AFIS1.0 integrates image analysis and expert system into a content-based image retrieval framework. In the the automatic identification module, AFIS1.0 gives candidate identification results. Afterwards users can do manual selection based on comparing unidentified images with a subset of images corresponding to the automatic identification result. The system uses Gabor surface features in automated identification and yielded an overall classification success rate of 87% to the species level by Independent Multi-part Image Automatic Identification Test. The system is useful for users with or without specific expertise on Tephritidae in the task of rapid and effective identification of fruit flies. It makes the application of computer vision technology to fruit fly recognition much closer to production level. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  16. Triaxial Accelerometer Error Coefficients Identification with a Novel Artificial Fish Swarm Algorithm

    Directory of Open Access Journals (Sweden)

    Yanbin Gao

    2015-01-01

    Full Text Available Artificial fish swarm algorithm (AFSA is one of the state-of-the-art swarm intelligence techniques, which is widely utilized for optimization purposes. Triaxial accelerometer error coefficients are relatively unstable with the environmental disturbances and aging of the instrument. Therefore, identifying triaxial accelerometer error coefficients accurately and being with lower costs are of great importance to improve the overall performance of triaxial accelerometer-based strapdown inertial navigation system (SINS. In this study, a novel artificial fish swarm algorithm (NAFSA that eliminated the demerits (lack of using artificial fishes’ previous experiences, lack of existing balance between exploration and exploitation, and high computational cost of AFSA is introduced at first. In NAFSA, functional behaviors and overall procedure of AFSA have been improved with some parameters variations. Second, a hybrid accelerometer error coefficients identification algorithm has been proposed based on NAFSA and Monte Carlo simulation (MCS approaches. This combination leads to maximum utilization of the involved approaches for triaxial accelerometer error coefficients identification. Furthermore, the NAFSA-identified coefficients are testified with 24-position verification experiment and triaxial accelerometer-based SINS navigation experiment. The priorities of MCS-NAFSA are compared with that of conventional calibration method and optimal AFSA. Finally, both experiments results demonstrate high efficiency of MCS-NAFSA on triaxial accelerometer error coefficients identification.

  17. Hybrid fission-fusion nuclear reactors

    International Nuclear Information System (INIS)

    Zucchetti, Massimo

    2011-01-01

    A fusion-fission hybrid could contribute to all components of nuclear power - fuel supply, electricity production, and waste management. The idea of the fusion-fission hybrid is many decades old. Several ideas, both new and revisited, have been investigated by hybrid proponents. These ideas appear to have attractive features, but they require various levels of advances in plasma science and fusion and nuclear technology. As a first step towards the development of hybrid reactors, fusion neutron sources can be considered as an option. Compact high-field tokamaks can be a candidate for being the neutron source in a fission-fusion hybrid, essentially due to their design characteristics, such as compact dimensions, high magnetic field, flexibility of operation. This study presents the development of a tokamak neutron source for a material testing facility using an Ignitor-based concept. The computed values show the potential of this neutron-rich device for fusion materials testing. Some full-power months of operation are sufficient to obtain relevant radiation damage values in terms of dpa. (Author)

  18. Hybrid GPU-CPU adaptive precision ray-triangle intersection tests for robust high-performance GPU dosimetry computations

    International Nuclear Information System (INIS)

    Perrotte, Lancelot; Bodin, Bruno; Chodorge, Laurent

    2011-01-01

    Before an intervention on a nuclear site, it is essential to study different scenarios to identify the less dangerous one for the operator. Therefore, it is mandatory to dispose of an efficient dosimetry simulation code with accurate results. One classical method in radiation protection is the straight-line attenuation method with build-up factors. In the case of 3D industrial scenes composed of meshes, the computation cost resides in the fast computation of all of the intersections between the rays and the triangles of the scene. Efficient GPU algorithms have already been proposed, that enable dosimetry calculation for a huge scene (800000 rays, 800000 triangles) in a fraction of second. But these algorithms are not robust: because of the rounding caused by floating-point arithmetic, the numerical results of the ray-triangle intersection tests can differ from the expected mathematical results. In worst case scenario, this can lead to a computed dose rate dramatically inferior to the real dose rate to which the operator is exposed. In this paper, we present a hybrid GPU-CPU algorithm to manage adaptive precision floating-point arithmetic. This algorithm allows robust ray-triangle intersection tests, with very small loss of performance (less than 5 % overhead), and without any need for scene-dependent tuning. (author)

  19. Comparison of a commercial biochemical kit and an oligonucleotide probe for identification of environmental isolates of Vibrio vulnificus

    DEFF Research Database (Denmark)

    Dalsgaard, A.; Dalsgaard, Inger; Høi, L.

    1996-01-01

    Methods for the identification and isolation of environmental isolates of Vibrio vulnificus were evaluated. Alkaline peptone water supplemented with polymyxin B and colistin-polymyxin B- cellobiose agar were employed for the isolation of suspected V. vulnificus from water, sediment and shellfish ...... hybridizing with the probe. The results indicated that, compared with colony hybridization, the API 20E assay was not adequate for the identification of environmental isolates of V. vulnificus....

  20. Hybrid brain-computer interface for biomedical cyber-physical system application using wireless embedded EEG systems.

    Science.gov (United States)

    Chai, Rifai; Naik, Ganesh R; Ling, Sai Ho; Nguyen, Hung T

    2017-01-07

    One of the key challenges of the biomedical cyber-physical system is to combine cognitive neuroscience with the integration of physical systems to assist people with disabilities. Electroencephalography (EEG) has been explored as a non-invasive method of providing assistive technology by using brain electrical signals. This paper presents a unique prototype of a hybrid brain computer interface (BCI) which senses a combination classification of mental task, steady state visual evoked potential (SSVEP) and eyes closed detection using only two EEG channels. In addition, a microcontroller based head-mounted battery-operated wireless EEG sensor combined with a separate embedded system is used to enhance portability, convenience and cost effectiveness. This experiment has been conducted with five healthy participants and five patients with tetraplegia. Generally, the results show comparable classification accuracies between healthy subjects and tetraplegia patients. For the offline artificial neural network classification for the target group of patients with tetraplegia, the hybrid BCI system combines three mental tasks, three SSVEP frequencies and eyes closed, with average classification accuracy at 74% and average information transfer rate (ITR) of the system of 27 bits/min. For the real-time testing of the intentional signal on patients with tetraplegia, the average success rate of detection is 70% and the speed of detection varies from 2 to 4 s.

  1. Conceptual design of distillation-based hybrid separation processes.

    Science.gov (United States)

    Skiborowski, Mirko; Harwardt, Andreas; Marquardt, Wolfgang

    2013-01-01

    Hybrid separation processes combine different separation principles and constitute a promising design option for the separation of complex mixtures. Particularly, the integration of distillation with other unit operations can significantly improve the separation of close-boiling or azeotropic mixtures. Although the design of single-unit operations is well understood and supported by computational methods, the optimal design of flowsheets of hybrid separation processes is still a challenging task. The large number of operational and design degrees of freedom requires a systematic and optimization-based design approach. To this end, a structured approach, the so-called process synthesis framework, is proposed. This article reviews available computational methods for the conceptual design of distillation-based hybrid processes for the separation of liquid mixtures. Open problems are identified that must be addressed to finally establish a structured process synthesis framework for such processes.

  2. Design and construction the identification of nitriding plasma process parameters using personal computer based on serial communication

    International Nuclear Information System (INIS)

    Frida Iswinning Diah; Slamet Santosa

    2012-01-01

    Design and construction the identification of process parameters using personal computer based on serial communication PLC M-series has been done. The function of this device is to identify the process parameters of a system (plan), to which then be analyzed and conducted a follow-up given to the plan by the user. The main component of this device is the M-Series T100MD1616 PLC and personal computer (PC). In this device the data plan parameters obtained from the corresponding sensor outputs in the form of voltage or current. While the analog parameter data is adjusted to the ADC analog input of the PLC using a signal conditioning system. Then, as the parameter is processed by the PLC then sent to a PC via RS232 to be displayed in the form of graphs or tables and stored in the database. Software to program the database is created using Visual Basic Programming V-6. The device operation test is performed for the measurement of temperature parameter and vacuum level on the plasma nitriding machine. The results indicate that the device has functioning as an identification device parameters process of plasma nitriding machine. (author)

  3. Methodology for the hybrid solution of systems of differential equations

    International Nuclear Information System (INIS)

    Larrinaga, E.F.; Lopez, M.A.

    1993-01-01

    This work shows a general methodology of solution to systems of differential equations in hybrid computers. Taking into account this methodology, a mathematical model was elaborated. It offers wide possibilities of recording and handling the results on the basis of using the hybrid system IBM-VIDAC 1224 which the ISCTN has. It also presents the results gained when simulating a simple model of a nuclear reactor, which was used in the validation of the results of the computational model

  4. Transgenic Drosophila simulans strains prove the identity of the speciation gene Lethal hybrid rescue.

    Science.gov (United States)

    Prigent, Stéphane R; Matsubayashi, Hiroshi; Yamamoto, Masa-Toshi

    2009-10-01

    Speciation genes are responsible for genetic incompatibilities in hybrids of incipient species and therefore participate in reproductive isolation leading to complete speciation. Hybrid males between Drosophila melanogaster females and D. simulans males die at late larval or prepupal stages due to a failure in chromosome condensation during mitosis. However a mutant male of D. simulans, named Lethal hybrid rescue (Lhr), produces viable hybrid males when crossed to females of D. melanogaster. Recently the Lhr gene has been proposed as corresponding to the CG18468 gene in D. melanogaster. However this identification relied on sequence characteristics more than on a precise mapping and the use of the GAL4/UAS system to drive the transgene in D. melanogaster might have increased the complexity of interaction. Thus here we propose an independent identification of the Lhr gene based on a more precise mapping and transgenic experiments in D. simulans. We have mapped the Lhr gene by using Single Nucleotide Polymorphisms (SNPs) and identified within the candidate region the gene homologous to CG18468 as the Lhr gene as it was previously reported. Transgenic experiments in D. simulans with the native promoter of CG18468 prove that it is the Lhr gene of D. simulans by inducing the lethality of the hybrid males.

  5. A Hybrid Soft Computing Approach for Subset Problems

    Directory of Open Access Journals (Sweden)

    Broderick Crawford

    2013-01-01

    Full Text Available Subset problems (set partitioning, packing, and covering are formal models for many practical optimization problems. A set partitioning problem determines how the items in one set (S can be partitioned into smaller subsets. All items in S must be contained in one and only one partition. Related problems are set packing (all items must be contained in zero or one partitions and set covering (all items must be contained in at least one partition. Here, we present a hybrid solver based on ant colony optimization (ACO combined with arc consistency for solving this kind of problems. ACO is a swarm intelligence metaheuristic inspired on ants behavior when they search for food. It allows to solve complex combinatorial problems for which traditional mathematical techniques may fail. By other side, in constraint programming, the solving process of Constraint Satisfaction Problems can dramatically reduce the search space by means of arc consistency enforcing constraint consistencies either prior to or during search. Our hybrid approach was tested with set covering and set partitioning dataset benchmarks. It was observed that the performance of ACO had been improved embedding this filtering technique in its constructive phase.

  6. Stability and economy analysis based on computational fluid dynamics and field testing of hybrid-driven underwater glider with the water quality sensor in Danjiangkou Reservoir

    Directory of Open Access Journals (Sweden)

    Chao Li

    2015-12-01

    Full Text Available Hybrid-driven underwater glider is a new kind of unmanned platform for water quality monitoring. It has advantages such as high controllability and maneuverability, low cost, easy operation, and ability to carry multiple sensors. This article develops a hybrid-driven underwater glider, PETRELII, and integrates a water quality monitoring sensor. Considering stability and economy, an optimal layout scheme is selected from four candidates by simulation using computational fluid dynamics method. Trials were carried out in Danjiangkou Reservoir—important headwaters of the Middle Route of the South-to-North Water Diversion Project. In the trials, a monitoring strategy with polygonal mixed-motion was adopted to make full use of the advantages of the unmanned platform. The measuring data, including temperature, dissolved oxygen, conductivity, pH, turbidity, chlorophyll, and ammonia nitrogen, are obtained. These data validate the practicability of the theoretical layout obtained using computational fluid dynamics method and the practical performance of PETRELII with sensor.

  7. A computational model for lower hybrid current drive

    International Nuclear Information System (INIS)

    Englade, R.C.; Bonoli, P.T.; Porkolab, M.

    1983-01-01

    A detailed simulation model for lower hybrid (LH) current drive in toroidal devices is discussed. This model accounts reasonably well for the magnitude of radio frequency (RF) current observed in the PLT and Alcator C devices. It also reproduces the experimental dependencies of RF current generation on toroidal magnetic field and has provided insights about mechanisms which may underlie the observed density limit of current drive. (author)

  8. The photon identification loophole in EPRB experiments: computer models with single-wing selection

    Directory of Open Access Journals (Sweden)

    De Raedt Hans

    2017-11-01

    Full Text Available Recent Einstein-Podolsky-Rosen-Bohm experiments [M. Giustina et al. Phys. Rev. Lett. 115, 250401 (2015; L. K. Shalm et al. Phys. Rev. Lett. 115, 250402 (2015] that claim to be loophole free are scrutinized. The combination of a digital computer and discrete-event simulation is used to construct a minimal but faithful model of the most perfected realization of these laboratory experiments. In contrast to prior simulations, all photon selections are strictly made, as they are in the actual experiments, at the local station and no other “post-selection” is involved. The simulation results demonstrate that a manifestly non-quantum model that identifies photons in the same local manner as in these experiments can produce correlations that are in excellent agreement with those of the quantum theoretical description of the corresponding thought experiment, in conflict with Bell’s theorem which states that this is impossible. The failure of Bell’s theorem is possible because of our recognition of the photon identification loophole. Such identification measurement-procedures are necessarily included in all actual experiments but are not included in the theory of Bell and his followers.

  9. The photon identification loophole in EPRB experiments: computer models with single-wing selection

    Science.gov (United States)

    De Raedt, Hans; Michielsen, Kristel; Hess, Karl

    2017-11-01

    Recent Einstein-Podolsky-Rosen-Bohm experiments [M. Giustina et al. Phys. Rev. Lett. 115, 250401 (2015); L. K. Shalm et al. Phys. Rev. Lett. 115, 250402 (2015)] that claim to be loophole free are scrutinized. The combination of a digital computer and discrete-event simulation is used to construct a minimal but faithful model of the most perfected realization of these laboratory experiments. In contrast to prior simulations, all photon selections are strictly made, as they are in the actual experiments, at the local station and no other "post-selection" is involved. The simulation results demonstrate that a manifestly non-quantum model that identifies photons in the same local manner as in these experiments can produce correlations that are in excellent agreement with those of the quantum theoretical description of the corresponding thought experiment, in conflict with Bell's theorem which states that this is impossible. The failure of Bell's theorem is possible because of our recognition of the photon identification loophole. Such identification measurement-procedures are necessarily included in all actual experiments but are not included in the theory of Bell and his followers.

  10. Technology for Large-Scale Translation of Clinical Practice Guidelines: A Pilot Study of the Performance of a Hybrid Human and Computer-Assisted Approach.

    Science.gov (United States)

    Van de Velde, Stijn; Macken, Lieve; Vanneste, Koen; Goossens, Martine; Vanschoenbeek, Jan; Aertgeerts, Bert; Vanopstal, Klaar; Vander Stichele, Robert; Buysschaert, Joost

    2015-10-09

    The construction of EBMPracticeNet, a national electronic point-of-care information platform in Belgium, began in 2011 to optimize quality of care by promoting evidence-based decision making. The project involved, among other tasks, the translation of 940 EBM Guidelines of Duodecim Medical Publications from English into Dutch and French. Considering the scale of the translation process, it was decided to make use of computer-aided translation performed by certificated translators with limited expertise in medical translation. Our consortium used a hybrid approach, involving a human translator supported by a translation memory (using SDL Trados Studio), terminology recognition (using SDL MultiTerm terminology databases) from medical terminology databases, and support from online machine translation. This resulted in a validated translation memory, which is now in use for the translation of new and updated guidelines. The objective of this experiment was to evaluate the performance of the hybrid human and computer-assisted approach in comparison with translation unsupported by translation memory and terminology recognition. A comparison was also made with the translation efficiency of an expert medical translator. We conducted a pilot study in which two sets of 30 new and 30 updated guidelines were randomized to one of three groups. Comparable guidelines were translated (1) by certificated junior translators without medical specialization using the hybrid method, (2) by an experienced medical translator without this support, and (3) by the same junior translators without the support of the validated translation memory. A medical proofreader who was blinded for the translation procedure, evaluated the translated guidelines for acceptability and adequacy. Translation speed was measured by recording translation and post-editing time. The human translation edit rate was calculated as a metric to evaluate the quality of the translation. A further evaluation was made of

  11. Reactor systems modeling for ICF hybrids

    International Nuclear Information System (INIS)

    Berwald, D.H.; Meier, W.R.

    1980-10-01

    The computational models of ICF reactor subsystems developed by LLNL and TRW are described and a computer program was incorporated for use in the EPRI-sponsored Feasibility Assessment of Fusion-Fission Hybrids. Representative parametric variations have been examined. Many of the ICF subsystem models are very preliminary and more quantitative models need to be developed and included in the code

  12. All-Particle Multiscale Computation of Hypersonic Rarefied Flow

    Science.gov (United States)

    Jun, E.; Burt, J. M.; Boyd, I. D.

    2011-05-01

    This study examines a new hybrid particle scheme used as an alternative means of multiscale flow simulation. The hybrid particle scheme employs the direct simulation Monte Carlo (DSMC) method in rarefied flow regions and the low diffusion (LD) particle method in continuum flow regions. The numerical procedures of the low diffusion particle method are implemented within an existing DSMC algorithm. The performance of the LD-DSMC approach is assessed by studying Mach 10 nitrogen flow over a sphere with a global Knudsen number of 0.002. The hybrid scheme results show good overall agreement with results from standard DSMC and CFD computation. Subcell procedures are utilized to improve computational efficiency and reduce sensitivity to DSMC cell size in the hybrid scheme. This makes it possible to perform the LD-DSMC simulation on a much coarser mesh that leads to a significant reduction in computation time.

  13. Large-Scale, Multi-Sensor Atmospheric Data Fusion Using Hybrid Cloud Computing

    Science.gov (United States)

    Wilson, B. D.; Manipon, G.; Hua, H.; Fetzer, E. J.

    2015-12-01

    NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, MODIS, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over decades. Moving to multi-sensor, long-duration presents serious challenges for large-scale data mining and fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over 10 years of data. HySDS is a Hybrid-Cloud Science Data System that has been developed and applied under NASA AIST, MEaSUREs, and ACCESS grants. HySDS uses the SciFlow workflow engine to partition analysis workflows into parallel tasks (e.g. segmenting by time or space) that are pushed into a durable job queue. The tasks are "pulled" from the queue by worker Virtual Machines (VM's) and executed in an on-premise Cloud (Eucalyptus or OpenStack) or at Amazon in the public Cloud or govCloud. In this way, years of data (millions of files) can be processed in a massively parallel way. Input variables (arrays) are pulled on-demand into the Cloud using OPeNDAP URLs or other subsetting services, thereby minimizing the size of the transferred data. We are using HySDS to automate the production of multiple versions of a ten-year A-Train water vapor climatology under a MEASURES grant. We will present the architecture of HySDS, describe the achieved "clock time" speedups in fusing datasets on our own nodes and in the Amazon Cloud, and discuss the Cloud cost tradeoffs for storage, compute, and data transfer. Our system demonstrates how one can pull A-Train variables (Levels 2 & 3) on-demand into the Amazon Cloud, and cache only those variables that are heavily used, so that any number of compute jobs can be

  14. Quantum Accelerators for High-performance Computing Systems

    Energy Technology Data Exchange (ETDEWEB)

    Humble, Travis S. [ORNL; Britt, Keith A. [ORNL; Mohiyaddin, Fahd A. [ORNL

    2017-11-01

    We define some of the programming and system-level challenges facing the application of quantum processing to high-performance computing. Alongside barriers to physical integration, prominent differences in the execution of quantum and conventional programs challenges the intersection of these computational models. Following a brief overview of the state of the art, we discuss recent advances in programming and execution models for hybrid quantum-classical computing. We discuss a novel quantum-accelerator framework that uses specialized kernels to offload select workloads while integrating with existing computing infrastructure. We elaborate on the role of the host operating system to manage these unique accelerator resources, the prospects for deploying quantum modules, and the requirements placed on the language hierarchy connecting these different system components. We draw on recent advances in the modeling and simulation of quantum computing systems with the development of architectures for hybrid high-performance computing systems and the realization of software stacks for controlling quantum devices. Finally, we present simulation results that describe the expected system-level behavior of high-performance computing systems composed from compute nodes with quantum processing units. We describe performance for these hybrid systems in terms of time-to-solution, accuracy, and energy consumption, and we use simple application examples to estimate the performance advantage of quantum acceleration.

  15. Modelling biochemical networks with intrinsic time delays: a hybrid semi-parametric approach

    Directory of Open Access Journals (Sweden)

    Oliveira Rui

    2010-09-01

    Full Text Available Abstract Background This paper presents a method for modelling dynamical biochemical networks with intrinsic time delays. Since the fundamental mechanisms leading to such delays are many times unknown, non conventional modelling approaches become necessary. Herein, a hybrid semi-parametric identification methodology is proposed in which discrete time series are incorporated into fundamental material balance models. This integration results in hybrid delay differential equations which can be applied to identify unknown cellular dynamics. Results The proposed hybrid modelling methodology was evaluated using two case studies. The first of these deals with dynamic modelling of transcriptional factor A in mammalian cells. The protein transport from the cytosol to the nucleus introduced a delay that was accounted for by discrete time series formulation. The second case study focused on a simple network with distributed time delays that demonstrated that the discrete time delay formalism has broad applicability to both discrete and distributed delay problems. Conclusions Significantly better prediction qualities of the novel hybrid model were obtained when compared to dynamical structures without time delays, being the more distinctive the more significant the underlying system delay is. The identification of the system delays by studies of different discrete modelling delays was enabled by the proposed structure. Further, it was shown that the hybrid discrete delay methodology is not limited to discrete delay systems. The proposed method is a powerful tool to identify time delays in ill-defined biochemical networks.

  16. Bond graph model-based fault diagnosis of hybrid systems

    CERN Document Server

    Borutzky, Wolfgang

    2015-01-01

    This book presents a bond graph model-based approach to fault diagnosis in mechatronic systems appropriately represented by a hybrid model. The book begins by giving a survey of the fundamentals of fault diagnosis and failure prognosis, then recalls state-of-art developments referring to latest publications, and goes on to discuss various bond graph representations of hybrid system models, equations formulation for switched systems, and simulation of their dynamic behavior. The structured text: • focuses on bond graph model-based fault detection and isolation in hybrid systems; • addresses isolation of multiple parametric faults in hybrid systems; • considers system mode identification; • provides a number of elaborated case studies that consider fault scenarios for switched power electronic systems commonly used in a variety of applications; and • indicates that bond graph modelling can also be used for failure prognosis. In order to facilitate the understanding of fault diagnosis and the presented...

  17. Exploratory Topology Modelling of Form-Active Hybrid Structures

    DEFF Research Database (Denmark)

    Holden Deleuran, Anders; Pauly, Mark; Tamke, Martin

    2016-01-01

    The development of novel form-active hybrid structures (FAHS) is impeded by a lack of modelling tools that allow for exploratory topology modelling of shaped assemblies. We present a flexible and real-time computational design modelling pipeline developed for the exploratory modelling of FAHS...... that enables designers and engineers to iteratively construct and manipulate form-active hybrid assembly topology on the fly. The pipeline implements Kangaroo2's projection-based methods for modelling hybrid structures consisting of slender beams and cable networks. A selection of design modelling sketches...

  18. Hybrid RANS-LES using high order numerical methods

    Science.gov (United States)

    Henry de Frahan, Marc; Yellapantula, Shashank; Vijayakumar, Ganesh; Knaus, Robert; Sprague, Michael

    2017-11-01

    Understanding the impact of wind turbine wake dynamics on downstream turbines is particularly important for the design of efficient wind farms. Due to their tractable computational cost, hybrid RANS/LES models are an attractive framework for simulating separation flows such as the wake dynamics behind a wind turbine. High-order numerical methods can be computationally efficient and provide increased accuracy in simulating complex flows. In the context of LES, high-order numerical methods have shown some success in predictions of turbulent flows. However, the specifics of hybrid RANS-LES models, including the transition region between both modeling frameworks, pose unique challenges for high-order numerical methods. In this work, we study the effect of increasing the order of accuracy of the numerical scheme in simulations of canonical turbulent flows using RANS, LES, and hybrid RANS-LES models. We describe the interactions between filtering, model transition, and order of accuracy and their effect on turbulence quantities such as kinetic energy spectra, boundary layer evolution, and dissipation rate. This work was funded by the U.S. Department of Energy, Exascale Computing Project, under Contract No. DE-AC36-08-GO28308 with the National Renewable Energy Laboratory.

  19. Analysis and identification of time-invariant systems, time-varying systems, and multi-delay systems using orthogonal hybrid functions theory and algorithms with Matlab

    CERN Document Server

    Deb, Anish; Sarkar, Gautam

    2016-01-01

    This book introduces a new set of orthogonal hybrid functions (HF) which approximates time functions in a piecewise linear manner which is very suitable for practical applications. The book presents an analysis of different systems namely, time-invariant system, time-varying system, multi-delay systems---both homogeneous and non-homogeneous type- and the solutions are obtained in the form of discrete samples. The book also investigates system identification problems for many of the above systems. The book is spread over 15 chapters and contains 180 black and white figures, 18 colour figures, 85 tables and 56 illustrative examples. MATLAB codes for many such examples are included at the end of the book.

  20. Identification and Endodontic Management of Middle Mesial Canal in Mandibular Second Molar Using Cone Beam Computed Tomography

    Directory of Open Access Journals (Sweden)

    Bonny Paul

    2015-01-01

    Full Text Available Endodontic treatments are routinely done with the help of radiographs. However, radiographs represent only a two-dimensional image of an object. Failure to identify aberrant anatomy can lead to endodontic failure. This case report presents the use of three-dimensional imaging with cone beam computed tomography (CBCT as an adjunct to digital radiography in identification and management of mandibular second molar with three mesial canals.

  1. STEM image simulation with hybrid CPU/GPU programming

    International Nuclear Information System (INIS)

    Yao, Y.; Ge, B.H.; Shen, X.; Wang, Y.G.; Yu, R.C.

