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Sample records for vector system based

  1. Prediction of Banking Systemic Risk Based on Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Shouwei Li

    2013-01-01

    Full Text Available Banking systemic risk is a complex nonlinear phenomenon and has shed light on the importance of safeguarding financial stability by recent financial crisis. According to the complex nonlinear characteristics of banking systemic risk, in this paper we apply support vector machine (SVM to the prediction of banking systemic risk in an attempt to suggest a new model with better explanatory power and stability. We conduct a case study of an SVM-based prediction model for Chinese banking systemic risk and find the experiment results showing that support vector machine is an efficient method in such case.

  2. Availability of thermodynamic system with multiple performance parameters based on vector-universal generating function

    International Nuclear Information System (INIS)

    Cai Qi; Shang Yanlong; Chen Lisheng; Zhao Yuguang

    2013-01-01

    Vector-universal generating function was presented to analyze the availability of thermodynamic system with multiple performance parameters. Vector-universal generating function of component's performance was defined, the arithmetic model based on vector-universal generating function was derived for the thermodynamic system, and the calculation method was given for state probability of multi-state component. With the stochastic simulation of the degeneration trend of the multiple factors, the system availability with multiple performance parameters was obtained under composite factors. It is shown by an example that the results of the availability obtained by the binary availability analysis method are somewhat conservative, and the results considering parameter failure based on vector-universal generating function reflect the operation characteristics of the thermodynamic system better. (authors)

  3. Virus Database and Online Inquiry System Based on Natural Vectors.

    Science.gov (United States)

    Dong, Rui; Zheng, Hui; Tian, Kun; Yau, Shek-Chung; Mao, Weiguang; Yu, Wenping; Yin, Changchuan; Yu, Chenglong; He, Rong Lucy; Yang, Jie; Yau, Stephen St

    2017-01-01

    We construct a virus database called VirusDB (http://yaulab.math.tsinghua.edu.cn/VirusDB/) and an online inquiry system to serve people who are interested in viral classification and prediction. The database stores all viral genomes, their corresponding natural vectors, and the classification information of the single/multiple-segmented viral reference sequences downloaded from National Center for Biotechnology Information. The online inquiry system serves the purpose of computing natural vectors and their distances based on submitted genomes, providing an online interface for accessing and using the database for viral classification and prediction, and back-end processes for automatic and manual updating of database content to synchronize with GenBank. Submitted genomes data in FASTA format will be carried out and the prediction results with 5 closest neighbors and their classifications will be returned by email. Considering the one-to-one correspondence between sequence and natural vector, time efficiency, and high accuracy, natural vector is a significant advance compared with alignment methods, which makes VirusDB a useful database in further research.

  4. Modelling and Simulation of SVPWM Based Vector Controlled HVDC Light Systems

    Directory of Open Access Journals (Sweden)

    Ajay Kumar MOODADLA

    2012-11-01

    Full Text Available Recent upgrades in power electronics technology have lead to the improvements of insulated gate bipolar transistor (IGBT based Voltage source converter High voltage direct current (VSC HVDC transmission systems. These are also commercially known as HVDC Light systems, which are popular in renewable, micro grid, and electric power systems. Out of different pulse width modulation (PWM schemes, Space vector PWM (SVPWM control scheme finds growing importance in power system applications because of its better dc bus utilization. In this paper, modelling of the converter is described, and SVPWM scheme is utilized to control the HVDC Light system in order to achieve better DC bus utilization, harmonic reduction, and for reduced power fluctuations. The simulations are carried out in the MATLAB/SIMULINK environment and the results are provided for steady state and dynamic conditions. Finally, the performance of SVPWM based vector controlled HVDC Light transmission system is compared with sinusoidal pulse width modulation (SPWM based HVDC Light system in terms of output voltage and total harmonic distortion (THD.

  5. VectorBase

    Data.gov (United States)

    U.S. Department of Health & Human Services — VectorBase is a Bioinformatics Resource Center for invertebrate vectors. It is one of four Bioinformatics Resource Centers funded by NIAID to provide web-based...

  6. A versatile system for USER cloning-based assembly of expression vectors for mammalian cell engineering.

    Directory of Open Access Journals (Sweden)

    Anne Mathilde Lund

    Full Text Available A new versatile mammalian vector system for protein production, cell biology analyses, and cell factory engineering was developed. The vector system applies the ligation-free uracil-excision based technique--USER cloning--to rapidly construct mammalian expression vectors of multiple DNA fragments and with maximum flexibility, both for choice of vector backbone and cargo. The vector system includes a set of basic vectors and a toolbox containing a multitude of DNA building blocks including promoters, terminators, selectable marker- and reporter genes, and sequences encoding an internal ribosome entry site, cellular localization signals and epitope- and purification tags. Building blocks in the toolbox can be easily combined as they contain defined and tested Flexible Assembly Sequence Tags, FASTs. USER cloning with FASTs allows rapid swaps of gene, promoter or selection marker in existing plasmids and simple construction of vectors encoding proteins, which are fused to fluorescence-, purification-, localization-, or epitope tags. The mammalian expression vector assembly platform currently allows for the assembly of up to seven fragments in a single cloning step with correct directionality and with a cloning efficiency above 90%. The functionality of basic vectors for FAST assembly was tested and validated by transient expression of fluorescent model proteins in CHO, U-2-OS and HEK293 cell lines. In this test, we included many of the most common vector elements for heterologous gene expression in mammalian cells, in addition the system is fully extendable by other users. The vector system is designed to facilitate high-throughput genome-scale studies of mammalian cells, such as the newly sequenced CHO cell lines, through the ability to rapidly generate high-fidelity assembly of customizable gene expression vectors.

  7. Raster images vectorization system

    OpenAIRE

    Genytė, Jurgita

    2006-01-01

    The problem of raster images vectorization was analyzed and researched in this work. Existing vectorization systems are quite expensive, the results are inaccurate, and the manual vectorization of a large number of drafts is impossible. That‘s why our goal was to design and develop a new raster images vectorization system using our suggested automatic vectorization algorithm and the way to record results in a new universal vectorial file format. The work consists of these main parts: analysis...

  8. Output-only modal parameter estimator of linear time-varying structural systems based on vector TAR model and least squares support vector machine

    Science.gov (United States)

    Zhou, Si-Da; Ma, Yuan-Chen; Liu, Li; Kang, Jie; Ma, Zhi-Sai; Yu, Lei

    2018-01-01

    Identification of time-varying modal parameters contributes to the structural health monitoring, fault detection, vibration control, etc. of the operational time-varying structural systems. However, it is a challenging task because there is not more information for the identification of the time-varying systems than that of the time-invariant systems. This paper presents a vector time-dependent autoregressive model and least squares support vector machine based modal parameter estimator for linear time-varying structural systems in case of output-only measurements. To reduce the computational cost, a Wendland's compactly supported radial basis function is used to achieve the sparsity of the Gram matrix. A Gamma-test-based non-parametric approach of selecting the regularization factor is adapted for the proposed estimator to replace the time-consuming n-fold cross validation. A series of numerical examples have illustrated the advantages of the proposed modal parameter estimator on the suppression of the overestimate and the short data. A laboratory experiment has further validated the proposed estimator.

  9. A simple and robust vector-based shRNA expression system used for RNA interference.

    Science.gov (United States)

    Wang, Xue-jun; Li, Ying; Huang, Hai; Zhang, Xiu-juan; Xie, Pei-wen; Hu, Wei; Li, Dan-dan; Wang, Sheng-qi

    2013-01-01

    RNA interference (RNAi) mediated by small interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs) has become a powerful genetic tool for conducting functional studies. Previously, vector-based shRNA-expression strategies capable of inducing RNAi in viable cells have been developed, however, these vector systems have some disadvantages, either because they were error-prone or cost prohibitive. In this report we described the development of a simple, robust shRNA expression system utilizing 1 long oligonucleotide or 2 short oligonucleotides for half the cost of conventional shRNA construction methods and with a >95% cloning success rate. The shRNA loop sequence and stem structure were also compared and carefully selected for better RNAi efficiency. Furthermore, an easier strategy was developed based on isocaudomers which permit rapid combination of the most efficient promoter-shRNA cassettes. Finally, using this method, the conservative target sites for hepatitis B virus (HBV) knockdown were systemically screened and HBV antigen expression shown to be successfully suppressed in the presence of connected multiple shRNAs both in vitro and in vivo. This novel design describes an inexpensive and effective way to clone and express single or multiple shRNAs from the same vector with the capacity for potent and effective silencing of target genes.

  10. CW-THz vector spectroscopy and imaging system based on 1.55-µm fiber-optics.

    Science.gov (United States)

    Kim, Jae-Young; Song, Ho-Jin; Yaita, Makoto; Hirata, Akihiko; Ajito, Katsuhiro

    2014-01-27

    We present a continuous-wave terahertz (THz) vector spectroscopy and imaging system based on a 1.5-µm fiber optic uni-traveling-carrier photodiode and InGaAs photo-conductive receiver. Using electro-optic (EO) phase modulators for THz phase control with shortened optical paths, the system achieves fast vector measurement with effective phase stabilization. Dynamic ranges of 100 dB · Hz and 75 dB · Hz at 300 GHz and 1 THz, and phase stability of 1.5° per minute are obtained. With the simultaneous measurement of absorbance and relative permittivity, we demonstrate non-destructive analyses of pharmaceutical cocrystals inside tablets within a few minutes.

  11. Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines.

    Science.gov (United States)

    del Val, Lara; Izquierdo-Fuente, Alberto; Villacorta, Juan J; Raboso, Mariano

    2015-06-17

    Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques used are spatial filtering, segmentation-based on a Gaussian Mixture Model (GMM) to separate the person from the background, masking-to reduce the dimensions of images-and binarization-to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements.

  12. Biosensor method and system based on feature vector extraction

    Science.gov (United States)

    Greenbaum, Elias [Knoxville, TN; Rodriguez, Jr., Miguel; Qi, Hairong [Knoxville, TN; Wang, Xiaoling [San Jose, CA

    2012-04-17

    A method of biosensor-based detection of toxins comprises the steps of providing at least one time-dependent control signal generated by a biosensor in a gas or liquid medium, and obtaining a time-dependent biosensor signal from the biosensor in the gas or liquid medium to be monitored or analyzed for the presence of one or more toxins selected from chemical, biological or radiological agents. The time-dependent biosensor signal is processed to obtain a plurality of feature vectors using at least one of amplitude statistics and a time-frequency analysis. At least one parameter relating to toxicity of the gas or liquid medium is then determined from the feature vectors based on reference to the control signal.

  13. A simple and robust vector-based shRNA expression system used for RNA interference.

    Directory of Open Access Journals (Sweden)

    Xue-jun Wang

    Full Text Available BACKGROUND: RNA interference (RNAi mediated by small interfering RNAs (siRNAs or short hairpin RNAs (shRNAs has become a powerful genetic tool for conducting functional studies. Previously, vector-based shRNA-expression strategies capable of inducing RNAi in viable cells have been developed, however, these vector systems have some disadvantages, either because they were error-prone or cost prohibitive. RESULTS: In this report we described the development of a simple, robust shRNA expression system utilizing 1 long oligonucleotide or 2 short oligonucleotides for half the cost of conventional shRNA construction methods and with a >95% cloning success rate. The shRNA loop sequence and stem structure were also compared and carefully selected for better RNAi efficiency. Furthermore, an easier strategy was developed based on isocaudomers which permit rapid combination of the most efficient promoter-shRNA cassettes. Finally, using this method, the conservative target sites for hepatitis B virus (HBV knockdown were systemically screened and HBV antigen expression shown to be successfully suppressed in the presence of connected multiple shRNAs both in vitro and in vivo. CONCLUSION: This novel design describes an inexpensive and effective way to clone and express single or multiple shRNAs from the same vector with the capacity for potent and effective silencing of target genes.

  14. Automated Vectorization of Decision-Based Algorithms

    Science.gov (United States)

    James, Mark

    2006-01-01

    Virtually all existing vectorization algorithms are designed to only analyze the numeric properties of an algorithm and distribute those elements across multiple processors. This advances the state of the practice because it is the only known system, at the time of this reporting, that takes high-level statements and analyzes them for their decision properties and converts them to a form that allows them to automatically be executed in parallel. The software takes a high-level source program that describes a complex decision- based condition and rewrites it as a disjunctive set of component Boolean relations that can then be executed in parallel. This is important because parallel architectures are becoming more commonplace in conventional systems and they have always been present in NASA flight systems. This technology allows one to take existing condition-based code and automatically vectorize it so it naturally decomposes across parallel architectures.

  15. Parameter identification based synchronization for a class of chaotic systems with offset vectors

    International Nuclear Information System (INIS)

    Chen Cailian; Feng Gang; Guan Xinping

    2004-01-01

    Based on a parameter identification scheme, a novel synchronization method is presented for a class of chaotic systems with offset vectors which can be represented by the so-called T-S fuzzy model. It is shown that the slave system can synchronize the master system and the unknown parameters of the master system can be identified simultaneously. The delayed feedback technique is also developed in order to reduce the energy and time required for the identification and synchronization. Numerical simulations demonstrate the effectiveness of the proposed method

  16. Anticipatory Monitoring and Control of Complex Systems using a Fuzzy based Fusion of Support Vector Regressors

    Energy Technology Data Exchange (ETDEWEB)

    Miltiadis Alamaniotis; Vivek Agarwal

    2014-10-01

    This paper places itself in the realm of anticipatory systems and envisions monitoring and control methods being capable of making predictions over system critical parameters. Anticipatory systems allow intelligent control of complex systems by predicting their future state. In the current work, an intelligent model aimed at implementing anticipatory monitoring and control in energy industry is presented and tested. More particularly, a set of support vector regressors (SVRs) are trained using both historical and observed data. The trained SVRs are used to predict the future value of the system based on current operational system parameter. The predicted values are then inputted to a fuzzy logic based module where the values are fused to obtain a single value, i.e., final system output prediction. The methodology is tested on real turbine degradation datasets. The outcome of the approach presented in this paper highlights the superiority over single support vector regressors. In addition, it is shown that appropriate selection of fuzzy sets and fuzzy rules plays an important role in improving system performance.

  17. Generation of arbitrary vector fields based on a pair of orthogonal elliptically polarized base vectors.

    Science.gov (United States)

    Xu, Danfeng; Gu, Bing; Rui, Guanghao; Zhan, Qiwen; Cui, Yiping

    2016-02-22

    We present an arbitrary vector field with hybrid polarization based on the combination of a pair of orthogonal elliptically polarized base vectors on the Poincaré sphere. It is shown that the created vector field is only dependent on the latitude angle 2χ but is independent on the longitude angle 2ψ on the Poincaré sphere. By adjusting the latitude angle 2χ, which is related to two identical waveplates in a common path interferometric arrangement, one could obtain arbitrary type of vector fields. Experimentally, we demonstrate the generation of such kind of vector fields and confirm the distribution of state of polarization by the measurement of Stokes parameters. Besides, we investigate the tight focusing properties of these vector fields. It is found that the additional degree of freedom 2χ provided by arbitrary vector field with hybrid polarization allows one to control the spatial structure of polarization and to engineer the focusing field.

  18. High performance computing on vector systems

    CERN Document Server

    Roller, Sabine

    2008-01-01

    Presents the developments in high-performance computing and simulation on modern supercomputer architectures. This book covers trends in hardware and software development in general and specifically the vector-based systems and heterogeneous architectures. It presents innovative fields like coupled multi-physics or multi-scale simulations.

  19. A stable RNA virus-based vector for citrus trees

    International Nuclear Information System (INIS)

    Folimonov, Alexey S.; Folimonova, Svetlana Y.; Bar-Joseph, Moshe; Dawson, William O.

    2007-01-01

    Virus-based vectors are important tools in plant molecular biology and plant genomics. A number of vectors based on viruses that infect herbaceous plants are in use for expression or silencing of genes in plants as well as screening unknown sequences for function. Yet there is a need for useful virus-based vectors for woody plants, which demand much greater stability because of the longer time required for systemic infection and analysis. We examined several strategies to develop a Citrus tristeza virus (CTV)-based vector for transient expression of foreign genes in citrus trees using a green fluorescent protein (GFP) as a reporter. These strategies included substitution of the p13 open reading frame (ORF) by the ORF of GFP, construction of a self-processing fusion of GFP in-frame with the major coat protein (CP), or expression of the GFP ORF as an extra gene from a subgenomic (sg) mRNA controlled either by a duplicated CTV CP sgRNA controller element (CE) or an introduced heterologous CE of Beet yellows virus. Engineered vector constructs were examined for replication, encapsidation, GFP expression during multiple passages in protoplasts, and for their ability to infect, move, express GFP, and be maintained in citrus plants. The most successful vectors based on the 'add-a-gene' strategy have been unusually stable, continuing to produce GFP fluorescence after more than 4 years in citrus trees

  20. An improved ternary vector system for Agrobacterium-mediated rapid maize transformation.

    Science.gov (United States)

    Anand, Ajith; Bass, Steven H; Wu, Emily; Wang, Ning; McBride, Kevin E; Annaluru, Narayana; Miller, Michael; Hua, Mo; Jones, Todd J

    2018-05-01

    A simple and versatile ternary vector system that utilizes improved accessory plasmids for rapid maize transformation is described. This system facilitates high-throughput vector construction and plant transformation. The super binary plasmid pSB1 is a mainstay of maize transformation. However, the large size of the base vector makes it challenging to clone, the process of co-integration is cumbersome and inefficient, and some Agrobacterium strains are known to give rise to spontaneous mutants resistant to tetracycline. These limitations present substantial barriers to high throughput vector construction. Here we describe a smaller, simpler and versatile ternary vector system for maize transformation that utilizes improved accessory plasmids requiring no co-integration step. In addition, the newly described accessory plasmids have restored virulence genes found to be defective in pSB1, as well as added virulence genes. Testing of different configurations of the accessory plasmids in combination with T-DNA binary vector as ternary vectors nearly doubles both the raw transformation frequency and the number of transformation events of usable quality in difficult-to-transform maize inbreds. The newly described ternary vectors enabled the development of a rapid maize transformation method for elite inbreds. This vector system facilitated screening different origins of replication on the accessory plasmid and T-DNA vector, and four combinations were identified that have high (86-103%) raw transformation frequency in an elite maize inbred.

  1. Development of oral CTL vaccine using a CTP-integrated Sabin 1 poliovirus-based vector system.

    Science.gov (United States)

    Han, Seung-Soo; Lee, Jinjoo; Jung, Yideul; Kang, Myeong-Ho; Hong, Jung-Hyub; Cha, Min-Suk; Park, Yu-Jin; Lee, Ezra; Yoon, Cheol-Hee; Bae, Yong-Soo

    2015-09-11

    We developed a CTL vaccine vector by modification of the RPS-Vax system, a mucosal vaccine vector derived from a poliovirus Sabin 1 strain, and generated an oral CTL vaccine against HIV-1. A DNA fragment encoding a cytoplasmic transduction peptide (CTP) was integrated into the RPS-Vax system to generate RPS-CTP, a CTL vaccine vector. An HIV-1 p24 cDNA fragment was introduced into the RPS-CTP vector system and a recombinant poliovirus (rec-PV) named vRPS-CTP/p24 was produced. vRPS-CTP/p24 was genetically stable and efficiently induced Th1 immunity and p24-specific CTLs in immunized poliovirus receptor-transgenic (PVR-Tg) mice. In challenge experiments, PVR-Tg mice that were pre-immunized orally with vRPS-CTP/p24 were resistant to challenge with a lethal dose of p24-expressing recombinant vaccinia virus (rMVA-p24). These results suggested that the RPS-CTP vector system had potential for developing oral CTL vaccines against infectious diseases. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. High stability vector-based direct power control for DFIG-based wind turbine

    DEFF Research Database (Denmark)

    Zhu, Rongwu; Chen, Zhe; Wu, Xiaojie

    2015-01-01

    This paper proposes an improved vector-based direct power control (DPC) strategy for the doubly-fed induction generator (DFIG)-based wind energy conversion system. Based on the small signal model, the proposed DPC improves the stability of the DFIG, and avoids the DFIG operating in the marginal...

  3. Forecasting systems reliability based on support vector regression with genetic algorithms

    International Nuclear Information System (INIS)

    Chen, K.-Y.

    2007-01-01

    This study applies a novel neural-network technique, support vector regression (SVR), to forecast reliability in engine systems. The aim of this study is to examine the feasibility of SVR in systems reliability prediction by comparing it with the existing neural-network approaches and the autoregressive integrated moving average (ARIMA) model. To build an effective SVR model, SVR's parameters must be set carefully. This study proposes a novel approach, known as GA-SVR, which searches for SVR's optimal parameters using real-value genetic algorithms, and then adopts the optimal parameters to construct the SVR models. A real reliability data for 40 suits of turbochargers were employed as the data set. The experimental results demonstrate that SVR outperforms the existing neural-network approaches and the traditional ARIMA models based on the normalized root mean square error and mean absolute percentage error

  4. Progress in developing cationic vectors for non-viral systemic gene therapy against cancer.

    Science.gov (United States)

    Morille, Marie; Passirani, Catherine; Vonarbourg, Arnaud; Clavreul, Anne; Benoit, Jean-Pierre

    2008-01-01

    Initially, gene therapy was viewed as an approach for treating hereditary diseases, but its potential role in the treatment of acquired diseases such as cancer is now widely recognized. The understanding of the molecular mechanisms involved in cancer and the development of nucleic acid delivery systems are two concepts that have led to this development. Systemic gene delivery systems are needed for therapeutic application to cells inaccessible by percutaneous injection and for multi-located tumor sites, i.e. metastases. Non-viral vectors based on the use of cationic lipids or polymers appear to have promising potential, given the problems of safety encountered with viral vectors. Using these non-viral vectors, the current challenge is to obtain a similarly effective transfection to viral ones. Based on the advantages and disadvantages of existing vectors and on the hurdles encountered with these carriers, the aim of this review is to describe the "perfect vector" for systemic gene therapy against cancer.

  5. A Versatile System for USER Cloning-Based Assembly of Expression Vectors for Mammalian Cell Engineering

    DEFF Research Database (Denmark)

    Lund, Anne Mathilde; Kildegaard, Helene Faustrup; Petersen, Maja Borup Kjær

    2014-01-01

    , in addition the system is fully extendable by other users. The vector system is designed to facilitate high-throughput genome-scale studies of mammalian cells, such as the newly sequenced CHO cell lines, through the ability to rapidly generate high-fidelity assembly of customizable gene expression vectors....

  6. Algevir: An Expression System for Microalgae Based on Viral Vectors

    Directory of Open Access Journals (Sweden)

    Bernardo Bañuelos-Hernández

    2017-06-01

    Full Text Available The use of recombinant algae for the production of valuable compounds is opening promising biotechnological applications. However, the development of efficient expression approaches is still needed to expand the exploitation of microalgae in biotechnology. Herein, the concept of using viral expression vectors in microalgae was explored for the first time. An inducible geminiviral vector leading to Rep-mediated replication of the expression cassette allowed the production of antigenic proteins at high levels. This system, called Algevir, allows the production of complex viral proteins (GP1 from Zaire ebolavirus and bacterial toxin subunits (B subunit of the heat-labile Escherichia coli enterotoxin, which retained their antigenic activity. The highest achieved yield was 1.25 mg/g fresh biomass (6 mg/L of culture, which was attained 3 days after transformation. The Algevir system allows for a fast and efficient production of recombinant proteins, overcoming the difficulties imposed by the low yields and unstable expression patterns frequently observed in stably transformed microalgae at the nuclear level; as well as the toxicity of some target proteins.

  7. Algevir: An Expression System for Microalgae Based on Viral Vectors

    Science.gov (United States)

    Bañuelos-Hernández, Bernardo; Monreal-Escalante, Elizabeth; González-Ortega, Omar; Angulo, Carlos; Rosales-Mendoza, Sergio

    2017-01-01

    The use of recombinant algae for the production of valuable compounds is opening promising biotechnological applications. However, the development of efficient expression approaches is still needed to expand the exploitation of microalgae in biotechnology. Herein, the concept of using viral expression vectors in microalgae was explored for the first time. An inducible geminiviral vector leading to Rep-mediated replication of the expression cassette allowed the production of antigenic proteins at high levels. This system, called Algevir, allows the production of complex viral proteins (GP1 from Zaire ebolavirus) and bacterial toxin subunits (B subunit of the heat-labile Escherichia coli enterotoxin), which retained their antigenic activity. The highest achieved yield was 1.25 mg/g fresh biomass (6 mg/L of culture), which was attained 3 days after transformation. The Algevir system allows for a fast and efficient production of recombinant proteins, overcoming the difficulties imposed by the low yields and unstable expression patterns frequently observed in stably transformed microalgae at the nuclear level; as well as the toxicity of some target proteins. PMID:28713333

  8. An episomal vector-based CRISPR/Cas9 system for highly efficient gene knockout in human pluripotent stem cells.

    Science.gov (United States)

    Xie, Yifang; Wang, Daqi; Lan, Feng; Wei, Gang; Ni, Ting; Chai, Renjie; Liu, Dong; Hu, Shijun; Li, Mingqing; Li, Dajin; Wang, Hongyan; Wang, Yongming

    2017-05-24

    Human pluripotent stem cells (hPSCs) represent a unique opportunity for understanding the molecular mechanisms underlying complex traits and diseases. CRISPR/Cas9 is a powerful tool to introduce genetic mutations into the hPSCs for loss-of-function studies. Here, we developed an episomal vector-based CRISPR/Cas9 system, which we called epiCRISPR, for highly efficient gene knockout in hPSCs. The epiCRISPR system enables generation of up to 100% Insertion/Deletion (indel) rates. In addition, the epiCRISPR system enables efficient double-gene knockout and genomic deletion. To minimize off-target cleavage, we combined the episomal vector technology with double-nicking strategy and recent developed high fidelity Cas9. Thus the epiCRISPR system offers a highly efficient platform for genetic analysis in hPSCs.

  9. Ces-VP: consultation expert system for vector programming of nuclear codes

    International Nuclear Information System (INIS)

    Fujisaki, Masahide; Makino, Mitsuhiro; Ishiguro, Misako

    1988-08-01

    Ces-VP is a prototype rule-based expert system for consulting the vector programming, based on the knowledge of vectorization of nuclear codes at JAERI during these 10 years. Experts in vectorization can restructure nuclear codes with high performance on vector processors, since they have know-how for choosing the best technique among a lot of techniques that were acquired from the experience of vectorization in the past. Frequency in trial and error will be reduced if a beginner can easily use the know-how of experts. In this report, at first the contents of Ces-VP and its intention are shown. Then, the method for acquiring the know-how of vectorization and the method for making rules from the know-how are described. The outline of Ces-VP implemented on Fujitsu expert tool ESHELL is described. Finally, the availability of Ces-VP is evaluated from the data gathered from practical use and its present problems are discussed. (author)

  10. Development of the system based code. v. 5. Method of margin exchange. pt. 2. Determination of quality assurance index based on a 'Vector Method'

    International Nuclear Information System (INIS)

    Asayama, Tai

    2003-03-01

    For the commercialization of fast breeder reactors, 'System Based Code', a completely new scheme of a code on structural integrity, is being developed. One of the distinguished features of the System Based Code is that it is able to determine a reasonable total margin on a structural of system, by allowing the exchanges of margins between various technical items. Detailed estimation of failure probability of a given combination of technical items and its comparison with a target value is one way to achieve this. However, simpler and easier methods that allow margin exchange without detailed calculation of failure probability are desirable in design. The authors have developed a simplified method such as a 'design factor method' from this viewpoint. This report describes a 'Vector Method', which was been newly developed. Following points are reported: 1) The Vector Method allows margin exchange evaluation on an 'equi-quality assurance plane' using vector calculation. Evaluation is easy and sufficient accuracy is achieved. The equi-quality assurance plane is obtained by a projection of an 'equi-failure probability surface in a n-dimensional space, which is calculated beforehand for typical combinations of design variables. 2) The Vector Method is considered to give the 'Quality Assurance Index Method' a probabilistic interpretation. 3) An algebraic method was proposed for the calculation of failure probabilities, which is necessary to obtain a equi-failure probability surface. This method calculates failure probabilities without using numerical methods such as Monte Carlo simulation or numerical integration. Under limited conditions, this method is quite effective compared to numerical methods. 4) An illustration of the procedure of margin exchange evaluation is given. It may be possible to use this method to optimize ISI plans; even it is not fully implemented in the System Based Code. (author)

  11. Parameter Improved Particle Swarm Optimization Based Direct-Current Vector Control Strategy for Solar PV System

    Directory of Open Access Journals (Sweden)

    NAMMALVAR, P.

    2018-02-01

    Full Text Available This paper projects Parameter Improved Particle Swarm Optimization (PIPSO based direct current vector control technology for the integration of photovoltaic array in an AC micro-grid to enhance the system performance and stability. A photovoltaic system incorporated with AC micro-grid is taken as the pursuit of research study. The test system features two power converters namely, PV side converter which consists of DC-DC boost converter with Perturbation and Observe (P&O MPPT control to reap most extreme power from the PV array, and grid side converter which consists of Grid Side-Voltage Source Converter (GS-VSC with proposed direct current vector control strategy. The gain of the proposed controller is chosen from a set of three values obtained using apriori test and tuned through the PIPSO algorithm so that the Integral of Time multiplied Absolute Error (ITAE between the actual and the desired DC link capacitor voltage reaches a minimum and allows the system to extract maximum power from PV system, whereas the existing d-q control strategy is found to perform slowly to control the DC link voltage under varying solar insolation and load fluctuations. From simulation results, it is evident that the proposed optimal control technique provides robust control and improved efficiency.

  12. Vector disparity sensor with vergence control for active vision systems.

    Science.gov (United States)

    Barranco, Francisco; Diaz, Javier; Gibaldi, Agostino; Sabatini, Silvio P; Ros, Eduardo

    2012-01-01

    This paper presents an architecture for computing vector disparity for active vision systems as used on robotics applications. The control of the vergence angle of a binocular system allows us to efficiently explore dynamic environments, but requires a generalization of the disparity computation with respect to a static camera setup, where the disparity is strictly 1-D after the image rectification. The interaction between vision and motor control allows us to develop an active sensor that achieves high accuracy of the disparity computation around the fixation point, and fast reaction time for the vergence control. In this contribution, we address the development of a real-time architecture for vector disparity computation using an FPGA device. We implement the disparity unit and the control module for vergence, version, and tilt to determine the fixation point. In addition, two on-chip different alternatives for the vector disparity engines are discussed based on the luminance (gradient-based) and phase information of the binocular images. The multiscale versions of these engines are able to estimate the vector disparity up to 32 fps on VGA resolution images with very good accuracy as shown using benchmark sequences with known ground-truth. The performances in terms of frame-rate, resource utilization, and accuracy of the presented approaches are discussed. On the basis of these results, our study indicates that the gradient-based approach leads to the best trade-off choice for the integration with the active vision system.

  13. Reversible Vector Ratchet Effect in Skyrmion Systems

    Science.gov (United States)

    Ma, Xiaoyu; Reichhardt, Charles; Reichhardt, Cynthia

    Magnetic skyrmions are topological non-trivial spin textures found in several magnetic materials. Since their motion can be controlled using ultralow current densities, skyrmions are appealing for potential applications in spintronics as information carriers and processing devices. In this work, we studied the collective transport properties of driven skyrmions based on a particle-like model with molecular dynamics (MD) simulation. Our results show that ac driven skyrmions interacting with an asymmetric substrate provide a realization of a new class of ratchet system, which we call a vector ratchet, that arises due to the effect of the Magnus term on the skyrmion dynamics. In a vector ratchet, the dc motion induced by the ac drive can be described as a vector that can be rotated up to 360 degrees relative to the substrate asymmetry direction. This could represent a new method for controlling skyrmion motion for spintronic applications.

  14. Traditional and robust vector selection methods for use with similarity based models

    International Nuclear Information System (INIS)

    Hines, J. W.; Garvey, D. R.

    2006-01-01

    Vector selection, or instance selection as it is often called in the data mining literature, performs a critical task in the development of nonparametric, similarity based models. Nonparametric, similarity based modeling (SBM) is a form of 'lazy learning' which constructs a local model 'on the fly' by comparing a query vector to historical, training vectors. For large training sets the creation of local models may become cumbersome, since each training vector must be compared to the query vector. To alleviate this computational burden, varying forms of training vector sampling may be employed with the goal of selecting a subset of the training data such that the samples are representative of the underlying process. This paper describes one such SBM, namely auto-associative kernel regression (AAKR), and presents five traditional vector selection methods and one robust vector selection method that may be used to select prototype vectors from a larger data set in model training. The five traditional vector selection methods considered are min-max, vector ordering, combination min-max and vector ordering, fuzzy c-means clustering, and Adeli-Hung clustering. Each method is described in detail and compared using artificially generated data and data collected from the steam system of an operating nuclear power plant. (authors)

  15. Efficient modeling of vector hysteresis using fuzzy inference systems

    International Nuclear Information System (INIS)

    Adly, A.A.; Abd-El-Hafiz, S.K.

    2008-01-01

    Vector hysteresis models have always been regarded as important tools to determine which multi-dimensional magnetic field-media interactions may be predicted. In the past, considerable efforts have been focused on mathematical modeling methodologies of vector hysteresis. This paper presents an efficient approach based upon fuzzy inference systems for modeling vector hysteresis. Computational efficiency of the proposed approach stems from the fact that the basic non-local memory Preisach-type hysteresis model is approximated by a local memory model. The proposed computational low-cost methodology can be easily integrated in field calculation packages involving massive multi-dimensional discretizations. Details of the modeling methodology and its experimental testing are presented

  16. Viral vector-based influenza vaccines

    Science.gov (United States)

    de Vries, Rory D.; Rimmelzwaan, Guus F.

    2016-01-01

    ABSTRACT Antigenic drift of seasonal influenza viruses and the occasional introduction of influenza viruses of novel subtypes into the human population complicate the timely production of effective vaccines that antigenically match the virus strains that cause epidemic or pandemic outbreaks. The development of game-changing vaccines that induce broadly protective immunity against a wide variety of influenza viruses is an unmet need, in which recombinant viral vectors may provide. Use of viral vectors allows the delivery of any influenza virus antigen, or derivative thereof, to the immune system, resulting in the optimal induction of virus-specific B- and T-cell responses against this antigen of choice. This systematic review discusses results obtained with vectored influenza virus vaccines and advantages and disadvantages of the currently available viral vectors. PMID:27455345

  17. A Subdivision-Based Representation for Vector Image Editing.

    Science.gov (United States)

    Liao, Zicheng; Hoppe, Hugues; Forsyth, David; Yu, Yizhou

    2012-11-01

    Vector graphics has been employed in a wide variety of applications due to its scalability and editability. Editability is a high priority for artists and designers who wish to produce vector-based graphical content with user interaction. In this paper, we introduce a new vector image representation based on piecewise smooth subdivision surfaces, which is a simple, unified and flexible framework that supports a variety of operations, including shape editing, color editing, image stylization, and vector image processing. These operations effectively create novel vector graphics by reusing and altering existing image vectorization results. Because image vectorization yields an abstraction of the original raster image, controlling the level of detail of this abstraction is highly desirable. To this end, we design a feature-oriented vector image pyramid that offers multiple levels of abstraction simultaneously. Our new vector image representation can be rasterized efficiently using GPU-accelerated subdivision. Experiments indicate that our vector image representation achieves high visual quality and better supports editing operations than existing representations.

  18. Support-Vector-Machine-Based Reduced-Order Model for Limit Cycle Oscillation Prediction of Nonlinear Aeroelastic System

    Directory of Open Access Journals (Sweden)

    Gang Chen

    2012-01-01

    Full Text Available It is not easy for the system identification-based reduced-order model (ROM and even eigenmode based reduced-order model to predict the limit cycle oscillation generated by the nonlinear unsteady aerodynamics. Most of these traditional ROMs are sensitive to the flow parameter variation. In order to deal with this problem, a support vector machine- (SVM- based ROM was investigated and the general construction framework was proposed. The two-DOF aeroelastic system for the NACA 64A010 airfoil in transonic flow was then demonstrated for the new SVM-based ROM. The simulation results show that the new ROM can capture the LCO behavior of the nonlinear aeroelastic system with good accuracy and high efficiency. The robustness and computational efficiency of the SVM-based ROM would provide a promising tool for real-time flight simulation including nonlinear aeroelastic effects.

  19. Lyapunov, singular and bred vectors in a multi-scale system: an empirical exploration of vectors related to instabilities

    International Nuclear Information System (INIS)

    Norwood, Adrienne; Kalnay, Eugenia; Ide, Kayo; Yang, Shu-Chih; Wolfe, Christopher

    2013-01-01

    We compute and compare the three types of vectors frequently used to explore the instability properties of dynamical models, namely Lyapunov vectors (LVs), singular vectors (SVs) and bred vectors (BVs) in two systems, using the Wolfe–Samelson (2007 Tellus A 59 355–66) algorithm to compute all of the Lyapunov vectors. The first system is the Lorenz (1963 J. Atmos. Sci. 20 130–41) three-variable model. Although the leading Lyapunov vector, LV1, grows fastest globally, the second Lyapunov vector, LV2, which has zero growth globally, often grows faster than LV1 locally. Whenever this happens, BVs grow closer to LV2, suggesting that in larger atmospheric or oceanic models where several instabilities can grow in different areas of the world, BVs will grow toward the fastest growing local unstable mode. A comparison of their growth rates at different times shows that all three types of dynamical vectors have the ability to predict regime changes and the duration of the new regime based on their growth rates in the last orbit of the old regime, as shown for BVs by Evans et al (2004 Bull. Am. Meteorol. Soc. 520–4). LV1 and BVs have similar predictive skill, LV2 has a tendency to produce false alarms, and even LV3 shows that maximum decay is also associated with regime change. Initial and final SVs grow much faster and are the most accurate predictors of regime change, although the characteristics of the initial SVs are strongly dependent on the length of the optimization window. The second system is the toy ‘ocean-atmosphere’ model developed by Peña and Kalnay (2004 Nonlinear Process. Geophys. 11 319–27) coupling three Lorenz (1963 J. Atmos. Sci. 20 130–41) systems with different time scales, in order to test the effects of fast and slow modes of growth on the dynamical vectors. A fast ‘extratropical atmosphere’ is weakly coupled to a fast ‘tropical atmosphere’ which is, in turn, strongly coupled to a slow ‘ocean’ system, the latter coupling

  20. "Lollipop-shaped" high-sensitivity Microelectromechanical Systems vector hydrophone based on Parylene encapsulation

    Science.gov (United States)

    Liu, Yuan; Wang, Renxin; Zhang, Guojun; Du, Jin; Zhao, Long; Xue, Chenyang; Zhang, Wendong; Liu, Jun

    2015-07-01

    This paper presents methods of promoting the sensitivity of Microelectromechanical Systems (MEMS) vector hydrophone by increasing the sensing area of cilium and perfect insulative Parylene membrane. First, a low-density sphere is integrated with the cilium to compose a "lollipop shape," which can considerably increase the sensing area. A mathematic model on the sensitivity of the "lollipop-shaped" MEMS vector hydrophone is presented, and the influences of different structural parameters on the sensitivity are analyzed via simulation. Second, the MEMS vector hydrophone is encapsulated through the conformal deposition of insulative Parylene membrane, which enables underwater acoustic monitoring without any typed sound-transparent encapsulation. Finally, the characterization results demonstrate that the sensitivity reaches up to -183 dB (500 Hz 0dB at 1 V/ μPa ), which is increased by more than 10 dB, comparing with the previous cilium-shaped MEMS vector hydrophone. Besides, the frequency response takes on a sensitivity increment of 6 dB per octave. The working frequency band is 20-500 Hz and the concave point depth of 8-shaped directivity is beyond 30 dB, indicating that the hydrophone is promising in underwater acoustic application.

  1. A support vector machine (SVM) based voltage stability classifier

    Energy Technology Data Exchange (ETDEWEB)

    Dosano, R.D.; Song, H. [Kunsan National Univ., Kunsan, Jeonbuk (Korea, Republic of); Lee, B. [Korea Univ., Seoul (Korea, Republic of)

    2007-07-01

    Power system stability has become even more complex and critical with the advent of deregulated energy markets and the growing desire to completely employ existing transmission and infrastructure. The economic pressure on electricity markets forces the operation of power systems and components to their limit of capacity and performance. System conditions can be more exposed to instability due to greater uncertainty in day to day system operations and increase in the number of potential components for system disturbances potentially resulting in voltage stability. This paper proposed a support vector machine (SVM) based power system voltage stability classifier using local measurements of voltage and active power of load. It described the procedure for fast classification of long-term voltage stability using the SVM algorithm. The application of the SVM based voltage stability classifier was presented with reference to the choice of input parameters; input data preconditioning; moving window for feature vector; determination of learning samples; and other considerations in SVM applications. The paper presented a case study with numerical examples of an 11-bus test system. The test results for the feasibility study demonstrated that the classifier could offer an excellent performance in classification with time-series measurements in terms of long-term voltage stability. 9 refs., 14 figs.

  2. A Kalman Filter for SINS Self-Alignment Based on Vector Observation.

    Science.gov (United States)

    Xu, Xiang; Xu, Xiaosu; Zhang, Tao; Li, Yao; Tong, Jinwu

    2017-01-29

    In this paper, a self-alignment method for strapdown inertial navigation systems based on the q -method is studied. In addition, an improved method based on integrating gravitational apparent motion to form apparent velocity is designed, which can reduce the random noises of the observation vectors. For further analysis, a novel self-alignment method using a Kalman filter based on adaptive filter technology is proposed, which transforms the self-alignment procedure into an attitude estimation using the observation vectors. In the proposed method, a linear psuedo-measurement equation is adopted by employing the transfer method between the quaternion and the observation vectors. Analysis and simulation indicate that the accuracy of the self-alignment is improved. Meanwhile, to improve the convergence rate of the proposed method, a new method based on parameter recognition and a reconstruction algorithm for apparent gravitation is devised, which can reduce the influence of the random noises of the observation vectors. Simulations and turntable tests are carried out, and the results indicate that the proposed method can acquire sound alignment results with lower standard variances, and can obtain higher alignment accuracy and a faster convergence rate.

  3. Implementation of a vector-based tracking loop receiver in a pseudolite navigation system.

    Science.gov (United States)

    So, Hyoungmin; Lee, Taikjin; Jeon, Sanghoon; Kim, Chongwon; Kee, Changdon; Kim, Taehee; Lee, Sanguk

    2010-01-01

    We propose a vector tracking loop (VTL) algorithm for an asynchronous pseudolite navigation system. It was implemented in a software receiver and experiments in an indoor navigation system were conducted. Test results show that the VTL successfully tracks signals against the near-far problem, one of the major limitations in pseudolite navigation systems, and could improve positioning availability by extending pseudolite navigation coverage.

  4. Great Ellipse Route Planning Based on Space Vector

    Directory of Open Access Journals (Sweden)

    LIU Wenchao

    2015-07-01

    Full Text Available Aiming at the problem of navigation error caused by unified earth model in great circle route planning using sphere model and modern navigation equipment using ellipsoid mode, a method of great ellipse route planning based on space vector is studied. By using space vector algebra method, the vertex of great ellipse is solved directly, and description of great ellipse based on major-axis vector and minor-axis vector is presented. Then calculation formulas of great ellipse azimuth and distance are deduced using two basic vectors. Finally, algorithms of great ellipse route planning are studied, especially equal distance route planning algorithm based on Newton-Raphson(N-R method. Comparative examples show that the difference of route planning between great circle and great ellipse is significant, using algorithms of great ellipse route planning can eliminate the navigation error caused by the great circle route planning, and effectively improve the accuracy of navigation calculation.

  5. MODELING OF DYNAMIC SYSTEMS WITH MODULATION BY MEANS OF KRONECKER VECTOR-MATRIX REPRESENTATION

    Directory of Open Access Journals (Sweden)

    A. S. Vasilyev

    2015-09-01

    Full Text Available The paper deals with modeling of dynamic systems with modulation by the possibilities of state-space method. This method, being the basis of modern control theory, is based on the possibilities of vector-matrix formalism of linear algebra and helps to solve various problems of technical control of continuous and discrete nature invariant with respect to the dimension of their “input-output” objects. Unfortunately, it turned its back on the wide group of control systems, which hardware environment modulates signals. The marked system deficiency is partially offset by this paper, which proposes Kronecker vector-matrix representations for purposes of system representation of processes with signal modulation. The main result is vector-matrix representation of processes with modulation with no formal difference from continuous systems. It has been found that abilities of these representations could be effectively used in research of systems with modulation. Obtained model representations of processes with modulation are best adapted to the state-space method. These approaches for counting eigenvalues of Kronecker matrix summaries, that are matrix basis of model representations of processes described by Kronecker vector products, give the possibility to use modal direction in research of dynamics for systems with modulation. It is shown that the use of controllability for eigenvalues of general matrixes applied to Kronecker structures enabled to divide successfully eigenvalue spectrum into directed and not directed components. Obtained findings including design problems for models of dynamic processes with modulation based on the features of Kronecker vector and matrix structures, invariant with respect to the dimension of input-output relations, are applicable in the development of alternate current servo drives.

  6. An introduction to vectors, vector operators and vector analysis

    CERN Document Server

    Joag, Pramod S

    2016-01-01

    Ideal for undergraduate and graduate students of science and engineering, this book covers fundamental concepts of vectors and their applications in a single volume. The first unit deals with basic formulation, both conceptual and theoretical. It discusses applications of algebraic operations, Levi-Civita notation, and curvilinear coordinate systems like spherical polar and parabolic systems and structures, and analytical geometry of curves and surfaces. The second unit delves into the algebra of operators and their types and also explains the equivalence between the algebra of vector operators and the algebra of matrices. Formulation of eigen vectors and eigen values of a linear vector operator are elaborated using vector algebra. The third unit deals with vector analysis, discussing vector valued functions of a scalar variable and functions of vector argument (both scalar valued and vector valued), thus covering both the scalar vector fields and vector integration.

  7. Support vector machine based diagnostic system for breast cancer using swarm intelligence.

    Science.gov (United States)

    Chen, Hui-Ling; Yang, Bo; Wang, Gang; Wang, Su-Jing; Liu, Jie; Liu, Da-You

    2012-08-01

    Breast cancer is becoming a leading cause of death among women in the whole world, meanwhile, it is confirmed that the early detection and accurate diagnosis of this disease can ensure a long survival of the patients. In this paper, a swarm intelligence technique based support vector machine classifier (PSO_SVM) is proposed for breast cancer diagnosis. In the proposed PSO-SVM, the issue of model selection and feature selection in SVM is simultaneously solved under particle swarm (PSO optimization) framework. A weighted function is adopted to design the objective function of PSO, which takes into account the average accuracy rates of SVM (ACC), the number of support vectors (SVs) and the selected features simultaneously. Furthermore, time varying acceleration coefficients (TVAC) and inertia weight (TVIW) are employed to efficiently control the local and global search in PSO algorithm. The effectiveness of PSO-SVM has been rigorously evaluated against the Wisconsin Breast Cancer Dataset (WBCD), which is commonly used among researchers who use machine learning methods for breast cancer diagnosis. The proposed system is compared with the grid search method with feature selection by F-score. The experimental results demonstrate that the proposed approach not only obtains much more appropriate model parameters and discriminative feature subset, but also needs smaller set of SVs for training, giving high predictive accuracy. In addition, Compared to the existing methods in previous studies, the proposed system can also be regarded as a promising success with the excellent classification accuracy of 99.3% via 10-fold cross validation (CV) analysis. Moreover, a combination of five informative features is identified, which might provide important insights to the nature of the breast cancer disease and give an important clue for the physicians to take a closer attention. We believe the promising result can ensure that the physicians make very accurate diagnostic decision in

  8. Development of new USER-based cloning vectors for multiple genes expression in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Kildegaard, Kanchana Rueksomtawin; Jensen, Niels Bjerg; Maury, Jerome

    2013-01-01

    auxotrophic and dominant markers for convenience of use. Our vector set also contains both integrating and multicopy vectors for stability of protein expression and high expression level. We will make the new vector system available to the yeast community and provide a comprehensive protocol for cloning...... the production strain with the proper phenotype and product yield. However, the sequential number of metabolic engineering is time-consuming. Furthermore, the number of available selectable markers is also limiting the number of genetic modifications. To overcome these limitations, we have developed a new set...... of shuttle vectors for convenience of use for high-throughput cloning and selectable marker recycling. The new USER-based cloning vectors consist of a unique USER site and a CRE-loxP-mediated marker recycling system. The USER site allows insertion of genes of interest along with a bidirectional promoter...

  9. On-line transient stability assessment of large-scale power systems by using ball vector machines

    International Nuclear Information System (INIS)

    Mohammadi, M.; Gharehpetian, G.B.

    2010-01-01

    In this paper ball vector machine (BVM) has been used for on-line transient stability assessment of large-scale power systems. To classify the system transient security status, a BVM has been trained for all contingencies. The proposed BVM based security assessment algorithm has very small training time and space in comparison with artificial neural networks (ANN), support vector machines (SVM) and other machine learning based algorithms. In addition, the proposed algorithm has less support vectors (SV) and therefore is faster than existing algorithms for on-line applications. One of the main points, to apply a machine learning method is feature selection. In this paper, a new Decision Tree (DT) based feature selection technique has been presented. The proposed BVM based algorithm has been applied to New England 39-bus power system. The simulation results show the effectiveness and the stability of the proposed method for on-line transient stability assessment procedure of large-scale power system. The proposed feature selection algorithm has been compared with different feature selection algorithms. The simulation results demonstrate the effectiveness of the proposed feature algorithm.

  10. PGMA-Based Cationic Nanoparticles with Polyhydric Iodine Units for Advanced Gene Vectors.

    Science.gov (United States)

    Sun, Yue; Hu, Hao; Yu, Bingran; Xu, Fu-Jian

    2016-11-16

    It is crucial for successful gene delivery to develop safe, effective, and multifunctional polycations. Iodine-based small molecules are widely used as contrast agents for CT imaging. Herein, a series of star-like poly(glycidyl methacrylate) (PGMA)-based cationic vectors (II-PGEA/II) with abundant flanking polyhydric iodine units are prepared for multifunctional gene delivery systems. The proposed II-PGEA/II star vector is composed of one iohexol intermediate (II) core and five ethanolamine (EA) and II-difunctionalized PGMA arms. The amphipathic II-PGEA/II vectors readily self-assemble into well-defined cationic nanoparticles, where massive hydroxyl groups can establish a hydration shell to stabilize the nanoparticles. The II introduction improves cell viabilities of polycations. Moreover, by controlling the suitable amount of introduced II units, the resultant II-PGEA/II nanoparticles can produce fairly good transfection performances in different cell lines. Particularly, the II-PGEA/II nanoparticles induce much better in vitro CT imaging abilities in tumor cells than iohexol (one commonly used commercial CT contrast agent). The present design of amphipathic PGMA-based nanoparticles with CT contrast agents would provide useful information for the development of new multifunctional gene delivery systems.

  11. Command vector memory systems: high performance at low cost

    OpenAIRE

    Corbal San Adrián, Jesús; Espasa Sans, Roger; Valero Cortés, Mateo

    1998-01-01

    The focus of this paper is on designing both a low cost and high performance, high bandwidth vector memory system that takes advantage of modern commodity SDRAM memory chips. To successfully extract the full bandwidth from SDRAM parts, we propose a new memory system organization based on sending commands to the memory system as opposed to sending individual addresses. A command specifies, in a few bytes, a request for multiple independent memory words. A command is similar to a burst found in...

  12. Performance monitoring for coherent DP-QPSK systems based on stokes vectors analysis

    Science.gov (United States)

    Louchet, Hadrien; Koltchanov, Igor; Richter, André

    2010-12-01

    We show how to estimate accurately the Jones matrix of the transmission line by analyzing the Stokes vectors of DP-QPSK signals. This method can be used to perform in-situ PMD measurement in dual-polarization QPSK systems, and in addition to the constant modulus algorithm (CMA) to mitigate polarization-induced impairments. The applicability of this method to other modulation formats is discussed.

  13. Kochen-Specker vectors

    International Nuclear Information System (INIS)

    Pavicic, Mladen; Merlet, Jean-Pierre; McKay, Brendan; Megill, Norman D

    2005-01-01

    We give a constructive and exhaustive definition of Kochen-Specker (KS) vectors in a Hilbert space of any dimension as well as of all the remaining vectors of the space. KS vectors are elements of any set of orthonormal states, i.e., vectors in an n-dimensional Hilbert space, H n , n≥3, to which it is impossible to assign 1s and 0s in such a way that no two mutually orthogonal vectors from the set are both assigned 1 and that not all mutually orthogonal vectors are assigned 0. Our constructive definition of such KS vectors is based on algorithms that generate MMP diagrams corresponding to blocks of orthogonal vectors in R n , on algorithms that single out those diagrams on which algebraic (0)-(1) states cannot be defined, and on algorithms that solve nonlinear equations describing the orthogonalities of the vectors by means of statistically polynomially complex interval analysis and self-teaching programs. The algorithms are limited neither by the number of dimensions nor by the number of vectors. To demonstrate the power of the algorithms, all four-dimensional KS vector systems containing up to 24 vectors were generated and described, all three-dimensional vector systems containing up to 30 vectors were scanned, and several general properties of KS vectors were found

  14. Genetic engineering in Actinoplanes sp. SE50/110 - development of an intergeneric conjugation system for the introduction of actinophage-based integrative vectors.

    Science.gov (United States)

    Gren, Tetiana; Ortseifen, Vera; Wibberg, Daniel; Schneiker-Bekel, Susanne; Bednarz, Hanna; Niehaus, Karsten; Zemke, Till; Persicke, Marcus; Pühler, Alfred; Kalinowski, Jörn

    2016-08-20

    The α-glucosidase inhibitor acarbose is used for treatment of diabetes mellitus type II, and is manufactured industrially with overproducing derivatives of Actinoplanes sp. SE50/110, reportedly obtained by conventional mutagenesis. Despite of high industrial significance, only limited information exists regarding acarbose metabolism, function and regulation of these processes, due to the absence of proper genetic engineering methods and tools developed for this strain. Here, a basic toolkit for genetic engineering of Actinoplanes sp. SE50/110 was developed, comprising a standardized protocol for a DNA transfer through Escherichia coli-Actinoplanes intergeneric conjugation and applied for the transfer of ϕC31, ϕBT1 and VWB actinophage-based integrative vectors. Integration sites, occurring once per genome for all vectors, were sequenced and characterized for the first time in Actinoplanes sp. SE50/110. Notably, in case of ϕC31 based vector pSET152, the integration site is highly conserved, while for ϕBT1 and the VWB based vectors pRT801 and pSOK804, respectively, no sequence similarities to those in other bacteria were detected. The studied plasmids were proven to be stable and neutral with respect to strain morphology and acarbose production, enabling future use for genetic manipulations of Actinoplanes sp. SE50/110. To further broaden the spectrum of available tools, a GUS reporter system, based on the pSET152 derived vector, was also established in Actinoplanes sp. SE50/110. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. A novel minicircle vector based system for inhibting the replication and gene expression of enterovirus 71 and coxsackievirus A16.

    Science.gov (United States)

    Yang, Zhuo; Li, Guodong; Zhang, Yingqiu; Liu, Xiaoman; Tien, Po

    2012-11-01

    Enterovirus 71 (EV 71) and Coxsackievirus A16 (CA 16) are two major causative agents of hand, foot and mouth disease (HFMD). They have been associated with severe neurological and cardiological complications worldwide, and have caused significant mortalities during large-scale outbreaks in China. Currently, there are no effective treatments against EV 71 and CA 16 infections. We now describe the development of a novel minicircle vector based RNA interference (RNAi) system as a therapeutic approach to inhibiting EV 71 and CA 16 replication. Small interfering RNA (siRNA) molecules targeting the conserved regions of the 3C(pro) and 3D(pol) function gene of the EV 71 and CA 16 China strains were designed based on their nucleotide sequences available in GenBank. This RNAi system was found to effectively block the replication and gene expression of these viruses in rhabdomyosarcoma (RD) cells and virus-infected mice model. The inhibitory effects were confirmed by a corresponding decrease in viral RNA, viral protein, and progeny virus production. In addition, no significant adverse off-target silencing or cytotoxic effects were observed. These results demonstrated the potential and feasibility of this novel minicircle vector based RNAi system for antiviral therapy against EV 71 and CA 16 infection. Copyright © 2012 Elsevier B.V. All rights reserved.

  16. High-speed vector-processing system of the MELCOM-COSMO 900II

    Energy Technology Data Exchange (ETDEWEB)

    Masuda, K; Mori, H; Fujikake, J; Sasaki, Y

    1983-01-01

    Progress in scientific and technical calculations has lead to a growing demand for high-speed vector calculations. Mitsubishi electric has developed an integrated array processor and automatic-vectorizing fortran compiler as an option for the MELCOM-COSMO 900II computer system. This facilitates the performance of vector calculations and matrix calculations, achieving significant gains in cost-effectiveness. The article outlines the high-speed vector system, includes discussion of compiler structuring, and cites examples of effective system application. 1 reference.

  17. Research on intrusion detection based on Kohonen network and support vector machine

    Science.gov (United States)

    Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

    2018-05-01

    In view of the problem of low detection accuracy and the long detection time of support vector machine, which directly applied to the network intrusion detection system. Optimization of SVM parameters can greatly improve the detection accuracy, but it can not be applied to high-speed network because of the long detection time. a method based on Kohonen neural network feature selection is proposed to reduce the optimization time of support vector machine parameters. Firstly, this paper is to calculate the weights of the KDD99 network intrusion data by Kohonen network and select feature by weight. Then, after the feature selection is completed, genetic algorithm (GA) and grid search method are used for parameter optimization to find the appropriate parameters and classify them by support vector machines. By comparing experiments, it is concluded that feature selection can reduce the time of parameter optimization, which has little influence on the accuracy of classification. The experiments suggest that the support vector machine can be used in the network intrusion detection system and reduce the missing rate.

  18. Multiple image encryption scheme based on pixel exchange operation and vector decomposition

    Science.gov (United States)

    Xiong, Y.; Quan, C.; Tay, C. J.

    2018-02-01

    We propose a new multiple image encryption scheme based on a pixel exchange operation and a basic vector decomposition in Fourier domain. In this algorithm, original images are imported via a pixel exchange operator, from which scrambled images and pixel position matrices are obtained. Scrambled images encrypted into phase information are imported using the proposed algorithm and phase keys are obtained from the difference between scrambled images and synthesized vectors in a charge-coupled device (CCD) plane. The final synthesized vector is used as an input in a random phase encoding (DRPE) scheme. In the proposed encryption scheme, pixel position matrices and phase keys serve as additional private keys to enhance the security of the cryptosystem which is based on a 4-f system. Numerical simulations are presented to demonstrate the feasibility and robustness of the proposed encryption scheme.

  19. The establishment of Saccharomyces boulardii surface display system using a single expression vector.

    Science.gov (United States)

    Wang, Tiantian; Sun, Hui; Zhang, Jie; Liu, Qing; Wang, Longjiang; Chen, Peipei; Wang, Fangkun; Li, Hongmei; Xiao, Yihong; Zhao, Xiaomin

    2014-03-01

    In the present study, an a-agglutinin-based Saccharomyces boulardii surface display system was successfully established using a single expression vector. Based on the two protein co-expression vector pSP-G1 built by Partow et al., a S. boulardii surface display vector-pSDSb containing all the display elements was constructed. The display results of heterologous proteins were confirmed by successfully displaying enhanced green fluorescent protein (EGFP) and chicken Eimeria tenella Microneme-2 proteins (EtMic2) on the S. boulardii cell surface. The DNA sequence of AGA1 gene from S. boulardii (SbAGA1) was determined and used as the cell wall anchor partner. This is the first time heterologous proteins have been displayed on the cell surface of S. boulardii. Because S. boulardii is probiotic and eukaryotic, its surface display system would be very valuable, particularly in the development of a live vaccine against various pathogenic organisms especially eukaryotic pathogens such as protistan parasites. Copyright © 2013 Elsevier Inc. All rights reserved.

  20. System for Automated Calibration of Vector Modulators

    Science.gov (United States)

    Lux, James; Boas, Amy; Li, Samuel

    2009-01-01

    Vector modulators are used to impose baseband modulation on RF signals, but non-ideal behavior limits the overall performance. The non-ideal behavior of the vector modulator is compensated using data collected with the use of an automated test system driven by a LabVIEW program that systematically applies thousands of control-signal values to the device under test and collects RF measurement data. The technology innovation automates several steps in the process. First, an automated test system, using computer controlled digital-to-analog converters (DACs) and a computer-controlled vector network analyzer (VNA) systematically can apply different I and Q signals (which represent the complex number by which the RF signal is multiplied) to the vector modulator under test (VMUT), while measuring the RF performance specifically, gain and phase. The automated test system uses the LabVIEW software to control the test equipment, collect the data, and write it to a file. The input to the Lab - VIEW program is either user-input for systematic variation, or is provided in a file containing specific test values that should be fed to the VMUT. The output file contains both the control signals and the measured data. The second step is to post-process the file to determine the correction functions as needed. The result of the entire process is a tabular representation, which allows translation of a desired I/Q value to the required analog control signals to produce a particular RF behavior. In some applications, corrected performance is needed only for a limited range. If the vector modulator is being used as a phase shifter, there is only a need to correct I and Q values that represent points on a circle, not the entire plane. This innovation has been used to calibrate 2-GHz MMIC (monolithic microwave integrated circuit) vector modulators in the High EIRP Cluster Array project (EIRP is high effective isotropic radiated power). These calibrations were then used to create

  1. Robust anti-synchronization of uncertain chaotic systems based on multiple-kernel least squares support vector machine modeling

    International Nuclear Information System (INIS)

    Chen Qiang; Ren Xuemei; Na Jing

    2011-01-01

    Highlights: Model uncertainty of the system is approximated by multiple-kernel LSSVM. Approximation errors and disturbances are compensated in the controller design. Asymptotical anti-synchronization is achieved with model uncertainty and disturbances. Abstract: In this paper, we propose a robust anti-synchronization scheme based on multiple-kernel least squares support vector machine (MK-LSSVM) modeling for two uncertain chaotic systems. The multiple-kernel regression, which is a linear combination of basic kernels, is designed to approximate system uncertainties by constructing a multiple-kernel Lagrangian function and computing the corresponding regression parameters. Then, a robust feedback control based on MK-LSSVM modeling is presented and an improved update law is employed to estimate the unknown bound of the approximation error. The proposed control scheme can guarantee the asymptotic convergence of the anti-synchronization errors in the presence of system uncertainties and external disturbances. Numerical examples are provided to show the effectiveness of the proposed method.