    2016-01-01

    STEM image simulation is achieved via hybrid CPU/GPU programming under parallel algorithm architecture to speed up calculation on a personal computer (PC). To utilize the calculation power of a PC fully, the simulation is performed using the GPU core and multi-CPU cores at the same time to significantly improve efficiency. GaSb and an artificial GaSb/InAs interface with atom diffusion have been used to verify the computation. - Highlights: • STEM image simulation is achieved by hybrid CPU/GPU programming under parallel algorithm architecture to speed up the calculation in the personal computer (PC). • In order to fully utilize the calculation power of the PC, the simulation is performed by GPU core and multi-CPU cores at the same time so efficiency is improved significantly. • GaSb and artificial GaSb/InAs interface with atom diffusion have been used to verify the computation. The results reveal some unintuitive phenomena about the contrast variation with the atom numbers.

  2. STEM image simulation with hybrid CPU/GPU programming

    Energy Technology Data Exchange (ETDEWEB)

    Yao, Y., E-mail: yaoyuan@iphy.ac.cn; Ge, B.H.; Shen, X.; Wang, Y.G.; Yu, R.C.

    2016-07-15

    STEM image simulation is achieved via hybrid CPU/GPU programming under parallel algorithm architecture to speed up calculation on a personal computer (PC). To utilize the calculation power of a PC fully, the simulation is performed using the GPU core and multi-CPU cores at the same time to significantly improve efficiency. GaSb and an artificial GaSb/InAs interface with atom diffusion have been used to verify the computation. - Highlights: • STEM image simulation is achieved by hybrid CPU/GPU programming under parallel algorithm architecture to speed up the calculation in the personal computer (PC). • In order to fully utilize the calculation power of the PC, the simulation is performed by GPU core and multi-CPU cores at the same time so efficiency is improved significantly. • GaSb and artificial GaSb/InAs interface with atom diffusion have been used to verify the computation. The results reveal some unintuitive phenomena about the contrast variation with the atom numbers.

  3. New hybrid conjugate gradient methods with the generalized Wolfe line search.

    Science.gov (United States)

    Xu, Xiao; Kong, Fan-Yu

    2016-01-01

    The conjugate gradient method was an efficient technique for solving the unconstrained optimization problem. In this paper, we made a linear combination with parameters β k of the DY method and the HS method, and putted forward the hybrid method of DY and HS. We also proposed the hybrid of FR and PRP by the same mean. Additionally, to present the two hybrid methods, we promoted the Wolfe line search respectively to compute the step size α k of the two hybrid methods. With the new Wolfe line search, the two hybrid methods had descent property and global convergence property of the two hybrid methods that can also be proved.

  4. Identification of pathogenic Nocardia species by reverse line blot hybridization targeting the 16S rRNA and 16S-23S rRNA gene spacer regions.

    Science.gov (United States)

    Xiao, Meng; Kong, Fanrong; Sorrell, Tania C; Cao, Yongyan; Lee, Ok Cha; Liu, Ying; Sintchenko, Vitali; Chen, Sharon C A

    2010-02-01

    Although 16S rRNA gene sequence analysis is employed most often for the definitive identification of Nocardia species, alternate molecular methods and polymorphisms in other gene targets have also enabled species determinations. We evaluated a combined Nocardia PCR-based reverse line blot (RLB) hybridization assay based on 16S and 16S-23S rRNA gene spacer region polymorphisms to identify 12 American Type Culture Collection and 123 clinical Nocardia isolates representing 14 species; results were compared with results from 16S rRNA gene sequencing. Thirteen 16S rRNA gene-based (two group-specific and 11 species-specific) and five 16S-23S spacer-targeted (two taxon-specific and three species-specific) probes were utilized. 16S rRNA gene-based probes correctly identified 124 of 135 isolates (sensitivity, 92%) but were unable to identify Nocardia paucivorans strains (n = 10 strains) and a Nocardia asteroides isolate with a novel 16S rRNA gene sequence. Nocardia farcinica and Nocardia cyriacigeorgica strains were identified by the sequential use of an N. farcinica-"negative" probe and a combined N. farcinica/N. cyriacigeorgica probe. The assay specificity was high (99%) except for weak cross-reactivity between the Nocardia brasiliensis probe with the Nocardia thailandica DNA product; however, cross-hybridization with closely related nontarget species may occur. The incorporation of 16S-23S rRNA gene spacer-based probes enabled the identification of all N. paucivorans strains. The overall sensitivity using both probe sets was >99%. Both N. farcinica-specific 16S-23S rRNA gene spacer-directed probes were required to identify all N. farcinica stains by using this probe set. The study demonstrates the utility of a combined PCR/RLB assay for the identification of clinically relevant Nocardia species and its potential for studying subtypes of N. farcinica. Where species assignment is ambiguous or not possible, 16S rRNA gene sequencing is recommended.

  5. Computational identification of strain-, species- and genus-specific proteins

    Directory of Open Access Journals (Sweden)

    Thiagarajan Rathi

    2005-11-01

    Full Text Available Abstract Background The identification of unique proteins at different taxonomic levels has both scientific and practical value. Strain-, species- and genus-specific proteins can provide insight into the criteria that define an organism and its relationship with close relatives. Such proteins can also serve as taxon-specific diagnostic targets. Description A pipeline using a combination of computational and manual analyses of BLAST results was developed to identify strain-, species-, and genus-specific proteins and to catalog the closest sequenced relative for each protein in a proteome. Proteins encoded by a given strain are preliminarily considered to be unique if BLAST, using a comprehensive protein database, fails to retrieve (with an e-value better than 0.001 any protein not encoded by the query strain, species or genus (for strain-, species- and genus-specific proteins respectively, or if BLAST, using the best hit as the query (reverse BLAST, does not retrieve the initial query protein. Results are manually inspected for homology if the initial query is retrieved in the reverse BLAST but is not the best hit. Sequences unlikely to retrieve homologs using the default BLOSUM62 matrix (usually short sequences are re-tested using the PAM30 matrix, thereby increasing the number of retrieved homologs and increasing the stringency of the search for unique proteins. The above protocol was used to examine several food- and water-borne pathogens. We find that the reverse BLAST step filters out about 22% of proteins with homologs that would otherwise be considered unique at the genus and species levels. Analysis of the annotations of unique proteins reveals that many are remnants of prophage proteins, or may be involved in virulence. The data generated from this study can be accessed and further evaluated from the CUPID (Core and Unique Protein Identification system web site (updated semi-annually at http://pir.georgetown.edu/cupid. Conclusion CUPID

  6. Utilization of the computational technique to improve the thermophysical performance in the transportation of an electrically conducting Al2O3 - Ag/H2O hybrid nanofluid

    Science.gov (United States)

    Iqbal, Z.; Azhar, Ehtsham; Maraj, E. N.

    2017-12-01

    In this study, we analyzed the induced magnetic field effect on stagnation-point flow of a Al2O3-Ag/water hybrid nanofluid over a stretching sheet. Hybrid nanofluid, a new type of conventional fluid has been used for enhancement of heat transfer within boundary layer flow. It is notable here that only 1% to 5% contribution of nanoparticles enhance thermal conductivity of water. Nonlinear governing equations are simplified into boundary layer equations under boundary layer approximation assumption. A coupled system of nonlinear partial differential equation is transformed into a nonlinear system of ordinary differential equation by implementing suitable similarity conversions. Numerical analysis is performed by means of Keller box scheme. Effects of different non-dimensional governing parameters on velocity, induced magnetic field and temperature profiles, along with skinfriction coefficient and local Nusselt number, are discussed and presented through graphs and tables. Hybrid nanofluid is considered by keeping the 0.1% volumetric fraction of silver. From this study it is observed that the heat transfer rate of hybrid nanofluid (Al2O3-Ag/water) is higher than nanofluid (Ag/water). Novel results computed are useful in academic studies of hybrid nanofluids in engineering and industry.

  7. On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models

    Science.gov (United States)

    Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.

    2017-12-01

    Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.

  8. Hybrid dynamical systems observation and control

    CERN Document Server

    Defoort, Michael

    2015-01-01

    This book is a collection of contributions defining the state of current knowledge and new trends in hybrid systems – systems involving both continuous dynamics and discrete events – as described by the work of several well-known groups of researchers. Hybrid Dynamical Systems presents theoretical advances in such areas as diagnosability, observability and stabilization for various classes of system. Continuous and discrete state estimation and self-triggering control of nonlinear systems are advanced. The text employs various methods, among them, high-order sliding modes, Takagi–Sugeno representation and sampled-data switching to achieve its ends. The many applications of hybrid systems from power converters to computer science are not forgotten; studies of flexible-joint robotic arms and – as representative biological systems – the behaviour of the human heart and vasculature, demonstrate the wide-ranging practical significance of control in hybrid systems. The cross-disciplinary origins of study ...

  9. Layout design and energetic analysis of a complex diesel parallel hybrid electric vehicle

    International Nuclear Information System (INIS)

    Finesso, Roberto; Spessa, Ezio; Venditti, Mattia

    2014-01-01

    Highlights: • Layout design, energetic and cost analysis of complex parallel hybrid vehicles. • Development of global and real-time optimizers for control strategy identification. • Rule-based control strategies to minimize fuel consumption and NO x . • Energy share across each working mode for battery and thermal engine. - Abstract: The present paper is focused on the design, optimization and analysis of a complex parallel hybrid electric vehicle, equipped with two electric machines on both the front and rear axles, and on the evaluation of its potential to reduce fuel consumption and NO x emissions over several driving missions. The vehicle has been compared with two conventional parallel hybrid vehicles, equipped with a single electric machine on the front axle or on the rear axle, as well as with a conventional vehicle. All the vehicles have been equipped with compression ignition engines. The optimal layout of each vehicle was identified on the basis of the minimization of the overall powertrain costs during the whole vehicle life. These costs include the initial investment due to the production of the components as well as the operating costs related to fuel consumption and to battery depletion. Identification of the optimal powertrain control strategy, in terms of the management of the power flows of the engine and electric machines, and of gear selection, is necessary in order to be able to fully exploit the potential of the hybrid architecture. To this end, two global optimizers, one of a deterministic nature and another of a stochastic type, and two real-time optimizers have been developed, applied and compared. A new mathematical technique has been developed and applied to the vehicle simulation model in order to decrease the computational time of the optimizers. First, the vehicle model equations were written in order to allow a coarse time grid to be used, then, the control variables (i.e., power flow and gear number) were discretized, and the

  10. Cloud computing for radiologists

    OpenAIRE

    Amit T Kharat; Amjad Safvi; S S Thind; Amarjit Singh

    2012-01-01

    Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as...

  11. Model Predictive Control for Connected Hybrid Electric Vehicles

    Directory of Open Access Journals (Sweden)

    Kaijiang Yu

    2015-01-01

    Full Text Available This paper presents a new model predictive control system for connected hybrid electric vehicles to improve fuel economy. The new features of this study are as follows. First, the battery charge and discharge profile and the driving velocity profile are simultaneously optimized. One is energy management for HEV for Pbatt; the other is for the energy consumption minimizing problem of acc control of two vehicles. Second, a system for connected hybrid electric vehicles has been developed considering varying drag coefficients and the road gradients. Third, the fuel model of a typical hybrid electric vehicle is developed using the maps of the engine efficiency characteristics. Fourth, simulations and analysis (under different parameters, i.e., road conditions, vehicle state of charge, etc. are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results reveal improvements in fuel economy using the proposed control method.

  12. Hybrid Chernoff Tau-Leap

    KAUST Repository

    Moraes, Alvaro

    2016-01-06

    Markovian pure jump processes can model many phenomena, e.g. chemical reactions at molecular level, protein transcription and translation, spread of epidemics diseases in small populations and in wireless communication networks among many others. In this work we present a novel hybrid algorithm for simulating individual trajectories which adaptively switches between the SSA and the Chernoff tauleap methods. This allows us to: (a) control the global exit probability of any simulated trajectory, (b) obtain accurate and computable estimates for the expected value of any smooth observable of the process with minimal computational work.

  13. Hybrid Chernoff Tau-Leap

    KAUST Repository

    Moraes, Alvaro

    2015-01-07

    Markovian pure jump processes can model many phenomena, e.g. chemical reactions at molecular level, protein transcription and translation, spread of epidemics diseases in small populations and in wireless communication networks among many others. In this work we present a novel hybrid algorithm for simulating individual trajectories which adaptively switches between the SSA and the Chernoff tauleap methods. This allows us to: (a) control the global exit probability of any simulated trajectory, (b) obtain accurate and computable estimates for the expected value of any smooth observable of the process with minimal computational work.

  14. Hybrid Chernoff Tau-Leap

    KAUST Repository

    Moraes, Alvaro

    2014-01-06

    Markovian pure jump processes can model many phenomena, e.g. chemical reactions at molecular level, protein transcription and translation, spread of epidemics diseases in small populations and in wireless communication networks among many others. In this work we present a novel hybrid algorithm for simulating individual trajectories which adaptively switches between the SSA and the Chernoff tauleap methods. This allows us to: (a) control the global exit probability of any simulated trajectory, (b) obtain accurate and computable estimates for the expected value of any smooth observable of the process with minimal computational work.

  15. Fusion of neural computing and PLS techniques for load estimation

    Energy Technology Data Exchange (ETDEWEB)

    Lu, M.; Xue, H.; Cheng, X. [Northwestern Polytechnical Univ., Xi' an (China); Zhang, W. [Xi' an Inst. of Post and Telecommunication, Xi' an (China)

    2007-07-01

    A method to predict the electric load of a power system in real time was presented. The method is based on neurocomputing and partial least squares (PLS). Short-term load forecasts for power systems are generally determined by conventional statistical methods and Computational Intelligence (CI) techniques such as neural computing. However, statistical modeling methods often require the input of questionable distributional assumptions, and neural computing is weak, particularly in determining topology. In order to overcome the problems associated with conventional techniques, the authors developed a CI hybrid model based on neural computation and PLS techniques. The theoretical foundation for the designed CI hybrid model was presented along with its application in a power system. The hybrid model is suitable for nonlinear modeling and latent structure extracting. It can automatically determine the optimal topology to maximize the generalization. The CI hybrid model provides faster convergence and better prediction results compared to the abductive networks model because it incorporates a load conversion technique as well as new transfer functions. In order to demonstrate the effectiveness of the hybrid model, load forecasting was performed on a data set obtained from the Puget Sound Power and Light Company. Compared with the abductive networks model, the CI hybrid model reduced the forecast error by 32.37 per cent on workday, and by an average of 27.18 per cent on the weekend. It was concluded that the CI hybrid model has a more powerful predictive ability. 7 refs., 1 tab., 3 figs.

  16. Population genetic diversity and hybrid detection in captive zebras.

    Science.gov (United States)

    Ito, Hideyuki; Langenhorst, Tanya; Ogden, Rob; Inoue-Murayama, Miho

    2015-08-21

    Zebras are members of the horse family. There are three species of zebras: the plains zebra Equus quagga, the Grevy's zebra E. grevyi and the mountain zebra E. zebra. The Grevy's zebra and the mountain zebra are endangered, and hybridization between the Grevy's zebra and the plains zebra has been documented, leading to a requirement for conservation genetic management within and between the species. We characterized 28 microsatellite markers in Grevy's zebra and assessed cross-amplification in plains zebra and two of its subspecies, as well as mountain zebra. A range of standard indices were employed to examine population genetic diversity and hybrid populations between Grevy's and plains zebra were simulated to investigate subspecies and hybrid detection. Microsatellite marker polymorphism was conserved across species with sufficient variation to enable individual identification in all populations. Comparative diversity estimates indicated greater genetic variation in plains zebra and its subspecies than Grevy's zebra, despite potential ascertainment bias. Species and subspecies differentiation were clearly demonstrated and F1 and F2 hybrids were correctly identified. These findings provide insights into captive population genetic diversity in zebras and support the use of these markers for identifying hybrids, including the known hybrid issue in the endangered Grevy's zebra.

  17. Analysis of hybrid systems: An ounce of realism can save an infinity of states

    DEFF Research Database (Denmark)

    Fränzle, Martin

    1999-01-01

    Hybrid automata have been introduced in both control engineering and computer science as a formal model for the dynamics of hybrid discrete-continuous systems. In the case of so-called linear hybrid automata this formalization supports semi-decision procedures for state reachability, yet no decis...

  18. An efficient hybrid pseudospectral/finite-difference scheme for solving the TTI pure P-wave equation

    KAUST Repository

    Zhan, Ge

    2013-02-19

    The pure P-wave equation for modelling and migration in tilted transversely isotropic (TTI) media has attracted more and more attention in imaging seismic data with anisotropy. The desirable feature is that it is absolutely free of shear-wave artefacts and the consequent alleviation of numerical instabilities generally suffered by some systems of coupled equations. However, due to several forward-backward Fourier transforms in wavefield updating at each time step, the computational cost is significant, and thereby hampers its prevalence. We propose to use a hybrid pseudospectral (PS) and finite-difference (FD) scheme to solve the pure P-wave equation. In the hybrid solution, most of the cost-consuming wavenumber terms in the equation are replaced by inexpensive FD operators, which in turn accelerates the computation and reduces the computational cost. To demonstrate the benefit in cost saving of the new scheme, 2D and 3D reverse-time migration (RTM) examples using the hybrid solution to the pure P-wave equation are carried out, and respective runtimes are listed and compared. Numerical results show that the hybrid strategy demands less computation time and is faster than using the PS method alone. Furthermore, this new TTI RTM algorithm with the hybrid method is computationally less expensive than that with the FD solution to conventional TTI coupled equations. © 2013 Sinopec Geophysical Research Institute.

  19. An efficient hybrid pseudospectral/finite-difference scheme for solving the TTI pure P-wave equation

    International Nuclear Information System (INIS)

    Zhan, Ge; Pestana, Reynam C; Stoffa, Paul L

    2013-01-01

    The pure P-wave equation for modelling and migration in tilted transversely isotropic (TTI) media has attracted more and more attention in imaging seismic data with anisotropy. The desirable feature is that it is absolutely free of shear-wave artefacts and the consequent alleviation of numerical instabilities generally suffered by some systems of coupled equations. However, due to several forward–backward Fourier transforms in wavefield updating at each time step, the computational cost is significant, and thereby hampers its prevalence. We propose to use a hybrid pseudospectral (PS) and finite-difference (FD) scheme to solve the pure P-wave equation. In the hybrid solution, most of the cost-consuming wavenumber terms in the equation are replaced by inexpensive FD operators, which in turn accelerates the computation and reduces the computational cost. To demonstrate the benefit in cost saving of the new scheme, 2D and 3D reverse-time migration (RTM) examples using the hybrid solution to the pure P-wave equation are carried out, and respective runtimes are listed and compared. Numerical results show that the hybrid strategy demands less computation time and is faster than using the PS method alone. Furthermore, this new TTI RTM algorithm with the hybrid method is computationally less expensive than that with the FD solution to conventional TTI coupled equations. (paper)

  20. Spatial and Spectral Hybrid Image Classification for Rice Lodging Assessment through UAV Imagery

    Directory of Open Access Journals (Sweden)

    Ming-Der Yang

    2017-06-01

    Full Text Available Rice lodging identification relies on manual in situ assessment and often leads to a compensation dispute in agricultural disaster assessment. Therefore, this study proposes a comprehensive and efficient classification technique for agricultural lands that entails using unmanned aerial vehicle (UAV imagery. In addition to spectral information, digital surface model (DSM and texture information of the images was obtained through image-based modeling and texture analysis. Moreover, single feature probability (SFP values were computed to evaluate the contribution of spectral and spatial hybrid image information to classification accuracy. The SFP results revealed that texture information was beneficial for the classification of rice and water, DSM information was valuable for lodging and tree classification, and the combination of texture and DSM information was helpful in distinguishing between artificial surface and bare land. Furthermore, a decision tree classification model incorporating SFP values yielded optimal results, with an accuracy of 96.17% and a Kappa value of 0.941, compared with that of a maximum likelihood classification model (90.76%. The rice lodging ratio in paddies at the study site was successfully identified, with three paddies being eligible for disaster relief. The study demonstrated that the proposed spatial and spectral hybrid image classification technology is a promising tool for rice lodging assessment.

  1. Hybrid mesons with auxiliary fields

    International Nuclear Information System (INIS)

    Buisseret, F.; Mathieu, V.

    2006-01-01

    Hybrid mesons are exotic mesons in which the color field is not in the ground state. Their understanding deserves interest from a theoretical point of view, because it is intimately related to nonperturbative aspects of QCD. Moreover, it seems that some recently detected particles, such as the π 1 (1600) and the Y(4260), are serious hybrid candidates. In this work, we investigate the description of such exotic hadrons by applying the auxiliary fields technique (also known as the einbein field method) to the widely used spinless Salpeter Hamiltonian with appropriate linear confinement. Instead of the usual numerical resolution, this technique allows to find simplified analytical mass spectra and wave functions of the Hamiltonian, which still lead to reliable qualitative predictions. We analyse and compare two different descriptions of hybrid mesons, namely a two-body q system with an excited flux tube, or a three-body qg system. We also compute the masses of the 1 -+ hybrids. Our results are shown to be in satisfactory agreement with lattice QCD and other effective models. (orig.)

  2. Hybrid-secure MPC 

    DEFF Research Database (Denmark)

    Lucas, Christoph; Raub, Dominik; Maurer, Ueli

    2010-01-01

    of the adversary, without being aware of the actual adversarial setting. Thus, hybrid-secure MPC protocols allow for graceful degradation of security. We present a hybrid-secure MPC protocol that provides an optimal trade-off between IT robustness and computational privacy: For any robustness parameter ρ ... obtain one MPC protocol that is simultaneously IT secure with robustness for up to t ≤ ρ actively corrupted parties, IT secure with fairness (no robustness) for up to t ... in the universal composability (UC) framework (based on a network of secure channels, a broadcast channel, and a common reference string). It achieves the bound on the trade-off between robustness and privacy shown by Ishai et al. [CRYPTO'06] and Katz [STOC'07], the bound on fairness shown by Cleve [STOC'86...

  3. Improved Hybrid Opponent System for Professional Military Training

    Directory of Open Access Journals (Sweden)

    Michael Pelosi

    2017-10-01

    Full Text Available Described herein is a general-purpose software engineering architecture for autonomous, computer controlled opponent implementation in modern maneuver warfare simulation and training. The implementation has been developed, refined, and tested in the user crucible for several years. The approach represents a hybrid application of various well-known AI techniques, including domain modeling, agent modeling, and object-oriented programming. Inspired by computer chess approaches, the methodology combines this theoretical foundation with a hybrid and scalable portfolio of additional techniques. The result remains simple enough to be maintainable, comprehensible for the code writers as well as the end-users, and robust enough to handle a wide spectrum of possible mission scenarios and circumstances without modification.

  4. Computation and brain processes, with special reference to neuroendocrine systems.

    Science.gov (United States)

    Toni, Roberto; Spaletta, Giulia; Casa, Claudia Della; Ravera, Simone; Sandri, Giorgio

    2007-01-01

    The development of neural networks and brain automata has made neuroscientists aware that the performance limits of these brain-like devices lies, at least in part, in their computational power. The computational basis of a. standard cybernetic design, in fact, refers to that of a discrete and finite state machine or Turing Machine (TM). In contrast, it has been suggested that a number of human cerebral activites, from feedback controls up to mental processes, rely on a mixing of both finitary, digital-like and infinitary, continuous-like procedures. Therefore, the central nervous system (CNS) of man would exploit a form of computation going beyond that of a TM. This "non conventional" computation has been called hybrid computation. Some basic structures for hybrid brain computation are believed to be the brain computational maps, in which both Turing-like (digital) computation and continuous (analog) forms of calculus might occur. The cerebral cortex and brain stem appears primary candidate for this processing. However, also neuroendocrine structures like the hypothalamus are believed to exhibit hybrid computional processes, and might give rise to computational maps. Current theories on neural activity, including wiring and volume transmission, neuronal group selection and dynamic evolving models of brain automata, bring fuel to the existence of natural hybrid computation, stressing a cooperation between discrete and continuous forms of communication in the CNS. In addition, the recent advent of neuromorphic chips, like those to restore activity in damaged retina and visual cortex, suggests that assumption of a discrete-continuum polarity in designing biocompatible neural circuitries is crucial for their ensuing performance. In these bionic structures, in fact, a correspondence exists between the original anatomical architecture and synthetic wiring of the chip, resulting in a correspondence between natural and cybernetic neural activity. Thus, chip "form

  5. Comparative genomic hybridization detects novel amplifications in fibroadenomas of the breast

    DEFF Research Database (Denmark)

    Ojopi, E P; Rogatto, S R; Caldeira, J R

    2001-01-01

    Comparative genomic hybridization analysis was performed for identification of chromosomal imbalances in 23 samples of fibroadenomas of the breast. Chromosomal gains rather than losses were a feature of these lesions. Only two cases with a familial and/or previous history of breast lesions had gain...

  6. Many-Body Coulomb Gauge Exotic and Charmed Hybrids

    OpenAIRE

    Llanes-Estrada, Felipe J.; Cotanch, Stephen R.

    2000-01-01

    Utilizing a QCD Coulomb gauge Hamiltonian with linear confinement specified by lattice, we report a relativistic many-body calculation for the light exotic and charmed hybrid mesons. The Hamiltonian successfully describes both quark and gluon sectors, with vacuum and quasiparticle properties generated by a BCS transformation and more elaborate TDA and RPA diagonalizations for the meson ($q\\bar{q}$) and glueball ($gg$) masses. Hybrids entail a computationally intense relativistic three quasipa...

  7. Contribute to quantitative identification of casting defects based on computer analysis of X-ray images

    Directory of Open Access Journals (Sweden)

    Z. Ignaszak

    2007-12-01

    Full Text Available The forecast of structure and properties of casting is based on results of computer simulation of physical processes which are carried out during the casting processes. For the effective using of simulation system it is necessary to validate mathematica-physical models describing process of casting formation and the creation of local discontinues, witch determinate the casting properties.In the paper the proposition for quantitative validation of VP system using solidification casting defects by information sources of II group (methods of NDT was introduced. It was named the VP/RT validation (virtual prototyping/radiographic testing validation. Nowadays identification of casting defects noticeable on X-ray images bases on comparison of X-ray image of casting with relates to the ASTM. The results of this comparison are often not conclusive because based on operator’s subjective assessment. In the paper the system of quantitative identification of iron casting defects on X-ray images and classification this defects to ASTM class is presented. The methods of pattern recognition and machine learning were applied.

  8. AMITIS: A 3D GPU-Based Hybrid-PIC Model for Space and Plasma Physics

    Science.gov (United States)

    Fatemi, Shahab; Poppe, Andrew R.; Delory, Gregory T.; Farrell, William M.