  2. Web-based GIS: the vector-borne disease airline importation risk (VBD-AIR) tool.

    Science.gov (United States)

    Huang, Zhuojie; Das, Anirrudha; Qiu, Youliang; Tatem, Andrew J

    2012-08-14

    Over the past century, the size and complexity of the air travel network has increased dramatically. Nowadays, there are 29.6 million scheduled flights per year and around 2.7 billion passengers are transported annually. The rapid expansion of the network increasingly connects regions of endemic vector-borne disease with the rest of the world, resulting in challenges to health systems worldwide in terms of vector-borne pathogen importation and disease vector invasion events. Here we describe the development of a user-friendly Web-based GIS tool: the Vector-Borne Disease Airline Importation Risk Tool (VBD-AIR), to help better define the roles of airports and airlines in the transmission and spread of vector-borne diseases. Spatial datasets on modeled global disease and vector distributions, as well as climatic and air network traffic data were assembled. These were combined to derive relative risk metrics via air travel for imported infections, imported vectors and onward transmission, and incorporated into a three-tier server architecture in a Model-View-Controller framework with distributed GIS components. A user-friendly web-portal was built that enables dynamic querying of the spatial databases to provide relevant information. The VBD-AIR tool constructed enables the user to explore the interrelationships among modeled global distributions of vector-borne infectious diseases (malaria. dengue, yellow fever and chikungunya) and international air service routes to quantify seasonally changing risks of vector and vector-borne disease importation and spread by air travel, forming an evidence base to help plan mitigation strategies. The VBD-AIR tool is available at http://www.vbd-air.com. VBD-AIR supports a data flow that generates analytical results from disparate but complementary datasets into an organized cartographical presentation on a web map for the assessment of vector-borne disease movements on the air travel network. The framework built provides a flexible

  3. Development of Novel Adenoviral Vectors to Overcome Challenges Observed With HAdV-5–based Constructs

    Science.gov (United States)

    Alonso-Padilla, Julio; Papp, Tibor; Kaján, Győző L; Benkő, Mária; Havenga, Menzo; Lemckert, Angelique; Harrach, Balázs; Baker, Andrew H

    2016-01-01

    Recombinant vectors based on human adenovirus serotype 5 (HAdV-5) have been extensively studied in preclinical models and clinical trials over the past two decades. However, the thorough understanding of the HAdV-5 interaction with human subjects has uncovered major concerns about its product applicability. High vector-associated toxicity and widespread preexisting immunity have been shown to significantly impede the effectiveness of HAdV-5–mediated gene transfer. It is therefore that the in-depth knowledge attained working on HAdV-5 is currently being used to develop alternative vectors. Here, we provide a comprehensive overview of data obtained in recent years disqualifying the HAdV-5 vector for systemic gene delivery as well as novel strategies being pursued to overcome the limitations observed with particular emphasis on the ongoing vectorization efforts to obtain vectors based on alternative serotypes. PMID:26478249

  4. Image Coding Based on Address Vector Quantization.

    Science.gov (United States)

    Feng, Yushu

    Image coding is finding increased application in teleconferencing, archiving, and remote sensing. This thesis investigates the potential of Vector Quantization (VQ), a relatively new source coding technique, for compression of monochromatic and color images. Extensions of the Vector Quantization technique to the Address Vector Quantization method have been investigated. In Vector Quantization, the image data to be encoded are first processed to yield a set of vectors. A codeword from the codebook which best matches the input image vector is then selected. Compression is achieved by replacing the image vector with the index of the code-word which produced the best match, the index is sent to the channel. Reconstruction of the image is done by using a table lookup technique, where the label is simply used as an address for a table containing the representative vectors. A code-book of representative vectors (codewords) is generated using an iterative clustering algorithm such as K-means, or the generalized Lloyd algorithm. A review of different Vector Quantization techniques are given in chapter 1. Chapter 2 gives an overview of codebook design methods including the Kohonen neural network to design codebook. During the encoding process, the correlation of the address is considered and Address Vector Quantization is developed for color image and monochrome image coding. Address VQ which includes static and dynamic processes is introduced in chapter 3. In order to overcome the problems in Hierarchical VQ, Multi-layer Address Vector Quantization is proposed in chapter 4. This approach gives the same performance as that of the normal VQ scheme but the bit rate is about 1/2 to 1/3 as that of the normal VQ method. In chapter 5, a Dynamic Finite State VQ based on a probability transition matrix to select the best subcodebook to encode the image is developed. In chapter 6, a new adaptive vector quantization scheme, suitable for color video coding, called "A Self -Organizing

  5. A method for attitude measurement of a test vehicle based on the tracking of vectors

    International Nuclear Information System (INIS)

    Yang, Ning; Yang, Ming; Huo, Ju

    2015-01-01

    In the vehicle simulation test, in order to improve the measuring precision for the attitude of a test vehicle, a measuring method based on the vectors of light beams is presented, in which light beams are mounted on the test vehicle as the cooperation target, and the attitude of the test vehicle is calculated with the light beams’ vectors in the test vehicle’s coordinate system and the world coordinate system. Meanwhile, in order to expand the measuring range of the attitude parameters, cooperation targets and light beams in each cooperation target are increased. On this basis, the concept of an attitude calculation container is defined, and the selection method for the attitude calculation container that participates in the calculation is given. Simultaneously, the vectors of light beams are tracked so as to ensure the normal calculation of the attitude parameters. The experiments results show that this measuring method based on the tracking of vectors can achieve the high precision and wide range of measurement for the attitude of the test vehicle. (paper)

  6. Dual delivery systems based on polyamine analog BENSpm as prodrug and gene delivery vectors

    Science.gov (United States)

    Zhu, Yu

    Combination drug and gene therapy shows promise in cancer treatment. However, the success of such strategy requires careful selection of the therapeutic agents, as well as development of efficient delivery vectors. BENSpm (N 1, N11-bisethylnorspermine), a polyamine analogue targeting the intracellular polyamine pathway, draws our special attention because of the following reasons: (1) polyamine pathway is frequently dysregulated in cancer; (2) BENSpm exhibits multiple functions to interfere with the polyamine pathway, such as to up-regulate polyamine metabolism enzymes and down-regulate polyamine biosynthesis enzymes. Therefore BENSpm depletes all natural polyamines and leads to apoptosis and cell growth inhibition in a wide range of cancers; (3) preclinical studies proved that BENSpm can act synergistically with various chemotherapy agents, making it a promising candidate in combination therapy; (4) multiple positive charges in BENSpm enable it as a suitable building block for cationic polymers, which can be further applied to gene delivery. In this dissertation, our goal was to design dual-function delivery vector based on BENSpm that can function as a gene delivery vector and, after intracellular degradation, as an active anticancer agent targeting dysregulated polyamine metabolism. We first demonstrated strong synergism between BENSpm and a potential therapeutic gene product TRAIL. Strong synergism was obtained in both estrogen-dependent MCF-7 breast cancer cells and triple-negative MDA-MB-231 breast cancer cells. Significant dose reduction of TRAIL in combination with BENSpm in MDA-MB-231 cells, together with the fact that BENSpm rendered MCF-7 cells more sensitive to TRAIL treatment verified our rationale of designing BENSpm-based delivery platform. This was expected to be beneficial for overcoming drug resistance in chemotherapy, as well as boosting the therapeutic effect of therapeutic genes. We first designed a lipid-based BENSpm dual vector (Lipo

  7. Comparison of four support-vector based function approximators

    NARCIS (Netherlands)

    de Kruif, B.J.; de Vries, Theodorus J.A.

    2004-01-01

    One of the uses of the support vector machine (SVM), as introduced in V.N. Vapnik (2000), is as a function approximator. The SVM and approximators based on it, approximate a relation in data by applying interpolation between so-called support vectors, being a limited number of samples that have been

  8. Wide-angle full-vector beam propagation method based on an alternating direction implicit preconditioner

    Science.gov (United States)

    Chui, Siu Lit; Lu, Ya Yan

    2004-03-01

    Wide-angle full-vector beam propagation methods (BPMs) for three-dimensional wave-guiding structures can be derived on the basis of rational approximants of a square root operator or its exponential (i.e., the one-way propagator). While the less accurate BPM based on the slowly varying envelope approximation can be efficiently solved by the alternating direction implicit (ADI) method, the wide-angle variants involve linear systems that are more difficult to handle. We present an efficient solver for these linear systems that is based on a Krylov subspace method with an ADI preconditioner. The resulting wide-angle full-vector BPM is used to simulate the propagation of wave fields in a Y branch and a taper.

  9. Quantitative Assessment of Pap Smear Cells by PC-Based Cytopathologic Image Analysis System and Support Vector Machine

    Science.gov (United States)

    Huang, Po-Chi; Chan, Yung-Kuan; Chan, Po-Chou; Chen, Yung-Fu; Chen, Rung-Ching; Huang, Yu-Ruei

    Cytologic screening has been widely used for controlling the prevalence of cervical cancer. Errors from sampling, screening and interpretation, still concealed some unpleasant results. This study aims at designing a cellular image analysis system based on feasible and available software and hardware for a routine cytologic laboratory. Totally 1814 cellular images from the liquid-based cervical smears with Papanicolaou stain in 100x, 200x, and 400x magnification were captured by a digital camera. Cell images were reviewed by pathologic experts with peer agreement and only 503 images were selected for further study. The images were divided into 4 diagnostic categories. A PC-based cellular image analysis system (PCCIA) was developed for computing morphometric parameters. Then support vector machine (SVM) was used to classify signature patterns. The results show that the selected 13 morphometric parameters can be used to correctly differentiate the dysplastic cells from the normal cells (pgynecologic cytologic specimens.

  10. Virtual-vector-based space vector pulse width modulation of the DC-AC multilevel-clamped multilevel converter (MLC2)

    DEFF Research Database (Denmark)

    Rodriguez, Pedro; Busquets-Monge, Sergio; Blaabjerg, Frede

    2011-01-01

    This work presents the development of the space vector pulse width modulation (SVPWM) of a new multi-level converter topology. First, the proposed converter and its natural space vector diagram are presented. Secondly, a modified space vector diagram based on the virtual-vectors technique is show...

  11. Vector and Raster Data Storage Based on Morton Code

    Science.gov (United States)

    Zhou, G.; Pan, Q.; Yue, T.; Wang, Q.; Sha, H.; Huang, S.; Liu, X.

    2018-05-01

    Even though geomatique is so developed nowadays, the integration of spatial data in vector and raster formats is still a very tricky problem in geographic information system environment. And there is still not a proper way to solve the problem. This article proposes a method to interpret vector data and raster data. In this paper, we saved the image data and building vector data of Guilin University of Technology to Oracle database. Then we use ADO interface to connect database to Visual C++ and convert row and column numbers of raster data and X Y of vector data to Morton code in Visual C++ environment. This method stores vector and raster data to Oracle Database and uses Morton code instead of row and column and X Y to mark the position information of vector and raster data. Using Morton code to mark geographic information enables storage of data make full use of storage space, simultaneous analysis of vector and raster data more efficient and visualization of vector and raster more intuitive. This method is very helpful for some situations that need to analyse or display vector data and raster data at the same time.

  12. Link-Based Similarity Measures Using Reachability Vectors

    Directory of Open Access Journals (Sweden)

    Seok-Ho Yoon

    2014-01-01

    Full Text Available We present a novel approach for computing link-based similarities among objects accurately by utilizing the link information pertaining to the objects involved. We discuss the problems with previous link-based similarity measures and propose a novel approach for computing link based similarities that does not suffer from these problems. In the proposed approach each target object is represented by a vector. Each element of the vector corresponds to all the objects in the given data, and the value of each element denotes the weight for the corresponding object. As for this weight value, we propose to utilize the probability of reaching from the target object to the specific object, computed using the “Random Walk with Restart” strategy. Then, we define the similarity between two objects as the cosine similarity of the two vectors. In this paper, we provide examples to show that our approach does not suffer from the aforementioned problems. We also evaluate the performance of the proposed methods in comparison with existing link-based measures, qualitatively and quantitatively, with respect to two kinds of data sets, scientific papers and Web documents. Our experimental results indicate that the proposed methods significantly outperform the existing measures.

  13. A Wavelet Kernel-Based Primal Twin Support Vector Machine for Economic Development Prediction

    Directory of Open Access Journals (Sweden)

    Fang Su

    2013-01-01

    Full Text Available Economic development forecasting allows planners to choose the right strategies for the future. This study is to propose economic development prediction method based on the wavelet kernel-based primal twin support vector machine algorithm. As gross domestic product (GDP is an important indicator to measure economic development, economic development prediction means GDP prediction in this study. The wavelet kernel-based primal twin support vector machine algorithm can solve two smaller sized quadratic programming problems instead of solving a large one as in the traditional support vector machine algorithm. Economic development data of Anhui province from 1992 to 2009 are used to study the prediction performance of the wavelet kernel-based primal twin support vector machine algorithm. The comparison of mean error of economic development prediction between wavelet kernel-based primal twin support vector machine and traditional support vector machine models trained by the training samples with the 3–5 dimensional input vectors, respectively, is given in this paper. The testing results show that the economic development prediction accuracy of the wavelet kernel-based primal twin support vector machine model is better than that of traditional support vector machine.

  14. Vectorization, parallelization and porting of nuclear codes on the VPP500 system (vectorization). Progress report fiscal 1997

    International Nuclear Information System (INIS)

    Kawasaki, Nobuo; Ogasawara, Shinobu; Adachi, Masaaki; Kume, Etsuo; Ishizuki, Shigeru; Tanabe, Hidenobu; Nemoto, Toshiyuki; Kawai, Wataru; Watanabe, Hideo

    1999-05-01

    Several computer codes in the nuclear field have been vectorized, parallelized and transported on the FUJITSU VPP500 system and/or the AP3000 system at Center for Promotion of Computational Science and Engineering in Japan Atomic Energy Research Institute. We dealt with 14 codes in fiscal 1997. These results are reported in 3 parts, i.e., the vectorization part, the parallelization part and the porting part. In this report, we describe the vectorization. In this vectorization part, the vectorization of multidimensional two-fluid model code ACE-3D for evaluation of constitutive equations, statistical decay code SD and three-dimensional thermal analysis code for in-core test section (T2) of HENDEL SSPHEAT are described. In the parallelization part, the parallelization of cylindrical direct numerical simulation code CYLDNS44N, worldwide version of system for prediction of environmental emergency dose information code WSPEEDI, extension of quantum molecular dynamics code EQMD and three-dimensional non-steady compressible fluid dynamics code STREAM are described. In the porting part, the porting of transient reactor analysis code TRAC-BF1 and Monte Carlo radiation transport code MCNP4A on the AP3000 are described. In addition, a modification of program libraries for command-driven interactive data analysis plotting program IPLOT is described. (author)

  15. Efficient Vector-Based Forwarding for Underwater Sensor Networks

    Directory of Open Access Journals (Sweden)

    Peng Xie

    2010-01-01

    Full Text Available Underwater Sensor Networks (UWSNs are significantly different from terrestrial sensor networks in the following aspects: low bandwidth, high latency, node mobility, high error probability, and 3-dimensional space. These new features bring many challenges to the network protocol design of UWSNs. In this paper, we tackle one fundamental problem in UWSNs: robust, scalable, and energy efficient routing. We propose vector-based forwarding (VBF, a geographic routing protocol. In VBF, the forwarding path is guided by a vector from the source to the target, no state information is required on the sensor nodes, and only a small fraction of the nodes is involved in routing. To improve the robustness, packets are forwarded in redundant and interleaved paths. Further, a localized and distributed self-adaptation algorithm allows the nodes to reduce energy consumption by discarding redundant packets. VBF performs well in dense networks. For sparse networks, we propose a hop-by-hop vector-based forwarding (HH-VBF protocol, which adapts the vector-based approach at every hop. We evaluate the performance of VBF and HH-VBF through extensive simulations. The simulation results show that VBF achieves high packet delivery ratio and energy efficiency in dense networks and HH-VBF has high packet delivery ratio even in sparse networks.

  16. Chikungunya Virus Vaccines: Viral Vector-Based Approaches.

    Science.gov (United States)

    Ramsauer, Katrin; Tangy, Frédéric

    2016-12-15

    In 2013, a major chikungunya virus (CHIKV) epidemic reached the Americas. In the past 2 years, >1.7 million people have been infected. In light of the current epidemic, with millions of people in North and South America at risk, efforts to rapidly develop effective vaccines have increased. Here, we focus on CHIKV vaccines that use viral-vector technologies. This group of vaccine candidates shares an ability to potently induce humoral and cellular immune responses by use of highly attenuated and safe vaccine backbones. So far, well-described vectors such as modified vaccinia virus Ankara, complex adenovirus, vesicular stomatitis virus, alphavirus-based chimeras, and measles vaccine Schwarz strain (MV/Schw) have been described as potential vaccines. We summarize here the recent data on these experimental vaccines, with a focus on the preclinical and clinical activities on the MV/Schw-based candidate, which is the first CHIKV-vectored vaccine that has completed a clinical trial. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

  17. Vectorization, parallelization and porting of nuclear codes on the VPP500 system (vectorization). Progress report fiscal 1996

    Energy Technology Data Exchange (ETDEWEB)

    Nemoto, Toshiyuki; Kawai, Wataru [Fujitsu Ltd., Tokyo (Japan); Kawasaki, Nobuo [and others

    1997-12-01

    Several computer codes in the nuclear field have been vectorized, parallelized and transported on the FUJITSU VPP500 system at Center for Promotion of Computational Science and Engineering in Japan Atomic Energy Research Institute. These results are reported in 3 parts, i.e., the vectorization part, the parallelization part and the porting part. In this report, we describe the vectorization. In this vectorization part, the vectorization of two and three dimensional discrete ordinates simulation code DORT-TORT, gas dynamics analysis code FLOWGR and relativistic Boltzmann-Uehling-Uhlenbeck simulation code RBUU are described. In the parallelization part, the parallelization of 2-Dimensional relativistic electromagnetic particle code EM2D, Cylindrical Direct Numerical Simulation code CYLDNS and molecular dynamics code for simulating radiation damages in diamond crystals DGR are described. And then, in the porting part, the porting of reactor safety analysis code RELAP5/MOD3.2 and RELAP5/MOD3.2.1.2, nuclear data processing system NJOY and 2-D multigroup discrete ordinate transport code TWOTRAN-II are described. And also, a survey for the porting of command-driven interactive data analysis plotting program IPLOT are described. (author)

  18. Signal Detection for QPSK Based Cognitive Radio Systems using Support Vector Machines

    Directory of Open Access Journals (Sweden)

    M. T. Mushtaq

    2015-04-01

    Full Text Available Cognitive radio based network enables opportunistic dynamic spectrum access by sensing, adopting and utilizing the unused portion of licensed spectrum bands. Cognitive radio is intelligent enough to adapt the communication parameters of the unused licensed spectrum. Spectrum sensing is one of the most important tasks of the cognitive radio cycle. In this paper, the auto-correlation function kernel based Support Vector Machine (SVM classifier along with Welch's Periodogram detector is successfully implemented for the detection of four QPSK (Quadrature Phase Shift Keying based signals propagating through an AWGN (Additive White Gaussian Noise channel. It is shown that the combination of statistical signal processing and machine learning concepts improve the spectrum sensing process and spectrum sensing is possible even at low Signal to Noise Ratio (SNR values up to -50 dB.

  19. Generalized decompositions of dynamic systems and vector Lyapunov functions

    Science.gov (United States)

    Ikeda, M.; Siljak, D. D.

    1981-10-01

    The notion of decomposition is generalized to provide more freedom in constructing vector Lyapunov functions for stability analysis of nonlinear dynamic systems. A generalized decomposition is defined as a disjoint decomposition of a system which is obtained by expanding the state-space of a given system. An inclusion principle is formulated for the solutions of the expansion to include the solutions of the original system, so that stability of the expansion implies stability of the original system. Stability of the expansion can then be established by standard disjoint decompositions and vector Lyapunov functions. The applicability of the new approach is demonstrated using the Lotka-Volterra equations.

  20. Stability and Control of Large-Scale Dynamical Systems A Vector Dissipative Systems Approach

    CERN Document Server

    Haddad, Wassim M

    2011-01-01

    Modern complex large-scale dynamical systems exist in virtually every aspect of science and engineering, and are associated with a wide variety of physical, technological, environmental, and social phenomena, including aerospace, power, communications, and network systems, to name just a few. This book develops a general stability analysis and control design framework for nonlinear large-scale interconnected dynamical systems, and presents the most complete treatment on vector Lyapunov function methods, vector dissipativity theory, and decentralized control architectures. Large-scale dynami

  1. Support vector machines optimization based theory, algorithms, and extensions

    CERN Document Server

    Deng, Naiyang; Zhang, Chunhua

    2013-01-01

    Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components of support vector machines (SVMs)-classification problems and regression problems. The book emphasizes the close connection between optimization theory and SVMs since optimization is one of the pillars on which SVMs are built.The authors share insight on many of their research achievements. They give a precise interpretation of statistical leaning theory for C-support vector classification. They also discuss regularized twi

  2. Misalignment calibration of geomagnetic vector measurement system using parallelepiped frame rotation method

    International Nuclear Information System (INIS)

    Pang, Hongfeng; Zhu, XueJun; Pan, Mengchun; Zhang, Qi; Wan, Chengbiao; Luo, Shitu; Chen, Dixiang; Chen, Jinfei; Li, Ji; Lv, Yunxiao

    2016-01-01

    Misalignment error is one key factor influencing the measurement accuracy of geomagnetic vector measurement system, which should be calibrated with the difficulties that sensors measure different physical information and coordinates are invisible. A new misalignment calibration method by rotating a parallelepiped frame is proposed. Simulation and experiment result show the effectiveness of calibration method. The experimental system mainly contains DM-050 three-axis fluxgate magnetometer, INS (inertia navigation system), aluminium parallelepiped frame, aluminium plane base. Misalignment angles are calculated by measured data of magnetometer and INS after rotating the aluminium parallelepiped frame on aluminium plane base. After calibration, RMS error of geomagnetic north, vertical and east are reduced from 349.441 nT, 392.530 nT and 562.316 nT to 40.130 nT, 91.586 nT and 141.989 nT respectively. - Highlights: • A new misalignment calibration method by rotating a parallelepiped frame is proposed. • It does not need to know sensor attitude information or local dip angle. • The calibration system attitude change angle is not strictly required. • It can be widely used when sensors measure different physical information. • Geomagnetic vector measurement error is reduced evidently.

  3. Misalignment calibration of geomagnetic vector measurement system using parallelepiped frame rotation method

    Energy Technology Data Exchange (ETDEWEB)

    Pang, Hongfeng [Academy of Equipment, Beijing 101416 (China); College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073 (China); Zhu, XueJun, E-mail: zhuxuejun1990@126.com [College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073 (China); Pan, Mengchun; Zhang, Qi; Wan, Chengbiao; Luo, Shitu; Chen, Dixiang; Chen, Jinfei; Li, Ji; Lv, Yunxiao [College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073 (China)

    2016-12-01

    Misalignment error is one key factor influencing the measurement accuracy of geomagnetic vector measurement system, which should be calibrated with the difficulties that sensors measure different physical information and coordinates are invisible. A new misalignment calibration method by rotating a parallelepiped frame is proposed. Simulation and experiment result show the effectiveness of calibration method. The experimental system mainly contains DM-050 three-axis fluxgate magnetometer, INS (inertia navigation system), aluminium parallelepiped frame, aluminium plane base. Misalignment angles are calculated by measured data of magnetometer and INS after rotating the aluminium parallelepiped frame on aluminium plane base. After calibration, RMS error of geomagnetic north, vertical and east are reduced from 349.441 nT, 392.530 nT and 562.316 nT to 40.130 nT, 91.586 nT and 141.989 nT respectively. - Highlights: • A new misalignment calibration method by rotating a parallelepiped frame is proposed. • It does not need to know sensor attitude information or local dip angle. • The calibration system attitude change angle is not strictly required. • It can be widely used when sensors measure different physical information. • Geomagnetic vector measurement error is reduced evidently.

  4. Large-scale production of lentiviral vector in a closed system hollow fiber bioreactor

    Directory of Open Access Journals (Sweden)

    Jonathan Sheu

    Full Text Available Lentiviral vectors are widely used in the field of gene therapy as an effective method for permanent gene delivery. While current methods of producing small scale vector batches for research purposes depend largely on culture flasks, the emergence and popularity of lentiviral vectors in translational, preclinical and clinical research has demanded their production on a much larger scale, a task that can be difficult to manage with the numbers of producer cell culture flasks required for large volumes of vector. To generate a large scale, partially closed system method for the manufacturing of clinical grade lentiviral vector suitable for the generation of induced pluripotent stem cells (iPSCs, we developed a method employing a hollow fiber bioreactor traditionally used for cell expansion. We have demonstrated the growth, transfection, and vector-producing capability of 293T producer cells in this system. Vector particle RNA titers after subsequent vector concentration yielded values comparable to lentiviral iPSC induction vector batches produced using traditional culture methods in 225 cm2 flasks (T225s and in 10-layer cell factories (CF10s, while yielding a volume nearly 145 times larger than the yield from a T225 flask and nearly three times larger than the yield from a CF10. Employing a closed system hollow fiber bioreactor for vector production offers the possibility of manufacturing large quantities of gene therapy vector while minimizing reagent usage, equipment footprint, and open system manipulation.

  5. Heading-vector navigation based on head-direction cells and path integration.

    Science.gov (United States)

    Kubie, John L; Fenton, André A

    2009-05-01

    Insect navigation is guided by heading vectors that are computed by path integration. Mammalian navigation models, on the other hand, are typically based on map-like place representations provided by hippocampal place cells. Such models compute optimal routes as a continuous series of locations that connect the current location to a goal. We propose a "heading-vector" model in which head-direction cells or their derivatives serve both as key elements in constructing the optimal route and as the straight-line guidance during route execution. The model is based on a memory structure termed the "shortcut matrix," which is constructed during the initial exploration of an environment when a set of shortcut vectors between sequential pairs of visited waypoint locations is stored. A mechanism is proposed for calculating and storing these vectors that relies on a hypothesized cell type termed an "accumulating head-direction cell." Following exploration, shortcut vectors connecting all pairs of waypoint locations are computed by vector arithmetic and stored in the shortcut matrix. On re-entry, when local view or place representations query the shortcut matrix with a current waypoint and goal, a shortcut trajectory is retrieved. Since the trajectory direction is in head-direction compass coordinates, navigation is accomplished by tracking the firing of head-direction cells that are tuned to the heading angle. Section 1 of the manuscript describes the properties of accumulating head-direction cells. It then shows how accumulating head-direction cells can store local vectors and perform vector arithmetic to perform path-integration-based homing. Section 2 describes the construction and use of the shortcut matrix for computing direct paths between any pair of locations that have been registered in the shortcut matrix. In the discussion, we analyze the advantages of heading-based navigation over map-based navigation. Finally, we survey behavioral evidence that nonhippocampal

  6. Vaxvec: The first web-based recombinant vaccine vector database and its data analysis

    Science.gov (United States)

    Deng, Shunzhou; Martin, Carly; Patil, Rasika; Zhu, Felix; Zhao, Bin; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    A recombinant vector vaccine uses an attenuated virus, bacterium, or parasite as the carrier to express a heterologous antigen(s). Many recombinant vaccine vectors and related vaccines have been developed and extensively investigated. To compare and better understand recombinant vectors and vaccines, we have generated Vaxvec (http://www.violinet.org/vaxvec), the first web-based database that stores various recombinant vaccine vectors and those experimentally verified vaccines that use these vectors. Vaxvec has now included 59 vaccine vectors that have been used in 196 recombinant vector vaccines against 66 pathogens and cancers. These vectors are classified to 41 viral vectors, 15 bacterial vectors, 1 parasitic vector, and 1 fungal vector. The most commonly used viral vaccine vectors are double-stranded DNA viruses, including herpesviruses, adenoviruses, and poxviruses. For example, Vaxvec includes 63 poxvirus-based recombinant vaccines for over 20 pathogens and cancers. Vaxvec collects 30 recombinant vector influenza vaccines that use 17 recombinant vectors and were experimentally tested in 7 animal models. In addition, over 60 protective antigens used in recombinant vector vaccines are annotated and analyzed. User-friendly web-interfaces are available for querying various data in Vaxvec. To support data exchange, the information of vaccine vectors, vaccines, and related information is stored in the Vaccine Ontology (VO). Vaxvec is a timely and vital source of vaccine vector database and facilitates efficient vaccine vector research and development. PMID:26403370

  7. Upport vector machines for nonlinear kernel ARMA system identification.

    Science.gov (United States)

    Martínez-Ramón, Manel; Rojo-Alvarez, José Luis; Camps-Valls, Gustavo; Muñioz-Marí, Jordi; Navia-Vázquez, Angel; Soria-Olivas, Emilio; Figueiras-Vidal, Aníbal R

    2006-11-01

    Nonlinear system identification based on support vector machines (SVM) has been usually addressed by means of the standard SVM regression (SVR), which can be seen as an implicit nonlinear autoregressive and moving average (ARMA) model in some reproducing kernel Hilbert space (RKHS). The proposal of this letter is twofold. First, the explicit consideration of an ARMA model in an RKHS (SVM-ARMA2K) is proposed. We show that stating the ARMA equations in an RKHS leads to solving the regularized normal equations in that RKHS, in terms of the autocorrelation and cross correlation of the (nonlinearly) transformed input and output discrete time processes. Second, a general class of SVM-based system identification nonlinear models is presented, based on the use of composite Mercer's kernels. This general class can improve model flexibility by emphasizing the input-output cross information (SVM-ARMA4K), which leads to straightforward and natural combinations of implicit and explicit ARMA models (SVR-ARMA2K and SVR-ARMA4K). Capabilities of these different SVM-based system identification schemes are illustrated with two benchmark problems.

  8. Breast cancer risk assessment and diagnosis model using fuzzy support vector machine based expert system

    Science.gov (United States)

    Dheeba, J.; Jaya, T.; Singh, N. Albert

    2017-09-01

    Classification of cancerous masses is a challenging task in many computerised detection systems. Cancerous masses are difficult to detect because these masses are obscured and subtle in mammograms. This paper investigates an intelligent classifier - fuzzy support vector machine (FSVM) applied to classify the tissues containing masses on mammograms for breast cancer diagnosis. The algorithm utilises texture features extracted using Laws texture energy measures and a FSVM to classify the suspicious masses. The new FSVM treats every feature as both normal and abnormal samples, but with different membership. By this way, the new FSVM have more generalisation ability to classify the masses in mammograms. The classifier analysed 219 clinical mammograms collected from breast cancer screening laboratory. The tests made on the real clinical mammograms shows that the proposed detection system has better discriminating power than the conventional support vector machine. With the best combination of FSVM and Laws texture features, the area under the Receiver operating characteristic curve reached .95, which corresponds to a sensitivity of 93.27% with a specificity of 87.17%. The results suggest that detecting masses using FSVM contribute to computer-aided detection of breast cancer and as a decision support system for radiologists.

  9. Environmental noise forecasting based on support vector machine

    Science.gov (United States)

    Fu, Yumei; Zan, Xinwu; Chen, Tianyi; Xiang, Shihan

    2018-01-01

    As an important pollution source, the noise pollution is always the researcher's focus. Especially in recent years, the noise pollution is seriously harmful to the human beings' environment, so the research about the noise pollution is a very hot spot. Some noise monitoring technologies and monitoring systems are applied in the environmental noise test, measurement and evaluation. But, the research about the environmental noise forecasting is weak. In this paper, a real-time environmental noise monitoring system is introduced briefly. This monitoring system is working in Mianyang City, Sichuan Province. It is monitoring and collecting the environmental noise about more than 20 enterprises in this district. Based on the large amount of noise data, the noise forecasting by the Support Vector Machine (SVM) is studied in detail. Compared with the time series forecasting model and the artificial neural network forecasting model, the SVM forecasting model has some advantages such as the smaller data size, the higher precision and stability. The noise forecasting results based on the SVM can provide the important and accuracy reference to the prevention and control of the environmental noise.

  10. Coal demand prediction based on a support vector machine model

    Energy Technology Data Exchange (ETDEWEB)

    Jia, Cun-liang; Wu, Hai-shan; Gong, Dun-wei [China University of Mining & Technology, Xuzhou (China). School of Information and Electronic Engineering

    2007-01-15

    A forecasting model for coal demand of China using a support vector regression was constructed. With the selected embedding dimension, the output vectors and input vectors were constructed based on the coal demand of China from 1980 to 2002. After compared with lineal kernel and Sigmoid kernel, a radial basis function(RBF) was adopted as the kernel function. By analyzing the relationship between the error margin of prediction and the model parameters, the proper parameters were chosen. The support vector machines (SVM) model with multi-input and single output was proposed. Compared the predictor based on RBF neural networks with test datasets, the results show that the SVM predictor has higher precision and greater generalization ability. In the end, the coal demand from 2003 to 2006 is accurately forecasted. l0 refs., 2 figs., 4 tabs.

  11. Recent Progress on the Second Generation CMORPH: LEO-IR Based Precipitation Estimates and Cloud Motion Vector

    Science.gov (United States)

    Xie, Pingping; Joyce, Robert; Wu, Shaorong

    2015-04-01

    As reported at the EGU General Assembly of 2014, a prototype system was developed for the second generation CMORPH to produce global analyses of 30-min precipitation on a 0.05olat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. Key to the success of the 2nd generation CMORPH, among a couple of other elements, are the development of a LEO-IR based precipitation estimation to fill in the polar gaps and objectively analyzed cloud motion vectors to capture the cloud movements of various spatial scales over the entire globe. In this presentation, we report our recent work on the refinement for these two important algorithm components. The prototype algorithm for the LEO IR precipitation estimation is refined to achieve improved quantitative accuracy and consistency with PMW retrievals. AVHRR IR TBB data from all LEO satellites are first remapped to a 0.05olat/lon grid over the entire globe and in a 30-min interval. Temporally and spatially co-located data pairs of the LEO TBB and inter-calibrated combined satellite PMW retrievals (MWCOMB) are then collected to construct tables. Precipitation at a grid box is derived from the TBB through matching the PDF tables for the TBB and the MWCOMB. This procedure is implemented for different season, latitude band and underlying surface types to account for the variations in the cloud - precipitation relationship. At the meantime, a sub-system is developed to construct analyzed fields of

  12. Linear Matrix Inequalities for Analysis and Control of Linear Vector Second-Order Systems

    DEFF Research Database (Denmark)

    Adegas, Fabiano Daher; Stoustrup, Jakob

    2015-01-01

    the Lyapunov matrix and the system matrices by introducing matrix multipliers, which potentially reduce conservativeness in hard control problems. Multipliers facilitate the usage of parameter-dependent Lyapunov functions as certificates of stability of uncertain and time-varying vector second-order systems......SUMMARY Many dynamical systems are modeled as vector second-order differential equations. This paper presents analysis and synthesis conditions in terms of LMI with explicit dependence in the coefficient matrices of vector second-order systems. These conditions benefit from the separation between....... The conditions introduced in this work have the potential to increase the practice of analyzing and controlling systems directly in vector second-order form. Copyright © 2014 John Wiley & Sons, Ltd....

  13. Segmentation of Clinical Endoscopic Images Based on the Classification of Topological Vector Features

    Directory of Open Access Journals (Sweden)

    O. A. Dunaeva

    2013-01-01

    Full Text Available In this work, we describe a prototype of an automatic segmentation system and annotation of endoscopy images. The used algorithm is based on the classification of vectors of the topological features of the original image. We use the image processing scheme which includes image preprocessing, calculation of vector descriptors defined for every point of the source image and the subsequent classification of descriptors. Image preprocessing includes finding and selecting artifacts and equalizating the image brightness. In this work, we give the detailed algorithm of the construction of topological descriptors and the classifier creating procedure based on mutual sharing the AdaBoost scheme and a naive Bayes classifier. In the final section, we show the results of the classification of real endoscopic images.

  14. I-F starting method with smooth transition to EMF based motion-sensorless vector control of PM synchronous motor/generator

    DEFF Research Database (Denmark)

    Blaabjerg, Frede; Teodorescu, Remus; Fatu, M.

    2008-01-01

    This paper proposes a novel hybrid motion- sensorless control system for permanent magnet synchronous motors (PMSM) using a new robust start-up method called I-f control, and a smooth transition to emf-based vector control. The I-f method is based on separate control of id, iq currents with the r......This paper proposes a novel hybrid motion- sensorless control system for permanent magnet synchronous motors (PMSM) using a new robust start-up method called I-f control, and a smooth transition to emf-based vector control. The I-f method is based on separate control of id, iq currents......-adaptive compensator to eliminate dc-offset and phase-delay. Digital simulations for PMSM start-up with full load torque are presented for different initial rotor-positions. The transitions from I-f to emf motion-sensorless vector control and back as well, at very low-speeds, are fully validated by experimental...

  15. Construction of permanently inducible miRNA-based expression vectors using site-specific recombinases

    Directory of Open Access Journals (Sweden)

    Garwick-Coppens Sara E

    2011-11-01

    Full Text Available Abstract Background RNA interference (RNAi is a conserved gene silencing mechanism mediated by small inhibitory microRNAs (miRNAs. Promoter-driven miRNA expression vectors have emerged as important tools for delivering natural or artificially designed miRNAs to eukaryotic cells and organisms. Such systems can be used to query the normal or pathogenic functions of natural miRNAs or messenger RNAs, or to therapeutically silence disease genes. Results As with any molecular cloning procedure, building miRNA-based expression constructs requires a time investment and some molecular biology skills. To improve efficiency and accelerate the construction process, we developed a method to rapidly generate miRNA expression vectors using recombinases instead of more traditional cut-and-paste molecular cloning techniques. In addition to streamlining the construction process, our cloning strategy provides vectors with added versatility. In our system, miRNAs can be constitutively expressed from the U6 promoter, or inducibly expressed by Cre recombinase. We also engineered a built-in mechanism to destroy the vector with Flp recombinase, if desired. Finally, to further simplify the construction process, we developed a software package that automates the prediction and design of optimal miRNA sequences using our system. Conclusions We designed and tested a modular system to rapidly clone miRNA expression cassettes. Our strategy reduces the hands-on time required to successfully generate effective constructs, and can be implemented in labs with minimal molecular cloning expertise. This versatile system provides options that permit constitutive or inducible miRNA expression, depending upon the needs of the end user. As such, it has utility for basic or translational applications.

  16. A Personalized Electronic Movie Recommendation System Based on Support Vector Machine and Improved Particle Swarm Optimization.

    Science.gov (United States)

    Wang, Xibin; Luo, Fengji; Qian, Ying; Ranzi, Gianluca

    2016-01-01

    With the rapid development of ICT and Web technologies, a large an amount of information is becoming available and this is producing, in some instances, a condition of information overload. Under these conditions, it is difficult for a person to locate and access useful information for making decisions. To address this problem, there are information filtering systems, such as the personalized recommendation system (PRS) considered in this paper, that assist a person in identifying possible products or services of interest based on his/her preferences. Among available approaches, collaborative Filtering (CF) is one of the most widely used recommendation techniques. However, CF has some limitations, e.g., the relatively simple similarity calculation, cold start problem, etc. In this context, this paper presents a new regression model based on the support vector machine (SVM) classification and an improved PSO (IPSO) for the development of an electronic movie PRS. In its implementation, a SVM classification model is first established to obtain a preliminary movie recommendation list based on which a SVM regression model is applied to predict movies' ratings. The proposed PRS not only considers the movie's content information but also integrates the users' demographic and behavioral information to better capture the users' interests and preferences. The efficiency of the proposed method is verified by a series of experiments based on the MovieLens benchmark data set.

  17. Analysis of Vector Quantizers Using Transformed Codebooks with Application to Feedback-Based Multiple Antenna Systems

    Directory of Open Access Journals (Sweden)

    Bhaskar D. Rao

    2008-07-01

    Full Text Available Transformed codebooks are obtained by a transformation of a given codebook to best match the statistical environment at hand. The procedure, though suboptimal, has recently been suggested for feedback of channel state information (CSI in multiple antenna systems with correlated channels because of their simplicity and effectiveness. In this paper, we first consider the general distortion analysis of vector quantizers with transformed codebooks. Bounds on the average system distortion of this class of quantizers are provided. It exposes the effects of two kinds of suboptimality introduced by the transformed codebook, namely, the loss caused by suboptimal point density and the loss caused by mismatched Voronoi shape. We then focus our attention on the application of the proposed general framework to providing capacity analysis of a feedback-based MISO system over spatially correlated fading channels. In particular, with capacity loss as an objective function, upper and lower bounds on the average distortion of MISO systems with transformed codebooks are provided and compared to that of the optimal channel quantizers. The expressions are examined to provide interesting insights in the high and low SNR regime. Numerical and simulation results are presented which confirm the tightness of the distortion bounds.

  18. A least square support vector machine-based approach for contingency classification and ranking in a large power system

    Directory of Open Access Journals (Sweden)

    Bhanu Pratap Soni

    2016-12-01

    Full Text Available This paper proposes an effective supervised learning approach for static security assessment of a large power system. Supervised learning approach employs least square support vector machine (LS-SVM to rank the contingencies and predict the system severity level. The severity of the contingency is measured by two scalar performance indices (PIs: line MVA performance index (PIMVA and Voltage-reactive power performance index (PIVQ. SVM works in two steps. Step I is the estimation of both standard indices (PIMVA and PIVQ that is carried out under different operating scenarios and Step II contingency ranking is carried out based on the values of PIs. The effectiveness of the proposed methodology is demonstrated on IEEE 39-bus (New England system. The approach can be beneficial tool which is less time consuming and accurate security assessment and contingency analysis at energy management center.

  19. Managing the resilience space of the German energy system - A vector analysis.

    Science.gov (United States)

    Schlör, Holger; Venghaus, Sandra; Märker, Carolin; Hake, Jürgen-Friedrich

    2018-07-15

    The UN Sustainable Development Goals formulated in 2016 confirmed the sustainability concept of the Earth Summit of 1992 and supported UNEP's green economy transition concept. The transformation of the energy system (Energiewende) is the keystone of Germany's sustainability strategy and of the German green economy concept. We use ten updated energy-related indicators of the German sustainability strategy to analyse the German energy system. The development of the sustainable indicators is examined in the monitoring process by a vector analysis performed in two-dimensional Euclidean space (Euclidean plane). The aim of the novel vector analysis is to measure the current status of the Energiewende in Germany and thereby provide decision makers with information about the strains for the specific remaining pathway of the single indicators and of the total system in order to meet the sustainability targets of the Energiewende. Within this vector model, three vectors (the normative sustainable development vector, the real development vector, and the green economy vector) define the resilience space of our analysis. The resilience space encloses a number of vectors representing different pathways with different technological and socio-economic strains to achieve a sustainable development of the green economy. In this space, the decision will be made as to whether the government measures will lead to a resilient energy system or whether a readjustment of indicator targets or political measures is necessary. The vector analysis enables us to analyse both the government's ambitiousness, which is expressed in the sustainability target for the indicators at the start of the sustainability strategy representing the starting preference order of the German government (SPO) and, secondly, the current preference order of German society in order to bridge the remaining distance to reach the specific sustainability goals of the strategy summarized in the current preference order (CPO

  20. Food-grade host/vector expression system for Lactobacillus casei based on complementation of plasmid-associated phospho-beta-galactosidase gene lacG.

    Science.gov (United States)

    Takala, T M; Saris, P E J; Tynkkynen, S S H

    2003-01-01

    A new food-grade host/vector system for Lactobacillus casei based on lactose selection was constructed. The wild-type non-starter host Lb. casei strain E utilizes lactose via a plasmid-encoded phosphotransferase system. For food-grade cloning, a stable lactose-deficient mutant was constructed by deleting a 141-bp fragment from the phospho-beta-galactosidase gene lacG via gene replacement. The deletion resulted in an inactive phospho-beta-galactosidase enzyme with an internal in-frame deletion of 47 amino acids. A complementation plasmid was constructed containing a replicon from Lactococcus lactis, the lacG gene from Lb. casei, and the constitutive promoter of pepR for lacG expression from Lb. rhamnosus. The expression of the lacG gene from the resulting food-grade plasmid pLEB600 restored the ability of the lactose-negative mutant strain to grow on lactose to the wild-type level. The vector pLEB600 was used for expression of the proline iminopeptidase gene pepI from Lb. helveticus in Lb. casei. The results show that the food-grade expression system reported in this paper can be used for expression of foreign genes in Lb. casei.

  1. Multiscale Distance Coherence Vector Algorithm for Content-Based Image Retrieval

    Science.gov (United States)

    Jiexian, Zeng; Xiupeng, Liu

    2014-01-01

    Multiscale distance coherence vector algorithm for content-based image retrieval (CBIR) is proposed due to the same descriptor with different shapes and the shortcomings of antinoise performance of the distance coherence vector algorithm. By this algorithm, the image contour curve is evolved by Gaussian function first, and then the distance coherence vector is, respectively, extracted from the contour of the original image and evolved images. Multiscale distance coherence vector was obtained by reasonable weight distribution of the distance coherence vectors of evolved images contour. This algorithm not only is invariable to translation, rotation, and scaling transformation but also has good performance of antinoise. The experiment results show us that the algorithm has a higher recall rate and precision rate for the retrieval of images polluted by noise. PMID:24883416

  2. Diagnosis of nutrient imbalances with vector analysis in agroforestry systems.

    Science.gov (United States)

    Isaac, Marney E; Kimaro, Anthony A

    2011-01-01

    Agricultural intensification has had unintended environmental consequences, including increased nutrient leaching and surface runoff and other agrarian-derived pollutants. Improved diagnosis of on-farm nutrient dynamics will have the advantage of increasing yields and will diminish financial and environmental costs. To achieve this, a management support system that allows for site-specific rapid evaluation of nutrient production imbalances and subsequent management prescriptions is needed for agroecological design. Vector diagnosis, a bivariate model to depict changes in yield and nutritional response simultaneously in a single graph, facilitates identification of nutritional status such as growth dilution, deficiency, sufficiency, luxury uptake, and toxicity. Quantitative data from cocoa agroforestry systems and pigeonpea intercropping trials in Ghana and Tanzania, respectively, were re-evaluated with vector analysis. Relative to monoculture, biomass increase in cocoa ( L.) under shade (35-80%) was accompanied by a 17 to 25% decline in P concentration, the most limiting nutrient on this site. Similarly, increasing biomass with declining P concentrations was noted for pigeonpea [ (L). Millsp.] in response to soil moisture availability under intercropping. Although vector analysis depicted nutrient responses, the current vector model does not consider non-nutrient resource effects on growth, such as ameliorated light and soil moisture, which were particularly active in these systems. We revisit and develop vector analysis into a framework for diagnosing nutrient and non-nutrient interactions in agroforestry systems. Such a diagnostic technique advances management decision-making by increasing nutrient precision and reducing environmental issues associated with agrarian-derived soil contamination. American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.

  3. A sight on the current nanoparticle-based gene delivery vectors

    Science.gov (United States)

    Dizaj, Solmaz Maleki; Jafari, Samira; Khosroushahi, Ahmad Yari

    2014-05-01

    Nowadays, gene delivery for therapeutic objects is considered one of the most promising strategies to cure both the genetic and acquired diseases of human. The design of efficient gene delivery vectors possessing the high transfection efficiencies and low cytotoxicity is considered the major challenge for delivering a target gene to specific tissues or cells. On this base, the investigations on non-viral gene vectors with the ability to overcome physiological barriers are increasing. Among the non-viral vectors, nanoparticles showed remarkable properties regarding gene delivery such as the ability to target the specific tissue or cells, protect target gene against nuclease degradation, improve DNA stability, and increase the transformation efficiency or safety. This review attempts to represent a current nanoparticle based on its lipid, polymer, hybrid, and inorganic properties. Among them, hybrids, as efficient vectors, are utilized in gene delivery in terms of materials (synthetic or natural), design, and in vitro/ in vivo transformation efficiency.

  4. An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System.

    Science.gov (United States)

    Zhao, Anbang; Ma, Lin; Ma, Xuefei; Hui, Juan

    2017-02-20

    In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequencydomain and achieves computational complexity reduction.

  5. An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System

    Directory of Open Access Journals (Sweden)

    Anbang Zhao

    2017-02-01

    Full Text Available In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequencydomain and achieves computational complexity reduction.

  6. A Novel CSR-Based Sparse Matrix-Vector Multiplication on GPUs

    Directory of Open Access Journals (Sweden)

    Guixia He

    2016-01-01

    Full Text Available Sparse matrix-vector multiplication (SpMV is an important operation in scientific computations. Compressed sparse row (CSR is the most frequently used format to store sparse matrices. However, CSR-based SpMVs on graphic processing units (GPUs, for example, CSR-scalar and CSR-vector, usually have poor performance due to irregular memory access patterns. This motivates us to propose a perfect CSR-based SpMV on the GPU that is called PCSR. PCSR involves two kernels and accesses CSR arrays in a fully coalesced manner by introducing a middle array, which greatly alleviates the deficiencies of CSR-scalar (rare coalescing and CSR-vector (partial coalescing. Test results on a single C2050 GPU show that PCSR fully outperforms CSR-scalar, CSR-vector, and CSRMV and HYBMV in the vendor-tuned CUSPARSE library and is comparable with a most recently proposed CSR-based algorithm, CSR-Adaptive. Furthermore, we extend PCSR on a single GPU to multiple GPUs. Experimental results on four C2050 GPUs show that no matter whether the communication between GPUs is considered or not PCSR on multiple GPUs achieves good performance and has high parallel efficiency.

  7. Digital video steganalysis using motion vector recovery-based features.

    Science.gov (United States)

    Deng, Yu; Wu, Yunjie; Zhou, Linna

    2012-07-10

    As a novel digital video steganography, the motion vector (MV)-based steganographic algorithm leverages the MVs as the information carriers to hide the secret messages. The existing steganalyzers based on the statistical characteristics of the spatial/frequency coefficients of the video frames cannot attack the MV-based steganography. In order to detect the presence of information hidden in the MVs of video streams, we design a novel MV recovery algorithm and propose the calibration distance histogram-based statistical features for steganalysis. The support vector machine (SVM) is trained with the proposed features and used as the steganalyzer. Experimental results demonstrate that the proposed steganalyzer can effectively detect the presence of hidden messages and outperform others by the significant improvements in detection accuracy even with low embedding rates.

  8. Cloud Monitoring for Solar Plants with Support Vector Machine Based Fault Detection System

    Directory of Open Access Journals (Sweden)

    Hong-Chan Chang

    2014-01-01

    Full Text Available This study endeavors to develop a cloud monitoring system for solar plants. This system incorporates numerous subsystems, such as a geographic information system, an instantaneous power-consumption information system, a reporting system, and a failure diagnosis system. Visual C# was integrated with ASP.NET and SQL technologies for the proposed monitoring system. A user interface for database management system was developed to enable users to access solar power information and management systems. In addition, by using peer-to-peer (P2P streaming technology and audio/video encoding/decoding technology, real-time video data can be transmitted to the client end, providing instantaneous and direct information. Regarding smart failure diagnosis, the proposed system employs the support vector machine (SVM theory to train failure mathematical models. The solar power data are provided to the SVM for analysis in order to determine the failure types and subsequently eliminate failures at an early stage. The cloud energy-management platform developed in this study not only enhances the management and maintenance efficiency of solar power plants but also increases the market competitiveness of solar power generation and renewable energy.

  9. Spatio-temporal Rich Model Based Video Steganalysis on Cross Sections of Motion Vector Planes.

    Science.gov (United States)

    Tasdemir, Kasim; Kurugollu, Fatih; Sezer, Sakir

    2016-05-11

    A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.

  10. Efficient gene transfer into nondividing cells by adeno-associated virus-based vectors.

    Science.gov (United States)

    Podsakoff, G; Wong, K K; Chatterjee, S

    1994-09-01

    Gene transfer vectors based on adeno-associated virus (AAV) are emerging as highly promising for use in human gene therapy by virtue of their characteristics of wide host range, high transduction efficiencies, and lack of cytopathogenicity. To better define the biology of AAV-mediated gene transfer, we tested the ability of an AAV vector to efficiently introduce transgenes into nonproliferating cell populations. Cells were induced into a nonproliferative state by treatment with the DNA synthesis inhibitors fluorodeoxyuridine and aphidicolin or by contact inhibition induced by confluence and serum starvation. Cells in logarithmic growth or DNA synthesis arrest were transduced with vCWR:beta gal, an AAV-based vector encoding beta-galactosidase under Rous sarcoma virus long terminal repeat promoter control. Under each condition tested, vCWR:beta Gal expression in nondividing cells was at least equivalent to that in actively proliferating cells, suggesting that mechanisms for virus attachment, nuclear transport, virion uncoating, and perhaps some limited second-strand synthesis of AAV vectors were present in nondividing cells. Southern hybridization analysis of vector sequences from cells transduced while in DNA synthetic arrest and expanded after release of the block confirmed ultimate integration of the vector genome into cellular chromosomal DNA. These findings may provide the basis for the use of AAV-based vectors for gene transfer into quiescent cell populations such as totipotent hematopoietic stem cells.

  11. LandSat-Based Land Use-Land Cover (Vector)

    Data.gov (United States)

    Minnesota Department of Natural Resources — Vector-based land cover data set derived from classified 30 meter resolution Thematic Mapper satellite imagery. Classification is divided into 16 classes with source...

  12. Time-frequency feature analysis and recognition of fission neutrons signal based on support vector machine

    International Nuclear Information System (INIS)

    Jin Jing; Wei Biao; Feng Peng; Tang Yuelin; Zhou Mi

    2010-01-01

    Based on the interdependent relationship between fission neutrons ( 252 Cf) and fission chain ( 235 U system), the paper presents the time-frequency feature analysis and recognition in fission neutron signal based on support vector machine (SVM) through the analysis on signal characteristics and the measuring principle of the 252 Cf fission neutron signal. The time-frequency characteristics and energy features of the fission neutron signal are extracted by using wavelet decomposition and de-noising wavelet packet decomposition, and then applied to training and classification by means of support vector machine based on statistical learning theory. The results show that, it is effective to obtain features of nuclear signal via wavelet decomposition and de-noising wavelet packet decomposition, and the latter can reflect the internal characteristics of the fission neutron system better. With the training accomplished, the SVM classifier achieves an accuracy rate above 70%, overcoming the lack of training samples, and verifying the effectiveness of the algorithm. (authors)

  13. Isomorphism Theorem on Vector Spaces over a Ring

    Directory of Open Access Journals (Sweden)

    Futa Yuichi

    2017-10-01

    Full Text Available In this article, we formalize in the Mizar system [1, 4] some properties of vector spaces over a ring. We formally prove the first isomorphism theorem of vector spaces over a ring. We also formalize the product space of vector spaces. ℤ-modules are useful for lattice problems such as LLL (Lenstra, Lenstra and Lovász [5] base reduction algorithm and cryptographic systems [6, 2].

  14. Support Vector Regression-Based Adaptive Divided Difference Filter for Nonlinear State Estimation Problems

    Directory of Open Access Journals (Sweden)

    Hongjian Wang

    2014-01-01

    Full Text Available We present a support vector regression-based adaptive divided difference filter (SVRADDF algorithm for improving the low state estimation accuracy of nonlinear systems, which are typically affected by large initial estimation errors and imprecise prior knowledge of process and measurement noises. The derivative-free SVRADDF algorithm is significantly simpler to compute than other methods and is implemented using only functional evaluations. The SVRADDF algorithm involves the use of the theoretical and actual covariance of the innovation sequence. Support vector regression (SVR is employed to generate the adaptive factor to tune the noise covariance at each sampling instant when the measurement update step executes, which improves the algorithm’s robustness. The performance of the proposed algorithm is evaluated by estimating states for (i an underwater nonmaneuvering target bearing-only tracking system and (ii maneuvering target bearing-only tracking in an air-traffic control system. The simulation results show that the proposed SVRADDF algorithm exhibits better performance when compared with a traditional DDF algorithm.

  15. A Core Set Based Large Vector-Angular Region and Margin Approach for Novelty Detection

    Directory of Open Access Journals (Sweden)

    Jiusheng Chen

    2016-01-01

    Full Text Available A large vector-angular region and margin (LARM approach is presented for novelty detection based on imbalanced data. The key idea is to construct the largest vector-angular region in the feature space to separate normal training patterns; meanwhile, maximize the vector-angular margin between the surface of this optimal vector-angular region and abnormal training patterns. In order to improve the generalization performance of LARM, the vector-angular distribution is optimized by maximizing the vector-angular mean and minimizing the vector-angular variance, which separates the normal and abnormal examples well. However, the inherent computation of quadratic programming (QP solver takes O(n3 training time and at least O(n2 space, which might be computational prohibitive for large scale problems. By (1+ε  and  (1-ε-approximation algorithm, the core set based LARM algorithm is proposed for fast training LARM problem. Experimental results based on imbalanced datasets have validated the favorable efficiency of the proposed approach in novelty detection.

  16. Energy Systems in the Era of Energy Vectors A Key to Define, Analyze and Design Energy Systems Beyond Fossil Fuels

    CERN Document Server

    Orecchini, Fabio

    2012-01-01

    What lies beyond the era of fossil fuels? While most answers focus on different primary energy resources, Energy Systems in the Era of Energy Vectors provides a completely new approach. Instead of providing a traditional consumption analysis of classical primary energy resources such as oil, coal, nuclear power and gas, Energy Systems in the Era of Energy Vectors describes and assesses energy technologies, markets and future strategies, focusing on their capacity to produce, exchange, and use energy vectors. Special attention is given to the renewable energy resources available in different areas of the world and made exploitable by the integration of energy vectors in the global energy system. Clear definitions of energy vectors and energy systems are used as the basis for a complete explanation and assessment of up-to-date, available technologies for energy resources, transport and storage systems, conversion and use. The energy vectors scheme allows the potential realisation of a worldwide sustainable ener...

  17. A method of recovering the initial vectors of globally coupled map lattices based on symbolic dynamics

    International Nuclear Information System (INIS)

    Sun Li-Sha; Kang Xiao-Yun; Zhang Qiong; Lin Lan-Xin

    2011-01-01

    Based on symbolic dynamics, a novel computationally efficient algorithm is proposed to estimate the unknown initial vectors of globally coupled map lattices (CMLs). It is proved that not all inverse chaotic mapping functions are satisfied for contraction mapping. It is found that the values in phase space do not always converge on their initial values with respect to sufficient backward iteration of the symbolic vectors in terms of global convergence or divergence (CD). Both CD property and the coupling strength are directly related to the mapping function of the existing CML. Furthermore, the CD properties of Logistic, Bernoulli, and Tent chaotic mapping functions are investigated and compared. Various simulation results and the performances of the initial vector estimation with different signal-to-noise ratios (SNRs) are also provided to confirm the proposed algorithm. Finally, based on the spatiotemporal chaotic characteristics of the CML, the conditions of estimating the initial vectors using symbolic dynamics are discussed. The presented method provides both theoretical and experimental results for better understanding and characterizing the behaviours of spatiotemporal chaotic systems. (general)

  18. A method of recovering the initial vectors of globally coupled map lattices based on symbolic dynamics

    Science.gov (United States)

    Sun, Li-Sha; Kang, Xiao-Yun; Zhang, Qiong; Lin, Lan-Xin

    2011-12-01

    Based on symbolic dynamics, a novel computationally efficient algorithm is proposed to estimate the unknown initial vectors of globally coupled map lattices (CMLs). It is proved that not all inverse chaotic mapping functions are satisfied for contraction mapping. It is found that the values in phase space do not always converge on their initial values with respect to sufficient backward iteration of the symbolic vectors in terms of global convergence or divergence (CD). Both CD property and the coupling strength are directly related to the mapping function of the existing CML. Furthermore, the CD properties of Logistic, Bernoulli, and Tent chaotic mapping functions are investigated and compared. Various simulation results and the performances of the initial vector estimation with different signal-to-noise ratios (SNRs) are also provided to confirm the proposed algorithm. Finally, based on the spatiotemporal chaotic characteristics of the CML, the conditions of estimating the initial vectors using symbolic dynamics are discussed. The presented method provides both theoretical and experimental results for better understanding and characterizing the behaviours of spatiotemporal chaotic systems.

  19. Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

    Directory of Open Access Journals (Sweden)

    Hailun Wang

    2017-01-01

    Full Text Available Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.

  20. Scanning vector Hall probe microscopy

    International Nuclear Information System (INIS)

    Cambel, V.; Gregusova, D.; Fedor, J.; Kudela, R.; Bending, S.J.

    2004-01-01

    We have developed a scanning vector Hall probe microscope for mapping magnetic field vector over magnetic samples. The microscope is based on a micromachined Hall sensor and the cryostat with scanning system. The vector Hall sensor active area is ∼5x5 μm 2 . It is realized by patterning three Hall probes on the tilted faces of GaAs pyramids. Data from these 'tilted' Hall probes are used to reconstruct the full magnetic field vector. The scanning area of the microscope is 5x5 mm 2 , space resolution 2.5 μm, field resolution ∼1 μT Hz -1/2 at temperatures 10-300 K

  1. Global Positioning Systems (GPS) Technology to Study Vector-Pathogen-Host Interactions

    Science.gov (United States)

    2016-12-01

    Award Number: W81XWH-11-2-0175 TITLE: Global Positioning Systems (GPS) Technology to Study Vector-Pathogen-Host Interactions PRINCIPAL...Positioning Systems (GPS) Technology to Study Vector-Pathogen-Host Interactions 5b. GRANT NUMBER W81XWH-11-2-0175 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...genetic diversity in the population, in hospitalized children with severe dengue illness and cluster investigation of their neighborhoods, and by using

  2. Product Quality Modelling Based on Incremental Support Vector Machine

    International Nuclear Information System (INIS)

    Wang, J; Zhang, W; Qin, B; Shi, W

    2012-01-01

    Incremental Support vector machine (ISVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. It is suitable for the problem of sequentially arriving field data and has been widely used for product quality prediction and production process optimization. However, the traditional ISVM learning does not consider the quality of the incremental data which may contain noise and redundant data; it will affect the learning speed and accuracy to a great extent. In order to improve SVM training speed and accuracy, a modified incremental support vector machine (MISVM) is proposed in this paper. Firstly, the margin vectors are extracted according to the Karush-Kuhn-Tucker (KKT) condition; then the distance from the margin vectors to the final decision hyperplane is calculated to evaluate the importance of margin vectors, where the margin vectors are removed while their distance exceed the specified value; finally, the original SVs and remaining margin vectors are used to update the SVM. The proposed MISVM can not only eliminate the unimportant samples such as noise samples, but also can preserve the important samples. The MISVM has been experimented on two public data and one field data of zinc coating weight in strip hot-dip galvanizing, and the results shows that the proposed method can improve the prediction accuracy and the training speed effectively. Furthermore, it can provide the necessary decision supports and analysis tools for auto control of product quality, and also can extend to other process industries, such as chemical process and manufacturing process.

  3. Selection vector filter framework

    Science.gov (United States)

    Lukac, Rastislav; Plataniotis, Konstantinos N.; Smolka, Bogdan; Venetsanopoulos, Anastasios N.