    2017-05-01

    We have developed, for the first time, an advanced modeling infrastructure in space simulations (AMITIS) with an embedded three-dimensional self-consistent grid-based hybrid model of plasma (kinetic ions and fluid electrons) that runs entirely on graphics processing units (GPUs). The model uses NVIDIA GPUs and their associated parallel computing platform, CUDA, developed for general purpose processing on GPUs. The model uses a single CPU-GPU pair, where the CPU transfers data between the system and GPU memory, executes CUDA kernels, and writes simulation outputs on the disk. All computations, including moving particles, calculating macroscopic properties of particles on a grid, and solving hybrid model equations are processed on a single GPU. We explain various computing kernels within AMITIS and compare their performance with an already existing well-tested hybrid model of plasma that runs in parallel using multi-CPU platforms. We show that AMITIS runs ∼10 times faster than the parallel CPU-based hybrid model. We also introduce an implicit solver for computation of Faraday’s Equation, resulting in an explicit-implicit scheme for the hybrid model equation. We show that the proposed scheme is stable and accurate. We examine the AMITIS energy conservation and show that the energy is conserved with an error < 0.2% after 500,000 timesteps, even when a very low number of particles per cell is used.

  9. Iterative Multiuser Equalization for Subconnected Hybrid mmWave Massive MIMO Architecture

    Directory of Open Access Journals (Sweden)

    R. Magueta

    2017-01-01

    Full Text Available Millimeter waves and massive MIMO are a promising combination to achieve the multi-Gb/s required by future 5G wireless systems. However, fully digital architectures are not feasible due to hardware limitations, which means that there is a need to design signal processing techniques for hybrid analog-digital architectures. In this manuscript, we propose a hybrid iterative block multiuser equalizer for subconnected millimeter wave massive MIMO systems. The low complexity user-terminals employ pure-analog random precoders, each with a single RF chain. For the base station, a subconnected hybrid analog-digital equalizer is designed to remove multiuser interference. The hybrid equalizer is optimized using the average bit-error-rate as a metric. Due to the coupling between the RF chains in the optimization problem, the computation of the optimal solutions is too complex. To address this problem, we compute the analog part of the equalizer sequentially over the RF chains using a dictionary built from the array response vectors. The proposed subconnected hybrid iterative multiuser equalizer is compared with a recently proposed fully connected approach. The results show that the performance of the proposed scheme is close to the fully connected hybrid approach counterpart after just a few iterations.

  10. Optical hybrid quantum teleportation and its applications

    Science.gov (United States)

    Takeda, Shuntaro; Okada, Masanori; Furusawa, Akira

    2017-08-01

    Quantum teleportation, a transfer protocol of quantum states, is the essence of many sophisticated quantum information protocols. There have been two complementary approaches to optical quantum teleportation: discrete variables (DVs) and continuous variables (CVs). However, both approaches have pros and cons. Here we take a "hybrid" approach to overcome the current limitations: CV quantum teleportation of DVs. This approach enabled the first realization of deterministic quantum teleportation of photonic qubits without post-selection. We also applied the hybrid scheme to several experiments, including entanglement swapping between DVs and CVs, conditional CV teleportation of single photons, and CV teleportation of qutrits. We are now aiming at universal, scalable, and fault-tolerant quantum computing based on these hybrid technologies.

  11. Hybrid energy system evaluation in water supply system energy production: neural network approach

    Energy Technology Data Exchange (ETDEWEB)

    Goncalves, Fabio V.; Ramos, Helena M. [Civil Engineering Department, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001, Lisbon (Portugal); Reis, Luisa Fernanda R. [Universidade de Sao Paulo, EESC/USP, Departamento de Hidraulica e Saneamento., Avenida do Trabalhador Saocarlense, 400, Sao Carlos-SP (Brazil)

    2010-07-01

    Water supply systems are large consumers of energy and the use of hybrid systems for green energy production is this new proposal. This work presents a computational model based on neural networks to determine the best configuration of a hybrid system to generate energy in water supply systems. In this study the energy sources to make this hybrid system can be the national power grid, micro-hydro and wind turbines. The artificial neural network is composed of six layers, trained to use data generated by a model of hybrid configuration and an economic simulator - CES. The reason for the development of an advanced model of forecasting based on neural networks is to allow rapid simulation and proper interaction with hydraulic and power model simulator - HPS. The results show that this computational model is useful as advanced decision support system in the design of configurations of hybrid power systems applied to water supply systems, improving the solutions in the development of its global energy efficiency.

  12. Error compensation for hybrid-computer solution of linear differential equations

    Science.gov (United States)

    Kemp, N. H.

    1970-01-01

    Z-transform technique compensates for digital transport delay and digital-to-analog hold. Method determines best values for compensation constants in multi-step and Taylor series projections. Technique also provides hybrid-calculation error compared to continuous exact solution, plus system stability properties.

  13. Structured oligonucleotides for target indexing to allow single-vessel PCR amplification and solid support microarray hybridization.

    Science.gov (United States)

    Girard, Laurie D; Boissinot, Karel; Peytavi, Régis; Boissinot, Maurice; Bergeron, Michel G

    2015-02-07

    The combination of molecular diagnostic technologies is increasingly used to overcome limitations on sensitivity, specificity or multiplexing capabilities, and provide efficient lab-on-chip devices. Two such techniques, PCR amplification and microarray hybridization are used serially to take advantage of the high sensitivity and specificity of the former combined with high multiplexing capacities of the latter. These methods are usually performed in different buffers and reaction chambers. However, these elaborate methods have high complexity and cost related to reagent requirements, liquid storage and the number of reaction chambers to integrate into automated devices. Furthermore, microarray hybridizations have a sequence dependent efficiency not always predictable. In this work, we have developed the concept of a structured oligonucleotide probe which is activated by cleavage from polymerase exonuclease activity. This technology is called SCISSOHR for Structured Cleavage Induced Single-Stranded Oligonucleotide Hybridization Reaction. The SCISSOHR probes enable indexing the target sequence to a tag sequence. The SCISSOHR technology also allows the combination of nucleic acid amplification and microarray hybridization in a single vessel in presence of the PCR buffer only. The SCISSOHR technology uses an amplification probe that is irreversibly modified in presence of the target, releasing a single-stranded DNA tag for microarray hybridization. Each tag is composed of a 3-nucleotide sequence-dependent segment and a unique "target sequence-independent" 14-nucleotide segment allowing for optimal hybridization with minimal cross-hybridization. We evaluated the performance of five (5) PCR buffers to support microarray hybridization, compared to a conventional hybridization buffer. Finally, as a proof of concept, we developed a multiplexed assay for the amplification, detection, and identification of three (3) DNA targets. This new technology will facilitate the design

  14. Near-term hybrid vehicle program, phase 1

    Science.gov (United States)

    1979-01-01

    The preliminary design of a hybrid vehicle which fully meets or exceeds the requirements set forth in the Near Term Hybrid Vehicle Program is documented. Topics addressed include the general layout and styling, the power train specifications with discussion of each major component, vehicle weight and weight breakdown, vehicle performance, measures of energy consumption, and initial cost and ownership cost. Alternative design options considered and their relationship to the design adopted, computer simulation used, and maintenance and reliability considerations are also discussed.

  15. TAREAN: a computational tool for identification and characterization of satellite DNA from unassembled short reads.

    Science.gov (United States)

    Novák, Petr; Ávila Robledillo, Laura; Koblížková, Andrea; Vrbová, Iva; Neumann, Pavel; Macas, Jirí

    2017-07-07

    Satellite DNA is one of the major classes of repetitive DNA, characterized by tandemly arranged repeat copies that form contiguous arrays up to megabases in length. This type of genomic organization makes satellite DNA difficult to assemble, which hampers characterization of satellite sequences by computational analysis of genomic contigs. Here, we present tandem repeat analyzer (TAREAN), a novel computational pipeline that circumvents this problem by detecting satellite repeats directly from unassembled short reads. The pipeline first employs graph-based sequence clustering to identify groups of reads that represent repetitive elements. Putative satellite repeats are subsequently detected by the presence of circular structures in their cluster graphs. Consensus sequences of repeat monomers are then reconstructed from the most frequent k-mers obtained by decomposing read sequences from corresponding clusters. The pipeline performance was successfully validated by analyzing low-pass genome sequencing data from five plant species where satellite DNA was previously experimentally characterized. Moreover, novel satellite repeats were predicted for the genome of Vicia faba and three of these repeats were verified by detecting their sequences on metaphase chromosomes using fluorescence in situ hybridization. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  16. Hybrid tracers for sentinel node biopsy

    International Nuclear Information System (INIS)

    Van Den Berg, N. S.; Kleinjan, G. I.; Valdés-Olmos, R. A.; Buckle, T.; Van Leeuwen, F. I.; Klop, W. M.; Horenblas, S.; Van Der Poel, H. G.

    2014-01-01

    Conventional sentinel node (SN) mapping is performed by injection of a radiocolloid followed by lymphoscintigraphy to identify the number and location of the primary tumor draining lymph node(s), the so-called SN(s). Over the last decade research has focused on the introduction of new imaging agents that can further aid (surgical) SN identification. Different tracers for SN mapping, with varying sizes and isotopes have been reported, most of which have proven their value in a clinical setting. A major challenge lies in transferring this diagnostic information obtained at the nuclear medicine department to the operating theatre thereby providing the surgeon with (image) guidance. Conventionally, an intraoperative injection of vital blue dye or a fluorescence dye is given to allow intraoperative optical SN identification. However, for some indications, the radiotracer-based approach remains crucial. More recently, hybrid tracers, that contain both a radioactive and fluorescent label, were introduced to allow for direct integration of pre- and intraoperative guidance technologies. Their potential is especially high when they are used in combination with new surgical imaging modalities and navigation tools. Next to a description of the known tracers for SN mapping, this review discusses the application of hybrid tracers during SN biopsy and how the introduction of these new techniques can further aid in translation of nuclear medicine information into the operating theatre.

  17. Cloud Computing (1/2)

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    Cloud computing, the recent years buzzword for distributed computing, continues to attract and keep the interest of both the computing and business world. These lectures aim at explaining "What is Cloud Computing?" identifying and analyzing it's characteristics, models, and applications. The lectures will explore different "Cloud definitions" given by different authors and use them to introduce the particular concepts. The main cloud models (SaaS, PaaS, IaaS), cloud types (public, private, hybrid), cloud standards and security concerns will be presented. The borders between Cloud Computing and Grid Computing, Server Virtualization, Utility Computing will be discussed and analyzed.

  18. Cloud Computing (2/2)

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    Cloud computing, the recent years buzzword for distributed computing, continues to attract and keep the interest of both the computing and business world. These lectures aim at explaining "What is Cloud Computing?" identifying and analyzing it's characteristics, models, and applications. The lectures will explore different "Cloud definitions" given by different authors and use them to introduce the particular concepts. The main cloud models (SaaS, PaaS, IaaS), cloud types (public, private, hybrid), cloud standards and security concerns will be presented. The borders between Cloud Computing and Grid Computing, Server Virtualization, Utility Computing will be discussed and analyzed.

  19. Identification of novel CYP2D7-2D6 hybrids: non-functional and functional variants

    Directory of Open Access Journals (Sweden)

    Andrea Gaedigk

    2010-10-01

    Full Text Available Polymorphic expression of CYP2D6 contributes to the wide range of activity observed for this clinically important drug metabolizing enzyme. In this report we describe novel CYP2D7/2D6 hybrid genes encoding non-functional and functional CYP2D6 protein and a CYP2D7 variant that mimics a CYP2D7/2D6 hybrid gene. Five kb long PCR products encompassing the novel genes were entirely sequenced. A quantitative assay probing in different gene regions was employed to determine CYP2D6 and 2D7 copy number variations and the relative position of the hybrid genes within the locus was assessed by long-range PCR. In addition to the previously known CYP2D6*13 and *66 hybrids, we describe three novel non-functional CYP2D7-2D6 hybrids with gene switching in exon 2 (CYP2D6*79, intron 2 (CYP2D6*80 and intron 5 (CYP2D6*67. A CYP2D7-specific T-ins in exon 1 causes a detrimental frame shift. One subject revealed a CYP2D7 conversion in the 5’-flanking region of a CYP2D6*35 allele, was otherwise unaffected (designated CYP2D6*35B. Finally, three DNAs revealed a CYP2D7 gene with a CYP2D6-like region downstream of exon 9 (designated CYP2D7[REP6]. Quantitative copy number determination, sequence analyses and long-range PCR mapping were in agreement and excluded the presence of additional gene units. Undetected hybrid genes may cause over-estimation of CYP2D6 activity (CYP2D6*1/*1 vs *1/hybrid, etc, but may also cause results that may interfere with the genotype determination. Detection of hybrid events, ‘single’ and tandem, will contribute to more accurate phenotype prediction from genotype data.

  20. Hybrid brain-computer interfaces and hybrid neuroprostheses for restoration of upper limb functions in individuals with high-level spinal cord injury.

    Science.gov (United States)

    Rohm, Martin; Schneiders, Matthias; Müller, Constantin; Kreilinger, Alex; Kaiser, Vera; Müller-Putz, Gernot R; Rupp, Rüdiger

    2013-10-01

    The bilateral loss of the grasp function associated with a lesion of the cervical spinal cord severely limits the affected individuals' ability to live independently and return to gainful employment after sustaining a spinal cord injury (SCI). Any improvement in lost or limited grasp function is highly desirable. With current neuroprostheses, relevant improvements can be achieved in end users with preserved shoulder and elbow, but missing hand function. The aim of this single case study is to show that (1) with the support of hybrid neuroprostheses combining functional electrical stimulation (FES) with orthoses, restoration of hand, finger and elbow function is possible in users with high-level SCI and (2) shared control principles can be effectively used to allow for a brain-computer interface (BCI) control, even if only moderate BCI performance is achieved after extensive training. The individual in this study is a right-handed 41-year-old man who sustained a traumatic SCI in 2009 and has a complete motor and sensory lesion at the level of C4. He is unable to generate functionally relevant movements of the elbow, hand and fingers on either side. He underwent extensive FES training (30-45min, 2-3 times per week for 6 months) and motor imagery (MI) BCI training (415 runs in 43 sessions over 12 months). To meet individual needs, the system was designed in a modular fashion including an intelligent control approach encompassing two input modalities, namely an MI-BCI and shoulder movements. After one year of training, the end user's MI-BCI performance ranged from 50% to 93% (average: 70.5%). The performance of the hybrid system was evaluated with different functional assessments. The user was able to transfer objects of the grasp-and-release-test and he succeeded in eating a pretzel stick, signing a document and eating an ice cream cone, which he was unable to do without the system. This proof-of-concept study has demonstrated that with the support of hybrid FES

  1. Discrimination of Species and Hybrid Detection in Myriophyllum Spp.: an Introduction to Biodiversity Conservation and Invasion Avoidance

    Directory of Open Access Journals (Sweden)

    R Ghahramanzadeh

    2014-03-01

    Full Text Available Minimizing economical loss through introduction of invasive alien species (IAS in local ecosystem is one of the most important issues in biosecurity. The hybridization potential between non-indigenous and native species has raised concerns due mainly to introgression, which can cause extirpation of native species through gene contamination. In the present study, 71 samples belonging to 12 species from Myriophyllum genus were assessed in Plant Breeding group of Wageningen University. Internal transcribed spacer (ITS was used for identification of invasive species from related native and possible hybrid plants. The result showed that based on universal application, high sequence divergence and species discrimination, ITS is a powerful sequence for the identification of invasive species from related non-invasive foreign and native species. In contrast to morphological data, ITS grouped suspected hybrid plants in to M. heterophyllum and demonstrated that they have not resulted from hybridization. These observations suggest that multiple introduction and genetic recombination among different introduced genotypes or genetic pools could be reasons of non-flowering in suspected hybrid plants. Results showed that molecular markers enable to distinguish invasive plant species from their most closely related congeners. This could be helpful with enforcing a ban on important of such invasive which can help to plant ecosystem and biodiversity stability.

  2. Extensive tests of Hybrid Photon Detectors (HPD) used to collect Cherenkov light

    International Nuclear Information System (INIS)

    Borsato, E.; Buccheri, A.; DalCorso, F.; Ferroni, F.; Iacovella, F.; Mazzoni, M.A.; Morandin, M.; Morganti, S.; Piredda, G.; Posocco, M.; Santacesaria, R.; Stroili, R.; Torassa, E.; Voci, C.

    1997-01-01

    The principle of operation of a newly developed proximity focused Hybrid Photon Detector is described. The HPD characteristics, performance and calibration are reported. Results from beam tests of aerogel threshold counters read out by HPD and the particle identification performance are presented. (orig.)

  3. Energy performance analysis for a photovoltaic, diesel, battery hybrid power supply system

    CSIR Research Space (South Africa)

    Tazvinga, Henerica

    2010-03-01

    Full Text Available This paper looks at an energy performance analysis for a photovoltaic, diesel, and battery hybrid power supply system. The procedure starts by the identification of the hourly load requirements for a typical target consumer and the concept of load...

  4. StackInsights: Cognitive Learning for Hybrid Cloud Readiness

    OpenAIRE

    Qiao, Mu; Bathen, Luis; Génot, Simon-Pierre; Lee, Sunhwan; Routray, Ramani

    2017-01-01

    Hybrid cloud is an integrated cloud computing environment utilizing a mix of public cloud, private cloud, and on-premise traditional IT infrastructures. Workload awareness, defined as a detailed full range understanding of each individual workload, is essential in implementing the hybrid cloud. While it is critical to perform an accurate analysis to determine which workloads are appropriate for on-premise deployment versus which workloads can be migrated to a cloud off-premise, the assessment...

  5. A Hybrid Scheme for Fine-Grained Search and Access Authorization in Fog Computing Environment

    Science.gov (United States)

    Xiao, Min; Zhou, Jing; Liu, Xuejiao; Jiang, Mingda

    2017-01-01

    In the fog computing environment, the encrypted sensitive data may be transferred to multiple fog nodes on the edge of a network for low latency; thus, fog nodes need to implement a search over encrypted data as a cloud server. Since the fog nodes tend to provide service for IoT applications often running on resource-constrained end devices, it is necessary to design lightweight solutions. At present, there is little research on this issue. In this paper, we propose a fine-grained owner-forced data search and access authorization scheme spanning user-fog-cloud for resource constrained end users. Compared to existing schemes only supporting either index encryption with search ability or data encryption with fine-grained access control ability, the proposed hybrid scheme supports both abilities simultaneously, and index ciphertext and data ciphertext are constructed based on a single ciphertext-policy attribute based encryption (CP-ABE) primitive and share the same key pair, thus the data access efficiency is significantly improved and the cost of key management is greatly reduced. Moreover, in the proposed scheme, the resource constrained end devices are allowed to rapidly assemble ciphertexts online and securely outsource most of decryption task to fog nodes, and mediated encryption mechanism is also adopted to achieve instantaneous user revocation instead of re-encrypting ciphertexts with many copies in many fog nodes. The security and the performance analysis show that our scheme is suitable for a fog computing environment. PMID:28629131

  6. A Hybrid Scheme for Fine-Grained Search and Access Authorization in Fog Computing Environment.

    Science.gov (United States)

    Xiao, Min; Zhou, Jing; Liu, Xuejiao; Jiang, Mingda

    2017-06-17

    In the fog computing environment, the encrypted sensitive data may be transferred to multiple fog nodes on the edge of a network for low latency; thus, fog nodes need to implement a search over encrypted data as a cloud server. Since the fog nodes tend to provide service for IoT applications often running on resource-constrained end devices, it is necessary to design lightweight solutions. At present, there is little research on this issue. In this paper, we propose a fine-grained owner-forced data search and access authorization scheme spanning user-fog-cloud for resource constrained end users. Compared to existing schemes only supporting either index encryption with search ability or data encryption with fine-grained access control ability, the proposed hybrid scheme supports both abilities simultaneously, and index ciphertext and data ciphertext are constructed based on a single ciphertext-policy attribute based encryption (CP-ABE) primitive and share the same key pair, thus the data access efficiency is significantly improved and the cost of key management is greatly reduced. Moreover, in the proposed scheme, the resource constrained end devices are allowed to rapidly assemble ciphertexts online and securely outsource most of decryption task to fog nodes, and mediated encryption mechanism is also adopted to achieve instantaneous user revocation instead of re-encrypting ciphertexts with many copies in many fog nodes. The security and the performance analysis show that our scheme is suitable for a fog computing environment.

  7. Somatic hybrid plants between Lycopersicon esculentum and Solanum lycopersicoides.

    Science.gov (United States)

    Handley, L W; Nickels, R L; Cameron, M W; Moore, P P; Sink, K C

    1986-02-01

    Leaf mesophyll protoplasts of Lycopersicon esculentum (2n=2x=24) were fused with suspension culture-derived protoplasts of Solanum lycopersicoides (2n=2x=24) and intergeneric somatic hybrid plants were regenerated following selective conditions. A two phase selection system was based on the inability of S. lycopersicoides protoplasts to divide in culture in modified medium 8E and the partial inhibition of L. esculentum protoplasts by the PEG/DMSO fusion solution. At the p-calli stage, putative hybrids were visually selected based on their hybrid vigor and lime-green coloration in contrast to slower growing parental calli characterized by a watery, whitish-brown coloration. Early identification of the eight hybrid plants studied was facilitated by isozyme analysis of leaf tissue samples taken from plants in vitro at the rooting stage. Regenerated plants growing in planting medium were further verified for hybridity by 5 isozymes marking 7 loci on 5 chromosomes in tomato. These included Skdh-1 mapped to chromosome 1 of tomato, Pgm-2 on chromosome 4, Got-2 and Got-3 on chromosome 7, Got-4 on chromosome 8, and Pgi-1 and Pgdh-2 both on chromosome 12. Fraction I protein small subunits further confirmed the hybrid nature of the plants with bands of both parents expressed in all hybrids. The parental chloroplasts could not be differentiated by the isoelectric points of the large subunit. Seven of the eight somatic hybrids had a chromosome number ranging from the expected 2n=4x=48 to 2n=68. Mixoploid root-tip cells containing 48, 53, 54 or 55 chromosomes for two of the hybrids were also observed.

  8. Computer system for identification of tool wear model in hot forging

    Directory of Open Access Journals (Sweden)

    Wilkus Marek

    2016-01-01

    Full Text Available The aim of the research was to create a methodology that will enable effective and reliable prediction of the tool wear. The idea of the hybrid model, which accounts for various mechanisms of tool material deterioration, is proposed in the paper. The mechanisms, which were considered, include abrasive wear, adhesive wear, thermal fatigue, mechanical fatigue, oxidation and plastic deformation. Individual models of various complexity were used for separate phenomena and strategy of combination of these models in one hybrid system was developed to account for the synergy of various mechanisms. The complex hybrid model was built on the basis of these individual models for various wear mechanisms. The individual models expanded from phenomenological ones for abrasive wear to multi-scale methods for modelling micro cracks initiation and propagation utilizing virtual representations of granular microstructures. The latter have been intensively developed recently and they form potentially a powerful tool that allows modelling of thermal and mechanical fatigue, accounting explicitly for the tool material microstructure.

  9. A hybrid solution using computational prediction and measured data to accurately determine process corrections with reduced overlay sampling

    Science.gov (United States)

    Noyes, Ben F.; Mokaberi, Babak; Mandoy, Ram; Pate, Alex; Huijgen, Ralph; McBurney, Mike; Chen, Owen

    2017-03-01

    Reducing overlay error via an accurate APC feedback system is one of the main challenges in high volume production of the current and future nodes in the semiconductor industry. The overlay feedback system directly affects the number of dies meeting overlay specification and the number of layers requiring dedicated exposure tools through the fabrication flow. Increasing the former number and reducing the latter number is beneficial for the overall efficiency and yield of the fabrication process. An overlay feedback system requires accurate determination of the overlay error, or fingerprint, on exposed wafers in order to determine corrections to be automatically and dynamically applied to the exposure of future wafers. Since current and future nodes require correction per exposure (CPE), the resolution of the overlay fingerprint must be high enough to accommodate CPE in the overlay feedback system, or overlay control module (OCM). Determining a high resolution fingerprint from measured data requires extremely dense overlay sampling that takes a significant amount of measurement time. For static corrections this is acceptable, but in an automated dynamic correction system this method creates extreme bottlenecks for the throughput of said system as new lots have to wait until the previous lot is measured. One solution is using a less dense overlay sampling scheme and employing computationally up-sampled data to a dense fingerprint. That method uses a global fingerprint model over the entire wafer; measured localized overlay errors are therefore not always represented in its up-sampled output. This paper will discuss a hybrid system shown in Fig. 1 that combines a computationally up-sampled fingerprint with the measured data to more accurately capture the actual fingerprint, including local overlay errors. Such a hybrid system is shown to result in reduced modelled residuals while determining the fingerprint, and better on-product overlay performance.

  10. Abstraction/Representation Theory for heterotic physical computing.

    Science.gov (United States)

    Horsman, D C

    2015-07-28

    We give a rigorous framework for the interaction of physical computing devices with abstract computation. Device and program are mediated by the non-logical representation relation; we give the conditions under which representation and device theory give rise to commuting diagrams between logical and physical domains, and the conditions for computation to occur. We give the interface of this new framework with currently existing formal methods, showing in particular its close relationship to refinement theory, and the implications for questions of meaning and reference in theoretical computer science. The case of hybrid computing is considered in detail, addressing in particular the example of an Internet-mediated social machine, and the abstraction/representation framework used to provide a formal distinction between heterotic and hybrid computing. This forms the basis for future use of the framework in formal treatments of non-standard physical computers. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  11. BIOMETRIC ANALYSIS OF THE ARTIFICIAL HYBRIDIZATION BETWEEN Pangasius djambal BLEEKER, 1846 AND Pangasianodon hypophthalmus SAUVAGE, 1878

    Directory of Open Access Journals (Sweden)

    Rudhy Gustiano

    2016-10-01

    Full Text Available It is really important, since the possible use of these pangasiid hybrids in aquaculture faces the problem of potential impact on wild population. Therefore, it is urgently needed to provide quick identification tools in the field. This study investigated morphological characters of Pangasius djambal and Pangasianodon hypophthalmus and their hybrids. A detailed morphological analysis using 32 morphometric measurements and five meristic counts was done on the hybridization of P. djambal and P. hypophthalmus. Morphometric analysis and meristic counts showed that the reciprocal hybrids have intermediate characters except for gill raker number in which lower than that of parental species. In general, the hybrids have tendency to be like P. hypophthalmus rather than P. djambal. The only typical character of P. djambal appeared on hybrids is teeth shape, both vomerine and palatine. It is clearly defined that the true hybrids have seven pelvic fin rays.