    2003-10-01

    We provide a unified framework of nonlinear vector techniques outputting the lowest ranked vector. The proposed framework constitutes a generalized filter class for multichannel signal processing. A new class of nonlinear selection filters are based on the robust order-statistic theory and the minimization of the weighted distance function to other input samples. The proposed method can be designed to perform a variety of filtering operations including previously developed filtering techniques such as vector median, basic vector directional filter, directional distance filter, weighted vector median filters and weighted directional filters. A wide range of filtering operations is guaranteed by the filter structure with two independent weight vectors for angular and distance domains of the vector space. In order to adapt the filter parameters to varying signal and noise statistics, we provide also the generalized optimization algorithms taking the advantage of the weighted median filters and the relationship between standard median filter and vector median filter. Thus, we can deal with both statistical and deterministic aspects of the filter design process. It will be shown that the proposed method holds the required properties such as the capability of modelling the underlying system in the application at hand, the robustness with respect to errors in the model of underlying system, the availability of the training procedure and finally, the simplicity of filter representation, analysis, design and implementation. Simulation studies also indicate that the new filters are computationally attractive and have excellent performance in environments corrupted by bit errors and impulsive noise.

  4. FUSION DECISION FOR A BIMODAL BIOMETRIC VERIFICATION SYSTEM USING SUPPORT VECTOR MACHINE AND ITS VARIATIONS

    Directory of Open Access Journals (Sweden)

    A. Teoh

    2017-12-01

    Full Text Available This paw presents fusion detection technique comparisons based on support vector machine and its variations for a bimodal biometric verification system that makes use of face images and speech utterances. The system is essentially constructed by a face expert, a speech expert and a fusion decision module. Each individual expert has been optimized to operate in automatic mode and designed for security access application. Fusion decision schemes considered are linear, weighted Support Vector Machine (SVM and linear SVM with quadratic transformation. The conditions tested include the balanced and unbalanced conditions between the two experts in order to obtain the optimum fusion module from  these techniques best suited to the target application.

  5. Correlation-based motion vector processing with adaptive interpolation scheme for motion-compensated frame interpolation.

    Science.gov (United States)

    Huang, Ai-Mei; Nguyen, Truong

    2009-04-01

    In this paper, we address the problems of unreliable motion vectors that cause visual artifacts but cannot be detected by high residual energy or bidirectional prediction difference in motion-compensated frame interpolation. A correlation-based motion vector processing method is proposed to detect and correct those unreliable motion vectors by explicitly considering motion vector correlation in the motion vector reliability classification, motion vector correction, and frame interpolation stages. Since our method gradually corrects unreliable motion vectors based on their reliability, we can effectively discover the areas where no motion is reliable to be used, such as occlusions and deformed structures. We also propose an adaptive frame interpolation scheme for the occlusion areas based on the analysis of their surrounding motion distribution. As a result, the interpolated frames using the proposed scheme have clearer structure edges and ghost artifacts are also greatly reduced. Experimental results show that our interpolated results have better visual quality than other methods. In addition, the proposed scheme is robust even for those video sequences that contain multiple and fast motions.

  6. Determinants of Health Service Responsiveness in Community-Based Vector Surveillance for Chagas Disease in Guatemala, El Salvador, and Honduras

    Science.gov (United States)

    Hashimoto, Ken; Zúniga, Concepción; Romero, Eduardo; Morales, Zoraida; Maguire, James H.

    2015-01-01

    Background Central American countries face a major challenge in the control of Triatoma dimidiata, a widespread vector of Chagas disease that cannot be eliminated. The key to maintaining the risk of transmission of Trypanosoma cruzi at lowest levels is to sustain surveillance throughout endemic areas. Guatemala, El Salvador, and Honduras integrated community-based vector surveillance into local health systems. Community participation was effective in detection of the vector, but some health services had difficulty sustaining their response to reports of vectors from the population. To date, no research has investigated how best to maintain and reinforce health service responsiveness, especially in resource-limited settings. Methodology/Principal Findings We reviewed surveillance and response records of 12 health centers in Guatemala, El Salvador, and Honduras from 2008 to 2012 and analyzed the data in relation to the volume of reports of vector infestation, local geography, demography, human resources, managerial approach, and results of interviews with health workers. Health service responsiveness was defined as the percentage of households that reported vector infestation for which the local health service provided indoor residual spraying of insecticide or educational advice. Eight potential determinants of responsiveness were evaluated by linear and mixed-effects multi-linear regression. Health service responsiveness (overall 77.4%) was significantly associated with quarterly monitoring by departmental health offices. Other potential determinants of responsiveness were not found to be significant, partly because of short- and long-term strategies, such as temporary adjustments in manpower and redistribution of tasks among local participants in the effort. Conclusions/Significance Consistent monitoring within the local health system contributes to sustainability of health service responsiveness in community-based vector surveillance of Chagas disease. Even with

  7. Determinants of Health Service Responsiveness in Community-Based Vector Surveillance for Chagas Disease in Guatemala, El Salvador, and Honduras.

    Science.gov (United States)

    Hashimoto, Ken; Zúniga, Concepción; Romero, Eduardo; Morales, Zoraida; Maguire, James H

    2015-01-01

    Central American countries face a major challenge in the control of Triatoma dimidiata, a widespread vector of Chagas disease that cannot be eliminated. The key to maintaining the risk of transmission of Trypanosoma cruzi at lowest levels is to sustain surveillance throughout endemic areas. Guatemala, El Salvador, and Honduras integrated community-based vector surveillance into local health systems. Community participation was effective in detection of the vector, but some health services had difficulty sustaining their response to reports of vectors from the population. To date, no research has investigated how best to maintain and reinforce health service responsiveness, especially in resource-limited settings. We reviewed surveillance and response records of 12 health centers in Guatemala, El Salvador, and Honduras from 2008 to 2012 and analyzed the data in relation to the volume of reports of vector infestation, local geography, demography, human resources, managerial approach, and results of interviews with health workers. Health service responsiveness was defined as the percentage of households that reported vector infestation for which the local health service provided indoor residual spraying of insecticide or educational advice. Eight potential determinants of responsiveness were evaluated by linear and mixed-effects multi-linear regression. Health service responsiveness (overall 77.4%) was significantly associated with quarterly monitoring by departmental health offices. Other potential determinants of responsiveness were not found to be significant, partly because of short- and long-term strategies, such as temporary adjustments in manpower and redistribution of tasks among local participants in the effort. Consistent monitoring within the local health system contributes to sustainability of health service responsiveness in community-based vector surveillance of Chagas disease. Even with limited resources, countries can improve health service

  8. An efficient rHSV-based complementation system for the production of multiple rAAV vector serotypes.

    Science.gov (United States)

    Kang, W; Wang, L; Harrell, H; Liu, J; Thomas, D L; Mayfield, T L; Scotti, M M; Ye, G J; Veres, G; Knop, D R

    2009-02-01

    Recombinant herpes simplex virus type 1 (rHSV)-assisted recombinant adeno-associated virus (rAAV) vector production provides a highly efficient and scalable method for manufacture of clinical grade rAAV vectors. Here, we present an rHSV co-infection system for rAAV production, which uses two ICP27-deficient rHSV constructs, one bearing the rep2 and cap (1, 2 or 9) genes of rAAV, and the second bearing an AAV2 ITR-gene of interest (GOI) cassette. The optimum rAAV production parameters were defined by producing rAAV2/GFP in HEK293 cells, yielding greater than 9000 infectious particles per cell with a 14:1 DNase resistance particle to infectious particle (DRP/ip) ratio. The optimized co-infection parameters were then used to generate large-scale stocks of rAAV1/AAT, which encode the human alpha-1-antitrypsin (hAAT) protein, and purified by column chromatography. The purified vector was extensively characterized by rAAV- and rHSV-specific assays and compared to transfection-made vector for in vivo efficacy in mice through intramuscular injection. The co-infection method was also used to produce rAAV9/AAT for comparison to rAAV1/AAT in vivo. Intramuscular administration of 1 x 10(11) DRP per animal of rHSV-produced rAAV1/AAT and rAAV9/AAT resulted in hAAT protein expression of 5.4 x 10(4) and 9.4 x 10(5) ng ml(-1) serum respectively, the latter being clinically relevant.

  9. A Fiber-Optic Borehole Seismic Vector Sensor System for Geothermal Site Characterization and Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Paulsson, Bjorn N.P. [Paulsson, Inc., Van Nuys, CA (United States); Thornburg, Jon A. [Paulsson, Inc., Van Nuys, CA (United States); He, Ruiqing [Paulsson, Inc., Van Nuys, CA (United States)

    2015-04-21

    Seismic techniques are the dominant geophysical techniques for the characterization of subsurface structures and stratigraphy. The seismic techniques also dominate the monitoring and mapping of reservoir injection and production processes. Borehole seismology, of all the seismic techniques, despite its current shortcomings, has been shown to provide the highest resolution characterization and most precise monitoring results because it generates higher signal to noise ratio and higher frequency data than surface seismic techniques. The operational environments for borehole seismic instruments are however much more demanding than for surface seismic instruments making both the instruments and the installation much more expensive. The current state-of-the-art borehole seismic instruments have not been robust enough for long term monitoring compounding the problems with expensive instruments and installations. Furthermore, they have also not been able to record the large bandwidth data available in boreholes or having the sensitivity allowing them to record small high frequency micro seismic events with high vector fidelity. To reliably achieve high resolution characterization and long term monitoring of Enhanced Geothermal Systems (EGS) sites a new generation of borehole seismic instruments must therefore be developed and deployed. To address the critical site characterization and monitoring needs for EGS programs, US Department of Energy (DOE) funded Paulsson, Inc. in 2010 to develop a fiber optic based ultra-large bandwidth clamped borehole seismic vector array capable of deploying up to one thousand 3C sensor pods suitable for deployment into ultra-high temperature and high pressure boreholes. Tests of the fiber optic seismic vector sensors developed on the DOE funding have shown that the new borehole seismic sensor technology is capable of generating outstanding high vector fidelity data with extremely large bandwidth: 0.01 – 6,000 Hz. Field tests have shown

  10. Conservative rigid body dynamics by convected base vectors with implicit constraints

    DEFF Research Database (Denmark)

    Krenk, Steen; Nielsen, Martin Bjerre

    2014-01-01

    of differential equations without additional algebraic constraints on the base vectors. A discretized form of the equations of motion is obtained by starting from a finite time increment of the Hamiltonian, and retracing the steps of the continuous formulation in discrete form in terms of increments and mean...... of the base vectors. Orthogonality and unit length of the base vectors are imposed by constraining the equivalent Green strain components, and the kinetic energy is represented corresponding to rigid body motion. The equations of motion are obtained via Hamilton’s equations including the zero...... values over each integration time increment. In this discrete form the Lagrange multipliers are given in terms of a representative value within the integration time interval, and the equations of motion are recast into a conservative mean-value and finite difference format. The Lagrange multipliers...

  11. Classification of e-government documents based on cooperative expression of word vectors

    Science.gov (United States)

    Fu, Qianqian; Liu, Hao; Wei, Zhiqiang

    2017-03-01

    The effective document classification is a powerful technique to deal with the huge amount of e-government documents automatically instead of accomplishing them manually. The word-to-vector (word2vec) model, which converts semantic word into low-dimensional vectors, could be successfully employed to classify the e-government documents. In this paper, we propose the cooperative expressions of word vector (Co-word-vector), whose multi-granularity of integration explores the possibility of modeling documents in the semantic space. Meanwhile, we also aim to improve the weighted continuous bag of words model based on word2vec model and distributed representation of topic-words based on LDA model. Furthermore, combining the two levels of word representation, performance result shows that our proposed method on the e-government document classification outperform than the traditional method.

  12. Global rotational motion and displacement estimation of digital image stabilization based on the oblique vectors matching algorithm

    Science.gov (United States)

    Yu, Fei; Hui, Mei; Zhao, Yue-jin

    2009-08-01

    The image block matching algorithm based on motion vectors of correlative pixels in oblique direction is presented for digital image stabilization. The digital image stabilization is a new generation of image stabilization technique which can obtains the information of relative motion among frames of dynamic image sequences by the method of digital image processing. In this method the matching parameters are calculated from the vectors projected in the oblique direction. The matching parameters based on the vectors contain the information of vectors in transverse and vertical direction in the image blocks at the same time. So the better matching information can be obtained after making correlative operation in the oblique direction. And an iterative weighted least square method is used to eliminate the error of block matching. The weights are related with the pixels' rotational angle. The center of rotation and the global emotion estimation of the shaking image can be obtained by the weighted least square from the estimation of each block chosen evenly from the image. Then, the shaking image can be stabilized with the center of rotation and the global emotion estimation. Also, the algorithm can run at real time by the method of simulated annealing in searching method of block matching. An image processing system based on DSP was used to exam this algorithm. The core processor in the DSP system is TMS320C6416 of TI, and the CCD camera with definition of 720×576 pixels was chosen as the input video signal. Experimental results show that the algorithm can be performed at the real time processing system and have an accurate matching precision.

  13. Vectorization, parallelization and porting of nuclear codes. Vectorization and parallelization. Progress report fiscal 1999

    Energy Technology Data Exchange (ETDEWEB)

    Adachi, Masaaki; Ogasawara, Shinobu; Kume, Etsuo [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Ishizuki, Shigeru; Nemoto, Toshiyuki; Kawasaki, Nobuo; Kawai, Wataru [Fujitsu Ltd., Tokyo (Japan); Yatake, Yo-ichi [Hitachi Ltd., Tokyo (Japan)

    2001-02-01

    Several computer codes in the nuclear field have been vectorized, parallelized and trans-ported on the FUJITSU VPP500 system, the AP3000 system, the SX-4 system and the Paragon system at Center for Promotion of Computational Science and Engineering in Japan Atomic Energy Research Institute. We dealt with 18 codes in fiscal 1999. These results are reported in 3 parts, i.e., the vectorization and the parallelization part on vector processors, the parallelization part on scalar processors and the porting part. In this report, we describe the vectorization and parallelization on vector processors. In this vectorization and parallelization on vector processors part, the vectorization of Relativistic Molecular Orbital Calculation code RSCAT, a microscopic transport code for high energy nuclear collisions code JAM, three-dimensional non-steady thermal-fluid analysis code STREAM, Relativistic Density Functional Theory code RDFT and High Speed Three-Dimensional Nodal Diffusion code MOSRA-Light on the VPP500 system and the SX-4 system are described. (author)

  14. Testing resonating vector strength: Auditory system, electric fish, and noise

    Science.gov (United States)

    Leo van Hemmen, J.; Longtin, André; Vollmayr, Andreas N.

    2011-12-01

    Quite often a response to some input with a specific frequency ν○ can be described through a sequence of discrete events. Here, we study the synchrony vector, whose length stands for the vector strength, and in doing so focus on neuronal response in terms of spike times. The latter are supposed to be given by experiment. Instead of singling out the stimulus frequency ν○ we study the synchrony vector as a function of the real frequency variable ν. Its length turns out to be a resonating vector strength in that it shows clear maxima in the neighborhood of ν○ and multiples thereof, hence, allowing an easy way of determining response frequencies. We study this "resonating" vector strength for two concrete but rather different cases, viz., a specific midbrain neuron in the auditory system of cat and a primary detector neuron belonging to the electric sense of the wave-type electric fish Apteronotus leptorhynchus. We show that the resonating vector strength always performs a clear resonance correlated with the phase locking that it quantifies. We analyze the influence of noise and demonstrate how well the resonance associated with maximal vector strength indicates the dominant stimulus frequency. Furthermore, we exhibit how one can obtain a specific phase associated with, for instance, a delay in auditory analysis.

  15. Near State Vector Selection-Based Model Predictive Control with Common Mode Voltage Mitigation for a Three-Phase Four-Leg Inverter

    Directory of Open Access Journals (Sweden)

    Abdul Mannan Dadu

    2017-12-01

    Full Text Available A high computational burden is required in conventional model predictive control, as all of the voltage vectors of a power inverter are used to predict the future behavior of the system. Apart from that, the common mode voltage (CMV of a three-phase four-leg inverter utilizes up to half of the DC-link voltage due to the use of all of the available voltage vectors. Thus, this paper proposes a near state vector selection-based model predictive control (NSV-MPC scheme to mitigate the CMV and reduce computational burden. In the proposed technique, only six active voltage vectors are used in the predictive model, and the vectors are selected based on the position of the future reference vector. In every sampling period, the position of the reference current is used to detect the voltage vectors surrounding the reference voltage vector. Besides the six active vectors, one of the zero vectors is also used. The proposed technique is compared with the conventional control scheme in terms of execution time, CMV variation, and load current ripple in both simulation and an experimental setup. The LabVIEW Field programmable gate array rapid prototyping controller is used to validate the proposed control scheme experimentally, and demonstrate that the CMV can be bounded within one-fourth of the DC-link voltage.

  16. An Effective NoSQL-Based Vector Map Tile Management Approach

    Directory of Open Access Journals (Sweden)

    Lin Wan

    2016-11-01

    Full Text Available Within a digital map service environment, the rapid growth of Spatial Big-Data is driving new requirements for effective mechanisms for massive online vector map tile processing. The emergence of Not Only SQL (NoSQL databases has resulted in a new data storage and management model for scalable spatial data deployments and fast tracking. They better suit the scenario of high-volume, low-latency network map services than traditional standalone high-performance computer (HPC or relational databases. In this paper, we propose a flexible storage framework that provides feasible methods for tiled map data parallel clipping and retrieval operations within a distributed NoSQL database environment. We illustrate the parallel vector tile generation and querying algorithms with the MapReduce programming model. Three different processing approaches, including local caching, distributed file storage, and the NoSQL-based method, are compared by analyzing the concurrent load and calculation time. An online geological vector tile map service prototype was developed to embed our processing framework in the China Geological Survey Information Grid. Experimental results show that our NoSQL-based parallel tile management framework can support applications that process huge volumes of vector tile data and improve performance of the tiled map service.

  17. Detection of ferromagnetic target based on mobile magnetic gradient tensor system

    Energy Technology Data Exchange (ETDEWEB)

    Gang, Y.I.N., E-mail: gang.gang88@163.com; Yingtang, Zhang; Zhining, Li; Hongbo, Fan; Guoquan, Ren

    2016-03-15

    Attitude change of mobile magnetic gradient tensor system critically affects the precision of gradient measurements, thereby increasing ambiguity in target detection. This paper presents a rotational invariant-based method for locating and identifying ferromagnetic targets. Firstly, unit magnetic moment vector was derived based on the geometrical invariant, such that the intermediate eigenvector of the magnetic gradient tensor is perpendicular to the magnetic moment vector and the source–sensor displacement vector. Secondly, unit source–sensor displacement vector was derived based on the characteristic that the angle between magnetic moment vector and source–sensor displacement is a rotational invariant. By introducing a displacement vector between two measurement points, the magnetic moment vector and the source–sensor displacement vector were theoretically derived. To resolve the problem of measurement noises existing in the realistic detection applications, linear equations were formulated using invariants corresponding to several distinct measurement points and least square solution of magnetic moment vector and source–sensor displacement vector were obtained. Results of simulation and principal verification experiment showed the correctness of the analytical method, along with the practicability of the least square method. - Highlights: • Ferromagnetic target detection method is proposed based on rotational invariants • Intermediate eigenvector is perpendicular to magnetic moment and displacement vector • Angle between magnetic moment and displacement vector is a rotational invariant • Magnetic moment and displacement vector are derived based on invariants of two points.

  18. Design of 2D time-varying vector fields.

    Science.gov (United States)

    Chen, Guoning; Kwatra, Vivek; Wei, Li-Yi; Hansen, Charles D; Zhang, Eugene

    2012-10-01

    Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects.

  19. Sequential Bethe vectors and the quantum Ernst system

    International Nuclear Information System (INIS)

    Niedermaier, M.; Samtleben, H.

    2000-01-01

    We give a brief review on the use of Bethe Ansatz techniques to construct solutions of recursive functional equations which emerged in a bootstrap approach to the quantum Ernst system. The construction involves two particular limits of a rational Bethe Ansatz system with complex inhomogeneities. First, we pinch two insertions to the critical value. This links Bethe systems with different number of insertions and leads to the concept of sequential Bethe vectors. Second, we study the semiclassical limit of the system in which the scale parameter of the insertions tends to infinity. (author)

  20. Effective genetic modification and differentiation of hMSCs upon controlled release of rAAV vectors using alginate/poloxamer composite systems.

    Science.gov (United States)

    Díaz-Rodríguez, P; Rey-Rico, A; Madry, H; Landin, M; Cucchiarini, M

    2015-12-30

    Viral vectors are common tools in gene therapy to deliver foreign therapeutic sequences in a specific target population via their natural cellular entry mechanisms. Incorporating such vectors in implantable systems may provide strong alternatives to conventional gene transfer procedures. The goal of the present study was to generate different hydrogel structures based on alginate (AlgPH155) and poloxamer PF127 as new systems to encapsulate and release recombinant adeno-associated viral (rAAV) vectors. Inclusion of rAAV in such polymeric capsules revealed an influence of the hydrogel composition and crosslinking temperature upon the vector release profiles, with alginate (AlgPH155) structures showing the fastest release profiles early on while over time vector release was more effective from AlgPH155+PF127 [H] capsules crosslinked at a high temperature (50°C). Systems prepared at room temperature (AlgPH155+PF127 [C]) allowed instead to achieve a more controlled release profile. When tested for their ability to target human mesenchymal stem cells, the different systems led to high transduction efficiencies over time and to gene expression levels in the range of those achieved upon direct vector application, especially when using AlgPH155+PF127 [H]. No detrimental effects were reported on either cell viability or on the potential for chondrogenic differentiation. Inclusion of PF127 in the capsules was also capable of delaying undesirable hypertrophic cell differentiation. These findings are of promising value for the further development of viral vector controlled release strategies. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. Robust and accurate vectorization of line drawings.

    Science.gov (United States)

    Hilaire, Xavier; Tombre, Karl

    2006-06-01

    This paper presents a method for vectorizing the graphical parts of paper-based line drawings. The method consists of separating the input binary image into layers of homogeneous thickness, skeletonizing each layer, segmenting the skeleton by a method based on random sampling, and simplifying the result. The segmentation method is robust with a best bound of 50 percent noise reached for indefinitely long primitives. Accurate estimation of the recognized vector's parameters is enabled by explicitly computing their feasibility domains. Theoretical performance analysis and expression of the complexity of the segmentation method are derived. Experimental results and comparisons with other vectorization systems are also provided.

  2. Establishment of the Credit Indicator System of Micro Enterprises Based on Support Vector Machine and R-Type Clustering

    Directory of Open Access Journals (Sweden)

    Zhanjiang Li

    2018-01-01

    Full Text Available The micro enterprises’ credit indicators with credit identification ability are selected by the two classification models of Support Vector Machine for the first round of indicator selection and then for the second round of indicator selection, deleting credit indicators with redundant information by clustering variables through the principle of minimum sum of deviation squares. This paper provides a screening model for credit evaluation indicators of micro enterprises and uses credit data of 860 micro enterprises samples in Inner Mongolia in western China for application analysis. The test results show that, first, the constructed final micro enterprises’ credit indicator system is in line with the 5C model; second, the validity test based on the ROC (Receiver Operating Characteristic curve reveals that each of the screened credit evaluation indicators is valid.

  3. Genetic manipulation of endosymbionts to control vector and vector borne diseases

    Directory of Open Access Journals (Sweden)

    Jay Prakash Gupta

    Full Text Available Vector borne diseases (VBD are on the rise because of failure of the existing methods of control of vector and vector borne diseases and the climate change. A steep rise of VBDs are due to several factors like selection of insecticide resistant vector population, drug resistant parasite population and lack of effective vaccines against the VBDs. Environmental pollution, public health hazard and insecticide resistant vector population indicate that the insecticides are no longer a sustainable control method of vector and vector-borne diseases. Amongst the various alternative control strategies, symbiont based approach utilizing endosymbionts of arthropod vectors could be explored to control the vector and vector borne diseases. The endosymbiont population of arthropod vectors could be exploited in different ways viz., as a chemotherapeutic target, vaccine target for the control of vectors. Expression of molecules with antiparasitic activity by genetically transformed symbiotic bacteria of disease-transmitting arthropods may serve as a powerful approach to control certain arthropod-borne diseases. Genetic transformation of symbiotic bacteria of the arthropod vector to alter the vector’s ability to transmit pathogen is an alternative means of blocking the transmission of VBDs. In Indian scenario, where dengue, chikungunya, malaria and filariosis are prevalent, paratransgenic based approach can be used effectively. [Vet World 2012; 5(9.000: 571-576

  4. Strategic vectors of transformational shifts in the national tourism system of Ukraine

    Directory of Open Access Journals (Sweden)

    Alla OKHRIMENKO

    2017-10-01

    Full Text Available The article determines transformational factors, which influence a national tourism system (NTS of Ukraine and proposes strategical vectors of its development. Research of the NTS as an economic system is a pre-condition for formation of strategic vectors of development. Transformational driving forces principally change scales, components, and proportions between external and internal factors of development of the NTS. Correspondingly, the mentioned processes objectively encourage modernization of the national tourism system and application of innovative managerial methods. The following Strategical vectors of transformational shifts in the NTS were grounded: 1 Safety of tourists and investors; 2 The normative and legislative framework of the NTS development; 3 Development of infrastructure of the NTS component; 4 Human resources development; 5 A marketing policy of the NTS promotion; 6 Ecological and cultural policies. Their implementation will improve efficiency and competitiveness of the NTS and the national economy.

  5. Support vector machine based battery model for electric vehicles

    International Nuclear Information System (INIS)

    Wang Junping; Chen Quanshi; Cao Binggang

    2006-01-01

    The support vector machine (SVM) is a novel type of learning machine based on statistical learning theory that can map a nonlinear function successfully. As a battery is a nonlinear system, it is difficult to establish the relationship between the load voltage and the current under different temperatures and state of charge (SOC). The SVM is used to model the battery nonlinear dynamics in this paper. Tests are performed on an 80Ah Ni/MH battery pack with the Federal Urban Driving Schedule (FUDS) cycle to set up the SVM model. Compared with the Nernst and Shepherd combined model, the SVM model can simulate the battery dynamics better with small amounts of experimental data. The maximum relative error is 3.61%

  6. Design of 2D Time-Varying Vector Fields

    KAUST Repository

    Chen, Guoning

    2012-10-01

    Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects. © 1995-2012 IEEE.

  7. Design of 2D Time-Varying Vector Fields

    KAUST Repository

    Chen, Guoning; Kwatra, Vivek; Wei, Li-Yi; Hansen, Charles D.; Zhang, Eugene

    2012-01-01

    Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects. © 1995-2012 IEEE.

  8. Nighttime Fire/Smoke Detection System Based on a Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Chao-Ching Ho

    2013-01-01

    Full Text Available Currently, video surveillance-based early fire smoke detection is crucial to the prevention of large fires and the protection of life and goods. To overcome the nighttime limitations of video smoke detection methods, a laser light can be projected into the monitored field of view, and the returning projected light section image can be analyzed to detect fire and/or smoke. If smoke appears within the monitoring zone created from the diffusion or scattering of light in the projected path, the camera sensor receives a corresponding signal. The successive processing steps of the proposed real-time algorithm use the spectral, diffusing, and scattering characteristics of the smoke-filled regions in the image sequences to register the position of possible smoke in a video. Characterization of smoke is carried out by a nonlinear classification method using a support vector machine, and this is applied to identify the potential fire/smoke location. Experimental results in a variety of nighttime conditions demonstrate that the proposed fire/smoke detection method can successfully and reliably detect fires by identifying the location of smoke.

  9. Fault Diagnosis of a Reconfigurable Crawling–Rolling Robot Based on Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Karthikeyan Elangovan

    2017-10-01

    Full Text Available As robots begin to perform jobs autonomously, with minimal or no human intervention, a new challenge arises: robots also need to autonomously detect errors and recover from faults. In this paper, we present a Support Vector Machine (SVM-based fault diagnosis system for a bio-inspired reconfigurable robot named Scorpio. The diagnosis system needs to detect and classify faults while Scorpio uses its crawling and rolling locomotion modes. Specifically, we classify between faulty and non-faulty conditions by analyzing onboard Inertial Measurement Unit (IMU sensor data. The data capture nine different locomotion gaits, which include rolling and crawling modes, at three different speeds. Statistical methods are applied to extract features and to reduce the dimensionality of original IMU sensor data features. These statistical features were given as inputs for training and testing. Additionally, the c-Support Vector Classification (c-SVC and nu-SVC models of SVM, and their fault classification accuracies, were compared. The results show that the proposed SVM approach can be used to autonomously diagnose locomotion gait faults while the reconfigurable robot is in operation.

  10. A support vector density-based importance sampling for reliability assessment

    International Nuclear Information System (INIS)

    Dai, Hongzhe; Zhang, Hao; Wang, Wei

    2012-01-01

    An importance sampling method based on the adaptive Markov chain simulation and support vector density estimation is developed in this paper for efficient structural reliability assessment. The methodology involves the generation of samples that can adaptively populate the important region by the adaptive Metropolis algorithm, and the construction of importance sampling density by support vector density. The use of the adaptive Metropolis algorithm may effectively improve the convergence and stability of the classical Markov chain simulation. The support vector density can approximate the sampling density with fewer samples in comparison to the conventional kernel density estimation. The proposed importance sampling method can effectively reduce the number of structural analysis required for achieving a given accuracy. Examples involving both numerical and practical structural problems are given to illustrate the application and efficiency of the proposed methodology.

  11. Back-to-back three-level converter controlled by a novel space-vector hysteresis current control for wind conversion systems

    Energy Technology Data Exchange (ETDEWEB)

    Ghennam, Tarak [Laboratoire d' Electronique de Puissance (LEP), UER: Electrotechnique, Ecole Militaire Polytechnique d' Alger, BP 17, Bordj EL Bahri, Alger (Algeria); Berkouk, El-Madjid [Laboratoire de Commande des Processus (LCP), Ecole Nationale Polytechnique d' Alger, BP 182, 10 avenue Hassen Badi, 16200 el Harrach (Algeria)

    2010-04-15

    In this paper, a novel space-vector hysteresis current control (SVHCC) is proposed for a back-to-back three-level converter which is used as an electronic interface in a wind conversion system. The proposed SVHCC controls the active and reactive powers delivered to the grid by the doubly fed induction machine (DFIM) through the control of its rotor currents. In addition, it controls the neutral point voltage by using the redundant inverter switching states. The three rotor current errors are gathered into a single space-vector quantity. The magnitude of the error vector is limited within boundary areas of a square shape. The control scheme is based firstly on the detection of the area and sector in which the vector tip of the current error can be located. Then, an appropriate voltage vector among the 27 voltage vectors of the three-level voltage source inverter (VSI) is applied to push the error vector towards the hysteresis boundaries. Simple look-up tables are required for the area and sector detection, and also for vector selection. The performance of the proposed control technique has been verified by simulations. (author)

  12. Thai Language Sentence Similarity Computation Based on Syntactic Structure and Semantic Vector

    Science.gov (United States)

    Wang, Hongbin; Feng, Yinhan; Cheng, Liang

    2018-03-01

    Sentence similarity computation plays an increasingly important role in text mining, Web page retrieval, machine translation, speech recognition and question answering systems. Thai language as a kind of resources scarce language, it is not like Chinese language with HowNet and CiLin resources. So the Thai sentence similarity research faces some challenges. In order to solve this problem of the Thai language sentence similarity computation. This paper proposes a novel method to compute the similarity of Thai language sentence based on syntactic structure and semantic vector. This method firstly uses the Part-of-Speech (POS) dependency to calculate two sentences syntactic structure similarity, and then through the word vector to calculate two sentences semantic similarity. Finally, we combine the two methods to calculate two Thai language sentences similarity. The proposed method not only considers semantic, but also considers the sentence syntactic structure. The experiment result shows that this method in Thai language sentence similarity computation is feasible.

  13. Adenoviral vector immunity: its implications and circumvention strategies.

    Science.gov (United States)

    Ahi, Yadvinder S; Bangari, Dinesh S; Mittal, Suresh K

    2011-08-01

    Adenoviral (Ad) vectors have emerged as a promising gene delivery platform for a variety of therapeutic and vaccine purposes during last two decades. However, the presence of preexisting Ad immunity and the rapid development of Ad vector immunity still pose significant challenges to the clinical use of these vectors. Innate inflammatory response following Ad vector administration may lead to systemic toxicity, drastically limit vector transduction efficiency and significantly abbreviate the duration of transgene expression. Currently, a number of approaches are being extensively pursued to overcome these drawbacks by strategies that target either the host or the Ad vector. In addition, significant progress has been made in the development of novel Ad vectors based on less prevalent human Ad serotypes and nonhuman Ad. This review provides an update on our current understanding of immune responses to Ad vectors and delineates various approaches for eluding Ad vector immunity. Approaches targeting the host and those targeting the vector are discussed in light of their promises and limitations.

  14. SAM: Support Vector Machine Based Active Queue Management

    International Nuclear Information System (INIS)

    Shah, M.S.

    2014-01-01

    Recent years have seen an increasing interest in the design of AQM (Active Queue Management) controllers. The purpose of these controllers is to manage the network congestion under varying loads, link delays and bandwidth. In this paper, a new AQM controller is proposed which is trained by using the SVM (Support Vector Machine) with the RBF (Radial Basis Function) kernal. The proposed controller is called the support vector based AQM (SAM) controller. The performance of the proposed controller has been compared with three conventional AQM controllers, namely the Random Early Detection, Blue and Proportional Plus Integral Controller. The preliminary simulation studies show that the performance of the proposed controller is comparable to the conventional controllers. However, the proposed controller is more efficient in controlling the queue size than the conventional controllers. (author)

  15. Modeling a ground-coupled heat pump system by a support vector machine

    Energy Technology Data Exchange (ETDEWEB)

    Esen, Hikmet; Esen, Mehmet [Department of Mechanical Education, Faculty of Technical Education, Firat University, 23119 Elazig (Turkey); Inalli, Mustafa [Department of Mechanical Engineering, Faculty of Engineering, Firat University, 23279 Elazig (Turkey); Sengur, Abdulkadir [Department of Electronic and Computer Science, Faculty of Technical Education, Firat University, 23119 Elazig (Turkey)

    2008-08-15

    This paper reports on a modeling study of ground coupled heat pump (GCHP) system performance (COP) by using a support vector machine (SVM) method. A GCHP system is a multi-variable system that is hard to model by conventional methods. As regards the SVM, it has a superior capability for generalization, and this capability is independent of the dimensionality of the input data. In this study, a SVM based method was intended to adopt GCHP system for efficient modeling. The Lin-kernel SVM method was quite efficient in modeling purposes and did not require a pre-knowledge about the system. The performance of the proposed methodology was evaluated by using several statistical validation parameters. It is found that the root-mean squared (RMS) value is 0.002722, the coefficient of multiple determinations (R{sup 2}) value is 0.999999, coefficient of variation (cov) value is 0.077295, and mean error function (MEF) value is 0.507437 for the proposed Lin-kernel SVM method. The optimum parameters of the SVM method were determined by using a greedy search algorithm. This search algorithm was effective for obtaining the optimum parameters. The simulation results show that the SVM is a good method for prediction of the COP of the GCHP system. The computation of SVM model is faster compared with other machine learning techniques (artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS)); because there are fewer free parameters and only support vectors (only a fraction of all data) are used in the generalization process. (author)

  16. Diagnosing tuberculosis with a novel support vector machine-based artificial immune recognition system.

    Science.gov (United States)

    Saybani, Mahmoud Reza; Shamshirband, Shahaboddin; Golzari Hormozi, Shahram; Wah, Teh Ying; Aghabozorgi, Saeed; Pourhoseingholi, Mohamad Amin; Olariu, Teodora

    2015-04-01

    Tuberculosis (TB) is a major global health problem, which has been ranked as the second leading cause of death from an infectious disease worldwide. Diagnosis based on cultured specimens is the reference standard, however results take weeks to process. Scientists are looking for early detection strategies, which remain the cornerstone of tuberculosis control. Consequently there is a need to develop an expert system that helps medical professionals to accurately and quickly diagnose the disease. Artificial Immune Recognition System (AIRS) has been used successfully for diagnosing various diseases. However, little effort has been undertaken to improve its classification accuracy. In order to increase the classification accuracy of AIRS, this study introduces a new hybrid system that incorporates a support vector machine into AIRS for diagnosing tuberculosis. Patient epacris reports obtained from the Pasteur laboratory of Iran were used as the benchmark data set, with the sample size of 175 (114 positive samples for TB and 60 samples in the negative group). The strategy of this study was to ensure representativeness, thus it was important to have an adequate number of instances for both TB and non-TB cases. The classification performance was measured through 10-fold cross-validation, Root Mean Squared Error (RMSE), sensitivity and specificity, Youden's Index, and Area Under the Curve (AUC). Statistical analysis was done using the Waikato Environment for Knowledge Analysis (WEKA), a machine learning program for windows. With an accuracy of 100%, sensitivity of 100%, specificity of 100%, Youden's Index of 1, Area Under the Curve of 1, and RMSE of 0, the proposed method was able to successfully classify tuberculosis patients. There have been many researches that aimed at diagnosing tuberculosis faster and more accurately. Our results described a model for diagnosing tuberculosis with 100% sensitivity and 100% specificity. This model can be used as an additional tool for

  17. Using Vector Projection Method to evaluate maintainability of mechanical system in design review

    International Nuclear Information System (INIS)

    Chen Lu; Cai Jianguo

    2003-01-01

    Maintainability of a mechanical system is one of the system design parameters that has a great impact in terms of ease of maintenance. In this article, based on the definition of the terms of maintenance and maintainability, an important tool of Design for Maintenance is developed as a way to improve maintainability through design. A set of standard and organized guidelines is provided and maintainability factors in terms of physical design, logistics support and ergonomics are identified. As a specific application of design review, a methodology so called Vector Projection Method is developed to evaluate the maintainability of the mechanical system. Lastly, an example is discussed

  18. A static investigation of the thrust vectoring system of the F/A-18 high-alpha research vehicle

    Science.gov (United States)

    Mason, Mary L.; Capone, Francis J.; Asbury, Scott C.

    1992-01-01

    A static (wind-off) test was conducted in the static test facility of the Langley 16-foot Transonic Tunnel to evaluate the vectoring capability and isolated nozzle performance of the proposed thrust vectoring system of the F/A-18 high alpha research vehicle (HARV). The thrust vectoring system consisted of three asymmetrically spaced vanes installed externally on a single test nozzle. Two nozzle configurations were tested: A maximum afterburner-power nozzle and a military-power nozzle. Vane size and vane actuation geometry were investigated, and an extensive matrix of vane deflection angles was tested. The nozzle pressure ratios ranged from two to six. The results indicate that the three vane system can successfully generate multiaxis (pitch and yaw) thrust vectoring. However, large resultant vector angles incurred large thrust losses. Resultant vector angles were always lower than the vane deflection angles. The maximum thrust vectoring angles achieved for the military-power nozzle were larger than the angles achieved for the maximum afterburner-power nozzle.

  19. Manga Vectorization and Manipulation with Procedural Simple Screentone.

    Science.gov (United States)

    Yao, Chih-Yuan; Hung, Shih-Hsuan; Li, Guo-Wei; Chen, I-Yu; Adhitya, Reza; Lai, Yu-Chi

    2017-02-01

    Manga are a popular artistic form around the world, and artists use simple line drawing and screentone to create all kinds of interesting productions. Vectorization is helpful to digitally reproduce these elements for proper content and intention delivery on electronic devices. Therefore, this study aims at transforming scanned Manga to a vector representation for interactive manipulation and real-time rendering with arbitrary resolution. Our system first decomposes the patch into rough Manga elements including possible borders and shading regions using adaptive binarization and screentone detector. We classify detected screentone into simple and complex patterns: our system extracts simple screentone properties for refining screentone borders, estimating lighting, compensating missing strokes inside screentone regions, and later resolution independently rendering with our procedural shaders. Our system treats the others as complex screentone areas and vectorizes them with our proposed line tracer which aims at locating boundaries of all shading regions and polishing all shading borders with the curve-based Gaussian refiner. A user can lay down simple scribbles to cluster Manga elements intuitively for the formation of semantic components, and our system vectorizes these components into shading meshes along with embedded Bézier curves as a unified foundation for consistent manipulation including pattern manipulation, deformation, and lighting addition. Our system can real-time and resolution independently render the shading regions with our procedural shaders and drawing borders with the curve-based shader. For Manga manipulation, the proposed vector representation can be not only magnified without artifacts but also deformed easily to generate interesting results.

  20. 2D Vector Field Simplification Based on Robustness

    KAUST Repository

    Skraba, Primoz

    2014-03-01

    Vector field simplification aims to reduce the complexity of the flow by removing features in order of their relevance and importance, to reveal prominent behavior and obtain a compact representation for interpretation. Most existing simplification techniques based on the topological skeleton successively remove pairs of critical points connected by separatrices, using distance or area-based relevance measures. These methods rely on the stable extraction of the topological skeleton, which can be difficult due to instability in numerical integration, especially when processing highly rotational flows. These geometric metrics do not consider the flow magnitude, an important physical property of the flow. In this paper, we propose a novel simplification scheme derived from the recently introduced topological notion of robustness, which provides a complementary view on flow structure compared to the traditional topological-skeleton-based approaches. Robustness enables the pruning of sets of critical points according to a quantitative measure of their stability, that is, the minimum amount of vector field perturbation required to remove them. This leads to a hierarchical simplification scheme that encodes flow magnitude in its perturbation metric. Our novel simplification algorithm is based on degree theory, has fewer boundary restrictions, and so can handle more general cases. Finally, we provide an implementation under the piecewise-linear setting and apply it to both synthetic and real-world datasets. © 2014 IEEE.

  1. Novel scanning procedure enabling the vectorization of entire rhizotron-grown root systems

    Directory of Open Access Journals (Sweden)

    Lobet Guillaume

    2013-01-01

    Full Text Available Abstract This paper presents an original spit-and-combine imaging procedure that enables the complete vectorization of complex root systems grown in rhizotrons. The general principle of the method is to (1 separate the root system into a small number of large pieces to reduce root overlap, (2 scan these pieces one by one, (3 analyze separate images with a root tracing software and (4 combine all tracings into a single vectorized root system. This method generates a rich dataset containing morphological, topological and geometrical information of entire root systems grown in rhizotrons. The utility of the method is illustrated with a detailed architectural analysis of a 20-day old maize root system, coupled with a spatial analysis of water uptake patterns.

  2. Novel scanning procedure enabling the vectorization of entire rhizotron-grown root systems.

    Science.gov (United States)

    Lobet, Guillaume; Draye, Xavier

    2013-01-04

    : This paper presents an original spit-and-combine imaging procedure that enables the complete vectorization of complex root systems grown in rhizotrons. The general principle of the method is to (1) separate the root system into a small number of large pieces to reduce root overlap, (2) scan these pieces one by one, (3) analyze separate images with a root tracing software and (4) combine all tracings into a single vectorized root system. This method generates a rich dataset containing morphological, topological and geometrical information of entire root systems grown in rhizotrons. The utility of the method is illustrated with a detailed architectural analysis of a 20-day old maize root system, coupled with a spatial analysis of water uptake patterns.

  3. Complex Polynomial Vector Fields

    DEFF Research Database (Denmark)

    The two branches of dynamical systems, continuous and discrete, correspond to the study of differential equations (vector fields) and iteration of mappings respectively. In holomorphic dynamics, the systems studied are restricted to those described by holomorphic (complex analytic) functions...... or meromorphic (allowing poles as singularities) functions. There already exists a well-developed theory for iterative holomorphic dynamical systems, and successful relations found between iteration theory and flows of vector fields have been one of the main motivations for the recent interest in holomorphic...... vector fields. Since the class of complex polynomial vector fields in the plane is natural to consider, it is remarkable that its study has only begun very recently. There are numerous fundamental questions that are still open, both in the general classification of these vector fields, the decomposition...

  4. Baculovirus expression vector system: An efficient tool for the ...

    African Journals Online (AJOL)

    Baculovirus expression vector system is considered one of the most successful and widely acceptable means for the production of recombinant proteins in extremely large quantities. Proper posttranslational modifications of the expressed proteins in insect cells, the usual host of baculoviruses, get them soluble, correctly ...

  5. Environmental management: a re-emerging vector control strategy.

    Science.gov (United States)

    Ault, S K

    1994-01-01

    Vector control may be accomplished by environmental management (EM), which consists of permanent or long-term modification of the environment, temporary or seasonal manipulation of the environment, and modifying or changing our life styles and practices to reduce human contact with infective vectors. The primary focus of this paper is EM in the control of human malaria, filariasis, arboviruses, Chagas' disease, and schistosomiasis. Modern EM developed as a discipline based primarily in ecologic principles and lessons learned from the adverse environmental impacts of rural development projects. Strategies such as the suppression of vector populations through the provision of safe water supplies, proper sanitation, solid waste management facilities, sewerage and excreta disposal systems, water manipulation in dams and irrigation systems, vector diversion by zooprophylaxis, and vector exclusion by improved housing, are discussed with appropriate examples. Vectors of malaria, filariasis, Chagas' disease, and schistosomiasis have been controlled by drainage or filling aquatic breeding sites, improved housing and sanitation, the use of expanded polystyrene beads, zooprophylaxis, or the provision of household water supplies. Community participation has been effective in the suppression of dengue vectors in Mexico and the Dominican Republic. Alone or combined with other vector control methods, EM has been proven to be a successful approach to vector control in a number of places. The future of EM in vector control looks promising.

  6. Risk based surveillance for vector borne diseases

    DEFF Research Database (Denmark)

    Bødker, Rene

    of samples and hence early detection of outbreaks. Models for vector borne diseases in Denmark have demonstrated dramatic variation in outbreak risk during the season and between years. The Danish VetMap project aims to make these risk based surveillance estimates available on the veterinarians smart phones...... in Northern Europe. This model approach may be used as a basis for risk based surveillance. In risk based surveillance limited resources for surveillance are targeted at geographical areas most at risk and only when the risk is high. This makes risk based surveillance a cost effective alternative...... sample to a diagnostic laboratory. Risk based surveillance models may reduce this delay. An important feature of risk based surveillance models is their ability to continuously communicate the level of risk to veterinarians and hence increase awareness when risk is high. This is essential for submission...

  7. Robustness-Based Simplification of 2D Steady and Unsteady Vector Fields

    KAUST Repository

    Skraba, Primoz

    2015-08-01

    © 2015 IEEE. Vector field simplification aims to reduce the complexity of the flow by removing features in order of their relevance and importance, to reveal prominent behavior and obtain a compact representation for interpretation. Most existing simplification techniques based on the topological skeleton successively remove pairs of critical points connected by separatrices, using distance or area-based relevance measures. These methods rely on the stable extraction of the topological skeleton, which can be difficult due to instability in numerical integration, especially when processing highly rotational flows. In this paper, we propose a novel simplification scheme derived from the recently introduced topological notion of robustness which enables the pruning of sets of critical points according to a quantitative measure of their stability, that is, the minimum amount of vector field perturbation required to remove them. This leads to a hierarchical simplification scheme that encodes flow magnitude in its perturbation metric. Our novel simplification algorithm is based on degree theory and has minimal boundary restrictions. Finally, we provide an implementation under the piecewise-linear setting and apply it to both synthetic and real-world datasets. We show local and complete hierarchical simplifications for steady as well as unsteady vector fields.

  8. Robustness-Based Simplification of 2D Steady and Unsteady Vector Fields.

    Science.gov (United States)

    Skraba, Primoz; Bei Wang; Guoning Chen; Rosen, Paul

    2015-08-01

    Vector field simplification aims to reduce the complexity of the flow by removing features in order of their relevance and importance, to reveal prominent behavior and obtain a compact representation for interpretation. Most existing simplification techniques based on the topological skeleton successively remove pairs of critical points connected by separatrices, using distance or area-based relevance measures. These methods rely on the stable extraction of the topological skeleton, which can be difficult due to instability in numerical integration, especially when processing highly rotational flows. In this paper, we propose a novel simplification scheme derived from the recently introduced topological notion of robustness which enables the pruning of sets of critical points according to a quantitative measure of their stability, that is, the minimum amount of vector field perturbation required to remove them. This leads to a hierarchical simplification scheme that encodes flow magnitude in its perturbation metric. Our novel simplification algorithm is based on degree theory and has minimal boundary restrictions. Finally, we provide an implementation under the piecewise-linear setting and apply it to both synthetic and real-world datasets. We show local and complete hierarchical simplifications for steady as well as unsteady vector fields.

  9. Robustness-Based Simplification of 2D Steady and Unsteady Vector Fields

    KAUST Repository

    Skraba, Primoz; Wang, Bei; Chen, Guoning; Rosen, Paul

    2015-01-01

    © 2015 IEEE. Vector field simplification aims to reduce the complexity of the flow by removing features in order of their relevance and importance, to reveal prominent behavior and obtain a compact representation for interpretation. Most existing simplification techniques based on the topological skeleton successively remove pairs of critical points connected by separatrices, using distance or area-based relevance measures. These methods rely on the stable extraction of the topological skeleton, which can be difficult due to instability in numerical integration, especially when processing highly rotational flows. In this paper, we propose a novel simplification scheme derived from the recently introduced topological notion of robustness which enables the pruning of sets of critical points according to a quantitative measure of their stability, that is, the minimum amount of vector field perturbation required to remove them. This leads to a hierarchical simplification scheme that encodes flow magnitude in its perturbation metric. Our novel simplification algorithm is based on degree theory and has minimal boundary restrictions. Finally, we provide an implementation under the piecewise-linear setting and apply it to both synthetic and real-world datasets. We show local and complete hierarchical simplifications for steady as well as unsteady vector fields.

  10. Design, development and evaluation of an online grading system for peeled pistachios equipped with machine vision technology and support vector machine

    Directory of Open Access Journals (Sweden)

    Hosein Nouri-Ahmadabadi

    2017-12-01

    Full Text Available In this study, an intelligent system based on combined machine vision (MV and Support Vector Machine (SVM was developed for sorting of peeled pistachio kernels and shells. The system was composed of conveyor belt, lighting box, camera, processing unit and sorting unit. A color CCD camera was used to capture images. The images were digitalized by a capture card and transferred to a personal computer for further analysis. Initially, images were converted from RGB color space to HSV color ones. For segmentation of the acquired images, H-component in the HSV color space and Otsu thresholding method were applied. A feature vector containing 30 color features was extracted from the captured images. A feature selection method based on sensitivity analysis was carried out to select superior features. The selected features were presented to SVM classifier. Various SVM models having a different kernel function were developed and tested. The SVM model having cubic polynomial kernel function and 38 support vectors achieved the best accuracy (99.17% and then was selected to use in online decision-making unit of the system. By launching the online system, it was found that limiting factors of the system capacity were related to the hardware parts of the system (conveyor belt and pneumatic valves used in the sorting unit. The limiting factors led to a distance of 8 mm between the samples. The overall accuracy and capacity of the sorter were obtained 94.33% and 22.74 kg/h, respectively. Keywords: Pistachio kernel, Sorting, Machine vision, Sensitivity analysis, Support vector machine

  11. Vectorization, parallelization and porting of nuclear codes (vectorization and parallelization). Progress report fiscal 1998

    International Nuclear Information System (INIS)

    Ishizuki, Shigeru; Kawai, Wataru; Nemoto, Toshiyuki; Ogasawara, Shinobu; Kume, Etsuo; Adachi, Masaaki; Kawasaki, Nobuo; Yatake, Yo-ichi

    2000-03-01

    Several computer codes in the nuclear field have been vectorized, parallelized and transported on the FUJITSU VPP500 system, the AP3000 system and the Paragon system at Center for Promotion of Computational Science and Engineering in Japan Atomic Energy Research Institute. We dealt with 12 codes in fiscal 1998. These results are reported in 3 parts, i.e., the vectorization and parallelization on vector processors part, the parallelization on scalar processors part and the porting part. In this report, we describe the vectorization and parallelization on vector processors. In this vectorization and parallelization on vector processors part, the vectorization of General Tokamak Circuit Simulation Program code GTCSP, the vectorization and parallelization of Molecular Dynamics NTV (n-particle, Temperature and Velocity) Simulation code MSP2, Eddy Current Analysis code EDDYCAL, Thermal Analysis Code for Test of Passive Cooling System by HENDEL T2 code THANPACST2 and MHD Equilibrium code SELENEJ on the VPP500 are described. In the parallelization on scalar processors part, the parallelization of Monte Carlo N-Particle Transport code MCNP4B2, Plasma Hydrodynamics code using Cubic Interpolated Propagation Method PHCIP and Vectorized Monte Carlo code (continuous energy model / multi-group model) MVP/GMVP on the Paragon are described. In the porting part, the porting of Monte Carlo N-Particle Transport code MCNP4B2 and Reactor Safety Analysis code RELAP5 on the AP3000 are described. (author)

  12. Researches on Key Algorithms in Analogue Seismogram Records Vectorization

    Directory of Open Access Journals (Sweden)

    Maofa WANG

    2014-09-01

    Full Text Available History paper seismograms are very important information for earthquake monitoring and prediction, and the vectorization of paper seismograms is a very import problem to be resolved. In our study, a new tracing algorithm for simulated seismogram curves based on visual filed feature is presented. We also give out the technological process to vectorizing simulated seismograms, and an analog seismic record vectorization system has been accomplished independently. Using it, we can precisely and speedy vectorize analog seismic records (need professionals to participate interactively.

  13. Track Circuit Fault Diagnosis Method based on Least Squares Support Vector

    Science.gov (United States)

    Cao, Yan; Sun, Fengru

    2018-01-01

    In order to improve the troubleshooting efficiency and accuracy of the track circuit, track circuit fault diagnosis method was researched. Firstly, the least squares support vector machine was applied to design the multi-fault classifier of the track circuit, and then the measured track data as training samples was used to verify the feasibility of the methods. Finally, the results based on BP neural network fault diagnosis methods and the methods used in this paper were compared. Results shows that the track fault classifier based on least squares support vector machine can effectively achieve the five track circuit fault diagnosis with less computing time.

  14. Axial-vector gluons and the fine structure of heavy quark--antiquark systems

    International Nuclear Information System (INIS)

    Feinberg, G.; Lynn, B.; Sucher, J.

    1979-01-01

    We point out that two models of the origin of spin-dependent forces in heavy quark systems make very different predictions about the relative size of these forces in c-barc and b-barb. The model in which these forces are relativistic corrections to vector or scalar gluon exchange predicts smaller spin-dependent effects in b-barb than in c-barc while a model in which these forces are due to exchange of axial-vector gluons predicts a similar size for spin-dependent splittings in the two systems

  15. Solution of single linear tridiagonal systems and vectorization of the ICCG algorithm on the Cray 1

    International Nuclear Information System (INIS)

    Kershaw, D.S.

    1981-01-01

    The numerical algorithms used to solve the physics equation in codes which model laser fusion are examined, it is found that a large number of subroutines require the solution of tridiagonal linear systems of equations. One dimensional radiation transport, thermal and suprathermal electron transport, ion thermal conduction, charged particle and neutron transport, all require the solution of tridiagonal systems of equations. The standard algorithm that has been used in the past on CDC 7600's will not vectorize and so cannot take advantage of the large speed increases possible on the Cray-1 through vectorization. There is however, an alternate algorithm for solving tridiagonal systems, called cyclic reduction, which allows for vectorization, and which is optimal for the Cray-1. Software based on this algorithm is now being used in LASNEX to solve tridiagonal linear systems in the subroutines mentioned above. The new algorithm runs as much as five times faster than the standard algorithm on the Cray-1. The ICCG method is being used to solve the diffusion equation with a nine-point coupling scheme on the CDC 7600. In going from the CDC 7600 to the Cray-1, a large part of the algorithm consists of solving tridiagonal linear systems on each L line of the Lagrangian mesh in a manner which is not vectorizable. An alternate ICCG algorithm for the Cray-1 was developed which utilizes a block form of the cyclic reduction algorithm. This new algorithm allows full vectorization and runs as much as five times faster than the old algorithm on the Cray-1. It is now being used in Cray LASNEX to solve the two-dimensional diffusion equation in all the physics subroutines mentioned above

  16. Speculative dynamic vectorization to assist static vectorization in a HW/SW co-designed environment

    OpenAIRE

    Kumar, R.; Martinez, A.; Gonzalez, A.

    2013-01-01

    Compiler based static vectorization is used widely to extract data level parallelism from computation intensive applications. Static vectorization is very effective in vectorizing traditional array based applications. However, compilers inability to reorder ambiguous memory references severely limits vectorization opportunities, especially in pointer rich applications. HW/SW co-designed processors provide an excellent opportunity to optimize the applications at runtime. The availability of dy...

  17. Stokes vector based interpolation method to improve the efficiency of bio-inspired polarization-difference imaging in turbid media

    Science.gov (United States)

    Guan, Jinge; Ren, Wei; Cheng, Yaoyu

    2018-04-01

    We demonstrate an efficient polarization-difference imaging system in turbid conditions by using the Stokes vector of light. The interaction of scattered light with the polarizer is analyzed by the Stokes-Mueller formalism. An interpolation method is proposed to replace the mechanical rotation of the polarization axis of the analyzer theoretically, and its performance is verified by the experiment at different turbidity levels. We show that compared with direct imaging, the Stokes vector based imaging method can effectively reduce the effect of light scattering and enhance the image contrast.

  18. Fuzzy-based multi-kernel spherical support vector machine for ...

    Indian Academy of Sciences (India)

    In the proposed classifier, we design a new multi-kernel function based on the fuzzy triangular membership function. Finally, a newly developed multi-kernel function is incorporated into the spherical support vector machine to enhance the performance significantly. The experimental results are evaluated and performance is ...

  19. Vector control of three-phase AC machines system development in the practice

    CERN Document Server

    Quang, Nguyen Phung; Dittrich, J

    2015-01-01

    This book addresses the vector control of three-phase AC machines, in particular induction motors with squirrel-cage rotors (IM), permanent magnet synchronous motors (PMSM) and doubly-fed induction machines (DFIM), from a practical design and development perspective. The main focus is on the application of IM and PMSM in electrical drive systems, where field-orientated control has been successfully established in practice. It also discusses the use of grid-voltage oriented control of DFIMs in wind power plants. This second, enlarged edition includes new insights into flatness-based  nonlinear

  20. A simple vector system to improve performance and utilisation of recombinant antibodies

    Directory of Open Access Journals (Sweden)

    Vincent Karen J

    2006-12-01

    Full Text Available Abstract Background Isolation of recombinant antibody fragments from antibody libraries is well established using technologies such as phage display. Phage display vectors are ideal for efficient display of antibody fragments on the surface of bacteriophage particles. However, they are often inefficient for expression of soluble antibody fragments, and sub-cloning of selected antibody populations into dedicated soluble antibody fragment expression vectors can enhance expression. Results We have developed a simple vector system for expression, dimerisation and detection of recombinant antibody fragments in the form of single chain Fvs (scFvs. Expression is driven by the T7 RNA polymerase promoter in conjunction with the inducible lysogen strain BL21 (DE3. The system is compatible with a simple auto-induction culture system for scFv production. As an alternative to periplasmic expression, expression directly in the cytoplasm of a mutant strain with a more oxidising cytoplasmic environment (Origami 2™ (DE3 was investigated and found to be inferior to periplasmic expression in BL21 (DE3 cells. The effect on yield and binding activity of fusing scFvs to the N terminus of maltose binding protein (a solubility enhancing partner, bacterial alkaline phosphatase (a naturally dimeric enzymatic reporter molecule, or the addition of a free C-terminal cysteine was determined. Fusion of scFvs to the N-terminus of maltose binding protein increased scFv yield but binding activity of the scFv was compromised. In contrast, fusion to the N-terminus of bacterial alkaline phosphatase led to an improved performance. Alkaline phosphatase provides a convenient tag allowing direct enzymatic detection of scFv fusions within crude extracts without the need for secondary reagents. Alkaline phosphatase also drives dimerisation of the scFv leading to an improvement in performance compared to monovalent constructs. This is illustrated by ELISA, western blot and

  1. Mapping of courses on vector biology and vector-borne diseases systems: time for a worldwide effort

    Science.gov (United States)

    Casas, Jérôme; Lazzari, Claudio; Insausti, Teresita; Launois, Pascal; Fouque, Florence

    2016-01-01

    Major emergency efforts are being mounted for each vector-borne disease epidemiological crisis anew, while knowledge about the biology of arthropods vectors is dwindling slowly but continuously, as is the number of field entomologists. The discrepancy between the rates of production of knowledge and its use and need for solving crises is widening, in particular due to the highly differing time spans of the two concurrent processes. A worldwide web based search using multiple key words and search engines of onsite and online courses in English, Spanish, Portuguese, French, Italian and German concerned with the biology of vectors identified over 140 courses. They are geographically and thematically scattered, the vast majority of them are on-site, with very few courses using the latest massive open online course (MOOC) powerfulness. Over two third of them is given in English and Western Africa is particularity poorly represented. The taxonomic groups covered are highly unbalanced towards mosquitoes. A worldwide unique portal to guide students of all grades and levels of expertise, in particular those in remote locations, is badly needed. This is the objective a new activity supported by the Special Programme for Research and Training in Tropical Diseases (TDR). PMID:27759770

  2. Complex Polynomial Vector Fields

    DEFF Research Database (Denmark)

    Dias, Kealey

    vector fields. Since the class of complex polynomial vector fields in the plane is natural to consider, it is remarkable that its study has only begun very recently. There are numerous fundamental questions that are still open, both in the general classification of these vector fields, the decomposition...... of parameter spaces into structurally stable domains, and a description of the bifurcations. For this reason, the talk will focus on these questions for complex polynomial vector fields.......The two branches of dynamical systems, continuous and discrete, correspond to the study of differential equations (vector fields) and iteration of mappings respectively. In holomorphic dynamics, the systems studied are restricted to those described by holomorphic (complex analytic) functions...

  3. Web-based public health geographic information systems for resources-constrained environment using scalable vector graphics technology: a proof of concept applied to the expanded program on immunization data

    Directory of Open Access Journals (Sweden)

    Kamadjeu Raoul

    2006-06-01

    Full Text Available Abstract Background Geographic Information Systems (GIS are powerful communication tools for public health. However, using GIS requires considerable skill and, for this reason, is sometimes limited to experts. Web-based GIS has emerged as a solution to allow a wider audience to have access to geospatial information. Unfortunately the cost of implementing proprietary solutions may be a limiting factor in the adoption of a public health GIS in a resource-constrained environment. Scalable Vector Graphics (SVG is used to define vector-based graphics for the internet using XML (eXtensible Markup Language; it is an open, platform-independent standard maintained by the World Wide Web Consortium (W3C since 2003. In this paper, we summarize our methodology and demonstrate the potential of this free and open standard to contribute to the dissemination of Expanded Program on Immunization (EPI information by providing interactive maps to a wider audience through the Internet. Results We used SVG to develop a database driven web-based GIS applied to EPI data from three countries of WHO AFRO (World Health Organization – African Region. The system generates interactive district-level country immunization coverage maps and graphs. The approach we describe can be expanded to cover other public health GIS demanding activities, including the design of disease atlases in a resources-constrained environment. Conclusion Our system contributes to accumulating evidence demonstrating the potential of SVG technology to develop web-based public health GIS in resources-constrained settings.

  4. Web-based public health geographic information systems for resources-constrained environment using scalable vector graphics technology: a proof of concept applied to the expanded program on immunization data.

    Science.gov (United States)

    Kamadjeu, Raoul; Tolentino, Herman

    2006-06-03

    Geographic Information Systems (GIS) are powerful communication tools for public health. However, using GIS requires considerable skill and, for this reason, is sometimes limited to experts. Web-based GIS has emerged as a solution to allow a wider audience to have access to geospatial information. Unfortunately the cost of implementing proprietary solutions may be a limiting factor in the adoption of a public health GIS in a resource-constrained environment. Scalable Vector Graphics (SVG) is used to define vector-based graphics for the internet using XML (eXtensible Markup Language); it is an open, platform-independent standard maintained by the World Wide Web Consortium (W3C) since 2003. In this paper, we summarize our methodology and demonstrate the potential of this free and open standard to contribute to the dissemination of Expanded Program on Immunization (EPI) information by providing interactive maps to a wider audience through the Internet. We used SVG to develop a database driven web-based GIS applied to EPI data from three countries of WHO AFRO (World Health Organization - African Region). The system generates interactive district-level country immunization coverage maps and graphs. The approach we describe can be expanded to cover other public health GIS demanding activities, including the design of disease atlases in a resources-constrained environment. Our system contributes to accumulating evidence demonstrating the potential of SVG technology to develop web-based public health GIS in resources-constrained settings.

  5. A new generation of pPRIG-based retroviral vectors

    Directory of Open Access Journals (Sweden)

    Boulukos Kim E

    2007-11-01

    Full Text Available Abstract Background Retroviral vectors are valuable tools for gene transfer. Particularly convenient are IRES-containing retroviral vectors expressing both the protein of interest and a marker protein from a single bicistronic mRNA. This coupled expression increases the relevance of tracking and/or selection of transduced cells based on the detection of a marker protein. pAP2 is a retroviral vector containing eGFP downstream of a modified IRES element of EMCV origin, and a CMV enhancer-promoter instead of the U3 region of the 5'LTR, which increases its efficiency in transient transfection. However, pAP2 contains a limited multicloning site (MCS and shows weak eGFP expression, which previously led us to engineer an improved version, termed pPRIG, harboring: i the wild-type ECMV IRES sequence, thereby restoring its full activity; ii an optimized MCS flanked by T7 and SP6 sequences; and iii a HA tag encoding sequence 5' of the MCS (pPRIG HAa/b/c. Results The convenience of pPRIG makes it a good basic vector to generate additional derivatives for an extended range of use. Here we present several novel pPRIG-based vectors (collectively referred to as PRIGs in which : i the HA tag sequence was inserted in the three reading frames 3' of the MCS (3'HA PRIGs; ii a functional domain (ER, VP16 or KRAB was inserted either 5' or 3' of the MCS (« modular » PRIGs; iii eGFP was replaced by either eCFP, eYFP, mCherry or puro-R (« single color/resistance » PRIGs; and iv mCherry, eYFP or eGFP was inserted 5' of the MCS of the IRES-eGFP, IRES-eCFP or IRES-Puro-R containing PRIGs, respectively (« dual color/selection » PRIGs. Additionally, some of these PRIGs were also constructed in a pMigR MSCV background which has been widely used in pluripotent cells. Conclusion These novel vectors allow for straightforward detection of any expressed protein (3'HA PRIGs, for functional studies of chimeric proteins (« modular » PRIGs, for multiple transductions and

  6. Product demand forecasts using wavelet kernel support vector machine and particle swarm optimization in manufacture system

    Science.gov (United States)

    Wu, Qi

    2010-03-01

    Demand forecasts play a crucial role in supply chain management. The future demand for a certain product is the basis for the respective replenishment systems. Aiming at demand series with small samples, seasonal character, nonlinearity, randomicity and fuzziness, the existing support vector kernel does not approach the random curve of the sales time series in the space (quadratic continuous integral space). In this paper, we present a hybrid intelligent system combining the wavelet kernel support vector machine and particle swarm optimization for demand forecasting. The results of application in car sale series forecasting show that the forecasting approach based on the hybrid PSOWv-SVM model is effective and feasible, the comparison between the method proposed in this paper and other ones is also given, which proves that this method is, for the discussed example, better than hybrid PSOv-SVM and other traditional methods.

  7. Support vector machine based fault detection approach for RFT-30 cyclotron

    Energy Technology Data Exchange (ETDEWEB)

    Kong, Young Bae, E-mail: ybkong@kaeri.re.kr; Lee, Eun Je; Hur, Min Goo; Park, Jeong Hoon; Park, Yong Dae; Yang, Seung Dae

    2016-10-21

    An RFT-30 is a 30 MeV cyclotron used for radioisotope applications and radiopharmaceutical researches. The RFT-30 cyclotron is highly complex and includes many signals for control and monitoring of the system. It is quite difficult to detect and monitor the system failure in real time. Moreover, continuous monitoring of the system is hard and time-consuming work for human operators. In this paper, we propose a support vector machine (SVM) based fault detection approach for the RFT-30 cyclotron. The proposed approach performs SVM learning with training samples to construct the classification model. To compensate the system complexity due to the large-scale accelerator, we utilize the principal component analysis (PCA) for transformation of the original data. After training procedure, the proposed approach detects the system faults in real time. We analyzed the performance of the proposed approach utilizing the experimental data of the RFT-30 cyclotron. The performance results show that the proposed SVM approach can provide an efficient way to control the cyclotron system.

  8. Hyperbolic-symmetry vector fields.

    Science.gov (United States)

    Gao, Xu-Zhen; Pan, Yue; Cai, Meng-Qiang; Li, Yongnan; Tu, Chenghou; Wang, Hui-Tian

    2015-12-14

    We present and construct a new kind of orthogonal coordinate system, hyperbolic coordinate system. We present and design a new kind of local linearly polarized vector fields, which is defined as the hyperbolic-symmetry vector fields because the points with the same polarization form a series of hyperbolae. We experimentally demonstrate the generation of such a kind of hyperbolic-symmetry vector optical fields. In particular, we also study the modified hyperbolic-symmetry vector optical fields with the twofold and fourfold symmetric states of polarization when introducing the mirror symmetry. The tight focusing behaviors of these vector fields are also investigated. In addition, we also fabricate micro-structures on the K9 glass surfaces by several tightly focused (modified) hyperbolic-symmetry vector fields patterns, which demonstrate that the simulated tightly focused fields are in good agreement with the fabricated micro-structures.

  9. A formula for the Bloch vector of some Lindblad quantum systems

    International Nuclear Information System (INIS)

    Salgado, D.; Sanchez-Gomez, J.L.

    2004-01-01

    Using the Bloch representation of an N-dimensional quantum system and immediate results from quantum stochastic calculus, we establish a closed formula for the Bloch vector, hence also for the density operator, of a quantum system following a Lindblad evolution with selfadjoint Lindblad operators

  10. Predictive control strategies for wind turbine system based on permanent magnet synchronous generator.

    Science.gov (United States)

    Maaoui-Ben Hassine, Ikram; Naouar, Mohamed Wissem; Mrabet-Bellaaj, Najiba

    2016-05-01

    In this paper, Model Predictive Control and Dead-beat predictive control strategies are proposed for the control of a PMSG based wind energy system. The proposed MPC considers the model of the converter-based system to forecast the possible future behavior of the controlled variables. It allows selecting the voltage vector to be applied that leads to a minimum error by minimizing a predefined cost function. The main features of the MPC are low current THD and robustness against parameters variations. The Dead-beat predictive control is based on the system model to compute the optimum voltage vector that ensures zero-steady state error. The optimum voltage vector is then applied through Space Vector Modulation (SVM) technique. The main advantages of the Dead-beat predictive control are low current THD and constant switching frequency. The proposed control techniques are presented and detailed for the control of back-to-back converter in a wind turbine system based on PMSG. Simulation results (under Matlab-Simulink software environment tool) and experimental results (under developed prototyping platform) are presented in order to show the performances of the considered control strategies. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  11. Symbolic computer vector analysis

    Science.gov (United States)

    Stoutemyer, D. R.

    1977-01-01

    A MACSYMA program is described which performs symbolic vector algebra and vector calculus. The program can combine and simplify symbolic expressions including dot products and cross products, together with the gradient, divergence, curl, and Laplacian operators. The distribution of these operators over sums or products is under user control, as are various other expansions, including expansion into components in any specific orthogonal coordinate system. There is also a capability for deriving the scalar or vector potential of a vector field. Examples include derivation of the partial differential equations describing fluid flow and magnetohydrodynamics, for 12 different classic orthogonal curvilinear coordinate systems.

  12. Object Recognition System-on-Chip Using the Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Houzet Dominique

    2005-01-01

    Full Text Available The first aim of this work is to propose the design of a system-on-chip (SoC platform dedicated to digital image and signal processing, which is tuned to implement efficiently multiply-and-accumulate (MAC vector/matrix operations. The second aim of this work is to implement a recent promising neural network method, namely, the support vector machine (SVM used for real-time object recognition, in order to build a vision machine. With such a reconfigurable and programmable SoC platform, it is possible to implement any SVM function dedicated to any object recognition problem. The final aim is to obtain an automatic reconfiguration of the SoC platform, based on the results of the learning phase on an objects' database, which makes it possible to recognize practically any object without manual programming. Recognition can be of any kind that is from image to signal data. Such a system is a general-purpose automatic classifier. Many applications can be considered as a classification problem, but are usually treated specifically in order to optimize the cost of the implemented solution. The cost of our approach is more important than a dedicated one, but in a near future, hundreds of millions of gates will be common and affordable compared to the design cost. What we are proposing here is a general-purpose classification neural network implemented on a reconfigurable SoC platform. The first version presented here is limited in size and thus in object recognition performances, but can be easily upgraded according to technology improvements.

  13. Smart DNA vectors based on cyclodextrin polymers: compaction and endosomal release.

    Science.gov (United States)

    Wintgens, Véronique; Leborgne, Christian; Baconnais, Sonia; Burckbuchler, Virginie; Le Cam, Eric; Scherman, Daniel; Kichler, Antoine; Amiel, Catherine

    2012-02-01

    Neutral β-cyclodextrin polymers (polyβCD) associated with cationic adamantyl derivatives (Ada) can be used to deliver plasmid DNA into cells. In absence of an endosomolytic agent, transfection efficiency remains low because most complexes are trapped in the endosomal compartment. We asked whether addition of an imidazole-modified Ada can increase efficiency of polyβCD/cationic Ada-based delivery system. We synthesized two adamantyl derivatives: Ada5, which has a spacer arm between the Ada moiety and a bi-cationic polar head group, and Ada6, which presents an imidazole group. Strength of association between polyβCD and Ada derivatives was evaluated by fluorimetric titration. Gel mobility shift assay, zeta potential, and dark field transmission electron microscopy experiments demonstrated the system allowed for efficient DNA compaction. In vitro transfection experiments performed on HepG2 and HEK293 cells revealed the quaternary system polyβCD/Ada5/Ada6/DNA has efficiency comparable to cationic lipid DOTAP. We successfully designed fine-tuned DNA vectors based on cyclodextrin polymers combined with two new adamantyl derivatives, leading to significant transfection associated with low toxicity.

  14. Vectorization of KENO IV code and an estimate of vector-parallel processing

    International Nuclear Information System (INIS)

    Asai, Kiyoshi; Higuchi, Kenji; Katakura, Jun-ichi; Kurita, Yutaka.

    1986-10-01

    The multi-group criticality safety code KENO IV has been vectorized and tested on FACOM VP-100 vector processor. At first the vectorized KENO IV on a scalar processor became slower than the original one by a factor of 1.4 because of the overhead introduced by the vectorization. Making modifications of algorithms and techniques for vectorization, the vectorized version has become faster than the original one by a factor of 1.4 and 3.0 on the vector processor for sample problems of complex and simple geometries, respectively. For further speedup of the code, some improvements on compiler and hardware, especially on addition of Monte Carlo pipelines to the vector processor, are discussed. Finally a pipelined parallel processor system is proposed and its performance is estimated. (author)

  15. Support vector machine for automatic pain recognition

    Science.gov (United States)

    Monwar, Md Maruf; Rezaei, Siamak

    2009-02-01

    Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.

  16. Engineering BioBrick vectors from BioBrick parts

    Directory of Open Access Journals (Sweden)

    Knight Thomas F

    2008-04-01

    Full Text Available Abstract Background The underlying goal of synthetic biology is to make the process of engineering biological systems easier. Recent work has focused on defining and developing standard biological parts. The technical standard that has gained the most traction in the synthetic biology community is the BioBrick standard for physical composition of genetic parts. Parts that conform to the BioBrick assembly standard are BioBrick standard biological parts. To date, over 2,000 BioBrick parts have been contributed to, and are available from, the Registry of Standard Biological Parts. Results Here we extended the same advantages of BioBrick standard biological parts to the plasmid-based vectors that are used to provide and propagate BioBrick parts. We developed a process for engineering BioBrick vectors from BioBrick parts. We designed a new set of BioBrick parts that encode many useful vector functions. We combined the new parts to make a BioBrick base vector that facilitates BioBrick vector construction. We demonstrated the utility of the process by constructing seven new BioBrick vectors. We also successfully used the resulting vectors to assemble and propagate other BioBrick standard biological parts. Conclusion We extended the principles of part reuse and standardization to BioBrick vectors. As a result, myriad new BioBrick vectors can be readily produced from all existing and newly designed BioBrick parts. We invite the synthetic biology community to (1 use the process to make and share new BioBrick vectors; (2 expand the current collection of BioBrick vector parts; and (3 characterize and improve the available collection of BioBrick vector parts.

  17. Integrating Transgenic Vector Manipulation with Clinical Interventions to Manage Vector-Borne Diseases.

    Directory of Open Access Journals (Sweden)

    Kenichi W Okamoto

    2016-03-01

    Full Text Available Many vector-borne diseases lack effective vaccines and medications, and the limitations of traditional vector control have inspired novel approaches based on using genetic engineering to manipulate vector populations and thereby reduce transmission. Yet both the short- and long-term epidemiological effects of these transgenic strategies are highly uncertain. If neither vaccines, medications, nor transgenic strategies can by themselves suffice for managing vector-borne diseases, integrating these approaches becomes key. Here we develop a framework to evaluate how clinical interventions (i.e., vaccination and medication can be integrated with transgenic vector manipulation strategies to prevent disease invasion and reduce disease incidence. We show that the ability of clinical interventions to accelerate disease suppression can depend on the nature of the transgenic manipulation deployed (e.g., whether vector population reduction or replacement is attempted. We find that making a specific, individual strategy highly effective may not be necessary for attaining public-health objectives, provided suitable combinations can be adopted. However, we show how combining only partially effective antimicrobial drugs or vaccination with transgenic vector manipulations that merely temporarily lower vector competence can amplify disease resurgence following transient suppression. Thus, transgenic vector manipulation that cannot be sustained can have adverse consequences-consequences which ineffective clinical interventions can at best only mitigate, and at worst temporarily exacerbate. This result, which arises from differences between the time scale on which the interventions affect disease dynamics and the time scale of host population dynamics, highlights the importance of accounting for the potential delay in the effects of deploying public health strategies on long-term disease incidence. We find that for systems at the disease-endemic equilibrium, even

  18. Very low speed performance of active flux based sensorless control: interior permanent magnet synchronous motor vector control versus direct torque and flux control

    DEFF Research Database (Denmark)

    Paicu, M. C.; Boldea, I.; Andreescu, G. D.

    2009-01-01

    This study is focused on very low speed performance comparison between two sensorless control systems based on the novel ‘active flux' concept, that is, the current/voltage vector control versus direct torque and flux control (DTFC) for interior permanent magnet synchronous motor (IPMSM) drives...... with space vector modulation (SVM), without signal injection. The active flux, defined as the flux that multiplies iq current in the dq-model torque expression of all ac machines, is easily obtained from the stator-flux vector and has the rotor position orientation. Therefore notable simplification...

  19. Efficient gene transfer into nondividing cells by adeno-associated virus-based vectors.

    OpenAIRE

    Podsakoff, G; Wong, K K; Chatterjee, S

    1994-01-01

    Gene transfer vectors based on adeno-associated virus (AAV) are emerging as highly promising for use in human gene therapy by virtue of their characteristics of wide host range, high transduction efficiencies, and lack of cytopathogenicity. To better define the biology of AAV-mediated gene transfer, we tested the ability of an AAV vector to efficiently introduce transgenes into nonproliferating cell populations. Cells were induced into a nonproliferative state by treatment with the DNA synthe...

  20. DSP Based Direct Torque Control of Permanent Magnet Synchronous Motor (PMSM) using Space Vector Modulation (DTC-SVM)

    DEFF Research Database (Denmark)

    Swierczynski, Dariusz; Kazmierkowski, Marian P.; Blaabjerg, Frede

    2002-01-01

    DSP Based Direct Torque Control of Permanent Magnet Synchronous Motor (PMSM) using Space Vector Modulation (DTC-SVM)......DSP Based Direct Torque Control of Permanent Magnet Synchronous Motor (PMSM) using Space Vector Modulation (DTC-SVM)...

  1. Multiscale asymmetric orthogonal wavelet kernel for linear programming support vector learning and nonlinear dynamic systems identification.

    Science.gov (United States)

    Lu, Zhao; Sun, Jing; Butts, Kenneth

    2014-05-01

    Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.

  2. Expression of Separate Proteins in the Same Plant Leaves and Cells Using Two Independent Virus-Based Gene Vectors

    Directory of Open Access Journals (Sweden)

    Maria R. Mendoza

    2017-11-01

    Full Text Available Plant viral vectors enable the expression of proteins at high levels in a relatively short time. For many purposes (e.g., cell biological interaction studies it may be desirable to express more than one protein in a single cell but that is often not feasible when using a single virus vector. Such a co-expression strategy requires the simultaneous delivery by two compatible and non-competitive viruses that can co-exist to each express a separate protein. Here, we report on the use of two agro-launchable coat-protein gene substitution GFP-expressing virus vector systems based on Tomato bushy stunt virus (TBSV referred to as TG, and Tobacco mosaic virus (TMV annotated as TRBO-G. TG expressed GFP in Nicotiana benthamiana, tomato, lettuce and cowpea, whereas expression from TRBO-G was detected only in the first two species. Upon co-infiltration of the two vectors co-expression was monitored by: molecular detection of the two slightly differently sized GFPs, suppressor-complementation assays, and using TG in combination with TRBO-RFP. All the results revealed that in N. benthamiana and tomato the TBSV and TMV vectors accumulated and expressed proteins in the same plants, the same leaves, and in the same cells. Therefore, co-expression by these two vectors provides a platform for fast and high level expression of proteins to study their cell biology or other properties.

  3. Vectorization of phase space Monte Carlo code in FACOM vector processor VP-200

    International Nuclear Information System (INIS)

    Miura, Kenichi

    1986-01-01

    This paper describes the vectorization techniques for Monte Carlo codes in Fujitsu's Vector Processor System. The phase space Monte Carlo code FOWL is selected as a benchmark, and scalar and vector performances are compared. The vectorized kernel Monte Carlo routine which contains heavily nested IF tests runs up to 7.9 times faster in vector mode than in scalar mode. The overall performance improvement of the vectorized FOWL code over the original scalar code reaches 3.3. The results of this study strongly indicate that supercomputer can be a powerful tool for Monte Carlo simulations in high energy physics. (Auth.)

  4. Learning word vector representations based on acoustic counts

    OpenAIRE

    Ribeiro, Sam; Watts, Oliver; Yamagishi, Junichi

    2017-01-01

    This paper presents a simple count-based approach to learning word vector representations by leveraging statistics of cooccurrences between text and speech. This type of representation requires two discrete sequences of units defined across modalities. Two possible methods for the discretization of an acoustic signal are presented, which are then applied to fundamental frequency and energy contours of a transcribed corpus of speech, yielding a sequence of textual objects (e.g. words, syllable...

  5. Measurement of Charmless B to Vector-Vector decays at BaBar

    International Nuclear Information System (INIS)

    Olaiya, Emmanuel

    2011-01-01

    The authors present results of B → vector-vector (VV) and B → vector-axial vector (VA) decays B 0 → φX(X = φ,ρ + or ρ 0 ), B + → φK (*)+ , B 0 → K*K*, B 0 → ρ + b 1 - and B + → K* 0 α 1 + . The largest dataset used for these results is based on 465 x 10 6 Υ(4S) → B(bar B) decays, collected with the BABAR detector at the PEP-II B meson factory located at the Stanford Linear Accelerator Center (SLAC). Using larger datasets, the BABAR experiment has provided more precise B → VV measurements, further supporting the smaller than expected longitudinal polarization fraction of B → φK*. Additional B meson to vector-vector and vector-axial vector decays have also been studied with a view to shedding light on the polarization anomaly. Taking into account the available errors, we find no disagreement between theory and experiment for these additional decays.

  6. Face Recognition Performance Improvement using a Similarity Score of Feature Vectors based on Probabilistic Histograms

    Directory of Open Access Journals (Sweden)

    SRIKOTE, G.

    2016-08-01

    Full Text Available This paper proposes an improved performance algorithm of face recognition to identify two face mismatch pairs in cases of incorrect decisions. The primary feature of this method is to deploy the similarity score with respect to Gaussian components between two previously unseen faces. Unlike the conventional classical vector distance measurement, our algorithms also consider the plot of summation of the similarity index versus face feature vector distance. A mixture of Gaussian models of labeled faces is also widely applicable to different biometric system parameters. By comparative evaluations, it has been shown that the efficiency of the proposed algorithm is superior to that of the conventional algorithm by an average accuracy of up to 1.15% and 16.87% when compared with 3x3 Multi-Region Histogram (MRH direct-bag-of-features and Principal Component Analysis (PCA-based face recognition systems, respectively. The experimental results show that similarity score consideration is more discriminative for face recognition compared to feature distance. Experimental results of Labeled Face in the Wild (LFW data set demonstrate that our algorithms are suitable for real applications probe-to-gallery identification of face recognition systems. Moreover, this proposed method can also be applied to other recognition systems and therefore additionally improves recognition scores.

  7. Systemic Errors in Quantitative Polymerase Chain Reaction Titration of Self-Complementary Adeno-Associated Viral Vectors and Improved Alternative Methods

    Science.gov (United States)

    Fagone, Paolo; Wright, J. Fraser; Nathwani, Amit C.; Nienhuis, Arthur W.; Davidoff, Andrew M.

    2012-01-01

    Abstract Self-complementary AAV (scAAV) vector genomes contain a covalently closed hairpin derived from a mutated inverted terminal repeat that connects the two monomer single-stranded genomes into a head-to-head or tail-to-tail dimer. We found that during quantitative PCR (qPCR) this structure inhibits the amplification of proximal amplicons and causes the systemic underreporting of copy number by as much as 10-fold. We show that cleavage of scAAV vector genomes with restriction endonuclease to liberate amplicons from the covalently closed terminal hairpin restores quantitative amplification, and we implement this procedure in a simple, modified qPCR titration method for scAAV vectors. In addition, we developed and present an AAV genome titration procedure based on gel electrophoresis that requires minimal sample processing and has low interassay variability, and as such is well suited for the rigorous quality control demands of clinical vector production facilities. PMID:22428975

  8. Direct-current vector control of three-phase grid-connected rectifier-inverter

    Energy Technology Data Exchange (ETDEWEB)

    Li, Shuhui; Haskew, Timothy A.; Hong, Yang-Ki; Xu, Ling [Department of Electrical and Computer Engineering, University of Alabama, Tuscaloosa, AL 35475 (United States)

    2011-02-15

    The three-phase grid-connected converter is widely used in renewable and electric power system applications. Traditionally, control of the three-phase grid-connected converter is based on the standard decoupled d-q vector control mechanism. Nevertheless, the study of this paper shows that there is a limitation in the conventional standard vector control method. Some of the limitations have also been found recently by other researchers. To overcome the shortage of the conventional vector control technique, this paper proposes a new direct-current d-q vector control mechanism in a nested-loop control structure, based on which an optimal control strategy is developed in a nonlinear programming formulation. The behaviors of both the conventional and proposed control methods are compared and evaluated in simulation and laboratory hardware experiment environments, both of which demonstrates that the proposed approach is effective for grid-connected power converter control in a wide system conditions while the conventional standard vector control approach may behave improperly especially when the converter operates beyond its PWM saturation limit. (author)

  9. Comparative Visualization of Vector Field Ensembles Based on Longest Common Subsequence

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Richen; Guo, Hanqi; Zhang, Jiang; Yuan, Xiaoru

    2016-04-19

    We propose a longest common subsequence (LCS) based approach to compute the distance among vector field ensembles. By measuring how many common blocks the ensemble pathlines passing through, the LCS distance defines the similarity among vector field ensembles by counting the number of sharing domain data blocks. Compared to the traditional methods (e.g. point-wise Euclidean distance or dynamic time warping distance), the proposed approach is robust to outlier, data missing, and sampling rate of pathline timestep. Taking the advantages of smaller and reusable intermediate output, visualization based on the proposed LCS approach revealing temporal trends in the data at low storage cost, and avoiding tracing pathlines repeatedly. Finally, we evaluate our method on both synthetic data and simulation data, which demonstrate the robustness of the proposed approach.

  10. Forced recombination of psi-modified murine leukaemia virus-based vectors with murine leukaemia-like and VL30 murine endogenous retroviruses

    DEFF Research Database (Denmark)

    Mikkelsen, J G; Lund, Anders Henrik; Duch, M

    1999-01-01

    Co-encapsidation of retroviral RNAs into virus particles allows for the generation of recombinant proviruses through events of template switching during reverse transcription. By use of a forced recombination system based on recombinational rescue of replication- defective primer binding site-imp....... We note that recombination-based rescue of primer binding site knock-out retroviral vectors may constitute a sensitive assay to register putative genetic interactions involving endogenous retroviral RNAs present in cells of various species.......-impaired Akv-MLV-derived vectors, we here examine putative genetic interactions between vector RNAs and copackaged endogenous retroviral RNAs of the murine leukaemia virus (MLV) and VL30 retroelement families. We show (i) that MLV recombination is not blocked by nonhomology within the 5' untranslated region...... harbouring the supposed RNA dimer-forming cis -elements and (ii) that copackaged retroviral RNAs can recombine despite pronounced sequence dissimilarity at the cross-over site(s) and within parts of the genome involved in RNA dimerization, encapsidation and strand transferring during reverse transcription...

  11. A Prototype SSVEP Based Real Time BCI Gaming System.

    Science.gov (United States)

    Martišius, Ignas; Damaševičius, Robertas

    2016-01-01

    Although brain-computer interface technology is mainly designed with disabled people in mind, it can also be beneficial to healthy subjects, for example, in gaming or virtual reality systems. In this paper we discuss the typical architecture, paradigms, requirements, and limitations of electroencephalogram-based gaming systems. We have developed a prototype three-class brain-computer interface system, based on the steady state visually evoked potentials paradigm and the Emotiv EPOC headset. An online target shooting game, implemented in the OpenViBE environment, has been used for user feedback. The system utilizes wave atom transform for feature extraction, achieving an average accuracy of 78.2% using linear discriminant analysis classifier, 79.3% using support vector machine classifier with a linear kernel, and 80.5% using a support vector machine classifier with a radial basis function kernel.

  12. A Prototype SSVEP Based Real Time BCI Gaming System

    Directory of Open Access Journals (Sweden)

    Ignas Martišius

    2016-01-01

    Full Text Available Although brain-computer interface technology is mainly designed with disabled people in mind, it can also be beneficial to healthy subjects, for example, in gaming or virtual reality systems. In this paper we discuss the typical architecture, paradigms, requirements, and limitations of electroencephalogram-based gaming systems. We have developed a prototype three-class brain-computer interface system, based on the steady state visually evoked potentials paradigm and the Emotiv EPOC headset. An online target shooting game, implemented in the OpenViBE environment, has been used for user feedback. The system utilizes wave atom transform for feature extraction, achieving an average accuracy of 78.2% using linear discriminant analysis classifier, 79.3% using support vector machine classifier with a linear kernel, and 80.5% using a support vector machine classifier with a radial basis function kernel.

  13. Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations

    KAUST Repository

    Smaili, Fatima Z.; Gao, Xin; Hoehndorf, Robert

    2018-01-01

    We propose the Onto2Vec method, an approach to learn feature vectors for biological entities based on their annotations to biomedical ontologies. Our method can be applied to a wide range of bioinformatics research problems such as similarity-based prediction of interactions between proteins, classification of interaction types using supervised learning, or clustering.

  14. Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations

    KAUST Repository

    Smaili, Fatima Zohra

    2018-01-31

    We propose the Onto2Vec method, an approach to learn feature vectors for biological entities based on their annotations to biomedical ontologies. Our method can be applied to a wide range of bioinformatics research problems such as similarity-based prediction of interactions between proteins, classification of interaction types using supervised learning, or clustering.

  15. UDE-based control of variable-speed wind turbine systems

    Science.gov (United States)

    Ren, Beibei; Wang, Yeqin; Zhong, Qing-Chang

    2017-01-01

    In this paper, the control of a PMSG (permanent magnet synchronous generator)-based variable-speed wind turbine system with a back-to-back converter is considered. The uncertainty and disturbance estimator (UDE)-based control approach is applied to the regulation of the DC-link voltage and the control of the RSC (rotor-side converter) and the GSC (grid-side converter). For the rotor-side controller, the UDE-based vector control is developed for the RSC with PMSG control to facilitate the application of the MPPT (maximum power point tracking) algorithm for the maximum wind energy capture. For the grid-side controller, the UDE-based vector control is developed to control the GSC with the power reference generated by a UDE-based DC-link voltage controller. Compared with the conventional vector control, the UDE-based vector control can achieve reliable current decoupling control with fast response. Moreover, the UDE-based DC-link voltage regulation can achieve stable DC-link voltage under model uncertainties and external disturbances, e.g. wind speed variations. The effectiveness of the proposed UDE-based control approach is demonstrated through extensive simulation studies in the presence of coupled dynamics, model uncertainties and external disturbances under varying wind speeds. The UDE-based control is able to generate more energy, e.g. by 5% for the wind profile tested.

  16. Gateway-compatible vectors for high-throughput protein expression in pro- and eukaryotic cell-free systems.

    Science.gov (United States)

    Gagoski, Dejan; Mureev, Sergey; Giles, Nichole; Johnston, Wayne; Dahmer-Heath, Mareike; Škalamera, Dubravka; Gonda, Thomas J; Alexandrov, Kirill

    2015-02-10

    Although numerous techniques for protein expression and production are available the pace of genome sequencing outstrips our ability to analyze the encoded proteins. To address this bottleneck, we have established a system for parallelized cloning, DNA production and cell-free expression of large numbers of proteins. This system is based on a suite of pCellFree Gateway destination vectors that utilize a Species Independent Translation Initiation Sequence (SITS) that mediates recombinant protein expression in any in vitro translation system. These vectors introduce C or N terminal EGFP and mCherry fluorescent and affinity tags, enabling direct analysis and purification of the expressed proteins. To maximize throughput and minimize the cost of protein production we combined Gateway cloning with Rolling Circle DNA Amplification. We demonstrate that as little as 0.1 ng of plasmid DNA is sufficient for template amplification and production of recombinant human protein in Leishmania tarentolae and Escherichia coli cell-free expression systems. Our experiments indicate that this approach can be applied to large gene libraries as it can be reliably performed in multi-well plates. The resulting protein expression pipeline provides a valuable new tool for applications of the post genomic era. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. Novel strategy for generation and titration of recombinant adeno-associated virus vectors.

    Science.gov (United States)

    Shiau, Ai-Li; Liu, Pu-Ste; Wu, Chao-Liang

    2005-01-01

    Recombinant adeno-associated virus (rAAV) vectors have many advantages for gene therapeutic applications compared with other vector systems. Several methods that use plasmids or helper viruses have been reported for the generation of rAAV vectors. Unfortunately, the preparation of large-scale rAAV stocks is labor-intensive. Moreover, the biological titration of rAAV is still difficult, which may limit its preclinical and clinical applications. For this study, we developed a novel strategy to generate and biologically titrate rAAV vectors. A recombinant pseudorabies virus (PrV) with defects in its gD, gE, and thymidine kinase genes was engineered to express the AAV rep and cap genes, yielding PS virus, which served as a packaging and helper virus for the generation of rAAV vectors. PS virus was useful not only for generating high-titer rAAV vectors by cotransfection with an rAAV vector plasmid, but also for amplifying rAAV stocks. Notably, the biological titration of rAAV vectors was also feasible when cells were coinfected with rAAV and PS virus. Based on this strategy, we produced an rAAV that expresses prothymosin alpha (ProT). Expression of the ProT protein in vitro and in vivo mediated by rAAV/ProT gene transfer was detected by immunohistochemistry and a bioassay. Taken together, our results demonstrate that the PrV vector-based system is useful for generating rAAV vectors carrying various transgenes.

  18. Vector grammars and PN machines

    Institute of Scientific and Technical Information of China (English)

    蒋昌俊

    1996-01-01

    The concept of vector grammars under the string semantic is introduced.The dass of vector grammars is given,which is similar to the dass of Chomsky grammars.The regular vector grammar is divided further.The strong and weak relation between the vector grammar and scalar grammar is discussed,so the spectrum system graph of scalar and vector grammars is made.The equivalent relation between the regular vector grammar and Petri nets (also called PN machine) is pointed.The hybrid PN machine is introduced,and its language is proved equivalent to the language of the context-free vector grammar.So the perfect relation structure between vector grammars and PN machines is formed.

  19. A Novel Rotor and Stator Magnetic Fields Direct-Orthogonalized Vector Control Scheme for the PMSM Servo System

    Directory of Open Access Journals (Sweden)

    Shi-Xiong Zhang

    2014-02-01

    Full Text Available Permanent Magnet Synchronous motor (PMSM has received widespread acceptance in recent years. In this paper, a new rotor and stator Magnetic Fields Direct-Orthogonalized Vector Control (MFDOVC scheme is proposed for PMSM servo system. This method simplified the complex calculation of traditional vector control, a part of the system resource is economized. At the same time, through the simulation illustration validation, the performance of PMSM servo system with the proposed MFDOVC scheme can achieve the same with the complex traditional vector control method, but much simpler calculation is implemented using the proposed method.

  20. Support-Vector-based Least Squares for learning non-linear dynamics

    NARCIS (Netherlands)

    de Kruif, B.J.; de Vries, Theodorus J.A.

    2002-01-01

    A function approximator is introduced that is based on least squares support vector machines (LSSVM) and on least squares (LS). The potential indicators for the LS method are chosen as the kernel functions of all the training samples similar to LSSVM. By selecting these as indicator functions the

  1. Inadvertent gene silencing of argininosuccinate synthase (bcass1) in Botrytis cinerea by the pLOB1 vector system

    NARCIS (Netherlands)

    Patel, R.M.; Kan, van J.A.L.; Bailey, A.M.; Foster, G.D.

    2010-01-01

    For several years, researchers working on the plant pathogen Botrytis cinerea and a number of other related fungi have routinely used the pLOB1 vector system, based on hygromycin resistance, under the control of the Aspergillus nidulans oliC promoter and what was reported to be the ß-tubulin (tubA)

  2. A Modified Recession Vector Method Based on the Optimization-Simulation Approach to Design Problems of Information Security Systems

    Directory of Open Access Journals (Sweden)

    A. Yu. Bykov

    2015-01-01

    Full Text Available Modern practical task-solving techniques for designing information security systems in different purpose automated systems assume the solution of optimization tasks when choosing different elements of a security system. Formulations of mathematical programming tasks are rather often used, but in practical tasks it is not always analytically possible to set target function and (or restrictions in an explicit form. Sometimes, calculation of the target function value or checking of restrictions for the possible decision can be reduced to carrying out experiments on a simulation model of system. Similar tasks are considered within optimization-simulation approach and require the ad hoc methods of optimization considering the possible high computational effort of simulation.The article offers a modified recession vector method, which is used in tasks of discrete optimization to solve the similar problems. The method is applied when the task to be solved is to minimize the cost of selected information security tools in case of restriction on the maximum possible damage. The cost index is the linear function of the Boolean variables, which specify the selected security tools, with the restriction set as an "example simulator". Restrictions can be actually set implicitly. A validity of the possible solution is checked using a simulation model of the system.The offered algorithm of a method considers features of an objective. The main advantage of algorithm is that it requires a maximum of m+1 of steps where m is a dimensionality of the required vector of Boolean variables. The algorithm provides finding a local minimum by using the Hamming metrics in the discrete space; the radius of neighborhood is equal to 1. These statements are proved.The paper presents solution results of choosing security tools with the specified basic data.

  3. Gene Therapy Vectors with Enhanced Transfection Based on Hydrogels Modified with Affinity Peptides

    Science.gov (United States)

    Shepard, Jaclyn A.; Wesson, Paul J.; Wang, Christine E.; Stevans, Alyson C.; Holland, Samantha J.; Shikanov, Ariella; Grzybowski, Bartosz A.; Shea, Lonnie D.

    2011-01-01

    Regenerative strategies for damaged tissue aim to present biochemical cues that recruit and direct progenitor cell migration and differentiation. Hydrogels capable of localized gene delivery are being developed to provide a support for tissue growth, and as a versatile method to induce the expression of inductive proteins; however, the duration, level, and localization of expression isoften insufficient for regeneration. We thus investigated the modification of hydrogels with affinity peptides to enhance vector retention and increase transfection within the matrix. PEG hydrogels were modified with lysine-based repeats (K4, K8), which retained approximately 25% more vector than control peptides. Transfection increased 5- to 15-fold with K8 and K4 respectively, over the RDG control peptide. K8- and K4-modified hydrogels bound similar quantities of vector, yet the vector dissociation rate was reduced for K8, suggesting excessive binding that limited transfection. These hydrogels were subsequently applied to an in vitro co-culture model to induce NGF expression and promote neurite outgrowth. K4-modified hydrogels promoted maximal neurite outgrowth, likely due to retention of both the vector and the NGF. Thus, hydrogels modified with affinity peptides enhanced vector retention and increased gene delivery, and these hydrogels may provide a versatile scaffold for numerous regenerative medicine applications. PMID:21514659

  4. Predictions of malaria vector distribution in Belize based on multispectral satellite data.

    Science.gov (United States)

    Roberts, D R; Paris, J F; Manguin, S; Harbach, R E; Woodruff, R; Rejmankova, E; Polanco, J; Wullschleger, B; Legters, L J

    1996-03-01

    Use of multispectral satellite data to predict arthropod-borne disease trouble spots is dependent on clear understandings of environmental factors that determine the presence of disease vectors. A blind test of remote sensing-based predictions for the spatial distribution of a malaria vector, Anopheles pseudopunctipennis, was conducted as a follow-up to two years of studies on vector-environmental relationships in Belize. Four of eight sites that were predicted to be high probability locations for presence of An. pseudopunctipennis were positive and all low probability sites (0 of 12) were negative. The absence of An. pseudopunctipennis at four high probability locations probably reflects the low densities that seem to characterize field populations of this species, i.e., the population densities were below the threshold of our sampling effort. Another important malaria vector, An. darlingi, was also present at all high probability sites and absent at all low probability sites. Anopheles darlingi, like An. pseudopunctipennis, is a riverine species. Prior to these collections at ecologically defined locations, this species was last detected in Belize in 1946.

  5. Entropy-Based Video Steganalysis of Motion Vectors

    Directory of Open Access Journals (Sweden)

    Elaheh Sadat Sadat

    2018-04-01

    Full Text Available In this paper, a new method is proposed for motion vector steganalysis using the entropy value and its combination with the features of the optimized motion vector. In this method, the entropy of blocks is calculated to determine their texture and the precision of their motion vectors. Then, by using a fuzzy cluster, the blocks are clustered into the blocks with high and low texture, while the membership function of each block to a high texture class indicates the texture of that block. These membership functions are used to weight the effective features that are extracted by reconstructing the motion estimation equations. Characteristics of the results indicate that the use of entropy and the irregularity of each block increases the precision of the final video classification into cover and stego classes.

  6. Real Time Monitoring System of Pollution Waste on Musi River Using Support Vector Machine (SVM) Method

    Science.gov (United States)

    Fachrurrozi, Muhammad; Saparudin; Erwin

    2017-04-01

    Real-time Monitoring and early detection system which measures the quality standard of waste in Musi River, Palembang, Indonesia is a system for determining air and water pollution level. This system was designed in order to create an integrated monitoring system and provide real time information that can be read. It is designed to measure acidity and water turbidity polluted by industrial waste, as well as to show and provide conditional data integrated in one system. This system consists of inputting and processing the data, and giving output based on processed data. Turbidity, substances, and pH sensor is used as a detector that produce analog electrical direct current voltage (DC). Early detection system works by determining the value of the ammonia threshold, acidity, and turbidity level of water in Musi River. The results is then presented based on the level group pollution by the Support Vector Machine classification method.

  7. Vector 33: A reduce program for vector algebra and calculus in orthogonal curvilinear coordinates

    Science.gov (United States)

    Harper, David

    1989-06-01

    This paper describes a package with enables REDUCE 3.3 to perform algebra and calculus operations upon vectors. Basic algebraic operations between vectors and between scalars and vectors are provided, including scalar (dot) product and vector (cross) product. The vector differential operators curl, divergence, gradient and Laplacian are also defined, and are valid in any orthogonal curvilinear coordinate system. The package is written in RLISP to allow algebra and calculus to be performed using notation identical to that for operations. Scalars and vectors can be mixed quite freely in the same expression. The package will be of interest to mathematicians, engineers and scientists who need to perform vector calculations in orthogonal curvilinear coordinates.

  8. Slope Deformation Prediction Based on Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Lei JIA

    2013-07-01

    Full Text Available This paper principally studies the prediction of slope deformation based on Support Vector Machine (SVM. In the prediction process,explore how to reconstruct the phase space. The geological body’s displacement data obtained from chaotic time series are used as SVM’s training samples. Slope displacement caused by multivariable coupling is predicted by means of single variable. Results show that this model is of high fitting accuracy and generalization, and provides reference for deformation prediction in slope engineering.

  9. Engineered XcmI cassette-containing vector for PCR-based ...

    Indian Academy of Sciences (India)

    Unknown

    A simple and general method is described to construct a new vector bearing a synthetic XcmI cassette for direct cloning of PCR-amplified genes of interest. Cleavage of the vector with XcmI generates a linearized molecule with a single thymidine (T) overhang at the 3′ ends (T-vector) that facilitates TA cloning of PCR ...

  10. Cognitive Development Optimization Algorithm Based Support Vector Machines for Determining Diabetes

    Directory of Open Access Journals (Sweden)

    Utku Kose

    2016-03-01

    Full Text Available The definition, diagnosis and classification of Diabetes Mellitus and its complications are very important. First of all, the World Health Organization (WHO and other societies, as well as scientists have done lots of studies regarding this subject. One of the most important research interests of this subject is the computer supported decision systems for diagnosing diabetes. In such systems, Artificial Intelligence techniques are often used for several disease diagnostics to streamline the diagnostic process in daily routine and avoid misdiagnosis. In this study, a diabetes diagnosis system, which is formed via both Support Vector Machines (SVM and Cognitive Development Optimization Algorithm (CoDOA has been proposed. Along the training of SVM, CoDOA was used for determining the sigma parameter of the Gauss (RBF kernel function, and eventually, a classification process was made over the diabetes data set, which is related to Pima Indians. The proposed approach offers an alternative solution to the field of Artificial Intelligence-based diabetes diagnosis, and contributes to the related literature on diagnosis processes.

  11. An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

    Science.gov (United States)

    Luo, Liyan; Xu, Luping; Zhang, Hua

    2015-07-07

    In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.

  12. Indonesian Stock Prediction using Support Vector Machine (SVM

    Directory of Open Access Journals (Sweden)

    Santoso Murtiyanto

    2018-01-01

    Full Text Available This project is part of developing software to provide predictive information technology-based services artificial intelligence (Machine Intelligence or Machine Learning that will be utilized in the money market community. The prediction method used in this early stages uses the combination of Gaussian Mixture Model and Support Vector Machine with Python programming. The system predicts the price of Astra International (stock code: ASII.JK stock data. The data used was taken during 17 yr period of January 2000 until September 2017. Some data was used for training/modeling (80 % of data and the remainder (20 % was used for testing. An integrated model comprising Gaussian Mixture Model and Support Vector Machine system has been tested to predict stock market of ASII.JK for l d in advance. This model has been compared with the Market Cummulative Return. From the results, it is depicts that the Gaussian Mixture Model-Support Vector Machine based stock predicted model, offers significant improvement over the compared models resulting sharpe ratio of 3.22.

  13. Generalization of concurrence vectors

    International Nuclear Information System (INIS)

    Yu Changshui; Song Heshan

    2004-01-01

    In this Letter, based on the generalization of concurrence vectors for bipartite pure state with respect to employing tensor product of generators of the corresponding rotation groups, we generalize concurrence vectors to the case of mixed states; a new criterion of separability of multipartite pure states is given out, for which we define a concurrence vector; we generalize the vector to the case of multipartite mixed state and give out a good measure of free entanglement

  14. Elliptic-symmetry vector optical fields.

    Science.gov (United States)

    Pan, Yue; Li, Yongnan; Li, Si-Min; Ren, Zhi-Cheng; Kong, Ling-Jun; Tu, Chenghou; Wang, Hui-Tian

    2014-08-11

    We present in principle and demonstrate experimentally a new kind of vector fields: elliptic-symmetry vector optical fields. This is a significant development in vector fields, as this breaks the cylindrical symmetry and enriches the family of vector fields. Due to the presence of an additional degrees of freedom, which is the interval between the foci in the elliptic coordinate system, the elliptic-symmetry vector fields are more flexible than the cylindrical vector fields for controlling the spatial structure of polarization and for engineering the focusing fields. The elliptic-symmetry vector fields can find many specific applications from optical trapping to optical machining and so on.

  15. Modulation transfer function (MTF) measurement method based on support vector machine (SVM)

    Science.gov (United States)

    Zhang, Zheng; Chen, Yueting; Feng, Huajun; Xu, Zhihai; Li, Qi

    2016-03-01

    An imaging system's spatial quality can be expressed by the system's modulation spread function (MTF) as a function of spatial frequency in terms of the linear response theory. Methods have been proposed to assess the MTF of an imaging system using point, slit or edge techniques. The edge method is widely used for the low requirement of targets. However, the traditional edge methods are limited by the edge angle. Besides, image noise will impair the measurement accuracy, making the measurement result unstable. In this paper, a novel measurement method based on the support vector machine (SVM) is proposed. Image patches with different edge angles and MTF levels are generated as the training set. Parameters related with MTF and image structure are extracted from the edge images. Trained with image parameters and the corresponding MTF, the SVM classifier can assess the MTF of any edge image. The result shows that the proposed method has an excellent performance on measuring accuracy and stability.

  16. Viral Hybrid Vectors for Somatic Integration - Are They the Better Solution?

    Directory of Open Access Journals (Sweden)

    Anja Ehrhardt

    2009-12-01

    Full Text Available The turbulent history of clinical trials in viral gene therapy has taught us important lessons about vector design and safety issues. Much effort was spent on analyzing genotoxicity after somatic integration of therapeutic DNA into the host genome. Based on these findings major improvements in vector design including the development of viral hybrid vectors for somatic integration have been achieved. This review provides a state-of-the-art overview of available hybrid vectors utilizing viruses for high transduction efficiencies in concert with various integration machineries for random and targeted integration patterns. It discusses advantages but also limitations of each vector system.

  17. Multi-disease data management system platform for vector-borne diseases.

    Directory of Open Access Journals (Sweden)

    Lars Eisen

    2011-03-01

    Full Text Available Emerging information technologies present new opportunities to reduce the burden of malaria, dengue and other infectious diseases. For example, use of a data management system software package can help disease control programs to better manage and analyze their data, and thus enhances their ability to carry out continuous surveillance, monitor interventions and evaluate control program performance.We describe a novel multi-disease data management system platform (hereinafter referred to as the system with current capacity for dengue and malaria that supports data entry, storage and query. It also allows for production of maps and both standardized and customized reports. The system is comprised exclusively of software components that can be distributed without the user incurring licensing costs. It was designed to maximize the ability of the user to adapt the system to local conditions without involvement of software developers. Key points of system adaptability include 1 customizable functionality content by disease, 2 configurable roles and permissions, 3 customizable user interfaces and display labels and 4 configurable information trees including a geographical entity tree and a term tree. The system includes significant portions of functionality that is entirely or in large part re-used across diseases, which provides an economy of scope as new diseases downstream are added to the system at decreased cost.We have developed a system with great potential for aiding disease control programs in their task to reduce the burden of dengue and malaria, including the implementation of integrated vector management programs. Next steps include evaluations of operational implementations of the current system with capacity for dengue and malaria, and the inclusion in the system platform of other important vector-borne diseases.

  18. Models for discrete-time self-similar vector processes with application to network traffic

    Science.gov (United States)

    Lee, Seungsin; Rao, Raghuveer M.; Narasimha, Rajesh

    2003-07-01

    The paper defines self-similarity for vector processes by employing the discrete-time continuous-dilation operation which has successfully been used previously by the authors to define 1-D discrete-time stochastic self-similar processes. To define self-similarity of vector processes, it is required to consider the cross-correlation functions between different 1-D processes as well as the autocorrelation function of each constituent 1-D process in it. System models to synthesize self-similar vector processes are constructed based on the definition. With these systems, it is possible to generate self-similar vector processes from white noise inputs. An important aspect of the proposed models is that they can be used to synthesize various types of self-similar vector processes by choosing proper parameters. Additionally, the paper presents evidence of vector self-similarity in two-channel wireless LAN data and applies the aforementioned systems to simulate the corresponding network traffic traces.

  19. Space vector-based analysis of overmodulation in triangle ...

    Indian Academy of Sciences (India)

    methods such as vector control or field oriented control are used for fast dynamic response .... This average voltage vector falls in sector-I as shown in figure 5 for .... The dwell times T1, T2 and Tz can be derived using volt-second balance.

  20. Two-host, two-vector basic reproduction ratio (R(0 for bluetongue.

    Directory of Open Access Journals (Sweden)

    Joanne Turner

    Full Text Available Mathematical formulations for the basic reproduction ratio (R(0 exist for several vector-borne diseases. Generally, these are based on models of one-host, one-vector systems or two-host, one-vector systems. For many vector borne diseases, however, two or more vector species often co-occur and, therefore, there is a need for more complex formulations. Here we derive a two-host, two-vector formulation for the R(0 of bluetongue, a vector-borne infection of ruminants that can have serious economic consequences; since 1998 for example, it has led to the deaths of well over 1 million sheep in Europe alone. We illustrate our results by considering the situation in South Africa, where there are two major hosts (sheep, cattle and two vector species with differing ecologies and competencies as vectors, for which good data exist. We investigate the effects on R(0 of differences in vector abundance, vector competence and vector host preference between vector species. Our results indicate that R(0 can be underestimated if we assume that there is only one vector transmitting the infection (when there are in fact two or more and/or vector host preferences are overlooked (unless the preferred host is less beneficial or more abundant. The two-host, one-vector formula provides a good approximation when the level of cross-infection between vector species is very small. As this approaches the level of intraspecies infection, a combination of the two-host, one-vector R(0 for each vector species becomes a better estimate. Otherwise, particularly when the level of cross-infection is high, the two-host, two-vector formula is required for accurate estimation of R(0. Our results are equally relevant to Europe, where at least two vector species, which co-occur in parts of the south, have been implicated in the recent epizootic of bluetongue.

  1. A classification system for one Killing vector solutions of Einstein's equations

    International Nuclear Information System (INIS)

    Hoenselaers, C.

    1978-01-01

    A double classification system for one Killing vector solutions in terms of the eigenvectors and eigenvalues of the Ricci and Bach tensor of the associated three manifold is proposed. The calculations of the Bach tensor are carried out for special cases. (author)

  2. ON THE ISSUE OF VECTOR CONTROL OF THE ASYNCHRONOUS MOTORS

    Directory of Open Access Journals (Sweden)

    B. I. Firago

    2015-01-01

    Full Text Available The paper considers the issue of one of the widespread types of vector control realization for the asynchronous motors with a short-circuited rotor. Of all more than 20 vector control types known presently, the following are applied most frequently: direct vector control with velocity pickup (VP, direct vector control without VP, indirect vector control with VP and indirect vector control without VP. Despite the fact that the asynchronous-motor indirect vector control without VP is the easiest and most spread, the absence of VP does not allow controlling the motor electromagnetic torque at zero velocity. This is the reason why for electric motor drives of such requirements they utilize the vector control with a velocity transducer. The systems of widest dissemination became the direct and indirect vector control systems with X-axis alignment of the synchronously rotating x–y-coordinate frame along the rotor flux-linkage vector inasmuch as this provides the simplest correlations for controlling variables. Although these two types of vector control are well presented in literature, a number of issues concerning their realization and practical application require further elaboration. These include: the block schemes adequate representation as consisted with the modern realization of vector control and clarification of the analytical expressions for evaluating the regulator parameters.The authors present a technique for evaluating the dynamics of an asynchronous electric motor drive with direct vector control and x-axis alignment along the vector of rotor flux linkage. The article offers a generalized structure of this vector control type with detailed description of its principal blocks: controlling system, frequency converter, and the asynchronous motor.The paper presents a direct vector control simulating model developed in the MatLab environment on the grounds of this structure. The authors illustrate the described technique with the results

  3. Hybrid Lentivirus-transposon Vectors With a Random Integration Profile in Human Cells

    DEFF Research Database (Denmark)

    Staunstrup, Nicklas H; Moldt, Brian; Mátés, Lajos

    2009-01-01

    Gene delivery by human immunodeficiency virus type 1 (HIV-1)-based lentiviral vectors (LVs) is efficient, but genomic integration of the viral DNA is strongly biased toward transcriptionally active loci resulting in an increased risk of insertional mutagenesis in gene therapy protocols. Nonviral...... Sleeping Beauty (SB) transposon vectors have a significantly safer insertion profile, but efficient delivery into relevant cell/tissue types is a limitation. In an attempt to combine the favorable features of the two vector systems we established a novel hybrid vector technology based on SB transposase......-mediated insertion of lentiviral DNA circles generated during transduction of target cells with integrase (IN)-defective LVs (IDLVs). By construction of a lentivirus-transposon hybrid vector allowing transposition exclusively from circular viral DNA substrates, we demonstrate that SB transposase added in trans...

  4. Ultrasound Vector Flow Imaging: Part I: Sequential Systems

    DEFF Research Database (Denmark)

    Jensen, Jørgen Arendt; Nikolov, Svetoslav Ivanov; Yu, Alfred C. H.

    2016-01-01

    , and variants of these. The review covers both 2-D and 3-D velocity estimation and gives a historical perspective on the development along with a summary of various vector flow visualization algorithms. The current state-of-the-art is explained along with an overview of clinical studies conducted and methods......The paper gives a review of the most important methods for blood velocity vector flow imaging (VFI) for conventional, sequential data acquisition. This includes multibeam methods, speckle tracking, transverse oscillation, color flow mapping derived vector flow imaging, directional beamforming...

  5. Vehicle Based Vector Sensor

    Science.gov (United States)

    2015-09-28

    buoyant underwater vehicle with an interior space in which a length of said underwater vehicle is equal to one tenth of the acoustic wavelength...underwater vehicle with an interior space in which a length of said underwater vehicle is equal to one tenth of the acoustic wavelength; an...unmanned underwater vehicle that can function as an acoustic vector sensor. (2) Description of the Prior Art [0004] It is known that a propagating

  6. Phase transitions in vector quantization and neural gas

    NARCIS (Netherlands)

    Witoelar, Aree; Biehl, Michael

    The statistical physics of off-learning is applied to winner-takes-all (WTA) and rank-based vector quantization (VQ), including the neural gas (NG). The analysis is based on the limit of high training temperatures and the annealed approximation. The typical learning behavior is evaluated for systems

  7. Quantum nonlinear lattices and coherent state vectors

    DEFF Research Database (Denmark)

    Ellinas, Demosthenes; Johansson, M.; Christiansen, Peter Leth

    1999-01-01

    for the state vectors invokes the study of the Riemannian and symplectic geometry of the CSV manifolds as generalized phase spaces. Next, we investigate analytically and numerically the behavior of mean values and uncertainties of some physically interesting observables as well as the modifications...... (FP) model. Based on the respective dynamical symmetries of the models, a method is put forward which by use of the associated boson and spin coherent state vectors (CSV) and a factorization ansatz for the solution of the Schrodinger equation, leads to quasiclassical Hamiltonian equations of motion...... state vectors, and accounts for the quantum correlations of the lattice sites that develop during the time evolution of the systems. (C) 1999 Elsevier Science B.V. All rights reserved....

  8. Medical image compression based on vector quantization with variable block sizes in wavelet domain.

    Science.gov (United States)

    Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

    2012-01-01

    An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality.

  9. Multigenic lentiviral vectors for combined and tissue-specific expression of miRNA- and protein-based antiangiogenic factors

    Directory of Open Access Journals (Sweden)

    Anne Louise Askou

    Full Text Available Lentivirus-based gene delivery vectors carrying multiple gene cassettes are powerful tools in gene transfer studies and gene therapy, allowing coexpression of multiple therapeutic factors and, if desired, fluorescent reporters. Current strategies to express transgenes and microRNA (miRNA clusters from a single vector have certain limitations that affect transgene expression levels and/or vector titers. In this study, we describe a novel vector design that facilitates combined expression of therapeutic RNA- and protein-based antiangiogenic factors as well as a fluorescent reporter from back-to-back RNApolII-driven expression cassettes. This configuration allows effective production of intron-embedded miRNAs that are released upon transduction of target cells. Exploiting such multigenic lentiviral vectors, we demonstrate robust miRNA-directed downregulation of vascular endothelial growth factor (VEGF expression, leading to reduced angiogenesis, and parallel impairment of angiogenic pathways by codelivering the gene encoding pigment epithelium-derived factor (PEDF. Notably, subretinal injections of lentiviral vectors reveal efficient retinal pigment epithelium-specific gene expression driven by the VMD2 promoter, verifying that multigenic lentiviral vectors can be produced with high titers sufficient for in vivo applications. Altogether, our results suggest the potential applicability of combined miRNA- and protein-encoding lentiviral vectors in antiangiogenic gene therapy, including new combination therapies for amelioration of age-related macular degeneration.

  10. Violation of vector dominance in the vector manifestation

    International Nuclear Information System (INIS)

    Sasaki, Chihiro

    2003-01-01

    The vector manifestation (VM) is a new pattern for realizing the chiral symmetry in QCD. In the VM, the massless vector meson becomes the chiral partner of pion at the critical point, in contrast with the restoration based on the linear sigma model. Including the intrinsic temperature dependences of the parameters of the hidden local symmetry (HLS) Lagrangian determined from the underlying QCD through the Wilsonian matching together with the hadronic thermal corrections, we present a new prediction of the VM on the direct photon-π-π coupling which measures the validity of the vector dominance (VD) of the electromagnetic form factor of the pion. We find that the VD is largely violated at the critical temperature, which indicates that the assumption of the VD made in several analysis on the dilepton spectra in hot matter may need to be weakened for consistently including the effect of the dropping mass of the vector meson. (author)

  11. A Bayesian least squares support vector machines based framework for fault diagnosis and failure prognosis

    Science.gov (United States)

    Khawaja, Taimoor Saleem

    A high-belief low-overhead Prognostics and Health Management (PHM) system is desired for online real-time monitoring of complex non-linear systems operating in a complex (possibly non-Gaussian) noise environment. This thesis presents a Bayesian Least Squares Support Vector Machine (LS-SVM) based framework for fault diagnosis and failure prognosis in nonlinear non-Gaussian systems. The methodology assumes the availability of real-time process measurements, definition of a set of fault indicators and the existence of empirical knowledge (or historical data) to characterize both nominal and abnormal operating conditions. An efficient yet powerful Least Squares Support Vector Machine (LS-SVM) algorithm, set within a Bayesian Inference framework, not only allows for the development of real-time algorithms for diagnosis and prognosis but also provides a solid theoretical framework to address key concepts related to classification for diagnosis and regression modeling for prognosis. SVM machines are founded on the principle of Structural Risk Minimization (SRM) which tends to find a good trade-off between low empirical risk and small capacity. The key features in SVM are the use of non-linear kernels, the absence of local minima, the sparseness of the solution and the capacity control obtained by optimizing the margin. The Bayesian Inference framework linked with LS-SVMs allows a probabilistic interpretation of the results for diagnosis and prognosis. Additional levels of inference provide the much coveted features of adaptability and tunability of the modeling parameters. The two main modules considered in this research are fault diagnosis and failure prognosis. With the goal of designing an efficient and reliable fault diagnosis scheme, a novel Anomaly Detector is suggested based on the LS-SVM machines. The proposed scheme uses only baseline data to construct a 1-class LS-SVM machine which, when presented with online data is able to distinguish between normal behavior

  12. A Systematic Approach for Solving the Great Circle Track Problems based on Vector Algebra

    Directory of Open Access Journals (Sweden)

    Chen Chih-Li

    2016-04-01

    Full Text Available A systematic approach, based on multiple products of the vector algebra (S-VA, is proposed to derive the spherical triangle formulae for solving the great circle track (GCT problems. Because the mathematical properties of the geometry and algebra are both embedded in the S-VA approach, derivations of the spherical triangle formulae become more understandable and more straightforward as compared with those approaches which use the complex linear combination of a vector basis. In addition, the S-VA approach can handle all given initial conditions for solving the GCT problems simpler, clearer and avoid redundant formulae existing in the conventional approaches. With the technique of transforming the Earth coordinates system of latitudes and longitudes into the Cartesian one and adopting the relative longitude concept, the concise governing equations of the S-VA approach can be easily and directly derived. Owing to the advantage of the S-VA approach, it makes the practical navigator quickly adjust to solve the GCT problems. Based on the S-VA approach, a program namely GCTPro_VA is developed for friendly use of the navigator. Several validation examples are provided to show the S-VA approach is simple and versatile to solve the GCT problems.

  13. Plasmid Vectors for Xylella fastidiosa Utilizing a Toxin-Antitoxin System for Stability in the Absence of Antibiotic Selection.

    Science.gov (United States)

    Burbank, Lindsey P; Stenger, Drake C

    2016-08-01

    The phytopathogen Xylella fastidiosa causes disease in a variety of important crop and landscape plants. Functional genetic studies have led to a broader understanding of virulence mechanisms used by this pathogen in the grapevine host. Plasmid shuttle vectors are important tools in studies of bacterial genetics but there are only a limited number of plasmid vectors available that replicate in X. fastidiosa, and even fewer that are retained without antibiotic selection. Two plasmids are described here that show stable replication in X. fastidiosa and are effective for gene complementation both in vitro and in planta. Plasmid maintenance is facilitated by incorporation of the PemI/PemK plasmid addiction system, consisting of PemK, an endoribonuclease toxin, and its cognate antitoxin, PemI. Vector pXf20pemIK utilizes a native X. fastidiosa replication origin as well as a high-copy-number pUC origin for propagation in Escherichia coli cloning strains. Broad-host-range vector pBBR5pemIK is a medium- to low-copy-number plasmid based on the pBBR1 backbone. Both plasmids are maintained for extended periods of time in the absence of antibiotic selection, as well as up to 14 weeks in grapevine, without affecting bacterial fitness. These plasmids present an alternative to traditional complementation and expression vectors which rely on antibiotic selection for plasmid retention.