  12. Hybrid and Blended Learning: Modifying Pedagogy across Path, Pace, Time, and Place

    Science.gov (United States)

    O'Byrne, W. Ian; Pytash, Kristine E.

    2015-01-01

    Hybrid or blended learning is defined as a pedagogical approach that includes a combination of face-to-face instruction with computer-mediated instruction. The terms "blended learning", "hybrid learning", and "mixed-mode learning" are used interchangeably in current research; however, in the United States,…

  13. Hybrid Computational Simulation and Study of Terahertz Pulsed Photoconductive Antennas

    Science.gov (United States)

    Emadi, R.; Barani, N.; Safian, R.; Nezhad, A. Zeidaabadi

    2016-11-01

    A photoconductive antenna (PCA) has been numerically investigated in the terahertz (THz) frequency band based on a hybrid simulation method. This hybrid method utilizes an optoelectronic solver, Silvaco TCAD, and a full-wave electromagnetic solver, CST. The optoelectronic solver is used to find the accurate THz photocurrent by considering realistic material parameters. Performance of photoconductive antennas and temporal behavior of the excited photocurrent for various active region geometries such as bare-gap electrode, interdigitated electrodes, and tip-to-tip rectangular electrodes are investigated. Moreover, investigations have been done on the center of the laser illumination on the substrate, substrate carrier lifetime, and diffusion photocurrent associated with the carriers temperature, to achieve efficient and accurate photocurrent. Finally, using the full-wave electromagnetic solver and the calculated photocurrent obtained from the optoelectronic solver, electromagnetic radiation of the antenna and its associated detected THz signal are calculated and compared with a measurement reference for verification.

  14. Progress and challenges in bioinformatics approaches for enhancer identification

    KAUST Repository

    Kleftogiannis, Dimitrios A.

    2017-02-03

    Enhancers are cis-acting DNA elements that play critical roles in distal regulation of gene expression. Identifying enhancers is an important step for understanding distinct gene expression programs that may reflect normal and pathogenic cellular conditions. Experimental identification of enhancers is constrained by the set of conditions used in the experiment. This requires multiple experiments to identify enhancers, as they can be active under specific cellular conditions but not in different cell types/tissues or cellular states. This has opened prospects for computational prediction methods that can be used for high-throughput identification of putative enhancers to complement experimental approaches. Potential functions and properties of predicted enhancers have been catalogued and summarized in several enhancer-oriented databases. Because the current methods for the computational prediction of enhancers produce significantly different enhancer predictions, it will be beneficial for the research community to have an overview of the strategies and solutions developed in this field. In this review, we focus on the identification and analysis of enhancers by bioinformatics approaches. First, we describe a general framework for computational identification of enhancers, present relevant data types and discuss possible computational solutions. Next, we cover over 30 existing computational enhancer identification methods that were developed since 2000. Our review highlights advantages, limitations and potentials, while suggesting pragmatic guidelines for development of more efficient computational enhancer prediction methods. Finally, we discuss challenges and open problems of this topic, which require further consideration.

  15. Progress and challenges in bioinformatics approaches for enhancer identification

    KAUST Repository

    Kleftogiannis, Dimitrios A.; Kalnis, Panos; Bajic, Vladimir B.

    2017-01-01

    Enhancers are cis-acting DNA elements that play critical roles in distal regulation of gene expression. Identifying enhancers is an important step for understanding distinct gene expression programs that may reflect normal and pathogenic cellular conditions. Experimental identification of enhancers is constrained by the set of conditions used in the experiment. This requires multiple experiments to identify enhancers, as they can be active under specific cellular conditions but not in different cell types/tissues or cellular states. This has opened prospects for computational prediction methods that can be used for high-throughput identification of putative enhancers to complement experimental approaches. Potential functions and properties of predicted enhancers have been catalogued and summarized in several enhancer-oriented databases. Because the current methods for the computational prediction of enhancers produce significantly different enhancer predictions, it will be beneficial for the research community to have an overview of the strategies and solutions developed in this field. In this review, we focus on the identification and analysis of enhancers by bioinformatics approaches. First, we describe a general framework for computational identification of enhancers, present relevant data types and discuss possible computational solutions. Next, we cover over 30 existing computational enhancer identification methods that were developed since 2000. Our review highlights advantages, limitations and potentials, while suggesting pragmatic guidelines for development of more efficient computational enhancer prediction methods. Finally, we discuss challenges and open problems of this topic, which require further consideration.

  16. A Novel Design and Optimization Software for Autonomous PV/Wind/Battery Hybrid Power Systems

    Directory of Open Access Journals (Sweden)

    Ali M. Eltamaly

    2014-01-01

    Full Text Available This paper introduces a design and optimization computer simulation program for autonomous hybrid PV/wind/battery energy system. The main function of the new proposed computer program is to determine the optimum size of each component of the hybrid energy system for the lowest price of kWh generated and the best loss of load probability at highest reliability. This computer program uses the hourly wind speed, hourly radiation, and hourly load power with several numbers of wind turbine (WT and PV module types. The proposed computer program changes the penetration ratio of wind/PV with certain increments and calculates the required size of all components and the optimum battery size to get the predefined lowest acceptable probability. This computer program has been designed in flexible fashion that is not available in market available software like HOMER and RETScreen. Actual data for Saudi sites have been used with this computer program. The data obtained have been compared with these market available software. The comparison shows the superiority of this computer program in the optimal design of the autonomous PV/wind/battery hybrid system. The proposed computer program performed the optimal design steps in very short time and with accurate results. Many valuable results can be extracted from this computer program that can help researchers and decision makers.

  17. Hybrid Logic and its Proof-Theory

    CERN Document Server

    Brauner, Torben

    2011-01-01

    This is the first book-length treatment of hybrid logic and its proof-theory. Hybrid logic is an extension of ordinary modal logic which allows explicit reference to individual points in a model (where the points represent times, possible worlds, states in a computer, or something else). This is useful for many applications, for example when reasoning about time one often wants to formulate a series of statements about what happens at specific times. There is little consensus about proof-theory for ordinary modal logic. Many modal-logical proof systems lack important properties and the relatio

  18. An accelerated hybrid TLM-IE method for the investigation of shielding effectiveness

    Directory of Open Access Journals (Sweden)

    N. Fichtner

    2010-09-01

    Full Text Available A hybrid numerical technique combining time-domain integral equations (TD-IE with the transmission line matrix (TLM method is presented for the efficient modeling of transient wave phenomena. This hybrid method allows the full-wave modeling of circuits in the time-domain as well as the electromagnetic coupling of remote TLM subdomains using integral equations (IE. By using the integral equations the space between the TLM subdomains is not discretized and consequently doesn't contribute to the computational effort. The cost for the evaluation of the time-domain integral equations (TD-IE is further reduced using a suitable plane-wave representation of the source terms. The hybrid TD-IE/TLM method is applied in the computation of the shielding effectiveness (SE of metallic enclosures.

  19. Development of seismic tomography software for hybrid supercomputers

    Science.gov (United States)

    Nikitin, Alexandr; Serdyukov, Alexandr; Duchkov, Anton

    2015-04-01

    Seismic tomography is a technique used for computing velocity model of geologic structure from first arrival travel times of seismic waves. The technique is used in processing of regional and global seismic data, in seismic exploration for prospecting and exploration of mineral and hydrocarbon deposits, and in seismic engineering for monitoring the condition of engineering structures and the surrounding host medium. As a consequence of development of seismic monitoring systems and increasing volume of seismic data, there is a growing need for new, more effective computational algorithms for use in seismic tomography applications with improved performance, accuracy and resolution. To achieve this goal, it is necessary to use modern high performance computing systems, such as supercomputers with hybrid architecture that use not only CPUs, but also accelerators and co-processors for computation. The goal of this research is the development of parallel seismic tomography algorithms and software package for such systems, to be used in processing of large volumes of seismic data (hundreds of gigabytes and more). These algorithms and software package will be optimized for the most common computing devices used in modern hybrid supercomputers, such as Intel Xeon CPUs, NVIDIA Tesla accelerators and Intel Xeon Phi co-processors. In this work, the following general scheme of seismic tomography is utilized. Using the eikonal equation solver, arrival times of seismic waves are computed based on assumed velocity model of geologic structure being analyzed. In order to solve the linearized inverse problem, tomographic matrix is computed that connects model adjustments with travel time residuals, and the resulting system of linear equations is regularized and solved to adjust the model. The effectiveness of parallel implementations of existing algorithms on target architectures is considered. During the first stage of this work, algorithms were developed for execution on

  20. Specification of real-time automation systems with HybridUML; Spezifikation von Echtzeit-Automatisierungssystemen mit HybridUML

    Energy Technology Data Exchange (ETDEWEB)

    Berkenkoetter, K.; Bisanz, S.; Hannemann, U.; Peleska, J. [Univ. Bremen (Germany)

    2004-07-01

    Complex automation systems require specification formalisms supporting the description of real-time requirements with respect to both discrete and time-continuous observables. For this purpose, the authors have designed the HybridUML specification language. Discrete events, communication, and variable assignments are specified by state machines, timers, and invariant conditions. The time-continuous aspects of system behaviour are described by associating differential equations or time-dependent algebraic conditions with system states. The complexity of large systems is controlled by decomposing the specification into parallel components and hierarchical state machines. Instead of inventing a new language syntax, HybridUML is represented as a profile of the Unified Modeling Language UML 2.0. This allows to re-use the syntactic framework of well-accepted graphical UML constructs and development support provided by various UML case tools. The profile is associated with a precise language semantics linking unambiguous meaning to all HybridUML specifications. As a consequence, HybridUML specifications can be compiled into executable code which is suitable for execution in hard realtime on multi-processor computers. This serves both for the development of automation systems and for specification-based testing in real-time. This paper contains an introduction to HybridUML which is illustrated by an example from the field of automated train control. (orig.)

  1. Multilevel Hybrid Chernoff Tau-Leap

    KAUST Repository

    Moraes, Alvaro

    2016-01-06

    Markovian pure jump processes can model many phenomena, e.g. chemical reactions at molecular level, protein transcription and translation, spread of epidemics diseases in small populations and in wireless communication networks, among many others. In this work [6] we present a novel multilevel algorithm for the Chernoff-based hybrid tauleap algorithm. This variance reduction technique allows us to: (a) control the global exit probability of any simulated trajectory, (b) obtain accurate and computable estimates for the expected value of any smooth observable of the process with minimal computational work.

  2. Multilevel Hybrid Chernoff Tau-Leap

    KAUST Repository

    Moraes, Alvaro

    2015-01-07

    Markovian pure jump processes can model many phenomena, e.g. chemical reactions at molecular level, protein transcription and translation, spread of epidemics diseases in small populations and in wireless communication networks, among many others. In this work [6] we present a novel multilevel algorithm for the Chernoff-based hybrid tauleap algorithm. This variance reduction technique allows us to: (a) control the global exit probability of any simulated trajectory, (b) obtain accurate and computable estimates for the expected value of any smooth observable of the process with minimal computational work.

  3. Multilevel Hybrid Chernoff Tau-Leap

    KAUST Repository

    Moraes, Alvaro

    2014-01-06

    Markovian pure jump processes can model many phenomena, e.g. chemical reactions at molecular level, protein transcription and translation, spread of epidemics diseases in small populations and in wireless communication networks, among many others. In this work [6] we present a novel multilevel algorithm for the Chernoff-based hybrid tauleap algorithm. This variance reduction technique allows us to: (a) control the global exit probability of any simulated trajectory, (b) obtain accurate and computable estimates for the expected value of any smooth observable of the process with minimal computational work.

  4. Hybrid incompatibilities in the parasitic wasp genus Nasonia: negative effects of hemizygosity and the identification of transmission ratio distortion loci.

    Science.gov (United States)

    Koevoets, T; Niehuis, O; van de Zande, L; Beukeboom, L W

    2012-03-01

    The occurrence of hybrid incompatibilities forms an important stage during the evolution of reproductive isolation. In early stages of speciation, males and females often respond differently to hybridization. Haldane's rule states that the heterogametic sex suffers more from hybridization than the homogametic sex. Although haplodiploid reproduction (haploid males, diploid females) does not involve sex chromosomes, sex-specific incompatibilities are predicted to be prevalent in haplodiploid species. Here, we evaluate the effect of sex/ploidy level on hybrid incompatibilities and locate genomic regions that cause increased mortality rates in hybrid males of the haplodiploid wasps Nasonia vitripennis and Nasonia longicornis. Our data show that diploid F(1) hybrid females suffer less from hybridization than haploid F(2) hybrid males. The latter not only suffer from an increased mortality rate, but also from behavioural and spermatogenic sterility. Genetic mapping in recombinant F(2) male hybrids revealed that the observed hybrid mortality is most likely due to a disruption of cytonuclear interactions. As these sex-specific hybrid incompatibilities follow predictions based on Haldane's rule, our data accentuate the need to broaden the view of Haldane's rule to include species with haplodiploid sex determination, consistent with Haldane's original definition.

  5. Stochastic hybrid systems with renewal transitions

    NARCIS (Netherlands)

    Guerreiro Tome Antunes, D.J.; Hespanha, J.P.; Silvestre, C.J.

    2010-01-01

    We consider Stochastic Hybrid Systems (SHSs) for which the lengths of times that the system stays in each mode are independent random variables with given distributions. We propose an analysis framework based on a set of Volterra renewal-type equations, which allows us to compute any statistical

  6. Evaluation of External Memory Access Performance on a High-End FPGA Hybrid Computer

    Directory of Open Access Journals (Sweden)

    Konstantinos Kalaitzis

    2016-10-01

    Full Text Available The motivation of this research was to evaluate the main memory performance of a hybrid super computer such as the Convey HC-x, and ascertain how the controller performs in several access scenarios, vis-à-vis hand-coded memory prefetches. Such memory patterns are very useful in stencil computations. The theoretical bandwidth of the memory of the Convey is compared with the results of our measurements. The accurate study of the memory subsystem is particularly useful for users when they are developing their application-specific personality. Experiments were performed to measure the bandwidth between the coprocessor and the memory subsystem. The experiments aimed mainly at measuring the reading access speed of the memory from Application Engines (FPGAs. Different ways of accessing data were used in order to find the most efficient way to access memory. This way was proposed for future work in the Convey HC-x. When performing a series of accesses to memory, non-uniform latencies occur. The Memory Controller of the Convey HC-x in the coprocessor attempts to cover this latency. We measure memory efficiency as a ratio of the number of memory accesses and the number of execution cycles. The result of this measurement converges to one in most cases. In addition, we performed experiments with hand-coded memory accesses. The analysis of the experimental results shows how the memory subsystem and Memory Controllers work. From this work we conclude that the memory controllers do an excellent job, largely because (transparently to the user they seem to cache large amounts of data, and hence hand-coding is not needed in most situations.

  7. Impact of PECS tablet computer app on receptive identification of pictures given a verbal stimulus.

    Science.gov (United States)

    Ganz, Jennifer B; Hong, Ee Rea; Goodwyn, Fara; Kite, Elizabeth; Gilliland, Whitney

    2015-04-01

    The purpose of this brief report was to determine the effect on receptive identification of photos of a tablet computer-based augmentative and alternative communication (AAC) system with voice output. A multiple baseline single-case experimental design across vocabulary words was implemented. One participant, a preschool-aged boy with autism and little intelligible verbal language, was included in the study. Although a functional relation between the intervention and the dependent variable was not established, the intervention did appear to result in mild improvement for two of the three vocabulary words selected. The authors recommend further investigations of the collateral impacts of AAC on skills other than expressive language.

  8. Hybrid simulation of reactor kinetics in CANDU reactors using a modal approach

    International Nuclear Information System (INIS)

    Monaghan, B.M.; McDonnell, F.N.; Hinds, H.W.T.; m.

    1980-01-01

    A hybrid computer model for simulating the behaviour of large CANDU (Canada Deuterium Uranium) reactor cores is presented. The main dynamic variables are expressed in terms of weighted sums of a base set of spatial natural-mode functions with time-varying co-efficients. This technique, known as the modal or synthesis approach, permits good three-dimensional representation of reactor dynamics and is well suited to hybrid simulation. The hybrid model provides improved man-machine interaction and real-time capability. The model was used in two applications. The first studies the transient that follows a loss of primary coolant and reactor shutdown; the second is a simulation of the dynamics of xenon, a fission product which has a high absorption cross-section for neutrons and thus has an important effect on reactor behaviour. Comparison of the results of the hybrid computer simulation with those of an all-digital one is good, within 1% to 2%

  9. Programmable architecture for quantum computing

    NARCIS (Netherlands)

    Chen, J.; Wang, L.; Charbon, E.; Wang, B.

    2013-01-01

    A programmable architecture called “quantum FPGA (field-programmable gate array)” (QFPGA) is presented for quantum computing, which is a hybrid model combining the advantages of the qubus system and the measurement-based quantum computation. There are two kinds of buses in QFPGA, the local bus and

  10. Hybrid-hybrid matrix structural refinement of a DNA three-way junction from 3D NOESY-NOESY

    International Nuclear Information System (INIS)

    Thiviyanathan, Varatharasa; Luxon, Bruce A.; Leontis, Neocles B.; Illangasekare, Nishantha; Donne, David G.; Gorenstein, David G.

    1999-01-01

    Homonuclear 3D NOESY-NOESY has shown great promise for the structural refinement of large biomolecules. A computationally efficient hybrid-hybrid relaxation matrix refinement methodology, using 3D NOESY-NOESY data, was used to refine the structure of a DNA three-way junction having two unpaired bases at the branch point of the junction. The NMR data and the relaxation matrix refinement confirm that the DNA three-way junction exists in a folded conformation with two of the helical stems stacked upon each other. The third unstacked stem extends away from the junction, forming an acute angle (∼60 deg.) with the stacked stems. The two unpaired bases are stacked upon each other and are exposed to the solvent. Helical parameters for the bases in all three strands show slight deviations from typical values expected for right-handed B-form DNA. Inter-nucleotide imino-imino NOEs between the bases at the branch point of the junction show that the junction region is well defined. The helical stems show mobility (± 20 deg.) indicating dynamic processes around the junction region. The unstacked helical stem adjacent to the unpaired bases shows greater mobility compared to the other two stems. The results from this study indicate that the 3D hybrid-hybrid matrix MORASS refinement methodology, by combining the spectral dispersion of 3D NOESY-NOESY and the computational efficiency of 2D refinement programs, provides an accurate and robust means for structure determination of large biomolecules. Our results also indicate that the 3D MORASS method gives higher quality structures compared to the 2D complete relaxation matrix refinement method

  11. Nuclear Hybrid Energy System Modeling: RELAP5 Dynamic Coupling Capabilities

    Energy Technology Data Exchange (ETDEWEB)

    Piyush Sabharwall; Nolan Anderson; Haihua Zhao; Shannon Bragg-Sitton; George Mesina

    2012-09-01

    The nuclear hybrid energy systems (NHES) research team is currently developing a dynamic simulation of an integrated hybrid energy system. A detailed simulation of proposed NHES architectures will allow initial computational demonstration of a tightly coupled NHES to identify key reactor subsystem requirements, identify candidate reactor technologies for a hybrid system, and identify key challenges to operation of the coupled system. This work will provide a baseline for later coupling of design-specific reactor models through industry collaboration. The modeling capability addressed in this report focuses on the reactor subsystem simulation.

  12. Computational Identification of Novel Genes: Current and Future Perspectives.

    Science.gov (United States)

    Klasberg, Steffen; Bitard-Feildel, Tristan; Mallet, Ludovic

    2016-01-01

    While it has long been thought that all genomic novelties are derived from the existing material, many genes lacking homology to known genes were found in recent genome projects. Some of these novel genes were proposed to have evolved de novo, ie, out of noncoding sequences, whereas some have been shown to follow a duplication and divergence process. Their discovery called for an extension of the historical hypotheses about gene origination. Besides the theoretical breakthrough, increasing evidence accumulated that novel genes play important roles in evolutionary processes, including adaptation and speciation events. Different techniques are available to identify genes and classify them as novel. Their classification as novel is usually based on their similarity to known genes, or lack thereof, detected by comparative genomics or against databases. Computational approaches are further prime methods that can be based on existing models or leveraging biological evidences from experiments. Identification of novel genes remains however a challenging task. With the constant software and technologies updates, no gold standard, and no available benchmark, evaluation and characterization of genomic novelty is a vibrant field. In this review, the classical and state-of-the-art tools for gene prediction are introduced. The current methods for novel gene detection are presented; the methodological strategies and their limits are discussed along with perspective approaches for further studies.

  13. Hybrid epidemic spreading - from Internet worms to HIV infection

    OpenAIRE

    Zhang, C.

    2015-01-01

    Epidemic phenomena are ubiquitous, ranging from infectious diseases, computer viruses, to information dissemination. Epidemics have traditionally been studied as a single spreading process, either in a fully mixed population or on a network. Many epidemics, however, are hybrid, employing more than one spreading mechanism. For example, the Internet worm Conficker spreads locally targeting neighbouring computers in local networks as well as globally by randomly probing any computer on the Inter...

  14. Speed-up of ab initio hybrid Monte Carlo and ab initio path integral hybrid Monte Carlo simulations by using an auxiliary potential energy surface

    International Nuclear Information System (INIS)

    Nakayama, Akira; Taketsugu, Tetsuya; Shiga, Motoyuki

    2009-01-01

    Efficiency of the ab initio hybrid Monte Carlo and ab initio path integral hybrid Monte Carlo methods is enhanced by employing an auxiliary potential energy surface that is used to update the system configuration via molecular dynamics scheme. As a simple illustration of this method, a dual-level approach is introduced where potential energy gradients are evaluated by computationally less expensive ab initio electronic structure methods. (author)

  15. Stochastic effects in hybrid inflation

    Science.gov (United States)

    Martin, Jérôme; Vennin, Vincent

    2012-02-01

    Hybrid inflation is a two-field model where inflation ends due to an instability. In the neighborhood of the instability point, the potential is very flat and the quantum fluctuations dominate over the classical motion of the inflaton and waterfall fields. In this article, we study this regime in the framework of stochastic inflation. We numerically solve the two coupled Langevin equations controlling the evolution of the fields and compute the probability distributions of the total number of e-folds and of the inflation exit point. Then, we discuss the physical consequences of our results, in particular, the question of how the quantum diffusion can affect the observable predictions of hybrid inflation.

  16. A hybrid approach to simulate multiple photon scattering in X-ray imaging

    International Nuclear Information System (INIS)

    Freud, N.; Letang, J.-M.; Babot, D.

    2005-01-01

    A hybrid simulation approach is proposed to compute the contribution of scattered radiation in X- or γ-ray imaging. This approach takes advantage of the complementarity between the deterministic and probabilistic simulation methods. The proposed hybrid method consists of two stages. Firstly, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Secondly, this set of scattering events is used as a starting point to compute the energy imparted to the detector, with a deterministic algorithm based on a 'forced detection' scheme. For each scattering event, the probability for the scattered photon to reach each pixel of the detector is calculated using well-known physical models (form factor and incoherent scattering function approximations, in the case of Rayleigh and Compton scattering respectively). The results of the proposed hybrid approach are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The convergence of the results when the number of scattering events increases is studied. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the number of pixels of the detector). This constitutes a substantial benefit, compared to classical simulation methods (Monte Carlo or deterministic approaches), which usually requires a parallel computing architecture to obtain comparable results

  17. A hybrid approach to simulate multiple photon scattering in X-ray imaging

    Energy Technology Data Exchange (ETDEWEB)

    Freud, N. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France)]. E-mail: nicolas.freud@insa-lyon.fr; Letang, J.-M. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France); Babot, D. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France)

    2005-01-01

    A hybrid simulation approach is proposed to compute the contribution of scattered radiation in X- or {gamma}-ray imaging. This approach takes advantage of the complementarity between the deterministic and probabilistic simulation methods. The proposed hybrid method consists of two stages. Firstly, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Secondly, this set of scattering events is used as a starting point to compute the energy imparted to the detector, with a deterministic algorithm based on a 'forced detection' scheme. For each scattering event, the probability for the scattered photon to reach each pixel of the detector is calculated using well-known physical models (form factor and incoherent scattering function approximations, in the case of Rayleigh and Compton scattering respectively). The results of the proposed hybrid approach are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The convergence of the results when the number of scattering events increases is studied. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the number of pixels of the detector). This constitutes a substantial benefit, compared to classical simulation methods (Monte Carlo or deterministic approaches), which usually requires a parallel computing architecture to obtain comparable results.

  18. Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

    Science.gov (United States)

    Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed

    2017-05-01

    Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.

  19. Hybrid FRP-concrete bridge deck system final report I : development and system performance validation.

    Science.gov (United States)

    2009-10-01

    In this study, the concept of the hybrid FRP-concrete structural systems was applied to both bridge : superstructure and deck systems. Results from the both experimental and computational analysis for : both the hybrid bridge superstructure and deck ...

  20. Qubus ancilla-driven quantum computation

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Katherine Louise [School of Physics and Astronomy, Louisiana State University, Baton Rouge, LA 70808, United States and School of Physics and Astronomy, University of Leeds, LS2 9JT (United Kingdom); De, Suvabrata; Kendon, Viv [School of Physics and Astronomy, University of Leeds, LS2 9JT (United Kingdom); Munro, Bill [National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan and NTT Basic Research Laboratories, 3-1, Morinosato Wakamiya Atsugi-shi, Kanagawa 243-0198 (Japan)

    2014-12-04

    Hybrid matter-optical systems offer a robust, scalable path to quantum computation. Such systems have an ancilla which acts as a bus connecting the qubits. We demonstrate how using a continuous variable qubus as the ancilla provides savings in the total number of operations required when computing with many qubits.

  1. Evaluation of the reliability concerning the identification of human factors as contributing factors by a computer supported event analysis (CEA)

    International Nuclear Information System (INIS)

    Wilpert, B.; Maimer, H.; Loroff, C.

    2000-01-01

    The project's objectives are the evaluation of the reliability concerning the identification of Human Factors as contributing factors by a computer supported event analysis (CEA). CEA is a computer version of SOL (Safety through Organizational Learning). Parts of the first step were interviews with experts from the nuclear power industry and the evaluation of existing computer supported event analysis methods. This information was combined to a requirement profile for the CEA software. The next step contained the implementation of the software in an iterative process of evaluation. The completion of this project was the testing of the CEA software. As a result the testing demonstrated that it is possible to identify contributing factors with CEA validly. In addition, CEA received a very positive feedback from the experts. (orig.) [de

  2. Hybrid simulation of a 900 Mwe nuclear plant

    International Nuclear Information System (INIS)

    Constantieux, Thierry; Deat, Max.