  14. Tag and Neighbor based Recommender systems for Medical events

    DEFF Research Database (Denmark)

    Bayyapu, Karunakar Reddy; Dolog, Peter

    2010-01-01

    This paper presents an extension of a multifactor recommendation approach based on user tagging with term neighbours. Neighbours of words in tag vectors and documents provide for hitting larger set of documents and not only those matching with direct tag vectors or content of the documents. Tag...... in the situations where the quality of tags is lower. We discuss the approach on the examples from the existing Medworm system to indicate the usefulness of the approach....

  15. Energy Based Clutter Filtering for Vector Flow Imaging

    DEFF Research Database (Denmark)

    Villagómez Hoyos, Carlos Armando; Jensen, Jonas; Ewertsen, Caroline

    2017-01-01

    for obtaining vector flow measurements, since the spectra overlaps at high beam-to-flow angles. In this work a distinct approach is proposed, where the energy of the velocity spectrum is used to differentiate among the two signals. The energy based method is applied by limiting the amplitude of the velocity...... spectrum function to a predetermined threshold. The effect of the clutter filtering is evaluated on a plane wave (PW) scan sequence in combination with transverse oscillation (TO) and directional beamforming (DB) for velocity estimation. The performance of the filter is assessed by comparison...

  16. Recent Advances in Non-viral Vectors for Gene Delivery

    Science.gov (United States)

    Guo, Xia; Huang, Leaf

    2011-01-01

    CONSPECTUS Non-viral vectors, typically based on cationic lipids or polymers, are preferred due to safety concerns with viral vectors. So far, non-viral vectors can proficiently transfect cells in culture, but obtaining efficient nanomedicines is far from evident. To overcome the hurdles associated with non-viral vectors is significant for improving delivery efficiency and therapeutic effect of nucleic acid. The drawbacks include the strong interaction of cationic delivery vehicles with blood components, uptake by the reticuloendothelial system (RES), toxicity, targeting ability of the carriers to the cells of interest, and so on. PEGylation is the predominant method used to reduce the binding of plasma proteins with non-viral vectors and minimize the clearance by RES after intravenous administration. The nanoparticles that are not rapidly cleared from the circulation accumulate in the tumors due to the enhanced permeability and retention effect, and the targeting ligands attached to the distal end of the PEGylated components allow binding to the receptors on the target cell surface. Neutral or anionic liposomes have been also developed for systemic delivery of nucleic acids in experimental animal model. Designing and synthesizing novel cationic lipids and polymers, and binding nucleic acid with peptides, targeting ligands, polymers, or environmentally sensitive moieties also attract many attentions for resolving the problems encountered by non-viral vectors. The application of inorganic nanoparticles in nucleic acid delivery is an emerging field, too. Recently, different classes of non-viral vectors appear to be converging and the features of different classes of non-viral vectors could be combined in one strategy. More hurdles associated with efficient nucleic acid delivery therefore might be expected to be overcome. In this account, we will focus on these novel non-viral vectors, which are classified into multifunctional hybrid nucleic acid vectors, novel

  17. a Method for the Seamlines Network Automatic Selection Based on Building Vector

    Science.gov (United States)

    Li, P.; Dong, Y.; Hu, Y.; Li, X.; Tan, P.

    2018-04-01

    In order to improve the efficiency of large scale orthophoto production of city, this paper presents a method for automatic selection of seamlines network in large scale orthophoto based on the buildings' vector. Firstly, a simple model of the building is built by combining building's vector, height and DEM, and the imaging area of the building on single DOM is obtained. Then, the initial Voronoi network of the measurement area is automatically generated based on the positions of the bottom of all images. Finally, the final seamlines network is obtained by optimizing all nodes and seamlines in the network automatically based on the imaging areas of the buildings. The experimental results show that the proposed method can not only get around the building seamlines network quickly, but also remain the Voronoi network' characteristics of projection distortion minimum theory, which can solve the problem of automatic selection of orthophoto seamlines network in image mosaicking effectively.

  18. A Biometric Face Recognition System Using an Algorithm Based on the Principal Component Analysis Technique

    Directory of Open Access Journals (Sweden)

    Gheorghe Gîlcă

    2015-06-01

    Full Text Available This article deals with a recognition system using an algorithm based on the Principal Component Analysis (PCA technique. The recognition system consists only of a PC and an integrated video camera. The algorithm is developed in MATLAB language and calculates the eigenfaces considered as features of the face. The PCA technique is based on the matching between the facial test image and the training prototype vectors. The mathcing score between the facial test image and the training prototype vectors is calculated between their coefficient vectors. If the matching is high, we have the best recognition. The results of the algorithm based on the PCA technique are very good, even if the person looks from one side at the video camera.

  19. Ultrasonic fluid quantity measurement in dynamic vehicular applications a support vector machine approach

    CERN Document Server

    Terzic, Jenny; Nagarajah, Romesh; Alamgir, Muhammad

    2013-01-01

    Accurate fluid level measurement in dynamic environments can be assessed using a Support Vector Machine (SVM) approach. SVM is a supervised learning model that analyzes and recognizes patterns. It is a signal classification technique which has far greater accuracy than conventional signal averaging methods. Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications: A Support Vector Machine Approach describes the research and development of a fluid level measurement system for dynamic environments. The measurement system is based on a single ultrasonic sensor. A Support Vector Machines (SVM) based signal characterization and processing system has been developed to compensate for the effects of slosh and temperature variation in fluid level measurement systems used in dynamic environments including automotive applications. It has been demonstrated that a simple ν-SVM model with Radial Basis Function (RBF) Kernel with the inclusion of a Moving Median filter could be used to achieve the high levels...

  20. The Short-Term Power Load Forecasting Based on Sperm Whale Algorithm and Wavelet Least Square Support Vector Machine with DWT-IR for Feature Selection

    Directory of Open Access Journals (Sweden)

    Jin-peng Liu

    2017-07-01

    Full Text Available Short-term power load forecasting is an important basis for the operation of integrated energy system, and the accuracy of load forecasting directly affects the economy of system operation. To improve the forecasting accuracy, this paper proposes a load forecasting system based on wavelet least square support vector machine and sperm whale algorithm. Firstly, the methods of discrete wavelet transform and inconsistency rate model (DWT-IR are used to select the optimal features, which aims to reduce the redundancy of input vectors. Secondly, the kernel function of least square support vector machine LSSVM is replaced by wavelet kernel function for improving the nonlinear mapping ability of LSSVM. Lastly, the parameters of W-LSSVM are optimized by sperm whale algorithm, and the short-term load forecasting method of W-LSSVM-SWA is established. Additionally, the example verification results show that the proposed model outperforms other alternative methods and has a strong effectiveness and feasibility in short-term power load forecasting.

  1. Learn the Lagrangian: A Vector-Valued RKHS Approach to Identifying Lagrangian Systems.

    Science.gov (United States)

    Cheng, Ching-An; Huang, Han-Pang

    2016-12-01

    We study the modeling of Lagrangian systems with multiple degrees of freedom. Based on system dynamics, canonical parametric models require ad hoc derivations and sometimes simplification for a computable solution; on the other hand, due to the lack of prior knowledge in the system's structure, modern nonparametric models in machine learning face the curse of dimensionality, especially in learning large systems. In this paper, we bridge this gap by unifying the theories of Lagrangian systems and vector-valued reproducing kernel Hilbert space. We reformulate Lagrangian systems with kernels that embed the governing Euler-Lagrange equation-the Lagrangian kernels-and show that these kernels span a subspace capturing the Lagrangian's projection as inverse dynamics. By such property, our model uses only inputs and outputs as in machine learning and inherits the structured form as in system dynamics, thereby removing the need for the mundane derivations for new systems as well as the generalization problem in learning from scratches. In effect, it learns the system's Lagrangian, a simpler task than directly learning the dynamics. To demonstrate, we applied the proposed kernel to identify the robot inverse dynamics in simulations and experiments. Our results present a competitive novel approach to identifying Lagrangian systems, despite using only inputs and outputs.

  2. Rigid Body Time Integration by Convected Base Vectors with Implicit Constraints

    DEFF Research Database (Denmark)

    Krenk, Steen; Nielsen, Martin Bjerre

    2013-01-01

    of the kinetic energy used in the present formulation is deliberately chosen to correspond to a rigid body rotation, and the orthonormality constraints are introduced via the equivalent Green strain components of the base vectors. The particular form of the extended inertia tensor used here implies a set...

  3. Development of expression vectors for Escherichia coli based on the pCR2 replicon

    Directory of Open Access Journals (Sweden)

    Deb J K

    2007-05-01

    Full Text Available Abstract Background Recent developments in metabolic engineering and the need for expanded compatibility required for co-expression studies, underscore the importance of developing new plasmid vectors with properties such as stability and compatibility. Results We utilized the pCR2 replicon of Corynebacterium renale, which harbours multiple plasmids, for constructing a range of expression vectors. Different antibiotic-resistance markers were introduced and the vectors were found to be 100% stable over a large number of generations in the absence of selection pressure. Compatibility of this plasmid was studied with different Escherichia coli plasmid replicons viz. pMB1 and p15A. It was observed that pCR2 was able to coexist with these E.coli plasmids for 60 generations in the absence of selection pressure. Soluble intracellular production was checked by expressing GFP under the lac promoter in an expression plasmid pCR2GFP. Also high level production of human IFNγ was obtained by cloning the h-IFNγ under a T7 promoter in the expression plasmid pCR2-IFNγ and using a dual plasmid heat shock system for expression. Repeated sub-culturing in the absence of selection pressure for six days did not lead to any fall in the production levels post induction, for both GFP and h-IFNγ, demonstrating that pCR2 is a useful plasmid in terms of stability and compatibility. Conclusion We have constructed a series of expression vectors based on the pCR2 replicon and demonstrated its high stability and sustained expression capacity, in the absence of selection pressure which will make it an efficient tool for metabolic engineering and co-expression studies, as well as for scale up of expression.

  4. Medical Image Compression Based on Vector Quantization with Variable Block Sizes in Wavelet Domain

    Directory of Open Access Journals (Sweden)

    Huiyan Jiang

    2012-01-01

    Full Text Available An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality.

  5. Molecular mechanism of mutagenesis induced by olaquindox using a shuttle vector pSP189/mammalian cell system

    International Nuclear Information System (INIS)

    Hao Lihua; Chen Qian; Xiao Xilong

    2006-01-01

    Olaquindox, a quinoxaline 1,4-dioxide derivative from quindoxin, is widely used as an animal growth promoter in China. We tested olaquindox as a mutagen in a SV40-based shuttle vector pSP189 and African green kidney cell (Vero E6 cell line) system to define the safety of olaquindox as a food-additive for animals. When applied at 6.6 μg/ml, olaquindox caused 12 times higher mutation frequency in comparison to untreated controls. More than 70% of base substitutions happened at G:C base pairs featuring G:C to T:A or G:C to A:T conversions. Frequency of point mutations for in vitro modified plasmids was also dramatically increased from the spontaneous background level. Olaquindox-induced mutations did not occur randomly along the supF shuttle vector, but instead, had a hot spot at base pair no. 155 which accounts for 37% of total mutations. Olaquindox-induced mutations also showed sequence-specificity in which most point mutations occurred at site N in a 5'-NNTTNN-3' sequence while most tandem bases deletion and rearrangement were seen at the 5'-ANGGCCNAAA-3' sequence. We conclude that olaquindox induces DNA mutation, therefore, should not be used as an additive to promote animal growth

  6. Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction.

    Science.gov (United States)

    Gao, Xiang-Ming; Yang, Shi-Feng; Pan, San-Bo

    2017-01-01

    Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

  7. Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

    Directory of Open Access Journals (Sweden)

    Xiang-ming Gao

    2017-01-01

    Full Text Available Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD and support vector machine (SVM optimized with an artificial bee colony (ABC algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

  8. Effective data compaction algorithm for vector scan EB writing system

    Science.gov (United States)

    Ueki, Shinichi; Ashida, Isao; Kawahira, Hiroichi

    2001-01-01

    We have developed a new mask data compaction algorithm dedicated to vector scan electron beam (EB) writing systems for 0.13 μm device generation. Large mask data size has become a significant problem at mask data processing for which data compaction is an important technique. In our new mask data compaction, 'array' representation and 'cell' representation are used. The mask data format for the EB writing system with vector scan supports these representations. The array representation has a pitch and a number of repetitions in both X and Y direction. The cell representation has a definition of figure group and its reference. The new data compaction method has the following three steps. (1) Search arrays of figures by selecting pitches of array so that a number of figures are included. (2) Find out same arrays that have same repetitive pitch and number of figures. (3) Search cells of figures, where the figures in each cell take identical positional relationship. By this new method for the mask data of a 4M-DRAM block gate layer with peripheral circuits, 202 Mbytes without compaction was highly compacted to 6.7 Mbytes in 20 minutes on a 500 MHz PC.

  9. Vector-valued measure and the necessary conditions for the optimal control problems of linear systems

    International Nuclear Information System (INIS)

    Xunjing, L.

    1981-12-01

    The vector-valued measure defined by the well-posed linear boundary value problems is discussed. The maximum principle of the optimal control problem with non-convex constraint is proved by using the vector-valued measure. Especially, the necessary conditions of the optimal control of elliptic systems is derived without the convexity of the control domain and the cost function. (author)

  10. Genetic modification of lymphocytes by retrovirus-based vectors.

    Science.gov (United States)

    Suerth, Julia D; Schambach, Axel; Baum, Christopher

    2012-10-01

    The genetic modification of lymphocytes is an important topic in the emerging field of gene therapy. Many clinical trials targeting immunodeficiency syndromes or cancer have shown therapeutic benefit; further applications address inflammatory and infectious disorders. Retroviral vector development requires a detailed understanding of the interactions with the host. Most researchers have used simple gammaretroviral vectors to modify lymphocytes, either directly or via hematopoietic stem and progenitor cells. Lentiviral, spumaviral (foamyviral) and alpharetroviral vectors were designed to reduce the necessity for cell stimulation and to utilize potentially safer integration properties. Novel surface modifications (pseudotyping) and transgenes, built using synthetic components, expand the retroviral toolbox, altogether promising increased specificity and potency. Product consistency will be an important criterion for routine clinical use. Copyright © 2012. Published by Elsevier Ltd.

  11. Meromorphic Vector Fields and Circle Packings

    DEFF Research Database (Denmark)

    Dias, Kealey

    The objective of the Ph.D. project is to initiate a classification of bifurcations of meromorphic vector fields and to clarify their relation to circle packings. Technological applications are to image analysis and to effective grid generation using discrete conformal mappings. The two branches...... of dynamical systems, continuous and discrete, correspond to the study of differential equations (vector fields) and iteration of mappings respectively. In holomorphic dynamics, the systems studied are restricted to those described by holomorphic (complex analytic) functions or meromorphic (allowing poles...... as singularities) functions. There already exists a well-developed theory for iterative holomorphic dynamical systems, and successful relations found between iteration theory and flows of vector fields have been one of the main motivations for the recent interest in holomorphic vector fields. Restricting...

  12. Novel Strategy to Control Transgene Expression Mediated by a Sendai Virus-Based Vector Using a Nonstructural C Protein and Endogenous MicroRNAs.

    Directory of Open Access Journals (Sweden)

    Masayuki Sano

    Full Text Available Tissue-specific control of gene expression is an invaluable tool for studying various biological processes and medical applications. Efficient regulatory systems have been utilized to control transgene expression in various types of DNA viral or integrating viral vectors. However, existing regulatory systems are difficult to transfer into negative-strand RNA virus vector platforms because of significant differences in their transcriptional machineries. In this study, we developed a novel strategy for regulating transgene expression mediated by a cytoplasmic RNA vector based on a replication-defective and persistent Sendai virus (SeVdp. Because of the capacity of Sendai virus (SeV nonstructural C proteins to specifically inhibit viral RNA synthesis, overexpression of C protein significantly reduced transgene expression mediated by SeVdp vectors. We found that SeV C overexpression concomitantly reduced SeVdp mRNA levels and genomic RNA synthesis. To control C expression, target sequences for an endogenous microRNA were incorporated into the 3' untranslated region of the C genes. Incorporation of target sequences for miR-21 into the SeVdp vector restored transgene expression in HeLa cells by decreasing C expression. Furthermore, the SeVdp vector containing target sequences for let-7a enabled cell-specific control of transgene expression in human fibroblasts and induced pluripotent stem cells. Our findings demonstrate that SeV C can be used as an effective regulator for controlling transgene expression. This strategy will contribute to efficient and less toxic SeVdp-mediated gene transfer in various biological applications.

  13. Experimental Evaluation of Integral Transformations for Engineering Drawings Vectorization

    Directory of Open Access Journals (Sweden)

    Vaský Jozef

    2014-12-01

    Full Text Available The concept of digital manufacturing supposes application of digital technologies in the whole product life cycle. Direct digital manufacturing includes such information technology processes, where products are directly manufactured from 3D CAD model. In digital manufacturing, engineering drawing is replaced by CAD product model. In the contemporary practice, lots of engineering paper-based drawings are still archived. They could be digitalized by scanner and stored to one of the raster graphics format and after that vectorized for interactive editing in the specific software system for technical drawing or for archiving in some of the standard vector graphics file format. The vector format is suitable for 3D model generating, too.The article deals with using of selected integral transformations (Fourier, Hough in the phase of digitalized raster engineering drawings vectorization.

  14. Adeno-associated viral vectors as agents for gene delivery : application in disorders and trauma of the central nervous system

    NARCIS (Netherlands)

    Ruitenberg, Marc J; Eggers, Ruben; Boer, Gerard J; Verhaagen, J.

    2002-01-01

    The use of viral vectors as agents for gene delivery provides a direct approach to manipulate gene expression in the mammalian central nervous system (CNS). The present article describes in detail the methodology for the injection of viral vectors, in particular adeno-associated virus (AAV) vectors,

  15. A New Curve Tracing Algorithm Based on Local Feature in the Vectorization of Paper Seismograms

    Directory of Open Access Journals (Sweden)

    Maofa Wang

    2014-02-01

    Full Text Available History paper seismograms are very important information for earthquake monitoring and prediction. The vectorization of paper seismograms is an import problem to be resolved. Auto tracing of waveform curves is a key technology for the vectorization of paper seismograms. It can transform an original scanning image into digital waveform data. Accurately tracing out all the key points of each curve in seismograms is the foundation for vectorization of paper seismograms. In the paper, we present a new curve tracing algorithm based on local feature, applying to auto extraction of earthquake waveform in paper seismograms.

  16. Medical Image Compression Based on Vector Quantization with Variable Block Sizes in Wavelet Domain

    OpenAIRE

    Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

    2012-01-01

    An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with vari...

  17. A Novel Neural Network Vector Control for Single-Phase Grid-Connected Converters with L, LC and LCL Filters

    Directory of Open Access Journals (Sweden)

    Xingang Fu

    2016-04-01

    Full Text Available This paper investigates a novel recurrent neural network (NN-based vector control approach for single-phase grid-connected converters (GCCs with L (inductor, LC (inductor-capacitor and LCL (inductor-capacitor-inductor filters and provides their comparison study with the conventional standard vector control method. A single neural network controller replaces two current-loop PI controllers, and the NN training approximates the optimal control for the single-phase GCC system. The Levenberg–Marquardt (LM algorithm was used to train the NN controller based on the complete system equations without any decoupling policies. The proposed NN approach can solve the decoupling problem associated with the conventional vector control methods for L, LC and LCL-filter-based single-phase GCCs. Both simulation study and hardware experiments demonstrate that the neural network vector controller shows much more improved performance than that of conventional vector controllers, including faster response speed and lower overshoot. Especially, NN vector control could achieve very good performance using low switch frequency. More importantly, the neural network vector controller is a damping free controller, which is generally required by a conventional vector controller for an LCL-filter-based single-phase grid-connected converter and, therefore, can overcome the inefficiency problem caused by damping policies.

  18. Vector magnetometer based on synchronous manipulation of nitrogen-vacancy centers in all crystal directions

    Science.gov (United States)

    Zhang, Chen; Yuan, Heng; Zhang, Ning; Xu, Lixia; Zhang, Jixing; Li, Bo; Fang, Jiancheng

    2018-04-01

    Negatively charged nitrogen vacancy (NV‑) centers in diamond have been extensively studied as high-sensitivity magnetometers, showcasing a wide range of applications. This study experimentally demonstrates a vector magnetometry scheme based on synchronous manipulation of NV‑ center ensembles in all crystal directions using double frequency microwaves (MWs) and multi-coupled-strip-lines (mCSL) waveguide. The application of the mCSL waveguide ensures a high degree of synchrony (99%) for manipulating NV‑ centers in multiple orientations in a large volume. Manipulation with double frequency MWs makes NV‑ centers of all four crystal directions involved, and additionally leads to an enhancement of the manipulation field. In this work, by monitoring the changes in the slope of the resonance line consisting of multi-axes NV‑ centers, measurement of the direction of the external field vector was demonstrated with a sensitivity of {{10}\\prime}/\\sqrt{Hz} . Based on the scheme, the fluorescence signal contrast was improved by four times higher and the sensitivity to the magnetic field strength was improved by two times. The method provides a more practical way of achieving vector sensors based on NV‑ center ensembles in diamond.

  19. CAS algorithm-based optimum design of PID controller in AVR system

    International Nuclear Information System (INIS)

    Zhu Hui; Li Lixiang; Zhao Ying; Guo Yu; Yang Yixian

    2009-01-01

    This paper presents a novel design method for determining the optimal PID controller parameters of an automatic voltage regulator (AVR) system using the chaotic ant swarm (CAS) algorithm. In the tuning process of parameters, the CAS algorithm is iterated to give the optimal parameters of the PID controller based on the fitness theory, where the position vector of each ant in the CAS algorithm corresponds to the parameter vector of the PID controller. The proposed CAS-PID controllers can ensure better control system performance with respect to the reference input in comparison with GA-PID controllers. Numerical simulations are provided to verify the effectiveness and feasibility of PID controller based on CAS algorithm.

  20. Design and Potential of Non-Integrating Lentiviral Vectors

    Directory of Open Access Journals (Sweden)

    Aaron Shaw

    2014-01-01

    Full Text Available Lentiviral vectors have demonstrated promising results in clinical trials that target cells of the hematopoietic system. For these applications, they are the vectors of choice since they provide stable integration into cells that will undergo extensive expansion in vivo. Unfortunately, integration can have unintended consequences including dysregulated cell growth. Therefore, lentiviral vectors that do not integrate are predicted to have a safer profile compared to integrating vectors and should be considered for applications where transient expression is required or for sustained episomal expression such as in quiescent cells. In this review, the system for generating lentiviral vectors will be described and used to illustrate how alterations in the viral integrase or vector Long Terminal Repeats have been used to generate vectors that lack the ability to integrate. In addition to their safety advantages, these non-integrating lentiviral vectors can be used when persistent expression would have adverse consequences. Vectors are currently in development for use in vaccinations, cancer therapy, site-directed gene insertions, gene disruption strategies, and cell reprogramming. Preclinical work will be described that illustrates the potential of this unique vector system in human gene therapy.

  1. Optical vector network analyzer based on double-sideband modulation.

    Science.gov (United States)

    Jun, Wen; Wang, Ling; Yang, Chengwu; Li, Ming; Zhu, Ning Hua; Guo, Jinjin; Xiong, Liangming; Li, Wei

    2017-11-01

    We report an optical vector network analyzer (OVNA) based on double-sideband (DSB) modulation using a dual-parallel Mach-Zehnder modulator. The device under test (DUT) is measured twice with different modulation schemes. By post-processing the measurement results, the response of the DUT can be obtained accurately. Since DSB modulation is used in our approach, the measurement range is doubled compared with conventional single-sideband (SSB) modulation-based OVNA. Moreover, the measurement accuracy is improved by eliminating the even-order sidebands. The key advantage of the proposed scheme is that the measurement of a DUT with bandpass response can also be simply realized, which is a big challenge for the SSB-based OVNA. The proposed method is theoretically and experimentally demonstrated.

  2. GOOD AND EVIL AS VECTORS OF FREE WILL IN THE STRUCTURE OF ANTHROPIC TIME

    Directory of Open Access Journals (Sweden)

    V. B. Khanzhy

    2017-12-01

    Full Text Available Purpose. The work is aimed at comprehending good and evil as vectors of free will in the structure of anthropic time. Methodology. The study is based on: 1 the general theory of systems (A. I. Uyomov, A. Yu. Tsofnas, L. N. Terentyeva – while justifying the possibility of representing the anthropic time as a system in general; 2 synergetics – while considering the anthropic time as a complex self-organizing system; 3 the concept of «а whole in a whole» (I. V. Yershova-Babenko – while identifying the optimal principle of correlation of the time units, taking into attention their ethical multi-vectority. Originality. In the context of the reconstruction of the concept of anthropic time: 1 the authors revealed ethical vectors of expansion of free will as the driving principle of human temporality (the vectors of «freedom for good» and «freedom for evil»; 2 the authors justified the optimality of using the principle of complementarity in solving the problem of harmonizing the coexistence of units of anthropic time («matryoshkas of time». Conclusion. 1 In a line with the tradition of anthropologization of the problem of good and evil, these intentions of human activity are interpreted as vectors of free will in the structure of anthropic time; 2 the paper represented anthropic time as a system in general (based on the general theory of systems and as a complex self-organizing system in particular (based on a synergetic methodology; 3 constituting of the system of anthropic time by the existential-actionable concept allowed to overcome the position of the one-vectored time, i.e.to reveal the ethical binarity of the anthropic time vectors prepared by the duality of expansion of free will as its driving principle; 4 formulation of the problem of discrepancy between the intentions of different temporal systems showed the optimality of the complementarity principle in solving the question how to harmonize the relations of anthropic time

  3. Modeling and control of PEMFC based on least squares support vector machines

    International Nuclear Information System (INIS)

    Li Xi; Cao Guangyi; Zhu Xinjian

    2006-01-01

    The proton exchange membrane fuel cell (PEMFC) is one of the most important power supplies. The operating temperature of the stack is an important controlled variable, which impacts the performance of the PEMFC. In order to improve the generating performance of the PEMFC, prolong its life and guarantee safety, credibility and low cost of the PEMFC system, it must be controlled efficiently. A nonlinear predictive control algorithm based on a least squares support vector machine (LS-SVM) model is presented for a family of complex systems with severe nonlinearity, such as the PEMFC, in this paper. The nonlinear off line model of the PEMFC is built by a LS-SVM model with radial basis function (RBF) kernel so as to implement nonlinear predictive control of the plant. During PEMFC operation, the off line model is linearized at each sampling instant, and the generalized predictive control (GPC) algorithm is applied to the predictive control of the plant. Experimental results demonstrate the effectiveness and advantages of this approach

  4. A Novel Approach to Asynchronous MVP Data Interpretation Based on Elliptical-Vectors

    Science.gov (United States)

    Kruglyakov, M.; Trofimov, I.; Korotaev, S.; Shneyer, V.; Popova, I.; Orekhova, D.; Scshors, Y.; Zhdanov, M. S.

    2014-12-01

    We suggest a novel approach to asynchronous magnetic-variation profiling (MVP) data interpretation. Standard method in MVP is based on the interpretation of the coefficients of linear relation between vertical and horizontal components of the measured magnetic field.From mathematical point of view this pair of linear coefficients is not a vector which leads to significant difficulties in asynchronous data interpretation. Our approach allows us to actually treat such a pair of complex numbers as a special vector called an ellipse-vector (EV). By choosing the particular definitions of complex length and direction, the basic relation of MVP can be considered as the dot product. This considerably simplifies the interpretation of asynchronous data. The EV is described by four real numbers: the values of major and minor semiaxes, the angular direction of the major semiaxis and the phase. The notation choice is motivated by historical reasons. It is important that different EV's components have different sensitivity with respect to the field sources and the local heterogeneities. Namely, the value of major semiaxis and the angular direction are mostly determined by the field source and the normal cross-section. On the other hand, the value of minor semiaxis and the phase are responsive to local heterogeneities. Since the EV is the general form of complex vector, the traditional Schmucker vectors can be explicitly expressed through its components.The proposed approach was successfully applied to interpretation the results of asynchronous measurements that had been obtained in the Arctic Ocean at the drift stations "North Pole" in 1962-1976.

  5. Video Vectorization via Tetrahedral Remeshing.

    Science.gov (United States)

    Wang, Chuan; Zhu, Jie; Guo, Yanwen; Wang, Wenping

    2017-02-09

    We present a video vectorization method that generates a video in vector representation from an input video in raster representation. A vector-based video representation offers the benefits of vector graphics, such as compactness and scalability. The vector video we generate is represented by a simplified tetrahedral control mesh over the spatial-temporal video volume, with color attributes defined at the mesh vertices. We present novel techniques for simplification and subdivision of a tetrahedral mesh to achieve high simplification ratio while preserving features and ensuring color fidelity. From an input raster video, our method is capable of generating a compact video in vector representation that allows a faithful reconstruction with low reconstruction errors.

  6. DODAB:monoolein-based lipoplexes as non-viral vectors for transfection of mammalian cells.

    Science.gov (United States)

    Silva, J P Neves; Oliveira, A C N; Casal, M P P A; Gomes, A C; Coutinho, P J G; Coutinho, O P; Oliveira, M E C D Real

    2011-10-01

    DNA/Cationic liposome complexes (lipoplexes) have been widely used as non-viral vectors for transfection. Neutral lipids in liposomal formulation are determinant for transfection efficiency using these vectors. In this work, we studied the potential of monoolein (MO) as helper lipid for cellular transfection. Lipoplexes composed of pDNA and dioctadecyldimethylammonium bromide (DODAB)/1-monooleoyl-rac-glycerol (MO) at different molar ratios (4:1, 2:1 and 1:1) and at different cationic lipid/DNA ratios were investigated. The physicochemical properties of the lipoplexes (size, charge and structure), were studied by Dynamic Light Scattering (DLS), Zeta Potential (ζ) and cryo-transmission electron microscopy (cryo-TEM). The effect of MO on pDNA condensation and the effect of heparin and heparan sulphate on the percentage of pDNA release from the lipoplexes were also studied by Ethidium Bromide (EtBr) exclusion assays and electrophoresis. Cytotoxicity and transfection efficiency of these lipoplexes were evaluated using 293T cells and compared with the golden standard helper lipids 1,2-dioleoyl-sn-glycero-3-hosphoethanolamine (DOPE) and cholesterol (Chol) as well as with a commercial transfection agent (Lipofectamine™ LTX). The internalization of transfected fluorescently-labeled pDNA was also visualized using the same cell line. The results demonstrate that the presence of MO not only increases pDNA compactation efficiency, but also affects the physicochemical properties of the lipoplexes, which can interfere with lipoplex-cell interactions. The DODAB:MO formulations tested showed little toxicity and successfully mediated in vitro cell transfection. These results were supported by fluorescence microscopy studies, which illustrated that lipoplexes were able to access the cytosol and deliver pDNA to the nucleus. DODAB:MO-based lipoplexes were thus validated as non-toxic, efficient lipofection vectors for genetic modification of mammalian cells. Understanding the

  7. Designing the input vector to ANN-based models for short-term load forecast in electricity distribution systems

    International Nuclear Information System (INIS)

    Santos, P.J.; Martins, A.G.; Pires, A.J.

    2007-01-01

    The present trend to electricity market restructuring increases the need for reliable short-term load forecast (STLF) algorithms, in order to assist electric utilities in activities such as planning, operating and controlling electric energy systems. Methodologies such as artificial neural networks (ANN) have been widely used in the next hour load forecast horizon with satisfactory results. However, this type of approach has had some shortcomings. Usually, the input vector (IV) is defined in a arbitrary way, mainly based on experience, on engineering judgment criteria and on concern about the ANN dimension, always taking into consideration the apparent correlations within the available endogenous and exogenous data. In this paper, a proposal is made of an approach to define the IV composition, with the main focus on reducing the influence of trial-and-error and common sense judgments, which usually are not based on sufficient evidence of comparative advantages over previous alternatives. The proposal includes the assessment of the strictly necessary instances of the endogenous variable, both from the point of view of the contiguous values prior to the forecast to be made, and of the past values representing the trend of consumption at homologous time intervals of the past. It also assesses the influence of exogenous variables, again limiting their presence at the IV to the indispensable minimum. A comparison is made with two alternative IV structures previously proposed in the literature, also applied to the distribution sector. The paper is supported by a real case study at the distribution sector. (author)

  8. Usability Evaluation of an Augmented Reality System for Teaching Euclidean Vectors

    Science.gov (United States)

    Martin-Gonzalez, Anabel; Chi-Poot, Angel; Uc-Cetina, Victor

    2016-01-01

    Augmented reality (AR) is one of the emerging technologies that has demonstrated to be an efficient technological tool to enhance learning techniques. In this paper, we describe the development and evaluation of an AR system for teaching Euclidean vectors in physics and mathematics. The goal of this pedagogical tool is to facilitate user's…

  9. Implicit Real Vector Automata

    Directory of Open Access Journals (Sweden)

    Jean-François Degbomont

    2010-10-01

    Full Text Available This paper addresses the symbolic representation of non-convex real polyhedra, i.e., sets of real vectors satisfying arbitrary Boolean combinations of linear constraints. We develop an original data structure for representing such sets, based on an implicit and concise encoding of a known structure, the Real Vector Automaton. The resulting formalism provides a canonical representation of polyhedra, is closed under Boolean operators, and admits an efficient decision procedure for testing the membership of a vector.

  10. A multi vector energy analysis for interconnected power and gas systems

    International Nuclear Information System (INIS)

    Devlin, Joseph; Li, Kang; Higgins, Paraic; Foley, Aoife

    2017-01-01

    Highlights: • The first multi vector energy system analysis for Britain and Ireland is performed. • Extreme weather driven gas demands were utilised to increase gas system stress. • GB gas system is capable of satisfying demand but restricts gas generator ramping. • Irish gas system congestion causes a 40% increase in gas generator short run cost. • Gas storage in Ireland relieved congestion reduced operational costs by 14%. - Abstract: This paper presents the first multi vector energy analysis for the interconnected energy systems of Great Britain (GB) and Ireland. Both systems share a common high penetration of wind power, but significantly different security of supply outlooks. Ireland is heavily dependent on gas imports from GB, giving significance to the interconnected aspect of the methodology in addition to the gas and power interactions analysed. A fully realistic unit commitment and economic dispatch model coupled to an energy flow model of the gas supply network is developed. Extreme weather events driving increased domestic gas demand and low wind power output were utilised to increase gas supply network stress. Decreased wind profiles had a larger impact on system security than high domestic gas demand. However, the GB energy system was resilient during high demand periods but gas network stress limited the ramping capability of localised generating units. Additionally, gas system entry node congestion in the Irish system was shown to deliver a 40% increase in short run costs for generators. Gas storage was shown to reduce the impact of high demand driven congestion delivering a reduction in total generation costs of 14% in the period studied and reducing electricity imports from GB, significantly contributing to security of supply.

  11. EVE: Explainable Vector Based Embedding Technique Using Wikipedia

    OpenAIRE

    Qureshi, M. Atif; Greene, Derek

    2017-01-01

    We present an unsupervised explainable word embedding technique, called EVE, which is built upon the structure of Wikipedia. The proposed model defines the dimensions of a semantic vector representing a word using human-readable labels, thereby it readily interpretable. Specifically, each vector is constructed using the Wikipedia category graph structure together with the Wikipedia article link structure. To test the effectiveness of the proposed word embedding model, we consider its usefulne...

  12. A Matrix-Based Structure for Vario-Scale Vector Representation over a Wide Range of Map Scales : The Case of River Network Data

    NARCIS (Netherlands)

    Huang, L.; Ai, Tinghua; van Oosterom, P.J.M.; Yan, Xiongfeng; Yang, Min

    2017-01-01

    The representation of vector data at variable scales has been widely applied in geographic information systems and map-based services. When the scale changes across a wide range, a complex generalization that involves multiple operations is required to transform the data. To present such complex

  13. Evaluation of systemic insecticides mixed in rodenticide baits for plague vector control

    DEFF Research Database (Denmark)

    Larsen, Kim Søholt; Lodal, Jens

    1997-01-01

    Rodenticide baits containing systemic insecticides were evaluated in the laboratory for their palatability to the house rat Rattus rattus and for their toxicity against the oriental rat flea Xenopsylla cheopis - both animals are important Vectors of plague in Africa. The test bait and a non...

  14. Local Patch Vectors Encoded by Fisher Vectors for Image Classification

    Directory of Open Access Journals (Sweden)

    Shuangshuang Chen

    2018-02-01

    Full Text Available The objective of this work is image classification, whose purpose is to group images into corresponding semantic categories. Four contributions are made as follows: (i For computational simplicity and efficiency, we directly adopt raw image patch vectors as local descriptors encoded by Fisher vector (FV subsequently; (ii For obtaining representative local features within the FV encoding framework, we compare and analyze three typical sampling strategies: random sampling, saliency-based sampling and dense sampling; (iii In order to embed both global and local spatial information into local features, we construct an improved spatial geometry structure which shows good performance; (iv For reducing the storage and CPU costs of high dimensional vectors, we adopt a new feature selection method based on supervised mutual information (MI, which chooses features by an importance sorting algorithm. We report experimental results on dataset STL-10. It shows very promising performance with this simple and efficient framework compared to conventional methods.

  15. Structural analysis of online handwritten mathematical symbols based on support vector machines

    Science.gov (United States)

    Simistira, Foteini; Papavassiliou, Vassilis; Katsouros, Vassilis; Carayannis, George

    2013-01-01

    Mathematical expression recognition is still a very challenging task for the research community mainly because of the two-dimensional (2d) structure of mathematical expressions (MEs). In this paper, we present a novel approach for the structural analysis between two on-line handwritten mathematical symbols of a ME, based on spatial features of the symbols. We introduce six features to represent the spatial affinity of the symbols and compare two multi-class classification methods that employ support vector machines (SVMs): one based on the "one-against-one" technique and one based on the "one-against-all", in identifying the relation between a pair of symbols (i.e. subscript, numerator, etc). A dataset containing 1906 spatial relations derived from the Competition on Recognition of Online Handwritten Mathematical Expressions (CROHME) 2012 training dataset is constructed to evaluate the classifiers and compare them with the rule-based classifier of the ILSP-1 system participated in the contest. The experimental results give an overall mean error rate of 2.61% for the "one-against-one" SVM approach, 6.57% for the "one-against-all" SVM technique and 12.31% error rate for the ILSP-1 classifier.

  16. Successful vectorization - reactor physics Monte Carlo code

    International Nuclear Information System (INIS)

    Martin, W.R.

    1989-01-01

    Most particle transport Monte Carlo codes in use today are based on the ''history-based'' algorithm, wherein one particle history at a time is simulated. Unfortunately, the ''history-based'' approach (present in all Monte Carlo codes until recent years) is inherently scalar and cannot be vectorized. In particular, the history-based algorithm cannot take advantage of vector architectures, which characterize the largest and fastest computers at the current time, vector supercomputers such as the Cray X/MP or IBM 3090/600. However, substantial progress has been made in recent years in developing and implementing a vectorized Monte Carlo algorithm. This algorithm follows portions of many particle histories at the same time and forms the basis for all successful vectorized Monte Carlo codes that are in use today. This paper describes the basic vectorized algorithm along with descriptions of several variations that have been developed by different researchers for specific applications. These applications have been mainly in the areas of neutron transport in nuclear reactor and shielding analysis and photon transport in fusion plasmas. The relative merits of the various approach schemes will be discussed and the present status of known vectorization efforts will be summarized along with available timing results, including results from the successful vectorization of 3-D general geometry, continuous energy Monte Carlo. (orig.)

  17. Principal components based support vector regression model for on-line instrument calibration monitoring in NPPs

    International Nuclear Information System (INIS)

    Seo, In Yong; Ha, Bok Nam; Lee, Sung Woo; Shin, Chang Hoon; Kim, Seong Jun

    2010-01-01

    In nuclear power plants (NPPs), periodic sensor calibrations are required to assure that sensors are operating correctly. By checking the sensor's operating status at every fuel outage, faulty sensors may remain undetected for periods of up to 24 months. Moreover, typically, only a few faulty sensors are found to be calibrated. For the safe operation of NPP and the reduction of unnecessary calibration, on-line instrument calibration monitoring is needed. In this study, principal component based auto-associative support vector regression (PCSVR) using response surface methodology (RSM) is proposed for the sensor signal validation of NPPs. This paper describes the design of a PCSVR-based sensor validation system for a power generation system. RSM is employed to determine the optimal values of SVR hyperparameters and is compared to the genetic algorithm (GA). The proposed PCSVR model is confirmed with the actual plant data of Kori Nuclear Power Plant Unit 3 and is compared with the Auto-Associative support vector regression (AASVR) and the auto-associative neural network (AANN) model. The auto-sensitivity of AASVR is improved by around six times by using a PCA, resulting in good detection of sensor drift. Compared to AANN, accuracy and cross-sensitivity are better while the auto-sensitivity is almost the same. Meanwhile, the proposed RSM for the optimization of the PCSVR algorithm performs even better in terms of accuracy, auto-sensitivity, and averaged maximum error, except in averaged RMS error, and this method is much more time efficient compared to the conventional GA method

  18. A terrestrial lidar-based workflow for determining three-dimensional slip vectors and associated uncertainties

    Science.gov (United States)

    Gold, Peter O.; Cowgill, Eric; Kreylos, Oliver; Gold, Ryan D.

    2012-01-01

    Three-dimensional (3D) slip vectors recorded by displaced landforms are difficult to constrain across complex fault zones, and the uncertainties associated with such measurements become increasingly challenging to assess as landforms degrade over time. We approach this problem from a remote sensing perspective by using terrestrial laser scanning (TLS) and 3D structural analysis. We have developed an integrated TLS data collection and point-based analysis workflow that incorporates accurate assessments of aleatoric and epistemic uncertainties using experimental surveys, Monte Carlo simulations, and iterative site reconstructions. Our scanning workflow and equipment requirements are optimized for single-operator surveying, and our data analysis process is largely completed using new point-based computing tools in an immersive 3D virtual reality environment. In a case study, we measured slip vector orientations at two sites along the rupture trace of the 1954 Dixie Valley earthquake (central Nevada, United States), yielding measurements that are the first direct constraints on the 3D slip vector for this event. These observations are consistent with a previous approximation of net extension direction for this event. We find that errors introduced by variables in our survey method result in <2.5 cm of variability in components of displacement, and are eclipsed by the 10–60 cm epistemic errors introduced by reconstructing the field sites to their pre-erosion geometries. Although the higher resolution TLS data sets enabled visualization and data interactivity critical for reconstructing the 3D slip vector and for assessing uncertainties, dense topographic constraints alone were not sufficient to significantly narrow the wide (<26°) range of allowable slip vector orientations that resulted from accounting for epistemic uncertainties.

  19. Paralleled comparison of vectors for the generation of CAR-T cells.

    Science.gov (United States)

    Qin, Di-Yuan; Huang, Yong; Li, Dan; Wang, Yong-Sheng; Wang, Wei; Wei, Yu-Quan

    2016-09-01

    T-lymphocytes genetically engineered with the chimeric antigen receptor (CAR-T) have shown great therapeutic potential in cancer treatment. A variety of preclinical researches and clinical trials of CAR-T therapy have been carried out to lay the foundation for future clinical application. In these researches, several gene-transfer methods were used to deliver CARs or other genes into T-lymphocytes, equipping CAR-modified T cells with a property of recognizing and attacking antigen-expressing tumor cells in a major histocompatibility complex-independent manner. Here, we summarize the gene-transfer vectors commonly used in the generation of CAR-T cell, including retrovirus vectors, lentivirus vectors, the transposon/transposase system, the plasmid-based system, and the messenger RNA electroporation system. The following aspects were compared in parallel: efficiency of gene transfer, the integration methods in the modified T cells, foreground of scale-up production, and application and development in clinical trials. These aspects should be taken into account to generate the optimal CAR-gene vector that may be suitable for future clinical application.

  20. Test of Understanding of Vectors: A Reliable Multiple-Choice Vector Concept Test

    Science.gov (United States)

    Barniol, Pablo; Zavala, Genaro

    2014-01-01

    In this article we discuss the findings of our research on students' understanding of vector concepts in problems without physical context. First, we develop a complete taxonomy of the most frequent errors made by university students when learning vector concepts. This study is based on the results of several test administrations of open-ended…

  1. Development of a Support Vector Machine - Based Image Analysis System for Focal Liver Lesions Classification in Magnetic Resonance Images

    International Nuclear Information System (INIS)

    Gatos, I; Tsantis, S; Kagadis, G; Karamesini, M; Skouroliakou, A

    2015-01-01

    Purpose: The design and implementation of a computer-based image analysis system employing the support vector machine (SVM) classifier system for the classification of Focal Liver Lesions (FLLs) on routine non-enhanced, T2-weighted Magnetic Resonance (MR) images. Materials and Methods: The study comprised 92 patients; each one of them has undergone MRI performed on a Magnetom Concerto (Siemens). Typical signs on dynamic contrast-enhanced MRI and biopsies were employed towards a three class categorization of the 92 cases: 40-benign FLLs, 25-Hepatocellular Carcinomas (HCC) within Cirrhotic liver parenchyma and 27-liver metastases from Non-Cirrhotic liver. Prior to FLLs classification an automated lesion segmentation algorithm based on Marcov Random Fields was employed in order to acquire each FLL Region of Interest. 42 texture features derived from the gray-level histogram, co-occurrence and run-length matrices and 12 morphological features were obtained from each lesion. Stepwise multi-linear regression analysis was utilized to avoid feature redundancy leading to a feature subset that fed the multiclass SVM classifier designed for lesion classification. SVM System evaluation was performed by means of leave-one-out method and ROC analysis. Results: Maximum accuracy for all three classes (90.0%) was obtained by means of the Radial Basis Kernel Function and three textural features (Inverse- Different-Moment, Sum-Variance and Long-Run-Emphasis) that describe lesion's contrast, variability and shape complexity. Sensitivity values for the three classes were 92.5%, 81.5% and 96.2% respectively, whereas specificity values were 94.2%, 95.3% and 95.5%. The AUC value achieved for the selected subset was 0.89 with 0.81 - 0.94 confidence interval. Conclusion: The proposed SVM system exhibit promising results that could be utilized as a second opinion tool to the radiologist in order to decrease the time/cost of diagnosis and the need for patients to undergo invasive

  2. Vision-Based Perception and Classification of Mosquitoes Using Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Masataka Fuchida

    2017-01-01

    Full Text Available The need for a novel automated mosquito perception and classification method is becoming increasingly essential in recent years, with steeply increasing number of mosquito-borne diseases and associated casualties. There exist remote sensing and GIS-based methods for mapping potential mosquito inhabitants and locations that are prone to mosquito-borne diseases, but these methods generally do not account for species-wise identification of mosquitoes in closed-perimeter regions. Traditional methods for mosquito classification involve highly manual processes requiring tedious sample collection and supervised laboratory analysis. In this research work, we present the design and experimental validation of an automated vision-based mosquito classification module that can deploy in closed-perimeter mosquito inhabitants. The module is capable of identifying mosquitoes from other bugs such as bees and flies by extracting the morphological features, followed by support vector machine-based classification. In addition, this paper presents the results of three variants of support vector machine classifier in the context of mosquito classification problem. This vision-based approach to the mosquito classification problem presents an efficient alternative to the conventional methods for mosquito surveillance, mapping and sample image collection. Experimental results involving classification between mosquitoes and a predefined set of other bugs using multiple classification strategies demonstrate the efficacy and validity of the proposed approach with a maximum recall of 98%.

  3. A virus vector based on Canine Herpesvirus for vaccine applications in canids.

    Science.gov (United States)

    Strive, T; Hardy, C M; Wright, J; Reubel, G H

    2007-01-31

    Canine Herpesvirus (CHV) is being developed as a virus vector for the vaccination of European red foxes. However, initial studies using recombinant CHV vaccines in foxes revealed viral attenuation and lack of antibody response to inserted foreign antigens. These findings were attributed both to inactivation of the thymidine kinase (TK) gene and excess foreign genetic material in the recombinant viral genome. In this study, we report an improved CHV-bacterial artificial chromosome (BAC) vector system designed to overcome attenuation in foxes. A non-essential region was identified in the CHV genome as an alternative insertion site for foreign genes. Replacement of a guanine/cytosine (GC)-rich intergenic region between UL21 and UL22 of CHV with a marker gene did not change growth behaviour in vitro, showing that this region is not essential for virus growth in cell culture. We subsequently produced a CHV-BAC vector with an intact TK gene in which the bacterial genes and the antigen expression cassette were inserted into this GC-rich locus. Unlike earlier constructs, the new CHV-BAC allowed self-excision of the bacterial genes via homologous recombination after transfection of BACs into cell culture. The BAC-CHV system was used to produce a recombinant virus that constitutively expressed porcine zona pellucida subunit C protein between the UL21 and UL22 genes of CHV. Complete self-excision of the bacterial genes from CHV was achieved within one round of replication whilst retaining antigen gene expression.

  4. Clinical validation of coronal and sagittal spinal curve measurements based on three-dimensional vertebra vector parameters.

    Science.gov (United States)

    Somoskeöy, Szabolcs; Tunyogi-Csapó, Miklós; Bogyó, Csaba; Illés, Tamás

    2012-10-01

    For many decades, visualization and evaluation of three-dimensional (3D) spinal deformities have only been possible by two-dimensional (2D) radiodiagnostic methods, and as a result, characterization and classification were based on 2D terminologies. Recent developments in medical digital imaging and 3D visualization techniques including surface 3D reconstructions opened a chance for a long-sought change in this field. Supported by a 3D Terminology on Spinal Deformities of the Scoliosis Research Society, an approach for 3D measurements and a new 3D classification of scoliosis yielded several compelling concepts on 3D visualization and new proposals for 3D classification in recent years. More recently, a new proposal for visualization and complete 3D evaluation of the spine by 3D vertebra vectors has been introduced by our workgroup, a concept, based on EOS 2D/3D, a groundbreaking new ultralow radiation dose integrated orthopedic imaging device with sterEOS 3D spine reconstruction software. Comparison of accuracy, correlation of measurement values, intraobserver and interrater reliability of methods by conventional manual 2D and vertebra vector-based 3D measurements in a routine clinical setting. Retrospective, nonrandomized study of diagnostic X-ray images created as part of a routine clinical protocol of eligible patients examined at our clinic during a 30-month period between July 2007 and December 2009. In total, 201 individuals (170 females, 31 males; mean age, 19.88 years) including 10 healthy athletes with normal spine and patients with adolescent idiopathic scoliosis (175 cases), adult degenerative scoliosis (11 cases), and Scheuermann hyperkyphosis (5 cases). Overall range of coronal curves was between 2.4 and 117.5°. Analysis of accuracy and reliability of measurements was carried out on a group of all patients and in subgroups based on coronal plane deviation: 0 to 10° (Group 1; n=36), 10 to 25° (Group 2; n=25), 25 to 50° (Group 3; n=69), 50 to 75

  5. Comparison of Different Computer–Aided Surgery Systems in Skull Base Surgery

    OpenAIRE

    Ecke, U.; Luebben, B.; Maurer, J.; Boor, S.; Mann, W. J.

    2003-01-01

    Computer–aided surgery (CAS) based on high–resolution imaging techniques represents an important adjunct to precise intraoperative orientation when anatomical landmarks are distorted or missing. Several commercial systems, mostly based on optical or electromagnetic navigation principles, are on the market. This study investigated the application of EasyGuide®, VectorVision®, and InstaTrak® CAS systems in ENT surgery under practical and laboratory conditions. System accuracy, time required, ha...

  6. Using Vector and Extended Boolean Matching in an Expert System for Selecting Foster Homes.

    Science.gov (United States)

    Fox, Edward A.; Winett, Sheila G.

    1990-01-01

    Describes FOCES (Foster Care Expert System), a prototype expert system for choosing foster care placements for children which integrates information retrieval techniques with artificial intelligence. The use of prototypes and queries in Prolog routines, extended Boolean matching, and vector correlation are explained, as well as evaluation by…

  7. Generation and characterization of a novel candidate gene therapy and vaccination vector based on human species D adenovirus type 56.

    Science.gov (United States)

    Duffy, Margaret R; Alonso-Padilla, Julio; John, Lijo; Chandra, Naresh; Khan, Selina; Ballmann, Monika Z; Lipiec, Agnieszka; Heemskerk, Evert; Custers, Jerome; Arnberg, Niklas; Havenga, Menzo; Baker, Andrew H; Lemckert, Angelique

    2018-01-01

    The vectorization of rare human adenovirus (HAdV) types will widen our knowledge of this family and their interaction with cells, tissues and organs. In this study we focus on HAdV-56, a member of human Ad species D, and create ease-of-use cloning systems to generate recombinant HAdV-56 vectors carrying foreign genes. We present in vitro transduction profiles for HAdV-56 in direct comparison to the most commonly used HAdV-5-based vector. In vivo characterizations demonstrate that when it is delivered intravenously (i.v.) HAdV-56 mainly targets the spleen and, to a lesser extent, the lungs, whilst largely bypassing liver transduction in mice. HAdV-56 triggered robust inflammatory and cellular immune responses, with higher induction of IFNγ, TNFα, IL5, IL6, IP10, MCP1 and MIG1 compared to HAdV-5 following i.v. administration. We also investigated its potential as a vaccine vector candidate by performing prime immunizations in mice with HAdV-56 encoding luciferase (HAdV-56-Luc). Direct comparisons were made to HAdV-26, a highly potent human vaccine vector currently in phase II clinical trials. HAdV-56-Luc induced luciferase 'antigen'-specific IFNγ-producing cells and anti-HAdV-56 neutralizing antibodies in Balb/c mice, demonstrating a near identical profile to that of HAdV-26. Taken together, the data presented provides further insight into human Ad receptor/co-receptor usage, and the first report on HAdV-56 vectors and their potential for gene therapy and vaccine applications.

  8. Screw Remaining Life Prediction Based on Quantum Genetic Algorithm and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Xiaochen Zhang

    2017-01-01

    Full Text Available To predict the remaining life of ball screw, a screw remaining life prediction method based on quantum genetic algorithm (QGA and support vector machine (SVM is proposed. A screw accelerated test bench is introduced. Accelerometers are installed to monitor the performance degradation of ball screw. Combined with wavelet packet decomposition and isometric mapping (Isomap, the sensitive feature vectors are obtained and stored in database. Meanwhile, the sensitive feature vectors are randomly chosen from the database and constitute training samples and testing samples. Then the optimal kernel function parameter and penalty factor of SVM are searched with the method of QGA. Finally, the training samples are used to train optimized SVM while testing samples are adopted to test the prediction accuracy of the trained SVM so the screw remaining life prediction model can be got. The experiment results show that the screw remaining life prediction model could effectively predict screw remaining life.

  9. Generation of a Vero-Based Packaging Cell Line to Produce SV40 Gene Delivery Vectors for Use in Clinical Gene Therapy Studies

    Directory of Open Access Journals (Sweden)

    Miguel G. Toscano

    2017-09-01

    Full Text Available Replication-defective (RD recombinant simian virus 40 (SV40-based gene delivery vectors hold a great potential for clinical applications because of their presumed non-immunogenicity and capacity to induce immune tolerance to the transgene products in humans. However, the clinical use of SV40 vectors has been hampered by the lack of a packaging cell line that produces replication-competent (RC free SV40 particles in the vector production process. To solve this problem, we have adapted the current SV40 vector genome used for the production of vector particles and generated a novel Vero-based packaging cell line named SuperVero that exclusively expresses the SV40 large T antigen. SuperVero cells produce similar numbers of SV40 vector particles compared to the currently used packaging cell lines, albeit in the absence of contaminating RC SV40 particles. Our unique SV40 vector platform named SVac paves the way to clinically test a whole new generation of SV40-based therapeutics for a broad range of important diseases.

  10. Policy-based secure communication with automatic key management for industrial control and automation systems

    Science.gov (United States)

    Chernoguzov, Alexander; Markham, Thomas R.; Haridas, Harshal S.

    2016-11-22

    A method includes generating at least one access vector associated with a specified device in an industrial process control and automation system. The specified device has one of multiple device roles. The at least one access vector is generated based on one or more communication policies defining communications between one or more pairs of devices roles in the industrial process control and automation system, where each pair of device roles includes the device role of the specified device. The method also includes providing the at least one access vector to at least one of the specified device and one or more other devices in the industrial process control and automation system in order to control communications to or from the specified device.

  11. Optical cage generated by azimuthal- and radial-variant vector beams.

    Science.gov (United States)

    Man, Zhongsheng; Bai, Zhidong; Li, Jinjian; Zhang, Shuoshuo; Li, Xiaoyu; Zhang, Yuquan; Ge, Xiaolu; Fu, Shenggui

    2018-05-01

    We propose a method to generate an optical cage using azimuthal- and radial-variant vector beams in a high numerical aperture optical system. A new kind of vector beam that has azimuthal- and radial-variant polarization states is proposed and demonstrated theoretically. Then, an integrated analytical model to calculate the electromagnetic field and Poynting vector distributions of the input azimuthal- and radial-variant vector beams is derived and built based on the vector diffraction theory of Richards and Wolf. From calculations, a full polarization-controlled optical cage is obtained by simply tailoring the radial index of the polarization, the uniformity U of which is up to 0.7748, and the cleanness C is zero. Additionally, a perfect optical cage can be achieved with U=1, and C=0 by introducing an amplitude modulation; its magnetic field and energy flow are also demonstrated in detail. Such optical cages may be helpful in applications such as optical trapping and high-resolution imaging.

  12. Retroviral Vectors: Post Entry Events and Genomic Alterations

    Directory of Open Access Journals (Sweden)

    Christof von Kalle

    2011-04-01

    Full Text Available The curative potential of retroviral vectors for somatic gene therapy has been demonstrated impressively in several clinical trials leading to sustained long-term correction of the underlying genetic defect. Preclinical studies and clinical monitoring of gene modified hematopoietic stem and progenitor cells in patients have shown that biologically relevant vector induced side effects, ranging from in vitro immortalization to clonal dominance and oncogenesis in vivo, accompany therapeutic efficiency of integrating retroviral gene transfer systems. Most importantly, it has been demonstrated that the genotoxic potential is not identical among all retroviral vector systems designed for clinical application. Large scale viral integration site determination has uncovered significant differences in the target site selection of retrovirus subfamilies influencing the propensity for inducing genetic alterations in the host genome. In this review we will summarize recent insights gained on the mechanisms of insertional mutagenesis based on intrinsic target site selection of different retrovirus families. We will also discuss examples of side effects occurring in ongoing human gene therapy trials and future prospectives in the field.

  13. Exotic composite vector boson

    International Nuclear Information System (INIS)

    Akama, K.; Hattori, T.; Yasue, M.

    1991-01-01

    An exotic composite vector boson V is introduced in two dynamical models of composite quarks, leptons, W, and Z. One is based on four-Fermi interactions, in which composite vector bosons are regarded as fermion-antifermion bound states and the other is based on the confining SU(2) L gauge model, in which they are given by scalar-antiscalar bound states. Both approaches describe the same effective interactions for the sector of composite quarks, leptons, W, Z, γ, and V

  14. Chromosome-based genetic complementation system for Xylella fastidiosa.

    Science.gov (United States)

    Matsumoto, Ayumi; Young, Glenn M; Igo, Michele M

    2009-03-01

    Xylella fastidiosa is a xylem-limited, gram-negative bacterium that causes Pierce's disease of grapevine. Here, we describe the construction of four vectors that facilitate the insertion of genes into a neutral site (NS1) in the X. fastidiosa chromosome. These vectors carry a colE1-like (pMB1) replicon and DNA sequences from NS1 flanking a multiple-cloning site and a resistance marker for one of the following antibiotics: chloramphenicol, erythromycin, gentamicin, or kanamycin. In X. fastidiosa, vectors with colE1-like (pMB1) replicons have been found to result primarily in the recovery of double recombinants rather than single recombinants. Thus, the ease of obtaining double recombinants and the stability of the resulting insertions at NS1 in the absence of selective pressure are the major advantages of this system. Based on in vitro and in planta characterizations, strains carrying insertions within NS1 are indistinguishable from wild-type X. fastidiosa in terms of growth rate, biofilm formation, and pathogenicity. To illustrate the usefulness of this system for complementation analysis, we constructed a strain carrying a mutation in the X. fastidiosa cpeB gene, which is predicted to encode a catalase/peroxidase, and showed that the sensitivity of this mutant to hydrogen peroxide could be overcome by the introduction of a wild-type copy of cpeB at NS1. Thus, this chromosome-based complementation system provides a valuable genetic tool for investigating the role of specific genes in X. fastidiosa cell physiology and virulence.

  15. Generalized correlation integral vectors: A distance concept for chaotic dynamical systems

    Energy Technology Data Exchange (ETDEWEB)

    Haario, Heikki, E-mail: heikki.haario@lut.fi [School of Engineering Science, Lappeenranta University of Technology, Lappeenranta (Finland); Kalachev, Leonid, E-mail: KalachevL@mso.umt.edu [Department of Mathematical Sciences, University of Montana, Missoula, Montana 59812-0864 (United States); Hakkarainen, Janne [Earth Observation Unit, Finnish Meteorological Institute, Helsinki (Finland)

    2015-06-15

    Several concepts of fractal dimension have been developed to characterise properties of attractors of chaotic dynamical systems. Numerical approximations of them must be calculated by finite samples of simulated trajectories. In principle, the quantities should not depend on the choice of the trajectory, as long as it provides properly distributed samples of the underlying attractor. In practice, however, the trajectories are sensitive with respect to varying initial values, small changes of the model parameters, to the choice of a solver, numeric tolerances, etc. The purpose of this paper is to present a statistically sound approach to quantify this variability. We modify the concept of correlation integral to produce a vector that summarises the variability at all selected scales. The distribution of this stochastic vector can be estimated, and it provides a statistical distance concept between trajectories. Here, we demonstrate the use of the distance for the purpose of estimating model parameters of a chaotic dynamic model. The methodology is illustrated using computational examples for the Lorenz 63 and Lorenz 95 systems, together with a framework for Markov chain Monte Carlo sampling to produce posterior distributions of model parameters.

  16. Hypergraph partitioning implementation for parallelizing matrix-vector multiplication using CUDA GPU-based parallel computing

    Science.gov (United States)

    Murni, Bustamam, A.; Ernastuti, Handhika, T.; Kerami, D.

    2017-07-01

    Calculation of the matrix-vector multiplication in the real-world problems often involves large matrix with arbitrary size. Therefore, parallelization is needed to speed up the calculation process that usually takes a long time. Graph partitioning techniques that have been discussed in the previous studies cannot be used to complete the parallelized calculation of matrix-vector multiplication with arbitrary size. This is due to the assumption of graph partitioning techniques that can only solve the square and symmetric matrix. Hypergraph partitioning techniques will overcome the shortcomings of the graph partitioning technique. This paper addresses the efficient parallelization of matrix-vector multiplication through hypergraph partitioning techniques using CUDA GPU-based parallel computing. CUDA (compute unified device architecture) is a parallel computing platform and programming model that was created by NVIDIA and implemented by the GPU (graphics processing unit).

  17. Towards human behavior recognition based on spatio temporal features and support vector machines

    Science.gov (United States)

    Ghabri, Sawsen; Ouarda, Wael; Alimi, Adel M.

    2017-03-01

    Security and surveillance are vital issues in today's world. The recent acts of terrorism have highlighted the urgent need for efficient surveillance. There is indeed a need for an automated system for video surveillance which can detect identity and activity of person. In this article, we propose a new paradigm to recognize an aggressive human behavior such as boxing action. Our proposed system for human activity detection includes the use of a fusion between Spatio Temporal Interest Point (STIP) and Histogram of Oriented Gradient (HoG) features. The novel feature called Spatio Temporal Histogram Oriented Gradient (STHOG). To evaluate the robustness of our proposed paradigm with a local application of HoG technique on STIP points, we made experiments on KTH human action dataset based on Multi Class Support Vector Machines classification. The proposed scheme outperforms basic descriptors like HoG and STIP to achieve 82.26% us an accuracy value of classification rate.

  18. Oblique decision trees using embedded support vector machines in classifier ensembles

    NARCIS (Netherlands)

    Menkovski, V.; Christou, I.; Efremidis, S.

    2008-01-01

    Classifier ensembles have emerged in recent years as a promising research area for boosting pattern recognition systems' performance. We present a new base classifier that utilizes oblique decision tree technology based on support vector machines for the construction of oblique (non-axis parallel)

  19. Vectorization, parallelization and porting of nuclear codes on the VPP500 system (porting). Progress report fiscal 1997

    International Nuclear Information System (INIS)

    Ishizuki, Shigeru; Nemoto, Toshiyuki; Kawai, Wataru; Watanabe, Hideo; Tanabe, Hidenobu; Kawasaki, Nobuo; Adachi, Masaaki; Ogasawara, Shinobu; Kume, Etsuo

    1999-05-01

    Several computer codes in the nuclear field have been vectorized, parallelized and transported on the FUJITSU VPP500 system and/or the AP3000 system at Center for Promotion of Computational Science and Engineering in Japan Atomic Energy Research Institute. We dealt with 14 codes in fiscal 1997. These results are reported in 3 parts, i.e., the vectorization part, the parallelization part and the porting part. In this report, we describe the porting. In this porting part, the porting of transient reactor analysis code TRAC-BF1 and Monte Carlo radiation transport code MCNP4A on the AP3000 are described. In addition, a modification of program libraries for command-driven interactive data analysis plotting program IPLOT is described. In the vectorization part, the vectorization of multidimensional two-fluid model code ACE-3D for evaluation of constitutive equations, statistical decay code SD and three-dimensional thermal analysis code for in-core test section (T2) of HENDEL SSPHEAT are described. In the parallelization part, the parallelization of cylindrical direct numerical simulation code CYLDNS44N, worldwide version of system for prediction of environmental emergency dose information code WSPEEDI, extension of quantum molecular dynamics code EQMD and three-dimensional non-steady compressible fluid dynamics code STREAM are described. (author)

  20. Relativistic gravitation from massless systems of scalar and vector fields

    International Nuclear Information System (INIS)

    Fonseca Teixeira, A.F. da.

    1979-01-01

    Under the laws of Einstein's gravitational theory, a massless system consisting of the diffuse sources of two fields is discussed. One fields is scalar, of long range, the other is a vector field of short range. A proportionality between the sources is assumed. Both fields are minimally coupled to gravitation, and contribute positive definitely to the time component of the energy momentum tensor. A class of static, spherically symmetric solutions of the equations is obtained, in the weak field limit. The solutions are regular everywhere, stable, and can represent large or small physical systems. The gravitational field presents a Schwarzschild-type asymptotic behavior. The dependence of the energy on the various parameters characterizing the system is discussed in some detail. (Author) [pt

  1. Design of a mixer for the thrust-vectoring system on the high-alpha research vehicle

    Science.gov (United States)

    Pahle, Joseph W.; Bundick, W. Thomas; Yeager, Jessie C.; Beissner, Fred L., Jr.

    1996-01-01

    One of the advanced control concepts being investigated on the High-Alpha Research Vehicle (HARV) is multi-axis thrust vectoring using an experimental thrust-vectoring (TV) system consisting of three hydraulically actuated vanes per engine. A mixer is used to translate the pitch-, roll-, and yaw-TV commands into the appropriate TV-vane commands for distribution to the vane actuators. A computer-aided optimization process was developed to perform the inversion of the thrust-vectoring effectiveness data for use by the mixer in performing this command translation. Using this process a new mixer was designed for the HARV and evaluated in simulation and flight. An important element of the Mixer is the priority logic, which determines priority among the pitch-, roll-, and yaw-TV commands.

  2. Vector manifestation and violation of vector dominance in hot matter

    International Nuclear Information System (INIS)

    Harada, Masayasu; Sasaki, Chihiro

    2004-01-01

    We show the details of the calculation of the hadronic thermal corrections to the two-point functions in the effective field theory of QCD for pions and vector mesons based on the hidden local symmetry (HLS) in hot matter using the background field gauge. We study the temperature dependence of the pion velocity in the low-temperature region determined from the hadronic thermal corrections, and show that, due to the presence of the dynamical vector meson, the pion velocity is smaller than the speed of the light already at one-loop level, in contrast to the result obtained in the ordinary chiral perturbation theory including only the pion at one-loop. Including the intrinsic temperature dependences of the parameters of the HLS Lagrangian determined from the underlying QCD through the Wilsonian matching, we show how the vector manifestation (VM), in which the massless vector meson becomes the chiral partner of pion, is realized at the critical temperature. We present a new prediction of the VM on the direct photon-π-π coupling which measures the validity of the vector dominance (VD) of the electromagnetic form factor of the pion: we find that the VD is largely violated at the critical temperature, which indicates that the assumption of the VD made in several analyses on the dilepton spectra in hot matter may need to be weakened for consistently including the effect of the dropping mass of the vector meson

  3. Reference Function Based Spatiotemporal Fuzzy Logic Control Design Using Support Vector Regression Learning

    Directory of Open Access Journals (Sweden)

    Xian-Xia Zhang

    2013-01-01

    Full Text Available This paper presents a reference function based 3D FLC design methodology using support vector regression (SVR learning. The concept of reference function is introduced to 3D FLC for the generation of 3D membership functions (MF, which enhance the capability of the 3D FLC to cope with more kinds of MFs. The nonlinear mathematical expression of the reference function based 3D FLC is derived, and spatial fuzzy basis functions are defined. Via relating spatial fuzzy basis functions of a 3D FLC to kernel functions of an SVR, an equivalence relationship between a 3D FLC and an SVR is established. Therefore, a 3D FLC can be constructed using the learned results of an SVR. Furthermore, the universal approximation capability of the proposed 3D fuzzy system is proven in terms of the finite covering theorem. Finally, the proposed method is applied to a catalytic packed-bed reactor and simulation results have verified its effectiveness.

  4. Vector mesons on the light front

    International Nuclear Information System (INIS)

    Naito, K.; Maedan, S.; Itakura, K.

    2004-01-01

    We apply the light-front quantization to the Nambu-Jona-Lasinio model with the vector interaction, and compute vector meson's mass and light-cone wavefunction in the large N limit. Following the same procedure as in the previous analyses for scalar and pseudo-scalar mesons, we derive the bound-state equations of a qq-bar system in the vector channel. We include the lowest order effects of the vector interaction. The resulting transverse and longitudinal components of the bound-state equation look different from each other. But eventually after imposing an appropriate cutoff, one finds these two are identical, giving the same mass and the same (spin-independent) light-cone wavefunction. Mass of the vector meson decreases as one increases the strength of the vector interaction

  5. Surveillance of vector-borne pathogens under imperfect detection: lessons from Chagas disease risk (mis)measurement.

    Science.gov (United States)

    Minuzzi-Souza, Thaís Tâmara Castro; Nitz, Nadjar; Cuba, César Augusto Cuba; Hagström, Luciana; Hecht, Mariana Machado; Santana, Camila; Ribeiro, Marcelle; Vital, Tamires Emanuele; Santalucia, Marcelo; Knox, Monique; Obara, Marcos Takashi; Abad-Franch, Fernando; Gurgel-Gonçalves, Rodrigo

    2018-01-09

    Vector-borne pathogens threaten human health worldwide. Despite their critical role in disease prevention, routine surveillance systems often rely on low-complexity pathogen detection tests of uncertain accuracy. In Chagas disease surveillance, optical microscopy (OM) is routinely used for detecting Trypanosoma cruzi in its vectors. Here, we use replicate T. cruzi detection data and hierarchical site-occupancy models to assess the reliability of OM-based T. cruzi surveillance while explicitly accounting for false-negative and false-positive results. We investigated 841 triatomines with OM slides (1194 fresh, 1192 Giemsa-stained) plus conventional (cPCR, 841 assays) and quantitative PCR (qPCR, 1682 assays). Detections were considered unambiguous only when parasitologists unmistakably identified T. cruzi in Giemsa-stained slides. qPCR was >99% sensitive and specific, whereas cPCR was ~100% specific but only ~55% sensitive. In routine surveillance, examination of a single OM slide per vector missed ~50-75% of infections and wrongly scored as infected ~7% of the bugs. qPCR-based and model-based infection frequency estimates were nearly three times higher, on average, than OM-based indices. We conclude that the risk of vector-borne Chagas disease may be substantially higher than routine surveillance data suggest. The hierarchical modelling approach we illustrate can help enhance vector-borne disease surveillance systems when pathogen detection is imperfect.

  6. Vectorization, parallelization and porting of nuclear codes (porting). Progress report fiscal 1999

    Energy Technology Data Exchange (ETDEWEB)

    Kawasaki, Nobuo; Nemoto, Toshiyuki; Kawai, Wataru; Ishizuki, Shigeru [Fujitsu Ltd., Tokyo (Japan); Ogasawara, Shinobu; Kume, Etsuo; Adachi, Masaaki [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Yatake, Yo-ichi [Hitachi Ltd., Tokyo (Japan)

    2001-01-01

    Several computer codes in the nuclear field have been vectorized, parallelized and transported on the FUJITSU VPP500 system, the AP3000 system, the SX-4 system and the Paragon system at Center for Promotion of Computational Science and Engineering in Japan Atomic Energy Research Institute. We dealt with 18 codes in fiscal 1999. These results are reported in 3 parts, i.e., the vectorization and the parallelization part on vector processors, the parallelization port on scalar processors and the porting part. In this report, we describe the porting. In this porting part, the porting of Assisted Model Building with Energy Refinement code version 5 (AMBER5), general purpose Monte Carlo codes far neutron and photon transport calculations based on continuous energy and multigroup methods (MVP/GMVP), automatic editing system for MCNP library code (autonj), neutron damage calculations for materials irradiations and neutron damage calculations for compounds code (SPECTER/SPECOMP), severe accident analysis code (MELCOR) and COolant Boiling in Rod Arrays, Two-Fluid code (COBRA-TF) on the VPP500 system and/or the AP3000 system are described. (author)

  7. An efficient deletion mutant packaging system for defective herpes simplex virus vectors: Potential applications to human gene therapy and neuronal physiology

    International Nuclear Information System (INIS)

    Geller, A.I.; Keyomarsi, K.; Bryan, J.; Pardee, A.B.

    1990-01-01

    The authors have previously described a defective herpes simplex virus (HSV-1) vector system that permits that introduction of virtually any gene into nonmitotic cells. pHSVlac, the prototype vector, stably expresses Escherichia coli β-galactosidase from a constitutive promoter in many human cell lines, in cultured rat neurons from throughout the nervous system, and in cells in the adult rat brain. HSV-1 vectors expressing other genes may prove useful for studying neuronal physiology or performing human gene therapy for neurological diseases, such as Parkinson disease or brain tumors. A HSV-1 temperature-sensitive (ts) mutant, ts K, has been used as helper virus; ts mutants revert to wild type. In contrast, HSV-1 deletion mutants essentially cannot revert to wild type; therefore, use of a deletion mutant as helper virus might permit human gene therapy with HSV-1 vectors. They now report an efficient packaging system for HSV-1 VECTORS USING A DELETION MUTANT, d30EBA, as helper virus; virus is grown on the complementing cell line M64A. pHSVlac virus prepared using the deletion mutant packaging system stably expresses β-galactosidase in cultured rat sympathetic neurons and glia. Both D30EBA and ts K contain a mutation in the IE3 gene of HSV-1 strain 17 and have the same phenotype; therefore, changing the helper virus from ts K to D30EBA does not alter the host range or other properties of the HSV-1 vector system

  8. Topological invariants and the dynamics of an axial vector torsion field

    International Nuclear Information System (INIS)

    Drechsler, W.

    1983-01-01

    A generalized throry of gravitation is discussed which is based on a Riemann-Cartan space-time, U 4 , with an axial vector torsion field. Besides Einstein's equations determining the metric of the U 4 a system of nonlinear field equations is established coupling an axial vector source current to the axial vector torsion field. The properties of the solutions of these equations are discussed assuming a London-type condition relating the axial current and torsion field. To characterize the solutions use is made of the Euler and Pontrjagin forms and the associated quadratic curvature invariants for the U 4 space-time. It is found that there exists for a Riemann-Cartan space-time a relation between the zeros of the axial vector torsion field and the singularities of the Pontrjagin invariant, which is analogous to the well-known Hopf relation between the zeros of vector fields and the Euler characteristic. (author)

  9. Effects of Vector Backbone and Pseudotype on Lentiviral Vector-mediated Gene Transfer: Studies in Infant ADA-Deficient Mice and Rhesus Monkeys

    Science.gov (United States)

    Carbonaro Sarracino, Denise; Tarantal, Alice F; Lee, C Chang I.; Martinez, Michele; Jin, Xiangyang; Wang, Xiaoyan; Hardee, Cinnamon L; Geiger, Sabine; Kahl, Christoph A; Kohn, Donald B

    2014-01-01

    Systemic delivery of a lentiviral vector carrying a therapeutic gene represents a new treatment for monogenic disease. Previously, we have shown that transfer of the adenosine deaminase (ADA) cDNA in vivo rescues the lethal phenotype and reconstitutes immune function in ADA-deficient mice. In order to translate this approach to ADA-deficient severe combined immune deficiency patients, neonatal ADA-deficient mice and newborn rhesus monkeys were treated with species-matched and mismatched vectors and pseudotypes. We compared gene delivery by the HIV-1-based vector to murine γ-retroviral vectors pseudotyped with vesicular stomatitis virus-glycoprotein or murine retroviral envelopes in ADA-deficient mice. The vesicular stomatitis virus-glycoprotein pseudotyped lentiviral vectors had the highest titer and resulted in the highest vector copy number in multiple tissues, particularly liver and lung. In monkeys, HIV-1 or simian immunodeficiency virus vectors resulted in similar biodistribution in most tissues including bone marrow, spleen, liver, and lung. Simian immunodeficiency virus pseudotyped with the gibbon ape leukemia virus envelope produced 10- to 30-fold lower titers than the vesicular stomatitis virus-glycoprotein pseudotype, but had a similar tissue biodistribution and similar copy number in blood cells. The relative copy numbers achieved in mice and monkeys were similar when adjusted to the administered dose per kg. These results suggest that this approach can be scaled-up to clinical levels for treatment of ADA-deficient severe combined immune deficiency subjects with suboptimal hematopoietic stem cell transplantation options. PMID:24925206

  10. Effects of vector backbone and pseudotype on lentiviral vector-mediated gene transfer: studies in infant ADA-deficient mice and rhesus monkeys.

    Science.gov (United States)

    Carbonaro Sarracino, Denise; Tarantal, Alice F; Lee, C Chang I; Martinez, Michele; Jin, Xiangyang; Wang, Xiaoyan; Hardee, Cinnamon L; Geiger, Sabine; Kahl, Christoph A; Kohn, Donald B

    2014-10-01

    Systemic delivery of a lentiviral vector carrying a therapeutic gene represents a new treatment for monogenic disease. Previously, we have shown that transfer of the adenosine deaminase (ADA) cDNA in vivo rescues the lethal phenotype and reconstitutes immune function in ADA-deficient mice. In order to translate this approach to ADA-deficient severe combined immune deficiency patients, neonatal ADA-deficient mice and newborn rhesus monkeys were treated with species-matched and mismatched vectors and pseudotypes. We compared gene delivery by the HIV-1-based vector to murine γ-retroviral vectors pseudotyped with vesicular stomatitis virus-glycoprotein or murine retroviral envelopes in ADA-deficient mice. The vesicular stomatitis virus-glycoprotein pseudotyped lentiviral vectors had the highest titer and resulted in the highest vector copy number in multiple tissues, particularly liver and lung. In monkeys, HIV-1 or simian immunodeficiency virus vectors resulted in similar biodistribution in most tissues including bone marrow, spleen, liver, and lung. Simian immunodeficiency virus pseudotyped with the gibbon ape leukemia virus envelope produced 10- to 30-fold lower titers than the vesicular stomatitis virus-glycoprotein pseudotype, but had a similar tissue biodistribution and similar copy number in blood cells. The relative copy numbers achieved in mice and monkeys were similar when adjusted to the administered dose per kg. These results suggest that this approach can be scaled-up to clinical levels for treatment of ADA-deficient severe combined immune deficiency subjects with suboptimal hematopoietic stem cell transplantation options.

  11. Design of a Two-level Adaptive Multi-Agent System for Malaria Vectors driven by an ontology

    Directory of Open Access Journals (Sweden)

    Etang Josiane

    2007-07-01

    Full Text Available Abstract Background The understanding of heterogeneities in disease transmission dynamics as far as malaria vectors are concerned is a big challenge. Many studies while tackling this problem don't find exact models to explain the malaria vectors propagation. Methods To solve the problem we define an Adaptive Multi-Agent System (AMAS which has the property to be elastic and is a two-level system as well. This AMAS is a dynamic system where the two levels are linked by an Ontology which allows it to function as a reduced system and as an extended system. In a primary level, the AMAS comprises organization agents and in a secondary level, it is constituted of analysis agents. Its entry point, a User Interface Agent, can reproduce itself because it is given a minimum of background knowledge and it learns appropriate "behavior" from the user in the presence of ambiguous queries and from other agents of the AMAS in other situations. Results Some of the outputs of our system present a series of tables, diagrams showing some factors like Entomological parameters of malaria transmission, Percentages of malaria transmission per malaria vectors, Entomological inoculation rate. Many others parameters can be produced by the system depending on the inputted data. Conclusion Our approach is an intelligent one which differs from statistical approaches that are sometimes used in the field. This intelligent approach aligns itself with the distributed artificial intelligence. In terms of fight against malaria disease our system offers opportunities of reducing efforts of human resources who are not obliged to cover the entire territory while conducting surveys. Secondly the AMAS can determine the presence or the absence of malaria vectors even when specific data have not been collected in the geographical area. In the difference of a statistical technique, in our case the projection of the results in the field can sometimes appeared to be more general.

  12. Differentiation of Enhancing Glioma and Primary Central Nervous System Lymphoma by Texture-Based Machine Learning.

    Science.gov (United States)

    Alcaide-Leon, P; Dufort, P; Geraldo, A F; Alshafai, L; Maralani, P J; Spears, J; Bharatha, A

    2017-06-01

    Accurate preoperative differentiation of primary central nervous system lymphoma and enhancing glioma is essential to avoid unnecessary neurosurgical resection in patients with primary central nervous system lymphoma. The purpose of the study was to evaluate the diagnostic performance of a machine-learning algorithm by using texture analysis of contrast-enhanced T1-weighted images for differentiation of primary central nervous system lymphoma and enhancing glioma. Seventy-one adult patients with enhancing gliomas and 35 adult patients with primary central nervous system lymphomas were included. The tumors were manually contoured on contrast-enhanced T1WI, and the resulting volumes of interest were mined for textural features and subjected to a support vector machine-based machine-learning protocol. Three readers classified the tumors independently on contrast-enhanced T1WI. Areas under the receiver operating characteristic curves were estimated for each reader and for the support vector machine classifier. A noninferiority test for diagnostic accuracy based on paired areas under the receiver operating characteristic curve was performed with a noninferiority margin of 0.15. The mean areas under the receiver operating characteristic curve were 0.877 (95% CI, 0.798-0.955) for the support vector machine classifier; 0.878 (95% CI, 0.807-0.949) for reader 1; 0.899 (95% CI, 0.833-0.966) for reader 2; and 0.845 (95% CI, 0.757-0.933) for reader 3. The mean area under the receiver operating characteristic curve of the support vector machine classifier was significantly noninferior to the mean area under the curve of reader 1 ( P = .021), reader 2 ( P = .035), and reader 3 ( P = .007). Support vector machine classification based on textural features of contrast-enhanced T1WI is noninferior to expert human evaluation in the differentiation of primary central nervous system lymphoma and enhancing glioma. © 2017 by American Journal of Neuroradiology.

  13. RNA interference-based therapeutics for human immunodeficiency virus HIV-1 treatment: synthetic siRNA or vector-based shRNA?

    Science.gov (United States)

    Subramanya, Sandesh; Kim, Sang-Soo; Manjunath, N; Shankar, Premlata

    2010-02-01

    Despite the clinical benefits of highly active antiretroviral therapy (HAART), the prospect of life-long antiretroviral treatment poses significant problems, which has spurred interest in developing new drugs and strategies to treat HIV infection and eliminate persistent viral reservoirs. RNAi has emerged as a therapeutic possibility for HIV. We discuss progress in overcoming hurdles to translating transient and stable RNAi enabling technologies to clinical application for HIV; covering the past 2 - 3 years. HIV inhibition can be achieved by transfection of chemically or enzymatically synthesized siRNAs or by DNA-based vector systems expressing short hairpin RNAs (shRNAs) that are processed intracellularly into siRNA. We compare these approaches, focusing on technical and safety issues that will guide the choice of strategy for clinical use. Introduction of synthetic siRNA into cells or its stable endogenous production using vector-driven shRNA have been shown to suppress HIV replication in vitro and, in some instances, in vivo. Each method has advantages and limitations in terms of ease of delivery, duration of silencing, emergence of escape mutants and potential toxicity. Both appear to have potential as future therapeutics for HIV, once the technical and safety issues of each approach are overcome.

  14. Support vector regression model based predictive control of water level of U-tube steam generators

    Energy Technology Data Exchange (ETDEWEB)

    Kavaklioglu, Kadir, E-mail: kadir.kavaklioglu@pau.edu.tr

    2014-10-15

    Highlights: • Water level of U-tube steam generators was controlled in a model predictive fashion. • Models for steam generator water level were built using support vector regression. • Cost function minimization for future optimal controls was performed by using the steepest descent method. • The results indicated the feasibility of the proposed method. - Abstract: A predictive control algorithm using support vector regression based models was proposed for controlling the water level of U-tube steam generators of pressurized water reactors. Steam generator data were obtained using a transfer function model of U-tube steam generators. Support vector regression based models were built using a time series type model structure for five different operating powers. Feedwater flow controls were calculated by minimizing a cost function that includes the level error, the feedwater change and the mismatch between feedwater and steam flow rates. Proposed algorithm was applied for a scenario consisting of a level setpoint change and a steam flow disturbance. The results showed that steam generator level can be controlled at all powers effectively by the proposed method.

  15. Test of understanding of vectors: A reliable multiple-choice vector concept test

    Science.gov (United States)

    Barniol, Pablo; Zavala, Genaro

    2014-06-01

    In this article we discuss the findings of our research on students' understanding of vector concepts in problems without physical context. First, we develop a complete taxonomy of the most frequent errors made by university students when learning vector concepts. This study is based on the results of several test administrations of open-ended problems in which a total of 2067 students participated. Using this taxonomy, we then designed a 20-item multiple-choice test [Test of understanding of vectors (TUV)] and administered it in English to 423 students who were completing the required sequence of introductory physics courses at a large private Mexican university. We evaluated the test's content validity, reliability, and discriminatory power. The results indicate that the TUV is a reliable assessment tool. We also conducted a detailed analysis of the students' understanding of the vector concepts evaluated in the test. The TUV is included in the Supplemental Material as a resource for other researchers studying vector learning, as well as instructors teaching the material.

  16. Current error vector based prediction control of the section winding permanent magnet linear synchronous motor

    Energy Technology Data Exchange (ETDEWEB)

    Hong Junjie, E-mail: hongjjie@mail.sysu.edu.cn [School of Engineering, Sun Yat-Sen University, Guangzhou 510006 (China); Li Liyi, E-mail: liliyi@hit.edu.cn [Dept. Electrical Engineering, Harbin Institute of Technology, Harbin 150000 (China); Zong Zhijian; Liu Zhongtu [School of Engineering, Sun Yat-Sen University, Guangzhou 510006 (China)

    2011-10-15

    Highlights: {yields} The structure of the permanent magnet linear synchronous motor (SW-PMLSM) is new. {yields} A new current control method CEVPC is employed in this motor. {yields} The sectional power supply method is different to the others and effective. {yields} The performance gets worse with voltage and current limitations. - Abstract: To include features such as greater thrust density, higher efficiency without reducing the thrust stability, this paper proposes a section winding permanent magnet linear synchronous motor (SW-PMLSM), whose iron core is continuous, whereas winding is divided. The discrete system model of the motor is derived. With the definition of the current error vector and selection of the value function, the theory of the current error vector based prediction control (CEVPC) for the motor currents is explained clearly. According to the winding section feature, the motion region of the mover is divided into five zones, in which the implementation of the current predictive control method is proposed. Finally, the experimental platform is constructed and experiments are carried out. The results show: the current control effect has good dynamic response, and the thrust on the mover remains constant basically.

  17. The design and implementation of cost-effective algorithms for direct solution of banded linear systems on the vector processor system 32 supercomputer

    Science.gov (United States)

    Samba, A. S.

    1985-01-01

    The problem of solving banded linear systems by direct (non-iterative) techniques on the Vector Processor System (VPS) 32 supercomputer is considered. Two efficient direct methods for solving banded linear systems on the VPS 32 are described. The vector cyclic reduction (VCR) algorithm is discussed in detail. The performance of the VCR on a three parameter model problem is also illustrated. The VCR is an adaptation of the conventional point cyclic reduction algorithm. The second direct method is the Customized Reduction of Augmented Triangles' (CRAT). CRAT has the dominant characteristics of an efficient VPS 32 algorithm. CRAT is tailored to the pipeline architecture of the VPS 32 and as a consequence the algorithm is implicitly vectorizable.

  18. GPU Accelerated Vector Median Filter

    Science.gov (United States)

    Aras, Rifat; Shen, Yuzhong

    2011-01-01

    Noise reduction is an important step for most image processing tasks. For three channel color images, a widely used technique is vector median filter in which color values of pixels are treated as 3-component vectors. Vector median filters are computationally expensive; for a window size of n x n, each of the n(sup 2) vectors has to be compared with other n(sup 2) - 1 vectors in distances. General purpose computation on graphics processing units (GPUs) is the paradigm of utilizing high-performance many-core GPU architectures for computation tasks that are normally handled by CPUs. In this work. NVIDIA's Compute Unified Device Architecture (CUDA) paradigm is used to accelerate vector median filtering. which has to the best of our knowledge never been done before. The performance of GPU accelerated vector median filter is compared to that of the CPU and MPI-based versions for different image and window sizes, Initial findings of the study showed 100x improvement of performance of vector median filter implementation on GPUs over CPU implementations and further speed-up is expected after more extensive optimizations of the GPU algorithm .

  19. Short-term traffic flow prediction model using particle swarm optimization–based combined kernel function-least squares support vector machine combined with chaos theory

    Directory of Open Access Journals (Sweden)

    Qiang Shang

    2016-08-01

    Full Text Available Short-term traffic flow prediction is an important part of intelligent transportation systems research and applications. For further improving the accuracy of short-time traffic flow prediction, a novel hybrid prediction model (multivariate phase space reconstruction–combined kernel function-least squares support vector machine based on multivariate phase space reconstruction and combined kernel function-least squares support vector machine is proposed. The C-C method is used to determine the optimal time delay and the optimal embedding dimension of traffic variables’ (flow, speed, and occupancy time series for phase space reconstruction. The G-P method is selected to calculate the correlation dimension of attractor which is an important index for judging chaotic characteristics of the traffic variables’ series. The optimal input form of combined kernel function-least squares support vector machine model is determined by multivariate phase space reconstruction, and the model’s parameters are optimized by particle swarm optimization algorithm. Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. The experimental results suggest that the new proposed model yields better predictions compared with similar models (combined kernel function-least squares support vector machine, multivariate phase space reconstruction–generalized kernel function-least squares support vector machine, and phase space reconstruction–combined kernel function-least squares support vector machine, which indicates that the new proposed model exhibits stronger prediction ability and robustness.

  20. Parallel Kalman filter track fit based on vector classes

    Energy Technology Data Exchange (ETDEWEB)

    Kisel, Ivan [GSI Helmholtzzentrum fuer Schwerionenforschung GmbH (Germany); Kretz, Matthias [Kirchhoff-Institut fuer Physik, Ruprecht-Karls Universitaet, Heidelberg (Germany); Kulakov, Igor [Goethe-Universitaet, Frankfurt am Main (Germany); National Taras Shevchenko University, Kyiv (Ukraine)

    2010-07-01

    Modern high energy physics experiments have to process terabytes of input data produced in particle collisions. The core of the data reconstruction in high energy physics is the Kalman filter. Therefore, developing the fast Kalman filter algorithm, which uses maximum available power of modern processors, is important, in particular for initial selection of events interesting for the new physics. One of processors features, which can speed up the algorithm, is a SIMD instruction set, which allows to pack several data items in one register and operate on all of them in one go, thus achieving more operations per clock cycle. Therefore a flexible and useful interface, which uses the SIMD instruction set on different CPU and GPU processors architectures, has been realized as a vector classes library. The Kalman filter based track fitting algorithm has been implemented with use of the vector classes. Fitting quality tests show good results with the residuals equal to 49 {mu}m and 44 {mu}m for x and y track parameters and relative momentum resolution of 0.7%. The fitting time of 0.053 {mu}s per track has been achieved on Intel Xeon X5550 with 8 cores at 2.6 GHz by using in addition Intel Threading Building Blocks.

  1. A Foxtail mosaic virus Vector for Virus-Induced Gene Silencing in Maize.

    Science.gov (United States)

    Mei, Yu; Zhang, Chunquan; Kernodle, Bliss M; Hill, John H; Whitham, Steven A

    2016-06-01

    Plant viruses have been widely used as vectors for foreign gene expression and virus-induced gene silencing (VIGS). A limited number of viruses have been developed into viral vectors for the purposes of gene expression or VIGS in monocotyledonous plants, and among these, the tripartite viruses Brome mosaic virus and Cucumber mosaic virus have been shown to induce VIGS in maize (Zea mays). We describe here a new DNA-based VIGS system derived from Foxtail mosaic virus (FoMV), a monopartite virus that is able to establish systemic infection and silencing of endogenous maize genes homologous to gene fragments inserted into the FoMV genome. To demonstrate VIGS applications of this FoMV vector system, four genes, phytoene desaturase (functions in carotenoid biosynthesis), lesion mimic22 (encodes a key enzyme of the porphyrin pathway), iojap (functions in plastid development), and brown midrib3 (caffeic acid O-methyltransferase), were silenced and characterized in the sweet corn line Golden × Bantam. Furthermore, we demonstrate that the FoMV infectious clone establishes systemic infection in maize inbred lines, sorghum (Sorghum bicolor), and green foxtail (Setaria viridis), indicating the potential wide applications of this viral vector system for functional genomics studies in maize and other monocots. © 2016 American Society of Plant Biologists. All Rights Reserved.

  2. Design and Modeling of a Novel Torque Vectoring Differential System

    Directory of Open Access Journals (Sweden)

    Chen Yu-Fan

    2017-01-01

    Full Text Available In this paper, a new concept torque vectoring differential (TVD system is presented. It is shown that the structure and the mechanism of the system, the operating methods, and the parameters design by a simulation program, i.e. SimulationX. First of all, the structure of the new TVD system is introduced, as well as the relevant mechanic equations. Second, we attempt to verify the feasibility and accuracy of SimulationX through establishing a simple mechanical model by MATLAB, so that the further modeling and simulation results of the new TVD system will be credible. Then, the simulation results at the setting conditions are presented. Finally, the sensitivity of the design parameters is analyzed, including adjusting the braking torque and the dimensions of the gear sets in the differential. According to these results, the characteristics of the new TVD system can be derived in order to develop the whole system with vehicle dynamic model in the next stage.

  3. Trial watch: Naked and vectored DNA-based anticancer vaccines.

    Science.gov (United States)

    Bloy, Norma; Buqué, Aitziber; Aranda, Fernando; Castoldi, Francesca; Eggermont, Alexander; Cremer, Isabelle; Sautès-Fridman, Catherine; Fucikova, Jitka; Galon, Jérôme; Spisek, Radek; Tartour, Eric; Zitvogel, Laurence; Kroemer, Guido; Galluzzi, Lorenzo

    2015-05-01

    One type of anticancer vaccine relies on the administration of DNA constructs encoding one or multiple tumor-associated antigens (TAAs). The ultimate objective of these preparations, which can be naked or vectored by non-pathogenic viruses, bacteria or yeast cells, is to drive the synthesis of TAAs in the context of an immunostimulatory milieu, resulting in the (re-)elicitation of a tumor-targeting immune response. In spite of encouraging preclinical results, the clinical efficacy of DNA-based vaccines employed as standalone immunotherapeutic interventions in cancer patients appears to be limited. Thus, efforts are currently being devoted to the development of combinatorial regimens that allow DNA-based anticancer vaccines to elicit clinically relevant immune responses. Here, we discuss recent advances in the preclinical and clinical development of this therapeutic paradigm.

  4. Gradient Evolution-based Support Vector Machine Algorithm for Classification

    Science.gov (United States)

    Zulvia, Ferani E.; Kuo, R. J.

    2018-03-01

    This paper proposes a classification algorithm based on a support vector machine (SVM) and gradient evolution (GE) algorithms. SVM algorithm has been widely used in classification. However, its result is significantly influenced by the parameters. Therefore, this paper aims to propose an improvement of SVM algorithm which can find the best SVMs’ parameters automatically. The proposed algorithm employs a GE algorithm to automatically determine the SVMs’ parameters. The GE algorithm takes a role as a global optimizer in finding the best parameter which will be used by SVM algorithm. The proposed GE-SVM algorithm is verified using some benchmark datasets and compared with other metaheuristic-based SVM algorithms. The experimental results show that the proposed GE-SVM algorithm obtains better results than other algorithms tested in this paper.

  5. On the Vectorization of FIR Filterbanks

    Directory of Open Access Journals (Sweden)

    Barbedo Jayme Garcia Arnal

    2007-01-01

    Full Text Available This paper presents a vectorization technique to implement FIR filterbanks. The word vectorization, in the context of this work, refers to a strategy in which all iterative operations are replaced by equivalent vector and matrix operations. This approach allows that the increasing parallelism of the most recent computer processors and systems be properly explored. The vectorization techniques are applied to two kinds of FIR filterbanks (conventional and recursi ve, and are presented in such a way that they can be easily extended to any kind of FIR filterbanks. The vectorization approach is compared to other kinds of implementation that do not explore the parallelism, and also to a previous FIR filter vectorization approach. The tests were performed in Matlab and , in order to explore different aspects of the proposed technique.

  6. On the Vectorization of FIR Filterbanks

    Directory of Open Access Journals (Sweden)

    Amauri Lopes

    2007-01-01

    Full Text Available This paper presents a vectorization technique to implement FIR filterbanks. The word vectorization, in the context of this work, refers to a strategy in which all iterative operations are replaced by equivalent vector and matrix operations. This approach allows that the increasing parallelism of the most recent computer processors and systems be properly explored. The vectorization techniques are applied to two kinds of FIR filterbanks (conventional and recursi ve, and are presented in such a way that they can be easily extended to any kind of FIR filterbanks. The vectorization approach is compared to other kinds of implementation that do not explore the parallelism, and also to a previous FIR filter vectorization approach. The tests were performed in Matlab and C, in order to explore different aspects of the proposed technique.

  7. Design and simulation of MEMS vector hydrophone with reduced cross section based meander beams

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Manoj; Dutta, S.; Pal, Ramjay; Jain, K. K.; Gupta, Sudha; Bhan, R. K. [Solid State Physics Laboratory, DRDO, Lucknow Road, Timarpur, Delhi, India 110054 (India)

    2016-04-13

    MEMS based vector hydrophone is being one of the key device in the underwater communications. In this paper, we presented a bio-inspired MEMS vector hydrophone. The hydrophone structure consists of a proof mass suspended by four meander type beams with reduced cross-section. Modal patterns of the structure were studied. First three modal frequencies of the hydrophone structure were found to be 420 Hz, 420 Hz and 1646 Hz respectively. The deflection and stress of the hydrophone is found have linear behavior in the 1 µPa – 1Pa pressure range.

  8. Problems and worked solutions in vector analysis

    CERN Document Server

    Shorter, LR

    2014-01-01

    ""A handy book like this,"" noted The Mathematical Gazette, ""will fill a great want."" Devoted to fully worked out examples, this unique text constitutes a self-contained introductory course in vector analysis for undergraduate and graduate students of applied mathematics.Opening chapters define vector addition and subtraction, show how to resolve and determine the direction of two or more vectors, and explain systems of coordinates, vector equations of a plane and straight line, relative velocity and acceleration, and infinitely small vectors. The following chapters deal with scalar and vect

  9. Optimizing structure of complex technical system by heterogeneous vector criterion in interval form

    Science.gov (United States)

    Lysenko, A. V.; Kochegarov, I. I.; Yurkov, N. K.; Grishko, A. K.

    2018-05-01

    The article examines the methods of development and multi-criteria choice of the preferred structural variant of the complex technical system at the early stages of its life cycle in the absence of sufficient knowledge of parameters and variables for optimizing this structure. The suggested methods takes into consideration the various fuzzy input data connected with the heterogeneous quality criteria of the designed system and the parameters set by their variation range. The suggested approach is based on the complex use of methods of interval analysis, fuzzy sets theory, and the decision-making theory. As a result, the method for normalizing heterogeneous quality criteria has been developed on the basis of establishing preference relations in the interval form. The method of building preferential relations in the interval form on the basis of the vector of heterogeneous quality criteria suggest the use of membership functions instead of the coefficients considering the criteria value. The former show the degree of proximity of the realization of the designed system to the efficient or Pareto optimal variants. The study analyzes the example of choosing the optimal variant for the complex system using heterogeneous quality criteria.

  10. ROBUSTNESS OF A FACE-RECOGNITION TECHNIQUE BASED ON SUPPORT VECTOR MACHINES

    OpenAIRE

    Prashanth Harshangi; Koshy George

    2010-01-01

    The ever-increasing requirements of security concerns have placed a greater demand for face recognition surveillance systems. However, most current face recognition techniques are not quite robust with respect to factors such as variable illumination, facial expression and detail, and noise in images. In this paper, we demonstrate that face recognition using support vector machines are sufficiently robust to different kinds of noise, does not require image pre-processing, and can be used with...

  11. Towards artificial intelligence based diesel engine performance control under varying operating conditions using support vector regression

    Directory of Open Access Journals (Sweden)

    Naradasu Kumar Ravi

    2013-01-01

    Full Text Available Diesel engine designers are constantly on the look-out for performance enhancement through efficient control of operating parameters. In this paper, the concept of an intelligent engine control system is proposed that seeks to ensure optimized performance under varying operating conditions. The concept is based on arriving at the optimum engine operating parameters to ensure the desired output in terms of efficiency. In addition, a Support Vector Machines based prediction model has been developed to predict the engine performance under varying operating conditions. Experiments were carried out at varying loads, compression ratios and amounts of exhaust gas recirculation using a variable compression ratio diesel engine for data acquisition. It was observed that the SVM model was able to predict the engine performance accurately.

  12. Cosmological evolution in vector-tensor theories of gravity

    International Nuclear Information System (INIS)

    Beltran Jimenez, Jose; Maroto, Antonio L.

    2009-01-01

    We present a detailed study of the cosmological evolution in general vector-tensor theories of gravity without potential terms. We consider the evolution of the vector field throughout the expansion history of the Universe and carry out a classification of models according to the behavior of the vector field in each cosmological epoch. We also analyze the case in which the Universe is dominated by the vector field, performing a complete analysis of the system phase map and identifying those attracting solutions which give rise to accelerated expansion. Moreover, we consider the evolution in a universe filled with a pressureless fluid in addition to the vector field and study the existence of attractors in which we can have a transition from matter domination to vector domination with accelerated expansion so that the vector field may play the role of dark energy. We find that the existence of solutions with late-time accelerated expansion is a generic prediction of vector-tensor theories and that such solutions typically lead to the presence of future singularities. Finally, limits from local gravity tests are used to get constraints on the value of the vector field at small (Solar System) scales.

  13. Biorthogonal vectors, sesquilinear forms, and some physical operators

    Science.gov (United States)

    Bagarello, F.; Inoue, H.; Trapani, C.

    2018-03-01

    Continuing the analysis undertaken in previous articles, we discuss some features of non-self-adjoint operators and sesquilinear forms which are defined starting from two biorthogonal families of vectors, like the so-called generalized Riesz systems, enjoying certain properties. In particular, we discuss what happens when they forms two D -quasi-bases.

  14. Simulation-Based Optimization of a Vector Showerhead System for the Control of Flow Field Profile in a Vertical Reactor Chamber

    Directory of Open Access Journals (Sweden)

    Huanxiong Xia

    2014-03-01

    Full Text Available Optimization of a vector showerhead in a vertical reactor involves thousands of holes on the showerhead face plate and the spatial distribution of physical fields, so parameterizing the geometry configuration of the holes in high resolution is very difficult, which makes the conventional optimization methods hard to deal with. To solve this problem, a profile error feedback (PEF optimization solution was proposed to optimize a vector showerhead gas delivery system for the control of mass transport. The gas velocity profile in the reactor and the continuous-feature impedance distribution profile on the showerhead face plate are defined as design objective and variables, respectively. A cyclic iterative approximation idea was implemented in this solution. The algorithm was started from a guessed initial design model and then cyclically adjusted the design variables by the constructed PEF iterative formula to generate a better model and to make the gas velocity profile in the critical domain of the new model continually approximate to the expected profile, until it could be accepted. Finally, the optimized impedance profile was mapped to the holes geometry configuration through the established equivalent impedance model for the showerhead face plate.

  15. A program system for ab initio MO calculations on vector and parallel processing machines. Pt. 1

    International Nuclear Information System (INIS)

    Ernenwein, R.; Rohmer, M.M.; Benard, M.

    1990-01-01

    We present a program system for ab initio molecular orbital calculations on vector and parallel computers. The present article is devoted to the computation of one- and two-electron integrals over contracted Gaussian basis sets involving s-, p-, d- and f-type functions. The McMurchie and Davidson (MMD) algorithm has been implemented and parallelized by distributing over a limited number of logical tasks the calculation of the 55 relevant classes of integrals. All sections of the MMD algorithm have been efficiently vectorized, leading to a scalar/vector ratio of 5.8. Different algorithms are proposed and compared for an optimal vectorization of the contraction of the 'intermediate integrals' generated by the MMD formalism. Advantage is taken of the dynamic storage allocation for tuning the length of the vector loops (i.e. the size of the vectorization buffer) as a function of (i) the total memory available for the job, (ii) the number of logical tasks defined by the user (≤13), and (iii) the storage requested by each specific class of integrals. Test calculations carried out on a CRAY-2 computer show that the average number of finite integrals computed over a (s, p, d, f) CGTO basis set is about 1180000 per second and per processor. The combination of vectorization and parallelism on this 4-processor machine reduces the CPU time by a factor larger than 20 with respect to the scalar and sequential performance. (orig.)

  16. A Support Vector Machine-Based Gender Identification Using Speech Signal

    Science.gov (United States)

    Lee, Kye-Hwan; Kang, Sang-Ick; Kim, Deok-Hwan; Chang, Joon-Hyuk

    We propose an effective voice-based gender identification method using a support vector machine (SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model (GMM)-based method using the mel frequency cepstral coefficients (MFCC). A novel approach of incorporating a features fusion scheme based on a combination of the MFCC and the fundamental frequency is proposed with the aim of improving the performance of gender identification. Experimental results demonstrate that the gender identification performance using the SVM is significantly better than that of the GMM-based scheme. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

  17. Vectoring of parallel synthetic jets

    Science.gov (United States)

    Berk, Tim; Ganapathisubramani, Bharathram; Gomit, Guillaume

    2015-11-01

    A pair of parallel synthetic jets can be vectored by applying a phase difference between the two driving signals. The resulting jet can be merged or bifurcated and either vectored towards the actuator leading in phase or the actuator lagging in phase. In the present study, the influence of phase difference and Strouhal number on the vectoring behaviour is examined experimentally. Phase-locked vorticity fields, measured using Particle Image Velocimetry (PIV), are used to track vortex pairs. The physical mechanisms that explain the diversity in vectoring behaviour are observed based on the vortex trajectories. For a fixed phase difference, the vectoring behaviour is shown to be primarily influenced by pinch-off time of vortex rings generated by the synthetic jets. Beyond a certain formation number, the pinch-off timescale becomes invariant. In this region, the vectoring behaviour is determined by the distance between subsequent vortex rings. We acknowledge the financial support from the European Research Council (ERC grant agreement no. 277472).

  18. Problems of vector Lagrangians in field theories

    International Nuclear Information System (INIS)

    Krivsky, I.Yu.; Simulik, V.M.

    1997-01-01

    A vector Lagrange approach to the Dirac spinor field and the relationship between the vector Lagrangians for the spinor and electromagnetic fields are considered. A vector Lagrange approach for the system of interacting electromagnetic B=(B μ υ)=(E-bar,H-bar) and spinor Ψ fields is constructed. New Lagrangians (scalar and vector) for electromagnetic field in terms of field strengths are found. The foundations of two new QED models are formulated

  19. VectorH : Taking SQL-on-Hadoop to the next level

    NARCIS (Netherlands)

    Costea, Andrei; Ionescu, Adrian; Raducanu, Bogdan; Świtakowski, Michał; Bârca, Cristian; Sompolski, Juliusz; Łuszczak, Alicja; Szafrański, Michał; De Nijs, Giel; Boncz, Peter

    2016-01-01

    Actian Vector in Hadoop (VectorH for short) is a new SQL-on-Hadoop system built on top of the fast Vectorwise analytical database system. VectorH achieves fault tolerance and storage scalability by relying on HDFS, and extends the state-of-the-art in SQL-on-Hadoop systems by instrumenting the HDFS

  20. Leak Location of Pipeline with Multibranch Based on a Cyber-Physical System

    Directory of Open Access Journals (Sweden)

    Xianming Lang

    2017-09-01

    Full Text Available Data cannot be shared and leakage cannot be located simultaneously among multiple pipeline leak detection systems. Based on cyber-physical system (CPS architecture, the method for locating leakage for pipelines with multibranch is proposed. The singular point of pressure signals at the ends of pipeline with multibranch is analyzed by wavelet packet analysis, so that the time feature samples could be established. Then, the Fischer-Burmeister function is introduced into the learning process of the twin support vector machine (TWSVM in order to avoid the matrix inversion calculation, and the samples are input into the improved twin support vector machine (ITWSVM to distinguish the pipeline leak location. The simulation results show that the proposed method is more effective than the back propagation (BP neural networks, the radial basis function (RBF neural networks, and the Lagrange twin support vector machine.

  1. BoHV-4-based vector delivering Ebola virus surface glycoprotein

    Directory of Open Access Journals (Sweden)

    Alfonso Rosamilia

    2016-11-01

    Full Text Available Abstract Background Ebola virus (EBOV is a Category A pathogen that is a member of Filoviridae family that causes hemorrhagic fever in humans and non-human primates. Unpredictable and devastating outbreaks of disease have recently occurred in Africa and current immunoprophylaxis and therapies are limited. The main limitation of working with pathogens like EBOV is the need for costly containment. To potentiate further and wider opportunity for EBOV prophylactics and therapies development, innovative approaches are necessary. Methods In the present study, an antigen delivery platform based on a recombinant bovine herpesvirus 4 (BoHV-4, delivering a synthetic EBOV glycoprotein (GP gene sequence, BoHV-4-syEBOVgD106ΔTK, was generated. Results EBOV GP was abundantly expressed by BoHV-4-syEBOVgD106ΔTK transduced cells without decreasing viral replication. BoHV-4-syEBOVgD106ΔTK immunized goats produced high titers of anti-EBOV GP antibodies and conferred a long lasting (up to 6 months, detectable antibody response. Furthermore, no evidence of BoHV-4-syEBOVgD106ΔTK viremia and secondary localization was detected in any of the immunized animals. Conclusions The BoHV-4-based vector approach described here, represents: an alternative antigen delivery system for vaccination and a proof of principle study for anti-EBOV antibodies generation in goats for potential immunotherapy applications.

  2. Vectorization, parallelization and porting of nuclear codes on the VPP500 system (parallelization). Progress report fiscal 1996

    Energy Technology Data Exchange (ETDEWEB)

    Watanabe, Hideo; Kawai, Wataru; Nemoto, Toshiyuki [Fujitsu Ltd., Tokyo (Japan); and others

    1997-12-01

    Several computer codes in the nuclear field have been vectorized, parallelized and transported on the FUJITSU VPP500 system at Center for Promotion of Computational Science and Engineering in Japan Atomic Energy Research Institute. These results are reported in 3 parts, i.e., the vectorization part, the parallelization part and the porting part. In this report, we describe the parallelization. In this parallelization part, the parallelization of 2-Dimensional relativistic electromagnetic particle code EM2D, Cylindrical Direct Numerical Simulation code CYLDNS and molecular dynamics code for simulating radiation damages in diamond crystals DGR are described. In the vectorization part, the vectorization of two and three dimensional discrete ordinates simulation code DORT-TORT, gas dynamics analysis code FLOWGR and relativistic Boltzmann-Uehling-Uhlenbeck simulation code RBUU are described. And then, in the porting part, the porting of reactor safety analysis code RELAP5/MOD3.2 and RELAP5/MOD3.2.1.2, nuclear data processing system NJOY and 2-D multigroup discrete ordinate transport code TWOTRAN-II are described. And also, a survey for the porting of command-driven interactive data analysis plotting program IPLOT are described. (author)

  3. Vectorization, parallelization and porting of nuclear codes on the VPP500 system (porting). Progress report fiscal 1996

    Energy Technology Data Exchange (ETDEWEB)

    Nemoto, Toshiyuki [Fujitsu Ltd., Tokyo (Japan); Kawasaki, Nobuo; Tanabe, Hidenobu [and others

    1998-01-01

    Several computer codes in the nuclear field have been vectorized, parallelized and transported on the FUJITSU VPP500 system at Center for Promotion of Computational Science and Engineering in Japan Atomic Energy Research Institute. These results are reported in 3 parts, i.e., the vectorization part, the parallelization part and the porting part. In this report, we describe the porting. In this porting part, the porting of reactor safety analysis code RELAP5/MOD3.2 and RELAP5/MOD3.2.1.2, nuclear data processing system NJOY and 2-D multigroup discrete ordinate transport code TWOTRAN-II are described. And also, a survey for the porting of command-driven interactive data analysis plotting program IPLOT are described. In the parallelization part, the parallelization of 2-Dimensional relativistic electromagnetic particle code EM2D, Cylindrical Direct Numerical Simulation code CYLDNS and molecular dynamics code for simulating radiation damages in diamond crystals DGR are described. And then, in the vectorization part, the vectorization of two and three dimensional discrete ordinates simulation code DORT-TORT, gas dynamics analysis code FLOWGR and relativistic Boltzmann-Uehling-Uhlenbeck simulation code RBUU are described. (author)

  4. Graphene materials as 2D non-viral gene transfer vector platforms.

    Science.gov (United States)

    Vincent, M; de Lázaro, I; Kostarelos, K

    2017-03-01

    Advances in genomics and gene therapy could offer solutions to many diseases that remain incurable today, however, one of the critical reasons halting clinical progress is due to the difficulty in designing efficient and safe delivery vectors for the appropriate genetic cargo. Safety and large-scale production concerns counter-balance the high gene transfer efficiency achieved with viral vectors, while non-viral strategies have yet to become sufficiently efficient. The extraordinary physicochemical, optical and photothermal properties of graphene-based materials (GBMs) could offer two-dimensional components for the design of nucleic acid carrier systems. We discuss here such properties and their implications for the optimization of gene delivery. While the design of such vectors is still in its infancy, we provide here an exhaustive and up-to-date analysis of the studies that have explored GBMs as gene transfer vectors, focusing on the functionalization strategies followed to improve vector performance and on the biological effects attained.

  5. Heterologous protein secretion in Lactobacilli with modified pSIP vectors.

    Directory of Open Access Journals (Sweden)

    Ingrid Lea Karlskås

    Full Text Available We describe new variants of the modular pSIP-vectors for inducible gene expression and protein secretion in lactobacilli. The basic functionality of the pSIP system was tested in Lactobacillus strains representing 14 species using pSIP411, which harbors the broad-host-range Lactococcus lactis SH71rep replicon and a β-glucuronidase encoding reporter gene. In 10 species, the inducible gene expression system was functional. Based on these results, three pSIP vectors with different signal peptides were modified by replacing their narrow-host-range L. plantarum 256rep replicon with SH71rep and transformed into strains of five different species of Lactobacillus. All recombinant strains secreted the target protein NucA, albeit with varying production levels and secretion efficiencies. The Lp_3050 derived signal peptide generally resulted in the highest levels of secreted NucA. These modified pSIP vectors are useful tools for engineering a wide variety of Lactobacillus species.

  6. 3D simulation of a MACH 3 Thrust Vector Control system

    International Nuclear Information System (INIS)

    Rainville, P.A.; DeChamplain, A.; Kretschmer, D.; Farinaccio, R.; Stowe, R.

    2002-01-01

    The purpose of a Thrust Vector Control (TVC) system is to allow directional control of a flight vehicle through the use of jet vanes acting on the exhaust plume of the motor. The objective of this study was to validate the commercial code Fluent for the simulation of the unsteady flow field within the nozzle of a solid propellant rocket motor equipped with TVC. The experimental data for the validation of Fluent were based on time-dependent test results completed at Defence R and D Canada - Valcartier (DRDC Valcartier). These experimental results include several parameters for the solid propellant motor that establish the operating conditions for the numerical simulation of the TVC system. With the preliminary numerical results from meshes of the original vane geometry (before subsequent essential modifications), the temperature deep inside the vane was generally underestimated. For the temperature predictions closer to the base of the vane where it is attached to the nozzle wall, the results were slightly higher than the experimental values. This would be caused by an oblique shock wave that strikes the vane at a different location with the modified geometry compared to the original geometry, and therefore causes substantial changes to the internal temperature field of the vane. The grid resolution for the vane boundary layer could also be a reason for these discrepancies. Further simulations are therefore underway to resolve these issues with the modified geometry and a more refined boundary layer. (author)

  7. Condition Assessment of Foundation Piles and Utility Poles Based on Guided Wave Propagation Using a Network of Tactile Transducers and Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Ulrike Dackermann

    2017-12-01

    Full Text Available This paper presents a novel non-destructive testing and health monitoring system using a network of tactile transducers and accelerometers for the condition assessment and damage classification of foundation piles and utility poles. While in traditional pile integrity testing an impact hammer with broadband frequency excitation is typically used, the proposed testing system utilizes an innovative excitation system based on a network of tactile transducers to induce controlled narrow-band frequency stress waves. Thereby, the simultaneous excitation of multiple stress wave types and modes is avoided (or at least reduced, and targeted wave forms can be generated. The new testing system enables the testing and monitoring of foundation piles and utility poles where the top is inaccessible, making the new testing system suitable, for example, for the condition assessment of pile structures with obstructed heads and of poles with live wires. For system validation, the new system was experimentally tested on nine timber and concrete poles that were inflicted with several types of damage. The tactile transducers were excited with continuous sine wave signals of 1 kHz frequency. Support vector machines were employed together with advanced signal processing algorithms to distinguish recorded stress wave signals from pole structures with different types of damage. The results show that using fast Fourier transform signals, combined with principal component analysis as the input feature vector for support vector machine (SVM classifiers with different kernel functions, can achieve damage classification with accuracies of 92.5% ± 7.5%.

  8. Image reconstruction for an electrical capacitance tomography system based on a least-squares support vector machine and a self-adaptive particle swarm optimization algorithm

    International Nuclear Information System (INIS)

    Chen, Xia; Hu, Hong-li; Liu, Fei; Gao, Xiang Xiang

    2011-01-01

    The task of image reconstruction for an electrical capacitance tomography (ECT) system is to determine the permittivity distribution and hence the phase distribution in a pipeline by measuring the electrical capacitances between sets of electrodes placed around its periphery. In view of the nonlinear relationship between the permittivity distribution and capacitances and the limited number of independent capacitance measurements, image reconstruction for ECT is a nonlinear and ill-posed inverse problem. To solve this problem, a new image reconstruction method for ECT based on a least-squares support vector machine (LS-SVM) combined with a self-adaptive particle swarm optimization (PSO) algorithm is presented. Regarded as a special small sample theory, the SVM avoids the issues appearing in artificial neural network methods such as difficult determination of a network structure, over-learning and under-learning. However, the SVM performs differently with different parameters. As a relatively new population-based evolutionary optimization technique, PSO is adopted to realize parameters' effective selection with the advantages of global optimization and rapid convergence. This paper builds up a 12-electrode ECT system and a pneumatic conveying platform to verify this image reconstruction algorithm. Experimental results indicate that the algorithm has good generalization ability and high-image reconstruction quality

  9. vSmartMOM: A vector matrix operator method-based radiative transfer model linearized with respect to aerosol properties

    International Nuclear Information System (INIS)

    Sanghavi, Suniti; Davis, Anthony B.; Eldering, Annmarie

    2014-01-01

    In this paper, we build up on the scalar model smartMOM to arrive at a formalism for linearized vector radiative transfer based on the matrix operator method (vSmartMOM). Improvements have been made with respect to smartMOM in that a novel method of computing intensities for the exact viewing geometry (direct raytracing) without interpolation between quadrature points has been implemented. Also, the truncation method employed for dealing with highly peaked phase functions has been changed to a vector adaptation of Wiscombe's delta-m method. These changes enable speedier and more accurate radiative transfer computations by eliminating the need for a large number of quadrature points and coefficients for generalized spherical functions. We verify our forward model against the benchmarking results of Kokhanovsky et al. (2010) [22]. All non-zero Stokes vector elements are found to show agreement up to mostly the seventh significant digit for the Rayleigh atmosphere. Intensity computations for aerosol and cloud show an agreement of well below 0.03% and 0.05% at all viewing angles except around the solar zenith angle (60°), where most radiative models demonstrate larger variances due to the strongly forward-peaked phase function. We have for the first time linearized vector radiative transfer based on the matrix operator method with respect to aerosol optical and microphysical parameters. We demonstrate this linearization by computing Jacobian matrices for all Stokes vector elements for a multi-angular and multispectral measurement setup. We use these Jacobians to compare the aerosol information content of measurements using only the total intensity component against those using the idealized measurements of full Stokes vector [I,Q,U,V] as well as the more practical use of only [I,Q,U]. As expected, we find for the considered example that the accuracy of the retrieved parameters improves when the full Stokes vector is used. The information content for the full Stokes

  10. Datum Feature Extraction and Deformation Analysis Method Based on Normal Vector of Point Cloud

    Science.gov (United States)

    Sun, W.; Wang, J.; Jin, F.; Liang, Z.; Yang, Y.

    2018-04-01

    In order to solve the problem lacking applicable analysis method in the application of three-dimensional laser scanning technology to the field of deformation monitoring, an efficient method extracting datum feature and analysing deformation based on normal vector of point cloud was proposed. Firstly, the kd-tree is used to establish the topological relation. Datum points are detected by tracking the normal vector of point cloud determined by the normal vector of local planar. Then, the cubic B-spline curve fitting is performed on the datum points. Finally, datum elevation and the inclination angle of the radial point are calculated according to the fitted curve and then the deformation information was analyzed. The proposed approach was verified on real large-scale tank data set captured with terrestrial laser scanner in a chemical plant. The results show that the method could obtain the entire information of the monitor object quickly and comprehensively, and reflect accurately the datum feature deformation.

  11. Registration of Urban Aerial Image and LiDAR Based on Line Vectors

    Directory of Open Access Journals (Sweden)

    Qinghong Sheng

    2017-09-01

    Full Text Available In a traditional registration of a single aerial image with airborne light detection and ranging (LiDAR data using linear features that regard line direction as a control or linear features as constraints in the solution, lacking the constraint of linear position leads to the error propagation of the adjustment model. To solve this problem, this paper presents a line vector-based registration mode (LVR in which image rays and LiDAR lines are expressed by a line vector that integrates the line direction and the line position. A registration equation of line vector is set up by coplanar imaging rays and corresponding control lines. Three types of datasets consisting of synthetic, theInternational Society for Photogrammetry and Remote Sensing (ISPRS test project, and real aerial data are used. A group of progressive experiments is undertaken to evaluate the robustness of the LVR. Experimental results demonstrate that the integrated line direction and the line position contributes a great deal to the theoretical and real accuracies of the unknowns, as well as the stability of the adjustment model. This paper provides a new suggestion that, for a single image and LiDAR data, registration in urban areas can be accomplished by accommodating rich line features.

  12. Acute evaluation of transthoracic impedance vectors using ICD leads.

    Science.gov (United States)

    Gottfridsson, Christer; Daum, Douglas; Kennergren, Charles; Ramuzat, Agnès; Willems, Roger; Edvardsson, Nils

    2009-06-01

    Minute ventilation (MV) has been proven to be very useful in rate responsive pacing. The aim of this study was to evaluate the feasibility of using implantable cardioverter-defibrillator (ICD) leads as part of the MV detection system. At implant in 10 patients, the transthoracic impedance was measured from tripolar ICD, tetrapolar ICD, and atrial lead vectors during normal, deep, and shallow voluntary respiration. MV and respiration rate (RespR) were simultaneously measured through a facemask with a pneumotachometer (Korr), and the correlations with impedance-based measurements were calculated. Air sensitivity was the change in impedance per change in respiratory tidal volume, ohms (Omega)/liter (L), and the signal-to-noise ratio (SNR) was the ratio of the respiratory and cardiac contraction components. The air sensitivity and SNR in tripolar ICD vector were 2.70 +/- 2.73 ohm/L and 2.19 +/- 1.31, respectively, and were not different from tetrapolar. The difference in RespR between tripolar ICD and Korr was 0.2 +/- 1.91 breaths/minute. The regressed correlation coefficient between impedance MV and Korr MV was 0.86 +/- 0.07 in tripolar ICD. The air sensitivity and SNR in tripolar and tetrapolar ICD lead vectors did not differ significantly and were in the range of the values in pacemaker leads currently used as MV sensors. The good correlations between impedance-based and Korr-based RespR and MV measurements imply that ICD leads may be used in MV sensor systems.