    1979-01-01

    To analyse the effects on PWRs of transients originating from the network, specific means of calculation must be elaborated. One of them which was conceived and set up on a hybrid computer by FRAMATOME and the FRENCH ATOMIC ENERGY COMMISSION, is described in this paper. The method chosen to validate this code is fairly original, since it consisted in carrying out a long duration test on a plan and in simulating this on the hybrid computer; then in carefully comparing the recorded data of the test with the results of the simulation. The quality of the results, thus obtained shows that a relatively unsophisticated model is able to give a good idea of actual process behavior, but only if the types of transients to be studied with the code are well identified before its elaboration

  3. Parallelized Genetic Identification of the Thermal-Electrochemical Model for Lithium-Ion Battery

    Directory of Open Access Journals (Sweden)

    Liqiang Zhang

    2013-01-01

    Full Text Available The parameters of a well predicted model can be used as health characteristics for Lithium-ion battery. This article reports a parallelized parameter identification of the thermal-electrochemical model, which significantly reduces the time consumption of parameter identification. Since the P2D model has the most predictability, it is chosen for further research and expanded to the thermal-electrochemical model by coupling thermal effect and temperature-dependent parameters. Then Genetic Algorithm is used for parameter identification, but it takes too much time because of the long time simulation of model. For this reason, a computer cluster is built by surplus computing resource in our laboratory based on Parallel Computing Toolbox and Distributed Computing Server in MATLAB. The performance of two parallelized methods, namely Single Program Multiple Data (SPMD and parallel FOR loop (PARFOR, is investigated and then the parallelized GA identification is proposed. With this method, model simulations running parallelly and the parameter identification could be speeded up more than a dozen times, and the identification result is batter than that from serial GA. This conclusion is validated by model parameter identification of a real LiFePO4 battery.

  4. BoB, a best-of-breed automated text de-identification system for VHA clinical documents.

    Science.gov (United States)

    Ferrández, Oscar; South, Brett R; Shen, Shuying; Friedlin, F Jeffrey; Samore, Matthew H; Meystre, Stéphane M

    2013-01-01

    De-identification allows faster and more collaborative clinical research while protecting patient confidentiality. Clinical narrative de-identification is a tedious process that can be alleviated by automated natural language processing methods. The goal of this research is the development of an automated text de-identification system for Veterans Health Administration (VHA) clinical documents. We devised a novel stepwise hybrid approach designed to improve the current strategies used for text de-identification. The proposed system is based on a previous study on the best de-identification methods for VHA documents. This best-of-breed automated clinical text de-identification system (aka BoB) tackles the problem as two separate tasks: (1) maximize patient confidentiality by redacting as much protected health information (PHI) as possible; and (2) leave de-identified documents in a usable state preserving as much clinical information as possible. We evaluated BoB with a manually annotated corpus of a variety of VHA clinical notes, as well as with the 2006 i2b2 de-identification challenge corpus. We present evaluations at the instance- and token-level, with detailed results for BoB's main components. Moreover, an existing text de-identification system was also included in our evaluation. BoB's design efficiently takes advantage of the methods implemented in its pipeline, resulting in high sensitivity values (especially for sensitive PHI categories) and a limited number of false positives. Our system successfully addressed VHA clinical document de-identification, and its hybrid stepwise design demonstrates robustness and efficiency, prioritizing patient confidentiality while leaving most clinical information intact.

  5. Detection and identification of intestinal pathogenic bacteria by hybridization to oligonucleotide microarrays

    Science.gov (United States)

    Jin, Lian-Qun; Li, Jun-Wen; Wang, Sheng-Qi; Chao, Fu-Huan; Wang, Xin-Wei; Yuan, Zheng-Quan

    2005-01-01

    AIM: To detect the common intestinal pathogenic bacteria quickly and accurately. METHODS: A rapid (<3 h) experimental procedure was set up based upon the gene chip technology. Target genes were amplified and hybridized by oligonucleotide microarrays. RESULTS: One hundred and seventy strains of bacteria in pure culture belonging to 11 genera were successfully discriminated under comparatively same conditions, and a series of specific hybridization maps corresponding to each kind of bacteria were obtained. When this method was applied to 26 divided cultures, 25 (96.2%) were identified. CONCLUSION: Salmonella sp., Escherichia coli, Shigella sp., Listeria monocytogenes, Vibrio parahaemolyticus, Staphylococcus aureus, Proteus sp., Bacillus cereus, Vibrio cholerae, Enterococcus faecalis, Yersinia enterocolitica, and Campylobacter jejuni can be detected and identified by our microarrays. The accuracy, range, and discrimination power of this assay can be continually improved by adding further oligonucleotides to the arrays without any significant increase of complexity or cost. PMID:16437687

  6. Scalable optical quantum computer

    International Nuclear Information System (INIS)

    Manykin, E A; Mel'nichenko, E V

    2014-01-01

    A way of designing a scalable optical quantum computer based on the photon echo effect is proposed. Individual rare earth ions Pr 3+ , regularly located in the lattice of the orthosilicate (Y 2 SiO 5 ) crystal, are suggested to be used as optical qubits. Operations with qubits are performed using coherent and incoherent laser pulses. The operation protocol includes both the method of measurement-based quantum computations and the technique of optical computations. Modern hybrid photon echo protocols, which provide a sufficient quantum efficiency when reading recorded states, are considered as most promising for quantum computations and communications. (quantum computer)

  7. An incidentally found inflamed uterine myoma Causing low abdominal pain, using TC-99m-tektrotyd single photon emission computed tomography-CT hybrid imaging

    Energy Technology Data Exchange (ETDEWEB)

    Zandieh, Shahin; Schuetz, Matthias; Bernt, Reinhard; Zwerina, Jochen; Haller, Joerg [Hanusch-Hospital, Teaching Hospital of Medical University of Vienna, Vienna (Australia)

    2013-10-15

    We report the case of a 50-year-old woman presented with a history of right hemicolectomy due to an ileocecal neuroendocrine tumor and left breast metastasis. Owing to a slightly elevated chromogranin A-level and lower abdominal pain, single photon emission computed tomography-computer tomography (SPECT-CT) was performed. There were no signs of recurrence on the SPECT-CT scan, but the patient was incidentally found to have an inflamed intramural myoma. We believe that the slightly elevated chromogranin A-level was caused by the hypertension that the patient presented. In the clinical context, this is a report of an inflamed uterine myoma seen as a false positive result detected by TC-99m-Tc-EDDA/HYNIC-Tyr3-Octreotide (Tektrotyd) SPECT-CT hybrid imaging.

  8. Evidence for the robustness of protein complexes to inter-species hybridization.

    Directory of Open Access Journals (Sweden)

    Jean-Baptiste Leducq

    Full Text Available Despite the tremendous efforts devoted to the identification of genetic incompatibilities underlying hybrid sterility and inviability, little is known about the effect of inter-species hybridization at the protein interactome level. Here, we develop a screening platform for the comparison of protein-protein interactions (PPIs among closely related species and their hybrids. We examine in vivo the architecture of protein complexes in two yeast species (Saccharomyces cerevisiae and Saccharomyces kudriavzevii that diverged 5-20 million years ago and in their F1 hybrids. We focus on 24 proteins of two large complexes: the RNA polymerase II and the nuclear pore complex (NPC, which show contrasting patterns of molecular evolution. We found that, with the exception of one PPI in the NPC sub-complex, PPIs were highly conserved between species, regardless of protein divergence. Unexpectedly, we found that the architecture of the complexes in F1 hybrids could not be distinguished from that of the parental species. Our results suggest that the conservation of PPIs in hybrids likely results from the slow evolution taking place on the very few protein residues involved in the interaction or that protein complexes are inherently robust and may accommodate protein divergence up to the level that is observed among closely related species.

  9. Hybrid expert system

    International Nuclear Information System (INIS)

    Tsoukalas, L.; Ikonomopoulos, A.; Uhrig, R.E.

    1991-01-01

    This paper presents a methodology that couples rule-based expert systems using fuzzy logic, to pre-trained artificial neutral networks (ANN) for the purpose of transient identification in Nuclear Power Plants (NPP). In order to provide timely concise, and task-specific information about the may aspects of the transient and to determine the state of the system based on the interpretation of potentially noisy data a model-referenced approach is utilized. In it, the expert system performs the basic interpretation and processing of the model data, and pre-trained ANNs provide the model. having access to a set of neural networks that typify general categories of transients, the rule based system is able to perform identification functions. Membership functions - condensing information about a transient in a form convenient for a rule-based identification system characterizing a transient - are the output of neural computations. This allows the identification function to be performed with a speed comparable to or faster than that of the temporal evolution of the system. Simulator data form major secondary system pipe rupture is used to demonstrate the methodology. The results indicate excellent noise-tolerance for ANN's and suggest a new method for transient identification within the framework of Fuzzy Logic

  10. Leptospira borgpetersenii hybrid leucine-rich repeat protein: Cloning and expression, immunogenic identification and molecular docking evaluation.

    Science.gov (United States)

    Sritrakul, Tepyuda; Nitipan, Supachai; Wajjwalku, Worawidh; La-Ard, Anchalee; Suphatpahirapol, Chattip; Petkarnjanapong, Wimol; Ongphiphadhanakul, Boonsong; Prapong, Siriwan

    2017-11-01

    Leptospirosis is an important zoonotic disease, and the major outbreak of this disease in Thailand in 1999 was due largely to the Leptospira borgpetersenii serovar Sejroe. Identification of the leucine-rich repeat (LRR) LBJ_2271 protein containing immunogenic epitopes and the discovery of the LBJ_2271 ortholog in Leptospira serovar Sejroe, KU_Sej_R21_2271, led to further studies of the antigenic immune properties of KU_Sej_LRR_2271. The recombinant hybrid (rh) protein was created and expressed from a hybrid PCR fragment of KU_Sej_R21_2271 fused with DNA encoding the LBJ_2271 signal sequence for targeting protein as a membrane-anchoring protein. The fusion DNA was cloned into pET160/GW/D-TOPO® to form the pET160_hKU_R21_2271 plasmid. The plasmid was used to express the rhKU_Sej_LRR_2271 protein in Escherichia coli BL21 Star™ (DE3). The expressed protein was immunologically detected by Western blotting and immunoreactivity detection with hyperimmune sera, T cell epitope prediction by HLA allele and epitope peptide binding affinity, and potential T cell reactivity analysis. The immunogenic epitopes of the protein were evaluated and verified by HLA allele and epitope peptide complex structure molecular docking. Among fourteen best allele epitopes of this protein, binding affinity values of 12 allele epitopes remained unchanged compared to LBJ_2271. Two epitopes for alleles HLA-A0202 and -A0301 had higher IC 50 values, while T cell reactivity values of these peptides were better than values from LBJ_2271 epitopes. Eight of twelve epitope peptides had positive T-cell reactivity scores. Although the molecular docking of two epitopes, 3FPLLKEFLV11/47FPLLKEFLV55 and 50KLSTVPEGV58, into an HLA-A0202 model revealed a good fit in the docked structures, 50KLSTVPEGV58 and 94KLSTVPEEV102 are still considered as the proteins' best epitopes for allele HLA-A0202. The results of this study showed that rhKU_Sej_LRR_2271 protein contained natural immunological properties that should

  11. Hybrid RANS/LES applied to complex terrain

    DEFF Research Database (Denmark)

    Bechmann, Andreas; Sørensen, Niels N.

    2011-01-01

    Large Eddy Simulation (LES) of the wind in complex terrain is limited by computational cost. The number of computational grid points required to resolve the near-ground turbulent structures (eddies) are very high. The traditional solution to the problem has been to apply a wall function...... aspect ratio in the RANS layer and thereby resolve the mean near-wall velocity profile. The method is applicable to complex terrain and the benefits of traditional LES are kept intact. Using the hybrid method, simulations of the wind over a natural complex terrain near Wellington in New Zealand...... that accounts for the whole near-wall region. Recently, a hybrid method was proposed in which the eddies close to the ground were modelled in a Reynolds-averaged sense (RANS) and the eddies above this region were simulated using LES. The advantage of the approach is the ability to use shallow cells of high...

  12. Identification of hybrids of painted and milky storks using FTA card-collected blood, molecular markers, and morphologies.

    Science.gov (United States)

    Yee, Elsie Yoke Sim; Zainuddin, Zainal Zahari; Ismail, Ahmad; Yap, Chee Kong; Tan, Soon Guan

    2013-10-01

    Suspicious hybrids of painted storks and milky storks were found in a Malaysian zoo. Blood of these birds was sampled on FTA cards for DNA fingerprinting. Of 44 optimized primers, 6 produced diagnostic markers that could identify hybrids. The markers were based on simple, direct PCR-generated multilocus banding patterns that provided two sets of genetic data, one for each of the two stork species and another for the hybrids. It also revealed that large DNA fragments (3,000 bp) could be amplified from blood collected on FTA cards. When the results of each individual bird's DNA fingerprint were compared with plumage characters, the hybrids were found to express a range of intermediate phenotypic traits of the pure breeds with no dominant plumage characteristic from either parental species.

  13. 5th Symposium on Hybrid RANS-LES Methods

    CERN Document Server

    Haase, Werner; Peng, Shia-Hui; Schwamborn, Dieter

    2015-01-01

    This book gathers the proceedings of the Fifth Symposium on Hybrid RANS-LES Methods, which was held on March 19-21 in College Station, Texas, USA. The different chapters, written by leading experts, reports on the most recent developments in flow physics modelling, and gives a special emphasis to industrially relevant applications of hybrid RANS-LES methods and other turbulence-resolving modelling approaches. The book addresses academic researchers, graduate students, industrial engineers, as well as industrial R&D managers and consultants dealing with turbulence modelling, simulation and measurement, and with multidisciplinary applications of computational fluid dynamics (CFD), such as flow control, aero-acoustics, aero-elasticity and CFD-based multidisciplinary optimization. It discusses in particular advanced hybrid RANS-LES methods. Further topics include wall-modelled Large Eddy Simulation (WMLES) methods, embedded LES, and a comparison of the LES methods with both hybrid RANS-LES and URANS methods. ...

  14. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

    Science.gov (United States)

    Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin; Choo, Kim-Kwang Raymond

    2016-01-01

    To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO).

  15. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

    Directory of Open Access Journals (Sweden)

    Firdaus Afifi

    Full Text Available To deal with the large number of malicious mobile applications (e.g. mobile malware, a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS and particle swarm optimization (PSO. Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE and ant colony optimization (ANFIS-ACO.

  16. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware

    Science.gov (United States)

    Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin

    2016-01-01

    To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO). PMID:27611312

  17. Safety analysis on tokamak helium cooling slab fuel fusion-fission hybrid reactor

    International Nuclear Information System (INIS)

    Wei Renjie; Jian Hongbing

    1992-01-01

    The thermal analyses for steady state, depressurization and total loss of flow in the tokamak helium cooling slab fuel element fusion-fission hybrid reactor are presented. The design parameters, computed results of HYBRID program and safety evaluation for conception design are given. After all, it gives some recommendations for developing the design

  18. EVALUATION OF HYBRIDIZATION BETWEEN PANGASIUS DJAMBAL BLEEKER 1846 AND PANGASIANODON HYPOPHTHALMUS (SAUVAGE 1878: BIOMETRIC CHARACTERIZATION AND GROWTH ANALYSIS

    Directory of Open Access Journals (Sweden)

    Rudhy Gustiano

    2007-06-01

    Full Text Available Possible use of pangasiid hybrids in aquaculture might generate potential impacts on wild populations. Therefore, rapid identification tools in the field such as growth rate are urgently needed. This study examines morphological characters and growth performance of P. djambal and P. hypophthalmus and their reciprocal hybrids. A detailed morphological study analysed 32 morphometric measurements and 5 meristic counts on hybrids of Pangasius djambal and P. hypophthalmus. Morphometric analysis and meristic counts showed that the reciprocal hybrids have intermediate characters except for gill rakers number which were lower than that of parental species. In general, the hybrids have tendency to be like P. hypophthalmus rather than P. djambal. The only typical character P. djambal appearing in hybrids is teeth shape, both vomerine and palatine. It was shown that the true hybrids have seven pelvic fin rays. Eight months of growth comparison in earthen ponds showed that the hybrids have a better performance for specific growth rate than the parental stock.

  19. sBCI-Headset—Wearable and Modular Device for Hybrid Brain-Computer Interface

    Directory of Open Access Journals (Sweden)

    Tatsiana Malechka

    2015-02-01

    Full Text Available Severely disabled people, like completely paralyzed persons either with tetraplegia or similar disabilities who cannot use their arms and hands, are often considered as a user group of Brain Computer Interfaces (BCI. In order to achieve high acceptance of the BCI by this user group and their supporters, the BCI system has to be integrated into their support infrastructure. Critical disadvantages of a BCI are the time consuming preparation of the user for the electroencephalography (EEG measurements and the low information transfer rate of EEG based BCI. These disadvantages become apparent if a BCI is used to control complex devices. In this paper, a hybrid BCI is described that enables research for a Human Machine Interface (HMI that is optimally adapted to requirements of the user and the tasks to be carried out. The solution is based on the integration of a Steady-state visual evoked potential (SSVEP-BCI, an Event-related (de-synchronization (ERD/ERS-BCI, an eye tracker, an environmental observation camera, and a new EEG head cap for wearing comfort and easy preparation. The design of the new fast multimodal BCI (called sBCI system is described and first test results, obtained in experiments with six healthy subjects, are presented. The sBCI concept may also become useful for healthy people in cases where a “hands-free” handling of devices is necessary.

  20. Energy metrics analysis of hybrid - photovoltaic (PV) modules

    Energy Technology Data Exchange (ETDEWEB)

    Tiwari, Arvind [Department of Electronics and Communication, Krishna Institute of Engineering and Technology, 13 k.m. stone, Ghaziabad - Meerut Road, Ghaziabad 201 206, UP (India); Barnwal, P.; Sandhu, G.S.; Sodha, M.S. [Centre for Energy Studies, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110 016 (India)

    2009-12-15

    In this paper, energy metrics (energy pay back time, electricity production factor and life cycle conversion efficiency) of hybrid photovoltaic (PV) modules have been analyzed and presented for the composite climate of New Delhi, India. For this purpose, it is necessary to calculate (1) the energy consumption in making different components of the PV modules and (2) the annual energy (electrical and thermal) available from the hybrid-PV modules. A set of mathematical relations have been reformulated for computation of the energy metrics. The manufacturing energy, material production energy, energy use and distribution energy of the system have been taken into account, to determine the embodied energy for the hybrid-PV modules. The embodied energy and annual energy outputs have been used for evaluation of the energy metrics. For hybrid PV module, it has been observed that the EPBT gets significantly reduced by taking into account the increase in annual energy availability of the thermal energy in addition to the electrical energy. The values of EPF and LCCE of hybrid PV module become higher as expected. (author)

  1. Hybrid adaptive ascent flight control for a flexible launch vehicle

    Science.gov (United States)

    Lefevre, Brian D.

    For the purpose of maintaining dynamic stability and improving guidance command tracking performance under off-nominal flight conditions, a hybrid adaptive control scheme is selected and modified for use as a launch vehicle flight controller. This architecture merges a model reference adaptive approach, which utilizes both direct and indirect adaptive elements, with a classical dynamic inversion controller. This structure is chosen for a number of reasons: the properties of the reference model can be easily adjusted to tune the desired handling qualities of the spacecraft, the indirect adaptive element (which consists of an online parameter identification algorithm) continually refines the estimates of the evolving characteristic parameters utilized in the dynamic inversion, and the direct adaptive element (which consists of a neural network) augments the linear feedback signal to compensate for any nonlinearities in the vehicle dynamics. The combination of these elements enables the control system to retain the nonlinear capabilities of an adaptive network while relying heavily on the linear portion of the feedback signal to dictate the dynamic response under most operating conditions. To begin the analysis, the ascent dynamics of a launch vehicle with a single 1st stage rocket motor (typical of the Ares 1 spacecraft) are characterized. The dynamics are then linearized with assumptions that are appropriate for a launch vehicle, so that the resulting equations may be inverted by the flight controller in order to compute the control signals necessary to generate the desired response from the vehicle. Next, the development of the hybrid adaptive launch vehicle ascent flight control architecture is discussed in detail. Alterations of the generic hybrid adaptive control architecture include the incorporation of a command conversion operation which transforms guidance input from quaternion form (as provided by NASA) to the body-fixed angular rate commands needed by the

  2. Hybrid power system (hydro, solar and wind) for rural electricity generation

    International Nuclear Information System (INIS)

    Mahinda Kurukulasuriya

    2000-01-01

    Generation of affordable cheap electric energy for rural development by a hybrid power system (10-50 kW) of hydropower, solar and wind energies on self determining basis and computer application to determine its performance. In this paper the following topics were discussed, design of hybrid power system, its justification and economic analysis, manufacturing and installation of the system. (Author)

  3. Game-based Abstraction and Controller Synthesis for Probabilistic Hybrid Systems

    DEFF Research Database (Denmark)

    Hahn, Ernst Moritz; Norman, Gethin; Parker, David

    2011-01-01

    We consider a class of hybrid systems that involve random phenomena, in addition to discrete and continuous behaviour. Examples of such systems include wireless sensing and control applications. We propose and compare two abstraction techniques for this class of models, which yield lower and upper...... bounds on the optimal probability of reaching a particular class of states. We also demonstrate the applicability of these abstraction techniques to the computation of long-run average reward properties and the synthesis of controllers. The first of the two abstractions yields more precise information......, while the second is easier to construct. For the latter, we demonstrate how existing solvers for hybrid systems can be leveraged to perform the computation....

  4. Review of the Optimal Design on a Hybrid Renewable Energy System

    Directory of Open Access Journals (Sweden)

    Wu Yuan-Kang

    2016-01-01

    Full Text Available Hybrid renewable energy systems, combining various kinds of technologies, have shown relatively high capabilities to solve reliability problems and have reduced cost challenges. The use of hybrid electricity generation/storage technologies is reasonable to overcome related shortcomings. While the hybrid renewable energy system is attractive, its design, specifically the determination of the size of PV, wind, and diesel power generators and the size of energy storage system in each power station, is very challenging. Therefore, this paper will focus on the system planning and operation of hybrid generation systems, and several corresponding topics and papers by using intelligent computing methods will be reviewed. They include typical case studies, modeling and system simulation, control and management, reliability and economic studies, and optimal design on a reliable hybrid generation system.

  5. Leishmania diagnostic and identification py using 32P labelled DNA probes

    International Nuclear Information System (INIS)

    Andrade, Antero Silva Ribeiro de; Melo, Maria Norma de

    1999-10-01

    P 32 labelled DNA probes are valious instruments for the parasitic diseases by using hybridization reaction. In this paper we describe the methodology and present the foundations for the radioactive probes production, based on the kinetoplast DNA (kDNA), for the Leishmania diagnostic an identification. We also describe the kDNA purification protocol from Leishmania reference cepa, the process of P 32 labelling of the kDNA by using the nick translation method, gathering, sample preparation and treatment, the optimum conditions for the hybridization reaction and the procedures for the autoradiography

  6. Influence of technological factors on characteristics of hybrid fluid-film bearings

    Science.gov (United States)

    Koltsov, A.; Prosekova, A.; Rodichev, A.; Savin, L.

    2017-08-01

    The influence of the parameters of micro- and macrounevenness on the characteristics of a hybrid bearing with slotted throttling is considered in the present paper. The quantitative assumptions of calculation of pressure distribution, load capacity, lubricant flow rate and power loss due to friction in a radial hybrid bearing with slotted throttling are taken into account, considering the shape, dimensions and roughness of the support surfaces inaccuracies. Numerical simulation of processes in the lubricating layer is based on the finite-difference solution of the Reynolds equation using an uneven orthogonal computational grid with adaptive condensation. The results of computational and physical experiments are presented.

  7. Hybrid chernoff tau-leap

    KAUST Repository

    Moraes, Alvaro

    2014-01-01

    Markovian pure jump processes model a wide range of phenomena, including chemical reactions at the molecular level, dynamics of wireless communication networks, and the spread of epidemic diseases in small populations. There exist algorithms such as Gillespie\\'s stochastic simulation algorithm (SSA) and Anderson\\'s modified next reaction method (MNRM) that simulate a single path with the exact distribution of the process, but this can be time consuming when many reactions take place during a short time interval. Gillespie\\'s approximated tau-leap method, on the other hand, can be used to reduce computational time, but it may lead to nonphysical values due to a positive one-step exit probability, and it also introduces a time discretization error. Here, we present a novel hybrid algorithm for simulating individual paths which adaptively switches between the SSA and the tau-leap method. The switching strategy is based on a comparison of the expected interarrival time of the SSA and an adaptive time step derived from a Chernoff-type bound for the one-step exit probability. Because this bound is nonasymptotic, we do not need to make any distributional approximation for the tau-leap increments. This hybrid method allows us (i) to control the global exit probability of any simulated path and (ii) to obtain accurate and computable estimates of the expected value of any smooth observable of the process with minimal computational work. We present numerical examples that illustrate the performance of the proposed method. © 2014 Society for Industrial and Applied Mathematics.

  8. Computer simulations of upper-hybrid and electron cyclotron resonance heating

    International Nuclear Information System (INIS)

    Lin, A.T.; Lin, C.C.

    1983-01-01

    A 2 1/2 -dimensional relativistic electromagnetic particle code is used to investigate the dynamic behavior of electron heating around the electron cyclotron and upper-hybrid layers when an extraordinary wave is obliquely launched from the high-field side into a magnetized plasma. With a large angle of incidence most of the radiation wave energy converts into electrostatic electron Bernstein waves at the upper-hybrid layer. These mode-converted waves propagate back to the cyclotron layer and deposit their energy in the electrons through resonant interactions dominated first by the Doppler broadening and later by the relativistic mass correction. The line shape for both mechanisms has been observed in the simulations. At a later stage, the relativistic resonance effects shift the peak of the temperature profile to the high-field side. The heating ultimately causes the extraordinary wave to be substantially absorbed by the high-energy electrons. The steep temperature gradient created by the electron cyclotron heating eventually reflects a substantial part of the incident wave energy. The diamagnetic effects due to the gradient of the mode-converted Bernstein wave pressure enhance the spreading of the electron heating from the original electron cyclotron layer

  9. 48 CFR 252.227-7014 - Rights in noncommercial computer software and noncommercial computer software documentation.

    Science.gov (United States)

    2010-10-01

    ...) Restricted rights in computer software, limited rights in technical data, or government purpose license... necessary to perfect a license or licenses in the deliverable software or documentation of the appropriate... the license rights obtained. (e) Identification and delivery of computer software and computer...