  13. Vectorization in quantum chemistry

    International Nuclear Information System (INIS)

    Saunders, V.R.

    1987-01-01

    It is argued that the optimal vectorization algorithm for many steps (and sub-steps) in a typical ab initio calculation of molecular electronic structure is quite strongly dependent on the target vector machine. Details such as the availability (or lack) of a given vector construct in the hardware, vector startup times and asymptotic rates must all be considered when selecting the optimal algorithm. Illustrations are drawn from: gaussian integral evaluation, fock matrix construction, 4-index transformation of molecular integrals, direct-CI methods, the matrix multiply operation. A cross comparison of practical implementations on the CDC Cyber 205, the Cray-IS and Cray-XMP machines is presented. To achieve portability while remaining optimal on a wide range of machines it is necessary to code all available algorithms in a machine independent manner, and to select the appropriate algorithm using a procedure which is based on machine dependent parameters. Most such parameters concern the timing of certain vector loop kernals, which can usually be derived from a 'bench-marking' routine executed prior to the calculation proper

  14. A gene delivery system with a human artificial chromosome vector based on migration of mesenchymal stem cells towards human glioblastoma HTB14 cells.

    Science.gov (United States)

    Kinoshita, Yusuke; Kamitani, Hideki; Mamun, Mahabub Hasan; Wasita, Brian; Kazuki, Yasuhiro; Hiratsuka, Masaharu; Oshimura, Mitsuo; Watanabe, Takashi

    2010-05-01

    Mesenchymal stem cells (MSCs) have been expected to become useful gene delivery vehicles against human malignant gliomas when coupled with an appropriate vector system, because they migrate towards the lesion. Human artificial chromosomes (HACs) are non-integrating vectors with several advantages for gene therapy, namely, no limitations on the size and number of genes that can be inserted. We investigated the migration of human immortalized MSCs bearing a HAC vector containing the herpes simplex virus thymidine kinase gene (HAC-tk-hiMSCs) towards malignant gliomas in vivo. Red fluorescence protein-labeled human glioblastoma HTB14 cells were implanted into a subcortical region in nude mice. Four days later, green fluorescence protein-labeled HAC-tk-hiMSCs were injected into a contralateral subcortical region (the HTB14/HAC-tk-hiMSC injection model). Tropism to the glioma mass and the route of migration were visualized by fluorescence microscopy and immunohistochemical staining. HAC-tk-hiMSCs began to migrate toward the HTB14 glioma area via the corpus callosum on day 4, and gathered around the HTB14 glioma mass on day 7. To test whether the delivered gene could effectively treat glioblastoma in vivo, HTB14/HAC-tk-hiMSC injected mice were treated with ganciclovir (GCV) or PBS. The HTB14 glioma mass was significantly reduced by GCV treatment in mice injected with HAC-tk-hiMSCs. It was confirmed that gene delivery by our HAC-hiMSC system was effective after migration of MSCs to the glioma mass in vivo. Therefore, MSCs containing HACs carrying an anticancer gene or genes may provide a new tool for the treatment of malignant gliomas and possibly of other tumor types.

  15. [New strategy for RNA vectorization in mammalian cells. Use of a peptide vector].

    Science.gov (United States)

    Vidal, P; Morris, M C; Chaloin, L; Heitz, F; Divita, G

    1997-04-01

    A major barrier for gene delivery is the low permeability of nucleic acids to cellular membranes. The development of antisenses and gene therapy has focused mainly on improving methods of oligonucleotide or gene delivery to the cell. In this report we described a new strategy for RNA cell delivery, based on a short single peptide. This peptide vector is derived from both the fusion domain of the gp41 protein of HIV and the nuclear localization sequence of the SV40 large T antigen. This peptide vector localizes rapidly to the cytoplasm then to the nucleus of human fibroblasts (HS-68) within a few minutes and exhibits a high affinity for a single-stranded mRNA encoding the p66 subunit of the HIV-1 reverse transcriptase (in a 100 nM range). The peptide/RNA complex formation involves mainly electrostatic interactions between the basic residues of the peptide and the charges on the phosphate group of the RNA. In the presence of the peptide-vector fluorescently-labelled mRNA is delivered into the cytoplasm of mammalian cells (HS68 human fibroblasts) in less than 1 h with a relatively high efficiency (80%). This new concept based on a peptide-derived vector offers several advantages compared to other compounds commonly used in gene delivery. This vector is highly soluble and exhibits no cytotoxicity at the concentrations used for optimal gene delivery. This result clearly supports the fact that this peptide vector is a powerful tool and that it can be used widely, as much for laboratory research as for new applications and development in gene and/or antisense therapy.

  16. Using adaptive network based fuzzy inference system to forecast regional electricity loads

    International Nuclear Information System (INIS)

    Ying, L.-C.; Pan, M.-C.

    2008-01-01

    Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads

  17. Using adaptive network based fuzzy inference system to forecast regional electricity loads

    Energy Technology Data Exchange (ETDEWEB)

    Ying, Li-Chih [Department of Marketing Management, Central Taiwan University of Science and Technology, 11, Pu-tzu Lane, Peitun, Taichung City 406 (China); Pan, Mei-Chiu [Graduate Institute of Management Sciences, Nanhua University, 32, Chung Keng Li, Dalin, Chiayi 622 (China)

    2008-02-15

    Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads. (author)

  18. In situ vector calibration of magnetic observatories

    Directory of Open Access Journals (Sweden)

    A. Gonsette

    2017-09-01

    Full Text Available The goal of magnetic observatories is to measure and provide a vector magnetic field in a geodetic coordinate system. For that purpose, instrument set-up and calibration are crucial. In particular, the scale factor and orientation of a vector magnetometer may affect the magnetic field measurement. Here, we highlight the baseline concept and demonstrate that it is essential for data quality control. We show how the baselines can highlight a possible calibration error. We also provide a calibration method based on high-frequency absolute measurements. This method determines a transformation matrix for correcting variometer data suffering from scale factor and orientation errors. We finally present a practical case where recovered data have been successfully compared to those coming from a reference magnetometer.

  19. Screw-vector bond graphs for kinetic-static modelling and analysis of mechanisms

    International Nuclear Information System (INIS)

    Bidard, Catherine

    1994-01-01

    This dissertation deals with the kinetic-static modelling and analysis of spatial mechanisms used in robotics systems. A framework is proposed, which embodies a geometrical and a network approach for kinetic-static modelling. For this purpose we use screw theory and bond graphs. A new form of bond graphs is introduced: the screw-vector bond graph, whose power variables are defined to be wrenches and twists expressed as intrinsic screw-vectors. The mechanism is then identified as a network, whose components are kinematic pairs and whose topology is described by a directed graph. A screw-vector Simple Junction Structure represents the topological constraints. Kinematic pairs are represented by one-port elements, defined by two reciprocal screw-vector spaces. Using dual bases of screw-vectors, a generic decomposition of kinematic pair elements is given. The reduction of kinetic-static models of series and parallel kinematic chains is used in order to derive kinetic-static functional models in geometric form. Thereupon, the computational causality assignment is adapted for the graphical analysis of the mobility and the functioning of spatial mechanisms, based on completely or incompletely specified models. (author) [fr

  20. Matrix-Vector Based Fast Fourier Transformations on SDR Architectures

    Directory of Open Access Journals (Sweden)

    Y. He

    2008-05-01

    Full Text Available Today Discrete Fourier Transforms (DFTs are applied in various radio standards based on OFDM (Orthogonal Frequency Division Multiplex. It is important to gain a fast computational speed for the DFT, which is usually achieved by using specialized Fast Fourier Transform (FFT engines. However, in face of the Software Defined Radio (SDR development, more general (parallel processor architectures are often desirable, which are not tailored to FFT computations. Therefore, alternative approaches are required to reduce the complexity of the DFT. Starting from a matrix-vector based description of the FFT idea, we will present different factorizations of the DFT matrix, which allow a reduction of the complexity that lies between the original DFT and the minimum FFT complexity. The computational complexities of these factorizations and their suitability for implementation on different processor architectures are investigated.

  1. Space vector modulation strategy for neutral-point voltage balancing in three-level inverter systems

    DEFF Research Database (Denmark)

    Choi, Uimin; Lee, Kyo Beum

    2013-01-01

    This study proposes a space vector modulation (SVM) strategy to balance the neutral-point voltage of three-level inverter systems. The proposed method is implemented by combining conventional symmetric SVM with nearest three-vector (NTV) modulation. The conventional SVM is converted to NTV...... modulation by properly adding or subtracting a minimum gate-on time. In addition, using this method, the switching frequency is reduced and a decrease of switching loss would be yielded. The neutral-point voltage is balanced by the proposed SVM strategy without additional hardware or complex calculations....... Simulation and experimental results are shown to verify the validity and feasibility of the proposed SVM strategy....

  2. A vector radiative transfer model for coupled atmosphere and ocean systems with a rough interface

    International Nuclear Information System (INIS)

    Zhai Pengwang; Hu Yongxiang; Chowdhary, Jacek; Trepte, Charles R.; Lucker, Patricia L.; Josset, Damien B.

    2010-01-01

    We report on an exact vector (polarized) radiative transfer (VRT) model for coupled atmosphere and ocean systems. This VRT model is based on the successive order of scattering (SOS) method, which virtually takes all the multiple scattering processes into account, including atmospheric scattering, oceanic scattering, reflection and transmission through the rough ocean surface. The isotropic Cox-Munk wave model is used to derive the ref and transmission matrices for the rough ocean surface. Shadowing effects are included by the shadowing function. We validated the SOS results by comparing them with those calculated by two independent codes based on the doubling/adding and Monte Carlo methods. Two error analyses related to the ocean color remote sensing are performed in the coupled atmosphere and ocean systems. One is the scalar error caused by ignoring the polarization in the whole system. The other is the error introduced by ignoring the polarization of the light transmitted through the ocean interface. Both errors are significant for the cases studied. This code fits for the next generation of ocean color study because it converges fast for absorbing medium as, for instance, ocean.

  3. Construction of an expression vector for Lactococcus lactis based on ...

    African Journals Online (AJOL)

    To construct an expression vector for Lactococcus lactis, the EmPMT fragment which contained the erythromycin resistance gene, P32 promoter, multiple cloning site (MCS) and terminator (T) was subcloned into the small cryptic plasmid pAR141. The resulting vector, designated as pAR1411, was found to be stably ...

  4. A regression-based Kansei engineering system based on form feature lines for product form design

    Directory of Open Access Journals (Sweden)

    Yan Xiong

    2016-06-01

    Full Text Available When developing new products, it is important for a designer to understand users’ perceptions and develop product form with the corresponding perceptions. In order to establish the mapping between users’ perceptions and product design features effectively, in this study, we presented a regression-based Kansei engineering system based on form feature lines for product form design. First according to the characteristics of design concept representation, product form features–product form feature lines were defined. Second, Kansei words were chosen to describe image perceptions toward product samples. Then, multiple linear regression and support vector regression were used to construct the models, respectively, that predicted users’ image perceptions. Using mobile phones as experimental samples, Kansei prediction models were established based on the front view form feature lines of the samples. From the experimental results, these two predict models were of good adaptability. But in contrast to multiple linear regression, the predict performance of support vector regression model was better, and support vector regression is more suitable for form regression prediction. The results of the case showed that the proposed method provided an effective means for designers to manipulate product features as a whole, and it can optimize Kansei model and improve practical values.

  5. GNSS-based multi-sensor system for structural monitoring applications

    Science.gov (United States)

    Bogusz, Janusz; Figurski, Mariusz; Nykiel, Grzegorz; Szolucha, Marcin; Wrona, Maciej

    2012-03-01

    In 2007 the Centre of Applied Geomatics of the Military University of Technology started measurements aimed at the monitoring of the dynamic state of the engineering structures using GNSS. The complexity of the problem forced us to apply an integrated system architecture. This concept is based on simultaneous measuring some selected elements of the structure using various types of sensors. Measurement information from numerous instruments is numerically integrated for determining the investigated parameter, e.g., the displacement vector. The CAG team performed the tests using such a system on the two permanent 500-meters long bridges, the temporary bridge crossing for military purposes and the 300-meters high chimney of the CHP station. The information about displacement vector together with the characteristic frequencies of the structure were determined using different techniques for increasing of its reliability. This paper presents the results of such tests, gives description of the integrated system designed in the CAG and brings forward with the plans for the future.

  6. An exotic composite vector boson

    International Nuclear Information System (INIS)

    Akama, Keiichi; Hattori, Takashi; Yasue, Masaki.

    1990-08-01

    An exotic composite vector boson, V, is introduced in two dynamical models of composite quarks, leptons, W and Z. One is based on four Fermi interactions, in which composite vector bosons are regarded as fermion-antifermion bound states and the other is based on the confining SU(2) L gauge model, in which they are given by scalar-antiscalar bound states. Both approaches describe the same effective interactions for the sector of composite quarks, leptons, W, Z, γ and V. (author)

  7. Support vector machine-based facial-expression recognition method combining shape and appearance

    Science.gov (United States)

    Han, Eun Jung; Kang, Byung Jun; Park, Kang Ryoung; Lee, Sangyoun

    2010-11-01

    Facial expression recognition can be widely used for various applications, such as emotion-based human-machine interaction, intelligent robot interfaces, face recognition robust to expression variation, etc. Previous studies have been classified as either shape- or appearance-based recognition. The shape-based method has the disadvantage that the individual variance of facial feature points exists irrespective of similar expressions, which can cause a reduction of the recognition accuracy. The appearance-based method has a limitation in that the textural information of the face is very sensitive to variations in illumination. To overcome these problems, a new facial-expression recognition method is proposed, which combines both shape and appearance information, based on the support vector machine (SVM). This research is novel in the following three ways as compared to previous works. First, the facial feature points are automatically detected by using an active appearance model. From these, the shape-based recognition is performed by using the ratios between the facial feature points based on the facial-action coding system. Second, the SVM, which is trained to recognize the same and different expression classes, is proposed to combine two matching scores obtained from the shape- and appearance-based recognitions. Finally, a single SVM is trained to discriminate four different expressions, such as neutral, a smile, anger, and a scream. By determining the expression of the input facial image whose SVM output is at a minimum, the accuracy of the expression recognition is much enhanced. The experimental results showed that the recognition accuracy of the proposed method was better than previous researches and other fusion methods.

  8. A vector-based system for the differentiation of mouse embryonic stem cells toward germ-line cells

    Directory of Open Access Journals (Sweden)

    Reza Ebrahimzadeh-Vesal

    2014-08-01

    Conclusion: In this study, we demonstrated the in vitro generation of mouse embryonic stem cells to germ cells by using a backbone vector containing the fusion gene Stra8-EGFP. The Stra8 gene is a retinoic acid-responsive protein and is able to regulate meiotic initiation.

  9. 3D Model Retrieval Based on Vector Quantisation Index Histograms

    International Nuclear Information System (INIS)

    Lu, Z M; Luo, H; Pan, J S

    2006-01-01

    This paper proposes a novel technique to retrieval 3D mesh models using vector quantisation index histograms. Firstly, points are sampled uniformly on mesh surface. Secondly, to a point five features representing global and local properties are extracted. Thus feature vectors of points are obtained. Third, we select several models from each class, and employ their feature vectors as a training set. After training using LBG algorithm, a public codebook is constructed. Next, codeword index histograms of the query model and those in database are computed. The last step is to compute the distance between histograms of the query and those of the models in database. Experimental results show the effectiveness of our method

  10. Emerging Vector-Borne Diseases - Incidence through Vectors.

    Science.gov (United States)

    Savić, Sara; Vidić, Branka; Grgić, Zivoslav; Potkonjak, Aleksandar; Spasojevic, Ljubica

    2014-01-01

    Vector-borne diseases use to be a major public health concern only in tropical and subtropical areas, but today they are an emerging threat for the continental and developed countries also. Nowadays, in intercontinental countries, there is a struggle with emerging diseases, which have found their way to appear through vectors. Vector-borne zoonotic diseases occur when vectors, animal hosts, climate conditions, pathogens, and susceptible human population exist at the same time, at the same place. Global climate change is predicted to lead to an increase in vector-borne infectious diseases and disease outbreaks. It could affect the range and population of pathogens, host and vectors, transmission season, etc. Reliable surveillance for diseases that are most likely to emerge is required. Canine vector-borne diseases represent a complex group of diseases including anaplasmosis, babesiosis, bartonellosis, borreliosis, dirofilariosis, ehrlichiosis, and leishmaniosis. Some of these diseases cause serious clinical symptoms in dogs and some of them have a zoonotic potential with an effect to public health. It is expected from veterinarians in coordination with medical doctors to play a fundamental role at primarily prevention and then treatment of vector-borne diseases in dogs. The One Health concept has to be integrated into the struggle against emerging diseases. During a 4-year period, from 2009 to 2013, a total number of 551 dog samples were analyzed for vector-borne diseases (borreliosis, babesiosis, ehrlichiosis, anaplasmosis, dirofilariosis, and leishmaniasis) in routine laboratory work. The analysis was done by serological tests - ELISA for borreliosis, dirofilariosis, and leishmaniasis, modified Knott test for dirofilariosis, and blood smear for babesiosis, ehrlichiosis, and anaplasmosis. This number of samples represented 75% of total number of samples that were sent for analysis for different diseases in dogs. Annually, on average more then half of the samples

  11. Predictive based monitoring of nuclear plant component degradation using support vector regression

    International Nuclear Information System (INIS)

    Agarwal, Vivek; Alamaniotis, Miltiadis; Tsoukalas, Lefteri H.

    2015-01-01

    Nuclear power plants (NPPs) are large installations comprised of many active and passive assets. Degradation monitoring of all these assets is expensive (labor cost) and highly demanding task. In this paper a framework based on Support Vector Regression (SVR) for online surveillance of critical parameter degradation of NPP components is proposed. In this case, on time replacement or maintenance of components will prevent potential plant malfunctions, and reduce the overall operational cost. In the current work, we apply SVR equipped with a Gaussian kernel function to monitor components. Monitoring includes the one-step-ahead prediction of the component's respective operational quantity using the SVR model, while the SVR model is trained using a set of previous recorded degradation histories of similar components. Predictive capability of the model is evaluated upon arrival of a sensor measurement, which is compared to the component failure threshold. A maintenance decision is based on a fuzzy inference system that utilizes three parameters: (i) prediction evaluation in the previous steps, (ii) predicted value of the current step, (iii) and difference of current predicted value with components failure thresholds. The proposed framework will be tested on turbine blade degradation data.

  12. Viral vector-based tools advance knowledge of basal ganglia anatomy and physiology.

    Science.gov (United States)

    Sizemore, Rachel J; Seeger-Armbruster, Sonja; Hughes, Stephanie M; Parr-Brownlie, Louise C

    2016-04-01

    Viral vectors were originally developed to deliver genes into host cells for therapeutic potential. However, viral vector use in neuroscience research has increased because they enhance interpretation of the anatomy and physiology of brain circuits compared with conventional tract tracing or electrical stimulation techniques. Viral vectors enable neuronal or glial subpopulations to be labeled or stimulated, which can be spatially restricted to a single target nucleus or pathway. Here we review the use of viral vectors to examine the structure and function of motor and limbic basal ganglia (BG) networks in normal and pathological states. We outline the use of viral vectors, particularly lentivirus and adeno-associated virus, in circuit tracing, optogenetic stimulation, and designer drug stimulation experiments. Key studies that have used viral vectors to trace and image pathways and connectivity at gross or ultrastructural levels are reviewed. We explain how optogenetic stimulation and designer drugs used to modulate a distinct pathway and neuronal subpopulation have enhanced our mechanistic understanding of BG function in health and pathophysiology in disease. Finally, we outline how viral vector technology may be applied to neurological and psychiatric conditions to offer new treatments with enhanced outcomes for patients. Copyright © 2016 the American Physiological Society.

  13. Structure-activity relationship study of oxindole-based inhibitors of cyclin-dependent kinases based on least-squares support vector machines

    International Nuclear Information System (INIS)

    Li Jiazhong; Liu Huanxiang; Yao Xiaojun; Liu Mancang; Hu Zhide; Fan Botao

    2007-01-01

    The least-squares support vector machines (LS-SVMs), as an effective modified algorithm of support vector machine, was used to build structure-activity relationship (SAR) models to classify the oxindole-based inhibitors of cyclin-dependent kinases (CDKs) based on their activity. Each compound was depicted by the structural descriptors that encode constitutional, topological, geometrical, electrostatic and quantum-chemical features. The forward-step-wise linear discriminate analysis method was used to search the descriptor space and select the structural descriptors responsible for activity. The linear discriminant analysis (LDA) and nonlinear LS-SVMs method were employed to build classification models, and the best results were obtained by the LS-SVMs method with prediction accuracy of 100% on the test set and 90.91% for CDK1 and CDK2, respectively, as well as that of LDA models 95.45% and 86.36%. This paper provides an effective method to screen CDKs inhibitors

  14. Construction of PVX virus-expression vector to express enterotoxin ...

    African Journals Online (AJOL)

    Potato X potyvirus (PVX)-based vector has been comprehensively applied in transient expression system. In order to produce the heterologous proteins more quickly and stably, the ClaI and NotI enzyme sites were introduced into the Enterotoxin fusion gene LTB-ST by polymerase chain reaction (PCR) and the LTB-ST ...

  15. Multifractal vector fields and stochastic Clifford algebra.

    Science.gov (United States)

    Schertzer, Daniel; Tchiguirinskaia, Ioulia

    2015-12-01

    In the mid 1980s, the development of multifractal concepts and techniques was an important breakthrough for complex system analysis and simulation, in particular, in turbulence and hydrology. Multifractals indeed aimed to track and simulate the scaling singularities of the underlying equations instead of relying on numerical, scale truncated simulations or on simplified conceptual models. However, this development has been rather limited to deal with scalar fields, whereas most of the fields of interest are vector-valued or even manifold-valued. We show in this paper that the combination of stable Lévy processes with Clifford algebra is a good candidate to bridge up the present gap between theory and applications. We show that it indeed defines a convenient framework to generate multifractal vector fields, possibly multifractal manifold-valued fields, based on a few fundamental and complementary properties of Lévy processes and Clifford algebra. In particular, the vector structure of these algebra is much more tractable than the manifold structure of symmetry groups while the Lévy stability grants a given statistical universality.

  16. Multifractal vector fields and stochastic Clifford algebra

    Energy Technology Data Exchange (ETDEWEB)

    Schertzer, Daniel, E-mail: Daniel.Schertzer@enpc.fr; Tchiguirinskaia, Ioulia, E-mail: Ioulia.Tchiguirinskaia@enpc.fr [University Paris-Est, Ecole des Ponts ParisTech, Hydrology Meteorology and Complexity HM& Co, Marne-la-Vallée (France)

    2015-12-15

    In the mid 1980s, the development of multifractal concepts and techniques was an important breakthrough for complex system analysis and simulation, in particular, in turbulence and hydrology. Multifractals indeed aimed to track and simulate the scaling singularities of the underlying equations instead of relying on numerical, scale truncated simulations or on simplified conceptual models. However, this development has been rather limited to deal with scalar fields, whereas most of the fields of interest are vector-valued or even manifold-valued. We show in this paper that the combination of stable Lévy processes with Clifford algebra is a good candidate to bridge up the present gap between theory and applications. We show that it indeed defines a convenient framework to generate multifractal vector fields, possibly multifractal manifold-valued fields, based on a few fundamental and complementary properties of Lévy processes and Clifford algebra. In particular, the vector structure of these algebra is much more tractable than the manifold structure of symmetry groups while the Lévy stability grants a given statistical universality.

  17. Immunogenicity of ORFV-based vectors expressing the rabies virus glycoprotein in livestock species.

    Science.gov (United States)

    Martins, Mathias; Joshi, Lok R; Rodrigues, Fernando S; Anziliero, Deniz; Frandoloso, Rafael; Kutish, Gerald F; Rock, Daniel L; Weiblen, Rudi; Flores, Eduardo F; Diel, Diego G

    2017-11-01

    The parapoxvirus Orf virus (ORFV) encodes several immunomodulatory proteins (IMPs) that modulate host-innate and pro-inflammatory responses and has been proposed as a vaccine delivery vector for use in animal species. Here we describe the construction and characterization of two recombinant ORFV vectors expressing the rabies virus (RABV) glycoprotein (G). The RABV-G gene was inserted in the ORFV024 or ORFV121 gene loci, which encode for IMPs that are unique to parapoxviruses and inhibit activation of the NF-κB signaling pathway. The immunogenicity of the resultant recombinant viruses (ORFV ∆024 RABV-G or ORFV ∆121 RABV-G, respectively) was evaluated in pigs and cattle. Immunization of the target species with ORFV ∆024 RABV-G and ORFV ∆121 RABV-G elicited robust neutralizing antibody responses against RABV. Notably, neutralizing antibody titers induced in ORFV ∆121 RABV-G-immunized pigs and cattle were significantly higher than those detected in ORFV ∆024 RABV-G-immunized animals, indicating a higher immunogenicity of ORFV Δ121 -based vectors in these animal species. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Advanced signal processing based on support vector regression for lidar applications

    Science.gov (United States)

    Gelfusa, M.; Murari, A.; Malizia, A.; Lungaroni, M.; Peluso, E.; Parracino, S.; Talebzadeh, S.; Vega, J.; Gaudio, P.

    2015-10-01

    The LIDAR technique has recently found many applications in atmospheric physics and remote sensing. One of the main issues, in the deployment of systems based on LIDAR, is the filtering of the backscattered signal to alleviate the problems generated by noise. Improvement in the signal to noise ratio is typically achieved by averaging a quite large number (of the order of hundreds) of successive laser pulses. This approach can be effective but presents significant limitations. First of all, it implies a great stress on the laser source, particularly in the case of systems for automatic monitoring of large areas for long periods. Secondly, this solution can become difficult to implement in applications characterised by rapid variations of the atmosphere, for example in the case of pollutant emissions, or by abrupt changes in the noise. In this contribution, a new method for the software filtering and denoising of LIDAR signals is presented. The technique is based on support vector regression. The proposed new method is insensitive to the statistics of the noise and is therefore fully general and quite robust. The developed numerical tool has been systematically compared with the most powerful techniques available, using both synthetic and experimental data. Its performances have been tested for various statistical distributions of the noise and also for other disturbances of the acquired signal such as outliers. The competitive advantages of the proposed method are fully documented. The potential of the proposed approach to widen the capability of the LIDAR technique, particularly in the detection of widespread smoke, is discussed in detail.

  19. Student difficulties regarding symbolic and graphical representations of vector fields

    Directory of Open Access Journals (Sweden)

    Laurens Bollen

    2017-08-01

    Full Text Available The ability to switch between various representations is an invaluable problem-solving skill in physics. In addition, research has shown that using multiple representations can greatly enhance a person’s understanding of mathematical and physical concepts. This paper describes a study of student difficulties regarding interpreting, constructing, and switching between representations of vector fields, using both qualitative and quantitative methods. We first identified to what extent students are fluent with the use of field vector plots, field line diagrams, and symbolic expressions of vector fields by conducting individual student interviews and analyzing in-class student activities. Based on those findings, we designed the Vector Field Representations test, a free response assessment tool that has been given to 196 second- and third-year physics, mathematics, and engineering students from four different universities. From the obtained results we gained a comprehensive overview of typical errors that students make when switching between vector field representations. In addition, the study allowed us to determine the relative prevalence of the observed difficulties. Although the results varied greatly between institutions, a general trend revealed that many students struggle with vector addition, fail to recognize the field line density as an indication of the magnitude of the field, confuse characteristics of field lines and equipotential lines, and do not choose the appropriate coordinate system when writing out mathematical expressions of vector fields.

  20. Student difficulties regarding symbolic and graphical representations of vector fields

    Science.gov (United States)

    Bollen, Laurens; van Kampen, Paul; Baily, Charles; Kelly, Mossy; De Cock, Mieke

    2017-12-01

    The ability to switch between various representations is an invaluable problem-solving skill in physics. In addition, research has shown that using multiple representations can greatly enhance a person's understanding of mathematical and physical concepts. This paper describes a study of student difficulties regarding interpreting, constructing, and switching between representations of vector fields, using both qualitative and quantitative methods. We first identified to what extent students are fluent with the use of field vector plots, field line diagrams, and symbolic expressions of vector fields by conducting individual student interviews and analyzing in-class student activities. Based on those findings, we designed the Vector Field Representations test, a free response assessment tool that has been given to 196 second- and third-year physics, mathematics, and engineering students from four different universities. From the obtained results we gained a comprehensive overview of typical errors that students make when switching between vector field representations. In addition, the study allowed us to determine the relative prevalence of the observed difficulties. Although the results varied greatly between institutions, a general trend revealed that many students struggle with vector addition, fail to recognize the field line density as an indication of the magnitude of the field, confuse characteristics of field lines and equipotential lines, and do not choose the appropriate coordinate system when writing out mathematical expressions of vector fields.

  1. Disturbance observer based current controller for vector controlled IM drives

    DEFF Research Database (Denmark)

    Teodorescu, Remus; Dal, Mehmet

    2008-01-01

    induction motor (IM) drives. The control design, based on synchronously rotating d-q frame model of the machine, has a simple structure that combines the proportional portion of a conventional PI control and output of the observer. The observer is predicted to estimate the disturbances caused by parameters...... coupling effects and increase robustness against parameters change without requiring any other compensation strategies. The experimental implementation results are provided to demonstrate validity and performance of the proposed control scheme.......In order to increase the accuracy of the current control loop, usually, well known parameter compensation and/or cross decoupling techniques are employed for advanced ac drives. In this paper, instead of using these techniques an observer-based current controller is proposed for vector controlled...

  2. Space Vector Pulse Width Modulation Strategy for Single-Phase Three-Level CIC T-source Inverter

    DEFF Research Database (Denmark)

    Shults, Tatiana E.; Husev, Oleksandr O.; Blaabjerg, Frede

    2016-01-01

    This paper presents a novel space vector pulse-width modulation strategy for a single-phase three-level buck-boost inverter based on an impedance-source network. The case study system is based on T-source inverter with continuous input current. To demonstrate the improved performance of the inver......This paper presents a novel space vector pulse-width modulation strategy for a single-phase three-level buck-boost inverter based on an impedance-source network. The case study system is based on T-source inverter with continuous input current. To demonstrate the improved performance...... of the inverter, the strategy was compared the traditional pulse-width modulation. It is shown that the approach proposed has fewer switching states and does not suffer from neutral point misbalance....

  3. Vector fields and gravity on the lattice

    International Nuclear Information System (INIS)

    Khatsymovsky, V.M.

    1988-01-01

    The problem of discretization of vector field on Regge lattice is considered. Our approach is based on geometrical interpretation of the vector field as the field of infinitesimal coordinate transformation. A discrete version of the vector field action is obtained as a particular case of the continuum action, and it is shown to have the true continuum limit

  4. Vector analysis

    CERN Document Server

    Newell, Homer E

    2006-01-01

    When employed with skill and understanding, vector analysis can be a practical and powerful tool. This text develops the algebra and calculus of vectors in a manner useful to physicists and engineers. Numerous exercises (with answers) not only provide practice in manipulation but also help establish students' physical and geometric intuition in regard to vectors and vector concepts.Part I, the basic portion of the text, consists of a thorough treatment of vector algebra and the vector calculus. Part II presents the illustrative matter, demonstrating applications to kinematics, mechanics, and e

  5. Estimation of Motion Vector Fields

    DEFF Research Database (Denmark)

    Larsen, Rasmus

    1993-01-01

    This paper presents an approach to the estimation of 2-D motion vector fields from time varying image sequences. We use a piecewise smooth model based on coupled vector/binary Markov random fields. We find the maximum a posteriori solution by simulated annealing. The algorithm generate sample...... fields by means of stochastic relaxation implemented via the Gibbs sampler....

  6. Strengthening tactical planning and operational frameworks for vector control: the roadmap for malaria elimination in Namibia.

    Science.gov (United States)

    Chanda, Emmanuel; Ameneshewa, Birkinesh; Angula, Hans A; Iitula, Iitula; Uusiku, Pentrina; Trune, Desta; Islam, Quazi M; Govere, John M

    2015-08-05

    Namibia has made tremendous gains in malaria control and the epidemiological trend of the disease has changed significantly over the past years. In 2010, the country reoriented from the objective of reducing disease morbidity and mortality to the goal of achieving malaria elimination by 2020. This manuscript outlines the processes undertaken in strengthening tactical planning and operational frameworks for vector control to facilitate expeditious malaria elimination in Namibia. The information sources for this study included all available data and accessible archived documentary records on malaria vector control in Namibia. A methodical assessment of published and unpublished documents was conducted via a literature search of online electronic databases, Google Scholar, PubMed and WHO, using a combination of search terms. To attain the goal of elimination in Namibia, systems are being strengthened to identify and clear all infections, and significantly reduce human-mosquito contact. Particularly, consolidating vector control for reducing transmission at the identified malaria foci will be critical for accelerated malaria elimination. Thus, guarding against potential challenges and the need for evidence-based and sustainable vector control instigated the strengthening of strategic frameworks by: adopting the integrated vector management (IVM) strategy; initiating implementation of the global plan for insecticide resistance management (GPIRM); intensifying malaria vector surveillance; improving data collection and reporting systems on DDT; updating the indoor residual spraying (IRS) data collection and reporting tool; and, improving geographical reconnaissance using geographical information system-based satellite imagery. Universal coverage with IRS and long-lasting insecticidal nets, supplemented by larval source management in the context of IVM and guided by vector surveillance coupled with rational operationalization of the GPIRM, will enable expeditious

  7. Sleeping Beauty-baculovirus hybrid vectors for long-term gene expression in the eye.

    Science.gov (United States)

    Turunen, Tytteli Anni Kaarina; Laakkonen, Johanna Päivikki; Alasaarela, Laura; Airenne, Kari Juhani; Ylä-Herttuala, Seppo

    2014-01-01

    A baculovirus vector is capable of efficiently transducing many nondiving and diving cell types. However, the potential of baculovirus is restricted for many gene delivery applications as a result of the transient gene expression that it mediates. The plasmid-based Sleeping Beauty (SB) transposon system integrates transgenes into target cell genome efficiently with a genomic integration pattern that is generally considered safer than the integration of many other integrating vectors; yet efficient delivery of therapeutic genes into cells of target tissues in vivo is a major challenge for nonviral gene therapy. In the present study, SB was introduced into baculovirus to obtain novel hybrid vectors that would combine the best features of the two vector systems (i.e. effective gene delivery and efficient integration into the genome), thus circumventing the major limitations of these vectors. We constructed and optimized SB-baculovirus hybrid vectors that bear either SB100x transposase or SB transposon in the forward or reverse orientations with respect to the viral backbone The functionality of the novel hybrid vectors was investigated in cell cultures and in a proof-of-concept study in the mouse eye. The hybrid vectors showed high and sustained transgene expression that remained stable and demonstrated no signs of decline during the 2 months follow-up in vitro. These results were verified in the mouse eye where persistent transgene expression was detected two months after intravitreal injection. Our results confirm that (i) SB-baculovirus hybrid vectors mediate long-term gene expression in vitro and in vivo, and (ii) the hybrid vectors are potential new tools for the treatment of ocular diseases. Copyright © 2014 John Wiley & Sons, Ltd.

  8. Single vector system for efficient N-myristoylation of recombinant proteins in E. coli.

    Directory of Open Access Journals (Sweden)

    Julian M Glück

    Full Text Available BACKGROUND: N-myristoylation is a crucial covalent modification of numerous eukaryotic and viral proteins that is catalyzed by N-myristoyltransferase (NMT. Prokaryotes are lacking endogenous NMT activity. Recombinant production of N-myristoylated proteins in E. coli cells can be achieved by coexpression of heterologous NMT with the target protein. In the past, dual plasmid systems were used for this purpose. METHODOLOGY/PRINCIPAL FINDINGS: Here we describe a single vector system for efficient coexpression of substrate and enzyme suitable for production of co- or posttranslationally modified proteins. The approach was validated using the HIV-1 Nef protein as an example. A simple and efficient protocol for production of highly pure and completely N-myristoylated Nef is presented. The yield is about 20 mg myristoylated Nef per liter growth medium. CONCLUSIONS/SIGNIFICANCE: The single vector strategy allows diverse modifications of target proteins recombinantly coexpressed in E. coli with heterologous enzymes. The method is generally applicable and provides large amounts of quantitatively processed target protein that are sufficient for comprehensive biophysical and structural studies.

  9. Automated system for lung nodules classification based on wavelet feature descriptor and support vector machine.

    Science.gov (United States)

    Madero Orozco, Hiram; Vergara Villegas, Osslan Osiris; Cruz Sánchez, Vianey Guadalupe; Ochoa Domínguez, Humberto de Jesús; Nandayapa Alfaro, Manuel de Jesús

    2015-02-12

    Lung cancer is a leading cause of death worldwide; it refers to the uncontrolled growth of abnormal cells in the lung. A computed tomography (CT) scan of the thorax is the most sensitive method for detecting cancerous lung nodules. A lung nodule is a round lesion which can be either non-cancerous or cancerous. In the CT, the lung cancer is observed as round white shadow nodules. The possibility to obtain a manually accurate interpretation from CT scans demands a big effort by the radiologist and might be a fatiguing process. Therefore, the design of a computer-aided diagnosis (CADx) system would be helpful as a second opinion tool. The stages of the proposed CADx are: a supervised extraction of the region of interest to eliminate the shape differences among CT images. The Daubechies db1, db2, and db4 wavelet transforms are computed with one and two levels of decomposition. After that, 19 features are computed from each wavelet sub-band. Then, the sub-band and attribute selection is performed. As a result, 11 features are selected and combined in pairs as inputs to the support vector machine (SVM), which is used to distinguish CT images containing cancerous nodules from those not containing nodules. The clinical data set used for experiments consists of 45 CT scans from ELCAP and LIDC. For the training stage 61 CT images were used (36 with cancerous lung nodules and 25 without lung nodules). The system performance was tested with 45 CT scans (23 CT scans with lung nodules and 22 without nodules), different from that used for training. The results obtained show that the methodology successfully classifies cancerous nodules with a diameter from 2 mm to 30 mm. The total preciseness obtained was 82%; the sensitivity was 90.90%, whereas the specificity was 73.91%. The CADx system presented is competitive with other literature systems in terms of sensitivity. The system reduces the complexity of classification by not performing the typical segmentation stage of most CADx

  10. Systems and Methods for Determining Inertial Navigation System Faults

    Science.gov (United States)

    Bharadwaj, Raj Mohan (Inventor); Bageshwar, Vibhor L. (Inventor); Kim, Kyusung (Inventor)

    2017-01-01

    An inertial navigation system (INS) includes a primary inertial navigation system (INS) unit configured to receive accelerometer measurements from an accelerometer and angular velocity measurements from a gyroscope. The primary INS unit is further configured to receive global navigation satellite system (GNSS) signals from a GNSS sensor and to determine a first set of kinematic state vectors based on the accelerometer measurements, the angular velocity measurements, and the GNSS signals. The INS further includes a secondary INS unit configured to receive the accelerometer measurements and the angular velocity measurements and to determine a second set of kinematic state vectors of the vehicle based on the accelerometer measurements and the angular velocity measurements. A health management system is configured to compare the first set of kinematic state vectors and the second set of kinematic state vectors to determine faults associated with the accelerometer or the gyroscope based on the comparison.

  11. A multi-label learning based kernel automatic recommendation method for support vector machine.

    Science.gov (United States)

    Zhang, Xueying; Song, Qinbao

    2015-01-01

    Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance.

  12. Vector-Tensor and Vector-Vector Decay Amplitude Analysis of B0→φK*0

    International Nuclear Information System (INIS)

    Aubert, B.; Bona, M.; Boutigny, D.; Couderc, F.; Karyotakis, Y.; Lees, J. P.; Poireau, V.; Tisserand, V.; Zghiche, A.; Grauges, E.; Palano, A.; Chen, J. C.; Qi, N. D.; Rong, G.; Wang, P.; Zhu, Y. S.; Eigen, G.; Ofte, I.; Stugu, B.; Abrams, G. S.

    2007-01-01

    We perform an amplitude analysis of the decays B 0 →φK 2 * (1430) 0 , φK * (892) 0 , and φ(Kπ) S-wave 0 with a sample of about 384x10 6 BB pairs recorded with the BABAR detector. The fractions of longitudinal polarization f L of the vector-tensor and vector-vector decay modes are measured to be 0.853 -0.069 +0.061 ±0.036 and 0.506±0.040±0.015, respectively. Overall, twelve parameters are measured for the vector-vector decay and seven parameters for the vector-tensor decay, including the branching fractions and parameters sensitive to CP violation

  13. Method of dynamic fuzzy symptom vector in intelligent diagnosis

    International Nuclear Information System (INIS)

    Sun Hongyan; Jiang Xuefeng

    2010-01-01

    Aiming at the requirement of diagnostic symptom real-time updating brought from diagnostic knowledge accumulation and great gap in unit and value of diagnostic symptom in multi parameters intelligent diagnosis, the method of dynamic fuzzy symptom vector is proposed. The concept of dynamic fuzzy symptom vector is defined. Ontology is used to specify the vector elements, and the vector transmission method based on ontology is built. The changing law of symptom value is analyzed and fuzzy normalization method based on fuzzy membership functions is built. An instance proved method of dynamic fussy symptom vector is efficient to solve the problems of symptom updating and unify of symptom value and unit. (authors)

  14. A NEW METHOD OF CHANNEL FRICTION INVERSION BASED ON KALMAN FILTER WITH UNKNOWN PARAMETER VECTOR

    Institute of Scientific and Technical Information of China (English)

    CHENG Wei-ping; MAO Gen-hai; LIU Guo-hua

    2005-01-01

    Channel friction is an important parameter in hydraulic analysis.A channel friction parameter inversion method based on Kalman Filter with unknown parameter vector is proposed.Numerical simulations indicate that when the number of monitoring stations exceeds a critical value, the solution is hardly affected.In addition, Kalman Filter with unknown parameter vector is effective only at unsteady state.For the nonlinear equations, computations of sensitivity matrices are time-costly.Two simplified measures can reduce computing time, but not influence the results.One is to reduce sensitivity matrix analysis time, the other is to substitute for sensitivity matrix.

  15. Double-stranded RNA transcribed from vector-based oligodeoxynucleotide acts as transcription factor decoy

    International Nuclear Information System (INIS)

    Xiao, Xiao; Gang, Yi; Wang, Honghong; Wang, Jiayin; Zhao, Lina; Xu, Li; Liu, Zhiguo

    2015-01-01

    Highlights: • A shRNA vector based transcription factor decoy, VB-ODN, was designed. • VB-ODN for NF-κB inhibited cell viability in HEK293 cells. • VB-ODN inhibited expression of downstream genes of target transcription factors. • VB-ODN may enhance nuclear entry ratio for its feasibility of virus production. - Abstract: In this study, we designed a short hairpin RNA vector-based oligodeoxynucleotide (VB-ODN) carrying transcription factor (TF) consensus sequence which could function as a decoy to block TF activity. Specifically, VB-ODN for Nuclear factor-κB (NF-κB) could inhibit cell viability and decrease downstream gene expression in HEK293 cells without affecting expression of NF-κB itself. The specific binding between VB-ODN produced double-stranded RNA and NF-κB was evidenced by electrophoretic mobility shift assay. Moreover, similar VB-ODNs designed for three other TFs also inhibit their downstream gene expression but not that of themselves. Our study provides a new design of decoy for blocking TF activity

  16. Double-stranded RNA transcribed from vector-based oligodeoxynucleotide acts as transcription factor decoy

    Energy Technology Data Exchange (ETDEWEB)

    Xiao, Xiao [State Key Laboratory of Cancer Biology and Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China); Gang, Yi [State Key Laboratory of Cancer Biology and Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China); Department of Infectious Diseases, Tangdu Hospital, Fourth Military Medical University, Xi’an 710038, Shaanxi Province (China); Wang, Honghong [No. 518 Hospital of Chinese People’s Liberation Army, Xi’an 710043, Shaanxi Province (China); Wang, Jiayin [The Genome Institute, Washington University in St. Louis, St. Louis, MO 63108 (United States); Zhao, Lina [Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China); Xu, Li, E-mail: lxuhelen@163.com [State Key Laboratory of Cancer Biology and Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China); Liu, Zhiguo, E-mail: liuzhiguo@fmmu.edu.cn [State Key Laboratory of Cancer Biology and Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China)

    2015-02-06

    Highlights: • A shRNA vector based transcription factor decoy, VB-ODN, was designed. • VB-ODN for NF-κB inhibited cell viability in HEK293 cells. • VB-ODN inhibited expression of downstream genes of target transcription factors. • VB-ODN may enhance nuclear entry ratio for its feasibility of virus production. - Abstract: In this study, we designed a short hairpin RNA vector-based oligodeoxynucleotide (VB-ODN) carrying transcription factor (TF) consensus sequence which could function as a decoy to block TF activity. Specifically, VB-ODN for Nuclear factor-κB (NF-κB) could inhibit cell viability and decrease downstream gene expression in HEK293 cells without affecting expression of NF-κB itself. The specific binding between VB-ODN produced double-stranded RNA and NF-κB was evidenced by electrophoretic mobility shift assay. Moreover, similar VB-ODNs designed for three other TFs also inhibit their downstream gene expression but not that of themselves. Our study provides a new design of decoy for blocking TF activity.

  17. Optical threshold secret sharing scheme based on basic vector operations and coherence superposition

    Science.gov (United States)

    Deng, Xiaopeng; Wen, Wei; Mi, Xianwu; Long, Xuewen

    2015-04-01

    We propose, to our knowledge for the first time, a simple optical algorithm for secret image sharing with the (2,n) threshold scheme based on basic vector operations and coherence superposition. The secret image to be shared is firstly divided into n shadow images by use of basic vector operations. In the reconstruction stage, the secret image can be retrieved by recording the intensity of the coherence superposition of any two shadow images. Compared with the published encryption techniques which focus narrowly on information encryption, the proposed method can realize information encryption as well as secret sharing, which further ensures the safety and integrality of the secret information and prevents power from being kept centralized and abused. The feasibility and effectiveness of the proposed method are demonstrated by numerical results.

  18. About vectors

    CERN Document Server

    Hoffmann, Banesh

    1975-01-01

    From his unusual beginning in ""Defining a vector"" to his final comments on ""What then is a vector?"" author Banesh Hoffmann has written a book that is provocative and unconventional. In his emphasis on the unresolved issue of defining a vector, Hoffmann mixes pure and applied mathematics without using calculus. The result is a treatment that can serve as a supplement and corrective to textbooks, as well as collateral reading in all courses that deal with vectors. Major topics include vectors and the parallelogram law; algebraic notation and basic ideas; vector algebra; scalars and scalar p

  19. Non-viral delivery systems for CRISPR/Cas9-based genome editing: Challenges and opportunities.

    Science.gov (United States)

    Li, Ling; Hu, Shuo; Chen, Xiaoyuan

    2018-07-01

    In recent years, CRISPR (clustered regularly interspaced short palindromic repeat)/Cas (CRISPR-associated) genome editing systems have become one of the most robust platforms in basic biomedical research and therapeutic applications. To date, efficient in vivo delivery of the CRISPR/Cas9 system to the targeted cells remains a challenge. Although viral vectors have been widely used in the delivery of the CRISPR/Cas9 system in vitro and in vivo, their fundamental shortcomings, such as the risk of carcinogenesis, limited insertion size, immune responses and difficulty in large-scale production, severely limit their further applications. Alternative non-viral delivery systems for CRISPR/Cas9 are urgently needed. With the rapid development of non-viral vectors, lipid- or polymer-based nanocarriers have shown great potential for CRISPR/Cas9 delivery. In this review, we analyze the pros and cons of delivering CRISPR/Cas9 systems in the form of plasmid, mRNA, or protein and then discuss the limitations and challenges of CRISPR/Cas9-based genome editing. Furthermore, current non-viral vectors that have been applied for CRISPR/Cas9 delivery in vitro and in vivo are outlined in details. Finally, critical obstacles for non-viral delivery of CRISPR/Cas9 system are highlighted and promising strategies to overcome these barriers are proposed. Published by Elsevier Ltd.

  20. An Android malware detection system based on machine learning

    Science.gov (United States)

    Wen, Long; Yu, Haiyang

    2017-08-01

    The Android smartphone, with its open source character and excellent performance, has attracted many users. However, the convenience of the Android platform also has motivated the development of malware. The traditional method which detects the malware based on the signature is unable to detect unknown applications. The article proposes a machine learning-based lightweight system that is capable of identifying malware on Android devices. In this system we extract features based on the static analysis and the dynamitic analysis, then a new feature selection approach based on principle component analysis (PCA) and relief are presented in the article to decrease the dimensions of the features. After that, a model will be constructed with support vector machine (SVM) for classification. Experimental results show that our system provides an effective method in Android malware detection.

  1. Lentiviral Vector Gene Transfer to Porcine Airways

    Directory of Open Access Journals (Sweden)

    Patrick L Sinn

    2012-01-01

    Full Text Available In this study, we investigated lentiviral vector development and transduction efficiencies in well-differentiated primary cultures of pig airway epithelia (PAE and wild-type pigs in vivo. We noted gene transfer efficiencies similar to that observed for human airway epithelia (HAE. Interestingly, feline immunodeficiency virus (FIV-based vectors transduced immortalized pig cells as well as pig primary cells more efficiently than HIV-1–based vectors. PAE express TRIM5α, a well-characterized species-specific lentiviral restriction factor. We contrasted the restrictive properties of porcine TRIM5α against FIV- and HIV-based vectors using gain and loss of function approaches. We observed no effect on HIV-1 or FIV conferred transgene expression in response to porcine TRIM5α overexpression or knockdown. To evaluate the ability of GP64-FIV to transduce porcine airways in vivo, we delivered vector expressing mCherry to the tracheal lobe of the lung and the ethmoid sinus of 4-week-old pigs. One week later, epithelial cells expressing mCherry were readily detected. Our findings indicate that pseudotyped FIV vectors confer similar tropisms in porcine epithelia as observed in human HAE and provide further support for the selection of GP64 as an appropriate envelope pseudotype for future preclinical gene therapy studies in the porcine model of cystic fibrosis (CF.

  2. Correlated Topic Vector for Scene Classification.

    Science.gov (United States)

    Wei, Pengxu; Qin, Fei; Wan, Fang; Zhu, Yi; Jiao, Jianbin; Ye, Qixiang

    2017-07-01

    Scene images usually involve semantic correlations, particularly when considering large-scale image data sets. This paper proposes a novel generative image representation, correlated topic vector, to model such semantic correlations. Oriented from the correlated topic model, correlated topic vector intends to naturally utilize the correlations among topics, which are seldom considered in the conventional feature encoding, e.g., Fisher vector, but do exist in scene images. It is expected that the involvement of correlations can increase the discriminative capability of the learned generative model and consequently improve the recognition accuracy. Incorporated with the Fisher kernel method, correlated topic vector inherits the advantages of Fisher vector. The contributions to the topics of visual words have been further employed by incorporating the Fisher kernel framework to indicate the differences among scenes. Combined with the deep convolutional neural network (CNN) features and Gibbs sampling solution, correlated topic vector shows great potential when processing large-scale and complex scene image data sets. Experiments on two scene image data sets demonstrate that correlated topic vector improves significantly the deep CNN features, and outperforms existing Fisher kernel-based features.

  3. Application of Bred Vectors To Data Assimilation

    Science.gov (United States)

    Corazza, M.; Kalnay, E.; Patil, Dj

    ,0,0]=1.8, less than 2 because one direction is more dominant than the other in representing the original data. The results (Patil et al, 2001) show that there are large regions where the bred vectors span a subspace of substantially lower dimension than that of the full space. These low dimensionality regions are dominant in the baroclinic extratropics, typically have a lifetime of 3-7 days, have a well-defined horizontal and vertical structure that spans 1 most of the atmosphere, and tend to move eastward. New results with a large number of ensemble members confirm these results and indicate that the low dimensionality regions are quite robust, and depend only on the verification time (i.e., the underlying flow). Corazza et al (2001) have performed experiments with a data assimilation system based on a quasi-geostrophic model and simulated observations (Morss, 1999, Hamill et al, 2000). A 3D-variational data assimilation scheme for a quasi-geostrophic chan- nel model is used to study the structure of the background error and its relationship to the corresponding bred vectors. The "true" evolution of the model atmosphere is defined by an integration of the model and "rawinsonde observations" are simulated by randomly perturbing the true state at fixed locations. It is found that after 3-5 days the bred vectors develop well organized structures which are very similar for the two different norms considered in this paper (potential vorticity norm and streamfunction norm). The results show that the bred vectors do indeed represent well the characteristics of the data assimilation forecast errors, and that the subspace of bred vectors contains most of the forecast error, except in areas where the forecast errors are small. For example, the angle between the 6hr forecast error and the subspace spanned by 10 bred vectors is less than 10o over 90% of the domain, indicating a pattern correlation of more than 98.5% between the forecast error and its projection onto the bred vector

  4. Learning Algorithms for Audio and Video Processing: Independent Component Analysis and Support Vector Machine Based Approaches

    National Research Council Canada - National Science Library

    Qi, Yuan

    2000-01-01

    In this thesis, we propose two new machine learning schemes, a subband-based Independent Component Analysis scheme and a hybrid Independent Component Analysis/Support Vector Machine scheme, and apply...

  5. Isometric Reflection Vectors and Characterizations of Hilbert Spaces

    Directory of Open Access Journals (Sweden)

    Donghai Ji

    2014-01-01

    Full Text Available A known characterization of Hilbert spaces via isometric reflection vectors is based on the following implication: if the set of isometric reflection vectors in the unit sphere SX of a Banach space X has nonempty interior in SX, then X is a Hilbert space. Applying a recent result based on well-known theorem of Kronecker from number theory, we improve this by substantial reduction of the set of isometric reflection vectors needed in the hypothesis.

  6. Vectors

    DEFF Research Database (Denmark)

    Boeriis, Morten; van Leeuwen, Theo

    2017-01-01

    should be taken into account in discussing ‘reactions’, which Kress and van Leeuwen link only to eyeline vectors. Finally, the question can be raised as to whether actions are always realized by vectors. Drawing on a re-reading of Rudolf Arnheim’s account of vectors, these issues are outlined......This article revisits the concept of vectors, which, in Kress and van Leeuwen’s Reading Images (2006), plays a crucial role in distinguishing between ‘narrative’, action-oriented processes and ‘conceptual’, state-oriented processes. The use of this concept in image analysis has usually focused...

  7. A Novel Covert Agent for Stealthy Attacks on Industrial Control Systems Using Least Squares Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Weize Li

    2018-01-01

    Full Text Available Research on stealthiness has become an important topic in the field of data integrity (DI attacks. To construct stealthy DI attacks, a common assumption in most related studies is that attackers have prior model knowledge of physical systems. In this paper, such assumption is relaxed and a covert agent is proposed based on the least squares support vector regression (LSSVR. By estimating a plant model from control and sensory data, the LSSVR-based covert agent can closely imitate the behavior of the physical plant. Then, the covert agent is used to construct a covert loop, which can keep the controller’s input and output both stealthy over a finite time window. Experiments have been carried out to show the effectiveness of the proposed method.

  8. Vector regression introduced

    Directory of Open Access Journals (Sweden)

    Mok Tik

    2014-06-01

    Full Text Available This study formulates regression of vector data that will enable statistical analysis of various geodetic phenomena such as, polar motion, ocean currents, typhoon/hurricane tracking, crustal deformations, and precursory earthquake signals. The observed vector variable of an event (dependent vector variable is expressed as a function of a number of hypothesized phenomena realized also as vector variables (independent vector variables and/or scalar variables that are likely to impact the dependent vector variable. The proposed representation has the unique property of solving the coefficients of independent vector variables (explanatory variables also as vectors, hence it supersedes multivariate multiple regression models, in which the unknown coefficients are scalar quantities. For the solution, complex numbers are used to rep- resent vector information, and the method of least squares is deployed to estimate the vector model parameters after transforming the complex vector regression model into a real vector regression model through isomorphism. Various operational statistics for testing the predictive significance of the estimated vector parameter coefficients are also derived. A simple numerical example demonstrates the use of the proposed vector regression analysis in modeling typhoon paths.

  9. A three-axis SQUID-based absolute vector magnetometer

    Energy Technology Data Exchange (ETDEWEB)

    Schönau, T.; Schmelz, M.; Stolz, R.; Anders, S.; Linzen, S.; Meyer, H.-G. [Department of Quantum Detection, Leibniz Institute of Photonic Technology, Jena 07745 (Germany); Zakosarenko, V.; Meyer, M. [Supracon AG, An der Lehmgrube 11, Jena 07751 (Germany)

    2015-10-15

    We report on the development of a three-axis absolute vector magnetometer suited for mobile operation in the Earth’s magnetic field. It is based on low critical temperature dc superconducting quantum interference devices (LTS dc SQUIDs) with sub-micrometer sized cross-type Josephson junctions and exhibits a white noise level of about 10 fT/Hz{sup 1/2}. The width of superconducting strip lines is restricted to less than 6 μm in order to avoid flux trapping during cool-down in magnetically unshielded environment. The long-term stability of the flux-to-voltage transfer coefficients of the SQUID electronics is investigated in detail and a method is presented to significantly increase their reproducibility. We further demonstrate the long-term operation of the setup in a magnetic field varying by about 200 μT amplitude without the need for recalibration.

  10. PCR-based detection of gene transfer vectors: application to gene doping surveillance.

    Science.gov (United States)

    Perez, Irene C; Le Guiner, Caroline; Ni, Weiyi; Lyles, Jennifer; Moullier, Philippe; Snyder, Richard O

    2013-12-01

    Athletes who illicitly use drugs to enhance their athletic performance are at risk of being banned from sports competitions. Consequently, some athletes may seek new doping methods that they expect to be capable of circumventing detection. With advances in gene transfer vector design and therapeutic gene transfer, and demonstrations of safety and therapeutic benefit in humans, there is an increased probability of the pursuit of gene doping by athletes. In anticipation of the potential for gene doping, assays have been established to directly detect complementary DNA of genes that are top candidates for use in doping, as well as vector control elements. The development of molecular assays that are capable of exposing gene doping in sports can serve as a deterrent and may also identify athletes who have illicitly used gene transfer for performance enhancement. PCR-based methods to detect foreign DNA with high reliability, sensitivity, and specificity include TaqMan real-time PCR, nested PCR, and internal threshold control PCR.

  11. A Foxtail mosaic virus Vector for Virus-Induced Gene Silencing in Maize1[OPEN

    Science.gov (United States)

    Mei, Yu; Kernodle, Bliss M.; Hill, John H.

    2016-01-01

    Plant viruses have been widely used as vectors for foreign gene expression and virus-induced gene silencing (VIGS). A limited number of viruses have been developed into viral vectors for the purposes of gene expression or VIGS in monocotyledonous plants, and among these, the tripartite viruses Brome mosaic virus and Cucumber mosaic virus have been shown to induce VIGS in maize (Zea mays). We describe here a new DNA-based VIGS system derived from Foxtail mosaic virus (FoMV), a monopartite virus that is able to establish systemic infection and silencing of endogenous maize genes homologous to gene fragments inserted into the FoMV genome. To demonstrate VIGS applications of this FoMV vector system, four genes, phytoene desaturase (functions in carotenoid biosynthesis), lesion mimic22 (encodes a key enzyme of the porphyrin pathway), iojap (functions in plastid development), and brown midrib3 (caffeic acid O-methyltransferase), were silenced and characterized in the sweet corn line Golden × Bantam. Furthermore, we demonstrate that the FoMV infectious clone establishes systemic infection in maize inbred lines, sorghum (Sorghum bicolor), and green foxtail (Setaria viridis), indicating the potential wide applications of this viral vector system for functional genomics studies in maize and other monocots. PMID:27208311

  12. Multi-agent systems in epidemiology: a first step for computational biology in the study of vector-borne disease transmission

    Directory of Open Access Journals (Sweden)

    Guégan Jean-François

    2008-10-01

    Full Text Available Abstract Background Computational biology is often associated with genetic or genomic studies only. However, thanks to the increase of computational resources, computational models are appreciated as useful tools in many other scientific fields. Such modeling systems are particularly relevant for the study of complex systems, like the epidemiology of emerging infectious diseases. So far, mathematical models remain the main tool for the epidemiological and ecological analysis of infectious diseases, with SIR models could be seen as an implicit standard in epidemiology. Unfortunately, these models are based on differential equations and, therefore, can become very rapidly unmanageable due to the too many parameters which need to be taken into consideration. For instance, in the case of zoonotic and vector-borne diseases in wildlife many different potential host species could be involved in the life-cycle of disease transmission, and SIR models might not be the most suitable tool to truly capture the overall disease circulation within that environment. This limitation underlines the necessity to develop a standard spatial model that can cope with the transmission of disease in realistic ecosystems. Results Computational biology may prove to be flexible enough to take into account the natural complexity observed in both natural and man-made ecosystems. In this paper, we propose a new computational model to study the transmission of infectious diseases in a spatially explicit context. We developed a multi-agent system model for vector-borne disease transmission in a realistic spatial environment. Conclusion Here we describe in detail the general behavior of this model that we hope will become a standard reference for the study of vector-borne disease transmission in wildlife. To conclude, we show how this simple model could be easily adapted and modified to be used as a common framework for further research developments in this field.

  13. Support vector machine based fault classification and location of a long transmission line

    Directory of Open Access Journals (Sweden)

    Papia Ray

    2016-09-01

    Full Text Available This paper investigates support vector machine based fault type and distance estimation scheme in a long transmission line. The planned technique uses post fault single cycle current waveform and pre-processing of the samples is done by wavelet packet transform. Energy and entropy are obtained from the decomposed coefficients and feature matrix is prepared. Then the redundant features from the matrix are taken out by the forward feature selection method and normalized. Test and train data are developed by taking into consideration variables of a simulation situation like fault type, resistance path, inception angle, and distance. In this paper 10 different types of short circuit fault are analyzed. The test data are examined by support vector machine whose parameters are optimized by particle swarm optimization method. The anticipated method is checked on a 400 kV, 300 km long transmission line with voltage source at both the ends. Two cases were examined with the proposed method. The first one is fault very near to both the source end (front and rear and the second one is support vector machine with and without optimized parameter. Simulation result indicates that the anticipated method for fault classification gives high accuracy (99.21% and least fault distance estimation error (0.29%.

  14. Finding a Hadamard matrix by simulated annealing of spin vectors

    Science.gov (United States)

    Bayu Suksmono, Andriyan

    2017-05-01

    Reformulation of a combinatorial problem into optimization of a statistical-mechanics system enables finding a better solution using heuristics derived from a physical process, such as by the simulated annealing (SA). In this paper, we present a Hadamard matrix (H-matrix) searching method based on the SA on an Ising model. By equivalence, an H-matrix can be converted into a seminormalized Hadamard (SH) matrix, whose first column is unit vector and the rest ones are vectors with equal number of -1 and +1 called SH-vectors. We define SH spin vectors as representation of the SH vectors, which play a similar role as the spins on Ising model. The topology of the lattice is generalized into a graph, whose edges represent orthogonality relationship among the SH spin vectors. Starting from a randomly generated quasi H-matrix Q, which is a matrix similar to the SH-matrix without imposing orthogonality, we perform the SA. The transitions of Q are conducted by random exchange of {+, -} spin-pair within the SH-spin vectors that follow the Metropolis update rule. Upon transition toward zeroth energy, the Q-matrix is evolved following a Markov chain toward an orthogonal matrix, at which the H-matrix is said to be found. We demonstrate the capability of the proposed method to find some low-order H-matrices, including the ones that cannot trivially be constructed by the Sylvester method.