  10. Scalable optical quantum computer

    Energy Technology Data Exchange (ETDEWEB)

    Manykin, E A; Mel' nichenko, E V [Institute for Superconductivity and Solid-State Physics, Russian Research Centre ' Kurchatov Institute' , Moscow (Russian Federation)

    2014-12-31

    A way of designing a scalable optical quantum computer based on the photon echo effect is proposed. Individual rare earth ions Pr{sup 3+}, regularly located in the lattice of the orthosilicate (Y{sub 2}SiO{sub 5}) crystal, are suggested to be used as optical qubits. Operations with qubits are performed using coherent and incoherent laser pulses. The operation protocol includes both the method of measurement-based quantum computations and the technique of optical computations. Modern hybrid photon echo protocols, which provide a sufficient quantum efficiency when reading recorded states, are considered as most promising for quantum computations and communications. (quantum computer)

  11. Hybrid Lanczos-type product methods

    Energy Technology Data Exchange (ETDEWEB)

    Ressel, K.J. [Swiss Center for Scientific Computing, Zuerich (Switzerland)

    1996-12-31

    A general framework is proposed to construct hybrid iterative methods for the solution of large nonsymmetric systems of linear equations. This framework is based on Lanczos-type product methods, whose iteration polynomial consists of the Lanczos polynomial multiplied by some other arbitrary, {open_quotes}shadow{close_quotes} polynomial. By using for the shadow polynomial Chebyshev (more general Faber) polynomials or L{sup 2}-optimal polynomials, hybrid (Chebyshev-like) methods are incorporated into Lanczos-type product methods. In addition, to acquire spectral information on the system matrix, which is required for such a choice of shadow polynomials, the Lanczos-process can be employed either directly or in an QMR-like approach. The QMR like approach allows the cheap computation of the roots of the B-orthogonal polynomials and the residual polynomials associated with the QMR iteration. These roots can be used as a good approximation for the spectrum of the system matrix. Different choices for the shadow polynomials and their construction are analyzed. The resulting hybrid methods are compared with standard Lanczos-type product methods, like BiOStab, BiOStab({ell}) and BiOS.

  12. Dissipative dynamics of superconducting hybrid qubit systems

    International Nuclear Information System (INIS)

    Montes, Enrique; Calero, Jesus M; Reina, John H

    2009-01-01

    We perform a theoretical study of composed superconducting qubit systems for the case of a coupled qubit configuration based on a hybrid qubit circuit made of both charge and phase qubits, which are coupled via a σ x x σ z interaction. We compute the system's eigen-energies in terms of the qubit transition frequencies and the strength of the inter-qubit coupling, and describe the sensitivity of the energy crossing/anti-crossing features to such coupling. We compute the hybrid system's dissipative dynamics for the cases of i) collective and ii) independent decoherence, whereby the system interacts with one common and two different baths of harmonic oscillators, respectively. The calculations have been performed within the Bloch-Redfield formalism and we report the solutions for the populations and the coherences of the system's reduced density matrix. The dephasing and relaxation rates are explicitly calculated as a function of the heat bath temperature.

  13. Justification of the hybrid nuclear medicine examinations

    International Nuclear Information System (INIS)

    Garcheva-Tsacheva, Marina B.

    2015-01-01

    The annual frequency of nuclear medicine examinations is increasing worldwide. This is partly a consequence of the recently introduced single photon emission tomography, combined with computed tomography, and positron emission tomography, combined with computed tomography, techniques, which combine functional, metabolic and morphological information important for the diagnosis of many diseases. However, since the effective radiation dose is the sum of the dose of two components, the hybrid examinations result in increased patient exposure. Accordingly, their justification becomes mandatory. It starts with their clinical importance-the opportunity to resolve a clinical problem decisive for patients' management. Knowledge of the indications, contraindications and the examinations' limitations is the responsibility of the nuclear medicine physician, as well as the choice of the most adequate examination and protocol. In conclusion, the cost and the accessibility of the examinations should not be the principal consideration as opposed to the diagnostic value and the exposure. Flexible protocols and algorithms should be used for hybrid nuclear medicine examinations. (authors)

  14. Dissipative dynamics of superconducting hybrid qubit systems

    Energy Technology Data Exchange (ETDEWEB)

    Montes, Enrique; Calero, Jesus M; Reina, John H, E-mail: enriquem@univalle.edu.c, E-mail: j.reina-estupinan@physics.ox.ac.u [Departamento de Fisica, Universidad del Valle, A.A. 25360, Cali (Colombia)

    2009-05-01

    We perform a theoretical study of composed superconducting qubit systems for the case of a coupled qubit configuration based on a hybrid qubit circuit made of both charge and phase qubits, which are coupled via a sigma{sub x} x sigma{sub z} interaction. We compute the system's eigen-energies in terms of the qubit transition frequencies and the strength of the inter-qubit coupling, and describe the sensitivity of the energy crossing/anti-crossing features to such coupling. We compute the hybrid system's dissipative dynamics for the cases of i) collective and ii) independent decoherence, whereby the system interacts with one common and two different baths of harmonic oscillators, respectively. The calculations have been performed within the Bloch-Redfield formalism and we report the solutions for the populations and the coherences of the system's reduced density matrix. The dephasing and relaxation rates are explicitly calculated as a function of the heat bath temperature.

  15. Three dimensional subsurface elemental identification of minerals using confocal micro-X-ray fluorescence and micro-X-ray computed tomography

    International Nuclear Information System (INIS)

    Cordes, Nikolaus L.; Seshadri, Srivatsan; Havrilla, George J.; Yuan, Xiaoli; Feser, Michael; Patterson, Brian M.

    2015-01-01

    Current non-destructive elemental characterization methods, such as scanning electron microscopy-based energy dispersive spectroscopy (SEM–EDS) and micro-X-ray fluorescence spectroscopy (MXRF), are limited to either elemental identification at the surface (SEM–EDS) or suffer from an inability to discriminate between surface or depth information (MXRF). Thus, a non-destructive elemental characterization of individual embedded particles beneath the surface is impossible with either of these techniques. This limitation can be overcome by using laboratory-based 3D confocal micro-X-ray fluorescence spectroscopy (confocal MXRF). This technique utilizes focusing optics on the X-ray source and detector which allows for spatial discrimination in all three dimensions. However, the voxel-by-voxel serial acquisition of a 3D elemental scan can be very time-intensive (~ 1 to 4 weeks) if it is necessary to locate individual embedded particles of interest. As an example, if each point takes a 5 s measurement time, a small volume of 50 × 50 × 50 pixels leads to an acquisition time of approximately 174 h, not including sample stage movement time. Initially screening the samples for particles of interest using micro-X-ray computed tomography (micro-CT) can significantly reduce the time required to spatially locate these particles. Once located, these individual particles can be elementally characterized with confocal MXRF. Herein, we report the elemental identification of high atomic number surface and subsurface particles embedded in a mineralogical matrix by coupling micro-CT and confocal MXRF. Synergistically, these two X-ray based techniques first rapidly locate and then elementally identify individual subsurface particles. - Highlights: • Coupling of confocal X-ray fluorescence spectroscopy and X-ray computed tomography • Qualitative elemental identification of surface and subsurface mineral particles • Non-destructive particle size measurements • Utilization of

  16. Three dimensional subsurface elemental identification of minerals using confocal micro-X-ray fluorescence and micro-X-ray computed tomography

    Energy Technology Data Exchange (ETDEWEB)

    Cordes, Nikolaus L., E-mail: ncordes@lanl.gov [Polymers and Coatings Group, Material Science and Technology Division, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Seshadri, Srivatsan, E-mail: srivatsan.seshadri@zeiss.com [Carl Zeiss X-ray Microscopy, Inc., Pleasanton, CA 94588 (United States); Havrilla, George J. [Chemical Diagnostics and Engineering, Chemistry Division, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Yuan, Xiaoli [Julius Kruttschnitt Mineral Research Centre, University of Queensland, Indooroopilly, Brisbane, QLD 4068 (Australia); Feser, Michael [Carl Zeiss X-ray Microscopy, Inc., Pleasanton, CA 94588 (United States); Patterson, Brian M. [Polymers and Coatings Group, Material Science and Technology Division, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)

    2015-01-01

    Current non-destructive elemental characterization methods, such as scanning electron microscopy-based energy dispersive spectroscopy (SEM–EDS) and micro-X-ray fluorescence spectroscopy (MXRF), are limited to either elemental identification at the surface (SEM–EDS) or suffer from an inability to discriminate between surface or depth information (MXRF). Thus, a non-destructive elemental characterization of individual embedded particles beneath the surface is impossible with either of these techniques. This limitation can be overcome by using laboratory-based 3D confocal micro-X-ray fluorescence spectroscopy (confocal MXRF). This technique utilizes focusing optics on the X-ray source and detector which allows for spatial discrimination in all three dimensions. However, the voxel-by-voxel serial acquisition of a 3D elemental scan can be very time-intensive (~ 1 to 4 weeks) if it is necessary to locate individual embedded particles of interest. As an example, if each point takes a 5 s measurement time, a small volume of 50 × 50 × 50 pixels leads to an acquisition time of approximately 174 h, not including sample stage movement time. Initially screening the samples for particles of interest using micro-X-ray computed tomography (micro-CT) can significantly reduce the time required to spatially locate these particles. Once located, these individual particles can be elementally characterized with confocal MXRF. Herein, we report the elemental identification of high atomic number surface and subsurface particles embedded in a mineralogical matrix by coupling micro-CT and confocal MXRF. Synergistically, these two X-ray based techniques first rapidly locate and then elementally identify individual subsurface particles. - Highlights: • Coupling of confocal X-ray fluorescence spectroscopy and X-ray computed tomography • Qualitative elemental identification of surface and subsurface mineral particles • Non-destructive particle size measurements • Utilization of

  17. Hybridization rates between lettuce (Lactuca sativa) and its wild relative (L. serriola) under field conditions.

    Science.gov (United States)

    D'Andrea, Luigi; Felber, François; Guadagnuolo, Roberto

    2008-01-01

    Hybridization and introgression between crops and wild relatives may have important evolutionary and ecological consequences such as gene swamping or increased invasiveness. In the present study, we investigated hybridization under field conditions between crop lettuce (Lactuca sativa) and its wild relative prickly lettuce (L. serriola), two cross-compatible, predominantly autogamous and insect pollinated species. In 2003 and 2004, we estimated the rates of hybridization between L. sativa and L. serriola in close-to-reality field experiments carried out in two locations of Northern Switzerland. Seeds set by the experimental wild plants were collected and sown (44 352 in 2003 and 252 345 in 2004). Progeny was screened morphologically for detecting natural hybrids. Prior to the experiment, specific RAPD markers were used to confirm that morphological characters were reliable for hybrid identification. Hybridization occurred up to the maximal distance tested (40 m), and hybridization rates varied between 0 to 26%, decreasing with distance. More than 80% of the wild plants produced at least one hybrid (incidence of hybridization, IH) at 0 m and 1 m. It equaled 4 to 5% at 40 m. In sympatric crop-wild populations, cross-pollination between cultivated lettuce and its wild relative has to be seen as the rule rather than the exception for short distances.

  18. Epistasis modifies the dominance of loci causing hybrid male sterility in the Drosophila pseudoobscura species group.

    Science.gov (United States)

    Chang, Audrey S; Noor, Mohamed A F

    2010-01-01

    Speciation, the evolution of reproductive isolation between populations, serves as the driving force for generating biodiversity. Postzygotic barriers to gene flow, such as F(1) hybrid sterility and inviability, play important roles in the establishment and maintenance of biological species. F(1) hybrid incompatibilities in taxa that obey Haldane's rule, the observation that the heterogametic sex suffers greater hybrid fitness problems than the homogametic sex, are thought to often result from interactions between recessive-acting X-linked loci and dominant-acting autosomal loci. Because they play such prominent roles in producing hybrid incompatibilities, we examine the dominance and nature of epistasis between alleles derived from Drosophila persimilis that confer hybrid male sterility in the genetic background of its sister species, D. pseudoobscura bogotana. We show that epistasis elevates the apparent dominance of individually recessive-acting QTL such that they can contribute to F(1) hybrid sterility. These results have important implications for assumptions underlying theoretical models of hybrid incompatibilities and may offer a possible explanation for why, to date, identification of dominant-acting autosomal "speciation genes" has been challenging.

  19. Dissecting the genetic architecture of F1 hybrid sterility in house mice.

    Science.gov (United States)

    Dzur-Gejdosova, Maria; Simecek, Petr; Gregorova, Sona; Bhattacharyya, Tanmoy; Forejt, Jiri

    2012-11-01

    Hybrid sterility as a postzygotic reproductive isolation mechanism has been studied for over 80 years, yet the first identifications of hybrid sterility genes in Drosophila and mouse are quite recent. To study the genetic architecture of F(1) hybrid sterility between young subspecies of house mouse Mus m. domesticus and M. m. musculus, we conducted QTL analysis of a backcross between inbred strains representing these two subspecies and probed the role of individual chromosomes in hybrid sterility using the intersubspecific chromosome substitution strains. We provide direct evidence that the asymmetry in male infertility between reciprocal crosses is conferred by the middle region of M. m. musculus Chr X, thus excluding other potential candidates such as Y, imprinted genes, and mitochondrial DNA. QTL analysis identified strong hybrid sterility loci on Chr 17 and Chr X and predicted a set of interchangeable autosomal loci, a subset of which is sufficient to activate the Dobzhansky-Muller incompatibility of the strong loci. Overall, our results indicate the oligogenic nature of F(1) hybrid sterility, which should be amenable to reconstruction by proper combination of chromosome substitution strains. Such a prefabricated model system should help to uncover the gene networks and molecular mechanisms underlying hybrid sterility. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

  20. Software For Computer-Security Audits

    Science.gov (United States)

    Arndt, Kate; Lonsford, Emily

    1994-01-01

    Information relevant to potential breaches of security gathered efficiently. Automated Auditing Tools for VAX/VMS program includes following automated software tools performing noted tasks: Privileged ID Identification, program identifies users and their privileges to circumvent existing computer security measures; Critical File Protection, critical files not properly protected identified; Inactive ID Identification, identifications of users no longer in use found; Password Lifetime Review, maximum lifetimes of passwords of all identifications determined; and Password Length Review, minimum allowed length of passwords of all identifications determined. Written in DEC VAX DCL language.

  1. Quadratic integrand double-hybrid made spin-component-scaled

    Energy Technology Data Exchange (ETDEWEB)

    Brémond, Éric, E-mail: eric.bremond@iit.it; Savarese, Marika [CompuNet, Istituto Italiano di Tecnologia, via Morego 30, I-16163 Genoa (Italy); Sancho-García, Juan C.; Pérez-Jiménez, Ángel J. [Departamento de Química Física, Universidad de Alicante, E-03080 Alicante (Spain); Adamo, Carlo [CompuNet, Istituto Italiano di Tecnologia, via Morego 30, I-16163 Genoa (Italy); Chimie ParisTech, PSL Research University, CNRS, Institut de Recherche de Chimie Paris IRCP, F-75005 Paris (France); Institut Universitaire de France, 103 Boulevard Saint Michel, F-75005 Paris (France)

    2016-03-28

    We propose two analytical expressions aiming to rationalize the spin-component-scaled (SCS) and spin-opposite-scaled (SOS) schemes for double-hybrid exchange-correlation density-functionals. Their performances are extensively tested within the framework of the nonempirical quadratic integrand double-hybrid (QIDH) model on energetic properties included into the very large GMTKN30 benchmark database, and on structural properties of semirigid medium-sized organic compounds. The SOS variant is revealed as a less computationally demanding alternative to reach the accuracy of the original QIDH model without losing any theoretical background.

  2. Attendance fingerprint identification system using arduino and single board computer

    Science.gov (United States)

    Muchtar, M. A.; Seniman; Arisandi, D.; Hasanah, S.

    2018-03-01

    Fingerprint is one of the most unique parts of the human body that distinguishes one person from others and is easily accessed. This uniqueness is supported by technology that can automatically identify or recognize a person called fingerprint sensor. Yet, the existing Fingerprint Sensor can only do fingerprint identification on one machine. For the mentioned reason, we need a method to be able to recognize each user in a different fingerprint sensor. The purpose of this research is to build fingerprint sensor system for fingerprint data management to be centralized so identification can be done in each Fingerprint Sensor. The result of this research shows that by using Arduino and Raspberry Pi, data processing can be centralized so that fingerprint identification can be done in each fingerprint sensor with 98.5 % success rate of centralized server recording.

  3. A computable phenotype for asthma case identification in adult and pediatric patients: External validation in the Chicago Area Patient-Outcomes Research Network (CAPriCORN).

    Science.gov (United States)

    Afshar, Majid; Press, Valerie G; Robison, Rachel G; Kho, Abel N; Bandi, Sindhura; Biswas, Ashvini; Avila, Pedro C; Kumar, Harsha Vardhan Madan; Yu, Byung; Naureckas, Edward T; Nyenhuis, Sharmilee M; Codispoti, Christopher D

    2017-10-13

    Comprehensive, rapid, and accurate identification of patients with asthma for clinical care and engagement in research efforts is needed. The original development and validation of a computable phenotype for asthma case identification occurred at a single institution in Chicago and demonstrated excellent test characteristics. However, its application in a diverse payer mix, across different health systems and multiple electronic health record vendors, and in both children and adults was not examined. The objective of this study is to externally validate the computable phenotype across diverse Chicago institutions to accurately identify pediatric and adult patients with asthma. A cohort of 900 asthma and control patients was identified from the electronic health record between January 1, 2012 and November 30, 2014. Two physicians at each site independently reviewed the patient chart to annotate cases. The inter-observer reliability between the physician reviewers had a κ-coefficient of 0.95 (95% CI 0.93-0.97). The accuracy, sensitivity, specificity, negative predictive value, and positive predictive value of the computable phenotype were all above 94% in the full cohort. The excellent positive and negative predictive values in this multi-center external validation study establish a useful tool to identify asthma cases in in the electronic health record for research and care. This computable phenotype could be used in large-scale comparative-effectiveness trials.

  4. Hybrid setup for micro- and nano-computed tomography in the hard X-ray range

    Science.gov (United States)

    Fella, Christian; Balles, Andreas; Hanke, Randolf; Last, Arndt; Zabler, Simon

    2017-12-01

    With increasing miniaturization in industry and medical technology, non-destructive testing techniques are an area of ever-increasing importance. In this framework, X-ray microscopy offers an efficient tool for the analysis, understanding, and quality assurance of microscopic samples, in particular as it allows reconstructing three-dimensional data sets of the whole sample's volume via computed tomography (CT). The following article describes a compact X-ray microscope in the hard X-ray regime around 9 keV, based on a highly brilliant liquid-metal-jet source. In comparison to commercially available instruments, it is a hybrid that works in two different modes. The first one is a micro-CT mode without optics, which uses a high-resolution detector to allow scans of samples in the millimeter range with a resolution of 1 μm. The second mode is a microscope, which contains an X-ray optical element to magnify the sample and allows resolving 150 nm features. Changing between the modes is possible without moving the sample. Thus, the instrument represents an important step towards establishing high-resolution laboratory-based multi-mode X-ray microscopy as a standard investigation method.

  5. Case for a field-programmable gate array multicore hybrid machine for an image-processing application

    Science.gov (United States)

    Rakvic, Ryan N.; Ives, Robert W.; Lira, Javier; Molina, Carlos

    2011-01-01

    General purpose computer designers have recently begun adding cores to their processors in order to increase performance. For example, Intel has adopted a homogeneous quad-core processor as a base for general purpose computing. PlayStation3 (PS3) game consoles contain a multicore heterogeneous processor known as the Cell, which is designed to perform complex image processing algorithms at a high level. Can modern image-processing algorithms utilize these additional cores? On the other hand, modern advancements in configurable hardware, most notably field-programmable gate arrays (FPGAs) have created an interesting question for general purpose computer designers. Is there a reason to combine FPGAs with multicore processors to create an FPGA multicore hybrid general purpose computer? Iris matching, a repeatedly executed portion of a modern iris-recognition algorithm, is parallelized on an Intel-based homogeneous multicore Xeon system, a heterogeneous multicore Cell system, and an FPGA multicore hybrid system. Surprisingly, the cheaper PS3 slightly outperforms the Intel-based multicore on a core-for-core basis. However, both multicore systems are beaten by the FPGA multicore hybrid system by >50%.

  6. SFC Optimization for Aero Engine Based on Hybrid GA-SQP Method

    Science.gov (United States)

    Li, Jie; Fan, Ding; Sreeram, Victor

    2013-12-01

    This study focuses on on-line specific fuel consumption (SFC) optimization of aero engines. For solving this optimization problem, a nonlinear pneumatic and thermodynamics model of the aero engine is built and a hybrid optimization technique which is formed by combining the genetic algorithm (GA) and the sequential quadratic programming (SQP) is presented. The ability of standard GA and standard SQP in solving this type of problem is investigated. It has been found that, although the SQP is fast, very little SFC reductions can be obtained. The GA is able to solve the problem well but a lot of computational time is needed. The presented hybrid GA-SQP gives a good SFC optimization effect and saves 76.6% computational time when compared to the standard GA. It has been shown that the hybrid GA-SQP is a more effective and higher real-time method for SFC on-line optimization of the aero engine.

  7. PV-HYBRID and MINI-GRID. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2006-07-01

    design and validation of PV-hybrid sysem technology for rural electrification programmes in remote areas of Europe (Xavier Valive); (17) Analysis of inverter-controlled Island grids - transient simulations with ATP-EMTP and PowerFactory (Martin Braun); (18) Design of a PV-diesel hybrid energy system (William Lawrance); (19) Hybrid storage systems in PV stand alone applications impact on sizing and performance (Julien Labbe); (20) Sizing and analysis of a small hydro PV hybrid system for the rural electrification in developing countries (Joseph Kenfack); (21) Identification of dynamic equivalents for microgrids with high penetration of solar energy using ANNs (F.O. Resende); (22) Constructing village PV hybrid power systems on a wide-scale in Western China: Experience gained (Henrik Bindner); (23) Experiences with large-scale construction of PH hybrid village power systems in Western China (Winfried Klinghammer); (24) A detailed data based analysis of the behaviour of a 10+5+20 KW wind-PV-diesel hybrid sysem (Luis M. Arribas); (25) PV hybrid village electrification in French Guyana (Christian Dumbs); (26) Energy consumption patterns in village PV-diesel-hybrid systems (Javier Munoz); (27) From Subag to Ponelo hybrid photovoltaic-diesel system in Indonesia, lessons learned (Adjat Sudradjat); (28) PV diesel hybrid system in rural Africa - an inter-disciplinary approach (Markus Landau); (29) Making PV-diesel hybrids and PV or wind mini-grids sustainable in remote developing country sites: the Nabouwalu case (Philippe Veyan); (30) Mini-grid for an isolated island sandwip in Bangladesh (B.K. Bala).

  8. Hybrid mimics and hybrid vigor in Arabidopsis

    Science.gov (United States)

    Wang, Li; Greaves, Ian K.; Groszmann, Michael; Wu, Li Min; Dennis, Elizabeth S.; Peacock, W. James

    2015-01-01

    F1 hybrids can outperform their parents in yield and vegetative biomass, features of hybrid vigor that form the basis of the hybrid seed industry. The yield advantage of the F1 is lost in the F2 and subsequent generations. In Arabidopsis, from F2 plants that have a F1-like phenotype, we have by recurrent selection produced pure breeding F5/F6 lines, hybrid mimics, in which the characteristics of the F1 hybrid are stabilized. These hybrid mimic lines, like the F1 hybrid, have larger leaves than the parent plant, and the leaves have increased photosynthetic cell numbers, and in some lines, increased size of cells, suggesting an increased supply of photosynthate. A comparison of the differentially expressed genes in the F1 hybrid with those of eight hybrid mimic lines identified metabolic pathways altered in both; these pathways include down-regulation of defense response pathways and altered abiotic response pathways. F6 hybrid mimic lines are mostly homozygous at each locus in the genome and yet retain the large F1-like phenotype. Many alleles in the F6 plants, when they are homozygous, have expression levels different to the level in the parent. We consider this altered expression to be a consequence of transregulation of genes from one parent by genes from the other parent. Transregulation could also arise from epigenetic modifications in the F1. The pure breeding hybrid mimics have been valuable in probing the mechanisms of hybrid vigor and may also prove to be useful hybrid vigor equivalents in agriculture. PMID:26283378

  9. Hybrid Multilevel Monte Carlo Simulation of Stochastic Reaction Networks

    KAUST Repository

    Moraes, Alvaro

    2015-01-01

    even more, we want to achieve this objective with near optimal computational work. We first introduce a hybrid path-simulation scheme based on the well-known stochastic simulation algorithm (SSA)[3] and the tau-leap method [2]. Then, we introduce a Multilevel Monte Carlo strategy that allows us to achieve a computational complexity of order O(T OL−2), this is the same computational complexity as in an exact method but with a smaller constant. We provide numerical examples to show our results.

  10. Identification of genetic loci in Lactobacillus plantarum that modulate the immune response of dendritic cells using comparative genome hybridization.

    Directory of Open Access Journals (Sweden)

    Marjolein Meijerink

    Full Text Available BACKGROUND: Probiotics can be used to stimulate or regulate epithelial and immune cells of the intestinal mucosa and generate beneficial mucosal immunomodulatory effects. Beneficial effects of specific strains of probiotics have been established in the treatment and prevention of various intestinal disorders, including allergic diseases and diarrhea. However, the precise molecular mechanisms and the strain-dependent factors involved are poorly understood. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we aimed to identify gene loci in the model probiotic organism Lactobacillus plantarum WCFS1 that modulate the immune response of host dendritic cells. The amounts of IL-10 and IL-12 secreted by dendritic cells (DCs after stimulation with 42 individual L. plantarum strains were measured and correlated with the strain-specific genomic composition using comparative genome hybridisation and the Random Forest algorithm. This in silico "gene-trait matching" approach led to the identification of eight candidate genes in the L. plantarum genome that might modulate the DC cytokine response to L. plantarum. Six of these genes were involved in bacteriocin production or secretion, one encoded a bile salt hydrolase and one encoded a transcription regulator of which the exact function is unknown. Subsequently, gene deletions mutants were constructed in L. plantarum WCFS1 and compared to the wild-type strain in DC stimulation assays. All three bacteriocin mutants as well as the transcription regulator (lp_2991 had the predicted effect on cytokine production confirming their immunomodulatory effect on the DC response to L. plantarum. Transcriptome analysis and qPCR data showed that transcript level of gtcA3, which is predicted to be involved in glycosylation of cell wall teichoic acids, was substantially increased in the lp_2991 deletion mutant (44 and 29 fold respectively. CONCLUSION: Comparative genome hybridization led to the identification of gene loci in L

  11. Safety Verification for Probabilistic Hybrid Systems

    Czech Academy of Sciences Publication Activity Database

    Zhang, J.; She, Z.; Ratschan, Stefan; Hermanns, H.; Hahn, E.M.

    2012-01-01

    Roč. 18, č. 6 (2012), s. 572-587 ISSN 0947-3580 R&D Projects: GA MŠk OC10048; GA ČR GC201/08/J020 Institutional research plan: CEZ:AV0Z10300504 Keywords : model checking * hybrid system s * formal verification Subject RIV: IN - Informatics, Computer Science Impact factor: 1.250, year: 2012

  12. A Hybrid Chaotic Quantum Evolutionary Algorithm

    DEFF Research Database (Denmark)

    Cai, Y.; Zhang, M.; Cai, H.

    2010-01-01

    A hybrid chaotic quantum evolutionary algorithm is proposed to reduce amount of computation, speed up convergence and restrain premature phenomena of quantum evolutionary algorithm. The proposed algorithm adopts the chaotic initialization method to generate initial population which will form a pe...... tests. The presented algorithm is applied to urban traffic signal timing optimization and the effect is satisfied....

  13. Compression of Born ratio for fluorescence molecular tomography/x-ray computed tomography hybrid imaging: methodology and in vivo validation.

    Science.gov (United States)

    Mohajerani, Pouyan; Ntziachristos, Vasilis

    2013-07-01

    The 360° rotation geometry of the hybrid fluorescence molecular tomography/x-ray computed tomography modality allows for acquisition of very large datasets, which pose numerical limitations on the reconstruction. We propose a compression method that takes advantage of the correlation of the Born-normalized signal among sources in spatially formed clusters to reduce the size of system model. The proposed method has been validated using an ex vivo study and an in vivo study of a nude mouse with a subcutaneous 4T1 tumor, with and without inclusion of a priori anatomical information. Compression rates of up to two orders of magnitude with minimum distortion of reconstruction have been demonstrated, resulting in large reduction in weight matrix size and reconstruction time.

  14. A portable system for nuclear, chemical agent, and explosives identification

    International Nuclear Information System (INIS)

    Parker, W.E.; Buckley, W.M.; Kreek, S.A.; Mauger, G.J.; Lavietes, A.D.; Dougan, A.D.; Caffrey, A.J.

    2001-01-01

    The FRIS/PINS hybrid integrates the LLNL-developed Field Radionuclide Identification System (FRIS) with the INEEL-developed Portable Isotopic Neutron Spectroscopy (PINS) chemical assay system to yield a combined general radioisotope, special nuclear material, and chemical weapons/explosives detection and identification system. The PINS system uses a neutron source and a high-purity germanium γ-ray detector. The FRIS system uses an electromechanically cooled germanium detector and its own analysis software to detect and identify special nuclear material and other radioisotopes. The FRIS/PINS combined system also uses the electromechanically-cooled germanium detector. There is no other currently available integrated technology that can combine a prompt-gamma neutron-activation analysis capability for CWE with a passive radioisotope measurement and identification capability for special nuclear material

  15. A Portable System for Nuclear, Chemical Agent and Explosives Identification

    International Nuclear Information System (INIS)

    Parker, W.E.; Buckley, W.M.; Kreek, S.A.; Caffrey, A.J.; Mauger, G.J.; Lavietes, A.D.; Dougan, A.D.

    2000-01-01

    The FRIS/PINS hybrid integrates the LLNL-developed Field Radionuclide Identification System (FRIS) with the INEEL-developed Portable Isotopic Neutron Spectroscopy (PINS) chemical assay system to yield a combined general radioisotope, special nuclear material, and chemical weapons/explosives detection and identification system. The PINS system uses a neutron source and a high-purity germanium γ-ray detector. The FRIS system uses an electrochemically cooled germanium detector and its own analysis software to detect and identify special nuclear material and other radioisotopes. The FRIS/PINS combined system also uses the electromechanically-cooled germanium detector. There is no other currently available integrated technology that can combine an active neutron interrogation and analysis capability for CWE with a passive radioisotope measurement and identification capability for special nuclear material

  16. Optical conoscopy of distorted uniaxial liquid crystals: computer simulation and experiment

    OpenAIRE

    Yu.A.Nastishin; O.B.Dovgyi; O.G.Vlokh

    2001-01-01

    We propose an algorithm to compute the conoscopic pattern for distorted uniaxial liquid crystal cells. The computed conoscopic figures for several cells (homeotropic, planar, twist, hybrid, hybrid under an external field) are compared to the corresponding experimental conoscopic patterns. We demonstrate that conoscopy can be used for the characterization of the distorted nematic cells with the director deformations which can not be detected and unambigously characterized by direct microscopy ...

  17. Molecular identification and histopathological study of natural Streptococcus agalactiae infection in hybrid tilapia (Oreochromis niloticus).

    Science.gov (United States)

    Laith, A A; Ambak, Mohd Azmi; Hassan, Marina; Sheriff, Shahreza Md; Nadirah, Musa; Draman, Ahmad Shuhaimi; Wahab, Wahidah; Ibrahim, Wan Nurhafizah Wan; Aznan, Alia Syafiqah; Jabar, Amina; Najiah, Musa

    2017-01-01

    The main objective of this study was to emphasize on histopathological examinations and molecular identification of Streptococcus agalactiae isolated from natural infections in hybrid tilapia ( Oreochromis niloticus ) in Temerloh Pahang, Malaysia, as well as to determine the susceptibility of the pathogen strains to various currently available antimicrobial agents. The diseased fishes were observed for variable clinical signs including fin hemorrhages, alterations in behavior associated with erratic swimming, exophthalmia, and mortality. Tissue samples from the eyes, brain, kidney, liver, and spleen were taken for bacterial isolation. Identification of S. agalactiae was screened by biochemical methods and confirmed by VITEK 2 and 16S rRNA gene sequencing. The antibiogram profiling of the isolate was tested against 18 standard antibiotics included nitrofurantoin, flumequine, florfenicol, amoxylin, doxycycline, oleandomycin, tetracycline, ampicillin, lincomycin, colistin sulfate, oxolinic acid, novobiocin, spiramycin, erythromycin, fosfomycin, neomycin, gentamycin, and polymyxin B. The histopathological analysis of eyes, brain, liver, kidney, and spleen was observed for abnormalities related to S. agalactiae infection. The suspected colonies of S. agalactiae identified by biochemical methods was observed as Gram-positive chained cocci, β-hemolytic, and non-motile. The isolate was confirmed as S. agalactiae by VITEK 2 (99% similarity), reconfirmed by 16S rRNA gene sequencing (99% similarity) and deposited in GenBank with accession no. KT869025. The isolate was observed to be resistance to neomycin and gentamicin. The most consistent gross findings were marked hemorrhages, erosions of caudal fin, and exophthalmos. Microscopic examination confirmed the presence of marked congestion and infiltration of inflammatory cell in the eye, brain, kidney, liver, and spleen. Eye samples showed damage of the lens capsule, hyperemic and hemorrhagic choroid tissue, and retina

  18. Molecular identification and histopathological study of natural Streptococcus agalactiae infection in hybrid tilapia (Oreochromis niloticus

    Directory of Open Access Journals (Sweden)

    Laith Abdul Razzak

    2017-01-01

    Full Text Available Aim: The main objective of this study was to emphasize on histopathological examinations and molecular identification of Streptococcus agalactiae isolated from natural infections in hybrid tilapia (Oreochromis niloticus in Temerloh Pahang, Malaysia, as well as to determine the susceptibility of the pathogen strains to various currently available antimicrobial agents. Materials and Methods: The diseased fishes were observed for variable clinical signs including fin hemorrhages, alterations in behavior associated with erratic swimming, exophthalmia, and mortality. Tissue samples from the eyes, brain, kidney, liver, and spleen were taken for bacterial isolation. Identification of S. agalactiae was screened by biochemical methods and confirmed by VITEK 2 and 16S rRNA gene sequencing. The antibiogram profiling of the isolate was tested against 18 standard antibiotics included nitrofurantoin, flumequine, florfenicol, amoxylin, doxycycline, oleandomycin, tetracycline, ampicillin, lincomycin, colistin sulfate, oxolinic acid, novobiocin, spiramycin, erythromycin, fosfomycin, neomycin, gentamycin, and polymyxin B. The histopathological analysis of eyes, brain, liver, kidney, and spleen was observed for abnormalities related to S. agalactiae infection. Results: The suspected colonies of S. agalactiae identified by biochemical methods was observed as Gram-positive chained cocci, β-hemolytic, and non-motile. The isolate was confirmed as S. agalactiae by VITEK 2 (99% similarity, reconfirmed by 16S rRNA gene sequencing (99% similarity and deposited in GenBank with accession no. KT869025. The isolate was observed to be resistance to neomycin and gentamicin. The most consistent gross findings were marked hemorrhages, erosions of caudal fin, and exophthalmos. Microscopic examination confirmed the presence of marked congestion and infiltration of inflammatory cell in the eye, brain, kidney, liver, and spleen. Eye samples showed damage of the lens capsule

  19. COMPARISON OF PARALLEL AND SERIES HYBRID POWERTRAINS FOR TRANSIT BUS APPLICATION

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Zhiming [ORNL; Daw, C Stuart [ORNL; Smith, David E [ORNL; Jones, Perry T [ORNL; LaClair, Tim J [ORNL; Parks, II, James E [ORNL

    2016-01-01

    The fuel economy and emissions of both conventional and hybrid buses equipped with emissions aftertreatment were evaluated via computational simulation for six representative city bus drive cycles. Both series and parallel configurations for the hybrid case were studied. The simulation results indicate that series hybrid buses have the greatest overall advantage in fuel economy. The series and parallel hybrid buses were predicted to produce similar CO and HC tailpipe emissions but were also predicted to have reduced NOx tailpipe emissions compared to the conventional bus in higher speed cycles. For the New York bus cycle (NYBC), which has the lowest average speed among the cycles evaluated, the series bus tailpipe emissions were somewhat higher than they were for the conventional bus, while the parallel hybrid bus had significantly lower tailpipe emissions. All three bus powertrains were found to require periodic active DPF regeneration to maintain PM control. Plug-in operation of series hybrid buses appears to offer significant fuel economy benefits and is easily employed due to the relatively large battery capacity that is typical of the series hybrid configuration.

  20. Identification of strain fields in pure Al and hybrid Ni/Al metal foams using X-ray micro-tomography under loading

    International Nuclear Information System (INIS)

    Fíla, T.; Jiroušek, O.; Jung, A.; Kumpová, I.

    2016-01-01

    Hybrid foams are materials formed by a core from a standard open cell metal foam that is during the process of electrodeposition coated by a thin layer of different nanocrystalline metals. The material properties of the base metal foam are in this way modified resulting in higher plateau stress and, more importantly, by introduction of strain-rate dependence to its deformation response. In this paper, we used time-lapse X-ray micro-tomography for the mechanical characterization of Ni/Al hybrid foams (aluminium open cell foams with nickel coating layer). To fully understand the effects of the coating layer on the material's effective properties, we compared the compressive response of the base uncoated foam to the response of the material with coating thickness of 50 and 75 μm. Digital volume correlation (DVC) was applied to obtain volumetric strain fields of the deforming micro-structure up to the densification region of the deforming cellular structure. The analysis was performed as a compressive mechanical test with simultaneous observation using X-ray radiography and tomography. A custom design experimental device was used for compression of the foam specimens in several deformation states directly in the X-ray setup. Planar X-ray images were taken during the loading phases and a X-ray tomography was performed at the end of each loading phase (up to engineering strain 22%). The samples were irradiated using micro-focus reflection type X-ray tube and images were taken using a large area flat panel detector. Tomography reconstructions were used for an identification of a strain distribution in the foam using digital volumetric correlation. A comparison of the deformation response of the coated and the uncoated foam in uniaxial quasi-static compression is summarized in the paper.

  1. A novel methodology for non-linear system identification of battery cells used in non-road hybrid electric vehicles

    Science.gov (United States)

    Unger, Johannes; Hametner, Christoph; Jakubek, Stefan; Quasthoff, Marcus

    2014-12-01

    An accurate state of charge (SoC) estimation of a traction battery in hybrid electric non-road vehicles, which possess higher dynamics and power densities than on-road vehicles, requires a precise battery cell terminal voltage model. This paper presents a novel methodology for non-linear system identification of battery cells to obtain precise battery models. The methodology comprises the architecture of local model networks (LMN) and optimal model based design of experiments (DoE). Three main novelties are proposed: 1) Optimal model based DoE, which aims to high dynamically excite the battery cells at load ranges frequently used in operation. 2) The integration of corresponding inputs in the LMN to regard the non-linearities SoC, relaxation, hysteresis as well as temperature effects. 3) Enhancements to the local linear model tree (LOLIMOT) construction algorithm, to achieve a physical appropriate interpretation of the LMN. The framework is applicable for different battery cell chemistries and different temperatures, and is real time capable, which is shown on an industrial PC. The accuracy of the obtained non-linear battery model is demonstrated on cells with different chemistries and temperatures. The results show significant improvement due to optimal experiment design and integration of the battery non-linearities within the LMN structure.

  2. Hybrid NN/SVM Computational System for Optimizing Designs

    Science.gov (United States)

    Rai, Man Mohan

    2009-01-01

    A computational method and system based on a hybrid of an artificial neural network (NN) and a support vector machine (SVM) (see figure) has been conceived as a means of maximizing or minimizing an objective function, optionally subject to one or more constraints. Such maximization or minimization could be performed, for example, to optimize solve a data-regression or data-classification problem or to optimize a design associated with a response function. A response function can be considered as a subset of a response surface, which is a surface in a vector space of design and performance parameters. A typical example of a design problem that the method and system can be used to solve is that of an airfoil, for which a response function could be the spatial distribution of pressure over the airfoil. In this example, the response surface would describe the pressure distribution as a function of the operating conditions and the geometric parameters of the airfoil. The use of NNs to analyze physical objects in order to optimize their responses under specified physical conditions is well known. NN analysis is suitable for multidimensional interpolation of data that lack structure and enables the representation and optimization of a succession of numerical solutions of increasing complexity or increasing fidelity to the real world. NN analysis is especially useful in helping to satisfy multiple design objectives. Feedforward NNs can be used to make estimates based on nonlinear mathematical models. One difficulty associated with use of a feedforward NN arises from the need for nonlinear optimization to determine connection weights among input, intermediate, and output variables. It can be very expensive to train an NN in cases in which it is necessary to model large amounts of information. Less widely known (in comparison with NNs) are support vector machines (SVMs), which were originally applied in statistical learning theory. In terms that are necessarily

  3. Fluorescence in situ hybridization on human metaphase chromosomes detected by near-field scanning optical microscopy

    NARCIS (Netherlands)

    Moers, M.H.P.; Moers, M.H.P.; Kalle, W.H.J.; Kalle, W.H.J.; Ruiter, A.G.T.; Wiegant, J.C.A.G.; Raap, A.K.; Greve, Jan; de Grooth, B.G.; van Hulst, N.F.

    1996-01-01

    Fluorescence in situ hybridization o­n human metaphase chromosomes is detected by near-field scanning optical microscopy. This combination of cytochemical and scanning probe techniques enables the localization and identification of several fluorescently labelled genomic DNA fragments o­n a single

  4. Model Reduction of Hybrid Systems

    DEFF Research Database (Denmark)

    Shaker, Hamid Reza

    gramians. Generalized gramians are the solutions to the observability and controllability Lyapunov inequalities. In the first framework the projection matrices are found based on the common generalized gramians. This framework preserves the stability of the original switched system for all switching...... is guaranteed to be preserved for arbitrary switching signal. To compute the common generalized gramians linear matrix inequalities (LMI’s) need to be solved. These LMI’s are not always feasible. In order to solve the problem of conservatism, the second framework is presented. In this method the projection......High-Technological solutions of today are characterized by complex dynamical models. A lot of these models have inherent hybrid/switching structure. Hybrid/switched systems are powerful models for distributed embedded systems design where discrete controls are applied to continuous processes...

  5. Computer Identification of Symptomatic Deep Venous Thrombosis Associated with Peripherally Inserted Central Catheters

    Science.gov (United States)

    Evans, R. Scott; Linford, Lorraine H.; Sharp, Jamie H.; White, Gayle; Lloyd, James F.; Weaver, Lindell K.

    2007-01-01

    Peripherally inserted central catheters (PICCs) are considered a safe method to provide long-term antibiotic therapy, chemotherapy and nutrition support. Deep venous thrombosis (DVT) is a complication that requires early PICC removal, may extend hospitalization and can result in pulmonary embolism. PICC insertion teams strive to understand risk factors and develop methods to prevent DVTs. However, they can only manage what they can measure. At LDS Hospital, identification of PICC associated DVTs was dependent on verbal notification or manual surveillance of more than a thousand free-text vascular reports. Accurate DVT rates were not known which hindered prevention. We describe the development of a computer application (PICC-DVT monitor) to identify PICC associated DVTs each day. A one-year evaluation of the monitor by the PICC team and a review of 445 random vascular reports found a positive predictive value of 98%, sensitivity of 94%, specificity of 100% and a PICC team associated DVT rate of 2.8%. PMID:18693831

  6. Computer identification of symptomatic deep venous thrombosis associated with peripherally inserted venous catheters.

    Science.gov (United States)

    Evans, R Scott; Linford, Lorraine H; Sharp, Jamie H; White, Gayle; Lloyd, James F; Weaver, Lindell K

    2007-10-11

    Peripherally inserted central catheters (PICCs) are considered a safe method to provide long-term antibiotic therapy, chemotherapy and nutrition support. Deep venous thrombosis (DVT) is a complication that requires early PICC removal, may extend hospitalization and can result in pulmonary embolism. PICC insertion teams strive to understand risk factors and develop methods to prevent DVTs. However, they can only manage what they can measure. At LDS Hospital, identification of PICC associated DVTs was dependent on verbal notification or manual surveillance of more than a thousand free-text vascular reports. Accurate DVT rates were not known which hindered prevention. We describe the development of a computer application (PICC-DVT monitor) to identify PICC associated DVTs each day. A one-year evaluation of the monitor by the PICC team and a review of 445 random vascular reports found a positive predictive value of 98%, sensitivity of 94%, specificity of 100% and a PICC team associated DVT rate of 2.8%.

  7. Hybrid incompatibilities in the parasitic wasp genus Nasonia : Negative effects of hemizygosity and the identification of transmission ratio distortion loci

    NARCIS (Netherlands)

    Koevoets, T.; Niehuis, O.; van de Zande, L.; Beukeboom, L. W.

    The occurrence of hybrid incompatibilities forms an important stage during the evolution of reproductive isolation. In early stages of speciation, males and females often respond differently to hybridization. Haldane's rule states that the heterogametic sex suffers more from hybridization than the

  8. Hybrid Predictive Control for Dynamic Transport Problems

    CERN Document Server

    Núñez, Alfredo A; Cortés, Cristián E

    2013-01-01

    Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from the area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed-integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: ●hybrid predictive control (HPC) ...

  9. An EEG/EOG-based hybrid brain-neural computer interaction (BNCI) system to control an exoskeleton for the paralyzed hand.

    Science.gov (United States)

    Soekadar, Surjo R; Witkowski, Matthias; Vitiello, Nicola; Birbaumer, Niels

    2015-06-01

    The loss of hand function can result in severe physical and psychosocial impairment. Thus, compensation of a lost hand function using assistive robotics that can be operated in daily life is very desirable. However, versatile, intuitive, and reliable control of assistive robotics is still an unsolved challenge. Here, we introduce a novel brain/neural-computer interaction (BNCI) system that integrates electroencephalography (EEG) and electrooculography (EOG) to improve control of assistive robotics in daily life environments. To evaluate the applicability and performance of this hybrid approach, five healthy volunteers (HV) (four men, average age 26.5 ± 3.8 years) and a 34-year-old patient with complete finger paralysis due to a brachial plexus injury (BPI) used EEG (condition 1) and EEG/EOG (condition 2) to control grasping motions of a hand exoskeleton. All participants were able to control the BNCI system (BNCI control performance HV: 70.24 ± 16.71%, BPI: 65.93 ± 24.27%), but inclusion of EOG significantly improved performance across all participants (HV: 80.65 ± 11.28, BPI: 76.03 ± 18.32%). This suggests that hybrid BNCI systems can achieve substantially better control over assistive devices, e.g., a hand exoskeleton, than systems using brain signals alone and thus may increase applicability of brain-controlled assistive devices in daily life environments.

  10. Wave propagation near the lower hybrid resonance in toroidal plasmas

    International Nuclear Information System (INIS)

    Ohkubo, K.; Ohasa, K.; Matsuura, K.

    1975-10-01

    Dielectric tensor and equipotential curves (ray trajectories) of an electrostatic wave near the lower hybrid resonance are investigated for the toroidal plasma with a shear magnetic field. The ray trajectories start from the vicinity of the plasma surface, and rotate in a spiral form around the magnetic axis, and then reach the lower or upper parts of lower hybrid resonance layer. The numerical computations are performed on the parameters of JIPP T-II device with two dimensional inhomogeneity. (auth.)

  11. Evaluation of models generated via hybrid evolutionary algorithms ...

    African Journals Online (AJOL)

    2016-04-02

    Apr 2, 2016 ... Evaluation of models generated via hybrid evolutionary algorithms for the prediction of Microcystis ... evolutionary algorithms (HEA) proved to be highly applica- ble to the hypertrophic reservoirs of South Africa. .... discovered and optimised using a large-scale parallel computational device and relevant soft-.

  12. A hybrid absorbing boundary condition for frequency-domain finite-difference modelling

    International Nuclear Information System (INIS)

    Ren, Zhiming; Liu, Yang

    2013-01-01

    Liu and Sen (2010 Geophysics 75 A1–6; 2012 Geophys. Prospect. 60 1114–32) proposed an efficient hybrid scheme to significantly absorb boundary reflections for acoustic and elastic wave modelling in the time domain. In this paper, we extend the hybrid absorbing boundary condition (ABC) into the frequency domain and develop specific strategies for regular-grid and staggered-grid modelling, respectively. Numerical modelling tests of acoustic, visco-acoustic, elastic and vertically transversely isotropic (VTI) equations show significant absorptions for frequency-domain modelling. The modelling results of the Marmousi model and the salt model also demonstrate the effectiveness of the hybrid ABC. For elastic modelling, the hybrid Higdon ABC and the hybrid Clayton and Engquist (CE) ABC are implemented, respectively. Numerical simulations show that the hybrid Higdon ABC gets better absorption than the hybrid CE ABC, especially for S-waves. We further compare the hybrid ABC with the classical perfectly matched layer (PML). Results show that the two ABCs cost the same computation time and memory space for the same absorption width. However, the hybrid ABC is more effective than the PML for the same small absorption width and the absorption effects of the two ABCs gradually become similar when the absorption width is increased. (paper)

  13. Hybrid variational principles and synthesis method for finite element neutron transport calculations

    International Nuclear Information System (INIS)

    Ackroyd, R.T.; Nanneh, M.M.

    1990-01-01

    A family of hybrid variational principles is derived using a generalised least squares method. Neutron conservation is automatically satisfied for the hybrid principles employing two trial functions. No interfaces or reflection conditions need to be imposed on the independent even-parity trial function. For some hybrid principles a single trial function can be employed by relating one parity trial function to the other, using one of the parity transport equation in relaxed form. For other hybrid principles the trial functions can be employed sequentially. Synthesis of transport solutions, starting with the diffusion theory approximation, has been used as a way of reducing the scale of the computation that arises with established finite element methods for neutron transport. (author)

  14. A multigrid solution method for mixed hybrid finite elements

    Energy Technology Data Exchange (ETDEWEB)

    Schmid, W. [Universitaet Augsburg (Germany)

    1996-12-31

    We consider the multigrid solution of linear equations arising within the discretization of elliptic second order boundary value problems of the form by mixed hybrid finite elements. Using the equivalence of mixed hybrid finite elements and non-conforming nodal finite elements, we construct a multigrid scheme for the corresponding non-conforming finite elements, and, by this equivalence, for the mixed hybrid finite elements, following guidelines from Arbogast/Chen. For a rectangular triangulation of the computational domain, this non-conforming schemes are the so-called nodal finite elements. We explicitly construct prolongation and restriction operators for this type of non-conforming finite elements. We discuss the use of plain multigrid and the multilevel-preconditioned cg-method and compare their efficiency in numerical tests.

  15. Identification of clinically relevant viridans streptococci by an oligonucleotide array.

    Science.gov (United States)

    Chen, Chao Chien; Teng, Lee Jene; Kaiung, Seng; Chang, Tsung Chain

    2005-04-01

    Viridans streptococci (VS) are common etiologic agents of subacute infective endocarditis and are capable of causing a variety of pyogenic infections. Many species of VS are difficult to differentiate by phenotypic traits. An oligonucleotide array based on 16S-23S rRNA gene intergenic spacer (ITS) sequences was developed to identify 11 clinically relevant VS. These 11 species were Streptococcus anginosus, S. constellatus, S. gordonii, S. intermedius, S. mitis, S. mutans, S. oralis, S. parasanguinis, S. salivarius, S. sanguinis, and S. uberis. The method consisted of PCR amplification of the ITS regions by using a pair of universal primers, followed by hybridization of the digoxigenin-labeled PCR products to a panel of species-specific oligonucleotides immobilized on a nylon membrane. After 120 strains of the 11 species of VG and 91 strains of other bacteria were tested, the sensitivity and specificity of the oligonucleotide array were found to be 100% (120 of 120 strains) and 95.6% (87 of 91 strains), respectively. S. pneumoniae cross-hybridized to the probes used for the identification of S. mitis, and simple biochemical tests such as optochin susceptibility or bile solubility should be used to differentiate S. pneumoniae from S. mitis. In conclusion, identification of species of VS by use of the present oligonucleotide array is accurate and could be used as an alternative reliable method for species identification of strains of VS.