  15. A vector-product information retrieval system adapted to heterogeneous, distributed computing environments

    Science.gov (United States)

    Rorvig, Mark E.

    1991-01-01

    Vector-product information retrieval (IR) systems produce retrieval results superior to all other searching methods but presently have no commercial implementations beyond the personal computer environment. The NASA Electronic Library Systems (NELS) provides a ranked list of the most likely relevant objects in collections in response to a natural language query. Additionally, the system is constructed using standards and tools (Unix, X-Windows, Notif, and TCP/IP) that permit its operation in organizations that possess many different hosts, workstations, and platforms. There are no known commercial equivalents to this product at this time. The product has applications in all corporate management environments, particularly those that are information intensive, such as finance, manufacturing, biotechnology, and research and development.

  16. Genomic Footprints of Selective Sweeps from Metabolic Resistance to Pyrethroids in African Malaria Vectors Are Driven by Scale up of Insecticide-Based Vector Control.

    Science.gov (United States)

    Barnes, Kayla G; Weedall, Gareth D; Ndula, Miranda; Irving, Helen; Mzihalowa, Themba; Hemingway, Janet; Wondji, Charles S

    2017-02-01

    Insecticide resistance in mosquito populations threatens recent successes in malaria prevention. Elucidating patterns of genetic structure in malaria vectors to predict the speed and direction of the spread of resistance is essential to get ahead of the 'resistance curve' and to avert a public health catastrophe. Here, applying a combination of microsatellite analysis, whole genome sequencing and targeted sequencing of a resistance locus, we elucidated the continent-wide population structure of a major African malaria vector, Anopheles funestus. We identified a major selective sweep in a genomic region controlling cytochrome P450-based metabolic resistance conferring high resistance to pyrethroids. This selective sweep occurred since 2002, likely as a direct consequence of scaled up vector control as revealed by whole genome and fine-scale sequencing of pre- and post-intervention populations. Fine-scaled analysis of the pyrethroid resistance locus revealed that a resistance-associated allele of the cytochrome P450 monooxygenase CYP6P9a has swept through southern Africa to near fixation, in contrast to high polymorphism levels before interventions, conferring high levels of pyrethroid resistance linked to control failure. Population structure analysis revealed a barrier to gene flow between southern Africa and other areas, which may prevent or slow the spread of the southern mechanism of pyrethroid resistance to other regions. By identifying a genetic signature of pyrethroid-based interventions, we have demonstrated the intense selective pressure that control interventions exert on mosquito populations. If this level of selection and spread of resistance continues unabated, our ability to control malaria with current interventions will be compromised.

  17. Genomic Footprints of Selective Sweeps from Metabolic Resistance to Pyrethroids in African Malaria Vectors Are Driven by Scale up of Insecticide-Based Vector Control.

    Directory of Open Access Journals (Sweden)

    Kayla G Barnes

    2017-02-01

    Full Text Available Insecticide resistance in mosquito populations threatens recent successes in malaria prevention. Elucidating patterns of genetic structure in malaria vectors to predict the speed and direction of the spread of resistance is essential to get ahead of the 'resistance curve' and to avert a public health catastrophe. Here, applying a combination of microsatellite analysis, whole genome sequencing and targeted sequencing of a resistance locus, we elucidated the continent-wide population structure of a major African malaria vector, Anopheles funestus. We identified a major selective sweep in a genomic region controlling cytochrome P450-based metabolic resistance conferring high resistance to pyrethroids. This selective sweep occurred since 2002, likely as a direct consequence of scaled up vector control as revealed by whole genome and fine-scale sequencing of pre- and post-intervention populations. Fine-scaled analysis of the pyrethroid resistance locus revealed that a resistance-associated allele of the cytochrome P450 monooxygenase CYP6P9a has swept through southern Africa to near fixation, in contrast to high polymorphism levels before interventions, conferring high levels of pyrethroid resistance linked to control failure. Population structure analysis revealed a barrier to gene flow between southern Africa and other areas, which may prevent or slow the spread of the southern mechanism of pyrethroid resistance to other regions. By identifying a genetic signature of pyrethroid-based interventions, we have demonstrated the intense selective pressure that control interventions exert on mosquito populations. If this level of selection and spread of resistance continues unabated, our ability to control malaria with current interventions will be compromised.

  18. Multiscale benchmarking of drug delivery vectors.

    Science.gov (United States)

    Summers, Huw D; Ware, Matthew J; Majithia, Ravish; Meissner, Kenith E; Godin, Biana; Rees, Paul

    2016-10-01

    Cross-system comparisons of drug delivery vectors are essential to ensure optimal design. An in-vitro experimental protocol is presented that separates the role of the delivery vector from that of its cargo in determining the cell response, thus allowing quantitative comparison of different systems. The technique is validated through benchmarking of the dose-response of human fibroblast cells exposed to the cationic molecule, polyethylene imine (PEI); delivered as a free molecule and as a cargo on the surface of CdSe nanoparticles and Silica microparticles. The exposure metrics are converted to a delivered dose with the transport properties of the different scale systems characterized by a delivery time, τ. The benchmarking highlights an agglomeration of the free PEI molecules into micron sized clusters and identifies the metric determining cell death as the total number of PEI molecules presented to cells, determined by the delivery vector dose and the surface density of the cargo. Copyright © 2016 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

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

    2009-01-01

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

  20. Thermodynamics of relation-based systems with applications in econophysics, sociophysics, and music

    Science.gov (United States)

    Gündüz, Güngör

    2012-10-01

    A methodology was developed to analyze relation-based systems evolving in time by using the fundamental concepts of thermodynamics. The behavior of such systems can be tracked from the scattering matrix which is actually a network of directed vectors (or pathways) connecting subsequent values, which characterize an event, such as the index values in stock markets. A system behaves in a rigid (elastic) way to an external effect and resists permanent deformation, or it behaves in a viscous (or soft) way and deforms in an irreversible way. It was shown in the past that a formula derived using the slope of paths gives a measure about the extent of viscoelastic behavior of relation-based systems Gündüz (2009) [5] Gündüz and Gündüz (2010) [6]. In this research the ‘work’ associated with ‘elastic’ component, and ‘heat’ associated with ‘viscous’ component were discussed and elaborated. In a simple two subsequent pathway system in a scattering diagram the first vector represents ‘the cause’ and the second ‘the effect’. By using work and heat energy relations that involve force and also storage and loss modulus terms, respectively, one can calculate the energy involved in relation-based systems. The modulus values can be found from the parallel and vertical components of the second vector with respect to the first vector. Once work-like and heat-like terms were determined the internal energy is also easily found from their summation. The parallel and vertical components can also be used to calculate the magnitude of torque and torque energy in the system. Three cases, (i) the behavior of the NASDAQ-100 index, (ii) a social revolt, and (iii) the structure of a melody were analyzed for their ‘work-like’, ‘heat-like’, and ‘torque-like’ energies in the course of their evolution. NASDAQ-100 exhibits highly dissipative behavior, and its work terms are very small but heat terms are of large magnitude. Its internal energy highly fluctuates

  1. Elementary vectors

    CERN Document Server

    Wolstenholme, E Œ

    1978-01-01

    Elementary Vectors, Third Edition serves as an introductory course in vector analysis and is intended to present the theoretical and application aspects of vectors. The book covers topics that rigorously explain and provide definitions, principles, equations, and methods in vector analysis. Applications of vector methods to simple kinematical and dynamical problems; central forces and orbits; and solutions to geometrical problems are discussed as well. This edition of the text also provides an appendix, intended for students, which the author hopes to bridge the gap between theory and appl

  2. 2D Vector Field Simplification Based on Robustness

    KAUST Repository

    Skraba, Primoz; Wang, Bei; Chen, Guoning; Rosen, Paul

    2014-01-01

    Vector field simplification aims to reduce the complexity of the flow by removing features in order of their relevance and importance, to reveal prominent behavior and obtain a compact representation for interpretation. Most existing simplification

  3. Development and applications of VSV vectors based on cell tropism

    Directory of Open Access Journals (Sweden)

    Hideki eTani

    2012-01-01

    Full Text Available Viral vectors have been available in various fields such as medical and biological research or gene therapy applications. Targeting vectors pseudotyped with distinct viral envelope proteins that influence cell tropism and transfection efficiency is a useful tool not only for examining entry mechanisms or cell tropisms but also for vaccine vector development. Vesicular stomatitis virus (VSV is an excellent candidate for development as a pseudotype vector. A recombinant VSV lacking its own envelope (G gene has been used to produce a pseudotype or recombinant VSV possessing the envelope proteins of heterologous viruses. These viruses possess a reporter gene instead of a VSV G gene in their genome, and therefore it is easy to evaluate their infectivity in the study of viral entry, including identification of viral receptors. Furthermore, advantage can be taken of a property of the pseudotype VSV, which is competence for single-round infection, in handling many different viruses that are either difficult to amplify in cultured cells or animals or that require specialized containment facilities. Here we describe procedures for producing pseudotype or recombinant VSVs and a few of the more prominent examples from among envelope viruses, such as hepatitis C virus, Japanese encephalitis virus, baculovirus, and hemorrhagic fever viruses.

  4. A concurrent visualization system for large-scale unsteady simulations. Parallel vector performance on an NEC SX-4

    International Nuclear Information System (INIS)

    Takei, Toshifumi; Doi, Shun; Matsumoto, Hideki; Muramatsu, Kazuhiro

    2000-01-01

    We have developed a concurrent visualization system RVSLIB (Real-time Visual Simulation Library). This paper shows the effectiveness of the system when it is applied to large-scale unsteady simulations, for which the conventional post-processing approach may no longer work, on high-performance parallel vector supercomputers. The system performs almost all of the visualization tasks on a computation server and uses compressed visualized image data for efficient communication between the server and the user terminal. We have introduced several techniques, including vectorization and parallelization, into the system to minimize the computational costs of the visualization tools. The performance of RVSLIB was evaluated by using an actual CFD code on an NEC SX-4. The computational time increase due to the concurrent visualization was at most 3% for a smaller (1.6 million) grid and less than 1% for a larger (6.2 million) one. (author)

  5. Space vector-based modeling and control of a modular multilevel converter in HVDC applications

    DEFF Research Database (Denmark)

    Bonavoglia, M.; Casadei, G.; Zarri, L.

    2013-01-01

    Modular multilevel converter (MMC) is an emerging multilevel topology for high-voltage applications that has been developed in recent years. In this paper, the modeling and the control of MMCs are restated in terms of space vectors, which may allow a deeper understanding of the converter behavior....... As a result, a control scheme for three-phase MMCs based on the previous theoretical analysis is presented. Numerical simulations are used to test its feasibility.......Modular multilevel converter (MMC) is an emerging multilevel topology for high-voltage applications that has been developed in recent years. In this paper, the modeling and the control of MMCs are restated in terms of space vectors, which may allow a deeper understanding of the converter behavior...

  6. A Novel Classification Algorithm Based on Incremental Semi-Supervised Support Vector Machine.

    Directory of Open Access Journals (Sweden)

    Fei Gao

    Full Text Available For current computational intelligence techniques, a major challenge is how to learn new concepts in changing environment. Traditional learning schemes could not adequately address this problem due to a lack of dynamic data selection mechanism. In this paper, inspired by human learning process, a novel classification algorithm based on incremental semi-supervised support vector machine (SVM is proposed. Through the analysis of prediction confidence of samples and data distribution in a changing environment, a "soft-start" approach, a data selection mechanism and a data cleaning mechanism are designed, which complete the construction of our incremental semi-supervised learning system. Noticeably, with the ingenious design procedure of our proposed algorithm, the computation complexity is reduced effectively. In addition, for the possible appearance of some new labeled samples in the learning process, a detailed analysis is also carried out. The results show that our algorithm does not rely on the model of sample distribution, has an extremely low rate of introducing wrong semi-labeled samples and can effectively make use of the unlabeled samples to enrich the knowledge system of classifier and improve the accuracy rate. Moreover, our method also has outstanding generalization performance and the ability to overcome the concept drift in a changing environment.

  7. Hierarchical Modulation with Vector Rotation for E-MBMS Transmission in LTE Systems

    Directory of Open Access Journals (Sweden)

    Hui Zhao

    2010-01-01

    Full Text Available Enhanced Multimedia Broadcast and Multicast Service (E-MBMS is considered of key importance for the proliferation of Long-Term Evolution (LTE network in mobile market. Hierarchical modulation (HM, which involves a “base-layer” (BL and an “enhancement-layer” (EL bit streams, is a simple technique for achieving tradeoff between service quality and radio coverage. Therefore, it is appealing for MBMS. Generally, HM suffers from the severe performance degradation of the less protected EL stream. In this paper, HM with vector rotation operation introduced to EL stream is proposed, in order to improve EL's performance. With the proper interleaving in frequency domain, this operation can exploit the inherent diversity gain from the multipath channel. In this way, HM with vector rotation can effectively enhance multimedia broadcasting on quality video and coverage. The simulation results with scalable video coding (SVC as source show the significant benefits in comparison with the conventional HM and alternative schemes.

  8. Performance improvement of 64-QAM coherent optical communication system by optimizing symbol decision boundary based on support vector machine

    Science.gov (United States)

    Chen, Wei; Zhang, Junfeng; Gao, Mingyi; Shen, Gangxiang

    2018-03-01

    High-order modulation signals are suited for high-capacity communication systems because of their high spectral efficiency, but they are more vulnerable to various impairments. For the signals that experience degradation, when symbol points overlap on the constellation diagram, the original linear decision boundary cannot be used to distinguish the classification of symbol. Therefore, it is advantageous to create an optimum symbol decision boundary for the degraded signals. In this work, we experimentally demonstrated the 64-quadrature-amplitude modulation (64-QAM) coherent optical communication system using support-vector machine (SVM) decision boundary algorithm to create the optimum symbol decision boundary for improving the system performance. We investigated the influence of various impairments on the 64-QAM coherent optical communication systems, such as the impairments caused by modulator nonlinearity, phase skew between in-phase (I) arm and quadrature-phase (Q) arm of the modulator, fiber Kerr nonlinearity and amplified spontaneous emission (ASE) noise. We measured the bit-error-ratio (BER) performance of 75-Gb/s 64-QAM signals in the back-to-back and 50-km transmission. By using SVM to optimize symbol decision boundary, the impairments caused by I/Q phase skew of the modulator, fiber Kerr nonlinearity and ASE noise are greatly mitigated.

  9. Wideband optical vector network analyzer based on optical single-sideband modulation and optical frequency comb.

    Science.gov (United States)

    Xue, Min; Pan, Shilong; He, Chao; Guo, Ronghui; Zhao, Yongjiu

    2013-11-15

    A novel approach to increase the measurement range of the optical vector network analyzer (OVNA) based on optical single-sideband (OSSB) modulation is proposed and experimentally demonstrated. In the proposed system, each comb line in an optical frequency comb (OFC) is selected by an optical filter and used as the optical carrier for the OSSB-based OVNA. The frequency responses of an optical device-under-test (ODUT) are thus measured channel by channel. Because the comb lines in the OFC have fixed frequency spacing, by fitting the responses measured in all channels together, the magnitude and phase responses of the ODUT can be accurately achieved in a large range. A proof-of-concept experiment is performed. A measurement range of 105 GHz and a resolution of 1 MHz is achieved when a five-comb-line OFC with a frequency spacing of 20 GHz is applied to measure the magnitude and phase responses of a fiber Bragg grating.

  10. Multithreading in vector processors

    Science.gov (United States)

    Evangelinos, Constantinos; Kim, Changhoan; Nair, Ravi

    2018-01-16

    In one embodiment, a system includes a processor having a vector processing mode and a multithreading mode. The processor is configured to operate on one thread per cycle in the multithreading mode. The processor includes a program counter register having a plurality of program counters, and the program counter register is vectorized. Each program counter in the program counter register represents a distinct corresponding thread of a plurality of threads. The processor is configured to execute the plurality of threads by activating the plurality of program counters in a round robin cycle.

  11. Monitoring by Use of Clusters of Sensor-Data Vectors

    Science.gov (United States)

    Iverson, David L.

    2007-01-01

    The inductive monitoring system (IMS) is a system of computer hardware and software for automated monitoring of the performance, operational condition, physical integrity, and other aspects of the health of a complex engineering system (e.g., an industrial process line or a spacecraft). The input to the IMS consists of streams of digitized readings from sensors in the monitored system. The IMS determines the type and amount of any deviation of the monitored system from a nominal or normal ( healthy ) condition on the basis of a comparison between (1) vectors constructed from the incoming sensor data and (2) corresponding vectors in a database of nominal or normal behavior. The term inductive reflects the use of a process reminiscent of traditional mathematical induction to learn about normal operation and build the nominal-condition database. The IMS offers two major advantages over prior computational monitoring systems: The computational burden of the IMS is significantly smaller, and there is no need for abnormal-condition sensor data for training the IMS to recognize abnormal conditions. The figure schematically depicts the relationships among the computational processes effected by the IMS. Training sensor data are gathered during normal operation of the monitored system, detailed computational simulation of operation of the monitored system, or both. The training data are formed into vectors that are used to generate the database. The vectors in the database are clustered into regions that represent normal or nominal operation. Once the database has been generated, the IMS compares the vectors of incoming sensor data with vectors representative of the clusters. The monitored system is deemed to be operating normally or abnormally, depending on whether the vector of incoming sensor data is or is not, respectively, sufficiently close to one of the clusters. For this purpose, a distance between two vectors is calculated by a suitable metric (e.g., Euclidean

  12. Space Vector Modulation Technique to Reduce Leakage Current of a Transformerless Three-Phase Four-Leg Photovoltaic System

    Directory of Open Access Journals (Sweden)

    F. Hasanzad

    2017-06-01

    Full Text Available Photovoltaic systems integrated to the grid have received considerable attention around the world. They can be connected to the electrical grid via galvanic isolation (transformer or without it (transformerless. Despite making galvanic isolation, low frequency transformer increases size, cost and losses. On the other hand, transformerless PV systems increase the leakage current (common-mode current, (CMC through the parasitic capacitors of the PV array. Inverter topology and switching technique are the most important parameters the leakage current depends on. As there is no need to extra hardware for switching scheme modification, it's an economical method for reducing leakage current. This paper evaluates the effect of different space vector modulation techniques on leakage current for a two-level three-phase four-leg inverter used in PV system. It proposes an efficient space vector modulation method which decreases the leakage current to below the quantity specified in VDE-0126-1-1 standard. furthermore, some other characteristics of the space vector modulation schemes that have not been significantly discussed for four-leg inverter, are considered, such as, modulation index, switching actions per period, common-mode voltage (CMV, and total harmonic distortion (THD. An extend software simulation using MATLAB/Simulink is performed to verify the effectiveness of the modulation technique.

  13. Analysis of vector wind change with respect to time for Vandenberg Air Force Base, California

    Science.gov (United States)

    Adelfang, S. I.

    1978-01-01

    A statistical analysis of the temporal variability of wind vectors at 1 km altitude intervals from 0 to 27 km altitude taken from a 10-year data sample of twice-daily rawinsode wind measurements over Vandenberg Air Force Base, California is presented.

  14. Duality in vector optimization

    CERN Document Server

    Bot, Radu Ioan

    2009-01-01

    This book presents fundamentals and comprehensive results regarding duality for scalar, vector and set-valued optimization problems in a general setting. After a preliminary chapter dedicated to convex analysis and minimality notions of sets with respect to partial orderings induced by convex cones a chapter on scalar conjugate duality follows. Then investigations on vector duality based on scalar conjugacy are made. Weak, strong and converse duality statements are delivered and connections to classical results from the literature are emphasized. One chapter is exclusively consecrated to the s

  15. Bunyavirus-Vector Interactions

    Directory of Open Access Journals (Sweden)

    Kate McElroy Horne

    2014-11-01

    Full Text Available The Bunyaviridae family is comprised of more than 350 viruses, of which many within the Hantavirus, Orthobunyavirus, Nairovirus, Tospovirus, and Phlebovirus genera are significant human or agricultural pathogens. The viruses within the Orthobunyavirus, Nairovirus, and Phlebovirus genera are transmitted by hematophagous arthropods, such as mosquitoes, midges, flies, and ticks, and their associated arthropods not only serve as vectors but also as virus reservoirs in many cases. This review presents an overview of several important emerging or re-emerging bunyaviruses and describes what is known about bunyavirus-vector interactions based on epidemiological, ultrastructural, and genetic studies of members of this virus family.

  16. Identification of Civil Engineering Structures using Vector ARMA Models

    DEFF Research Database (Denmark)

    Andersen, P.

    The dissertation treats the matter of systems identification and modelling of load-bearing constructions using Auto-Regressive Moving Average Vector (ARMAV) models.......The dissertation treats the matter of systems identification and modelling of load-bearing constructions using Auto-Regressive Moving Average Vector (ARMAV) models....

  17. A Classification Detection Algorithm Based on Joint Entropy Vector against Application-Layer DDoS Attack

    Directory of Open Access Journals (Sweden)

    Yuntao Zhao

    2018-01-01

    Full Text Available The application-layer distributed denial of service (AL-DDoS attack makes a great threat against cyberspace security. The attack detection is an important part of the security protection, which provides effective support for defense system through the rapid and accurate identification of attacks. According to the attacker’s different URL of the Web service, the AL-DDoS attack is divided into three categories, including a random URL attack and a fixed and a traverse one. In order to realize identification of attacks, a mapping matrix of the joint entropy vector is constructed. By defining and computing the value of EUPI and jEIPU, a visual coordinate discrimination diagram of entropy vector is proposed, which also realizes data dimension reduction from N to two. In terms of boundary discrimination and the region where the entropy vectors fall in, the class of AL-DDoS attack can be distinguished. Through the study of training data set and classification, the results show that the novel algorithm can effectively distinguish the web server DDoS attack from normal burst traffic.

  18. Performance optimization of Sparse Matrix-Vector Multiplication for multi-component PDE-based applications using GPUs

    KAUST Repository

    Abdelfattah, Ahmad

    2016-05-23

    Simulations of many multi-component PDE-based applications, such as petroleum reservoirs or reacting flows, are dominated by the solution, on each time step and within each Newton step, of large sparse linear systems. The standard solver is a preconditioned Krylov method. Along with application of the preconditioner, memory-bound Sparse Matrix-Vector Multiplication (SpMV) is the most time-consuming operation in such solvers. Multi-species models produce Jacobians with a dense block structure, where the block size can be as large as a few dozen. Failing to exploit this dense block structure vastly underutilizes hardware capable of delivering high performance on dense BLAS operations. This paper presents a GPU-accelerated SpMV kernel for block-sparse matrices. Dense matrix-vector multiplications within the sparse-block structure leverage optimization techniques from the KBLAS library, a high performance library for dense BLAS kernels. The design ideas of KBLAS can be applied to block-sparse matrices. Furthermore, a technique is proposed to balance the workload among thread blocks when there are large variations in the lengths of nonzero rows. Multi-GPU performance is highlighted. The proposed SpMV kernel outperforms existing state-of-the-art implementations using matrices with real structures from different applications. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  19. Performance optimization of Sparse Matrix-Vector Multiplication for multi-component PDE-based applications using GPUs

    KAUST Repository

    Abdelfattah, Ahmad; Ltaief, Hatem; Keyes, David E.; Dongarra, Jack

    2016-01-01

    Simulations of many multi-component PDE-based applications, such as petroleum reservoirs or reacting flows, are dominated by the solution, on each time step and within each Newton step, of large sparse linear systems. The standard solver is a preconditioned Krylov method. Along with application of the preconditioner, memory-bound Sparse Matrix-Vector Multiplication (SpMV) is the most time-consuming operation in such solvers. Multi-species models produce Jacobians with a dense block structure, where the block size can be as large as a few dozen. Failing to exploit this dense block structure vastly underutilizes hardware capable of delivering high performance on dense BLAS operations. This paper presents a GPU-accelerated SpMV kernel for block-sparse matrices. Dense matrix-vector multiplications within the sparse-block structure leverage optimization techniques from the KBLAS library, a high performance library for dense BLAS kernels. The design ideas of KBLAS can be applied to block-sparse matrices. Furthermore, a technique is proposed to balance the workload among thread blocks when there are large variations in the lengths of nonzero rows. Multi-GPU performance is highlighted. The proposed SpMV kernel outperforms existing state-of-the-art implementations using matrices with real structures from different applications. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  20. Dragon pulse information management system (DPIMS): A unique model-based approach to implementing domain agnostic system of systems and behaviors

    Science.gov (United States)

    Anderson, Thomas S.

    2016-05-01

    The Global Information Network Architecture is an information technology based on Vector Relational Data Modeling, a unique computational paradigm, DoD network certified by USARMY as the Dragon Pulse Informa- tion Management System. This network available modeling environment for modeling models, where models are configured using domain relevant semantics and use network available systems, sensors, databases and services as loosely coupled component objects and are executable applications. Solutions are based on mission tactics, techniques, and procedures and subject matter input. Three recent ARMY use cases are discussed a) ISR SoS. b) Modeling and simulation behavior validation. c) Networked digital library with behaviors.

  1. Chord Recognition Based on Temporal Correlation Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Zhongyang Rao

    2016-05-01

    Full Text Available In this paper, we propose a method called temporal correlation support vector machine (TCSVM for automatic major-minor chord recognition in audio music. We first use robust principal component analysis to separate the singing voice from the music to reduce the influence of the singing voice and consider the temporal correlations of the chord features. Using robust principal component analysis, we expect the low-rank component of the spectrogram matrix to contain the musical accompaniment and the sparse component to contain the vocal signals. Then, we extract a new logarithmic pitch class profile (LPCP feature called enhanced LPCP from the low-rank part. To exploit the temporal correlation among the LPCP features of chords, we propose an improved support vector machine algorithm called TCSVM. We perform this study using the MIREX’09 (Music Information Retrieval Evaluation eXchange Audio Chord Estimation dataset. Furthermore, we conduct comprehensive experiments using different pitch class profile feature vectors to examine the performance of TCSVM. The results of our method are comparable to the state-of-the-art methods that entered the MIREX in 2013 and 2014 for the MIREX’09 Audio Chord Estimation task dataset.

  2. A load predictive energy management system for supercapacitor-battery hybrid energy storage system in solar application using the Support Vector Machine

    International Nuclear Information System (INIS)

    Chia, Yen Yee; Lee, Lam Hong; Shafiabady, Niusha; Isa, Dino

    2015-01-01

    Highlights: • A novel energy management system (EMS) for supercapacitor-battery hybrid energy storage system is implemented. • It is a load predictive EMS which is implemented using Support Vector Machine (SVM). • An optimum SVM load prediction model is obtained, which yields 100% accuracy in 0.004866 s of training time. • The implemented load predictive EMS is compared with the conventional sequential programming control. • This methodology reduces the number of power electronics used and prolong battery lifespan. - Abstract: This paper presents the use of a Support Vector Machine load predictive energy management system to control the energy flow between a solar energy source, a supercapacitor-battery hybrid energy storage combination and the load. The supercapacitor-battery hybrid energy storage system is deployed in a solar energy system to improve the reliability of delivered power. The combination of batteries and supercapacitors makes use of complementary characteristic that allow the overlapping of a battery’s high energy density with a supercapacitors’ high power density. This hybrid system produces a straightforward benefit over either individual system, by taking advantage of each characteristic. When the supercapacitor caters for the instantaneous peak power which prolongs the battery lifespan, it also minimizes the system cost and ensures a greener system by reducing the number of batteries. The resulting performance is highly dependent on the energy controls implemented in the system to exploit the strengths of the energy storage devices and minimize its weaknesses. It is crucial to use energy from the supercapacitor and therefore minimize jeopardizing the power system reliability especially when there is a sudden peak power demand. This study has been divided into two stages. The first stage is to obtain the optimum SVM load prediction model, and the second stage carries out the performance comparison of the proposed SVM-load predictive

  3. Rule-Based Design of Plant Expression Vectors Using GenoCAD.

    Science.gov (United States)

    Coll, Anna; Wilson, Mandy L; Gruden, Kristina; Peccoud, Jean

    2015-01-01

    Plant synthetic biology requires software tools to assist on the design of complex multi-genic expression plasmids. Here a vector design strategy to express genes in plants is formalized and implemented as a grammar in GenoCAD, a Computer-Aided Design software for synthetic biology. It includes a library of plant biological parts organized in structural categories and a set of rules describing how to assemble these parts into large constructs. Rules developed here are organized and divided into three main subsections according to the aim of the final construct: protein localization studies, promoter analysis and protein-protein interaction experiments. The GenoCAD plant grammar guides the user through the design while allowing users to customize vectors according to their needs. Therefore the plant grammar implemented in GenoCAD will help plant biologists take advantage of methods from synthetic biology to design expression vectors supporting their research projects.

  4. Controllability of linear vector fields on Lie groups

    International Nuclear Information System (INIS)

    Ayala, V.; Tirao, J.

    1994-11-01

    In this paper, we shall deal with a linear control system Σ defined on a Lie group G with Lie algebra g. The dynamic of Σ is determined by the drift vector field which is an element in the normalizer of g in the Lie algebra of all smooth vector field on G and by the control vectors which are elements in g considered as left-invariant vector fields. We characterize the normalizer of g identifying vector fields on G with C ∞ -functions defined on G into g. For this class of control systems we study algebraic conditions for the controllability problem. Indeed, we prove that if the drift vector field has a singularity then the Lie algebra rank condition is necessary for the controllability property, but in general this condition does not determine this property. On the other hand, we show that the rank (ad-rank) condition is sufficient for the controllability of Σ. In particular, we extend the fundamental Kalman's theorem when G is an Abelian connected Lie group. Our work is related with a paper of L. Markus and we also improve his results. (author). 7 refs

  5. Perinatal systemic gene delivery using adeno-associated viral vectors

    Directory of Open Access Journals (Sweden)

    Rajvinder eKarda

    2014-11-01

    Full Text Available Neurodegenerative monogenic diseases can also affect a broad range of tissues and organs throughout the body. An effective treatment would require a systemic approach. The intravenous administration of novel therapies is ideal but is hampered by the inability of such drugs to cross the blood-brain barrier and precludes efficacy in the central nervous system. A number of these early lethal intractable diseases also present devastating irreversible pathology at birth or soon after. Therefore, any therapy would ideally be administered during the perinatal period to prevent, stop or ameliorate disease progression. The concept of perinatal gene therapy has moved a step further towards being a feasible approach to treating such disorders. This has primarily been driven by the recent discoveries that particular serotypes of adeno-associated virus (AAV gene delivery vectors have the ability to cross the blood-brain barrier following intravenous administration. Furthermore, this has been safely demonstrated in perinatal mice and non-human primates. This review focuses on the progress made in using AAV to achieve systemic transduction and what this means for developing perinatal gene therapy for early lethal neurodegenerative diseases.

  6. Engineering web maps with gradual content zoom based on streaming vector data

    Science.gov (United States)

    Huang, Lina; Meijers, Martijn; Šuba, Radan; van Oosterom, Peter

    2016-04-01

    Vario-scale data structures have been designed to support gradual content zoom and the progressive transfer of vector data, for use with arbitrary map scales. The focus to date has been on the server side, especially on how to convert geographic data into the proposed vario-scale structures by means of automated generalisation. This paper contributes to the ongoing vario-scale research by focusing on the client side and communication, particularly on how this works in a web-services setting. It is claimed that these functionalities are urgently needed, as many web-based applications, both desktop and mobile, require gradual content zoom, progressive transfer and a high performance level. The web-client prototypes developed in this paper make it possible to assess the behaviour of vario-scale data and to determine how users will actually see the interactions. Several different options of web-services communication architectures are possible in a vario-scale setting. These options are analysed and tested with various web-client prototypes, with respect to functionality, ease of implementation and performance (amount of transmitted data and response times). We show that the vario-scale data structure can fit in with current web-based architectures and efforts to standardise map distribution on the internet. However, to maximise the benefits of vario-scale data, a client needs to be aware of this structure. When a client needs a map to be refined (by means of a gradual content zoom operation), only the 'missing' data will be requested. This data will be sent incrementally to the client from a server. In this way, the amount of data transferred at one time is reduced, shortening the transmission time. In addition to these conceptual architecture aspects, there are many implementation and tooling design decisions at play. These will also be elaborated on in this paper. Based on the experiments conducted, we conclude that the vario-scale approach indeed supports gradual

  7. Active damage detection method based on support vector machine and impulse response

    International Nuclear Information System (INIS)

    Taniguchi, Ryuta; Mita, Akira

    2004-01-01

    An active damage detection method was proposed to characterize damage in bolted joints. The purpose of this study is to propose a damage detection method that can obtain the detailed information of the damage by creating feature vectors for pattern recognition. In the proposed method, the wavelet transform is applied to the sensor signals, and the feature vectors are defined by second power average of the amplitude. The feature vectors generated by experiments were successfully used as the training data for Support Vector Machine (SVM). By applying the wavelet transform to time-frequency analysis, the accuracy of pattern recognition was raised in both correlation coefficient and SVM applications. Moreover, the SVM could identify the damage with very strong discernment capability than others. Applicability of the proposed method was successfully demonstrated. (author)

  8. Subspace identification of Hammer stein models using support vector machines

    International Nuclear Information System (INIS)

    Al-Dhaifallah, Mujahed

    2011-01-01

    System identification is the art of finding mathematical tools and algorithms that build an appropriate mathematical model of a system from measured input and output data. Hammerstein model, consisting of a memoryless nonlinearity followed by a dynamic linear element, is often a good trade-off as it can represent some dynamic nonlinear systems very accurately, but is nonetheless quite simple. Moreover, the extensive knowledge about LTI system representations can be applied to the dynamic linear block. On the other hand, finding an effective representation for the nonlinearity is an active area of research. Recently, support vector machines (SVMs) and least squares support vector machines (LS-SVMs) have demonstrated powerful abilities in approximating linear and nonlinear functions. In contrast with other approximation methods, SVMs do not require a-priori structural information. Furthermore, there are well established methods with guaranteed convergence (ordinary least squares, quadratic programming) for fitting LS-SVMs and SVMs. The general objective of this research is to develop new subspace algorithms for Hammerstein systems based on SVM regression.

  9. Short term prediction of the horizontal wind vector within a wake vortex warning system

    Energy Technology Data Exchange (ETDEWEB)

    Frech, M.; Holzaepfel, F.; Gerz, T. [DLR Deutsches Zentrum fuer Luft- und Raumfahrt e.V., Wessling (Germany). Inst. fuer Physik der Atmosphaere; Konopka, J. [Deutsche Flugsicherung (DFS) GmbH, Langen (Germany)

    2000-07-14

    A wake vortex warning system (WVWS) has been developed for Frankfurt airport. This airport has two parallel runways which are separated by 518 m, a distance too short to operate them independently because wake vortices may be advected to the adjacent runway. The objective of the WVWS is to enable operation with reduced separation between two aircraft approaching the parallel runways at appropriate wind conditions. The WVWS applies a statistical persistence model to predict the crosswind within a 20 minute period. One of the main problems identified in the old WVWS are discontinuities between successive forecasts. These forecast breakdowns were not acceptable to airtraffic controllers. At least part of the problem was related to the fact that the forecast was solely based on the prediction of crosswind. A new method is developed on the basis of 523 days of sonic anemometer measurements at Frankfurt airport. It is demonstrated that the prediction of the horizontal wind vector avoids these difficulties and significantly improves the system's performance. (orig.)

  10. Internet-based biosurveillance methods for vector-borne diseases: Are they novel public health tools or just novelties?

    Science.gov (United States)

    Pollett, Simon; Althouse, Benjamin M; Forshey, Brett; Rutherford, George W; Jarman, Richard G

    2017-11-01

    Internet-based surveillance methods for vector-borne diseases (VBDs) using "big data" sources such as Google, Twitter, and internet newswire scraping have recently been developed, yet reviews on such "digital disease detection" methods have focused on respiratory pathogens, particularly in high-income regions. Here, we present a narrative review of the literature that has examined the performance of internet-based biosurveillance for diseases caused by vector-borne viruses, parasites, and other pathogens, including Zika, dengue, other arthropod-borne viruses, malaria, leishmaniasis, and Lyme disease across a range of settings, including low- and middle-income countries. The fundamental features, advantages, and drawbacks of each internet big data source are presented for those with varying familiarity of "digital epidemiology." We conclude with some of the challenges and future directions in using internet-based biosurveillance for the surveillance and control of VBD.

  11. Internet-based biosurveillance methods for vector-borne diseases: Are they novel public health tools or just novelties?

    Directory of Open Access Journals (Sweden)

    Simon Pollett

    2017-11-01

    Full Text Available Internet-based surveillance methods for vector-borne diseases (VBDs using "big data" sources such as Google, Twitter, and internet newswire scraping have recently been developed, yet reviews on such "digital disease detection" methods have focused on respiratory pathogens, particularly in high-income regions. Here, we present a narrative review of the literature that has examined the performance of internet-based biosurveillance for diseases caused by vector-borne viruses, parasites, and other pathogens, including Zika, dengue, other arthropod-borne viruses, malaria, leishmaniasis, and Lyme disease across a range of settings, including low- and middle-income countries. The fundamental features, advantages, and drawbacks of each internet big data source are presented for those with varying familiarity of "digital epidemiology." We conclude with some of the challenges and future directions in using internet-based biosurveillance for the surveillance and control of VBD.

  12. Vector assembly of colloids on monolayer substrates

    Science.gov (United States)

    Jiang, Lingxiang; Yang, Shenyu; Tsang, Boyce; Tu, Mei; Granick, Steve

    2017-06-01

    The key to spontaneous and directed assembly is to encode the desired assembly information to building blocks in a programmable and efficient way. In computer graphics, raster graphics encodes images on a single-pixel level, conferring fine details at the expense of large file sizes, whereas vector graphics encrypts shape information into vectors that allow small file sizes and operational transformations. Here, we adapt this raster/vector concept to a 2D colloidal system and realize `vector assembly' by manipulating particles on a colloidal monolayer substrate with optical tweezers. In contrast to raster assembly that assigns optical tweezers to each particle, vector assembly requires a minimal number of optical tweezers that allow operations like chain elongation and shortening. This vector approach enables simple uniform particles to form a vast collection of colloidal arenes and colloidenes, the spontaneous dissociation of which is achieved with precision and stage-by-stage complexity by simply removing the optical tweezers.

  13. Genetic stability of attenuated mengovirus vectors with duplicate primary cleavage sequences

    International Nuclear Information System (INIS)

    Binder, J.J.; Hoffman, M.A.; Palmenberg, A.C.

    2003-01-01

    Short poly(C)-tract Mengoviruses have proven vaccine efficacy in many species of animals. A novel vector for the delivery of foreign proteins was created by insertion of a second autoproteolytic primary cleavage cassette linked to a multiple cloning site (MCS) into an attenuated variant of Mengo. Nineteen cDNAs from foreign sequences that ranged from 39 to 1653 bases were cloned into the MCS. The viral reading frame was maintained and translation resulted in dual, autocatalytic excision of the foreign peptides without disruption of any Mengo proteins. All cDNAs except those with the largest insertions produced viable virus. Active proteins such as GFP, CAT, and SIV p27 were expressed within infected cells. Relative to parental Mengo, the growth kinetics and genetic stability of each vector was inversely proportional to the size of the inserted sequence. While segments up to 1000 bases could be carried, inserts greater than 500-600 bases were usually reduced in size during serial passage. The limit on carrying capacity was probably due to difficulties in virion assembly or particle stability. Yet for inserts less than 500-600 bases, the Mengo vectors provided an effective system for the delivery of foreign epitopes into cells and mice

  14. Modified montmorillonite as vector for gene delivery.

    Science.gov (United States)

    Lin, Feng-Huei; Chen, Chia-Hao; Cheng, Winston T K; Kuo, Tzang-Fu

    2006-06-01

    Currently, gene delivery systems can be divided into two parts: viral or non-viral vectors. In general, viral vectors have a higher efficiency on gene delivery. However, they may sometimes provoke mutagenesis and carcinogenesis once re-activating in human body. Lots of non-viral vectors have been developed that tried to solve the problems happened on viral vectors. Unfortunately, most of non-viral vectors showed relatively lower transfection rate. The aim of this study is to develop a non-viral vector for gene delivery system. Montmorillonite (MMT) is one of clay minerals that consist of hydrated aluminum with Si-O tetrahedrons on the bottom of the layer and Al-O(OH)2 octahedrons on the top. The inter-layer space is about 12 A. The room is not enough to accommodate DNA for gene delivery. In the study, the cationic hexadecyltrimethylammonium (HDTMA) will be intercalated into the interlayer of MMT as a layer expander to expand the layer space for DNA accommodation. The optimal condition for the preparation of DNA-HDTMA-MMT is as follows: 1 mg of 1.5CEC HDTMA-MMT was prepared under pH value of 10.7 and with soaking time for 2 h. The DNA molecules can be protected from nuclease degradation, which can be proven by the electrophoresis analysis. DNA was successfully transfected into the nucleus of human dermal fibroblast and expressed enhanced green fluorescent protein (EGFP) gene with green fluorescence emission. The HDTMA-MMT has a great potential as a vector for gene delivery in the future.

  15. Emerging vector borne diseases – incidence through vectors

    Directory of Open Access Journals (Sweden)

    Sara eSavic

    2014-12-01

    Full Text Available Vector borne diseases use to be a major public health concern only in tropical and subtropical areas, but today they are an emerging threat for the continental and developed countries also. Nowdays, in intercontinetal countries, there is a struggle with emerging diseases which have found their way to appear through vectors. Vector borne zoonotic diseases occur when vectors, animal hosts, climate conditions, pathogens and susceptible human population exist at the same time, at the same place. Global climate change is predicted to lead to an increase in vector borne infectious diseases and disease outbreaks. It could affect the range and popultion of pathogens, host and vectors, transmission season, etc. Reliable surveilance for diseases that are most likely to emerge is required. Canine vector borne diseases represent a complex group of diseases including anaplasmosis, babesiosis, bartonellosis, borreliosis, dirofilariosis, erlichiosis, leishmaniosis. Some of these diseases cause serious clinical symptoms in dogs and some of them have a zoonotic potential with an effect to public health. It is expected from veterinarians in coordination with medical doctors to play a fudamental role at primeraly prevention and then treatment of vector borne diseases in dogs. The One Health concept has to be integrated into the struggle against emerging diseases.During a four year period, from 2009-2013, a total number of 551 dog samples were analysed for vector borne diseases (borreliosis, babesiosis, erlichiosis, anaplasmosis, dirofilariosis and leishmaniasis in routine laboratory work. The analysis were done by serological tests – ELISA for borreliosis, dirofilariosis and leishmaniasis, modified Knott test for dirofilariosis and blood smear for babesiosis, erlichiosis and anaplasmosis. This number of samples represented 75% of total number of samples that were sent for analysis for different diseases in dogs. Annually, on avarege more then half of the samples

  16. The consequences of poor vectorization

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    This talk briefly discusses the vectorization problem and how it impacts scientific and engineering systems. A simple cost model of designing such system in context of different phases of software lifetime is considered. Finally a concept for scalable solution is presented.

  17. A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-08-25

    This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.

  18. Ordering sparse matrices for cache-based systems

    International Nuclear Information System (INIS)

    Biswas, Rupak; Oliker, Leonid

    2001-01-01

    The Conjugate Gradient (CG) algorithm is the oldest and best-known Krylov subspace method used to solve sparse linear systems. Most of the coating-point operations within each CG iteration is spent performing sparse matrix-vector multiplication (SPMV). We examine how various ordering and partitioning strategies affect the performance of CG and SPMV when different programming paradigms are used on current commercial cache-based computers. However, a multithreaded implementation on the cacheless Cray MTA demonstrates high efficiency and scalability without any special ordering or partitioning

  19. Attitude Determination Algorithm based on Relative Quaternion Geometry of Velocity Incremental Vectors for Cost Efficient AHRS Design

    Science.gov (United States)

    Lee, Byungjin; Lee, Young Jae; Sung, Sangkyung

    2018-05-01

    A novel attitude determination method is investigated that is computationally efficient and implementable in low cost sensor and embedded platform. Recent result on attitude reference system design is adapted to further develop a three-dimensional attitude determination algorithm through the relative velocity incremental measurements. For this, velocity incremental vectors, computed respectively from INS and GPS with different update rate, are compared to generate filter measurement for attitude estimation. In the quaternion-based Kalman filter configuration, an Euler-like attitude perturbation angle is uniquely introduced for reducing filter states and simplifying propagation processes. Furthermore, assuming a small angle approximation between attitude update periods, it is shown that the reduced order filter greatly simplifies the propagation processes. For performance verification, both simulation and experimental studies are completed. A low cost MEMS IMU and GPS receiver are employed for system integration, and comparison with the true trajectory or a high-grade navigation system demonstrates the performance of the proposed algorithm.

  20. Vector-vector production in photon-photon interactions

    International Nuclear Information System (INIS)

    Ronan, M.T.

    1988-01-01

    Measurements of exclusive untagged /rho/ 0 /rho/ 0 , /rho//phi/, K/sup *//bar K//sup */, and /rho/ω production and tagged /rho/ 0 /rho/ 0 production in photon-photon interactions by the TPC/Two-Gamma experiment are reviewed. Comparisons to the results of other experiments and to models of vector-vector production are made. Fits to the data following a four quark model prescription for vector meson pair production are also presented. 10 refs., 9 figs

  1. Estimating the temporal and spatial risk of bluetongue related to the incursion of infected vectors into Switzerland

    Directory of Open Access Journals (Sweden)

    Griot C

    2008-10-01

    Full Text Available Abstract Background The design of veterinary and public health surveillance systems has been improved by the ability to combine Geographical Information Systems (GIS, mathematical models and up to date epidemiological knowledge. In Switzerland, an early warning system was developed for detecting the incursion of the bluetongue disease virus (BT and to monitor the frequency of its vectors. Based on data generated by this surveillance system, GIS and transmission models were used in order to determine suitable seasonal vector habitat locations and risk periods for a larger and more targeted surveillance program. Results Combined thematic maps of temperature, humidity and altitude were created to visualize the association with Culicoides vector habitat locations. Additional monthly maps of estimated basic reproduction number transmission rates (R0 were created in order to highlight areas of Switzerland prone to higher BT outbreaks in relation to both vector activity and transmission levels. The maps revealed several foci of higher risk areas, especially in northern parts of Switzerland, suitable for both vector presence and vector activity for 2006. Results showed a variation of R0 values comparing 2005 and 2006 yet suggested that Switzerland was at risk of an outbreak of BT, especially if the incursion arrived in a suitable vector activity period. Since the time of conducting these analyses, this suitability has proved to be the case with the recent outbreaks of BT in northern Switzerland. Conclusion Our results stress the importance of environmental factors and their effect on the dynamics of a vector-borne disease. In this case, results of this model were used as input parameters for creating a national targeted surveillance program tailored to both the spatial and the temporal aspect of the disease and its vectors. In this manner, financial and logistic resources can be used in an optimal way through seasonally and geographically adjusted

  2. A compact dual promoter adeno-associated viral vector for efficient delivery of two genes to dorsal root ganglion neurons

    NARCIS (Netherlands)

    Fagoe, N D; Eggers, R; Verhaagen, J; Mason, M R J

    Adeno-associated viral (AAV) vectors based on serotype 5 are an efficient means to target dorsal root ganglia (DRG) to study gene function in the primary sensory neurons of the peripheral nervous system. In this study, we have developed a compact AAV dual promoter vector composed of the

  3. Vector-Parallel processing of the successive overrelaxation method

    International Nuclear Information System (INIS)

    Yokokawa, Mitsuo

    1988-02-01

    Successive overrelaxation method, called SOR method, is one of iterative methods for solving linear system of equations, and it has been calculated in serial with a natural ordering in many nuclear codes. After the appearance of vector processors, this natural SOR method has been changed for the parallel algorithm such as hyperplane or red-black method, in which the calculation order is modified. These methods are suitable for vector processors, and more high-speed calculation can be obtained compared with the natural SOR method on vector processors. In this report, a new scheme named 4-colors SOR method is proposed. We find that the 4-colors SOR method can be executed on vector-parallel processors and it gives the most high-speed calculation among all SOR methods according to results of the vector-parallel execution on the Alliant FX/8 multiprocessor system. It is also shown that the theoretical optimal acceleration parameters are equal among five different ordering SOR methods, and the difference between convergence rates of these SOR methods are examined. (author)

  4. Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs.

    Science.gov (United States)

    Javaid, Nadeem; Ahmed, Farwa; Wadud, Zahid; Alrajeh, Nabil; Alabed, Mohamad Souheil; Ilahi, Manzoor

    2017-08-01

    Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network.

  5. Vector control programs in Saint Johns County, Florida and Guayas, Ecuador: successes and barriers to integrated vector management.

    Science.gov (United States)

    Naranjo, Diana P; Qualls, Whitney A; Jurado, Hugo; Perez, Juan C; Xue, Rui-De; Gomez, Eduardo; Beier, John C

    2014-07-02

    MCP relies heavily on the community for vector control while the American MCP relies on technologies and research. IVM based recommendations direct health policy leaders toward improving surveillance systems both entomologically and epidemiologically, improving community risk perceptions by integrating components of community participation, maximizing resources though the use of applied research, and protecting the environment by selecting low-risk pesticides. Outcomes of the research revealed that inter-sectorial and multidisciplinary interventions are critical to improve public health.

  6. Vector control programs in Saint Johns County, Florida and Guayas, Ecuador: successes and barriers to integrated vector management

    Science.gov (United States)

    2014-01-01

    included how the Ecuadorian MCP relies heavily on the community for vector control while the American MCP relies on technologies and research. Conclusion IVM based recommendations direct health policy leaders toward improving surveillance systems both entomologically and epidemiologically, improving community risk perceptions by integrating components of community participation, maximizing resources though the use of applied research, and protecting the environment by selecting low-risk pesticides. Outcomes of the research revealed that inter-sectorial and multidisciplinary interventions are critical to improve public health. PMID:24990155

  7. DOA and Polarization Estimation Using an Electromagnetic Vector Sensor Uniform Circular Array Based on the ESPRIT Algorithm.

    Science.gov (United States)

    Wu, Na; Qu, Zhiyu; Si, Weijian; Jiao, Shuhong

    2016-12-13

    In array signal processing systems, the direction of arrival (DOA) and polarization of signals based on uniform linear or rectangular sensor arrays are generally obtained by rotational invariance techniques (ESPRIT). However, since the ESPRIT algorithm relies on the rotational invariant structure of the received data, it cannot be applied to electromagnetic vector sensor arrays (EVSAs) featuring uniform circular patterns. To overcome this limitation, a fourth-order cumulant-based ESPRIT algorithm is proposed in this paper, for joint estimation of DOA and polarization based on a uniform circular EVSA. The proposed algorithm utilizes the fourth-order cumulant to obtain a virtual extended array of a uniform circular EVSA, from which the pairs of rotation invariant sub-arrays are obtained. The ESPRIT algorithm and parameter pair matching are then utilized to estimate the DOA and polarization of the incident signals. The closed-form parameter estimation algorithm can effectively reduce the computational complexity of the joint estimation, which has been demonstrated by numerical simulations.

  8. The Weighted Support Vector Machine Based on Hybrid Swarm Intelligence Optimization for Icing Prediction of Transmission Line

    Directory of Open Access Journals (Sweden)

    Xiaomin Xu

    2015-01-01

    Full Text Available Not only can the icing coat on transmission line cause the electrical fault of gap discharge and icing flashover but also it will lead to the mechanical failure of tower, conductor, insulators, and others. It will bring great harm to the people’s daily life and work. Thus, accurate prediction of ice thickness has important significance for power department to control the ice disaster effectively. Based on the analysis of standard support vector machine, this paper presents a weighted support vector machine regression model based on the similarity (WSVR. According to the different importance of samples, this paper introduces the weighted support vector machine and optimizes its parameters by hybrid swarm intelligence optimization algorithm with the particle swarm and ant colony (PSO-ACO, which improves the generalization ability of the model. In the case study, the actual data of ice thickness and climate in a certain area of Hunan province have been used to predict the icing thickness of the area, which verifies the validity and applicability of this proposed method. The predicted results show that the intelligent model proposed in this paper has higher precision and stronger generalization ability.

  9. Rare Hadronic B Decays to Vector, Axial-Vector and Tensors

    International Nuclear Information System (INIS)

    Gao, Y.Y.

    2011-01-01

    The authors review BABAR measurements of several rare B decays, including vector-axial-vector decays B ± → φK 1 ± (1270), B ± → φ K 1 ± (1400) and B ± → b 1 # -+ρ# ± , vector-vector decays B ± → φK* ± (1410), B 0 → K* 0 (bar K)* 0 , B 0 → K*0K*0 and B 0 → K*+K*-, vector-tensor decays B ± → φK* 2 (1430) ± and φK 2 (1770)/ ± (1820), and vector-scalar decays B ± → φK* 0 (1430) ± . Understanding the observed polarization pattern requires amplitude contributions from an uncertain source.

  10. VectorH: taking SQL-on-Hadoop to the next level

    NARCIS (Netherlands)

    M. Switakowski; A. Costea (Andrei); A. Ionescu (Adrian); B. Raducanu (Bogdan); C. Bârca; J. Sompolski (Juliusz); A. Łuszczak; M. Szafranski (Michal); G. De Nijs; P.A. Boncz (Peter)

    2016-01-01

    htmlabstractIn this paper we describe VectorH: a new SQL-on-Hadoop system built on top of the fast Vectorwise analytical database system. VectorH achieves fault tolerance and scalable data storage by relying on HDFS, extending the state-of-the-art in SQL-on-Hadoop systems by instrumenting the HDFS

  11. Interior point decoding for linear vector channels

    International Nuclear Information System (INIS)

    Wadayama, T

    2008-01-01

    In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector channels include many practically important channels such as inter-symbol interference channels and partial response channels. It is shown that the maximum likelihood decoding (MLD) rule for a linear vector channel can be relaxed to a convex optimization problem, which is called a relaxed MLD problem

  12. Interior point decoding for linear vector channels

    Energy Technology Data Exchange (ETDEWEB)

    Wadayama, T [Nagoya Institute of Technology, Gokiso, Showa-ku, Nagoya, Aichi, 466-8555 (Japan)], E-mail: wadayama@nitech.ac.jp

    2008-01-15

    In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector channels include many practically important channels such as inter-symbol interference channels and partial response channels. It is shown that the maximum likelihood decoding (MLD) rule for a linear vector channel can be relaxed to a convex optimization problem, which is called a relaxed MLD problem.

  13. Bioreactor production of recombinant herpes simplex virus vectors.

    Science.gov (United States)

    Knop, David R; Harrell, Heather

    2007-01-01

    Serotypical application of herpes simplex virus (HSV) vectors to gene therapy (type 1) and prophylactic vaccines (types 1 and 2) has garnered substantial clinical interest recently. HSV vectors and amplicons have also been employed as helper virus constructs for manufacture of the dependovirus adeno-associated virus (AAV). Large quantities of infectious HSV stocks are requisite for these therapeutic applications, requiring a scalable vector manufacturing and processing platform comprised of unit operations which accommodate the fragility of HSV. In this study, production of a replication deficient rHSV-1 vector bearing the rep and cap genes of AAV-2 (denoted rHSV-rep2/cap2) was investigated. Adaptation of rHSV production from T225 flasks to a packed bed, fed-batch bioreactor permitted an 1100-fold increment in total vector production without a decrease in specific vector yield (pfu/cell). The fed-batch bioreactor system afforded a rHSV-rep2/cap2 vector recovery of 2.8 x 10(12) pfu. The recovered vector was concentrated by tangential flow filtration (TFF), permitting vector stocks to be formulated at greater than 1.5 x 10(9) pfu/mL.

  14. Singular vectors, predictability and ensemble forecasting for weather and climate

    International Nuclear Information System (INIS)

    Palmer, T N; Zanna, Laure

    2013-01-01

    The local instabilities of a nonlinear dynamical system can be characterized by the leading singular vectors of its linearized operator. The leading singular vectors are perturbations with the greatest linear growth and are therefore key in assessing the system’s predictability. In this paper, the analysis of singular vectors for the predictability of weather and climate and ensemble forecasting is discussed. An overview of the role of singular vectors in informing about the error growth rate in numerical models of the atmosphere is given. This is followed by their use in the initialization of ensemble weather forecasts. Singular vectors for the ocean and coupled ocean–atmosphere system in order to understand the predictability of climate phenomena such as ENSO and meridional overturning circulation are reviewed and their potential use to initialize seasonal and decadal forecasts is considered. As stochastic parameterizations are being implemented, some speculations are made about the future of singular vectors for the predictability of weather and climate for theoretical applications and at the operational level. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘Lyapunov analysis: from dynamical systems theory to applications’. (review)

  15. Using Covariant Lyapunov Vectors to Understand Spatiotemporal Chaos in Fluids

    Science.gov (United States)

    Paul, Mark; Xu, Mu; Barbish, Johnathon; Mukherjee, Saikat

    2017-11-01

    The spatiotemporal chaos of fluids present many difficult and fascinating challenges. Recent progress in computing covariant Lyapunov vectors for a variety of model systems has made it possible to probe fundamental ideas from dynamical systems theory including the degree of hyperbolicity, the fractal dimension, the dimension of the inertial manifold, and the decomposition of the dynamics into a finite number of physical modes and spurious modes. We are interested in building upon insights such as these for fluid systems. We first demonstrate the power of covariant Lyapunov vectors using a system of maps on a lattice with a nonlinear coupling. We then compute the covariant Lyapunov vectors for chaotic Rayleigh-Bénard convection for experimentally accessible conditions. We show that chaotic convection is non-hyperbolic and we quantify the spatiotemporal features of the spectrum of covariant Lyapunov vectors. NSF DMS-1622299 and DARPA/DSO Models, Dynamics, and Learning (MoDyL).

  16. Angle Control-Based Multi-Terminal Out-of-Step Protection System

    Directory of Open Access Journals (Sweden)

    Antans Sauhats

    2017-03-01

    Full Text Available From time to time a sequence of unexpected and overlapping contingencies may lead to power system angular instability and even blackouts if not addressed adequately by means of an out-of-step (OOS protection system. The motivation of the paper is an attempt to develop a workable prototype of the OOS protection system. The deficiencies of the protection currently used in the Latvian Power System network are highlighted and a new protection structure is proposed. The protection system comprises of several strategically located terminals, exchanging information in real time by means of a communication network. The OOS condition detection method is based on system-wide generation sources, electromotive forces, vectors, and angle control. The network splitting decision is based on generator coherence evaluation. Protection terminals determine online the groups of coherent generators and choose the splitting boundary from a predefined transmission lines (TLs cut sets list. The protection system structure, algorithm of operation, and possible IEC 61850 communication standard-based implementation are described.

  17. Declining Prevalence of Disease Vectors Under Climate Change

    Science.gov (United States)

    Escobar, Luis E.; Romero-Alvarez, Daniel; Leon, Renato; Lepe-Lopez, Manuel A.; Craft, Meggan E.; Borbor-Cordova, Mercy J.; Svenning, Jens-Christian

    2016-12-01

    More than half of the world population is at risk of vector-borne diseases including dengue fever, chikungunya, zika, yellow fever, leishmaniasis, chagas disease, and malaria, with highest incidences in tropical regions. In Ecuador, vector-borne diseases are present from coastal and Amazonian regions to the Andes Mountains; however, a detailed characterization of the distribution of their vectors has never been carried out. We estimate the distribution of 14 vectors of the above vector-borne diseases under present-day and future climates. Our results consistently suggest that climate warming is likely threatening some vector species with extinction, locally or completely. These results suggest that climate change could reduce the burden of specific vector species. Other vector species are likely to shift and constrain their geographic range to the highlands in Ecuador potentially affecting novel areas and populations. These forecasts show the need for development of early prevention strategies for vector species currently absent in areas projected as suitable under future climate conditions. Informed interventions could reduce the risk of human exposure to vector species with distributional shifts, in response to current and future climate changes. Based on the mixed effects of future climate on human exposure to disease vectors, we argue that research on vector-borne diseases should be cross-scale and include climatic, demographic, and landscape factors, as well as forces facilitating disease transmission at fine scales.

  18. Ax-Kochen-Ershov principles for valued and ordered vector spaces

    OpenAIRE

    Kuhlmann, Franz-Viktor; Kuhlmann, Salma

    1997-01-01

    We study extensions of valued vector spaces with variable base field, introducing the notion of disjointness and valuation disjointness in this setting. We apply the results to determine the model theoretic properties of valued vector spaces (with variable base field) relative to that of their skeletons. We study the model theory of the skeletons in special cases. We apply the results to ordered vector spaces with compatible valuation.

  19. Novel recombinant alphaviral and adenoviral vectors for cancer immunotherapy.

    Science.gov (United States)

    Osada, Takuya; Morse, Michael A; Hobeika, Amy; Lyerly, H Kim

    2012-06-01

    Although cellular immunotherapy based on autolgous dendritic cells (DCs) targeting antigens expressed by metastatic cancer has demonstrated clinical efficacy, the logistical challenges in generating an individualized cell product create an imperative to develop alternatives to DC-based cancer vaccines. Particularly attractive alternatives include in situ delivery of antigen and activation signals to resident antigen-presenting cells (APCs), which can be achieved by novel fusion molecules targeting the mannose receptor and by recombinant viral vectors expressing the antigen of interest and capable of infecting DCs. A particular challenge in the use of viral vectors is the well-appreciated clinical obstacles to their efficacy, specifically vector-specific neutralizing immune responses. Because heterologous prime and boost strategies have been demonstrated to be particularly potent, we developed two novel recombinant vectors based on alphaviral replicon particles and a next-generation adenovirus encoding an antigen commonly overexpressed in many human cancers, carcinoembryonic antigen (CEA). The rationale for developing these vectors, their unique characteristics, the preclinical studies and early clinical experience with each, and opportunities to enhance their effectiveness will be reviewed. The potential of each of these potent recombinant vectors to efficiently generate clinically active anti-tumor immune response alone, or in combination, will be discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

  20. A support vector machine integrated system for the classification of operation anomalies in nuclear components and systems

    International Nuclear Information System (INIS)

    Rocco S, Claudio M.; Zio, Enrico

    2007-01-01

    A support vector machine (SVM) approach to the classification of transients in nuclear power plants is presented. SVM is a machine-learning algorithm that has been successfully used in pattern recognition for cluster analysis. In the present work, single- and multiclass SVM are combined into a hierarchical structure for distinguishing among transients in nuclear systems on the basis of measured data. An example of application of the approach is presented with respect to the classification of anomalies and malfunctions occurring in the feedwater system of a boiling water reactor. The data used in the example are provided by the HAMBO simulator of the Halden Reactor Project