  16. High-frequency electromagnetic properties of soft magnetic metal-polyimide hybrid thin films

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sang Woo [Nano-Materials Research Center, Korea Institute of Science and Technology, 39-1 Haweoulgog-dong, Sungbuk-gu, Seoul 136-791 (Korea, Republic of)]. E-mail: swkim@kist.re.kr; Yoon, Chong S. [Division of Advanced Materials Science, Hanyang University, Seoul 133-791 (Korea, Republic of)

    2007-09-15

    Although there are a lot of demands for suppression of unwanted high-frequency electromagnetic noise in highly integrated electronic devices such as mobile phones and notebook computers, electromagnetic thin films that effectively work in the high-frequency range have still been underdeveloped. Soft magnetic metal-polyimide (PI) hybrid films with high electrical resistivity were prepared by thermal imidization and selective oxidation between the metal alloy layer and polyamic acid (PAA) layer. Electromagnetic properties of the hybrid thin films in the radio-frequency range were characterized by using the microstrip line method and were correlated with their material parameters. Although anisotropy field of the CoFe/NiFe hybrid film was two times lower than that of the NiFe hybrid film, the saturation magnetization of the CoFe/NiFe hybrid film was three times higher than that of the NiFe hybrid film. The CoFe/NiFe hybrid film showed higher power loss in the frequency range of 3-6 GHz compared to the NiFe hybrid film. The high power loss of the CoFe/NiFe hybrid film was caused by high relative permeability and high ferromagnetic resonance (FMR) frequency due to high saturation magnetization.

  17. High-frequency electromagnetic properties of soft magnetic metal-polyimide hybrid thin films

    International Nuclear Information System (INIS)

    Kim, Sang Woo; Yoon, Chong S.

    2007-01-01

    Although there are a lot of demands for suppression of unwanted high-frequency electromagnetic noise in highly integrated electronic devices such as mobile phones and notebook computers, electromagnetic thin films that effectively work in the high-frequency range have still been underdeveloped. Soft magnetic metal-polyimide (PI) hybrid films with high electrical resistivity were prepared by thermal imidization and selective oxidation between the metal alloy layer and polyamic acid (PAA) layer. Electromagnetic properties of the hybrid thin films in the radio-frequency range were characterized by using the microstrip line method and were correlated with their material parameters. Although anisotropy field of the CoFe/NiFe hybrid film was two times lower than that of the NiFe hybrid film, the saturation magnetization of the CoFe/NiFe hybrid film was three times higher than that of the NiFe hybrid film. The CoFe/NiFe hybrid film showed higher power loss in the frequency range of 3-6 GHz compared to the NiFe hybrid film. The high power loss of the CoFe/NiFe hybrid film was caused by high relative permeability and high ferromagnetic resonance (FMR) frequency due to high saturation magnetization

  18. Quality parameters and RAPD-PCR differentiation of commercial baker's yeast and hybrid strains.

    Science.gov (United States)

    El-Fiky, Zaki A; Hassan, Gamal M; Emam, Ahmed M

    2012-06-01

    Baker's yeast, Saccharomyces cerevisiae, is a key component in bread baking. Total of 12 commercial baker's yeast and 2 hybrid strains were compared using traditional quality parameters. Total of 5 strains with high leavening power and the 2 hybrid strains were selected and evaluated for their alpha-amylase, maltase, glucoamylase enzymes, and compared using random amplified polymorphic DNA (RAPD). The results revealed that all selected yeast strains have a low level of alpha-amylase and a high level of maltase and glucoamylase enzymes. Meanwhile, the Egyptian yeast strain (EY) had the highest content of alpha-amylase and maltase enzymes followed by the hybrid YH strain. The EY and YH strains have the highest content of glucoamylase enzyme almost with the same level. The RAPD banding patterns showed a wide variation among commercial yeast and hybrid strains. The closely related Egyptian yeast strains (EY and AL) demonstrated close similarity of their genotypes. The 2 hybrid strains were clustered to Turkish and European strains in 1 group. The authors conclude that the identification of strains and hybrids using RAPD technique was useful in determining their genetic relationship. These results can be useful not only for the basic research, but also for the quality control in baking factories. © 2012 Institute of Food Technologists®

  19. Modelling and Verifying Communication Failure of Hybrid Systems in HCSP

    DEFF Research Database (Denmark)

    Wang, Shuling; Nielson, Flemming; Nielson, Hanne Riis

    2016-01-01

    Hybrid systems are dynamic systems with interacting discrete computation and continuous physical processes. They have become ubiquitous in our daily life, e.g. automotive, aerospace and medical systems, and in particular, many of them are safety-critical. For a safety-critical hybrid system......, in the presence of communication failure, the expected control from the controller will get lost and as a consequence the physical process cannot behave as expected. In this paper, we mainly consider the communication failure caused by the non-engagement of one party in communication action, i.......e. the communication itself fails to occur. To address this issue, this paper proposes a formal framework by extending HCSP, a formal modeling language for hybrid systems, for modeling and verifying hybrid systems in the absence of receiving messages due to communication failure. We present two inference systems...

  20. Optical computing.

    Science.gov (United States)

    Stroke, G. W.

    1972-01-01

    Applications of the optical computer include an approach for increasing the sharpness of images obtained from the most powerful electron microscopes and fingerprint/credit card identification. The information-handling capability of the various optical computing processes is very great. Modern synthetic-aperture radars scan upward of 100,000 resolvable elements per second. Fields which have assumed major importance on the basis of optical computing principles are optical image deblurring, coherent side-looking synthetic-aperture radar, and correlative pattern recognition. Some examples of the most dramatic image deblurring results are shown.

  1. Molecular cytogenetic identification of a novel dwarf wheat line with ...

    Indian Academy of Sciences (India)

    2012-01-08

    Jan 8, 2012 ... of a pAs1 hybridization band on 2DL chromosome of 31505-1. Two SSR ... [Chen G, Zheng Q, Bao Y, Liu S, Wang H and Li X 2012 Molecular cytogenetic identification of a novel dwarf wheat line with ..... translocations (Fedak and Han 2005; Li et al. ... growth (Cambridge, UK: Cambridge University Press).

  2. Mapping the Most Significant Computer Hacking Events to a Temporal Computer Attack Model

    OpenAIRE

    Heerden , Renier ,; Pieterse , Heloise; Irwin , Barry

    2012-01-01

    Part 4: Section 3: ICT for Peace and War; International audience; This paper presents eight of the most significant computer hacking events (also known as computer attacks). These events were selected because of their unique impact, methodology, or other properties. A temporal computer attack model is presented that can be used to model computer based attacks. This model consists of the following stages: Target Identification, Reconnaissance, Attack, and Post-Attack Reconnaissance stages. The...

  3. Neutronics issues in fusion-fission hybrid reactor design

    International Nuclear Information System (INIS)

    Liu Chengan

    1995-01-01

    The coupled neutron and γ-ray transport equations and nuclear number density equations, and its computer program systems concerned in fusion-fission hybrid reactor design are briefly described. The current status and focal point for coming work of nuclear data used in fusion reactor design are explained

  4. Computationally Probing the Performance of Hybrid, Heterogeneous, and Homogeneous Iridium-Based Catalysts for Water Oxidation

    Energy Technology Data Exchange (ETDEWEB)

    García-Melchor, Max [SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford CA (United States); Vilella, Laia [Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology (BIST),Tarragona (Spain); Departament de Quimica, Universitat Autonoma de Barcelona, Barcelona (Spain); López, Núria [Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology (BIST), Tarragona (Spain); Vojvodic, Aleksandra [SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park CA (United States)

    2016-04-29

    An attractive strategy to improve the performance of water oxidation catalysts would be to anchor a homogeneous molecular catalyst on a heterogeneous solid surface to create a hybrid catalyst. The idea of this combined system is to take advantage of the individual properties of each of the two catalyst components. We use Density Functional Theory to determine the stability and activity of a model hybrid water oxidation catalyst consisting of a dimeric Ir complex attached on the IrO2(110) surface through two oxygen atoms. We find that homogeneous catalysts can be bound to its matrix oxide without losing significant activity. Hence, designing hybrid systems that benefit from both the high tunability of activity of homogeneous catalysts and the stability of heterogeneous systems seems feasible.

  5. Primary Pulmonary Synovial Sarcoma: A Case with Unique and Impressive Computed Tomography Findings

    Directory of Open Access Journals (Sweden)

    Jaspreet S Kambo

    2015-01-01

    Full Text Available Primary pulmonary synovial sarcoma (PPSS is a rare malignancy. Its etiology, imaging features and optimal treatment are not well understood. Pulmonary pseudoaneurysms and lymphadenopathy are rare complications of synovial sarcomas. A 40-year-old woman with mild hemoptysis and thoracic back pain underwent a computed tomography scan that revealed multiple pulmonary lesions, paraesophageal lymphadenopathy and incidental bilateral pulmonary emboli. A diagnosis of PPSS was made through the identification of an SS18 translocation by fluorescence in situ hybridization. She was started on adriamycin, ifosfamide and mesna chemotherapy. Over the subsequent two months, she developed three pulmonary artery pseudoaneurysms, ultimately requiring endovascular coiling. Seven months after starting treatment, the patient was asymptomatic. The lesions and lymphadenopathy decreased in size. The present case highlights complications of a rare malignancy and demonstrates positive response to ifosfamide-based chemotherapy in the setting of PPSS.

  6. A novel field method to distinguish between cryptic carcharhinid sharks, Australian blacktip shark Carcharhinus tilstoni and common blacktip shark C. limbatus, despite the presence of hybrids.

    Science.gov (United States)

    Johnson, G J; Buckworth, R C; Lee, H; Morgan, J A T; Ovenden, J R; McMahon, C R

    2017-01-01

    Multivariate and machine-learning methods were used to develop field identification techniques for two species of cryptic blacktip shark. From 112 specimens, precaudal vertebrae (PCV) counts and molecular analysis identified 95 Australian blacktip sharks Carcharhinus tilstoni and 17 common blacktip sharks Carcharhinus limbatus. Molecular analysis also revealed 27 of the 112 were C. tilstoni × C. limbatus hybrids, of which 23 had C. tilstoni PCV counts and four had C. limbatus PCV counts. In the absence of further information about hybrid phenotypes, hybrids were assigned as either C. limbatus or C. tilstoni based on PCV counts. Discriminant analysis achieved 80% successful identification, but machine-learning models were better, achieving 100% successful identification, using six key measurements (fork length, caudal-fin peduncle height, interdorsal space, second dorsal-fin height, pelvic-fin length and pelvic-fin midpoint to first dorsal-fin insertion). Furthermore, pelvic-fin markings could be used for identification: C. limbatus has a distinct black mark >3% of the total pelvic-fin area, while C. tilstoni has markings with diffuse edges, or has smaller or no markings. Machine learning and pelvic-fin marking identification methods were field tested achieving 87 and 90% successful identification, respectively. With further refinement, the techniques developed here will form an important part of a multi-faceted approach to identification of C. tilstoni and C. limbatus and have a clear management and conservation application to these commercially important sharks. The methods developed here are broadly applicable and can be used to resolve species identities in many fisheries where cryptic species exist. © 2016 The Fisheries Society of the British Isles.

  7. Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

    Directory of Open Access Journals (Sweden)

    Laszlo Papp

    2018-06-01

    Full Text Available Medical imaging has evolved from a pure visualization tool to representing a primary source of analytic approaches toward in vivo disease characterization. Hybrid imaging is an integral part of this approach, as it provides complementary visual and quantitative information in the form of morphological and functional insights into the living body. As such, non-invasive imaging modalities no longer provide images only, but data, as stated recently by pioneers in the field. Today, such information, together with other, non-imaging medical data creates highly heterogeneous data sets that underpin the concept of medical big data. While the exponential growth of medical big data challenges their processing, they inherently contain information that benefits a patient-centric personalized healthcare. Novel machine learning approaches combined with high-performance distributed cloud computing technologies help explore medical big data. Such exploration and subsequent generation of knowledge require a profound understanding of the technical challenges. These challenges increase in complexity when employing hybrid, aka dual- or even multi-modality image data as input to big data repositories. This paper provides a general insight into medical big data analysis in light of the use of hybrid imaging information. First, hybrid imaging is introduced (see further contributions to this special Research Topic, also in the context of medical big data, then the technological background of machine learning as well as state-of-the-art distributed cloud computing technologies are presented, followed by the discussion of data preservation and data sharing trends. Joint data exploration endeavors in the context of in vivo radiomics and hybrid imaging will be presented. Standardization challenges of imaging protocol, delineation, feature engineering, and machine learning evaluation will be detailed. Last, the paper will provide an outlook into the future role of hybrid

  8. Special Issue: New trends and applications on hybrid artificial intelligence systems

    OpenAIRE

    Corchado Rodríguez, Emilio; Graña Romay, Manuel; Woźniak, MichaŁ

    2017-01-01

    This Special Issue is an outgrowth of the HAIS'10, the 5th International Conference on Hybrid Artificial Intelligence Systems, which was held in San Sebastián, Spain, 23–25 June 2010. The HAIS conference series is devoted to the presentation of innovative techniques involving the hybridization of emerging and active topics in data mining and decision support systems, information fusion, evolutionary computation, visualization techniques, ensemble models, intelligent agent-based systems (compl...

  9. Prediction of industrial tomato hybrids from agronomic traits and ISSR molecular markers.

    Science.gov (United States)

    Figueiredo, A S T; Resende, J T V; Faria, M V; Da-Silva, P R; Fagundes, B S; Morales, R G F

    2016-05-13

    Heterosis is a highly relevant phenomenon in plant breeding. This condition is usually established in hybrids derived from crosses of highly divergent parents. The success of a breeder in obtaining heterosis is directly related to the correct identification of genetically contrasting parents. Currently, the diallel cross is the most commonly used methodology to detect contrasting parents; however, it is a time- and cost-consuming procedure. Therefore, new tools capable of performing this task quickly and accurately are required. Thus, the purpose of this study was to estimate the genetic divergence in industrial tomato lines, based on agronomic traits, and to compare with estimates obtained using inter-simple sequence repeat (ISSR) molecular markers. The genetic divergence among 10 industrial tomato lines, based on nine morphological characters and 12 ISSR primers was analyzed. For data analysis, Pearson and Spearman correlation coefficients were calculated between the genetic dissimilarity measures estimated by Mahalanobis distance and Jaccard's coefficient of genetic dissimilarity from the heterosis estimates, combining ability, and means of important traits of industrial tomato. The ISSR markers efficiently detected contrasting parents for hybrid production in tomato. Parent RVTD-08 was indicated as the most divergent, both by molecular and morphological markers, that positively contributed to increased heterosis and by the specific combining ability in the crosses in which it participated. The genetic dissimilarity estimated by ISSR molecular markers aided the identification of the best hybrids of the experiment in terms of total fruit yield, pulp yield, and soluble solids content.

  10. Computer vision based room interior design

    Science.gov (United States)

    Ahmad, Nasir; Hussain, Saddam; Ahmad, Kashif; Conci, Nicola

    2015-12-01

    This paper introduces a new application of computer vision. To the best of the author's knowledge, it is the first attempt to incorporate computer vision techniques into room interior designing. The computer vision based interior designing is achieved in two steps: object identification and color assignment. The image segmentation approach is used for the identification of the objects in the room and different color schemes are used for color assignment to these objects. The proposed approach is applied to simple as well as complex images from online sources. The proposed approach not only accelerated the process of interior designing but also made it very efficient by giving multiple alternatives.

  11. Mobile, hybrid Compton/coded aperture imaging for detection, identification and localization of gamma-ray sources at stand-off distances

    Science.gov (United States)

    Tornga, Shawn R.

    The Stand-off Radiation Detection System (SORDS) program is an Advanced Technology Demonstration (ATD) project through the Department of Homeland Security's Domestic Nuclear Detection Office (DNDO) with the goal of detection, identification and localization of weak radiological sources in the presence of large dynamic backgrounds. The Raytheon-SORDS Tri-Modal Imager (TMI) is a mobile truck-based, hybrid gamma-ray imaging system able to quickly detect, identify and localize, radiation sources at standoff distances through improved sensitivity while minimizing the false alarm rate. Reconstruction of gamma-ray sources is performed using a combination of two imaging modalities; coded aperture and Compton scatter imaging. The TMI consists of 35 sodium iodide (NaI) crystals 5x5x2 in3 each, arranged in a random coded aperture mask array (CA), followed by 30 position sensitive NaI bars each 24x2.5x3 in3 called the detection array (DA). The CA array acts as both a coded aperture mask and scattering detector for Compton events. The large-area DA array acts as a collection detector for both Compton scattered events and coded aperture events. In this thesis, developed coded aperture, Compton and hybrid imaging algorithms will be described along with their performance. It will be shown that multiple imaging modalities can be fused to improve detection sensitivity over a broader energy range than either alone. Since the TMI is a moving system, peripheral data, such as a Global Positioning System (GPS) and Inertial Navigation System (INS) must also be incorporated. A method of adapting static imaging algorithms to a moving platform has been developed. Also, algorithms were developed in parallel with detector hardware, through the use of extensive simulations performed with the Geometry and Tracking Toolkit v4 (GEANT4). Simulations have been well validated against measured data. Results of image reconstruction algorithms at various speeds and distances will be presented as well as

  12. Hybrid Arrays for Chemical Sensing

    Science.gov (United States)

    Kramer, Kirsten E.; Rose-Pehrsson, Susan L.; Johnson, Kevin J.; Minor, Christian P.

    In recent years, multisensory approaches to environment monitoring for chemical detection as well as other forms of situational awareness have become increasingly popular. A hybrid sensor is a multimodal system that incorporates several sensing elements and thus produces data that are multivariate in nature and may be significantly increased in complexity compared to data provided by single-sensor systems. Though a hybrid sensor is itself an array, hybrid sensors are often organized into more complex sensing systems through an assortment of network topologies. Part of the reason for the shift to hybrid sensors is due to advancements in sensor technology and computational power available for processing larger amounts of data. There is also ample evidence to support the claim that a multivariate analytical approach is generally superior to univariate measurements because it provides additional redundant and complementary information (Hall, D. L.; Linas, J., Eds., Handbook of Multisensor Data Fusion, CRC, Boca Raton, FL, 2001). However, the benefits of a multisensory approach are not automatically achieved. Interpretation of data from hybrid arrays of sensors requires the analyst to develop an application-specific methodology to optimally fuse the disparate sources of data generated by the hybrid array into useful information characterizing the sample or environment being observed. Consequently, multivariate data analysis techniques such as those employed in the field of chemometrics have become more important in analyzing sensor array data. Depending on the nature of the acquired data, a number of chemometric algorithms may prove useful in the analysis and interpretation of data from hybrid sensor arrays. It is important to note, however, that the challenges posed by the analysis of hybrid sensor array data are not unique to the field of chemical sensing. Applications in electrical and process engineering, remote sensing, medicine, and of course, artificial

  13. HybridGO-Loc: mining hybrid features on gene ontology for predicting subcellular localization of multi-location proteins.

    Science.gov (United States)

    Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

    2014-01-01

    Protein subcellular localization prediction, as an essential step to elucidate the functions in vivo of proteins and identify drugs targets, has been extensively studied in previous decades. Instead of only determining subcellular localization of single-label proteins, recent studies have focused on predicting both single- and multi-location proteins. Computational methods based on Gene Ontology (GO) have been demonstrated to be superior to methods based on other features. However, existing GO-based methods focus on the occurrences of GO terms and disregard their relationships. This paper proposes a multi-label subcellular-localization predictor, namely HybridGO-Loc, that leverages not only the GO term occurrences but also the inter-term relationships. This is achieved by hybridizing the GO frequencies of occurrences and the semantic similarity between GO terms. Given a protein, a set of GO terms are retrieved by searching against the gene ontology database, using the accession numbers of homologous proteins obtained via BLAST search as the keys. The frequency of GO occurrences and semantic similarity (SS) between GO terms are used to formulate frequency vectors and semantic similarity vectors, respectively, which are subsequently hybridized to construct fusion vectors. An adaptive-decision based multi-label support vector machine (SVM) classifier is proposed to classify the fusion vectors. Experimental results based on recent benchmark datasets and a new dataset containing novel proteins show that the proposed hybrid-feature predictor significantly outperforms predictors based on individual GO features as well as other state-of-the-art predictors. For readers' convenience, the HybridGO-Loc server, which is for predicting virus or plant proteins, is available online at http://bioinfo.eie.polyu.edu.hk/HybridGoServer/.

  14. Multi-level damage identification with response reconstruction

    Science.gov (United States)

    Zhang, Chao-Dong; Xu, You-Lin

    2017-10-01

    Damage identification through finite element (FE) model updating usually forms an inverse problem. Solving the inverse identification problem for complex civil structures is very challenging since the dimension of potential damage parameters in a complex civil structure is often very large. Aside from enormous computation efforts needed in iterative updating, the ill-condition and non-global identifiability features of the inverse problem probably hinder the realization of model updating based damage identification for large civil structures. Following a divide-and-conquer strategy, a multi-level damage identification method is proposed in this paper. The entire structure is decomposed into several manageable substructures and each substructure is further condensed as a macro element using the component mode synthesis (CMS) technique. The damage identification is performed at two levels: the first is at macro element level to locate the potentially damaged region and the second is over the suspicious substructures to further locate as well as quantify the damage severity. In each level's identification, the damage searching space over which model updating is performed is notably narrowed down, not only reducing the computation amount but also increasing the damage identifiability. Besides, the Kalman filter-based response reconstruction is performed at the second level to reconstruct the response of the suspicious substructure for exact damage quantification. Numerical studies and laboratory tests are both conducted on a simply supported overhanging steel beam for conceptual verification. The results demonstrate that the proposed multi-level damage identification via response reconstruction does improve the identification accuracy of damage localization and quantization considerably.

  15. Adaptive hybrid control of manipulators

    Science.gov (United States)

    Seraji, H.

    1987-01-01

    Simple methods for the design of adaptive force and position controllers for robot manipulators within the hybrid control architecuture is presented. The force controller is composed of an adaptive PID feedback controller, an auxiliary signal and a force feedforward term, and it achieves tracking of desired force setpoints in the constraint directions. The position controller consists of adaptive feedback and feedforward controllers and an auxiliary signal, and it accomplishes tracking of desired position trajectories in the free directions. The controllers are capable of compensating for dynamic cross-couplings that exist between the position and force control loops in the hybrid control architecture. The adaptive controllers do not require knowledge of the complex dynamic model or parameter values of the manipulator or the environment. The proposed control schemes are computationally fast and suitable for implementation in on-line control with high sampling rates.

  16. A hybrid time-domain discontinuous galerkin-boundary integral method for electromagnetic scattering analysis

    KAUST Repository

    Li, Ping; Shi, Yifei; Jiang, Lijun; Bagci, Hakan

    2014-01-01

    A scheme hybridizing discontinuous Galerkin time-domain (DGTD) and time-domain boundary integral (TDBI) methods for accurately analyzing transient electromagnetic scattering is proposed. Radiation condition is enforced using the numerical flux on the truncation boundary. The fields required by the flux are computed using the TDBI from equivalent currents introduced on a Huygens' surface enclosing the scatterer. The hybrid DGTDBI ensures that the radiation condition is mathematically exact and the resulting computation domain is as small as possible since the truncation boundary conforms to scatterer's shape and is located very close to its surface. Locally truncated domains can also be defined around each disconnected scatterer additionally reducing the size of the overall computation domain. Numerical examples demonstrating the accuracy and versatility of the proposed method are presented. © 2014 IEEE.

  17. A hybrid time-domain discontinuous galerkin-boundary integral method for electromagnetic scattering analysis

    KAUST Repository

    Li, Ping

    2014-05-01

    A scheme hybridizing discontinuous Galerkin time-domain (DGTD) and time-domain boundary integral (TDBI) methods for accurately analyzing transient electromagnetic scattering is proposed. Radiation condition is enforced using the numerical flux on the truncation boundary. The fields required by the flux are computed using the TDBI from equivalent currents introduced on a Huygens\\' surface enclosing the scatterer. The hybrid DGTDBI ensures that the radiation condition is mathematically exact and the resulting computation domain is as small as possible since the truncation boundary conforms to scatterer\\'s shape and is located very close to its surface. Locally truncated domains can also be defined around each disconnected scatterer additionally reducing the size of the overall computation domain. Numerical examples demonstrating the accuracy and versatility of the proposed method are presented. © 2014 IEEE.

  18. A hybrid fingerprint identification system for immigration control ...

    African Journals Online (AJOL)

    Journal of Computer Science and Its Application. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 21, No 2 (2014) >. Log in or Register to get access to full text downloads.

  19. Parallel Multivariate Spatio-Temporal Clustering of Large Ecological Datasets on Hybrid Supercomputers

    Energy Technology Data Exchange (ETDEWEB)

    Sreepathi, Sarat [ORNL; Kumar, Jitendra [ORNL; Mills, Richard T. [Argonne National Laboratory; Hoffman, Forrest M. [ORNL; Sripathi, Vamsi [Intel Corporation; Hargrove, William Walter [United States Department of Agriculture (USDA), United States Forest Service (USFS)

    2017-09-01

    A proliferation of data from vast networks of remote sensing platforms (satellites, unmanned aircraft systems (UAS), airborne etc.), observational facilities (meteorological, eddy covariance etc.), state-of-the-art sensors, and simulation models offer unprecedented opportunities for scientific discovery. Unsupervised classification is a widely applied data mining approach to derive insights from such data. However, classification of very large data sets is a complex computational problem that requires efficient numerical algorithms and implementations on high performance computing (HPC) platforms. Additionally, increasing power, space, cooling and efficiency requirements has led to the deployment of hybrid supercomputing platforms with complex architectures and memory hierarchies like the Titan system at Oak Ridge National Laboratory. The advent of such accelerated computing architectures offers new challenges and opportunities for big data analytics in general and specifically, large scale cluster analysis in our case. Although there is an existing body of work on parallel cluster analysis, those approaches do not fully meet the needs imposed by the nature and size of our large data sets. Moreover, they had scaling limitations and were mostly limited to traditional distributed memory computing platforms. We present a parallel Multivariate Spatio-Temporal Clustering (MSTC) technique based on k-means cluster analysis that can target hybrid supercomputers like Titan. We developed a hybrid MPI, CUDA and OpenACC implementation that can utilize both CPU and GPU resources on computational nodes. We describe performance results on Titan that demonstrate the scalability and efficacy of our approach in processing large ecological data sets.

  20. Unsteady computational fluid dynamics in aeronautics

    CERN Document Server

    Tucker, P G

    2014-01-01

    The field of Large Eddy Simulation (LES) and hybrids is a vibrant research area. This book runs through all the potential unsteady modelling fidelity ranges, from low-order to LES. The latter is probably the highest fidelity for practical aerospace systems modelling. Cutting edge new frontiers are defined.  One example of a pressing environmental concern is noise. For the accurate prediction of this, unsteady modelling is needed. Hence computational aeroacoustics is explored. It is also emerging that there is a critical need for coupled simulations. Hence, this area is also considered and the tensions of utilizing such simulations with the already expensive LES.  This work has relevance to the general field of CFD and LES and to a wide variety of non-aerospace aerodynamic systems (e.g. cars, submarines, ships, electronics, buildings). Topics treated include unsteady flow techniques; LES and hybrids; general numerical methods; computational aeroacoustics; computational aeroelasticity; coupled simulations and...